This LNCS volume contains the papers presented at SEAL 2008, the 7th Int- nationalConference on Simulated Evolutionand Learning,held December 7–10, 2008, in Melbourne, Australia. SEAL is a prestigious international c...
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ISBN:
(数字)9783540896944
ISBN:
(纸本)9783540896937
This LNCS volume contains the papers presented at SEAL 2008, the 7th Int- nationalConference on Simulated Evolutionand Learning,held December 7–10, 2008, in Melbourne, Australia. SEAL is a prestigious international conference series in evolutionary computation and learning. This biennial event was ?rst held in Seoul, Korea, in 1996, and then in Canberra, Australia (1998), Nagoya, Japan (2000), Singapore (2002), Busan, Korea (2004), and Hefei, China (2006). SEAL 2008 received 140 paper submissions from more than 30 countries. After a rigorous peer-review process involving at least 3 reviews for each paper (i.e., over 420 reviews in total), the best 65 papers were selected to be presented at the conference and included in this volume, resulting in an acceptance rate of about 46%. The papers included in this volume cover a wide range of topics in simulated evolution and learning: from evolutionarylearning to evolutionary optimization, from hybrid systems to adaptive systems, from theoretical issues to real-world applications. They represent some of the latest and best research in simulated evolution and learning in the world.
Bug detection in Hardware Design Languages (HDLs) is an important problem in the System-on-Chip (SoC) development cycle. It is crucial to find defects at the earliest stage possible. While most fault localization requ...
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Bug detection in Hardware Design Languages (HDLs) is an important problem in the System-on-Chip (SoC) development cycle. It is crucial to find defects at the earliest stage possible. While most fault localization requires the use of ‘tests’ (e.g. test benches, fuzzing and assertions) and a simulation or emulation framework, the advent of Large Language Models (LLMs) provides an opportunity for a test-free fault localization approach. This paper proposes such a tool, called FLAG, which can identify functional and security defects in Register Transfer Level (RTL) code without synthesis or simulation. FLAG combines syntactic and generative AI techniques to implement fault localization in RTL code. It takes an RTL design as an input and outputs a set of line(s) that likely contain defects. It targets elements of RTL code most likely to contain bugs through static analysis means and then implements token-level and line-level analysis to obtain differences in original code and code generated by LLM to identify a line as buggy or not. The token-level approach evaluates each generated token (one at a time) and the line level approach evaluates the entire line generated by the LLM. We evaluate our approach on a corpus of synthetic and real-world bugs, of both functional and security related issues, in Verilog and SystemVerilog. Using line-level analysis, FLAG can identify 38 out of 120 real-world bugs and using token-level analysis, FLAG can identify 32 out of 81 synthetic bugs through the top-5 most likely bug locations identified without tests.
This Three-Volume-Set constitutes the refereed proceedings of the Second International Conference on softwareengineering and computer Systems, ICSECS 2011, held in Kuantan, Malaysia, in June 2011.The 190 revised full...
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ISBN:
(数字)9783642221705
ISBN:
(纸本)9783642221699
This Three-Volume-Set constitutes the refereed proceedings of the Second International Conference on softwareengineering and computer Systems, ICSECS 2011, held in Kuantan, Malaysia, in June 2011.
The 190 revised full papers presented together with invited papers in the three volumes were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on softwareengineering; network; bioinformatics and e-health; biometrics technologies; Web engineering; neural network; parallel and distributed; e-learning; ontology; image processing; information and data management; engineering; software security; graphics and multimedia; databases; algorithms; signal processing; software design/testing; e- technology; ad hoc networks; social networks; software process modeling; miscellaneous topics in softwareengineering and computer systems.
This volume contains a selection of revised papers that were presented at the software Aspects of Robotic Systems, SARS 2011 Workshop and the Machine Learning for System Construction, MLSC 2011 Workshop, held during O...
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ISBN:
(数字)9783642347818
ISBN:
(纸本)9783642347801
This volume contains a selection of revised papers that were presented at the software Aspects of Robotic Systems, SARS 2011 Workshop and the Machine Learning for System Construction, MLSC 2011 Workshop, held during October 17-18 in Vienna, Austria, under the auspices of the International Symposium Series on Leveraging Applications of Formal Methods, Verification, and Validation, ISoLA. The topics covered by the papers of the SARS and the MLSC workshop demonstrate the breadth and the richness of the respective fields of the two workshops stretching from robot programming to languages and compilation techniques, to real-time and fault tolerance, to dependability, software architectures, computer vision, cognitive robotics, multi-robot-coordination, and simulation to bio-inspired algorithms, and from machine learning for anomaly detection, to model construction in software product lines to classification of web service interfaces. In addition the SARS workshop hosted a special session on the recently launched KOROS project on collaborating robot systems that is borne by a consortium of researchers of the faculties of architecture and planning, computer science, electrical engineering and information technology, and mechanical and industrial engineering at the Vienna University of Technology. The four papers devoted to this session highlight important research directions pursued in this interdisciplinary research project.
This book constitutes the refereed proceedings of the 6th Mexican Conference on Pattern Recognition, MCPR 2014, held in Cancun, Mexico, in June 2014. The 39 revised full papers presented were carefully reviewed and se...
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ISBN:
(数字)9783319074917
ISBN:
(纸本)9783319074900
This book constitutes the refereed proceedings of the 6th Mexican Conference on Pattern Recognition, MCPR 2014, held in Cancun, Mexico, in June 2014. The 39 revised full papers presented were carefully reviewed and selected from 68 submissions and are organized in topical sections on pattern recognition and artificial intelligence; computer vision; image processing and analysis; animal biometric recognition and applications of pattern recognition.
ItwasourpleasuretoholdtheInternationalWorkshoponSecurity2006(IWSEC 2006) this year in Kyoto and to publish the proceedings as a volume of the Lecture Notes in computer Science series. The workshop was our ?rst trial i...
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ISBN:
(数字)9783540477006
ISBN:
(纸本)9783540476993
ItwasourpleasuretoholdtheInternationalWorkshoponSecurity2006(IWSEC 2006) this year in Kyoto and to publish the proceedings as a volume of the Lecture Notes in computer Science series. The workshop was our ?rst trial in that two major academic society groups on security in Japan, viz. ISEC and CSEC, jointly organized it; ISEC is a te- nical group on information security of the Institute of Electronics, Information and Communication Engineers (IEICE), and CSEC is a special interest group on computer security of the Information Processing Society of Japan (IPSJ). It was Ryoichi Sasaki, the former head of CSEC, who proposed holding such an international workshop in Japan for the ?rst time, two years ago. The two groups supported his idea and started organizing the workshop. CSEC has its annual domestic symposium, the computer Security Symposium (CSS), in - tober for three days, and we decided to organize the workshop prior to CSS this year. The initial aim of the workshop was primarily to provide young researchers with the opportunity to present their work in English. However, due to more submissions than we had anticipated, the quality of the accepted papers became far better than we had expected. Theconferencereceived147submissions,outofwhichtheprogramcommittee selected 30 for presentation. These proceedings contain the ?nal versions of the accepted papers, which the authors ?nalized on the basis of comments from the reviewers. Since these revisions were not subject to editorial review, the authors bear full responsibility for the contents of their papers.
The advancement of the Internet of Medical Things (IoMT) has led to the emergence of various health and emotion care services, e.g., health monitoring. To cater to increasing computational requirements of IoMT service...
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The advancement of the Internet of Medical Things (IoMT) has led to the emergence of various health and emotion care services, e.g., health monitoring. To cater to increasing computational requirements of IoMT services, Mobile Edge Computing (MEC) has emerged as an indispensable technology in smart health. Benefiting from the cost-effectiveness of deployment, unmanned aerial vehicles (UAVs) equipped with MEC servers in Non-Orthogonal Multiple Access (NOMA) have emerged as a promising solution for providing smart health services in proximity to medical devices (MDs). However, the escalating number of MDs and the limited availability of communication resources of UAVs give rise to a significant increase in transmission latency. Moreover, due to the limited communication range of UAVs, the geographically-distributed MDs lead to workload imbalance of UAVs, which deteriorates the service response delay. To this end, this paper proposes a UAV-enabled Distributed computation Offloading and Power control method with Multi-Agent, named DOPMA, for NOMA-based IoMT environment. Specifically, this paper introduces computation and transmission queue models to analyze the dynamic characteristics of task execution latency and energy consumption. Moreover, a credit assignment scheme-based reward function is designed considering both system-level rewards and rewards tailored to each MD, and an improved multi-agent deep deterministic policy gradient algorithm is developed to derive offloading and power control decisions independently. Extensive simulations demonstrate that the proposed method outperforms existing schemes, achieving \(7.1\%\) reduction in energy consumption and \(16\%\) decrease in average delay.
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