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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Vijay Karnatak Neha Tripathi Amit Kumar Mishra Mohammad Wazid Ashok Kumar Das Mohsen Guizani Sachin Shetty Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India Department of Computer Science and Engineering Graphic Era Hill University Dehradun India Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad India Machine Learning Department Mohamed bin Zayed University of Artificial Intelligence (MBZUAI) Abu Dhabi UAE Department of Computational Modeling and Simulation Engineering Virginia Modeling Analysis and Simulation Center Old Dominion University Suffolk VA USA

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

Critical infrastructure refers to the key systems, assets, and facilities, whether they are physical or virtual, that are necessary for the overall functioning of a country. As our reliance on technology and networked systems continues to expand, so does the significance of taking precautions to protect critical infrastructure from being compromised by cyberattacks. We need some security schemes to secure the communication happening in the critical infrastructure devices. Therefore, in this paper, we focus on the design of an authentication and key establishment scheme, which is used in the critical infrastructure to secure its data transmissions. A secure authentication and key management mechanism for fog computing-based IoT-driven critical infrastructures (in short, AKM-FCCI) is proposed in the paper. We then provide the network model and threat model of the proposed AKM-FCCI to explain its deployment and organization of devices and servers. The threat model further explains the various threats of this communication environment. In addition, the security analysis of AKM-FCCI is presented to demonstrate that it is secure against the many different kinds of attacks that could be launched against it. The comparisons demonstrate that the performance of AKM-FCCI is superior to that of the other currently used schemes. In addition to that, it offers a high level of security and utility. Therefore, the proposed AKM-FCCI is appropriate for use in protecting critical infrastructure equipment against a wide variety of threats.

关键词： Threat modeling Wireless communication Performance evaluation Authentication Organizations Critical infrastructure Safety

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Knee Detection in Bayesian Multi-Objective Optimization Using Thompson Sampling

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IEEE Transactions on Evolutionary Computation 2024年

作者： Heidari, Arash Qing, Jixiang Gonzalez, Sebastian Rojas Branke, Juergen Dhaene, Tom Couckuyt, Ivo Computer Science at IDLab Ghent University Ghent Belgium Imperial College London United Kingdom Department of Computational Mathematics Data Science Institute Belgium Warwick Business School University of Warwick Coventry United Kingdom Computer Modeling and Simulation Research Group University of Antwerp Antwerp Belgium Cluster in IDLab Ghent University Belgium

Real-world problems often consist of multiple conflicting objectives to be optimized simultaneously, featuring a set of Pareto-optimal solutions. Estimating the entire Pareto front can be computationally expensive, and is not always necessary, as decision makers will likely be interested only in specific regions of the Pareto front. In the absence of knowledge about the decision maker preferences, the so-called knees in the Pareto front are considered to be particularly attractive. In this paper, we propose using Thompson Sampling in the Bayesian optimization framework to estimate the location of the knee regions in a data-efficient manner. Our experimental results show that the proposed methods accurately locate the knee regions after a very small number of evaluations, providing a computationally efficient approach to single-and multi-knee detection in multi-objective optimization. © 1997-2012 IEEE.

关键词： Multiobjective optimization

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Assessing Media’s Representation of Frustration Towards Venezuelan Migrants in Colombia 16th

Assessing Media’s Representation of Frustration Towards Ven...

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16th International Conference on Social Computing, Behavioral-Cultural modeling and Prediction and Behavior Representation in modeling and simulation, SBP-BRiMS 2023

作者： Llinas, Brian Huseynli, Guljannat Frydenlund, Erika Palacio, Katherine Llinas, Humberto Padilla, Jose J. Computer Science Department Old Dominion University NorfolkVA United States Graduate Program of International Studies Old Dominion University NorfolkVA United States Virginia Modeling Analysis and Simulation Center Old Dominion University SuffolkVA United States Universidad del Norte Kilómetro 5 Vía Atlántico Puerto Colombia Colombia

ISBN: (纸本)9783031431289

This research utilizes statistical path modeling to examine the relationship between the number of Venezuelans migrating to Colombia due to economic collapse and the media's coverage of specific topics. We focus on media coverage expressing frustration regarding migration, infrastructure, government, and geopolitics. Our approach combines quantitative analysis of code frequencies from qualitative content analysis of 1,360 regional newspaper articles on migration-related issues. Our findings indicate that an increase in the Venezuelan population in Colombia leads to more negative media coverage of infrastructure impacts, such as hospitals and schools. This negative coverage, referred to as "frustration," indirectly contributes to increased coverage of infrastructure frustration. This suggests an opportunity for intervention by balancing media coverage to reduce the excessive use of negative language and stereotypes, potentially mitigating anti-migrant sentiment fueled by frustration towards infrastructure. Furthermore, we observe that as migration increases, coverage of frustration towards geopolitics decreases, while frustration towards the Colombian government rises. This shift may reflect a transition from contemplating the causes of migration to focusing on the humanitarian response (or lack thereof) by the host government in accommodating the new arrivals. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Artificial intelligence

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Evolutionary Interest Representation Network for Click-Through Rate Prediction

Evolutionary Interest Representation Network for Click-Throu...

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IEEE International Conference on Web Services (ICWS)

作者： Renjie Zhou Zhenming Jin Jian Wan Jilin Zhang Xingyu Guo Qiang Liu Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China Key Laboratory of Complex Systems Modeling and Simulation of the Ministry of Education ITMO Joint Institute Hangzhou Dianzi University Hangzhou China School of Information and Electronic Engineering Zhejiang University of Science and Technology Hangzhou China Dept. of Computer and Information Technology Zhejiang Police College Hangzhou China

The rapid development of the Internet has revo-lutionized our lives, providing us with an array of convenient services. However, this revolution has also led to the problem of data overload. Personalized recommendation services have been widely recognized as an effective solution to this problem by both the industrial and academic communities. Accurate prediction of click-through rate (CTR) is a critical task in personalized recommendation systems since it can improve the user’s shopping experience, ultimately increasing revenue for the platform. To achieve accurate CTR prediction, it is crucial to capture user interests. While several methods for interest modeling exist, challenges related to user interest evolution and user behavior noise need further attention. This paper proposes a novel CTR prediction model named the Evolutionary Interest Representation Network (EIRN), which learns the evolving interest representation of users from their behaviors, profiles, and environmental attributes. In the model, we introduce an advertisement correlation graph decomposition layer and a noise filter layer to enhance and purify the user behavior representation. An interest extraction layer is designed to capture sequential correlations and common characteristics between user behaviors, representing their interests. Additionally, as user interests evolve over time and their importance changes, an attention-based interest evolution layer is designed to track the evolution of user interests. Our proposed method is validated using four public datasets and an industrial dataset, showing its superiority over existing CTR prediction methods.

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Numerical investigation of magnetized nanofluid flow in a non-Darcian medium with convective heating conditions across a rotating disk

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International Journal of Numerical Methods for Heat and Fluid Flow 2025年第5期35卷 1736-1763页

作者： Bhatti, Muhammad Mubashir Ellahi, R. Sait, Sadiq M. Department of Material Science Innovation and Modelling North-West University Mmabatho South Africa Department of Mathematics and Statistics International Islamic University Islamabad Pakistan Department of Computer Engineering King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Department of Physics College of Science Korea University Seongbuk-gu South Korea Center for Modeling and Computer Simulation Research Institute King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Department of Mechanical Engineering University of California Riverside CA United States Interdisciplinary Research Center for Smart Mobility and Logistics King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia

Purpose: A novel approach of Buongiorno and Arrhenius energy models is proposed to examine magnetized nanofluid flow saturated in a non-Darcian medium with convective boundary conditions over a rotating disk. The proposed work has substantial applications in the domain of Heat Transfer within industrial operations, including power plants, electronic devices and nuclear reactors. It also pertains to the design of energy-efficient systems, rotating machinery and equipment such as centrifugal pumps, turbines and rotating heat exchangers. It is also pertinent to environmental engineering, which deals with fluid filtration and thermal management, and biomedical engineering, which includes drug delivery systems and the treatment of hyperthermia. It also discusses applications of magnetic fields, such as magnetorheological fluids, magnetic refrigeration and magnetic cooling systems. Design/methodology/approach: The Von Karman’s methodology is used to develop a mathematical formulation. The resulting series of nonlinear differential equations are solved by generalized differential quadrature (GDQ) technique. The Newton–Raphson iterative method is used to get numerical solutions. Findings: Effects of evolving parameters such as radial velocity, azimuthal velocity, transverse velocity, thermal and concentration patterns are examined through graphs and tables. The outcomes of skin friction coefficient, Nusselt number, Sherwood number and residual error are also presented. A comparison with the existing literature has been made as a special case for the validation of results. Originality/value: A blend framework of Buongiorno and Arrhenius energy models for magnetized nanofluid flow across a uniformly rotating disk inside a non-Darcian structure with convective boundary conditions is presented. © 2025, Emerald Publishing Limited.

关键词： Arrhenius energy Buongiorno model Convective boundary conditions Generalized differential quadrature approach Magnetized nanofluid flow Non-Darcy medium

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Visual Episodic Memory-based Exploration

arXiv

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arXiv 2024年

作者： Vice, Jack Ruiz-Sanchez, Natalie Douglas, Pamela K. Sukthankar, Gita Dept. of Computer Science University of Central Florida Orlando United States Dept. of ECE University of Central Florida Orlando United States Dept. of Modeling and Simulation University of Central Florida Orlando United States

In humans, intrinsic motivation is an important mechanism for open-ended cognitive development;in robots, it has been shown to be valuable for exploration. An important aspect of human cognitive development is episodic memory which enables both the recollection of events from the past and the projection of subjective future. This paper explores the use of visual episodic memory as a source of intrinsic motivation for robotic exploration problems. Using a convolutional recurrent neural network autoencoder, the agent learns an efficient representation for spatiotemporal features such that accurate sequence prediction can only happen once spatiotemporal features have been learned. Structural similarity between ground truth and autoencoder generated images is used as an intrinsic motivation signal to guide exploration. Our proposed episodic memory model also implicitly accounts for the agent's actions, motivating the robot to seek new interactive experiences rather than just areas that are visually dissimilar. When guiding robotic exploration, our proposed method outperforms the Curiosity-driven Variational Autoencoder (CVAE) at finding dynamic *** Codes I.2.9 © 2024, CC BY-NC-SA.

关键词： Recurrent neural networks

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Prophet: Prompting Large Language Models with Complementary Answer Heuristics for Knowledge-based Visual Question Answering

arXiv

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arXiv 2023年

作者： Yu, Zhou Ouyang, Xuecheng Shao, Zhenwei Wang, Meng Yu, Jun The Key Laboratory of Complex Systems Modeling and Simulation the School of Computer Science Hangzhou Dianzi University China The HDU-ITMO Joint Institute Hangzhou Dianzi University China The School of Computer Science and Information Engineering Hefei University of Technology China

Knowledge-based visual question answering (VQA) requires external knowledge beyond the image to answer the question. Early studies retrieve required knowledge from explicit knowledge bases (KBs), which often introduces irrelevant information to the question, hence restricting the performance of their models. Recent works have resorted to using a powerful large language model (LLM) as an implicit knowledge engine to acquire the necessary knowledge for answering. Despite the encouraging results achieved by these methods, we argue that they have not fully activated the capacity of the blind LLM as the provided textual input is insufficient to depict the required visual information to answer the question. In this paper, we present Prophet—a conceptually simple, flexible, and general framework designed to prompt LLM with answer heuristics for knowledge-based VQA. Specifically, we first train a vanilla VQA model on a specific knowledge-based VQA dataset without external knowledge. After that, we extract two types of complementary answer heuristics from the VQA model: answer candidates and answer-aware examples. Finally, the two types of answer heuristics are jointly encoded into a formatted prompt to facilitate the LLM’s understanding of both the image and question, thus generating a more accurate answer. By incorporating the state-of-the-art LLM GPT-3 [1], Prophet significantly outperforms existing state-of-the-art methods on four challenging knowledge-based VQA datasets. To demonstrate the generality of our approach, we instantiate Prophet with the combinations of different VQA models (i.e., both discriminative and generative ones) and different LLMs (i.e., both commercial and open-source ones). © 2023, CC BY.

关键词： Knowledge based systems

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Electro-magneto-hydrodynamic Eyring-Powell fluid flow through micro-parallel plates with heat transfer and non-Darcian effects

Electro-magneto-hydrodynamic Eyring-Powell fluid flow throug...

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作者： Bhatti, Muhammad Mubashir Doranehgard, Mohammad Hossein Ellahi, Rahmat College of Mathematics and Systems Science Shandong University of Science and Technology Qingdao China Department of Mechanical and Aerospace Engineering Hong Kong University of Science and Technology Clear Water Bay Hong Kong Center for Modeling & Computer Simulation Research Institute King Fahd University of Petroleum and Minerals Dhahran Saudi Arabia Department of Mathematics and Statistics International Islamic University Islamabad Pakistan

The Eyring-Powell fluid flow between two micro-parallel plates in the context of electro-magneto-hydrodynamic is the focus of the article. The Lorentz force, which is generated by the interactions of a vertical magnetic field and an externally imposed horizontal electrical field, is presumed to be unilateral and one-dimensional. Using the Darcy-Brinkman-Forchheimer model, the medium of the micro-parallel plates is assumed to be porous. The energy equation evaluates the effect of viscous dissipation and joule heating as well. To solve the nonlinear coupled differential equations, analytical solutions are derived using the multi-step differential transform method. For the velocity and temperature profiles, the impact of all evolving variables is explored and illustrated in graphs and tables. It can be seen from the graphical results that the Darcy parameter, and also the magnetic field, are oppositional to both fluid motion and temperature profile. Additionally, the thermal Grashof number improves the velocity and temperature profiles of the system. On the velocity and temperature profiles, the outcomes for both fluid parameters are nearly identical. © 2022 John Wiley & Sons Ltd.

关键词： Temperature control

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Multimodal Fluorescence Lifetime Imaging and Optical Coherence Elastography for Mesoscopic Structural, Biomechanical, and Molecular Imaging

Multimodal Fluorescence Lifetime Imaging and Optical Coheren...

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2024 Clinical and Translational Biophotonics, Translational 2024 - Part of Optica Biophotonics Congress: Biomedical Optic

作者： Chavez, Luis Gao, Shan Pandey, Vikas Yuan, Nanxue Li, Jiayue Hepburn, Matt S. Smith, Percy Edelheit, Caroline Corr, David T. Kennedy, Brendan F. Intes, Xavier Center for Modeling Simulation and Imaging for Medicine Rensselaer Polytechnic Institute TroyNY12180 United States BRITElab Harry Perkins Institute of Medical Research QEII Medical Centre Nedlands and Centre for Medical Research The University of Western Australia PerthWA6009 Australia Department of Electrical Electronic & Computer Engineering School of Engineering The University of Western Australia PerthWA6009 Australia Institute of Physics Nicolaus Copernicus University Torun Poland

We report on a methodology to manufacture multimodal phantoms with fluorescence lifetime imaging and optical coherence elastography contrasts. Phantom validation demonstrates the ability to tune fluorescence and strai... 详细信息

关键词： Phantoms

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MemoryScan Environments: Creating Large-Scale Memory-Evocative Digital Twins

MemoryScan Environments: Creating Large-Scale Memory-Evocati...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Lori C. Walters Robert A. Michlowitz Esteban Segarra Martinez Ryan P. McMahan Joseph T. Kider IST School of Modeling Simulation and Training University of Central Florida Orlando Florida Department of History University of Central Florida Orlando Florida Department of Computer Science University of Central Florida Orlando Florida

The MemoryScan project seeks to create large-scale memory-evocative digital virtual environments designed to enhance and amplify the detail and granularity of captured memories and historical recollections. This project integrates diverse data sources such as large-scale point clouds, 3D models, virtual reality interfaces, and satellite imagery to build an interactive virtual environment accessible through head-mounted displays (HMDs) or web browsers. This approach transcends traditional collection methods facilitating an enriched and multisensory engagement with the past through these human-centric Digital Twins, fostering a deeper connection with the historical narratives and collective memories encapsulated within this interactive digital world.

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