Computer Sciences Commons^™

Spatial Frequency Implications For Global And Local Processing In Autistic Children, Riya Mody, Ayra Tusneem, Louanne Boyd, Vincent Berardi

Student Scholar Symposium Abstracts and Posters

Visual processing in humans is done by integrating and updating multiple streams of global and local sensory input. Interaction between these two systems can be disrupted in individuals with ASD and other learning disabilities. When this integration is not done smoothly, it becomes difficult to see the “big picture”, which has been found to have implications on emotion recognition, social skills, and conversation skills. An example of this phenomenon is local interference, which is when local details are prioritized over the global features. Previous research in this field has aimed to decrease local interference by developing and evaluating a filter …

Deep Learning For Screening Covid-19 Using Chest X-Ray Images, Sanhita Basu, Sushmita Mitra, Nilanjan Saha

ISI Best Publications

With the ever increasing demand for screening millions of prospective 'novel coronavirus' or COVID-19 cases, and due to the emergence of high false negatives in the commonly used PCR tests, the necessity for probing an alternative simple screening mechanism of COVID-19 using radiological images (like chest X-Rays) assumes importance. In this scenario, machine learning (ML) and deep learning (DL) offer fast, automated, effective strategies to detect abnormalities and extract key features of the altered lung parenchyma, which may be related to specific signatures of the COVID-19 virus. However, the available COVID-19 datasets are inadequate to train deep neural networks. Therefore, …

Processor Modules For The Classroom Development Of Physical Computers, Lakshmi Ongolu

Master’s Theses and Projects

Processors are present in almost all the electronic components available in the market now. As they perform trillions of operations per second and are complex internally. This project is to build building modules for students, who will be able to develop their own processor. The main idea is that this will help students to experience the detailed workflow of a processor and focus on design and development instead of spending time on wiring and soldering. Different components such as Program Counter, Instruction Register, Memory, Multiplexer, Adder and transceivers are designed and printed as individual modules on printed circuit boards (PCB’s). …

Human Parsing Based Texture Transfer From Single Image To 3d Human Via Cross-View Consistency, Fang Zhao, Shengcai Liao, Kaihao Zhang, Ling Shao

Machine Learning Faculty Publications

This paper proposes a human parsing based texture transfer model via cross-view consistency learning to generate the texture of 3D human body from a single image. We use the semantic parsing of human body as input for providing both the shape and pose information to reduce the appearance variation of human image and preserve the spatial distribution of semantic parts. Meanwhile, in order to improve the prediction for textures of invisible parts, we explicitly enforce the consistency across different views of the same subject by exchanging the textures predicted by two views to render images during training. The perceptual loss …

Building Postsecondary Pathways For Latinx Students In Computing: Lessons From Hispanic-Serving Institutions, Anne-Marie Núñez, David S. Knight, Sanga Kim

Departmental Technical Reports (CS)

While the COVID-19 pandemic has transformed the use of technology in education and the workforce, a shortage of computer scientists continues, and computing remains one of the least diverse STEM disciplines. Efforts to diversify the computing industry often focus on the most selective postsecondary institutions, which are predominantly White. We highlight the role of Hispanic-Serving Institutions (HSI) in gradating large numbers of STEM graduates of color, particularly Latinx students. HSIs are uniquely positioned to leverage asset-based approaches that value students’ cultural background. We describe the practices educators use in the Computing Alliance for Hispanic-Serving Institutions, a network of 40 HSIs …

Hategan: Adversarial Generative-Based Data Augmentation For Hate Speech Detection, Rui Cao, Roy Ka-Wei Lee

SCIS Student Publications

Academia and industry have developed machine learning and natural language processing models to detect online hate speech automatically. However, most of these existing methods adopt a supervised approach that heavily depends on labeled datasets for training. This results in the methods’ poor detection performance of the hate speech class as the training datasets are highly imbalanced. In this paper, we propose HateGAN, a deep generative reinforcement learning model, which addresses the challenge of imbalance class by augmenting the dataset with hateful tweets. We conduct extensive experiments to augment two commonly-used hate speech detection datasets with the HateGAN generated tweets. Our …

Narrowing The Wealth And Income Gap In Poland, China, And The United States, Cyndy Carboo, Zhiling Song, Jiawei Feng, Xudong Zhu

School of Professional Studies

With the widespread of globalization, the wealth gap continues to widen globally. Due to the enormous differences in national conditions and political systems of various countries, this article selects China, the United States, and Poland as the research objects, and uses a specific time unit as the benchmark, and mainly focuses on the four directions of medical care, education, job opportunities, and pensions. A reader could understand the correlation between the wealth gap and multiple factors deeply in this article. This article analyzes the impact of income disparity on these three countries and proposes solutions to help narrow the gap …

Worst Time Being Poor? The Hunger Problem In U.S. During Covid-19 Pandemic, Yuanhang Hu

School of Professional Studies

Food insecurity is deeply rooted in American society during and before the COVID-19 pandemic. Food Insecurity usually associates with economic indicators, such as unemployment rate, income level, etc. Currently, there are two main tools to fight the war of hunger. The first one is the government food assistance programs. And the second one is food pantries from the private sectors of the community. Both tools are facing numerous challenges due to COVID-19. The purpose of this article is to provide rational reasons to persuade the government to enhance the benefits of the Supplemental Nutrition Assistance Program (SNAP) and use administrative …

The Practical Applications Of Video Games Beyond Entertainment, Jack Martin

School of Professional Studies

Much of the attention directed toward video games is focused on their role as entertainment. However, researchers have found that video games can have other, more practical uses for society. This thesis is designed to examine three specific examples of the practical applications of video games: video games in education, video games as accessible technology, and the social uses of video games. This project is based on pre-existing research conducted by professionals studying the aforementioned subtopics. Anecdotal stories from educators, people with disabilities, and developers are also discussed. The thesis explores specific examples of video games being used practically, and …

Approximating Special Social Influence Maximization Problems, Jie Wu, Ning Wang

College of Science & Mathematics Departmental Research

Social Influence Maximization Problems (SIMPs) deal with selecting k seeds in a given Online Social Network (OSN) to maximize the number of eventually-influenced users. This is done by using these seeds based on a given set of influence probabilities among neighbors in the OSN. Although the SIMP has been proved to be NP-hard, it has both submodular (with a natural diminishing-return) and monotone (with an increasing influenced users through propagation) that make the problem suitable for approximation solutions. However, several special SIMPs cannot be modeled as submodular or monotone functions. In this paper, we look at several conditions under which …

The R Journal (December 2020) 12(2): Complete Issue, The R Foundation

The R Journal

Editorial, Michael J. Kane

Contributed Research Articles

The biglasso Package: A Memory- and Computation-Efficient Solver for Lasso Model Fitting with Big Data in R, Yaohui Zeng and Patrick Breheny

Comparing Multiple Survival Functions with Crossing Hazards in R, Hsin-wen Chang, Pei-Yuan Tsai, Jen-Tse Kao, and Guo-You Lan

A Unified Algorithm for the Non-Convex Penalized Estimation: The ncpen Package, Dongshin Kim, Sangin Lee, and Sunghoon Kwon

TULIP: A Toolbox for Linear Discriminant Analysis with Penalties, Yuqing Pan, Qing Mai, and Xin Zhang

fitzRoy: An R Package to Encourage Reproducible Sports Analysis, Robert Nguyen, James Day, David Warton, and Oscar Lane

Assembling …

A Fully Open-Source Framework For Deep Learning Protein Real-Valued Distances, Badri Adhikari

Computer Science Faculty Works

As deep learning algorithms drive the progress in protein structure prediction, a lot remains to be studied at this merging superhighway of deep learning and protein structure prediction. Recent findings show that inter-residue distance prediction, a more granular version of the well-known contact prediction problem, is a key to predicting accurate models. However, deep learning methods that predict these distances are still in the early stages of their development. To advance these methods and develop other novel methods, a need exists for a small and representative dataset packaged for faster development and testing. In this work, we introduce protein distance …

Transparency And Yielding Of Law Officers Reform (Taylor) Act Of 2020: Proposal For Police Reform, Marwa Alnaal, Matthew L. Anderson, Hannah Brier, Mollie Campbell, Rose Wine

School of Professional Studies

The Transparency and Yielding of Law Officers Reform Act of 2020 (TAYLOR) proposes an example bill for law enforcement reform. During the summer of 2020, the United States witnessed civilian demonstrations nationwide calling for a change to policing. Our proposal is hoping to heed that call, offering a foundation for change that police forces and localities across the United States can utilize to rebuild trust and accountability.

The goal of the TAYLOR Act is not to defund the police; but rather, TAYLOR rethinks the priorities of the police. There can be no denying that the relationship of trust and security …

How Museum Utilize Social Media On Communication, Jiake Han

School of Professional Studies

With the development of Internet, social media became more and more popular among people. Many industries realize the importance of social media in business. Traditionally, museum concentrates more on personal visual experience, which is hard to be replaced by online media. However, museums now also put more concentrate on social media platform because it expands the way of engagement. Especially, for Coronavirus, many organizations including museums have to close. Therefore, museums have to depend more on social media platforms to communicate with audiences. This research aims at finding how different kind of social media help museum communicate and engage with …

Healthy Food Portal Business Plan And Its Function Model, Alena Raupova

School of Professional Studies

Business planning is a tool of paramount importance in the process of company management, on the efficiency of which the future functioning of the enterprise depends. Formation of a business plan enables the team to productively and competently use existing funds and resources in their work and apply planning as a very effective management mechanism (Hamm, 2016).

The goal of this final project is to develop a business plan for a healthy nutrition portal for Bellyful LLC. Bellyful is based in Boston, USA, and the portal will be its first product. Our client is interested in researching the prospects of …

A Web-Based Ai Assistant Application Using Python And Javascript, Viet Le, Tej Bahadur, Jainee Shah, Roushan Ara

School of Professional Studies

Our research is mainly based on a chatbot which is powered by Artificial Intelligence. Nowadays, Artificial Intelligence assistants such as Apple’s Siri, Google’s Now and Amazon’s Alexa are currently fast-growing and widely integrated with many smart devices. These assistants are built with the primary purpose of being personal assistants for every individual user in certain contexts. In this research, we would highlight the development process of the chatbots, features, problems, case studies and limitations.

This research delivers the information, helps developers to build answer bots and integrate chatbots with business accounts. The aim is to assist users and allow transactions …

Rcap Solutions Breach Management - Case Study, Eugene Adu-Gyamfi, Gio Al Muarrawi, Kwame Ofori

School of Professional Studies

Companies get hacked every day, and our in-scope company for this case study, RCAP Solution, was not an exception. Security incidents have increased both in volume and range in recent years, and cyber-attacks have become more sophisticated than ever before. There are so many reasons that drive this fact; one is that our infrastructure was not protected efficiently, but also attackers have become more knowledgeable in initiating advanced attacks at a scale. Additionally, the entrance of emerging technologies such as blockchain, machine learning, and the internet of things, added additional complexity to the already complex scene. Cybercriminals are using various …

Cvs Covid-19 Screening Website: Test Automation, Savya Rawat

School of Professional Studies

CVS Pharmacy is an American retail corporation, also known as, and originally named, the Consumer Value Store owned by CVS Health, it is headquartered in Woonsocket, Rhode Island. CVS Pharmacy is currently the largest pharmacy chain in the United States by number of locations over 9,600 and total prescription revenue. CVS sells prescription drugs and a wide assortment of general merchandise, including over-the-counter drugs.

Now, coming to the reason why I have selected CVS pharmacy’s website cvs.com as my case study topic is because of CVS’s response to the covid-19 pandemic’s no-cost testing strategy. Whole of the world is suffering …

Message From The General Chairs, Falko Dressler, Sajal K. Das

Computer Science Faculty Research & Creative Works

No abstract provided.

The Impact Of Special Interest Groups On The Federal Dietary Guidelines: Consequences For American Health, Dory Mcmillan

School of Professional Studies

This research paper explores the impact of relationships between lobbyists and both the USDA and HSS, and the impact these relationships have on the Dietary Guidelines for Americans that the agencies work together to create. The paper focuses specifically on the information the guidelines present in regard to red meat consumption, and the impacts this may have on American health, and healthcare costs associated. It was hypothesized that a relationship would be found between special interest groups and the U.S. Department of Health and Human Services and/or the U.S. Department of Agriculture. Research found there was a relationship between special …

The Killingly Mascot Case Study, Jordan Lumpkins

School of Professional Studies

In the summer of 2019, in Killingly, Connecticut the local Board of Education voted to retire the "Redmen" mascot name it had used for nearly a century. This legislation was widely opposed and received extensive media coverage. Within a few months, the town experienced a massive political referendum where several local Board of Education members and Councilmen were replaced by single issue politicians promising to reinstate the "Redmen" name. Now holding a majority on the Board of Education, these Board members made Killingly the first school in U.S. history to reinstate a mascot after being deemed "derogatory."

It is the …

Higher Education Responses To Crisis: A Case Study Of Clark University And The Pandemic Of 2020, Lisa Gillingham

School of Professional Studies

The COVID-19 pandemic has delivered an existential challenge to universities and other academic institutions at a time when they are already grappling with other weighty issues that may alter the fabric of higher education. COVID-19 has forced these institutions to consider and employ new ways of conducting its work with a sense urgency that is unprecedented in the recent history of the academy. The rate of learning around these models is rapid, and Higher Education is ripe for change.

Clark University has addressed the pandemic with a plan to protect and pivot using strategies that support the continuation of its …

Special Issue On 6g Wireless Systems, Periklis Chatzimisios, David Soldani, Abbas Jamalipour, Antonio Manzalini, Sajal K. Das

Computer Science Faculty Research & Creative Works

No abstract provided.

A Distance Based Multisample Test For High-Dimensional Compositional Data With Applications To The Human Microbiome, Qingyang Zhang, Thy Dao

Mathematical Sciences Faculty Publications and Presentations

Background

Compositional data refer to the data that lie on a simplex, which are common in many scientific domains such as genomics, geology and economics. As the components in a composition must sum to one, traditional tests based on unconstrained data become inappropriate, and new statistical methods are needed to analyze this special type of data.

Results

In this paper, we consider a general problem of testing for the compositional difference between K populations. Motivated by microbiome and metagenomics studies, where the data are often over-dispersed and high-dimensional, we formulate a well-posed hypothesis from a Bayesian point of view and …

Adaptive Discounting In Reinforcement Learning, Milan Zinzuvadiya

Master's Theses

In Markov Decision Process (MDP) models of sequential decision-making, it is common practice to account for temporal discounting by incorporating a constant discount factor. While the effectiveness of fixed-rate discounting in various Reinforcement Learning (RL) settings is well-established, the efficiency of this scheme has been questioned in recent studies. Another notable shortcoming of fixed-rate discounting stems from abstracting away the experiential information of the agent, which is shown to be a significant component of delay discounting in human cognition. To address this issue, this thesis proposes a novel method for adaptive discounting entitled State-wise Adaptive Discounting from Experience (SADE). This …

Fundamentals Of Human-Centric Artificial Intelligence (A.I.): Comparative Analysis Of Europe And The U. S. Landscape, Torré A. Williams

Cybersecurity Undergraduate Research Showcase

This research is a comparative analysis of human-centric Artificial Intelligence (A.I.) in Europe and the U.S. This research establishes fundamentals that are critical to what makes A.I. human-centric. This research contains eight phases: 1) Lawful A.I.; 2) Robust A.I.; 3) Ethical A.I.; 4) Human-centric A.I.; 5) Current State of A.I.; 6) A.I. in Europe; 7) A.I. in the U.S.; 9) Importance of Human-centric A.I. This research shows that there are still ongoing changes with having a human-centric A.I. and why it is very important to society. This research is the beginning of the making of a successful and reliable human-centric …

Generating Adversarial Examples For Recruitment Ranking Algorithms, Anahita Samadi

Computer Science and Engineering Theses - Archive

There is no doubt that recruitment process plays an important role for both employers and applicants. Based on huge number of job candidates and open vacancies, recruitment process is expensive, time consuming and stressful for both applicants and companies. In today’s world so many recruitment processes are based on machine learning techniques. Therefore, it is very important to ensure security of these algorithms. Adversarial examples are proposed to examine vulnerability of machine leaning algorithms. Many research studies have been done on evaluating the resistance of artificial intelligence-based systems, in computer vision and text classification, against adversarial examples. However, to the …

Semi-Automatic Hand Pose Estimation Using A Single Depth Camera, Giffy Jerald Chris

Computer Science and Engineering Theses - Archive

This paper addresses the problem of 3D hand pose annotations using a single depth camera. Although hand pose estimation methods rely critically on accurate 3D training data, creating such reliable training data is challenging and labor intensive. We propose a semi-automatic method for efficiently and accurately labeling the 3D hand key-points in a hand depth video. The process starts by selecting a subset of frames that are representative of all the frames in the dataset and the annotator only provides an estimate of the 2D hand key-points in these selected frames. We use this information to infer the 3D location …

A Survey On Ddos Attacks In Edge Servers, Iftakhar Ahmad

Computer Science and Engineering Theses - Archive

In modern times, the need for latency sensitive applications is growing rapidly. Cloud computing infrastructure is unable to provide support to such delay sensitive applications. Therefore, a new paradigm called edge computing has emerged. In edge computing various paradigms like Fog, Cloudlet, Mobile Edge Computing, etc. provide real-time, location aware services to users. As a result number of requests are generated for processing in the edge servers. If these edge servers for some reason become unavailable for providing service, users will not be able to perform their delay sensitive or location aware operations. Like other servers in the network, edge …

Incomplete Time Series Forecasting Using Generative Neural Networks, Harshit Tarun Shah

Computer Science and Engineering Theses - Archive

Dealing with missing data is a long pervading problem and it becomes more challenging when forecasting time series data because of the complex relationships between data and time, which is why incomplete data can lead to unreliable results. While some general-purpose methods like mean, zero, or median imputation can be employed to alleviate the problem, they might disrupt the inherent structure and the underlying data distributions. Another problem associated with conventional time series forecasting methods whose goal is to predict mean values is that they might sometimes overlook the variance or fluctuations in the input data and eventually lead to …