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Articles 511 - 540 of 4315
Full-Text Articles in Computer Sciences
Lang2views Capstone: The Importance Of A Conscientious Team Lead, Joseph Wornath
Lang2views Capstone: The Importance Of A Conscientious Team Lead, Joseph Wornath
University Honors Theses
This review essay reflects the Lang2views capstone project from the perspective of a team lead. The Lang2views capstone project was a web-based user interface designed to simplify how the Lang2views corporation localizes videos into other languages for their clients. Our capstone group was split into three subgroups: front-end, back-end, and DevOps. The strategy for completing the project went through a major change midway through development wherein we changed our software development methodology from a more rigid Waterfall-type approach to a more flexible Agile methodology. Because of this, many of the initially planned features had to be reevaluated as out of …
Dappscan: Building Large-Scale Datasets For Smart Contract Weaknesses In Dapp Projects, Zibin Zheng, Jianzhong Su, Jiachi Chen, David Lo, Zhijie Zhong, Mingxi Ye
Dappscan: Building Large-Scale Datasets For Smart Contract Weaknesses In Dapp Projects, Zibin Zheng, Jianzhong Su, Jiachi Chen, David Lo, Zhijie Zhong, Mingxi Ye
Research Collection School Of Computing and Information Systems
The Smart Contract Weakness Classification Registry (SWC Registry) is a widely recognized list of smart contract weaknesses specific to the Ethereum platform. Despite the SWC Registry not being updated with new entries since 2020, the sustained development of smart contract analysis tools for detecting SWC-listed weaknesses highlights their ongoing significance in the field. However, evaluating these tools has proven challenging due to the absence of a large, unbiased, real-world dataset. To address this problem, we aim to build a large-scale SWC weakness dataset from real-world DApp projects. We recruited 22 participants and spent 44 person-months analyzing 1,199 open-source audit reports …
Applicability And Challenges Of Indoor Localization Using One-Sided Round Trip Time Measurements, Quang Hai Truong, Xi Kai Justin Lam, Guru Anand Anish, Rajesh Krishna Balan
Applicability And Challenges Of Indoor Localization Using One-Sided Round Trip Time Measurements, Quang Hai Truong, Xi Kai Justin Lam, Guru Anand Anish, Rajesh Krishna Balan
Research Collection School Of Computing and Information Systems
Radio Frequency fingerprinting, based on WiFi or cellular signals, has been a popular approach for localization. However, adoptions in real-world applications have confronted with challenges due to low accuracy, especially in crowded environments. The received signal strength (RSS) could be easily interfered by a large number of other devices or strictly depends on physical surrounding environments, which may cause localization errors of a few meters. On the other hand, the fine time measurement (FTM) round-trip time (RTT) has shown compelling improvement in indoor localization with ~1-2 meter accuracy in both 2D and 3D environments [13]. This method relies on the …
Smart Hpa: A Resource-Efficient Horizontal Pod Auto-Scaler For Microservice Architectures, Hussain Ahmad, Christoph Treude, Markus Wagner, Claudia Szabo
Smart Hpa: A Resource-Efficient Horizontal Pod Auto-Scaler For Microservice Architectures, Hussain Ahmad, Christoph Treude, Markus Wagner, Claudia Szabo
Research Collection School Of Computing and Information Systems
Microservice architectures have gained prominence in both academia and industry, offering enhanced agility, reusability, and scalability. To simplify scaling operations in microservice architectures, container orchestration platforms such as Kubernetes feature Horizontal Pod Auto-scalers (HPAs) designed to adjust the resources of microservices to accommodate fluctuating workloads. However, existing HPAs are not suitable for resourceconstrained environments, as they make scaling decisions based on the individual resource capacities of microservices, leading to service unavailability and performance degradation. Furthermore, HPA architectures exhibit several issues, including inefficient data processing and a lack of coordinated scaling operations. To address these concerns, we propose Smart HPA, a …
Enhancing Government Service Delivery: A Case Study Of Acqar Implementation And Lessons Learned From Chatgpt Integration In A Singapore Government Agency, Hui Shan Lee, Shankararaman, Venky, Eng Lieh Ouh
Enhancing Government Service Delivery: A Case Study Of Acqar Implementation And Lessons Learned From Chatgpt Integration In A Singapore Government Agency, Hui Shan Lee, Shankararaman, Venky, Eng Lieh Ouh
Research Collection Lee Kong Chian School Of Business
This paper presents the pilot implementation of AI Based Citizen Question-Answer Recommender (ACQAR) as an attempt to enhance citizen service delivery within a Singaporean government agency. Drawing insights from previous studies on the Empath library's use in Service Level Agreement (SLA) prediction and the implementation of the Citizen Question-Answer system (CQAS), we redesigned the pilot system, ACQAR. ACQAR integrates the outputs from Empath X SLA predictor and CQAS as essential inputs to the ChatGPT engine, creating contextually aware responses for customer service officers to use as responses to the citizens.Empath X SLA predictor anticipates the expected service response time based …
Refining Chatgpt-Generated Code: Characterizing And Mitigating Code Quality Issues, Yue Liu, Thanh Le-Cong, Ratnadira Widyasari, Chakkrit Kla Tantihamthavorn, Li Li, Xuan-Bach Dinh Le, David Lo
Refining Chatgpt-Generated Code: Characterizing And Mitigating Code Quality Issues, Yue Liu, Thanh Le-Cong, Ratnadira Widyasari, Chakkrit Kla Tantihamthavorn, Li Li, Xuan-Bach Dinh Le, David Lo
Research Collection School Of Computing and Information Systems
Since its introduction in November 2022, ChatGPT has rapidly gained popularity due to its remarkable ability in language understanding and human-like responses. ChatGPT, based on GPT-3.5 architecture, has shown great promise for revolutionizing various research fields, including code generation. However, the reliability and quality of code generated by ChatGPT remain unexplored, raising concerns about potential risks associated with the widespread use of ChatGPT-driven code generation.In this article, we systematically study the quality of 4,066 ChatGPT-generated programs of code implemented in two popular programming languages, i.e., Java and Python, for 2,033 programming tasks. The goal of this work is threefold. First, …
Ethical Considerations Toward Protestware, Marc Cheong, Raula Kula, Christoph Treude
Ethical Considerations Toward Protestware, Marc Cheong, Raula Kula, Christoph Treude
Research Collection School Of Computing and Information Systems
This article looks into possible scenarios where developers might consider turning their free and open source software into protestware. Using different frameworks commonly used in artificial intelligence (AI) ethics, we extend the applications of AI ethics to the study of protestware.
Detecting Foot Strikes During Running With Earbuds, Changshuo Hu, Thivya Kandappu, Jake Stuchbury-Wass, Yang Liu, Anthony Tang, Cecelia Mascolo, Dong Ma
Detecting Foot Strikes During Running With Earbuds, Changshuo Hu, Thivya Kandappu, Jake Stuchbury-Wass, Yang Liu, Anthony Tang, Cecelia Mascolo, Dong Ma
Research Collection School Of Computing and Information Systems
Running is a widely embraced form of aerobic exercise, offering various physical and mental benefits. However, improper running gaits (i.e., the way of foot landing) can pose safety risks and impact running efficiency. As many runners lack the knowledge or continuous attention to manage their foot strikes during running, in this work, we present a portable and non-invasive running gait monitoring system. Specifically, we leverage the in-ear microphone on wireless earbuds to capture the vibrations generated by foot strikes. Landing with different parts of the foot (e.g., forefoot and heel) generates distinct vibration patterns, and thus we utilize machine learning …
Criticality Aware Canvas-Based Visual Perception At The Edge, Ila Gokarn
Criticality Aware Canvas-Based Visual Perception At The Edge, Ila Gokarn
Research Collection School Of Computing and Information Systems
Efficient and effective machine perception remains a formidable challenge in sustaining high fidelity and high throughput of perception tasks on affordable edge devices. This is especially due to the continuing increase in resolution of sensor streams (e.g., video input streams generated by 4K/8K cameras and neuromorphic event cameras that produce ≥ 10 MEvents/second) and computational complexity of Deep Neural Network (DNN) models, which overwhelms edge platforms, adversely impacting machine perception efficiency. Given the insufficiency of the available computation resources, a question then arises on whether selected regions/components of the perception task can be prioritized (and executed preferentially) to achieve highest …
Empirical Exploration Of Software Testing, Samia Alblwi
Empirical Exploration Of Software Testing, Samia Alblwi
Dissertations
Despite several advances in software engineering research and development, the quality of software products remains a considerable challenge. For all its theoretical limitations, software testing remains the main method used in practice to control, enhance, and certify software quality. This doctoral work comprises several empirical studies aimed at analyzing and assessing common software testing approaches, methods, and assumptions. In particular, the concept of mutant subsumption is generalized by taking into account the possibility for a base program and its mutants to diverge for some inputs, demonstrating the impact of this generalization on how subsumption is defined. The problem of mutant …
A Survey Of Practical Haskell: Parsing, Interpreting, And Testing, Parker Landon
A Survey Of Practical Haskell: Parsing, Interpreting, And Testing, Parker Landon
Honors Projects
Strongly typed pure functional programming languages like Haskell have historically been confined to academia as vehicles for programming language research. While features of functional programming have greatly influenced mainstream programming languages, the imperative programming style remains pervasive in practical software development. This paper illustrates the practical utility of Haskell and pure functional programming by exploring “hson,” a scripting language for processing JSON developed in Haskell. After introducing the relevant features of Haskell to the unfamiliar reader, this paper reveals how hson leverages functional programming to implement parsing, interpreting, and testing. By showcasing how Haskell’s language features enable the creation of …
Analysis Of Green Data Center Efforts And Energy Usage, Dillon J. Goicoechea
Analysis Of Green Data Center Efforts And Energy Usage, Dillon J. Goicoechea
Honors Projects
This paper is an undergraduate level literature review and analysis of research surrounding the Green Data Center phenomenon. Review of work covering energy usage, data usage, usage predictions, and strategies for decreasing energy requirements is the main analysis of this work. The analysis shows that while data centers are becoming greener, the increase in usage of their capacities is negating those efficiency increases. The increase in the energy efficiency of data centers is crucial, however, there must be made efforts to lower computational and data usage to help achieve lower energy usage of data centers.
Program Analysis Of C For Conversion To Memory-Safe Rust, Dylan Cassidy
Program Analysis Of C For Conversion To Memory-Safe Rust, Dylan Cassidy
Honors Scholar Theses
C is a memory-unsafe language, which can cause software security issues. Rust is a more recent high-performance language that has memory-safe features, which motivates developers to move software to Rust. However, given the large existing C codebase, this is a tedious task, and current approaches result in memory-unsafe blocks of code remaining unsafe after conversion. We seek to use program analysis techniques to create software that identifies blocks of C code that could be safely converted to memory-safe Rust, despite using seemingly memory- unsafe access patterns. We performed manual translation of functions within the libGeoIP C library to Rust, ensuring …
Software Development And Market Research Process Of Plasma Software Distribution, Connor Moore
Software Development And Market Research Process Of Plasma Software Distribution, Connor Moore
Honors College Theses
When trying to find the right software for scientific research, one may have to comb through the internet to acquire a suitable tool. Much of the scientific software online is in mostly unknown web pages where the only way to find the software is to already know about it, be told about it, or find the software by pure chance. Even worse, with few verification systems in place they may try a new program only for it to turn out to be malware. The search for the right software takes time away from the scientists, slowing the overall pace of …
Machine Learning: Face Recognition, Mohammed E. Amin
Machine Learning: Face Recognition, Mohammed E. Amin
Publications and Research
This project explores the cutting-edge intersection of machine learning (ML) and face recognition (FR) technology, utilizing the OpenCV library to pioneer innovative applications in real-time security and user interface enhancement. By processing live video feeds, our system encodes visual inputs and employs advanced face recognition algorithms to accurately identify individuals from a database of photos. This integration of machine learning with OpenCV not only showcases the potential for bolstering security systems but also enriches user experiences across various technological platforms. Through a meticulous examination of unique facial features and the application of sophisticated ML algorithms and neural networks, our project …
A Nlp Approach To Automating The Generation Of Surveys For Market Research, Anav Chug
A Nlp Approach To Automating The Generation Of Surveys For Market Research, Anav Chug
Honors College Theses
Market Research is vital but includes activities that are often laborious and time consuming. Survey questionnaires are one possible output of the process and market researchers spend a lot of time manually developing questions for focus groups. The proposed research aims to develop a software prototype that utilizes Natural Language Processing (NLP) to automate the process of generating survey questions for market research. The software uses a pre-trained Open AI language model to generate multiple choice survey questions based on a given product prompt, send it to a targeted email list, and also provides a real-time analysis of the responses …
Surmounting Challenges In Aggregating Results From Static Analysis Tools, Dr. Ann Marie Reinhold, Brittany Boles, A. Redempta Manzi Muneza, Thomas Mcelroy, Dr. Clemente Izurieta
Surmounting Challenges In Aggregating Results From Static Analysis Tools, Dr. Ann Marie Reinhold, Brittany Boles, A. Redempta Manzi Muneza, Thomas Mcelroy, Dr. Clemente Izurieta
Military Cyber Affairs
Aggregation poses a significant challenge for software practitioners because it requires a comprehensive and nuanced understanding of raw data from diverse sources. Suites of static-analysis tools (SATs) are commonly used to assess organizational security but simultaneously introduce significant challenges. Challenges include unique results, scales, configuration environments for each SAT execution, and incompatible formats between SAT outputs. Here, we document our experiences addressing these issues. We highlight the problem of relying on a single vendor's SAT version and offer a solution for aggregating findings across multiple SATs, aiming to enhance software security practices and deter threats early with robust defensive operations.
Generative Machine Learning For Cyber Security, James Halvorsen, Dr. Assefaw Gebremedhin
Generative Machine Learning For Cyber Security, James Halvorsen, Dr. Assefaw Gebremedhin
Military Cyber Affairs
Automated approaches to cyber security based on machine learning will be necessary to combat the next generation of cyber-attacks. Current machine learning tools, however, are difficult to develop and deploy due to issues such as data availability and high false positive rates. Generative models can help solve data-related issues by creating high quality synthetic data for training and testing. Furthermore, some generative architectures are multipurpose, and when used for tasks such as intrusion detection, can outperform existing classifier models. This paper demonstrates how the future of cyber security stands to benefit from continued research on generative models.
Exploring Decentralized Computing Using Solid And Ipfs For Social Media Applications, Pranav Balasubramanian Natarajan
Exploring Decentralized Computing Using Solid And Ipfs For Social Media Applications, Pranav Balasubramanian Natarajan
Computer Science and Computer Engineering Undergraduate Honors Theses
As traditional centralized social media platforms face growing concerns over data privacy, censorship, and lack of user control, there has been an increasing interest in decentralized alternatives. This thesis explores the design and implementation of a decentralized social media application by integrating two key technologies: Solid and the InterPlanetary File System (IPFS). Solid, led by Sir Tim Berners-Lee, enables users to store and manage their personal data in decentralized "Pods," giving them ownership over their digital identities. IPFS, a peer-to-peer hypermedia protocol, facilitates decentralized file storage and sharing, ensuring content availability and resilience against censorship. By leveraging these technologies, the …
Automatic Extraction Of Vulnerability Information For Security Operators Using Gpt Models, Waeland Elder
Automatic Extraction Of Vulnerability Information For Security Operators Using Gpt Models, Waeland Elder
Computer Science and Computer Engineering Undergraduate Honors Theses
Artificial intelligence has progressed rapidly in recent years, greatly revolutionizing the world and helping to automate increasingly complex tasks. However, there are still some disciplines where the problem of automation has not yet been thoroughly tackled, such as in software vulnerability management. Vulnerability management is a critical component of cybersecurity for an organization. Until recently, learning about a vulnerability required a security operator to manually search and read through online information and security advisories to find needed information. Doing so is a significantly time-consuming task, as these advisories tend to be quite lengthy and packed with information about various technologies. …
The Quantitative Analysis And Visualization Of Nfl Passing Routes, Sandeep Chitturi
The Quantitative Analysis And Visualization Of Nfl Passing Routes, Sandeep Chitturi
Computer Science and Computer Engineering Undergraduate Honors Theses
The strategic planning of offensive passing plays in the NFL incorporates numerous variables, including defensive coverages, player positioning, historical data, etc. This project develops an application using an analytical framework and an interactive model to simulate and visualize an NFL offense's passing strategy under varying conditions. Using R-programming and data management, the model dynamically represents potential passing routes in response to different defensive schemes. The system architecture integrates data from historical NFL league years to generate quantified route scores through designed mathematical equations. This allows for the prediction of potential passing routes for offensive skill players in response to the …
Factors Influencing Performance Of Students In Software Automated Test Tools Course, Susmita Haldar, Mary Pierce, Luiz Fernando Capretz
Factors Influencing Performance Of Students In Software Automated Test Tools Course, Susmita Haldar, Mary Pierce, Luiz Fernando Capretz
Electrical and Computer Engineering Publications
Formal software testing education is important for building efficient QA professionals. Various aspects of quality assurance approaches are usually covered in courses for training software testing students. Automated Test Tools is one of the core courses in the software testing post-graduate curriculum due to the high demand for automated testers in the workforce. It is important to understand which factors are affecting student performance in the automated testing course to be able to assist the students early on based on their needs. Various metrics that are considered for predicting student performance in this testing course are student engagement, grades on …
An Evaluation Of Heart Rate Monitoring With In-Ear Microphones Under Motion, Kayla-Jade Butkow, Ting Dang, Andrea Ferlini, Dong Ma, Yang Liu, Cecilia Mascolo
An Evaluation Of Heart Rate Monitoring With In-Ear Microphones Under Motion, Kayla-Jade Butkow, Ting Dang, Andrea Ferlini, Dong Ma, Yang Liu, Cecilia Mascolo
Research Collection School Of Computing and Information Systems
With the soaring adoption of in-ear wearables, the research community has started investigating suitable in-ear heart rate detection systems. Heart rate is a key physiological marker of cardiovascular health and physical fitness. Continuous and reliable heart rate monitoring with wearable devices has therefore gained increasing attention in recent years. Existing heart rate detection systems in wearables mainly rely on photoplethysmography (PPG) sensors, however, these are notorious for poor performance in the presence of human motion. In this work, leveraging the occlusion effect that enhances low-frequency bone-conducted sounds in the ear canal, we investigate for the first time in-ear audio-based motion-resilient …
Vascular Brain Digital Twins For Medical Training And Education In Metaverse, Shamma Khaled Alghafri
Vascular Brain Digital Twins For Medical Training And Education In Metaverse, Shamma Khaled Alghafri
Theses
This study addresses the need for innovative educational tools in the field of anatomy, specifically focusing on brain anatomy. The objective is to develop a virtual reality application and a 3D visualization that offer immersive and interactive learning experiences for students. The VR application, developed using Unity and designed for the Oculus Quest 2 headset, creates an immersive virtual laboratory environment. This environment includes interactive elements such as a table with buttons for displaying brain models and a whiteboard for user interaction. Users can manipulate and explore different brain structures, enhancing their understanding of complex anatomical features. Additionally, we integrated …
Formalization Of A Security Framework Design For A Health Prescription Assistant In An Internet Of Things System, Thomas Rolando Mellema
Formalization Of A Security Framework Design For A Health Prescription Assistant In An Internet Of Things System, Thomas Rolando Mellema
Electronic Theses and Dissertations
Security system design flaws will create greater risks and repercussions as the systems being secured further integrate into our daily life. One such application example is incorporating the powerful potential of the concept of the Internet of Things (IoT) into software services engineered for improving the practices of monitoring and prescribing effective healthcare to patients. A study was performed in this application area in order to specify a security system design for a Health Prescription Assistant (HPA) that operated with medical IoT (mIoT) devices in a healthcare environment. Although the efficiency of this system was measured, little was presented to …
Comparative Predictive Analysis Of Stock Performance In The Tech Sector, Asaad Sendi
Comparative Predictive Analysis Of Stock Performance In The Tech Sector, Asaad Sendi
LSU New Orleans Theses and Dissertations
This study compares the performance of deep learning models, including Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Transformer, in predicting stock prices across five companies (AAPL, CSCO, META, MSFT, and TSLA) from July 2019 to July 2023. Key findings reveal that GRU models generally exhibit the lowest Mean Absolute Error (MAE), indicating higher precision, particularly notable for CSCO with a remarkably low MAE. While LSTM models often show slightly higher MAE values, they outperform Transformer models in capturing broader trends and variance in stock prices, as evidenced by higher R-squared (R2) values. Transformer models generally exhibit higher MAE …
Dancetag: Using Sensors To Improve Feedback Given To Dance Students, Yanelly Mego
Dancetag: Using Sensors To Improve Feedback Given To Dance Students, Yanelly Mego
Student Scholar Symposium Abstracts and Posters
The structure of dance classrooms has remained unchanged for several years. Very little, if any, technology has been incorporated to improve the quality of teaching. This has motivated our research project, whose goal is to capture dance movements with wearable sensors, to develop DANCETAG (Data Analytics and Notation with Captured Event Tagging). This is a platform that allows the gathering of data captured by Sony’s Mocopi sensors and annotating them with the dancer's movements. The Mocopi sensors make up a motion capture system. It is comprised of six small, round sensors that can be attached to velcro straps and clips. …
A Ui-Enhanced Approach To Generic Web-Based Scheduling, Tyler Hinrichs
A Ui-Enhanced Approach To Generic Web-Based Scheduling, Tyler Hinrichs
Honors Scholar Theses
Administrative scheduling is a key aspect of a wide variety of systems, but despite being a widespread need, it is not a straightforward task. Organizational uniqueness introduces complexity when attempting to use algorithmic methods to automate scheduling, as individual organizations often have their own ways of determining various details and constraints of a schedule. However, in this paper, we assert that there are relevant commonalities that many different schedules fundamentally possess, allowing us to create a generic scheduling application that can be productively used for as many different scenarios as possible. After devising a schema that captures this generic representation, …
An Intelligent Academic Advising System For Course Recommendation Using Large Language Models, Malika Maya Iratni
An Intelligent Academic Advising System For Course Recommendation Using Large Language Models, Malika Maya Iratni
Theses
Academic advising is an important resource for students, especially in higher education, in order to guide them to make the best possible decisions to improve their overall academic performance and overall academic journey. With the increasing number of students joining these institutions each year, traditional advising becomes a time-consuming and inefficient process that can leave students discouraged, and advisors overwhelmed. Therefore, there is a need to develop intelligent advising systems that make use of the recent advancements in technology, to support the advising process, and increase overall student satisfaction. In this work, an academic advising model that uses Recommender Systems …
Improving The Performance Of Wi-Fi Indoor Localization In Both Dense And Unknown Environments, Quang Truong Hai
Improving The Performance Of Wi-Fi Indoor Localization In Both Dense And Unknown Environments, Quang Truong Hai
Dissertations and Theses Collection (Open Access)
Indoor localization is important for various pervasive applications, garnering considerable research attention over recent decades. Despite numerous proposed solutions, the practical application of these methods in real-world environments with high applicability remains challenging. One compelling use case for building owners is the ability to track individuals as they navigate through the building, whether for security, customer analytics, space utilization planning, or other management purposes. However, this task becomes exceedingly difficult in environments with hundreds or thousands of people in motion. Conversely, the need to track oneself’s location is also meaningful from the perspective of individuals traversing in crowded spaces. These …