Calveta’s Dining Services, Inc: A Recipe for Growth? Essay

Higher chances of attaining goals and will obtain desired market penetration Increases Calveta’s geographic coverage and market share GSD is presently in a good position, when the revenue generation is taken into consideration. Calveta would attain a great deal of customer potential as it was maintained by GSD. The organization hierarchy could be restructured so that it could accommodate significant growth while preserving the company’s core values. The disadvantages of choosing this option are: Very risky Plagued with labor issues and management turnover Quality of service may suffer. Higher debt load Does not have a strong balance sheet but has great income potential. Jennifer Calveta COO of firm: Could have been CEO instead of her brother Very detail oriented and concerned about preserving the company’s culture Is concerned about the acquisition of business for growth expansion Is concerned with the organizations structural modification 1. What role (if any) have Calveta’s values played in the organization’s success? Calveta has clearly defined values to guide the staff’s behavior. The immense growth of the organization confirms that Calveta’s is doing an excellent in embedding their values in their employees’ actions and management decisions. The values necessitate the inclusion of everyone and the exclusion of none. The organization’s values enabled all levels of management to usher the employees toward a continuous growth. 2. Does Calveta’s operating approach offer a sustainable competitive advantage? Calveta’s operating approach offered a unique competitive edge over many of its competitors. While their competitors focused on highly regularized systems and standards, Calveta chose to build local food service teams and menu offers to serve each facility distinctively. Additionally, Calveta’s wait staff treated the residents like family following their behavioral standards. This type of customer service garnered rave written reviews from the facility’s residents. Finally, implementing programs that increase efficiency while satisfying the needs of bed ridden or immobile residents confirm a very innovative operating approach that resulted in a sustainable competitive advantage. 3. Why haven’t other food service providers copied Calveta’s approach? Calveta’s competitors were not focused on conducting a profitable business without straying away from its core values. Passion, customer service and efficiency remained at the forefront of every decision. On the other hand, their competitors were focused on growth, meeting financial goals and increasing market share. Rarely do we find companies who keep both service and profit as a priority. 4. Given Calveta’s communication and internal organizational challenges, how important will training and development be to maintaining growth and culture? The internal challenges within Calveta confirm that the organization must continue to rely on training and development to ensure success. However, training and development should not be done in a manner that reduces quality or at the expense of the residents’ positive experiences. Upper management must create systems that focuses on the development of new managers and establishes a solid means of communication between staff and management. Growing pains is inevitable but it cannot become a deterrent to taking the company to the next level. 5. Calveta’s fifth goal is profitable growth. Goals one through four is more ethical in nature. Is goal five inconsistent with the first four? Establishing growth as a goal is consistent with Calevta’s other goals. However growth, whether by acquisition or market penetration, should not mean that â€Å"Antonio’s Way† is watered down in any way or removed from the way Calveta conducts business. Calveta’s unique approach to business cannot be lost while increasing revenues and market share. As long as Calveta’s values remain the guiding force to management decisions and employees’ actions, having growth as a priority should be expected. 6. How, if at all, should Calveta’s organizational structure be changed to resolve communication issues, preserve the company’s culture, and support future growth? Calveta’s uses the top-down management structure. This structure contains layers of managers (rank structure) which all communications must pass through. With each layer there is a risk of distorted information being sent to the next level. Each level adds to the communication becoming more confused and out of context. Therefore more layers mean a greater risk of distortion and confusion among the staff. Such distortions cause a lack of productivity, frustration, confusion, and inept management. Conversely, management is receiving feedback from the field that is invalid since the original plans, orders, and ideas were not acted on; the same risk of distortion exists with the return flow. The end result of this is that customer service suffers. The image and prestige of Calveta is damaged. Calveta should simplify its management structure, implement an information network, combine some positions and eliminate others. The implementation of a more flat management structure will reduce the chances of distorting communication. 7. Should Frank Calveta move forward with an expansion into the hospital sector? With the proposed acquisition? Calveta should focus on making serious internal improvements before piling on debt, increasing the chances of management turnovers, and getting into business with an organization known to not have the best reputation. Calveta has a great reputation and its ability to function and grow with little debt confirms that their balance sheet is in excellent condition as well. An internal restructure and a recommitment to its values and goals should be the number one priority. Calveta should not move forward with the expansion into the hospital sector at this time. On the other hand the acquisition of GSD may be an excellent move for Celveta. This acquisition will increase Celveta’s geographical presence and increase its assets without increasing its debt load. With some management restructuring done within GSD, Frank should be able to meet his father’s financial goal to double profit in 5 years.

Distinguishing Bipolar and Bpd Disorders

Distinguishing Bipolar and BPD Disorders Tonjanika Boyd North Carolina Central University Introduction Bipolar and Borderline Personality Disorder are mood and personality disorder respectively, that have had many challenges amongst psychiatrist in differentiation. Not only does the two disorders share several symptoms and associated impairments, there is also continuing debates in the psychiatric literature about whether the two disorders actually represent different conditions (Hatchet, 2010).The following paper compares and contrasts Bipolar and Borderline Personality Disorders and discusses implications of differential diagnosis of the disorders that can lead to long-term effects for the patient due to the fundamentally different treatment each disorder needs. Comparison of Bipolar and Borderline Personality Disorder Bipolar Disorder According to the Diagnostic and Statistics Manual of Mental Disorder, 4th edition Text Revision (DSM-IV-TR), bipolar is a recurrent mood disorder fe aturing one or more episodes of mania or mixed episodes of mania and depression (Antai-Otong, 2008).The bipolar disorders include, bipolar I disorder, bipolar II disorder, cyclothymic, and bipolar NOS disorders. Bipolar I disorder includes one or more manic or mixed episodes, usually with a major depressive episode. Bipolar II disorder includes one or two major depressive episodes and at least one hypomanic episode. Cyclothymic disorder includes at least 2 years of hypomanic periods that do not meet the criteria for the other disorders. Bipolar NOS, does not meet any of the other bipolar criteria. The etiology of Bipolar disorder has been researched and documented for many years and has many theories and perspectives.Causative factors include psychodynamic, existential, cognitive behavioral and developmental and complex biologic and genetic factors (Antai-Otong, 2008). Signs and Symptoms (s/s) of Bipolar disorder varies from the type of episode they patient is experiencing. Major de pressive episodes include a depressed mood or lose of interest for at least 2 weeks and five or more of the following: Significant weight loss or gain, insomnia or hypersomnia, psychomotor agitation or retardation, fatigue, worthless feelings or inappropriate guilt, problem concentrating or recurrent thoughts of death.Manic episodes s/s includes, persistent elevated irritable mood of more than one week, increased self-esteem, decreased sleep, increased, increase talk and pressured speech, racing thoughts and ideas, distractibility, extreme goal-directed activity, excessive buying, sex and business investments (Pederson, 2012). In order to have successful treatment of bipolar disorder, a holistic approach is the best therapy. This includes, pharmacologic and psychotherapeutic interventions. Pharmacologic include mood stabilizers, anti-depressants, anti-psychotics and electroconvulsive therapy.There has been a controversy with the use of anti-depressants for treatment due to its effec t with mood stabilizers. It is not a mainstay, but is still prescribe when they are not sure if it is unipolar or bipolar, but becomes dangerous when switching from a depressive episode to a manic or hypomanic episode (Antai-Otong, 2011). Electroconvulsive therapy is the last resort if the mood stabilizers and anti-psychotics fail or when an immediate intervention is needed. Psychotherapeutic intervention is mostly where the nursing care is used more frequently.Psychosocial and behavioral intervention, both fall under the umbrella of psychotherapeutic treatment and are important for more positive treatment outcomes. If a patient is in the acute phase, the nurses’ main focuses are safety and maintain a therapeutic milieu that facilitates resolution of symptoms and minimizes complications. The nurse also educated the client and family about medications, treatment options and other psychotherapies (Antai-Otong, 2011). Borderline Personality Disorder (BPD)BPD originated in the 19 30’s, when it was used to describe patients who were on the â€Å"border† between neuroses and psychosis. It is the most common complex and severely impairing personality disorders. According to DSM-IV, it is a pattern of instability in interpersonal relationships, self-image, affect and marked impulsivity (Swift, 2009). The etiology of BPD includes, genetic predisposition, family history of mood disorders and maybe related to bipolar disorder, physical and sexual abuse. About 2% of the population experiences BPD and mostly female.The symptoms of BPD are maladaptive behavior learnt to make sense of the world and to manage the persistent negative messages received (Eastwick & Grant, 2005). Signs and symptoms, consists of patterns of unstable interpersonal relationships, fear of abandonment, splitting (love or hate), impulsiveness in sex, substance abuse, binge eating and reckless driving, suicidal gestures, such as self-mutilation, intense mood changes that last for hou rs, chronic emptiness, intense anger and transient paranoid ideation (Pedersen, 2012).Managing BPD is challenging and can be emotionally and physically draining for the nurse involved and other members of the healthcare team. The nurse-patient relationship is frequently confrontational due to the patient difficulty with interpersonal relationships and dysfunctional emotional regulation, which results in aggression towards the nurse. Evidence has shown that people experiencing BPD are more likely to harm themselves than others (Swift, 2009). Treatment of BPD requires an integrated psychobiologic approach that includes, pharmacologic and psychotherapeutic interventions.This combination is called psychopharmacologic therapy. There have been many variations of drugs used to treat BPD, due to limited success. There has been limited success in the use of psychotropic medications in clients with borderline personality disorder. Mood stabilizers, anti-depressants and anti-psychotics are onl y effective in providing relief in the symptoms of difficulty controlling behaviors, impulsivity, self-injurious behaviors and depression (Antai-Otong, 2011).Diagnostic Dilemma of Bipolar and BPD Disorder According to the criteria outlined in the DSM-IV-TR there is a systematic difference between patients with BPD and bipolar disorder. It was found that patients with bipolar II exhibited mood swings that varied between euthymia, elation and depression and mood swings with BPD rotated between euthymia, anger and anxiety. A diagnosis between the two boiled down to how the emotional and behavioral instability exhibited by a client is conceptualized.In other words, a counselor must decide whether the symptoms are best attributed to an acute mood disorder or they are just the latest manifestations of a more chronic problem (Hatchett, 2010). The challenge is not the case of being able to rule out acute episodes of mania, but when assessing the possibility of rapid-cycling bipolar disorder or a mixed episode. The actual definition of rapid cycling is often misunderstood in the mental health community and ruling out mixed episode is even a greater test in distinguishing between bipolar and BPD, due to many patients not having an accurate history of their symptoms.This is important because, according to DSM-IV-TR (2000) â€Å"The individual experiences rapidly alternating moods (sadness, irritability, euphoria) accompanied by symptoms of a Manic Episode†¦and a Major Depressive Episode† (p. 362). It becomes difficult and nearly impossible to distinguish a mixed episode from the chronic anger and dysphoria common to those with BPD. Repercussions for differentiating between the disorders for treatment are evident for counselors who are responsible for creating and implementing treatment plans. Accurate diagnosis is fundamental for effective treatment.A diagnosis of Bipolar disorder is treated with psychoactive medication, whereas for BPD patients, that is not effective as a mainstay of therapy. When BPD is appropriately diagnosed, it encompasses a more holistic approach of intervention strategies, such as dialectical behavior therapy (DBT). Those who consider BPD to be a variant of bipolar disorder contend that treatment should proceed with mood stabilizers and atypical anti-psychotics and those on the other side of the debate recommend an intensive psychotherapy model, such as DBT (Hatchett, 2010).Conclusion Careful consideration to distinguish more accurately the difference between an acute mood disorder and a more chronic and pervasive personality disorder through the diagnostic process is essential. A mood disorder is discerned by distinct episodes of mania, hypomania, or depression that continue for specified periods and a personality disorder is characterized by persistent and rigid patterns of maladaptive behavior and intrapersonal experience that influence areas of functioning.I feel the debate between differential diagnosis of t hese disorders can at least shift towards a solution by considering an overhaul in the definition and placement of mood and personality disorders in Axis I and II. Through Axis II was developed to encourage clinicians to consider more enduring personality characteristics that may impact treatment, as Fowler et al (2007) pointed out, some Axis I disorders are actually more chronic than many Axis II disorders, which are more likely to remit than is commonly believed.Also, I noticed through my research that maybe there needs to be another type of assessment tool created when assessing patients for mood or personality disorders or specific training on how to distinguish between BPD an bipolar disorder to ensure more accurate diagnosis. For the DSM-V now being drafted, proposals have been made to either eliminate personality disorders altogether or integrate theme into Axis I. In that scenario BDP might be reclassified as a mood or impulse control disorder (Hatchett, 2010).Distinguishing between Bipolar and BPD disorder is significant for the patient, treatment teams, family and mental health community, due to the major difference in the treatment plans for each disorder. Recognizing which disorder the patient has is fundamental in positive outcomes as they progress through the proper comprehensive psychopharmacologic therapy. References American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders (4th ed. , text rev. ). doi:10. 1176/appi. books. 9780890423349.Antai-Otong, D. (2008). Psychiatric Nursing: Biological and Behavioral Concepts, 2nd ed. , Thomson, Delmar Learning. Hatchett, G. T. (2010). Differential Diagnosis of Borderline Personality Disorder from Bipolar Disorder: Journal of Mental Health Counseling, 32:3, 189-205. Pederson, D. D. (2012). Psych Notes: Clinical Pocket Guide, 3rd ed. , F. A. Davis Co. Philadelphia. Swift, E. (2009). Borderline personality disorder: aetiology, presentation and therapeutic relationship: Mental Health Nursing, 13:3, 22-25.

English for Special purposes program design Assignment

English for Special purposes program design - Assignment Example In terms of learning the language it is a big group. Specific teaching strategies should be applied to the students of such a quantity in order to make the learning effective. Specialization of the group that the present program is designed for is Information Technologies, particularly Informatics and Programming. The level of English is Low to Intermediate. The students are supposed to have basic language proficiency prior to the study of English for Science and Technology (EST). A student should also be trained into handling skills, abilities and proficiency that clearly belong to the domain of general English. The only source of grammar that this program is designed to use is "English Grammar In Use with Answers and CD ROM: A Self-study Reference and Practice Book for Intermediate Students of English (Grammar in Use) (Paperback)", a book by Raymond Murphy. Another course book that will be used during the program of EST is "Technical English" by Comfort, Hick and Savage. This book is aimed to assist students in learning English for use in technical areas. The students will use this book after completing and passing the test on Murphy, the previous text book. The reason to use the books one by one is due to the fact that "Technical English" is meant to be used with previous knowledge of the language. However this book requires understanding basic English, it is designed specifically for EST purposes and that is why even in case the students will not pass the grammatical test, it will not hinder the learning of the technical English. Besides, special vocabulary is designed for students with Information Technology specialization so that they would be proficient in their field. The targeted students need to know specific vocabulary and that is the reason that a list of thousand words has been developed to introduce students to the subject. English for Science and Technology (EST) requires specific teaching strategies and learning activities to deliver the knowledge to students. Practically, EST eliminates teaching informal language and does not encompass the whole range of language requirements that a regular learner of ESL has. For purposes of current program, a student should be able to read literature pertaining to his subject, to discuss it with his colleagues, to give lectures and write his own articles in English. However the level of English would be basic, that would let the student to reflect his or her ideas without applying rich vocabulary, but with a knowledge of scientific words.Here are a few of specific terms that the vocabulary will include: total quality management, total quality control; total productive maintenance; design to cost, life cycle cost; concurrent engineering ; project management; productivity improvements; modeling; how enterprises adjust to environmental issues; expert systems; multi-te chnology systems etc. (3) a number of teaching strategi

Marketing Mix Assignment Example | Topics and Well Written Essays - 1750 words

Marketing Mix - Assignment Example The Le Bistrot Pierre restaurant chain provides a wide array of dishes to be presented to its customers. It is found that the restaurant provides a wide range of dishes on appetizers ranging from vegetable to non-vegetable dishes. For instance, the vegetable dishes consist of items like tomato preparations, onion soups and mushroom dishes. In the non-vegetarian section the restaurant in the appetizer front presents its customers with items like snail dipped in garlic butter. (Pierre’s Bistro, 2010) The restaurant is widely known not only for its flavored dishes but also for its economical price ranges. It is observed that the restaurant provides two to three courses of lunch at highly affordable rates. The rates charged for the lunch sessions at the restaurant vary between ten to twelve pounds only making it highly attractive from the customer’s side. The customers can even order for a glass of wine before commencing on the lunch at a humble rate of fifteen pounds. (Le Bistrot Pierre, n.d.; Le Bistrot Pierre: Restaurant Views, n.d.; Le Bistrot, 2010). In regards to its distribution parameters the restaurant chain Le Bistrot Pierre has opened up its eight unit in Harrogate, a township in Yorkshire. It is also planning to open up with its ninth arm sometime later this year. The restaurant chain Le Bistrot Pierre claims that its newly opened arm would help attract huge footfalls for the presence of a bar cum dining space. It also states that it is promoting a space for the balcony purpose also in the restaurant. The restaurant chain has other operating units spread along different key areas of United Kingdom. They include areas like Nottingham, Leicester, Derby, Leamington Spa, Stratford-upon-Avon and Sheffield. (Chomka, 2010) The restaurant outlet of Le Bistrot Pierre situated at Leamington Spa is in the center of many shopping outlets and

Inferential Statistics Project Example | Topics and Well Written Essays - 1500 words

Inferential - Statistics Project Example The data sets are divided into two sets; Android, Windows and Others representing the operating systems in the market and a dependent variable Smartphone on the category indicating the total cell phone sold with the operating system. The independent variables are the App is representing the App store, GUI represents the Graphical User Interface of the smartphone and the Functionality representing the functions carried out by the operating systems and the apps. The data is bivariate data as two variables are measured in a single study (William Mendenhall III, 2013). We calculated the operating system market share and the customer buying behavior towards the software capabilities of the smartphone. Most consumers prefer smartphones running on Android platform; on average 10 Android phones are sold daily. The consumer‘s are influenced by the app store on the phone, with 9 people every day says that the app store matters to them most. The positive coefficient indicates the directional effects of the independent variables and the effect they will have on the depend variable smartphone. Thus, with an increase in App, GUI or Functionality results to increase in sales of smartphones. Meaning that the consumer behavior depends on the software installed or can be installed on the gizmo. Goodness to fit ≠¥ 0.80 or 80% and we reject Reject H0 if p-value ≠¤ ÃŽ ±, where ÃŽ ± is the level of significance for the test (David R. Anderson, 2011). Thus p-value ≠¥ 0.0000, thus the null hypothesis is accepted. At 95% confidence level (1.869, 5.088), this are plausible values of parameter where mean may lie; thus, we expect more consumers to be influenced by App store parameter in smartphone. Thus we expect the sales of Android phones to increase with the same parameter as they are the market

How you have experienced social change in Qatar over the last 5 years Essay

How you have experienced social change in Qatar over the last 5 years or so - Essay Example The above changes are largely because Qatar has been hosting numerous sporting events. Mubarak Al Mana, who is the head of the country’s women’s sport committee, has played an important role in supporting women’s involvement in sports. Apart from the increase in the number of women participating in the country’s labor force, most of them tend to focus in certain occupations, particularly teaching and clerical jobs. As the Qatar society started the complex process of implementing social change decade ago, the imbalanced status of women became prominent. It also became a difficult obstacle. Nevertheless, the country has taken vital recognizable steps in the past five years to ensure that women have similar privileges as men. For instance, women have the privilege to vote and contend for any political position during their parliamentary elections (Great Britain, 2004). In 2010, Sheikha Maha Mansour was appointed as the first woman judge in the country. This greatly indicated how Qatar was experiencing a speedy social change. The situation also created an important example to other women who are currently studying different courses previously meant for men. Another recognizable social change is the organization of the family laws. Formerly, resolutions of family problems were dependent on the judge’s understanding of Islamic law. However, this has changed since 2003 when women were given th e privilege to participate in public life and business. In addition, they also have the privilege to travel alone because laws requiring a guardian’s authority for a woman to be given a passport were withdrawn during this

Cross Cultural Management Issues of UK, China, Spain, and Finland Essay

Cross Cultural Management Issues of UK, China, Spain, and Finland - Essay Example This paper will assess the management issues which could arise in an international team consisting of English, Chinese, Spanish and Finnish members. It will then seek to propose methods for addressing these issues and dealing with them effectively. Cross-Cultural Concepts and Issues Which Could Arise There exist many differing theories as to the way in which cultures differ considerably on several levels. One pertinent theory put forth by Maletzke (1996) categorises cultural differences into 9 groups. Although these will be briefly stated, they are relevant in assessing which problems could arise for a manager of an international group. Maletzke states that cultural differences can consist in many different categories (1996). The national character of a culture consists in the shared basic behavioural patterns and personality traits of the people in the culture. In the business arena this can be an issue if one culture, being inherently different to another, finds it difficult to und erstand, or co-operate with the other. For example, the Spanish culture is open, loud and friendly whereas the Finnish culture is formal, softly spoken and favours courteousness. This may cause the Finnish person to be offended or overwhelmed by the playful, less formal characteristics of the Spanish person. The Spanish may also overwhelm the Chinese person as Chinese tend to be more softly spoken and less verbal. Another important element of culture is time concept, which has the potential to differ greatly between cultures and cause problems when co-ordinating meetings and planning schedules. Here there exists the potential for the Chinese and the English person to conflict in that the former is less prompt for meetings, and often has no fixed start or end time whereas the English person desires a more specified form of time management. This also applies to the Spanish who may stand alone in his lack of planning, relaxed perception of time and lack of willingness to restrict his d ay to particularly planned schedules and meeting times. The space concept of culture can cause problems in that the Finnish, English and Chinese may conflict with the Spanish concept of space. The Mediterranean culture of the Spanish places little importance on private space, and may even adopt constant forms of physical contact in order to communicate and express himself. This may cause discomfort, particularly for the Finnish culture which is likely to see physical contact between mere business associates as inappropriate and even offensive. For example, the Finnish method of greeting is a simple handshake with a smile, as is the English method. The Spanish is more likely to shake hands, yet place a hand on the back of the person he greets, or even kiss the cheek of the person he greets. The two methods are rather different and have the potential to cause issues in the business arena. Perception as a facet of culture also has the potential to be an issue, in that it could represen ts which each culture defines as important and non-important. Perhaps the largest potential of raising issues is the language and non-verbal communication of each culture. Of course, different languages are a major problem, though more importantly, even if

Persuasive memo on Internet Essay Example | Topics and Well Written Essays - 250 words

Persuasive memo on Internet - Essay Example A modified and lenient regulation on Internet use can prove to be useful in more than one ways for our organization. First of all, it will provide the employees with the much needed incentive to persevere even more for the accomplishment of the company’s goals. Secondly, it is often observed that employees tend to retard during breaks and lunch periods; however, if such a regulation is passed, then it will act as a catalyst in energizing employees and boosting their motivation levels during breaks. The permission to interact with their friends and family members on social networking websites, surf news or watch highlights of a soccer game, can all prove to be key drivers in bringing out enhanced performance from the employees. Moreover, through internet use in breaks, employees can share information with each other, which would develop a knowledge-based culture in our organization. Consequently, a regulation to allow internet use during breaks and lunch periods would ultimately benefit both the employees and the

A rose for emily Essay Example | Topics and Well Written Essays - 250 words - 1

A rose for emily - Essay Example At the time Emily remains indoors, Tobe’s hair is used in place of Emily’s to tell time in the town. The reader knows about this symbolism following the change in timing of events every time hair is used. Pocket watch has also been used a symbol of time in the story. Board of Aldermen members visited Emily to deliberate on tax issues ten years before her death (Faulkner, 2007). During this visit, a pocket watch that was invisible ticked within Emily’s clothing. â€Å"Then they could hear the invisible watch ticking at the end of the gold chain† (Faulkner, 2007).This represents that Emily was aware of time factor in her life, and that time acted as an invisible force that compelled her to become self-conscious about her life and the people around. At this time, time is ticking down towards happiness chances for Emily. The reader knows about this symbolism from the flashbacks presented in the story. Pocket watch is literally used to observe time, and each event in the story is time conscious. This is more so in relation to Emily’s

Managerial Leadership role for Nurses’ Use of Research Evidence Essay Example for Free

Managerial Leadership role for Nurses’ Use of Research Evidence Essay The rapid noticeable change in healthcare delivery coupled with professional responsibilities of nurses to incorporate research evidence into their decision making underscores the need to understand the factors involved in implementing evidence-based practice. Linking current research findings with patients’ conditions, values, and circumstances is the defining feature of evidence-based practice. Significant and rational for using evidence in practice in nursing care Evidence-based practice (EBP) is an approach to health care where the best evidence possible is used in health professionals to make clinical decisions for individual. It involves complex and conscientious decision-making based on the available evidence, patient characteristics, situations, and preferences( McKibbon, 1998). Evidence-based practice in nursing is defined as â€Å"integration of the best evidence available, nursing expertise, and the values and preferences of the individuals, families and communities who are served† (Sigma Theta Tau International position statement on evidence-based practice February 2007 summary, 2008). The gist of evidence based health care is the integration of individual clinical expertise with the best available external clinical evidence and the values and expectations of the patient. There are different recourses of evidence which includes the following: †¢Research Evidence: which refers to methodologically sound, clinically relevant research about the effectiveness and safety of interventions, the accuracy of assessment measures, the strength of causal relationships and the cost-effectiveness of nursing interventions. †¢Patients Experiences and Preferences: identification and consideration of patient’s experiences and preferences are central to evidence-based decision making. Patients may have varying views about their health care options, depending on factors such as their condition personal values and experiences, degree of aversion to risk, resources, availability of information, cultural beliefs, and family influences. †¢ Clinical Expertise. AS the mixing of these different types of evidence may be influenced by factors in the practice context such as available resources, practice cultures and norms leadership styles, and data management, we must consider the level of evidence while using the research evidence to take the proper decision, look to appendix A which is represent the level of evidence. (Haynes, Devereaux, Guyatt, 2002; Sigma Theta Tau International position statement on evidence-based practice February 2007 summary, 2008). Evidence-based practice is a prominent issue in international health care which is intended to develop and promote an explicit and rational process for clinical decision making that emphasizing the importance of incorporating the best research findings into clinical care to ensure the best possible treatment and care derived from the best available evidence (E. Fineout-Overholt, Levin, Melnyk, 2004) Once a new research is completed new evidence comes into play every day, technology advances, and patients present with unique challenges and personal experiences(Krainovich-Miller, Haber, Yost, Jacobs, 2009). The nurse who bases practice on what was learned in basic nursing education soon becomes outdated, then becomes dangerous. Patients are not safe if they do not receive care that is based on the best evidence available to assist them at the time their needs arise, so all aspects of nursing, from education to management to direct patient care, should be based on the best evidence available at the time (Reavy Tavernier, 2008). Through reviewing the literature there is a dramatically changing and advancing in the technology, available body information and quality of care provided, the rapid pace of change in healthcare delivery coupled with professional responsibilities of nurses to incorporate research evidence into their provided care and decision making underscores the need to understand the factors involved in implementing evidence-based practice (Bostrà ¶m, Ehrenberg, Gustavsson, Wallin, 2009; Ellen Fineout-Overholt, Williamson, Kent, Hutchinson, 2010; Gerrish, et al., 2011; Gifford, Davies, Edwards, Griffin, Lybanon, 2007). Before that nurses must first believe that basing their practice on the best evidence will lead to the highest quality of care and outcomes for patients and their families(Ellen Fineout-Overholt, et al., 2010; Melnyk, et al., 2004). To let change occuring, â€Å"there must be a clear vision, written goals, and a well-developed strategic plan, including strategies for overcoming anticipated barriers along the course of the change†(Melnyk, et al., 2004). Emerging evidence indicates that the  leadership behaviors of nurse managers and administrators play an important role in successfully utlizing research evidence into clinical nursing(Amabile, Schatzel, Moneta, Kramer, 2004; Antrobus Kitson, 1999; Gifford, et al., 2007). There is a consistency between many researches that clamethe importance role of the leadership and leadership factors such as support and commitment of managers on the staff at the implication of EBP(Aitken, et al., 2011; Antrobus Kitson, 1999; Melnyk, et al., 2004; Winch, Creedy, Chaboyer, 2002). Nurse managers and administrators are responsible for the professional practice environments where nurses provide care, and are strategically positioned to enable nurses to use research. As being a role model, administrators must be committed to provide the necessary resources such as EBP mentors, computers, and EBP education. Some administrators have tried to encourage a change to EBP by integrating EBP competencies into clinical promotions. However, Miller (2010) argue that this extrinsic motivational strategy is unlikely to be as effective as when people are intrinsically motivated to change. Also there is a claimed that if people are involved in the strategic planning process, they ar e more likely to change to EBP. Intervention protocol for promoting nurses compliance to EBP As the Decision making in health care has changed dramatically, with nurses expected to make choices which based on the best available evidence and continually review them as new evidence comes to light (Pearson et al, 2007). Evidence-based practice involves the use of reliable, explicit and judicious evidence to make decisions about the care of individual patients. As an important role in providing safe and high quality care the nurses must take into account the quality of evidence, assessing the degree to which it meets the four principles of feasibility, appropriateness, meaningfulness and (Doody Doody, 2011; Johnson, Gardner, Kelly, Maas, McCloskey, 1991). What nurses need to operate in an evidence-based manner, is to be aware of how to introduce, develop and evaluate evidence-based practice. There more than one model for introducing the EBP in health care one of them that I chose is the Iowa model. The Iowa model focuses on organization and collaboration incorporating conduct use of research, along with other types of evidence(Doody Doody, 2011; Johnson, et al., 1991). Since its origin in 1994, it has been continually referenced in nursing journal articles and extensively used in clinical research programmes. This model uses key triggers that can be either problem focused or knowledge focused, leading staff to question current nursing practices and whether care can be improved through the use of current research findings(Bauer, 2010; Doody Doody, 2011; Johnson, et al., 1991; Titler, et al., 2001). By using Iowa Model; a question is generated either from a problem or as a result of becoming aware of new knowledge. Then a determination is made about the question relevance to organizational priorities. If the question posed is relevant, then the next step is to determine if there is any evidence to answer the question. Once the evidence has been examined, if there is sufficient evidence, then a pilot of the practice change is performed. If there is insufficient evidence, then the model supports that new evidence should be generated through research (Bauer, 2010). Step one of the Iowa model is to formulate a question. The question if asked in a PICO format is easier to use to search the literature. A PICO format uses the following method to frame the question: Frame question in PICO format †¢ P= Population of interest †¢ I= Intervention †¢ C= Comparison of what you will do †¢ O= Outcome(Hoogendam, de Vries Robbà ©, Overbeke, 2012). The final step to the process is to share the outcomes of the practice change with other in the form of an article or poster. In using the Iowa model, there are seven steps to follow in detail as it is outlined in the figure shown in appendix B. Step 1: Selection of a topic In selecting a topic for evidence-based practice, several factors need to be considered. These include the priority and magnitude of the problem, its application to all areas of practice, its contribution to improving care, the availability of data and evidence in the problem area, the multidisciplinary nature of the problem, and the commitment of staff. Step 2: Forming a team The team is responsible for development, implementation, and evaluation. The composition of the team should be directed by the chosen topic and include all interested stakeholders. The process of changing a specific area of practice will be assisted by specialist staff team members, who can provide input and support, and discuss the practicality of guideline. A bottom-up approach to implementing evidence-based practice is essential as change is more successful when initiated by frontline practitioners, rather than imposed by management. Staff support is also important. Without the necessary resources and managerial involvement, the team will not feel they have the authority to change care or the support from their organization to implement the change in practice. To develop evidence-based practice at unit level, the team should draw up written policies, procedures and guidelines that are evidence based. Interaction should take place between the organization’s direct care providers and management such as nurse managers, to support these changes(Antrobus Kitson, 1999; Cookson, 2005; Doody Doody, 2011; Hughes, Duke, Bamford, Moss, 2006). Step 3: Evidence retrieval Evidence should be retrieved through electronic databases such as Cinahl, Medline, Cochrane and up-to-date web site. Step 4: Grading the evidence To grade the evidence, the team will address quality areas of the individual research and the strength of the body of evidence overall (see appendix A for level of evidence). Step 5: Developing an Evidence-Based Practice (EBP) standard After a critique of the literature, team members come together to set recommendations for practice. The type and strength of evidence used in practice needs to be and based in the consistency of replicated studies. The design of the studies and recommendations made should be based on identifiable benefits and risks to the patient. This sets the standard of practice guidelines, assessments, actions, and treatment as required. These will be based on the group decision, considering the relevance for practice, its feasibility, appropriateness, meaningfulness, and effectiveness for practice. To support evidence-based practice, guidelines should be devised for the patient group, health screening issues addressed, and policy and procedural guidelines devised highlighting frequency and areas of screening. Evidence-based practice is ideally a patient centered approach, which when implemented is highly individualized. Step 6: Implementing EPB For implementation to occur, aspects such as written policy, procedures and guidelines that are evidence based need to be considered. There needs to be a direct interaction between the direct care providers, the organization, and its leadership roles (e.g. nurse managers) to support these changes. The evidence also needs to be diffused and should focus on its strengths and perceived benefits, including the manner in which it is communicated. This can be achieved through in-service education, audit and feedback provided by team members. Social and organizational factors can affect implementation and there needs to be support and value placed on the integration of evidence into practice and the application of research findings(Aitken, et al., 2011; Doody Doody, 2011; Gerrish, et al., 2011; Reavy Tavernier, 2008) Step 7: Evaluation Evaluation is essential to seeing the value and contribution of the evidence into practice. A baseline of the data before implementation would benefit, as it would show how the evidence has contributed to patient care. Audit and feedback through the process of implementation should be conducted and support from leaders and the organization is needed for success. Evaluation will highlight the programme’s impact. Barriers also need to be identified. Information and skill deficit are common barriers to evidence-based practice. A lack of knowledge regarding the indications and contraindications, current recommendations, and guidelines or results of research, has the potential to cause nurses to feel they do not have sufficient training, skill or expertise to implement the change. Awareness of evidence must be increased to promote the translation of evidence into practice . A useful method for identifying perceived barriers is the use of a force field analysis conducted by the team leader. Impact evaluation, which relates to the immediate effect of the intervention, should be carried out. However, some benefits may only become apparent after a considerable period of time. This is known as the sleep effect. On the contrary, the back-sliding effect could also occur where the intervention has a more or less immediate effect, which decreases over time. We must not to evaluate  too late, to avoid missing the measures of the immediate impact. Even if we do observe the early effect, we cannot assume it will last. Therefore, evaluation should be carried out at different periods during and following the intervention (Doody Doody, 2011). Nursing leadership is an essential role for promoting evidence-based practice while the nurse managers and administrators are responsible for the professional practice environments where nurses provide care, are strategically positioned to enable nurses to use research. AS the leadership is essential for creating change for effective patient care the leadership behaviors are critical in successfully influencing the stimulation, acceptance, and utilization of innovations in organizations (Antrobus Kitson, 1999; Gifford, et al., 2007). From my perspective I consider that the leaders and managers are the corner stone for utilizing researches and make practices based on evidence. By playing a role model for staff and handling the authority they have a magic force to urges the staff to use evidence based in there practice. Leaders can encourage the staff to use EBP in their practice in several ways such as increase the staff awareness, stimulating the intrinsic motivation of people, implying an effort to increase the will and internal desire to change through support encouragement, education, and appealing to a common purpose, monitoring performance, strengthen the body of knowledge that the staff have by forcing them to attend and participate in conferences, workshops Journal clups, giving rewards to staff who collaborate in finding, utilizing and applying the EBP and make promotion and appraisal according to adherence to application of EBP. Implication of EBP For implementation to occur, aspects such as written policy, procedures and guidelines that are evidence based need to be considered. There needs to be a direct interaction between the direct care providers, the organization, and its leadership roles (e.g. nurse managers) to support these changes. The evidence also needs to be diffused and should focus on its strengths and perceived benefits, including the manner in which it is communicated. This can be achieved through in-service education, audit and feedback provided by team members. Social and organizational factors can affect implementation and there needs to be support and value placed on the integration of evidence into practice and the application of research findings. There are many ways that can be used to create an environment to implement and sustain an area of EBP such as : -Development of EBP champions; Use of EBP mentors; Provision of resources such as time and money; Creation of a culture and expectation related to EBP; Use of practical strategies including EBP workgroups, journal club and nursing rounds (Aitken, et al., 2011). EBP is being used in every aspect of the life, especially in the health care. The most common application of EBP is not only in intervention or treatment plane, but also the EBP process has been applied to making choices about diagnostic tests and protocols to insure thorough and accurate diagnosis, selecting preventive or harm-reduction interventions or programs, determining the etiology of a disorder or illness, determining the course or progression of a disorder or illness, determining the prevalence of symptoms as part of establishing or refining diagnostic criteria, completing economic decision-making about medical and social service programs. Nursing research proves pivotal to achieving Magnet recognition, yet the term research often evokes an hunch of mystery. Most of the policy, guidelines. And protocols that guide the work in the organization are based on evidance (Weeks Satusky, 2005). Also, it is also useful to think of EBP as a much larger social movement. Drisko and Grady (2012) argue that at a macro-level, EBP is actively used by policy makers to shape service delivery and funding. EBP is impacting the kinds of interventions that agencies offer, and even shaping how supervision is done. EBP is establishing a hierarchy of research evidence that is privileging experimental research over other ways of knowing. There are other aspects of EBP beyond the core practice decision-making process that are re-shaping social work practice, social work education, and our clients lives. As such, it may be viewed as a public idea or a social movement at a macro level (Evidence-Based Practice: Why Does It Matter?, 2012). Cost effectiveness of using EBP in health care  Beneficial outcomes of the implementation and use of evidence-based practice by staff nurses include increased ability to offer safe, cost-effective,  and patient-specific interventions. Critical thinking skills and leadership abilities can also grow because of the use of evidence based practice; it is a way for staff nurses to become involved in change and regain ownership of their practice (Reavy Tavernier, 2008). EBP used in clinical practice lead to make improvement in quality of provided care, which lead to improve the patients outcome, patient satisfaction and employee satisfaction. All these aspect are directly and indirectly lead to increase the cost effectiveness of the organization. When the patient satisfaction increased the patient acceptance to the organization increased, the employee satisfaction also increases and turnover will decrease all these things will increase the financial revenue to the organization. Also when using EBP in health care this will lead to decrease errors, complications and losses (e.g. compliance of evidence based infection control guidelines will lead to decrease incidence of infection, decrease length of stay an d decrease the cost of patient treatment), another example is using EBP to treat diabetic foot will result in decreasing the loses and increases the satisfaction so adherence to EBP will be costly effective when it result in better outcome, quality of care and satisfaction. Sometimes using EBP in certain area is costly; in such cases we must weighing the benefits ( immediately and after considered period of time) and mak e our decision based on the collected data and information. References: Aitken, L. M., Hackwood, B., Crouch, S., Clayton, S., West, N., Carney, D., et al. (2011). Creating an environment to implement and sustain evidence based practice: A developmental process. Australian Critical Care, 24(4), 244-254. Amabile, T. M., Schatzel, E. A., Moneta, G. B., Kramer, S. J. (2004). Leader behaviors and the work environment for creativity: Perceived leader support. The Leadership Quarterly, 15(1), 5-32. Antrobus, S., Kitson, A. (1999). Nursing leadership: influencing and shaping health policy and nursing practice. Journal of Advanced Nursing, 29(3), 746-753. Bauer, C. (2010). Evidence Based Practice:Demystifying the Iowa Model Providing optimal care through promotion of professional standard, networking and development, 25(2). Bostrà ¶m, A.-M., Ehrenberg, A., Gustavsson, J. P., Wallin, L. (2009). Registered nurses application of evidence-based practice: a national survey. Journal Of Evaluation In Clinical Practice, 15(6), 1159-1163. Cookson, R. (2005). Evidence-based policy making in health care: what it is and what it isnt. Journal Of Health Services Research Policy, 10(2), 118-121. Doody, C. M., Doody, O. (2011). Introducing evidence into nursing practice: using the IOWA model. British Journal of Nursing, 20(11), 661-664. Evidence-Based Practice: Why Does It Matter? (2012). ISNA Bulletin, 39(1), 6-10. Fineout-Overholt, E., Levin, R. F., Melnyk, B. M. (2004). Strategies for advancing evidence-based practice in clinical settings. Journal of the New York State Nurses Association, 35(2), 28-32. Fineout-Overholt, E., Williamson, K. M., Kent, B., Hutchinson, A. M. (2010). Teaching EBP: strategies for achieving sustainable organizational change toward evidence-based practice. Worldviews On Evidence-Based Nursing / Sigma Theta Tau International, Honor Society Of Nursing, 7(1), 51-53. Gerrish, K., Guillaume, L., Kirshbaum, M., McDonnell, A., Tod, A., Nolan, M. (2011). Factors influencing the contribution of advanced practice nurses to promoting evidence-based practice among front-line nurses: findings from a cross-sectional survey. Journal of Advanced Nursing, 67(5), 1079-1090. Gifford, W., Davies, B., Edwards, N., Griffin, P., Lybanon, V. (2007). Managerial leadership for nurses use of research evidence: an integrative review of the literature. Worldviews on Evidence-Based Nursing, 4(3), 126-145. Haynes, R. B., Devereaux, P. J., Guyatt, G. H. (2002). Clinical expertise in the era of evidence-based medicine and patient choice. ACP Journal Club, 136(2), A11-A14. Hoogendam, A., de Vries Robbà ©, P. F., Overbeke, A. J. P. M. (2012). Comparing patient characteristics, type of intervention, control, and outcome (PICO) queries with unguided searching: a randomized controlled crossover trial. Journal Of The Medical Library Association: JMLA, 100(2), 121-126. Hughes, F., Duke, J., Bamford, A., Moss, C. (2006). Enhancing nursing leadership: Through policy, politics, and strategic alliances. Nurse Leader, 4(2), 24-27. Johnson, M., Gardner, D., Kelly, K., Maas, M., McCloskey, J. C. (1991). The Iowa Model: a proposed model for nursing administration. Nursing Economic$, 9(4), 255-262. Krainovich-Miller, B., Haber, J., Yost, J., Jacobs, S. K. (2009). Evidence-based practice challenge: teaching critical appraisal of systematic reviews and clinical practice guidelines to graduate students. Journal of Nursing Education, 48(4), 186-195. Melnyk, B. M., Fineout-Overholt, E., Feinstein, N. F., Li, H., Small, L., Wilcox, L., et al. (2004). Nurses perceived knowledge, beliefs, skills, and needs regarding evidence-based practice: implications for accelerating the paradigm shift. Worldviews on Evidence-Based Nursing, 1(3), 185-193. Reavy, K., Tavernier, S. (2008). Nurses reclaiming ownership of their practice: implementation of an evidence-based practice model and process. Journal of Continuing Education in Nursing, 39(4), 166-172. Sigma Theta Tau International position statement on evidence-based practice February 2007 summary. (2008). Worldviews on Evidence-Based Nursing, 5(2), 57-59. Titler, M. G., Kleiber, C., Steelman, V. J., Rakel, B. A., Budreau, G., Everett, C. L. Q., et al. (2001). The Iowa Model of Evidence-Based Practice to Promote Quality Care. Critical Care Nursing Clinics of North America, 13(4), 497-509. Weeks, S. K., Satusky, M. J. (2005). Demystifying nursing research: to encourage compliance with Magnet accreditation standards, further you r facilitys research initiatives. Nursing Management, 36(2), 42. Winch, S., Creedy, D., Chaboyer, W. (2002). Governing nursing conduct: the rise of evidence-based practice. Nursing Inquiry, 9(3), 156-161.

Human Comfort And Thermal Comfort Engineering Essay

Human Comfort And Thermal Comfort Engineering Essay Abstract: The main purpose of the HVAC system is to achieve clean indoor air quality and human comfort (thermal comfort), there are many HVAC systems a designer or owner has the option to select based on the factors such as the type of the building, architecture, location, shape, surrounding climate, occupancy, envelop, level and frequency of activities, and the system operation schedule. In addition to the above base factors that an HVAC system is expected to be selected upon, the energy consumption, system efficiency, initial and operational cost, and finally, feasibility (short and long term rebound positive effect) are of the owners and designers critical concerns. This paper will discuss the elements of a typical feasible high performance low cost, fine tuned HVAC DDC integrated system to achieve the best for users, owners, and environment. 1. Introduction HVAC and its associated auxiliaries system are major energy consumers in a building, the rapid development of the advanced technology nowadays boosts the HVAC system feasibility as more complex control systems are developed for this industry and additional fine-tune, prompt response, standardized communication, ease of control and monitor, and remote accessibility. The BMS/DDC (Building Management System/ Direct Digital Control) integrated system is the core of a good feasible high-efficient HVAC system. The BMS is the most recent High-Tech energy management system that manage a building performance to the maximum desirable pre-determined set of parameters which able to control, monitor, adjust, save and record mostly all of the building facilities and utilities when integrated with all of the compatible buildings Sub-LANs, a DDC is one of those LANs and can communicate with other control LANs under the supervision of the BMS. BMS is able to supervise, control, adjust and record the illumination, electric power control, HVAC, security and observation, magnetic card and access, fire alarm, lifts, and other engineering systems. Integrated with the BMS, the DDC performs the HVAC control management and communicates with the other building controllers via the BMS to achieve integration based on a specified, programmed event sequence. I The DDC is the heart of an efficient HVAC system, it finely tunes the digital/analog input/output communication between sensors, probes, stand-alone controllers, LANs controllers, and finally the controlled element which could be an actuator that adjust the process variable (flow, temperature, level, or pressure), and allows for a feedback signal to further adjust the desired process set-point. This whole process is reported in a real-time manner to the BMS system for further coordination with the other buildings controllable systems to achieve integration based on the pre-programmed parameters. In order to achieve the highest human comfort, energy saving, and a long term rebound effect strategy, The BMS/DDC system should be interlocked and integrated with a high-efficient and feasible HVAC system, this combination can awards energy saving, system and environment sustainability, human comfort, and business feasibility. An Optimal Air System is a good example of a low-coast, high-performance, energy-efficient and a good investment for long-term rebound pay-back effect. Optimal Air System concept is based on the low temperature supply system that needs, less energy consumption by the most energy consumer auxiliary that is the fan, this affects the sizing of the ducts (less duck size), air handling units and fan motors, all of which will be smaller and results in a system that requires less space and uses less power. As this paper focuses on the HVAC/DDC integrated system application for human comfort, energy saving, and feasibility (long-term rebound effect), I will discuss and focus on the DDC and Optimal Air System integration for the above purposes and define characteristics, elements, and functions of both systems. II 2. DDC DDC has became the latest and the most recently used system for HVAC controls after the pneumatic and electromechanical control systems, digital pre-programmable controllers can handle extensive digital/analog data process from inputs (sensors, tranceducers and transmitters) that tyapically mesure temperature, flow, humidity, pressure or level, and outputs to final controlled devices to adjust a process variable based on a preset parameters, also recives a feedback signals from inputs again to further adjust signal command errors for best results based again on the setpoints. Digital inputs are Dry contacts from a control device, analog inputs are voltage and current signals that mesure variables such as humidity, pressure, level or flow form sensing devices and converted to percentage. Digital outputs are of 1 or 0 binary that either stops or starts equipments via a relay, analog outputs are voltage or current signals that control a process variable control devices such as valves, m otors or dampers. The DDC program code may be customized for intended use such as: Time schedule, sequence of operation, trend logs, alarms. 2.1 Elements of a DDC As described above, the three functional elements needed to perform the functions of a DDC system are: a) A measurement element (Sensor, prob, Transmitter, Transducer) b) An error detection element (Digital/Analog/pneumatic Controller, PCU) c) A final control element (Motor/Piston Actuator, VFD, VSD, Relay) 2.2 DDC controled mediums The DDC controls two variables: I. A controlled variable is the process variable that is maintained at a specified value or within a specified range. II. A manipulated variable is the process that is acted on by the control system to maintain the controlled variable at the specified value or within the specified range. 1 2.3 Functions of DDC system In any DDC, the four basic functions that occur are: a) Measurement b) Comparison c) Computation d) Correction 3. DDC LAN-WAN Configuration DDC is where mechanical and electrical systems and equipment are joined with microprocessors that communicate with each other and to a central computer BMS. This computer and controllers in the building Management system can be networked to the internet or serve as a stand alone system for the local peer-to-peer controller network only Fig 1. Additionally, the controllers themselves do not need a computer to operate efficiently as many of these controllers are designed to operate as stand-alone controllers and control the specific equipment they are assigned to control. Fig 1. Typical peer-to-peer controller network [1] 2 With a few exceptions, each DDC or building automation controller holds their own programs and has the ability to communicate to other DDC building automation controllers. It is important for the DDC or building automation controllers to communicate to each other. If the network fails for whatever reason then the system may still function (because the DDC controllers in a BMS system are stand-alone) but it will not function as efficiently as designed. The DDC/BMS system can be configured as independent (localized) closed-system, or DDC open-system based on accessibility options required by a group of buildings managed by a single company or property management firm (centralized), or a single property to be monitored and controlled by its own (localized) Fig 2. Fig 2. DDC/BMS LAN/WAN configuration [2] 3 3.1 BACnet compatibility BACnet is the term commonly used to refer to the ANSI/ASHRAE Standard 135- 1995, adopted and supported by the American National Standards Institute (ANSI) and the American Society of Heating Refrigeration and Air-Conditioning Engineers (ASHRAE). BACnet stands for Building Automation and Control network. BACnet is a true, non-proprietary open protocol communication standard conceived by a consortium of building management, system users and manufacturers [3]. A closed protocol is a proprietary protocol used by a specific equipment manufacturer. An open protocol system uses a protocol available to anyone, but not published by a standards organization. A standard protocol system uses a protocol available to anyone. It is created by a standards organization. Open Systems: An open system is defined as a system that allows components from different manufacturers to co-exist on the same network. These components would not need a gateway to communicate with one another and would not require a manufacturer specific workstation to visualize data. This would allow more than one vendors product to meet a specific application requirement. The DDC/BMS BACnet based LANs and Sub-LANs can be accessed, controlled and monitored from remote locations via the Internet trough a centralized data management system which is capable of collecting data from multiple sites. This is accomplished by connecting with a gateway for collecting data from the lighting and air-conditioning control systems installed in each building or factory, and the center server for providing data collection, database and web server functions along with security measures applied to all transmitted data. Based on the capability of real-time monitoring and analysis of actual energy consumption such as electricity and gas from a remote location by using a web browser, this system is able to achieve the maximum level of energy saving in buildings and factories which in turn, reduce the emissions and the environmental impacts by taking advantage of its cost effectiveness and by limiting the required energy for a specific application or function. 4 Fig 3, Integrated BACnet based WEB Browser BMS Control System Layout [4] 5 4. DDC/BMS integrated features, application and functions 4.1 Energy saving DDC/BMS allows the owner to set up schedules of operation for the equipment and lighting systems so that energy savings can be realized when the building or spaces in the building are unoccupied. Have algorithms as reset schedules for heating plants, static pressure control, and other systems where energy savings can be realized through these predictive programs. 4.2 Human comfort (thermal Comfort) DDC/BMS system allows the equipment optimal start with pre-scheduled program. Optimal start is allowing the equipment to be brought on in an ordered and sequential manner automatically on a schedule before the building is reoccupied so that space set points can be realized before occupation. Event sequence programming features allow the system to compare space temperature, outside air conditions, and equipment capabilities so that the equipment can be turned on at an appropriate time to ensure space set points are achieved before occupation. Have trim and respond capabilities. Based on zone demand the set point for various heating and cooling sources will change according to demand from the zones. For instance, in a Variable Air Volume system, all the VAV boxes are served from a central air handling unit. If all the zones are at set point then the supply air temperature set point of the air handler is automatically changed to prevent mechanical cooling from occurring when it is unnecessary. When the zones grow warmer the supply air temperature set point is automatically lowered to allow mechanical cooling to satisfy demand. In conjunction with the appropriate mechanical system set-up, offer economizing based on enthalpy calculations and/or CO2 set point control. 4.3 Long-term rebound effects Offer load shedding when power companies are at peak demand and need business and industry to cut-back on power usage to prevent black outs. Building Management systems for instance, allow the owner to cycle various things off like water heaters or drinking fountains where use of these things- 6 -will not be noticed even though they are off. Management companies who acquire a good DDC/BMS can set up the system to bill tenants for energy usage (fewer employees required). 4.4 Proactive Ability to send alarms via email, pager, or telephone to alert building managers and/or technicians of the developing problems, and system failures. 4.5 Other applications and compatibilities Have the ability to monitor energy usage including the ability to meter electric, gas, water, steam, hot water, chilled water, and fuel oil services. Have the communications abilities to be integrated with other buildings via WAN setup using the standardized TCP/IP family of protocols. It is BACnet base web browser compatible and other open source communication protocol which allows the system to be accessed via the web browser from remote locations. (Refer to 4.2) 5. High-performance Low-energy HVAC design Recall the Introduction, In addition to BMS/DDC System application for energy saving and high HVAC system performance, a green HVAC system design will achieve all aspects of comfort, energy saving, low initial and operational capital costs, and adds more efficient performance in conjunction with the DDC system, an example of such green HVAC system would be an Optimal Air System [5]. Optimal Air System concept, idea and example are taken from McQuay Air Conditionning/2002 McQuay International/Application Guide AG 31-005 as an example to illustrate its benefits for energy saving, human comfort, lower initial cost and long term rebound effects. Optimal Air systems uses less energy than conventional systems on an annual basis, for example, In a conventional system, supply air temperatures run between 54Â °F -57Â °F from the air handling unit. With duct heat gain, the supply air ranges from approximately 56Â °F-59Â °F out of the air diffuser. 7 In Optimal Air System, supply air temperature run between 45-52Â °F from the air handling unit to optimize energy consumption, reduce first capital cost and improve humidity control. Optimal Air has for years been extensively used in grocery stores and is gaining increasing popularity in comfort cooling applications such as offices and schools. 5.1 Advantages There are several benefits of Optimal Air that make it an attractive system for use in a wide variety of applications. It Saves Space and Reduces Energy and Construction Costs, increases the amount of sensible heat that each CFM delivered to a zone can absorb. While 50Â °F air may not seem much colder than 55Â °F air, the delta T rises from 20Â °F to 25Â °F. That is an increase of 25%. This affects the sizing of the ducts, air handling units and fan motors, all of which will be smaller and results in a system that requires less space and uses less power. In many applications, fans can use more power annually than refrigeration (chillers, condensing units, pumps, and compressors). An example of annual 10-story building energy usage of 200,000 square-feet of HVAC components, the fan energy use is high because the fans operate every hour the building is occupied providing minimum air movement, ventilation air, heating, etc. In this case, an Optimal Air system would have a very real impact on overall energy costs. Fig 4, Annual HVAC Energy Usage [6] 8 5.2 Less Humidity, more comfort Optimal Air systems take more moisture out of the return and ventilation air mixture as it passes over the cooling coil. The lower moisture content in the supply air reduces the Psychrometric balance point humidity level in the conditioned space. This allows the space temperature to be set higher while achieving the same comfort level for occupants and further reduces the supply air quantity and fan power requirement. 5.3 Quieter and Improve Indoor Air Quality (IAQ) The lower air volume required for Optimal Air systems makes them quieter than conventional systems. Fan sound generation is a function of fan type, static pressure and air volume. By reducing air volume (and often the total fan static pressure) Optimal Air systems generate lower fan sound which can result in more desirable space conditions. This reduced sound generation can also be used to reduce the cost of any required noise attenuation in critical applications. The lower required air volume can also be used to reduce filter face velocities, allowing more efficient filters to be used without high energy cost penalties. The lower air temperature and resultant humidity levels also reduce the chance of mold growth in the air handling units, ducts or the occupied space. The example of the building above requires a supply air of 26,667 CFM. The HVAC system is floor by floor VAV air handling units with a two chiller primary secondary system, Optimal air works equally well with applied rooftop units or indoor vertical self-contained units. Table 1, HVAC system performance with optimal air system [7] 9 Table 1 shows the HVAC system performance as the supply air temperature, to the duct, is lowered. It is important to differentiate between supply air temperature off the cooling coil and supply air temperature into the duct. To accommodate the lower supply air temperature, the chilled water supply temperature (CWST) was gradually lowered, the air handling unit coils deepened to allow for closer approaches, and chiller performance was adjusted to deal will the increased lift. Because of their basic operating differences, DX rooftop and self-contained systems may have a different Optimal Air temperature than a chilled water system. When considering multiple system options, it is important to use Energy Analyzer for each in order to identify the best option. 5.4 Optimal Air Balance Point Reduced fan energy must be traded off against increased refrigeration energy. This trade off varies with the type of building, the type temperature control system, the type air conditioning system and geographic locale. Therefore, the optimal supply air temperature is different for every job. When only energy costs are a factor and no thermal storage is involved, this optimal supply air temperature generally falls in the 47Â °F -52Â °F range. It can be determined by comparing total system energy consumption with varying supply air temperatures using an energy analysis program. 5.5 Space Design Temperature and Related Comfort Temperature, humidity, air velocity and mean radiant temperature directly influence occupant comfort. Conventional designs are usually based on maintaining 75Â °F and 50% RH (Relative Humidity) in the occupied space. Figure 5 shows the ASHRAE comfort zone where 80% of the people engaged in light office work are satisfied. As the relative humidity is lowered, the space air temperature can be raised and still provide occupant comfort. The leaving air condition from the air handling unit is the primarily control of the relative humidity in the occupied space. The internal moisture gains from people, kitchens, etc, as well as infiltration also play a part. 10 Fig 5, Equivalent comfort chart [8] In most climates, the lower the supply air temperature, the lower the humidity ratio and the drier the space. Figure 5 shows sensible heat ratio lines for conventional, Optimal and low supply air temperatures. As the space relative humidity is lowered, the space temperature set-point rises from 74Â °F to 78Â °F. 5.6 ASHRAE Compliance The 1999 and 2001 version of ASHRAE Standard 90.1, Energy Standard for Buildings except Low Rise Residential Buildings [9], has mandatory requirements for refrigeration equipment and prescriptive requirements for fan work. The Standard recognizes that Optimal Air systems improve fan work significantly and provides credits to account for improved fan performance. In addition, refrigeration system performance is rated at conventional conditions or special tables are provided to account for non-standard operating conditions (as is the case with centrifugal chillers). In either case, ASHRAE Standard 90.1 does not penalize Optimal Air systems. 11 5.7 Design Considerations Design of refrigeration and air handling equipment for an Optimal Air system is similar to the design of a conventional air temperature system. Attention must be paid, however, to air distribution, controls and duct design. Conventional diffusers, when properly applied, will work with Optimal Air. Controls also require only minor changes from conventional systems. In particular, programming of economizer controls and supply air temperature reset. Finally, the ducting system must be sized for the reduced air volume to take full advantage of the potential capital savings. Duct insulation and sweating should also be reviewed to provide a trouble free system. Not every building type is a good candidate for Optimal Air. When air volumes are dictated by air turnover rates, such as some health care applications, Optimal Air offers no advantage. In fact, there would be increased reheat costs. Office buildings are a strong candidate for Optimal Air. They have high sensible heat ratios and typically less than 20% ventilation loads. Schools can also be a possibility. Generally speaking, as the percentage ventilation load increases, Optimal Air becomes less attractive. Location and climate also impact whether or not Optimal Air is a good candidate. Locations where weather provides significant economizer hours between 45 and 55Â °F will limit the savings. Ultimately, each project must be checked by performing the applicable specific calculations. The following should be considered: Load and Balance Point calculations, Space Temperature Set-point evaluation, Design Load Calculation, Primary and Secondary System Selection, Parallel, mixing or series VAV-Fan powered boxes, Perimeter Heating, Air Distribution, Diffusers (based on air flow and the throw distance calculation), Duct design (considering duct heat gain, sweating and insulation). 5.8 System Life-Cycle Analysis Evaluating different engineering solutions is always part of a good proposal. Optimal Air systems are no different. 12 In the case of Optimal Air, there may be no need to do any calculations because Optimal Air systems cost less to build (lower capital cost) and have the same operating cost as conventional systems (assuming the balance point was used for the design). Duct sizing will decrease almost linearly with reduction in air volume. The installed cost will not change linearly because of the labor portion. A 20% reduction in air volume can result in 80% savings of the 20% reduction or 16% overall savings in sheet metal cost. On the plus side, there are less pounds of steel and fewer man-hours to install it. On the minus side there is more insulation. Terminal boxes and diffusers will be a wash since there are fewer of them but the equipment cost will be higher than conventional equipment. HVAC equipment will cost about the same. This is conservative because the air handling equipment will cost less and refrigeration equipment will be slightly more. There is typically more capital invested in air handling than refrigeration. Building envelope should be the same for new construction. In the case of retrofit applications, it will depend on the quality of the existing building. The cost of space may also need to be evaluated. Not accounting for space savings is conservative. There will be space savings but they may be difficult to realize. If enough plenum height savings can be realized to add another floor within the same building envelope, then that rentable space should be accounted for. Simple payback calculations do not take into account the cost of money, taxes and depreciation, inflation, maintenance or increases in the cost of energy. A more complete analysis should include Internal Rate of Return (IRR) and net present value (NPV). In the HVAC industry, many projects fail simple back (they are in the 5-year range) while passing IRR (they offer a 25% rate of return). Software analysis tools can be used to perform both energy and life-cycle analysis that include simple payback, IRR and NPV. 13 6. Conclusion Building owners and designers faced with increased concerns for energy saving and environmental stewardship search for cost effective system options for their projects. The DDC, integrated with a high-performance low-energy HVAC system as the Optimal Air system can deliver both low first costs and reduced energy costs in a new construction and retrofit applications. This integrated system will not only meet the efficiency and sustainability of its performance at the desired set-parameters, but when designed with advanced selection tools, installed with the most advanced DDC/BMS system, and supported by trained operators, will achieve both energy saving and long term rebound effect (pay-back), maximum human thermal comfort, in addition, it allows building owners to compare predicted energy use to actual performance, this leads to a flexible budgeting, further future system adjustment and energy consumption cut-back. The whole integrated DDC/BMS HVAC system function will also contribute in the environmental impacts reduction. In todays challenging energy efficiency, building owners need proven system that delivers the necessary performance to meet their integrated environmental sustainability and business goals [10].

Essay --

Holocaust Essay One of the world’s greatest events in the twentieth century was the Holocaust. This event was tragic and dreadful to all, deceased and alive, Jews. Between January 30, 1933 and May 8, 1945, over six million Jews were tortured then killed without having a say. Having to live day by day with this terrifying experience hammered in their minds, roughly three million Jews were blessed with survival. â€Å"Only be careful and watch yourselves closely so that you do not forget the things your eyes have seen, or let them slip from your heart as long as you live. Teach them to your children and to their children after them.† -Deuteronomy 4:9 From the Holocaust we learn that feelings are important aspects of our daily lives. We must protect ourselves from all evils. Every man has naturally occurring evil built inside of them. It is our duty as being man, to secure that evil. The Holocaust is an example of what can become if that evil is unleashed. Man has to be aware of his, and the evil of others. If, however, evil is kept left alone, it may become stronger and more powerful. A person is not judged by their surroundings, but by the evil of its enemies. Man must learn to tolerate and respect those who differ. To do this we must avoid discrimination. Jews were discriminated because of their religious beliefs, appearance, and knowledge. Intolerance leads to unwanted hatred and cruelty. Man must steer clear of failing to care about the pain of others. When one dodges this action, he uproots cruelty. Cruelty shows proof of one being fulfilled with hatred. Hate was the cause of world destruction for Jews and other faultless victims. Hitler loathed Jews and because of this, he sought them out to be scapegoats. Although Adolf Hitl... ...truction, and becoming a follower. If these acts are ignored, the world can possibly be turned around, again. Some go against the thought of believing what took place between those years of the past. Also, what can become in the near by future. For others, six million guiltless lives had to be buried just for them to realize that evil does exist and that it has potential. As a whole we must always believe that even the worst can happen. Man should never give up his freedoms. I personally pray that all people, the world, become aware of our own negativity before it gets out of control. The hatred and violent crimes has to be ceased. As learned from the Holocaust, it only takes the hatred of one to commit to disaster. I also believe that for some, such as Hitler, their say is the only say. In my opinion, man is not born evil or good, he simply adjusts to his society.

Analysis Of The Scarlet Letter :: essays research papers

The Scarlet Letter is a story that illustrates intricate pieces of the Puritan lifestyle. Centered first on a sin committed by Hester Prynne and her secret lover before the story ever begins, the novel details how sin affects the lives of the people involved. For Hester, the sin forces her into isolation from society and even from herself. Her qualities that Hawthorne describes at the opening of the book, her pale beauty, womanly qualities, and passion are, after a time, eclipsed by the ‘A’ she is forced to wear. An example of this is her hair. Long hair is something in this time period that is a symbol of a woman. At the beginning of the story, Hawthorne tells of Hester’s long flowing hair. After she wears the scarlet letter for a time, he paints a picture of her with her hair out of site under a cap, and all the womanliness gone from her. Yet, even with her true eclipsed behind the letter, of the three main characters affected, Hester has the easiest time because her sin is out in the open. More than a tale of sin, the Scarlet Letter is also an intense love story that shows itself in the forest scene between Hester and the minister Arthur Dimmesdale. With plans to run away with each, Arthur and Hester show that their love has surpassed distance and time away from each other. This love also explains why Hester would not reveal the identity of her fellow sinner when asked on the scaffolding. Roger Chillingworth is the most affected by the sin, though he was not around when the sin took place. Demented by his thoughts of revenge and hate, Hawthorne shows Mr. Chillingworth to be a devil or as a man with an evil nature. He himself commits one of the   Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Ã‚  Quinn 2 seven deadly sins with his wrath. By the end of the tale that surpasses seven years, Hester is respected and revered by the community as a doer of good works, and the minister is worshipped for his service in the church. Only Mr. Chillingsworth is looked upon badly by the townspeople although no one knows why. Through it all, Hawthorne illustrates that even sin can produce purity, and that purity came in the form of the sprightly Pearl. Though she is isolated with her mother, Pearl finds her company and joy in the nature that surrounds her.

Home Confinement: An Alternative to Incarceration Essay -- Argumentati

Home Confinement: An Alternative to Incarceration      Ã‚   West Virginia state prisons have a maximum capacity of 2,154 inmates; currently they house 2,363 inmates, and more remain in City and County lockups to manage the overflow (West Virginia Blue Book). Home Confinement solves this problem. Reduction of the prison population should be reason enough to institute home confinement, but other reasons do exist. Would you like lower taxes? Home confinement costs much less than incarceration. Do you favor less crime? For certain types of criminals, home confinement has a better rehabilitation rate. Home confinement also differs from incarceration by the fact that it allows the confined person to contribute to society. For all of these reasons, minor offenders, who pose no real threat to society, should be sentenced to home confinement.      Ã‚  Ã‚  Ã‚  Ã‚   The easiest way to solve the overcrowded prison problem is, simply, not to arrest so many people. That will never happen as it cannot be justified. Another alternative, to build more prisons or add on to existing ones, will cost a great deal. Home confinement is the best solution; the offender does not take up space in prison and can hold a job or take care of familial obligation. If a prisoner is under house arrest, it seems nothing prevents him from escaping. In most cases, flight is not a viable option for the home confined. Their sentence is usually light and the re... ...se two counties realize great success with these endeavors, encouraging others to follow.       Works Cited Ball, Richard A., Huff, C. Ronald, Lilly, J. Robert. House Arrest and Correctional Policy: Doing Time at Home. California: Sage, 1988. "Good Idea, In Spades." Editorial. The Herald Dispatch 26 Sept. 1998: 6A. "Home Confinement Proves Effective in Dollars and Sense." March 1997. Available at  Ã‚     http://www.uscourts.gov/mar97ttp/homeprob.htm. McCarthy, Belinda R. Intermediate Punishments: Intensive Supervision, Home Confinement and Electronic Surveillance. New York: Criminal Justice Press, 1987. West Virginia Blue Book. Holmes, Darrel E. Ed. Charleston WV: Chapman, 1997      

Open Domain Event Extraction from Twitter

Open Domain Event Extraction from Twitter Alan Ritter University of Washington Computer Sci. & Eng. Seattle, WA [email  protected] washington. edu Mausam University of Washington Computer Sci. & Eng. Seattle, WA [email  protected] washington. edu Oren Etzioni University of Washington Computer Sci. & Eng. Seattle, WA [email  protected] washington. edu Sam Clark? Decide, Inc. Seattle, WA sclark. [email  protected] com ABSTRACT Tweets are the most up-to-date and inclusive stream of information and commentary on current events, but they are also fragmented and noisy, motivating the need for systems that can extract, aggregate and categorize important events.Previous work on extracting structured representations of events has focused largely on newswire text; Twitter’s unique characteristics present new challenges and opportunities for open-domain event extraction. This paper describes TwiCal— the ? rst open-domain event-extraction and categorization system for Twitt er. We demonstrate that accurately extracting an open-domain calendar of signi? cant events from Twitter is indeed feasible. In addition, we present a novel approach for discovering important event categories and classifying extracted events based on latent variable models.By leveraging large volumes of unlabeled data, our approach achieves a 14% increase in maximum F1 over a supervised baseline. A continuously updating demonstration of our system can be viewed at http://statuscalendar. com; Our NLP tools are available at http://github. com/aritter/ twitter_nlp. Entity Steve Jobs iPhone GOP Amanda Knox Event Phrase died announcement debate verdict Date 10/6/11 10/4/11 9/7/11 10/3/11 Type Death ProductLaunch PoliticalEvent Trial Table 1: Examples of events extracted by TwiCal. vents. Yet the number of tweets posted daily has recently exceeded two-hundred million, many of which are either redundant [57], or of limited interest, leading to information overload. 1 Clearly, we can bene? t from more structured representations of events that are synthesized from individual tweets. Previous work in event extraction [21, 1, 54, 18, 43, 11, 7] has focused largely on news articles, as historically this genre of text has been the best source of information on current events. Read also Twitter Case StudyIn the meantime, social networking sites such as Facebook and Twitter have become an important complementary source of such information. While status messages contain a wealth of useful information, they are very disorganized motivating the need for automatic extraction, aggregation and categorization. Although there has been much interest in tracking trends or memes in social media [26, 29], little work has addressed the challenges arising from extracting structured representations of events from short or informal texts.Extracting useful structured representations of events from this disorganized corpus of noisy text is a challenging problem. On the other hand, individual tweets are short and self-contained and are therefore not composed of complex discourse structure as is the case for texts containing narratives. In this paper we demonstrate that open-domain event extraction from Twitter is indeed feasible, for example our highest-con? dence extracted f uture events are 90% accurate as demonstrated in  §8.Twitter has several characteristics which present unique challenges and opportunities for the task of open-domain event extraction. Challenges: Twitter users frequently mention mundane events in their daily lives (such as what they ate for lunch) which are only of interest to their immediate social network. In contrast, if an event is mentioned in newswire text, it 1 http://blog. twitter. com/2011/06/ 200-million-tweets-per-day. html Categories and Subject Descriptors I. 2. 7 [Natural Language Processing]: Language parsing and understanding; H. 2. [Database Management]: Database applications—data mining General Terms Algorithms, Experimentation 1. INTRODUCTION Social networking sites such as Facebook and Twitter present the most up-to-date information and buzz about current ? This work was conducted at the University of Washington Permission to make digital or hard copies of all or part of this work for personal or classr oom use is granted without fee provided that copies are not made or distributed for pro? t or commercial advantage and that copies bear this notice and the full citation on the ? rst page.To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior speci? c permission and/or a fee. KDD’12, August 12–16, 2012, Beijing, China. Copyright 2012 ACM 978-1-4503-1462-6 /12/08 †¦ $10. 00. is safe to assume it is of general importance. Individual tweets are also very terse, often lacking su? cient context to categorize them into topics of interest (e. g. Sports, Politics, ProductRelease etc†¦ ). Further because Twitter users can talk about whatever they choose, it is unclear in advance which set of event types are appropriate.Finally, tweets are written in an informal style causing NLP tools designed for edited texts to perform extremely poorly. Opportunities: The short and self-contained nature of tweets means they have very simple d iscourse and pragmatic structure, issues which still challenge state-of-the-art NLP systems. For example in newswire, complex reasoning about relations between events (e. g. before and after ) is often required to accurately relate events to temporal expressions [32, 8]. The volume of Tweets is also much larger than the volume of news articles, so redundancy of information can be exploited more easily.To address Twitter’s noisy style, we follow recent work on NLP in noisy text [46, 31, 19], annotating a corpus of Tweets with events, which is then used as training data for sequence-labeling models to identify event mentions in millions of messages. Because of the terse, sometimes mundane, but highly redundant nature of tweets, we were motivated to focus on extracting an aggregate representation of events which provides additional context for tasks such as event categorization, and also ? lters out mundane events by exploiting redundancy of information.We propose identifying im portant events as those whose mentions are strongly associated with references to a unique date as opposed to dates which are evenly distributed across the calendar. Twitter users discuss a wide variety of topics, making it unclear in advance what set of event types are appropriate for categorization. To address the diversity of events discussed on Twitter, we introduce a novel approach to discovering important event types and categorizing aggregate events within a new domain. Supervised or semi-supervised approaches to event categorization would require ? st designing annotation guidelines (including selecting an appropriate set of types to annotate), then annotating a large corpus of events found in Twitter. This approach has several drawbacks, as it is apriori unclear what set of types should be annotated; a large amount of e? ort would be required to manually annotate a corpus of events while simultaneously re? ning annotation standards. We propose an approach to open-domain eve nt categorization based on latent variable models that uncovers an appropriate set of types which match the data.The automatically discovered types are subsequently inspected to ? lter out any which are incoherent and the rest are annotated with informative labels;2 examples of types discovered using our approach are listed in ? gure 3. The resulting set of types are then applied to categorize hundreds of millions of extracted events without the use of any manually annotated examples. By leveraging large quantities of unlabeled data, our approach results in a 14% improvement in F1 score over a supervised baseline which uses the same set of types. Stanford NER T-seg P 0. 62 0. 73 R 0. 5 0. 61 F1 0. 44 0. 67 F1 inc. 52% Table 2: By training on in-domain data, we obtain a 52% improvement in F1 score over the Stanford Named Entity Recognizer at segmenting entities in Tweets [46]. 2. SYSTEM OVERVIEW TwiCal extracts a 4-tuple representation of events which includes a named entity, event p hrase, calendar date, and event type (see Table 1). This representation was chosen to closely match the way important events are typically mentioned in Twitter. An overview of the various components of our system for extracting events from Twitter is presented in Figure 1.Given a raw stream of tweets, our system extracts named entities in association with event phrases and unambiguous dates which are involved in signi? cant events. First the tweets are POS tagged, then named entities and event phrases are extracted, temporal expressions resolved, and the extracted events are categorized into types. Finally we measure the strength of association between each named entity and date based on the number of tweets they co-occur in, in order to determine whether an event is signi? cant.NLP tools, such as named entity segmenters and part of speech taggers which were designed to process edited texts (e. g. news articles) perform very poorly when applied to Twitter text due to its noisy and u nique style. To address these issues, we utilize a named entity tagger and part of speech tagger trained on in-domain Twitter data presented in previous work [46]. We also develop an event tagger trained on in-domain annotated data as described in  §4. 3. NAMED ENTITY SEGMENTATION NLP tools, such as named entity segmenters and part of speech taggers which were designed to process edited texts (e. g. ews articles) perform very poorly when applied to Twitter text due to its noisy and unique style. For instance, capitalization is a key feature for named entity extraction within news, but this feature is highly unreliable in tweets; words are often capitalized simply for emphasis, and named entities are often left all lowercase. In addition, tweets contain a higher proportion of out-ofvocabulary words, due to Twitter’s 140 character limit and the creative spelling of its users. To address these issues, we utilize a named entity tagger trained on in-domain Twitter data presented in previous work [46]. Training on tweets vastly improves performance at segmenting Named Entities. For example, performance compared against the state-of-the-art news-trained Stanford Named Entity Recognizer [17] is presented in Table 2. Our system obtains a 52% increase in F1 score over the Stanford Tagger at segmenting named entities. 4. EXTRACTING EVENT MENTIONS This annotation and ? ltering takes minimal e? ort. One of the authors spent roughly 30 minutes inspecting and annotating the automatically discovered event types. 2 In order to extract event mentions from Twitter’s noisy text, we ? st annotate a corpus of tweets, which is then 3 Available at http://github. com/aritter/twitter_nlp. Temporal Resolution S M T W T F S Tweets POS Tag NER Signi? cance Ranking Calendar Entries Event Tagger Event Classi? cation Figure 1: Processing pipeline for extracting events from Twitter. New components developed as part of this work are shaded in grey. used to train sequence models to extract events. While we apply an established approach to sequence-labeling tasks in noisy text [46, 31, 19], this is the ? rst work to extract eventreferring phrases in Twitter.Event phrases can consist of many di? erent parts of speech as illustrated in the following examples: †¢ Verbs: Apple to Announce iPhone 5 on October 4th?! YES! †¢ Nouns: iPhone 5 announcement coming Oct 4th †¢ Adjectives: WOOOHOO NEW IPHONE TODAY! CAN’T WAIT! These phrases provide important context, for example extracting the entity, Steve Jobs and the event phrase died in connection with October 5th, is much more informative than simply extracting Steve Jobs. In addition, event mentions are helpful in upstream tasks such as categorizing events into types, as described in  §6.In order to build a tagger for recognizing events, we annotated 1,000 tweets (19,484 tokens) with event phrases, following annotation guidelines similar to those developed for the Event tags in Timebank [43] . We treat the problem of recognizing event triggers as a sequence labeling task, using Conditional Random Fields for learning and inference [24]. Linear Chain CRFs model dependencies between the predicted labels of adjacent words, which is bene? cial for extracting multi-word event phrases.We use contextual, dictionary, and orthographic features, and also include features based on our Twitter-tuned POS tagger [46], and dictionaries of event terms gathered from WordNet by Sauri et al. [50]. The precision and recall at segmenting event phrases are reported in Table 3. Our classi? er, TwiCal-Event, obtains an F-score of 0. 64. To demonstrate the need for in-domain training data, we compare against a baseline of training our system on the Timebank corpus. precision 0. 56 0. 48 0. 24 recall 0. 74 0. 70 0. 11 F1 0. 64 0. 57 0. 15 TwiCal-Event No POS TimebankTable 3: Precision and recall at event phrase extraction. All results are reported using 4-fold cross validation over the 1,000 manu ally annotated tweets (about 19K tokens). We compare against a system which doesn’t make use of features generated based on our Twitter trained POS Tagger, in addition to a system trained on the Timebank corpus which uses the same set of features. as input a reference date, some text, and parts of speech (from our Twitter-trained POS tagger) and marks temporal expressions with unambiguous calendar references. Although this mostly rule-based system was designed for use on newswire text, we ? d its precision on Tweets (94% estimated over as sample of 268 extractions) is su? ciently high to be useful for our purposes. TempEx’s high precision on Tweets can be explained by the fact that some temporal expressions are relatively unambiguous. Although there appears to be room for improving the recall of temporal extraction on Twitter by handling noisy temporal expressions (for example see Ritter et. al. [46] for a list of over 50 spelling variations on the word â€Å"tomorrow †), we leave adapting temporal extraction to Twitter as potential future work. . CLASSIFICATION OF EVENT TYPES To categorize the extracted events into types we propose an approach based on latent variable models which infers an appropriate set of event types to match our data, and also classi? es events into types by leveraging large amounts of unlabeled data. Supervised or semi-supervised classi? cation of event categories is problematic for a number of reasons. First, it is a priori unclear which categories are appropriate for Twitter. Secondly, a large amount of manual e? ort is required to annotate tweets with event types.Third, the set of important categories (and entities) is likely to shift over time, or within a focused user demographic. Finally many important categories are relatively infrequent, so even a large annotated dataset may contain just a few examples of these categories, making classi? cation di? cult. For these reasons we were motivated to investigate un- 5. EXTRACTING AND RESOLVING TEMPORAL EXPRESSIONS In addition to extracting events and related named entities, we also need to extract when they occur. In general there are many di? rent ways users can refer to the same calendar date, for example â€Å"next Friday†, â€Å"August 12th†, â€Å"tomorrow† or â€Å"yesterday† could all refer to the same day, depending on when the tweet was written. To resolve temporal expressions we make use of TempEx [33], which takes Sports Party TV Politics Celebrity Music Movie Food Concert Performance Fitness Interview ProductRelease Meeting Fashion Finance School AlbumRelease Religion 7. 45% 3. 66% 3. 04% 2. 92% 2. 38% 1. 96% 1. 92% 1. 87% 1. 53% 1. 42% 1. 11% 1. 01% 0. 95% 0. 88% 0. 87% 0. 85% 0. 85% 0. 78% 0. 71% Con? ct Prize Legal Death Sale VideoGameRelease Graduation Racing Fundraiser/Drive Exhibit Celebration Books Film Opening/Closing Wedding Holiday Medical Wrestling OTHER 0. 69% 0. 68% 0. 67% 0. 66% 0. 66% 0. 65 % 0. 63% 0. 61% 0. 60% 0. 60% 0. 60% 0. 58% 0. 50% 0. 49% 0. 46% 0. 45% 0. 42% 0. 41% 53. 45% Label Sports Concert Perform TV Movie Sports Politics Figure 2: Complete list of automatically discovered event types with percentage of data covered. Interpretable types representing signi? cant events cover roughly half of the data. supervised approaches that will automatically induce event types which match the data.We adopt an approach based on latent variable models inspired by recent work on modeling selectional preferences [47, 39, 22, 52, 48], and unsupervised information extraction [4, 55, 7]. Each event indicator phrase in our data, e, is modeled as a mixture of types. For example the event phrase â€Å"cheered† might appear as part of either a PoliticalEvent, or a SportsEvent. Each type corresponds to a distribution over named entities n involved in speci? c instances of the type, in addition to a distribution over dates d on which events of the type occur. Including calen dar dates in our model has the e? ct of encouraging (though not requiring) events which occur on the same date to be assigned the same type. This is helpful in guiding inference, because distinct references to the same event should also have the same type. The generative story for our data is based on LinkLDA [15], and is presented as Algorithm 1. This approach has the advantage that information about an event phrase’s type distribution is shared across it’s mentions, while ambiguity is also naturally preserved. In addition, because the approach is based on generative a probabilistic model, it is straightforward to perform many di? rent probabilistic queries about the data. This is useful for example when categorizing aggregate events. For inference we use collapsed Gibbs Sampling [20] where each hidden variable, zi , is sampled in turn, and parameters are integrated out. Example types are displayed in Figure 3. To estimate the distribution over types for a given event , a sample of the corresponding hidden variables is taken from the Gibbs markov chain after su? cient burn in. Prediction for new data is performed using a streaming approach to inference [56]. TV Product MeetingTop 5 Event Phrases tailgate – scrimmage tailgating – homecoming – regular season concert – presale – performs – concerts – tickets matinee – musical priscilla – seeing wicked new season – season ? nale – ? nished season episodes – new episode watch love – dialogue theme – inception – hall pass – movie inning – innings pitched – homered homer presidential debate osama – presidential candidate – republican debate – debate performance network news broadcast – airing – primetime drama – channel stream unveils – unveiled – announces – launches wraps o? shows trading – hall mtg – zoning – brie? g stocks – tumbled – trading report – opened higher – tumbles maths – english test exam – revise – physics in stores – album out debut album – drops on – hits stores voted o? – idol – scotty – idol season – dividendpaying sermon – preaching preached – worship preach declared war – war shelling – opened ? re wounded senate – legislation – repeal – budget – election winners – lotto results enter – winner – contest bail plea – murder trial – sentenced – plea – convicted ? lm festival – screening starring – ? lm – gosling live forever – passed away – sad news – condolences – burried add into – 50% o? up shipping – save up donate – tornado relief disaster relief – donated – raise mone y Top 5 Entities espn – ncaa – tigers – eagles – varsity taylor swift – toronto britney spears – rihanna – rock shrek – les mis – lee evans – wicked – broadway jersey shore – true blood – glee – dvr – hbo net? ix – black swan – insidious – tron – scott pilgrim mlb – red sox – yankees – twins – dl obama president obama – gop – cnn america nbc – espn – abc – fox mtv apple – google – microsoft – uk – sony town hall – city hall club – commerce – white house reuters – new york – u. . – china – euro english – maths – german – bio – twitter itunes – ep – uk – amazon – cd lady gaga – american idol – america – beyonce – glee church – jesus – pastor faith – god libya – afghanistan #syria – syria – nato senate – house – congress – obama – gop ipad – award – facebook – good luck – winners casey anthony – court – india – new delhi supreme court hollywood – nyc – la – los angeles – new york michael jackson afghanistan john lennon – young – peace groupon – early bird facebook – @etsy – etsy japan – red cross – joplin – june – africaFinance School Album TV Religion Con? ict Politics Prize Legal Movie Death Sale Drive 6. 1 Evaluation To evaluate the ability of our model to classify signi? cant events, we gathered 65 million extracted events of the form Figure 3: Example event types discovered by our model. For each type t, we list the top 5 entities which have highest probability given t, and the 5 event phrases which as sign highest probability to t. Algorithm 1 Generative story for our data involving event types as hidden variables.Bayesian Inference techniques are applied to invert the generative process and infer an appropriate set of types to describe the observed events. for each event type t = 1 . . . T do n Generate ? t according to symmetric Dirichlet distribution Dir(? n ). d Generate ? t according to symmetric Dirichlet distribution Dir(? d ). end for for each unique event phrase e = 1 . . . |E| do Generate ? e according to Dirichlet distribution Dir(? ). for each entity which co-occurs with e, i = 1 . . . Ne do n Generate ze,i from Multinomial(? e ). Generate the entity ne,i from Multinomial(? n ). e,i TwiCal-Classify Supervised Baseline Precision 0. 85 0. 61 Recall 0. 55 0. 57 F1 0. 67 0. 59 Table 4: Precision and recall of event type categorization at the point of maximum F1 score. d,i end for end for 0. 6 end for for each date which co-occurs with e, i = 1 . . . Nd do d Generate ze,i from Multinomial(? e ). Generate the date de,i from Multinomial(? zn ). Precision 0. 8 1. 0 listed in Figure 1 (not including the type). We then ran Gibbs Sampling with 100 types for 1,000 iterations of burnin, keeping the hidden variable assignments found in the last sample. One of the authors manually inspected the resulting types and assigned them labels such as Sports, Politics, MusicRelease and so on, based on their distribution over entities, and the event words which assign highest probability to that type. Out of the 100 types, we found 52 to correspond to coherent event types which referred to signi? cant events;5 the other types were either incoherent, or covered types of events which are not of general interest, for example there was a cluster of phrases such as applied, call, contact, job interview, etc†¦ hich correspond to users discussing events related to searching for a job. Such event types which do not correspond to signi? cant events of general interest were simply marked as OTHER. A complete list of labels used to annotate the automatically discovered event types along with the coverage of each type is listed in ? gure 2. Note that this assignment of labels to types only needs to be done once and produces a labeling for an arbitrarily large number of event instances. Additionally the same set of types can easily be used to lassify new event instances using streaming inference techniques [56]. One interesting direction for future work is automatic labeling and coherence evaluation of automatically discovered event types analogous to recent work on topic models [38, 25]. In order to evaluate the ability of our model to classify aggregate events, we grouped together all (entity,date) pairs which occur 20 or more times the data, then annotated the 500 with highest association (see  §7) using the event types discovered by our model. To help demonstrate the bene? s of leveraging large quantities of unlabeled data for event classi? cation, we compare against a supervised Maximum Entropy baseline which makes use of the 500 annotated events using 10-fold cross validation. For features, we treat the set of event phrases To scale up to larger datasets, we performed inference in parallel on 40 cores using an approximation to the Gibbs Sampling procedure analogous to that presented by Newmann et. al. [37]. 5 After labeling some types were combined resulting in 37 distinct labels. 4 0. 4 Supervised Baseline TwiCal? Classify 0. 0 0. 2 0. 4 Recall 0. 0. 8 Figure 4: types. Precision and recall predicting event that co-occur with each (entity, date) pair as a bag-of-words, and also include the associated entity. Because many event categories are infrequent, there are often few or no training examples for a category, leading to low performance. Figure 4 compares the performance of our unsupervised approach to the supervised baseline, via a precision-recall curve obtained by varying the threshold on the probability of the most lik ely type. In addition table 4 compares precision and recall at the point of maximum F-score.Our unsupervised approach to event categorization achieves a 14% increase in maximum F1 score over the supervised baseline. Figure 5 plots the maximum F1 score as the amount of training data used by the baseline is varied. It seems likely that with more data, performance will reach that of our approach which does not make use of any annotated events, however our approach both automatically discovers an appropriate set of event types and provides an initial classi? er with minimal e? ort, making it useful as a ? rst step in situations where annotated data is not immediately available. . RANKING EVENTS Simply using frequency to determine which events are signi? cant is insu? cient, because many tweets refer to common events in user’s daily lives. As an example, users often mention what they are eating for lunch, therefore entities such as McDonalds occur relatively frequently in associat ion with references to most calendar days. Important events can be distinguished as those which have strong association with a unique date as opposed to being spread evenly across days on the calendar. To extract signi? ant events of general interest from Twitter, we thus need some way to measure the strength of association between an entity and a date. In order to measure the association strength between an 0. 8 0. 2 Supervised Baseline TwiCal? Classify 100 200 300 400 tweets. We then added the extracted triples to the dataset used for inferring event types described in  §6, and performed 50 iterations of Gibbs sampling for predicting event types on the new data, holding the hidden variables in the original data constant. This streaming approach to inference is similar to that presented by Yao et al. 56]. We then ranked the extracted events as described in  §7, and randomly sampled 50 events from the top ranked 100, 500, and 1,000. We annotated the events with 4 separate criter ia: 1. Is there a signi? cant event involving the extracted entity which will take place on the extracted date? 2. Is the most frequently extracted event phrase informative? 3. Is the event’s type correctly classi? ed? 4. Are each of (1-3) correct? That is, does the event contain a correct entity, date, event phrase, and type? Note that if (1) is marked as incorrect for a speci? event, subsequent criteria are always marked incorrect. Max F1 0. 4 0. 6 # Training Examples Figure 5: Maximum F1 score of the supervised baseline as the amount of training data is varied. entity and a speci? c date, we utilize the G log likelihood ratio statistic. G2 has been argued to be more appropriate for text analysis tasks than ? 2 [12]. Although Fisher’s Exact test would produce more accurate p-values [34], given the amount of data with which we are working (sample size greater than 1011 ), it proves di? cult to compute Fisher’s Exact Test Statistic, which results in ? ating poin t over? ow even when using 64-bit operations. The G2 test works su? ciently well in our setting, however, as computing association between entities and dates produces less sparse contingency tables than when working with pairs of entities (or words). The G2 test is based on the likelihood ratio between a model in which the entity is conditioned on the date, and a model of independence between entities and date references. For a given entity e and date d this statistic can be computed as follows: G2 = x? {e, ¬e},y? {d, ¬d} 2 8. 2 BaselineTo demonstrate the importance of natural language processing and information extraction techniques in extracting informative events, we compare against a simple baseline which does not make use of the Ritter et. al. named entity recognizer or our event recognizer; instead, it considers all 1-4 grams in each tweet as candidate calendar entries, relying on the G2 test to ? lter out phrases which have low association with each date. 8. 3 Results The results of the evaluation are displayed in table 5. The table shows the precision of the systems at di? rent yield levels (number of aggregate events). These are obtained by varying the thresholds in the G2 statistic. Note that the baseline is only comparable to the third column, i. e. , the precision of (entity, date) pairs, since the baseline is not performing event identi? cation and classi? cation. Although in some cases ngrams do correspond to informative calendar entries, the precision of the ngram baseline is extremely low compared with our system. In many cases the ngrams don’t correspond to salient entities related to events; they often consist of single words which are di? ult to interpret, for example â€Å"Breaking† which is part of the movie â€Å"Twilight: Breaking Dawn† released on November 18. Although the word â€Å"Breaking† has a strong association with November 18, by itself it is not very informative to present to a user. 7 Our high- con? dence calendar entries are surprisingly high quality. If we limit the data to the 100 highest ranked calendar entries over a two-week date range in the future, the precision of extracted (entity, date) pairs is quite good (90%) – an 80% increase over the ngram baseline.As expected precision drops as more calendar entries are displayed, but 7 In addition, we notice that the ngram baseline tends to produce many near-duplicate calendar entries, for example: â€Å"Twilight Breaking†, â€Å"Breaking Dawn†, and â€Å"Twilight Breaking Dawn†. While each of these entries was annotated as correct, it would be problematic to show this many entries describing the same event to a user. Ox,y ? ln Ox,y Ex,y Where Oe,d is the observed fraction of tweets containing both e and d, Oe, ¬d is the observed fraction of tweets containing e, but not d, and so on.Similarly Ee,d is the expected fraction of tweets containing both e and d assuming a model of independence. 8. EXPERIMENTS To estimate the quality of the calendar entries generated using our approach we manually evaluated a sample of the top 100, 500 and 1,000 calendar entries occurring within a 2-week future window of November 3rd. 8. 1 Data For evaluation purposes, we gathered roughly the 100 million most recent tweets on November 3rd 2011 (collected using the Twitter Streaming API6 , and tracking a broad set of temporal keywords, including â€Å"today†, â€Å"tomorrow†, names of weekdays, months, etc. ).We extracted named entities in addition to event phrases, and temporal expressions from the text of each of the 100M 6 https://dev. twitter. com/docs/streaming-api Mon Nov 7 Justin meet Other Motorola Pro+ kick Product Release Nook Color 2 launch Product Release Eid-ul-Azha celebrated Performance MW3 midnight release Other Tue Nov 8 Paris love Other iPhone holding Product Release Election Day vote Political Event Blue Slide Park listening Music Release Hedley album Music Rele ase Wed Nov 9 EAS test Other The Feds cut o? Other Toca Rivera promoted Performance Alert System test Other Max Day give OtherNovember 2011 Thu Nov 10 Fri Nov 11 Robert Pattinson iPhone show debut Performance Product Release James Murdoch Remembrance Day give evidence open Other Performance RTL-TVI France post play TV Event Other Gotti Live Veterans Day work closed Other Other Bambi Awards Skyrim perform arrives Performance Product Release Sat Nov 12 Sydney perform Other Pullman Ballroom promoted Other Fox ? ght Other Plaza party Party Red Carpet invited Party Sun Nov 13 Playstation answers Product Release Samsung Galaxy Tab launch Product Release Sony answers Product Release Chibi Chibi Burger other Jiexpo Kemayoran promoted TV EventFigure 6: Example future calendar entries extracted by our system for the week of November 7th. Data was collected up to November 5th. For each day, we list the top 5 events including the entity, event phrase, and event type. While there are several err ors, the majority of calendar entries are informative, for example: the Muslim holiday eid-ul-azha, the release of several videogames: Modern Warfare 3 (MW3) and Skyrim, in addition to the release of the new playstation 3D display on Nov 13th, and the new iPhone 4S in Hong Kong on Nov 11th. # calendar entries 100 500 1,000 ngram baseline 0. 50 0. 6 0. 44 entity + date 0. 90 0. 66 0. 52 precision event phrase event 0. 86 0. 56 0. 42 type 0. 72 0. 54 0. 40 entity + date + event + type 0. 70 0. 42 0. 32 Table 5: Evaluation of precision at di? erent recall levels (generated by varying the threshold of the G2 statistic). We evaluate the top 100, 500 and 1,000 (entity, date) pairs. In addition we evaluate the precision of the most frequently extracted event phrase, and the predicted event type in association with these calendar entries. Also listed is the fraction of cases where all predictions (â€Å"entity + date + event + type†) are correct.We also compare against the precision of a simple ngram baseline which does not make use of our NLP tools. Note that the ngram baseline is only comparable to the entity+date precision (column 3) since it does not include event phrases or types. remains high enough to display to users (in a ranked list). In addition to being less likely to come from extraction errors, highly ranked entity/date pairs are more likely to relate to popular or important events, and are therefore of greater interest to users. In addition we present a sample of extracted future events on a calendar in ? ure 6 in order to give an example of how they might be presented to a user. We present the top 5 entities associated with each date, in addition to the most frequently extracted event phrase, and highest probability event type. 9. RELATED WORK While we are the ? rst to study open domain event extraction within Twitter, there are two key related strands of research: extracting speci? c types of events from Twitter, and extracting open-domain even ts from news [43]. Recently there has been much interest in information extraction and event identi? cation within Twitter. Benson et al. 5] use distant supervision to train a relation extractor which identi? es artists and venues mentioned within tweets of users who list their location as New York City. Sakaki et al. [49] train a classi? er to recognize tweets reporting earthquakes in Japan; they demonstrate their system is capable of recognizing almost all earthquakes reported by the Japan Meteorological Agency. Additionally there is recent work on detecting events or tracking topics [29] in Twitter which does not extract structured representations, but has the advantage that it is not limited to a narrow domain. Petrovi? t al. investigate a streaming approach to identic fying Tweets which are the ? rst to report a breaking news story using Locally Sensitive Hash Functions [40]. Becker et al. [3], Popescu et al. [42, 41] and Lin et al. [28] investigate discovering clusters of rela ted words or tweets which correspond to events in progress. In contrast to previous work on Twitter event identi? cation, our approach is independent of event type or domain and is thus more widely applicable. Additionally, our work focuses on extracting a calendar of events (including those occurring in the future), extract- . 4 Error Analysis We found 2 main causes for why entity/date pairs were uninformative for display on a calendar, which occur in roughly equal proportion: Segmentation Errors Some extracted â€Å"entities† or ngrams don’t correspond to named entities or are generally uninformative because they are mis-segmented. Examples include â€Å"RSVP†, â€Å"Breaking† and â€Å"Yikes†. Weak Association between Entity and Date In some cases, entities are properly segmented, but are uninformative because they are not strongly associated with a speci? c event on the associated date, or are involved in many di? rent events which happen to oc cur on that day. Examples include locations such as â€Å"New York†, and frequently mentioned entities, such as â€Å"Twitter†. ing event-referring expressions and categorizing events into types. Also relevant is work on identifying events [23, 10, 6], and extracting timelines [30] from news articles. 8 Twitter status messages present both unique challenges and opportunities when compared with news articles. Twitter’s noisy text presents serious challenges for NLP tools. On the other hand, it contains a higher proportion of references to present and future dates.Tweets do not require complex reasoning about relations between events in order to place them on a timeline as is typically necessary in long texts containing narratives [51]. Additionally, unlike News, Tweets often discus mundane events which are not of general interest, so it is crucial to exploit redundancy of information to assess whether an event is signi? cant. Previous work on open-domain informat ion extraction [2, 53, 16] has mostly focused on extracting relations (as opposed to events) from web corpora and has also extracted relations based on verbs.In contrast, this work extracts events, using tools adapted to Twitter’s noisy text, and extracts event phrases which are often adjectives or nouns, for example: Super Bowl Party on Feb 5th. Finally we note that there has recently been increasing interest in applying NLP techniques to short informal messages such as those found on Twitter. 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