Computer Engineering Commons^™

Niche: A Curated Dataset Of Engineered Machine Learning Projects In Python, Ratnadira Widyasari, Zhou Yang, Ferdian Thung, Sheng Qin Sim, Fiona Wee, Camellia Lok, Jack Phan, Haodi Qi, Constance Tan, David Lo, David Lo

Research Collection School Of Computing and Information Systems

Machine learning (ML) has gained much attention and has been incorporated into our daily lives. While there are numerous publicly available ML projects on open source platforms such as GitHub, there have been limited attempts in filtering those projects to curate ML projects of high quality. The limited availability of such a high-quality dataset poses an obstacle to understanding ML projects. To help clear this obstacle, we present NICHE, a manually labelled dataset consisting of 572 ML projects. Based on the evidence of good software engineering practices, we label 441 of these projects as engineered and 131 as non-engineered. This …

Analysis And Implementation Of A New High-Buck Dc-Dc Converter With Interleaved Output Inductors And Soft Switching Capability, Sajad Ghabeli Sani, Mohamad Reza Banaei, Seyed Hossein Hosseini

Turkish Journal of Electrical Engineering and Computer Sciences

This paper proposes an innovative structure for DC-DC converters with high buck gain by using a lower number of elements. The converter provides highly efficient output power and an extended output voltage range. In addition, the distribution of output current between two inductors and the soft-switching capability of the power switches have made the converter suitable for applications that require high output current. All power switches accomplish the ZVZCS (zero-voltage and zero-current switching) condition with the aid of a small auxiliary inductor (Lx), which charges and discharges parallel capacitors of main switches to provide soft-switching conditions. Thus, the switching losses …

Integration Of Neural Network And Distance Relay To Improve The Fault Localization On Transmission Lines, Linh Tran

Turkish Journal of Electrical Engineering and Computer Sciences

Power transmission lines are integral and very important components of power systems. Because of the length of these lines and the complexity of the power grids, the lines may encounter various incidents such as lightning strike, shortage, and breakage. When an incident or a fault occurs, a fast process of identification, localization, and isolation of the fault is desired. An accurate fault localization would have a great impact in reducing the restoration time of the system. One of the most popular solutions for fault detection and localization is the distance relays using the impedance-based algorithms. However, these relays are still …

Deep Learning-Based Turkish Spelling Error Detection With A Multi-Class False Positive Reduction Model, Burak Aytan, Cemal Okan Şakar

Turkish Journal of Electrical Engineering and Computer Sciences

Spell checking and correction is an important step in the text normalization process. These tasks are more challenging in agglutinative languages such as Turkish since many words can be derived from the root word by combining many suffixes. In this study, we propose a two-step deep learning-based model for misspelled word detection in the Turkish language. A false positive reduction model is integrated into the system to reduce the false positive predictions originating from the use of foreign words and abbreviations that are commonly used in Internet sharing platforms. For this purpose, we create a multi-class dataset by developing a …

Breath Analysis For Detection Of Lung Cancer With Hybrid Sensor-Based Electronic Nose, Ümi̇t Özsandikcioğlu, Ayten Atasoy

Turkish Journal of Electrical Engineering and Computer Sciences

Lung cancer has the highest death rates among all types of cancer worldwide. Detection of lung cancer in its early stages significantly increases the survival rate. In this study, the aim is to improve the lung cancer detection performance of electronic noses (e-noses) with breath analysis by using two different types of gas sensor-based e-nose. The developed e-nose system consists of 14 quartz crystal microbalance (QCM) sensors and 8 metal oxide semiconductor (MOS) sensors. Breath samples were collected from a total of 100 volunteers, including 60 patients with lung cancer, 20 healthy nonsmokers, and 20 healthy smokers, and were classified …

An Analytical Solution Of Fractional Order Pi Controller Design For Stable/Unstable/Integrating Processes With Time Delay, Erdal Çökmez, İbrahi̇m Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

This paper aims to put forward an analytical solution for tuning parameters of a fractional order PI (FOPI) controller for stable, unstable, and integrating processes with time delay. Following this purpose, the analytical weighted geometrical center (AWGC) method has been extended to the design of fractional order PI controllers. To apply AWGC, the stability equations of the closed-loop system are written in terms of process and fractional order PI controller parameters. With the proposed method, the centroid can be calculated analytically, and the controller parameters can be easily calculated without the need of repetitive drawings of the stability boundary regions. …

An Efficient Deep Learning Architecture For Turkish Lira Recognition And Counterfeit Detection, Burak İyi̇kesi̇ci̇, Ergun Erçelebi̇

Turkish Journal of Electrical Engineering and Computer Sciences

Banknote counterfeiting is a common practice worldwide. Due to the recent developments in technology, banknote imitation has become easier than before. There are different kinds of algorithms developed for the detection of counterfeit banknotes for different countries in the literature. The earlier algorithms utilized classical image processing techniques where the implementations of machine learning and deep learning algorithms appeared with the developments in the artificial intelligence field as well as the computer hardware. In this study, a novel convolutional neural networks-based deep learning algorithm has been developed that detects counterfeit Turkish Lira banknotes and their denominations using the banknote images …

Unbiased Federated Learning In Energy Harvesting Error-Prone Channels, Zeynep Çakir, Eli̇f Tuğçe Ceran Arslan

Turkish Journal of Electrical Engineering and Computer Sciences

Federated learning (FL) is a communication-efficient and privacy-preserving learning technique for collaborative training of machine learning models on vast amounts of data produced and stored locally on the distributed users. This paper investigates unbiased FL methods that achieve a similar convergence as state-of-the-art methods in scenarios with various constraints like an error-prone channel or intermittent energy availability. For this purpose, we propose FL algorithms that jointly design unbiased user scheduling and gradient weighting according to each user's distinct energy and channel profile. In addition, we exploit a prevalent metric called the age of information (AoI), which quantifies the staleness of …

Quadratic Programming Based Partitioning For Block Cimmino With Correct Value Representation, Zuhal Taş, Fahreddi̇n Şükrü Torun

Turkish Journal of Electrical Engineering and Computer Sciences

The block Cimmino method is successfully used for the parallel solution of large linear systems of equations due to its amenability to parallel processing. Since the convergence rate of block Cimmino depends on the orthogonality between the row blocks, advanced partitioning methods are used for faster convergence. In this work, we propose a new partitioning method that is superior to the state-of-the-art partitioning method, GRIP, in several ways. Firstly, our proposed method exploits the Mongoose partitioning library which can outperform the state-of-the-art methods by combining the advantages of classical combinatoric methods and continuous quadratic programming formulations. Secondly, the proposed method …

More Wifi For Everyone: Increasing Spectral Efficiency In Wifi6 Networks Using A Distributed Obss/Pd Mechanism, Ali̇ Karakoç, Hüseyi̇n Bi̇rkan Yilmaz, Mehmet Şükrü Kuran

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, we propose a distributed algorithm that determines effective Overlapping Basic Service Set/Preamble Detection (OBSS/PD) threshold levels in each WiFi6 device to maximize the total throughput by increasing the spectral efficiency. Within WiFi6 standard, OBSS/PD mechanism is introduced to increase the overall efficiency of WiFi networks by tuning the receiver sensitivity as well as the transmission power. In a nutshell, the proposed algorithm, RACEBOT, tunes the hearing (i.e. reception) and speaking (i.e. transmission) parameters of each WiFi device individually for the betterment of the WiFi experience of all WiFi networks in a neighborhood. WiFi experience is not only …

Systemic Risk Analysis Of Human Factors In Phishing, Mark Guilford

Engineering Management & Systems Engineering Theses & Dissertations

The scope of this study is the systemic risk of the role of humans in the risk of phishing. The relevance to engineering managers and systems engineers of the risks of phishing attacks is the theft of data which has significantly increased in the past couple of years. Phishing has become a systemic persistent threat to all internet users. Understanding the role of humans in phishing from a systemic perspective is a critical objective towards creating a strong defense against complex and manipulative phishing attacks. The systemic view of phishing concentrates on how phishing affects the entire organizational system, not …

Roboretrieve--In A Dual Role As A Hand-Held Surgical Robot And A Collaborative Robot End-Effector To Perform Spillage-Free Specimen Retrieval In Laparoscopy, Siqin Dong

Mechanical & Aerospace Engineering Theses & Dissertations

Recent advances in surgical robotics attempt to overcome limitations of manual surgery by augmenting the surgeon’s capabilities while performing suturing, incision, retraction, and retrieval tasks. This dissertation presents novel approaches for spillage-free specimen retrieval in confined spaces, targeted toward the surgical domain of minimally invasive robotic surgery. The retrieval task involves extraction of a resected specimen, residing in the abdominal cavity, completely outside of the patient’s body. A major challenge in this context is the spillage of content being retrieved, which may cause dissemination of malignancy. To address this challenge, this dissertation develops RoboRetrieve, a portable hand-held robot that …

Wearable Sensor Gait Analysis For Fall Detection Using Deep Learning Methods, Haben Girmay Yhdego

Electrical & Computer Engineering Theses & Dissertations

World Health Organization (WHO) data show that around 684,000 people die from falls yearly, making it the second-highest mortality rate after traffic accidents [1]. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. In light of the recent widespread adoption of wearable sensors, it has become increasingly critical that fall detection models are developed that can effectively process large and sequential sensor signal data. Several researchers have recently developed fall detection algorithms based on wearable sensor data. However, real-time fall detection remains challenging because of the wide …

Probabilistic Verification For Modular Network-On-Chip Systems, Jonah W. Boe

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Modeling physical systems with formal analysis tools can help in the design of more fault-proof systems, by helping to determine if unpredictable or unwanted behavior may occur. Probabilistic verification further advances such processes, by providing quantitative information about the system. More complex systems can especially benefit from formal modeling and verification, as testing the physical system in every possible condition manually, can be extremely complex, and often impossible.

There is a growing interest in the application of Network-on-Chip (NoC) systems. NoCs can help simplify communication between the subsystems of many technologies, including the ever more complex multicore processors being produced. …

Opensim-Based Musculoskeletal Modeling: Foundation For Interactive Obstetric Simulator, Bahador Dodge

Electrical & Computer Engineering Theses & Dissertations

The use of mathematical and computational models to understand complex biological systems, such as the human birth process, is a rapidly growing field in medicine. These models can be used to optimize and personalize medical treatments for individual patients, enhance training, and aid in educational efforts. While recent advancements in healthcare, particularly in obstetrics, have improved care for mothers and babies, studies and government reports indicate a rising rate of maternal mortality in the United States.

Despite this rising trend, there is a lack of detailed studies concerning the use of modeling and simulation to develop an interactive obstetrics simulator …

2023 (Spring) Ensi Informer Magazine, Morehead State University. Engineering Sciences Department

ENSI Informer Magazine Archive

The ENSI Informer Magazine published in the spring of 2023.

User Classification Based On Mouse Dynamic Authentication Using K-Nearest Neighbor, Didih Rizki Chandranegara, Anzilludin Ashari, Zamah Sari, Hardianto Wibowo, Wildan Suharso

Makara Journal of Technology

Mouse dynamics authentication is a method for identifying a person by analyzing the unique pattern or rhythm of their mouse movement. Owing to its distinctive properties, such mouse movements can be used as the basis for security. The development of technology is followed by the urge to keep private data safe from hackers. Therefore, increasing the accuracy of user classification and reducing the false acceptance rate (FAR) are necessary to improve data security. In this study, we propose to combine the K-nearest neighbor method and simple random sampling and obtain a sample from a dataset to improve the classification of …

Power Amplifier Based On Composite Injection-Voltaic Transistors, Nodira Batirdjanovna Alimova

Chemical Technology, Control and Management

The problem of high-current radio engineering devices is related to the fact that the use of high-power transistors and other semiconductor devices is limited by such a phenomenon as a secondary breakdown, in which there is a sharp decrease in the voltage on the device with simultaneous internal current lacing, and the device fails. To solve the problem of secondary breakdown, schemes have been proposed that operate stably at reverse voltage values 4-5 times higher than usual and at power dissipation 2-3 times higher than the maximum allowable power for an individual device. The problem is proposed to be solved …

Methods And Algorithms For Monitoring And Prediction Of Various Fire Hazardous Situations, Mizaakbar Xakkulmirzayevich Hudayberdiyev, Oybek Zokirovich Koraboshev

Chemical Technology, Control and Management

This article analyzes emergency situations arising from natural disasters (fires, explosions, earthquakes, floods, landslides, etc.) and man-made accidents. The event in which the values of fire risks in the area decrease uniformly and at the same time the amount of fire risks is minimal is considered optimal. Models, methods, and logistic regression algorithm have been used to predict fire hazard situations and identify potential fire safety measures.

Motion Control Simulation Of A Hexapod Robot, Weishu Zhan

Dartmouth College Master’s Theses

This thesis addresses hexapod robot motion control. Insect morphology and locomotion patterns inform the design of a robotic model, and motion control is achieved via trajectory planning and bio-inspired principles. Additionally, deep learning and multi-agent reinforcement learning are employed to train the robot motion control strategy with leg coordination achieves using a multi-agent deep reinforcement learning framework. The thesis makes the following contributions:

First, research on legged robots is synthesized, with a focus on hexapod robot motion control. Insect anatomy analysis informs the hexagonal robot body and three-joint single robotic leg design, which is assembled using SolidWorks. Different gaits are …

Infrastructure-As-Code: Automating The Deployment On Aws Using Terraform, Srikar Pratap

Masters Projects

In my master’s project, I used Terraform to create a scalable infrastructure on Amazon Web Services (AWS) for my personal website. Terraform is an open-source infrastructure-as-code (IAC) tool that allows you to create, manage and provision infrastructure resources, such as virtual machines, storage accounts, networks, and more, across multiple cloud providers and on-premises data centers using a declarative configuration language. A scalable infrastructure is important because it enables a system or application to handle increasing amounts of traffic or workload without experiencing performance issues or downtime. It ensures that the system remains responsive, available, and reliable as an organization grows …

Analysis Of The Adherence Of Mhealth Applications To Hipaa Technical Safeguards, Bilash Saha

Master of Science in Information Technology Theses

The proliferation of mobile health technology, or mHealth apps, has made it essential to protect individual health details. People now have easy access to digital platforms that allow them to save, share, and access their medical data and treatment information as well as easily monitor and manage health-related issues. It is crucial to make sure that protected health information (PHI) is effectively and securely transmitted, received, created, and maintained in accordance with the rules outlined by the Health Insurance Portability and Accountability Act (HIPAA), as the use of mHealth apps increases. Unfortunately, many mobile app developers, particularly those of mHealth …

College Of Business Prospective Students Application, Caden Bewley, Joseph Morton, Brayden Reddin, Marvin Martinez, Ashlyn Ward

ATU Scholars Symposium

The College of Business wanted a webpage that makes applying to one of their majors more user-friendly. Currently, incoming freshmen tend to choose the wrong major as the application process can be confusing. They needed to reduce the redundancy of inputting information, so they asked for the application on their webpage to auto-fill on Arkansas Tech University's application webpage.

Graduate Faculty Directory, Christopher Andrews, Cody Mckenney, Drake Traylor, Joseph Freeman

ATU Scholars Symposium

The Graduate College would like to update the current faculty search page to filter search results by Department and Research in addition to Name. With the current system, a person who wanted to find an unknown professor based upon a department or an interest in research topic would be unable to search because the only option is to type the professor's name. We have created a website linked to a database containing graduate faculty that is able to search by name, filter by department, and search through the professors' listed research topics. This website will be much more useful and …

Encrypted Malicious Network Traffic Detection Using Machine Learning, Niklas Knipschild

Symposium of Student Scholars

The research project aims to find ways to detect malicious packets inside encrypted network traffic. In addition to this goal maintaining user privacy is a priority. As encryption has become less expensive to implement more and more network traffic is encrypted. Currently, 90% of all network traffic is encrypted, and this trend is expected to increase. The creators of malware areemploying various methods to ensure delivery of their malware, including encryption. One proposed method to combat this suggests implementing machine learning with various algorithms to analyze packet attributes to determine if they contain malware, without actually knowing what's inside …

Ransomware: Evaluation Of Mitigation And Prevention Techniques, Juanjose Rodriguez-Cardenas

Symposium of Student Scholars

Ransomware is classified as one of the main types of malware and involves the design of exploitations of new vulnerabilities through a host. That allows for the intrusion of systems and encrypting of any information assets and data in order to demand a sum of payment normally through untraceable cryptocurrencies such as Monero for the decryption key. This rapid security threat has put governments and private enterprises on high alert and despite evolving technologies and more sophisticated encryption algorithms critical assets are being held for ransom and the results are detrimental, including the recent Colonial Pipeline ransomware attack in 2021 …

A Study Of Iot-Optimized Low Power Asset Tracking With Cloud-Enabled Lorawan, Fatima Salman

Symposium of Student Scholars

The world of technology is expanding very quickly today, including technologies like cloud-based asset monitoring, but this makes it difficult to keep up with this technology's development and many other things. It is possible to monitor and manage your assets remotely with a cloud-based system thanks to its many features. The lifecycle of any commodity, including inventory, machinery, vehicles, and real estate, can be tracked using this kind of cloud-based system. Wide-area networks can be used to send data with the aid of low-power wide-area network (LPWAN) technologies like LoRa, SigFox, and NB-IoT. This project will examine traditional, cloud-based, LPWAN-based …

Models Of Team Structure In Information Security Incident Investigation, Fayzullajon Botirov

Chemical Technology, Control and Management

This article discusses the models of the group structure in the investigation of information security incidents, contradictions in the investigation of information security incidents, methods for assessing information security incidents at the enterprise, processes for assessing information security incidents based on its factors.

Detection Optimization Of Rare Attacks In Software-Defined Network Using Ensemble Learning, Ahmed M. El-Shamy, Nawal A. El-Fishawy, Gamal M. Attiya, Mokhtar Ahmed

Mansoura Engineering Journal

Software-defined networking (SDN) is a highly flexible architecture that automates and facilitates network configuration and management. Intrusion detection systems (IDS) are becoming essential components in the network to detect malicious attacks and suspicious activities by continuously monitoring network traffic. Integration between SDN and machine learning (ML) techniques is extensively used to build an effective IDS against all potential cyber-attacks that aim at breaking the network security policy and stealing valuable data. Implementing an IDS based on SDN and ML has the advantage of managing traffic dynamically and fully autonomously to provide high protection against security threats. The main objective of …

Ransomware: What Is Ransomware, And How To Prevent It, Brandon Chambers

Cybersecurity Undergraduate Research Showcase

This research paper answers the question, “What is Ransomware, and How to prevent it?”. This paper will discuss what ransomware is, its history about ransomware, how ransomware attacks Windows systems, how to prevent ransomware, how to handle ransomware once it is already on the network, ideas for training professionals to avoid ransomware, and how anti-virus helps defend against ransomware. Many different articles, case studies, and professional blogs will be used to complete the research on this topic.