Multihop-Rag: A Longitudinal Study On Its Implementation And Benchmarks, 2024 Western University
Multihop-Rag: A Longitudinal Study On Its Implementation And Benchmarks, Murtaza Asrani, Rishabh Agrawal, Apurva Narayan
Undergraduate Student Research Internships Conference
In recent years, the popularization of large language model (LLM) applications such as ChatGPT has made it easy for anyone to access new knowledge and solve problems. However, these LLM applications come with precaution; often, the LLMs powering these applications can provide misleading or entirely incorrect answers referred to as hallucinations. Hallucinations can occur for many reasons, one of which is due to short- comings in the dataset used to train the LLM. In combatance to such events, re- searchers have devised a new method of response generation known as Retrieval Augmented Generation (RAG). However, inadequate response quality emerges in …
Federated Learning Systems For Mobile Sensing Data, 2024 New Jersey Institute of Technology
Federated Learning Systems For Mobile Sensing Data, Xiaopeng Jiang
Dissertations
Federated Learning (FL) has emerged as a new distributed Deep Learning (DL) paradigm that enables privacy-aware training and inference on mobile devices with help from the cloud. This dissertation presents a comprehensive exploration of FL with mobile sensing data, covering systems, applications, and optimizations.
First, a mobile-cloud FL system, FLSys, is designed to balance model performance with resource consumption, tolerate communication failures, and achieve scalability. In FLSys, different DL models with different FL aggregation methods can be trained and accessed concurrently by different apps. In addition, FLSys provides advanced privacy-preserving mechanisms and a common API for third-party app developers to …
Extending Application Runtime Systems For Effective Data Tiering On Complex Memory Platforms, 2024 University of Tennessee, Knoxville
Extending Application Runtime Systems For Effective Data Tiering On Complex Memory Platforms, Brandon Kammerdiener
Doctoral Dissertations
Computing platforms that package multiple types of memory, each with their own performance characteristics, are quickly becoming mainstream. To operate efficiently, heterogeneous memory architectures require new data management solutions that are able to match the needs of each application with an appropriate type of memory. As the primary generators of memory usage, applications create a great deal of information that can be useful for guiding memory tiering, but the community still lacks tools to collect, organize, and leverage this information effectively. To address this gap, this work introduces a novel software framework that collects and analyzes object-level information to guide …
Development Of Feature Extraction Models To Improve Image Analysis Applications In Cancer, 2024 University of Nebraska-Lincoln
Development Of Feature Extraction Models To Improve Image Analysis Applications In Cancer, Yu Shi
Dissertations and Doctoral Documents from University of Nebraska-Lincoln, 2023–
Cancer poses a significant global health challenge. With an estimated 20 million new cases diagnosed worldwide in 2022 and 9.7 million fatalities attributable to the disease, the economic burden of cancer is immense. It impacts healthcare systems and imposes substantial costs for its care on patients and their families. Despite advancements in early detection, prevention, and treatment that have reduced overall cancer mortality rates, the growing prevalence of cancer, particularly among younger individuals, remains a pressing issue.
Recent advancements in medical imaging technology have progressed significantly with the help of emerging computer vision and artificial intelligence (AI) technology. Despite these …
Exploring The Integration Of Blockchain In Iot Use Cases: Challenges And Opportunities, 2024 California State University, San Bernardino
Exploring The Integration Of Blockchain In Iot Use Cases: Challenges And Opportunities, Ivannah George
Electronic Theses, Projects, and Dissertations
Blockchain and The Internet of Things (IoT) is a significant paradigm which has gained traction in today’s digital age as two complimentary technologies. The combination of IoT's connectivity with blockchain's security creates new opportunities and solves problems associated with centralized systems. This culminating project aims to delve deeper into the integration of blockchain technology in IoT applications based on select use cases to uncover potential benefits and significant challenges of blockchain integration across different sectors. The research objectives to be addressed are: (RO1) How emerging vulnerabilities manifest in the implementation of blockchain within current IoT ecosystems. (RO2) How current opportunities …
Smart Airports: Artificial Intelligence–Enabled Internet Of Things Networks Using Blockchain Technology, 2024 Independent Scholar
Smart Airports: Artificial Intelligence–Enabled Internet Of Things Networks Using Blockchain Technology, Edwin Ongola
Journal of Aviation Technology and Engineering
This article provides a perspective on how an internet of heterogeneous self-service airport terminal systems can be used for data collection, which is stored on a private or consortium blockchain depending on the ownership or operations of an airport or both. Such a setup would help to increase efficiency, reduce costs, and improve traveler experience at airport terminals. Moreover, it would allow airports to gather data directly from passengers as opposed to waiting to receive the same data from airlines. Subsequently, this data, now on a blockchain system, becomes a data source for other applications such as machine learning. In …
Microservices Architecture: Evolution, Realizing Benefits, And Addressing Challenges In The Modern Software Era -A Systematic Literature Review, 2024 future university in egypt
Microservices Architecture: Evolution, Realizing Benefits, And Addressing Challenges In The Modern Software Era -A Systematic Literature Review, Linah M. Elnaghi, Ramadan Moawad
Future Computing and Informatics Journal
This paper explores the world of modern software development and the rising popularity of microservices architecture. Microservices, a modern approach, brings benefits like scalability, Reusability, and fault tolerance. challenging traditional monolithic approaches.This survey involves a detailed comparison, unraveling the motivations behind the wide usage of microservices. This paper extracts insights from a diverse range of studies, presenting a clear and accessible synthesis of the key benefits and challenges associated with microservices architecture. Through a methodical analysis of these factors, the study aims to discern the most pivotal advantages and challenges within the domain of microservices. Steering away from complicated terminology, …
Microkarta: Visualising Microservice Architectures, 2024 Singapore Management University
Microkarta: Visualising Microservice Architectures, Oscar Manglaras, Alex Farkas, Peter Fule, Christoph Treude, Markus Wagner
Research Collection School Of Computing and Information Systems
Conceptualising and debugging a microservice architecture can be a challenge for developers due to the complex topology of inter-service communication, which may only apparent when viewing the architecture as a whole. In this paper, we present MicroKarta, a dashboard containing three types of network diagram that visualise complex microservice architectures, and that are designed to address problems faced by developers of these architectures. Initial feedback from industry developers has been positive. This dashboard can be used by developers to explore and debug microservice architectures, and can be used to compare the effectiveness of different types of network visualisation for assisting …
Accessible Real-Time Eye-Gaze Tracking For Neurocognitive Health Assessments, A Multimodal Web-Based Approach, 2024 California Polytechnic State University, San Luis Obispo
Accessible Real-Time Eye-Gaze Tracking For Neurocognitive Health Assessments, A Multimodal Web-Based Approach, Daniel C. Tisdale
Master's Theses
We introduce a novel integration of real-time, predictive eye-gaze tracking models into a multimodal dialogue system tailored for remote health assessments. This system is designed to be highly accessible requiring only a conventional webcam for video input along with minimal cursor interaction and utilizes engaging gaze-based tasks that can be performed directly in a web browser. We have crafted dynamic subsystems that capture high-quality data efficiently and maintain quality through instances of user attrition and incomplete calls. Additionally, these subsystems are designed with the foresight to allow for future re-analysis using improved predictive models, as well as enable the creation …
Performance Interference Detection For Cloud-Native Applications Using Unsupervised Machine Learning Models, 2024 California Polytechnic State University, San Luis Obispo
Performance Interference Detection For Cloud-Native Applications Using Unsupervised Machine Learning Models, Eli Bakshi
Master's Theses
Contemporary cloud-native applications frequently adopt the microservice architecture, where applications are deployed within multiple containers that run on cloud virtual machines (VMs). These applications are typically hosted on public cloud platforms, where VMs from multiple cloud subscribers compete for the same physical resources on a cloud server. When a cloud subscriber application running on a VM competes for shared physical resources from other applications running on the same VM or from other VMs co-located on the same cloud server, performance interference may occur when the performance of an application degrades due to shared resource contention. Detecting such interference is crucial …
Analysis Of Green Data Center Efforts And Energy Usage, 2024 Seattle Pacific University
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.
Generative Machine Learning For Cyber Security, 2024 Washington State University
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.
Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, 2024 University of South Alabama
Side Channel Detection Of Pc Rootkits Using Nonlinear Phase Space, Rebecca Clark
Poster Presentations
Cyberattacks are increasing in size and scope yearly, and the most effective and common means of attack is through malicious software executed on target devices of interest. Malware threats vary widely in terms of behavior and impact and, thus, effective methods of detection are constantly being sought from the academic research community to offset both volume and complexity. Rootkits are malware that represent a highly feared threat because they can change operating system integrity and alter otherwise normally functioning software. Although normal methods of detection that are based on signatures of known malware code are the standard line of defense, …
Multithreaded Applications On The Heterogeneous Research Computing Environment., 2024 University of Louisville
Multithreaded Applications On The Heterogeneous Research Computing Environment., Sungbo Jung
Electronic Theses and Dissertations
Bioinformatics is a domain that has experienced rapid research growth in recent years, as evidenced by the increasing number of articles in biomedical databases such as PubMed, which adds over a million publications every year. However, this also poses a challenge for researchers who need to find relevant citations for their work. Therefore, developing efficient indexing and searching methods for text data is crucial for Bioinformatics. One key technique for information retrieval is document inversion, which involves creating an inverted index to enable efficient searching through vast collections of text or documents. This Ph.D. research aims to design the research …
Crash Detecting System Using Deep Learning, 2024 California State University, San Bernardino
Crash Detecting System Using Deep Learning, Yogesh Reddy Muddam
Electronic Theses, Projects, and Dissertations
Accidents pose a significant risk to both individual and property safety, requiring effective detection and response systems. This work introduces an accident detection system using a convolutional neural network (CNN), which provides an impressive accuracy of 86.40%. Trained on diverse data sets of images and videos from various online sources, the model exhibits complex accident detection and classification and is known for its prowess in image classification and visualization.
CNN ensures better accident detection in various scenarios and road conditions. This example shows its adaptability to a real-world accident scenario and enhances its effectiveness in detecting early events. A key …
Exploring Decentralized Computing Using Solid And Ipfs For Social Media Applications, 2024 University of Arkansas, Fayetteville
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 …
Multi-Script Handwriting Identification By Fragmenting Strokes, 2024 University of South Alabama
Multi-Script Handwriting Identification By Fragmenting Strokes, Joshua Jude Thomas
Theses and Dissertations
This study tests the effectiveness of Multi-Script Handwriting Identification after simplifying character strokes, by segmenting them into sub-parts. Character simplification is performed through splitting the character by branching-points and end-points, a process called stroke fragmentation in this study. The resulting sub-parts of the character are called stroke fragments and are evaluated individually to identify the writer. This process shares similarities with the concept of stroke decomposition in Optical Character Recognition which attempts to recognize characters through the writing strokes that make them up. The main idea of this study is that the characters of different writing‑scripts (English, Chinese, etc.) may …
Data Engineering: Building Software Efficiency In Medium To Large Organizations, 2024 Whittier College
Data Engineering: Building Software Efficiency In Medium To Large Organizations, Alessandro De La Torre
Whittier Scholars Program
The introduction of PoetHQ, a mobile application, offers an economical strategy for colleges, potentially ushering in significant cost savings. These savings could be redirected towards enhancing academic programs and services, enriching the educational landscape for students. PoetHQ aims to democratize access to crucial software, effectively removing financial barriers and facilitating a richer educational experience. By providing an efficient software solution that reduces organizational overhead while maximizing accessibility for students, the project highlights the essential role of equitable education and resource optimization within academic institutions.
A Design Science Approach To Investigating Decentralized Identity Technology, 2024 William & Mary
A Design Science Approach To Investigating Decentralized Identity Technology, Janelle Krupicka
Cybersecurity Undergraduate Research Showcase
The internet needs secure forms of identity authentication to function properly, but identity authentication is not a core part of the internet’s architecture. Instead, approaches to identity verification vary, often using centralized stores of identity information that are targets of cyber attacks. Decentralized identity is a secure way to manage identity online that puts users’ identities in their own hands and that has the potential to become a core part of cybersecurity. However, decentralized identity technology is new and continually evolving, which makes implementing this technology in an organizational setting challenging. This paper suggests that, in the future, decentralized identity …
Binder, 2024 Arkansas Tech University
Binder, Tyler A. Peaster, Lindsey M. Davenport, Madelyn Little, Alex Bales
ATU Research Symposium
Binder is a mobile application that aims to introduce readers to a book recommendation service that appeals to devoted and casual readers. The main goal of Binder is to enrich book selection and reading experience. This project was created in response to deficiencies in the mobile space for book suggestions, library management, and reading personalization. The tools we used to create the project include Visual Studio, .Net Maui Framework, C#, XAML, CSS, MongoDB, NoSQL, Git, GitHub, and Figma. The project’s selection of books were sourced from the Google Books repository. Binder aims to provide an intuitive interface that allows users …