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Articles 5491 - 5520 of 25750
Full-Text Articles in Computer Engineering
Society Dilemma Of Computer Technology Management In Today's World, Iwasan D. Kejawa Ed.D
Society Dilemma Of Computer Technology Management In Today's World, Iwasan D. Kejawa Ed.D
School of Computing: Faculty Publications
Abstract - Is it true that some of the inhabitants of the world’s today are still hesitant in using computers? Research has shown that today many people are still against the use of computers. Computer technology management can be said to be obliterated by security problems. Research shows that some people in society feel reluctant or afraid to use computers because of errors and exposure of their privacy and their sophistication, which sometimes are caused by computer hackers and malfunction of the computers. The dilemma of not utilizing computer technology at all or, to its utmost, by certain people in …
Cova Cci Undergrad Cyber Research, Nana Jeffrey
Cova Cci Undergrad Cyber Research, Nana Jeffrey
Cybersecurity Undergraduate Research Showcase
Is your digital assistant your worst enemy? Modern technology has impacted our lives in a positive way making tasks that were once time consuming become more convenient. For example a few years ago writing down your grocery list with a paper and pen was a norm, now with technology we have access to IoT devices such as smart fridges that can inform us on what items are low in stock, send a message to our digital assistants such as iOS Siri and Amazon's Alexa to remind us to buy those groceries. Although these digital assistants have helped make our daily …
Dynamics And Simulations Of Discretized Caputo-Conformable Fractional-Order Lotka–Volterra Models, Yousef Feras, Semmar Billel, Al Nasr Kamal
Dynamics And Simulations Of Discretized Caputo-Conformable Fractional-Order Lotka–Volterra Models, Yousef Feras, Semmar Billel, Al Nasr Kamal
Computer Science Faculty Research
In this article, a prey–predator system is considered in Caputo-conformable fractional-order derivatives. First, a discretization process, making use of the piecewise-constant approximation, is performed to secure discrete-time versions of the two fractional-order systems. Local dynamic behaviors of the two discretized fractional-order systems are investigated. Numerical simulations are executed to assert the outcome of the current work. Finally, a discussion is conducted to compare the impacts of the Caputo and conformable fractional derivatives on the discretized model.
Conditional Variational Autoencoder (Cvae) For The Augmentation Of Ecl Biosensor Data, Matthew Dulcich
Conditional Variational Autoencoder (Cvae) For The Augmentation Of Ecl Biosensor Data, Matthew Dulcich
Honors Theses
Machine Learning (ML) is vastly improving the world, from computer vision to fully self-driving cars, we are now able accomplish objectives that were thought to only be dreams. In order to train ML models accurately, they require mountains of information to work with, but sometimes it becomes impossible to collect the data needed, so we turn to data augmentation. In this project we use a conditional variational auto encoder to supplement the original video electrochemiluminescence biosensor dataset, in order to increase the accuracy of a future classification model. In other words, using a cVAE we will create unique realistic videos …
Towards Improved Inertial Navigation By Reducing Errors Using Deep Learning Methodology, Hua Chen, Tarek M. Taha, Vamsy P. Chodavarapu
Towards Improved Inertial Navigation By Reducing Errors Using Deep Learning Methodology, Hua Chen, Tarek M. Taha, Vamsy P. Chodavarapu
Electrical and Computer Engineering Faculty Publications
Autonomous vehicles make use of an Inertial Navigation System (INS) as part of vehicular sensor fusion in many situations including GPS-denied environments such as dense urban places, multi-level parking structures, and areas with thick tree-coverage. The INS unit incorporates an Inertial Measurement Unit (IMU) to process the linear acceleration and angular velocity data to obtain orientation, position, and velocity information using mechanization equations. In this work, we describe a novel deep-learning-based methodology, using Convolutional Neural Networks (CNN), to reduce errors from MEMS IMU sensors. We develop a CNN-based approach that can learn from the responses of a particular inertial sensor …
The Music Bluetooth Controller: An Intersection Between Technology And Music, Lydia Wu
The Music Bluetooth Controller: An Intersection Between Technology And Music, Lydia Wu
Senior Honors Theses
The modern musician faces a new challenge: how can technology be used to enhance a performance? This thesis documents the development of a Bluetooth remote controller that will aid today’s performing musicians by interacting with a digital display (e.g., an iPad) to flip musical score pages remotely. At its core, while mimicking a Bluetooth pedal (the current industry standard), this device attaches to the musician’s hand. In its pilot stages, the device has been referred to “MBC” (Music Bluetooth Controller).
Generative Adversarial Networks Take On Hand Drawn Sketches: An Application To Louisiana Culture And Mardi Gras Fashion, Stephanie Hines
Generative Adversarial Networks Take On Hand Drawn Sketches: An Application To Louisiana Culture And Mardi Gras Fashion, Stephanie Hines
Honors Capstones
No abstract provided.
Ux/U-Eye: Designing Graphical User Interfaces For Exclusive Eye Gaze Control, Timothy Curol
Ux/U-Eye: Designing Graphical User Interfaces For Exclusive Eye Gaze Control, Timothy Curol
Honors Capstones
No abstract provided.
Pre-Training Graph Neural Networks For Link Prediction In Biomedical Networks, Yahui Long, Min Wu, Yong Liu, Yuan Fang, Chee Kong Kwoh, Jiawei Luo, Xiaoli Li
Pre-Training Graph Neural Networks For Link Prediction In Biomedical Networks, Yahui Long, Min Wu, Yong Liu, Yuan Fang, Chee Kong Kwoh, Jiawei Luo, Xiaoli Li
Research Collection School Of Computing and Information Systems
Motivation: Graphs or networks are widely utilized to model the interactions between different entities (e.g., proteins, drugs, etc) for biomedical applications. Predicting potential links in biomedical networks is important for understanding the pathological mechanisms of various complex human diseases, as well as screening compound targets for drug discovery. Graph neural networks (GNNs) have been designed for link prediction in various biomedical networks, which rely on the node features extracted from different data sources, e.g., sequence, structure and network data. However, it is challenging to effectively integrate these data sources and automatically extract features for different link prediction tasks. Results: In …
An Overview Of The Potential For Blockchain Technology To Improve Cybersecurity, Stanley Mierzwa
An Overview Of The Potential For Blockchain Technology To Improve Cybersecurity, Stanley Mierzwa
Center for Cybersecurity
The purpose of this short research commentary is to provide a focused, semi-deep dive into the effort the industry places on cybersecurity defense and operations and the potential to integrate blockchain technology. As cybersecurity threats and incidents continue to rise, better procedures and strategies to protect our organizations’ data and systems are crucial to sustaining viable operations. Given that blockchain technology can potentially disrupt other industries (Moore, 2020), it is imperative to examine how it may improve our cybersecurity.
Cybersecurity Best Practices For The Manufacturing Industry, David Ortiz, Stanley Mierzwa
Cybersecurity Best Practices For The Manufacturing Industry, David Ortiz, Stanley Mierzwa
Center for Cybersecurity
The manufacturing and industrial sectors have evolved with the introduction of technologies over the past many decades. Progress in improving processes, techniques, output, quality, and efficiencies have been gained with new emerging technologies, resulting in positive and fortuitous changes for organizations. With the rapid movement towards a modern-day manufacturing environment, new and connected technologies that employ greater cyber-connectedness continue to grow, but at the same time, introduce cybersecurity risks.
Assessing Security Risks With The Internet Of Things, Faith Mosemann
Assessing Security Risks With The Internet Of Things, Faith Mosemann
Senior Honors Theses
For my honors thesis I have decided to study the security risks associated with the Internet of Things (IoT) and possible ways to secure them. I will focus on how corporate, and individuals use IoT devices and the security risks that come with their implementation. In my research, I found out that IoT gadgets tend to go unnoticed as a checkpoint for vulnerability. For example, often personal IoT devices tend to have the default username and password issued from the factory that a hacker could easily find through Google. IoT devices need security just as much as computers or servers …
Discovering Ways To Increase Inclusivity For Dyslexic Students In Computing Education, Felicia Hellems, Sajal Bhatia
Discovering Ways To Increase Inclusivity For Dyslexic Students In Computing Education, Felicia Hellems, Sajal Bhatia
School of Computer Science & Engineering Faculty Publications
The years accompanying entrance into the university system are often characterized by a period of great transformation. These years can also be wrought with difficulties for many students, difficulties which are often compounded in students with disabilities (SWD). Reports from the U.S. Department of Education show that as recently as 2015--16, 19% of undergraduate students experienced some form of disability1. Additionally, statistics show that SWD tend to have lower post secondary completion rates than their counterparts [3]. A review of pertinent literature has shown that there still exist gaps within the field of computing education (CE) for teaching cybersecurity concepts …
Privacy-Preserving Information Security For The Energy Grid Of Things, Mohammed Alsaid, Nirupama Bulusu, Abdullah Barghouti, N. Sonali Fernando, John M. Acken, Tylor E. Slay, Robert B. Bass
Privacy-Preserving Information Security For The Energy Grid Of Things, Mohammed Alsaid, Nirupama Bulusu, Abdullah Barghouti, N. Sonali Fernando, John M. Acken, Tylor E. Slay, Robert B. Bass
Electrical and Computer Engineering Faculty Publications and Presentations
Smart grid infrastructure relies on information exchange between multiple actors in order to ensure system reliability. These actors include but are not limited to smart loads, grid control, and energy management technologies. As information exchange between these actors is susceptible to cyber-attacks, security and privacy issues are indispensable to ensure a reliable and stable grid. This position paper proposes a privacy-preserving, trust-augmented secure scheme for a smart grid implementation.
Exploring The Efficiency Of Neural Architecture Search (Nas) Modules, Joshua Dulcich
Exploring The Efficiency Of Neural Architecture Search (Nas) Modules, Joshua Dulcich
Honors Theses
Machine learning is obscure and expensive to develop. Neural architecture search (NAS) algorithms automate this process by learning to create premier ML networks, minimizing the bias and necessity of human experts. From this recently emerging field, most research has focused on optimizing a promisingly unique combination of NAS’s three segments. Despite regularly acquiring state of the art results, this practice sacrifices computing time and resources for slight increases in accuracy; this also obstructs performance comparison across papers. To resolve this issue, we use NASLib’s modular library to test the efficiency per module in a unique subset of combinations. Each NAS …
Quadratic Neural Network Architecture As Evaluated Relative To Conventional Neural Network Architecture, Reid Taylor
Quadratic Neural Network Architecture As Evaluated Relative To Conventional Neural Network Architecture, Reid Taylor
Senior Theses
Current work in the field of deep learning and neural networks revolves around several variations of the same mathematical model for associative learning. These variations, while significant and exceptionally applicable in the real world, fail to push the limits of modern computational prowess. This research does just that: by leveraging high order tensors in place of 2nd order tensors, quadratic neural networks can be developed and can allow for substantially more complex machine learning models which allow for self-interactions of collected and analyzed data. This research shows the theorization and development of mathematical model necessary for such an idea to …
Development Of A Ppg Sensor Array As A Wearable Device For Monitoring Cardiovascular Metrics, Jose Ignacio Rodriguez-Labra
Development Of A Ppg Sensor Array As A Wearable Device For Monitoring Cardiovascular Metrics, Jose Ignacio Rodriguez-Labra
Masters Theses
Wearable devices with integrated sensors for tracking human vitals are widely used for a variety of applications, including exercise, wellness, and health monitoring. Photoplethysmography (PPG) sensors use pulse oximetry to measure pulse rate, cardiac cycle, oxygen saturation, and blood flow by passing a light beam of variable wavelength through the skin and measuring its reflection. A multi-channel PPG wearable system was developed to include multiple nodes of pulse oximeters, each capable of using different wavelengths of light. The system uses sensor fusion along with a machine learning model to perform feature extraction of relevant cardiovascular metrics across multiple pulse oximeters …
Learning Domain Invariant Information To Enhance Presentation Attack Detection In Visible Face Recognition Systems, Jennifer Hamblin
Learning Domain Invariant Information To Enhance Presentation Attack Detection In Visible Face Recognition Systems, Jennifer Hamblin
Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research
Face signatures, including size, shape, texture, skin tone, eye color, appearance, and scars/marks, are widely used as discriminative, biometric information for access control. Despite recent advancements in facial recognition systems, presentation attacks on facial recognition systems have become increasingly sophisticated. The ability to detect presentation attacks or spoofing attempts is a pressing concern for the integrity, security, and trust of facial recognition systems. Multi-spectral imaging has been previously introduced as a way to improve presentation attack detection by utilizing sensors that are sensitive to different regions of the electromagnetic spectrum (e.g., visible, near infrared, long-wave infrared). Although multi-spectral presentation attack …
Verifiable Searchable Encryption Framework Against Insider Keyword-Guessing Attack In Cloud Storage, Yinbin Miao, Robert H. Deng, Kim-Kwang Raymond Choo, Ximeng Liu, Hongwei Li
Verifiable Searchable Encryption Framework Against Insider Keyword-Guessing Attack In Cloud Storage, Yinbin Miao, Robert H. Deng, Kim-Kwang Raymond Choo, Ximeng Liu, Hongwei Li
Research Collection School Of Computing and Information Systems
Searchable encryption (SE) allows cloud tenants to retrieve encrypted data while preserving data confidentiality securely. Many SE solutions have been designed to improve efficiency and security, but most of them are still susceptible to insider Keyword-Guessing Attacks (KGA), which implies that the internal attackers can guess the candidate keywords successfully in an off-line manner. Also in existing SE solutions, a semi-honest-but-curious cloud server may deliver incorrect search results by performing only a fraction of retrieval operations honestly (e.g., to save storage space). To address these two challenging issues, we first construct the basic Verifiable SE Framework (VSEF), which can withstand …
Improving Feature Generalizability With Multitask Learning In Class Incremental Learning, Dong Ma, Chi Ian Tang, Cecilia Mascolo
Improving Feature Generalizability With Multitask Learning In Class Incremental Learning, Dong Ma, Chi Ian Tang, Cecilia Mascolo
Research Collection School Of Computing and Information Systems
Many deep learning applications, like keyword spotting [1], [2], require the incorporation of new concepts (classes) over time, referred to as Class Incremental Learning (CIL). The major challenge in CIL is catastrophic forgetting, i.e., preserving as much of the old knowledge as possible while learning new tasks. Various techniques, such as regularization, knowledge distillation, and the use of exemplars, have been proposed to resolve this issue. However, prior works primarily focus on the incremental learning step, while ignoring the optimization during the base model training. We hypothesise that a more transferable and generalizable feature representation from the base model would …
On The Reliability Of Wearable Sensors For Assessing Movement Disorder-Related Gait Quality And Imbalance: A Case Study Of Multiple Sclerosis, Steven Díaz Hernández
On The Reliability Of Wearable Sensors For Assessing Movement Disorder-Related Gait Quality And Imbalance: A Case Study Of Multiple Sclerosis, Steven Díaz Hernández
USF Tampa Graduate Theses and Dissertations
Approximately 33 million American adults had a movement disorder associated with medication use, ear infections, injury, or neurological disorders in 2008, with over 18 million people affected by neurological disorders worldwide. Physical therapists assist people with movement disorders by providing interventions to reduce pain, improve mobility, avoid surgeries, and prevent falls and secondary complications of neurodegenerative disorders. Current gait assessments used by physical therapists, such as the Multiple Sclerosis Walking Scale, provide only semi-quantitative data, and cannot assess walking quality in detail or describe how one’s walking quality changes over time. As a result, quantitative systems have grownas useful tools …
Seabem: An Artificial Intelligence Powered Web Application To Predict Cover Crop Biomass, Aime Christian Tuyishime, Andrea Basche
Seabem: An Artificial Intelligence Powered Web Application To Predict Cover Crop Biomass, Aime Christian Tuyishime, Andrea Basche
Honors Program: Senior Projects (Public)
SEABEM, the Stacked Ensemble Algorithms Biomass Estimator Model, is a web application with a stacked ensemble of Machine Learning (ML) algorithms running on the backend to predict cover crop biomass for locations in Sub-Saharan. The SEABEM model was developed using a previously developed database of crop growth and yield that included site characteristics such as latitude, longitude, soil texture (sand, silt, and clay percentages), temperature, and precipitation. The goal of SEABEM is to provide global farmers, mainly small-scale African farmers, the knowledge they need before practicing and benefiting from cover crops while avoiding the expensive and time-consuming operations that come …
Mix Method Approach Of Measuring Vr As A Pedagogical Tool To Enhance Experimental Learning: Motivation From Literature Survey Of Previous Study, Muhammad Mujtaba Asad, Aisha Naz Ansari, Prathamesh Churi, Antonio José Moreno Guerrero, Anas A. Salameh
Mix Method Approach Of Measuring Vr As A Pedagogical Tool To Enhance Experimental Learning: Motivation From Literature Survey Of Previous Study, Muhammad Mujtaba Asad, Aisha Naz Ansari, Prathamesh Churi, Antonio José Moreno Guerrero, Anas A. Salameh
Institute for Educational Development, Karachi
This research has been experimented on our previous literature review. Technological advancement has prevailed in the modern era from the 20th century. Artificial intelligence and virtual worlds have been created for rapid technological development. This paper is aimed at exploring the effect of virtual reality as a pedagogical tool for enhancing experiential learning among undergraduate students. Considering this, it was a mixed-methods study following the design of sequential exploratory–which includes qualitative followed by quantitative part. The targeted population was undergraduate students taking education programs from Public Sector Universities of Sindh. For the qualitative part, the sample of eight undergraduate students …
Barriers And Enablers For Older Adults Participating In A Home-Based Pragmatic Exercise Program Delivered And Monitored By Amazon Alexa: A Qualitative Study, Paul Jansons, Jackson Fyfe, Jack Dalla Via, Robin M. Daly, Eugene Gvozdenko, David Scott
Barriers And Enablers For Older Adults Participating In A Home-Based Pragmatic Exercise Program Delivered And Monitored By Amazon Alexa: A Qualitative Study, Paul Jansons, Jackson Fyfe, Jack Dalla Via, Robin M. Daly, Eugene Gvozdenko, David Scott
Research outputs 2022 to 2026
Background: The remote delivery and monitoring of individually-tailored exercise programs using voice-controlled intelligent personal assistants (VIPAs) that support conversation-based interactions may be an acceptable alternative model of digital health delivery for older adults. The aim of this study was to evaluate the enablers and barriers for older adults participating in a home-based exercise program delivered and monitored by VIPAs. Method: This qualitative study used videoconferencing to conduct semi-structured interviews following a 12-week, prospective single-arm pilot study in 15 adults aged 60 to 89 years living alone in the community. All participants were prescribed an individualized, brief (10 min, 2–4 times …
A Combined Approach For Private Indexing Mechanism, Pranita Maruti Desai Ms., Vijay Maruti Shelake Mr.
A Combined Approach For Private Indexing Mechanism, Pranita Maruti Desai Ms., Vijay Maruti Shelake Mr.
Journal of Digital Forensics, Security and Law
Private indexing is a set of approaches for analyzing research data that are similar or resemble similar ones. This is used in the database to keep track of the keys and their values. The main subject of this research is private indexing in record linkage to secure the data. Because unique personal identification numbers or social security numbers are not accessible in most countries or databases, data linkage is limited to attributes such as date of birth and names to distinguish between the number of records and the real-life entities they represent. For security reasons, the encryption of these identifiers …
New Embedded Simulation Technology For Smart Internet Of Things, Bohu Li, Xudong Chai, Lin Zhang, Duzheng Qing, Guoqiang Shi, Tingyu Lin, Liqin Guo, Chen Yang, Mu Gu, Zhengxuan Jia, Hui Gong, Zhen Tang
New Embedded Simulation Technology For Smart Internet Of Things, Bohu Li, Xudong Chai, Lin Zhang, Duzheng Qing, Guoqiang Shi, Tingyu Lin, Liqin Guo, Chen Yang, Mu Gu, Zhengxuan Jia, Hui Gong, Zhen Tang
Journal of System Simulation
Abstract: Human society in the new development era and journey is facing the new situation. The operation paradigm, technology and ecosystem of industries related to the national economy and people's livelihood、national security are changing significantly towards the digital, networked, cloud-based and intelligent "Smart Internet of Things". The new embedded simulation technology, with the capabilities of online and continuous analysis, cognition, learning, decision-making, operation and optimization,is urgently needed for the development of "Smart Internet of Things". "Smart Internet of Things" is briefly introduced and the connotation, characteristics and application mode of the new embedded simulation technology are proposed and its architecture, …
Research On Integrated Scheduling Of Agv And Machine In Flexible Job Shop, Kui Chen, Li Bi, Wenya Wang
Research On Integrated Scheduling Of Agv And Machine In Flexible Job Shop, Kui Chen, Li Bi, Wenya Wang
Journal of System Simulation
Abstract: Aiming at the flexible job shop scheduling problem with AGV (automated guided vehicle), a dual resource integrated scheduling optimization model with the objective of minimizing makespan is established. In the process of population initialization, a heuristic initialization method is proposed to improve the quality of population initial solution and accelerate the convergence speed of the algorithm. A hybrid discrete particle swarm optimization algorithm that can effectively avoid premature maturation is proposed by combining the competitive learning mechanism and the random restart mechanism to address the disadvantages of discrete particle swarm algorithms that are prone to premature maturation. Simulation experiments …
Cause Analysis Of Vocs Hazards In Related Areas Based On Object Function Petri Net, Guangqiu Huang, Tiantian Wu
Cause Analysis Of Vocs Hazards In Related Areas Based On Object Function Petri Net, Guangqiu Huang, Tiantian Wu
Journal of System Simulation
Abstract: The multi-resolution formal description based on discrete event system specification (DEVS) has the ability of hierarchical and structured description, but the description of the intelligent behavior inside the module is relatively lacking, while Agent-based modeling can describe the characteristics of individual perception, behavior, communication, cooperation, learning and evolution. Under the framework of multi-resolution modeling, DEVS and Agent model descriptions are combined to provide the description capabilities for events, behaviors, mechanisms, etc. Based on the description of multi-resolution DEVS models, a formal model description method with coupling closure is proposed, which includes the description of the multi-resolution entity-level atomic model …
Research On Algebraic Loop Of Synchronous Generator Simulation Based On Simulink, Shuang Wang, Zhaohui Gao, Siyu Chen, Xiao Tang, Zhan Xi
Research On Algebraic Loop Of Synchronous Generator Simulation Based On Simulink, Shuang Wang, Zhaohui Gao, Siyu Chen, Xiao Tang, Zhan Xi
Journal of System Simulation
Abstract: The problem of algebraic loop is common in Simulink simulation. The existence of algebraic loop will reduce the speed and accuracy of simulation, and even lead to errors in simulation results. Taking the simulation of synchronous generator as an example, the problem of algebraic loop and its elimination method in Simulink simulation are discussed. Starting from the analysis of the basic equations of synchronous generator, the cause of algebraic loop in simulation is discussed, the influence of the algebraic loop on the system simulation is pointed out, using disassembly method and transformation method, focusing on eliminating the algebraic loop, …
Research On 3d Path Planning Algorithm Based On Fast Rrt Algorithm, Zhaoqiang Li, Shiyu Zhang
Research On 3d Path Planning Algorithm Based On Fast Rrt Algorithm, Zhaoqiang Li, Shiyu Zhang
Journal of System Simulation
Abstract: RRT (rapidly exploring random tree) algorithm is a sampling-based path planning algorithm, which can search a path in high-dimensional environment. The traditional RRT algorithm has the problems of low node utilization and large amount of calculation. To solve these problems, the fast RRT* (Quick RRT*) algorithm is improved by optimizing the strategy of reselection of parent node and pruning range, improving the sampling method and introducing adaptive step size, which makes the algorithm time-consuming and path length shorter. At the same time, the node connection screening strategy is added to eliminate the excessive turning angle in the path. …