Electrical and Computer Engineering Commons^™

Modern Significance And Development Trends In The Production Of Vegetable Oils, Umidjon Ruziev, F.O. Qosimov, M.K. Shodiev

Chemical Technology, Control and Management

This article provides a comprehensive analytical review of the current state of the global vegetable oil production market. It describes the diversity of raw materials supplied, which includes both traditional and emerging fat sources. The paper also describes the technological stages of production, emphasizing modern innovations that contribute to more efficient, high-quality, and safe production. The article also covers global trends by comparing production dynamics between countries, highlighting regions with the highest rates of production growth and explaining the reasons for their competitive advantages. Particular attention is paid to environmental and socio-economic aspects, including sustainable land use, certification, carbon footprint, …

Investigation Of The Fuel Combustion Process In Gas-Fired Furnaces For Automation Systems, N.R. Yusupbekov, Sh.M. Gulyamov, A.T. Rajabov, U.U. Kholmanov

Chemical Technology, Control and Management

The regularities of the combustion process of gaseous fuel in chamber furnaces are described. This process represents a homogeneous reaction in which there is no distinct boundary surface between the fuel and the oxidizer. It is shown that the latter either mix and then burn subsequently, or both processes occur simultaneously, corresponding respectively to kinetic and diffusion combustion. The structure of a turbulent-diffusion flame of gaseous fuel combustion is presented.

Development Of Fire Prediction And Prevention Digital System Algorithms, Oybek Zokirovich Koraboshev

Chemical Technology, Control and Management

This research work is devoted to the development of algorithms for a digital system aimed at early detection, prediction and prevention of fire hazards. In the work, the process of fire hazard assessment is modeled on the basis of modern information technologies and artificial intelligence tools. The main focus is on collecting data in real time, analyzing it and creating algorithms that determine the level of danger. In the process of research, methods of data cleaning, normalization and determination of correlation between variables were used to process multidimensional data streams obtained from various sensors (temperature, smoke, gas concentration and humidity …

Algorithms For The Synthesis Of A Temperature Control System For The Inner Tube Heat Exchanger With A Steam Jacket, H.Z. Igamberdiyev, Jasur Sevinov, U.F. Mamirov, Sh.M. Abdishukurov

Chemical Technology, Control and Management

The synthesis of a feedback propagation control law for an inner tube heat exchanger with a steam jacket is addressed in this text. A controller has been developed that, based on temperature measurements taken at four points. The maintains the output temperature at a specified level by acting on the steam jacket temperature. To determine the parameters of the plant, a linear quadratic optimal (LQ-optimal) algorithm is employed. In the considered case, the optimal controller includes a proportional–integral (PI) component, as well as an additional term that requires storing the control input over the current interval for its computation. The …

Intelligent Method Of Dynamic Control For A Class Of Stochastic Nonlinear Systems, Isamidin Khakimovich Siddikov, Davronbek Abdalimovich Khalmatov, Gulchekhra Rakhimjanovna Alimova, Dilnoza Rakhmanovna Khushnazarova

Chemical Technology, Control and Management

The paper considered the problems of researching the stabilisation system and backstepping control of stochastic nonlinear systems. The characteristics of stochastic nonlinear dynamic control systems are random signals with normal lawful distribution, which significantly complicates task control. In stochastic control, it is necessary to determine the trajectories of the control variables in order to achieve the desired control objective at minimum cost. Since the mathematical equations of stochastic nonlinear systems are not always constant, not every model-based controller can be accurate. Therefore, in this work, a neuro-fuzzy network is used to evaluate the parameters of the control system with backstepping, …

Reinforcement Learning In A Virtual World: A Study Of Ppo And Sac Within Unity Ml Agents, Rufat Mammadzada

Chemical Technology, Control and Management

This study explores the use of Unity3D as a versatile platform for developing, training, and evaluating intelligent agents through reinforcement learning. Leveraging the Unity ML-Agents Toolkit, a dynamic 3D environment was created to examine agent learning behavior using two advanced algorithms: Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC). The simulation environment consisted of navigable terrain bounded by red borders, with collectible blue balls serving as rewards and a purple cube representing the agent. A carefully designed reward system was implemented to encourage goal-directed behavior and penalize inefficiency, while time constraints introduced an additional challenge requiring both precision and speed. …

Possibilities Of Digitizing And Applying Artificial Intelligence To National Occupational Classification (Noc-2025) In Uzbekistan, Shohrux Nurali O‘G‘Li Narzullayev

Chemical Technology, Control and Management

This article examines the process of digitizing National Occupational Classification (NOC-2025) in Uzbekistan, developed on the basis of the International Standard Classification of Occupations (ISCO-08), and the possibilities of applying artificial intelligence technologies to it. Although this classification exists today in a national form, and its digitization and the introduction of artificial intelligence elements to it based on modern technologies remain a pressing issue. In order to digitize the classification, international systems such as the International Standard Classification of Occupations (ISCO-08, ILO), European Skills, Competences, Qualifications and Occupations (ESCO), Occupational Information Network (O*NET, USA) and National Occupational Classification (NOC, Canada) …

Generation Expansion Planning: Transitioning Toward Decarbonization With A Focus On Reliability And Dunkelflaute, Taraneh Ghanbarzadeh, Daryoush Habibi, S. M.Muslem Uddin, Asma Aziz

Research outputs 2022 to 2026

Modern power systems increasingly rely on variable renewable energy sources, supported by energy storage systems and gas power plants, to meet decarbonization targets. However, the high penetration of renewables introduces significant uncertainty due to their weather-dependent nature, posing challenges to system reliability. This paper proposes a probabilistic, multi-level generation expansion planning framework that integrates reliability assessments, with a particular emphasis on the role of energy storage systems. A novel probabilistic approach is also introduced to model the Dunkelflaute phenomenon and evaluate its impact on system reliability. Additionally, the study explores the influence of regulatory mechanisms — referred to as embedded …

Harmonic Mitigation In Unbalanced Grids Using Hybrid Pso-Ga Tuned Pr Controller For Two-Level Spwm Inverter, Pema Dorji, Taimoor Muzaffar Gondal, Stefan Lachowicz, Octavian Bass

Research outputs 2022 to 2026

This study proposes an integrated control–optimization framework for harmonic mitigation in two-level, grid-connected inverters with battery energy storage operating under unbalanced grid conditions. A proportional–resonant controller in the stationary (Formula presented.) frame and a proportional–integral controller in the synchronous (Formula presented.) frame are compared, with controller gains optimized using PSO, GA, and a hybrid PSO–GA approach. The hybrid method achieves superior trade-offs among THD, convergence speed, and computational effort. For the PR controller, hybrid PSO–GA reduces THD to 1.07%, satisfying IEEE 1547 and IEC 61727 standards, while for the PI controller it achieves 2.70%, outperforming standalone PSO (4.12%) and GA …

Adaptive Guard Band And Power Control For Resource Allocation In Mobile And Fixed Mission-Critical Iout Networks, Walid K. Hasan, Iftekhar Ahmad, Quoc Viet Phung, Daryoush Habibi

Research outputs 2022 to 2026

The Internet of Underwater Things (IoUT) is transforming underwater communication by enabling essential mission-critical applications such as precise navigation, emergency response coordination, diver safety, robust security and surveillance systems, and real-time environmental monitoring. However, Underwater Acoustic Communication (UAC), which serves as the primary communication medium for IoUT, experiences substantial challenges, including limited bandwidth availability, severe signal attenuation and Doppler-induced frequency shifts, especially pronounced in mobile underwater environments. These challenges degrade throughput and increase latency, making it difficult to meet the strict delay and reliability demands of mission-critical IoUT applications. Without adaptive solutions, real-time underwater communication remains unreliable and inefficient. This …

Cost-Optimized Energy Management For Urban Multi-Story Residential Buildings With Community Energy Sharing And Flexible Ev Charging, Nishadi Weerasinghe Mudiyanselage, Asma Aziz, Bassam Al-Hanahi, Iftekhar Ahmad

Research outputs 2022 to 2026

Multi-story residential buildings present distinct challenges for demand-side management due to shared infrastructure, diverse occupant behaviors, and complex load profiles. Although demand-side management strategies are well established in industrial sectors, their application in high-density residential communities remains limited. This study proposes a cost-optimized energy management framework for urban multi-story apartment buildings, integrating rooftop solar photovoltaic (PV) generation, shared battery energy storage, and flexible electric vehicle (EV) charging. A Mixed-Integer Linear Programming (MILP) model is developed to simulate 24 h energy operations across nine architecturally identical apartments equipped with the same set of smart appliances but exhibiting varied usage patterns to …

Crisis Observatory: Extracting Credible Signals During A Crisis In The Age Of Llms, Kuan-Chieh Lo, Pranav Maneriker, Sriram Sai Ganesh, Dominik Winecki, Kelly Garrett, Ayaz Hyder, Arnab Nandi, Valerie Shalin, Shannon A. Bowen Ph.D., Amit Sheth, Srinivasan Parthasarathy

Publications

Systems for crisis response have required several different models for the analysis of unstructured text, such as identifying needs, locations, topics, routing, and matching of needs with available responders. Large Language Models (LLMs) have replaced task-specific models across various language processing tasks. However, LLMs are known to be limited by their training data, collected before the crisis. In this demo, we explore the use of LLMs for crisis response scenarios with rapidly evolving information environments. We show how the augmentation of these models with external reliable sources of crisis-specific information can help build adaptive systems for response. The demonstration video …

باستخدام مجموعة بيانات متعددة من الطائرات بدون طيار Yolo البحث والإنقاذ البحري القائم على في ظروف الطقس الصعبة, Aysha Ali Alshebli

Theses

Object detection models, powered by deep learning and computer vision, are revolutionizing marine search and rescue (SAR). By analyzing aerial imagery and live drone footage, these systems automatically identify critical targets like survivors, life rafts, and debris across vast and treacherous ocean areas. This capability enhances operational efficiency by reducing human workload and accelerating response times, even in challenging conditions such as poor light, high seas, or cluttered backgrounds. The result is continuous monitoring, faster decision-making, and a significantly improved probability of successful rescue.

Departing from prior methodologies, YOLO introduced a paradigm shift through its single-shot architecture, which concurrently predicts …

Microstrip Antenna Design Based On Ai And Machine Learning, Waleed Mohamed Sha Moulavi

Theses

Microstrip patch antennas (MPAs) rely on precise impedance matching for efficient power transfer between the antenna and feed line. This is often achieved using a number of different techniques, one of which is the quarter-wavelength transformer (QWT). While commercial electromagnetic (EM) solvers offer robust optimization capabilities, they often operate as "black boxes" without providing physical insights into parameter interdependencies. Furthermore, this thesis focuses on the specific scenario where the antenna input impedance is purely real. To address the lack of explicit design relationships for these specific conditions, this thesis develops and comparatively evaluates artificial intelligence (AI) models for QWT width …

A Light-Dependent Resistor Based Embedded Image Acquisition System For Use In Low-Resolution Application-Specific Data Processing, Connor Best

Journal of Undergraduate Research at Minnesota State University, Mankato

This paper proposes an efficient hardware-based approach to image acquisition & processing to replace complex camera systems in simple industrial & commercial applications.

Environment Mapping And Gps-Based Trailer Parking Using Low-Cost Peripheral Sensors And Post-Processing Algorithms, Connor Best

Journal of Undergraduate Research at Minnesota State University, Mankato

This paper explores the merit of software data optimization through two practical examples: environment mapping & GPS navigation.

Model-Based Assessment Of Ocean Monitoring Temporal And Spatial Resolution Requirements For Acoustic Operations, William K. Stevens, Martin Siderius

Electrical and Computer Engineering Faculty Publications and Presentations

Understanding present and future ocean conditions is essential for the effective planning and execution of a wide range of naval and commercial acoustic operations. The four-dimensional structure of temperature and salinity}from the ocean surface to the seabed}is a critical factor influencing acoustic transmission properties. Modern numerical ocean modeling systems consist of three primary components: ocean observations, a numerical forecasting model, and a data assimilation system. Of the tens of millions of global ocean observations assimilated daily, the majority derive from satellite-based surface measurements. In stark contrast, subsurface water column measurements number only in the thousands per day. This disparity highlights …

Teaching Machine Learning To Undergraduate Electrical Engineering Students, Gerald L. Fudge, Anika Rimu, William Zorn, July Ringle, Cody Barnet

Faculty Publications

Proficiency in machine learning (ML) and the associated computational math foundations have become critical skills for engineers. Required areas of proficiency include the ability to use available ML tools and the ability to develop new tools to solve engineering problems. Engineers also need to be proficient in using generative artificial intelligence (AI) tools in a variety of contexts, including as an aid to learning, research, writing, and code generation. Using these tools properly requires a solid understanding of the associated computational math foundation. Without this foundation, engineers will struggle with developing new tools and can easily misuse available ML/AI tools, …

Development Trends And Priority Research Fields Of Electrochemical Discipline In The 15th Five Year Plan Period, Lin Zhuang, Wen-Bin Cai, Heng-Xing Ji, Qing Li, Gong-Wei Wang, Sen Xin, Qing Zhao, Fang-Yi Cheng, Yu-Guo Guo, Lan-Qun Mao, Yang Tian, Fei Wu, Li-Min Zhang, Yan Xiang, Jin-Song Hu, Rui Cao, Li Xiao, Hua-Bing Tao, Wei Xing, Dong-Ping Zhan, Hong-Gang Liao, Mei-Ling Xiao, Bin Ren, Zhang-Quan Peng, Rui Wen, Xiang Wang, Yue-Feng Song, Hou-Fu Lv, Bao-Yu Xia, Guo-Xiong Wang, Jun Cheng, Zhi-Pan Liu, Min Zhou, Bing Huang, Cun-Pu Li, Yu-Qin Zou, Shuang-Yin Wang, Hai-Bo Lin, Zi-Dong Wei

Journal of Electrochemistry

In fulfillment of the national science-and-technology development agenda, the Department of Chemical Sciences of the National Natural Science Foundation of China (NSFC) convened the Strategic Symposium on the Fifteenth Five-Year (2026–2030) Development Plan for Electrochemistry held in Xiamen on 29 August, 2025—the culminating year of the Fourteenth Five-Year (2021–2025) Development Plan. More than forty leading experts in the field of electrochemistry participated with spanning nine thematic fronts: Interfacial Electrocatalysis, Interfacial Electrochemistry for Energy Storage, Bioelectrochemistry, Electrochemistry of Hydrogen Energy, Electrochemical Micro-/Nano-Manufacturing, Operando Electrochemical Characterization, Electro-Thermal Coupling Catalysis, Theoretical and Computational Electrochemistry, and Electrochemical Synthesis. The forum assembled China’s foremost electrochemical …

High-Voltage Solid-State Lithium Batteries: A Review Of Electrolyte Design, Interface Engineering, And Future Perspectives, Cheng Yang, Zi-Xin Liang, Ming-Yun Zhang, Ming-Zhe Chen, Kai Zhang, Li-Min Zhou

Journal of Electrochemistry

Solid-state lithium batteries have become a research hotspot in the field of large-scale energy storage due to their excellent safety performance. The development of high-voltage positive electrode materials matched with lithium metal anode have advanced the energy density of solid-state lithium batteries close to or even exceeding that of lithium batteries based on a liquid electrolyte, which is expected to be commercialized in the future. However, in high voltage conditions (> 4.3 V), the decomposition of electrolyte components, structural degradation, and interface side reactions significantly reduce battery performance and hinder its further development. This review summarizes the latest research progress …

Strategies For Obtaining High-Performance Li-Ion Solid-State Electrolytes For Solid-State Batteries, Yi-Cheng Deng, Zi-Chang You, Geng-Zhong Lin, Guo Tang, Jing-Hua Wu, Zhi-Min Zhou, Xiang-Chun Zhuang, Li-Xuan Yang, Zhen-Jie Zhang, Zhao-Yin Wen, Xia-Yin Yao, Chang-Hong Wang, Qian Zhou, Guang-Lei Cui, Ping He, Hui Li, Xin-Ping Ai

Journal of Electrochemistry

With the widespread adoption of lithium-ion batteries (LIBs), safety concerns associated with flammable organic electrolytes have become increasingly critical. Solid-state lithium batteries (SSLBs), with enhanced safety and higher energy density potential, are regarded as a promising next-generation energy storage technology. However, the practical application of solid-state electrolytes (SSEs) remains hindered by several challenges, including low Li⁺ ion conductivity, poor interfacial compatibility with electrodes, unfavorable mechanical properties and difficulties in scalable manufacturing. This review systematically examines recent progress in SSEs, including inorganic types (oxides, sulfides, halides), organic types (polymers, plastic crystals, poly(ionic liquids) (PILs)), and the emerging class of soft …

A Radiation-Hardened 4-Bit Flash Adc With Compact Fault-Tolerant Logic For Seu Mitigation, Fnu Naveed, Jeff Dix

Electrical Engineering and Computer Science Faculty Publications and Presentations

This paper presents a radiation-hardened 4-bit flash analog-to-digital converter (ADC) implemented in a 22 nm fully depleted silicon-on-insulator (FD-SOI) process for high-reliability applications in radiation environments. To improve single-event upsets (SEU) tolerance, the design introduces a compact fault-tolerant logic scheme based on Dual Modular Redundancy (DMR), offering reliability comparable to Triple Modular Redundancy (TMR) while using two storage nodes instead of three, and a simple XOR-based check in place of a majority voter. A distributed sampling architecture mitigates SEU vulnerabilities in the input path, while thin-oxide devices are used in analog-critical circuits to enhance total ionizing dose (TID) resilience. Post-layout …

Design And Implementation Of A Cross-Platform, Modular Electronic-Nose System, Kaushika Rudraraju

USF Tampa Graduate Theses and Dissertations

Electronic noses (e-noses) are a subject of great research. They are useful in multiple platforms and serve a great purpose in both studies and safety. This thesis presents a portable, modular e-nose platform that spans the full pipeline from sensing to visualization, with emphasis on scalability, repeatability, and straightforward integration. The hardware is organized as swappable sensor modules each hosting multiple commercial sensors and local signal-conditioning networked to a master microcontroller via structured communication protocols. High-resolution acquisition, time alignment, and efficient streaming to a host enable reliable logging and analysis. A controlled exposure chamber and a repeatable sampling protocol (baseline-exposure-purge …

Development And Validation Of A Composite Digital Balance Score For Spinocerebellar Ataxia: A Prospective Study., James Mcnames, Vrutangkumar V. Shah, Hannah L. Casey, Kristen L. Sowalsky, Mahmoud El-Gohary, Delaram Safarpour, Patricia Carlson-Kuhta, Jeremy D. Schmahmann, Liana S. Rosenthal, Susan Perlman, Multiple Additional Authors

Electrical and Computer Engineering Faculty Publications and Presentations

Clinical trials in spinocerebellar ataxia are currently limited by the large sample sizes required by available clinical endpoints. We aimed to devise a digital composite measure of standing and walking balance using wearable inertial sensors that would require smaller sample sizes. The new score is called the Score of Integrated Balance in Ataxia (SIBA).

Measures To Improve The Structure And Operating Principle Of Perovsite Light-Emitting Devices, Latofat Utkir Qizi Shuhratova, Rustam Rashidovich Kabulov, Farrux Anvar Ugli Akbarov, Anvar Akbarovich Alimov

Technical science and innovation

Since the discovery of the unique properties of perovskite materials, these materials have been used as active layers in various optoelectronic devices. In particular, perovskite-based light-emitting diodes (LEDs) have attracted the attention of many researchers as a highly efficient and versatile technology for lighting and display devices. Perovskite-based LEDs allow for tunable light emission and can be manufactured at low cost and with flexible fabrication technology. These advantages make them suitable for use in devices ranging from modern displays to wearable electronics. Despite their potential, solving problems such as material stability and industrial scale is one of the current challenges …

Methodology For Creating An Intelligent Mechatron Module Based On A Synergistic Approach, Nurbek Rustamovich Matyokubov, Temurbek Omonboyevich Rakhimov

Technical science and innovation

This article is devoted to the methodology of creating an intelligent mechatron module based on a synergistic approach. Creating a multi-coordinate intelligent mechatron module and expanding the functional capabilities of the controlled object based on them, allows to optimize the dynamic characteristics. Also, the methodology for creating an intelligent mechatronic module based on a synergistic approach allows for the integration of electrical, magnetic, and mechanical components into a single circuit, the integration of technical parameter modification, and the integration of processing functions into a single information-measuring module. In addition, the article proposes a Eurorhythm scheme for expressing how …

The Method Of Power Networks Mode Optimization In Basis Of Genetic Algorithm, Tulkin Shernazarovich Gayibov, Gulnaz Makhmutovna Turmanova

Technical science and innovation

One of the main tasks solved in planning short-term and managing operational modes of electric power systems (EPS) is the optimization of their network modes on the adjustable parameters. For modern complex EPS, this task is often characterized by the multi-extremality of the objective function, the appearance of discontinuous functions, the presence of initial information of a probabilistic and partially uncertain nature. In such conditions, solving the problem by traditional algorithms using mainly linear and nonlinear programming methods, Lagrange, gradient, etc., is associated with a number of difficulties in simplifying them and bringing them to a convenient form for calculations. …

Comparative Assessment Of Battery And Hydrogen Energy Storage In A Grid-Connected Heat-Electricity Integrated Microgrid, Naglaa Elsherbiny, Mohamed Elgamal, Islam Ismael, Akram Elmitwally

Mansoura Engineering Journal

Given the significant challenges of conventional power systems, including high emissions and operational costs, transitioning to microgrids (MGs) is increasingly critical. This paper presents a comprehensive evaluation of three energy management strategies for a grid-connected, heat-electricity integrated MG: (i) a base case without storage, (ii) a battery-based energy storage system (B-BESS), and (iii) a hydrogenbased energy storage system (H-BESS) comprising an electrolyzer (ELC), hydrogen tank (HT), and fuel cell (FC). This study optimizes operational profit and emissions reduction by integrating renewable energy and heat recovery mechanisms. Simulation results show that, compared to the base case, both B-BESS and H-BESS significantly …

Climate Change Projections Through Optimized Machine Learning And Deep Learning Models: A Comprehensive Analysis, Hala H. Youssef, Salma S. Mohammed, Hanan M. Amer, Abeer T. Khalil

Mansoura Engineering Journal

One major worldwide issue that has far-reaching effects on environmental stability and the avoidance of natural disasters is climate change. Developing efficient mitigating strategies depends on precise climate change forecasts. To predict important climate change indicators, including temperature fluctuations, greenhouse gas (CO2, N2O, CH4, and SF6) emissions, population dynamics, sea level changes, Arctic Sea ice extent, and Antarctica mass, this study evaluated the predictive capabilities of several Machine Learning (ML) and Deep Learning (DL) techniques. The set of machine learning algorithms includes Multiple Linear Regression (MLR), K-Nearest Neighbors (KNN), Support Vector Machines (SVMs), Artificial Neural Networks (ANN), Random Forest (RF), …

An Integrated Pcb-Based Heating And Auto-Ranging Platform For Volatile Organic Compound (Voc) Detection Using Carbon Nanotube Based Sensors, Thomas Kalach

USF Tampa Graduate Theses and Dissertations

This thesis presents the development, characterization, and integration of a novel low-cost, high-dynamic-range sensor platform for the detection of volatile organic compounds (VOCs), leveraging the unique electrical properties of carbon nanotube (CNT) thin films. The platform introduces a fully integrated auto-ranging analog front-end circuit capable of real-time resistance measurement spanning over eight orders of magnitude ranging from tens of ohms to hundreds of megaohms, without compromising signal resolution or precision. This was achieved through a digitally controlled, multi-path feedback architecture and controllable current source.

To further enhance sensor performance, the system incorporates a copper trace heater beneath the sensor array, …