Digital Commons Network^™

Factors Influencing Performance Of Students In Software Automated Test Tools Course, Susmita Haldar, Mary Pierce, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

Formal software testing education is important for building efficient QA professionals. Various aspects of quality assurance approaches are usually covered in courses for training software testing students. Automated Test Tools is one of the core courses in the software testing post-graduate curriculum due to the high demand for automated testers in the workforce. It is important to understand which factors are affecting student performance in the automated testing course to be able to assist the students early on based on their needs. Various metrics that are considered for predicting student performance in this testing course are student engagement, grades on …

Explainable Artificial Intelligence Approach For Diagnosing Faults In An Induction Furnace, Sajad Moosavi, Roozbeh Razavi-Far, Vasile Palade, Mehrdad Saif

Electrical and Computer Engineering Publications

For over a century, induction furnaces have been used in the core of foundries for metal melting and heating. They provide high melting/heating rates with optimal efficiency. The occurrence of faults not only imposes safety risks but also reduces productivity due to unscheduled shutdowns. The problem of diagnosing faults in induction furnaces has not yet been studied, and this work is the first to propose a data-driven framework for diagnosing faults in this application. This paper presents a deep neural network framework for diagnosing electrical faults by measuring real-time electrical parameters at the supply side. Experimental and sensory measurements are …

Vertical Free-Swinging Photovoltaic Racking Energy Modeling: A Novel Approach To Agrivoltaics, Koami Soulemane Hayibo, Joshua M. Pearce

Electrical and Computer Engineering Publications

To enable lower-cost building materials, a free-swinging bifacial vertical solar photovoltaic (PV) rack has been proposed, which complies with Canadian building codes and is the lowest capital-cost agrivoltaics rack. The wind force applied to the free-swinging PV, however, causes it to have varying tilt angles depending on the wind speed and direction. No energy performance model accurately describes such a system. To provide a simulation model for the free-swinging PV, where wind speed and direction govern the array tilt angle, this study builds upon the open-source System Advisor Model (SAM) using Python. After the SAM python model is validated, a …

A Novel Multidimensional Reference Model For Heterogeneous Textual Datasets Using Context, Semantic And Syntactic Clues, Ganesh Kumar, Shuib Basri, Abdullahi Abubakar Imam, Abdullateef Abdullateef Oluwagbemiga Balogun, Hussaini Mamman, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

With the advent of technology and use of latest devices, they produces voluminous data. Out of it, 80% of the data are unstructured and remaining 20% are structured and semi-structured. The produced data are in heterogeneous format and without following any standards. Among heterogeneous (structured, semi-structured and unstructured) data, textual data are nowadays used by industries for prediction and visualization of future challenges. Extracting useful information from it is really challenging for stakeholders due to lexical and semantic matching. Few studies have been solving this issue by using ontologies and semantic tools, but the main limitations of proposed work were …

Search-Based Fairness Testing: An Overview, Hussaini Mamman, Shuib Basri, Abdullateef Balogun, Abdullahi Abubakar Imam, Ganesh Kumar, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

Artificial Intelligence (AI) has demonstrated remarkable capabilities in domains such as recruitment, finance, healthcare, and the judiciary. However, biases in AI systems raise ethical and societal concerns, emphasizing the need for effective fairness testing methods. This paper reviews current research on fairness testing, particularly its application through search-based testing. Our analysis highlights progress and identifies areas of improvement in addressing AI systems’ biases. Future research should focus on leveraging established search-based testing methodologies for fairness testing.

Investigating Continual Learning Strategies In Neural Networks, Christopher Tam, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

This paper explores the role of continual learning strategies when neural networks are confronted with learning tasks sequentially. We analyze the stability-plasticity dilemma with three factors in mind: the type of network architecture used, the continual learning scenario defined and the continual learning strategy implemented. Our results show that complementary learning systems and neural volume significantly contribute towards memory retrieval and consolidation in neural networks. Finally, we demonstrate how regularization strategies such as elastic weight consolidation are more well-suited for larger neural networks whereas rehearsal strategies such as gradient episodic memory are better suited for smaller neural networks.

Software Testing And Code Refactoring: A Survey With Practitioners, Danilo Leandro Lima, Ronnie Souza Santos, Guilherme Pires Garcia, Sildemir S. Silva, Cesar Franca, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

Nowadays, software testing professionals are commonly required to develop coding skills to work on test automation. One essential skill required from those who code is the ability to implement code refactoring, a valued quality aspect of software development; however, software developers usually encounter obstacles in successfully applying this practice. In this scenario, the present study aims to explore how software testing professionals (e.g., software testers, test engineers, test analysts, and software QAs) deal with code refactoring to understand the benefits and limitations of this practice in the context of software testing. We followed the guidelines to conduct surveys in software …

Integrating Traditional Cs Class Activities With Computing For Social Good, Ethics, And Communications And Leadership Skills, Renato Cortinovis, Devender Goyal, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

Software and information technologies are becoming increasingly integrated and pervasive in human society and range from automated decision making and social media and entertainment, to running critical social and physical infrastructures like government programs, utilities, and financial institutions. As a result, there is a growing awareness of the need to develop professionals who will harness these technologies in fair and inclusive ways and use them to address global issues like health, water management, poverty, and human rights. In this regard, many academic researchers have expressed the need to complement traditional teaching of CS technical skills with computer and information ethics …

Using Machine Learning To Assist Auditory Processing Evaluation, Hasitha Wimalarathna, Sangamanatha Veeranna, Minh Vu Duong, Chris Allan Prof, Sumit K. Agrawal, Prudence Allen, Jagath Samarabandu, Hanif M. Ladak

Electrical and Computer Engineering Publications

Introduction: Approximately 0.2–5% of school-age children complain of listening difficulties in the absence of hearing loss. These children are often referred to an audiologist for an auditory processing disorder (APD) assessment. Adequate experience and training is necessary to arrive at an accurate diagnosis due to the heterogeneity of the disorder.

Objectives: The main goal of the study was to determine if machine learning (ML) can be used to analyze data from the APD clinical test battery to accurately categorize children with suspected APD into clinical sub-groups, similar to expert labels.

Methods: The study retrospectively collected data from 134 children referred …

Explainable Software Defect Prediction From Cross Company Project Metrics Using Machine Learning, Susmita Haldar, Luiz Fernando Capretz

Electrical and Computer Engineering Publications

Predicting the number of defects in a project is critical for project test managers to allocate budget, resources, and schedule for testing, support and maintenance efforts. Software Defect Prediction models predict the number of defects in given projects after training the model with historical defect related information. The majority of defect prediction studies focused on predicting defect-prone modules from methods, and class-level static information, whereas this study predicts defects from project-level information based on a cross-company project dataset. This study utilizes software sizing metrics, effort metrics, and defect density information, and focuses on developing defect prediction models that apply various …

Trading Electricity With Blockchain Systems, David Bowker, Anant Venkateswaran, Fazel Mohammadi, Abdulraheem Al Garni, Marko Vukobratovic, Claudio Lima, Farrokh Rahimi, Igor Ferreira, Davor Bosnjak, Hannes Agabus, Praveen Agarwal, Santosh Jain, Simon Mikulich, Victor Francisco, Toshiyuki Sawa, Umit Cali, Vladislav Berezovsky, Hannah Davis, Subhendu Subhendu, Gregor Karlovsek, Alex Barakat, Vivek Bhandari, Ivan Ostheimer, Jemma Green

Electrical and Computer Engineering Publications

On the wave of the development of new ICT technologies and renewable energy, the power system will certainly experience great changes to its outdated architecture over the next several decades. One of the key drivers of change in the power system is distributed energy resources. They are completely changing the paradigm of the power system as a system with a centralized hierarchy and one-way power flows from generation to customer and from high voltage to low voltage. Because the goals of net zero greenhouse gas emissions are gathering pace and are being accepted by countries around the world, slowdown in …

Design And Fabrication Of Embroidered Textile Strain Sensors: An Alternative To Stitch-Based Strain Sensors, Jose Guillermo Colli Alfaro, Ana Luisa Trejos

Electrical and Computer Engineering Publications

Smart textile sensors have been gaining popularity as alternative methods for the continuous monitoring of human motion. Multiple methods of fabrication for these textile sensors have been proposed, but the simpler ones include stitching or embroidering the conductive thread onto an elastic fabric to create a strain sensor. Although multiple studies have demonstrated the efficacy of textile sensors using the stitching technique, there is almost little to no information regarding the fabrication of textile strain sensors using the embroidery method. In this paper, a design guide for the fabrication of an embroidered resistive textile strain sensor is presented. All of …

Event-Based Robust Control Techniques For Wheel-Based Robots Under Cyber-Attack And Dynamic Quantizer, Mobin Saeedi, Jafar Zarei, Mehrdad Saif, Allahyar Montazeri

Electrical and Computer Engineering Publications

Nowadays, mobile robots are becoming an increasingly significant part of daily human life. Humanoid robots, wheeled mobile robots, aerial vehicles, mobile manipulators, and more are examples of mobile robots. As opposed to other robots, they are capable of moving autonomously, with sufficient intelligence to make decisions in response to the perceptions they receive from their environment. In today’s world, cooperative tasks and the ability to control robots via networks make them a component of cyber-physical systems (CPSs). In this study, mobile robots that are acting as a part of CPSs are examined. Data-network burden, signal quantizers, cyber security, delayed transition, …

Scheduling Electric Vehicle Charging For Grid Load Balancing, Zhixin Han, Katarina Grolinger, Miriam Capretz, Syed Mir

Electrical and Computer Engineering Publications

In recent years, electric vehicles (EVs) have been widely adopted because of their environmental benefits. However, the increasing volume of EVs poses capacity issues for grid operators as simultaneously charging many EVs may result in grid instabilities. Scheduling EV charging for grid load balancing has a potential to prevent load peaks caused by simultaneous EV charging and contribute to balance of supply and demand. This paper proposes a user-preference-based scheduling approach to minimize costs for the user while balancing grid loads. The EV owners benefit by charging when the electricity cost is lower, but still within the user-defined preferred charging …

A Reference Framework For Variability Management Of Software Product Lines, Saiqa Aleem, Luiz Fernando Capretz, Faheem Ahmed

Electrical and Computer Engineering Publications

Variability management (VM) in software product line engineering (SPLE) is introduced as an abstraction that enables the reuse and customization of assets. VM is a complex task involving the identification, representation, and instantiation of variability for specific products, as well as the evolution of variability itself. This work presents a comparison and contrast between existing VM approaches using “qualitative meta-synthesis” to determine the underlying perspectives, metaphors, and concepts of existing methods. A common frame of reference for the VM was proposed as the result of this analysis. Putting metaphors in the context of the dimensions in which variability occurs and …

A New Economic Dispatch For Coupled Transmission And Active Distribution Networks Via Hierarchical Communication Structure, Wael T. El-Sayed, Ahmad Sa Awad, Maher Azzouz, Mostafa F. Shaaban

Electrical and Computer Engineering Publications

Traditionally, the economic dispatch problem (EDP) of the bulk generators connected to transmission networks (TNs) is solved in a centralized dispatching center (CDC) while modeling distribution networks as passive loads. With the increasing penetration levels of distributed generation, coordinating the economic dispatch between TNs and active distribution networks (ADNs) became vital to maximizing system efficiency. This article proposes a hierarchical communication structure, which requires minimal upgrades to the CDC, for solving the EDP of coupled TNs and ADNs. Based on the minimal data transfer between the CDC and distribution network operators, the problem is formulated and solved while considering the …

What Pakistani Computer Science And Software Engineering Students Think About Software Testing?, Luiz Fernando Capretz, Abdul Rehman Gilal

Electrical and Computer Engineering Publications

Software testing is one of the crucial supporting processes of the software life cycle. Unfortunately for the software industry, the role is stigmatized, partly due to misperception and partly due to treatment of the role. The present study aims to analyze the situation to explore what restricts computer science and software engineering students from taking up a testing career in the software industry. To conduct this study, we surveyed 88 Pakistani students taking computer science or software engineering degrees. The results showed that the present study supports previous work into the unpopularity of testing compared to other software life cycle …

Virtual Sensor Middleware: Managing Iot Data For The Fog-Cloud Platform, Fadi Almahamid, Hanan Lutfiyya, Katarina Grolinger

Electrical and Computer Engineering Publications

This paper introduces the Virtual Sensor Middleware (VSM), which facilitates distributed sensor data processing on multiple fog nodes. VSM uses a Virtual Sensor as the core component of the middleware. The virtual sensor concept is redesigned to support functionality beyond sensor/device virtualization, such as deploying a set of virtual sensors to represent an IoT application and distributed sensor data processing across multiple fog nodes. Furthermore, the virtual sensor deals with the heterogeneous nature of IoT devices and the various communication protocols using different adapters to communicate with the IoT devices and the underlying protocol. VSM uses the publish-subscribe design pattern …

Agglomerative Hierarchical Clustering With Dynamic Time Warping For Household Load Curve Clustering, Fadi Almahamid, Katarina Grolinger

Electrical and Computer Engineering Publications

Energy companies often implement various demand response (DR) programs to better match electricity demand and supply by offering the consumers incentives to reduce their demand during critical periods. Classifying clients according to their consumption patterns enables targeting specific groups of consumers for DR. Traditional clustering algorithms use standard distance measurement to find the distance between two points. The results produced by clustering algorithms such as K-means, K-medoids, and Gaussian Mixture Models depend on the clustering parameters or initial clusters. In contrast, our methodology uses a shape-based approach that combines Agglomerative Hierarchical Clustering (AHC) with Dynamic Time Warping (DTW) to classify …

Using Deep Learning For Task And Tremor Type Classification In People With Parkinson’S Disease, Ghazal Farhani, Yue Zhou, Mary E. Jenkins, Michael D. Naish, Ana Luisa Trejos

Electrical and Computer Engineering Publications

Hand tremor is one of the dominating symptoms of Parkinson’s disease (PD), which significantly limits activities of daily living. Along with medications, wearable devices have been proposed to suppress tremor. However, suppressing tremor without interfering with voluntary motion remains challenging and improvements are needed. The main goal of this work was to design algorithms for the automatic identification of the tremor type and voluntary motions, using only surface electromyography (sEMG) data. Towards this goal, a bidirectional long short-term memory (BiLSTM) algorithm was implemented that uses sEMG data to identify the motion and tremor type of people living with PD when …

Optimal Inverter And Wire Selection For Solar Photovoltaic Fencing Applications, Koami Soulemane Hayibo, Joshua M. Pearce

Electrical and Computer Engineering Publications

Despite the benefits and the economic advantages of agrivoltaics, capital costs limit deployment velocity. One recent potential solution to this challenge is to radically reduce the cost of racking materials by using existing farm fencing as vertical photovoltaic (PV) racking. This type of fenced-based PV system is inherently electrically challenging because of the relatively long distances between individual modules that are not present in more densely packed conventional solar PV farms. This study provides practical insights for inverter selection and wire sizing optimization for fence-based agrivoltaic systems. Numerical simulation sensitivities on the levelized cost of electricity (LCOE) were performed for …

Autonomous Unmanned Aerial Vehicle Navigation Using Reinforcement Learning: A Systematic Review, Fadi Almahamid, Katarina Grolinger

Electrical and Computer Engineering Publications

There is an increasing demand for using Unmanned Aerial Vehicle (UAV), known as drones, in different applications such as packages delivery, traffic monitoring, search and rescue operations, and military combat engagements. In all of these applications, the UAV is used to navigate the environment autonomously --- without human interaction, perform specific tasks and avoid obstacles. Autonomous UAV navigation is commonly accomplished using Reinforcement Learning (RL), where agents act as experts in a domain to navigate the environment while avoiding obstacles. Understanding the navigation environment and algorithmic limitations plays an essential role in choosing the appropriate RL algorithm to solve the …

The Applications Of Blockchain Technologies To Electricity Markets, David Bowker, Vladislav Berezovsky, Marko Vukobratović, Santosh Jain, Subhendu Mukherjee, Fazel Mohammadi, Hannes Agabus

Electrical and Computer Engineering Publications

This paper is a summary of the CIGRE Technical Brochure 824 The Role of Blockchain Technologies in Power Markets [17]. The work of the contributors to the Technical Brochure is recognised. It is proposed to follow up this work in a new working group with a more in-depth look at the potential applications for blockchain in the area of energy trading.

Editorial: Robotics, Autonomous Systems And Ai For Nonurgent/Nonemergent Healthcare Delivery During And After The Covid-19 Pandemic, A. L. Trejos, S. F. Atashzar, S. P. Dimaio, P. M. Pilarski, M. Tavakoli

Electrical and Computer Engineering Publications

No abstract provided.

Monofacial Vs Bifacial Solar Photovoltaic Systems In Snowy Environments, Koami Soulemane Hayibo, Aliaksei Petsiuk, Pierce Mayville, Laura Brown, Joshua M. Pearce

Electrical and Computer Engineering Publications

There has been a recent surge in interest in the more accurate snow loss estimates for solar photovoltaic (PV) systems as large-scale deployments move into northern latitudes. Preliminary results show bifacial modules may clear snow faster than monofacial PV. This study analyzes snow losses on these two types of systems using empirical hourly data including energy, solar irradiation and albedo, and open-source image processing methods from images of the arrays in a northern environment in the winter. Projection transformations based on reference anchor points and snowless ground truth images provide reliable masking and optical distortion correction with fixed surveillance cameras. …

Resilient Consensus Control Design For Dc Microgrids Against False Data Injection Attacks Using A Distributed Bank Of Sliding Mode Observers, Yousof Barzegari, Jafar Zarei, Roozbeh Razavi-Far, Mehrdad Saif, Vasile Palade

Electrical and Computer Engineering Publications

This paper investigates the problem of false data injection attack (FDIA) detection in microgrids. The grid under study is a DC microgrid with distributed boost converters, where the false data are injected into the voltage data so as to investigate the effect of attacks. The proposed algorithm uses a bank of sliding mode observers that estimates the states of the neighbor agents. Each agent estimates the neighboring states and, according to the estimation and communication data, the detection mechanism reveals the presence of FDIA. The proposed control scheme provides resiliency to the system by replacing the conventional consensus rule with …

Multi-Agent Based Protection Scheme Using Current-Only Directional Overcurrent Relays For Looped/Meshed Distribution Systems, Mohammad Ali Ataei, Mohsen Gitizadeh, Matti Lehtonen, Roozbeh Razavi-Far

Electrical and Computer Engineering Publications

The complexity of the design of the protection system using directional over current relays, for modern power distribution systems has been increased due to the looped/meshed operation and the penetration of distributed generations. Finding a reliable and efficient protection scheme that can be easily implemented in these distribution systems is a major challenge. An efficient solution could be the use of artificial intelligent-based multi-agent systems. This paper proposes a novel distributed intelligent based multi-agent protection scheme, which makes use of current-only directional over current relays as agents for detecting and locating faults and isolating faulty areas (lines/busbars) in the distribution …

Foam-Based Floatovoltaics: A Potential Solution To Disappearing Terminal Natural Lakes, Koami Soulemane Hayibo, Joshua M. Pearce

Electrical and Computer Engineering Publications

Terminal lakes are disappearing worldwide because of direct and indirect human activities. Floating photovoltaics (FPV) are a synergistic system with increased energy output because of water cooling, while the FPV reduces water evaporation. This study explores how low-cost foam-based floatovoltaic systems can mitigate the disappearance of natural lakes. A case study is performed on 10%–50% FPV coverage of terminal and disappearing Walker Lake. Water conservation is investigated with a modified Penman-Monteith evapotranspiration method and energy generation is calculated with an operating temperature model experimentally determined from foam-based FPV. Results show FPV saves 52,000,000 m3/year of water and US$6,000,000 at 50% …

Case Study Of Tv Spectrum Sensing Model Based On Machine Learning Techniques, Abdalaziz Mohammad, Faroq Ali Awin, Esam Abdel-Raheem

Electrical and Computer Engineering Publications

Spectrum sensing is an essential component in cognitive radios (CR). Machine learning (ML) algorithms are powerful techniques for designing a promising spectrum sensing model. In this work, the supervised ML algorithms, support vector machine (SVM), k-nearest neighbor (kNN), and decision tree (DT) are applied to detect the existence of primary users (PU) over the TV band. Moreover, the Principal Component Analysis (PCA) is incorporated to speed up the learning of the classifiers. Furthermore, the ensemble classification-based approach is employed to enhance the classifier predictivity and performance. Simulation results have shown that the highest performance is achieved by the ensemble classifier. …

The Greenest Solar Power? Life Cycle Assessment Of Foam-Based Flexible Floatovoltaics, Koami Soulemane Hayibo, Pierce Mayville, Joshua M. Pearce

Electrical and Computer Engineering Publications

This study presents a life cycle analysis (LCA) of a 10 MW foam-based floatovoltaics (FPV) plant installed on Lake Mead, Nevada, U.S. A material inventory of the flexible crystalline silicon (c-Si)-based module involved massing and determination of material composition of the module's encapsulation layers with ATR/FTR spectroscopy and electron microscopy. The LCA was performed using SimaPro and the results were interpreted in terms of cumulative energy demands, energy payback time, global warming potential, GHG emissions, and water footprint including negative values for reduced evaporation. A sensitivity analysis was performed on the lifetime of the modules and the foam-based racking. The …