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 However, as detailed in the manuscript's literature review, existing benchmark datasets are predominantly synthetic, outdated, or imbalanced and fail to capture the complexity of the contemporary threat landscape.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 …

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 …

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 …

Between Blockchain And Black Markets: South Africa's Legal Readiness For Crypto-Driven Cyberfraud, Sagwadi Mabunda, Yassin Chande

Communications of the IIMA

This paper examines whether the proliferation of cryptocurrency-facilitated fraud warrants a reclassification of the terrestrial crime of fraud into the distinct statutory offence of cyberfraud under South African law. Engaging with established fraud typologies — exit scams, Initial Coin Offering (ICO) scams, Ponzi schemes, pump-and-dump schemes, and market manipulation — the article tests their definitional fit against both the common law of fraud and section 8 of the Cybercrimes Act 19 of 2020. Through a hypothetical composite scenario combining multiple fraud typologies, the article demonstrates that whilst cryptocurrency significantly amplifies the reach and complexity of fraudulent schemes, it functions primarily …

Saas As The Backbone Of Digital Transformation: How Ai Turned Cloud Software Into Intelligent Enterprise Infrastructure, Amar Fejzić

Communications of the IIMA

Software-as-a-Service (SaaS) has become one of the most consequential infrastructures of digital transformation because it lowers the cost, time, and complexity of adopting enterprise capabilities. At the same time, artificial intelligence (AI), especially generative and conversational AI, is changing SaaS from a delivery model into an intelligent operating layer that automates workflows, personalizes customer interactions, and supports data-driven decisions. This paper develops a conceptual synthesis of academic literature and public organizational cases to examine how SaaS shaped digital transformation and how AI is reshaping SaaS itself. The analysis shows that SaaS enables scalable experimentation, faster deployment, and modular integration, while …

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 …

Designing Classifact: Towards A Transparent And Secure Platform For Stakeholder-In-The-Loop Data Annotation, Philippine Waisvisz

Communications of the IIMA

AI systems depend on human judgment, yet many annotation workflows are either designed for data-science specialists or managed through external commercial platforms. The first approach may demand more technical skills than relevant stakeholders possess. The second can require organizations to transfer data, expertise, and governance to an outside provider. Both can limit the involvement of people who understand what data means in its real-world context. Human-in-the-loop approaches introduce human judgment. Stakeholder-in-the-loop annotation focuses on selecting and organizing people whose contextual knowledge fits the AI application.

This paper presents Classifact, a transparent and secure platform for stakeholder-in-the-loop data annotation and validation. …

From Retrieval To Generation: Building And Evaluating An Ai Accompanist For Piano Duets With An Anticipatory Music Transformer, Sai Ruthvik Uppala

Masters Theses

Systems that accompany a live musician, such as ACCompanion, work by retrieval: they hold a written accompaniment and stretch its timing to follow the soloist, so they can only accompany music whose second part already exists as a score. This thesis asks whether that second part can instead be generated, and specifically whether a machine learning model can write an accompaniment for a piece whose score it has never seen. A player performs the primo, the melody; a model produces the secondo, the accompaniment; and a score follower places the generated notes against the live performance. If this works, a …

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 …

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.

Curated Spaces: Cognition By Design, Sydney Harvey

Dissertations, Theses, and Capstone Projects

“Curated Spaces: Cognition by Design” is a dissertation that considers the connection between designed spaces and cognition. This work combines philosophy of mind and aesthetics. The dissertation introduces the term “Curated Cognition”, which builds on the concept of situated cognition ( Brooks, 1991; Odling-Smee, Laland, and Feldman,  2003;  Sterelny, 2010; Krueger, 2015; Colombetti, 2020 ). The dissertation argues that the environment is essential to cognition, and all environments are curated; therefore, the way we think, feel, and act is curated as well. Some non-human animals may inhabit worlds that are not curated. For example, an octopus may find shelter in …

How Do Governments Combat Jihad Online?, Noah Cook

Honors College Theses

Since the September 11th, 2001 attacks, jihadist groups like ISIS, al-Qaeda, and al-Shabaab have used the internet as a tool for recruitment, radicalization, and propaganda dissemination. Since then, governments, non-governmental organizations, and private companies have developed strategies to combat jihadism on the internet. This paper examines how these actors have worked to mitigate the digital jihadist footprint and its effects by analyzing three main approaches to countering violent Islamist extremism on the internet: counter narrative initiatives, awareness-raising programs, and content removals. This paper finds that each of these methods has its own strengths and weaknesses. Counter narrative campaigns show the …

Using Clustering Techniques And Mitre Att&Ck Threat Interpretation To Detect Anomalies In Modbus/Tcp For Industrial Control Systems, Shivanjali Khare, Tirthankar Ghosh, Jhansi Sreya Jagarapu, Atharva Haridas Sagare

Journal of Cybersecurity Education, Research and Practice

Recent attacks on America's critical infrastructure have drawn increased attention on securing industrial control systems and operational technology in power plants, utility companies, and other sectors providing public services. Attack detection and mitigation strategies on these systems have shown promising results using machine learning and other statistical baselining techniques, mostly using supervised learning and classification. Unsupervised learning using cluster analysis and other techniques remain mostly unexplored. In this paper, we propose multi-layered feature extraction and hybrid clustering framework to detect fine-grained nested attack patterns in Modbus-over-TCP traffic. Operating under the assumption of known number of distinct network categories, our approach …

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 …

Biki: Design Overhaul, Meg Rawson

Computer Science and Engineering Senior Theses

For children from bilingual households, kindergarten can represent both an introduction to formal mathematics education and a period of increased exposure to the English language. Students may therefore be learning foundational mathematical concepts while simultaneously developing the English vocabulary used to describe those concepts. BiKi (Bilingual Math for Kindergartners) was developed to help bridge this gap through an educational application that combines visual, auditory, and interactive learning activities to reinforce mathematical vocabulary in both English and a student’s home language.

This work builds upon the existing BiKi application while maintaining its original educational goals and intended audience. The primary focus …