Computer and Systems Architecture Commons^™

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 …

Resilient, Sustainable, And Secure Systems Support For Ultra-Low-Power Computational Things, Nicole Tobias

All Dissertations

Wireless battery-free and energy-harvesting devices are expanding the reach and vision of the Internet of Things, where trillions of embedded computational things interconnect ubiquitously around us and inform many different aspects of our everyday lives. Designing these systems without batteries and interconnecting wires lowers maintenance, environmental, and economic costs while also extending device lifetime and deployment opportunities. Over the last decade, research on these ultra-low-power embedded sensors and systems has dramatically increased — enabling new and exciting prospects in many different scientific fields, from smart building and health monitoring applications to animal and activity tracking.

These systems are not without …

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 …

Melanoma Detection Based On Deep Learning Networks, Sanjay Devaraneni

Electronic Theses, Projects, and Dissertations

Our main objective is to develop a method for identifying melanoma enabling accurate assessments of patient’s health. Skin cancer, such as melanoma can be extremely dangerous if not detected and treated early. Detecting skin cancer accurately and promptly can greatly increase the chances of survival. To achieve this, it is important to develop a computer-aided diagnostic support system. In this study a research team introduces a sophisticated transfer learning model that utilizes Resnet50 to classify melanoma. Transfer learning is a machine learning technique that takes advantage of trained models, for similar tasks resulting in time saving and enhanced accuracy by …

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 …

Smart Service Function Chain System For Dynamic Traffic Steering Using Reinforcement Learning (Chrl), Ahmed Nadhum, Ahmed Al-Saadi

Karbala International Journal of Modern Science

The rapid development of the Internet and network services coupled with the growth of communication infrastructure necessitates the employment of intelligent systems. The complexity of the network is heightened by these systems, as they offer diverse services contingent on traffic type, user needs, and security considerations. In this context, a service function chain offers a toolkit to facilitate the management of intricate network systems. However, various traffic types require dynamic adaptation in the sets of function chains. The problem of optimizing the order of service functions in the chain must be solved using the proposed approach, along with balancing the …

Enabling Intelligent Network Management Through Multi-Agent Systems: An Implementation Of Autonomous Network System, Petro Mushidi Tshakwanda

Electrical and Computer Engineering ETDs

This Ph.D. dissertation presents a pioneering Multi-Agent System (MAS) approach for intelligent network management, particularly suited for next-generation networks like 5G and 6G. The thesis is segmented into four critical parts. Firstly, it contrasts the benefits of agent-based design over traditional micro-service architectures. Secondly, it elaborates on the implementation of network service agents in Python Agent Development Environment (PADE), employing machine learning and deep learning algorithms for performance evaluation. Thirdly, a new scalable approach, Scalable and Efficient DevOps (SE-DO), is introduced to optimize agent performance in resource-constrained settings. Fourthly, the dissertation delves into Quality of Service (QoS) and Radio Resource …

Sel4 On Risc-V - Developing High Assurance Platforms With Modular Open-Source Architectures, Michael A. Doran Jr

Masters Theses

Virtualization is now becoming an industry standard for modern embedded systems. Modern embedded systems can now support multiple applications on a single hardware platform while meeting power and cost requirements. Virtualization on an embedded system is achieved through the design of the hardware-software interface. Instruction set architecture, ISA, defines the hardware-software interface for an embedded system. At the hardware level the ISA, provides extensions to support virtualization.

In addition to an ISA that supports hypervisor extensions it is equally important to provide a hypervisor completely capable of exploiting the benefits of virtualization for securing modern embedded systems. Currently there does …

An Enhanced Adaptive Learning System Based On Microservice Architecture, Abdelsalam Helmy Ibrahim, Mohamed Eliemy, Aliaa Abdelhalim Youssif

Future Computing and Informatics Journal

This study aims to enhance Adaptive Learning Systems (ALS) in Petroleum Sector in Egypt by using the Microservice Architecture and measure the impact of enhancing ALS by participating ALS users through a statistical study and questionnaire directed to them if they accept to apply the Cloud Computing Service “Microservices” to enhance the ALS performance, quality and cost value or not. The study also aims to confirm that there is a statistically significant relationship between ALS and Cloud Computing Service “Microservices” and prove the impact of enhancing the ALS by using Microservices in the cloud in Adaptive Learning in the Egyptian …

Visual Question Answering: A Survey, Gehad Assem El-Naggar

Future Computing and Informatics Journal

Visual Question Answering (VQA) has been an emerging field in computer vision and natural language processing that aims to enable machines to understand the content of images and answer natural language questions about them. Recently, there has been increasing interest in integrating Semantic Web technologies into VQA systems to enhance their performance and scalability. In this context, knowledge graphs, which represent structured knowledge in the form of entities and their relationships, have shown great potential in providing rich semantic information for VQA. This paper provides an abstract overview of the state-of-the-art research on VQA using Semantic Web technologies, including knowledge …

Optimizing High-Performance Computing Design: The Impacts Of Bandwidth And Topology Across Workloads For Distributed Shared Memory Systems, Jonathan A. Milton

Electrical and Computer Engineering ETDs

With the complexity of high-performance computing designs continuously increasing, the importance of evaluating with simulation also grows. One of the key design aspects is the network architecture; topology and bandwidth greatly influence the overall performance and should be optimized. This work uses simulations written to run in the Structural Simulation Toolkit software framework to evaluate a variety of architecture configurations, identify the optimal design point based on expected workload, and evaluate the changes with increased scale. The results show that advanced topologies outperform legacy architectures justifying the additional design complexity; and that after a certain point increasing the bandwidth provides …

Vi Energy-Efficient Memristor-Based Neuromorphic Computing Circuits And Systems For Radiation Detection Applications, Jorge Iván Canales Verdial

Electrical and Computer Engineering ETDs

Radionuclide spectroscopic sensor data is analyzed with minimal power consumption through the use of neuromorphic computing architectures. Memristor crossbars are harnessed as the computational substrate in this non-conventional computing platform and integrated with CMOS-based neurons to mimic the computational dynamics observed in the mammalian brain’s visual cortex. Functional prototypes using spiking sparse locally competitive approximations are presented. The architectures are evaluated for classification accuracy and energy efficiency. The proposed systems achieve a 90% true positive accuracy with a high-resolution detector and 86% with a low-resolution detector.

Chatgpt As Metamorphosis Designer For The Future Of Artificial Intelligence (Ai): A Conceptual Investigation, Amarjit Kumar Singh (Library Assistant), Dr. Pankaj Mathur (Deputy Librarian)

Library Philosophy and Practice (e-journal)

Abstract

Purpose: The purpose of this research paper is to explore ChatGPT’s potential as an innovative designer tool for the future development of artificial intelligence. Specifically, this conceptual investigation aims to analyze ChatGPT’s capabilities as a tool for designing and developing near about human intelligent systems for futuristic used and developed in the field of Artificial Intelligence (AI). Also with the helps of this paper, researchers are analyzed the strengths and weaknesses of ChatGPT as a tool, and identify possible areas for improvement in its development and implementation. This investigation focused on the various features and functions of ChatGPT that …

Wifi Sensing At The Edge Towards Scalable On-Device Wireless Sensing Systems, Steven M. Hernandez

Theses and Dissertations

WiFi sensing offers a powerful method for tracking physical activities using the radio-frequency signals already found throughout our homes and offices. This novel sensing modality offers continuous and non-intrusive activity tracking since sensing can be performed (i) without requiring wearable sensors, (ii) outside the line-of-sight, and even (iii) through the wall. Furthermore, WiFi has become a ubiquitous technology in our computers, our smartphones, and even in low-cost Internet of Things devices. In this work, we consider how the ubiquity of these low-cost WiFi devices offer an unparalleled opportunity for improving the scalability of wireless sensing systems. Thus far, WiFi sensing …

Towards Multipronged On-Chip Memory And Data Protection From Verification To Design And Test, Senwen Kan, Jennifer Dworak

Computer Science and Engineering Theses and Dissertations

Modern System on Chips (SoCs) generally include embedded memories, and these memories may be vulnerable to malicious attacks such as hardware trojan horses (HTHs), test access port exploitation, and malicious software. This dissertation contributes verification as well as design obfuscation solutions aimed at design level detection of memory HTH circuits as well as obfuscation to prevent HTH triggering for embedded memory during functional operation. For malicious attack vectors stemming from test/debug interfaces, this dissertation presents novel solutions that enhance design verification and securitization of an IJTAG based test access interface. Such solutions can enhance SoC protection by preventing memory test …

Development Of Directed Randomization For Discussing A Minimal Security Architecture, Henrique Oyama, Dominic Messina, Keshav Kasturi Rangan, Akkarakaran Francis Leonard, Kip Nieman, Helen Durand, Katie Tyrrell, Katrina Hinzman, Michael Williamson

Chemical Engineering and Materials Science Faculty Research Publications

Strategies for mitigating the impacts of cyberattacks on control systems using a control-oriented perspective have become of greater interest in recent years. Our group has contributed to this trend by developing several methods for detecting cyberattacks on process sensors, actuators, or both sensors and actuators simultaneously using an advanced optimization-based control strategy known as Lyapunov-based economic model predictive control (LEMPC). However, each technique comes with benefits and limitations, both with respect to one another and with respect to traditional information technology and computer science-type approaches to cybersecurity. An important question to ask, therefore, is what the goal should be of …

Compilation Optimizations To Enhance Resilience Of Big Data Programs And Quantum Processors, Travis D. Lecompte

LSU Doctoral Dissertations

Modern computers can experience a variety of transient errors due to the surrounding environment, known as soft faults. Although the frequency of these faults is low enough to not be noticeable on personal computers, they become a considerable concern during large-scale distributed computations or systems in more vulnerable environments like satellites. These faults occur as a bit flip of some value in a register, operation, or memory during execution. They surface as either program crashes, hangs, or silent data corruption (SDC), each of which can waste time, money, and resources. Hardware methods, such as shielding or error correcting memory (ECM), …

Height Information Aided 3d Real-Time Large-Scale Underground User Positioning, Houbing Song, Chengkai Tang, Cunle Zhang, Lingling Zhang, Yi Zhang

Publications

Due to the cost of inertial navigation and visual navigation equipment and lake of satellite navigation signals, they cannot be used in large‐scale underground mining environment. To solve this problem, this study proposes large‐scale underground 3D real‐time positioning method with seam height assistance. This method uses the ultrawide band positioning base station as the core and is combined with seam height information to build a factor graph confidence transfer model to realise3D positioning. The simulation results show that the proposed real‐time method is superior to the existing algorithms in positioning accuracy and can meet the needs of large‐scale underground users.

Evaluating Serverless Computing, Charitra Maharjan

LSU Master's Theses

Function as a Service (FaaS) is gaining admiration because of its way of deploying the computations to serverless backends in the different clouds. It transfers the complexity of provisioning and allocating the necessary resources for an application to the cloud providers. The cloud providers also give an illusion of always availability of resources to the users. Among the cloud providers, AWS serverless platform offers a new paradigm for developing cloud applications without worrying about the underlying hardware infrastructure. It manages not only the resource provisioning and scaling of an application but also provides an opportunity to reimagine the cloud infrastructure …

A Memory-Centric Customizable Domain-Specific Fpga Overlay For Accelerating Machine Learning Applications, Atiyehsadat Panahi

Graduate Theses and Dissertations

Low latency inferencing is of paramount importance to a wide range of real time and userfacing Machine Learning (ML) applications. Field Programmable Gate Arrays (FPGAs) offer unique advantages in delivering low latency as well as energy efficient accelertors for low latency inferencing. Unfortunately, creating machine learning accelerators in FPGAs is not easy, requiring the use of vendor specific CAD tools and low level digital and hardware microarchitecture design knowledge that the majority of ML researchers do not possess. The continued refinement of High Level Synthesis (HLS) tools can reduce but not eliminate the need for hardware-specific design knowledge. The designs …

Computer Aided Diagnosis System For Breast Cancer Using Deep Learning., Asma Baccouche

Electronic Theses and Dissertations

The recent rise of big data technology surrounding the electronic systems and developed toolkits gave birth to new promises for Artificial Intelligence (AI). With the continuous use of data-centric systems and machines in our lives, such as social media, surveys, emails, reports, etc., there is no doubt that data has gained the center of attention by scientists and motivated them to provide more decision-making and operational support systems across multiple domains. With the recent breakthroughs in artificial intelligence, the use of machine learning and deep learning models have achieved remarkable advances in computer vision, ecommerce, cybersecurity, and healthcare. Particularly, numerous …

Credit Card Fraud Detection Using Machine Learning Techniques, Nermin Samy Elhusseny, Shimaa Mohamed Ouf, Amira M. Idrees Ami

Future Computing and Informatics Journal

This is a systematic literature review to reflect the previous studies that dealt with credit card fraud detection and highlight the different machine learning techniques to deal with this problem. Credit cards are now widely utilized daily. The globe has just begun to shift toward financial inclusion, with marginalized people being introduced to the financial sector. As a result of the high volume of e-commerce, there has been a significant increase in credit card fraud. One of the most important parts of today's banking sector is fraud detection. Fraud is one of the most serious concerns in terms of monetary …

A Nano-Drone Safety Architecture, Connor J. Sexton

Master's Theses

As small-form factor drones grow more intelligent, they increasingly require more sophisticated capabilities to record sensor data and system state, ensuring safe and improved operation. Already regulations for black boxes, electronic data recorders (EDRs), for determining liabilities and improving the safety of large-form factor autonomous vehicles are becoming established. Conventional techniques use hardened memory storage units that conserve all sensor (visual) and system operational state; and N-way redundant models for detecting uncertainty in system operation. For small-form factor drones, which are highly limited by weight, power, and computational resources, these techniques become increasingly prohibitive. In this paper, we propose a …

Developing A Miniature Smart Boat For Marine Research, Michael Isaac Eirinberg

Computer Engineering

This project examines the development of a smart boat which could serve as a possible marine research apparatus. The smart boat consists of a miniature vessel containing a low-cost microcontroller to live stream a camera feed, GPS telemetry, and compass data through its own WiFi access point. The smart boat also has the potential for autonomous navigation. My project captivated the interest of several members of California Polytechnic State University, San Luis Obispo’s (Cal Poly SLO) Marine Science Department faculty, who proposed a variety of fascinating and valuable smart boat applications.

Chapter 3: Basis, Basis Vectors, And Inner Product, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

No abstract provided.

Chapter 27: Bloch Sphere And Single-Qubit Arbitrary Unitary Gate, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

No abstract provided.

Chapter 28: Quantum Phase Estimation, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

No abstract provided.

Improving Intelligent Transportation Safety And Reliability Through Lowering Costs, Integrating Machine Learning, And Studying Model Sensitivity, Cavender Holt

All Theses

As intelligent transportation becomes increasingly prevalent in the domain of transportation, it is essential to understand the safety, reliability, and performance of these systems. We investigate two primary areas in the problem domain. The first area concerns increasing the feasibility and reducing the cost of deploying pedestrian detection systems to intersections in order to increase safety. By allowing pedestrian detection to be placed in intersections, the data can be better utilized to create systems to prevent accidents from occurring. By employing a dynamic compression scheme for pedestrian detection, we show the reduction of network bandwidth improved by 2.12× over the …

Structural Checking Tool Restructure And Matching Improvements, Derek Taylor

Graduate Theses and Dissertations

With the rising complexity and size of hardware designs, saving development time and cost by employing third-party intellectual property (IP) into various first-party designs has become a necessity. However, using third-party IPs introduces the risk of adding malicious behavior to the design, including hardware Trojans. Different from software Trojan detection, the detection of hardware Trojans in an efficient and cost-effective manner is an ongoing area of study and has significant complexities depending on the development stage where Trojan detection is leveraged. Therefore, this thesis research proposes improvements to various components of the soft IP analysis methodology utilized by the Structural …

Live Access Control Policy Error Detection Through Hardware, Bryce Mendenhall

Graduate Theses and Dissertations

Access Control (AC) is a widely used security measure designed to protect resources and infrastructure in an information system. The integrity of the AC policy is crucial to the protection of the system. Errors within an AC policy may cause many vulnerabilities such as information leaks, information loss, and malicious activities. Thus, such errors must be detected and promptly fixed. However, current AC error detection models do not allow for real-time error detection, nor do they provide the source of errors. This thesis presents a live error detection model called LogicDetect which utilizes emulated Boolean digital logic circuits to provide …