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2011 22nd International Workshop on Database and Expert Systems Applications, DEXA 2011

作者： Szczodrak, Maciej Kotus, Jozef Kopaczewski, Krzysztof Lopatka, Kuba Czyzewski, Andrzej Krawczyk, Henryk Multimedia Systems Department Gdansk University of Technology Gdansk Poland Department of Computer Architecture Gdansk University of Technology Gdansk Poland

ISBN: (纸本)9780769544861

A concept and practical implementation of a crowd management system which acquires input data by the set of monitoring cameras is presented. Two leading threads are considered. First concerns the crowd behavior analysis. Second thread focuses on detection of a hold-ups in the doorway. The optical flow combined with soft computing methods (neural network) is employed to evaluate the type of crowd behavior, and fuzzy logic aids detection of the hold-ups. The experiments with the behavior classification algorithm were performed employing prepared repository of typical and untypical behavior recordings. The effectiveness of the analysis was assessed by comparing algorithmic processing results to a set of prepared reference data, which provides a description of behavior type occurring in each video frame. Application of parallel image processing and influence of parallelization on achieved performance is explained. Apart from the crowd management the behavior analysis may be used in automatic surveillance system deployed in a city area. © 2011 IEEE.

关键词： Fuzzy logic

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Adaptive Marine Predator Optimization Algorithm(AOMA)-Deep Supervised Learning Classification(DSLC)based IDS framework for MANET security

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Intelligent and Converged Networks 2024年第1期5卷 1-18页

作者： M.Sahaya Sheela A.Gnana Soundari Aditya Mudigonda C.Kalpana K.Suresh K.Somasundaram Yousef Farhaoui Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai 600069India Department of Computer Science and Engineering Saveetha School of EngineeringSIMATSChennai 602105India JNIAS School of Planning and Architecture Hyderabad 500034India Department of Computer Science and Engineering NPR College of Engineering and TechnologyNatham Dindigul 624401India Department of Computer Science and Engineering PSNA College of Engineering and TechnologyPoolangulathupatti 620009India Department of Computer Science and Engineering Sri Muthukumaran Institute of TechnologyChennai 600069India Department of Computer Science Moulay Ismail UniversityMeknes 5003Morocco

Due to the dynamic nature and node mobility,assuring the security of Mobile Ad-hoc Networks(MANET)is one of the difficult and challenging tasks *** MANET,the Intrusion Detection System(IDS)is crucial because it aids in the identification and detection of malicious attacks that impair the network’s regular *** machine learning and deep learning methodologies are used for this purpose in the conventional works to ensure increased security of ***,it still has significant flaws,including increased algorithmic complexity,lower system performance,and a higher rate of ***,the goal of this paper is to create an intelligent IDS framework for significantly enhancing MANET security through the use of deep learning ***,the min-max normalization model is applied to preprocess the given cyber-attack datasets for normalizing the attributes or fields,which increases the overall intrusion detection performance of ***,a novel Adaptive Marine Predator Optimization Algorithm(AOMA)is implemented to choose the optimal features for improving the speed and intrusion detection performance of ***,the Deep Supervise Learning Classification(DSLC)mechanism is utilized to predict and categorize the type of intrusion based on proper learning and training *** evaluation,the performance and results of the proposed AOMA-DSLC based IDS methodology is validated and compared using various performance measures and benchmarking datasets.

关键词： Intrusion Detection System(IDS) Security Mobile Ad-hoc Network(MANET) min-max normalization Adaptive Marine Predator Optimization Algorithm(AOMA) Deep Supervise Learning Classification(DSLC)

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Improving latency tolerance of network processors through simultaneous multithreading

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6th International Workshop on Advanced Parallel Processing Technologies, APPT 2005

作者： Liang, Bo An, Hong Lu, Fang Guo, Rui Department of Computer Science and Technology University of Science and Technology of China Hefei 230026 China Computer Architecture Laboratory Institute of Computing Technology Chinese Academy of Sciences Beijing 100086 China

ISBN: (纸本)3540296395

Existing multithreaded network processors architecture with multiple processing engines (PEs), aims at taking advantage of blocked multithreading technique which executes instructions of different user-defined threads in the same PE pipeline, in explicit and interleave way. Multiple PEs, each of which is a multithreaded processor core, process several packets in parallel to hide long memory access latency. Most of them are optimized for throughputs mostly in data-plane. In future network workloads, the boundaries between data-plane and control-plane become blurred, so that PEs are demanded not only wire speed packet forwarding on data-plane, but also highly intelligent and increased complex packet processing function on control-plane. In this paper, we analyze SMT's short latency tolerance potential when used in out-of-order and dynamic scheduling PE cores. We show in this paper that 2-4 issue SMT provides an excellent short memory and branch latency tolerance, which gain higher instructions throughout as well as much simpler structures. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Network protocols

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Expert mutation operators for the evolution of radial basis function neural networks

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6th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2001

作者： González, J. Rojas, I. Pomares, H. Salmerón, M. Department of Computer Architecture and Computer Technology University of Granada Campus de Fuen temev a GranadaE 18071 Spain

ISBN: (纸本)3540422358

This paper compares some m utationoperators containing expert knowledge about the problem of optimizing the parameters of a Radial Basis Function Neural Network. It is sho wn that the expert kno wledge is not abrays able to improve the results obtained by a blind evolutionary algorithm, and that the final results depend strongly on how the expert knowledge is utilized. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Radial basis function networks

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Two-Dimensional Error Estimation in Point Positioning with Fuzzy Logic

Two-Dimensional Error Estimation in Point Positioning with F...

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2018 International Conference on Artificial Intelligence and Data Processing, IDAP 2018

作者： Bülbül, Mehmet Akif Öztürk, Celal Ilçi, Veli Ozulu, Ibrahim Murat Computer Technology Department Hitit University Çorum Turkey Computer Engineering Department Erciyes University Kayseri Turkey Architecture and City Planning Department Hitit University Çorum Turkey

ISBN: (纸本)9781538668788

Developments in technology and computer aims to facilitate the human life. Every new technology developed by computer science is tried to integrate into systems. Rapidly developing satellite, navigation and geographic information systems also use computer science. The position information that these systems provide to people has had too much importance in recent years. The low margin of error in point position estimation has become a criterion for developed technologies. In this study, a model based on fuzzy logic is developed for estimation of point position error. With this derived model, point position error prediction has been determined and the accuracy of estimates of the system has been measured. © 2018 IEEE.

关键词： Fuzzy logic

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Big data-oriented energy prosumption service in smart community districts: a multi-case study perspective

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Energy Informatics 2019年第1期2卷 1-26页

作者： Anthony, Bokolo Petersen, Sobah Abbas Ahlers, Dirk Krogstie, John Livik, Klaus Department of Computer Science Norwegian University of Science and Technology NTNU TrondheimNO-7491 Norway Department of Architecture and Planning Norwegian University of Science and Technology Trondheim Norway Powel AS Klæbuveien 194 TrondheimNO-7037 Norway

The smart grid achieves bidirectional information and energy flow between energy consumer and utility grid, aiding energy users not only to utilize energy, but also to produce, sell, and share energy with other consumers or with the utility grid. This type of energy user is referred to as the "prosumer". Thus, prosumer management structures are important within energy market. However, prior studies on energy sustainability has paid little attention on prosumer involvement and management. Likewise, the continuous growth of cities has increased data processing complexity. Consequently, processing and analysis of historical, online, and real-time streaming data from energy sensors and metering devices has become a major issue in smart cities. Therefore, this research aims to present an architecture based on big data to improve energy prosumption in smart community districts by applying enterprise architecture approach grounded on The Open Group architecture Framework (TOGAF). Accordingly, qualitative methodology is adopted to collect data by employing case study by focus group interview from two energy companies in Norway to preliminarily validate the architecture. Findings from the case studies was demonstrated in ArchiMate modeling language to evaluate the applicability of the architecture. Moreover, findings from this study provides practical scenario that energy service providers can refer to in designing their own energy data platforms. Essentially, the architecture can be utilized as a guide to help municipalities and policy makers in creating approach for energy data analytics in smart community districts towards making decisions for future energy prosumption planning. © 2019, The Author(s).

关键词： Big data

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Parallel stochastic search for protein secondary structure prediction 5th

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5th International Conference on Parallel Processing and Applied Mathematics, PPAM 2003

作者： Robles, Victor Pérez, María S. Herves, Vanessa Peña, José M. Larrañaga, Pedro Department of Computer Architecture and Technology Technical University of Madrid Madrid Spain Department of Computer Science and Artificial Intelligence University of the Basque Country San Sebastián Spain

ISBN: (纸本)3540219463

Prediction of the secondary structure of a protein from its aminoacid sequence remains an important and difficult task. Up to this moment, three generations of Protein Secondary Structure Algorithms have been defined: The first generation is based on statistical information over single aminoacids, the second generation is based on windows of aminoacids-typically 11-21 aminoacids- and the third generation is based on the usage of evolutionary information. In this paper we propose the usage of naïve Bayes and Interval Estimation Naïve Bayes (IENB) -a new semi naïve Bayes approach- as suitable third generation methods for Protein Secondary Structure Prediction (PSSP). One of the main stages of IENB is based on a heuristic optimization, carried out by estimation of distribution algorithms (EDAs). EDAs are non-deterministic, stochastic and heuristic search strategies that belong to the evolutionary computation approaches. These algorithms under complex problems, like Protein Secondary Structure Prediction, require intensive calculation. This paper also introduces a parallel variant of IENB called PIENB (Parallel Interval Estimation Naïve Bayes). © Springer-Verlag Berlin Heidelberg 2004.

关键词： Evolutionary algorithms

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First-order gradient damage theory

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Applied Mathematics and Mechanics(English Edition) 2010年第8期31卷 987-994页

作者：赵冰郑颖人曾明华唐雪松李小纲 Department of Architectural Engineering Logistical Engineering University of the People's Liberation Army School of Civil Engineering and Architecture Changsha University of Science and Technology School of Mathematics and Computer Science Ningxia University

Taking the strain tensor, the scalar damage variable, and the damage gradient as the state variables of the Helmholtz free energy, the general expressions of the firstorder gradient damage constitutive equations are derived directly from the basic law of irreversible thermodynamics with the constitutive functional expansion method at the natural state. When the damage variable is equal to zero, the expressions can be simplified to the linear elastic constitutive equations. When the damage gradient vanishes, the expressions can be simplified to the classical damage constitutive equations based on the strain equivalence hypothesis. A one-dimensional problem is presented to indicate that the damage field changes from the non-periodic solutions to the spatial periodic-like solutions with stress increment. The peak value region develops a localization band. The onset mechanism of strain localization is proposed. Damage localization emerges after damage occurs for a short time. The width of the localization band is proportional to the internal characteristic length.

关键词： damage gradient damage localization thermodynamics constitutive functional expansion method Helmholtz free energy

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Evolutive identification of fuzzy systems for time-series prediction 7th

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7th International Conference on Parallel Problem Solving from Nature, PPSN 2002

作者： González, Jesús Rojas, Ignacio Pomares, Héctor Department of Computer Architecture and Computer Technology E.T.S. Ingeniería Informática University of Granada GranadaE. 18071 Spain

ISBN: (纸本)3540441395

This paper presents a new algorithm for designing fuzzy systems. It automatically identifies the optimum number of rules in the fuzzy knowledge base and adjusts the parameters defining them. This algorithm hybridizes the robustness and capability of evolutive algorithms with multiobjective optimization techniques which are able to minimize both the prediction error of the fuzzy system and its complexity, i.e. the number of parameters. In order to guide the search and accelerate the algorithm’s convergence, new specific genetic operators have been designed, which combine several heuristic and analytical methods. The results obtained show the validity of the proposed algorithm for the identification of fuzzy systems when applied to time-series prediction. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Multiobjective optimization

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Server consolidation for Internet applications in virtualized data centers

Server consolidation for Internet applications in virtualize...

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24th High Performance Computing Symposium, HPC 2016, Part of the 2016 Spring Simulation Multi-Conference, SpringSim 2016

作者： Wang, Bo Song, Ying Sun, Yuzhong Liu, Jun Department of Computer Science and Technology Xi'an Jiaotong University Xi'an710049 China SKL Computer Architecture ICT CAS Beijing100190 China SPKLSTN Lab Department of Computer Science and Technology Xi'an Jiaotong University Xi'an710049 China

ISBN: (纸本)9781510824256

Server consolidation based on virtualization technology simplifies system administration and improves energy efficiency by improving resource utilizations and reducing the physical machine (PM) number in contemporary service-oriented data centers. The elasticity of Internet applications changes the consolidation technologies from addressing virtual machines (VMs) to PMs mapping schemes which must know the VMs statuses, i.e. the number of VMs and the profiling data of each VM, into providing the application-to-VM-to-PM mapping. In this paper, we study on the consolidation of multiple Internet applications, minimizing the number of PMs with required performance. We first model the consolidation providing the application-to-VM-to-PM mapping to minimize the number of PMs as an integer linear programming problem, and then present a heuristic algorithm to solve the problem in polynomial time. Extensive experimental results show that our heuristic algorithm consumes less than 4.3% more resources than the optimal amounts with few overheads. Existing consolidation technologies using the input of the VM statuses output by our heuristic algorithm consume 1.06% more PMs. © 2016 Society for Modeling & Simulation International (SCS).

关键词： Elasticity

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