The Role Of Artificial Intelligence In Determining The Criminal Fingerprint, 2024 Journal of Police and Legal Sciences
The Role Of Artificial Intelligence In Determining The Criminal Fingerprint, Saeed Al Matrooshi
Journal of Police and Legal Sciences
The research aimed to identify the motives and justifications for the use of artificial intelligence in predicting crimes, to explain the challenges of artificial intelligence algorithms, the risks of bias and their ethical rules, and to highlight the role of artificial intelligence in identifying the criminal fingerprint during the detection of crimes. The research relied on the analytical approach, for the purpose of identifying the motives and justifications for the use of intelligence. Artificial intelligence in crime detection, explaining the challenges of artificial intelligence algorithms, their risks of bias, and ethical rules, and exploring how artificial intelligence technology can hopefully …
Securing Edge Computing: A Hierarchical Iot Service Framework, 2024 Northern Kentucky University
Securing Edge Computing: A Hierarchical Iot Service Framework, Sajan Poudel, Nishar Miya, Rasib Khan
Posters-at-the-Capitol
Title: Securing Edge Computing: A Hierarchical IoT Service Framework
Authors: Nishar Miya, Sajan Poudel, Faculty Advisor: Rasib Khan, Ph.D.
Department: School of Computing and Analytics, College of Informatics, Northern Kentucky University
Abstract:
Edge computing, a paradigm shift in data processing, faces a critical challenge: ensuring security in a landscape marked by decentralization, distributed nodes, and a myriad of devices. These factors make traditional security measures inadequate, as they cannot effectively address the unique vulnerabilities of edge environments. Our research introduces a hierarchical framework that excels in securing IoT-based edge services against these inherent risks.
Our secure by design approach prioritizes …
Parallel Algorithm For Testing The Singularity Of An N-Th Order Matrix, 2024 Kerbala University: University of Kerbala madhatiyah, Babil IRAQ
Parallel Algorithm For Testing The Singularity Of An N-Th Order Matrix, Ehab Alasadi
Al-Bahir Journal for Engineering and Pure Sciences
Analyze the possibilities of implementing a parallel algorithm to test the singularity of the N-th order matrix. Design and implement in ( C/C++) a solution based on sending messages between nodes using the PVM system library. Distribute the load among the nodes such that the computation time is as small as possible. Find out how the execution time and calculation acceleration depend on the number of nodes and the size of the problem (indicate the table and graphs). Based on the results, estimate the communication latency, for what size the task is (well) scalable on the given architecture, and what …
Alice In Cyberspace 2024, 2024 Kean University
Alice In Cyberspace 2024, Stanley Mierzwa
Center for Cybersecurity
‘Alice in Cyberspace’ Conference Nurtures Women’s Interest, Representation in Cybersecurity
Immersive Framework For Designing Trajectories Using Augmented Reality, 2024 Embry-Riddle Aeronautical University
Immersive Framework For Designing Trajectories Using Augmented Reality, Joseph Anderson, Leo Materne, Karis Cooks, Michelle Aros, Jaia Huggins, Jesika Geliga-Torres, Kamden Kuykendall, David Canales, Barbara Chaparro
Publications
The intuitive interaction capabilities of augmented reality make it ideal for solving complex 3D problems that require complex spatial representations, which is key for astrodynamics and space mission planning. By implementing common and complex orbital mechanics algorithms in augmented reality, a hands-on method for designing orbit solutions and spacecraft missions is created. This effort explores the aforementioned implementation with the Microsoft Hololens 2 as well as its applications in industry and academia. Furthermore, a human-centered design process and study are utilized to ensure the tool is user-friendly while maintaining accuracy and applicability to higher-fidelity problems.
Reinventing Integrated Photonic Devices And Circuits For High Performance Communication And Computing Applications, 2024 University of Kentucky
Reinventing Integrated Photonic Devices And Circuits For High Performance Communication And Computing Applications, Venkata Sai Praneeth Karempudi
Theses and Dissertations--Electrical and Computer Engineering
The long-standing technological pillars for computing systems evolution, namely Moore's law and Von Neumann architecture, are breaking down under the pressure of meeting the capacity and energy efficiency demands of computing and communication architectures that are designed to process modern data-centric applications related to Artificial Intelligence (AI), Big Data, and Internet-of-Things (IoT). In response, both industry and academia have turned to 'more-than-Moore' technologies for realizing hardware architectures for communication and computing. Fortunately, Silicon Photonics (SiPh) has emerged as one highly promising ‘more-than-Moore’ technology. Recent progress has enabled SiPh-based interconnects to outperform traditional electrical interconnects, offering advantages like high bandwidth density, …
The Impact Of Social Media On Charitable Giving For Nonprofit Organization, 2024 Pace University - New York
The Impact Of Social Media On Charitable Giving For Nonprofit Organization, Namchul Shin
Journal of International Technology and Information Management
Research has extensively studied nonprofit organizations’ use of social media for communications and interactions with supporters. However, there has been limited research examining the impact of social media on charitable giving. This research attempts to address the gap by empirically examining the relationship between the use of social media and charitable giving for nonprofit organizations. We employ a data set of the Nonprofit Times’ top 100 nonprofits ranked by total revenue for the empirical analysis. As measures for social media traction, i.e., how extensively nonprofits draw supporters on their social media sites, we use Facebook Likes, Twitter Followers, and Instagram …
Gen-Acceleration: Pioneering Work For Hardware Accelerator Generation Using Large Language Models, 2023 New Jersey Institute of Technology
Gen-Acceleration: Pioneering Work For Hardware Accelerator Generation Using Large Language Models, Durga Lakshmi Venkata Deepak Vungarala
Theses
Optimizing computational power is critical in the age of data-intensive applications and Artificial Intelligence (AI)/Machine Learning (ML). While facing challenging bottlenecks, conventional Von-Neumann architecture with implementing such huge tasks looks seemingly impossible. Hardware Accelerators are critical in efficiently deploying these technologies and have been vastly explored in edge devices. This study explores a state-of-the-art hardware accelerator; Gemmini is studied; we leveraged the open-sourced tool. Furthermore, we developed a Hardware Accelerator in the study we compared with the Non-Von-Neumann architecture. Gemmini is renowned for efficient matrix multiplication, but configuring it for specific tasks requires manual effort and expertise. We propose implementing …
Application Of Quantum Algorithms In The Synthesis Of Dynamic Objects, 2023 Tashkent State Technical University, Address: 2 Universitetskaya st., 100095, Tashkent city, Republic of Uzbekistan. E-mail: yakubova.noila@gmail.com, Phone: +998946853505.
Application Of Quantum Algorithms In The Synthesis Of Dynamic Objects, Noilakhon Yakubova
Chemical Technology, Control and Management
Around the world, the food industry is focusing on achieving energy and resource efficiency. One of the main challenges in the field of process automation is the creation of effective control systems using intelligent technologies to improve the quality of processes and achieve the production of high-quality products with less energy and resources. Therefore, it is necessary to work with a large amount of data. Particular attention is paid to the development of computational algorithms for automated high-speed computational analysis systems for processing this data at high speed. Therefore, the article discusses the use of quantum computing methods in controlling …
Reducing Food Scarcity: The Benefits Of Urban Farming, 2023 Brigham Young University
Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia
Journal of Nonprofit Innovation
Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.
Imagine Doris, who is …
Improving Credit Card Fraud Detection Using Transfer Learning And Data Resampling Techniques, 2023 California State University - San Bernardino
Improving Credit Card Fraud Detection Using Transfer Learning And Data Resampling Techniques, Charmaine Eunice Mena Vinarta
Electronic Theses, Projects, and Dissertations
This Culminating Experience Project explores the use of machine learning algorithms to detect credit card fraud. The research questions are: Q1. What cross-domain techniques developed in other domains can be effectively adapted and applied to mitigate or eliminate credit card fraud, and how do these techniques compare in terms of fraud detection accuracy and efficiency? Q2. To what extent do synthetic data generation methods effectively mitigate the challenges posed by imbalanced datasets in credit card fraud detection, and how do these methods impact classification performance? Q3. To what extent can the combination of transfer learning and innovative data resampling techniques …
Pollutant Forecasting Using Neural Network-Based Temporal Models, 2023 Western Kentucky University
Pollutant Forecasting Using Neural Network-Based Temporal Models, Richard Pike
Masters Theses & Specialist Projects
The Jing-Jin-Ji region of China is a highly industrialized and populated area of the country. Its periodic high pollution and smog includes particles smaller than 2.5 μm, known as PM2.5, linked to many respiratory and cardiovascular illnesses. PM2.5 concentration around Jing-Jin-Ji has exceeded China’s urban air quality safety threshold for over 20% of all days in 2017 through 2020.
The quantity of ground weather stations that measure the concentrations of these pollutants, and their valuable data, is unfortunately small. By employing many machine learning strategies, many researchers have focused on interpolating finer spatial grids of PM2.5, or hindcasting PM2.5. However, …
Remote Side-Channel Disassembly On Field-Programmable Gate Arrays, 2023 University of South Alabama
Remote Side-Channel Disassembly On Field-Programmable Gate Arrays, Brandon R. Baggett
Theses and Dissertations
Over the last two decades, side-channel vulnerabilities have shown to be a major threat to embedded devices. Most side-channel research has developed our understanding of the vulnerabilities to cryptographic devices due to their implementation and how we can protect them. However, side-channel leakage can yield useful information about many other processes that run on the device. One promising area that has received little attention is the side-channel leakage due to the execution of assembly instructions. There has been some work in this area that has demonstrated the idea’s potential, but so far, this research has assumed the adversary has physical …
Enhancing Accident Investigation Using Traffic Cctv Footage, 2023 California State University, San Bernardino
Enhancing Accident Investigation Using Traffic Cctv Footage, Aksharapriya Peddi
Electronic Theses, Projects, and Dissertations
This Culminating Experience Project investigated how the densenet-161 model will perform on accident severity prediction compared to proposed methods. The research questions are: (Q1) What is the impact of usage of augmentation techniques on imbalanced datasets? (Q2) How will the hyper parameter tuning affect the model performance? (Q3) How effective is the proposed model compared to existing work? The findings are: Q1. The effectiveness of our model depends on the implementation of augmentation techniques that pay attention to handling imbalanced datasets. Our dataset poses a challenge due to distribution of classes in terms of accident severity. To address this challenge …
Classification Of Large Scale Fish Dataset By Deep Neural Networks, 2023 California State University, San Bernardino
Classification Of Large Scale Fish Dataset By Deep Neural Networks, Priyanka Adapa
Electronic Theses, Projects, and Dissertations
The development of robust and efficient fish classification systems has become essential to preventing the rapid depletion of aquatic resources and building conservation strategies. A deep learning approach is proposed here for the automated classification of fish species from underwater images. The proposed methodology leverages state-of-the-art deep neural networks by applying the compact convolutional transformer (CCT) architecture, which is famous for faster training and lower computational cost. In CCT, data augmentation techniques are employed to enhance the variability of the training data, reducing overfitting and improving generalization. The preliminary outcomes of our proposed method demonstrate a promising accuracy level of …
Qasm-To-Hls: A Framework For Accelerating Quantum Circuit Emulation On High-Performance Reconfigurable Computers, 2023 Florida Institute of Technology
Qasm-To-Hls: A Framework For Accelerating Quantum Circuit Emulation On High-Performance Reconfigurable Computers, Anshul Maurya
Theses and Dissertations
High-performance reconfigurable computers (HPRCs) make use of Field-Programmable Gate Arrays (FPGAs) for efficient emulation of quantum algorithms. Generally, algorithm-specific architectures are implemented on the FPGAs and there is very little flexibility. Moreover, mapping a quantum algorithm onto its equivalent FPGA emulation architecture is challenging. In this work, we present an automation framework for converting quantum circuits to their equivalent FPGA emulation architectures. The framework processes quantum circuits represented in Quantum Assembly Language (QASM) and derives high-level descriptions of the hardware emulation architectures for High-Level Synthesis (HLS) on HPRCs. The framework generates the code for a heterogeneous architecture consisting of a …
Low-Power, Event-Driven System On A Chip For Charge Pulse Processing Applications, 2023 University of Nebraska-Lincoln
Low-Power, Event-Driven System On A Chip For Charge Pulse Processing Applications, Joseph A. Schmitz
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
This dissertation presents an electronic architecture and methodology capable of processing charge pulses generated by a range of sensors, including radiation detectors and tactile synthetic skin. These sensors output a charge signal proportional to the input stimulus, which is processed electronically in both the analog and digital domains. The presented work implements this functionality using an event-driven methodology, which greatly reduces power consumption compared to standard implementations. This enables new application areas that require a long operating time or compact physical dimensions, which would not otherwise be possible. The architecture is designed, fabricated, and tested in the aforementioned applications to …
Deep Learning Frameworks For Accelerated Magnetic Resonance Image Reconstruction Without Ground Truths, 2023 University of Arkansas-Fayetteville
Deep Learning Frameworks For Accelerated Magnetic Resonance Image Reconstruction Without Ground Truths, Ibsa Kumara Jalata
Graduate Theses and Dissertations
Magnetic Resonance Imaging (MRI) is typically a slow process because of its sequential data acquisition. To speed up this process, MR acquisition is often accelerated by undersampling k-space signals and solving an ill-posed problem through a constrained optimization process. Image reconstruction from under-sampled data is posed as an inverse problem in traditional model-based learning paradigms. While traditional methods use image priors as constraints, modern deep learning methods use supervised learning with ground truth images to learn image features and priors. However, in some cases, ground truth images are not available, making supervised learning impractical. Recent data-centric learning frameworks such as …
Decentralized Machine Learning On Blockchain: Developing A Federated Learning Based System, 2023 California Polytechnic State University, San Luis Obispo
Decentralized Machine Learning On Blockchain: Developing A Federated Learning Based System, Nikhil Sridhar
Master's Theses
Traditional Machine Learning (ML) methods usually rely on a central server to per-
form ML tasks. However, these methods have problems like security risks, data
storage issues, and high computational demands. Federated Learning (FL), on the
other hand, spreads out the ML process. It trains models on local devices and then
combines them centrally. While FL improves computing and customization, it still
faces the same challenges as centralized ML in security and data storage.
This thesis introduces a new approach combining Federated Learning and Decen-
tralized Machine Learning (DML), which operates on an Ethereum Virtual Machine
(EVM) compatible blockchain. The …
Towards Multi-Modal Interpretable Video Understanding, 2023 University of Arkansas-Fayetteville
Towards Multi-Modal Interpretable Video Understanding, Quang Sang Truong
Graduate Theses and Dissertations
This thesis introduces an innovative approach to video comprehension, which simulates human perceptual mechanisms and establishes a comprehensible and coherent narrative representation of video content. At the core of this approach lies the creation of a Visual-Linguistic (VL) feature for an interpretable video portrayal and an adaptive attention mechanism (AAM) aimed at concentrating solely on principal actors or pertinent objects while modeling their interconnections. Taking cues from the way humans disassemble scenes into visual and non-visual constituents, the proposed VL feature characterizes a scene via three distinct modalities: (i) a global visual environment, providing a broad contextual comprehension of the …