Sackett And The Continued Atomization Of The Clean Water Act, Robert W. Adler

Case Western Reserve Law Review

No abstract provided.

Sackett V. Epa And The Regulatory, Property, And Human Rights-Based Strategies For Protecting American Waterways, Erin Ryan

Case Western Reserve Law Review

No abstract provided.

Amorphous Boron Carbide-Amorphous Silicon Heterojunction Devices, Vojislav Medic

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This dissertation will show successful development and characterization of amorphous boron carbide-amorphous silicon heterojunction device with potential for neutron detection.

The amorphous hydrogenated boron carbide (a-BC:H) has been extensively researched as a semiconductor for neutron voltaic device fabrication. Naturally occurring boron contains 19.8% of boron isotope B¹⁰ that has a high absorption cross section of thermal neutrons at lower energies, and boron carbide contains 14.7% of that B¹⁰ isotope. Therefore, as a semiconductor compound of boron a-BC:H has the ability to absorb radiation, generate charge carriers, and collect those carriers.

Previous work on a-BC:H devices investigated the fabrication …

Fledge: Ledger-Based Federated Learning Resilient To Inference And Backdoor Attacks, Jorge Castillo, Phillip Rieger, Hossein Fereidooni, Qian Chen, Ahmad Sadeghi

Informatics and Engineering Systems Faculty Publications

Federated learning (FL) is a distributed learning process that uses a trusted aggregation server to allow multiple parties (or clients) to collaboratively train a machine learning model without having them share their private data. Recent research, however, has demonstrated the effectiveness of inference and poisoning attacks on FL. Mitigating both attacks simultaneously is very challenging. State-of-the-art solutions have proposed the use of poisoning defenses with Secure Multi-Party Computation (SMPC) and/or Differential Privacy (DP). However, these techniques are not efficient and fail to address the malicious intent behind the attacks, i.e., adversaries (curious servers and/or compromised clients) seek to exploit a …

Stopping The Revolving Door: Mdp-Based Decision Support For Community Corrections Placement, Xiaoquan Gao, Pengyi Shi, Nan Kong

Research Collection Lee Kong Chian School Of Business

Community corrections (CC) programs offer an alternative to incarceration that can reduce jail overcrowding and recidivism rates. The aim is to address the root causes behind criminal behavior, ultimately breaking the cycle of reincarceration. However, placing all eligible individuals in CC may strain case managers, resulting in reduced supervision, increased violations, and higher recidivism rates, which undermines the intended benefits for all participants in the programs. We take the first step in building a comprehensive analytical framework based on a queueing system to support the placement decisions and related decisions such as capacity planning. We develop a Markov Decision Process …

Assessing Chondrocyte Viability Of Articular Cartilage Using Label-Free Imaging Methods, Hongming Fan

All Dissertations

ABSTRACT

Articular cartilage covers the ends of bones, providing a protective layer that can endure forces during movement. Chondrocytes, the only cell type found in articular cartilage, produce collagen fibers and proteoglycans that maintain the extracellular matrix (ECM). Cartilage damage impairs chondrocytes and their ability to maintain tissue stability. There are various factors that can cause cell death, which can be broadly classified into two categories: programmed cell death (apoptosis) and non-programmed cell death (necrosis). The consequences of cell death can have significant impacts on the extracellular matrix (ECM). The ECM is a complex network of proteins and carbohydrates that …

An In Vitro Platform To Characterize Myocardial Wound Remodeling, Jonathan Heywood

All Dissertations

Heart Failure, sometimes called Congestive Heart Failure, is a collection of pathological disruptions in which the heart is unable to pump blood properly. It affects over 6 million people in the United States, with the cost-per-patient at approximately $30,000 and the total cost estimated to be $160 billion by 2030. There is no single cause of heart failure, as it can manifest as a varying array of diseases, disorders, and syndromes. However, many of these underlying diseases result specifically from dysregulation of mechanically active cells called cardiac fibroblasts, which play a critical role in the remodeling of the extracellular matrix …

Influence Of Access To Public Parks On Mortality Among Older Adults In The United States, Jiaying Dong

All Dissertations

Research shows the health benefits of green spaces are universal, but there's a noticeable disparity in their distribution in the U.S., especially between urban and rural areas. Marginalized groups, particularly those of lower economic status or racial minorities, often have limited access to these spaces. This inequity could be more impactful on the elderly, who are more vulnerable to health issues. However, specific health benefits of green spaces for seniors are not well defined. This study examines the correlation between park access, mortality in those over 65, and income disparities across all U.S. counties.

The study employed a quantitative approach …

Physics-Based Machine Learning Methods For Control And Sensing In Fish-Like Robots, Colin Rodwell

All Dissertations

Underwater robots are important for the construction and maintenance of underwater infrastructure, underwater resource extraction, and defense. However, they currently fall far behind biological swimmers such as fish in agility, efficiency, and sensing capabilities. As a result, mimicking the capabilities of biological swimmers has become an area of significant research interest. In this work, we focus specifically on improving the control and sensing capabilities of fish-like robots.

Our control work focuses on using the Chaplygin sleigh, a two-dimensional nonholonomic system which has been used to model fish-like swimming, as part of a curriculum to train a reinforcement learning agent to …

Multidimensional Chromatographic Coupling Strategies Implementing Capillary-Channeled Polymer Fiber Stationary Phases, Sarah Wysor

All Dissertations

Liquid chromatography (LC) is a widely employed technique in analytical separations due to the ease of implementing rapid analysis methods to isolate targeted analytes. While LC is commonplace, challenges often arise with complex macromolecules as it often effects isolation via only one attribute of the targeted analyte (i.e., physical, chemical). To cater to increasingly complex samples requiring multiple chromatographic workflows, two-dimensional liquid chromatography (2DLC) has emerged. Various applications, such as drug discovery, pharmaceutical manufacturing, and specialty chemical manufacturing, require highly pure final products for release to the market. Consequently, multiple chromatographic steps are necessary for isolation and purification. Within pharmaceuticals, …

Cfrp Delamination Density Propagation Analysis By Magnetostriction Theory, Brandon Eugene Williams

All Dissertations

While Carbon Fiber Reinforced Polymers (CFRPs) have exceptional mechanical properties concerning their overall weight, their failure profile in demanding high-stress environments raises reliability concerns in structural applications. Two crucial limiting factors in CFRP reliability are low-strain material degradation and low fracture toughness. Due to CFRP’s low strain degradation characteristics, a wide variety of interlaminar damage can be sustained without any appreciable change to the physical structure itself. This damage suffered by the energy transfer from high- stress levels appears in the form of microporosity, crazes, microcracks, and delamination in the matrix material before any severe laminate damage is observed. This …

The Effects Of Math Pathways On Pupils In Poverty, Edward Kameen

All Dissertations

This was a Mixed Methods study that evaluated the implementation of a Math Pathways Program at Crestview High School. The study leveraged Improvement Science and a long-range PDSA cycle with the aim of improving outcomes for Pupils in Poverty in Dual Credit math courses. This study sought to answer three research questions. The first two research questions were answered with quantitative data and the final research question was answered with qualitative data. The research questions that guided this study were (1) What effects did the Math Pathways Program have on the enrollment of Pupils in Poverty in Dual Credit math? …

Atomistic And Mesoscale Modeling Of Microstructure Development During Solid-State Sintering, Omar Marwan Isa Hussein

All Dissertations

Interfaces are ubiquitous in materials systems, and they influence the processing and properties of nearly all engineering and functional materials. Examples include grain boundaries (GBs) in polycrystalline materials, free surfaces in nanoparticles, and phase boundaries in multiphase materials. Therefore, understanding and controlling interfacial processes is a key aspect of materials design and discovery efforts. Recent developments in advanced manufacturing and synthesis techniques have enabled the fabrication of materials architectures with intricate nanoscale features. Of particular interest is solid-state sintering, known for creating complex and high-precision geometries with controlled microstructures. While sintering science has been the subject of active research, very …

Improving Hexapod Platform Pose Accuracy - A Photogrammetry-Based Approach, Sourabh Karmakar

All Dissertations

The aim of this research is to make a newly constructed Stewart-Gough Platform-based test frame Tiger 66.1 operational by developing control software and estimating the error in its pose accuracy. The accuracy of the platform is affected by one source or multiple sources. The typical error sources are kinematic and structural, some of them originate from manufacturing imperfections, assembly deviations, elastic deformations, thermal deformations, and joint clearances which change the expected kinematic behavior of the manipulator. Also, some non-mechanical errors like transmission error, sensor accuracy, algorithm error, and truncation error in calculation contribute significantly in some cases. Using pose deviations …

Did That Help? Harnessing Natural Language Processing To Uncover Characteristics Of Peer Feedback And Their Impacts On Teamwork-Skills Learning., Annamaria V. Wolf

All Dissertations

Peer Evaluation Systems (PESs) allow members of student teams to provide one another with computer-mediated feedback in the form of qualitative, open-ended comments. The current research leverages unsupervised Natural Language Processing (NLP), namely Biterm Topic Modeling (BTM) and sentiment analysis, to uncover latent topics and degree of positivity and negativity expressed in peer feedback, respectively. BTM results revealed a 6-topic model that was reliably replicated over 10 Gibbs initializations 80% of the time. Topics were labeled Timely Communication, Idea Generation, Coordination & Adaptation, Work Quality, Team Support & Focusing, and Work Accountability. Qualitative comparison suggests that these topics demonstrate …

New Preconditioned Conjugate Gradient Methods For Some Structured Problems In Physics, Tianqi Zhang

All Dissertations

This dissertation concerns the development and analysis of new preconditioned conjugate gradient (PCG) algorithms for three important classes of large-scale and complex physical problems characterized by special structures. We propose several new iterative methods for solving the eigenvalue problem or energy minimization problem, which leverage the unique structures inherent in these problems while preserving the underlying physical properties. The new algorithms enable more efficient and robust large-scale modeling and simulations in many areas, including condensed matter physics, optical properties of materials, stabilities of dynamical systems arising from control problems, and many more. Some methods are expected to be applicable to …

Hpc-Enabled Fast And Configurable Dynamic Simulation, Analysis, And Learning For Complex Power System Adaptation And Control, Cong Wang

All Dissertations

This dissertation presents an HPC-enabled fast and configurable dynamic simulation, analysis, and learning framework for complex power system adaptation and control. Dynamic simulation for a large transmission system comprising thousands of buses and branches implies the latency of complicated numerical computations. However, faster-than-real-time execution is often required to provide timely support for power system planning and operation. The traditional approaches for speeding up the simulation demand extensive computing facilities such as CPU-based multi-core supercomputers, resulting in heavily resource-dependent solutions. In this work, by coupling the Message Passing Interface (MPI) protocol with an advanced heterogeneous programming environment, further acceleration can be …

Enhancing Security And Performance Of Deep Neural Networks, Azadeh Gholamrezazadeh Famili

All Dissertations

The significance of security is often overlooked until a catastrophic event occurs. This holds for the security of existing IoT devices. Numerous devices have been deployed and repurposed without adequately considering their security vulnerabilities. There is a lack of comprehensive security protocols for devices that frequently interact with one another. Even in emerging fields like machine learning (ML), which has found extensive applications in strategy optimization, decision-making, data classification, and other domains, discussions around security vulnerabilities are not widespread. Regarding security in ML, the focus tends to revolve around specific topics such as adversarial attacks. However, due to the remarkable …

Trust-Based Variable Impedance Control And Passivity-Based Switched System Analysis For Human-Robot Cooperative Manipulation, Zhanrui Liao

All Dissertations

Human-robot cooperative manipulation (co-manipulation) is one of the most prominent human-robot collaboration (HRC) tasks, where humans and robots manipulate the same object. Trust in HRC is crucial in determining human acceptance of robots and, hence, robot utilization. A probabilistic dynamic Bayesian network (DBN) trust model that integrates a time-series trust model is presented in this thesis. The trust model is learned using a continuous and normalized Baum-Welch (BW) algorithm, devised to account for the continuous nature of trust evolution and the limitations of the classic parameter learning method. To ensure a good HRC in co-manipulation, a variable impedance control framework …

Making The Move Toward Meaningfulness In Learning Activities: Enhancing Teacher Self-Efficacy In Student Engagement Through An Instructional Coaching Approach In Improvement Science, Maureen Tiller

All Dissertations

Student engagement is a common problem in schools today and a challenging one to solve. Choosing to dive deeper into this complex problem at one high school, ten teachers participated in a coaching cycle designed to impact self-efficacy in student engagement with the support of the school’s instructional coach in collaboration with the principal. One overarching research question guided this improvement science study: What impact does an instructional coaching cycle focused on meaningfulness in learning activities have on teachers’ self-efficacy in student engagement? To answer the research question, I conducted a quantitative and qualitative data analysis of pre- and …

Citizenship And Human Rights: The Path To Reparation, Larissa Rocha

Graduate Theses and Dissertations

Human rights and citizenship are strictly tied together. Without citizenship to a country, one cannot have their human rights guaranteed. In the framework of reparative citizenship, and methodology of feminist political philosophy, I search for solutions for the statelessness and citizenship issues in India and Ukraine. I offer an analysis of the differences and similarities between both cases while going through both countries' colonial histories and understanding their impacts on the issues they are facing today.

Enhancement Of Cloud Computing Environment Using Machine Learning Algorithms Mlce, Mohammed E. Seno, Ban N., Omer K. Jasim Mohammad

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Cloud computing is an eVolving and high-demand research field at the forefront of technological advancements. It aims to provide software resources and operates based on service-oriented delivery. Within the infrastructure as a service (IaaS) framework, the cloud offers end customers access to crucial infrastructure resources, including CPU, bandwidth, and memory. When a cloud system fails to deliver as expected, it is referred to as an event, signifying a deviation from the anticipated service. To meet their service-level agreement (SLA) obligations, cloud service providers (CSPs) must ensure continuous access to fault-tolerant, on-demand resources for their clients, particularly during outages. Consequently, finding …

Short-Term Load Forecasting Using Nonlinear Dynamic Time Series Autoregressive With Feedback For Azadi Control-Station Erbil-Iraq, Wafeeq Sh. Hanna, Velar H., Dlawer R. Maruf

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The load forecasting is a human or computational technique for accurate preanticipation of electrical load to enhance reliable operation and optimal planning control of system plant for electrical energy flowing without facing any economical and technical limitations, therefore appropriate estimation for present and future consumption cost of electrical loads which are necessary to predict the load demand for generating near to accurate power. During advanced technology at the last few decades, artificial neural networks(ANNs) have been extensively employed in electrical system, they are trained using historical data obtained from plant station. This work is intended to be a study of …

Improve Multi-Object Detection And Tracking For An Automated Traffic Surveillance System, Rashad N. Razak, Hadeel N.

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Multi-Object Detection and Tracking (MODT) are essential in many application fields. Still, many enhancements in the speed of detection and tracking were required to overcome the challenges during implementation. This paper presents a new algorithm system for (MODT) to improve the execution time to be robust in real-time applications. A background subtraction detection algorithm with a Kalman filter was used to track and predict the object position and speed parameters. To improve the processing time, its needs to reduce some frames in a way that does not affect the detection accuracy too much and instead use the prediction and the …

A Survey On Business Intelligence Approach Based On Deep Learning, Asaad R. Kareem, Hasanen S.

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The article provides an overview of two recent developments in technology: Business Intelligence (BI) and Deep Learning (DL). In order to support decision-making processes, BI entails gathering, integrating, and analyzing data from various sources, while DL uses artificial neural networks to learn and generate predictions from complicated datasets. This paper introduces the concepts and principles and highlights recent developments and applications in different domains of research: education, organizations, stock market, forecasting, decision-making in real-time, and security. However, the fundamental problem with the business intelligence approach is that there is no learning inVolved. Other limitations and challenges include the capacity that …

A Hybrid Fault Detection And Fault Tolerant Control Based On Knn And Nn Approaches For Abs Speed Sensors, Ayad Q. Abdulkareem, Abdulrahim Th., Oday A. Ahmed

Iraqi Journal of Computers, Communications, Control and Systems Engineering

To perform fault tolerance for Anti-lock Braking System (ABS), This paper proposes a hybrid Fault Detection and Fault Tolerant Control (FD-FTC) for ABS speed sensors. It utilizes a Fault Detection (FD) unit and a Data Construction (DC) unit. The first one, the FD unit, is based on a kNN classifier model with 99.9% fault detection accuracy to perform three tasks: early fault detection, fault location diagnosis, and excluding faulty signals from being utilized in further processes. On the other hand, the second one, the DC Unit, is based on two separate neural network models. These models have an MSE of …

Design Of Face Detection And Recognition System To Enhance Security Of Safe Locker, Mohammed Majid Msallam

Iraqi Journal of Computers, Communications, Control and Systems Engineering

In recent years, safe lockers have been spread in public places to secure valuable belongings. The people are concerned about losing safe locker keys or use of the spare key by others and will remain worried about their things. To solve the forenamed matter, this paper proposed a system that depends on biometrics to secure valuable things and can minimize their concerns and worries. The proposed system consists of two major parts, software, and hardware. In the hardware part, A microcontroller with a camera and an electronic lock will be used to securely open or close the door of the …

Dynamic Shifts In Digital Currencies: Tracing The Evolution Of Digital Currencies From Bitcoin's Inception To 2023, Asmaa A. Mohammed, Abdul Monem S., Hala B. Abdulwahad

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The rapid "development of communication technology" has had a considerable impact on financial transactions, leading to the appearance of new types of "currency." These digital currencies are intended to streamline processes, decrease time and effort expenditures, and minimize financial losses while doing away with the need for traditional financial intermediaries and central bank regulation. Despite persistent worries and hazards that remain in the minds of people participating in currency trading and stock exchanges, digital currencies have significantly impacted the global financial industry. The fundamental Issue with digital currencies is the question of the legal and regulatory frameworks. Since digital currencies …

Ensemble Feature Selection For Age Estimation From Speech, Umniah Hameed Jaid, Alia Karim

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The voice signal carries a wide range of data about the speaker, including their physical characteristics, feelings, and level of health. There are several uses for the estimate of these physical characteristics from the speech in forensics, security, surveillance, marketing, and customer service. The primary goal of this research is to identify the auditory characteristics that aid in estimating a speaker’s age. To this end, an ensemble feature selection model is proposed that selects the best features from a baseline acoustic feature vector for age estimation from speech. Using a feature vector that covers various spectral, temporal, and prosodic aspects …

Analytical And Comparative Study For Optimization Problems, Sanaa Ali Jabber, Soukaena H., Shatha H. Jafer

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Finding an optimal solution to some problem, like minimizing and maximizing the objective function, is the goal of Single-Objective Optimization (SOP). Real-world problems, on the other hand, are more complicated and inVolve a wider range of objectives, several objectives should be maximized in such problems. No single solution could be enhanced in all objectives without deteriorating at least one other goal, which is the definition of Pareto-optimality. Understanding the idea of MultiObjective Optimization (MOP) is thus necessary to find the optimum solution. Multiobjective eVolutionary algorithm (MOEA) are made to simultaneously assess many objectives and find Pareto-optimal solutions, MOEA can resolve …