Computer Sciences Commons^™

Gc-243 - Analysis Of Alternatives Of Workstation Deployment Solutions, Mohammed S. Alam, Rahima Daino, Brittany Davis

C-Day Computing Showcase

Best suited for IT students who are able to use on-site (@ KSU) testing environment Perform a market survey of the best reviewed and used workstation deployment solutions Determine a set of requirements the business needs the solution to meet Determine metrics based off the requirements to measure the tools against each other Test the top 3 tools and provide a recommendation to the organization for which tool and its instructions for its basic initial setup

Gc-244 Msit Capstone Project Fall 2022, Megen Cochran, Skylar Story, Tatiana Brown, Simisola Babatunde

C-Day Computing Showcase

Computer network system administrators need to inspect and analyze network traffic and detect malicious communications, monitor system performance, and provide operational services. However, identifying threats contained within encrypted network traffic, which has become increasingly prevalent, poses a unique set of challenges. It is imperative to monitor this traffic or threats and malware but do so in a way that maintains privacy. This project aims to develop a machine learning-based system that can accurately detect malware communication in this setting.

Gc-250 Object Detection And Tracking: Deep Learning-Based Framework With Euclidean Distance, Iou, And Hungarian Algorithm, Md Jobair Hossain Faruk

C-Day Computing Showcase

Object tracking is an important basis for the logistics industry where multiple packages are moved on conveyor belts at a time. Accurate datasets and efficient benchmarks are a few of the several problems for both object detection and tracking for training the deep learning-based framework. Preparing 100% accurate correspondence between objects throughout different frames by assigning human annotated unique_attributes to train framework efficiently over ground truth data. In this research, we develop an (i) OpenCV-based framework that allows the user to assign human-annotated identification between objects and (ii) a novel application for object detection and tracking. We utilize the assigned …

Gc-311 Singsingmarketplace.Com: E-Commerce Marketplace For Remote Vendors, Daniel K. Tor, Ebikela Ogegbene-Ise

C-Day Computing Showcase

American residents in the (Nigerian, Liberian, Indian, Ghanaian, etc.) Diaspora have strong ties back home and as such support loved ones, back home, on a regular basis, by sending cash remittances through Western Union, MoneyGram, etc. Remittances are expensive. Remitters have no control over how funds are spent once received. Remitters cannot send small amounts because the fees cannot be justified. We built a marketplace platform that allows the Diaspora to remit goods and services, instead of sending money to relatives back home in. The objectives are to remove or greatly reduce the cost of remittances, give more control to …

Gr-241 On Training Explainable Neurons, Lance Kennedy

C-Day Computing Showcase

Neural networks have become increasingly powerful and commonplace tools for guiding decision-making. However, due to the black-box nature of many of these networks, it is often difficult to understand exactly what guides them to a certain prediction, making them dangerous to use for sensitive decision making, and making it difficult to ensure confidence in their output. For instance, a network which classifies images of dogs and cats may turn out to be flawed with little consequence, but a neural network that diagnoses the presence of diseases should be assured to make sound predictions. By understanding why a network makes the …

Gr-245 Parsimonics: Achieving High Classification Accuracy Even With High Dimensional Image Reduction, Joshua Owens

C-Day Computing Showcase

The asl-alphabet dataset, hosted by Kaggle, is a collection of 87000 color images sized 200x200x3, grouped into 29 classes of 3000 images apiece (dataset A). The classes consist of the 26 English letters plus three classes for space, delete and nothing. As a proof of concept, the dataset was first truncated by deleting 2700 images from each class, leaving only the first 300 images per class and totaling 8700 images, or 10% of the original number of images (dataset B). Then, transfer learning was applied to dataset B using Alexnet with Imagenet weights. >99% accuracy with dataset B was readily …

Gr-252 Solving Multiple Traveling Salesman Problem Using K Means Clustering And Mixed Integer Programming - An Integrated Approach, Navneet Verma

C-Day Computing Showcase

In this research paper, we explore an efficient algorithm for multiple Traveling Salesman Problem (m-TSP) using an approach which combines K Means clustering algorithm and Mixed Integer Programming (MIP). The Traveling Salesman problem is an NP hard problem which relates to generation of minimum cost round trip tours for multiple salesmen visiting several cities in their territory. Our novel approach has the promise of reaching closer to the optimal solution as compared to heuristics-based approaches such as genetic algorithms.

Gr-267 Churn Prediction, Manoj Kumar Dasari, Nikhil Thota, Dinesh Kumar Thota, Rishi Sai Basava, Prudhvi Kalyan Sai Sugguna

C-Day Computing Showcase

Employee churn is a situation where people leave the organization voluntarily or involuntarily. This has become a serious problem in recent times. We have also seen that attrition rates in several industries are going high. So, it is very much required to understand and analyze the reason behind attrition and why this is happening. We must conduct an analysis to know what the factors affecting employee churn are. It will create a huge impact on the organization if the attrition rate goes high. In order to resolve this issue, we are trying to take up this issue and find the …

Gr-273 Building A Chatbot, Varun Gottam, Sathwik Chepyala, Sai Mohit Saimpu, Venkata Sai Krishna Yalavarthi, Nikhil Sai Buddiga

C-Day Computing Showcase

A chatbot is now a part of many online applications like Health Care, Education, E-commerce, etc. It made the conversation between the customers and the service providers much more convenient as the chatbot can answer most of the queries without human intervention from the website side. This saves a lot of time and work.

Analyzing Academic Self-Regulation Improvement Via Proccoli Task And Time Management Application, Le Jie Bennett

Computer Science

In the academic context, success is dependent on the individual’s ability to keep track of what needs to be done in a timely manner. But, for most students, procrastination often stands in their way. The time management application, Proccoli, is a tool that the Sahebi/Feyzi lab has developed to study individual and group procrastination behavior and help improve students’ ability to track and manage their tasks and time. Drawing foundations from Human Computer Interaction literature, the application provided features and functionalities to help promote selfregulatory behaviors such as self-observation, self-judgement, and self-reflection. An evaluation survey was sent to previous Proccoli …

Addressing Human Error Through Effective Cyber Policy Design, Katherine Amoresano

Emergency Preparedness, Homeland Security, and Cybersecurity

Human error is a significant contributing factor to the rise in Cybersecurity attacks regardless of increased technical control implemented to safeguard Information systems. Adversaries can circumvent technical safeguards due to human errors which result from inadequate enforceable policies and training on Cybersecurity for the everyday user. Several studies and articles show that the majority of successful attacks are human enabled, proving the need for human-centric cybersecurity research and practices. This exploratory work reviews the human aspect of Cybersecurity by investigating the cybersecurity policies at SUNY Albany and other SUNY institutions. We used a survey of students and faculty members at …

Wordmuse, John M. Nelson

Computer Science and Software Engineering

Wordmuse is an application that allows users to enter a song and a list of keywords to create a new song. Built on Spotify's API, this project showcases the fusion of music composition and artificial intelligence. This paper also discusses the motivation, design, and creation of Wordmuse.

A Unified Dialogue User Simulator For Few-Shot Data Augmentation, Dazhen Wan, Zheng Zhang, Qi Zhu, Lizi Liao, Minlie Huang

Research Collection School Of Computing and Information Systems

Pre-trained language models have shown superior performance in task-oriented dialogues. However, existing datasets are on limited scales, which cannot support large-scale pre-training. Fortunately, various data augmentation methods have been developed to augment largescale task-oriented dialogue corpora. However, they heavily rely on annotated data in the target domain, which require a tremendous amount of data collection and human labeling work. In this paper, we build a unified dialogue user simulation model by pre-training on several publicly available datasets. The model can then be tuned on a target domain with fewshot data. The experiments on a target dataset across multiple domains show …

Non-Localized Physical Processes Can Help Speed Up Computations, Be It Hidden Variables In Quantum Physics Or Non-Localized Energy In General Relativity, Michael Zakharevich, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

While most physical processes are localized -- in the sense that each event can only affect events in its close vicinity -- many physicists believe that some processes are non-local. These beliefs range from more heretic -- such as hidden variables in quantum physics -- to more widely accepted, such as the non-local character of energy in General Relativity. In this paper, we attract attention to the fact that non-local processes bring in the possibility of drastically speeding up computations.

How Viscosity Of An Asphalt Binder Depends On Temperature: Theoretical Explanation Of An Empirical Dependence, Edgar Daniel Rodriguez Velasquez, Vladik Kreinovich

Departmental Technical Reports (CS)

Pavement must be adequate for all the temperatures, ranging from the winter cold to the summer heat. In particular, this means that for all possible temperatures, the viscosity of the asphalt binder must stay within the desired bounds. To predict how the designed pavement will behave under different temperatures, it is desirable to have a general idea of how viscosity changes with temperature. Pavement engineers have come up with an empirical approximate formula describing this change. However, since this formula is purely empirical, with no theoretical justification, practitioners are often somewhat reluctant to depend on this formula. In this paper, …

Graph Approach To Uncertainty Quantification, Hector A. Reyes, Cliff Joslyn, Vladik Kreinovich

Departmental Technical Reports (CS)

Traditional analysis of uncertainty of the result of data processing assumes that all measurement errors are independent. In reality, there may be common factor affecting these errors, so these errors may be dependent. In such cases, the independence assumption may lead to underestimation of uncertainty. In such cases, a guaranteed way to be on the safe side is to make no assumption about independence at all. In practice, however, we may have information that a few pairs of measurement errors are indeed independent -- while we still have no information about all other pairs. Alternatively, we may suspect that for …

Why In Mond -- Alternative Gravitation Theory -- A Specific Formula Works The Best: Complexity-Based Explanation, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Based on the rotation of the stars around a galaxy center, one can estimate the corresponding gravitational acceleration -- which turns out to be much larger than what Newton's theory predicts based on the masses of all visible objects. The majority of physicists believe that this discrepancy indicates the presence of "dark" matter, but this idea has some unsolved problems. An alternative idea -- known as Modified Newtonian Dynamics (MOND, for short) is that for galaxy-size distances, Newton's gravitation theory needs to be modified. One of the most effective versions of this idea uses so-called simple interpolating function. In this …

Analyzing Business-Focused Social Networks In Hiring: The Influence Of A Job Candidate's Network On A Recruiter's Hiring Recommendation, Hannah V. Kibby

Theses and Dissertations

Social media has altered the ways in which people interact. Business-focused social media profiles, such as those on LinkedIn, can act as a proxy for a traditional resume. However, these websites differ from a traditional resume in that information presented is sometimes informal, personal, and irrelevant to the member’s career. Furthermore, HR employees are able to view a job candidate’s social network. This research investigates the influence of a recruiter’s knowledge of an applicant’s professional network on the recruiter’s perception of the applicant’s trustworthiness and hence their willingness to take risk in the hiring relationship. A review of the literature …

Learnfca: A Fuzzy Fca And Probability Based Approach For Learning And Classification, Suraj Ketan Samal

Computer Science and Engineering: Theses, Dissertations, and Student Research

Formal concept analysis(FCA) is a mathematical theory based on lattice and order theory used for data analysis and knowledge representation. Over the past several years, many of its extensions have been proposed and applied in several domains including data mining, machine learning, knowledge management, semantic web, software development, chemistry ,biology, medicine, data analytics, biology and ontology engineering.

This thesis reviews the state-of-the-art of theory of Formal Concept Analysis(FCA) and its various extensions that have been developed and well-studied in the past several years. We discuss their historical roots, reproduce the original definitions and derivations with illustrative examples. Further, we provide …

Attention In The Faithful Self-Explanatory Nlp Models, Mostafa Rafaiejokandan

Computer Science and Engineering: Theses, Dissertations, and Student Research

Deep neural networks (DNNs) can perform impressively in many natural language processing (NLP) tasks, but their black-box nature makes them inherently challenging to explain or interpret. Self-Explanatory models are a new approach to overcoming this challenge, generating explanations in human-readable languages besides task objectives like answering questions. The main focus of this thesis is the explainability of NLP tasks, as well as how attention methods can help enhance performance. Three different attention modules are proposed, SimpleAttention, CrossSelfAttention, and CrossModality. It also includes a new dataset transformation method called Two-Documents that converts every dataset into two separate documents required by the …