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8th International Conference on Advances in Artificial Intelligence, ICAAI 2024

作者： Møller, Cecilie Grace Ang, Ke En de Lourdes Bongiovanni, María Khalid, Md Saifuddin Wu, Jiayan Department of Digitalization Copenhagen Business School Fredriksberg Denmark Department of Applied Mathematics and Computer Science Danmarks Tekniske Universitet Lyngby Denmark

ISBN: (纸本)9798400718014

The rapid advancement of Artificial Intelligence (AI), particularly through Large Language Models (LLMs), has catalysed a technological revolution, leading to the widespread adoption of AI-driven chatbots across industries. OpenAI’s customisable generative pretrained transformer (GPT) offerings have popularised generative AI, enabling organisations of all sizes to implement chatbots for customer support. This development presents an opportunity for businesses to offer 24/7, cost-efficient customer service that can overcome the historical limitations of chatbots that lack a "human element." However, despite the proliferation of AI chatbots, there remains a crucial need to evaluate their effectiveness in meeting user needs and preferences for human-like interaction. Current service quality assessment tools, such as SERVQUAL and E-SERVQUAL, are unable to evaluate AI-specific capabilities like language intelligence and recognition. Existing research also lacks information on factors that affect user satisfaction and the continued use of AI chatbots. Based on a mixed-methods study, this paper proposes a new instrument for measuring user satisfaction with AI chatbots, specifically for customer support roles. Using the Stanford five-step Design Thinking Process, this study devised a customer support AI chatbot evaluation instrument through a literature review, Cheatstorming, and SCAMPER techniques, followed by testing in a Danish company. The research employs Prentice and Nguyen’s three-stage scale development process to ensure content, reliability, and construct validity, addressing gaps in current scholarship and advancing understanding of AI chatbot user satisfaction. © 2024 Copyright held by the owner/author(s).

关键词： Sales

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Taenia solium taeniasis and cysticercosis:extinction or outbreak

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Animal Diseases 2023年第2期3卷 90-103页

作者： Jacob I.Irunde Faraja B.Luhanda Department of Mathematics Physics and InformaticsMkwawa University College of EducationIringaTanzania Department of Applied Mathematics and Computational Sciences The Nelson Mandela African Institution of Science and TechnologyArushaTanzania

Taenia solium taeniasis and cysticercosis are neglected zoonotic diseases that affect human health and economies of developing *** this work,we formulate and analyze deterministic and continuous time Markov chain(CTMC)stochastic models to determine parameters that drive Taenia solium taeniasis and cysticercosis and the likelihood of their *** basic reproduction number R0 is computed by the next generation matrix approach,sensitivity index of each parameter in R0 is derived by the normalized forward sensitivity index and the likelihood of diseases’extinction is computed by the multitype branching *** analysis shows that humans with Taenia solium taeniasis,infectious pork and Taenia solium eggs in the environment play an important role in the transmission of Taenia solium taeniasis and cysticercosis,and the model exhibits forward bifurcation at R0=*** implies that R0<1 is a sufficient condition to eliminate Taenia solium taeniasis and *** CTMC model,analysis shows that the probability of Taenia solium taeniasis and cysticercosis extinction is high if the diseases emerge from humans with Taenia solium cysticercosis and there is an outbreak if the diseases emerge from either humans with Taenia solium taeniasis or infectious pork or Taenia solium eggs in the *** control Taenia solium taeniasis and cysticercosis,the intervention strategies should focus on improving hygiene and sanitation for reducing shedding rate of Taenia solium eggs in the environment,inspection of pork for reducing the rate of acquiring Taenia solium taeniasis and spraying of insecticides for killing Taenia solium eggs in the environment.

关键词： Taeniasis Cysticercosis Basic reproduction number Sensitivity analysis Multitype branching process Stochastic model

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A Novel Multiple Dependent State Sampling Plan Based on Time Truncated Life Tests Using Mean Lifetime

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computers, Materials & Continua 2022年第12期73卷 4611-4626页

作者： Pramote Charongrattanasakul Wimonmas Bamrungsetthapong Poom Kumam Division of Mathematics Department of Mathematics and Computer ScienceFaculty of Science and TechnologyRajamangala University of Technology KrungthepBangkok10120Thailand Division of Applied Statistics Department of Mathematics and Computer ScienceFaculty of Science and TechnologyRajamangala University of Technology ThanyaburiPathum Thani12110Thailand Center of Excellence in Theoretical and Computational Science(TaCS-CoE)&KMUTT Fixed Point Research Laboratory Room SCL 802 Fixed Point LaboratoryScience Laboratory BuildingDepartments of MathematicsFaculty of ScienceKing Mongkut’s University of Technology Thonburi(KMUTT)Bangkok10140Thailand

The design of a new adaptive version of the multiple dependent state(AMDS)sampling plan is presented based on the time truncated life test under the Weibull *** achieved the proposed sampling plan by applying the concept of the double sampling plan and existing multiple dependent state sampling plans.A warning sign for acceptance number was proposed to increase the probability of current lot *** optimal plan parameters were determined simultaneously with nonlinear optimization problems under the producer’s risk and consumer’s risk.A simulation study was presented to support the proposed sampling plan.A comparison between the proposed and existing sampling plans,namely multiple dependent state(MDS)sampling plans and a modified multiple dependent state(MMDS)sampling plan,was considered under the average sampling number and operating characteristic curve *** addition,the use of two real datasets demonstrated the practicality and usefulness of the proposed sampling *** results indicated that the proposed plan is more flexible and efficient in terms of the average sample number compared to the existing MDS and MMDS sampling plans.

关键词： Adaptive version of multiple dependent state sampling plan time truncated life test quality level weibull distribution mean lifetime

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Fully-Scalable MPC Algorithms for Clustering in High Dimension 51

Fully-Scalable MPC Algorithms for Clustering in High Dimensi...

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51st International Colloquium on Automata, Languages, and Programming, ICALP 2024

作者： Czumaj, Artur Gao, Guichen Jiang, Shaofeng H.-C. Krauthgamer, Robert Veselý, Pavel Department of Computer Science University of Warwick Coventry United Kingdom School of Computer Science Peking University Beijing China Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot Israel Computer Science Institute of Charles University Prague Czech Republic

ISBN: (纸本)9783959773225

We design new parallel algorithms for clustering in high-dimensional Euclidean spaces. These algorithms run in the Massively Parallel Computation (MPC) model, and are fully scalable, meaning that the local memory in each machine may be nσ for arbitrarily small fixed σ > 0. Importantly, the local memory may be substantially smaller than the number of clusters k, yet all our algorithms are fast, i.e., run in O(1) rounds. We first devise a fast MPC algorithm for O(1)-approximation of uniform Facility Location. This is the first fully-scalable MPC algorithm that achieves O(1)-approximation for any clustering problem in general geometric setting;previous algorithms only provide poly(log n)-approximation or apply to restricted inputs, like low dimension or small number of clusters k;e.g. [Bhaskara and Wijewardena, ICML’18;Cohen-Addad et al., NeurIPS’21;Cohen-Addad et al., ICML’22]. We then build on this Facility Location result and devise a fast MPC algorithm that achieves O(1)-bicriteria approximation for k-Median and for k-Means, namely, it computes (1 + Ε)k clusters of cost within O(1/Ε2)-factor of the optimum for k clusters. A primary technical tool that we introduce, and may be of independent interest, is a new MPC primitive for geometric aggregation, namely, computing for every data point a statistic of its approximate neighborhood, for statistics like range counting and nearest-neighbor search. Our implementation of this primitive works in high dimension, and is based on consistent hashing (aka sparse partition), a technique that was recently used for streaming algorithms [Czumaj et al., FOCS’22]. © Artur Czumaj, Guichen Gao, Shaofeng H.-C. Jiang, Robert Krauthgamer, and Pavel Veselý.

关键词： Nearest neighbor search

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A Partial RKDG Method for Solving the 2D Ideal MHD Equations Written in Semi-Lagrangian Formulation on Moving Meshes with Exactly Divergence-Free Magnetic Field

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Advances in applied mathematics and Mechanics 2023年第4期15卷 932-963页

作者： Shijun Zou Xijun Yu Zihuan Dai Fang Qing Xiaolong Zhao School of Mathematical Sciences Peking UniversityBeijing 100871China Institute of Applied Physics and Computational Mathematics Beijing 100088China Department of Mathematics Southern University of Science and TechnologyShenzhenGuangdong 518055China School of Mathematics and Statistics Zhengzhou UniversityZhengzhouHenan 450001China

A partial Runge-Kutta Discontinuous Galerkin(RKDG)method which preserves the exactly divergence-free property of the magnetic field is proposed in this paper to solve the two-dimensional ideal compressible magnetohydrodynamics(MHD)equations written in semi-Lagrangian formulation on moving quadrilateral *** this method,the fluid part of the ideal MHD equations along with zcomponent of the magnetic induction equation is discretized by the RKDG method as our previous paper[47].The numerical magnetic field in the remaining two directions(i.e.,x and y)are constructed by using the magnetic flux-freezing principle which is the integral form of the magnetic induction equation of the ideal *** the divergence of the magnetic field in 2D is independent of its z-direction component,an exactly divergence-free numerical magnetic field can be obtained by this *** propose a new nodal solver to improve the calculation accuracy of velocities of the moving meshes.A limiter is presented for the numerical solution of the fluid part of the MHD equations and it can avoid calculating the complex eigen-system of the MHD *** numerical examples are presented to demonstrate the accuracy,non-oscillatory property and preservation of the exactly divergence-free property of our method.

关键词： Ideal compressible MHD equations semi-Lagrangian formulation exactly divergence-free magnetic field Runge-Kutta discontinuous Galerkin method

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Symmetric Matrix Completion with ReLU Sampling 41

Symmetric Matrix Completion with ReLU Sampling

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41st International Conference on Machine Learning, ICML 2024

作者： Liu, Huikang Wang, Peng Huang, Longxiu Qu, Qing Balzano, Laura Antai College of Economics and Management Shanghai Jiao Tong University China Department of Electrical Engineering and Computer Science University of Michigan United States Department of Computational Mathematics Science and Engineering Department of Mathematics Michigan State University United States

We study the problem of symmetric positive semidefinite low-rank matrix completion (MC) with deterministic entry-dependent sampling. In particular, we consider rectified linear unit (ReLU) sampling, where only positive entries are observed, as well as a generalization to threshold-based sampling. We first empirically demonstrate that the landscape of this MC problem is not globally benign: Gradient descent (GD) with random initialization will generally converge to stationary points that are not globally optimal. Nevertheless, we prove that when the matrix factor with a small rank satisfies mild assumptions, the nonconvex objective function is geodesically strongly convex on the quotient manifold in a neighborhood of a planted low-rank matrix. Moreover, we show that our assumptions are satisfied by a matrix factor with i.i.d. Gaussian entries. Finally, we develop a tailor-designed initialization for GD to solve our studied formulation, which empirically always achieves convergence to the global minima. We also conduct extensive experiments and compare MC methods, investigating convergence and completion performance with respect to initialization, noise level, dimension, and rank. © 2024 Proceedings of Machine Learning Research. All rights reserved.

关键词： Matrix factorization

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Unsteady squeezing flow and heat transport of SiO_(2)/kerosene oil nanofluid around radially stretchable parallel rotating disks with upper disk oscillating

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Propulsion and Power Research 2024年第1期13卷 64-79页

作者： Folarin Oluwaseun Sicelo Goqo Hiranmoy Mondal School of Mathematics Statistics and Computer ScienceUniversity of KwaZulu-NatalPrivate Bag X01ScottsvilePietermaritzburg 3209South Africa Department of Applied Mathematics Maulana Abul Kalam Azad University of TechnologyWest BengalKolkata 700064India

In this study,we have analyzedfluid mobility and thermal transport of the SiO_(2)/kerosene nanofluid within two rotating stretchable *** top disk is simulated to be oscil-lating with a periodic velocity and squeezing continuously the nanofluid within a porous me-dium and making thefluid toflow perpendicularly to the situated *** radiation effects are considered in the heat transfer *** non-linear(NL)PDEs that describe the nanofluid mobility structure and thermal transport are transformed into system of NL-ODEs by introducing adequately suitable non-dimensional variables after which the NL-ODEs were numerically solved via spectral quasi-linearization method(SQLM)on over-lapping *** consequences of several pertinent parameters of the model on pressure,tem-perature,velocity,skin drag coefficient and thermal transport rate are examined and elucidated in detail with the aid offigures and *** was found that theflow structure with prescribing conditions develops negative pressure situation which has vast applications in modern day medical engineering,especially in the construction of air pressure stabilizers used in medical isolation and wound therapy physiology.

关键词： Nanofluids Unsteady Squeezing Stretchable Overlapping spectral quasi-linearization SiO_(2) Kerosene Rotating disks

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Parallel Domain Decomposition-Based Solver for the Simulation of Flow over an Ahmed Reference Model

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Advances in applied mathematics and Mechanics 2023年第3期15卷 769-785页

作者： Zhengzheng Yan Rongliang Chen Chao Wang Lei Xu Jingzhi Li Shenzhen Institutes of Advanced Technology Chinese Academy of SciencesShenzhen 518055China Faculty of Computational Mathematics and Cybernetics Shenzhen MSU-BIT UniversityShenzhen 518172China Department of Mathematics&National Center for Applied Mathematics Shenzhen&SUSTech International Center for Mathematics Southern University of Science and TechnologyShenzhen 518055China

The Ahmed model is a standard bluff body used to study the flow behavior around an *** important issue when investigating turbulent flow fields is the large computational load driven by accurate prediction approaches,such as the large eddy simulation *** this paper,we present a powerful domain decomposition method-based parallel solver to efficiently utilize existing supercomputer *** 3D unsteady incompressible Navier–Stokes equations with a subgridscale(SGS)fluid model are discretized on a pure unstructured tetrahedral grid by a stable P_(1-)P_(1-)finite element method in space,while an implicit second-order backward differentiation formula is employed for the time *** then solve the nonlinear algebraic system by means of the Newton–Krylov–Schwarz method by imposing a restricted additive Schwarz(RAS)right preconditioner for the parallel *** validate the proposed method toward the comparison of the flow field,including the velocity profiles and flow structures,with experimental investigations,and we show the parallel efficiency and scalability of the solver with up to 8192 processors.

关键词： Aerodynamics Ahmed model full Navier-Stokes equations Newton-Krylov-Schwarz algorithm parallel computing

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Numerical scheme to solve a class of variable–order Hilfer–Prabhakar fractional differential equations with Jacobi wavelets polynomials

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applied mathematics(A Journal of Chinese Universities) 2022年第1期37卷 35-51页

作者： B.Bagherzadeh Tavasani A.H.Refahi Sheikhani H.Aminikhah Department of Applied Mathematics Faculty of Mathematical SciencesLahijan BranchIslamic Azad UniversityLahijanIran Department of Applied Mathematics and Computer Science Faculty of Mathematical SciencesUniversity of GuilanRashtIran

In this paper,we introduced a numerical approach for solving the fractional differential equations with a type of variable-order Hilfer-Prabhakar derivative of orderμ(t)andν(t).The proposed method is based on the Jacobi wavelet collocation *** to this method,an operational matrix is *** use this operational matrix of the fractional derivative of variable-order to reduce the solution of the linear fractional equations to the system of algebraic *** considerations are ***,some numerical examples are presented to demonstrate the accuracy of the proposed method.

关键词： Hilfer-Prabhakar derivative Jacobi wavelets operational matrices variable order

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Optimizing solar radiation prediction: a novel SVM approach for renewable energy systems

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International Journal of Information Technology (Singapore) 2025年 1-13页

作者： Basha, S. Sharief Rao, A. Nagaraja Department of Mathematics School of Advanced Science Vellore Institute of Technology Tamil Nadu Vellore 632014 India Department of Computational Intelligence School of Computer Science & Engineering Vellore Institute of Technology Tamil Nadu Vellore 632014 India

The global transition toward renewable energy sources, driven by fossil fuel depletion and environmental imperatives, has positioned solar power as a crucial sustainable alternative. This study presents an advanced methodological framework for solar radiation (SR) prediction utilizing Support Vector Machine (SVM) techniques. The research analyzes comprehensive solar radiation data collected from India’s Vellore district throughout 2023, implementing a novel Support Vector Regression (SVR) approach with both polynomial and radial basis function (RBF) kernels. While conventional methodologies predominantly focus on minimizing training errors, our approach emphasizes reducing the generalization error bound to enhance predictive performance. The proposed model incorporates diverse meteorological parameters for SR prediction, demonstrating superior generalization capabilities compared to traditional approaches. Empirical results indicate that the SVR_rbf model significantly outperformed both SVR_poly and artificial neural network (ANN) models in SR prediction accuracy. The model's efficacy is validated through rigorous performance metrics: RMSE (10.3032), MAE (4.2728), MAPE (0.0152), and R² (0.9795). This research advances the understanding of machine learning applications in renewable energy forecasting, particularly for regions with limited meteorological data availability. Research findings enhance solar energy utilization and contribute to the transition towards sustainable energy. Future research directions may explore the integration of additional environmental parameters and the model’s adaptability across diverse geographical contexts. © Bharati Vidyapeeth's Institute of computer Applications and Management 2025.

关键词： Artificial neural network Predictive models Solar radiation Support vector regression

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