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GraphiCon 2021 - proceedings of the 31st International Conference on computer Graphics and vision

GraphiCon 2021 - Proceedings of the 31st International Confe...

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31st International Conference on computer Graphics and vision, GraphiCon 2021

The proceedings contain 124 papers. The topics discussed include: light transport simulation and realistic rendering: state of the art report;the real-time rendering of gradient media;rendering the real-time caustics with DirectX raytracing;real-time rendering of small-scale volumetric structure on animated surfaces;reliable GPU-based methods and algorithms of implementation dynamic relief shadows in virtual environment systems;approximate instancing for modeling plant ecosystems;rendering of newton's rings in monochrome light;comparison of the results of modeling a dispersed medium by wave and ray methods;towards hardware OpenGL support in cloud computing;and applying objective quality metrics to video-codec comparisons: choosing the best metric for subjective quality estimation.

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Design of neuro‐simulation system in situational management of control and quality assessment for complex production assembly system 5

Design of neuro‐simulation system in situational management...

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5th International Scientific workshop on modeling, Information Processing and Computing, MIP: Computing-V 2022

作者： Zolkin, A.L. Lavrov, E.A. Zaitseva, I.N. Bityutskiy, A.S. Mironchuk, V.A. Computer and Information Sciences Department Povolzhskiy State University of Telecommunications and Informatics Samara443010 Russia Computer Science Department Sumy State University Sumy40007 Ukraine Department of Physics Radio Engineering and Electronics Bunin Yelets State University oblast Elets Lipetsk399770 Russia "Invent Technology" LLP AlmatyA10E5P4 Kazakhstan Department of Economic Cybernetics Federal State Budgetary Educational Institution of Higher Education "Kuban State Agrarian University named after I.T. Trubilin" Krasnodar350044 Russia

The specific challenge for application of developed system of situational input in control process is generalized by authors, flowgraph model is demonstrated, synthesis methodology is generalized and assessment of effectiveness based on group of parameters of regression nature to implemented neuro-fuzzy regulation system is described. Decomposition and structural analysis of specificity of application of implemented model, its characteristic function and balance-model (before implementation) are described. The steps of development of this complex technology are reviewed. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Fuzzy control

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RerrFact: Reduced Evidence Retrieval Representations for Scientific Claim Verification

RerrFact: Reduced Evidence Retrieval Representations for Sci...

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2022 workshop on Scientific Document Understanding, SDU 2022

作者： Rana, Ashish Khanna, Deepanshu Ghosal, Tirthankar Singh, Muskaan Singh, Harpreet Rana, Prashant Singh School of Business Informatics and Mathematics University of Mannheim Germany Department of Electronics & Communication Engineering Thapar Institute of Engineering & Technology India Institute of Formal and Applied Linguistics Faculty of Mathematics and Physics Charles University Czech Republic Department of Computer Science & Engineering Thapar Institute of Engineering & Technology India

Exponential growth in digital information outlets and the race to publish has made scientific misinformation more prevalent than ever. However, the task to fact-verify a given scientific claim is not straightforward even for researchers. Scientific claim verification requires in-depth knowledge and great labor from domain experts to substantiate supporting and refuting evidence from credible scientific sources. The SciFact dataset and corresponding task provide a benchmarking leaderboard to the community to develop automatic scientific claim verification systems via extracting and assimilating relevant evidence rationales from source abstracts. In this work, we propose a modular approach that sequentially carries out binary classification for every prediction subtask as in the SciFact leaderboard. Our simple classifier-based approach uses reduced abstract representations to retrieve relevant abstracts. These are further used to train the relevant rationale-selection model. Finally, we carry out two-step stance predictions that first differentiate non-relevant rationales and then identify supporting or refuting rationales for a given claim. Experimentally, our system RerrFact with no fine-tuning, simple design, and a fraction of model parameters fairs competitively on the leaderboard against large-scale, modular, and joint modeling approaches. © 2022 Copyright for this paper by its authors.

关键词： Abstracting

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5th workshop on computer Modelling in Decision Making, CMDM 2020

5th Workshop on Computer Modelling in Decision Making, CMDM ...

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5th workshop on computer Modelling in Decision Making, CMDM 2020

The proceedings contain 12 papers. The topics discussed include: improving multi-material structures using topological optimization and the modified SIMP method;predicting the dynamics of the maximum and optimal profits of innovative enterprises;econometric modeling of economic factors' impact on the labor force per capita;making decisions on issuing sub-federal bonds in Russia: key factors modeling;mathematical modeling of circular sandwich plate interaction with viscous liquid layer for predicting its hydroelastic response;impact of healthcare innovation on the population's well-being in Russia;study of Russian households income differentiation with various inequality measures;the scenario modeling of regional competitiveness risks based on the chapman-Kolmogorov equations;and mathematical models of the development of industrial enterprises, with the effect of lagging internal and external.

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5th International workshop on Active Inference, IWAI 2024

5th International Workshop on Active Inference, IWAI 2024

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5th International workshop on Active Inference, IWAI 2024

ISBN: (纸本)9783031771378

The proceedings contain 17 papers. The special focus in this conference is on Active Inference. The topics include: Free Energy in a Circumplex Model of Emotion;learning in Hybrid Active Inference Models;learning and Embodied Decisions in Active Inference;online Structure Learning with Dirichlet Processes Through Message Passing;exploring and Learning Structure: Active Inference Approach in Navigational Agents;belief Sharing: A Blessing or a Curse;coupled Autoregressive Active Inference Agents for Control of Multi-joint Dynamical Systems;reactive Environments for Active Inference Agents with ***;selection of Exploratory or Goal-Directed Behavior by a Physical Robot Implementing Deep Active Inference;epistemic Value Anticipation into the Deep Active Inference Model;planning to Avoid Ambiguous States Through Gaussian Approximations to Non-linear Sensors in Active Inference Agents;message Passing-based Bayesian Control of a Cart-Pole System;reducing Intuitive-physics Prediction Error Through Playing;modeling Sustainable Resource Management Using Active Inference;contextuality, Cognitive Engagement, and Active Inference.

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workshop held at the 12th International Conference on Model and Data Engineering, MEDI 2023

Workshop held at the 12th International Conference on Model ...

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workshop held at the 12th International Conference on Model and Data Engineering, MEDI 2023

ISBN: (纸本)9783031557286

The proceedings contain 18 papers. The special focus in this conference is on Model and Data Engineering. The topics include: Towards an Open Domain Arabic Question Answering System: Assessment of the Bert Approach;Multi-lingual Scene Text Detection Containing the Arabic Scripts Using an Optimal then Enhanced YOLO Model;transfer Learning Model for Cyberbullying Detection in Tunisian Social Networks;node2Vec Stability: Preliminary Study to Ensure the Compatibility of Embeddings with Incremental Data Alignment;towards Enabling Domain-Specific modeling Language Exchange Between modeling Tools;the Power of Prognosis: Cox Model Prediction of Disease-Free Survival in Colon Cancer;transfer Learning in Segmenting Myocardium Perfusion Images;smart Saliency Detection for Prosthetic vision;automatic Detection of Multiple Sclerosis Using Genomic Expression;distributed and Collaborative Learning Approach for Stroke Prediction;ioT Technologies for Smart Healthcare Buildings with Distributed Deep Learning Techniques;How Does Blockchain Enhance Zero Trust Security in IoMT?;HIPAA and GDPR Compliance in IoT Healthcare Systems;a Secure IoT Architecture for Industry 4.0;From Functional Requirements to NoSQL Database Models: Application to IoT Geospatial Data;a Survey on Intrusion Detection Systems for IoT Networks based on Long Short-Term Memory.

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Service modeling and Architecting for Self-Adaptive IoT-based Systems 11

Service Modeling and Architecting for Self-Adaptive IoT-Base...

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11th Seminary of computer Science Research at Feminine, RIF 2022

作者： Merabet, Fatima Zohra Benmerzoug, Djamel LIRE Laboratory University of Constantine2 Abdelhamid Mehri Constantine Algeria

In recent years, the Internet of Things (IoT) environment dynamics has increased, leading to an increase in the complexity of modern software systems. Therefore, the need to manage these complex systems comes with several challenges, and service-oriented systems (SoS) are a good option to realize this. Several research initiatives have addressed this vision. However, there is a clear need for flexibility and self-adaptation for service-based IoT applications to promote higher customization and adaptation to manage unpredictable changes and uncertain situations. In our research, we advocate the use of the SoS paradigm for building next-generation services using the IoT, and the main objective of our work is to ensure the self-adaptation of these complex systems. In this paper, we provide a particular perspective on the evolution of the field of self-adaptation with a new conception. By proposing a BPMN extension named BPMN4SAS (BPMN for the self-adaptive system), we stress the idea of adaptation in the design phase, starting from the first step in the BPM (Business Process Management) life cycle. The proposed extension is illustrated through an example dealing with accident management in a smart city system. The second contribution of this paper concerns the optimization phase, where we propose a global architecture to ensure the self-adaptation of the IoT services at run time. The proposed architecture aims to let the system collect data about the uncertainties during execution. The system uses this data to resolve uncertainties, be aware of itself, and adjust and satisfy the changing conditions, especially the quality-of-service (QoS) constraints. © 2020 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Quality of service

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Development of a gradient descent algorithm for pathway routing based on functional-voxel modeling 31

Development of a gradient descent algorithm for pathway rout...

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31st International Conference on computer Graphics and vision, GraphiCon 2021

作者： Tolok, Alexey Petukhov, Pavel V.A. Trapeznikov Institute of Control Science of Russian Academy of Sciences 65 Profsoyuznaya street Moscow117997 Russia Moscow State University of Technology "STANKIN" 1 Vadkovsky street Moscow127994 Russia

This paper considers a pathfinding algorithm using the gradient method for functional-voxel modeling problems. The basic principles of constructing gradient lines based on the functional voxel model are investigated. The tool to describe the scene with obstacles is the mathematical apparatus of R-functions. To solve the problem of pathfinding in a weakly deterministic environment, we propose an algorithm that is based on the use of: gradient method analyzing the color palette of images of local features of the function;mathematical apparatus of R-functions describing the topography of the solution surface at the current moment in time. An algorithm of target control that solves the problem of getting out of possible "trapped objects" is considered. For this, the principle of changing the position of the target was developed to control the gradient direction. © 2021 Copyright for this paper by its authors.

关键词： Gradient methods

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7th International workshop on Knowledge Graph Management and Applications, KGMA 2024, 6th International workshop on Semi-structured Big Data Management and Applications, SemiBDMA 2024, 1st International workshop on Mobile Applications and Data Management, MADM 2024, 1st International workshop on Artificial Intelligence in Education and Educational Data Mining, AIEDM 2024 and 1st International workshop on Spatio-Temporal Big Data Management, STBDM 2024 held in conjunction with APWeb-WAIM 2024

7th International Workshop on Knowledge Graph Management and...

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7th International workshop on Knowledge Graph Management and Applications, KGMA 2024, 6th International workshop on Semi-structured Big Data Management and Applications, SemiBDMA 2024, 1st International workshop on Mobile Applications and Data Management, MADM 2024, 1st International workshop on Artificial Intelligence in Education and Educational Data Mining, AIEDM 2024 and 1st International workshop on Spatio-Temporal Big Data Management, STBDM 2024 held in conjunction with APWeb-WAIM 2024

ISBN: (纸本)9789819600540

The proceedings contain 28 papers. The special focus in this conference is on Knowledge Graph Management and Applications. The topics include: ASM: Adaptive Subgraph Matching via Efficient Compression and Label Filter;learning Multi-semantic based on Cross-Attention for Image-Text Retrieval;integrated Global Semantics and Local Details for Image-Text Retrieval;adversarial Graph Convolutional Network Hashing for Cross-Modal Retrieval;FS-IGA: Feature Selection Method based on Improved Genetic Algorithm;shearlet Transform based Multiscale Fusion Network for Image Super Resolution;application of Segmental-based Transfinite Mapping Method for Quadrilateral Mesh Generation of Complex Domain;augmenting Knowledge Tracing: Personalized modeling by Considering Forgetting Behavior in Learning Process;a Time-Aware Sequential Recommendation based on Attention Mechanism;integrating User Sentiment and Behavior for Explainable Recommendation;SACC: Secure-Cooperative Adaptive Cruise Control for Unmanned Vehicles;A Systematic Mapping Study of LLM Applications in Mobile Device Research;application Framework for OpenHarmony Distributed Trusted Execution Environment;design and Implementation of a Multi-metric Performance Analysis Tool for Android System and Its Applications;Towards Optimal Leakage Assessment of TVLA;Joint UAV Trajectory Optimization and Task Offloading in Integrated Air-Ground Networks;research on Ethical Issues of Classroom Dialogue in the Era of Large Language Model;adaptive Exploration: Elevating Educational Impact of Unsupervised Knowledge Graph Question Answering;xLSTM-FER: Enhancing Student Expression Recognition with Extended vision Long Short-Term Memory Network;RDNeRF: Radiance Distribution Guided NeRF for Floaters Removing;Multi-user VR Content Wireless Delivery Using Motion Prediction and Adaptive Multicasting;MEGKT: Multi-edge Features Enhancement for Graph-based Knowledge Tracing;Collaborative Inference for Adaptive DNN Pipeline-Aware Alignment;a Unified Fr

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Simulating pandemic emergency scenarios considering mobility patterns through an agent-based model 1

Simulating pandemic emergency scenarios considering mobility...

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1st workshop on Agent-based modeling and Policy-Making, AMPM 2021

作者： Fazio, Martina Pluchino, Alessandro Inturri, Giuseppe Le Pira, Michela Giuffrida, Nadia Ignaccolo, Matteo Department of Physics and Astronomy University of Catania Via Santa Sofia 64 Catania Italy INFN Section of Catania Catania Italy Department of Electrical Electronic and Computer Engineering University of Catania Via Santa Sofia 64 Catania Italy Department of Civil Engineering and Architecture University of Catania Via Santa Sofia 64 Catania Italy Spatial Dynamics Lab University College Dublin UCD Richview Campus Belfield DublinD04 V1W8 Ireland

One of the main policies to contain a pandemic spreading is to reduce people mobility. However, it is not easy to predict its actual impact, and this is a limitation for policy-makers who need to act effectively and timely to limit virus spreading. Data are fundamental for monitoring purposes;however, models are needed to predict the impact of different scenarios at a granular scale. based on this premise, this paper presents the first results of an agent-based model (ABM) able to dynamically simulate a pandemic spreading under mobility restriction scenarios. The model is here used to reproduce the first wave of COVID-19 pandemic in Italy and considers factors that can be attributed to the diffusion and lethality of the virus and population mobility patterns. The model is calibrated with real data (considering the first wave), and it is based on a combination of static and dynamic parameters. First results show the ability of the model to reproduce the pandemic spreading considering the lockdown strategy adopted by the Italian Government and pave the way for scenario analysis of different mobility restrictions. This could be helpful to support policy-making by providing a strategic decision-tool to contrast pandemics. © 2021 Copyright for this paper by its authors.

关键词： Viruses

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