Electrical and Computer Engineering Commons^™

Relative Rate Observer-Based Online Tuning Mechanism For Single-Input Interval Type-2 Fuzzy Pid Controllers, Oqba Aldreiei, Cenk Ulu, Mert Can Kurucu, Müjde Güzelkaya

Turkish Journal of Electrical Engineering and Computer Sciences

The characteristics of the footprint of uncertainty (FOU) in interval type-2 membership functions (IT2-MFs) are crucial to the performance and robustness of interval type-2 fuzzy controllers (IT2-FCs). However, existing IT2-FC design approaches mostly use fixed FOU structures. This study proposes an online membership function (MF) adjustment mechanism for a single-input interval type-2 fuzzy PID controller (SIT2-FPID)  that adjusts the FOU of the antecedent MFs and weights of the consequent MFs, respectively, to achieve high performance and robustness. The proposed online adjustment mechanism consists of a relative rate observer (RRO), a two-input rule-base adjustment system, and a first-order smoothing filter. The …

Cuip-X25: A Real-World Network Intrusion Dataset For Next-Generation Ai-Driven Security, Arshad Iqbal, Sohail Asghar

Turkish Journal of Electrical Engineering and Computer Sciences

The efficacy of artificial intelligence (AI) in intrusion detection systems (IDS) is critically dependent on high-fidelity training data. However, as detailed in the manuscript's literature review, existing benchmark datasets are predominantly synthetic, outdated, or imbalanced and fail to capture the complexity of the contemporary threat landscape. To bridge this gap, this study introduces CUIP-X25, a novel real-world cyber-attack dataset captured over a four-month period using a dionaea honeypot deployed on a public network. Unlike synthetic alternatives, this dataset provides an authentic representation of modern adversarial tactics, techniques, and procedures, encompassing 3.16 million real events across ten distinct attack categories, including …

Robust Load Frequency Control For Multiarea Electrical Power Systems Via Analytical Proportional-Integral-Derivative Plus Second Order Derivative Controller Design, Yavuz Güler, Mustafa Nalbantoğlu, Ibrahim Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

This research presents a proportional-integral-derivative plus second order derivative (PIDD2) controller design based on the Direct Synthesis Method (DSM) for load frequency control (LFC) of interconnected power systems. The parameters of the proposed PIDD2 controller are determined using the DSM, which offers an analytical approach for tuning. The design approaches have been developed specifically for single, two, and three-area power systems, encompassing nonreheated and reheated thermal turbines. In the proposed design method, the best values of PIDD2 controller parameters were found by using a multicriteria objective function that includes the integral of absolute error (IAE) and settling time. In response …

Boundary Layer Sliding Mode Control Strategy For Variable-Speed Compressor In Deep Freezers: Experimental Validation Of Energy Efficiency And Freezing Capacity, Sertan Aksoy, Kami̇l Çeti̇n, Sezai̇ Taşkin

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the design and experimental validation of a nonlinear sliding mode controller developed for a deep freezer equipped with a variable-speed compressor. The proposed control strategy aims to minimize energy consumption while maintaining rapid and stable cooling performance under varying ambient conditions. A detailed thermal model of the deep freezer was established using an equivalent resistance–capacitance network representation, enabling precise analysis of temperature dynamics. The sliding mode-based control algorithm dynamically adjusts the compressor’s operating frequency according to temperature deviation, ambient conditions, and time-dependent factors, providing robust performance without requiring parameter retuning for different models. Beyond theoretical-based analysis, a …

Empowering Edge Intelligence Through Reparameterized Lightweight Transformers And Distributed Inference, Hosein Esmaeili, Mohammad Ali Afshar Kazemi, Reza Radfar, Nazanin Pilevari

Turkish Journal of Electrical Engineering and Computer Sciences

Deploying advanced transformer-based models on resource-constrained edge devices remains a significant challenge due to their high memory footprint and substantial compute requirements. In this paper, we propose a reparameterized transformer framework that integrates High-Rank Factorization (HRF) during training, layer merging at inference, and dynamic, load-balanced distributed inference across multiple devices. To further reduce resource usage, our framework supports mixed-precision quantization down to 4-bit, enabling flexible accuracy–latency–energy trade-offs. Experimental evaluations on the ESC-50 environmental sound dataset demonstrate that our method matches or exceeds the performance of larger baseline models while using 20–30% fewer parameters, achieving up to 48% latency reduction in …

A Binary Multiobjective Hippopotamus Optimization Algorithm For Feature Selection In Phishing Website Detection, Fatima Belmessaoud, Sofiane Maza, Djaafar Zouache

Turkish Journal of Electrical Engineering and Computer Sciences

Phishing website detection remains a major challenge in cybersecurity as attackers continuously develop new techniques to deceive users. Identifying the most informative features from large datasets is essential to improve classification accuracy while reducing computational complexity. Feature selection is therefore widely addressed using metaheuristic optimization techniques due to their flexibility and global search capability. In this study, we propose a Binary Multiobjective Hippopotamus Optimization Algorithm (B-MOHOA) for feature selection in phishing website detection. The proposed method simultaneously optimizes two conflicting objectives: maximizing classification accuracy and minimizing the number of selected features. Unlike many existing studies that mainly focus on transfer …

Range–Angle-Dependent Oam Beamforming With A Concentric Helical Circular Fda, Uğur Yeşi̇lyurt

Turkish Journal of Electrical Engineering and Computer Sciences

Secure and spatially selective wireless transmission requires orbital angular momentum (OAM) beams that are confined to a specific range and angle, rather than propagating indefinitely along the beam axis. In this paper, a concentric helical circular frequency diverse array (CHCFDA) is proposed to generate range–angle-dependent OAM beams without requiring external phase shifters. The helical element positioning inherently provides the necessary interelement phase distribution through physical step height, while logarithmically increasing frequency offsets are applied across concentric rings—and optionally across individual elements—to eliminate range periodicity and achieve a single, well-focused OAM beam exclusively at the target location. Both linear and logarithmic …

Measurement-Aware Zero-Phase Iterative Learning Control For Robust Regulation Of Nonideal Boost Converters In Electric Vehicle Fast Charging, Aytaç Altan, Mohammed S. Alzaidi, Cağfer Yanarateş

Turkish Journal of Electrical Engineering and Computer Sciences

Integrating battery energy storage with DC-DC boost converters for electric vehicle fast charging exposes the regulator to ageing-induced parameter drift, periodic load pulses, and, critically, the nonidealities in the output-voltage sensing chain. This paper proposes a measurement-aware, zero-phase iterative learning control scheme for robust output-voltage regulation of a nonideal boost converter whose parameters are matched to those of a commercial Texas Instruments TPS6102x battery regulator. The controller combines an inner proportional-integral stabilizing loop with an outer zero-phase learning law that updates a feedforward correction based on the sensor-captured output trajectory; a forward-backward robustness filter suppresses the amplification of measurement noise …

When Does Global Search Pay For Itself? A Measured Exploration Cost And Energy Break-Even Analysis Of A Metaheuristic Search Controller In Solar Energy Systems, Mohamed Ali Muammar Ezgour

Communications of the IIMA

Autonomous energy systems increasingly delegate the choice of operating point to embedded search algorithms, trading a fast local optimizer that can settle on a wrong point against a slower global search that guarantees the right one at a measurable cost. This paper reframes maximum power point tracking under partial shading as that decision and measures its economics on a fixed photovoltaic plant in MATLAB/Simulink. A Hippopotamus Optimization global search handed over to incremental conductance is compared with incremental conductance alone across seventeen initial duty cycles and thirty random seeds. The hybrid reached the global peak in all thirty seeds, whereas …

Doing Less With More: A First-Principles Exploration Of The Suitability Of Agentic Computing Over Alternative Architectural Choices, Ritvik Garimella, Biplav Srivastava, Amit Sheth

Publications

There is growing interest in automating business activities with Agentic Artificial Intelligence (AI) due to latter's seeming ease of use. Never has it been easier, or costlier, to do less with more. However, little is known about when agents are preferable to established alternatives such as local computation, Representational State Transfer (REST), the Simple Object Access Protocol (SOAP), and the Model Context Protocol (MCP), particularly when development speed, performance, and operational cost are considered. We investigate this question using a controlled mathematical task that compares seven methods on a benchmark of 1,000 arithmetic expressions where semantics of operator precedence has …

Techno-Economic Assessment Of Residential Prosumer Systems Using Real Household Consumption Data: A Case Study From Bosnia And Herzegovina, Alen Selmanović, Mehrija Hasičić

Communications of the IIMA

This paper evaluates the technical, economic, and environmental feasibility of residential prosumer implementation in Sarajevo, Bosnia and Herzegovina, through the integration of photovoltaic (PV) generation and battery energy storage. A simulation‑based assessment was performed in HOMER Pro using a measured 12‑month household load profile with an average daily consumption of 11.25 kWh and a peak demand of 2.85 kW. Six system configurations were investigated, consisting of 3 kW, 4 kW, and 5 kW PV installations, each analyzed with and without a 5.04 kWh lithium‑ion battery, over a 25‑year project lifetime under a zero‑credit export scheme. Among the analyzed configurations, the …

Ai-Based Displacement Forecasting For Real-Time Landslide Risk Assessment In The Danube Region, Amina Čehaja, Asja Muharemović, Jasmin Kevrić, Dejan Jokić, Mirza Ponjavić

Communications of the IIMA

This paper presents a dual-layered AI framework for real-time landslide risk assessment developed under the GeoNetSee project within the Interreg Danube Region Programme. The first layer employs a fuzzy logic model, inspired by the Slovenian MASPREM system, which integrates Landslide Susceptibility Maps (LSS) with high-resolution precipitation forecasts from the Open-Meteo API to generate a Predicted Landslide Hazard (PLSH) score on a 0–5 scale, updated every 6–12 hours. The second layer focuses on real-time ground displacement detection by fusing low-cost dual-frequency GNSS receivers with MEMS accelerometers and applying machine learning regression algorithms, including Support Vector Regression (SVR), Long Short-Term Memory (LSTM), …

Comparative Analysis Of Takagi-Sugeno And Mamdani Fuzzy Inference Architectures With Anfis-Based Automated Rule Generation For Eeg-Based Cognitive State Monitoring, Amina Radončić, Mehrija Hasičić, Jasmin Kevrić

Communications of the IIMA

Fuzzy inference systems have demonstrated considerable promise for EEG-based cognitive state monitoring in neurodegenerative conditions. However, two design decisions significantly influence system performance and clinical applicability: the choice of inference architecture (Takagi-Sugeno vs Mamdani) and the method of rule and membership function generation (manual expert-driven vs data-driven automated). This paper presents a comparative analysis of both dimensions in the context of an EEG-based Alzheimer’s disease monitoring system operating on the ds004504 OpenNeuro dataset (88 subjects: 36 AD, 23 FTD, 29 HC). A Takagi-Sugeno system, implemented as a hybrid FSM-Fuzzy architecture, is compared against a Mamdani equivalent across four axes: inference …

The Evolution Of Reliability Methods For Nondestructive Evaluation (Nde): From Probability Of Detection (Pod) Conception To Contemporary Practices, Christine E. Knott, Jennifer Brown, John Aldrin, Christine M. Schubert Kabban

Faculty Publications

Nondestructive evaluation (NDE) methods are powerful tools for detecting and characterizing flaws in structural components, but their reliability must be evaluated before they can be used in critical applications. For more than 50 years, probabilistic and statistical methods have been used effectively to estimate reliability by describing an NDE system’s Probability of Detection (POD) for flaws of realistic sizes. The POD methods used by the USAF and NASA, like Hit/Miss, Signal-Response (â vs. a), and Point Estimate method (PEM, a.k.a. 29/29) have evolved, alongside newer approaches like Limited Sample POD (LS-POD) method, and Model Assisted Probability of Detection …

Harmonicthreads: A Formative Evaluation Of A Fabric-Based Digital Musical Instrument Toward Inclusive Music-Making, Ellie Nguyen, Franceli L. Cibrian

Engineering Faculty Articles and Research

Background:

Inclusive music-making requires instruments that support varied bodies, abilities, musical backgrounds, and forms of participation. Digital musical instruments provide diverse approaches to sound creation, and fabric-based interfaces offer an alternative interaction modality that may support participation for some users and contexts. Their tactile and deformable properties enable forms of interaction that differ from conventional rigid or screen-based controllers and may offer inclusive possibilities in particular settings.

Objective:

This paper presents HarmonicThreads as a formative interaction-design case of a fabric-based digital musical instrument. The prototype explores how tactile cues, fabric deformation, projected visual feedback, and assisted accompaniment can support low-barrier …

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 …

Mechatronics: Fundamentals, Design, Integration, And Validation, Guoming Zhu

Mechatronics

This textbook is a product of Co-DREAM OER (Collaborative Development of Robotics, Mechatronics, and Advanced Manufacturing Open Educational Resources), an initiative funded by the U.S. Department of Education to develop open educational resource textbooks on robotics, mechatronics, and advanced manufacturing processes. The texts are written for students enrolled in 2-year associate’s, 4-year bachelor’s, and graduate-level courses. This specific text has been created by a team of scholars, students, support staff, and other professionals from across the country. It is intended for mechatronics courses for 4-year bachelor’s and graduate-level programs.

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 …

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 …