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Business Analytics for Technology and Security (ICBATS), International Conference on

作者： Muhammad Bashir Sidra Tahir Maram Fahaad Almufareh Bushra Hamid Farkhanda Qamar Pmas Arid Agriculture University Rawalpindi Punjab Pakistan Department of Information Systems College of Computer and Information Sciences Jouf University Sakakah AL-Jouf Applied Science Research Center Applied Science Private University Amman Jordan

MANET is a wireless medium, with no infrastructure, for nodes to communicate within a network. Movement of nodes is a lot more in this network than other networks due to lack of infrastructure (Wireless nature). In a mobile ad hoc network, each node functions as a router and finds the best path forwarding a packet via origin to destination. This network is important in places where building a framework is impossible, like in a military setting. A mobile ad-hoc network (MANET) is a temporary network created by unrestricted nodes that can move around and communicate without a centralized network. In a black hole attack, several or even more attacker node use a tunnel-like private channel to find a wormhole attack. Wormhole tunnel will then start collecting the data packets and transferring them to another location. The proposed work encouraged secure and effective routing in MANET. At that point, we selected 20 important attributes to create a dataset that was labelled with the aid of a unique node address. Apply two well-known machine learning classifiers that categorise data into two groups, specifically normal and malicious, to test sample data in this manner. For feature selection and SVM (Support Vector Machine) classification, respectively, we employ genetic algorithms. The demonstration of the technology was assessed on many quantifiable characteristics and compared to contemporary techniques.

关键词： Wireless communication Support vector machine classification Machine learning Predictive models Routing Communication system security Security

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SAPIENT: Mastering Multi-turn Conversational Recommendation with Strategic Planning and Monte Carlo Tree Search

arXiv

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arXiv 2024年

作者： Du, Hanwen Peng, Bo Ning, Xia Department of Computer Science and Engineering The Ohio State University United States Division of Medicinal Chemistry and Pharmacognosy College of Pharmacy The Ohio State University United States Department of Biomedical Informatics The Ohio State University United States Translational Data Analytics Institute The Ohio State University United States

Conversational Recommender systems (CRS) proactively engage users in interactive dialogues to elicit user preferences and provide personalized recommendations. Existing methods train Reinforcement Learning (RL)-based agent with greedy action selection or sampling strategy, and may suffer from suboptimal conversational planning. To address this, we present a novel Monte Carlo Tree Search (MCTS)-based CRS framework SAPIENT. SAPIENT consists of a conversational agent (S-agent) and a conversational planner (S-planner). S-planner builds a conversational search tree with MCTS based on the initial actions proposed by S-agent to find conversation plans. The best conversation plans from S-planner are used to guide the training of S-agent, creating a self-training loop where S-agent can iteratively improve its capability for conversational planning. Furthermore, we propose an efficient variant SAPIENT-e for trade-off between training efficiency and performance. Extensive experiments on four benchmark datasets validate the effectiveness of our approach, showing that SAPIENT outperforms the state-of-the-art baselines. © 2024, CC BY.

关键词： Chatbots

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Modeling social resilience: Questions, answers, open problems

arXiv

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arXiv 2022年

作者： Schweitzer, Frank Andres, Georges Casiraghi, Giona Gote, Christoph Roller, Ramona Scholtes, Ingo Vaccario, Giacomo Zingg, Christian Systems Design ETH Zurich Switzerland Complexity Science Hub Vienna Austria Department of Informatics University of Zurich Switzerland Computer Science XV Julius-Maximilians-Universität Würzburg Germany

Resilience denotes the capacity of a system to withstand shocks and its ability to recover from them. We develop a framework to quantify the resilience of highly volatile, non-equilibrium social organizations, such as collectives or collaborating teams. It consists of four steps: (i) delimitation, i.e., narrowing down the target systems, (ii) conceptualization, i.e., identifying how to approach social organizations, (iii) formal representation using a combination of agent-based and network models, (iv) operationalization, i.e. specifying measures and demonstrating how they enter the calculation of resilience. Our framework quantifies two dimensions of resilience, the robustness of social organizations and their adaptivity, and combines them in a novel resilience measure. It allows monitoring resilience instantaneously using longitudinal data instead of an ex-post evaluation. Copyright © 2022, The Authors. All rights reserved.

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Sentiment Analysis-Based Product Review System for Enhanced Recommendations

Sentiment Analysis-Based Product Review System for Enhanced ...

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Artificial Intelligence and Data Engineering (AIDE), International Conference on

作者： Ashok Hake Jambukeshwar Pujari Lingaraju S V Naveen Kumar H S Department of Computer Science and Business Systems KIT’s College of Engineering(Autonomous) Kolhapur Maharashtra India Department of Mechanical Engineering T. K. I. E. T Warana University Warananagar Maharashtra India Department of Mechanical Engineering Government Polytechnic Holenarasipur Karnataka India

ISBN: (数字)9798331527518

ISBN: (纸本)9798331527525

The rapid growth of e-commerce has resulted in an overwhelming amount of user-generated content in the form of product reviews. Harnessing these reviews effectively is critical for enhancing recommendation systems. This paper presents a sentiment analysis-based approach that delves into specific product attributes, such as quality, design, price, durability, usability, comfort, value for money, and customer service, to extract actionable insights. By employing natural language processing (NLP) techniques, our system calculates both overall and attribute-specific sentiment scores, which are aggregated into a comprehensive recommendation score. The proposed methodology bridges the gap between unstructured text reviews and structured product recommendations, offering a detailed, attribute-focused perspective to improve user decision-making.

关键词： Sentiment analysis Reviews Statistical analysis Customer services Customer satisfaction User-generated content Tag clouds Electronic commerce Usability Recommender systems

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Role of ephaptic coupling in discordant alternans domain sizes and action potential propagation in the heart

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Physical Review E 2023年第5期107卷 054407-054407页

作者： Niels F. Otani Eileen Figueroa James Garrison Michelle Hewson Laura Muñoz Flavio H. Fenton Alain Karma Seth H. Weinberg School of Mathematical Sciences Rochester Institute of Technology Rochester New York 14623 USA Department of Electrical Computer and Telecommunications Engineering Technology Rochester Institute of Technology Rochester New York 14623 USA Department of Mathematics and Computer Science Hampden-Sydney College Hampden-Sydney Virginia 23943 USA Department of Mathematics and Computer Science Western Carolina University Cullowhee North Carolina 28723 USA School of Physics Georgia Institute of Technology Atlanta Georgia 30332 USA Physics Department and Center for Interdisciplinary Research on Complex Systems Northeastern University Boston Massachusetts 02115 USA Department of Biomedical Engineering The Ohio State University Columbus Ohio 43210 USA

Discordant alternans, the spatially out-of-phase alternation of the durations of propagating action potentials in the heart, has been linked to the onset of fibrillation, a major cardiac rhythm disorder. The sizes of the regions, or domains, within which these alternations are synchronized are critical in this link. However, computer models employing standard gap junction-based coupling between cells have been unable to reproduce simultaneously the small domain sizes and rapid action potential propagation speeds seen in experiments. Here we use computational methods to show that rapid wave speeds and small domain sizes are possible when a more detailed model of intercellular coupling that accounts for so-called ephaptic effects is used. We provide evidence that the smaller domain sizes are possible, because different coupling strengths can exist on the wavefronts, for which both ephaptic and gap-junction coupling are involved, in contrast to the wavebacks, where only gap-junction coupling plays an active role. The differences in coupling strength are due to the high density of fast-inward (sodium) channels known to localize on the ends of cardiac cells, which are only active (and thus engage ephaptic coupling) during wavefront propagation. Thus, our results suggest that this distribution of fast-inward channels, as well as other factors responsible for the critical involvement of ephaptic coupling in wave propagation, including intercellular cleft spacing, play important roles in increasing the vulnerability of the heart to life-threatening tachyarrhythmias. Our results, combined with the absence of short-wavelength discordant alternans domains in standard gap-junction-dominated coupling models, also provide evidence that both gap-junction and ephaptic coupling are critical in wavefront propagation and waveback dynamics.

关键词： Action potential propagation Cardiac dynamics Heart diseases Spiral & scroll waves Coherent structures Heart Traveling waves

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SKOLEM MEETS BATEMAN-HORN

arXiv

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arXiv 2023年

作者： Luca, Florian Maynard, James Noubissie, Armand Ouaknine, Joël Worrell, James School of Mathematics University of Witwatersrand Johannesburg South Africa Department of Mathematics University of Oxford Oxford United Kingdom Max Planck Institute for Software Systems Saarland Informatics Campus Saarbrücken Germany Department of Computer Science University of Oxford Oxford United Kingdom

The Skolem Problem asks to determine whether a given integer linear recurrence sequence has a zero term. This problem arises across a wide range of topics in computer science, including loop termination, formal languages, automata theory, and control theory, amongst many others. Decidability of the Skolem Problem is notoriously open. The state of the art is a decision procedure for recurrences of order at most 4: an advance achieved some 40 years ago, based on Baker’s theorem on linear forms in logarithms of algebraic numbers. A new approach to the Skolem Problem was recently initiated in [LOW21, LOW22] via the notion of a Universal Skolem Set—a set S of positive integers such that it is decidable whether a given non-degenerate linear recurrence sequence has a zero in S. Clearly, proving decidability of the Skolem Problem is equivalent to showing that N itself is a Universal Skolem Set. The main contribution of the present paper is to construct a Universal Skolem Set that has lower density at least 0.29. We show moreover that this set has density one subject to the Bateman-Horn conjecture. The latter is a central unifying hypothesis concerning the frequency of prime numbers among the values of systems of polynomials. © 2023, CC BY.

关键词： Computability and decidability

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Data-driven Optimal Cooperative Output Regulation of Unknown Linear Discrete-time Multi-agent systems

Data-driven Optimal Cooperative Output Regulation of Unknown...

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Chinese Control and Decision Conference, CCDC

作者： Dong Liang Yi Dong Chaoli Wang Engang Tian Department of Control Science and Engineering School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai China College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China

The cooperative output regulation problem has been extensively studied on the basis of the distributed observer approach. However, the majority of the existing research assumes that the dynamics is known previously. To remove this condition, the cooperative output regulation problem is further solved via the data-driven framework where the dynamics of the plant is unknown. First, a data-driven distributed observer is established to estimate the state of the leader with unknown dynamics subject to external inputs. Second, the unknown regulator equations are solved using the iterative recurrent neural network approach. Third, the state-based data-driven distributed control law is synthesized to solve the problem. The optimal gains are derived by solving convex optimization problems using input and state data. Finally, a numerical example is presented to verify the feasibility of the proposed framework.

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Pedometers for Smartphones: Analysis and Comparison of Real-Time Algorithms

Pedometers for Smartphones: Analysis and Comparison of Real-...

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IEEE World Forum on Internet of Things (WF-IoT)

作者： Giacomo Neri Federico Montori Lorenzo Gigli Luca Bedogni Marco Di Felice Luciano Bononi Department of Computer Science and Engineering University of Bologna Italy Advanced Research Center in Electronic Systems University of Bologna Italy Department of Physics Informatics and Mathematics University of Modena and Reggio Emilia Italy

The recent years have witnessed the rise of an enormous number of software algorithms that implement pe-dometers (or step counters), which led to the development of several context-aware IoT-based smartphone apps for sports and healthcare, among others. While the number of scientific works in this context is high, there is no comparison study that analyzes the different proposal at implementation level. In this paper we first perform a literature review of software implementations of pedometers for smartphones and then classify them into a taxonomy. With this, we highlight the similarities of their scheme, which is based on a number of defined steps to be applied in a pipeline. We then develop a smartphone application that implements all the configurations of these steps found in literature and evaluates them in various scenarios. Finally, we present comparative results obtained by running extensive and real tests that show the importance of a carefully designed filtering step.

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An Atom Quest Optimizer for CNN to Distinguish IDs in SDN and IoT Eco System

An Atom Quest Optimizer for CNN to Distinguish IDs in SDN an...

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Computing, Power and Communication Technologies (IC2PCT), IEEE International Conference on

作者： V.S Anusuya Devi Vijilius Helena Raj Balasubramanian Prabhu Kavin E. Gangadevi Balamurugan Balusamy Shilpa Gite New Horizon College of Engineering Ring Road Bellandur Post Bengaluru India Department of Data Science and Business Systems SRM Institute of Science and Technology Kattankulathur Chengalpattu India Department of Computer Science Loyola College Chennai India Shiv Nadar University Delhi-National Capital Region (NCR) India AIML Department Symbiosis Institute of Technology Pune Symbiosis International (Deemed University) Pune India

Security has become crucial as Internet of Things (IoT) applications have grown in popularity. The prevalence of IoT vulnerabilities was recently exposed by a distributed denial-of-service (DDoS) assault, and many IoT strategies unintentionally assisted in the DDoS attack. The new software-defined anything (SDx) paradigm offers a method for managing IoT devices in a secure manner. We initially provide a broad agenda for the software-defined Internet of Things (SD-IoT) in this paper, which is based on the SDx paradigm. The implementation of an IDS based on Deep Learning (DL) procedures into an SDN construction is the focus of this paper, which also suggests a very real-world method to shorten the delay by using the consecutive implementation of prototypes with cumulative hardware difficulty. This method enables quick tests to identify the key issues, address them, and then implement the solution.

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HOIAnimator: Generating Text-Prompt Human-Object Animations Using Novel Perceptive Diffusion Models

HOIAnimator: Generating Text-Prompt Human-Object Animations ...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Wenfeng Song Xinyu Zhang Shuai Li Yang Gao Aimin Hao Xia Hau Chenglizhao Chen Ning Li Hong Qin Beijing Information Science and Technology University Zhongguancun Laboratory China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Research Unit of Virtual Human and Virtual Surgery (2019RU004) Chinese Academy of Medical Sciences College of Computer Science and Technology China University of Petroleum (East China) Department of Computer Science Stony Brook University (SUNY at Stony Brook) New York USA

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

To date, the quest to rapidly and effectively produce human-object interaction (HOI) animations directly from textual descriptions stands at the forefront of computer vision research. The underlying challenge demands both a discriminating interpretation of language and a comprehen-sive physics-centric model supporting real-world dynamics. To ameliorate, this paper advocates HOIAnimator, a novel and interactive diffusion model with perception ability and also ingeniously crafted to revolutionize the animation of complex interactions from linguistic narratives. The effectiveness of our model is anchored in two ground-breaking innovations: (1) Our Perceptive Diffusion Models (PDM) brings together two types of models: one focused on hu-man movements and the other on objects. This combination allows for animations where humans and objects move in concert with each other, making the overall motion more realistic. Additionally, we propose a Perceptive Message Passing (PMP) mechanism to enhance the communication bridging the two models, ensuring that the animations are smooth and unified; (2) We devise an Interaction Contact Field (ICF), a sophisticated model that implicitly captures the essence of HOls. Beyond mere predictive contact points, the ICF assesses the proximity of human and object to their respective environment, informed by a probabilistic distribution of interactions learned throughout the denoising phase. Our comprehensive evaluation showcases HOlani-mator's superior ability to produce dynamic, context-aware animations that surpass existing benchmarks in text-driven animation synthesis.

关键词： computer vision Technological innovation Message passing Computational modeling Noise reduction Linguistics Animation

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