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Structural Decomposition-Based Control Synthesis For Multivariable Systems Using Oblique Projection Operators, Abdukaxxarov Inomjon Ilxom Ugli Mr, Oripjon Olimovich Zaripov, Jasur Usmonovich Sevinov

Chemical Technology, Control and Management

This paper proposes a novel approach to control synthesis for multivariable systems with algebraic constraints using oblique projection operators and their structural decomposition. The method transforms a standard control law into a structured form by decomposing the control input into constraint-satisfying and null-space components. A generalized oblique projector is constructed using a dual matrix, ensuring flexibility in shaping system properties. Furthermore, a recursive decomposition algorithm is developed, allowing the global projector to be represented as a sum of local operators corresponding to subsystem structures. The proposed framework enables modular control design, decoupling of interactions, and efficient implementation for large-scale systems. …

Using Ali-4 Z-Implication In Controller Design, Shamil Azer Ahmadov

Chemical Technology, Control and Management

One of the widely used theories in the information processing is Professor Zadeh's fuzzy logic theory. Fuzzy implications form the basis of this theory. When processing information using fuzzy implication, the chosen judgment method and the type of implication affect the result. Referring to the review of the relevant literature on fuzzy implications, it can be noted that there are still unresolved problems and issues. For example, fuzzy implications cannot be used in processing imperfect information or information based on probabilistic and fuzzy uncertainty. Existing fuzzy implications face limitations in practical applications. Fuzzy implications only take into account inaccuracy, but …

Enhanced Parametric Approach For Solving Interval-Valued Trapezoidal Neutrosophic Linear Fractional Programming Problems, Hamiden Abd El- Wahed Khalifa H.A.Khalifa, Moodi Abdulrahman Abdullah Al-Rajeh, Sultan S. Alodhaibi

Neutrosophic Systems with Applications

Neutrosophic sets (NSs) generalize the classical versions, by providing a flexible framework capable of representing incomplete, inconsistent, and unclassified data that frequently arises in practical decision frameworks. In this study, a linear fractional programming (LFP) problem with uncertain parameters is investigated. All coefficients in the objective function (OF) as well as the left- and right-hand sides of the constraints are represented using fully trapezoidal neutrosophic numbers (NNs). By employing a suitable score function, the proposed neutrosophic LFP model is transformed into an equivalent scalar LFP problem. Subsequently, a parametric solution procedure is established to regulate the neutrosophic optimum solution. This …

Modeling Agentic Artificial Intelligence Uncertainty In Agriculture Based 6generation: A Hybrid Q-Rung Orthopair Fuzzy Mcdm Methodology, Zekra Sakr, Mona Mohamed

Neutrosophic Systems with Applications

In era of advanced intelligent revolutions, the collaboration between intelligent technologies became imperative. For instance, integrating 6G communications with agentic artificial intelligence considered a catalyst to shift agriculture sector into optimized and intelligence sector. This integration resulted in transitioning the sector from static automation to autonomous, agent-based ecosystems. Accordingly, the efficiency roles for artificial intelligence agents (AIAs), deploying and selecting optimal AIA is important. Yet, selection process is still difficult because agricultural criteria are multifaceted and there are inherent environmental uncertainties. To address these challenges and bolster the selection process, this paper suggests a hybrid multi-criteria decision-making (MCDM) that bolstered …

Gauss Elimination Method For Solving The System Of Neutrosophic Linear Equations, Elsayed Badr, Shokry Nada, Saeed Ali, Aya Rabie

Neutrosophic Systems with Applications

This paper proposes a unified computational framework for solving linear systems under trapezoidal Neutrosophic uncertainty. The system is formulated as A( I )x = b( I ), where both the coefficient matrix and the right-hand side vector incorporate an indeterminacy parameter I, expressed as A( I ) = A₀ + IA₁ and b( I ) = b₀ + Ib₁. A decomposition strategy is developed to separate the model into deterministic and indeterminacy components, yielding a solution of the form x( I ) = x₀ + Ix₁. The deterministic component is obtained via …

Uncertainty Handling In Stock Market Prediction: A Fuzzy Markov Chain Approach, Alpa Singh Rajput, Arpan Singh Rajput

Neutrosophic Systems with Applications

Predicting the stock market is never easy because it is influenced by many uncertain and constantly changing factors such as economic conditions, investor behaviour, and global events. Traditional models like the Crisp Markov Chain (CMC) try to predict market movements by using fixed probabilities for different states like bullish, bearish, or stagnant. However, real markets do not behave in such a strict way—they often move gradually between states, which these models fail to capture. To overcome this limitation, this study introduces a Fuzzy Markov Chain (FMC) model, where fuzzy logic is used to handle uncertainty and allow smoother transitions between …

An Improved Logarithmic Ratio-Product Type Estimator For Mean Modeling And Estimation Under Neutrosophic Uncertainty, Anchal Yadav, Mukesh Kumar

Neutrosophic Systems with Applications

In classical statistics, population mean estimation generally assumes precise and determinate data along with known auxiliary information. However, in real-world situations where observations are imprecise or expressed in interval form, such as temperature variations or financial market data, classical approaches become less effective. To address this limitation, neutrosophic statistics provide a more flexible framework for handling uncertainty and indeterminacy. This study proposes a neutrosophic logarithmic ratio-product type estimator for estimating the finite population mean using auxiliary information. The bias and mean squared error (MSE) of the proposed estimator are derived using a first-order approximation. Furthermore, performance evaluation is carried out …

Efficient Energy Management In Networked Microgrids Using Multi-Agent Deep Reinforcement Learning In The Presence Of Uncertainties, Ayodele Benjamin Chukwuyem

Thesis/ Dissertation Defenses

Microgrid technology is essential in facilitating the transition to smart energy grids in developed countries and mitigating energy poverty in developing countries, particularly in areas where grid extensions are not feasible. Recently, the concept of networked microgrids (NMGs) has garnered tremendous attention due to the plausibility of interactions among interconnected microgrids leading to power networks that are more resilient, reliable, and stable. However, because each microgrid has diverse distributed generation resources (renewables and controllable generators) and each microgrid operator (MO) has different objectives, coordinated energy management is required to satisfy local and system-wide goals under conditions with significant uncertainty. Existing …

The Pid-Based Three Quadcopter Uavs Formation Control Under External Disturbance, Vo Van An, Trinh Luong Mien

Makara Journal of Technology

This paper presents the design and evaluation of a formation control strategy for three quadcopter UAVs, based on a PID controller in a leader–follower structure, under the influence of external disturbances. Each UAV employs a six-degree of-freedom dynamic model and utilises a cascade PID control architecture, in which the inner control loop stabilises the attitude. In contrast, the outer control loop regulates position and maintains the formation. The PID parameters are tuned using the Ziegler–Nichols method to ensure simple implementation and low computational cost. The performance of the control system is evaluated through simulations in the MATLAB environment for two …

Multicriteria Analysis Of Vehicle Exhausts Emission Using Fuzzy Analytic Hierarchy, Sunday Ayoola Oke, Ibraheem Adedotun Abdul, Ismaila Badmus, John Rajan, Swaminathan Jose, Adekunle Adetayo Yekinni, Kabiru Alani Olaiya, Mofoluwaso Kehinde Adeniran, Pandiaraj Benrajesh

Makara Journal of Technology

This study employs the fuzzy analytic hierarchy process (FAHP) to identify the critical factors and their degree of relevance to the vehicle emission process. Its innovation lies in the potential to blend ambiguity and uncertainty with the established AHP. FAHP transforms information into a defuzzification state through signal-to-noise ratios, normalization, and pairwise comparison. The principal parameters considered are revenue, sold packing units, CAGR, packing materials, consumption, and CO2 emissions (A, B, C, D, E, and F, respectively). From the normalized defuzzified weight result, consumption (Parameter E) is the best (normalized weight, 0.8685917), while CO2 emissions (Parameter F) was the worst …

Optimization Of A Point Absorber Wave Energy Converter (Wec), Rutwa Dilipkumar Nagar

Electronic Theses and Dissertations 2020 - Present

This study examines the performance and optimization of a point absorber wave energy converter with a partially submerged spherical float. A comprehensive open-source computational framework integrates frequency-domain hydrodynamic analysis with time-domain simulation using Capytaine, BEMIO, and WEC-Sim. Hydrodynamic coefficients such as added mass, radiation damping, and excitation forces are calculated and integrated into the governing equation of motion using the Cummins formulation. A parametric analysis varies the float diameter and geometric configurations across several cases. Hydrodynamic coefficients and response amplitude operators are assessed to analyze system behavior and resonance characteristics. Results indicate consistent trends in normalized added mass, with radiation …

Individualized Models For Perception And Cognition, Dominic Marticorena

McKelvey School of Engineering Graduate Student Theses & Dissertations

This dissertation develops individualized models of perceptual and cognitive behavior, inferring latent capacities from limited data with sufficient efficiency, precision, and generality for person-level prediction. In perception, a nonparametric Bayesian framework for adaptive psychophysics is extended from audition to vision, producing an estimator that recovers dense individualized contrast sensitivity profiles through variational inference, a generalized kernel, and information-guided stimulus selection. A multitask extension enables simultaneous estimation of multiple psychometric fields by exploiting shared latent structure. Transferring this inferential logic to cognition, where relevant dimensions must be supplied by task design rather than physics, requires new measurement infrastructure. A Minecraft-based platform …

Inference-Time Scaling For Robust And Adaptive Computational Imaging, Yuyang Hu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Computational imaging has transformed fields such as medical imaging, computational photography, and remote sensing by combining physical measurement models with advanced image reconstruction algorithms. Two major paradigms have driven significant progress: model-based deep learning (MBDL), which integrates learned priors with physics-based data consistency, and generative models, especially diffusion models, which capture complex image distributions and enable posterior sampling for uncertainty quantification. Despite their success, most existing methods still operate under static inference: they rely on fixed pretrained priors, predetermined sampling procedures, and a fixed forward model during reconstruction. This rigidity limits their robustness in the presence of distribution shift, complex …

Wavetable Modification In Frequency Domain: Fourier Analysis With Matlab Implementation, Caleb Kortens

Senior Honors Theses

One of the challenges in creating computer generated music is producing life-like sounds. Music produced through computer synthesis can often sound thin and synthetic rather than vibrant and energetic. Wavetable synthesis is a method of waveform generation that uses a wavetable, which is a set of single period waves, or frames, that have varying characteristics. This method allows a synthesizer to transition between waveforms to produce a sound with time varying tone and harmonic characteristics. This adds life and movement to computer generated sounds. Wavetable synthesis is often used to imitate actual instruments, but unique wavetables can be created that …

Molecular Catalysts For Electrochemical Nitrogen Activation Toward Sustainable Ammonia Synthesis, Jin-Xiu Han, Hao Xue, Xian-Biao Fu

Journal of Electrochemistry

Homogeneous electrocatalytic nitrogen reduction reaction (NRR) provides a powerful framework to interrogate molecular nitrogen-fixation pathways under mild conditions. By tuning the metal center, ligand architecture, and reaction medium, these systems enable capturing key intermediates and delivering mechanistic insight at the molecular-level resolution. Nevertheless, advances remain constrained by highly reduced operating potentials, intense competition from the hydrogen evolution reaction (HER), limited durability in turnover, and inadequate long-term stability.

In this review, we take electron delivery to the molecular active site as the guiding principle for organizing homogeneous electrochemical N₂ activation and transformation. We classify reported systems into direct electron transfer …

Water-Driven Solid Electrolyte Interphase Governs Continuous-Flow Ammonia Electrosynthesis, Peng-Bo Liu, Sheng-Liang Zhai, Ji Huang, Zhong-Shuo Zhang, Jie Zeng, Shao-Feng Li

Journal of Electrochemistry

Flow-cell architectures have emerged as a powerful platform for continuous and stable lithium-mediated nitrogen reduction (Li-NRR), enabling ambient-condition electrochemical ammonia synthesis and offering a promising alternative to Haber-Bosch processes. However, Li-NRR is exceptionally sensitive to trace water, and even minor variations in water content can profoundly alter interfacial chemistry. Here, we systematically investigate how initial water concentration affects Li-NRR performance in a continuous-flow cell. Excess water drives the formation of a thick solid electrolyte interphase (SEI) layer, which may impede nitrogen access to metallic lithium and hinder lithium-ion transport. As a result, the ammonia Faradaic efficiency collapses from ~61% to …

Insertion Of Noble Metal Free Cathodic Catalyst Layer With Fe-N-C Catalyst For Boosted Performance Of Pemfc, Shi Zhou, Muhammad Tariq, Asif Nadeem Tabish, Muhammad Salman, Fan-Di Ning, Muhammad Rayyan Tayyab, Ran-Ran Peng, Meng-Geng Hao, Wen-Mu Li, Xiao-Chun Zhou

Journal of Electrochemistry

Economical Fe-N-C catalysts are considered as promising alternatives to platinum group metal catalysts for proton exchange membrane fuel cells (PEMFCs). Despite exhibiting robust activity on rotating disk electrodes, their performance within membrane electrode assemblies often experiences limitations, such as decreased O₂ diffusion, high H₂O₂ formation, low proton conduction, and a lower electron transfer number. In this study, key factors, including proton transport, electron conduction, and gas diffusion within air-breathing PEMFCs, have been investigated by adjusting cathode catalyst layer (CCL) compositions. From the experimental results, the optimal peak power density was obtained when the loading of Fe-N-C …

On Time-Series Analysis By Structured Matrix Decompositions With Applications To Signal Direction-Of-Arrival Estimation, Georgios Ierotheos Orfanidis

Electronic Theses and Dissertations 2020 - Present

Modern autonomous systems operating in highly dynamic, non-stationary environments require reliable inference from short, potentially corrupted time-series measurements, where conventional statistical methods relying on large-sample support and stationarity assumptions become fundamentally inapplicable. This dissertation develops a unified, model-free theoretical framework for time-series analysis, with a particular application to signal Direction-of-Arrival (DoA) estimation, grounded in structured matrix decompositions under both the L2-norm and L1-norm formulations.

We first approach the problem from a conventional viewpoint by carrying out standard matrix analysis directly on Hankel-structured representations of time-series data. In this context, we demonstrate that L1-norm decompositions of Hankel matrices offer strong resistance …

A Comparative Study Of Tin Electrorefining In Molten Licl–Kcl–Cacl₂: Experimental Two-Electrode Current Control And Theoretical Three-Electrode Potential Control, Bryant Johnson, George Ankrah, Ander Fuller, Devin Rappleye

Reviews, Analyses, and Instructional Studies in Electrochemistry (RAISE)

Molten salt electrorefining is a mature technology for metal recovery, yet conventional current‑controlled, two‑electrode operation provides limited electrochemical selectivity and restricted insight into electrode‑specific behavior. In this work, a simplified model is developed to compare current‑controlled two‑electrode electrorefining data with a potential‑controlled three‑electrode electrorefining simulation using tin in molten LiCl–KCl–CaCl₂ as a surrogate for plutonium processing. The model examines anodic and cathodic limitations under fixed‑potential operation and evaluates implications for selectivity, efficiency, and runtime relative to experimentally demonstrated two‑electrode performance. Results indicate that independent potential control enables operation closer to thermodynamic selectivity limits, with the potential to suppress impurity oxidation …

Open Multi-Agent Systems: The Free-Range-Zoo Framework And Moasei Competition, Ceferino J. Patino Iv

School of Computing: Dissertations, Theses, and Student Research

The field of multi-agent reinforcement learning (MARL) has made significant strides in addressing sequential decision-making problems under uncertainty. However, traditional MARL frameworks assume closed-world settings with fixed agent sets, static task distributions, and unchanging environment dynamics. This thesis presents two complementary contributions that advance the state of open-world multi-agent systems research: (1) the free-range-zoo framework, an open-source environment suite for MARL in open environments featuring dynamic agent populations, evolving task sets, and changing operational frames; and (2) the MOASEI Competition, an international benchmarking event that leverages free-range-zoo to evaluate how artificial agents handle openness in complex, partially observable domains. The …

Extraction And Interpretation Of Eeg Features For Diagnosis And Severity Prediction Of Ad And Ftd Using Deep Learning, Tuan Vo

Electronic Theses and Dissertations 2020 - Present

Alzheimer’s disease (AD) is the most common form of dementia and is characterized by progressive cognitive decline and memory impairment. Frontotemporal dementia (FTD), the second most prevalent form, primarily affects the frontal and temporal lobes and often leads to changes in personality, behavior, and language. Due to overlapping clinical symptoms, FTD is frequently misdiagnosed as AD. Electroencephalography (EEG) offers a portable, non-invasive, and cost-effective method for studying brain activity; however, its diagnostic utility for differentiating dementia subtypes is limited by signal complexity and noise. In this dissertation, I propose an EEG-based feature extraction framework that leverages deep learning to identify …

2026 - The Thirtieth Annual Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the 30th Annual Symposium of Student Scholars, held on April 22-24, 2026. Includes abstracts from the presentations and posters.

Mechanisms Behind The Impacts Of Co2 Concentration On Microbial Methanogenesis In Coal Seams, Wang Junyu, Liu Bingjun, Jiang Xiangqing, Chen Ruifeng, Xue Sheng, Zhou Wanlong, Yang Yundu

Coal Geology & Exploration

Background Coal seams exhibit the extensive distribution of a variety of indigenous functional microorganisms. Among these, some archaea enable methane metabolism using CO₂ as a substrate, providing the potential for the biological CO₂ storage and utilization in coal seams. However, conventional studies focus primarily on the degradation characteristics of coal matrix, leading to a lack of a systematic understanding of the mechanisms governing the adjustment of the methanation process in CO₂-bearing environments. Methods This study investigated the bituminous coals with a high volatile content in the Huainan mining area. Using laboratory-scale experiments on methanogenesis through anaerobic …

Dynamic Response Characteristics And Failure Mechanism Of Coal-Rock Combination Under Different Immersion Conditions, Zhang Xiangyang, Tong Zhipeng, Duan Yungang, Yang Weikun, Chen Jianben, Xu Linfeng

Coal Geology & Exploration

Background In practical engineering, the waterproof coal pillar usually suffers from different degrees of dynamic load from the overlying strata, and its internal water distribution is non-uniform. Although the traditional “water content” index can reflect the overall water content, it is difficult to describe the non-uniform characteristics of the soaking space. Therefore, it is of great significance to clarify the dynamic failure mechanism of coal and rock mass under different immersion conditions for stability zoning control. Methods On this basis, the coal–rock combined bodies under three different forms of immersion, namely: complete immersion, unilateral immersion, and non-immersion were prepared. These …

Mechanisms Underlying Lateral Force Applied To A Pdc Cutter On A Pdc Drill Bit During Rotary Rock Breaking, Wei Jiusen, Han Xin, Liu Wei, Gao Deli

Coal Geology & Exploration

Objective To improve the rock-breaking efficiency and durability of drill bits in the theoretical research on the optimal design of drill bits, the key is to systematically reveal both the rock-breaking mechanisms of polycrystalline diamond compact (PDC) cutters and the characteristics of forces applied to them. Methods Existing studies on rock breaking using a single PDC cutter generally adopt a linear or approximately linear cutting mode while neglecting the impacts of the radius of gyration. To address this issue, this study conducted experiments on cylindrical granite samples using a laboratory experimental setting for single-cutter rock breaking. With cutting depth and …

Strategic Layout And Optimization Paths Of The Standard System For The Exploration And Exploitation Of Deep Coalbed Methane, Chen Xinjun, Liu Zengqin, Shen Baojian, Zhao Shihu, Ye Jincheng, Zhang Jiaqi, Wang Tianyun

Coal Geology & Exploration

Objective In China, the deep coalbed methane (CBM) industry has emerged as a key sector for the reserve growth and production addition of natural gas. However, the current CBM technical standard system, which was developed based on shallow CBM practices, is incompatible with the demands for the exploration and development of deep CBM. To address this challenge, this study proposes the optimization paths of the current standard system, aiming to provide standardization support for large-scale exploitation of deep CBM.Methods Deep CBM reservoirs exhibit complex geological conditions of high temperature, pressure, and in-situ stress, as well as the CBM occurrence …

Structural Design And Parameter Optimization Of A Vibration Absorber For Rescue Casing-While-Drilling Rigs, Liu Pu, Yao Ningping, Zou Zujie, Fan Dong, Wei Hongchao, He Binjie

Coal Geology & Exploration

Objective Rescue drilling rigs undergo intense vibration at borehole mouths when operating in a confined underground space of coal mines. To address this issue, this study designed a compact multi-directional, passive dynamic vibration absorber, aiming to improve the operational stability and safety of the rigs. Methods Based on the spring-mass-damping system theory, a stepwise optimization design method was proposed for the longitudinal and transverse dynamic models of the vibration absorber. For the longitudinal vibration model, the particle swarm optimization (PSO) algorithm was applied for multi-objective parameter optimization. In contrast, for the transverse vibration model, the fixed point theory was employed …

Exploring The Vertical Heterogeneity Of Extremely Thick Aquifers In Coal Mines Through Layered Fine-Scale Pumping Tests, Guo Xiaoming

Coal Geology & Exploration

Objective Extremely thick aquifers in mining areas typically exhibit strong heterogeneity and high water yield. Therefore, they are prone to cause severe water inflow in mines and induce water disasters, representing a major factor affecting the mining safety of numerous mines in China. However, the vertical heterogeneity of these aquifers remains poorly understood, emerging as a primary bottleneck in the prevention and control of such water hazards. Methods To scientifically reveal the vertical heterogeneity characteristics of extremely thick aquifers, this study investigated the extremely thick Luohe Formation aquifer in a coal seam roof of a representative coal mine in the …

Mechanisms Behind Thermal Evolution Of The Structural Alignment Of Polycyclic Aromatic Hydrocarbons In Coals: Implications For Structural Transition Of Coal Macromolecules, Song Yu, Jiang Bo, Cheng Guoxi, Zheng Sijian, Li Ming, Ge Yao, Dai Yan, Wang Qian, Feng Guangjun

Coal Geology & Exploration

Objective Coals are highly sensitive to variations in temperature and pressure conditions. The structural evolution of coal macromolecules, driven by tectono-thermal processes, is the key to understanding coal rank transition and geological evolution. The structural alignment of polycyclic aromatic hydrocarbons (PAHs) in coals represents a critical indicator for characterizing coal rank transition and geological evolution. However, due to limited studies, there is a lack of systematic experimental demonstration and theoretical support for the structural alignment and microstructural characteristics of PAHs in coals, as well as their intrinsic relationships with the structural transition of coal macromolecules, during pyrolysis. Methods This study …

Sedimentary Characteristics And Coal Accumulation Patterns Of The Permian Shallow-Water Deltas In Shandong And Its Adjacent Regions, Feng Kai, Li Zengxue, Li Ying, Li Xuchao, Zhang Hui, Zhou Xiaojuan

Coal Geology & Exploration

Objective The Shanxi Formation, deposited during the critical transitional period from the sedimentary filling of epicontinental sea basins to the sedimentation of continental basins, exhibits well-developed shallow-water delta systems and significant coal-forming processes. This study aims to reveal the characteristics of sedimentary environment transformation during the late stage of sedimentary filling of epicontinental sea basins in North China. To this end, the Early Permian shallow-water delta systems in Shandong and its adjacent regions during that period was investigated, including their primary sedimentary characteristics, the predominant bases of sedimentary transformation, and the lithofacies paleogeographic characteristics of coal-forming processes.Methods Based on …