Digital Commons Network^™

Policy Reflections On Promoting Strategic Oriented Basic Research In China: Insights From The U. S. Department Of Energy’S Basic Research Funding System, You Yu, Yun Liu, Wenneng Zhou

Bulletin of Chinese Academy of Sciences (Chinese Version)

Strategy-oriented basic research is a key pathway to driving major original breakthroughs at the frontiers of science, serving national strategic needs, and securing a leading position in global science and technology. It is also a vital pillar for achieving high-level self-reliance and self-strengthening in science and technology and enhancing the capacity for original innovation. Faced with the urgent need to build a science and technology powerhouse and achieve breakthroughs in key core technologies, China has gradually improved its organizational framework for advancing strategy-oriented basic research and has established a solid foundation for policy support and resource allocation. Nevertheless, when measured …

Community Energy Storage: A Framework For Enhanced Energy Trading And Cost Efficiency, Bassam Al-Hanahi, Aziz

Research outputs 2022 to 2026

The integration of renewable energy sources (RES) into modern electricity grids introduces substantial challenges, primarily due to their inherent variability and the critical need for real-time supply-demand balancing. Community Battery Storage system (CBSS) has emerged as an effective strategy to address these challenges, enhancing grid stability and providing localized economic benefits through optimized energy storage and management. This paper presents a novel energy trading framework that prioritizes community welfare by balancing the reduction of user energy costs with CBSS revenue generation. The proposed model employs a multi-objective optimization approach, utilizing the epsilon-constraint method to strike an optimal balance between minimizing …

Provocable Forgiveness In Noisy Brand--Consumer Systems:An Agent-Based Study Of Repeated Interaction, Tahere Ahmadiyan, Hamidreza Navidi, Behbod Keshavarzi

Northeast Journal of Complex Systems (NEJCS)

Repeated brand--consumer exchange is often treated as a managerial problem of loyalty, recovery, and trust. It can also be read as a small complex system: many local decisions about cooperation, retaliation, and forgiveness accumulate into market-level selection. This study uses that perspective to examine which relational rules survive when communication is imperfect. Eight canonical Iterated Prisoner's Dilemma strategies are translated into marketing archetypes and evaluated through round-robin tournaments, a six-level noise sweep, proportional-fitness ecological dynamics, and finite-population Moran invasion tests. The tournament leaderboard is calculated without same-strategy self-play, so that reported payoffs reflect inter-archetype competition rather than homogeneous self-coordination. At …

Explainable Machine Learning For Biomedical Diagnostics: Optical Imaging And Eeg Signal Analysis, Fozia Rajbdad

LSU Doctoral Dissertations

The growing convenience of complex biomedical data begins new roads for better disease detection and functional identification via artificial intelligence (AI). Nevertheless, conventional analysis methods often rely on basic metrics that drop sensitive biotic differences, and various AI systems are difficult to infer, limiting their clinical reliability and practical use. There is a growing need for explainable, physiologically relevant computational models that can extract key biomarkers from diverse biomedical data sources. This dissertation addresses this problem by obtaining explainable machine learning and deep learning procedures for studying biomedical signals and optical imaging data.

This dissertation is divided into two parts; …

Seasonal Changes In Sediment Sound Speed Profiles, Charles W. Holland, Chad Smith, Tim Sonnemann

Electrical and Computer Engineering Faculty Publications and Presentations

Marine sediment sound speed profiles in the upper ten meters are generally assumed to be constant with time. Models predict that substantive changes occur because of thermal conduction from seasonally varying bottom water temperature. However, definitive measurements have been lacking. In this work, sediment sound speed profiles obtained during different seasons show significant differences in the upper 9 m of mud at the New England Patch. Gradients in late March 2017 are 6.0 s−1 and in early October 2025, 2.6 s−1. This change is shown to have a significant impact on acoustic propagation.

Techno-Economic And Environmental Analysis Of A Hybrid Renewable Energy System With V2h Support For Remote Australian Communities, Tushar Kanti Roy, K. Das, Md Apel Mahmud

Research outputs 2022 to 2026

Remote Australian communities continue to experience persistent energy insecurity and increased greenhouse gas emissions due to their reliance on diesel-based microgrids. In response, this study presents a comprehensive techno-economic and environmental assessment of a hybrid renewable energy system integrating solar photovoltaics (PVs), wind turbines (WTs), battery energy storage systems (BESSs), and electric vehicles (Evs) with vehicle-to-home (V2H) functionality. Three system configurations are evaluated over a full-year simulation horizon using realistic solar irradiance, wind speed, household electricity demand, and driving profiles of electric vehicles: (i) off-grid (PV–WT–diesel generator (DG)), (ii) on-grid (PV–WT-BESS–Grid), and (iii) off-grid with V2H. System operation is coordinated …

Efficient Edge Implementation Of Midasnet For Real-Time Depth Estimation In Indoor Robotics, Muhammed Yasi̇n Adiyaman, İsmai̇l Fai̇k Başkaya

Turkish Journal of Electrical Engineering and Computer Sciences

Real-time depth estimation is crucial in many vision-related tasks, including autonomous driving, 3D reconstruction, robotics, and simultaneous localization and mapping. In recent years, many methods have been proposed to solve depth maps from images by utilizing different modality setups like monocular vision, binocular vision, or sensor fusion. However, for real-time deployment on edge devices, complex methods are not suitable due to latency constraints and limited computation capacity. For edge implementation, models should be simple, minimal in size, and hardware-friendly. Considering these factors, we implemented MiDaSNet, which works on the simplest setup of monocular vision and utilizes hardware-friendly convolutional neural network-based …

Evolutionary Neural Architecture Search: A Survey, Ferda Nur Özçeli̇k, Mehmet Önder Efe

Turkish Journal of Electrical Engineering and Computer Sciences

Deep Neural Networks (DNNs) have achieved remarkable success across diverse machine learning applications, yet designing effective architectures remains a laborious, expert-driven process. Neural Architecture Search (NAS) was introduced to automate this process, with Evolutionary NAS (ENAS) emerging as one of the most effective and widely adopted NAS paradigms. This survey provides a comprehensive and systematic review of 164 ENAS studies published between 2020 and 2024, categorized according to the specific evolutionary algorithm employed as the search strategy. Unlike prior surveys—which either treat evolutionary methods at a high level or focus on general NAS pipelines—this study is, to the best of …

A Holistic Approach For Workforce Scheduling And Routing, Kerem Can Manalp, Ansel Kaplan Erol, Kutluhan Erol, Cem Evrendi̇lek

Turkish Journal of Electrical Engineering and Computer Sciences

The workforce scheduling and routing problem (WSRP) involves assigning tasks across multiple locations while accounting for varying travel times, service durations, time windows, and skill requirements in a wide range of industries, from healthcare to telecommunications. This paper presents a mixed-integer programming model for the WSRP that balances the trade-off between cost and customer satisfaction using a score-generation function and subsequently evaluates the trade-off between solution quality and computation time for several algorithms on well-known datasets. We demonstrate that our model effectively balances cost, service-level agreement satisfaction, and task priorities while providing high-quality solutions in a timely manner. Observing that …

Cnkg: Harnessing Large Language Models For Cognitive Neuroscience Knowledge Graph Construction, Ali Sarabadani, Kheirollah Rahsepar Fard, Hamid Dalvand

Turkish Journal of Electrical Engineering and Computer Sciences

Textual resources are among the most valuable sources of information in cognitive neuroscience (CN) for understanding and investigating brain activity and cognitive processes. Extracting and constructing knowledge graphs (KGs) from these texts can facilitate medical research by providing deeper insights into neurological diseases and brain function. In recent years, the use of large language models (LLMs) in natural language processing (NLP) has become increasingly widespread, significantly enhancing the extraction of meaningful information from large volumes of text. This study proposes a novel approach for constructing and evaluating a specialized knowledge graph, termed the cognitive neuroscience knowledge graph (CNKG), from scientific …

Dual-Stream Bilstm Framework With Histogram-Based Shape Features For Household Load Forecasting, Chang Xu, Wong Jee Keen Raymond, Hazlee Azil Illias, Hazlie Mokhlis

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a dual-stream BiLSTM framework for household load forecasting that integrates time-series dynamics with histogram-based daily shape features. Unlike existing models relying on weather or external data, the proposed method extracts intrinsic load-shape information directly from normalized daily curves. A multihead attention module fuses temporal and shape representations, enabling adaptive weighting of informative dimensions. Experiments on three real-world datasets show consistent improvements over the baseline BiLSTM, with up to 30.12%, 24.27%, and 19.03% reductions in MAE, RMSE, and SMAPE, respectively. The results highlight the framework’s robustness and efficiency for fine-grained load forecasting without external inputs.

Robust Variable-Gain Backstepping Control For Nonlinear Systems With Real-Time Application To Induction Motor, Fadi Alyoussef, İbrahi̇m Kaya, Ahmad Akrad, Rabia Sehab, Cristina Morel

Turkish Journal of Electrical Engineering and Computer Sciences

This study proposes a novel variable-gain mechanism with a minimal number of tuning parameters to enhance the performance of conventional backstepping controllers for nonlinear systems while avoiding singularity and peaking phenomena. The proposed approach is simple, computationally efficient, and well suited for real-time implementation without imposing a significant computational burden. Its effectiveness is validated through real-time experiments conducted using a dSPACE DS1104 controller board and a 7.5-kW induction motor (IM). Simulation results demonstrate that the proposed controller outperforms the conventional backstepping controller. Robustness analyses under variations in stator resistance, load inertia, and viscous friction coefficient reveal substantial reductions in the …

Enhancement Of Nested Hexagonal Fractal Antenna Performance For Multiband Wireless Applications, Abdelbasset Azzouz, Rachid Bouhmidi, Mohammed Chetioui, Redouane Berber, Ahmed Jamal Abdullah Al-Gburi

Turkish Journal of Electrical Engineering and Computer Sciences

This work focuses on developing a compact multiband antenna to meet the growing demand for versatile and efficient radiating structures in modern wireless communication systems. A hexagonal fractal antenna is proposed and analyzed for applications such as mobile communications, WLAN, industrial, scientific and medical (ISM) bands, Wi-Fi, satellite links, radar systems, and military communications. By iteratively modifying the antenna geometry with larger hexagonal elements, the design enhances multiband behavior and improves key performance parameters including gain, S11, voltage standing wave ratio (VSWR), and radiation characteristics. The antenna is modeled using high-frequency structure simulator (HFSS)® and fabricated on a low-cost 0.8 …

Parameter Optimization Of Dual-Qsg Based Pll For Real-Time Control Of Grid-Connected Ev Chargers, Gaurav Yadav, Sudhanshu Mittal, Vineet Kumar, Sombir Kundu, Praveen Bansal

Turkish Journal of Electrical Engineering and Computer Sciences

Dual-Quadrature Signal Generator (D-QSG) based Phase lock loop (PLL) has been recently proposed to handle the nonideal grid voltage conditions. However, selecting the parameter for D-QSG based controller has been a great challenge, especially for higher-order systems. Inappropriate parameter selection tends to increase settling time both in terms of amplitude as well as harmonics attenuation. Hence, in the proposed work, the main focus is on parameter selection to achieve a faster response. Here, a fourth-order Quasi-Synchronous Generator has been realized by cascading the two nonidentical second order generalized integrators (NISOGIs). Furthermore, the parameters of both the NISOGIs are selected in …

Erratum To “Sgsc-Kko-Lstm: A Deeplearning Classifier Model For Smart Grid” [Turkish Journal Of Electrical Engineering & Computer Sciences 34 (2) 2026 185-213], Samaniba Imchen, Dushmanta Kumar Das

Turkish Journal of Electrical Engineering and Computer Sciences

The first and second authors were incorrectly ordered in the article PDF due to a typesetting error. To rectify this oversight and ensure the accuracy of the published work, the author order have been corrected as follows: 1. Samaniba Imchen – First Author 2. Dushmanta Kumar Das – Second Author

A link to the original article can be found at: https://doi.org/10.55730/1300-0632.4170

A Revenue-Driven Approach For Enhanced Task Utilization In Vehicular Cloud Computing, Ashish Singh Saluja, Satyabrata Das, Sanjib Kumar Nayak, Sohan Kumar Pande

Turkish Journal of Electrical Engineering and Computer Sciences

Vehicular networks support intelligent transportation through vehicle-to-roadside Units (V2R) and vehicle-to-vehicle (V2V) communication but face challenges from dynamic topologies, limited RSU coverage, and bandwidth scarcity, which impact service delivery and revenue. RDA-ITU addresses these challenges by integrating V2R and V2V paradigms to maximize RSU revenue, enhance service availability, and improve system efficiency. It dynamically allocates services based on real-time network conditions and vehicle mobility, leveraging V2V relays to optimize both RSU-direct and cooperative communication. Through extensive simulations, RDA-ITU significantly outperforms four baselines: RBSM, VVMM-U, VVMM-LW, and VVMM-MA. It achieves 81.1% higher total revenue, 154.8% more completed requests, and 103.6% higher …

Class-Aligned Frequency Augmentation Using Variational Mode Decomposition Forfew-Shot Image Classification, Leila Boussaad

Turkish Journal of Electrical Engineering and Computer Sciences

Few-shot image classification benefits from data augmentation, yet most existing methods operate in pixel space with limited control over spectral semantics. We introduce a lightweight, frequency-guided augmentation strategy based on Variational Mode Decomposition (VMD). Our method constructs an offline, per-class ModeBank by decomposing downsampled luminance patches and retaining midband modes that encode class-specific texture patterns. During episodic training, VMD is never executed online: instead, for each support image, a same-class midband mode is selected and blended using PSNR-targeted scaling with a luminance energy cap, ensuring perceptual consistency. The augmentation is fast, reproducible, class-consistent, and integrates seamlessly into standard metric-based pipelines …

Scalefusion: Hierarchical Feature Aggregation For Unified Multiscale Object Detection, Ayşenur Yaylaci, Berru Kaya, Mehmet Kiliçarslan

Turkish Journal of Electrical Engineering and Computer Sciences

Detecting objects across a wide range of scales, particularly small ones, remains a significant challenge in computer vision. Existing methods often improve small object detection at the cost of performance on larger objects or introduce significant computational overhead through external techniques like image slicing. This paper introduces ScaleFusion, a novel, unified, end-to-end object detection architecture designed to provide robust performance across all scales within a single model. The core of our approach is a hierarchical feature aggregation strategy structured like a tree. ScaleFusion processes an image by running a shared backbone network only on fine-grained patches at the lowest level …

Swindeitvit: A Soft Voting Vision Transformer Ensemble For Accurate And Explainable Solar Panel Fault Detection, Mahe Zabin

Turkish Journal of Electrical Engineering and Computer Sciences

Solar panels are becoming very essential in providing sustainable energy but they are usually affected by defects on the surface like dust, snow, bird droppings, physical damages and electrical faults which interfere with their performance. These faults must be identified accurately and in a timely manner to enhance energy efficiency, lower the maintenance cost, and supplement the traditional manual methods of inspection which are labor-intensive, time-consuming and subject to human errors in judgment. The most common methods, such as traditional CNNs and hybrid architectures tend to be less accurate, less explainable and cannot be properly evaluated to be deployed in …

Mxene-Based Optical Fiber Sensors For Chemical And Biosensing: Review And Perspectives, Chen Zhu, Huaijun Guan, Chenxi Huang, Rex E. Gerald, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

No abstract provided.

Assessing Computer Vision Based Conflict Detection In Uas Traffic Monitoring Under Secure Communication Constraints, Fadjimata Issoufou Anaroua

Doctoral Dissertations and Master's Theses

The rapid growth of Unmanned Aircraft Systems (UAS) and Advanced Air Mobility (AAM) is creating a new low-altitude airspace ecosystem where drones, air taxis, service suppliers, communication networks, sensors, and ground-based monitoring systems must work together safely. Within this ecosystem, UAS Traffic Management (UTM) is expected to provide a digital framework for coordinating operations beyond traditional air traffic control. However, reliable integration also requires resilient monitoring methods that can detect non-cooperative aircraft, protect communication links, and maintain timely situational awareness under real-world constraints.

This dissertation examines how computer vision can support cooperative monitoring systems such as Remote ID and ADS-B …

Coherent Two-Photon Backscattering And Induced Angular Quantum Correlations In Multiple-Scattered Two-Photon States Of The Light, Nooshin M. Estakhri, Theodore B. Norris

Engineering Faculty Articles and Research

We present the emergence of coherent two-photon backscattering, a manifestation of weak localization, in multiple scattering of maximally entangled pure and fully mixed two-photon states and examine the effect of entanglement and classical correlations. Quantum correlations in backscattering are investigated for finite three-dimensional disordered structures in the weak localization regime, as well as systems of a small number of scatterers with specified spatial arrangements. No assumptions are made about the statistical behavior of the scattering matrix elements. Furthermore, we study the interplay between quantum correlations induced by multiple scattering and the correlations that may be present in the illumination fields, …

Energy Efficiency Limits And Future Electricity Demand Of Computing Devices, Ricardo Pinto, Tiago Domingos, Paul E. Brockway, Matthew Kuperus Heun, Tânia Sousa

University Faculty Publications and Creative Works

• ICT (information and communication technologies) represented 4% of the world electricity consumption in 2020; 
• Computing devices represented 2% of the world electricity consumption in 2020; 
• In recent scenarios datacentre electricity demand reaches 3% of world electricity in 2030, and more than 4% in 2035

Modeling Of Terpolymerization Kinetics And Determination Of Reactivity Ratios In The Tdma–Styrene–Maleic Anhydride System, Shohrux Boboxon Ugli Mavlonov, Sadriddin Fayzullayevich Fozilov

Technical science and innovation

In this study, the kinetics of terpolymerization, compositional evolution, and monomer reactivity ratios in the TDMA–styrene–maleic anhydride system were comprehensively investigated. Increasing the initiator concentration from 16.8×10⁻⁶ to 51.3×10⁻⁶ mol•L⁻¹ led to an increase in conversion from 6.4% to 15.2% and reaction rate from 4.075×10⁻⁶ to 8.965×10⁻⁶ mol•L⁻¹•s⁻¹. At low conversion (Xw≈0.02–0.09), the terpolymer composition remained close to the initial feed, although deviations due to differences in monomer reactivity were observed. With increasing conversion, some systems exhibited stable composition (±0.02), while others showed compositional drift (increase of MA fraction from 0.50 to 0.70). The determined reactivity ratios (rTDMA/St≈0.99; rSt/TDMA≈1.62; rTDMA/MA≈2.02; …

Calculation Of The Basic Parameters Of The Hybrid Power Plant (Hpu) On The Spark Car, Rustam Raximovich Tillahodjaev, Jamoliddin Pardaboy Ugli Turdiev

Technical science and innovation

This article presents one of the effective ways to improve fuel efficiency and reduce emissions of toxic substances, the use of internal combustion engines with the use of an electric drive in their designs. In recent years, two directions in the development of cars with electromechanical drives have been clearly identified, the first is the creation of a pure electric car, the second is the development of an electromechanical drive with a combined (hybrid) power plant. Due to the lack of efficient energy storage available for mass production, pure electric vehicles have relatively low mileage on a single charge. This …

Experimental Study Of An Automotive Cooling System With A Mechatronic Control System, Avaz Israilovich Yangibayev

Technical science and innovation

This article presents the results of experimental investigations of a passenger car engine cooling system equipped with a mechatronic control system. The experiments were conducted on an intelligent hardware-software laboratory test bench developed using original components of a Chevrolet Gentra vehicle. The study determined the thermodynamic response characteristics and energy performance of the system under varying ambient temperatures (-10 to +50 °C) and engine thermal loads. The experimental results demonstrated that the mechatronic system can maintain coolant temperature with minimal fluctuation amplitude, ensure smooth transient processes, and significantly reduce electrical energy consumption. Based on the obtained results, scientific and practical …

Techedu.Uz: A Web-Based Virtual Laboratory Platform For Studying Induction Heating Processes., Abror Obidovich Pulatov, Murat Fikhratovich Shamiyev, Kutbiddin Asliddin Ugli Boboniyozov

Technical science and innovation

The challenges of integrating high-voltage induction furnace equipment into university laboratory settings were examined, including prohibitive equipment costs, limited student capacity, and serious safety risks. A conceptual design was proposed for a web-based platform called TechEdu.uz, which integrates both a Remote Laboratory module and a Virtual Laboratory module for induction furnace study within a single interface. The Remote module was designed to enable users to start, control, and monitor a real induction crucible furnace via a web interface, with live video surveillance and sensor devices intended to provide real-time measurements of temperature, power, and current values. The Virtual module was …

Use Of New Improved Methods For Assessing The Engineering-Geological Characteristics Of Deposits By Depth (Using The Example Of The Akba Deposit)., Elboy Shavkatovich Qurbonov Salom, Abduboqib Djalilovich Karimov, Yokub Yarash Ugli Isomiddinov

Technical science and innovation

The article examines the fracturing and filtration properties of rocks in boreholes, rock outcrops, and underground mine workings at the Akba gold deposit. Based on the results of hydrogeological and engineering-geological studies, methods that fully meet modern requirements were used, the values of the RMR rating of rocks and the indicators of the qualitative content of RQD rocks, as well as the intervals of their changes, were studied, as a result of which it became possible to quickly and accurately assess the strength state of the rock mass of the deposit territory by depth and area.

Investigation Of Energy Efficiency Of An Autonomous Mobile Photovoltaic-Thermal (Pv/T) System With A Polycarbonate Absorber, Sanjar Kodir Ugli Shoguchkarov, Anvar Rakhmat Ugli Rakhmatov, Rushana Husen Kizi Abdullaeva, Orazbek Maratbay Ugli Temirbaev

Technical science and innovation

This study analyzes the enhancement of energy efficiency in photovoltaic-thermal (PV/T) systems, which enable the simultaneous generation of electrical and thermal energy from solar radiation. The research focus is an autonomous mobile unit based on multi-channel polycarbonate heat collectors with a hydraulic diameter of 8 mm, characterized by their lightweight nature and superior corrosion resistance compared to conventional metal absorbers. Experimental investigations were conducted at the solar testing field of the Physical-Technical Institute of the Academy of Sciences of Uzbekistan under extreme continental climatic conditions to determine the system's stable thermophysical indicators. The results demonstrated that active water cooling using …

Development Of An Optimal Composition Of A Composite Solvent For Asphalt–Resin–Paraffin Deposits, Gulmira Abduvaliyevna Tadjiyeva, Xasan Irgashevich Kadirov, Shaxnoza Abduvaliyevna Tadjiyeva, Fazliddin Zokir Ugli Murodullayev, Bekmurodjon Baxtiyorjon Ugli Raximjonov

Technical science and innovation

A solvent formulation composed of aromatic hydrocarbons of the C9 fraction and aliphatic alcohols in a 1:1 ratio, supplemented with 1–3 wt.% of a nonionic surfactant, has been developed. The proposed composition demonstrates more than a twofold increase in dissolving and washing efficiency toward paraffin-type asphaltene–resin deposits. Furthermore, the solvent system exhibits pronounced depressant–dispersant properties with respect to paraffin-containing organic deposits. Although numerous investigations have addressed the development of technologies for removing organic deposits in oilfield equipment—primarily focusing on specific aspects of eliminating or preventing asphaltene–resin–paraffin deposits (ARPD) in wells—limited attention has been given to the design of integrated approaches. …