Digital Commons Network^™

Scaling Logical Reasoning On Modern Hpc Hardware, Yihao Sun

Dissertations - ALL

Deductive logic reasoning has evolved from a theoretical symbolic artificial intelligence tool into a massive computational workload. Modern domains, ranging from static program analysis and binary reverse engineering to knowledge-graph reasoning, rely on Datalog, a logical query language, to express deeply recursive, declarative specifications. However, scaling logic reasoning to these industrial workload exposes two interlocking ceilings in traditional engines. Architecturally, the memory bandwidth and parallel throughput of single-node CPUs fall drastically short of the read- and write-heavy demands of semi-naive evaluation. Asymptotically, traditional query processing algorithms, such as binary join algorithms generate massive intermediate relations that exhaust device memory on …

A Comparative Study Of Attitudes Towards Trust In Ai And Ethics In Ai Between Indian International Students And American Students In The Us Universities, Niraj Sitaula

Dissertations - ALL

This dissertation shows that Indian international students studying AI in the US universities have different attitudes towards trust in AI and ethics in AI compared to American students studying AI in the US universities. This dissertation used the survey method and examined 447 survey responses from Indian international students and American students from 97 universities in the US. Trust in AI was analyzed with three constructs of trust: dispositional trust, functionality trust, and institutional trust. Likewise, the attitude towards ethics in AI was examined using three constructs: the importance of ethical principles for AI, attitude towards transparency in AI, and …

Learning Under Information And Experience Constraints In Multi-Agent Reinforcement Learning, Qinwei Huang

Dissertations - ALL

Reinforcement learning is a powerful approach for training cooperative multi-agent systems. However, it is usually studied under idealized conditions. Standard formulations assume abundant experience, reliable communication, and cleanly observable state. Physical multi-agent systems rarely satisfy these assumptions, and instead operate under several kinds of scarcity. This dissertation studies reinforcement learning for cooperative multi-agent systems under two practical resource constraints. We show that effective learning in these settings depends not only on how much communication, computation, or experience is available, but also on how limited information and experience are represented, reused, and evaluated. Part I addresses information constraints in cooperative multi-agent …

Using Low-Frequency Vibrational Spectroscopy To Develop Analytical Profiles For Polymorphic Organic Molecular Crystals, Salvatore Zarrella

Dissertations - ALL

Low-frequency vibrational spectroscopy provides a sensitive approach for characterizing polymorphism and intermolecular dynamics in organic molecular crystals. Terahertz time-domain spectroscopy (THz-TDS) and low-frequency Raman spectroscopy probe collective lattice vibrations arising from weak intermolecular interactions, offering direct insight into crystal packing, phase stability, and structural organization that is often inaccessible to conventional diffraction and mid-infrared techniques. To interpret these modes, experimental measurements are combined with periodic solid-state density functional theory (ss-DFT), which enables vibrational assignments to specific intermolecular motions, and crystal structure prediction (CSP), which maps accessible polymorphic energy landscapes. Together, these methods form a unified experimental–computational framework for understanding molecular …

Bio-Inspired Visual Intelligence: Improving Efficiency And Robustness Through Foveal-Peripheral Sampling And Learned Saccades, Jiayang Liu

Dissertations - ALL

Deep neural networks have achieved state-of-the-art performance across a wide range of computer vision tasks, yet their deployment in real-world and safety-critical domains remains limited by two major challenges: vulnerability to adversarial perturbations and high computational cost. While adversarial training can improve robustness under certain threat models, it is computationally expensive and often generalizes poorly to black-box or transferable attacks. At the same time, conventional vision pipelines process uniformly sampled high-resolution images, introducing substantial data redundancy, latency, and energy overhead. In contrast, the human visual system achieves efficient and robust perception through space-variant foveal-peripheral sampling, attention-guided saccadic eye movements, and …

Wmu Board Of Trustee Board Meeting, Thursday June 25, 2026, Wmu Board Of Trustees

WMU Board of Trustees Meetings

• Acceptance of the Agenda
• Approval of the Minutes (April 16, 2026)
• Remarks by the Chair of the Board
• Remarks by the President
• Updates by the Faculty Senate President
• Updates by the Western Student Association Speaker of the Assembly
• Updates by the Graduate Student Association President
• Western Michigan University Employee Graduates
• Academic Tenure and Promotion
•  Public Comments Regarding Action Items

Action Items

• Academic Tenure and Promotion
• Fall 2026 Differential Tuition Rates
• Fall 2026 Tuition and Required Fee Rates
• 2026-27 General Fund Operating Budget
• Teaching Assistants Union (TAU) Labor Agreement
• Michigan State Employees Association (MSEA) Labor Agreement
• President’s Annual Review/Compensation/Contract
•  Memorandum of …

Agentic Ai-Enabled Physics-Informed Machine Learning Framework For Intelligent Building Modeling, Control, And Automation, Zixin Jiang

Dissertations - ALL

Buildings account for a significant share of global energy consumption, and meeting the 2050 net-zero decarbonization targets requires retrofitting approximately 10,000 buildings per day in the United States alone. However, current human-centered workflows for building modeling, simulation, control, and operation remain too slow and labor-intensive to support deployment at this scale. This dissertation proposes an integrated two-pillar framework consisting of a physics-informed machine learning framework for integrated building modeling, control, and simulation, and a multi-agent agentic AI framework for automating building energy engineering workflows built on top of that foundation. The first pillar introduces a Physics-Informed Modularized Neural Network (PI-ModNN) …

(R2161) Robust Optimization Of Industrial Hazardous Waste Location-Routing Problem Considering Response Actions To Environmental Risk, Sharareh Teimoori, Farhad Hosseinzadeh Lotfi, Seyyed Esmaeil Najafi, Navid Rafiei

Applications and Applied Mathematics: An International Journal (AAM)

The management of hazardous industrial waste has emerged as a significant global challenge due to rapid technological advancements. Industrial hazardous waste management systems must be designed not only to be cost-effective but also to minimize environmental risks. This study proposes a mixed-integer programming model for the location-routing of industrial hazardous waste that incorporates both primary and secondary environmental risks, along with suitable response actions. Furthermore, a scenario-based robust optimization model is developed to address uncertainties in the quantities of industrial hazardous waste. A case study is conducted to demonstrate the applicability and comparative performance of the nominal and robust models. …

Subliminal Priming Effects On Motor And Cognitive Performance: Pilot Evidence With Implications For Neurorehabilitation, Rehab E Aljuhni, Ghader A Alqadhi, Saud A Alhassan, Sultan A Alanazi

Neurosciences

Objective: To investigate whether subliminal priming modalities (visual, auditory, or word-based) influence motor and cognitive performance in healthy young adults, and whether these effects vary by gender.

Methods: A total of 30 healthy adults were assigned to visual, auditory, or word-based priming using single-blind, stratified randomization. Subliminal stimuli were presented for 50 ms. Motor outcomes included reaction time on dominant (RT-R) and non-dominant (RT-L) sides, comfortable and maximal walking speeds measured by the 10-Meter Walk Test (10MWT), and functional mobility assessed using the Timed Up and Go (TUG) test. Cognitive performance assessed using the Trail Making Test (TMT). Outcomes were …

Wearable Sensor Technology And Biomechanical Gait Analysis In Post-Stroke Rehabilitation: A Review With Implications For The Saudi Healthcare System, Abdullah H. Alzahrani

Neurosciences

Stroke remains a major cause of disability worldwide, with gait impairment affecting up to 80% of survivors and contributing to long-term dependence, fall risk, and reduced quality of life. In Saudi Arabia, stroke incidence is rising, with a significant burden on younger populations and disparities in access to post-stroke rehabilitation services. Conventional gait analysis tools rely on expensive, specialized laboratory equipment, which limits their availability in low-resource and rural settings. Recent advances in wearable sensor technologies, including inertial measurement units, pressure insoles, and electromyography systems, offer portable, scalable, and cost-efficient options for assessing gait in real-world environments. These systems can …

(R2077) Enhancing Queue Management: Dynamic Server Allocation And Optional Services In Stochastic Modeling, G. Ayyappan, S. Sankeetha

Applications and Applied Mathematics: An International Journal (AAM)

Consider a queueing system with a single server, where customer arrivals follow a Markovian arrival process and service times follow a phase-type distribution. The main server has the capability to recruit an additional server when the number of customers in the system exceeds a certain threshold, denoted as L. Both servers provide normal service to customers, and optional service is provided upon request. The main server takes multiple vacations, with the durations following an exponential distribution with rate parameter η, until there is at least one customer in the system. This system can be represented as a Markov chain process, …

(R2142) Queueing System With Batched Services, Server-Controlled Re-Service, Set-Up Time And Multiple Vacation, S. Karpagam, N. Aarthy, B. Somasundaram

Applications and Applied Mathematics: An International Journal (AAM)

To analyze a bulk queueing system with server-controlled admission for reservice, low-batch service, multiple vacation and set-up time. The study explores how the server dynamically adjusts between low-batch and bulk services based on the queue size. After completing a bulk service, the departing batch may request reservice with a certain probability. However, accepting the request is not mandatory, and the server admits it with some probability. Whenever the queue becomes empty, whether after reservicing, completing service with no reservice request, or ending the low-batch service, the server enters a random-length vacation. If the queue still has less than ‘a’ customers …

(R2080) Homomorphism And Anti-Homomorphism Of Interval Valued Neutrosophic Fuzzy Ideals Of Near-Rings, K. Lenin Muthu Kumaran, S. Selvaraj

Applications and Applied Mathematics: An International Journal (AAM)

This paper introduces and elucidates the concepts of homomorphism and anti-homomorphism for interval-valued neutrosophic fuzzy ideals of near-rings. Here we proved if an interval valued neutrosophic fuzzy left ideals of R′ then its inverse image is interval valued neutrosophic fuzzy left ideals of R and converse part is true if the mapping is onto homomorphism. Additionally, we establish the notion of the direct product of n-interval-valued neutrosophic fuzzy ideals within near-rings is also a interval-valued neutrosophic fuzzy ideals of near-rings. To illustrate these concepts, we provide an example showcasing the direct product of interval-valued neutrosophic fuzzy ideals of near-rings.

(R2153) Advanced Numerical Method For One Dimensional Burgers Equation With A Source Term, Yahaya Alassane Mahaman Nouri, Djibo Moustapha, Maman Yarodji Abdoul, Saley Bisso

Applications and Applied Mathematics: An International Journal (AAM)

This paper investigates a numerical strategy for the one-dimensional Burgers equation with a nonzero source term. Such equations arise in simplified models of transport and diffusion processes and are often used to assess the performance of numerical schemes for nonlinear evolution problems. The proposed approach combines a second-order Crank–Nicolson time discretization with a projection-based procedure that separates the nonlinear convective contribution from diffusive effects. Spatial approximation is carried out using a Chebyshev spectral collocation method, which provides high accuracy for smooth solutions with a limited number of degrees of freedom. The resulting fully discretized system is solved through an iterative …

(R2124) Impact Of Delay And Awareness On Hiv/Aids Epidemic Model, Debashis Biswas

Applications and Applied Mathematics: An International Journal (AAM)

A delayed HIV/AIDS epidemic model with awareness has been taken here. Essentially, it is mentioned that the disease spreads among the population only through contact (horizontal transmission). The equilibrium points of both the proposed models are investigated, and their stability is discussed. Both models have two types of equilibria, namely the disease-free and the disease positive. The basic reproductive number of both models has been calculated by using the next generation matrix technique. In this paper, the main motivation is to find a way to decrease the disease transmission. Also discussed the impact of delay and awareness on the HIV/AIDS …

(R2138) Analytical Approaches To Integral Equations In The Dynamics Of The Oblate Spheroidal: Earth-Sun-Satellite System, Kumari Ranjana, M. Shahbaz Ullah, M. Javed Idrisi

Applications and Applied Mathematics: An International Journal (AAM)

The deployment of artificial satellites in different gravitational environments has significantly impacted space exploration. We have introduced the study of artificial satellites under the influence of gravitational forces from oblate spheroids. To confront complex obstacles the myriads of both numerical and analytical techniques have been formulated. Among these methods, a new approach involving the integration of integral equations has been introduced. This innovative approach has been applied to study the trajectories of artificial satellites as they navigate the gravitational influence of oblate spheroids. Suitable kernels have been carefully chosen to solve the integral equations. The solutions have been found and …

(R2139) Italian Domination Number For Some Classes Of Trees, Amritha Prakash, Ragukumar Pandurangan

Applications and Applied Mathematics: An International Journal (AAM)

For a graph G with vertex set V , an Italian dominating function is a function f from V to {0, 1, 2} which has the property that for every vertex which is assigned 0, it must either adjacent to a vertex assigned 2 under f or adjacent to at least two vertices assigned 1 under f. The weight of an Italian dominating function is the sum of all weights assigned to the vertices. The minimum weight of an Italian dominating function f is the Italian domination number. Finding a graph’s Italian domination number is a well-known NP-Complete problem. Even …

(R2159) A Novel Extension Of Picard’S Method For Fractional Initial Value Problems With Convergence Analysis On Finite And Infinite Intervals, Jag Mohan, Anju Sood

Applications and Applied Mathematics: An International Journal (AAM)

In recent years, fractional differential equations have emerged as powerful tools for modeling phenomena with memory and hereditary effects, owing to their non-local characteristics. These equations excel in tackling intricate problems across physics, engineering, and other fields. As analytical solutions are often infeasible, numerical methods play a vital role in their practical application. In this study, we have generalized Picard’s method to address fractional differential initial value problems with Caputo derivative, establishing an existence and uniqueness theorem applicable to both finite and infinite intervals. To substantiate our findings, we provide an example with graphical evidence demonstrating the convergence of the …

(R2175) Application Of Similarity Measures On Bipolar Complex Neutrosophic Matrices In United Nations’ Sdg-17 Using Python, T. Muthuraji, N. Krishnapraveen

Applications and Applied Mathematics: An International Journal (AAM)

The increasing complexity of decision-making environments demands mathematical frameworks capable of modeling bipolar, indeterminate, and phase-dependent uncertainty simultaneously. Bipolar Complex Neutrosophic theory provides such a structure, but the extension of similarity measures to matrix-based environments remains largely unexplored. In this study, we formally develop cosine, Dice, Jaccard, and hybrid vector similarity measures for Bipolar Complex Neutrosophic Matrices (BCNMs). Each matrix element is represented by a Bipolar Complex Neutrosophic Number (BCNN), enabling structured representation of multidimensional uncertainty within a matrix framework. We also design and implement efficient Python-based computational tools to automate similarity evaluation for BCNMs. The proposed algorithms reduce computational …

(R2185) Operations On Bipolar Complex Neutrosophic Matrices And Its Application In Un’S Sdg-14 & Sdg-3 Using Python, N. Krishnapraveen, T. Muthuraji

Applications and Applied Mathematics: An International Journal (AAM)

Decision-making in sustainability oriented environments frequently involves bipolar evaluations, indeterminate information and phase dependent uncertainty that cannot be adequately represented by existing neutrosophic matrix models. To address this limitation, this study introduces a Bipolar Complex Neutrosophic Matrix (BCNM) framework that integrates bipolar semantics with complex valued uncertainty in a coherent algebraic structure. Fundamental operations and structural properties are rigorously established to ensure mathematical consistency. To facilitate practical multi criteria decision analysis (MCDA), novel score, accuracy, and hybrid aggregation operators are developed. The computational feasibility of the proposed approach is analyzed, demonstrating linear complexity with respect to the number of alternatives …

(R2140) Verifying The Proper Efficiency In Multi-Objective Problems, Javad Bavali, Hadi Basirzadeh

Applications and Applied Mathematics: An International Journal (AAM)

Over the past decade, numerous approaches have been put forward to address multi-objective optimization problems-focusing on approximating proper efficient solutions instead of the efficient solutions. These methods are important because, according to Geoffrion’s conjecture, proper non-dominated solutions constitute a dense subset of the non-dominated solution set. In the current study, first, using the definition of Kuhn-Tucker’s proper efficiency, we present a linear subproblem that investigates the proper efficiency of a randomly selected feasible point. Additionally, the relationship between the different types of solutions to this sub-problem and the proper efficient solutions of the main problem has been analyzed. Next, we …

(R2187) Analysis Of Neurological Impairments In Hospitalized Patients Using Cubic Neutrosophic Sets, B. Anitha, M. Lavanya

Applications and Applied Mathematics: An International Journal (AAM)

This study introduces an MCDM-based framework for identifying neurological diseases in hospitalized patients using symptom-based evaluations. A team of interns, guided by the chief doctor, was responsible for determining each patient’s precise condition from the presented neurological symptoms. To enhance diagnostic accuracy, the interns employed the TOPSIS and WASPAS methods to assess and rank the potential disease options. The combined analysis yielded a clear identification of the highest ranked disease for every patient, highlighting the effectiveness of these MCDM techniques in supporting clinical decision making.

Application Of Ai Risk Prediction Tools For Cardiovascular Care In Hong Kong: A Systematic Review With Insights From Clinicians, Celine Sze Ling Chui, Celia Jiaxi Lin, Ruibang Luo, Yekai Zhou, Nadeem Qureshi, Li Wah Tam, Carmen Chan, Ian Chi Kei Wong, Kai Hang Yiu, P-Cardiac Consortium

Journal of the Hong Kong College of Cardiology

Background: Cardiovascular diseases (CVD) present a substantial burden on global and local healthcare systems, particularly within Hong Kong's overstretched public secondary care settings coupled with an aging population. The Personalized CARdiovascular DIsease risk Assessment for Chinese (P-CARDIAC), a locally developed and validated artificial intelligence (AI) powered cardiovascular risk assessment tool, offers a transformative opportunity for enhancing care through systematic risk prediction and a multidisciplinary care approach. Implementation strategies for its application in secondary care remain undefined. Methods: We gathered local insights from one expert meeting and thirteen semi-structured interviews with cardiologists and pharmacists, matched these with barriers and respective facilitators …

Drawing The Line: Roadbeds, Dedications, And Title Uncertainty In Louisiana, Mary Catherine Joiner

LSU Journal of Energy Law and Resources

No abstract provided.

Overcoming Legal And Policy Barriers To Net Energy Generation At Water Resource Recovery Facilities, David Strifling, Nigel Blake, Scout Devoti

LSU Journal of Energy Law and Resources

No abstract provided.

Balancing Innovation & Safety: The Role Of State Law As The Use Of Artificial Intelligence Increases In Oil And Gas Operations, Anna Trahan

LSU Journal of Energy Law and Resources

No abstract provided.

Mid-Barataria Sediment Diversion Project: Navigating Endangered Species Act Litigation For Human Welfare, Dane Eastman

LSU Journal of Energy Law and Resources

No abstract provided.

Much Ado Abbott Navigability: Decoupling Navigability's Roles In Natural Resources Management And Regulation Of Commerce, Mark S. Davis, Isabel A. Englehart

LSU Journal of Energy Law and Resources

No abstract provided.

(R2149) Heat, Hall, And Ion Slip Effects On Chemically Reacting Mhd Casson Flow Through Moving Surface, Gaurav Kumar, Vinod Kumar

Applications and Applied Mathematics: An International Journal (AAM)

The present investigation aims to analyze the combined effects of heat generation/absorption, Hall current, and ion slip on the flow of chemically reacting MHD Casson fluid over a moving vertical surface, considering ramped wall temperature and mass diffusion. The flow medium has been made porous. The analytical solution of the model's partial differential equations is derived using the Laplace transform technique aided by the Heaviside step function. The expressions for the Sherwood Number, Nusselt Number, and shear stress on the plate have been derived. The results obtained are found to be in outstanding agreement. The outcomes achieved are displayed through …

(R2129) Layer Resolving Classical Scheme For A System Of N Time-Dependent Singularly Perturbed Problems With Spatial Delay And Robin Initial Conditions, K. Ramiya Bharathi, G. E. Chatzarakis, M. Joseph Paramasivam

Applications and Applied Mathematics: An International Journal (AAM)

This article deals with solving a system of n time-dependent singularly perturbed problems with spatial delay and robin initial conditions. Each equation’s leading term is multiplied by a distinct small positive parameter, inducing overlapping initial layers. Due to presence of these parameters and delay terms, intricate layers occur at interior regions of the domain. To capture the behavior of these layers the solution is decomposed into two components and layer functions are also formulated. The formulation of the layer resolving numerical scheme involves temporal and spatial discretization on uniform and piecewise uniform Shishkin meshes respectively. The proposed framework is found …