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7th International Conference on Computational Science (ICCS 2007)

作者： Kim, Moonseong Kang, Minseok Choo, Hyunseung Yang, Jong S. Bang, Young-Cheol School of Info. and Comm. Engineering Sungkyunkwan University South Korea Dep. of Computer Engineering Korea Polytechnic University South Korea Korea Institute of Industrial Technology Evaluation and Planning South Korea

ISBN: (纸本)9783540725879

In this paper, we study the problem of constructing minimum cost group multicast trees with bandwidth reservations. Our algorithm uses multiple candidate paths to select a path from source to each destination member in each multicast tree construction. We show that our proposed algorithm performs better in terms of total tree cost for real life networks over well-known algorithm GKMB. The enhancement is up to about 10% similar to 25% in terms of normalized surcharge for the GKMB tree cost.

关键词： group multicast routing algorithm minimum Steiner trees group KMB (GKMB) algorithm and minimum cost multicast tree (MCMT) algorithm

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A Smart Fuzzing Method for Detecting Heap-Based Buffer Overflow in Executable Codes

A Smart Fuzzing Method for Detecting Heap-Based Buffer Overf...

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Pacific Rim International Symposium on dep.ndable Computing

作者： Maryam Mouzarani Babak Sadeghiyan Mohammad Zolfaghari Dep. of Computer Engineering & Information Technology Amirkabir University of Technology Tehran Iran Dep. of Electronic & Computer Engineering Isfahan University of Technology Isfahan Iran

ISBN: (纸本)9781467393775

This paper presents a new concolic execution-based smart fuzzer for detecting heap-based buffer overflow in the executable codes. The proposed fuzzer executes the target program with concrete input data and calculates the constraints of the executed path symbolically. The path constraints are used to generate test data that traverse new execution paths in the target program. For each executed path, the fuzzer also calculates heap-based buffer overflow constraints. These constraints determine what input data may cause heap-based buffer overflow in the executed path. By combining the path and vulnerability constraints new test data are generated, if possible, that traverse a specific execution path and activate specific vulnerability in that path. We implemented the proposed smart fuzzer as a plug-in for Valgrind framework. The implemented fuzzer is tested on different groups of test programs. The experiments demonstrate that the fuzzer can detect the vulnerabilities in these programs accurately.

关键词： Concrete Instruments Software Resource management computers Electronic mail Testing

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Granularity of Knowledge Computed by Genetic Algorithms Based on Rough Sets Theory

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南昌工程学院学报 2006年第2期25卷 97-101,121页

作者： Wenyuan Yang Xiaoping Ye Yong Tang Pingping Wei Dep. of Computer Engineering Zhangzhou Institute of Technology Zhangzhou 363000China Dep. of Computer Science Sun Yat-Sen University Guangzhou 510275China Dep. of Math and Computer Science Guizhou Institute of Education Guiyang 550003China

Rough set philosophy hinges on the granularity of data, which is used to build all its basic concepts, like approximations, dep.ndencies, reduction etc. Genetic Algorithms provides a general frame to optimize problem solution of complex system without dep.nding on the domain of *** is robust to many kinds of *** paper combines Genetic Algorithms and rough sets theory to compute granular of knowledge through an example of information table. The combination enable us to compute granular of knowledge *** is also useful for computer auto-computing and information processing.

关键词： granularity of knowledge Genetic Algorithms Pawlak Model Rough Set Theory information table

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Exploring Genetic Programming Models in computer-Aided Diagnosis of Skin Cancer Images 13

Exploring Genetic Programming Models in Computer-Aided Diagn...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Ain, Qurrat Ui Al-Sahaf, Harith Xue, Bing Zhang, Mengjie School of Engineering and Computer Science Victoria University of Wellington PO Box 600 Wellington New Zealand College of Engineering and Info. Technology AlShaab University Dep. of Cybersecurity Engineering Baghdad Iraq

ISBN: (纸本)9798350308365

Extracting important information from complex skin lesion images is vital to effectively distinguish between different types of skin cancer images. In addition to providing high classification performance, such computer-aided diagnostic methods are needed where the models are interpretable and can provide knowledge about the discriminative features in skin lesion images. This underlying information can significantly assist dermatologists in identifying a particular stage or type of cancer. With its flexible representation and global search abilities, Genetic Programming (GP) is an ideal learning al-gorithm to evolve interpretable models and identify important features with significant information to discriminate between skin cancer classes. This paper provides an in-dep.h analysis of a recent GP-based feature learning method where different well-developed feature descriptors are integrated into the learning algorithms to extract high-level features for skin cancer image classification. The study explores the effectiveness of utilizing feature learning for this complex task and designing program structure to suit the problem domain as it has shown promising results compared to commonly used feature descriptors and an existing GP-based feature learning method developed for general image classification. This study analyzes the GP-evolved models to identify the prominent features and most effective feature descriptors important for the classification of these skin cancer images. The evolved models are interpretable, they provide knowledge that can assist dermatologists in making diagnoses in real-time clinical situations by identifying prominent skin cancer characteristics captured by the feature descriptors and learned during the evolutionary process. © 2024 IEEE.

关键词： Genetic programming

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Energy management in mobile robotics system based on biologically inspired honeybees behavior

Energy management in mobile robotics system based on biologi...

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2011 IEEE Conference on computer Applications and Industrial Electronics, ICCAIE 2011

作者： Faisul Arif, A. Ramli, Abdul Rahman Samsudin, Khairulmizam Hashim, S.J. Institute of Advanced Technology Universiti Putra Malaysia Selangor Malaysia Dep. of Computer and Communication Systems Eng. Faculty of Engineering Universiti Putra Malaysia Selangor Malaysia

ISBN: (纸本)9781457720581

Operating multiple mobile robots while having finite amount of energy is one of limitation on doing a task in long term. In this work, a decentralized controller system based on inspired of swarm honeybees in foraging food's behavior has been developed and applied on the mobile robot. This system is simulated in Player/Stage. The algorithm is divided by working robot and foraging robot. The change of behaviors are based on remaining energy, which is defined as energy for worker and energy for forager. Mobile robots will be working while energy is enough and then, autonomously looking for energy source when battery in state of energy for forager. The information of position for power source energy that is getting from a forager robot will be shared with other mobile robots by local communication. In the player stage simulator, the communication process is done through UDP port. This experimental result shows that mobile robot is able to continuously work, forage, recharge and back to work by themselves without having intervention by human. © 2011 IEEE.

关键词： Mobile robots

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Big Data from Space for Precision Agriculture Applications 11

Big Data from Space for Precision Agriculture Applications

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11th International Symposium on Digital Earth, ISDE 2019

作者： Bovolo, F. Bruzzone, L. Fernández-Prieto, D. Paris, C. Solano-Correa, Y.T. Volden, E. Zanetti, M. Fondazione Bruno Kessler Center for Information and Communication Technology Trento Italy Dep. of Information Engineering and Computer Science University of Trento Trento Italy ESRIN Frascati Italy

This paper presents an approach for precision agriculture large scale applications based on the analysis of big data consisting in Satellite Image Time Series (SITS) acquired by ESA Sentinel-2 (S2) satellite constellation. The approach has been developed in the framework of the ESA SEOM - Scientific Exploitation of Operational Missions - S2-4Sci Land and Water project [1]. To focus only on agricultural areas, images are first filtered based on a land cover (LC) map that is generated by updating available old maps by means of recent images. Then S2 SITS are used to analyse agricultural areas. Two macro challenges are therefore considered: (i) automatic update of LC maps and generation of agricultural areas mask;and (ii) unsupervised multi-temporal (MT) fine characterization of land plots. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Precision agriculture

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Vegetation and Drought Trends in Sweden's Mälardalen Region-Year-on-Year Comparison by Gaussian Process Regression

Vegetation and Drought Trends in Sweden's Mälardalen Region...

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2020 Swedish Workshop on Data Science, SweDS 2020

作者： Paszkowsky, Nuria Agues Brannvall, Rickard Carlstedt, Johan Milz, Mathias Kovacs, Gyorgy Liwicki, Marcus Unit for Data Center Systems and Applied Data Science Research Institutes of Sweden Sweden Luleå University of Technology Dep. of Computer Science Electrical and Space Engineering Sweden

ISBN: (纸本)9781728192048

This article describes analytical work carried out in a pilot project for the Swedish Space Data Lab (SSDL), which focused on monitoring drought in the Mälardalen region in central Sweden. Normalized Difference Vegetation Index (NDVI) and the Moisture Stress Index (MSI)-commonly used to analyse drought- A re estimated from Sentinel 2 satellite data and averaged over a selection of seven grassland areas of interest. To derive a complete time-series over a season that interpolates over days with missing data, we use Gaussian Process Regression, a technique from multivariate Bayesian analysis. The analysis show significant differences at 95% confidence for five out of seven areas when comparing the peak drought period in the dry year 2018 compared to the corresponding period in 2019. A cross-validation analysis indicates that the model parameter estimates are robust for temporal covariance structure (while inconclusive for the spatial dimensions). There were no signs of over-fitting when comparing in-sample and out-of-sample RMSE. © 2020 IEEE.

关键词： Remote sensing

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Feature selection methods in persian sentiment analysis

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18th International Conference on Application of Natural Language to Information Systems, NLDB 2013

作者： Saraee, Mohamad Bagheri, Ayoub School of Computing Science and Engineering University of Salford Manchester United Kingdom Intelligent Database Data Mining and Bioinformatics Lab Electrical and Computer Engineering Dep. Isfahan University of Technology Isfahan Iran

ISBN: (纸本)9783642388231

With the enormous growth of digital content in internet, various types of online reviews such as product and movie reviews present a wealth of subjective information that can be very helpful for potential users. Sentiment analysis aims to use automated tools to detect subjective information from reviews. Up to now as there are few researches conducted on feature selection in sentiment analysis, there are very rare works for Persian sentiment analysis. This paper considers the problem of sentiment classification using different feature selection methods for online customer reviews in Persian language. Three of the challenges of Persian text are using of a wide variety of declensional suffixes, different word spacing and many informal or colloquial words. In this paper we study these challenges by proposing a model for sentiment classification of Persian review documents. The proposed model is based on stemming and feature selection and is employed Naive Bayes algorithm for classification. We evaluate the performance of the model on a collection of cellphone reviews, where the results show the effectiveness of the proposed approaches. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Feature Selection

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Finite state machine IP watermarking: A tutorial

Finite state machine IP watermarking: A tutorial

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1st NASA/ESA Conference on Adaptive Hardware and Systems

作者： Abdel-Hamid, Amr T. Tahar, Sofiene Aboulhamid, El Mostapha Electrical and Computer Engineering Department Institute of Technology West Virginia University Montgomery United States Electrical and Computer Engineering Department Concordia University Montreal Canada Dep. d'Informatique et de Recherche Operationnelle Université de Montréal Montreal Canada

ISBN: (纸本)0769526144

Sharing Intellectual Property (IP) blocks in today's competitive market poses significant high security risks. In this paper, we present a tutorial for a watermarking approach based on the embedding of the ownership proof as part of the IP design's finite state machine (FSM). It utilizes coinciding as well as unused transitions in the state transition graph of the design. Based on this approach, we have developed a robust watermarking framework, used for copyright protection. The developed technique increases the robustness of the watermark and allows a secure implementation, hence enabling the development of the first public-key IP watermarking scheme at the FSM level. In order to integrate these algorithms in the design cycle of industrial projects, we extend the above techniques to enable the watermarking of hierarchical finite state machines (HFSMs).

关键词： Digital watermarking

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Minimization of wind power curtailment using dynamic line rating 10

Minimization of wind power curtailment using dynamic line ra...

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10th IEEE PES Innovative Smart Grid Technologies Europe, ISGT-Europe 2020

作者： Chakrapani Manakari, Vageesh Thengius, Sandra Tammanur Ravi, Akshaya Morozovska, Kateryna Hilber, Patrik KTH Royal Institute of Technology Div. of Electric Power and Energy Systems School of Electrical Engineering and Computer Science Stockholm Sweden Heimdall Power AS Oslo Norway KTH Royal Institute of Technology School of Electrical Engineering and Computer Science Dep. of Electromagnetic Engineering Stockholm Sweden

ISBN: (数字)9781728171005

ISBN: (纸本)9781728171005

Large scale penetration of wind power to the grid and unevenly spread power demand can result in the transmission system not being able to dispatch all the produced wind power, causing in wind power *** line rating (DLR) is a technology which uses thermal properties of overhead conductors and weather data to determine the real-time ampacity limits of transmission lines. In general, dynamic rating allows extending capacity limits of power lines and helps to remove congestion in the grid.(/p)(p This study looks into the possibility of using dynamic line rating for removing congestion in the power system to allow dispatching more wind power and minimize the need for curtailment. The results of case-studies have shown that DLR allows to significantly reduce the curtailment of generation, especially during winter, when wind production is highest and day time, when the power demand is the highest. © 2020 IEEE.

关键词： Wind power

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