Writing an online news story about a speech in AP style Article

Writing an online news story about a speech in AP style - Article Example The realization however was not immediate. He did not even expect to learn it. He even had an unusual and different reason when he joined the military service. He signed up because college tuition was expensive and joining the military would help him get his degree. Wes Moore had no appetite for fighting or war even when he joined the military service. He just wanted to finish school through the help of military service. But when 9/11 came, it dramatically changed the role of military and that included Wes Moore’s role in the service. The 9/11 attack was about that unforgettable day in September 11, 2011 when terrorists simultaneously hijacked airplanes and slammed it to various structures the most famous of which was the World Trade Center that collapsed for the world to see (www.history.com, nd). From schooling in UK, he rejoined the Army and was sent overseas to fight as an officer. Wes Moore did not talk in details about his tour of duty as most servicemen would indicating that he had his share of the fight. Suffice to say that he could relate with the experience of a war to speak candidly about it and to also tell what many veterans are struggling. The speech was told in a manner that the listeners could relate. In the speech, Wes Moore bared the humanity of these struggles and the brotherhood forged in combat in the name of service without the heroic or stern military faà §ade. No adventurous combat stories were told but only the sacrifices made by the men and women in uniform in the name of service. And these experiences changed them with some still haunted by it. Thus, his apologies for what they have become (such as avoiding big crowds) that most of us would find odd solicited understanding and sympathy. And Wes Moore advocated that from the understanding and appreciation of these struggles should the words â€Å"thank you for your service† be contextualized and said for

Flow Measurement Using Venturi Meter Lab Report

Flow Measurement Using Venturi Meter - Lab Report Example All these were ascertained through the aspect of making appropriate records as per the experimental results and the actual measurements of the prevailing pressure level. The discharge co-efficient was then determined using the graph’s gradient. The major concept that is dealt with in this entire report is the aspect of the fluid’s flow rate in pipes. The flow rate often tends to vary due to variations in the volume and the cross-sectional area of the pipes. Generally, it dwells on the aspect of inflow and outflow which should remain constant. Generally, flow measurement refers to the aspect of fluid movement quantification within a given medium. There are a variety of ways for measurement of the flow rate movements. Positive-displacement types of flow meters tend to accumulate a predetermined fluid volume while counting the sequence in which the volume is entirely filled so as to adequately measure the flow (ALLEN & DITSWORTH, 1972).Other measurement methods with regards to the flow rates often rely on the forces that are duly produced by the entire flow while overcoming a specific constriction. Flow might be measured through the measurement of the fluid’s velocity over a given area. A Venturi meter refers to a type of a flow meter with a definite design. It generally has a 10˚ divergent segment and a 21˚ convergent segment. The fluid flow rate in a given pipe can be determined by application of both the continuity and Bernoulli’s equation, alongside the inner streamline edge between the throat and the mouth of the entire Venturi meter while recording the variations with regards to the static pressure (MERZKIRCH, 2005). As a main instrument that is usually used for determination of the volumetric flow rates, Venturi meter tends to constrict the entire flow in a specific manner, and the pressure sensors are usually utilized during the

Summary of Outliers by Malcolm Gladwell Essay Example for Free

Summary of Outliers by Malcolm Gladwell Essay Gladwell’s Outliers started with the introduction of the Roseto Mystery in which he presented the facts and findings of the physician, Stewart Wolf on how the Rosetans lived a life differently from Americans living in the city. Evidences and findings on how the Rosetans have a better life and little cases of heart diseases was not only due to the atmosphere of the place, the things they do, or the food they eat but simply the way Roseto is in which people greeted each other, go to church every day, and their strong family ties. In the first chapter, The Matthew Effect, we may glean from it the idea or phenomenon of â€Å"the rich becomes richer while the poor becomes poorer†. He mentioned about observations on the birth dates of Canadian hockey players and the eligibility of children to participate in youth hockey leagues. This was deemed important as it was a factor that would determine a child’s strength and ability on hockey since they were able to start earlier and they are most likely to be the ones to belong in the elite team in the future. Despite of the fact that birth date is an important factor, an individual’s own skill is really the key to reach the top. In the second chapter, The 10,000-Hour Rule, Gladwell presented that to become truly a master of something, an individual must undergo 10,000 hours of practice and mastery on a particular skill which is like doing 20 hours of work a week for 10 years. He cites examples like K. Anders Ericsson’s study at an elite Academy of Music in Berlin. The study was conducted on seeing the potential of music students by dividing them into three groups based on the potential they could see in them. According to the study, those students who belong in the elite/star group practiced more hours than the others that’s why by the age of twenty, these group of people will probably achieved mastery as they have totaled ten thousand hours of practice. Gladwell also mentioned the success of Bill Joy as he was a genius, and devoted time on computers and programming. Other examples were how the Beatles achieved the 10,000 hours rule due to the number of concerts and performances that they did. He also mentioned how William Henry â€Å"Bill† Gates achieved the 10,000 hours rule and it was not only that. According to his interview with Gates, he paved his way to success not only because of his penchant for computers but also of the opportunities opened to him during his lifetime. In the third and fourth chapter, The Trouble with Geniuses Parts 1 2, it was mentioned that being a genius is not enough to determine whether a person will truly be successful. He mentioned the story of Christopher Langan, a man with an IQ of 195 (higher than Einstein because he only had 150). Despite of Langan’s skills, he was not able to reach a high level of success because of the lack of opportunities and there is no one in his life to lead him to a higher level of success. In the fifth chapter, The Three Lessons from Joe Flom, presented three lessons according to Flom on how a person could achieve success. Lesson 1: The Importance of Being Jewish presents how Jewish people were exposed to work at an early age especially when it comes to clothing that lead them to their success in business. Lesson 2: Demographic Luck shows us how location can determine your place e.g. a place rich with gold and minerals possible for putting up a mining industry vs. a place with little natural resources. Lesson 3: Garment Industry and Meaningful Work presents how hard work is definitely an important factor to success. Reflection Looking at Gladwell’s observations, collection of ideas and stories from people about attaining success or being successful in life made me realize that one factor is not enough to be successful. According to the book, the date of birth, place of birth, how the individual was nurtured, social influences, interests, devotions, intellectual abilities, talents, etc are some of the many factors that determine one’s success Going back to Frank Lynch’s article on Social Acceptance Reconsidered, I realized that some of his points like Pakikisama is one of the factors that could help one become successful. Looking back at Chris Langan’s story, he wasn’t able to attain a higher level of success because he didn’t have someone to help him which means he lacks the value of Pakikisama. Let’s look at this: most successful business people not only in the Philippines but in the whole world achieve success not only by themselves but because of their partners or people who backed them up. Bill Gates too is one example since he had Paul Allen in putting up Microsoft Corporation. It is because of the value of Pakikisama that people achieve success because at times, we cannot accomplish things by depending only on ourselves. Thinking about the Philippines, I think that the ideals in the book, when applied can truly help our country towards development and prosperity. The Philippines is a country laden with a lot of natural resources which means that we possess the demographic luck. We also have some good universities that produce some of the brightest Filipinos that we have today. If only the Philippines would increase the way it encourages people and seek people’s potentials even at a young age, then we may be able to predict what we should mold our future human resources into so that by after 10 years on refining themselves on their chosen field, they could possibly achieve the 10,000 hours rule and achieve mastery on their field.

Behavoural changes ie smoking censation

Behavoural changes ie smoking censation Behavoural Changes ie smoking censation This essay will discuss the Behaviour Change Model of Health education or The Trans-theoretical Model, (TTM) in relation to smoking cessation. As G. K. Chesterton once said, â€Å"It isnt that they cant see the solution. It is that they cant see the problem.† Families, friends, neighbours, or employees, however, are often well aware that the pre-contemplators have problems. Stages of Change Prochaska DiClement`s transtheoretical model (1984,1986; Prochaska et al 1992) is important in describing the process of change. The model derived from their work on encouraging change in addiction behaviours, although it can be used to show that most people go through stages when trying to change or acquire behaviours. American psychologists, Jim Prochaska and Carlo Di Clement, Termination. Process of change. Downloaded By: [Glasgow Caledonian University] At: 14:49 12 July 2009 4 ADDICTIONS NURSING NETWORKNOLUME 5, NUMBER 1,1993 In our studies using the discrete categorization measurement of stages of change, we ask whether the individual is seriously intending to change the problem behavior in the near future, typically within the next six months. If not, he or she is classified as a precontemplator. Even precontemplators can wish to change, but this seems to be quite different from intending or seriously considering change in the next six months. Items that are used to identify precontemplation on the continuous stage of change measure include â€Å"As far as Im concerned, I dont have any problems that need changing† and â€Å"I guess I have faults, but theres nothing that I really need to change.† Resistance to recognizing or modifying a problem is the hallmark of precontemplation . Splral Pattern of Change. Many New Years resolvers report five or more years of consecutive pledges before maintaining the behavioral goal for at least six months (Norcross Vangarelli, 1989). Relapse and recycling through the stages occur quite frequently as individuals attempt to modify or cease addictive behaviors. Variations of the stage model are being used increasingly by behavior change specialists to investigate the dynamics of relapse (e.g., Brownell et al., 1986; Donovan Marlatt, 1988). Because relapse is the rule rather than the exception with addictions, we found that we needed to modify our original stage model. Initially we conceptualized change as a linear progression through the stages; people were supposed to progress simply and discretely through each step. Linear progression is a possible but relatively rare phenomenon with addictive behaviors. Figure 1 presents a spiral pattern that illustrates how most people actually move through the stages of change. In this spiral pattern, people can progress from contemplation to preparation to action to maintenance, but most individuals will relapse. During relapse, individuals regress to an earlier stage. Some TERYINATION a YAHTENANCE PRECONTEYPLATIOW CONTEYPLATKJN PREPARATKJ relapsers feel like failures-embanassed, ashamed, and guilty. These individuals become demoralized and resist thinking about behavior change. As a result, they return to the precontemplation stage and can remain there for various periods of time. Approximately 15% of smokers who relapsed in our self-change research regressed back to the precontemplation stage (Prochaska DiClemente, 1986). Fortunately, this research indicates that the vast majority of relapsers85% of smokers, for example- recycle back to the contemplation or preparation stages (Prochaska DiClemente, 1984). They begin to consider plans for their next action attempt while trying to learn from their recent efforts. To take another example, fully 60% of unsuccessful New Years resolvers make the same pledge the next year (Norcross, Ratzin, Payne, 1989; Norcross Vangarelli, 1989). The spiral model suggests that most relapsers do not resolve endlessly in circles and that they do not regress all the way back to where they began. Instead, each time relapsers recycle through the stages, they potentially learn from their mistakes and can try something different the next time around (DiClemente et al., 1991). On any one trial, successful behavior change is limited in the absolute numbers of individuals who are able to achieve maintenance (Cohen et al., 1989; Schachter, 1982). Nevertheless, in a cohort of individuals, the number of successes continues to increase gradually over time. However, a large number of individuals remain in contemplation and precontemplation stages. Ordinarily, the more action taken, the better the prognosis. Much more research is needed to better distinguish those who benefit from recycling from those who end up spinning their wheels. Arguments for and against Conclusion Influencing the people to change behaviours such as how they eat,excersice ,drink, smoke requires a long term commoitment but it is a process that they can sucseed. Nurses have a key role to play in influencing behaviour of their patients, and health promotion should be embed MAINTENANCE: practice required for the new behaviour to be consistently maintained, incorporated into the repertoire of behaviours available to a person at any one time. ACTION: people make changes, acting on previous decisions, experience, information, new skills, and motivations for making the change. PREPARATION: person prepares to undertake the desired change requires gathering information, finding out how to achieve the change, ascertaining skills necessary, deciding when change should take place may include talking with others to see how they feel about the likely change, considering impact change will have and who will be affected. CONTEMPLATION: something happens to prompt the person to start thinking about change perhaps hearing that someone has made changes or something else has changed resulting in the need for further change. PRECONTEMPLATION: changing a behaviour has not been considered; person might not realise that change is possible or that it might be of interest to them. Source: The Behavior Change spiral from What do they want us to do now? AFAO 1996 ded in daily practice. E following review explores and considers some of the major theories of behaviour and behaviour change that may be pertinent to the development of effective interventions in travel behaviour, including theories and concepts from mainstream psychology, and the associated sub-disciplines of health, leisure, recreation, physical activity and exercise psychology. For many years conceptual models of behaviour change, such as Banduras Social Cognitive Learning Theory (1986), Beckers Health Belief Model (1974), Azjen and Fishbeins Theory of Reasoned Action (1975); have been applied across a wide variety of disciplines, including travel and road user behaviour. Considerable attention has been given in the literature to models of individual behaviour change per se but much less attention has been given to models or theories that attempt to understand behaviour change within groups, organisations and whole communities. The design of programs to reach populations requires an understanding of how those communities work, their barriers and enablers to change, and what influences their behaviours in general. Stage Theories of Behaviour Change Mounting evidence suggests that behaviour change occurs in stages or steps and that movement through these stages is neither unitary or linear, but rather, cyclical, involving a pattern of adoption, maintenance, relapse, and readoption over time. The work of Prochaska and DiClemente (1986) and their colleagues have formally identified the dynamics and structure of staged behaviour change. In attempting to explain these patterns of behaviour, Prochaska and DiClemente developed a transtheoretical model of behavioural change, which proposes that behaviour change occurs in five distinct stages through which people move in a cyclical or spiral pattern. The first of these stages is termed precontemplation. In this stage, there is no intent on the part of the individual to change his or her behaviour in the foreseeable future. The second stage is called contemplation, where people are aware that a problem exists and are seriously considering taking some action to address the problem. However, at this stage, they have not made a commitment to undertake action. The third stage is described as preparation, and involves both intention to change and some behaviour, usually minor, and often meeting with limited success. Action is the fourth stage where individuals actually modify their behaviour, experiences, or environment in order to overcome their problems or to meet their goals. The fifth and final stage, maintenance, is where people work to prevent relapse and consolidate the gains attained in the action stage. The stabilization of behaviour change and the avoidance of relapse are characteristic of the maintenance stage. Prochaska and DiClemente further suggest that behavioural change occurs in a cyclical process that involves both progress and periodic relapse. That is, even with successful behaviour change, people likely will move back and forth between the five stages for some time, experiencing one or more periods of relapse to earlier stages, before moving once again through the stages of contemplation, preparation, action and eventually, maintenance. In successful behavioural change, while relapses to earlier stages inevitably occur, individuals never remain within the earlier stage to MAINTENANCE: practice required for the new behaviour to be consistently maintained, incorporated into the repertoire of behaviours available to a person at any one time. ACTION: people make changes, acting on previous decisions, experience, information, new skills, and motivations for making the change. PREPARATION: person prepares to undertake the desired change requires gathering information, finding out how to achieve the change, ascertaining skills necessary, deciding when change should take place may include talking with others to see how they feel about the likely change, considering impact change will have and who will be affected. CONTEMPLATION: something happens to prompt the person to start thinking about change perhaps hearing that someone has made changes or something else has changed resulting in the need for further change. PRECONTEMPLATION: changing a behaviour has not been considered; person might not realise that change is possible or that it might be of interest to them. Source: The Behavior Change spiral from What do they want us to do now? AFAO 1996 which they have regressed, but rather, spiral upwards, until eventually they reach a state where most of their time is spent in the maintenance stage. Further work undertaken and reported by Prochaska et el (1992) suggests that behaviour change can only take place in the context of an enabling or supportive environment. Prochaskas and DiClementes model has received considerable support in the research literature. Their model has also been shown to have relevance for understanding, among other things, patterns of physical activity participation and adherence and would have relevance in bringing about change in travel behaviours. Consistent with the above perspective, Sallis and Nader (1988) also have suggested a stage approach to explaining movement behaviour, particularly in family groups, with research aimed at understanding better the cyclical patterns of movement activity SOCIAL FEATURES nature of personal elationships; expectations of class, position, age, gender;access to knowledge, information. CULTURAL FEATURES the behaviours and attitudes considered acceptable in given contexts eg. relating to sex, gender, drugs, leisure, participation. ETHICAL SPIRITUAL FEATURES influence of personal and shared values and discussion about moral systems from which those are derived can include rituals, religion nd rights of passage. LEGAL FEATURES laws determining what people can do and activities to encourage observance of those laws . POLITICAL FEATURES systems of governance in which change will have to take place can, for example, limit access to information and involvement in social action. RESOURCE FEATURES affect what is required to make things happen covers human, financial and material resources; community knowledge and skills; and items for exchange Source: The Behavior Change spiral from What do they want us to do now? AFAO 1996 involvement, including adoption, maintenance, and relapse, and interventions aimed at minimizing the amount of time individuals spend in the relapse stage as well as maximizing time spent in action or maintenance. This stage approach is contrasted to the all or none approach to physical activity participation that often characterized early research on exercise adherence. Such a staged approach sits well with any school based program that is focussed on travel behaviour change given that the context in which the program is to be applied would see fluctuations in the positive and negative influences according to such things as work and time demands of family members, weather, events or incidents in the local neighbourhood that may influence perceptions of safety. Parallel with the work of Prochaska and DiClemente, Rogers, (1983) also developed a stage-based theory to explain how new ideas or innovations are disseminated and adopted at the community and population levels. Rogers identified five distinct stages in the process of diffusion of any new initiative or innovation. These are knowledge, persuasion, decision, implementation, and confirmation. Rogers argued that the diffusion of an innovation is enhanced when the perceived superiority of an innovation is high compared to existing practice (i.e. the relative advantage), and when the compatibility of the innovation with the existing social system is perceived to be high (i.e. compatibility). Other important influences on the diffusion process are said to be complexity, triability, and observability, with innovations which are of low complexity, easily observed, and that are able to be adopted on a trial basis, being associated with greater adoption and swifter diffusion. Building success and comfort during the early stages of the implementation of the TravelSMART Schools program will be paramount to its success. Rogers classifies individuals as innovators, early adopters, early majority, late majority, late adopters, and laggards, dependent upon when during the overall diffusion process they adopt a new idea or behaviour. While this model has not been tested empirically to date, it has been adapted and applied in health promotion settings usually in conjunction with social learning theory and/or self-efficacy theory, with some success. It certainly warrants attention in the development of the TravelSMART Schools program. In summarizing the various stage models of behaviour change that have been proposed over the past two decades, Owen and Lee (1984) highlighted a number of commonalties they share. These authors propose an integrated stage-based model in which behaviour change is viewed as a cyclical process that involves five stages of: awareness of the problem and a need to change motivation to make a change skill development to prepare for the change initial adoption of the new activity or behaviour, and maintenance of the new activity and integration into the lifestyle. In terms of a TravelSMART program this may mean: Five stages of behaviour change Examples of content and processes Awareness of the problem and a need to change Provision of, or ways to seek information on the dependence on motorised travel; evidence of the greenhouse effect; issues relation to building relationships and fitness Motivation to make a change Benefits of increased personal fitness; benefits of leaving the car at home eg. environmental and social Skill development to prepare for the change Mapping of the local area to identify alternative forms of travel, ways to negotiate with reluctant family members or peers to manage the need to carry; strategies for trip chaining and travel blending Initial adoption of the new activity or behaviour Self monitoring of newly adopted behaviours to, opportunities for reflections and comparisons Maintenance of the new activity and integration into the lifestyle Provision of feedback on how the change is going, and an injection of new ideas or strategy An important aspect of both Prochaskas and DiClementes approach and that suggested by Owen and Lee is that each of the five stages of behaviour change is said to involve different cognitive processes and require different treatments or intervention strategies for the overall change process to be successful. Prochaska and DiClemente (1992) outlined a number of cognitive change processes that have been found to be associated with each stage. Other researchers also propose that different stages in the change process require different intervention strategies, and generally recommend a multifaceted, community-based approach to intervention in which all stages are addressed so that individuals at all stages of readiness for change can potentially be influenced. This sits well with the overall TravelSMART programs TravelSMART Communities, TravelSMART Workplaces and TravelSMART Schools. A major insight offered by stage theories of behaviour change, then, is the emphasis they place on matching interventions to the stage of readiness of the individual. This kind of approach provides an excellent framework for understanding and examining individual differences in motivation for, and involvement in, change in travel behaviours over time, including patterns of initiation, maintenance, relapse, and resumption. In summary, theories that conceptualise behaviour change in terms of a cyclical process through which individuals move in stages, have received empirical support in the research, and appear to offer much promise for understanding travel behaviours and curricula to bring about changes in travel behaviour. A major strength of the Stages of Change model is that it has also been used in conjunction with a variety of other theories and models that are relevant to different levels of influence at an intrapersonal, interpersonal, institutional, community or public policy level. (Glanz and Rimer (1995) as reported by Oldenberg et al (1999)) Social Cognitive-Behavioural Theories and Similar Theories Social Cognitive Theory explains human behaviour in terms of a triadic, dynamic and reciprocal model in which behaviour, personal factors, and environmental influences interact. It addresses both the psychological dynamics underlying behaviour and their methods for promoting behaviour change. It is a very complex theory and includes many key constructs. Self-efficacy is one of the key concepts. Self-efficacy refers to ones confidence in the ability to take action and persist in action. It is seen by Bandura (1986) as perhaps the single most important factor in promoting changes in behaviour. Measures of self-efficacy and some of the other key concepts from Social Cognitive Theory have also been identified as key determinants of movement through the stages of change, (Oldenburg, 1999). Self-efficacy expectations have been found repeatedly to be important determinants of: the choice of activities in which people engage how much energy they will expend on such activities and the degree of persistence they demonstrate in the face of failure and/or adversity. In general, higher levels of self-efficacy for a given activity are associated with higher participation in that activity. Similarly, and closely aligned to Social Cognitive Theory, Attribution Theory proposes that individuals generally view their performance (and thus, their successes and failures) as dependent upon ability, effort, task difficulty, and luck. In addition, causal influences are seen as either internal to the individual (e.g. personal ability), or external (e.g. barriers to community safety, lack of convenient and attractive travel alternatives). The distinction between internal and external attributions is an important one, in that how we attribute our personal successes and failures has been shown to be related to not only our behaviour, but our self-esteem, our perceptions of personal control, our self-efficacy for different tasks and/or performance situations, and our ongoing involvement in different activities. For example, a person who attributes their failure to change their dependence on motorised travel to their inherent lack of ability to identify and use alternatives will be less likely to continue with the alternative modes of travel after the educational program has ceased. A persons attributions for personal success and failure in a given situation, then, determines how that person feels about the task, as well as the amount of effort he or she is likely to invest in the task the next time around. When failure is attributed to low personal ability and a difficult task, individuals are more likely to give up sooner, select easier alternatives, such as using personal motorised travel, and lower their goals. Conversely, when failure is attributed to external factors such as bad luck, individuals are likely to have higher motivations to continue and to try again for success. Attitudes and their potential relationship to behaviour also have been studied extensively. In general, attitudes have not generally been found to be consistently related to behaviour. This failure to demonstrate a consistent relationship between attitudes and behaviour may be because situational factors also exert a powerful influence on behaviour. In addition, how attitudes have been defined and measured in different studies varies considerably. Research has demonstrated consistently that an attitude is likely to predict behaviour when: the attitude includes a specific behavioural intention when both the attitude and the intention are very specific and when the attitude is based on first-hand experience . These aspects of the behaviour-attitude relationship have been addressed in the Theory of Reasoned Action, which focuses on the role of context-specific attitudes in defining behaviour. In this model, behaviour is seen as a function of a persons intention, which in turn is comprised of the individuals attitudes towards performing the behaviour and the influence of perceived social norms concerning the performance of the behaviour. Attitudes are affected by the persons beliefs about the perceived consequences of performing a given action, and his or her subjective evaluation of each of the consequences. Drawing this together, any published individually focused and community based health behaviour change and health promotion programs have generally been based on Social Cognitive theories utilising techniques that emphasise the cognitive and social mediators of behaviour. Interventions based on cognitive learning theory emphasize self-management principles and strategies. Other Theories to Consider Personality Theories Personality theories explain behaviour largely in terms of stable traits or patterns of behaviour which are viewed as resistant to change and inalterable. Rogers, (1985), classification of individuals into the five categories of innovators, early adopters, early majority, late majority, late adopters, and laggards is an example of this kind of approach to understanding behaviour. A major limitation of personality theories is that they do not take account of important aspects of the physical, social and economic environments, or the previous experiences of the individual, which also are known to strongly influence behaviour. For this reason, personality theories alone now are generally considered inadequate to explain behaviour change. Learning and Behaviour Theories Learning theorists have demonstrated that behaviour can be changed by providing appropriate rewards, incentives, and/or disincentives. In learning or behaviourist approaches, these rewards and incentives are typically incorporated into structured reinforcement schedules, and the process of behaviour changes is often termed behaviour modification. While effective in bringing about behaviour change, such approaches require a high level of external control over both the physical and social environment, and the incentives (or disincentives) used to reinforce certain behaviours and discourage others. This kind of control is hard to maintain in real life settings, and thus, strict behaviourist approaches are subject to a number of limitations. Social Learning Theory Social learning theory is similar to learning and behaviour theories in that it focuses on specific, measurable aspects of behaviour. Learning theories, however, view behaviour as being shaped primarily by events within the environment, whereas social learning theory views the individual as an active participant in his or her behaviour, interpreting events and selecting courses of action based on past experience. Again, one important theory deriving from social learning theory which has had a major impact on many current models of behaviour change is that of self-efficacy. As stated earlier, self-efficacy expectations have to do with a persons beliefs in his or her abilities to successfully execute the actions necessary to meet specific situational demands. Such expectations have been found to be consistently related to behaviour across a wide range of situations and populations sub-groups. Social Psychological Theories Social psychological theories are concerned with understanding how events and experiences external to a person (i.e. aspects of the social situation and physical environment) influence his or her behaviour. Emphasis is placed on aspects of the social context in which behaviour occurs, including social norms and expectations, cultural mores, social stereotypes, group dynamics, cohesion, attitudes and beliefs. A number of useful concepts have emerged from social psychological theories, including attribution, locus of control, and cognitive dissonance, to name a few. Social Cognitive Approaches Social cognitive approaches combine aspects of social psychological theories with components of both social learning theory and cognitive behavioural approaches. Social-cognitive approaches emphasize the persons subjective perceptions and interpretations of a given situation or set of events, and argue that these need to be taken into account if we are to understand adequately both behaviour and the processes of behaviour change. A number of social psychological concepts have been found to be consistently related to behaviour change across a wide range of situations. For example, the social reality of a the group (e.g. peer group, school group, family group etc.) will affect an individuals behaviour. All groups are characterized by certain group norms, beliefs and ways of behaving, and these can strongly affect the behaviour of the group members. Expectations of significant or respected others can also have a strong influence on a persons behaviour. This phenomenon has been most consistently demonstrated in the early research on self-fulfilling prophecies, which showed that teachers expectations of their students were consistently related to the students subsequent performance, even when these expectations were based on falsified information. Thus, support and encouragement, or conversely, low expectations from significant or respected others, can affect and bring about, (or not), changes in individual behaviour. Health Belief Model The Health Belief Model attempts to explain health-behaviour in terms of individual decision-making, and proposes that the likelihood of a person adopting a given healthrelated behaviour is a function of that individuals perception of a threat to their personal health, and their belief that the recommended behaviour will reduce this threat. Thus, a person would be more likely to adopt a given behaviour (e.g. walk or cycle regularly) if non-adoption of that behaviour (e.g. unclean air or confused traffic situations) is perceived as a health threat and adoption is seen as reducing that threat. To date, the Health Belief Model has not received consistent or strong support in explaining behaviour change. When the concept of self-efficacy is added to the model, however, prediction of behaviour increases. Social Marketing Another approach that has been used to bring about behaviour change is that of social marketing. The concept of social marketing is based on marketing principles and focuses on four key elements, including: development of a product the promotion of the product the place the price. As such, this approach is not so much a theory of behaviour change but a proposed framework, which situates people as consumer who will potentially buy into a certain idea or argument, given the appropriate selling techniques are applied. It is then assumed that the buying in to that idea by individuals will result in behaviour change. Theory of Interpersonal Behaviour Habit strength is another concept that has been found to be important in predicting or changing behaviour. Habit is an important element of the theory of interpersonal behaviour, which proposes that the likelihood of engaging in a given behaviour is a function of: the habit of performing the behaviour the intention to perform the behaviour conditions which act to facilitate or inhibit performance of the behaviour. In turn, intentions are said to be shaped by a cognitive component, an affective component, a social component, and a personal normative belief. The theory of i

Romeo and Juliet by William Shakespeare :: Free Essay Writer

Romeo and Juliet by William Shakespeare "Violent delights have violent ends" Romeo and Juliet, two young people from Verona, come from two families in conflict. They meet at a ball and fall in love and only to find out their roots and families. They realise their stubborn families would not approve and plan on how they can be together. As we see in the play the friars words "violent delights have violent ends", has a very significant meaning to the story where things that are started violently have often have violent ends. At the beginning of the play the scene opens with the Montages and the Capulets fighting in the market place of Verona. Already from the first scene we know that there will be more violence and possibly a tragic end. Here the friar's premonition is already coming true before he has even said it. The prince suddenly appears and says, "thrice has my city been disturbed by your fighting". He vows that if they disturb again the culprits would be put to death. The climate in Verona is very hot and dry this often sparks fights and people's tempers become fiery. The main characters in the play are Romeo and Juliet who are in love and the play is centred on them. Mercutio is a Montague; he is a lighthearted man and a joker. Benvolio is also a Montague; he is a ver peaceful and sensible man. Tybalt is very aggressive and passionate. Romeo and Juliet meet at a masked ball hosted by the Capulet family. Romeo goes because he thinks that Roselyn the girl he admires will be there. When Romeo arrives there he puts his mask on so they do not recognise him, as he is the Capulets enemy. Romeo begins to dance and he spots Juliet she also spots him. They gaze at each other's eyes and begin to dance. It could be said that fate is already at work here. Juliet's nurse calls for her and here is where they both find out each there's identity. They are both devastated.

Biometrics Security Essay -- Biometric Technology

Biometrics Security Biometrics uses personal characteristics to identify users. When it comes to security, mapping unique patterns and traits in fingerprints, irises or voices is considered light years ahead of forcing employees to memorize combination of letters and numbers -- which are easily compromised and easily forgotten. The technology works by taking measurements -- whether it is the weight and length of bones in the hand or the pattern of blood vessels inside the eye or the pattern of fingerprints -- and then storing the specifics, often called minutiae, in a database. When a user scans a hand or retina, the new mapping is compared with the stored data. Access is either granted or denied based on matching patterns that are unique to each individual. It's that ability to identify someone based on unique physical traits that is driving biometrics into the corporate enterprise. As more high-priced transactions are conducted over the Internet, businesses increasingly need ironclad authentication of someone's identity. Add to that the increasing amount of in"house security breaches and corporate espionage, and you'll find network and security administrators grappling for a better way to secure information from unauthorized eyes. "Somebody who is doing stock trades online wants security that is amazingly accurate," says Michael Thieme, a senior consultant for International Biometric Group in Manhattan, an independent biometrics consulting and integration firm." A lot of recent security incidents are making people aware that they have a lot of data that just isn't as secure as they thought it would be. . . . If biometrics can even be a small part of that, it will be a tremendous market." Costs are dropping Until recen... ...s fingerprint. That all amounts to an unlawful search." And that is bound to make some users uneasy or even unwilling to hand over their fingerprints. Grant Evans, vice president of Identix, calls it a small problem. "The fact is Big Brother has all the information he needs on you without your fingerprints," he says. Gail Koehler, vice president of technology for Purdue Employees Credit Union in West Lafayette, Ind., was worried that members would be upset when she first deployed fingerprint scanners in her automated branch kiosks. Koehler says 12,000 members have registered their fingerprints with the credit union. "We spent the majority of our marketing dollars preparing ourselves to convince members that this was secure and not an invasion of their privacy," she says. "It was wasted dollars. We've basically had no objections. Members prefer the security."

Healthcare Industry

The global healthcare industry is expected to grow at a CAGR of 24.7%. This is made possible by the leveraging of various analytics tools and practices by the healthcare providers for improving their operational efficiency. Source: http://www.thehealthcareanalytics.comUnited States is at the front of the growth, accounting for 65.84% which can be attributed to country's substantial investment in healthcare. Europe and Asia are on a path of steady growth with increased expenditure on technology, R;D and the emergence of Big Data. Source: http://www.thehealthcareanalytics.comThe volume of data available is expected to be increasing at an exponential rate in the years ahead. Current cumbersome techniques of evaluation will soon have to pave the way for advanced analytics. These techniques, which have the ability to process, act on, manage and distribute data from variety of sources, will become the backbone of the healthcare sector. With this evaluation, the vast health data will be better understood and more effective, real time, specific decisions can be taken. Source: http://www.techferry.com Current SituationBefore discussing about the future, it is important to reflect upon the current scenario. After the introduction of Electronic Health Records (EHR), amount of data collected have gone up significantly, creating meta data that can be used for querying. Healthcare organizations have resorted to analytical tools to improve the efficiency of patient examination. With a wide range of information about patient's history, genetics and demographics, more customized quality care could be provided. More and more venture capitalists have started investing into healthcare analytics. However, healthcare organizations are a long way from making effective use of such information. Proper understanding about the vast applications of such a resource is still scarce. Differentiating between quality data and noise has been becoming more and more difficult. High cost of analytic solutions and lack of skilled professionals have been a pain point in many organizations. Leveraging bigdata analytics in healthcarePatient profile analytics: Analytics can be applied to the existing patient profiles to identify those who may need preventive care. Patients who are at a risk of developing a disease like diabetes can be helped with lifestyle changes and preventive care.Public health: By analysing the large amount of data available, disease patterns can be identified and outbreaks can be predicted by finding various correlations among the data points.Resource management: With the development of location tracking technologies like RFIDs, patients, staffs, instruments and other resources in the enterprise can be effectively tracked and managed on a real time basis.Fraud analysis: Hospitals on a daily basis receives large number of insurance claims. With the help of big data analytics, valid claims can be segregated out reducing wastage of time and resources.Genomic Analytics: Genes of an individual and high-powered computing are combined to produce personalize d treatments for each patient. Genetic disorders can be identified and target therapies can be developed.Real-Time health care: Various mobile applications are being developed that help individuals to manage their care in a personalized manner. Wearables are being developed that can effectively track the safety and monitor the conditions in real-time by analysing the large volumes of fast moving data.R & D: Predictive modelling and statistical methods can be used to improve clinical trials and finding the follow-on indications. Trial failures can be reduced and new product development can be given the push it demands.Concerns and mitigation strategiesData Integrity: The data in many situations comes from places with questionable data governance standards. Obtaining data that meets with the standards required for accurate use is one of the major ongoing battles in organizations. Lack of understanding of the usage of EHR (Electronic Healthcare Records) and importance of capturing qual ity data further adds to the lack of data quality.Future: Improvements in data capture by prioritizing valuable data types and educating clinicians about how to ensure that data is useful for downstream analytics are some of the ways forward.Filtering: Presence of inaccurate unwanted data (noise) can derail the effectiveness of the analytics system. The data, which comes from disparate data sources in multiple formats, unless acted upon properly will lead to inconsistency. Though Data cleaning, process of ensuring the datasets are consistent, accurate and relevant, are being done, most organizations still use inefficient manual methods. Future: IT vendors are now coming up with applications which use machine learning that use rules to filter and segregate data, which will make the process effective and affordableStorage: With the latest developments in technology, amount of data being generated and captured is increasing at an alarming rate. Even though most enterprises currently pr efer on premise data storage which has the advantage of having better control on security and access, it has become difficult to modify, scale and adapt to situations.Future: Many organizations are slowly shifting to cloud storage and various hybrid approaches to store their data. This provides a highly scalable, cost effective solution which provides ease of access.Security: With the recent episodes of high profile hackings, security breaches, ransomwares etc security has become a huge concern in this technological era.From a small action like leaving the laptop unsecured to highly sophisticated hacking, data is not safe in spite of many initiatives being taken.Future: Employees are being educated in transmission security, authentication protocols, and controls over access, integrity, and auditing. Procedures such as using latest anti-virus software, setting up firewalls, encrypting sensitive data, and using multi-factor authentication are some of the ways to prevent security attac ks. As we move forward in 2018, organizations will have to analyse much more complex and high-volume data. With the development of customized, highly efficient data analytics practices, organizations can make sense of the data and use it for providing efficient personalized care. Data integrity is bound to become the most important factor as effectiveness of data analytical methods are dependent on incorporation of error free, relevant data from quality sources.References1. http://www.thehealthcareanalytics.com 2. Healthcare Industry The global healthcare industry is expected to grow at a CAGR of 24.7%. This is made possible by the leveraging of various analytics tools and practices by the healthcare providers for improving their operational efficiency. Source: http://www.thehealthcareanalytics.comUnited States is at the front of the growth, accounting for 65.84% which can be attributed to country's substantial investment in healthcare. Europe and Asia are on a path of steady growth with increased expenditure on technology, R;D and the emergence of Big Data. Source: http://www.thehealthcareanalytics.comThe volume of data available is expected to be increasing at an exponential rate in the years ahead. Current cumbersome techniques of evaluation will soon have to pave the way for advanced analytics. These techniques, which have the ability to process, act on, manage and distribute data from variety of sources, will become the backbone of the healthcare sector. With this evaluation, the vast health data will be better understood and more effective, real time, specific decisions can be taken. Source: http://www.techferry.com Current SituationBefore discussing about the future, it is important to reflect upon the current scenario. After the introduction of Electronic Health Records (EHR), amount of data collected have gone up significantly, creating meta data that can be used for querying. Healthcare organizations have resorted to analytical tools to improve the efficiency of patient examination. With a wide range of information about patient's history, genetics and demographics, more customized quality care could be provided. More and more venture capitalists have started investing into healthcare analytics. However, healthcare organizations are a long way from making effective use of such information. Proper understanding about the vast applications of such a resource is still scarce. Differentiating between quality data and noise has been becoming more and more difficult. High cost of analytic solutions and lack of skilled professionals have been a pain point in many organizations. Leveraging bigdata analytics in healthcarePatient profile analytics: Analytics can be applied to the existing patient profiles to identify those who may need preventive care. Patients who are at a risk of developing a disease like diabetes can be helped with lifestyle changes and preventive care.Public health: By analysing the large amount of data available, disease patterns can be identified and outbreaks can be predicted by finding various correlations among the data points.Resource management: With the development of location tracking technologies like RFIDs, patients, staffs, instruments and other resources in the enterprise can be effectively tracked and managed on a real time basis.Fraud analysis: Hospitals on a daily basis receives large number of insurance claims. With the help of big data analytics, valid claims can be segregated out reducing wastage of time and resources.Genomic Analytics: Genes of an individual and high-powered computing are combined to produce personalize d treatments for each patient. Genetic disorders can be identified and target therapies can be developed.Real-Time health care: Various mobile applications are being developed that help individuals to manage their care in a personalized manner. Wearables are being developed that can effectively track the safety and monitor the conditions in real-time by analysing the large volumes of fast moving data.R & D: Predictive modelling and statistical methods can be used to improve clinical trials and finding the follow-on indications. Trial failures can be reduced and new product development can be given the push it demands.Concerns and mitigation strategiesData Integrity: The data in many situations comes from places with questionable data governance standards. Obtaining data that meets with the standards required for accurate use is one of the major ongoing battles in organizations. Lack of understanding of the usage of EHR (Electronic Healthcare Records) and importance of capturing qual ity data further adds to the lack of data quality.Future: Improvements in data capture by prioritizing valuable data types and educating clinicians about how to ensure that data is useful for downstream analytics are some of the ways forward.Filtering: Presence of inaccurate unwanted data (noise) can derail the effectiveness of the analytics system. The data, which comes from disparate data sources in multiple formats, unless acted upon properly will lead to inconsistency. Though Data cleaning, process of ensuring the datasets are consistent, accurate and relevant, are being done, most organizations still use inefficient manual methods. Future: IT vendors are now coming up with applications which use machine learning that use rules to filter and segregate data, which will make the process effective and affordableStorage: With the latest developments in technology, amount of data being generated and captured is increasing at an alarming rate. Even though most enterprises currently pr efer on premise data storage which has the advantage of having better control on security and access, it has become difficult to modify, scale and adapt to situations.Future: Many organizations are slowly shifting to cloud storage and various hybrid approaches to store their data. This provides a highly scalable, cost effective solution which provides ease of access.Security: With the recent episodes of high profile hackings, security breaches, ransomwares etc security has become a huge concern in this technological era.From a small action like leaving the laptop unsecured to highly sophisticated hacking, data is not safe in spite of many initiatives being taken.Future: Employees are being educated in transmission security, authentication protocols, and controls over access, integrity, and auditing. Procedures such as using latest anti-virus software, setting up firewalls, encrypting sensitive data, and using multi-factor authentication are some of the ways to prevent security attac ks. As we move forward in 2018, organizations will have to analyse much more complex and high-volume data. With the development of customized, highly efficient data analytics practices, organizations can make sense of the data and use it for providing efficient personalized care. Data integrity is bound to become the most important factor as effectiveness of data analytical methods are dependent on incorporation of error free, relevant data from quality sources.References1. http://www.thehealthcareanalytics.com 2.