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检索条件"任意字段=24th International Conference on Control Systems and Computer Science, CSCS 2023"

共 927 条记录，以下是221-230 订阅

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Compositional Verification of Stigmergic Collective systems 1

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24th international conference on Verification, Model Checking, and Abstract Interpretation (VMCAI) part of the 50th ACM SIGPLAN Symposium on Principles of Programming Languages (POPL)

作者： Di Stefano, Luca Lang, Frederic Univ Grenoble Alpes INRIA CNRS Grenoble INPLIG Grenoble France Univ Gothenburg Gothenburg Sweden

ISBN: (数字)9783031249501

ISBN: (纸本)9783031249495;9783031249501

Collective adaptive systems may be broadly defined as ensembles of autonomous agents, whose interaction may lead to the emergence of global features and patterns. Formal verification may provide strong guarantees about the emergence of these features, but may suffer from scalability issues caused by state space explosion. Compositional verification techniques, whereby the state space of a system is generated by combining (an abstraction of) those of its components, have shown to be a promising countermeasure to the state space explosion problem. therefore, in this work we apply these techniques to the problem of verifying collective adaptive systems with stigmergic interaction. Specifically, we automatically encode these systems into networks of LNT processes, apply a static value analysis to prune the state space of individual agents, and then reuse compositional verification procedures provided by the CADP toolbox. We demonstrate the effectiveness of our approach by verifying a collection of representative systems.

关键词： Adaptive systems

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GNSS/IMU Integrated Navigation Methods with NLOS Mitigation 24

GNSS/IMU Integrated Navigation Methods with NLOS Mitigation

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24th COTA international conference of Transportation Professionals: Resilient, Intelligent, Connected, and Lowcarbon Multimodal Transportation, CICTP 2024

作者： Zuo, Yang Duan, Xuting Xia, Haiying Zhou, Jianshan School of Transportation Science and Engineering Beihang Univ. Beijing China State Key Lab of Intelligent Transportation System Beijing China Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China Zhongguancun Laboratory Beijing China Key Laboratory of Operation Safety Technology on Transport Vehicles Ministry of Transport Beijing China

ISBN: (数字)9780784485484

ISBN: (纸本)9780784485484

With the development of computer technology, intelligent vehicles have become a popular orientation at present. this paper provides a solution for the traditional GNSS/IMU integrated navigation to mitigate the influence of non-line-of-sight (NLOS) environments and achieve high-precision navigation. the LOS/NLOS switching is treated as a transition in a Markov chain, and the DIMM filtering is applied to obtain GNSS-filtered data free from the influence of NLOS. GNSS/IMU integrated navigation is loose coupling in that the method combines IMU information with processed GNSS measurement using the ESKF (Error-State Kalman Filter) to achieve accurate target tracking and positioning by utilizing the state difference as the state variable. Simulation results demonstrate that the proposed method significantly improves tracking and positioning accuracy by effectively mitigating NLOS effects compared to traditional methods. this research provides an effective solution for real-world autonomous vehicle navigation systems and optimizes the city driving experience. © ASCE.

关键词： Markov chains

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DyST: Dynamic Specification Mining for Heterogenous IoT systems with WoT 24th

DyST: Dynamic Specification Mining for Heterogenous IoT Syst...

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24th international conference Web Engineering (ICWE)

作者： Korkan, Ege Ramirez, Silvia Oliva Steinhorst, Sebastian Siemens Munich Bavaria Germany Tech Univ Munich Munich Bavaria Germany

ISBN: (纸本)9783031623615;9783031623622

the comprehension of a distributed system and its verification is one of the most challenging problems in today's software engineering, commonly referred to as observability. the complexity increases when one cannot control all the components, like in IoT systems composed of third-party devices. the Web of things standards by the W3C help with this by describing what one can do with an IoT device via network messages. However, no work has leveraged these standards to offer an observability solution that works with any set of IoT devices. this work addresses this gap by proposing a method to verify the correctness of the system by mining its specification from device interactions. Our approach can reverse engineer complex application logic in the form of UML Sequence Diagrams from the analysis of network messages of any protocol between the devices during system runtime, which can be used to programmatically assert the correctness of the mined specification. We have evaluated our approach with three case studies to assess our mining technique, the performance of our algorithms, and the applicability of our contributions to system verification in the IoT. Our results show that our approach can produce accurate Sequence Diagrams that help understand and verify the behavior of IoT systems.

关键词： Internet of things Process Mining Web of things

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Analysis of design solutions for autonomous drones

Analysis of design solutions for autonomous drones

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international conference on control systems and computer science (cscs)

作者： Bogdan Nedelcu Adina Magda Florea Faculty of Automatic Control and Computers Politehnica University of Bucharest

Drones as a particular case of robots were recently regulated by the EU as a guideline for all member states, raising several barriers in the use of drones in industrial applications for the future. Because of safety risks and privacy concerns, from the legal point of view, drones have now a limited applicability outside the visual line of sight of the human pilot therefore a limited economical applicability to some areas accessible by the pilot and outside urban areas. In this paper, we identify the key paths autonomous drone technology should progress towards, to establish a strong basis for a future certification of operating at human tolerable safety risks, and we explore the existing options to simulate in 3D environments the behavior of drones and use simulator rendered data to capture sensor data and images for constructing a set of training and validation data. Moreover, we report on the abilities of simulators to integrate software and hardware in the loop autopilots of drones, explore ways of using custom network architectures on drones, and test the ability of low power computing chips to run custom design neural network architectures. We explore the existing options to simulate in 3D environments the behavior of drones and use simulator rendered data to capture sensor data and images for constructing a set of training and validation data. We also test the abilities of simulators to integrate software and hardware in the loop autopilots of drones and possibility to integrate well known programming languages. To further explore the possibility of using custom network architectures on drones, we test the ability of low power computing chips to run custom design neural network architectures, and we identify some of the challenges ahead.

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Utilizing Machine Learning in Medical Diagnosis: Systematic Review and Empirical Analysis 24

Utilizing Machine Learning in Medical Diagnosis: Systematic ...

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24th international Arab conference on Information Technology, ACIT 2023

作者： Alazaidah, Raed Hassan, Mohammad Al-Rbabah, Lara Samara, Ghassan Yusof, Marina Al-Sherideh, Ala'a Saeb Zarqa University Ai Faculty of Information Technology Department of Data Science Zarqa Jordan Zarqa University Faculty of Information Technology Department of Computer Science Zarqa Jordan The Hashemite University Faculty of Engineering Department of Computer Engineering Zarqa Jordan Selanger Malaysia Zarqa University Faculty of Information Technology Department of Cyber Security Zarqa Jordan

ISBN: (纸本)9798350384307

During the last few years, several real-life applications have attempted to utilize the proven high capabilities of artificial intelligence in general and machine learning in particular. Machine learning has been utilized in several domains, such as spam detection, image recognition, recommendation systems, self-driving cars, and medical diagnosis. this paper aims to survey the most related work of utilizing machine learning in the domain of medical diagnosis. Moreover, the paper proposes a comparative analysis for identifying and determining the best classification model and feature selection method in mind of handling medical datasets. Hence, four different medical datasets have been used to train twenty-three classification models and four well-known feature selection methods with respect to several evaluation metrics such as Accuracy, True Positive ratio, False Positive ratio, Precision, and Recall. the results reveal that RandomForest, J48, and SMO classifiers are the best classifiers when it comes to handling medical datasets respectively. Furthermore, the Gain Ratio method is the best choice for handling the step of feature selection. © 2023 IEEE.

关键词： Classification Feature Selection Machine Learning Medical Diagnosis Prediction

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Improving Code Comprehension through Scaffolded Self-explanations 24th

Improving Code Comprehension Through Scaffolded Self-explana...

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24th international conference on Artificial Intelligence in Education (AIED)

作者： Oli, Priti Banjade, Rabin Narayanan, Arun Balajiee Lekshmi Chapagain, Jeevan Tamang, Lasang Jimba Brusilovsky, Peter Rus, Vasile Univ Memphis Memphis TN 38152 USA Univ Pittsburgh Pittsburgh PA 15260 USA

ISBN: (纸本)9783031363351;9783031363368

Self-explanations could increase student's comprehension in complex domains;however, it works most efficiently with a human tutor who could provide corrections and scaffolding. In this paper, we present our attempt to scale up the use of self-explanations in learning programming by delegating assessment and scaffolding of explanations to an intelligent tutor. To assess our approach, we performed a randomized control trial experiment that measured the impact of automatic assessment and scaffolding of self-explanations on code comprehension and learning. the study results indicate that low-prior knowledge students in the experimental condition learn more compared to high-prior knowledge in the same condition but such difference is not observed in a similar grouping of students based on prior knowledge in the control condition.

关键词： Program Comprehension Scaffolding computer science Education Java Programming Intelligent Tutoring System

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A Novel Leak Localization Method for Water Pipeline systems Based on Acoustic Emission Monitoring and Event Correlation 24th

A Novel Leak Localization Method for Water Pipeline Systems ...

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24th international conference on Computational science and Its Applications (ICCSA)

作者： Nguyen, Duc-thuan Kim, Jong-Myon Univ Ulsan Dept Elect Elect & Comp Engn Ulsan 44610 South Korea Prognosis & Diagnost Technol Co Ltd Ulsan 44610 South Korea

ISBN: (纸本)9783031646072;9783031646089

this paper proposes a novel method for leak localization in water pipeline systems through the monitoring of acoustic emissions and cross-correlation of acoustic emission events. the method is designed to overcome limitations in the calculation of the time difference of arrival by traditional methods such as time-of-arrival detection and cross-correlation. the proposed method combines these two conventional techniques, specifically by examining cross-correlation at positions associated with arrived acoustic emission events. the positions of acoustic emission events are initially identified using the constant false alarm rate signal detection algorithm. Subsequently, the minimum entropy deconvolution is applied at these positions to eliminate noise and reveal signal information. Finally, cross-correlation at the identified positions is computed to determine the time difference of arrival and localize the leak position. Experimental validations on a real-world testbed demonstrate the effectiveness of the proposed method with a high level of accuracy. the proposed method exhibits superior accuracy in comparison to other methods.

关键词： Leak Localization Pipeline systems Acoustic Emission Constant False Alarm Rate Minimum Entropy Deconvolution

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Conducting Rapid Experimentation with an Open-Source Adaptive Tutoring System 1

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24th international conference on Artificial Intelligence in Education (AIED)

作者： Pardos, Zachary A. Anastasopoulos, Ioannis Sheel, Shreya K. Univ Calif Berkeley Sch Educ Berkeley CA 94720 USA

ISBN: (数字)9783031363368

ISBN: (纸本)9783031363351;9783031363368

Intelligent Tutoring systems have been an area of particular relevance and importance to AIED. In this tutorial, we introduce uses of a new tool to accelerate the speed at which the community can innovate and experiment in the general area of computer tutoring systems. We showcase the field's first fully fledged and open-source adaptive tutoring system (OATutor) with a completely creative commons licensed problem library based on popular open-licensed algebra textbooks. We demonstrate, with hands-on tutorials, how the system can be deployed on *** and used to help AIED researchers rapidly run A/B experiments, including how to add or modify content in the system, analyze its log data, and link OATutor content to learning management system with LTI. Our open-sourcing of three textbooks worth of questions and tutoring content in a structured data format (JSON) also opens up avenues for AIED researchers to apply new and legacy educational data mining and NLP techniques.

关键词： Intelligent Tutoring systems Authoring Creative Commons A/B Testing HCI

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ADS Modeling and Safety Verification in Extreme Driving Scenarios 24

ADS Modeling and Safety Verification in Extreme Driving Scen...

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24th IEEE international conference on Software Quality, Reliability and Security Companion, QRS-C 2024

作者： Zhao, Ying Zhu, Yi Zhao, Li Li, Zexin Yin, Chan School of Computer Science and Technology Jiangsu Normal University Xuzhou China Ministry of Industry and Information Technology Nanjing University of Aeronautics and Astronautics Key Laboratory of Safety-Critical Software Nanjing China

ISBN: (纸本)9798350365658

Autonomous vehicles play a vital role in improving traffic efficiency and reducing traffic accidents. the spatio-temporal data in driving scenarios is complex and unpredictable, with uncertain interaction behavior. Despite efforts by developers to model road dynamics for evaluating Autonomous Driving systems (ADS), safety concerns under accidental and catastrophic road conditions have been overlooked. Firstly, to tackle this, this paper proposes extending feature variables for catastrophic scenarios using Domain-Specific Modeling Language (DSML). Introducing the Accidental and Catastrophic Automatic Driving Scenario Modeling Language (AC-ADSML) aims to accurately model ADS behavior in accidental and catastrophic road conditions. the AC-ADSML meta-model categorizes scenario variables and specifies abstract and concrete syntax along with operational semantics. Secondly, it is then transformed into Networks of Stochastic Hybrid Automata (NSHA) following ATL rules. the CARLA simulator is employed to replicate urban driving scenarios during natural disasters with PCTL scenario specifications. Model security can be verified using UPP AAL-SMC. Finally, an autonomous vehicle with adaptive cruise control is used as an example to verify the safety of the proposed model under different road condition parameters. © 2024 IEEE.

关键词： Stochastic systems

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Remote controlled Individuals? the Future of Neuralink: Ethical Perspectives on the Human-computer Interactions 24

Remote Controlled Individuals? The Future of Neuralink: Ethi...

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24th international conference on Enterprise Information systems (ICEIS)

作者： Cernat, Maria Bortun, Dumitru Matei, Corina Sorana Natl Sch Polit Sci & Adm Commun & Publ Relat Dept Bucharest Romania Titu Maiorescu Univ Commun & Publ Relat Dept Bucharest Romania

ISBN: (纸本)9789897585692

In an experiment presented to the public, a monkey with a Neuralink inserted in its brain is able interact directly with the computer. the Neuralink experiment opens the door to an extremely complex debate with questions ranging from ontology to epistemology. We explore the political economy of these cutting-edge technologies. What we aim to investigate are ethical questions, namely: is it ethical to install such a device in someone's brain and connect it to a computer? And who controls the computer, since it is plausible to assume that the communication could be bidirectional? We argue that this is in fact the key question we, as social scientists, IT specialists, and computer science specialists, have to ask and attempt to find answers to. Oftentimes, scientific discoveries could lead to disasters and in the era of "surveillance capitalism" we could easily imagine a scenario where companies are competing to gain access to our consciousness, and where our decisions are being marketed and sold to the higher bidder. Scientific discoveries do not occur in a purely rational society and questions of power, access, and control are vital for a future where technology and society are not at odds.

关键词： Human-computer Interaction Political Economy of Scientific Discoveries Ethics of computer science Research Commodification of Scientific Discoveries

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