TechCoaches Innovations Systems Design

By Nathan B. Smith Recruitment is a substantial impediment to doing social science research. Beginning early and planning for success is vital to handle this issue properly. This article highlights some essential aspects of designing and recruiting for productive research projects. Academic researchers often recruit study participants using ill-defined procedures that eventually generate terrible findings, either by violating ethical standards or failing to create a representative sample of the population. For instance, a researcher may want to perform a study comparing two distinct leadership styles and determining which is the most successful. Recruitment of research volunteers for this type of project often entails placing an advertisement on the Internet. However, these advertisements may be sparse in their content, indicating insufficient research preparation. Discussion Issues associated with inadequate study information The sample design and recruitment of participants for socia...

By Nathan B. Smith In many computer systems which experience an exponential growth in the number of users, scalability becomes the most influential characteristic for sustainability. Logical clocks play an enabling technology in the implementation of concurreny across distributed systems. Distributed systems depend on parallelism and concurrency, which is largely based on the concepts of software threading and tasking. To leverage the the theory of threading on a much larger scale in distributed systems, logical clocks offer an important solution for keeping distributed nodes synchronized while sharing the computing power to solve a given calculation (Gorton, 2022).  The theory of logical clocks in distributed systems is complex. Leslie Lamport (2015) won the 2013 ACM Turing award based on his early work on logical clocks and the ordering of system events. It is interesting to note that most of Lamport’s work was done near 35 years before he won the Turing Award. That is, it took m...

By Nathan B. Smith According to Juniper Research, between 2020 and 2024, online fraud will cost organizations more than $200 billion. 1 The astounding quantity is a result of the intelligence and multiplicity of attack avenues in fraud efforts. And although fraudsters have modified their methods to avoid detection, banks are fighting back harder than ever. Between 2020 and 2024, companies will lose more than $200 billion to online fraud. The astounding quantity is a result of the intelligence and multiplicity of attack avenues in fraud efforts. Graph analytics, however, has given banks a new tool in the fight against fraud. According to Richard Henderson of TigerGraph, these methods may be used to combat financial crime by analyzing the connections between individuals, phones, and bank accounts to discover symptoms of fraudulent behavior and aid banks in identifying suspicious activity in a sea of data (Hendersoon, 2020). Discussion For storing and searching for data created for data w...

By Nathan B. Smith The objective of this discussion is to develop the building blocks of a system for healthcare big data analytics and compare them to a system of DNA networked clusters which is typically used by genomic sequencing companies. Discussion In the field of bioinformatics, several high-throughput methods, such as next-generation sequencing, lead to an onslaught of sequences that originate from a variety of sources but are not defined. Processing this enormous amount of sequencing data using the traditional methods is a laborious and challenging undertaking. In addition, the processing of vast amounts of diverse, complicated, and complex data demands a significant number of resources. The production of findings from such an analysis might take several hours or even days.  To expedite the processing of data, bioinformatics research, in general, relies on platforms that are high in both computational power and storage capacity. Cloud computing has traditionally been the o...

By Nathan B. Smith The purpose of this paper is to discuss published papers regarding data analytics in various health care fields that discuss the theories and techniques covered in terms of data analytics for big data.  The academic and professional communities in this realm have covered the data analytics theories and techniques and how they are used in health care and biomedical research. "Big data" refers to very large volumes of information that, when properly analyzed, may do amazing things. Because it conceals a significant amount of untapped potential, in the last two decades it has developed into a subject that has garnered a lot of attention. Big data is being generated, stored, and analyzed across a variety of businesses, both in the public and commercial sectors, with the goal of improving the services being offered. Big data may come from a variety of sources in the healthcare business. Some of these sources include hospital records, the medical records of patie...

By Nathan B. Smith Big data analytics (BDA) uses a wide range of mathematical methods that may be utilized to get insight from very vast and diverse datasets that may be unstructured, semi-structured, or structured. These algorithms include machine learning (ML) and deep learning (DL) techniques, which lie under the umbrella of artificial intelligence (AI). The purpose of BDA is to provide more rapid and accurate decision-making, modeling, and forecasting of future events. Classification and pattern matching are also essential BDA applications.  Discussion Genetics is a branch of molecular biology that examines heredity through the production of proteins. Proteins are the building blocks of living creatures and are synthesized according to DNA or deoxyribonucleic acid instructions. The DNA molecule is a double-helical structure composed of guanine, adenine, cytosine, and thymine nucleotides. The nucleus of every live cell contains the whole genome. The genome contains the instructi...

By Nathan B. Smith This article reviews the usage of big data analytics to enable cybersecurity in the healthcare sector to satisfy the Health Insurance Portability and Accountability Act's data privacy regulations using the library and the Internet (HIPAA). This article then proposes a policy for a healthcare organization that outlines the repercussions of data breaches, including both personal and organizational repercussions), the significance of using analytics with security in mind, and the significance of data privacy (to the patient, staff, and organization), and the steps the staff will take to adhere to data privacy laws and HIPAA. According to Juniper Research, between 2020 and 2024, online fraud will cost organizations more than $200 billion. The astounding quantity results from the intelligence and diversity of attack avenues in fraud efforts. Moreover, although fraudsters have modified their methods to avoid detection, banks are fighting back harder than ever. Between ...