检索结果-内蒙古大学图书馆

7th International conference on Smart City and Informatization, iSCI 2019

作者： Wang, Qifan Zhou, Lei Tang, Zhe Wang, Guojun School of Computer Science and Engineering Central South University Changsha410083 China School of Computer Science Guangzhou University Guangzhou510006 China

ISBN: (纸本)9789811513008

Internet of Vehicles (IoV) provides a broad range of services of data exchange of traffic information to improve the effectiveness of smart vehicles. However, the security issues in Internet of Vehicles are multifaceted: data theft, message tampering and forgery, etc., which results in possibilities of incorrect data sharing. To address above issues, we proposed an efficient blockchain-based data sharing model. In this paper, we leverage the consortium blockchain and enhanced Diffie-Hellman algorithm to build a trust decentralized verifying mechanism, which is designed to secure the data sharing process in IoV. To improve the performance, we optimize the consensus mechanism on our blockchain-based system by decreasing the consensus delay without affecting the correctness of consensus verifying. The security analysis and simulation experiments show that our model meets security requirements and the overhead from our system is acceptable for IoV. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Vehicles

来源：评论

学校读者我要写书评

暂无评论

FATIGUE OF WELDED TUBULAR X-JOINTS IN OFFSHORE WIND PLATFORMS 38

FATIGUE OF WELDED TUBULAR X-JOINTS IN OFFSHORE WIND PLATFORM...

引用

38th ASME International conference on Ocean, Offshore and Arctic Engineering (OMAE 2019)

作者： Papatheocharis, Theocharis Sarvanis, Gregory C. Perdikaris, Philip C. Karamanos, Spyros A. Univ Thessaly Dept Civil Engn Volos Greece Univ Thessaly Dept Mech Engn Volos Greece Univ Edinburgh Sch Engn Edinburgh Midlothian Scotland

ISBN: (纸本)9780791858790

The paper is part of the European research program JABACO (2015-2018), on the optimization of design and construction of offshore jacket platforms for supporting large wind turbines (5 - 10 MW) in water depths ranging from 30m to 80m. In particular, the paper describes an experimental investigation on the high-cycle fatigue performance of welded tubular connections, subjected to in-plane bending loading. Experimental results from seven (7) X-joint specimens are presented. The specimens were manufactured with 18-inch diameter tubes and a brace-to-chord-diameter ratio equal to 1. Furthermore, the brace-to-chord-thickness ratio is equal 0.6, and the brace-chord angle is 90-degrees. The specimens are made of regular carbon steel grade 355, and have been fabricated using two different welding techniques: (a) manual (semi-automatic) welding (5 specimens);and (b) robot (automatic) welding (2 specimens). The comparison of the fatigue design life of those welding methods is a major objective of the present study. Prior to testing, numerical simulations have been performed to determine the critical locations around the weld toe, for proper instrumentation of the tubular specimens in terms of strain gage locations. This research work aims at a critical evaluation of available design standards, towards the development of more reliable design tools and reduction of the construction cost of the platform.

关键词： Fatigue Welding computer simulation Robots Carbon steel Construction Ocean engineering Bracing (Construction) Chords (Trusses) Design Instrumentation Optimization Testing Fatigue design Strain gages Water Wind Wind turbines Offshore platform jackets high cycle fatigue

来源：评论

学校读者我要写书评

暂无评论

conference Reports: Recap of the 37th Edition of the International conference on computer-Aided Design (ICCAD 2018)

Conference Reports: Recap of the 37th Edition of the Interna...

引用

作者： Bahar, R. Iris Brown University United States

Jointly sponsored by IEEE and ACM, the International conference on computer-Aided Design (ICCAD) is the premier forum to explore emerging technology challenges in electronic design automation, present leading-edge research and development solutions, and identify future roadmaps for design automation research areas. This year, ICCAD was held in San Diego, CA, on 4-8 November 2018 at the Hilton Resort in Mission Bay. San Diego's dependably perfect weather made for a great backdrop for the 37th installment of the conference. We had over 400 attendees at ICCAD this year for the regular program and workshops combined, thanks in part to the location. We hope to have ICCAD back in San Diego at some point in the near future. © 2013 IEEE.

关键词： Electronic design automation

来源：评论

学校读者我要写书评

暂无评论

Using Hadoop for high Energy Physics Data Analysis 1

引用

1st International conference on Big Scientific Data Management (BigSDM)

作者： Huang, Qiulan Wei, Zhanchen Sun, Gongxing Cheng, Yaodong Cheng, Zhenjing Hu, Qingbao IHEP Comp Ctr POB 918-7 19B Yuquan Rd Beijing 100049 Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (数字)9783030280611

ISBN: (纸本)9783030280611;9783030280604

With the development of the new generation of high Energy Physics (HEP) experiments, huge amounts of data are being generated. Efficient parallel algorithms/frameworks and high IO throughput are key to meet the scalability and performance requirements of HEP offline data analysis. Though Hadoop has gained a lot of attention from scientific community for its scalability and parallel computing framework for large data sets, it's still difficult to make HEP data processing tasks run directly on Hadoop. In this paper we investigate the application of Hadoop to makeHEPjobs run on it transparently. Particularly, we discuss a new mechanism to support HEP software to random access data in HDFS. Because HDFS is streaming data stored only supporting sequential write and append. It cannot satisfy HEP jobs to random access data. This new feature allows the Map/Reduce tasks to random read/write on the local file system on data nodes instead of using Hadoop data streaming interface. This makes HEP jobs run on Hadoop possible. Wealso develop diverse MapReduce model forHEPjobs such as Corsika simulation, ARGOdetector simulation and Medea++ reconstruction. And we develop a toolkit for users to submit/query/remove jobs. In addition, we provide cluster monitoring and account system to benefit to the system availability. This work has been in production for HEP experiment to gain about 40,000 CPU hours per month since September, 2016.

关键词： Hadoop HDFS Mapreduce HEP data analysis

来源：评论

学校读者我要写书评

暂无评论

highly scalable discrete-particle simulations with novel coarse-graining: accessing the microscale

引用

MOLECULAR PHYSICS 2018年第15-16期116卷 2061-2069页

作者： Mattox, Timothy I. Larentzos, James P. Moore, Stan G. Stone, Christopher P. Ibanez, Daniel A. Thompson, Aidan P. Lisal, Martin Brennan, John K. Plimpton, Steven J. US Army Res Lab Engil Corp DoD High Performance Comp Modernizat Program HPCM PETTT Grp Aberdeen Proving Ground MD 21005 USA US Army Res Lab Weapons & Mat Res Directorate Aberdeen Proving Ground MD USA Sandia Natl Labs Multiscale Sci Dept POB 5800 Albuquerque NM 87185 USA US Air Force Res Lab Computat Sci & Engn LLC DoD High Performance Comp Modernizat Program HPCM PETTT Grp Dayton OH USA Sandia Natl Labs Computat Multiphys Dept POB 5800 Albuquerque NM 87185 USA CAS Dept Mol & Mesoscop Modelling Inst Chem Proc Fundamentals Vvi Prague Czech Republic Univ JE Purkyne Dept Phys Fac Sci Usti Nad Labem Czech Republic

Simulating energetic materials with complex microstructure is a grand challenge, where until recently, an inherent gap in computational capabilities had existed in modelling grain-scale effects at the microscale. We have enabled a critical capability in modelling the multiscale nature of the energy release and propagation mechanisms in advanced energetic materials by implementing, in the widely used LAMMPS molecular dynamics (MD) package, several novel coarse-graining techniques that also treat chemical reactivity. Our innovative algorithmic developments rooted within the dissipative particle dynamics framework, along with performance optimisations and application of acceleration technologies, have enabled extensions in both the length and time scales far beyond those ever realised by atomistic reactive MD simulations. In this paper, we demonstrate these advances by modelling a shockwave propagating through a microstructured material and comparing performance with the state-of-the-art in atomistic reactive MD techniques. As a result of this work, unparalleled explorations in energetic materials research are now possible. [GRAPHICS] .

关键词： coarse-graining dissipative particle dynamics energetic materials microstructure reaction kinetics scalable parallel simulation

来源：评论

学校读者我要写书评

暂无评论

Search for a diffuse astrophysical neutrino flux from the Galactic Ridge using KM3NeT/ARCA data 38

Search for a diffuse astrophysical neutrino flux from the Ga...

引用

38th International Cosmic Ray conference, ICRC 2023

作者： Filippini, Francesco Aiello, S. Albert, A. Alves Garre, S. Aly, Z. Ambrosone, A. Ameli, F. Andre, M. Androutsou, E. Anguita, M. Aphecetche, L. Ardid, M. Ardid, S. Atmani, H. Aublin, J. Bailly-Salins, L. Bardačová, Z. Baret, B. Bariego-Quintana, A. Basegmez du Pree, S. Becherini, Y. Bendahman, M. Benfenati, F. Benhassi, M. Benoit, D.M. Berbee, E. Bertin, V. Biagi, S. Boettcher, M. Bonanno, D. Boumaaza, J. Bouta, M. Bouwhuis, M. Bozza, C. Bozza, R.M. Brânzaş, H. Bretaudeau, F. Bruijn, R. Brunner, J. Bruno, R. Buis, E. Buompane, R. Busto, J. Caiffi, B. Calvo, D. Campion, S. Capone, A. Carenini, F. Carretero, V. Cartraud, T. Castaldi, P. Cecchini, V. Celli, S. Cerisy, L. Chabab, M. Chadolias, M. Chen, A. Cherubini, S. Chiarusi, T. Circella, M. Cocimano, R. Coelho, J.A.B. Coleiro, A. Coniglione, R. Coyle, P. Creusot, A. Cruz, A. Cuttone, G. Dallier, R. Darras, Y. De Benedittis, A. De Martino, B. Decoene, V. Del Burgo, R. Di Cerbo, U.M. Di Mauro, L.S. Di Palma, I. Díaz, A.F. Diaz, C. Diego-Tortosa, D. Distefano, C. Domi, A. Donzaud, C. Dornic, D. Dörr, M. Drakopoulou, E. Drouhin, D. Dvornický, R. Eberl, T. Eckerová, E. Eddymaoui, A. van Eeden, T. Eff, M. van Eijk, D. El Bojaddaini, I. El Hedri, S. Enzenhöfer, A. Ferrara, G. Filipović, M.D. Filippini, F. Franciotti, D. Fusco, L.A. Gabriel, J. Gagliardini, S. Gal, T. García Méndez, J. Garcia Soto, A. Gatius Oliver, C. Geißelbrecht, N. Ghaddari, H. Gialanella, L. Gibson, B.K. Giorgio, E. Goos, I. Goupilliere, D. Gozzini, S.R. Gracia, R. Graf, K. Guidi, C. Guillon, B. Gutiérrez, M. van Haren, H. Heijboer, A. Hekalo, A. Hennig, L. Hernández-Rey, J.J. Huang, F. Idrissi Ibnsalih, W. Illuminati, G. James, C.W. de Jong, M. de Jong, P. Jung, B.J. Kalaczyński, P. Kalekin, O. Katz, U.F. Khan Chowdhury, N.R. Khatun, A. Kistauri, G. Kopper, C. Kouchner, A. Kulikovskiy, V. Kvatadze, R. Labalme, M. Lahmann, R. Larosa, G. Lastoria, C. Lazo, A. Le Stum, S. Lehaut, G. Leonora, E. Università di Bologna Dipartimento di Fisica e Astronomia v.le C. Berti-Pichat 6/2 Bologna40127 Italy INFN Sezione di Bologna v.le C. Berti-Pichat 6/2 Bologna40127 Italy INFN Sezione di Catania Via Santa Sofia 64 Catania95123 Italy Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France IFIC - Instituto de Física Corpuscular CSIC - Universitat de València c/Catedrático José Beltrán 2 Paterna Valencia46980 Spain Aix Marseille Univ CNRS IN2P3 CPPM Marseille France INFN Sezione di Napoli Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy Università di Napoli "Federico II" Dip. Scienze Fisiche "E. Pancini" Complesso Universitario di Monte S. Angelo Via Cintia ed. G Napoli80126 Italy INFN Sezione di Roma Piazzale Aldo Moro 2 Roma00185 Italy Universitat Politècnica de Catalunya Laboratori d’Aplicacions Bioacústiques Centre Tecnològic de Vilanova i la Geltrú Avda. Rambla Exposició s/n Vilanova i la Geltrú08800 Spain NCSR Demokritos Institute of Nuclear and Particle Physics Ag. Paraskevi Attikis Athens15310 Greece University of Granada Dept. of Computer Architecture and Technology CITIC Granada18071 Spain Subatech IMT Atlantique IN2P3-CNRS Université de Nantes 4 rue Alfred Kastler - La Chantrerie BP 20722 Nantes44307 France Universitat Politècnica de València Instituto de Investigación para la Gestión Integrada de las Zonas Costeras C/ Paranimf 1 Gandia46730 Spain University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 RabatR.P. 10000 Morocco Université Paris Cité CNRS Astroparticule et Cosmologie ParisF-75013 France LPC CAEN Normandie Univ ENSICAEN UNICAEN CNRS IN2P3 6 boulevard Maréchal Juin Caen14050 France Czech Technical University in Prague Institute of Experimental and Applied Physics Husova 240/5 Prague110 00 Czech Republic Comenius University in Bratislava Department of Nuclear Physics and Biophysics Mlynska dolina F1 Bratislava842 48 Slov

Several theoretical models predict and describe the properties of part of the diffuse neutrino flux, originating from the interaction of Galactic cosmic rays with the interstellar medium matter located in the centre of our Galaxy. This neutrino flux is expected to be of the same order of magnitude as the diffuse γ-ray flux measured by Fermi-LAT, close to the Galactic plane. Recently hints by the ANTARES Collaboration, at a significance level over 2 σ, and the observation by the IceCube Collaboration, at a significance level of 4.5 σ, of a high-energy neutrino emission from the Galactic plane have been reported. For these reasons, and considering the privileged position of the KM3NeT/ARCA telescope, being located in the Northern hemisphere, data have been analysed searching for a possible excess of events coming from an extended region, with Galactic coordinates |l| ◦ and |b| ◦, namely the Galactic Ridge. In this contribution, the result of the analysis exploiting data gathered with KM3NeT/ARCA in the period in which comprises 6, 8, 19 or 21 active detection units is presented, showing the capabilities and performance of KM3NeT. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmology

来源：评论

学校读者我要写书评

暂无评论

Predicting the Global Maximum Power Point Locus using Shading Information 19

Predicting the Global Maximum Power Point Locus using Shadin...

引用

19th IEEE International conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2019

作者： Ma, Jieming Bi, Ziqiang Man, Ka Lok Liang, Hai-Ning Smith, Jeremy S. Department of Computer Science and Software Engineering Xi'An Jiaotong-Liverpool University Suzhou215123 China Xi'an Jiaotong-Liverpool University Suzhou215123 China Department of Electrical Engineering and Electronics University of Liverpool LiverpoolL69 3GJ United Kingdom

ISBN: (纸本)9781728106526

The power-voltage characteristic curves of a series-connected photovoltaic (PV) system exhibit multiple peaks in partial shading scenario (PSS). However, there lacks a feasible model that obtains the capability of predicting the global maximum power point (GMPP) locus. This paper analyzes the GMPP characterization and demonstrates that the voltage at the GMPP is located over a large range in various PSS. With the aim of improving the prediction performance, multiple Gaussian process regression (MGPR) models are proposed to predict the GMPP locus by using shading information, such as the shading rate and shading strength. The performance of the method is evaluated using a dataset obtained in a variety of environmental conditions. The results show that it outperforms the existing prediction models in terms of accuracy. With its high prediction capability, the proposed method can be used to increase the maximum power point tracking performance in PV systems. © 2019 IEEE.

关键词： Gaussian distribution

来源：评论

学校读者我要写书评

暂无评论

HUSP Mining Techniques to Detect Most Weighted Disease and Most Affected Diseases for the Healthcare Industry 5

HUSP Mining Techniques to Detect Most Weighted Disease and M...

引用

5th IEEE International conference on Science, Technology, Engineering and Mathematics, ICONSTEM 2019

作者： Canessane, R. Aroul Dhanalakshmi, R. Pavithra, B. Sasikanth, Bandaru Sandeep, Chamarthy Sathyabama Institute of Science and Technology Department of Computer Science and Engineering Chennai India Jeppiaar Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9781728115993

Data mining technique involves extracting or mining large volume of information for KDD - knowledge discovery database. The approach of Machine learning permits the program to examine statistics, comprehend correlations and gain insights for problem solving to improve facts and predictions. In the clinical field the technique of data mining holds very significant. There are heavy volumes of patient's records in the medical enterprise, majority of which are not used effectively. In order to cure various critical or non-critical diseases the approach of data mining proves to be essential also they aid in making medical conclusions for treating various diseases. As mentioned before, the healthcare organization assembles massive lot of medical data which generally remains un-mined, resultant the hidden information remains unexplored for valuable decision making. The information if mined and discovered can prove to be beneficial for the healthcare officials for the betterment of the hospital. Many prior experiments are carried out in order to evaluate the performance but the results reveal low accuracy and unsatisfied performance. The existing paper recommends HUSP- high Utility Sequence Pattern algorithm which helps in detecting disease that affects the maximum and is most weighted, thereby highlights it in the topmost list for the benefit of the healthcare industry. Following are the levels in the recommended technique: data collection, data pre-processing, feature selection, clustering and classification in order to detect highest weighted diseases. The paper primarily targets to identify and place the most weighted disease in topmost list for the benefit of the healthcare sector. This source of data is mined/extracted effectively to draw out valuable patterns/relations. The process of sequential pattern mining is basically performed on the basis of traditional process of item-set mining, the reason being that the later approach can be generalized by interpreting the

关键词： Data mining

来源：评论

学校读者我要写书评

暂无评论

SW Runtime Estimation using Automata Theory and Deep Learning on HPC

SW Runtime Estimation using Automata Theory and Deep Learnin...

引用

Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C), IEEE International conference on

作者： Hyunjoon Cheon Jinseung Ryu Chan Yeol Park Yo-Sub Han Department of Computer Science Yonsei University Seoul Republic of Korea Center for Supercomputer Development Korea Institute of Science and Technology Information Daejeon Republic of Korea

ISBN: (数字)9781728184142

ISBN: (纸本)9781728184159

People use high performance computers (HPCs) for computation-intensive tasks. Often these tasks require a lot of running time of their corresponding softwares. It is important to execute several tasks simultaneously for the system utilization while finishing all tasks within their desired deadlines. Therefore, it is important to know the runtime of each computation-intensive task without executing them in order to schedule the tasks on HPC and obtain better system performance. We propose a method for predicting runtime of MPI-based softwares on HPC using automata theory and deep learning. We first analyze a source code of an input program by representing the code as finite automata and measuring their state complexities. Next, we train the execution runtime of each module of our finite automata using deep neural network (DNN) together with its own state complexity. Then we combine all modules and make a single SW-runtime-prediction model. For experiment, we train the proposed model using OSU benchmark data, HPL and two in-house datasets, and present the usefulness of our model. We also demonstrate the adaptability of our model by updating the current model for new inputs using incremental DNN, which is an important feature for coping with new softwares or new systems.

关键词： Software Runtime Computational modeling Complexity theory Unified modeling language Estimation Task analysis

来源：评论

学校读者我要写书评

暂无评论

A Deep Learning Approach for Volterra Kernel Extraction for Time Domain Simulation of Weakly Nonlinear Circuits 69

A Deep Learning Approach for Volterra Kernel Extraction for ...

引用

69th IEEE Electronic Components and Technology conference (ECTC)

作者： Thong Nguyen Wang, Xinying Chen, Xu Schutt-Aine, Jose Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA

ISBN: (纸本)9781728114989

Volterra kernels are well known to be the multidimensional extension of the impulse response of a linear time invariant (LTI) system. It can be used to accurately model weakly nonlinear, specifically, polynomial nonlinearity systems. It has been used in the past for white-box model order reduction (MOR) to model frequency-domain performance metric quantities such as distortion in power amplifiers (PA). In this paper, we train a neural network from time-domain response of high-speed link buffers to extract multiple high-order kernels at once. Once the kernels are extracted, they can fully characterize the dynamics of the buffers of interest. Using the kernels, we demonstrate that time-domain response is straight-forward to obtain using super-, or multi-dimensional convolution. Previous work has used a shallow feed-forward neural network to train the system by using Gaussian noise as the identification signal. This is not convenient for the method to be compatible with existing computer-aided design tools. In this work, we directly use a pseudo random bit sequence (PRBS) to train the network. The proposed technique is more challenging because the PRBS has flat regions which have highly rich frequency spectrum and requires longer memory length, but allows the method to be compatible with existing simulation programs. We investigate different topologies including feed-forward neural network and recurrent neural network. Comparisons between training phase, inference phase, convergence are presented using different neural network topologies. The paper presents a numerical example using a 28Gbps data rate PAM4 transceiver to validate the proposed method against traditional simulation methods such as IBIS or SPICE level simulation for comparison in speed and accuracy. Using Volterra kernels promises a novel way to perform accurate nonlinear circuit simulation in the LTI system framework which is already well known and well developed. It can be conveniently incorporated into

关键词： Volterra Series Volterra Kernels Weakly Nonlinear Time-invariant Neural Network Behavioral Modeling Signal Integrity PAM4 high-speed channel

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：