Importance of Human Interaction in William Faulkners A Rose for Emily

Importance of Human Interaction in William Faulkner's A Rose for Emily Are human beings responsible for the well being of others that they come into contact with? William Faulkner's story "A Rose for Emily" considers the significance that human interaction has or does not have on people's lives. Faulkner creatively uses a shocking ending to cause readers to reevaluate their own interactions with others in their lives. Throughout the story, Faulkner uses characters that may relate to the readers more than they want to admit. Homer Barron, the construction worker from the North, and the residents of Jefferson are used to expose the opportunities, although different, they are afforded to affect the life of Emily Grierson, who is the town's recluse. Faulkner offers Homer and the townspeople opportunities to affect Emily's life, and the story tells how these humans react to Emily and her situation. Ultimately, Homer and the townspeople choose not to intervene, and thus the devastation of Emily's life is inevitable. First, before human interaction can occur, an emotional response has to be provoked. Faulkner uses human curiosity to provide the opportunities that Homer and the residents of Jefferson will have to affect Emily's life. At one time, all people would have wanted to be included in the same social class to which Emily and her father belonged. Just as in Faulkner's own life, the Civil War changed life in the South forever. Emily is now a misplaced icon as industry has taken over her street, and the once-beautiful house is decaying and oddly out of place among the garages and the machines. Faulkner refers to Emily's house as "an eyesore among eyesores." Like her house, Emily has fallen out of grace, and the townspeople ... ...d leaning forward, that faint and invisible dust dry and acrid in the nostrils, we saw a long strand of iron-gray hair." So desperate for human contact, Emily has been sleeping next to a dead man's body. No one in the whole town had the slightest human insight to see this lady's predicament of needing human contact. Faulkner could be drawing attention to the proximity of a desperate person in the reader's life and could be questioning whether or not the reader will react once he acknowledges the need. The world needs more human interactions that overcome fear, hatred, and death. If curiosity evokes action and if this action produces guidance, not necessarily conformity, then human beings truly can have a significant effect on others' lives. Works Cited: Faulkner, William. "A Rose for Emily." Collected Stories of William Faulkner. New York: Random House, 1950.

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.

OF MICE AND MEN ESSAY Libre - 2222 Words

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