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convergence estimates in simultaneous approximation for Certain generalized Baskakov operators 1st

Convergence estimates in simultaneous approximation for Cert...

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1st international conference on Modern Mathematical Methods and High Performance computing in Science and technology, M3HPCST 2015

作者： Gupta, Vijay Singh, Vinai K. Department of Mathematics Netaji Subhas Institute of Technology Sector 3 Dwarka New Delhi110078 India Raj Kumar Goel Institute of Technology NH-58 Delhi-Meerut Road Ghaziabad201003 India

ISBN: (纸本)9789811014536

In the present article, we consider the Durrmeyer type integral modification of the generalized Baskakov operators. The special cases of our operators provides thewell-known Baskakov–Durrmeyer and Szász–Durrmeyer operators. We estimate convergence estimates in simultaneous approximation. © Springer Science+Business Media Singapore 2016.

关键词： Estimation

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Generalized absolute convergence of trigonometric fourier series 1

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1st international conference on Modern Mathematical Methods and High Performance computing in Science and technology, M3HPCST 2015

作者： Vyas, R.G. Faculty of Science Department of Mathematics The Maharaja Sayajirao University of Baroda VadodaraGujarat India

ISBN: (数字)9789811014543

ISBN: (纸本)9789811014536

Recently, Moricz and Veres generalized the classical results of Bernstein, Szasz, Zygmund and others related to the absolute convergence of single and multiple Fourier series. In this paper, we have extended this result for single Fourier series of functions of the classes ΛBV() and ΛBV(p)(). © Springer Science+Business Media Singapore 2016.

关键词： Fourier series Generalized β−absolute convergence ΛBV(p)(𝕋)

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Numerical simulation of water entry of 2D wedges 26

Numerical simulation of water entry of 2D wedges

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26th Annual international Ocean and Polar Engineering conference, ISOPE 2016

作者： Ma, Zhihua Qian, Ling Ferrer, Pedro Martinez Causon, Derek Mingham, Clive School of Computing Mathematics and Digital Technology Manchester Metropolitan University Manchester United Kingdom

ISBN: (纸本)9781880653883

The open source CFD library OpenFOAM is utilised to simulate the hydrodynamic impact process of 2D wedges. Incompressible multiphase flow solver interFoam is employed to calculate the free fall of structure from air into water using dynamic deforming mesh technique. A convergence study of dynamics as well as kinematics is carried out on successively refined meshes. Obtained results are presented and compared to experimental measurements. The computed impact loadings show reasonable mesh convergence. © Copyright 2016 by the international Society of Offshore and Polar Engineers (ISOPE).

关键词： Hydrodynamics

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A Cooperative and Hybrid Network Intrusion Detection Framework in Cloud computing Based on Snort and Optimized Back Propagation Neural Network 7

A Cooperative and Hybrid Network Intrusion Detection Framewo...

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7th international conference on Ambient Systems, Networks and Technologies (ANT) / 6th international conference on Sustainable Energy Information technology (SEIT)

作者： Chiba, Z. Abghour, N. Moussaid, K. El Omri, A. Rida, M. Hassan II Univ Casablanca Team Modeling & Optimizat Mobile Serv Fac Sci Casablanca 20100 Morocco

Cloud computing provides a framework for supporting end users easily attaching powerful services and applications through Internet. To give secure and reliable services in cloud computing environment is an important issue. Providing security requires more than user authentication with passwords or digital certificates and confidentiality in data transmission, because it is vulnerable and prone to network intrusions that affect confidentiality, availability and integrity of Cloud resources and offered services. To detect DoS attack and other network level malicious activities in Cloud, use of only traditional firewall is not an efficient solution. In this paper, we propose a cooperative and hybrid network intrusion detection system (CH-NIDS) to detect network attacks in the Cloud environment by monitoring network traffic, while maintaining performance and service quality. In our NIDS framework, we use Snort as a signature based detection to detect known attacks, while for detecting network anomaly, we use Back-Propagation Neural network (BPN). By applying snort prior to the BPN classifier, BPN has to detect only unknown attacks. So, detection time is reduced. To solve the problem of slow convergence of BPN and being easy to fall into local optimum, we propose to optimize the parameters of it by using an optimization algorithm in order to ensure high detection rate, high accuracy, low false positives and low false negatives with affordable computational cost. In addition, in this framework, the IDSs operate in cooperative way to oppose the DoS and DDoS attacks by sharing alerts stored in central log. In this way, unknown attacks that were detected by any IDS can easily be detected by others IDSs. This also helps to reduce computational cost for detecting intrusions at others IDS, and improve detection rate in overall the Cloud environment. (C) 2016 The Authors. Published by Elsevier B.V.

关键词： Cloud computing Network intrusion detection Back-propagation neural network Snort Optimization algorithm

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A Novel Hybrid Flow-Based Handler with DDoS Attacks in Software-Defined Networking 13

A Novel Hybrid Flow-Based Handler with DDoS Attacks in Softw...

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13th IEEE international conference on Ubiquitous Intelligence and computing, 13th IEEE international conference on Advanced and Trusted computing, 16th IEEE international conference on Scalable computing and Communications, IEEE international conference on Cloud and Big Data computing, IEEE international conference on Internet of People and IEEE Smart World Congress and Workshops, UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld 2016

作者： Phan, Trung V. Bao, Nguyen Khac Park, Minho Department of Information Communication Materials and Chemistry Convergence Technology Soongsil University Seoul156-743 Korea Republic of

ISBN: (纸本)9781509027705

In this paper, we firstly introduce a new combined approach to enhance the performance of classification in network traffic. The proposed combination mainly focuses on taking advantages of two classification algorithms, Support Vector Machine (SVM), Self Organizing Map (SOM). We utilize both advantages that SVM takes a little time to produce outputs with a high accuracy, SOM makes a reliable prediction based on their neurons. Next, we propose a hybrid flow-based work mechanism, which applies the proposed combination SVMs-SOM, for handling with Distributed Denial-of-Service (DDoS) attacks, network component protection from resource exhaustion in Software-Defined Networking. In the introduced scheme, multiple Linear SVMs first classify flow entries existing in flow-tables from OpenFlow switches. In the case that a flow's position is located between two margin lines or a vague region in the Linear SVM representation, it will be then forwarded to a SOM to make a final decision. Afterwards, an attack classifier, a policy enforcement module will be applied to attack flows with the purpose of attack diminution, the SDN controller protection. Besides, we also provide readers with a new view of DDoS attacks in the Software-Defined Networking. Thorough practical experiments conducted in the Software-Defined Networking environment, it is proved that the proposed classification combination outperforms original algorithms, the novel hybrid mechanism can be an effective, innovative approach to face with DDoS attacks, protect the OpenFlow switches, the SDN controller from being overloaded. © 2016 IEEE.

关键词： Support vector machines

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Cooperative Compounded Particle Swarm Optimization and application 15

Cooperative Compounded Particle Swarm Optimization and appli...

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15th IEEE international conference on Cognitive Informatics and Cognitive computing, ICCI*CC 2016

作者： Wang, Hongbo Wang, Kezhen Xue, Yanze Tu, Xuyan Department of Computer Science and Technology School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China

ISBN: (纸本)9781509038466

In real-time high dimensions optimization problem, how to quickly find the optimal solution and give timely response or decisive adjustment is very important. Inspired by the mutual parasitic behaviors, this paper suggests a new PSO variant, Cooperative Compounded Particle Swarm Optimization (COMPSO) that improves the convergence speed and reduces the possibility of particles into the local optimum. By using of real encoding mechanism, COMPSO is applied to the vehicle routing problem. Compared with other PSO algorithms, experimental results show the superiority of COMPSO algorithm in terms of the solution quality and computational efficiency. It proves a helpful guiding significance. © 2016 IEEE.

关键词： Computational efficiency

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Efficient and secure data delivery in software defined WBAN for virtual hospital 2

Efficient and secure data delivery in software defined WBAN ...

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2nd international conference on Control, Electronics, Renewable Energy, and Communications, ICCEREC 2016

作者： Shayokh, Md Al Abeshu, Abebe Satrya, G.B. Nugroho, M.A. IT Convergence Engineering Kumoh National Institute of Technology Korea Republic of Computer Science and IT La Trobe University Australia Telkom School of Computing Telkom University Indonesia

ISBN: (纸本)9781509007448

Sedentary lifestyle and recent advancement in physiological low powered sensors triggers the concept of Wireless Body Area Networks (WBAN) for efficient healthcare system. Proliferation of Cloud computing technology merged into WBAN become a new trend for smart healthcare. To manage the complexity in network infrastructure new technology named as Software Defined Networking (SDN) has been introduced recently. In terms of quality of service (QoS), medical data needs to be sent securely for a trustworthy system where every single data is sensitive for patient. In this paper, efficient data delivery system with a secured networking authentication protocol named as Kerberos has been proposed for software defined virtual hospital systems. This paper also demonstrate with simulation results for a better data delivery system with adequate networking security through Kerberos system for the next generation smart healthcare architecture. © 2016 IEEE.

关键词： Quality of service

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Doubly accelerated stochastic variance reduced dual averaging method for regularized empirical risk minimization 17

Doubly accelerated stochastic variance reduced dual averagin...

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Proceedings of the 31st international conference on Neural Information Processing Systems

作者： Tomoya Murata Taiji Suzuki NTT DATA Mathematical Systems Inc. Tokyo Japan Department of Mathematical Informatics Graduate School of Information Science and Technology The University of Tokyo Tokyo Japan and PRESTO Japan Science and Technology Agency Japan and Center for Advanced Integrated Intelligence Research RIKEN Tokyo Japan

ISBN: (纸本)9781510860964

We develop a new accelerated stochastic gradient method for efficiently solving the convex regularized empirical risk minimization problem in mini-batch settings. The use of mini-batches has become a golden standard in the machine learning community, because the mini-batch techniques stabilize the gradient estimate and can easily make good use of parallel computing. The core of our proposed method is the incorporation of our new "double acceleration" technique and variance reduction technique. We theoretically analyze our proposed method and show that our method much improves the mini-batch efficiencies of previous accelerated stochastic methods, and essentially only needs size √n mini-batches for achieving the optimal iteration complexities for both non-strongly and strongly convex objectives, where n is the training set size. Further, we show that even in non-mini-batch settings, our method achieves the best known convergence rate for non-strongly convex and strongly convex objectives.

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Classification of two class motor imagery task using Jaya based k-means clustering

Classification of two class motor imagery task using Jaya ba...

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2016 international conference on Global Trends in Signal Processing, Information computing and Communication, ICGTSPICC 2016

作者： Suraj Sinha, Rakesh Kumar Ghosh, Subhojit Department of Electrical and Electronics Engineering Birla Institute of Technology Mesra Ranchi India Department of Bio-Engineering Birla Institute of Technology Mesra Ranchi India Department of Electrical Engineering National Institute of Technology Raipur India

ISBN: (纸本)9781509004676

The brain-computer interface (BCI), identify brain patterns to translate thoughts into action. The identification relies on the performance of the classifier. In this paper identification of electroencephalogram (EEG) based BCI for motor imagery (MI) task is done through asynchronous approach. Transferring the brain computer interface (BCI) from laboratory state to real time application desires BCI to be functional asynchronously exclusive of any time constraint. In this case, ongoing brains activities are analyzed continuously irrespective of state i.e. control or non-control. The k-means is the most commonly used and one of the best clustering technique. With k-means, there is a possibility of convergence to the local minima. In literature, it is reported that k-mean modified with optimization techniques have able to address this problem by avoiding premature convergence of local minima. In this article, we have used algorithm-specific parameter-less Jaya optimization to select the initial cluster for k-means. Though enhancement in the accuracy is marginal, it is the speed which makes Jaya based k-means to be an obvious choice for the problem under consideration, i.e. classifying motor imagery task. Supremacy of the proposed Jaya based k-means among the considered algorithm is validated through Friedman test. © 2016 IEEE.

关键词： Brain computer interface

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Lightweight Authentication Method for Controller Area Network 22

Lightweight Authentication Method for Controller Area Networ...

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22nd IEEE international conference on Embedded and Real-Time computing Systems and Applications, RTCSA 2016

作者： Kang, Ki-Dong Baek, Youngmi Lee, Seonghun Son, Sang H. Department of Information and Communication Engineering DGIST Daegu Korea Republic of CPS Global Center DGIST Daegu Korea Republic of Convergence Research Center for Future Automotive Technology DGIST Korea Republic of

ISBN: (纸本)9781509024797

In the age of smart and connected vehicles, there are significant issues in providing security for in-vehicle networking. Many security efforts for in-vehicle networks are still insufficient to build a lightweight security mechanism. Typically, it comes from the limitations of Controller Area Network (CAN) protocol common to in-vehicle network. We propose a lightweight authentication method based on one-way hash chain in CAN. In addition, we identify three technical challenges to be addressed for the proposed method and present our key idea to address them. © 2016 IEEE.

关键词： Authentication

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