5153 research outputs found
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Modi’s Social Media Effects on Media: Analysis of Big Data from Indian Elections in 2014
No full textSrishti Puri's and Mohammed Al-Azdee's poster analyzing the effects of social media on the media in India's 2014 elections through the use of big data analytics
Towards Efficient Features Dimensionality Reduction for Network Intrusion Detection on Highly Imbalanced Traffic
No full textThe performance of an IDS is significantly improved when the features are more discriminative and representative. This research effort is able to reduce the CICIDS2017 dataset’s feature dimensions from 81 to 10, while maintaining a high accuracy of 99.6% in multi-class and binary classification. Furthermore, we propose a Multi-Class Combined performance metric CombinedMc with respect to class distribution to compare various multi-class and binary classification systems through incorporating FAR, DR, Accuracy, and class distribution parameters. In addition, we developed a uniform distribution based balancing approach to handle the imbalanced distribution of the minority class instances in the CICIDS 2017 network intrusion dataset
China's Monetary Policy Since 1948
No full textThere is a dearth of literature on the modern monetary history of China. This paper is the first to trace the origin of China’s foray into modern monetary policy. I chronicled the development of monetary policy in China since the PBC was established in 1948. I proposed a set of recommendations for China’s monetary authority to consider
Effect Of Hyperbolic Discounting - A Cognitive Bias
No full textHyperbolic Discounting is a cognitive bias, where people’s tendency will be to over-value immediate rewards at the expense of their long-term intentions . When offered a larger reward in exchange for waiting a set amount of time, people act less impulsively (i.e., choose to wait) as the rewards happen further in the future. This bias is considered as “time inconsistent” , because reward valuation falls rapidly with small periods of delay and then slowly for longer delay periods
2019 College of Health Sciences Winter Commencement Ceremony (December 14 2019)
No full textThe College of Health Sciences Winter Commencement ceremony with a listing of every graduate and honorary degree recipients. President's message and Dean's message noted. Commencement speaker Stephen M. Perle Professor of Clinical Studies, School of Chiropractic
What is the Role of Non-Pharmacotherapy in the Treatment of Depression with Cardiovascular Disease?
No full textDepression and cardiovascular disease are two of the leading causes of disability and death in the U.S. and worldwide, respectively. Both health disparities are frequently managed and treated with conventional medicine using drugs that may increase the pain and suffering of patients due to unwanted side-effects, thereby likely prompting patient nonadherence to physician guidance and pharmaceutical interventions. This study aims to determine the effects of various non-pharmaceutical therapies including psychotherapy, exercise therapy, meditation, and acupuncture with musical therapy, and their influence on depression and cardiovascular disease. The main question in this review asks: do non-pharmaceutical therapies have positive effects on depression and cardiovascular disease? The results indicate that several non-pharmaceutical interventions do have positive effects on depression and cardiovascular disease, and can even be as effective as antidepressants for the treatment of depression, when used alone or in combination with conventional medical practices. While the current research on non-pharmaceutical therapy for depression and cardiovascular disease is promising, additional studies are needed to gain a complete understanding of this influence. The intent of this review was also to encourage the health care community to implement a multidisciplinary and integrative approach to treating depression and heart disease, which are frequently comorbid and bidirectional, where the alleviation of one condition should prompt the recovery from the other
Enhancing Software Project Outcomes: Using Machine Learning and Open Source Data to Employ Software Project Performance Determinants
No full textMany factors can influence the ongoing management and execution of technology projects. Some of these elements are known a priori during the project planning phase. Others require real-time data gathering and analysis throughout the lifetime of a project. These real-time project data elements are often neglected, misclassified, or otherwise misinterpreted during the project execution phase resulting in increased risk of delays, quality issues, and missed business opportunities. The overarching motivation for this research endeavor is to offer reliable improvements in software technology management and delivery. The primary purpose is to discover and analyze the impact, role, and level of influence of various project related data on the ongoing management of technology projects. The study leverages open source data regarding software performance attributes. The goal is to temper the subjectivity currently used by project managers (PMs) with quantifiable measures when assessing project execution progress. Modern-day PMs who manage software development projects are charged with an arduous task. Often, they obtain their inputs from technical leads who tend to be significantly more technical. When assessing software projects, PMs perform their role subject to the limitations of their capabilities and competencies. PMs are required to contend with the stresses of the business environment, the policies, and procedures dictated by their organizations, and resource constraints. The second purpose of this research study is to propose methods by which conventional project assessment processes can be enhanced using quantitative methods that utilize real-time project execution data. Transferability of academic research to industry application is specifically addressed vis-à-vis a delivery framework to provide meaningful data to industry practitioners
Network Virtualization Technologies and Challenges
No full textNetwork virtualization is dividing or combining hardware resources that the users can make use of, and every user has his own specific perspective, these resources can be nodes or links. Network virtualization became one of the most important technologies recently. The architecture and base platform of a NV hardware is crucially looked at for its importance in implementing an advanced consumer service. It also an important part is to follow the technical requirements when implementing the system
Groundswell Spring 2019 UB’s Magazine of Literature and the Arts
No full textThis is the Spring 2019 edition of the University of Bridgeport's Student magazine of literature and the arts. This edition may include poetry, art, and phtography as well as literary contributions. The editor for this edition is Emilia Rivera. The advisory board includes Eric D. Lehman, Amy Nawrocki, and Emily Larned.
"Groundswell is the annual publication of the University of Bridgeport, English Department, intended solely as a repository for exhibiting UB undergraduate students' best creative work.
Increasing Awareness of Type 3 Diabetes: Present and Future Implications
No full textBackground: In the United States alone, Type 2 Diabetes is the 7th leading cause of death, with Alzheimer’s Disease ahead as the 6th leading cause of mortality. While specific mechanisms have yet to be recognized by mainstream medicine, the term Type 3 Diabetes has been adopted to describe diabetes of the brain. Overarching commonalities amongst each disease include (a) oxidative stress, (b) inflammation, (c) mitochondrial dysfunction, and (d) neuroendocrine abnormalities. Collectively, these factors have been found to directly contribute to pro-death genes, impaired energy metabolism, and cerebral hypoperfusion. Yet, Type 2 Diabetes remains one of the most adjustable risk factors for the development of Alzheimer’s Disease. This dissertation explores the available literature on increasing the awareness of Type 3 Diabetes in terms of present and future implications. Methods: The review highlighted the following topics: (a) Alzheimer’s disease, (b) Types 1 and 2 diabetes, (c) insulin resistance and cognitive decline, (d) Type 3 diabetes (e) ApoE(4) genetic perturbations, (f) prevention and lifestyle support for Alzheimer’s disease, (g) prevention and lifestyle support for diabetes, (h) social and economic consequences of Alzheimer’s disease, (I) social and economic consequences of diabetes. Results: While AD is a complex disorder, there is a plethora of irrefutable research that supports viewing it as Type 3 Diabetes. Increasing patient education of Type 3 Diabetes and focusing on prevention strategies would decrease disease burden, increase quality of life and at the same time, save trillions of dollars in healthcare spending. Conclusions: Since there is no pharmaceutical cure for AD, increasing awareness of Type 3 Diabetes has the potential to provide patients with sustainable, integrative therapies, allowing them to become invested in their health choices. This will also promote individual accountability and a sense of conscientiousness in taking back one’s own health through lifestyle choices while reducing unnecessary suffering for patients, family members and society