Digital Commons Network^™

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 …

Spatiotemporal Variations Of Tidal Asymmetry Along The Coast Of Taiwan: Characteristics And Implications, Ting-Chieh Lin, Tai-Wen Hsu, Tzu-Chun Huang, Chun-Yuan Lin

Journal of Marine Science and Technology–Taiwan

This study presents the first systematic investigation into the spatiotemporal characteristics and evolutionary trends of tidal asymmetry along the coast of Taiwan from 2003 to 2022, employing a moving window method combined with the S_TIDE toolbox.  By quantifying the skewness of the Main Tidal Asymmetry Combinations (MTAC) and their temporal variations, the study reveals significant regional disparities between the eastern and western coasts.  The western coast is primarily dominated by the M2-M4 combination, with the northwestern region exhibiting a flood dominance pattern and the southwestern region characterized by ebb dominance.  Conversely, the eastern coast, attributed to its open topography and …

Synchronous Deep Reinforcement Learning For Optimized Storage Assignment Of Ship Blocks, Gawon Lee, Jaehyeon Heo, Misung Kim, Hyerim Bae

Journal of Marine Science and Technology–Taiwan

This paper presents a deep reinforcement learning (RL) framework for optimizing block storage allocation in shipbuilding yards. During the shipbuilding process, vessels are constructed in block units to maximize the operational efficiency. Following assembly, these blocks must be stored in limited yard spaces, creating a complex variant of the binary packing problem. This storage allocation problem is further complicated by operational constraints, including the barge capacity and transportation time restrictions. Moreover, poor storage decisions can lead to redundant block movements, which can adversely affect downstream processes and increase operational costs. To resolve this problem, a policy-gradient-based synchronous RL model was …

Exploring Consultancy-Related Variations In Public Building Projects: A Review Towards A Management Framework, Grayson Bambaza, Ismail W. R. Taifa, George S, Mwaluko

Tanzania Journal of Engineering and Technology (TJET)

Consultancy-related variations remain one of the leading causes of cost overruns, schedule delays, quality deficiencies, and contractual disputes in public building projects. Although various studies have been undertaken to document the causes of variations in construction works, the same level of interest has not been shown for consulting services variations across the consulting services spectrum and their consequences for effective management. This study explores variations in consulting services for public works by systematically reviewing the existing literature using the PRISMA (Preferred Reporting Items for Systematic reviews and Meta Analyses) guidelines. Relevant articles published from 2020 to 2026 were retrieved from …

Decision Support Tool For The Maintenance Of Meter Gauge Railway Permanent-Way Infrastructures: A Concept Paper, Hamisi J. Maulid, Beatus A.T Kundi, Juma M. Matindana, Ismail W. R. Taifa Dr

Tanzania Journal of Engineering and Technology (TJET)

A Decision Support Tool (DST) represents a transformative way of modernising maintenance practice on the permanent-way infrastructure of Meter Gauge Railway (MGR). Maintenance practice remains largely reactive, as the MGR plays a strategic role in transporting both freight and passengers, resulting in inefficient resource allocation, high operational risk, and growing Lifecycle expenses. This concept paper explores the potential and the design challenges for a DST that combines fuzzy analytic hierarchy process (Fuzzy-AHP) modelling, multi-criteria decision analysis (MCDA), Geographic Information Systems (GIS) and predictive machine learning (ML) analytics for evidence-based, future-oriented maintenance management. The paper draws on peer-reviewed studies from …

Project-Based Conversion Versus Prototype-Based Instruction In Automotive Teacher Education, Ramdhani Ramdhani, Sriyono Sriyono, Wahid Munawar, Raafi Rizki Maulana, Apriyansah Bahrudin

Jurnal Pendidikan: Teori, Penelitian, dan Pengembangan

The transition to electric and hydrogen mobility is reshaping the competencies that automotive vocational teaching requires, yet institutions with limited equipment must choose between authentic learning designs without evidence of what each produces. Indonesian research to date has built substitute learning media and reported feasibility ratings rather than measured learning. This study asks what cognitive and psychomotor gains two contrasting designs produce and how those gains compare. Two pre-experimental studies were conducted in one automotive teacher education programme in Indonesia. Study A used a time-series design across three project cycles of 200 minutes in which 15 undergraduates converted a combustion …

Hydrothermal Alteration Mapping Of The Northern Coongan Greenstone Belt Using Remote Sensing Imagery, Meaza Bogale, Elias Woldeyohanis

Journal of Sustainable Mining

Archean greenstone belts are well known for their ore deposits, diverse lithostratigraphy, and well-preserved evidence from the early Earth. The Northern Coongan Greenstone Belt is an Archean greenstone belt that is part of the Eastern Pilbara Craton of Western Australia. The rock units of this area have the potential to be sources of valuable mineral deposits, which could be economically beneficial for extraction. Studies have been conducted in the northern Coongan greenstone belt, mostly using geological field methods and geophysical interpretations, excluding remote sensing methods for mapping mineral indices. Therefore, this study aims at providing surface mineral distribution maps and …

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 …

The Evolution Characteristics Of Gas Pressure Around Coal Seam Directional Long Extraction Boreholes With Nonlinear Extraction Negative Pressure, Zhang Qi, Jia Jinlong, Li Zhiguo, Zhang Longgang, Qin Zhengyuan, Zhang Weizhong, Li Jin

Journal of Sustainable Mining

Nonlinear pressure of coal seam gas in the directional borehole and surrounding areas affects extraction efficiency. A multi-field coupling numerical model, including gas desorption, diffusion, fracture seepage, and borehole extraction, is developed for the No. 3 coal seam of the GJH mine. Using the numerical simulation method of control variables, extraction was developed to investigate the nonlinear evolution of axial pressure gradients in directional long borehole and the spatiotemporal response characteristics of gas pressure. Results show that coal seam seepage pressure exhibits a nonlinear radial gradient attenuation around the borehole, evolving through rapid pressure change, stabilization, and slow adjustment. The …

Parametric Study On The Plastic Hinge Length Of Precast Concrete Columns With Grouted Sleeve Connections, Rizky Tri Amalia, Harun Alrasyid

Journal of Sustainable Construction Materials and Technologies

The use of precast concrete structures with grouted sleeve (GS) connections has gained significant traction in the acceleration of bridge construction. The plastic hinge length (Lp) is a critical parameter for assessing the seismic performance and deformation capacity of such structural members. The previous study has proposed empirical equations for Lp in monolithic columns; however, a comprehensive understanding of the influential parameters on Lp in precast concrete columns with GS connections remains limited. This study presents a detailed parametric investigation to evaluate the effects of key design parameters on the plastic hinge length of a precast concrete columns with GS …

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. …

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), …

Polymer Nanocomposite Dielectrics For High-Temperature Superconducting Cables: Cryogenic Characterization And Testing Environment Development, Jared R. Ericksen

Theses and Dissertations

High-temperature superconducting (HTS) cables require dielectric insulation materials that can withstand cryogenic operating environments while maintaining electrical reliability, mechanical stability, and manufacturing compatibility. This thesis investigates polyamide-based polymer nanocomposites as candidate HTS cable insulation materials and develops cryogenic testing platforms for evaluating thin-film dielectrics at reduced temperatures. Two silicon-based filler systems are studied: sol-gel-derived silicon dioxide (SiO 2 ) nanoparticles and polyhedral oligomeric silsesquioxane (POSS). Dielectric breakdown behavior is evaluated under DC and AC high-potential testing, while mechanical behavior is assessed through tensile testing. The results show that PA/SiO 2 nanocomposites provide the strongest overall balance of mechanical reinforcement and …

From Disaster To Resilience: Developing Smart Settlements In The Himalayas, Keshav Bhattarai, Ambika P. Adhikari

Himalayan Research Papers Archive

Nepal’s catastrophic 26 August 2026 Bhote Koshi–Trishuli flood should be understood not only as a humanitarian tragedy but also as a potentially major turning point in updating national settlement and reconstruction policy. Engineers and scientists have described the floods as a glacier–bedrock collapse that triggered an ice-rock avalanche and debris flow. As per the live updates on September 7, 2026, the total death toll was 1,355, and 4,996 people were missing (The Hindu, 2026). Indian and Nepali rescuers worked urgently to locate and rescue people buried under hydropower tunnels, buildings, mud, and landslide debris.

UN News reported on September 3, …

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 …

From Himalayan Catastrophe To National Resilience: Lessons From The 2026 Bhote Koshi And Trishuli River Floods In Nepal, Keshav Bhattarai, Ambika P. Adhikari

Himalayan Research Papers Archive

On the morning of 26 August 2026, the mountains above Nepal’s northern frontier delivered a disaster of almost unimaginable speed and scale. A massive mass of ice, rock, and sediment detached in the high Himalayan terrain near the Nepal–Tibet border, descended roughly 1,200 metres, interacted with the Lhende Khola system, and generated a debris-rich flood that surged through the Bhote Koshi and Trishuli river corridors, destroying settlements, markets, roads, bridges, hydropower facilities, and an international border crossing and transforming them into fields of mud, boulders, and wreckage within minutes (ICIMOD, 2026b; Reuters, 2026a). Satellite analysis indicates that a substantial section …

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 …

Studying Electromagnetic Wave Scattering From Small Dielectric Particles Using Neural Networks, Bryan Taylan, Patrick Corzo, Chris Velissaris, Theodoros Panagiotakopoulos

Undergraduate Scholarship and Creative Works

Physics-informed neural networks solve the Helmholtz equation without labeled data, but a low residual alone does not confirm that a solution preserves the physical distinction a downstream task depends on. We trained a four-layer SIREN with physics-based residuals, a Sommerfeld condition, Adam, and L-BFGS, modeling a Gaussian source and a plane wave scattering from a small dielectric inclusion. Fine-tuning from four base models produced 600 complex fields spanning omega = 4 to 20. A compact CNN, three ResNet-18 variants, and a frozen OpenCLIP encoder classified these fields under five random seeds. The CNN achieved (95.65 +/- 0.77)% accuracy, outperforming OpenCLIP …

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 …

Artificial Intelligence In Food Engineering For Food Safety, Quality Assurance, And Human Health, Ayad Abbood Abdulhasan, A. M. Mustafa, F. F. Sayyid, Marwan B. Hussein, Mohanad Muzahem Khalaf

AUIQ Technical Engineering Science

Artificial intelligence (AI) is increasingly reshaping food engineering by providing data-driven tools for safeguarding food safety, ensuring quality assurance, and improving human health outcomes. This review synthesizes current evidence on the application of machine learning, deep learning, computer vision, and the Internet of Things (IoT) across the food production continuum, from raw material inspection to consumer-facing nutrition guidance. We examine how convolutional neural networks, hyperspectral imaging, and sensor-fusion approaches enable rapid, non-destructive detection of contaminants and pathogens, and how predictive models support shelf-life estimation and quality grading. We further discuss AI-enabled traceability systems, including blockchain-integrated supply chains, and the growing …

Edge Computing-Enabled Secure Federated Learning For Anomaly Detection In Industrial Iot Sensor Streams, Wijdan Noaman Marzoog Al Mukhtar

AUIQ Technical Engineering Science

The rise of the Industrial IoT (IIoT) will result in a surge of IIoT devices with high-velocity data streams requiring rapid, real-time analysis of these data streams to power predictive maintenance and assure cybersecurity. Centralized cloud-based approaches to anomaly detection are hindered by their inherent latency and privacy issues while independent or stand-alone approaches to edge-based anomaly detection do not have enough data to effectively detect anomalies. This paper presents a federated learning framework to collaboratively develop an anomaly detection model from multiple edge nodes, without sharing the raw sensor data, so that data sovereignty is preserved. Two major contributions …

Notes For The Contributors, Space & Defense

Space and Defense

No abstract provided.

Autonomous Navigation In Cislunar Satellites, Heith Johnson

Space and Defense

Cislunar space—the region between Earth’s geosynchronous orbit (about 36,000 kilometers from Earth) and the Moon (roughly 384,000 kilometers away)—is becoming a critical frontier for future space exploration and commercialization.1 This zone includes the Moon’s orbit, transfer orbits, and the Earth-Moon Lagrange points. Additionally, as more nations and corporations launch lunar missions and establish long-term infrastructure, cislunar space is increasingly becoming a strategic focus for exploration, logistics, and transportation.

Space & Defense Vol. 17 No. 1 Editor's Note, Damon Coletta

Space and Defense

No abstract provided.

Space & Defense Volume 17 Issue 1 Summer 2026 (Whole Issue), Space & Defense

Space and Defense

No abstract provided.

Individualized Bayesian Inference Identifies Novel Genetic Variants For Parkinson's Disease, Jin Ren, Yasaman J. Soofi, Md Asad Rahman, Qing Lu, Jinling Liu

Engineering Management and Systems Engineering Faculty Research & Creative Works

Parkinson's disease (PD) is a complex neurodegenerative disorder with a significant genetic component. While genome-wide association studies (GWAS) have been instrumental in identifying genetic variants associated with PD, the reliance on large sample sizes and population-level analyses may overlook variants with lower minor allele frequencies or individual-specific relevance. Individualized Bayesian Inference (IBI) offers a promising method to complement GWAS by identifying and prioritizing candidate genetic markers at both the individual and patients-like-me subgroup levels. This study evaluates the application of IBI to PD genetics, using GWAS as a baseline for comparison. We analyzed genetic data from the Fox Insight online …

A Framework For Automated Quantity Extraction From .Ifc Models And Normalized Bid Comparison, Asmaa Mohamed Farouk

Theses and Dissertations

Accurate bid comparison remains a major challenge in construction tendering due to

differences in Bill of Quantities formats, item naming conventions, and pricing methods across

contractor submissions. These variations require time-consuming manual work and often lead to

subjective decisions. This research presents a computational framework that uses Building

Information Modeling through the .ifc file format, combined with text analysis techniques for

automated bid normalization.

The developed system uses a dual-component approach. Phase 1 extracts quantities from .ifc

model files using 3D geometric calculations, automated element classification. Phase 2 uses text

mining with a domain-specific dictionary of construction terms to interpret …

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.

Kentucky Transportation Cabinet Secretary’S Office Of Safety ‘Safety Academy’, Gabriel Dadi, Farshid Taherpour, Amanda Casolare

Kentucky Transportation Center Research Report

The Kentucky Transportation Cabinet (KYTC) Safety Academy was developed to provide a structured and practical safety training program that strengthens safety leadership, planning, communication, employee engagement, hazard recognition, and continuous improvement across KYTC operations. The program was refined over the course of multiple discussions with Cabinet representatives to ensure that the content reflected the needs and responsibilities of KYTC personnel. The final Safety Academy consists of six modules: Safety Academy Welcome, Safety Leadership, Safety Planning, Safety Engagement, Hazard Recognition, and Safety Academy Closeout and Evaluation. The modules combine instructional content with discussions, practical examples, group exercises, and KYTC-related scenarios to …

The Instability And Unsustainability Of Our Planned, Or Imagined Media Future, Thom Gencarelli

Proceedings of the New York State Communication Association

In the face of the growth and planned growth of industrial developments in artificial intelligence, embodied AI, immersive media/virtual reality, and the fintech industry and cryptocurrencies – and the energy requirements for each of these and all of them together – this paper examines the question of whether the plans for growth and future development in these areas is probable, possible, problematic, or impossible.  Additionally, the examination is situated atop both state-based and criminal threats to use the Internet and mobile Internet to wreak havoc and instability.