Digital Commons Network^™

Deployment-Oriented Evaluation Of Temporal And Spatial Forecasting Approaches For Electric Vehicle Charging Demand In Energy Systems, Maher Alaraj, Eyob Solomon Getachew

All Works

Accurate short-term electric vehicle (EV) charging demand forecasting is important for charging infrastructure operation, grid management, and energy-system planning. This study presents a deployment-oriented and reproducible evaluation of temporal, spatial, and unified spatio-temporal forecasting approaches for day-ahead EV charging demand prediction. Using publicly available charging-session data aggregated at hourly resolution across ZIP-code regions, we compare persistence and ARIMA baselines, XGBoost, Long Short-Term Memory (LSTM) networks, Graph Convolutional Networks (GCNs), and a unified GCN+LSTM architecture under a consistent preprocessing pipeline, leakage-free validation protocol, and rolling-origin evaluation framework. For the Boulder ZIP-code dataset considered in this study, temporal information provided the dominant …

Coverage-Aware Gradient-Boosted Intrusion Detection For Smart-Meter Distributed Denial-Of-Service Resilience, Harsh Kumar, Sanjeev Kumar

Electrical and Computer Engineering Faculty Publications

Advanced metering infrastructure (AMI) relies on continuous communication among smart meters, gateways, routers, and utility monitoring systems, increasing exposure to distributed denial-of-service (DDoS) traffic. This study presents a system-level intrusion-detection methodology integrating coverage-aware sensor placement with leakage-controlled gradient-boosted classification. The contribution lies in combining monitoring visibility, training-only feature sanitization, duplicate and cross-partition overlap removal, false-positive-constrained threshold selection, repeated external testing, and a validated feature-budget mode. Seventeen CIC-DDoS2019 parquet files were analyzed. After removing conflicting labels, exact duplicate feature vectors, and 4,666 testing records overlapping the training partition, the final dataset contained 121,088 training records and 297,790 external testing records with …

Dustmambanet: A Hybrid Inceptionv3–State-Space Network For Robust Solar Panel Dust Detection, Kadhim Hayawi, Sakib Shahriar

All Works

To develop a robust, scalable vision-based model for automatic detection and quantification of dust accumulation on solar photovoltaic panels, overcoming limitations of existing convolutional and attention-based methods and supporting proactive maintenance. We propose DustMambaNet, a hybrid model that consists of a pretrained InceptionV3 convolutional neural network as a feature extractor and two selective state space sequence modules. The state space modules use gated depthwise convolutions to represent long-range spatial dependencies that are of linear complexity, after rearranging spatial features to form sequences. The network provides a binary classification of dust with a severity index (DSI) and a continuous one. All …

Homotopy-Safe Trajectory Planning And Attack Detection For Low-Altitude Uav Under False Map Information Injection Attacks, Chen Li, Qi, Juntao Zhao, Xin Yuan, Kai Wu, Wei Ni, Ren Ping Liu

Research outputs 2022 to 2026

Low-altitude unmanned aerial vehicles (UAVs) have been extensively deployed in logistics support, surveillance, and disaster relief. However, their open communication networks and inherently vulnerable navigation systems render them susceptible to false map information injection attacks (FMIIA). To effectively mitigate the impact of FMIIA, this paper presents a UAV local flight trajectory optimization framework that integrates a robust attack detection method based on initial excitation (IE) and an efficient local path reconstruction approach utilizing the Marden theorem. First, an IE-based adaptive robust observer is formulated, where IE enhances the observability of the system's input-output responses, enabling joint estimation of the UAV's …

Electrification Of Australian Remote Communities Through Degradation-Aware Techno-Economic And Environmental Optimization Of Sustainable Vehicle-To-Home Enabled Hybrid Renewable Energy Systems, Tushar Kanti Roy, Barun K. Das, Md Apel Mahmud

Research outputs 2022 to 2026

The integration of hybrid renewable energy systems (HRES) with vehicle-to-home (V2H) capabilities presents a promising pathway to achieve sustainable electrification in remote communities. This work presents an innovative energy management system (EMS) in which a multi-objective optimization problem is formulated to simultaneously minimize net present cost (NPC), lifecycle CO2 emissions, and loss of power supply probability (LPSP). Three configuration-specific objective functions are proposed where these configurations include (i) off-grid photovoltaic (PV)–wind turbine (WT)–battery energy storage system (BESS)–diesel generator (DG), (ii) on-grid PV–WT–BESS–Grid, and (iii) off-grid PV–WT–BESS–DG with V2H. The EMS integrates mixed-integer linear programming (MILP) for degradation-aware deterministic dispatch, sequential …

Thermal Management Of Heat Sinks Equipped With Internal Cooling Mechanism: A Comparison With Advanced Heat Dissipation Techniques, Saif Ullah Khalid, Muhammad Ali Nasir, Mehmet Karahan, Muhammad Saleem Khan, Furqan Jamil

Research outputs 2022 to 2026

Thermal management devices aim to remove extra heat from heat generation devices. There are numerous ways of heat rejection from the source, including active and passive cooling. The cooling techniques may be natural or forced, and the popular tools are heat pipes, heat sinks, and heat exchangers. In this piece of literature, several heat pipe and heat sink configurations are tested, including a novel internally cooled configuration using mono and hybrid nanofluids. Among heat sinks, solid finned and hollow finned configurations are mainly compared with the state-of-the-art heat pipes and thermal management systems for broader comparisons. Solid cylindrical fins are …

The Sliding Aperture Transform: A Mathematical Method Applied To Radiation-Induced Dlts Capacitance Transients, Md Abu Bakkar Siddique

Graduate Masters Theses

This thesis presents the Sliding Aperture Transform (SLAPt), a novel mathematical technique for extracting exponential argument and pre-factor  from experimental data. The method transforms measured waveforms into an inverse-domain representation where exponential decay processes appear as distinct peaks, simplifying data analysis and reducing the effects of baseline offsets and noise. The technique is here applied to time dependent capacitance transients associated with irradiated and non-irradiated silicon pn junction diodes. The technique is further developed and applied to positive argument exponentials using an axillary function. This allows forward bias  current-voltage measurements, and forward pulse-bias current transient measurements to be SLAP analyzed, …

Determination Of The Content Of Water-Soluble Vitamins In The Composition Of Beet Beetroot Composition, Jasur Esirgapovich Safarov, Shakhnoza Abduvaxitovna Sultanova, Muhammad Rasul Oglu Najafli, Doston Ishmuhammat Ugli Samandarov

Chemical Technology, Control and Management

The aim of this study was to determine the content of water-soluble vitamins in various parts of beetroot (pulp, leaves and stems) that had been subjected to various drying methods in a bid to explore the effect of physical processes, i.e., the application of ultrasound, on micronutrient preservation. The experiments were performed at the Department of Service Technologies of Tashkent State Technical University, and chromatographic analysis was performed in the Institute of Bioorganic Chemistry of the Academy of Sciences of the Republic of Uzbekistan. Chromatography was performed on Agilent-1200 chromatograph with Exlipse XDB C18 column and diode array detector using …

Methods For Treating Wastewater Generated During The Production Of Basalt Fiber Using Modified Bentonite Clay, Abdurasul O'Ktamovich Husenov, Baxtiyor Toxtayevich Sabirov, Diyor Asadullayevich Xadjibayev

Chemical Technology, Control and Management

This scientific article notes that in technological processes, wastewater is contaminated with various organic and mineral substances, including poisonous and toxic substances. Sources of environmental pollution include organic and inorganic substances formed during the production of basalt fiber. In this research work, the task is set to purify wastewater formed during the production of basalt fiber from organic substances. Bentonite clay is a very good natural sorbent and has the ability to purify some cations. When conducting laboratory experiments, bentonite clays from the "Azkamar" and "Navbahor" deposits were selected to purify wastewater formed during the production of basalt fiber from …

Mathematical Models Of Magnetoelastic Acceleration Transducers Developed Based On The Theory Of Lumped Parameter Circuits, Amirov Fayzullayevich Sulton, Kamila Kamilovna Jurayeva, Shovkat Dilshodovich Turayev

Chemical Technology, Control and Management

In this article, based on the theory of lumped-parameter circuits, algebraic and differential equations describing the mechanical, electrical, and magnetic circuits of new magnetoelastic acceleration transducers, their analytical solutions, as well as mathematical models establishing the relationship between the electromotive forces at the outputs of the transducers and acceleration, which is the input quantity of the transducer, have been developed. Analysis of these mathematical models and the graphs constructed on their basis shows that under the influence of acceleration applied to the transducers, with an increase in the mechanical stresses arising in the magnetic circuit of the transducer, a redistribution …

Optimal Procedure For Measuring The Parameters Of Optical Signals Considering Noise, Yuriy Gennadyevich Shipulin, Azimjon Mamadaliyevich Xusanov

Chemical Technology, Control and Management

It has been shown that to achieve the required level of measurement accuracy and reliability, it is necessary to transition from quality control of finished products to quality management based on cost-effective methods during the stages when product properties are formed. It is shown that the complexity of measuring optical signal parameters during analysis or synthesis requires them to be considered as part of a general information processing system. Based on the nonlinear filtration method, an optimal procedure for measuring a variable position in time against a background of spatial noise was obtained. Structural diagrams of optimal measuring instruments for …

Development And Uncertainty Assessment Of Secondary Method For Ph Measurement In Physicochemical Measurements, Sarvar Rakhmatullaev, Dostonbek Xujakulov, Mohinur Nigmatova

Chemical Technology, Control and Management

In physicochemical measurements across various industries, laboratory analyses commonly require the determination of pH as an indicator of hydrogen ion activity in aqueous solutions. Ensuring the accuracy and reliability of these measurements, obtaining precise readings from pH measuring instruments, and maintaining overall measurement quality represent critical challenges in guaranteeing the safety of both products and processes. This requires constant monitoring, accuracy assessment, calibration, metrological verification, and control of measuring instruments. In this case, it should be carried out not with solutions prepared in any laboratory, but with certified reference materials (СRM) with appropriate regulatory framework, ensuring metrological observation. …

Robust-Adaptive Estimation Of Unmeasurable States And External Disturbances Of A Dynamic Object Based On An Augmented Kalman Filter, Husan Igamberdiev, Uktam Farkhodovich Mamirov, Lu Liu, Bohong Wang, Bunyod Buronov

Chemical Technology, Control and Management

The paper addresses the problem of joint estimation of the directly unmeasurable states of a dynamic object and of external disturbances when information is available only on the control inputs and on the measured output signals. To solve this problem, a robust-adaptive algorithm based on an augmented Kalman filter is proposed, in which the external disturbance is included in the extended state vector. Two operating modes of the algorithm are considered. For slowly varying disturbances, a random-walk model with a constant process-noise covariance is used, whereas for rapidly varying inputs a signal adaptation  driven by the normalized innovation is proposed. …

Fast Algorithms For Combined Synthesis Of Dynamic Object Control Systems, Isomiddin Khakimovich Siddikov, Gulchexra Alimova

Chemical Technology, Control and Management

The paper considers the issues of combined synthesis of a control system for a nonlinear dynamic object. The combined synthesis algorithms are based on the hybrid application of the theory of ordinary differential equations in the Cauchy form and the theory of automatic control. In this case, the dynamics of the control system are described in the input-output representation and by state-space equations. Algorithms for solving stabilization problems, finite control, and the inverse dynamics problem are presented in explicit form. These algorithms are based on the concept of reducibility of a general Cauchy-form system to the block-canonical Frobenius form. The …

Analysis Of The Throttle Settings Under Uncertain Information, Latafat Gardashova, Nihad Afandi

Chemical Technology, Control and Management

Although classical fuzzy logic controllers are capable of modelling non-linear control systems, they fail to consider the reliability of linguistic information, sensor measurements, and expert knowledge. In this paper, an intelligent controller based on the use of Z-numbers is developed for steam-turbine throttle control. Linguistic information and its confidence degree are considered simultaneously in such a controller. The temperature and pressure values are taken as input variables, while the throttle rotation is selected as the controller output variable. At first, the Z-number representation system is constructed to include the credibility of linguistic measurements and control rules. Then, a Mamdani Type-1 …

Nonlinear System Identification Based On Fuzzy Radial Basis Neural Network With Multi-Connected Weight Connections, Kabul Khudaybergenov

Chemical Technology, Control and Management

This paper builds on our earlier radial basis function network with multiple connections (RBFMC) by placing it within a fuzzy inference framework for nonlinear system identification. The idea is inspired by the diversity of neurotransmitters found in biological neurons: instead of a single hidden-to-output weight, RBFMC gives each hidden unit a multi-dimensional connection whose components act as independent filters. Once fuzzy logic is added, each hidden neuron becomes a fuzzy rule, and its antecedent is built from several Gaussian membership functions, one per connection. The resulting Fuzzy RBFMC produces an interpretable, multi-filter description of local regions of the input space …

Performance Evaluation Of Controllers Using Fuzzy Delphi And Ahp Techniques, Kamala. R. Aliyeva, Nihad Mehdiyev, Shamil Mehdi

Chemical Technology, Control and Management

This study introduces an enhanced decision-support framework that integrates the Fuzzy Delphi method with the Analytic Hierarchy Process (AHP) to improve controller tuning and performance evaluation in uncertain environments. Traditional tuning techniques typically depend on crisp expert judgments and deterministic performance indices; however, industrial control systems are characterized by nonlinear behaviors, uncertain parameter variations, and subjective expert evaluations that are often vague or inconsistent. The Fuzzy Delphi procedure is applied to systematically gather, filter, and consolidate expert insights, enabling a refined set of performance criteria such as stability margins, robustness to disturbances, settling time, overshoot, control effort, and energy consumption …

Documentation And Project Change Management System – Honeywell Trace, Farukh Adilov, N.R Yusupbekov, Maksim Fedorovich Astafurov, Kamola Rustamovna Abdullayeva

Chemical Technology, Control and Management

The article examines modern approaches to organizing documentation and managing changes in industrial automation projects using the Honeywell Trace software platform. The evolution of documentation tools from the Documentation Tool utility within the TDC 2000/3000 system to modern intelligent solutions is described. The architecture, functional capabilities, and supported interfaces of Honeywell Trace are analyzed. Particular attention is paid to automated configuration change tracking, comprehensive search by process tags, and the detection of potential errors. The possibilities of integrating the system with industrial process control systems, controllers, auxiliary systems, and industrial communication protocols are considered. The application of Honeywell Trace during …

One Size Does Not Fit All: Revisiting World Models And Neurosymbolic Ai, Amit P. Sheth, Madhur Thareja, Anushka Pawar, Niyati Rawal

Publications

World models are being built twice, from opposite ends, without a shared theory of how the two halves should meet. One lineage grounds the world model in perception: a self-supervised, latent-predictive encoder – exemplified by Joint Embedding Predictive Architectures (JEPA) – that learns the structure of sensory experi-ence. A second, older lineage grounds the world model in cognition: an explicit, inspectable structure of entities, rules, and constraints, ranging from knowledge graphs to formal logic to physical law. Neither lineage alone has produced a world model that is simultane-ously adaptive and auditable. We argue this is not solved by picking a …

Early Detection Of Alzheimer’S Disease Using Federated Learning Based On Personalized Gans: A Data-Driven Approach, Iffat Fatima, Uzair Iqbal, Uzair Ishtiaq, Muhammad Burhan Ul Islam Khan

Makara Journal of Technology

Alzheimer’s disease (AD) is a complicated neurodegenerative disease marked by the slow worsening of memory and cognitive functions. Early detection is a key to effective disease management, but the creation of reliable machine learning models is not an easy task because medical data are limited, and there are strict privacy requirements, such as GDPR and HIPAA, that inhibit the creation of central databases. In this paper, a new privacy-saving model that combines personalized federated learning (PFL) with generative adversarial networks (GANs) is proposed to diagnose Alzheimer’s disease. Under the proposed method, the synthesis of data using GAN is conducted on …

Microwave-Assisted Synthesis Of Core-Shell Structured Pd@Pdptcufe Recessed Truncated Octahedral Nanocrystals For Multifunctional Electrocatalysis, De-Zhong Hu, Wen-Dan Jiang, Wei Keat Ng, Jun Yang, Xiong-Wu Kang

Journal of Electrochemistry

Developing cost-efficient and durable multifunctional electrocatalysts of hydrogen evolution reaction, oxygen reduction reaction and oxygen evolution reaction is crucial for improving energy conversion efficiency in electrolytic water splitting electrolyzer and advancing rechargeable zinc-air batteries. Polyhedral shaped nanocrystals with well-defined crystal facets represent a type of model catalysts that enables the exploration of structure-activity relationships. However, it is still very challenging to prepare alloy nanocrystals with multiple metal components due to their complicated redox potentials and mixing enthalpy. Herein, we report a rapid microwave-assisted polyol reduction method for syntheses of core-shell Pd@PdPtCu, Pd@PdPtCuNi, Pd@PdPtCuCo and Pd@PdPtCuZn octahedral nanocrystals, and recessed truncated-octahedral …

Neural Network Driven By Electrochemical Performance Data For Predicting The Discharge Termination Time Of Seawater Electrolyte-Based Metal-Air Batteries, Peng-Peng Shen, Yi-Chi Pan, Yu-Rong Liu, Lu-Dan Zhang, Ning Niu, Guan-Jun Wang, De-Kun Yang, Xin-Long Tian, Peng Rao

Journal of Electrochemistry

Seawater electrolyte-based metal-air batteries exhibit great promise for marine energy supply systems. However, conventional statistical analysis methods, though applicable to seawater metal-air battery lifetime prediction, have inherent limitations of insufficient prediction accuracy and large error. Herein, a deep time-series regression framework based on InceptionTime and incorporating prior-biased attention pooling is proposed to construct a nonlinear mapping between electrochemical performance sequences and the discharge termination time of catalysts. Specifically, chronoamperometric profiles are employed to extract long-term stability features, while prior knowledge derived from linear sweep voltammetry is introduced to strengthen the attention weighting over critical potential regions. Under a nested leave-one-catalyst-out …

A Comprehensive Review Of Perovskite Materials For Electronic Device Applications, Md Abdul Kuddus Sheikh, Md Shazarul Islam, Daniel Drane, Hasina Huq

Electrical and Computer Engineering Faculty Publications

Perovskite materials have gained remarkable attention as promising candidates for next-generation electronic and optoelectronic devices owing to their outstanding optical absorption, high carrier mobility, tunable bandgap, and cost-effective fabrication. This review explores the recent progress and future potential of perovskite materials across different categories, including organic-inorganic hybrid perovskites, oxide perovskites, and all-inorganic perovskites, emphasizing their structural diversity and electronic tunability. Special consideration is given to various dimensional perovskites (3D, 2D, 1D, and 0D), where reduced dimensionality provides enhanced stability and unique quantum confinement effects advantageous for device performance. The rapid development of lead-free perovskites is also discussed as an environmentally …

Ensuring Safety In Battery Management Systems: A Control Barrier Function Approach, Magdalena Kossek

Electronic Theses and Dissertations

Safe and efficient operation of batteries is paramount to extending their lifespan and ensuring reliability in battery management systems. This work presents a new approach for maximizing safety and performance of lithium-ion batteries in a variety of applications with a view towards efficiency in computation. The aim is to maximize a battery’s output (its power, speed of charging, and overall efficiency) while preserving its longevity and ensuring operational safety. This challenge is tackled by developing a novel control algorithm for advanced lithium-ion battery management leveraging control barrier functions (CBFs) to ensure safe and efficient operation during fast charging and discharging. …

Techno-Economic Analysis Of Implementing Carbon Capture And Storage (Ccs) At The Punagaya 2×100 Mw Coal Power Plant, Ricky Andreas Kristianto Siringoringo, Rahma Muthia, Widodo Wahyu Purwanto

Journal of Materials Exploration and Findings

The increase in greenhouse gases due to the combustion of fossil fuels is one of the major drivers of global warming and consequently drives the development of low-carbon technologies such as Carbon Capture and Storage (CCS). The aim of this study is to evaluate the technical and economical feasibility of the implementation of CCS technology in the Punagaya Subcritical Coal-Fired Power Plant (CFPP) 2×100 MW as a part of the energy transition strategy towards Net Zero Emissions (NZE) 2060. The simulation was carried out using Aspen HYSYS software, including coal combustion, CO₂ capture through MDEA-PZ solvent, dehydration, transportation, and storage …

Flexible Power Point Tracking For Active Frequency Regulation In Grid-Connected Photovoltaic Power Plants, Castor K. Haule, Sophia D. Kigodi, Emmanuel S. Matee, Francis Mwasilu

Tanzania Journal of Science

The increasing penetration of photovoltaic (PV) systems into modern power grids necessitates advanced control strategies capable of supporting grid stability. Traditional PV systems rely on Maximum Power Point Tracking (MPPT) to maximize energy extraction, limiting their ability to participate in grid-support functions such as frequency regulation or power curtailment. This paper presents a flexible power point tracking (FPPT) control strategy that enables PV systems to operate at arbitrary points along the power–voltage (P–V) curve. A multi-mode power management scheme is proposed, integrating conventional Perturb and Observe (P&O) MPPT with FPPT, allowing the system to switch dynamically between energy maximization and …

Mitigation Of Power Quality Problems In Songwe Power Distribution Line Using A Static Distribution Compensator, James Mhame, Emmanuel Matee, Francis Mwasilu, Sophia D. Kigodi

Tanzania Journal of Science

The Songwe electrical distribution system is prone to severe voltage drops that lead to frequent power outages in long feeders, light flickering, and the multi-operation of equipment and other appliances. The voltage at the switching station averaged 27.6 kV, 28.21 kV, and 25.79 kV in the years 2023, 2022, and 2021, respectively. Additionally, the maximum was 32.2 kV, below the nominal voltage, and the feeder has a very low power factor, which drops to 0.6 during peak hours. Currently, TANESCO uses automatic voltage regulators connected to a distant location from the switching station to two feeders with critical voltage drop …

Design And Characterization Of A 3d-Printed Dual Stacked Patch Antenna With Tunable Coupling For Uav Applications, Isabelle Lynn Brigman

Masters Theses

Antennas are a critical component of unmanned aerial vehicle (UAV) communication systems where compact size, light weight, and reliable operation across multiple frequency bands are critical. While microstrip patch antennas are attractive for UAV applications due to their low profile, low cost, and ease of fabrication, they are often limited by narrow bandwidth and fixed-frequency operation. To address these limitations, this thesis investigates a mechanically and electrically reconfigurable dual-stacked patch antenna fabricated using additive manufacturing techniques.

The proposed antenna consists of a slotted driven patch operating near 2.5 GHz with a second resonant mode near 5 GHz. A parasitic patch …

Correlation And Redundancy Analysis Of Statistical Features For Permanent Magnet Synchronous Motor Fault Detection, Ibrahim Muhammad, Benjamin Olabisi Akinloye

Mansoura Engineering Journal

Feature selection plays a critical role in designing efficient and interpretable condition monitoring frameworks for electrical drives. In this paper, a correlation analysis of statistical and spectral features is performed for Permanent Magnet Synchronous Motor (PMSM) fault detection in naval windlass systems. Using both simulated data from a MATLAB/Simulink model and real shipboard current signals acquired from five Nigerian Navy vessels over one-month monitoring periods, higher-order statistical moments (Mean, Variance, Standard Deviation, Skewness, Kurtosis) and the Fault Severity Index (FSI) were computed alongside Total Harmonic Distortion (THD). Pearson correlation coefficients were employed to quantify feature relationships under healthy and faulty …

Characterization Of An Ambe Tagged Neutron Source For A 30-Ton Wbls Detector, Rylee Grover

Discovery Day - Daytona Beach

Understanding the detection capabilities of water-based liquid scintillator (WbLS) is critical for its deployment in next-generation neutrino detectors such as THEIA and Phase II of the Deep Underground Neutrino Experiment (DUNE). This study focuses on the characterization and alignment testing of an Americium-Beryllium (AmBe) radioactive neutron source. We plan to dope the 30-ton WbLS detector at Brookhaven National Laboratory (BNL) with Gadolinium (Gd) to improve neutron detection capabilities. This will be tested by the implementation of an AmBe source as a calibration metric. The AmBe source emits neutrons coincident with a 4.4 MeV gamma ray, making it possible to perform …