Fluent Essays

please find the attached document and reply to student posts. student names in bold. xav_shan_sa_replies.docx Unformatted Attachment Preview Read below student posts and reply each in 130 words Monica- Cryptocurrencies are digital mode of exchange, and contain value. The cryptocurrency can be created by cryptography. It is totally secure and verified payment method. These cryptocurrencies are considered safe investment because they are limited in number, and as their number goes near maximum limit, their price will start increasing. Value of crypto currencies are compared to American dollar, in order to examine the performance of crypto currencies, they are compared with conventional investment. The prices of cryptocurrencies keep on fluctuating (What is Cryptocurrency., n.d.). Comparison and Contrast of Ethereum and Litecoin Ethereum is possible to trade in stock exchange, and was created by Vitalik Buterin . Ethereum is capable to transfer property. Litecoin was created in 2011; it is considered a currency and a mode of payment in various places. Litecoin is similar to Bitcoin, and its maximum limit is 84M. The rest of the rules are same, as their price will start increasing as they will grow (Fernando, 2019). The similarity between Ethereum and Litecoin is both can be traded and exchanged in Coinbase, and their transactions are faster. They are different in respect of interest they are used for; Ethereum is used by developers and investors whereas Litecoin is used as alternative to Bitcoin (Huffman, 2019). Personal Experience My experience of using cryptocurrency was new to me and was also full of extreme excitements as I have never used virtual currency before. I registered to a website that sells cryptocurrency, and provide the price of Ethereum cryptocurrency, which was $170 at that time, through my debit card. This amount and was transferred to my account wallet, which I later used to purchase Ethereum currency. I had no plans of using it for earning revenue, and I spend it in shopping when I ran out of money at the end of month. I feel cryptocurrency was a whole new thing, as large e-commerce websites were willing to accept cryptocurrencies. Anuteja- Bitcoin Bitcoin is digital money not regulated by an overseeing third party, developed the aim in 2009 developed an alternative to an economic model controlled by the banks and governments. Just in order, bitcoins use blockchain, a growing list of records that are linked together to keep the system secure using cryptography. Miners add these blocks to blockchain who find the blocks by solving a cryptographic puzzle. Miners are people with computers to process the transactions by contribution. Their power to process electricity and computer to the bitcoin system. The Bitcoin system in exchange is structured so that the miner receives several bitcoins for finding a block. The movement of the amount fluctuates over time. A block includes some of the ongoing transactions, but not all transactions which have ever been made before. A transaction is considered verified when it is part of a transaction block inside a blockchain. In addition to the incentive to locate the stone, the miner also receives the fees per transaction falling within its block. It takes an average of ten minutes to get a miner to find a block somewhere. That means an average of every ten minutes an extra bitcoins are applied to the device for minutes. There are nearly 2,644 million bitcoins left, which are not yet in circulation. At only 21 million bitcoins will still exist, which means there are only 13.35 million bitcoins available. Among those 18.35 million, it is estimated that among issues like hard drive crashes and misplaced private keys, 30 percent of those will be lost forever. Ethereum Ethereum is a particular blockchain-based software framework that enables contracts and so-called distributed applications to be built and run. Such a network is also the base of the associated virtual currency. Ethereum offers a complete programming language for the interpretation of smart contracts that allows the development of programs and running them on the blockchain. Ethereum uses accounts and their balances, which shift through changes in the state. The state denotes the existing balances of all accounts, plus other extra data necessary. The state is not stored directly on the blockchain but is encoded and kept by accounts in a different data structure configured as a Merkle Patricia tree. Divyesh- Chapter 3, The Quality of Social Simulation: An Example from Research Policy Modelling Of all the three views mentioned in chapter 3, Based on the situation introduced, the best quality appraisal for the recreation is the client network. Social recreation is characterized as the use of innovations and PC based techniques to copy the social conduct of individuals in different situations and conditions. A social reproduction will in general duplicate social situation or procedures with the assistance of a PC program. In this situation, the client network social recreation is the best and which includes connecting with the network where the network is completed so genuine information and direct data is acquired (Cioffi-Revilla, 2014). In the greater part of cases, the client network is frequently client-driven, intuitive, or intelligent it requires tolerance ability to bargain in both sides informative aptitudes and t is likewise persuasive in nature. In the greater part of the cases, the client network partakes in giving data to the adjusting approach, other than that it isnt that easy to affirm the quality, accessibility, and presence of information and check for database prerequisites and for the organizations. Since the nature of the reproduction shifts according to the client it, along these lines, relies upon the nature of model adjustment and information, as such a great deal of exertion and time is spent in the coordination of issue with client network. So as to look at the precision of the recreation three perspectives will be utilized these are a reality, equity, and magnificence. (Zilberman, D. 2002) The fact of the matter depends on the experimental clarification of the substance model, equity is on how much the model improves life, and magnificence is the stylish clarification of the substance approach subsequently, on the off chance that the social reenactment doesnt depict any of these viewpoints, at that point it isnt sufficiently exact. Paul- The Quality of Social Simulation and Research Policy Modeling Policy modeling deals with the target and the better Model from the abstraction of the goal. The Policy is simulated using the simulated data and find the similarities form the best Model. The best process is to implement the validation and verification of the process to evaluate the running project. The actual data and the implementing steps are compared to evaluate the project status to verify the outcome. The defining of the whole Model to deal with the project includes target, goal, Model, and measuring quality machine. Quality Stimulation involves the problem determination and followed by Observation. Problem determination includes the theory of the actual problem. Observation provides for the interpretation of real data and Observations done due to the theorys definition. Every Observation includes quantitative or qualitative. Quantitative deals with the actual numbers of the project and qualitative give the content information. Observables and stimulation are both are the two ways to deal with the project. Observables are depended on what is calculated, and stimulation is the encouragement to develop more (Bruch, 2005). To stimulate the Policy, the research has to be reconsidered against the target to view with a different angle. The Conventions are evaluated to verify the actual data. At the base, there are agreements and social expectation which are enhanced to assess the quality of the Model. The Policy evaluated depending upon the best content which profits to policy stimulation. The policymaking involves the expectation, predictions, and community experiences to assess the quality of the Policy to build new knowledge (Doran, 1994). Prerana- Big data in healthcare” refers to the abundant health data amassed from numerous sources including electronic health records (EHRs), medical imaging, genomic sequencing, payor records, pharmaceutical research, wearables, and medical devices, to name a few. With big data growth in biomedical and healthcare communities, accurate analysis of medical data benefits early disease detection, patient care, and community services. However, the analysis accuracy is reduced when the quality of medical data is incomplete. Moreover, different regions exhibit unique characteristics of certain regional diseases, which may weaken the prediction of disease outbreaks. The rise of healthcare big data comes in response to the digitization of healthcare information and the rise of value-based care, which has encouraged the industry to use data analytics to make strategic business decisions. Faced with the challenges of healthcare data – such as volume, velocity, variety, and veracity – health systems need to adopt technology capable of collecting, storing, and analyzing this information to produce actionable insights. A major challenge with healthcare big data is sorting and prioritizing information. Data capacities are so vast that oftentimes it can be difficult to determine which data points and insights are useful. As a result, many organizations use AI or machine learning to process this data with exceptional agility. Another challenge is ensuring that the right access to big data insights and analysis is given to the right people so they can work intelligently. Even though healthcare data is pulled from many different systems, organizations need to make sure critical personnel across the industry have comprehensive access to the information. The analysis of data from IoT would require an updated operating software because of its specific nature along with advanced hardware and software applications. We would need to manage data inflow from IoT instruments in realtime and analyze it by the minute. Associates in the healthcare system are trying to trim down the cost and ameliorate the quality of care by applying advanced analytics to both internally and externally generated data. Healthcare big data will also continue to help make marketing touchpoints smarter and more integrated. Additionally, the amount of data available will grow as wearable technology and the Internet of Things (IoT) gains popularity. Constant patient monitoring via wearable technology and the IoT will become standard and will add enormous amounts of information to big data stores. With this information, healthcare marketers can integrate a large volume of healthcare insights to find and retain patients with the highest propensity for services. Ashok- Big data in Healthcare The rise of big data in the healthcare industry is a result of technological advances of healthcare data, which has created various opportunities and hope the sector, such as treatment innovations, reduce health costs and improvement of patient outcomes, among other benefits. With this vast volume of information, the health care industry is forced to adopt digitalized techniques for collecting and analyzing data for the production of actionable insights. Health care cost is expensive. The vast growing amount of data is challenging; thus, with bid data, in the health system, it is possible to turn these challenges to opportunities. Big data is not only focused on reducing health care costs but also improving the care personalization and efficiency in the industry (Bora, 2019). In the US, the challenge in the healthcare industry due to high heath cost has resulted in the nation adopting big data as now many insurance companies are switching from fee-forservice plans to other better initiatives such as prioritization of patient health, which has improved the patient outcomes. The vast amount of data in the industry has paved the way for electronic health records (HER), which is the most spread form of application of big data. The EHR entails all the digital patient records, which includes laboratory tests, medical history, and allergies, among other health records. EHR is being adopted by countries such as the US as over 94\% of hospitals are using it according to research conducted by HITECH. Additionally, the US has implemented a system called the Health Connect, which allows the sharing of medical data across the medical facilities, thus makes use of HER (Kumar, Sood KauL, & Vasuja,2019) On the other hand, several challenges have resulted due to big data in the healthcare industry. One main challenge is the sorting and prioritization of information. Due to vast health information, the problem of determining which data points and insights are useful rises. Also, access to the right patient information is a challenge for scientific research due to patient privacy concerns. The difficulty of obtaining the correct data can also be caused by factors such as unclear diagnosis and procedure codes, big inconsistent data, among other problems. Aside from these challenges, the implementation of big data I huge step towards digitalization. with it comes massive promises such as integration with other technologies such as Artificial Intelligence (AI) and Internet of Things (IoT) to allow room for the creation of a large volume of healthcare insights for improving the health sector. Ashok- he rise of big data in the healthcare industry is a result of technological advances of healthcare data, which has created various opportunities and hope the sector, such as treatment innovations, reduce health costs and improvement of patient outcomes, among other benefits. With this vast volume of information, the health care industry is forced to adopt digitalized techniques for collecting and analyzing data for the production of actionable insights. Health care cost is expensive. The vast growing amount of data is challenging; thus, with bid data, in the health system, it is possible to turn these challenges to opportunities. Big data is not only focused on reducing health care costs but also improving the care personalization and efficiency in the industry (Bora, 2019). In the US, the challenge in the healthcare industry due to high heath cost has resulted in the nation adopting big data as now many insurance companies are switching from fee-forservice plans to other better initiatives such as prioritization of patient health, which has improved the patient outcomes. The vast amount of data in the industry has paved the way for electronic health records (HER), which is the most spread form of application of big data. The EHR entails all the digital patient records, which includes laboratory tests, medical history, and allergies, among other health records. EHR is being adopted by countries such as the US as over 94\% of hospitals are using it according to research conducted by HITECH. Additionally, the US has implemented a system called the Health Connect, which allows the sharing of medical data across the medical facilities, thus makes use of HER (Kumar, Sood KauL, & Vasuja,2019) On the other hand, several challenges have resulted due to big data in the healthcare industry. One main challenge is the sorting and prioritization of information. Due to vast health information, the problem of determining which data points and insights are useful rises. Also, access to the right patient information is a challenge for scientific research due to patient privacy concerns. The difficulty of obtaining the correct data can also be caused by factors such as unclear diagnosis and procedure codes, big inconsistent data, among other problems. Aside from these challenges, the implementation of big data I huge step towards digitalization. with it comes massive promises such as integration with other technologies such as Artificial Intelligence (AI) and Internet of Things (IoT) to allow room for the creation of a large volume of healthcare insights for improving the health sector. ... Purchase answer to see full attachment