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6th CAA International Conference on Vehicular control and Intelligence, CVCI 2022

作者： Cui, Zhihao Li, Meng Huang, Yanjun Wang, Yulei Chen, Hong Clean Energy Automotive Engineering Center School of Automotive Studies Tongji University Shanghai China Tongji University Department of Control Science and Engineering Shanghai China Clean Energy Automotive Engineering Center Shanghai Research Institute for Intelligent Autonomous Systems School of Automotive Studies Tongji University Shanghai China Shanghai Research Institute for Autonomous Systems Tongji University Department of Control Science and Engineering Shanghai China Clean Energy Automotive Engineering Center Shanghai Research Institute for Autonomous Systems Tongji University Department of Control Science and Engineering Shanghai China

ISBN: (数字)9781665453745

ISBN: (纸本)9781665453745

Decision-making for autonomous vehicles is critical to achieving safe and efficient autonomous driving. In recent years, deep reinforcement learning (DRL) techniques have emerged as the most promising way to enable intelligent decision-making. However, DRL with 'black box' nature is not widely understood by humans, thus hindering their social acceptance. In this paper, we combine SHapley Additive exPlanation (SHAP) and random forest (RF) techniques to bring transparency to decision-making obtained by DRL. Specifically, we first implement decision-making of autonomous vehicles following in discrete action space based on DRL algorithm with the goal of safety and efficiency. Then we use the SHAP technique to simplify the feature space, which shows that relative distance, longitudinal speed of the ego vehicle, and longitudinal speed of the proceeding vehicle have a critical impact on vehicle following task. Finally, we collect the state-action pairs generated by the DRL model and perform feature filtering, and fit the decision model with an interpretable RF model. The simulation results show that the RF model achieves the behavioral explanation of autonomous vehicle following. © 2022 IEEE.

关键词： Autonomous vehicles

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Key Reduction of McEliece's Cryptosystem Using List Decoding

Key Reduction of McEliece's Cryptosystem Using List Decoding

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IEEE International Symposium on Information Theory (ISIT)

作者： Barbier, Morgan Barreto, Paulo S. L. M. Computer Science Laboratory of École Polytechnique LIX INRIA Saclay Île France Department of Computer and Digital Systems Engineering Escola Politécnica University of São Paulo Brazil

ISBN: (纸本)9781457705953

Different variants of the code-based McEliece cryptosystem were proposed to reduce the size of the public key. All these variants use very structured codes, which open the door to new attacks exploiting the underlying structure. In this paper, we show that the quasi-dyadic variant can be designed to resist all known attacks. In light of a new study on list decoding algorithms for binary Goppa codes, we explain, as already suggested by Bernstein, Lange and Peters, how to increase the security level for given public keysizes. Using the state-of-the-art list decoding algorithm instead of unique decoding, we exhibit a keysize gain of about 4% for the standard McEliece cryptosystem and up to 21% for the adjusted quasi-dyadic variant.

关键词： computer science Decoding Goppa codes Polynomials Public key binary Goppa codes binary codes code-based McEliece cryptosystem decoding decoding algorithms public key cryptography public key size rduction quasidyadic variant security level state-of-the-art list decoding algorithm

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Classification of Retroviruses Based on Genomic Data Using RVGC

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computers, Materials & Continua 2021年第12期69卷 3829-3844页

作者： Khalid Mahmood Aamir Muhammad Bilal Muhammad Ramzan Muhammad Attique Khan Yunyoung Nam Seifedine Kadry Department of CS&IT University of SargodhaSargodha40100Pakistan Department of CS&IT University of MianwaliMianwali42200Pakistan School of Systems and Technology University of Management and TechnologyLahore54782Pakistan Department of Computer Science HITEC University TaxilaTaxilaPakistan Department of Computer Science and Engineering Soonchunhyang UniversityAsanKorea Faculty of Applied Computing and Technology Noroff University CollegeKristiansandNorway

Retroviruses are a large group of infectious agents with similar virion structures and replication ***,cancer,neurologic disorders,and other clinical conditions can all be fatal due to retrovirus *** of retroviruses by genome sequence is a biological problem that benefits from computational *** National Center for Biotechnology Information(NCBI)promotes science and health by making biomedical and genomic data available to the *** research aims to classify the different types of rotavirus genome sequences available at the ***,nucleotide pattern occurrences are counted in the given genome sequences at the preprocessing *** on some significant results,the number of features used for classification is reduced to *** classification shall be carried out in two *** first phase of classification shall select only two *** data in the first phase is transferred to the next phase,where the final decision is taken with the remaining three *** data sets of animals and human retroviruses are selected;the training data set is used to minimize the classifier’s number and training;the validation data set is used to validate the *** performance of the classifier is analyzed using the test data ***,we use decision tree,naive Bayes,knearest neighbors,and vector support machines to compare *** results show that the proposed approach performs better than the existing methods for the retrovirus’s imbalanced genome-sequence dataset.

关键词： Retroviruses machine learning bioinformatics classification

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Rule and Encryption based Secure Routing for Internet of Vehicle Networks 2

Rule and Encryption based Secure Routing for Internet of Veh...

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2nd IEEE International Conference on Networking and Communications, ICNWC 2024

作者： Anand, M. Muthurajkumar, S. Selvi, M. Thangaramya, K. Svn, Santhosh Kumar Kannan, A. Anna University Madras Institute of Technolog Department of Computer Technology Chennai India Vellore Institute of Technology School of Computer Science and Engineering Vellore India Vellore Institute of Technology School of Computer Science Engineering and Information Systems Vellore India

ISBN: (纸本)9798350365269

The Internet of Vehicles (IoV) has become one challenging communication technology in the current internet world. IoV enables real-time data exchange between vehicles, road infrastructures, and mobile communication devices and hence it helps in information exchange to vehicle drivers and the passengers. In IoV, Cybersecurity threats including Denial-of-Service (DoS) attacks are present and it compromises the security in communication among the vehicles and the passengers. Therefore, it is needed to develop a robust security mechanism that can protect the data communicated through routing in IoV. The inclusion of Encryption and Signature verification techniques in the routing algorithm will enhance the security. This paper proposes a Rule with Encryption-Oriented Secure Routing Protocol (REO-SRP) is proposed using clustering and RSA encryption with DSA Digital signature verification with rules for routing. Here, routing is performed after encryption of data and analysis of other vehicles using rules for reliable and secured data delivery. © 2024 IEEE.

关键词： Vehicles

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Circularity Reinforcement of Critical Raw Materials in Europe: A Case of Niobium

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Circular Economy and Sustainability 2024年第4期4卷 2449-2472页

作者： von Rennenberg, Theresa Yu, Yifei Fraccascia, Luca Yazan, Devrim Murat Department of Industrial Engineering and Business Information Systems University of Twente Drienerlolaan 5 Enschede 7522 NB Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Via Ariosto 25 Rome 00185 Italy

Critical Raw Materials attract increasing attention due to their depleting reserves and low recyclability. Niobium, one of the most rare and vital elements, is primarily found in Brazil. This research explores the potential impact of Circular Economy (CE) strategies on mitigating niobium's criticality within Europe. First, a niobium supply chain is designed and analysed by Enterprise Input–Output modelling. Second, the supply risk is calculated based on the criticality matrix proposed by the European Commission under three scenarios associated with resources, technologies, and policies. The results show that urban mining is a potential solution to reduce niobium’s criticality and mitigate its environmental impacts. A higher recycling input rate and/or a mix of recycling and substitution strategies is necessary to offset niobium’s criticality. Aligned with the CE action plan, the research offers a scientific foundation to strategically prevent the risk of niobium supply shortages. © The Author(s) 2024.

关键词： Circular economy Critical raw materials Enterprise input–output Niobium supply chain Scenario analysis

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The structure of intrinsic complexity of learning 2nd

The structure of intrinsic complexity of learning

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2nd European Conference on Computational Learning Theory, EuroCOLT 1995

作者： Jain, Sanjay Sharma, Arun Department of Information Systems and Computer Science National University of Singapore Singapore0511 Singapore School of Computer Science and Engineering The University of New South Wales SydneyNSW2052 Australia

ISBN: (纸本)9783540591191

Recently, a new approach to the study of "intrinsic" complexity of learning has originated in the work of Freivalds, and has been investigated for identification in the limit of functions by Freivalds, Kin-ber, and Smith and for identification in the limit of languages by Jain and Sharma. Instead of concentrating on the complexity of the learning algorithm, this approach uses the notion of reducibility to investigate the complexity of the concept classes being learned. Three representative classes have been presented that classify learning problems of increasing difficulty. (a) Classes that can be learned by machines that confirm their success (singleton languages). (b) Classes that can be learned by machines that cannot confirm their success but can provide an upper bound on the number of mind changes after inspecting an element of the language (pattern languages). (c) Classes that can be learned by machines that can neither confirm success nor can provide an upper bound on the number of mind changes (finite languages). The present paper shows that there is an infinite hierarchy of language classes that represent learning problems of increasing difficulty. Language classes constituting this hierarchy are languages with bounded cardinality, and it can be shown that collections of languages that can be identified using bounded number of mind changes are reducible to the classes in this hierarchy. It is also shown that language classes in this hierarchy are incomparable, under the reductions introduced, to the collection ofpattern languages. The structure of intrinsic complexity is shown to be rich as any finite, acyclic, directed graph can be embedded in this structure. However, it is also established that this structure is not dense. © Springer-Verlag Berlin Heidelberg 1995.

关键词： Learning algorithms

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A compiler-in-the-loop framework to explore Horizontally Partitioned Cache architectures

A compiler-in-the-loop framework to explore Horizontally Par...

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2008 Asia and South Pacific Design Automation Conference, ASP-DAC

作者： Shrivastava, Aviral Issenin, Ilya Dutt, Nikil Compiler and Microarchitecture Labs Department of Computer Science and Engineering Arizona State University Tempe AZ United States Center for Embedded Computer Systems Department of Information and Computer Science University of California Irvine Irvine CA United States

ISBN: (纸本)9781424419227

Horizontally Partitioned Caches (HPCs) are a promising architectural feature to reduce the energy consumption of the memory subsystem. However, the energy reduction obtained using HPC architectures is very sensitive to the HPC parameters. Therefore it is very important to explore the HPC design space and carefully choose the HPC parameters that result in minimum energy consumption for the application. However, since in HPC architectures, the compiler has a significant impact on the energy consumption of the memory subsystem, it is extremely important to include compiler while deciding the HPC design parameters. While there has been no previous approaches to HPC design exploration, existing cache design space exploration methodologies do not include the compiler effects during DSE. In this paper, we present a Compiler-in-the-Loop (CIL) Design Space Exploration (DSE) methodology to explore and decide the HPC design parameters. Our experimental results on HP iPAQ h4300-like memory subsystem running benchmarks from the MiBench suite demonstrate that CIL DSE can discover HPC configurations with up to 80% lesser energy consumption than the HPC configuration in the iPAQ. In contrast, tradition simulation-only exploration can discover HPC design parameters that result in only 57% memory subsystem energy reduction. Finally our hybrid CIL DSE heuristic saves 67% of the exploration time as compared to the exhaustive exploration, while providing maximum possible energy savings on our set of benchmarks. ©2008 IEEE.

关键词： Energy utilization

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Quality and Context-Aware Smart Health Care: Evaluating the Cost-Quality Dynamics

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IEEE systems, Man and Cybernetics Magazine 2016年第2期2卷 15-25页

作者： Roy, Nirmalya Julien, Christine Misra, Archan Das, Sajal K. Information Systems University of Maryland Baltimore County BaltimoreMD21250 United States Department of Electrical and Computer Engineering University of Texas at Austin AustinTX United States School of Information Systems Singapore Management University Singapore Singapore Singapore Department of Computer Science Missouri University of Science and Technology RollaMO United States

Many emerging pervasive health-care applications require the determination of a variety of context attributes of an individual's activities and medical parameters and her surrounding environment. Context is a high-level representation of an entity's state, which captures activities, relationships, capabilities, etc. In practice, high-level context measures are often difficult to sense from a single data source and must instead be inferred using multiple sensors embedded in the environment. A key challenge in deploying context-driven health-care applications involves energy-efficient determination or inference of high-level context information from low-level sensor data streams. Because this abstraction has the potential to reduce the quality of the context information, it is also necessary to model the tradeoff between the cost of sensor data collection and the quality of the inferred context. This article describes a model of context inference in pervasive computing, the associated research challenges, and the significant practical impact of intelligent use of such context in pervasive health-care environments. © 2015 IEEE.

关键词： Ubiquitous computing

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An intelligent assistant for power plants based on factored MDPs

An intelligent assistant for power plants based on factored ...

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2009 15th International Conference on Intelligent System Applications to Power systems, ISAP '09

作者： Reyes, Alberto Spaan, Matthijs T. J. Sucar, L. Enrique Instrumentation and Control Department Instituto de Investigaciones Eléctricas Cuernavaca Mexico Institute for Systems and Robotics Lisbon Portugal Computer Science Department INAOE Puebla Mexico

ISBN: (纸本)9781424450985

Making good operation decisions during abnormal power plant conditions represents in many cases the possibility to avoid a unit trip or having economical losses. This paper introduces AsistO, an intelligent assistant for the decision support based on decision theoretic planning techniques. It provides power plant operators with useful recommendations to (i) maintain a plant running under safe conditions, or (ii) deal with process transients when an unexpected event occurs. We present the formalism of Markov decision processes as the core of the intelligent assistant which uses a factored representation of plant states. We also show a very intutive algorithm to approximate decision models based on training data collected through random exploration routines in a simulated environment. We have tested our system in the steam generation system of a combined power plant to deal with load disturbances. © 2009 IEEE.

关键词： Markov processes

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The SWH-Analytics Framework 2

The SWH-Analytics Framework

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2nd Italian Conference on Big Data and Data science, ITADATA 2023

作者： Antelmi, Alessia Torquati, Massimo Gregori, Daniele Polzella, Francesco Spinatelli, Gianmarco Aldinucci, Marco Computer Science Department University of Torino Italy Computer Science Department University of Pisa Italy HPC-KTT national lab CINI Italy E4 Computer Engineering SpA Italy Zerodivision systems Srl Italy

The Software Heritage (SWH) dataset serves as a vast repository for open-source code, with the ambitious goal of preserving all publicly available open-source projects. Despite being designed to effectively archive project files, its size of nearly 1 petabyte presents challenges in efficiently supporting Big Data MapReduce or AI systems. To address this disparity and enable seamless custom analytics on the SWH dataset, we present the SWH-Analytics (SWHA) architecture. This development environment quickly and transparently runs custom analytic applications on open-source software data preserved over time by SWH. © 2023 Copyright for this paper by its authors.

关键词： Open source software

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