Computer Engineering Commons^™

Vertex And Region Colourings Of Planar Idempotent Divisor Graphsof Commutative Rings., Mohammed N. Authman, Husam Q. Mohammad, Nazar H. Shuker

Iraqi Journal for Computer Science and Mathematics

The idempotent divisor graph of a commutative ring R is a graph with vertices set in R * = R-{0}, andany distinct vertices x and y are adjacent if and only if x.y = e. For some non-unit idempotent elemente2=e∈R, it isdenoted byΠ(R) . The purpose of this work is to use some properties of ring theory and graph theory to determine theclique number, the chromatic number and the region chromatic number for each planar idempotent divisor graph ofthe commutative rings. furthermore, we show that the clique number is equal to the chromatic number for any planaridempotent divisor graph. Results …

Fuzzy Soc-T-Abso Sub-Modules, Saad S. Marie, Hatam Y. Khalaf

Iraqi Journal for Computer Science and Mathematics

This research analyses the correlation that exists between fuzzy T-ABSO and fuzzy socle. To answerthis question, we define a new concept called, fuzzy socle T-ABSO submodules. Results showed many propertiesthat satisfied the new notion. In addition, we applied some algebra operations and found the relationship betweenfuzzy T-ABSO and fuzzy socle -T-ABSO. We also investigated the structure of fuzzy socle T-ABSO sub- modules ofa module under fuzzy direct sum, homomorphic image and intersection. Moreover, the relation between fuzzy socleT-ABSO sub-module and other types of fuzzy sub-module was presented. The implications of this study could beused to define new concepts that depend …

Leveraging Machine Learning For Detecting Iot-Based Interference In Operational Wifi Networks, Josh Pulse

Honors Program Theses

IoT (Internet of Things) devices have become increasingly popular in recent years while WiFi continues to serve as primary network provider indoors. With the advancements in technology, the networks of IoT devices continue to weave closely with indoor WiFi network deployments. Both kinds of these networks primarily operate in 2.4 GHz ISM Band (though latest WiFi standards can operate in 5 GHz and 60 GHz bands, too). With the multitude of tiny IoT sensors being deployed indoors alongside operational WiFi networks, severe interference scenarios cannot be ruled out. As a result of this interference, performance of WiFi networks is bound …

Design Of Human Inspired Feet For Mithra, A High-Performance Humanoid Robot, Spencer Lyle Brewster

Electronic Theses and Dissertations

This thesis explores the foot design for the new humanoid robot Mithra, with the goal to improve impact mitigation, natural gait throughout the gait cycle and balance. Using human gait parameters, a stiff aluminum foot was designed to emulate human center of pressure rollover trajectories. In addition, a 2D dynamic Finite Element Analysis (FEA) of the gait cycle was created in Abaqus to rapidly prototype foot designs. Data from the FE model provided impact forces, parameters for distal foot power evaluation and maximum lean angles. From this model a flexible nylon foot was optimized for the given design objectives. The …

Bfv-Based Homomorphic Encryption For Privacy-Preserving Cnn Models, Febrianti Wibawa, Ferhat Ozgur Catak, Salih Sarp, Murat Kuzlu

Engineering Technology Faculty Publications

Medical data is frequently quite sensitive in terms of data privacy and security. Federated learning has been used to increase the privacy and security of medical data, which is a sort of machine learning technique. The training data is disseminated across numerous machines in federated learning, and the learning process is collaborative. There are numerous privacy attacks on deep learning (DL) models that attackers can use to obtain sensitive information. As a result, the DL model should be safeguarded from adversarial attacks, particularly in medical data applications. Homomorphic encryption-based model security from the adversarial collaborator is one of the answers …

Design And Control Of Quasi-Direct Drive Actuation For Lightweight And Versatile Wearable Robots, Shuangyue Yu

Dissertations and Theses

Wearable robots have shown great potential for augmenting the physical capabilities of humans in lab settings. However, wearable robots for augmenting the physical capabilities of humans under community-based conditions are the new frontier of robotics. Furthermore, the design and control are still considered to be grand challenges for providing physical augmentation for humans. In terms of design, the state-of-the-art exoskeletons are typically rigid, bulky, and limited to lab settings. In terms of control, most of the rhythmic controllers are not versatile and are focused only on steady-state walking assistance.

The motivation behind my research is to improve both the design …

The Implementation Of Advanced Digitalization In The Oil And Gas Industry, Ensieh Rezafar

Walden Dissertations and Doctoral Studies

AbstractThe immature advanced digitalization in the oil and gas industry can limit access to the potential value of mature progressive digitalization. Oil and gas leaders must expedite the implementation of advanced digitalization to increase organizational proficiencies and reduce costs and losses. Grounded in Pettigrew and Whipp’s dimensions of strategic change theory, the purpose of this qualitative multiple case study was to explore strategies some leaders in the oil and gas industry used to implement advanced digitalization. The participants were seven leaders in two oil service companies in North America involved in the successful implementation of progressive digitalization. Data were collected …

Mixed-Criticality System Design For Real-Time Scheduling And Routing Upon Platforms With Uncertainties, Sudharsan Vaidhun Bhaskar

Electronic Theses and Dissertations, 2020-2023

Unlike typical computing systems, applications in real-time systems require strict timing guarantees. In the pursuit of providing guarantees, the complex dynamic behaviors of these systems are simplified using models to keep the analysis tractable. In order to guarantee safety, such models often involve pessimistic assumptions. While the amount of pessimism was reasonable for simple computing platforms, for modern platforms the pessimism involves ignoring features that improve performance such as cache usage, instruction pipelines, and more. In this work, we explore routing and scheduling problems in real-time systems, where the uncertainties in the operation are carefully accounted for by complex models …

Speaker Encoding For Zero-Shot Speech Synthesis, Tristin W. Cory

Graduate Theses/Dissertations

Spoken communication, for many, is an essential part of everyday life. Some individuals can lose or not be born with the ability to speak. To function on a day-to-day basis, these individuals find other ways of communication. Adaptive speech synthesis is one of those ways. It recreates a user’s previous voice or creates a voice that blends with their regional dialect. Current adaptive speech synthesis techniques that achieve human-like speech require thirty minutes, to a few hours of high-quality audio recordings of a target speaker. This amount of recorded audio is not commonly possessed by people in need of a …

Incommensurate Conformable-Type Three-Dimensional Lotka–Volterramodel: Discretization, Stability, And Bifurcation, Feras Yousef, Billel Semmar, Kamal Al Nasr

Computer Science Faculty Research

The classic Lotka–Volterra model is a two-dimensional system of differential equations used to model population dynamics among two-species: a predator and its prey. In this article, we consider a modified three-dimensional fractional-order Lotka–Volterra system that models population dynamics among three-species: a predator, an omnivore and their mutual prey. Biologically speaking, population models with a discrete and continuous structure often provide richer dynamics than either discrete or continuous models, so we first discretize the model while keeping one time-continuous dependent variable in each equation. Then, we analyze the stability and bifurcation near the equilibria. The results demonstrated that the dynamic behaviors …

Novel Architecture Of Onem2m-Based Convergence Platform For Mixed Reality And Iot, Seungwoon Lee, Woogeun Kil, Byeong Hee Roh, Si-Jung Kim, Jin Suk Kang

College of Engineering Faculty Research

There have been numerous works proposed to merge augmented reality/mixed reality (AR/MR) and Internet of Things (IoT) in various ways. However, they have focused on their specific target applications and have limitations on interoperability or reusability when utilizing them to different domains or adding other devices to the system. This paper proposes a novel architecture of a convergence platform for AR/MR and IoT systems and services. The proposed architecture adopts the oneM2M IoT standard as the basic framework that converges AR/MR and IoT systems and enables the development of application services used in general-purpose environments without being subordinate to specific …

Review Of Mathematical Modelling Techniques With Applicationsin Biosciences, Ahmed Hasan Alridha, Ahmed Sabah Al-Jilawi, Fouad H. Abd Alsharify

Iraqi Journal for Computer Science and Mathematics

Modelling can provide intellectual frameworks that are necessary to translate data into knowledge.Mathematical modelling has played an important role in many applications, such as ecology, genetics, engineering,psychology, sociology, physics and computer science, in recent years. This study focused on reviewing mathematicalmodelling and its applications to biological systems by tracing many metabolic activities of cellular interactions onthe one hand and between the spread of epidemics and population growth on the other hand. Various mathematicalequations have played fundamental roles in the formation of these systems for model development proceduresby describing them mathematically and establishing relationships that characterise the dynamics of a biologicalphenomenon. …

A Machine Learning Approach To Intended Motion Prediction For Upper Extremity Exoskeletons, Justin Berdell

Graduate Research Theses & Dissertations

A fully solid-state, software-defined, one-handed, handle-type control device built around a machine-learning (ML) model that provides intuitive and simultaneous control in position and orientation each in a full three degrees-of-freedom (DOF) is proposed in this paper. The device, referred to as the “Smart Handle”, and it is compact, lightweight, and only reliant on low-cost and readily available sensors and materials for construction. Mobility chairs for persons with motor difficulties could make use of a control device that can learn to recognize arbitrary inputs as control commands. Upper-extremity exoskeletons used in occupational settings and rehabilitation require a natural control device like …

Efficacy Of Reported Issue Times As A Means For Effort Estimation, Paul Phillip Maclean

Graduate Theses, Dissertations, and Problem Reports (ETD)

Software effort is a measure of manpower dedicated to developing and maintaining and software. Effort estimation can help project managers monitor their software, teams, and timelines. Conversely, improper effort estimation can result in budget overruns, delays, lost contracts, and accumulated Technical Debt (TD). Issue Tracking Systems (ITS) have become mainstream project management tools, with over 65,000 companies using Jira alone. ITS are an untapped resource for issue resolution effort research. Related work investigates issue effort for specific issue types, usually Bugs or similar. They model their developer-documented issue resolution times using features from the issues themselves. This thesis explores a …

A Tool For Biometric Interpretation Of Forensic Str Dna Profiles, Ahmad Jamal Baroudi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Rapid DNA biometric identification applications are becoming more essential and widely used in human identity validation processes. Despite their powerful identification capabilities, processing a sample to generate a forensic DNA profile still takes longer compared with other rapid biometric technologies. Methods used to speed up the analysis could lead to signal artifacts similar to those arising from low copy or degraded DNA samples, making the electropherogram unsuitable for forensic interpretation and analysis. The goal of this research effort is to apply biometrics and mathematical approaches to forensic STR (Short Tandem Repeat) profiles. To accomplish this goal, a multi-function software tool …

An Efficient Ar Model-Based Method For The Detection Of Forced Oscillations In Power Networks: Implementation And Analysis, Maria Waleska Suarez

Graduate Theses, Dissertations, and Problem Reports (ETD)

An active research topic is the detection of various oscillations that may lead to instability and potential disruption in the operation of a power network. Forced Oscillations (FOs) play a unique role in power system stability among various oscillations. They are perturbances that change the system’s state and are caused for many reasons, including but not limited to persistent load changes and oscillatory load or generation, fault, triplane, and other mechanical anomalies. These factors can hugely affect the power grid by either increasing or decreasing the amplitude, causing corrupt modes leading to blackouts, affecting the equipment involved, delivering poor power …

Synthesizing Realistic Substitute Data For A Law Enforcement Database Using A Python Library, Anthony Carrola

Graduate Theses, Dissertations, and Problem Reports (ETD)

In many databases, there is private or sensitive data that should not be accessible to any but a few individuals, such as HIPAA (Health Insurance Portability and Accountability Act) protected or LE (law enforcement) data. However, there is often a need to work with the data or change it for proper and thorough testing, especially for the developers . In some cases, the developers may be authorized to access and view the data, but it is rarely allowable for that data to be changed. Further, it is unlikely, especially on a large project, that all of the developers will have …

Generation Of High Performing Morph Datasets, Kelsey Lynn O'Haire

Graduate Theses, Dissertations, and Problem Reports (ETD)

Facial recognition systems play a vital role in our everyday lives. We rely on this technology from menial tasks to issues as vital as national security. While strides have been made over the past ten years to improve facial recognition systems, morphed face images are a viable threat to the reliability of these systems. Morphed images are generated by combining the face images of two subjects. The resulting morphed face shares the likeness of the contributing subjects, confusing both humans and face verification algorithms. This vulnerability has grave consequences for facial recognition systems used on international borders or for law …

Improving Robotic Decision-Making In Unmodeled Situations, Nicholas Scott Ohi

Graduate Theses, Dissertations, and Problem Reports (ETD)

Existing methods of autonomous robotic decision-making are often fragile when faced with inaccurate or incompletely modeled distributions of uncertainty, also known as ambiguity. While decision-making under ambiguity is a field of study that has been gaining interest, many existing methods tend to be computationally challenging, require many assumptions about the nature of the problem, and often require much prior knowledge. Therefore, they do not scale well to complex real-world problems where fulfilling all of these requirements is often impractical if not impossible. The research described in this dissertation investigates novel approaches to robotic decision-making strategies which are resilient to …

A Novel Computational Network Methodology For Discovery Of Biomarkers And Therapeutic Targets, Qing Ye

Graduate Theses, Dissertations, and Problem Reports (ETD)

Lung cancer has the second highest cancer incidence rate and the top cancer-related mortality worldwide. An estimate from the American Cancer Society shows that, in 2022, there will be about 236,740 lung cancer cases (117,910 men and 118,830 women) in the US. To date, there are no prognostic/predictive biomarkers to select chemotherapy, immunotherapy, and radiotherapy in individual non-small cell lung cancer (NSCLC) patients. There is an unmet clinical need to identify patients with early-stage NSCLC who are likely to develop recurrence and to predict their therapeutic responses. This dissertation developed a novel computational methodology for modeling molecular gene association networks …

Nbp 2.0: Updated Next Bar Predictor, An Improved Algorithmic Music Generator, Belinda M. Dungan, Proceso L. Fernandez Jr

Electronics, Computer, and Communications Engineering Faculty Publications

Deep neural network advancements have enabled machines to produce melodies emulating human-composed music. However, the implementation of such machines is costly in terms of resources. In this paper, we present NBP 2.0, a refinement of the previous model next bar predictor (NBP) with two notable improvements: first, transforming each training instance to anchor all the notes to its musical scale, and second, changing the model architecture itself. NBP 2.0 maintained its straightforward and lightweight implementation, which is an advantage over the baseline models. Improvements were assessed using quantitative and qualitative metrics and, based on the results, the improvements from these …

Multimodal Adversarial Learning, Uche Osahor

Graduate Theses, Dissertations, and Problem Reports (ETD)

Deep Convolutional Neural Networks (DCNN) have proven to be an exceptional tool for object recognition, generative modelling, and multi-modal learning in various computer vision applications. However, recent findings have shown that such state-of-the-art models can be easily deceived by inserting slight imperceptible perturbations to key pixels in the input. A good target detection systems can accurately identify targets by localizing their coordinates on the input image of interest. This is ideally achieved by labeling each pixel in an image as a background or a potential target pixel. However, prior research still confirms that such state of the art targets models …

High Energy And Power Density Peptidoglycan Musclesthrough Super-Viscous Nanoconfined Water, Haozhen Wang, Zhi-Lun Liu, Jianpei Lao, Sheng Zhang, Rinat Abzalimov, Tong Wang, Xi Chen

Advanced Science Research Center

Water-responsive (WR) materials that reversibly deform in response to humidity changes show great potential for developing muscle-like actuators for miniature and biomimetic robotics. Here, it is presented that Bacillus (B.) subtilis’ peptidoglycan (PG) exhibits WR actuation energy and power densities reaching 72.6 MJ m−3 and 9.1 MW m−3, respectively, orders of magnitude higher than those of frequently used actuators, such as piezoelectric actuators and dielectric elastomers. PG can deform as much as 27.2% within 110 ms, and its actuation pressure reaches ≈354.6 MPa. Surprisingly, PG exhibits an energy conversion efficiency of ≈66.8%, which can be attributed to its super-viscous nanoconfined …

A Reynolds Number Based Sampling Technique For 3-D Vector Fields In Computational Fluid Dynamic Environments, Trent James Schweitzer

Graduate Student Theses, Dissertations, & Professional Papers

Effective visualization of unsteady, time-dependent vector fields in a virtual environment is not a trivial task. This is due to the fact that most visualization techniques require the user to have a prior understanding of how the vector field will behave to set the parameters used to create the visualization. In this thesis we will take air flow data from a computational fluid dynamic simulations to calculate the amount of turbulence (represented as Reynolds numbers) to identify regions of interest. We then calculate wind pathlines that will intersect with these points sampled from these regions. We address the issue of …

Factors Influencing The Effectiveness Of Managing Human–Robot Teams, Theodore B. Terry

Walden Dissertations and Doctoral Studies

Certain factors can influence the capabilities of a robot–human team by affecting their social and behavioral dynamics in a work environment. But these factors were not known due to the progressive nature of human–robot partnerships and a lack of peer-reviewed literature on the topic. This e-Delphi study aimed to identify and understand these unknown influential factors based on the participants’ insights. The overarching research question asked about the need to determine factors that might influence the effectiveness of managing human-robot teams. The basis for the conceptual framework for this study was the theory of communication used in organizational management. Twelve …

Jitim Front Cover Vol 31 1 2022

Journal of International Technology and Information Management

Table of Content JITIM Vol 31. issue 1, 2022

Performance Of Sensor Fusion For Vehicular Applications, Nikola Janevski

Graduate Theses, Dissertations, and Problem Reports (ETD)

Sensor fusion is a key system in Advanced Driver Assistance Systems, ADAS. The perfor-
mance of the sensor fusion depends on many factors such as the sensors used, the kinematic
model used in the Extended Kalman Filter, EKF, the motion of the vehicles, the type of
road, the density of vehicles, and the gating methods. The interactions between parameters
and the extent to which individual parameters contribute to the overall accuracy of a sensor
fusion system can be difficult to assess.
In this study, a full-factorial experimental evaluation of a sensor fusion system based
on a real vehicle was performed. …

Learning Representations For Human Identification, Sinan Sabri

Graduate Theses, Dissertations, and Problem Reports (ETD)

Long-duration visual tracking of people requires the ability to link track snippets (a.k.a. tracklets) based on the identity of people. In lack of the availability of motion priors or hard biometrics (e.g., face, fingerprint, or iris), the common practice is to leverage soft biometrics for matching tracklets corresponding to the same person in different sightings. A common choice is to use the whole-body visual appearance of the person, as determined by the clothing, which is assumed to not change during tracking. The problem is challenging because distinct images of the same person may look very different, since no restrictions are …

Face Recognition With Attention Mechanisms, Qiangchang Wang

Graduate Theses, Dissertations, and Problem Reports (ETD)

Face recognition has been widely used in people’s daily lives due to its contactless process and high accuracy. Existing works can be divided into two categories: global and local approaches. The mainstream global approaches usually extract features on whole faces. However, global faces tend to suffer from dramatic appearance changes under the scenarios of large pose variations, heavy occlusions, and so on. On the other hand, since some local patches may remain similar, they can play an important role in such scenarios. Existing local approaches mainly rely on cropping local patches around facial landmarks and then extracting corresponding local representations. …

Face Representation Learning And Its Applications: From Image Editing To 3d Avatar Animation, Xudong Liu

Graduate Theses, Dissertations, and Problem Reports (ETD)

Face representation learning is one of the most popular research topics in the computer vision community, as it is the foundation of face recognition and face image generation. Numerous representation learning frameworks have been integrated into applications in daily life, such as face recognition, image editing, and face tracking. Researchers have developed advanced algorithms for face recognition with successful commercial productions, for example, FaceID on the smartphone. The performance record on face recognition is constantly updated and becoming saturated with the help of large-scale datasets and advanced computational resources. Thanks to the robust representation in face recognition, in this dissertation, …