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Articles 29011 - 29040 of 715186

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A Neutrosophic And Q-Rung Orthopair Fuzzy Sets Approach For Desertification Susceptibility Mapping: A Case Study In Matrouh, Egypt, Nabil M. Abdelaziz, Khalid A. Eldrandaly, Amira M. Fawzy, Gehan A. Fouad, Safa Al-Saeed Jun 2025

A Neutrosophic And Q-Rung Orthopair Fuzzy Sets Approach For Desertification Susceptibility Mapping: A Case Study In Matrouh, Egypt, Nabil M. Abdelaziz, Khalid A. Eldrandaly, Amira M. Fawzy, Gehan A. Fouad, Safa Al-Saeed

Neutrosophic Systems with Applications

This study introduces an innovative approach to desertification susceptibility mapping by integrating q-rung orthopair fuzzy sets (Q-ROFS) with a neutrosophic environment. Conducted in Matrouh, Egypt, the research quantifies desertification risk through advanced modeling techniques that address uncertainty and non-linearity in environmental data. The Q-ROFS framework enhances risk prediction by capturing complex relationships among desertification indicators. Neutrosophic logic, meanwhile, effectively addresses imprecision and ambiguity. The resulting susceptibility map clearly distinguishes between vulnerable and non-vulnerable regions, offering valuable guidance for policymakers and planners. The analysis revealed that approximately 79.98% of the study area falls under moderate susceptibility, 14.27% under high susceptibility, and …

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A Proposed Mathematical Framework For Fuzzy It Service Management (F-Itsm) And Neutrosophic It Service Management (N-Itsm), Takaaki Fujita Jun 2025

A Proposed Mathematical Framework For Fuzzy It Service Management (F-Itsm) And Neutrosophic It Service Management (N-Itsm), Takaaki Fujita

Neutrosophic Systems with Applications

Fuzzy sets, rough sets, hyperrough sets, intuitionistic fuzzy sets, neutrosophic sets, plithogenic sets , and other frameworks for handling uncertainty are under active research every day. These concepts can model a wide range of real-world phenomena and are frequently investigated to facilitate more efficient decision-making. IT Service Management is a systematic approach to designing, delivering, managing, and improving IT services in alignment with organizational objectives. In this paper, we explore the Mathematical Frameworks for Fuzzy IT Service Management (F-ITSM) and Neutrosophic IT Service Management (N-ITSM), which combine these uncertainty-based ideas with IT Service Management practices.

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A Critical Evaluation Of The Criticisms Against Neutrosophic Statistical Methods, Muhammad Aslam, Abdulrahman Alaita, Florentin Smarandache Jun 2025

A Critical Evaluation Of The Criticisms Against Neutrosophic Statistical Methods, Muhammad Aslam, Abdulrahman Alaita, Florentin Smarandache

Neutrosophic Systems with Applications

Neutrosophic statistical analysis has gained attention for incorporating the degree of indeterminacy when analyzing imprecise and interval data under uncertainty–-an aspect often overlooked by classical statistics, fuzzy statistical analysis, and interval statistics. Recently, critical discussions have emerged regarding the use and applications of neutrosophic statistics, with some questioning its usefulness and validity. In this paper, we present a critical assessment of the existing literature, focusing on areas where misunderstandings and misinterpretations of neutrosophic statistical methods have occurred. We also examine flawed comparisons made between the results of neutrosophic statistics and interval statistics. Furthermore, substantial issues have been identified in the …

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Biochar Suppresses Growth, Pupation And Eclosion Success Of A Specialist (Manduca Sexta) And A Generalist (Spodoptera Frugiperda) Insect Herbivore, Nischal Wagle, Soumya Unnikrishnan, Satinderpal Kaur, Engil Isadora Pujol Pereira, Rupesh R. Kariyat Jun 2025

Biochar Suppresses Growth, Pupation And Eclosion Success Of A Specialist (Manduca Sexta) And A Generalist (Spodoptera Frugiperda) Insect Herbivore, Nischal Wagle, Soumya Unnikrishnan, Satinderpal Kaur, Engil Isadora Pujol Pereira, Rupesh R. Kariyat

School of Earth, Environmental, & Marine Sciences Faculty Publications

Biochar is a charcoal-like substance made by the pyrolysis of organic material from agricultural and forestry waste. While biochar is well documented for altering soil physicochemical conditions, few studies have investigated its possible effects on the management of arthropod pests. Tobacco hornworm (Manduca sexta) and fall armyworm (Spodoptera frugiperda, FAW) are specialist and generalist insect herbivores respectively, that can cause significant defoliation in natural and agricultural ecosystems. In this study, we examined whether walnut shell biochar can affect growth and development of these herbivores. Specifically, we investigated how biochar influences parameters such as mass gain, length …

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Exposure To Metoprolol And Propranolol Mixtures On Biochemical, Immunohistochemical, And Molecular Alterations In The American Oyster, Crassostrea Virginica, Andrew Salinas, Md Saydur Rahman Jun 2025

Exposure To Metoprolol And Propranolol Mixtures On Biochemical, Immunohistochemical, And Molecular Alterations In The American Oyster, Crassostrea Virginica, Andrew Salinas, Md Saydur Rahman

School of Earth, Environmental, & Marine Sciences Faculty Publications

Pharmaceutical drugs, particularly beta-blockers (e.g., metoprolol, propranolol, etc.), are extensively used to treat human cardiovascular conditions, yet pose significant risks to non-target aquatic organisms when introduced into coastal and marine environments via wastewater effluent. This study aimed to investigate the effects of short-term exposure (one week) to environmentally relevant concentrations of metoprolol and propranolol (MP) mixtures (low-dose: 50 ng/L propranolol and 250 ng/L metoprolol, and high-dose: 250 ng/L propranolol and 650 ng/L metoprolol) in the American oyster (Crassostrea virginica, a commercially and ecologically important marine bivalve mollusk) under controlled laboratory conditions. Histopathological assessments revealed structural damage to gills, …

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Investigation Of Retention And Dehydration Of Preformed Particle Gel For Conformance Control In Fractured Carbonates, Abdulaziz A. Almakimi, Abdullah O. Almansour, Junchen Liu, Baojun Bai, Ibnelwaleed A. Hussein Jun 2025

Investigation Of Retention And Dehydration Of Preformed Particle Gel For Conformance Control In Fractured Carbonates, Abdulaziz A. Almakimi, Abdullah O. Almansour, Junchen Liu, Baojun Bai, Ibnelwaleed A. Hussein

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Preformed particle gel (PPG) treatment has proved to be among the most effective methods to reduce excessive water production in fractured reservoirs. The blocking ability of PPGs to fractures or fracture-like features is highly dependent on injected gel properties and volume. Gel dehydration during extrusion through fracture is common and has a considerable effect on gel properties, transport, and plugging efficiency. As the gel particles propagate through the fracture, continuous dehydration is often associated and causes the gel to concentrate and require high-pressure gradients to move. Dehydration might be desirable to a certain limit because it can help to form …

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Advancing Fake News Detection With Graph Neural Network And Deep Learning, Haji Gul, Feras Al-Obeidat, Muhammad Wasim, Adnan Amin, Fernando Moreira Jun 2025

Advancing Fake News Detection With Graph Neural Network And Deep Learning, Haji Gul, Feras Al-Obeidat, Muhammad Wasim, Adnan Amin, Fernando Moreira

All Works

In the modern era of digital technology, the rapid distribution of news via social media platforms substantially contributes to the propagation of false information, presenting challenges in upholding the accuracy and reliability of information. This study presents an updated approach that utilizes graph neural networks (GNNs) alongside with advanced deep learning techniques to improve the identification of false information. In contrast to traditional approaches that primarily rely on analyzing text and assessing the credibility of sources, our methodology utilizes the structural information of news propagation networks. This allows for a detailed comprehension of the interconnections and patterns that are indicative …

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Adapting Teaching And Learning With Existing Generative Ai By Higher Education Students: Comparative Study Of Zayed University And King Abdulaziz University, Dina Tbaishat, Ghada Amoudi, Maha Elfadel Jun 2025

Adapting Teaching And Learning With Existing Generative Ai By Higher Education Students: Comparative Study Of Zayed University And King Abdulaziz University, Dina Tbaishat, Ghada Amoudi, Maha Elfadel

All Works

This study examines the role of higher education students’ perceptions in adapting Generative AI (GenAI) tools for teaching and learning, with a particular focus on the factors that influence student satisfaction and engagement. A comparative approach is adopted, exploring student experiences at Zayed University (ZU) in the UAE and King Abdulaziz University (KAU) in Saudi Arabia. The principal variables of interest, including Expected Benefits (EB), University Support (US), Ethical Awareness (EA), and Technology Self-Efficacy (TSE), are examined, with particular attention to their direct and mediated influences through Behavioral Intention (BI) on student satisfaction (SS). Data were collected through surveys and …

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A Novel Fractional Order Model For Analyzing Counterterrorism Operations And Mitigating Extremism, Mutaz Mohammad, Isa Abdullahi Baba, Evren Hincal, Fathalla A. Rihan Jun 2025

A Novel Fractional Order Model For Analyzing Counterterrorism Operations And Mitigating Extremism, Mutaz Mohammad, Isa Abdullahi Baba, Evren Hincal, Fathalla A. Rihan

All Works

This study examines the profound impact of terrorism on individuals and society by developing a fractional-order mathematical model to analyze and enhance counterterrorism efforts. The model accounts for the persistent and complex nature of extremist behavior, particularly emphasizing the importance of preventing violent extremism before it escalates into terrorism. Real-world data on terrorist activities in Nigeria – specifically from the Boko Haram insurgency – was used to calibrate and validate the model, ensuring its relevance and accuracy. The model reveals that the basic reproduction number (R0) plays a decisive role in determining the long-term success of counterterrorism strategies. Numerical simulations …

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Nsf Eec: Establishing Utrgv’S Center For Broadening Participation In Engineering: Engage, Educate, Enrich, Ala Qubbaj, Laura Benitez, Noe Vargas Hernandez, Constantine Tarawneh, Arturo A. Fuentes, Nazmul Islam, Edna Orozco-Leonhardt, Thuy Vu, Angela M. Chapman Jun 2025

Nsf Eec: Establishing Utrgv’S Center For Broadening Participation In Engineering: Engage, Educate, Enrich, Ala Qubbaj, Laura Benitez, Noe Vargas Hernandez, Constantine Tarawneh, Arturo A. Fuentes, Nazmul Islam, Edna Orozco-Leonhardt, Thuy Vu, Angela M. Chapman

Mechanical Engineering Faculty Publications

Hispanics are one of the fastest growing populations in the US, yet they are underrepresented in engineering. University of Texas Rio Grande Valley (UTRGV), a major Hispanic Serving Institution (HSI) with a student population over 95% Hispanic, is well-positioned to address this disparity. UTRGV established a Center for Broadening Participation in Engineering: Engage, Educate, Enrich (CBPE-E3) to enhance Hispanic participation in engineering from early awareness through professional employment. The CBPE -E3 aims to increase enrollment, retention, and advancement rates of Hispanic students in higher education engineering, especially Latinas facing intersectional barriers of race and gender. The CBPE -E3 envisions becoming …

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Satellite And Eddy Covariance Analysis Reveals Short-Lived Evapotranspiration Changes After Fire In Mediterranean Woodland, Hoang Long Nguyen, Simone Gelsinari, J. Nik Callow, Richard Silberstein, Sally E. Thompson Jun 2025

Satellite And Eddy Covariance Analysis Reveals Short-Lived Evapotranspiration Changes After Fire In Mediterranean Woodland, Hoang Long Nguyen, Simone Gelsinari, J. Nik Callow, Richard Silberstein, Sally E. Thompson

Research outputs 2022 to 2026

Ecosystem evapotranspiration (ET) varies through space and time in response to environmental gradients and disturbances like fire. Field-based techniques (e.g. eddy covariance) can directly measure how ET responds to fire; however, these measurements are localised and only represent small areas. Remotely sensed ET products can potentially evaluate fire impacts on ecosystem ET, but their performance for this task remains largely unassessed. This paper uses three widely available remote sensing products: the CSIRO MODIS ReScaled ET (CMRSET), MODIS ET (MOD16), and Penman–Monteith–Leuning (PML), to assess ET changes caused by a fuel reduction burn in a Mediterranean woodland in comparison to the …

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Proton Exchange Membrane Fuel Cells In Electric Vehicles: Innovations, Challenges, And Pathways To Sustainability, Tarek Abedin, Jagadeesh Pasupuleti, Johnny Koh Siaw Paw, Yaw Chong Tak, Monowar Mahmud, Md Pauzi Abdullah, Mohammad Nur-E-Alam Jun 2025

Proton Exchange Membrane Fuel Cells In Electric Vehicles: Innovations, Challenges, And Pathways To Sustainability, Tarek Abedin, Jagadeesh Pasupuleti, Johnny Koh Siaw Paw, Yaw Chong Tak, Monowar Mahmud, Md Pauzi Abdullah, Mohammad Nur-E-Alam

Research outputs 2022 to 2026

Proton exchange membrane fuel cells are leading the shift to sustainable energy, especially in fuel-cell electric vehicles. In PEMFCs, hydrogen is converted into electricity which contributes to reduced greenhouse gas emissions and decreased dependence on fossil fuels. Many works have been conducted to improve the power density and longevity of the whole system to be adopted in vehicles. The power density was considerably increased by a stack design incorporating lightweight material such as graphene-coated Ni form and weak carbon nanofiber films. Hydrogen refueling failures such as overfilling with hydrogen, hydrogen flow overfill, and hydrogen leakage need mitigation by developing advanced …

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Biological Age Acceleration Associated With The Progression Trajectory Of Cardio-Renal–Metabolic Multimorbidity: A Prospective Cohort Study, Yixing Tian, Jinqi Wang, Tianyu Zhu, Xia Li, Haiping Zhang, Xiaoyu Zhao, Xinghua Yang, Yanxia Luo, Lixin Tao, Zhiyuan Wu, Xiuhua Guo Jun 2025

Biological Age Acceleration Associated With The Progression Trajectory Of Cardio-Renal–Metabolic Multimorbidity: A Prospective Cohort Study, Yixing Tian, Jinqi Wang, Tianyu Zhu, Xia Li, Haiping Zhang, Xiaoyu Zhao, Xinghua Yang, Yanxia Luo, Lixin Tao, Zhiyuan Wu, Xiuhua Guo

Research outputs 2022 to 2026

Objectives: Previous studies have confirmed that biological age (BA) acceleration is associated with single cardio-renal–metabolic diseases (CRMDs), typically including type 2 diabetes mellitus, cardiovascular disease, and chronic kidney disease. However, its association with progression to cardio-renal–metabolic multimorbidity (CRMM, coexistence of ≥2 CRMDs) and subsequent mortality remains unexplored. Methods: Using the multi-state model, we analyzed 278,927 UK Biobank participants free of CRMDs at baseline to investigate the association between BA acceleration—measured by phenotypic age (PhenoAge) and Klemera–Doubal method age (KDMAge)—and CRMM progression trajectory, from health to the first CRMD and then to CRMM and death. BA acceleration was the residual from …

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Multi-Point And Multi-Station Orbit Propagation For Non-Functional Drifting Geo Satellites, Hritik Mitra Jun 2025

Multi-Point And Multi-Station Orbit Propagation For Non-Functional Drifting Geo Satellites, Hritik Mitra

Theses

Currently, there are thousands of man-made space objects that are orbiting the Earth. These satellites serve a host of essential purposes (scientific research, technical applications, services) and they are all required to remain within their mission parameters. Most critical for them is to maintain the orbital parameters that are specified to achieve a particular mission’s objectives. If a satellite deviates beyond a certain limit, there is not only a risk of mission failure but there is a major hazard for possible collisions with other objects such as active satellites, space debris and even natural objects in some cases. There is …

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Measurement And Improvement Of Photon Identification Efficiencies Using Machine Learning Techniques In The Atlas Detector At The Lhc, Abdulla Esam Mahboub Jun 2025

Measurement And Improvement Of Photon Identification Efficiencies Using Machine Learning Techniques In The Atlas Detector At The Lhc, Abdulla Esam Mahboub

Theses

Photons play a crucial role in numerous analyses at the Large Hadron Collider (LHC), particularly in studies like the Higgs boson decay to two photons. Precise photon identification is essential for enhancing the sensitivity and accuracy of such measurements. This thesis focuses on the development of a machine learning (ML)-based photon identification algorithm to improve the photon identification efficiency within the ATLAS detector, using a Deep Neural Network (DNN) approach. The primary goal is to boost photon identification efficiency by using advanced neural network techniques. Traditional photon identification relies on cuts applied to shower shape variables, which can limit the …

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Data-Driven Machine Learning Applications For Predictive Modeling Of Petrochemical And Ecofriendly Systems, Noora Saleh Al Mansoori Jun 2025

Data-Driven Machine Learning Applications For Predictive Modeling Of Petrochemical And Ecofriendly Systems, Noora Saleh Al Mansoori

Theses

Traditional experimental approaches in industrial processes, such as Fourier Transform Infrared Spectroscopy (FTIR) spectroscopy, thermogravimetric analysis (TGA), and well-drilling operations, are often constrained by time, cost, and operational limitations. This research explores the application of data-driven Machine Learning (ML)-based predictive modeling to improve efficiency and reduce dependency on resource-intensive experimentation. The study develops ML models for three distinct processes: FTIR intensity prediction of bitumen thermal cracking products, thermal degradation of Medium-Density Fibreboard (MDF) using TGA data, and Rate of Penetration (ROP) prediction in petrochemical industry. Six algorithms: Linear Regression (LinReg), Partial Least Squares Regression (PLSR), Support Vector Regression (SVR), Gradient …

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Wavelet-Based Multi-Step Methods For Systems Of Differential Equations, Rashad Assad Hijji Jun 2025

Wavelet-Based Multi-Step Methods For Systems Of Differential Equations, Rashad Assad Hijji

Theses

Wavelets have been widely used in many areas of engineering and mathematics, including the development of multistep algorithms to solve initial value problems (IVPs) in the context of the Galerkin method using Daubechies' wavelets. The main scope of our work is to build a comprehensive framework for solving Systems of Differential equations using the compactly supported wavelets proposed by I. Daubechies. Wavelets are mathematical functions that decompose data into distinct frequency components, and each element is analyzed with a resolution that matches its scale. Compact support of Daubechies wavelets is key in allowing them to be computationally efficient for high-dimensional …

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Roadmap For Mainstreaming Integrated Pest Management (Ipm) Into A Climate Smart One-Health (Cs-Oh) Framework, Henri E.Z. Tonnang, Ghislain T. Tepa-Yotto, Bonoukpoè Mawuko Sokame, Jeannette K. Winsou, Manuele Tamò, Rousseau F. Djouaka Jun 2025

Roadmap For Mainstreaming Integrated Pest Management (Ipm) Into A Climate Smart One-Health (Cs-Oh) Framework, Henri E.Z. Tonnang, Ghislain T. Tepa-Yotto, Bonoukpoè Mawuko Sokame, Jeannette K. Winsou, Manuele Tamò, Rousseau F. Djouaka

All Peer-Reviewed Publications

Climate change presents significant challenges to agricultural sustainability, particularly in integrated pest management (IPM). To address these challenges, we propose a holistic and interdisciplinary conceptual framework, climate-smart One-Health (CS-OH), which integrates ecological, environmental, and socio-economic factors, considering human, animal, soil, and water health within the environment. This paper introduces a roadmap for Climate-Smart OH IPM, combining One-Health (OH) principles with climate-smart agriculture to promote sustainable pest management amid climate change. The roadmap utilizes Systems Thinking (ST) & System Dynamics (SD) methodologies to comprehend complex interactions in climate-affected agricultural systems. Additionally, we provide a step-by-step implementation of Digital Twin (DT) IPM, …

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Mitigating Nonlinear Impairments In High-Speed Optical Communication Systems Via Volterra Nonlinear Equalizer, Safa Jabbar Mohammed, Jalil A. Hamadamin Jun 2025

Mitigating Nonlinear Impairments In High-Speed Optical Communication Systems Via Volterra Nonlinear Equalizer, Safa Jabbar Mohammed, Jalil A. Hamadamin

Polytechnic Journal

This paper presents an in-depth investigation into applying a frequency domain Volterra series nonlinear equalizer (FD-VNLE) to mitigate nonlinear impairments in optical communication systems operating at high speeds. The study aims to address the issues presented by nonlinear effects, specifically self-phase modulation (SPM), which significantly degrades system performance at higher power levels. A comprehensive mathematical model of the FD-VNLE was developed to provide theoretical insight, while its implementation was carried out using MATLAB co-simulated with OptiSystem. The performance of the 40 Gbps dual-polarization quadrature phase shift keying (DP-QPSK) system was rigorously evaluated, focusing on critical performance metrics like bit error …

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On-Site Water Management Field Sampling Plan (Fsp), 2025 Update, Mark Thompson, Rampart Solutions Jun 2025

On-Site Water Management Field Sampling Plan (Fsp), 2025 Update, Mark Thompson, Rampart Solutions

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

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An Eco-Epidemiological Model For Malaria With Microsporidia Mb As Bio-Control Agent, Charlène N.T. Mfangnia, Henri E.Z. Tonnang, Berge Tsanou, Jeremy Keith Herren Jun 2025

An Eco-Epidemiological Model For Malaria With Microsporidia Mb As Bio-Control Agent, Charlène N.T. Mfangnia, Henri E.Z. Tonnang, Berge Tsanou, Jeremy Keith Herren

All Peer-Reviewed Publications

Microsporidia MB is an endosymbiont which naturally infects Anopheles mosquitoes. Due to its ability to block Plasmodium transmission, it shows potential as a bio-based agent for the control of malaria. Its self-sustainability is promising, as it can spread through both vertical and horizontal transmissions. However, its low prevalence in mosquito populations remains a challenge. We develop an eco-epidemiological mathematical model describing the co-dynamics of Microsporidia MB (within mosquito population) and malaria (within human population). The model is used to assess the potential of Microsporidia MB-infected mosquitoes on the control of malaria infection. The results on the basic reproduction numbers, the …

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Building Narratives And Probing Concepts: Preparing Materials For Co-Design With Autistic Livestreamers, Terrance Mok, Tyson Hartley, Anthony Tang, Adam Mccrimmon, Lora Oehlberg Jun 2025

Building Narratives And Probing Concepts: Preparing Materials For Co-Design With Autistic Livestreamers, Terrance Mok, Tyson Hartley, Anthony Tang, Adam Mccrimmon, Lora Oehlberg

Research Collection School Of Computing and Information Systems

Based on ten semi-structured interviews with autistic Twitch streamers, we introduce a series of scenario-based design narratives coupled with technology design concepts as a starting point for co-design discussion about autistic streaming. This work builds on prior thematic analysis of the unique intersection between autism and livestreaming. Our user-centered scenarios highlight the needs, goals, and challenges of autistic individuals in livestreaming contexts. By using evocative narratives, the scenarios serve to facilitate empathy and deeper engagement with the needs of autistic users, and help facilitate and support co-creative dialogues and discussions about new technology designs. We contribute this starting point for …

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Meta-Learning Hyperparameters For Foundation Model Adaptation In Remote-Sensing Imagery, Zichen Tian, Yaoyao Liu, Qianru Sun Jun 2025

Meta-Learning Hyperparameters For Foundation Model Adaptation In Remote-Sensing Imagery, Zichen Tian, Yaoyao Liu, Qianru Sun

Research Collection School Of Computing and Information Systems

Training large foundation models of remote-sensing (RS) images is almost impossible due to the limited and long-tailed data problems. Fine-tuning natural image pre-trained models on RS images is a straightforward solution. To reduce computational costs and improve performance on tail classes, existing methods apply parameter-efficient fine-tuning (PEFT) techniques, such as LoRA and AdaptFormer. However, we observe that fixed hyperparameters -- such as intra-layer positions, layer depth, and scaling factors, can considerably hinder PEFT performance, as fine-tuning on RS images proves highly sensitive to these settings. To address this, we propose MetaPEFT, a method incorporating adaptive scalers that dynamically adjust module …

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Chatgpt’S Performance Evaluation In Spreadsheets Modeling To Inform Assessments Redesign, Michelle L. F. Cheong Jun 2025

Chatgpt’S Performance Evaluation In Spreadsheets Modeling To Inform Assessments Redesign, Michelle L. F. Cheong

Research Collection School Of Computing and Information Systems

Background: Increasingly, students are using ChatGPT to assist them in learning and even completing their assessments, raising concerns of academic integrity and loss of critical thinking skills. Many articles suggested educators to redesign assessments which are more “Generative-AI-resistant” and to focus on assessing students on higher order thinking skills. However, there is a lack of articles that attempt to quantify assessments at different cognitive levels to provide empirical study insights on ChatGPT’s performance at different levels, which will affect how educators redesign their assessments.Objectives: Educators need new information on how well ChatGPT performs to redesign future assessments to assess their …

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Linear Systems Over Pura Vida Neutrosophic Algebra, Rayyanu Abdullahi Muhammad, Abdulhadi Aminu Jun 2025

Linear Systems Over Pura Vida Neutrosophic Algebra, Rayyanu Abdullahi Muhammad, Abdulhadi Aminu

Neutrosophic Systems with Applications

Neutrosophic numbers offers a strong foundation for representing uncertainty, indeterminacy, and imprecision within mathematical systems. Pura Vida Neutrosophic Algebra (PVNA) expands upon max-plus algebra (also known as tropical algebra or path algebra) using neutrosophic numbers. In this study, we propose a novel extension of the Pura Vida Neutrosophic Algebra (PVNA) by formulating and analyzing linear systems within this algebraic context–an area that, to the best of our knowledge, has not been previously examined. Specifically, we introduce the concept of Neutrosophic Max-Plus Linear Systems, develop an algebraic methodology for their representation, and establish the necessary and sufficient conditions for the existence …

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Evaluating Disaster Relief In Supply Chains Using A Neutrosophic Mcdm Approach, Nada A. Nabeeh Jun 2025

Evaluating Disaster Relief In Supply Chains Using A Neutrosophic Mcdm Approach, Nada A. Nabeeh

Neutrosophic Systems with Applications

Disaster-prone regions and affected areas encounter persistent challenges in maintaining supply chain continuity due to environmental uncertainties and infrastructure disruptions. Effective supply chain disaster management (SCDM) is essential for relief disaster disruptions, specifically in upstream processes and functions within the humanitarian supply chain. The integration of advanced technologies like the metaverse and Multiple-Criteria Decision-Making (MCDM) methods supports strategic planning and enhances resilience. This study presents a multi-criteria decision-making (MCDM) proposed approach for disaster relief evaluation in supply chain management. The proposed model integrates Interval-Valued Neutrosophic Numbers (IVNNs) to manage uncertainty and ambiguity inherent in disaster various criteria which are often …

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Outperforming The Best With Minimal Effort: Algorithm Selection For Constrained Multi-Objective Optimization, Mustafa Misir, Aldy Gunawan Jun 2025

Outperforming The Best With Minimal Effort: Algorithm Selection For Constrained Multi-Objective Optimization, Mustafa Misir, Aldy Gunawan

Research Collection School Of Computing and Information Systems

The present study performs algorithm selection on a suite of optimization algorithms targeting the constrained multi-objective optimization problems. The idea is to utilize the existing, relevant algorithmic experience in the literature to deliver an improved solver with limited effort. The reason being that algorithm development, in general, is a challenging and time-consuming process, especially with the goal of outperforming the existing methods from varying perspectives such as performance, speed, and robustness. Concerning the multi-objective optimization problems, the required development efforts happen to be even harder than addressing the single-objective ones. Furthermore, referring to the fact that the number of candidate …

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Alayadb: The Data Foundation For Efficient And Effective Long-Context Llm Inference, Yangshen Deng, Zhengxin You, Long Xiang, Qilong Li, Peiqi Yuan, Zhaoyang Hong, Yitao Zheng, Wanting Li, Runzhong Li, Haotian Liu, Kyriakos Mouratidis, Man Lung Yiu, Huan Li, Qiaomu Shen, Rui Mao, Bo Tang Jun 2025

Alayadb: The Data Foundation For Efficient And Effective Long-Context Llm Inference, Yangshen Deng, Zhengxin You, Long Xiang, Qilong Li, Peiqi Yuan, Zhaoyang Hong, Yitao Zheng, Wanting Li, Runzhong Li, Haotian Liu, Kyriakos Mouratidis, Man Lung Yiu, Huan Li, Qiaomu Shen, Rui Mao, Bo Tang

Research Collection School Of Computing and Information Systems

AlayaDB is a cutting-edge vector database system natively architected for efficient and effective long-context inference for Large Language Models (LLMs) at AlayaDB AI. Specifically, it decouples the KV cache and attention computation from the LLM inference systems, and encapsulates them into a novel vector database system. For the Model as a Service providers (MaaS), AlayaDB consumes fewer hardware resources and offers higher generation quality for various workloads with different kinds of Service Level Objectives (SLOs), when compared with the existing alternative solutions (e.g., KV cache disaggregation, retrieval-based sparse attention). The crux of AlayaDB is that it abstracts the attention computation …

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Reaccept: Automated Co-Evolution Of Production And Test Code Based On Dynamic Validation And Large Language Models, Jianlei Chi, Xiaotian Wang, Yuhan Huang, Lechen Yu, Di Cui, Jianguo Sun, Jun Sun Jun 2025

Reaccept: Automated Co-Evolution Of Production And Test Code Based On Dynamic Validation And Large Language Models, Jianlei Chi, Xiaotian Wang, Yuhan Huang, Lechen Yu, Di Cui, Jianguo Sun, Jun Sun

Research Collection School Of Computing and Information Systems

Synchronizing production and test code, known as PT co-evolution, is critical for software quality. Given the significant manual effort involved, researchers have tried automating PT co-evolution using predefined heuristics and machine learning models. However, existing solutions are still incomplete. Most approaches only detect and flag obsolete test cases, leaving developers to manually update them. Meanwhile, existing solutions may suffer from low accuracy, especially when applied to real-world software projects. In this paper, we propose ReAccept, a novel approach leveraging large language models (LLMs), retrievalaugmented generation (RAG), and dynamic validation to fully automate PT co-evolution with high accuracy. ReAccept employs an …

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De-Duplicating Silent Compiler Bugs Via Deep Semantic Representation, Junjie Chen, Xingyu Fan, Chen Yang, Shuang Liu, Jun Sun Jun 2025

De-Duplicating Silent Compiler Bugs Via Deep Semantic Representation, Junjie Chen, Xingyu Fan, Chen Yang, Shuang Liu, Jun Sun

Research Collection School Of Computing and Information Systems

The compiler bug duplication problem (where many test failures are caused by the same compiler bug) can lead to huge waste of time and resource in diagnosing test failures produced by compiler testing. It is particularly challenging with regard to the silent compiler bugs that do not produce any error messages. To address this problem, multiple white-box techniques were proposed, but they are inapplicable in many practical scenarios. Black-box techniques are more practical, but the existing ones are less effective as they often rely on irrelevant syntactic information. To bridge this gap, we propose a novel black-box technique (BLADE), which …

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