Digital Commons Network^™

Cross-Dataset Stability Assessment Of A Fixed-Configuration Catboost Model Across Heterogeneous Civil Engineering Material Datasets, Arslan Qayyum Khan, Ali Raza, Amorn Pimanmas

Civil Engineering Faculty Publications

Machine learning (ML) has increasingly been applied in civil and structural engineering for predicting material and structural performance. However, most existing studies either benchmark several algorithms within a single dataset or review such findings, leaving the cross-dataset stability of one fixed model configuration largely unquantified. This study proposes a generalized ML evaluation framework to investigate the robustness and stability of a fixed-configuration model across multiple civil engineering material datasets. Ten datasets representing diverse structural and material problems were compiled, including 3D printed concrete (3DPC), conventional and advanced concrete including normal and high strength concrete (NHSC), recycled aggregate concrete (RAC), ultra-high-performance …

Sensors And Smart Food Packaging For Supply Chains: Bridging Expiration Dates And Actual Perishability, Muhammad Umar Azam, Jolina Rodrigues, Mohamed Hamid Salim, Sarath Haridas Kaniyamparambil, Khalid Askar, Imane Belyamani, Blaise L. Tardy, Nouha Alcheikh

All Works

The food supply chain is undergoing critical changes to minimize environmental hazards, such as those associated with packaging, and reduce food waste and loss. One of the critical components of the latter is associated with the high variance in the perishability of individual foodstuffs. Herein, we review the state of the art in smart sensor systems and emphasize the critical role they could play in addressing the mismatch between “batch” based expiry dates and individual food products’ time-dependent responses to spoilage. Following a brief overview of food shelf life and associated legislation, a subsequent section summarizes the development of sensors …

The Vegetated-Canopy Roughness Sublayer Through A Tke-Budget Lens, Giulia Salmaso, Raul Bayoan Cal, Marc Calaf

Mechanical and Materials Engineering Faculty Publications and Presentations

It is well understood that vegetated canopies perturb the atmospheric flow within and immediately above the canopy, deviating from the inertial sublayer (ISL) regime characteristic of non-vegetated rough surfaces. Only above a certain height, denoted as the roughness sublayer height (RSL, 𝑧∗), do these flows return to ISL-like behavior. This distinction is critical, as parameterizations in Earth System Models (ESMs) are typically developed for ISL flows. Yet, most 𝑧∗ estimates stem from studies over flat, homogeneous canopies and may be biased. In contrast, little is known about 𝑧∗ in non-homogeneous or heterogeneous canopies that are not of agricultural interest, with …

Performance Evaluation Of Header Pipe In Heat Pipe Evacuated Tube Solar Collector By Dimpled Condensers, Furqan Jamil, Mehdi Khiadani, Yasir M. Al-Abdeli, Abdellah Shafieian

Research outputs 2022 to 2026

Among different solar water heaters, heat pipe-based solar water heaters foster potential solutions to alleviate water scarcity. However, a lower outlet temperature at the outlet section of their header pipe reveals low system efficiency due to limited heat transfer between the flowing fluid and the heat pipe condenser walls. The main aim of this study is to investigate a model manifold header pipe having five condenser sections with a dimple pattern to replicate internal features of heat pipe condensers within an evacuated tube solar collector, and its significance is to provide a comprehensive understanding of flow and thermal behaviour in …

Size-Tunable Tellurium Quantum Dots By Glancing Angle Deposition, S. M. Sayem, Salim Hussain, Fernando Maia De Oliveira, Ranjitha Kumarapuram Hariharalakshmanan, Gregory Guisbiers, Tansel Karabacak

Faculty Scholarship

Tellurium has a unique helical crystal arrangement and pronounced anisotropy that influence its electronic and optical properties at the nanoscale. This study reports the synthesis of pure tellurium quantum dots (Te QDs) on silicon wafer using glancing angle deposition (GLAD). Quasi-hemispherical dots with lateral sizes ranging from 9 to 28 nm and vertical dimensions of 6 to 10 nm were produced as a function of the deposition duration. A comparison of the dot sizes with the Bohr radii of the charge carriers indicated a regime of strong to intermediate confinement. Structural analyses confirmed the polycrystalline nature and trigonal phase of …

Aidws1: Building With Llms And Ai Agent, Olivier Kepler Francois

Paul English Applied Artificial Intelligence (AI) Institute Publications

The Paul English Applied Artificial Intelligence Institute (PEAAII) at the University of Massachusetts Boston hosted the first session of its AI Demo Workshop Series, “Building with LLMs and AI Agents,” on October 5, 2026, led by Olivier Kepler Francois, Founder and Researcher of WebAIAgent. This hands-on workshop introduced participants to developing AI-powered web applications using Large Language Models (LLMs), Next.js, React, HTTP communication, and the OpenAI API. Through guided demonstrations and practical exercises, participants explored frontend and backend development, API integration, user interaction, and the end-to-end process of building an interactive AI application. The session provided foundational knowledge and practical …

Analysis And Design Of Multi-Winding Current Ballasted Magnetics For Integrated Dc-Dc Conversion, Kishalay Datta

Dartmouth College Ph.D Dissertations

Power conversion circuits have become a bottleneck in terms of reducing the size and cost of modern electronic systems in a vast number of applications ranging from personal devices, to automotive systems, to data centers. This has motivated designs at higher frequencies where smaller passive components can be used. Unfortunately, magnetic components scale poorly to smaller dimensions. In addition, the AC resistance of magnetic components deteriorates due to current crowding effects at high frequencies. This has resulted in fully- integrated power converters with planar magnetic components having efficiencies lower than what may be theoretically achieved. In this work, we investigate …

Treatment Of Municipal Solid Waste Incineration Bottom Ash Using Cement For Integrated Recovery Of Hydrogen And Production Of Supplementary Cementitious Material, Muhammad Haris Javed, Wenyu Liao, Fathma Zuhra, David Vollero, David Schmidenberg, Hongyan Ma

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Municipal solid waste incineration (MSWI) bottom ash (MBA) represents both a disposal challenge and a potential resource for sustainable construction materials, including use as a supplementary cementitious material (SCM). However, the conventional use of MBA in cement-based materials is hindered by its high metallic aluminum content, which reacts in alkaline environments to release hydrogen gas and causes volumetric instability (e.g., expansion and cracking). This study investigates a cement-based alkali pretreatment method using diluted cement suspension to stabilize metallic aluminum and improve the compatibility of MBA as an SCM. Compared to conventional alkali solutions, the proposed approach avoids the direct use …

Graphene Oxide–Driven In Situ Bismuth Reduction Enables Highly Efficient Electroreduction Of Co2 To Formic Acid, Hao Feng, Bohong Zhang, Jie Huang, Xinhua Liang

Electrical and Computer Engineering Faculty Research & Creative Works

To enable large scale efficient electrochemical CO₂ reduction reaction (CO₂RR) to formic acid (HCOOH), it is important to develop catalysts that can be operated in a wide potential window with good stability. Herein, we successfully synthesized Bi₂O₃ catalyst supported on graphene oxide (GO) and graphene (G) and found that Bi₂O₃/GO catalyst had a better overall performance than Bi₂O₃/G. The Bi₂O₃/GO catalyst demonstrated an outstanding CO₂RR performance with a greater than 90% faradaic efficiency (FE) across a wide applied potential window …

Thermo-Mechanical Behaviour Of Metal-Coated Optical Fibers For Distributed High-Temperature Sensing: From Laboratory Characterization To Industrial Case Validation, Koustav Dey, Rony Kumer Saha, Bohong Zhang, Laura Bartlett, Jeffrey D. Smith, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Reliable distributed temperature sensing in high-temperature environments remains a significant challenge due to the thermal and mechanical limitations of conventional optical fibers. In particular, polymer-coated fibers degrade above ∼300 °C due to coating failure, mechanical fragility and hydrogen ingress. Metal-coated optical fibers offer a robust alternative for harsh environments such as Electric Arc Furnaces (EAFs), aerospace engines, nuclear systems, and oil and gas wells, owing to their superior mechanical strength and hermetic sealing. In this work, a first comprehensive experimental investigation of the thermo-mechanical behavior of metal-coated optical fibers for distributed high temperature sensing is presented over a wide temperature …

Rheology Modifiers For Water-Based Slurry Pipeline Transportation: Overview, Efficiency, And Intensification, Ahmed Alalou, Mohammed El Asri, Ahmed Boulahna, Muthanna H. Al-Dahhan

Chemical and Biochemical Engineering Faculty Research & Creative Works

Owing to their cost-efficiency and eco-friendliness, water-based slurry pipelines are the state-of-the-art technology for the transportation of several types of solids such as coal, fly ash, petcoke, iron ore, phosphate rock and other minerals. This review comprehensively examines the effect of numerous commercial dispersants and novel chemical additives that are used as rheology modifiers to enhance the slurryability and fluidity of solid-water slurries at high solids loading. Several key performance parameters such as the rheological characteristics (shear stress, apparent viscosity, yields stress, and flow behavior), the potential stability, surface tension and contact angle that highlight the efficiency of the rheology …

Ph-Compensated Hydrogen Peroxide Quantification Using A Dual-Modal Fiber-Optic Probe, Homayoon Soleimani Dinani, Bohong Zhang, Maryam Karimi, Rex E. Gerald, Shelley D. Minteer, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

We report a dual-modal fiber-optic probe that integrates electrochemical quantification of hydrogen peroxide (H₂O₂) with co-localized fluorescent pH sensing for pH-indexed interpretation of the H₂O₂ response. H₂O₂ is a reactive oxygen species involved in oxidative stress, inflammation, and cellular signaling, and local pH modulates both its production and electrochemical response. Many electrochemical H₂O₂ sensors exhibit pH-dependent sensitivity, creating ambiguity unless pH is measured and used for compensation, which is difficult in small, heterogeneous, or rapidly changing microenvironments. A three-electrode configuration—working (WE), counter (CE), and Ag/AgCl pseudo-reference (pRE) electrodes—is fabricated directly on the cylindrical surface of a 710-µm-diameter optical fiber using …

An Eco-Inspired Emulsion Membrane Harnessed With Waste Vegetable Oil For Effective Separation Of Ibuprofen: Insights Into Stability, Performance, And Kinetics, Huma Warsi Khan, A. Vijaya Bhaskar Reddy, Parvez Alam Khan, Samsur Akm Rahman, Muhammad Moniruzzaman

Publications and Research

Emulsion liquid membranes (ELMs) have emerged as excellent alternatives for the separation and recovery of biologically active drugs (BADs) from industrial waste at trace concentrations. Conventional ELMs generally utilize toxic petroleum-based solvents (PBS) that pose environmental and health risks. Although virgin vegetable oils have been appeared as sustainable alternatives to PBS, their widespread application is limited by economic constraints, resource sustainability, and competition with the food supply. In contrast, waste vegetable oil (WVO) represents an abundant, low-cost, and eco-friendly alternative, yet its potential as a green diluent for ELMs remains largely unexplored. To address this challenge, present study investigated the …

Factors Influencing Enterprise Adoption Of Ai-Enabled Computers: An Expert Judgment Quantification Approach Across Multiple Sectors, Yu Shan Su, Tugrul Daim, Chia-Hao Hung, Leong Chan, Dana Bakry

Engineering and Technology Management Faculty Publications and Presentations

This study examines the key factors influencing the adoption of Artificial Intelligence Personal Computers (AIPCs) by enterprises, exploring both the benefits and challenges of their business applications. As enterprises increasingly require real-time computing, autonomous decision-making, and improved cybersecurity, AIPC—combining artificial intelligence and edge computing—has become a strategic technology for boosting competitiveness. Particularly in scenarios with less reliance on cloud services, businesses are more likely to adopt devices with local processing and standalone AI capabilities to meet the dual needs of operational efficiency and data privacy. Through an extensive review of the literature, this study identifies four main dimensions and sixteen …

A Unified Pipeline For Network-Based Gene Pattern Discovery, Siddhartha Reddy Pullannagari, Sharlee Climer

Undergraduate Research Symposium

Large-scale genetic datasets from diverse diseases, including cancer and neurodegenerative disorders such as Alzheimer’s disease, provide unprecedented opportunities to study disease pathogenesis and generate hypotheses for drug discovery. However, identifying meaningful genetic interaction patterns within these datasets remains challenging due to combinatorial relationships amongst genes and heterogeneous biological underpinnings across subtypes. This project systematically analyzes a diverse collection of omics datasets (e.g., GSE44076, GSE97810, GSE127711, GSE112679) obtained from the NCBI Gene Expression Omnibus (GEO), spanning multiple biological conditions and data types. We use a unified computational pipeline designed to handle variation in dataset size, structure, and context. The steps in …

Disturbance-Learning Inertia Estimation Using Artificial Neural Networks For Power System Stability, Sospeter Igaanja Gabriel, Francis Mwasilu, Peter Makolo Dr.

Tanzania Journal of Engineering and Technology (TJET)

ABSTRACT

Power systems are progressively shifting towards low inertia as a result of incorporating significant amounts of intermittent and converter-based renewable energy sources, such as wind and solar power, into the current power grid network. This integration poses considerable problems to inertia and frequency control within the network due to a reduction in the proportion of synchronous generators. Furthermore, rapid frequency deviations occur due to the disparity between supply and demand during contingencies, complicating the maintenance of frequency stability within the power system. The disturbance-learning inertia estimation method for power system stability is presented. The simulation analysis is performed using …

The Algorithmic Narcissus: Ai Validation And The Atrophy Of The 'Athletic' Social Self, Ilham Phalosa Reswara, Anggi Mayangsari

Jurnal Psikologi Sosial

Artificial intelligence systems designed around continuous affirmation and minimal friction are becoming increasingly prominent as social and relational partners in everyday life. This article examines how sustained interaction with such frictionless AI systems may reshape the developmental conditions under which social selfhood forms and is maintained. Drawing on Cooley's (1902) looking glass self, Kohut's (1971) concept of optimal frustration, and the developmental literature on social competence, the article argues that frictionless AI may distort the social mirror through which identity forms, remove the manageable frustration that appears necessary for psychological growth, weaken empathic capacity, and erode the social stakes that …

Decision Support System For The Selection Of Thumbprint Recognition Algorithms In Biometric Security Systems, Toqeer Jameel, Muhammad Riaz

Neutrosophic Systems with Applications

This study investigates fingerprint recognition in immigration operations, emphasizing the role of biometric verification in enhancing security, fairness, and operational efficiency in international mobility. To address the uncertainty, vagueness, and imprecision inherent in fingerprint identification, a novel decision-making framework is proposed by integrating interval-valued picture fuzzy (IVPF) information. Fairly aggregation operators are introduced to combine decision makers' evaluations, while extracted fingerprint features are modeled using positive, neutral, and negative membership degrees within the IVPF environment. Objective criterion weights are determined using the criteria importance through intercriteria correlation (CRITIC) method, and individual ranking is performed via the alternative ranking order method …

A Data-Driven Neutrosophic Multi-Criteria Intelligent System For Functional Disability Severity Assessment, Ehab Abdel Aziz Al-Beblawi, Mirna Samy, Abduallah Gamal

Neutrosophic Systems with Applications

Functional disability assessment is a multidimensional problem because individuals may experience different levels of difficulty across daily activities such as walking, standing, dressing, eating, grasping objects, and social participation. This paper proposes NIFDA, a data-driven neutrosophic multi-criteria intelligent system for functional disability severity assessment. The proposed framework represents each functional response through three components: confirmed limitation, indeterminacy, and preserved functional ability. This allows the model to handle valid responses, uncertain information, and missing or non-informative data without forcing them into a single crisp score. To reduce dependence on subjective expert weighting, NIFDA derives criterion weights objectively using a hybrid CRITIC–MEREC …

Thermal Displacement Quantification And Dynamic Disparity Compensation For Automotive Stereo Cameras, Bisheng Wang, Xiyuan Hu, Ran Meng, An Jiang

Journal of System Simulation

Abstract: This paper presents a full-field thermal displacement inversion and dynamic disparity compensation method to address the disparity drift issue in mass-produced automotive-grade stereo cameras induced by thermal expansion and rigid-body displacement of image sensors under wide-temperature-range operating conditions. The proposed method leverages a high-precision static speckle pattern and digital image correlation (DIC) technique to achieve quantitative characterization of the nonuniform horizontal thermal deformation fields of the left and right image sensors. On this basis, a dynamic disparity compensation model is established, integrating a temperature-dependent quadratic polynomial translation term and a radial thermal expansion correction term. Experiments were conducted by …

Vehicle Cross-Modal Trajectory Prediction Model Based On Driving Style Hypergraphs, Guozhu Cheng, Changyuan Wang, Wenzhi Wang, Yifan Zhang, Tianjun Feng

Journal of System Simulation

Abstract: To address the shortcomings of existing motorway vehicle trajectory prediction methods which overlook differences in driving styles and the future interactions between trajectories of different modes. This paper proposes a cross-modal trajectory prediction model based on a dual-hypergraph Transformer for driving styles. The method first quantifies driving styles by extracting vehicle kinematic features and calculates a similarity matrix between vehicles; it then constructs a dual-hypergraph Transformer, using a homogeneous hypergraph to model the group interactions of vehicles with similar driving styles, and a heterogeneous hypergraph to capture the interaction relationships between spatially neighbouring but stylistically dissimilar vehicles; Finally, a …

Long-Tail Object Detection Method In Transportation Scene Images Based On Improved Rt-Detr, Mingjun Deng, Peihua Nie, Junhua Guo, Ningbo Gao

Journal of System Simulation

Abstract: Detecting rare objects in transportation environments is crucial for the safety and reliability of autonomous driving systems. To address the challenges of limited detection capability on rare objects that appear only a few times during training, we propose an improved long-tailed object detection method for traffic scene images named TF-DETR (tail free DETR) based on RT-DETR model. First, the lightweight CSP-EDA (CSP-efficient depthwise aggregation) was constructed to reconstruct the backbone network. Its core unit, the efficient depthwise aggregation, integrated the pooled-transpose attention and convolutional gated linear unit to enhance feature representations for tail-class samples. Second, the spatially-adaptive dynamic cognitive …

Vehicle Sar Image Simulation: Progress, Application And Challenge, Shengjie Luo, Zhigang Liu, Xihai Li, Yiting Wang, Xiaoniu Zeng, Xiaofeng Tan, Hongru Li, Tianyou Liu, Yun Zhang

Journal of System Simulation

Abstract: SAR image simulation technology can efficiently generate large-scale annotated data by flexibly configuring system parameters and scene conditions, breaking through the inherent limitations of high cost and long acquisition cycles associated with real SAR images, and effectively mitigating the problem of data scarcity. To elaborate on the overall research status of vehicle SAR image simulation, a classification framework for simulation methods is first established based on technical principles and methodological approaches. Subsequently, a comprehensive review of research progress is provided, offering an in-depth analysis of the theoretical foundations, practical applications, and suitable scenarios of various methods. Finally, based on …

Act Action Chunk Adaptive Optimization Method For Chemistry-Oriented Robots, Tan Li, Congying Wu, Shenghua Li, Nanjiang Chen, Weining Song, Fangfang Gao, Qi Wang, Yanwen Lin, Runmin Yin

Journal of System Simulation

Abstract: Chemical R&D laboratories face persistent challenges such as long R&D cycles and high experimental repetitiveness. With the growing demand for automation and intelligence in laboratory processes, embodied intelligent robots capable of learning expert operational experience and executing tasks stably in complex environments have become a key direction for improving chemical R&D efficiency and reducing human error. Although the hardware and software for embodied intelligence are advancing rapidly, current research focuses primarily on general-purpose operations, with limited attention to the specific constraints of chemistry laboratory settings. Traditional ACT algorithms, which use fixed action chunk sizes, fail to meet the requirements …

High-Dimensional Multi-Objective Optimization Algorithm Based On Large Language Model Assistance, Yichao Ma, Jingxuan Wei

Journal of System Simulation

Abstract: The increase in the dimension of objective functions in optimization problems makes it challenging to balance convergence and diversity in population-based algorithms, which is a key factor leading to performance degradation of multi-objective evolutionary algorithms. To address this issue, a dynamic switching mechanism assisted by a large language model is proposed. By continuously evaluating the changes in hypervolume and convergence metrics of the solution set, the search process is adaptively divided into three phases: convergence-oriented, diversity-oriented, and large language model-suggested phases, achieving precise allocation of computational resources. Furthermore, to mitigate the high computational cost of large language models in …

Modeling, Dynamical Analysis, And Lmplementation Of Switched Memristive Neural Networks, Zhuang Qu, Shaohua Zhang, Cong Wang, Hongli Zhang, Xinkai Li, Ping Ma

Journal of System Simulation

Abstract: To simulate the dynamic functional switching of brain networks, a time-switched memristive Hopfield neural network (TSM-HNN) model is proposed. The model utilizes external time-sequential signals to control memristive synapses, allowing it to dynamically generate multi-scroll chaotic attractors of varying numbers and morphologies without altering the system's structure. This overcomes the limitation of traditional chaotic systems, which can typically only produce a single type of attractor. The model exhibits complex chaotic behavior, high sensitivity to initial conditions, and coexisting attractors. Its physical feasibility has been verified through PSPice circuit simulations. This enhanced complexity and randomness give the model significant potential …

Design And Research Of A Microfocus X-Ray Tube, Haodong Zhao, Shizong Wei, Daolong Yu, Zhixia Liu, Yuezhong Chen, Ji Xu

Journal of System Simulation

Abstract: With the rapid advancement of high-resolution imaging and Micro-nano detection technology, microfocus X-ray sources show great potential for applications in industrial non-destructive testing, biomedical imaging, and material microstructure analysis. Achieving a focal spot size below 10 μm is essential for enhancing spatial resolution. However, traditional X-ray tubes are constrained by heat source dimensions, electron beam divergence, and limited focusing capabilities, which makes it challenging to simultaneously achieve focal spot miniaturization and adequate radiation intensity. In this study, a hot cathode electron gun is modeled using CST particle studio. Simulations are conducted to analyze the influence of the first anode …

Research On Characteristics Of Inclined Jet Flow For Aircraft De-Icing Based On Multiphysics Coupling, Zhiwei Xing, Hongbin Zhang, Ke Sun, Wenliang Miao

Journal of System Simulation

Abstract: To address the complex multiphysics coupling and lack of theoretical guidance for spray parameters in aircraft ground de-icing, a simulation model based on the Phase-Field method and Realizable k-ε turbulence model is proposed to investigate inclined jet flow over airfoil surfaces. The model enables the numerical reconstruction of jet impingement, liquid film flow, and unsteady heat transfer processes, providing a framework to elucidate the regulatory mechanisms of jet angles on momentum distribution and thermal characteristics. The simulation results reveal distinct variations in the flow and heat-transfer characteristics at different jet inclination angles. At a jet angle of 15°, the …

Physics-Driven Efficient Simulation Platform For Warhead-Target Engagement And Damage Assessment, Yidan Cui, Jingyao Ke, Yufeng Zheng, Kun Xue

Journal of System Simulation

Abstract: To address the limitations of incomplete physical modeling, low computational efficiency, fragmented simulation workflows, and insufficient visual immersion in existing damage simulations of fragment warheads, this paper proposes and develops a physics-driven, high-efficiency visualization platform for warhead-target engagement and damage assessment. The platform implements a full-chain, closed-loop simulation framework covering scenario configuration, force-field computation, fragment dispersion, warhead-target intersection, and damage evaluation. A finite element-discrete element (JK2024-06) coupled dynamics framework is established, integrating a detonation model, shell expansion correction, and fragment velocity inheritance to accurately reproduce the complete dynamic process from detonation to dispersion. A three-level acceleration algorithm based on …

Research On Simulation Technology Of Sea Yawing Test For Amphibious Vehicles, Yue Zhong, Wenlong Ji, Shiqi Feng, Feng Xu, Shuangping Ye

Journal of System Simulation

Abstract: Addressing the challenges of achieving extreme operating conditions and understanding the boundary conditions of yaw performance in offshore yaw tests for amphibious vehicles, a heading-flow direction angle mapping analysis method based on computational fluid dynamics (CFD) simulation and a three-dimensional hydrodynamic stratified model is proposed. Under environmental conditions of second-level (wave height of 0.5 m, wind speed of 3.3 m/s) and third-level (wave height of 1.0 m, wind speed of 5.1 m/s) sea states, a hundred-meter yaw test is simulated to reveal the nonlinear evolution law of yaw displacement and heading-flow direction angle. The research indicates that the extreme …