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Articles 1 - 30 of 24259
Full-Text Articles in Computer Engineering
High Gain Defected Slots 3d Antenna Structure For Millimetre Applications, Arkan Mousa Majeed, Fatma Taher, Taha A. Elwi, Zaid A. Abdul Hassain, Sherif K. El-Diasty, Mohamed Fathy Abo Sree, Sara Yehia Abdel Fatah, Umi Aisah Asli
High Gain Defected Slots 3d Antenna Structure For Millimetre Applications, Arkan Mousa Majeed, Fatma Taher, Taha A. Elwi, Zaid A. Abdul Hassain, Sherif K. El-Diasty, Mohamed Fathy Abo Sree, Sara Yehia Abdel Fatah, Umi Aisah Asli
All Works
The antenna is structured in three dimensions, employing a conductive cylindrical cone as its base. This cone configuration is achieved through the etching of an elliptical slot array onto the antenna. To enhance its performance, a conductive circular reflector is situated beneath the cone, thereby augmenting its gain. The antenna demonstrates operational bandwidth across various frequencies: Ultra-Wideband (UWB) operates at approximately 5 GHz, extending to about 15 GHz; Wideband (WB) is cantered at roughly 20 GHz, while narrowband operates at approximately 27 GHz. Within the frequency range of interest, the antenna's gain varies between 3dBi and 15dBi. Geometric specifications of …
Navigating The Future Advancing Autonomous Vehicles Through Robust Target Recognition And Real-Time Avoidance, Mohammed Ahmed Mohammed Hussein
Navigating The Future Advancing Autonomous Vehicles Through Robust Target Recognition And Real-Time Avoidance, Mohammed Ahmed Mohammed Hussein
Theses and Dissertations
The problem being tackled by this thesis is a very important one and very relevant to our days and times: it is about making improved target recognition and enhanced real-time response skills in AVs under simulated conditions. Our plan is to put some enhanced sensory capabilities into these vehicles and see if that makes them safer and more reliable. We are using as our base a particular object recognition algorithm (YOLOv7) and a particular simulation environment (CARLA). We utilized the CARLA 0.9.14 simulator on Ubuntu 20.04 as a more stable option than the initially used CARLA 0.9.15 on Ubuntu 22.04, …
Design And Implementation Of Uvm-Based Verification Framework For Deep Learning Accelerators, Randa Ahmed Hussein Aboudeif
Design And Implementation Of Uvm-Based Verification Framework For Deep Learning Accelerators, Randa Ahmed Hussein Aboudeif
Theses and Dissertations
Recent advancements in deep learning (DL) have made hardware accelerators, known as deep learning accelerators (DLAs), a preferred solution for numerous high-performance computing (HPC) applications, including speech recognition, computer vision, and image classification. DLAs are composed of hundreds of parallel processing engines to speed up computations and can gain access to pre-trained networks from the cloud or through on-chip memory to implement the DNN inference process. DLA verification is becoming an important and challenging phase. The verification process is required to handle the complex DLA design. Moreover, the reliability of DLAs is critical for assessment as they are involved in …
Speech Coding Based On A Hybrid Approach: Dct, Huffman And Run-Length Coding, Sundos Abdulameer Alazawi, Esraa Jaffar Baker, Shahbaa Mohammed Abdulmaged
Speech Coding Based On A Hybrid Approach: Dct, Huffman And Run-Length Coding, Sundos Abdulameer Alazawi, Esraa Jaffar Baker, Shahbaa Mohammed Abdulmaged
Al-Esraa University College Journal for Engineering Sciences
The exponential expansion of data in the digital world necessitates the development of effective methods for data transmission and storage. Data compression (DC) strategies are suggested to reduce the quantity of data stored or conveyed due to constrained resources. As a result of DC ideas' ability to efficiently use existing storage space and transmission capacity, different methods have been developed in various areas. Speech coding is a lossy method of coding; therefore, the output signal differs slightly from the input signal. Speech coding is useful for message encryption, communication over long distances and speech quality. In the fields of digital …
The Evolution Of The University Of Al-Anbar Urban Planning Based On The Mental Picture's Diversity And The Contemporary Planning Spaces Filling, Ali Abdulsamea Hameed
The Evolution Of The University Of Al-Anbar Urban Planning Based On The Mental Picture's Diversity And The Contemporary Planning Spaces Filling, Ali Abdulsamea Hameed
Al-Esraa University College Journal for Engineering Sciences
This research concentrated on the role of environmental graphic design (EGD) and the place-making idea in the interior environment of Al-Anbar University. To develop an identity being visual for the University of Al-Anbar internal environment (IE) is this goal of project. The search sought to create and enhance the shape of the internal University of Al-Anbar vacuum by reviving the idea of place building. In order to build and filling the internal emptiness of the campus, the identity being visual must also be strengthened. The descriptive analytical approach was chosen since it was best suited to achieve the goal of …
Exploring The Benefits Of Feature Selection Based On Bat Algorithm And Deep Learning In Brain Cancer Diagnosis, Noor Fawzi Shafiq
Exploring The Benefits Of Feature Selection Based On Bat Algorithm And Deep Learning In Brain Cancer Diagnosis, Noor Fawzi Shafiq
Al-Esraa University College Journal for Engineering Sciences
Brain cancer is considered one of the most dangerous types that must be treated as soon as possible. Therefore, it is necessary to detect brain cancer in its early stages to enhance the diagnosis of the condition. This study proposes to combine the bat algorithm (BA) with deep learning methods to identify and classify brain tumors in medical images accurately.
In this paper, the bat algorithm was used to select distinctive features from the input brain images. The Bat Algorithm (BA) is a metaheuristic optimization algorithm that mimics the echolocation behavior of bats. It efficiently explores the feature space to …
An Intelligent System Using Deep Learning For Healthcare Monitoring In Light Of The Covid-19 And Future Pandemics Based On Iot, Sara Salman Qasim, Rajaa J. Khanjar, Jamal Nasir Hasoon, Baesher Abdullateff Abad, Ali Hussein Fadil, Shajan.M. Alsowaidi
An Intelligent System Using Deep Learning For Healthcare Monitoring In Light Of The Covid-19 And Future Pandemics Based On Iot, Sara Salman Qasim, Rajaa J. Khanjar, Jamal Nasir Hasoon, Baesher Abdullateff Abad, Ali Hussein Fadil, Shajan.M. Alsowaidi
Al-Esraa University College Journal for Engineering Sciences
Recently, the Internet of Things has become a compelling research field as a new topic of research in various disciplines, particularly in the field of healthcare, because the Internet of Things is rebuilding modern healthcare systems by integrating technology, economics, and social perspectives. The development of healthcare systems from traditional to more personalized systems in which patients can be easily diagnosed, monitored and treated and many people can be helped. People are treated and cared for remotely and this is what some people need in the crisis the world has been through like COVID-19. This epidemic is caused by the …
Capacity Of Self Compact Concrete Walls Using Attapulgite As A Partial Replacement Of Cement Under One Way And Two Way Action Restriction, Wissam Kadhim Alsaraj, Luma Abdul Ghani Zghair, Akhlas Hashem Mohammed
Capacity Of Self Compact Concrete Walls Using Attapulgite As A Partial Replacement Of Cement Under One Way And Two Way Action Restriction, Wissam Kadhim Alsaraj, Luma Abdul Ghani Zghair, Akhlas Hashem Mohammed
Al-Esraa University College Journal for Engineering Sciences
This investigation about the structural performance of sustainable self-compact concrete walls exposed to eccentric axial regularly dispersed loading, including the effect of aspect ratio (AR) and slenderness ratio (λ) by one-way and two-way action. The experimental program includes testing ten wall panels, the eccentricity of the loading system equivalent to one-sixth of depth. These wall panels are separated into four groups, each one consisting of three specimens. first and second groups clarify the aspect ratio (H/L) effect. The results indicated for decreasing AR from (0.75 to 0.625), (0.625 to 0.5), and (0.75 to 0.5), the increase of final load is …
A Study On Improving The Accuracy And Effectiveness Of Similarity Detection Processes In Text Files Using Nlp Techniques, Noor Abdulmuttaleb Jaafar
A Study On Improving The Accuracy And Effectiveness Of Similarity Detection Processes In Text Files Using Nlp Techniques, Noor Abdulmuttaleb Jaafar
Al-Esraa University College Journal for Engineering Sciences
The rapid expansion of the Internet has revolutionized access to information, especially in the area of unstructured data, most of which consists of textual content. While instant access to information brings many advantages, it has also given rise to a prevalent problem – plagiarism. Copying and reusing materials without proper permission poses a significant threat to academic integrity and integrity. Rates of plagiarism, especially in academic and scientific publications, have risen with the advent of the Internet, reaching alarming levels, such as 60% in student projects. This study examines the proposed model that includes computation of similarity using cosine coefficients, …
Unveiling The Hidden Threat: How Wireless Networks Fuel Serious Cyber Attacks, Ibtesam Jomaa Hawi
Unveiling The Hidden Threat: How Wireless Networks Fuel Serious Cyber Attacks, Ibtesam Jomaa Hawi
Al-Esraa University College Journal for Engineering Sciences
The spread of wireless networks has led to an increase in serious cyber attacks due to their weak architecture. This article focuses on reevaluating cybersecurity in wireless network technology by integrating statistical information detection methods and artificial intelligence (AI) algorithms. To construct a wireless networking scenario that accurately reflects real-life conditions, we created a data fabrication that included four pre-existing anomalies as well as four newly introduced anomalies. The synthetic dataset created from these generation processes contains 20 thousand distinguishable values, which are later divided into training and validation sets. Using the strategy described before, we began to analyze the …
Towards Rare Event And Anomaly Prediction In Manufacturing: Bridging Methodological Gaps In Industrial Applications, Chathurangi Shyalika, Ruwan Wickramarachchi, Amit Sheth
Towards Rare Event And Anomaly Prediction In Manufacturing: Bridging Methodological Gaps In Industrial Applications, Chathurangi Shyalika, Ruwan Wickramarachchi, Amit Sheth
Publications
Rare event prediction is critical in industrial applications, including real-world Industry 4.0 applications. These events, defined by their low occurrence frequency, are often difficult to predict due to the skewed data distribution, which complicates modeling and evaluation. In our research, we provide a comprehensive review of current approaches to rare event prediction across four key dimensions: rare event data, data processing techniques, algorithmic approaches, and evaluation methodologies [1]. By analyzing diverse datasets with multiple modalities, including numerical, image, text, and audio, we categorize the primary challenges and present the gaps in current research. Specifically, we present three novel research contributions …
A Benchmark Knowledge Graph Of Driving Scenes For Knowledge Completion Tasks, Ruwan Wickramarachchi, Cory Henson, Amit Sheth
A Benchmark Knowledge Graph Of Driving Scenes For Knowledge Completion Tasks, Ruwan Wickramarachchi, Cory Henson, Amit Sheth
Publications
Knowledge graph completion (KGC) is a problem of significant importance due to the inherent incompleteness in knowledge graphs (KGs). The current approaches for KGC using link prediction (LP) mostly rely on a common set of benchmark datasets that are quite different from real-world industrial KGs. Therefore, the adaptability of current LP methods for real-world KGs and domain-specific ap- plications is questionable. To support the evaluation of current and future LP and KGC methods for industrial KGs, we introduce DSceneKG, a suite of real-world driving scene knowledge graphs that are currently being used across various industrial applications. The DSceneKG is publicly …
Causal Neuro-Symbolic Ai For Root Cause Analysis In Smart Manufacturing, Utkarshani Jaimini, Cory Henson, Amit Sheth
Causal Neuro-Symbolic Ai For Root Cause Analysis In Smart Manufacturing, Utkarshani Jaimini, Cory Henson, Amit Sheth
Publications
Root cause analysis is the process of investigating the cause of a failure and providing measures to prevent future failures. It is an active area of research due to the complexities in manufacturing production lines and the vast amount of data that requires manual inspection. We present a combined approach of causal neuro-symbolic AI for root cause analysis to identify failures in smart manufacturing production lines. We have used data from an industry-grade rocket assembly line and a simulation package to demonstrate the effectiveness and relevance of our approach.
Visual Causal Question And Answering With Knowledge Graph Link Prediction, Utkarshani Jaimini, Cory Henson, Amit Sheth
Visual Causal Question And Answering With Knowledge Graph Link Prediction, Utkarshani Jaimini, Cory Henson, Amit Sheth
Publications
The ability to answer causal questions is important for any system that requires robust scene under- standing. In this demonstration, we develop a prototype system that leverages our causal link prediction framework, CausalLP. CausalLP framework uses a visual causal knowledge graph and associated knowledge graph embedding for two visual causal question and answering tasks- (i) causal explanation and (ii) causal prediction. In the live demonstration sessions, the participants will be invited to test the efficiency and effectiveness of the system for visual causal question and answering.
Causal Knowledge Graph For Scene Understanding In Autonomous Driving, Utkarshani Jaimini, Cory Henson, Amit Sheth
Causal Knowledge Graph For Scene Understanding In Autonomous Driving, Utkarshani Jaimini, Cory Henson, Amit Sheth
Publications
The current approaches to autonomous driving focus on learning from observation or simulated data. These approaches are based on correlations rather than causation. For safety-critical applications, like autonomous driving, it’s important to represent causal dependencies among variables in addition to the domain knowledge expressed in a knowledge graph. This will allow for a better understanding of causation during scenarios that have not been observed, such as malfunctions or accidents. The causal knowledge graph, coupled with domain knowledge, demonstrates how autonomous driving scenes can be represented, learned, and explained using counterfactual and intervention reasoning to infer and understand the behavior of …
Ontology Design Metapattern For Relationtype Role Composition, Utkarshani Jaimini, Ruwan Wickramarachchi, Cory Henson, Amit Sheth
Ontology Design Metapattern For Relationtype Role Composition, Utkarshani Jaimini, Ruwan Wickramarachchi, Cory Henson, Amit Sheth
Publications
RelationType is a metapattern that specifies a property in a knowledge graph that directly links the head of a triple with the type of the tail. This metapattern is useful for knowledge graph link prediction tasks, specifically when one wants to predict the type of a linked entity rather than the entity instance itself. The RelationType metapattern serves as a template for future extensions of an ontology with more fine-grained domain information.
Prototyping Interactive Tactile Digital Logic Simulations: A Hybrid Approach, Logan Bateman
Prototyping Interactive Tactile Digital Logic Simulations: A Hybrid Approach, Logan Bateman
MS in Computer Science Project Reports
Tactile exhibits are common in museums and on the walls of university halls. However, few (if any) tools exist for creating tactile exhibits for teaching digital logic or computing concepts. This project implemented a framework for creating tactile digital logic simulation exhibits, with a focus on rapid prototyping and distributed architecture. Prototyping allows for fast iteration, with the ability to simulate unlimited hardware components such as buttons, light emitting diodes (LEDs), and other input or output devices. Through the abstraction of implementations and a distributed communication protocol, switching to real hardware is seamless and works in tandem with simulated hardware. …
Towards An Iot-Enabled Digital Earth For Sdgs: The Data Quality Challenge, Msb Syed, Paula Kelly, Paul Stacey, Damon Berry
Towards An Iot-Enabled Digital Earth For Sdgs: The Data Quality Challenge, Msb Syed, Paula Kelly, Paul Stacey, Damon Berry
Articles
Digital Earth (DE), a technology offering real-time visualisation of Earth's processes, has shown promising results in aiding decision-making for a sustainable world, raising awareness about individual impacts on our planet, and supporting the United Nations Sustainable Development Goals (UN SDGs) agenda. However, both DE and SDGs face a common obstacle: Data Quality (DQ). This review investigates the challenge of DQ in the context of DE for SDGs and explores how IoT can address this challenge and extend the reach of DE to support SDGs. Furthermore, the study discusses three core aspects; first, the potential of IoT as a data source …
Mouasla: Integrating Iot And Ai For An Intelligent Trans-Portation Payment System, Hany El-Ghaish Dr., Haitham Darweesh
Mouasla: Integrating Iot And Ai For An Intelligent Trans-Portation Payment System, Hany El-Ghaish Dr., Haitham Darweesh
Journal of Engineering Research
Smart payment systems have emerged as vital components of global public transportation, offering passengers a more efficient and convenient fare payment method. The Mouasla system addresses traditional payment limitations through IoT devices and AI-backed backend services. Features of Mouasla It employs RFID smart card and IoT features from the device to ensure all components such as a card reader function, driver functions, charging units function, and payment are combined with this system alongside a mobile application for quick access backend services. Each passenger dataset is analyzed by an AI-powered backend service to provide insight that can be used to improve …
A Parallel Methodology For Early Fake News Detection Based On Hybrid Features On Social Media, Asmaa Mohemed Elsaieed Dr
A Parallel Methodology For Early Fake News Detection Based On Hybrid Features On Social Media, Asmaa Mohemed Elsaieed Dr
Journal of Engineering Research
The increased use of social media platforms has made it easier to publish and distribute news items, but it has also opened up new opportunities for distributing fake news. Fake news is information that has been written with the goal of misleading or deceiving readers. As a result, there is a need for efficient false news identification tools where the information can be gathered from the text of posts or from publicly available social data (such as user information or feedback on articles or the social network). The detection of fake news in its early stages is a major challenge. …
Early Autism Detection Using Machine Learning Techniques: A Review, Shaimaa Fouad Sharabash, Hany Ali Elghaish
Early Autism Detection Using Machine Learning Techniques: A Review, Shaimaa Fouad Sharabash, Hany Ali Elghaish
Journal of Engineering Research
Abstract- This article provides a comprehensive literature review on technology-based interventions for Autism Spectrum Disorder (ASD). It emphasizes the challenges in early detection and treatment of ASD, highlighting the spectrum nature of the disorder. The review discusses traditional diagnostic strategies such as behavioural observations, developmental screening and medical testing and goes on to explore advanced machine learning and deep learning models, including SVM, k-nearest neighbours, decision tree and LSTM, for predicting ASD characteristics in toddlers and children. Additionally, recent techniques employing more than ten strategies for ASD detection are summarized and various datasets used in early detection are described. The …
Digital Assessments For Children And Adolescents With Adhd: A Scoping Review, Franceli L. Cibrian, Elissa M. Monteiro, Kimberley D. Lakes
Digital Assessments For Children And Adolescents With Adhd: A Scoping Review, Franceli L. Cibrian, Elissa M. Monteiro, Kimberley D. Lakes
Engineering Faculty Articles and Research
Introduction: In spite of rapid advances in evidence-based treatments for attention deficit hyperactivity disorder (ADHD), community access to rigorous gold-standard diagnostic assessments has lagged far behind due to barriers such as the costs and limited availability of comprehensive diagnostic evaluations. Digital assessment of attention and behavior has the potential to lead to scalable approaches that could be used to screen large numbers of children and/or increase access to high-quality, scalable diagnostic evaluations, especially if designed using user-centered participatory and ability-based frameworks. Current research on assessment has begun to take a user-centered approach by actively involving participants to ensure the development …
2024 Gateway Magazine, College Of Computing, Michigan Technological University
2024 Gateway Magazine, College Of Computing, Michigan Technological University
College of Computing Annual Magazines
Table of Contents
- 50 Years of Computer Science at Michigan Tech
- Data Science for a Changing Planet
- Healthcare Transformed
- Mechatronics Matters
- Powered by Michigan Tech Talent
- Esports: Bringing Everything Great about Sports to More People
- The Michigander Scholars Program: Electrifying Careers in Michigan
- College of Computing News
Instructional Systems Design: The Diffusion And Adoption Of Technology: (Volume 2), Cassandra Celaya (Author), Pamela J. Downing (Author), Jessica Shifflett (Author), Debbie Gdula (Author), Tracie Barr (Author), Miguel Ramlatchan (Author & Editor)
Instructional Systems Design: The Diffusion And Adoption Of Technology: (Volume 2), Cassandra Celaya (Author), Pamela J. Downing (Author), Jessica Shifflett (Author), Debbie Gdula (Author), Tracie Barr (Author), Miguel Ramlatchan (Author & Editor)
University Administration Bookshelf
Instructional designers, instructional systems designers, and other educational technologists are, by their nature, innovators. These professionals apply and extend the applied science of learning, systems, communication, and instructional design theory to help students learn. Technology in some capacity is used to make the connections between subject matter experts, teachers, instructors, and their learners. It is common for instructional designers to seek new tools, techniques, and innovations for the improvement of learning, access, quality, and student satisfaction. However, the adoption and diffusion of new educational technology and innovation is a complex process that depends on many variables. Understanding these processes and …
2024 (Fall) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department
2024 (Fall) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department
ENSI Informer Magazine Archive
The ENSI Informer Magazine published in the fall of 2024.
Feasibility Of Creating A Non-Profit And Nongovernmental Organization Cybersecurity Incident Dataset Repository Using Osint, Stanley Mierzwa, Iassen Christov
Feasibility Of Creating A Non-Profit And Nongovernmental Organization Cybersecurity Incident Dataset Repository Using Osint, Stanley Mierzwa, Iassen Christov
Center for Cybersecurity
Organizations of all types are prone to cybersecurity and information security attacks. Non-Profit Organizations (NPOs) and Non-Governmental Organizations (NGOs) are not exempt from using information technology solutions and, thus, have been the recipient victims of cyber attackers. There exist many areas and venues where data are collected to report back annually on the status and numbers of cybersecurity attacks against many sectors of our society. The Department of Homeland Security (DHS) Cybersecurity and Infrastructure Security Agency (CISA) catalogs sixteen critical sectors that are considered vital to the United States. However, finding where the NPO and NGO community should reside with …
Utilizing A Virtual Firewall Appliance For Introducing And Reinforcing The Concepts And Implementation Of Devices To Improve Security In A Computing Environment, Stanley Mierzwa, Christopher Eng
Utilizing A Virtual Firewall Appliance For Introducing And Reinforcing The Concepts And Implementation Of Devices To Improve Security In A Computing Environment, Stanley Mierzwa, Christopher Eng
Center for Cybersecurity
The educational realm of higher education cybersecurity curriculum continues to evolve to provide more opportunities for experiential hands-on and work role-related practical applications of technology solutions. Gaining more excellent competencies is quickly becoming a standard requirement for programs with the National Security Agency Center of Academic Excellence designation. The work roles of cybersecurity include a variety of knowledge, skills, and abilities, depending on the activity category or task. Firewalls have been a staple cybersecurity, network security, and information security device and strategy to protect organization networks and computing environments. This paper will provide details and a description of the effort …
Computer Vision In A Robotic Arm, Jack Maxwell
Computer Vision In A Robotic Arm, Jack Maxwell
College of Engineering Summer Undergraduate Research Program
We used a machine learning-based object detection algorithm to give a robotic arm the ability to "see" with its camera.
Ai Integration For Intellisar, Eric Lee
Ai Integration For Intellisar, Eric Lee
College of Engineering Summer Undergraduate Research Program
IntelliSAR aims to integrate AI techniques into Search and Rescue (SAR) operations, building on the foundation laid by previous SURP initiatives. IntelliSAR’s core elements include a front-end for SAR forms, a comprehensive command center dashboard, and AI-driven components designed to enhance SAR decision-making. During summer, our efforts focused on streamlining the user interface by integrating various machine learning models into a unified, interactive dashboard. Our models predict critical factors such as missing persons’ behavior, potential locations, and resource requirements, with the goal of optimizing response times and improving the effectiveness of SAR teams.
Wearable Sensing Systems And Data Analytics For Pressure Sensing Socket Prostheses, Stacey Le, Mio Nakagawa
Wearable Sensing Systems And Data Analytics For Pressure Sensing Socket Prostheses, Stacey Le, Mio Nakagawa
College of Engineering Summer Undergraduate Research Program
Prosthetics have been widely used as the primary solution for lower limb amputations, but residual limb volume fluctuations have posed challenges to the effectiveness and comfortability of these devices. In this project, we aim to observe pressure distribution patterns in the prosthetic socket during gait using sensing technology and investigate the performance of different machine learning algorithms on determining good or bad fit.