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2022

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Articles 1141 - 1170 of 1255

Full-Text Articles in Computer Engineering

An Experimental Study Towards Underwater Propulsion System Using Structure Borne Traveling Waves, Shreyas Suhas Gadekar Jan 2022

An Experimental Study Towards Underwater Propulsion System Using Structure Borne Traveling Waves, Shreyas Suhas Gadekar

Dissertations, Master's Theses and Master's Reports

The method of generating steady-state structure-borne traveling waves underwater in an infinite media creates abundant opportunities in the field of propulsive applications, and they are gaining attention from several researchers. This experimental study provides a framework for harnessing traveling waves in a 1D beam immersed under quiescent water using two force input methods and providing a motion to an object floating on the surface of the water.

In this study, underwater traveling waves are tailored using structural vibrations at five different frequencies in the range of 10Hz to 300Hz. The resulting fluid motion provides a propulsive thrust that moves a …


Developing Reactive Distributed Aerial Robotics Platforms For Real-Time Contaminant Mapping, Joshua Ashley Jan 2022

Developing Reactive Distributed Aerial Robotics Platforms For Real-Time Contaminant Mapping, Joshua Ashley

Theses and Dissertations--Electrical and Computer Engineering

The focus of this research is to design a sensor data aggregation system and centralized sensor-driven trajectory planning algorithm for fixed-wing aircraft to optimally assist atmospheric simulators in mapping the local environment in real-time. The proposed application of this work is to be used in the event of a hazardous contaminant leak into the atmosphere as a fleet of sensing unmanned aerial vehicles (UAVs) could provide valuable information for evacuation measures. The data aggregation system was designed using a state-of-the-art networking protocol and radio with DigiMesh and a process/data management system in the ROS2 DDS. This system was tested to …


Core Point Pixel-Level Localization By Fingerprint Features In Spatial Domain, Xueyi Ye, Yuzhong Shen, Maosheng Zeng, Yirui Liu, Huahua Chen, Zhijing Zhao Jan 2022

Core Point Pixel-Level Localization By Fingerprint Features In Spatial Domain, Xueyi Ye, Yuzhong Shen, Maosheng Zeng, Yirui Liu, Huahua Chen, Zhijing Zhao

Computational Modeling & Simulation Engineering Faculty Publications

Singular point detection is a primary step in fingerprint recognition, especially for fingerprint alignment and classification. But in present there are still some problems and challenges such as more false-positive singular points or inaccurate reference point localization. This paper proposes an accurate core point localization method based on spatial domain features of fingerprint images from a completely different viewpoint to improve the fingerprint core point displacement problem of singular point detection. The method first defines new fingerprint features, called furcation and confluence, to represent specific ridge/valley distribution in a core point area, and uses them to extract the innermost Curve …


Schaeffler F-250 Bev Conversion: Power Electronics, Leslie Sawyer Jan 2022

Schaeffler F-250 Bev Conversion: Power Electronics, Leslie Sawyer

Williams Honors College, Honors Research Projects

This report shows the work that was done on the power electronics system in the industry sponsored Schaeffler demonstration truck project. The goal of the project was to convert a combustion Ford F250 into a battery electric vehicle, while using as much Schaeffler technology as possible. After the vehicle is converted it will be used as a demonstration vehicle to show potential investors. While this project is still in progress, the work that was done during this time was substantial to the development of this project. Progress that has been made on the power electronics system includes developments in selecting …


Novel Natural Language Processing Models For Medical Terms And Symptoms Detection In Twitter, Farahnaz Golrooy Motlagh Jan 2022

Novel Natural Language Processing Models For Medical Terms And Symptoms Detection In Twitter, Farahnaz Golrooy Motlagh

Browse all Theses and Dissertations

This dissertation focuses on disambiguation of language use on Twitter about drug use, consumption types of drugs, drug legalization, ontology-enhanced approaches, and prediction analysis of data-driven by developing novel NLP models. Three technical aims comprise this work: (a) leveraging pattern recognition techniques to improve the quality and quantity of crawled Twitter posts related to drug abuse; (b) using an expert-curated, domain-specific DsOn ontology model that improve knowledge extraction in the form of drug-to-symptom and drug-to-side effect relations; and (c) modeling the prediction of public perception of the drug’s legalization and the sentiment analysis of drug consumption on Twitter. We collected …


Garden Bot: Autonomous Home Garden Weed Removal Robot, Brendon Lovejoy, Robert Connolly, Isaac Lucas, Stevan Veselinov Jan 2022

Garden Bot: Autonomous Home Garden Weed Removal Robot, Brendon Lovejoy, Robert Connolly, Isaac Lucas, Stevan Veselinov

Williams Honors College, Honors Research Projects

With frequent weeding being a tedious chore and an essential task for a successful garden, there is need for an automated method of handling this routine. Existing technologies utilize computer vision, GPS, multiple units and other tools to remove weeds from garden plots. However, these solutions are often complex and expensive, suited for large agricultural plots in contrast to small-scale home gardens. In addition, many of these technologies, along with manual tillers and cultivators suited for home use, are unable to perform weeding within rows of crops in a process known as intra-row weeding. The Garden Bot is an autonomous, …


A Solder-Defined Computer Architecture For Backdoor And Malware Resistance, Marc W. Abel Jan 2022

A Solder-Defined Computer Architecture For Backdoor And Malware Resistance, Marc W. Abel

Browse all Theses and Dissertations

This research is about securing control of those devices we most depend on for integrity and confidentiality. An emerging concern is that complex integrated circuits may be subject to exploitable defects or backdoors, and measures for inspection and audit of these chips are neither supported nor scalable. One approach for providing a “supply chain firewall” may be to forgo such components, and instead to build central processing units (CPUs) and other complex logic from simple, generic parts. This work investigates the capability and speed ceiling when open-source hardware methodologies are fused with maker-scale assembly tools and visible-scale final inspection.

The …


Vehicle Maintenance Tracking Program, Jared Tomlinson Jan 2022

Vehicle Maintenance Tracking Program, Jared Tomlinson

Williams Honors College, Honors Research Projects

In order to help consumers and businesses keep track of vehicle maintenance, I will create a program paired with a database that can track vehicle maintenance needs and when they should be performed. The program will be capable of tracking entire fleets of vehicles and based on the vehicle’s mileage, will notify users of what maintenance should be performed. Users will be able to add, remove, and edit vehicles in the system as needed and each vehicle will be paired with a maintenance schedule based on its needs. As maintenance is performed, it can be tracked on the schedule, which …


Few-Shot Malware Detection Using A Novel Adversarial Reprogramming Model, Ekula Praveen Kumar Jan 2022

Few-Shot Malware Detection Using A Novel Adversarial Reprogramming Model, Ekula Praveen Kumar

Browse all Theses and Dissertations

The increasing sophistication of malware has made detecting and defending against new strains a major challenge for cybersecurity. One promising approach to this problem is using machine learning techniques that extract representative features and train classification models to detect malware in an early stage. However, training such machine learning-based malware detection models represents a significant challenge that requires a large number of high-quality labeled data samples while it is very costly to obtain them in real-world scenarios. In other words, training machine learning models for malware detection requires the capability to learn from only a few labeled examples. To address …


Evaluating Similarity Of Cross-Architecture Basic Blocks, Elijah L. Meyer Jan 2022

Evaluating Similarity Of Cross-Architecture Basic Blocks, Elijah L. Meyer

Browse all Theses and Dissertations

Vulnerabilities in source code can be compiled for multiple processor architectures and make their way into several different devices. Security researchers frequently have no way to obtain this source code to analyze for vulnerabilities. Therefore, the ability to effectively analyze binary code is essential. Similarity detection is one facet of binary code analysis. Because source code can be compiled for different architectures, the need can arise for detecting code similarity across architectures. This need is especially apparent when analyzing firmware from embedded computing environments such as Internet of Things devices, where the processor architecture is dependent on the product and …


Locality Analysis Of Patched Php Vulnerabilities, Luke N. Holt Jan 2022

Locality Analysis Of Patched Php Vulnerabilities, Luke N. Holt

Browse all Theses and Dissertations

The size and complexity of modern software programs is constantly growing making it increasingly difficult to diligently find and diagnose security exploits. The ability to quickly and effectively release patches to prevent existing vulnerabilities significantly limits the exploitation of users and/or the company itself. Due to this it has become crucial to provide the capability of not only releasing a patched version, but also to do so quickly to mitigate the potential damage. In this thesis, we propose metrics for evaluating the locality between exploitable code and its corresponding sanitation API such that we can statistically determine the proximity of …


Reflecting On Recurring Failures In Iot Development, Dharun Anandayuvaraj, James C. Davis Jan 2022

Reflecting On Recurring Failures In Iot Development, Dharun Anandayuvaraj, James C. Davis

Department of Electrical and Computer Engineering Faculty Publications

As IoT systems are given more responsibility and autonomy, they offer greater benefits, but also carry greater risks. We believe this trend invigorates an old challenge of software engineering: how to develop high-risk software-intensive systems safely and securely under market pressures? As a first step, we conducted a systematic analysis of recent IoT failures to identify engineering challenges. We collected and analyzed 22 news reports and studied the sources, impacts, and repair strategies of failures in IoT systems. We observed failure trends both within and across application domains. We also observed that failure themes have persisted over time. To alleviate …


Reflections On Software Failure Analysis, Paschal C. Amusuo, Aishwarya Sharma, Siddharth R. Rao, Abbey Vincent, James C. Davis Jan 2022

Reflections On Software Failure Analysis, Paschal C. Amusuo, Aishwarya Sharma, Siddharth R. Rao, Abbey Vincent, James C. Davis

Department of Electrical and Computer Engineering Faculty Publications

Failure studies are important in revealing the root causes, behaviors, and life cycle of defects in software systems. These studies either focus on understanding the characteristics of defects in specific classes of systems or the characteristics of a specific type of defect in the systems it manifests in. Failure studies have influenced various software engineering research directions, especially in the area of software evolution, defect detection, and program repair.

In this paper, we reflect on the conduct of failure studies in software engineering. We reviewed a sample of 52 failure study papers. We identified several recurring problems in these studies, …


Sok: Analysis Of Software Supply Chain Security By Establishing Secure Design Properties, Chinenye Okafor, Taylor R. Schorlemmer, Santiao Torres-Arias, James C. Davis Jan 2022

Sok: Analysis Of Software Supply Chain Security By Establishing Secure Design Properties, Chinenye Okafor, Taylor R. Schorlemmer, Santiao Torres-Arias, James C. Davis

Department of Electrical and Computer Engineering Faculty Publications

This paper systematizes knowledge about secure software supply chain patterns. It identifies four stages of a software supply chain attack and proposes three security properties crucial for a secured supply chain: transparency, validity, and separation. The paper describes current security approaches and maps them to the proposed security properties, including research ideas and case studies of supply chains in practice. It discusses the strengths and weaknesses of current approaches relative to known attacks and details the various security frameworks put out to ensure the security of the software supply chain. Finally, the paper highlights potential gaps in actor and operation-centered …


Exploiting Input Sanitization For Regex Denial Of Service, Efe Barlas, Xin Du, James C. Davis Jan 2022

Exploiting Input Sanitization For Regex Denial Of Service, Efe Barlas, Xin Du, James C. Davis

Department of Electrical and Computer Engineering Faculty Publications

Web services use server-side input sanitization to guard against harmful input. Some web services publish their sanitization logic to make their client interface more usable, e.g., allowing clients to debug invalid requests locally. However, this usability practice poses a security risk. Specifically, services may share the regexes they use to sanitize input strings — and regex-based denial of service (ReDoS) is an emerging threat. Although prominent service outages caused by ReDoS have spurred interest in this topic, we know little about the degree to which live web services are vulnerable to ReDoS.

In this paper, we conduct the first black-box …


Discrepancies Among Pre-Trained Deep Neural Networks: A New Threat To Model Zoo Reliability, Diego Montes, Pongpatapee Peerapatanapokin, Jeff Schultz, Chengjun Guo, Wenxin Jiang, James C. Davis Jan 2022

Discrepancies Among Pre-Trained Deep Neural Networks: A New Threat To Model Zoo Reliability, Diego Montes, Pongpatapee Peerapatanapokin, Jeff Schultz, Chengjun Guo, Wenxin Jiang, James C. Davis

Department of Electrical and Computer Engineering Faculty Publications

Training deep neural networks (DNNs) takes significant time and resources. A practice for expedited deployment is to use pre-trained deep neural networks (PTNNs), often from model zoos.collections of PTNNs; yet, the reliability of model zoos remains unexamined. In the absence of an industry standard for the implementation and performance of PTNNs, engineers cannot confidently incorporate them into production systems. As a first step, discovering potential discrepancies between PTNNs across model zoos would reveal a threat to model zoo reliability. Prior works indicated existing variances in deep learning systems in terms of accuracy. However, broader measures of reliability for PTNNs from …


An Empirical Study On The Impact Of Deep Parameters On Mobile App Energy Usage, Qiang Xu, James C. Davis, Y Charlie Hu, Abhilash Jindal Jan 2022

An Empirical Study On The Impact Of Deep Parameters On Mobile App Energy Usage, Qiang Xu, James C. Davis, Y Charlie Hu, Abhilash Jindal

Department of Electrical and Computer Engineering Faculty Publications

Improving software performance through configuration parameter tuning is a common activity during software maintenance. Beyond traditional performance metrics like latency, mobile app developers are interested in reducing app energy usage. Some mobile apps have centralized locations for parameter tuning, similar to databases and operating systems, but it is common for mobile apps to have hundreds of parameters scattered around the source code. The correlation between these "deep" parameters and app energy usage is unclear. Researchers have studied the energy effects of deep parameters in specific modules, but we lack a systematic understanding of the energy impact of mobile deep parameters. …


Design Of Computer Vision Systems For Optimizing The Threat Detection Accuracy, Sina Gholamnejad Davani Jan 2022

Design Of Computer Vision Systems For Optimizing The Threat Detection Accuracy, Sina Gholamnejad Davani

Wayne State University Dissertations

This dissertation considers computer vision (CV) systems in which a central monitoring station receives and analyzes the video streams captured and delivered wirelessly by multiple cameras. It addresses how the bandwidth can be allocated to various cameras by presenting a cross-layer solution that optimizes the overall detection or recognition accuracy. The dissertation presents and develops a real CV system and subsequently provides a detailed experimental analysis of cross-layer optimization. Other unique features of the developed solution include employing the popular HTTP streaming approach, utilizing homogeneous cameras as well as heterogeneous ones with varying capabilities and limitations, and including a new …


Sdn-Enabled Efficient Resource Utilization In A Secure, Trustworthy And Privacy Preserving Iov-Fog Environment, Jamal N. Alotaibi Jan 2022

Sdn-Enabled Efficient Resource Utilization In A Secure, Trustworthy And Privacy Preserving Iov-Fog Environment, Jamal N. Alotaibi

Wayne State University Dissertations

The development of intelligent transportation systems (ITS) is aided by the advent of Internet-of-Vehicles (IoV), which is a decentralized network that allows connected vehicles and vehicular ad hoc networks to share data (VANETs). However, today's IoV networks face a number of challenges, including effective resource utilization, security and privacy, trust, information irregularity, etc. In addition, IoV applications have a wide range of Quality-of-Service (QoS) requirements, making it difficult to develop an efficient solution to deal with big data in IoV. Furthermore, the solution should be scalable and extendable, as well as lightweight and cost-effective to maintain. By outsourcing computationally-intensive operations …


Machine Learning For Accessible Web Navigation, Tlamelo W. Makati Jan 2022

Machine Learning For Accessible Web Navigation, Tlamelo W. Makati

Conference papers

This research looks at the application of Machine Learning to Web Accessibility. It considers how Machine Learning (ML) can be used to help make the processes of Web Navigation more accessible in line with Web Content Accessibility Guideline (WCAG) 2.4 Navigable, which demands that ways be provided "to help users navigate, find content, and determine where they are." ML techniques such as reinforcement learning have been applied to website navigation in diverse ways. These include goal-directed search to answer questions and task-oriented problems such as booking a flight. Related work includes Web Automation and Testing. These techniques typically involve a …


Smart Uv-C Disinfectant Module, Nicole Baldy, Luke Rogers, Haitham Saleh Jan 2022

Smart Uv-C Disinfectant Module, Nicole Baldy, Luke Rogers, Haitham Saleh

Williams Honors College, Honors Research Projects

The Smart UV Disinfectant device shall sanitize objects which are 18”x14”x8” or smaller and less than 20 lbs. using UV-C light. This device should contain many safety measures to prevent human and animal exposure to the UV-C light and have no public touchpoints to operate the interface. In order to achieve the first objective, this device shall contain a "sanitizing chamber" which completely encloses the object to be sanitized to prevent outside exposure with detection of any lifeforms inside of the chamber; for the second objective, it will contain a wireless interface to an Android application which can be used …


Design Project: 3d Printer/Injection Molder Hybrid, Lee Paolucci, Luke Everhart, Brandon Leap, Karson Lorey Jan 2022

Design Project: 3d Printer/Injection Molder Hybrid, Lee Paolucci, Luke Everhart, Brandon Leap, Karson Lorey

Williams Honors College, Honors Research Projects

In the realm of rapid, small-scale prototyping, there are a few main factors that drive decisions to invest resources in technology to make that prototyping possible. Cost and ease of use are two of the most influential when looking at most SMEs (Small to Medium-sized Enterprises). The U.S. Small Business Administration defines an SME as smaller than 1,250 employees. According to An Assessment of Implementation of Entry-Level 3D Printers from the Perspective of Small Businesses, 59% of small manufacturers had implemented 3D printers as of 2014. However, no matter what technology is used in rapid prototyping, there are common …


Nject-3d, Kody Rinkevich, Logan Henderson, Nathaniel Anderson, James Patton, Cameron Wilson Jan 2022

Nject-3d, Kody Rinkevich, Logan Henderson, Nathaniel Anderson, James Patton, Cameron Wilson

Williams Honors College, Honors Research Projects

NJECT-3D is a student initiated design project where the utilities of a 3D printer and an injection molding machine are integrated into one cohesive unit. The goal of our project was to test the limits of rapid prototyping by utilizing printed molds. We developed an automated system where a mold can be printed on a 3D printer, translated from said 3D printer to an injection molder, then compressed and injected at said injection molder to output a finalized injection molded part.


Smart Bike Aftermarket System (Sbams), Noah Lamadanie, Jack Bullock, Dawson Beachy, John Albrecht Jan 2022

Smart Bike Aftermarket System (Sbams), Noah Lamadanie, Jack Bullock, Dawson Beachy, John Albrecht

Williams Honors College, Honors Research Projects

The Smart Bike Aftermarket System will be a set of connected modules, which, when installed on a standard bicycle, will allow it to mimic some of the safety and quality-of-life functionalities of an E-bike. The most notable of these safety features is an ability to detect vehicles approaching from behind and alert the user of potential collisions. The system will also implement lighting (Headlights, taillights, and turn signals), and a coupled application so a user can view more advanced information about their cycling. The primary advantage of this system over a standard E-bike is that it will have a lower …


Cardbot, Jakob Reiter, Grant Crump, Drake Drivere, Adam Miner Jan 2022

Cardbot, Jakob Reiter, Grant Crump, Drake Drivere, Adam Miner

Williams Honors College, Honors Research Projects

Many people enjoy playing cards but playing cards in the times of COVID-19 is difficult. There are many designs for dealing and shuffling robots, but few include sanitization and autonomous operation. This design is for a BlackJack card dealing and shuffling robot that will be autonomous and will sanitize the playing cards using UV-C LEDs. This will assist in keeping the user safe while playing a game of BlackJack


Magic: The Gathering Card Virtualizer, Vincent Garbonick, Jacen C. Conlan, Jaret A. Varn Jan 2022

Magic: The Gathering Card Virtualizer, Vincent Garbonick, Jacen C. Conlan, Jaret A. Varn

Williams Honors College, Honors Research Projects

Any well-versed Magic: The Gathering (MTG) player or collector knows how difficult it can be to keep track of all cards in their collection. Some spend hours searching for that one specific card, and others are constantly scouring the internet for how much their collection costs. However, this issue does not only affect casual fans. Resale companies spend hours a day determining the costs of cards, and tournament judges painstakingly check players’ decks to ensure they are not cheating. To assist with these struggles, the design team proposed to create the MTG Card Virtualizer. This device scans MTG playing cards …


Lapnitor: A Web Service That Protects Your Laptop From Theft., Michael Ameteku Jan 2022

Lapnitor: A Web Service That Protects Your Laptop From Theft., Michael Ameteku

Williams Honors College, Honors Research Projects

Laptop theft is an issue worldwide. According to an article from 2018, Security Boulevard stated that a laptop is stolen every 53 seconds. Using a laptop's camera, we can monitor the surroundings of the laptop and reduce a laptop's probability of being stolen. According to the University of Pittsburgh, a laptop has a 1-in- 10 chance of being stolen and nearly half of these thefts occur in offices or classrooms. These thefts mostly occur when a laptop owner leaves their device unattended for a certain period of time to maybe go visit the restroom or attend to a call when …


Efficient And Accurate Cordic Pipelined Architecture Chip Design Based On Binomial Approximation For Biped Robot, Rih-Lung Chung, Yen Hsueh, Shih-Lun Chen, Patricia Angela R. Abu Jan 2022

Efficient And Accurate Cordic Pipelined Architecture Chip Design Based On Binomial Approximation For Biped Robot, Rih-Lung Chung, Yen Hsueh, Shih-Lun Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Recently, much research has focused on the design of biped robots with stable and smooth walking ability, identical to human beings, and thus, in the coming years, biped robots will accomplish rescue or exploration tasks in challenging environments. To achieve this goal, one of the important problems is to design a chip for real-time calculation of moving length and rotation angle of the biped robot. This paper presents an efficient and accurate coordinate rotation digital computer (CORDIC)-based efficient chip design to calculate the moving length and rotation angle for each step of the biped robot. In a previous work, the …


Identifying Code Reading Strategies In Debugging Using Sta With A Tolerance Algorithm, Christine Lourrine S. Tablatin, Ma. Mercedes T. Rodrigo Jan 2022

Identifying Code Reading Strategies In Debugging Using Sta With A Tolerance Algorithm, Christine Lourrine S. Tablatin, Ma. Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

The purpose of this study was to identify the common code reading strategies of the high and low performing students engaged in a debugging task. Using Scanpath Trend Analysis (STA) with a tolerance on eye tracking data, common scanpaths of high and low performing students were generated. The common scanpaths revealed differences in the code reading patterns and code reading strategies of high and low performing students. High performing students follow a bottom-up code reading strategy when debugging complex programs with logical and semantic errors. A top-down code reading strategy is employed when debugging programs with simple control structures, few …


Predicting Pair Success In A Pair Programming Eye Tracking Experiment Using Cross-Recurrence Quantification Analysis, Maureen M. Villamor, Maria Mercedes T. Rodrigo Jan 2022

Predicting Pair Success In A Pair Programming Eye Tracking Experiment Using Cross-Recurrence Quantification Analysis, Maureen M. Villamor, Maria Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

Pair programming is a model of collaborative learning. It has become a well-known pedagogical practice in teaching introductory programming courses because of its potential benefits to students. This study aims to investigate pair patterns in the context of pair program tracing and debugging to determine what characterizes collaboration and how these patterns relate to success, where success is measured in terms of performance task scores. This research used eye-tracking methodologies and techniques such as cross-recurrence quantification analysis. The potential indicators for pair success were used to create a model for predicting pair success. Findings suggest that it is possible to …