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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 …

Oregon State Rank Assessment For Steens Mountain Cushion Buckwheat (Eriogonum Ovalifolium Var. Rubidum), Lindsey K. Wise

Institute for Natural Resources Publications

Oregon state conservation status assessment for Steens Mountain Cushion Buckwheat (Eriogonum ovalifolium var. rubidum) using NatureServe methodology, 2026.

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 …

Assessing The Role Of Model Complexity In Virtual Clinical Trial Outcomes, Jana L. Gevertz, Joanna R. Wares

Department of Math & Statistics Faculty Publications

Virtual clinical trials (VCTs) hold significant promise for improving the drug development process, yet their predictive reliability depends critically on design decisions that remain poorly understood. This study examines how model complexity influences VCT outcomes, as well as how the choice of prior parameter distributions and virtual patient inclusion criteria affects those outcomes. Using oncolytic virotherapy treatment of murine tumors as a case study, we compared a relative hierarchy of three mathematical models of increasing complexity under different parameter priors (uniform and normal distributions) and two inclusion methods (accept-or-reject and accept-or-perturb). Our results demonstrate that the simplest model produces a …

Llm-As-A-Judge For Infection Prevention And Control And Antimicrobial Resistance Impact: Comparing Three Main Llms Vs. Human Experts' Assessment, Marcello Di Pumpo, Leonardo Villani, Maria Rosaria Gualano, Danilo Buonsenso, Francesca Raffaelli, Daniele Donà, Patrizia Laurenti, Vittorio Maio, Stefania Boccia, Walter Ricciardi

College of Population Health Faculty Papers

BACKGROUND: Large language models (LLMs) are increasingly used to generate health information, yet their reliability as evaluators remains unclear. This study investigated the feasibility of an LLM-as-a-judge methodology in the context of infection prevention and antimicrobial resistance (AMR), comparing automated ratings with human expert benchmarks.

METHODS: We performed a secondary analysis of an expert-annotated dataset of health messages. Three leading LLMs (ChatGPT, Claude, Gemini) independently evaluated the same messages using an adapted DISCERN tool across five domains: information reliability, quality, AMR impact, persuasiveness, and overall score. We utilized descriptive statistics, intra-rater reliability tests, and mixed-effects ordinal regression to analyze divergence …

Physical And Chemical Ameliorations Of A Heavy Soil Constrained By Sodicity And Alkalinity For Improving Productivity In The Low Rainfall Regions Of Western Australia, Md. Shahinur Rahman, Gaus Azam Dr

Grain and Other Field Crops Research Articles

Heavy soil can be compacted and poorly structured with dense sodic and alkaline (high pH) clay in the B-horizon, which prevents root exploration in the subsoil layer, potentially restricting grain yield in the low rainfall regions of Western Australia (WA) and globally. This study investigated whether loosening of compacted soil layers through deep ripping with or without phosphorus (P) and gypsum addition can increase barley (Hordeum vulgare L.) crop productivity in a 3-year-long field experiment. Soil loosening significantly increased barley root exploration and yield immediately after deep ripping in 2021 and showed no significant difference in 2022 and 2023. The …

Influence Of Supermassive Black Holes On The Star Formation Activities Of Their Host Active Galaxies, Ananthamoorthy Bannanje

University Departments

Active galactic nuclei (AGN) release substantial energy into their surrounding environn1ent, influencing the physical properties of the host galaxy and regulating the accretion of matter onto the central 'supermassive black hole (SMBI-D.' This process is known as ?GN feedback.' While AGN feedback is consideied an essential component in simulations to reproduce several observed properties of galaxies and clusters" direct observational evidence for its immediate and long-term impact on 'star formation' (SF) in both strong- and weak-jetted systems remains sparse and often contrasting. The primary limitation arises from the lack of high-resolution observations required for spatially resolved investigations of SF down …

Cybersecurity Governance Of Industrial Iot In Sub-Saharan Africa: Policy Gaps, Threat Landscape, And Lessons From Comparative African Contexts, Faztudo Languisse Eng.

Journal of Cybersecurity Education, Research and Practice

The rapid deployment of Industrial Internet of Things (IIoT) systems across Sub-Saharan Africa's extractive, energy, logistics, and agro-industrial sectors has introduced a cybersecurity challenge of growing urgency: industrial networks that were designed for operational efficiency are increasingly exposed to cyber threats for which neither the organizations nor the regulatory frameworks are adequately prepared. This article examines the cybersecurity governance of IIoT systems in a developing African economy, using Mozambique as a primary case study and drawing comparative lessons from South Africa, Rwanda, and Kenya. Through an integrative literature review and documentary analysis of national digital, cybersecurity, and industrial policies, the …

Challenges In Scaling R-Tree Spatial Search On Processing-In-Memory, Tasmia Jannat, Michael Gowanlock, Satish Puri

Computer Science Faculty Research & Creative Works

Spatial query processing is important in scientific, geospatial, and data-intensive applications. R-trees are widely used to index spatial objects, but their query-dependent traversal creates irregular work across different regions. This poster studies the challenges of scaling R-tree spatial search on a commercial Processing-in-Memory (PIM) system. Although PIM reduces CPU to memory data movement by executing search near memory, it does not remove full-pipeline overheads: the host still manages data placement, query batching, kernel launches, result retrieval, and aggregation. Our results show strong DPU-side search acceleration, with PIM kernel speedup ranging from about 20 x to 73 x, but end-to-end speedup …

Operator Theoretic Methods For Coupled Pde In General Geometries, Yuhao Mu

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

This thesis develops and applies operator theoretic methods applied to coupled PDE analysis in general geometries, in which the coupling involves interchange across a boundary. The general geometries refer to domains with merely Lipschitz continuous boundaries (e.g. any non-convex polygon), as opposed to those with any further smoothness conditions on the boundary. The key results include a new pressure elimination method for coupled fluid–structure interaction (FSI) PDEs with boundary interchange, which allows an explicit semigroup representation of the PDE in terms of just the fluid and structure variables. This novel technique, valid over arbitrary bounded Lipschitz domains, leads to a …

Learning Programming In Informal Spaces: Using Emotion As A Lens To Understand Novice Struggles On R/Learnprogramming, Alif Al Hasan, Subarna Saha, Mia Mohammad Imran

Computer Science Faculty Research & Creative Works

Novice programmers experience emotional difficulties in informal online learning environments, where Confusion and Frustration can hinder motivation and learning outcomes. This study investigates novice programmers' emotional experiences in informal settings, identifies causes of emotional struggle, and explores design opportunities for affect-aware support systems. We manually annotated 1,500 posts from r/learnprogramming using the Learning-Centered Emotions framework, applying clustering, and axial coding. Confusion, Curiosity, and Frustration dominated emotional experiences, sometimes co-occurring and linked to early learning stages. Positive emotions were infrequent. The primary emotional triggers included ambiguous errors, unclear learning pathways, and misaligned resources. We identify five key areas where novice programmers …

Performance Evaluation Of Approximate Nearest Neighbor Search On Nvidia Bluefield-3 Dpu, Sophia Bhoria, Nathan Tibbetts, Arjun Kirubakaran, Alima Subedi, Satish Puri

Computer Science Faculty Research & Creative Works

Advanced SmartNICs known as Data Processing Units (DPU) enable in-network data analytics, being equipped with standard processors and accelerators capable of doing custom computation on-NIC. These SmartNICs are advantageous because the host CPU can delegate simpler data analytics tasks, like filtering, to the NIC where the data first arrives. Only data needing further refinement must be passed on to the host CPU. Our benchmarks focus on NVIDIA's commercially available Bluefield-3 DPU. Similarity search, particularly Approximate Nearest Neighbor (ANN) search, is an important domain with wide usage across numerous applications. We explore ANN search on SmartNICs, providing insight into the performance …

Genedit: A Context-Aware Equity, Diversity And Inclusion Principles Integration Tool For Software Engineering Education, Chetan Arora, Ajanie Kodagoda Bammanna Arachchige, Jinchun Du, Muhammad Aamir Cheema, Aster Cosmos, Antonette Shibani, Vasudha Malhotra, Naeem Janjua, Afaq Shah

Research outputs 2022 to 2026

Equity, diversity and inclusion (EDI) is widely acknowledged as essential in software engineering (SE), yet day-to-day integration into teaching remains uncommon due to time pressures, low instructor confidence, and fragmented resources. We present GenEDIt, a purpose-built, LLM-backed chatbot that helps educators weave EDI into SE education artefacts without altering intended learning outcomes. Unlike generic chat interfaces, GenEDIt provides a tailored UI and workflow, and embeds retrieval over a vetted EDI knowledge base. The tool supports five educator-centred modes - (1) methods for integrating EDI into current activities; (2) examples/datasets; (3) EDI-integrated assessments and rubrics; (4) reflective prompts; and (5) rapid …

Building The Next Cybersecurity Workforce: A Grades 7–12 Curriculum To Close The Cyber Talent Gap, Mohammed A. Salam, Iqbal Shareef, Rich P. Manprisio

Journal of Cybersecurity Education, Research and Practice

In today’s rapidly evolving technological landscape, cyberattacks pose increasing threats, yet a global shortage of cybersecurity and digital forensics professionals leaves industries vulnerable, similar to having too few law enforcement officers in a densely populated city. The judicial system faces rising digital crimes and fraud cases, further strained by the lack of experts to analyze and extract digital evidence. Despite high demand, millions of positions remain unfilled. This paper identifies the root causes of the cybersecurity workforce shortage and proposes a targeted solution: a curriculum for Grades 7–12 designed to foster cybersecurity awareness and interest. The methodology included a comprehensive …

Human-Driven, Autonomous, Or Hybrid? The Optimal Fleet Configurations For Ride-Hailing Platforms, Wenjing Li, Yali Zhang, Jun Sun, Zhaojun Yang

Information Systems Faculty Publications

The growing commercialization of autonomous vehicles (AVs) is reshaping consumer service preferences and prompting ride-hailing platforms to redesign fleet structures that accommodate the coexistence of human-driven vehicles (HVs) and AVs. This article develops a queueing game framework that incorporates vehicle heterogeneity and consumer preference differences to systematically compare three fleet configuration strategies: the pure HV (PHV) strategy (HVs only), the pure AV (PAV) strategy (AVs only), and the hybrid strategy (both HVs and AVs). The analysis highlights how consumer mismatch losses, AV operating costs, and service rates jointly shape equilibrium outcomes. Results show that when consumer mismatch losses are moderate, …

Capturing An Electron In The Virtual State, Alok Nath Singh, Bibek Bhandari, Rafael Sánchez, Andrew N. Jordan

Mathematics, Physics, and Computer Science Faculty Articles and Research

We address a foundational question in quantum mechanics: can a particle be directly found in a classically-forbidden virtual state? We instantiate this conceptual question by investigating the traversal of electrons through a tunnel barrier, which we define in a triple quantum dot system where the occupation of the central dot is energetically avoided. The motivation behind this setup is to answer whether the central dot is occupied or not during a virtual transition when it is being explicitly monitored. We investigate this problem in two different limits of continuous measurements: the stochastic quantum diffusion and the quantum jump. We find …

Taxing Ai In The Wake Of The Emergence Of Agentic Ai, Reuven S. Avi-Yonah, Herbert Snitz

Articles

This article addresses taxation measures to regulate AI agents (i.e., AI that is not fully under the control of humans, including both ANI and AGI). In each case, the focus is on what the agent’s capabilities would be, not on how it becomes capable of successfully performing its tasks (though the latter would likely be relevant to important philosophical questions, e.g., might robots achieve sentience or consciousness, and if so, would they have rights?). Regarding mirroring what we human beings can do, the hallmark of AGI is that it will not be task-specific (like ANI), but will possess broad capabilities, …

Contemporary Cybersecurity Challenges In Emerging Technologies: A Systematic Literature Analysis, Faztudo Languisse Prof

Journal of Cybersecurity Education, Research and Practice

The accelerating convergence of artificial intelligence (AI), the Internet of Things (IoT), cloud computing, blockchain, and quantum computing has fundamentally transformed the global threat landscape, introducing cybersecurity challenges of unprecedented complexity and scale. This systematic literature review synthesizes findings from peer-reviewed publications, institutional reports, and regulatory documents published primarily between 2020 and 2025 to provide an integrated analysis of contemporary cybersecurity challenges across five key emerging technology domains. The review identifies critical vulnerabilities inherent to each domain, documents the evolution of threat actors and attack methodologies — including AI-powered ransomware, adversarial machine learning, and harvest-now-decrypt-later quantum attacks — and evaluates …

Ecological Footprint Assessment, Santina Benincasa

Open Educational Resources

This handout guides students through a structured ecological footprint assessment using the online Footprint Calculator. By following a series of steps—selecting their location, entering detailed lifestyle information, and reviewing personalized results—students evaluate how many planets would be required if everyone lived with their same resource consumption patterns. The activity prompts learners to identify the largest contributors to their footprint, quantify their impact in global hectares, and explore scenario-based changes that could reduce their environmental demand. Through reflection, students consider how everyday human behaviors influence Earth’s productive capacity and resource availability. Overall, the exercise encourages critical thinking about sustainability and personal …

Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit Insufficiently Reclaimed Sites Quality Assurance Project Plan, Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit Unreclaimed Sites Quality Assurance Project Plan, Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Experimental And Density Functional Theory Study Of The Structural, Optical, And Electronic Properties Of La2Nimno6 And Nd2Nimno6 Double Perovskite Ceramics, Mahmoud S. Alkathy, Anibal Thiago Bezerra, Person Pereira Neves, Mariama Rebello De Sousa Dias, Alexandre José Gualdi, Marco Daldin Teodoro, Valmo R. Mastelaro, José A. Eiras

Physics Faculty Publications

Despite extensive study of La₂NiMnO₆ double perovskites, a systematic understanding of the effects of A-site rare-earth substitution on coupled structural, electronic, and optical properties remains lacking. Here, we provide the first integrated experimental-computational comparison of La₂NiMnO₆ (LaNMO) and Nd₂NiMnO₆ (NdNMO), establishing quantitative structure–property relationships. Rietveld refinement demonstrates that Nd³⁺ substitution amplifies MnO₆ and NiO₆ octahedral distortions 5-fold (Δd_Mn: 4.69 × 10^–4 to 23.9 × 10^–4; Δd_Ni: 1.18 × 10^–4 to 5.91 × 10^–4), reduces Mn–O–Ni bond …

Re: Conditional Approval Letter For The Butte Priority Soils Operable Unit Unreclaimed Sites Quality Assurance Project Plan, Emma Rott

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Narrowband Searches For Continuous Gravitational Waves From Known Pulsars In The First Two Parts Of The Fourth Ligo–Virgo–Kagra Observing Run, A. G. Abac, I. Abouelfettouh, Teviet Creighton, Mario C. Diaz, Raul Alberto Espinosa Perez, J. Lawrence, Francisco Llamas Villarreal, Miriam Ramos Arevalo, Soma Mukherjee, Gaukhar Nurbek, Volker Quetschke, Wenhui Wang

Physics & Astronomy Faculty Publications

Rotating nonaxisymmetric neutron stars (NSs) are promising sources for continuous gravitational waves (CWs). CWs may, if detected, inform us about the internal structure and equation of state of NSs. Here, we present a narrowband search for CWs from known pulsars, for which a matched-filter search can be applied. Narrowband searches are robust to mismatches between electromagnetic (EM) and gravitational emissions, in contrast to fully targeted searches where they are assumed to be phase-locked. In this work, we search for the CW counterparts emitted by 34 pulsars using data from the first and second parts of the fourth LIGO–Virgo–KAGRA observing run. …

Gwtc-4.0: Population Properties Of Merging Compact Binaries, A. G. Abac, I. Abouelfettouh, Teviet Creighton, Mario C. Diaz, Raul Alberto Espinosa Perez, J Lawrence, Francisco Llamas Villarreal, Soma Mukherjee, Volker Quetschke, Wenhui Wang

Physics & Astronomy Faculty Publications

We detail the population properties of binary neutron star, neutron star–black hole binary, and binary black hole mergers using 158 events from the cumulative Gravitational-Wave Transient Catalog 4.0. The black hole primary mass distribution consists of a power-law-like continuum that steepens above 35 M⊙ with overdensities at 10 M⊙ and 35 M⊙. Binary black holes with primary masses near 10 M⊙ are more likely to have less massive secondaries, with a mass ratio distribution peaking at  q=0.74+0.13−0.13, potentially a signature of stable mass transfer during binary evolution. Black hole spins are inferred to be nonextremal, with …

2026 July 9 - Tennessee Weekly Drought Summary, Tennessee Climate Office, East Tennessee State University

Tennessee Climate Office Weekly Drought Summaries

No abstract provided.

Signal And Substance: Why Methodological Sophistication Fails To Guarantee Inference, Aamir Rashid, Rizwana Rasheed

Publications and Research

Despite increasing analytical sophistication, empirical research in organization studies continues to suffer from fragile inference, uneven theoretical accumulation, and contested credibility. This paper seeks to explain why these problems persist by shifting attention from authors’ methodological choices to the evaluative dynamics of peer review. Adopting a conceptual and theory-analytic approach, the paper theorizes peer review as an inferential gatekeeping system. Drawing on research design, theory evaluation, and philosophy-of-science literatures, this study develops an analytical framework to examine how evaluative routines shape what constitutes empirical rigor during the review process. The analysis identifies five recurring reviewer blind spots: inferential scope inflation, …