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In-vehicle visualization of data by means of augmented reality 24

In-vehicle visualization of data by means of augmented reali...

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24th KES international conference on Knowledge-Based and Intelligent Information and Engineering systems, KES 2020

作者： Bran, Emanuela Sburlan, Dragos Florin Popovici, Dorin Mircea Puchianu, Crenguta Madalina Bautu, Elena Departament of Mathematics and Computer Science Ovidius University Constanta Romania

Recently, in-vehicle systems have considered integrating Augmented Reality (AR) to serve various purposes. the information offered to the driver by an in-vehicle system should be presented such that it can be easily interpreted without negatively affecting the driver's attention for the driving task. the interface must be accessible, visible and easily legible, while also being symbolically relevant. In this paper, we explain the requirements and design decisions that lead to the proposal of our current AR-based visualization component of our in-vehicle system. the 3D AR visualization scheme we propose enhances the automatic adaptive notification filtering module of the in-vehicle system previously proposed. We integrated voice and gesture commands in order to manage common actions during driving, such as navigation system functions, control of the radio or of the air conditioner, or generic actions regarding incoming notifications. the system is tested in an artificial setting in the laboratory, using a simulated prototype vehicle deck and windshield. © 2020 the Authors. Published by Elsevier B.V.

关键词： Augmented reality

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Role and object domain-based access control model for graduate education information system 24

Role and object domain-based access control model for gradua...

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24th KES international conference on Knowledge-Based and Intelligent Information and Engineering systems, KES 2020

作者： Jin, Gangzeng Wang, Daojiang Yang, Dawei Hong, Daocheng Dong, Qiwen Wang, Ye School of Data Science and Engineering East China Normal University Shanghai200062 China Information Technology Services East China Normal University Shanghai200062 China

With the booming of Chinese education informatization 2.0, East China Normal University proposes to design a new generation system of graduate education to provide better services for teachers and students. Within the graduate education system, ensuring system service availability and data security has become the primary challenge, and access control is one of the main strategies for Network security prevention and protection [1]. Hence, we proposed the role and object domain-based access control model (RDBAC) which specifies the object domain category for each role based on prior works. In the new model, when the account is assigned a role, the system specifies a specific object domain instance to achieve more fine-grained access control to student objects. Besides, on the basis of the formulation of RESTful [2] API specification and Trie tree, a matching algorithm is proposed to optimize the matching efficiency between access requests and URL patterns for more efficient system authorization. Furthermore, a comparison experiment with the regular method verifies that the Trie tree method has good performance on graduate education system including URL pattern construction, matching, and scalability. Our research also establishes that future advance of access control is a valuable avenue for education system development and will inspire much more design research for education information systems. © 2020 the Authors. Published by Elsevier B.V.

关键词： Informatization

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Temporal-fault diagnosis for critical-decision making in discrete-event systems 24

Temporal-fault diagnosis for critical-decision making in dis...

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24th KES international conference on Knowledge-Based and Intelligent Information and Engineering systems, KES 2020

作者： Bertoglio, Nicola Lamperti, Gianfranco Zanella, Marina Zhao, Xiangfu Department of Information Engineering University of Brescia Brescia25123 Italy School of Computer and Control Engineering Yantai University Yantai264005 China

Since its appearance in AI, model-based diagnosis is intrinsically set-oriented. Given a sequence of observations, the diagnosis task generates a set of diagnoses, or candidates, each candidate complying with the observations. What all the approaches in the literature have in common is that a candidate is invariably a set of faulty elements (components, events, or otherwise). In this paper, we consider a posteriori diagnosis of discrete-event systems (DESs), which are described by networks of components that are modeled as communicating automata. the diagnosis problem consists in generating the candidates involved in the trajectories of the DES that conform with a given temporal observation. Oddly, in the literature on diagnosis of DESs, a candidate is still a set of faulty events, despite the temporal dimension of trajectories. In our view, when dealing with critical domains, such as power networks or nuclear plants, set-oriented diagnosis may be less than optimal in explaining the supposedly abnormal behavior of the DES, owing to the lack of any temporal information relevant to faults, along with the inability to discriminate between single and multiple occurrences of the same fault. Embedding temporal information in candidates may be essential for critical-decision making. this is why a temporal-oriented approach is proposed for diagnosis of DESs, where candidates are sequences of faults. this novel perspective comes with the burden of unbounded candidates and infinite collections of candidates, though. To cope with, a notation based on regular expressions on faults is adopted. the diagnosis task is supported by a temporal diagnoser, a flexible data structure that can grow over time based on new observations and domain-dependent scenarios. © 2020 the Authors. Published by Elsevier B.V.

关键词： Discrete event simulation

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Static Detection of control-Flow-Related Vulnerabilities Using Graph Embedding 24

Static Detection of Control-Flow-Related Vulnerabilities Usi...

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24th international conference on Engineering of Complex computer systems (ICECCS)

作者： Cheng, Xiao Wang, Haoyu Hua, Jiayi Zhang, Miao Xu, Guoai Yi, Li Sui, Yulei Beijing Univ Posts & Telecommun Beijing Peoples R China Natl Comp Network Emergency Response Tech Team Coordinat Ctr Beijing Peoples R China Univ Technol Sydney Sydney NSW Australia

ISBN: (纸本)9781728146461

Static vulnerability detection has shown its effectiveness in detecting well-defined low-level memory errors. However, high-level control-flow related (CFR) vulnerabilities, such as insufficient control flow management (CWE-691), business logic errors (CWE-840), and program behavioral problems (CWE-438), which are often caused by a wide variety of bad programming practices, posing a great challenge for existing general static analysis solutions. this paper presents a new deep-learning-based graph embedding approach to accurate detection of CFR vulnerabilities. Our approach makes a new attempt by applying a recent graph convolutional network to embed code fragments in a compact and low-dimensional representation that preserves high-level control-flow information of a vulnerable program. We have conducted our experiments using 8,368 realworld vulnerable programs by comparing our approach with several traditional static vulnerability detectors and state-of-the-art machine-learning-based approaches. the experimental results show the effectiveness of our approach in terms of both accuracy and recall. Our research has shed light on the promising direction of combining program analysis with deep learning techniques to address the general static analysis challenges.

关键词： Static analysis graph embedding vulnerabilities control-flow

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Explainable robotics in human-robot interactions 24

Explainable robotics in human-robot interactions

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24th KES international conference on Knowledge-Based and Intelligent Information and Engineering systems, KES 2020

作者： Setchi, Rossitza Dehkordi, Maryam Banitalebi Khan, Juwairiya Siraj Cardiff University CardiffCF24 3AA United Kingdom Centre for Advanced Studies Dr. A.P.J.Abdul Kalam Technical University Lucknow India

this paper introduces a new research area called Explainable Robotics, which studies explainability in the context of human-robot interactions. the focus is on developing novel computational models, methods and algorithms for generating explanations that allow robots to operate at different levels of autonomy and communicate with humans in a trustworthy and human-friendly way. Individuals may need explanations during human-robot interactions for different reasons, which depend heavily on the context and human users involved. therefore, the research challenge is identifying what needs to be explained at each level of autonomy and how these issues should be explained to different individuals. the paper presents the case for Explainable Robotics using a scenario involving the provision of medical health care to elderly patients with dementia with the help of technology. the paper highlights the main research challenges of Explainable Robotics. the first challenge is the need for new algorithms for generating explanations that use past experiences, analogies and real-time data to adapt to particular audiences and purposes. the second research challenge is developing novel computational models of situational and learned trust and new algorithms for the real-time sensing of trust. Finally, more research is needed to understand whether trust can be used as a control variable in Explainable Robotics. © 2020 the Authors. Published by Elsevier B.V.

关键词： Human robot interaction

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the production quality control process, enhanced with augmented reality glasses and the new generation computing support system 24

The production quality control process, enhanced with augmen...

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24th KES international conference on Knowledge-Based and Intelligent Information and Engineering systems, KES 2020

作者： Szajna, Andrzej Stryjski, Roman Wozniak, Waldemar Chamier-Gliszczynski, Norbert Królikowski, Tomasz Digital Technology Poland [DTP Ltd. Wysockiego 4 Zielona Góra66-002 Poland Faculty of Mechanical Engineering University of Zielona Gora Szafrana 4 Zielona Góra65-516 Poland Faculty of Mechanical Engineering Koszalin University of Technology sniadeckich 2 Koszalin75-453 Poland

the world is accelerating the digitisation of many branches of the economy. In production, it is often called Industry 4.0 -the term invented by Prof. Wahlster in Germany. One branch of 'Production Digitisation' is Augmented Reality (AR)-a technology that gives a very convenient and natural human-machine interface. Users are presented with the information requested, right in front of their eyes, and can communicate with the system through simple gestures and speech. the key advantage of AR is having one's handsfree so that the user can perform his/her regular tasks, unhindered. In the first part of this paper, the concept of using AR glasses, in the quality control process, is presented. the present authors describe a proprietary support system. A specific example is then given in a real production environment on a real production process, comparing the old way with the new AR way of conducting test procedures. An evaluation of its usability is characterised using important factors that can affect the final outcome or features of the product and the manner in which it is applied in real life. In concluding, the authors focus on its advantages, the disadvantages, the technological imperfections, and the limitations and go on to deliberate on the conclusions and further research topics. © 2020 the Authors. Published by Elsevier B.V.

关键词： Glass

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the Application of Virtual Logic Models to Simulate Real Environment for Testing Advanced Driving-Assistance systems 24

The Application of Virtual Logic Models to Simulate Real Env...

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24th international conference on Methods and Models in Automation and Robotics (MMAR)

作者： Pikus, Michal Was, Jaroslaw AGH Univ Sci & Technol Dept Appl Comp Sci Fac Elect Engn Automat Comp Sci & Biomed Engn Al Mickiewicza 30 PL-30059 Krakow Poland

ISBN: (纸本)9781728109336

Advanced driving-assistance systems (ADAS) have become more popular and received more aid in automotive business. ADAS systems evolution requires more efforts to prepare efficient and reliable systems. Because of safety restrictions we need to validate systems by driving over several million kilometers in different conditions. that is why research, development and verification processes are highly required. the best solution to solve this problem are computer simulations. Application of digital scenarios saves time, money and human resources. there are many simulators which are developed by automotive companies. In our paper we would like to present set of simulators which are used to simulate and validate camera sensors, control and path planning algorithms for ADAS. Our tools are able to simulate/emulate vehicle components and road environment elements. However, mainly in case of ADAS systems this is a difficult task. Our paper presents approaches the methodology of virtual simulations [1].

关键词： ADAS Software Verification Software Testing MIL SIL HIL Software models

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Machine Learning-enabled feedback loops for metal powder bed fusion additive manufacturing 24

Machine Learning-enabled feedback loops for metal powder bed...

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24th KES international conference on Knowledge-Based and Intelligent Information and Engineering systems, KES 2020

作者： Liu, Chao Le Roux, Léopold Ji, Ze Kerfriden, Pierre Lacan, Franck Bigot, Samuel School of Engineering Cardiff University CardiffCF24 3AA United Kingdom Centres des Matériaux Mines ParisTech PSL University Evry91100 France

Metal Powder Bed Fusion (PBF) has been attracting an increasing attention as an emerging metal Additive Manufacturing (AM) technology. Despite its distinctive advantages compared to traditional subtractive manufacturing such as high design flexibility, short development time, low tooling cost, and low production waste, the inconsistent part quality caused by inappropriate product design, non-optimal process plan and inadequate process control has significantly hindered its wide acceptance in the industry. To improve the part quality control in metal PBF process, this paper proposes a novel Machine Learning (ML)-enabled approach for developing feedback loops throughout the entire metal PBF process. A categorisation of metal PBF feedback loops is proposed along with a summary of the critical PBF manufacturing data in each process stage. A generic framework of ML-enabled metal PBF feedback loops is proposed with detailed explanations and examples. the opportunities and challenges of the proposed approach are also discussed. the applications of ML techniques in metal PBF process allow efficient and effective decision-makings to be achieved in each PBF process stage, and hence have a great potential in reducing the number of experiments needed, thus saving a significant amount of time and cost in metal PBF production. © 2020 the Authors. Published by Elsevier B.V.

关键词： Powder metals

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24th international conference on Formal Methods for Industrial Critical systems, FMICS 2019

24th International Conference on Formal Methods for Industri...

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24th international conference on Formal Methods for Industrial Critical systems, FMICS 2019

ISBN: (纸本)9783030270070

the proceedings contain 9 papers. the special focus in this conference is on Formal Methods for Industrial Critical systems. the topics include: Formal Modelling and Verification of an Interlocking Using mCRL2;A DFT Modeling Approach for Infrastructure Reliability Analysis of Railway Station Areas;multiple Analyses, Requirements Once:: Simplifying Testing and Verification in Automotive Model-Based Development;the Impact of Requirement Splitting on the Efficiency of Supervisory control Synthesis;Incremental Development of a Safety Critical System Combining formal Methods and DSMLs: − Application to a Railway System −;probabilistic Verification for Reliable Network-on-Chip System Design;A Simulator for LLVM Bitcode.

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Safe Inputs Approximation for Black-Box systems 24

Safe Inputs Approximation for Black-Box Systems

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24th international conference on Engineering of Complex computer systems (ICECCS)

作者： Xue, Bai Liu, Yang Ma, Lei Zhang, Xiyue Sun, Meng Xie, Xiaofei CAS Inst Software State Key Lab Comp Sci Columbus OH USA Univ Chinese Acad Sci Beijing Peoples R China Beijing Inst Control Engn Beijing Peoples R China Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore Kyushu Univ Fac Informat Sci & Elect Engn Fukuoka Japan Peking Univ Sch Math Sci Beijing Peoples R China

ISBN: (纸本)9781728146461

Given a family of independent and identically distributed samples extracted from the input region and their corresponding outputs, in this paper we propose a method to under-approximate the set of safe inputs that lead the black-box system to respect a given safety specification. Our method falls within the framework of probably approximately correct (PAC) learning. the computed under-approximation comes with statistical soundness provided by the underlying PAC learning process. Such a set, which we call a PAC under-approximation, is obtained by computing a PAC model of the black-box system with respect to the specified safety specification. In our method, the PAC model is computed based on the scenario approach, which encodes as a linear program. the linear program is constructed based on the given family of input samples and their corresponding outputs. the size of the linear program does not depend on the dimensions of the state space of the black-box system, thus providing scalability. Moreover, the linear program does not depend on the internal mechanism of the black-box system, thus being applicable to systems that existing methods are not capable of dealing with. Some case studies demonstrate these properties, general performance and usefulness of our approach.

关键词： Black-Box systems Linear Programming Probably Approximate Safety

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