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Non-Convex Potential Games for Finding Global Solutions to Sensor Network Localization

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Non-Convex Potential Games for Finding Global Solutions to S...

European Control Conference (ECC)

作者： Gehui Xu Guanpu Chen Yiguang Hong Baris Fidan Thomas Parisini Karl H. Johansson Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Beijing China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Control Science and Engineering Tongji University Shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai China Department of Mechanical and Mechatronics Engineering University of Waterloo Waterloo ON Canada Department of Electrical and Electronic Engineering Imperial College London London UK Department of Engineering and Architecture University of Trieste Trieste Italy

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

Sensor network localization (SNL) problems require determining the physical coordinates of all sensors in a network. This process relies on the global coordinates of anchors and the available measurements between non-anchor and anchor nodes. Attributed to the intrinsic non-convexity, obtaining a globally optimal solution to SNL is challenging, as well as implementing corresponding algorithms. In this paper, we formulate a non-convex multi-player potential game for a generic SNL problem to investigate the identification condition of the global Nash equilibrium (NE) therein, where the global NE represents the global solution of SNL. We employ canonical duality theory to transform the non-convex game into a complementary dual problem. Then we develop a conjugation-based algorithm to compute the stationary points of the complementary dual problem. On this basis, we show an identification condition of the global NE: the stationary point of the proposed algorithm satisfies a duality relation. Finally, simulation results are provided to validate the effectiveness of the theoretical results.

关键词： Location awareness Coordinate measuring machines Simulation Current measurement Noise Europe Games

PRIVACY-PRESERVING LINKAGE OF DISTRIBUTED DATASETS USING THE PERSONAL HEALTH TRAIN

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arXiv 2023年

作者： Jugl, Maximilian Welten, Sascha Mou, Yongli Yediel, Yeliz U. Beyan, Oya D. Sax, Ulrich Kirsten, Toralf Chair of Computer Science 5 RWTH Aachen University Aachen Germany Department of Medical Data Science University Medical Center Leipzig Leipzig Germany Department of Data Science and Artificial Intelligence Fraunhofer FIT Sankt Augustin Germany Institute for Medical Informatics Faculty of Medicine University Hospital Cologne Cologne Germany Department of Medical Informatics University Medical Center Göttingen Göttingen Germany

With the generation of personal and medical data at several locations, medical data science faces unique challenges when working on distributed datasets. Growing data protection requirements in recent years drastically limit the use of personally identifiable information. Distributed data analysis aims to provide solutions for securely working on highly sensitive data while minimizing the risk of information leaks, which would not be possible to the same degree in a centralized approach. A novel concept in this field is the Personal Health Train (PHT), which encapsulates the idea of bringing the analysis to the data, not vice versa. Data sources are represented as train stations. Trains containing analysis tasks move between stations and aggregate results. Train executions are coordinated by a central station which data analysts can interact with. Data remains at their respective stations and analysis results are only stored inside the train, providing a safe and secure environment for distributed data analysis. Duplicate records across multiple locations can skew results in a distributed data analysis. On the other hand, merging information from several datasets referring to the same real-world entities may improve data completeness and therefore data quality. In this paper, we present an approach for record linkage on distributed datasets using the Personal Health Train. We verify this approach and evaluate its effectiveness by applying it to two datasets based on real-world data and outline its possible applications in the context of distributed data analysis tasks. The source code for the services and analysis scripts mentioned in this paper is open source and available from the authors1 © 2023, CC BY.

关键词： Sensitive data

A Pipeline for the Implementation of Immersive Experience in Cultural Heritage Sites in Sicily 3rd

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A Pipeline for the Implementation of Immersive Experience...

3rd Florence Heri-Tech International Conference, Florence Heri-Tech 2022

作者： Barbera, Roberto Condorelli, Francesca Di Gregorio, Giuseppe Di Piazza, Giuseppe Farella, Mariella Lo Bosco, Giosué Megvinov, Andrey Pirrone, Daniele Schicchi, Daniele Zora, Antonino Department of Physics and Astronomy "E. Maiorana" University of Catania Piazza Università 2 Catania95131 Italy Department of Civil Engineering and Architecture University of Catania Piazza Università 2 Catania95131 Italy Department of Computer Science University of Palermo Via Archirafi 34 Palermo90123 Italy National Research Council of Italy - Institute for Educational Technology Via Ugo La Malfa 153 Palermo90146 Italy Department of Sciences for Technological Innovation Euro-Mediterranean Institute of Science and Technology Via Michele Miraglia 20 Palermo90133 Italy

ISBN: (纸本)9783031203015

Modern digital technologies allow potentially to explore Cultural Heritage sites in immersive virtual environments. This is surely an advantage for the users that can better experiment and understand a specific site, also before a real visit. This specific approach has gained increasing attention during the extreme conditions of the recent COVID-19 pandemic. In this work, we present the processes that lead to the implementation of an immersive app for different kinds of low and high-cost devices, which have been attained in the context of the 3dLab-Sicilia project. 3dLab-Sicilia’s main objective is to sponsor the creation, development, and validation of a sustainable infrastructure that interconnects three main Sicilian centres specialized in augmented and virtual reality. The project gives great importance to the cultural heritage, as well as to the tourism-related areas. Despite the presentation of the case study of the Santa Maria La Vetere church, the process of the final app implementation guided by the general pipeline here presented is general and can be applied to other cultural heritage sites. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Virtual reality

architecture Descriptions Analysis Based on Text Mining and Crawling Technology 3

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Architecture Descriptions Analysis Based on Text Mining and ...

3rd IEEE International Conference on Frontiers Technology of Information and computer, ICFTIC 2021

作者： Zheng, Tong Zhao, Dongmiao Wang, Xingtian Gao, Weijun Miao, Sheng Qingdao University College of Computer Science and Technology Qingdao China Qingdao University of Technology Innovation Institute for Sustainable Maritime Architecture Research and Technology Qingdao China Faculty of Environmental Engineering University of Kitakyushu Kitakyushu Japan Qingdao University of Technology School of Information and Control Engineering Qingdao China

ISBN: (纸本)9781665406055

Nowadays, text mining technology is developed rapidly and employed by various contexts, such as healthcare, public opinion analysis, and document retrieval. Architectural design descriptions usually include large amount of massive text, which means information and knowledge are hidden. Since more and more attention are paid to the sustainable development, this paper research the main building design factors on nature aspect by using text mining. Collecting and processing 41,062 descriptions of architecture projects from website, the frequency of occurrence words with nature aspect are analyzed in 11 architecture categories respectively. The top 100 words of frequency are taken to constitute the word cloud, and the design factors on natural environment aspect could be summarized as area, light, landscape, structure, material, façade, site, water, wind, and view. This will provide architects guidance on dealing with the contradiction between building and nature. It will help us to further explore the relationship between architectural design and natural environment and realize a green and sustainable future. © 2021 IEEE.

关键词： Architectural design

Artificial Neural Network and Implementation of Robotic Arm for Mineral Extraction in Mines with Permanent Magnet Synchronous Motor

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Artificial Neural Network and Implementation of Robotic Arm ...

International Conference on Inventive Computation Technologies (ICICT)

作者： G. Yadagir M. Sudha Vidya Sagar Reddy G D.Shobha Rani S Sophia J Femila Roseline Collegiate Education Jayashankar Vidya Bhavan Hyderabad Telangana India Department of Electronics and Communication engineering Paavai Engineering College (Autonomous) Namakkal Tamil Nadu India School of Architecture Koneru Lakshmaiah Educational Foundation Guntur Andhra Pradesh India Department of Computer Science and Engineering Chadalawada Ramanamma Engineering college Tirupathi Tamil Nadu India Department of Computer Science and Engineering Karunya Institute of Technology and Sciences Coimbatore Tamil Nadu India Department of Electronics and Communication Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences (SIMATS) Chennai Tamil Nadu India

The implementation of a robotic arm for mineral extraction in mines is a challenging task that requires advanced technology and innovation. This paper proposes a solution using artificial intelligence (AI) and a permanent magnet synchronous motor (PMSM) to control the robotic arm's movement. A robotic arm with several degrees of freedom, a PMSM to move the arm, and AI algorithms to manage its motion make up the proposed system. The PMSM gives the arm's movements excellent control and enhances the precision and effectiveness of the mineral extraction procedure. The AI algorithms are in charge of directing the robotic arm's motion by examining sensor data and making choices following the situation at hand. The system is capable of adapting to its surroundings to improve the efficiency of mineral extraction. Compared to conventional mining methods, the suggested system has several benefits, including greater safety, increased efficiency, and lower costs. The system can completely transform the mining sector and can be applied in a variety of mining applications. Using a robotic arm and AI technologies, the suggested method offers a novel approach to mineral extraction in mines. The technology has several advantages over conventional mining methods and has the potential to greatly increase the productivity and security of the mining sector.

关键词：

HYPER-REALIST RENDERING: A THEORETICAL FRAMEWORK

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arXiv 2024年

作者： Akleman, Ergun Kurt, Murat Akleman, Derya Bruins, Gary Deng, Sitong Subramanian, Meena Visual Computing & Computational Media School of PVFA Computer Science and Engineering College of Engineering Texas A&M University College StationTX77831 United States International Computer Institute Ege University Izmir Turkey Department of Statistics Texas A&M University College StationTX77831 United States Visualization Program Department of Architecture Texas A&M University College StationTX77831 United States Department of Visualization Texas A&M University College StationTX77831 United States

This is the first paper in a series on hyper-realist rendering. In this paper, we introduce the concept of hyper-realist rendering and present a theoretical framework to obtain hyper-realist images. We are using the term Hyper-realism as an umbrella word that captures all types of visual artifacts that can evoke an impression of reality. The hyper-realist artifacts are visual representations that are not necessarily created by following logical and physical principles and can still be perceived as representations of reality. This idea stems from the principles of representational arts, which attain visually acceptable renderings of scenes without implementing strict physical laws of optics and materials. The objective of this work is to demonstrate that it is possible to obtain visually acceptable illusions of reality by employing such artistic approaches. With representational art methods, we can even obtain an alternate illusion of reality that looks more real even when it is not real. This paper demonstrates that it is common to create illusions of reality in visual arts with examples of paintings by representational artists. We propose an approach to obtain expressive local and global illuminations to obtain these stylistic illusions with a set of well-defined and formal methods. Our formalism is based on four principles: (1) colors and textures must be represented by algebraically complete structures, (2) we should allow impossible and inconsistent shapes in scene concepts, (3) we have to decompose illumination and shading, and (4) we must build our shading functions using statistic-based methods instead of physics-based methods. We claim that these principles allow us to develop simple methods since we can avoid algebraic inconsistencies. Using such simple methods, it can be possible to significantly speed up modeling and rendering algorithms by focusing only on essential elements that can create illusions of reality. © 2024, CC BY.

关键词： Formal methods

Lecture Notes in Computer Science (including subseries Lectu...

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Preface

Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2025年 14784 LNCS卷 v页

作者： Bai, Guangdong Ishikawa, Fuyuki Aït-Ameur, Yamine Papadopoulos, George A. School of Electrical Engineering and Computer Science Faculty of Engineering Architecture and Information Technology University of Queensland BrisbaneQLD Australia Information Systems Architecture Science Research Division National Institute of Informatics Tokyo Chiyoda-ku Japan IRIT University of Toulouse Toulouse France Department of Computer Science University of Cyprus Nicosia Cyprus

Explainable AI for Bioinformatics: Methods, Tools, and Applications

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arXiv 2022年

作者： Karim, Md. Rezaul Islam, Tanhim Beyan, Oya Lange, Christoph Cochez, Michael Rebholz-Schuhmann, Dietrich Decker, Stefan Department of Data Science and Artificial Intelligence Fraunhofer FIT Germany Chair of Computer Science 5 - Information Systems and Databases RWTH Aachen University Germany University of Cologne Faculty of Medicine University Hospital Cologne Institute for Biomedical Informatics Germany Department of Computer Science Vrije Univeriteit Amsterdam Netherlands Elsevier Discovery Lab Amsterdam Netherlands ZBMED - Information Center for Life Sciences Germany Faculty of Medicine University of Cologne Germany

Artificial intelligence (AI) systems utilizing deep neural networks (DNNs) and machine learning (ML) algorithms are widely used for solving important problems in bioinformatics, biomedical informatics, and precision medicine. However, complex DNNs or ML models, which are often perceived as opaque and black-box, can make it difficult to understand the reasoning behind their decisions. This lack of transparency can be a challenge for both end-users and decision-makers, as well as AI developers. Additionally, in sensitive areas like healthcare, explainability and accountability are not only desirable but also legally required for AI systems that can have a significant impact on human lives. Fairness is another growing concern, as algorithmic decisions should not show bias or discrimination towards certain groups or individuals based on sensitive attributes. Explainable artificial intelligence (XAI) aims to overcome the opaqueness of black-box models and provide transparency in how AI systems make decisions. Interpretable ML models can explain how they make predictions and the factors that influence their outcomes. However, most state-of-the-art interpretable ML methods are domain-agnostic and evolved from fields like computer vision, automated reasoning, or statistics, making direct application to bioinformatics problems challenging without customization and domain-specific adaptation. In this paper, we discuss the importance of explainability in the context of bioinformatics, provide an overview of model-specific and model-agnostic interpretable ML methods and tools, and outline their potential caveats and drawbacks. Besides, we discuss how to customize existing interpretable ML methods for bioinformatics problems. Nevertheless, we demonstrate how XAI methods can improve transparency through case studies in bioimaging, cancer genomics, and text mining (GitHub repo: https://***/rezacsedu/XAI-for-bioinformatics. Our review aims to provide valuable insights and se

关键词： Bioinformatics

Diffusion Unit: Interpretable Edge Enhancement and Suppression Learning for 3D Point Cloud Segmentation

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arXiv 2022年

作者： Xiu, Haoyi Liu, Xin Wang, Weimin Kim, Kyoung-Sook Shinohara, Takayuki Chang, Qiong Matsuoka, Masashi Artificial Intelligence Research Center AIST Tokyo Japan Department of Architecture and Building Engineering Tokyo Institute of Technology Tokyo Japan Innovation Technology Office Research Center PASCO Corporation Tokyo Japan Department of Computer Science Tokyo Institute of Technology Tokyo Japan

3D point clouds are discrete samples of continuous surfaces which can be used for various applications. However, the lack of true connectivity information, i.e., edge information, makes point cloud recognition challenging. Recent edge-aware methods incorporate edge modeling into network designs to better describe local structures. Although these methods show that incorporating edge information is beneficial, how edge information helps remains unclear, making it difficult for users to analyze its usefulness. To shed light on this issue, in this study, we propose a new algorithm called Diffusion Unit (DU) that handles edge information in a principled and interpretable manner while providing decent improvement. First, we theoretically show that DU learns to perform task-beneficial edge enhancement and suppression. Second, we experimentally observe and verify the edge enhancement and suppression behavior. Third, we empirically demonstrate that this behavior contributes to performance improvement. Extensive experiments and analyses performed on challenging benchmarks verify the effectiveness of DU. Specifically, our method achieves state-of-the-art performance in object part segmentation using ShapeNet part and scene segmentation using S3DIS. Our source code is available at https://***/martianxiu/DiffusionUnit. © 2022, CC BY.

关键词： Diffusion