Digital Commons Network^™

Applications Of Nanotechnology In Building Envelopes: An Analytical Study Of Environmental Performance And Architectural Form, Essam Salah Said Abdelmagid

Mansoura Engineering Journal

Contemporary architecture has witnessed a rapid evolution in the integration of nanotechnology within the design of building envelopes, due to its significant capability to enhance the physical and environmental properties of materials and to redefine the relationship between functional performance and architectural form. The building envelope is considered one of the most influential components affecting energy efficiency, indoor environmental quality,  and visual identity, which has made it a primary field for the application of nanomaterials and nanotechnologies.

This research aims to investigate and analyze the impact of nanotechnology applications in building envelopes on both environmental performance and architectural form through …

Could 'Real Existing Ai' Be Sentient?, Tim Crane

Animal Sentience

Jonathan Birch is rightly sceptical about the idea that today’s AI machines (e.g. LLMs) are candidates for sentience. Nonetheless, he gives three reasons for taking the future possibility of AI sentience seriously. I dispute them all. Birch fails to distinguish the very idea of an artificial mind from computational AI (what I call ‘Real Existing AI’); he does not adequately distinguish a simulation from a replica or copy; and he fails to acknowledge that the appeal to computational functionalism in this context is straightforwardly question-begging.

Direct Electrochemical Detection Of Carbaryl In Water Using Boron-Doped Diamond Electrodes, Natasha Fransisca, Chico Permana Putra, Salma Nur Zakiyyah, Muhammad Ihda Hamlu Liwaissunati Zein, Yeni Wahyuni Hartati, Irkham Irkham

Chimica et Natura Acta

Carbaryl (1-naphthyl methylcarbamate) is a carbamate pesticide used to cause adverse environmental and health effects when misused through water contamination. Therefore, this research aimed to develop a direct electrochemical detection method for carbaryl in aqueous media using boron-doped diamond (BDD) electrodes. In this context, BDD electrodes exhibited superior electrochemical performance compared to conventional materials such as gold (Au), platinum (Pt), and glassy carbon electrodes (GCE) due to a wide potential window, low background current, and excellent chemical stability. Cyclic and differential pulse voltammetry reported a well-defined oxidation peak for carbaryl at 1.30 V, with significantly enhanced sensitivity. The results showed …

Willingness To Pilot Under Varying Weather And Tower System Conditions: Mediating Effects Of Risk, Nathan Royal Schultz

Doctoral Dissertations and Master's Theses

The implementation of Remote Tower Systems (RTS) within the National Airspace System (NAS) offers potential improvements in operational efficiency, cost-effectiveness, and scalability; however, its success depends on pilots' willingness to operate in such environments. This study examined the effects of tower system type (RTS vs. Traditional Tower Systems [TTS]) and weather conditions (visual meteorological conditions [VMC], marginal visual meteorological conditions [MVMC], and instrument meteorological conditions [IMC]) on pilots’ willingness to pilot (WTP), while also evaluating the mediating role of perceived risk (PR). Grounded in Paul Slovic’s Risk Perception Theory (RPT), this research employed a quantitative experimental design using a factorial …

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 …

A Review Of Natural Hydrogen Generation From Iron-Rich Rocks: Mechanisms, Influencing Factors, Techniques, And Knowledge Gaps, Kaveh Moghanirahimi, Lionel Esteban, Marina Pervukhina, Muhammad Arif, Stefan Iglauer, Alireza Keshavarz

Research outputs 2022 to 2026

Natural hydrogen has emerged as a promising clean energy resource with significant potential for large-scale subsurface production. Among the various geological sources, water–rock interactions involving iron-bearing rocks are among the most extensively studied pathways for natural hydrogen generation. This study provides a comprehensive review of hydrogen production from iron-rich lithologies, including mafic and ultramafic rocks, iron oxides, iron carbonates, and peralkaline granites. The fundamental mechanism involves the reduction of water coupled with the oxidation of ferrous iron to ferric iron under anoxic conditions. Key processes, including serpentinization, magnetite alteration, and siderite decomposition, are critically evaluated using experimental and modelling data. …

Ai-Driven Biomarker Discovery & Progression Modeling For Precision Diagnosis Of Glaucoma, Cheng Huang

Computer Science and Engineering Theses and Dissertations

This dissertation presents a comprehensive study on the integration of artificial intelligence (AI) for glaucoma diagnosis and retinal image analysis. Leveraging multimodal imaging data including fundus photography, Optical Coherence Tomography Optical Coherence Tomography (OCT) and Optical Coherence Tomography Angiography (OCTA), the research develops a suite of deep learning frameworks designed to detect early glaucomatous changes with high precision, robustness, and interpretability. A series of novel architectures are introduced, spanning vessel segmentation networks, biomarker discovery pipelines, and multimodal fusion models, all designed to enhance diagnostic accuracy and generalizability across diverse populations. To facilitate reproducible and scalable ophthalmic AI research, this work …

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 …

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 …

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 …

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 …

Decoding Surface Chemistry Effects On Polystyrene Nanoplastic Fouling In Plasma-Grafted Pes Membranes With Distinct Functional Groups, Mohadeseh Najafi, Javad Farahbakhsh, Ebrahim Mahmoudi, Michael Johns, Masoumeh Zargar

Research outputs 2022 to 2026

Nanoplastic (NP) fouling remains a key challenge for ultrafiltration (UF) membranes, yet systematic, controlled comparisons of how membrane functional groups govern NP-membrane interactions are still limited. Here, the role of membrane surface chemistry was systematically investigated using a controlled comparative framework based on plasma-grafted polyethersulfone (PES) UF membranes tailored with structurally comparable methacrylate monomers bearing distinct terminal functionalities, including mono-2-(methacryloyloxy)ethyl succinate (MMES, -COOH), N-[3-(dimethylamino)propyl] methacrylamide (DMAPMA, -N(CH3)2), and [2-(methacryloyloxy)ethyl]dimethyl-(3-sulfopropyl)ammonium hydroxide (SBMA, zwitterionic). Comprehensive characterisations supported successful surface grafting while preserving the membrane substructure. Fouling and separation were assessed using polystyrene (PS) NPs having different surface chemistries, i.e., PS, PS-COOH and …

Nanoparticle-Enabled Superplasticity In Extruded Az91 Magnesium Alloy With Elongation Exceeding 600%, Bai Xin Dong, Hong Yu Yang, Xin Zhang, Feng Qiu, Qi Chuan Jiang, Lai Chang Zhang

Research outputs 2022 to 2026

No abstract provided.

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 …

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 …

Numerically Evaluating The Effect Of Pin Geometries On Interlayer Material Mixing And Thermo-Mechanical Characteristics During Additive Friction Stir Deposition (Afsd), Numan Habib, Ana Vafadar, Ferdinando Guzzomi

Research outputs 2022 to 2026

Additive Friction Stir Deposition (AFSD) is an additive manufacturing technique used to fabricate large-sized components layer-by-layer in a solid state, below the melting temperature. Poor interlayer mixing between subsequent layers results in a lack of mechanical interlocking, leading to low-strength components. The role of pin design plays a crucial role in fabricating high-strength components, requiring a comprehensive understanding of thermo-mechanical behaviour and flow pattern in the deposition zone. In this study, five different pin geometries are presented and investigated using a three-dimensional (3D) computational fluid dynamics (CFD) model. A user-defined function (UDF) was used to calculate strain- and temperature-dependent viscosity. …

Ph-Responsive Mixed-Charge Ultrafiltration Membranes For Adaptive Control Of Single And Mixed Nanoplastic Fouling, Mohadeseh Najafi, Javad Farahbakhsh, Roham Ghanbari, Ebrahim Mahmoudi, Michael Johns, Masoumeh Zargar

Research outputs 2022 to 2026

Nanoplastic (NP) fouling is an emerging barrier to the reliable application of ultrafiltration (UF) membranes, particularly in chemically complex waters where NP surface functionality governs deposition, cake formation, and cleaning performance. Herein, pH-responsive mixed-charge UF membranes were fabricated by plasma-induced graft copolymerisation of mono-2-(methacryloyloxy) ethyl succinate (MMES) and N-[3-(dimethylamino)propyl] methacrylamide (DMAPMA) onto poly(ethersulfone) (PES) to simultaneously regulate surface charge, hydration, and fouling reversibility. Unlike conventional single-charge or zwitterionic modifications, this approach enabled independent tuning of anionic and cationic moieties, generating composition-dependent and pH-switchable interfacial properties. ATR-FTIR, XPS, FESEM/EDX, AFM, WCA, streaming zeta potential, and MWCO analyses confirmed successful grafting, modified …

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 …

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 …

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 …

A Neutrosophic Memory-Integrity Calculus For Contradiction-Preserving Persistent Ai Agents, Rana Muhammad Zulqarnain, Saalam Ali

Neutrosophic Systems with Applications

Persistent AI agents increasingly convert interaction histories into long-lived memory, making memory transformation not retrieval alone—a central reliability problem. NMIC (Neutrosophic Memory-Integrity Calculus) formalizes the integrity of write, merge, consolidation, revision, and retrieval operations over persistent memory. Each proposition is represented through an evidence ledger carrying independent truth, indeterminacy, and falsity degrees together with reliability, provenance, temporal validity, contextual applicability, and inter-evidence dependence. A dependence-normalized hazard aggregation preserves simultaneous support and opposition while making the resulting state invariant to exact evidence duplication. Pure consolidation is governed by five integrity conditions: no support invention, no opposition invention, no manufactured certainty, contradiction …

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 …