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Developing a User-friendly Sensor Network Simulator to Imitate Wireless Charging Vehicle Behaviors

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Developing a User-friendly Sensor Network Simulator to Imita...

International Conference on Computing, Networking and Communications

作者： Shuo-Han Chen Tseng-Yi Chen Yu-Chun Cheng Hsin-Wen Wei Tsan-sheng Hsu Wei-Kuan Shih Department of Computer Science National Tsing Hua University Institute of Information Systems and Applications National Tsing Hua University Department of Electrical Engineering Tamkang University Institute of Information Science Academia Sinica

ISBN: (纸本)9781467385800

An emerging breakthrough in wireless charging technology is expected to solve the power constraint problem in wireless sensor networks (WSN). In various works, wireless chargers are being bundled with mobile vehicles to recharge sensor nodes. In these works, simulations of mobile vehicles are typically used in experiments because building a wireless sensor network test bed is very costly and many details of a wireless sensor network are neither standardized nor finalized. Accordingly, a simulator is extremely useful in testing new applications or protocols in wireless sensor networks. However, several well-known wireless sensor network simulators have no or limited support for wireless recharging. Researchers may want to construct their own simulating modules, but the highly complex design of current simulators is intimidating and stops researchers from testing their applications. This work develops a framework for simulating a WSN and focuses on the simulation of wireless power transfer and mobile vehicles. This simulator eliminates the need for researchers to build their own simulator or integrate complex wireless charging modules, allowing them simply to implement their algorithm. Moreover, the proposed simulator has been verified by implementing the work of Xie et al. [20].

关键词： Wireless Sensor Network (WSN) Simulation Simulator Wireless Power Transfer Wireless Charging Vehicle (WCV)

MoS2 heterostructure with tunable phase stability: Strain induced interlayer covalent bond formation

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arXiv 2017年

作者： Ouyang, Bin Xiong, Shiyun Yang, Zhi Jing, Yuhang Wang, Yongjie National Center for Supercomputing Applications University of Illinois at Urbana-Champaign UrbanaIL61801 United States Collaborative Innovation Center of Suzhou Nano Science and Technology Soochow University Suzhou JiangSu215123 China College of Physics and Optoelectronics Taiyuan University of Technology Taiyuan ShanXi030024 China Key Lab of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province Taiyuan University of Technology Taiyuan ShanXi030024 China Department of Astronautical Science and Mechanics Harbin Institute of Technology Harbin Heilongjiang150001 China Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Electrical Engineering and Computer Engineering University of Michigan Ann ArborMI48109 United States

Due to the distinguished properties offered by different structural phases of monolayer MoS2, phase engineering design are urgently required for achieving switchable structural phase. Strain engineering is widely accepted as a clean and flexible method, however, can not be achieved in engineering monolayer MoS2 phase transition because the critical biaxial strain required (~15%) is much larger than measured elastic limit (~11%). In this study, employing density functional theoretical calculations, it has been found out that with the forming of heterostructure between MoS2 with buckled 2D materials such as silicence, germanene and stanene, only a small strain can trigger the phase transition. As being suggested by the constructed phase stability diagram, biaxial deformation as low as 3% in MoS2/silicene and MoS2/stanene sandwich structure, would be sufficient to induce the structural phase transition in MoS2 lattice. This strain falls well within experimental elastic limit, thus would be feasible to realize in experiment. The origin of such behavior can be understood as strain induced interlayer covalent bond formation, which finally make MoS2 lattice more sensitive to external strain. This theoretical work provides one realistic route for achieving flexible phase stabilities in experimental design. Copyright © 2017, The Authors. All rights reserved.

关键词： Molybdenum compounds

Optimal Adaptive Genetic Algorithm Based Hybrid Signcryption Algorithm for Information Security

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computer Modeling in engineering & sciences 2015年第5期105卷 47-68页

作者： R.Sujatha M.Ramakrishnan N.Duraipandian B.Ramakrishnan Velammal Engineering College Anna UniversityIndia School of Computer Applications Madurai Kamarajar UniversityIndia Department of Computer Science and Research Centre S.T.Hindu CollegeMadurai Kamarajar UniversityIndia

The functions of digital signature and public key encryption are simultaneously fulfilled by signcryption,which is a cryptographic *** securely communicate very large messages,the cryptographic primitive called signcryption efficiently implements the same and while most of the public key based systems are suitable for small messages,hybrid encryption(KEM-DEM)provides a competent and practical *** this paper,we develop a hybrid signcryption *** hybrid signcryption is based on the KEM and DEM *** KEM algorithm utilizes the KDF technique to encapsulate the symmetric *** DEM algorithm utilizes the Adaptive Genetic Algorithm based Elliptic curve cryptography algorithm to encrypt the original ***,for the security purpose,we introduce the three games and we proved the attackers fail to find the security attributes of our proposed signcryption *** proposed algorithm is analyzed with Daniel of Service(DOS),Brute Force attack and Man In Middle(MIM)attacks to ensure the secure data transaction.

关键词： Hybrid Signcryption KEM DEM Adaptive Genetic Algorithm EllipticCurve Cryptography

Voltage induced switching of an antiferromagnetically ordered topological Dirac semimetal

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arXiv 2017年

作者： Kim, Youngseok Kang, Kisung Schleife, André Gilbert, Matthew J. Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Micro and Nanotechnology Laboratory University of Illinois 208 N. Wright Street UrbanaIL61801 United States Department of Materials Science and Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Frederick Seitz Materials Research Laboratory University of Illinois at Urbana-Champaign UrbanaIL61801 United States National Center for Supercomputing Applications University of Illinois at Urbana-Champaign UrbanaIL61801 United States

An antiferromagnetic semimetal has been recently identified as a new member of topological semimetals that may host three-dimensional symmetry-protected Dirac fermions. A reorientation of the Néel vector may break the underlying symmetry and open a gap in the quasi-particle spectrum, inducing the (semi)metal-insulator transition. Here, we predict that such transition may be controlled by manipulating the chemical potential location of the material. We perform both analytical and numerical analysis on the thermodynamic potential of the model Hamiltonian and find that the gapped spectrum is preferred when the chemical potential is located at the Dirac point. As the chemical potential deviates from the Dirac point, the system shows a possible transition from the gapped to the gapless phase and switches the corresponding Néel vector configuration. We perform density functional theory calculations to verify our analysis using a realistic material and discuss a two terminal transport measurement as a possible route to identify the voltage induced switching of the Néel vector. Copyright © 2017, The Authors. All rights reserved.

关键词： Chemical potential

Metaheuristic based workflow scheduling in cloud environment

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Metaheuristic based workflow scheduling in cloud environment

International Conference on Reliability, Infocom Technologies and Optimization (ICRITO) (Trends and Future Directions)

作者： Sunil Kumar Sumit Mittal Manpreet Singh Department of Computer Science & Applications Guru Nanak College for Girls Sri Muktsar Sahib India M M Institute of Computer Technology & Business Management M. M University Mullana India Department of Computer Science & Engineering M. M. University Sadopur India

ISBN: (纸本)9781509014903

Workflow scheduling deals with the mapping of interdependent and compute intensives tasks to the system resources considering all application's requirements. Due to its elastic capabilities, the cloud has been instrumental in effective scheduling of workflow activities. This paper presents a genetic algorithm based metaheuristics to schedule workflow applications on cloud resources with an objective to improve both the makespan and resource utilization. The performance of proposed algorithm is tested for different workflow applications (Montage, Fork-Join, Epigenome) under various load conditions in a scalable environment.

关键词： Genetic algorithms Resource management Sociology Statistics Cloud computing Schedules Scheduling

Enhancing participant selection through caching in mobile crowd sensing

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Enhancing participant selection through caching in mobile cr...

International Workshop on Quality of Service

作者： Hanshang Li Ting Li Fan Li Weichao Wang Yu Wang Department of Computer Science University of North Carolina at Charlotte Charlotte NC USA Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications Beijing China School of Computer Science Beijing Institute of Technology Beijing China

With the rapid increasing of smart phones and their embedded sensing technologies, mobile crowd sensing (MCS) becomes an emerging sensing paradigm for performing large-scale sensing tasks. One of the key challenges of large-scale mobile crowd sensing systems is how to effectively select the minimum set of participants from the huge user pool to perform the tasks and achieve certain level of coverage. In this paper, we introduce a new MCS architecture which leverages the cached sensing data to fulfill partial sensing tasks in order to reduce the size of selected participant set. We present a newly designed participant selection algorithm with caching and evaluate it via extensive simulations with a real-world mobile dataset.

关键词： Sensors Mobile communication Memory Algorithm design and analysis Smart phones Probabilistic logic Data models

Three-dimensional discrete Boltzmann models for compressible flows in and out of equilibrium

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arXiv 2017年

作者： Gan, Yanbiao Xu, Aiguo Zhang, Guangcai Lai, Huilin North China Institute of Aerospace Engineering Langfang065000 China National Key Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics P. O. Box 8009-26 Beijing100088 China Center for Applied Physics and Technology MOE Key Center for High Energy Density Physics Simulations College of Engineering Peking University Beijing100871 China School of Mathematics and Computer Science Fujian Normal University Fuzhou350007 China Fujian Key Laborotary of Mathematical Analysis and Applications Fujian Normal University Fuzhou350007 China

We present a series of three-dimensional discrete Boltzmann (DB) models for compressible flows in and out of equilibrium. The key formulating technique is the construction of discrete equilibrium distribution function through inversely solving the kinetic moment relations that it satisfies. The crucial physical requirement is that all the used kinetic moment relations must be consistent with the non-equilibrium statistical mechanics. The necessity of such a kinetic model is that, with increasing the complexity of flows, the dynamical characterization of non-equilibrium state and the understanding of the constitutive relations need higher order kinetic moments and their evolution. The DB models at the Euler and Navier-Stokes levels proposed by this scheme are validated by several well-known benchmarks, ranging from one-dimension to three-dimension. Particularly, when the local Mach number, temperature ratio, and pressure ratio are as large as 102, 104, and 105, respectively, the simulation results are still in excellent agreement with the Riemann solutions. How to model deeper thermodynamic non-equilibrium flows by DB is indicated. Via the DB method, it convenient to simulate nonequilibrium flows without knowing exact form of the hydrodynamic equations. Copyright © 2017, The Authors. All rights reserved.

关键词： Navier Stokes equations

Simulink comparison of varying-parameter convergent-differential neural-network and gradient neural network for solving online linear time-varying equations

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Simulink comparison of varying-parameter convergent-differen...

World Congress on Intelligent Control and Automation (WCICA)

作者： Zhijun Zhang Siwei Li Xiaoyan Zhang Guangzhou Key Laboratory of Brain Computer Interaction and Applications South China University of Technology Guangzhou P.R. China School of Computer Science and Software Engineering Shenzhen University Shenzhen P.R. China

ISBN: (纸本)9781467384155

A novel kind of recurrent neural network (called varying-parameter convergent-differential neural-network, VP-CDNN) is proposed in this paper for online solving linear time-varying equations. Different from traditional gradient-base neural network (called GNN) with scalar-valued error functions, such new VP-CDNN is designed based on matrix-valued or vector-valued error functions and their coefficients related to convergence is time-varying. In other words, the coefficients are the functions of time t. In addition, this kind of VP-CDNN is depicted in implicit dynamics but not explicit dynamics. To illustrate the effectiveness of the new neural network, the comparative simulations with MATLAB Simulink of the proposed VP-CDNN and GNN for solving online linear time-varying equations are implemented and presented. computer-simulation results verify the fast convergence and good robustness.

关键词： Mathematical model Convergence Computational modeling Biological neural networks MATLAB

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arXiv 2017年

作者： Surya Prasath, V.B. Abu Alfeilat, Haneen Arafat Lasassmeh, Omar Hassanat, Ahmad B.A. Tarawneh, Ahmad S. Division of Biomedical Informatics Cincinnati Children’s Hospital Medical Center OH45229 United States Department of Pediatrics University of Cincinnati College of Medicine CincinnatiOH United States Department of Biomedical Informatics College of Medicine University of Cincinnati OH45267 United States Department of Electrical Engineering and Computer Science University of Cincinnati OH45221 United States Department of Information Technology Mutah University Karak Jordan Department of Algorithm and Their Applications Etvs Lornd University Budapest Hungary

The K-nearest neighbor (KNN) classifier is one of the simplest and most common classifiers, yet its performance competes with the most complex classifiers in the literature. The core of this classifier depends mainly on measuring the distance or similarity between the tested examples and the training examples. This raises a major question about which distance measures to be used for the KNN classifier among a large number of distance and similarity measures available? This review attempts to answer this question through evaluating the performance (measured by accuracy, precision and recall) of the KNN using a large number of distance measures, tested on a number of real-world datasets, with and without adding different levels of noise. The experimental results show that the performance of KNN classifier depends significantly on the distance used, and the results showed large gaps between the performances of different distances. We found that a recently proposed non-convex distance performed the best when applied on most datasets comparing to the other tested distances. In addition, the performance of the KNN with this top performing distance degraded only about 20% while the noise level reaches 90%, this is true for most of the distances used as well. This means that the KNN classifier using any of the top 10 distances tolerate noise to a certain degree. Moreover, the results show that some distances are less affected by the added noise comparing to other distances. Copyright © 2017, The Authors. All rights reserved.

关键词： Machine learning