Computer Engineering Commons^™

Identifying Roles Of Software Developers From Their Answers On Stack Overflow, Dean Power

Dissertations

Stack Overflow is the world’s largest community of software developers. Users ask and answer questions on various tagged topics of software development. The set of questions a site user answers is representative of their knowledge base, or “wheelhouse”. It is proposed that clustering users by their wheelhouse yields communities of similar software developers by skill-set. These communities represent the different roles within software development and could be used as the basis to define roles at any point in time in an ever-evolving landscape of software development. A network graph of site users, linked if they answered questions on the same …

Can Generative Adversarial Networks Help Us Fight Financial Fraud?, Sean Mciver

Dissertations

Transactional fraud datasets exhibit extreme class imbalance. Learners cannot make accurate generalizations without sufficient data. Researchers can account for imbalance at the data level, algorithmic level or both. This paper focuses on techniques at the data level. We evaluate the evidence of the optimal technique and potential enhancements. Global fraud losses totalled more than 80 % of the UK’s GDP in 2019. The improvement of preprocessing is inherently valuable in fighting these losses. Synthetic minority oversampling technique (SMOTE) and extensions of SMOTE are currently the most common preprocessing strategies. SMOTE oversamples the minority classes by randomly generating a point between …

Performance Comparison Between A Distributed Particle Swarm Algorithm And A Centralised Algorithm, Ciarán O’Loughlin

Dissertations

Particle Swarm optimisation (PSO) is a particular form of swarm intelligence, which itself is an innovative intelligent paradigm for solving optimization problems. PSO is generally used to find a global optimum in a single optimisation function. This typically occurs on one node(machine) but there has been a significant body of research into creating distributed implementations of the PSO algorithm. Such research has often focused on the creation and performance of the distributed implementation in an isolated manner or compared to different distributed algorithms.

This research piece aims to bridge a gap in the existing literature, by testing a distributed implementation …

Vind: A Blockchain-Enabled Supply Chain Provenance Framework For Energy Delivery Systems, Eranga Bandara, Sachin Shetty, Deepak Tosh, Xueping Liang

VMASC Publications

Enterprise-level energy delivery systems (EDSs) depend on different software or hardware vendors to achieve operational efficiency. Critical components of these systems are typically manufactured and integrated by overseas suppliers, which expands the attack surface to adversaries with additional opportunities to infiltrate into EDSs. Due to this reason, the risk management of the EDS supply chain is crucial to ensure that we are knowledgeable about the vulnerabilities in software and hardware components that comprise any critical part, quantifiable risk metrics to assess the severity and exploitability of the attack, and provide remediation solutions that can influence a prioritized mitigation plan. There …

Visualization For Solving Non-Image Problems And Saliency Mapping, Divya Chandrika Kalla

All Master's Theses

High-dimensional data play an important role in knowledge discovery and data science. Integration of visualization, visual analytics, machine learning (ML), and data mining (DM) are the key aspects of data science research for high-dimensional data. This thesis is to explore the efficiency of a new algorithm to convert non-images data into raster images by visualizing data using heatmap in the collocated paired coordinates (CPC). These images are called the CPC-R images and the algorithm that produces them is called the CPC-R algorithm. Powerful deep learning methods open an opportunity to solve non-image ML/DM problems by transforming non-image ML problems into …

Determination Of Hydrogel Degradation By Passive Mechanical Testing, Avery Rosh-Gorsky

Honors Theses

This paper details a new technique to measure the mechanical properties of ETTMP PEGDA hydrogels using Hertz Contact Theory and simultaneously analyze both the model drug release and gel erosion in situ. This method involves curing a drug loaded hydrogel in a standard cuvette and placing a glass bead and phosphate buffer solution (PBS). Over time, the cross-linked network of the hydrogel breaks down, and, as a result, the ball sinks into the hydrogel. This method provides a macroscopic and inexpensive way to continuously and passively measure properties of the hydrogel as the hydrogel degrades. By plotting both the …

Ieee Access Special Section Editorial: Trends And Advances In Bio-Inspired Image-Based Deep Learning Methodologies And Applications, Peter Peer, Carlos M. Travieso-Gonzalez, Vijayan K. Asari, Malay Kishore Dutta

Electrical and Computer Engineering Faculty Publications

Many of the technological advances we enjoy today have been inspired by biological systems due to their ease of operation and outstanding efficiency. Designing technological solutions based on biological inspiration has become a cornerstone of research in a variety of areas ranging from control theory and optimization to computer vision, machine learning, and artificial intelligence. Especially in the latter few areas, biologically relevant solutions are becoming increasingly important as we look for new ways to make artificial systems more efficient, intelligent, and overall effective.

การพยากรณ์ปริมาณและความเข้มข้นสารฟลอกคูแลต์ในกระบวนการพักใสสำหรับอุตสาหกรรมการผลิตน้ำตาลจากอ้อย, สิงหดิศร์ จันทรักษ์

Chulalongkorn University Theses and Dissertations (Chula ETD)

กระบวนการพักใสเป็นกระบวนการที่สำคัญในกระบวนการผลิตน้ำตาล ซึ่งกระบวนการมีการทำงานเพื่อแยกระหว่างตะกอนกับน้ำอ้อยออกจากกันโดยใช้สารฟลอกคูแลนต์ โดยในการใส่ปริมาณและความเข้มข้นสารฟลอกคูแลนต์ลงไปในน้ำอ้อยทำให้ส่งผลกระทบโดยตรงต่อความเร็วการตกตะกอนและค่าความขุ่นของน้ำอ้อย วิทยานิพนธ์เล่มนี้เสนอวิธีการพยากรณ์ปริมาณและความเข้มข้นสารฟลอกคูแลต์ในกระบวนการพักใสสำหรับอุตสาหกรรมการผลิตน้ำตาลจากอ้อย โดยใช้โครงข่ายประสาทเทียมแบบวนซ้ำชนิดพิเศษ Long Short-Term Memory โดยข้อมูลที่นำมาใช้เป็นข้อมูลขาเข้าสำหรับการสร้างโมเดลได้แก่ ปริมาณอ้อยสด, ปริมาณอ้อยเผา, ความขุ่นของน้ำอ้อย และปริมาณน้ำฝน และข้อมูลขาออกได้แก่ ปริมาณและความเข้มข้นของสารฟลอกคูแลนต์ ทั้งนี้ข้อมูลที่ได้นำมาจากโรงงานผลิตน้ำตาลแห่งหนึ่งในประเทศไทย ผลการทดลองแสดงให้เห็นถึงประสิทธิภาพของโมเดลที่ได้นำเสนอ LSTM โดยการเปรียบเทียบกับโมเดลอื่นๆ ได้แก่ Autoregressive Integrated Moving Average (ARIMA), Recurrent Neural Network (RNN) และ Gated Recurrent Unit (GRU) โดยใช้ตัวแปร RMSE และ MAPE เป็นตัววัดประสิทธิภาพของโมเดล พบว่าโมเดลที่นำเสนอมีประสิทธิภาพที่สุดในการพยากรณ์ปริมาณและความเข้มข้นของสารฟลอกคูแลนต์

การจำแนกปัญหาของเทคโนโลยีฐานข้อมูลในชุมชนถามตอบออนไลน์, ณัฐนัย สุวรรณชูชิต

Chulalongkorn University Theses and Dissertations (Chula ETD)

วิทยานิพนธ์นี้นำเสนอแนวทางการสร้างเครื่องมือการทำงานอัตโนมัติเพื่อจำแนกคำถามบนเว็บไซต์สแต็กโอเวอร์โฟลว์ โดยเฉพาะที่เกี่ยวกับชนิดของผลิตภัณฑ์ฐานข้อมูล ซึ่งถือเป็นข้อมูลที่มีค่าสำหรับเจ้าของผลิตภัณฑ์ฐานข้อมูลในการนำไปปรับปรุงผลิตภัณฑ์ หมวดหมู่ของคำถามกำหนดไว้เป็นสองระดับได้แก่ ระดับปัญหา และ ปัญหาย่อย โดยที่ระดับปัญหาประกอบด้วย การพัฒนา การติดตั้ง และ การปรับปรุงประสิทธิภาพ ในขณะที่ ปัญหาย่อย ประกอบด้วย การออกแบบ ข้อจำกัด และการอภิปรายปัญหา ด้วยการรวมทั้งสองระดับเข้าด้วยกัน คำถามจะถูกจำแนกออกเป็นเก้าหมวดของปัญหา-ปัญหาย่อย การประมวลผลภาษาธรรมชาติและการจำแนกข้อความถูกนำมาใช้ โดยใช้อัลกอริทึมการเรียนรู้ของเครื่องที่หลากหลาย โมเดลการจำแนกประเภทที่มีประสิทธิภาพดีที่สุดจะถูกนำมาใช้ในเว็บแอปพลิเคชัน เพื่อจำแนกแต่ละคำถามโดยใช้แท็กปัญหา-ปัญหาย่อย นอกจากนี้คำถามที่ถูกจำแนกออกตามหมวดแล้ว สามารถนำมาวิเคราะห์เพิ่มเติมโดยใช้อัลกอริทึมการสร้างแบบจำลองหัวข้อ เพื่อให้ทราบว่าคำถามในแต่ละหมวดนั้นกล่าวถึงหัวข้อใดบ้าง ซึ่งจะเป็นข้อมูลเพิ่มเติมให้กับเจ้าของผลิตภัณฑ์ฐานข้อมูลในการทำความเข้าใจถึงปัญหาของผลิตภัณฑ์เพื่อจะได้ทำการปรับปรุงต่อไป

Event-Driven Servers Using Asynchronous, Non-Blocking Network I/O: Performance Evaluation Of Kqueue And Epoll, Lorcan Leonard

Dissertations

This research project evaluates the performance of kqueue and epoll in the context of event-driven servers. The evaluation is done through benchmarking and tracing which are used to measure throughput and execution time respectively. The experiment is repeated for both a virtualised and native server environment. The results from the experiment are statistically analysed and compared. These results show significant differences between kqueue and epoll, and a profound impact of virtualisation as a variable.

Dachash: A Dynamic, Cache-Aware And Concurrent Hash Table On Gpus, Hao Zhou

Electronic Theses and Dissertations

GPU acceleration of hash tables in high-volume transaction applications such as computational geometry and bio-informatics are emerging. Recently, several hash table designs have been proposed on GPUs, but our analysis shows that they still do not adequately factor in several important aspects of a GPU’s execution environment, leaving large room forfurther optimization.

Deep Learning Approach On Symptom Questionnaire And Abdominal Radiography For Diagnosis Of Dyssynergic Defecation, Sornsiri Poovongsaroj

Chulalongkorn University Theses and Dissertations (Chula ETD)

Dyssynergic defecation is one of the most common causes of chronic constipation. It is a behavioral problem in which the pelvic floor muscles are unable to coordinate with the surrounding muscles and nerves to evacuate stool. Patients are required to undergo specialized tests only available at tertiary healthcare centers for diagnosis. The aim of this thesis is to develop deep learning-based models to prescreen potential patients from primary and secondary healthcare centers for further diagnostic tests by using easily obtainable data such as symptom questionnaire and abdominal radiography. First, we developed a model which uses symptom questionnaire as an input …

Ping Pong Ball Collecting Robot, Gina Lanese, Jason Colonna, Sarah Kuchcinski, Johndavid Rogers

Williams Honors College, Honors Research Projects

The ping pong ball collecting robot will collect ping pong balls in a ping pong arena, such as after a game or practice session. Ball collection is now typically done by a human, collecting the balls either by hand or with a net. A robot, autonomously collecting the ping pong balls from the floor, would allow for the time spent playing or practicing to be maximized. The team will design the software and hardware for the robot, including the mechanical system, the software, and circuit boards. This robot will serve as a capstone project for the senior design team consisting …

Sample Mislabeling Detection And Correction In Bioinformatics Experimental Data, Soon Jye Kho

Browse all Theses and Dissertations

Sample mislabeling or incorrect annotation has been a long-standing problem in biomedical research and contributes to irreproducible results and invalid conclusions. These problems are especially prevalent in multi-omics studies in which a large set of biological samples are characterized by multiple types of omics platforms at different times or different labs. While multi-omics studies have demonstrated tremendous value in understanding disease biology and improving patient outcomes, the complexity of these studies may increase opportunities for human error. Fortunately, the interrelated nature of the data collected in multi-omics studies can be exploited to facilitate the identification and, in some cases, correction …

Guitar Store Inventory, Alexander Didonato

Williams Honors College, Honors Research Projects

This project displays my senior programming project for a made up Guitar store inventory.

A Novel Approach Toward High Accuracy Indoor Localization}{Masters Of Science, Yunshu Wang

Electronic Theses and Dissertations

This thesis presents a novel approach towards high accuracy indoor localization with smartphones. Better than all the existing indoor localization methods, our approach has the advantage of being infrastructural-free, robust, and it does not require any pre-installation in a new environment. To make this goal come true, we built a testbed that only uses the Inertial Measurement Units (IMU) of the smartphones to access the smartphones' raw acceleration and orientation data, then use these data to calculate the user's location by coordinate transformation and interactions. We conducted extensive experiments and evaluations for testbed validation as well as to carefully examine …

Design Project: Smart Headband, John Michel, Jack Durkin, Noah Lewis

Williams Honors College, Honors Research Projects

Concussion in sports is a prevalent medical issue. It can be difficult for medical professionals to diagnose concussions. With the fast pace nature of many sports, and the damaging effects of concussions, it is important that any concussion risks are assessed immediately. There is a growing trend of wearable technology that collects data such as steps and provides the wearer with in-depth information regarding their performance. The Smart Headband project created a wearable that can record impact data and provide the wearer with a detailed analysis on their risk of sustaining a concussion. The Smart Headband uses accelerometers and gyroscopes …

A Rebellion Framework With Learning For Goal-Driven Autonomy, Zahiduddin Mohammad

Browse all Theses and Dissertations

Modeling an autonomous agent that decides for itself what actions to take to achieve its goals is a central objective of artificial intelligence. There are various approaches used to build autonomous agents including neural networks, state machines, utility functions, learning agents, and cognitive architectures. In this thesis, we focus on cognitive architectures. Our approach uses specific knowledge of the world, the goals they pursue, and the actions being performed. Most agents do what they are told (i.e., achieve the goals given to them by a human), but a genuinely autonomous agent does more. It can formulate its own goal or …

Partial Facial Re-Imaging Using Generative Adversarial Networks, Derek Desentz

Browse all Theses and Dissertations

Existing facial recognition software relies heavily on using neural networks to extract key facial features to accurately classify known individuals. Some of these key features include the shape, size, and distance between an individual’s eyes, nose, and mouth. When these key features cannot be extracted due to facial coverings, existing applications become inaccurate and unreliable. The accuracy and reliability of these technologies are growing concerns as the facial recognition market continues to grow at an exponential rate. In this thesis, we have developed a web-based application service that is able to take in a partially covered face image and generate …

Automated Blind Control, Daniel Nahra, Matthew Lacek, Timothy Kurczewski, William Daulton Baksa

Williams Honors College, Honors Research Projects

The objective of this project would be to design and prototype an automated, light and temperature sensing window blinds system. The device would detect temperature, both inside and outside, and incoming sunlight to determine proper window blind position for maximum energy savings. The user would also have the ability to change the settings of the blind from a remote device to a setting that they desire at any given time

Soil Sensor Network, Andrea Wyder, Ross Klonowski, Alexis Alves, Luke Farnsworth

Williams Honors College, Honors Research Projects

Water management during crop irrigation is a problem for the agricultural industry. To help farmers better maintain water usage, a wireless soil sensor network comprised of a sensor pod and wireless communication has been designed and implemented. It was proven that the sensor pod can be installed 6-8 inches below the ground and communicate up to at least a 6km distance back to the gateway. The senor pod shells have a 2 mm thick shell to prevent the pod from shattering when coming into contact with the ground after being released from the planter, as calculated through the force of …

Light Loaded Automated Guided Vehicle, Marcus Radtka, Nazar Paramashchuk, Lawrence Shevock

Williams Honors College, Honors Research Projects

The objective of the locomotion system was to design and implement the mechanical, electrical, and software related functions to ensure the LLAGV had the capability of maneuvering its surroundings. The LLAGV’s motors were represented in an open loop transfer function to utilize RPM feedback and a compensator when needed. The modeled compensator helped control the LLAGV’s speed and acceleration, enabling further control of the LLAGV. The internal circuitry has the means to properly distributed power to all components and allowed the user to control the LLAGV to their desire. The application software within the LLAGV locomotion system (LLAGV-LS) had consideration …

The Youplanner, Taylor Burgess

Williams Honors College, Honors Research Projects

Staying organized can be difficult. A four tier web application was created to help in the endeavor. Utilizing software engineering practices, an online notepad was created where users can add, update, and delete notes. The application was a full stack application. For the backend, MySQL was the language and phpMyAdmin was the server. For the front end, PHP and Bootstrap 5.1 was used.

Schizophrenia Classification Using Resting State Eeg Functional Connectivity: Source Level Outperforms Sensor Level, Sima Azizi, Daniel B. Hier, Donald C. Wunsch

Chemistry Faculty Research & Creative Works

Disrupted Functional and Structural Connectivity Measures Have Been Used to Distinguish Schizophrenia Patients from Healthy Controls. Classification Methods based on Functional Connectivity Derived from EEG Signals Are Limited by the Volume Conduction Problem. Recorded Time Series at Scalp Electrodes Capture a Mixture of Common Sources Signals, Resulting in Spurious Connections. We Have Transformed Sensor Level Resting State EEG Times Series to Source Level EEG Signals Utilizing a Source Reconstruction Method. Functional Connectivity Networks Were Calculated by Computing Phase Lag Values between Brain Regions at Both the Sensor and Source Level. Brain Complex Network Analysis Was Used to Extract Features and …

Subsumption Reduces Dataset Dimensionality Without Decreasing Performance Of A Machine Learning Classifier, Donald C. Wunsch, Daniel B. Hier

Chemistry Faculty Research & Creative Works

When Features in a High Dimension Dataset Are Organized Hierarchically, There is an Inherent Opportunity to Reduce Dimensionality. Since More Specific Concepts Are Subsumed by More General Concepts, Subsumption Can Be Applied Successively to Reduce Dimensionality. We Tested Whether Sub-Sumption Could Reduce the Dimensionality of a Disease Dataset Without Impairing Classification Accuracy. We Started with a Dataset that Had 168 Neurological Patients, 14 Diagnoses, and 293 Unique Features. We Applied Subsumption Repeatedly to Create Eight Successively Smaller Datasets, Ranging from 293 Dimensions in the Largest Dataset to 11 Dimensions in the Smallest Dataset. We Tested a MLP Classifier on All …

Robust Acceleration Of Data-Centric Applications Using Resistive Computing Systems, Baogang Zhang

Electronic Theses and Dissertations, 2020-2023

With the accessible data reaching zettabyte level, CMOS technology is reaching its limit for the data hungry applications. Moore's law has been reaching its depletion in recent studies. On the other hand, von Neumann architecture is approaching the bottleneck due to the data movement between the computing and memory units. With data movement and power budgets becoming the limiting factors of today's computing systems, in-memory computing using emerging non-volatile resistive devices has attracted an increasing amount of attention. A non-volatile resistive device may be realized using memristor, resistive random access memory (ReRAM), phase change memory (PCM), or spin-transfer torque magnetic …

Joint Carrier Frequency And Phase Offset Estimation Algorithm For Cpm-Dsssbased Secure Point-To-Point Communication, Saima Shehzadi, Farzana Kulsoom, Muhammad Zeeshan, Qasim Umar Khan, Shahzad Amin Sheikh

Turkish Journal of Electrical Engineering and Computer Sciences

A point-to-point (P2P) communication system based on the CPM-DSSS scheme ensures reliability, security, and antijamming capabilities. However, for reliable detection of data carrier synchronization of CPM-DSSS based system is one of the requirements. This paper presents a joint algorithm for carrier frequency offset (CFO) and carrier phase offset (CPO) estimation for CPM-DSSS based P2P system. The results indicate that the proposed CFO estimator is unbiased and can accurately estimate a wide range of offsets. Moreover, the proposed algorithm is compared with another research work. The results show that the proposed CFO and CPO estimation algorithm outperforms its counterpart with a …

A Hybrid Numerical Model For Long-Range Electromagnetic Wave Propagation, Gül Yesa Altun, Özlem Özgün

Turkish Journal of Electrical Engineering and Computer Sciences

A hybrid numerical model is presented for solving long range electromagnetic wave propagation problems involving objects on or above the ground surface by hybridizing the two-way split-step parabolic equation (2W-SSPE) method with the method of moments (MoM). The advantages of the proposed model are twofold: (i) It reduces the staircasing error in irregular terrain modeling, which usually occurs when the standard SSPE method is used alone. This is achieved by employing the MoM to more accurately obtain the scattered fields from slanted/curved surfaces. (ii) It enables the SSPE method to handle the problems involving objects above the Earth's surface, which …

Comparison Of Metaheuristic Optimization Algorithms With A New Modifieddeb Feasibility Constraint Handling Technique, Murat Erhan Çi̇men, Zeynep Gari̇p, Ali̇ Fuat Boz

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, the modification of the Deb feasibility method is considered to solve the constrained optimization problems. In the developed modified Deb feasibility constraint method, the third rule in its procedure was revised in order to increase the performance of the Deb feasibility constraint handling method. The innovation in the method is based on generating a new individual by using both possible solutions that violate the constraints in the method used for solving the problem. In detail, discussions were given about the application and usefulness of six constrained handling techniques. Furthermore, genetic algorithm, particle swarm optimization, Harris hawks optimization, …

Medical Image Fusion With Convolutional Neural Network In Multiscaletransform Domain, Asan Abas, Hasan Erdi̇nç Koçer, Nurdan Baykan

Turkish Journal of Electrical Engineering and Computer Sciences

Multimodal medical image fusion approaches have been commonly used to diagnose diseases and involve merging multiple images of different modes to achieve superior image quality and to reduce uncertainty and redundancy in order to increase the clinical applicability. In this paper, we proposed a new medical image fusion algorithm based on a convolutional neural network (CNN) to obtain a weight map for multiscale transform (curvelet/ non-subsampled shearlet transform) domains that enhance the textual and edge property. The aim of the method is achieving the best visualization and highest details in a single fused image without losing spectral and anatomical details. …