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检索条件"任意字段=2016 International Conference on Data Mining and Advanced Computing, SAPIENCE 2016"

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Studying security of data in cloud computing through cryptographic approach 19th

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19th international conference on Interactive Collaborative Learning, ICL 2016

作者： El-Sofany, Hosam F. El-Seoud, Samir A. Department of Computer Science Cairo Higher Institute Cairo Egypt Faculty of Informatics and Computer Science British University in Egypt-BUE Cairo Egypt

ISBN: (纸本)9783319503394

Cloud computing is a set of IT services offered to users over the WWW on a rented base. Cloud computing has many advantages such as flexibility, efficiency, scalability, integration, and capital reduction. Moreover, it provides an advanced virtual space for organizations to deploy their applications and to run their systems. For secure communication over Cloud network, data can be protected by the method of encryption. Encryption exchanges that data by any encryption algorithm using the key in twisted form. Only user can access the key used to decrypt the encrypted data. The purpose of encryption is used to preventing leak or secrecy in communications. Encryption algorithms play a huge role in providing data security against bad and malicious attacks. This paper studies the basic concepts and analyzes the essentials of data security issues pertaining to Cloud computing. Then we elaborate on each issue by discussing its nature. Specifically, we emphasize on issues of protecting data such as: data confidentiality, data integrity, data availability, securing data access, data auditing, enforcing the regulations and compliances regarding to data security and privacy. © Springer international Publishing AG 2017.

关键词： Cryptography

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5th international conference on Frontiers in Intelligent computing Theory and Applications, FICTA 2016

5th International Conference on Frontiers in Intelligent Com...

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5th international conference on Frontiers in Intelligent computing Theory and Applications, FICTA 2016

ISBN: (纸本)9789811031526

The proceedings contain 79 papers. The special focus in this conference is on Frontiers in Intelligent computing Theory and Applications. The topics include: Human action recognition using trajectory-based spatiotemporal descriptors;ensemble learning for identifying muscular dystrophy diseases using codon bias pattern;basic arithmetic coding based approach to compress a character string;comparative analysis of different feature ranking techniques in data mining-based android malware detection;feature optimality-based semi-supervised face recognition approach;energy efficient resource allocation for heterogeneous workload in cloud computing;accent recognition system using deep belief networks for Telugu speech signals;a hybrid genetic algorithm for cell formation problems using operational time;performance analysis of compressed sensing in cognitive radio networks;a hybrid approach using chaos theory and multivariate adaptive regression splines;graph partitioning methods;color image visual cryptography scheme with enhanced security;fault mitigation in five-level inverter-fed induction motor drive using redundant cell;on the security of chaos-based watermarking scheme for secure communication;neighborhood topology to discover influential nodes in a complex network;venn diagram-based feature ranking technique for key term extraction;bangla handwritten city name recognition using gradient-based feature;shortest path algorithms for social network strengths;improvised symbol table structure;a soft computing approach for modeling of nonlinear dynamical systems;optimization of workload scheduling in computational grid;cloud based malware detection technique and abnormal network traffic detection using support vector data description.

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12th international conference on High Performance computing for Computational Science, VECPAR 2016

12th International Conference on High Performance Computing ...

引用

12th international conference on High Performance computing for Computational Science, VECPAR 2016

ISBN: (纸本)9783319619811

The proceedings contain 23 papers. The special focus in this conference is on High Performance computing for Computational Science. The topics include: Scalable algorithms for Bayesian inference of large-scale models from large-scale data;analysis of high performance applications using workload requirements;possible numerical remedies in linear algebra solvers;SIMD parallel sparse matrix-vector and transposed matrix-vector multiplication in DD precision;accelerating the conjugate gradient algorithm with GPUs in CFD simulations;parallelisation of MACOPA, a multi-physics asynchronous solver;performance analysis of SA-AMG method by setting extracted near kernel vectors;computing the bidiagonal SVD through an associated tridiagonal eigenproblem;a data parallel algorithm for seismic raytracing;a cross-core performance model for heterogeneous many-core architectures;evaluation of runtime cut-off approaches for parallel programs;implementation and evaluation of NAS parallel cg benchmark on GPU cluster with proprietary interconnect TCA;the design of advanced communication to reduce memory usage for exa-scale systems;a vectorized, cache efficient LLL implementation;versat, a minimal coarse-grain reconfigurable array;an application-level solution for the dynamic reconfiguration of MPI applications;scientific workflow scheduling with provenance support in multisite cloud;aspect oriented parallel framework for java;Gaspar data-centric framework and a heterogeneous runtime environment for scientific desktop computing.

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18th international conference on data Analytics and Management in data-Intensive Domains, DAMDID 2016

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18th international conference on data Analytics and Management in data-Intensive Domains, DAMDID 2016

ISBN: (纸本)9783319571348

The proceedings contain 19 papers. The special focus in this conference is on data Analytics and Management in data-Intensive Domains. The topics include: Conceptualization of methods and experiments in data intensive research domains;semantic search in a personal digital library;mathematical knowledge analytics and management;development of fuzzy cognitive map for optimizing E-learning course;supporting biological pathway curation through text mining;text processing framework for emergency event detection in the arctic zone;fact extraction from natural language texts with conceptual modeling;hybrid distributed computing service based on the DIRAC interware;hierarchical multiple stellar systems;semantics and verification of entity resolution and data fusion operations via transformation into a formal notation;a study of several matrix-clustering vertical partitioning algorithms in a disk-based environment;clustering of goods and user profiles for personalizing in E-commerce recommender systems based on real implicit data;on data persistence models for mobile crowdsensing applications;the European strategy in research infrastructures and open science cloud;creating inorganic chemistry data infrastructure for materials science specialists;visual analytics of multidimensional dynamic data with a financial case study and metadata for experiments in nanoscience foundries.

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Prediction of Child Tumours from Microarray Gene Expression data Through Parallel Gene Selection and Classification on Spark 3rd

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3rd international conference on Computational Intelligence in data mining (ICCIDM)

作者： Lokeswari, Y. V. Jacob, Shomona Gracia Sri Sivasubramaniya Nadar Coll Engn Dept CSE Madras Tamil Nadu India

ISBN: (纸本)9789811038747;9789811038730

Microarray gene expression data play a major role in predicting chronic disease at an early stage. It also helps to identify the most appropriate drug for curing the disease. Such microarray gene expression data is huge in volume to handle. All gene expressions are not necessary to predict a disease. Gene selection approaches pick only genes that play a prominent role in detecting a disease and drug for the same. In order to handle huge gene expression data, gene selection algorithms can be executed in parallel programming frameworks such as Hadoop Mapreduce and Spark. Paediatric cancer is a threatening illness that affects children at age of 0-14 years. It is very much necessary to identify child tumours at early stage to save the lives of children. So the authors investigate on paediatric cancer gene data to identify the optimal genes that cause cancer in children. The authors propose to execute parallel Chi-Square gene selection algorithm on Spark, selected genes are evaluated using parallel logistic regression and support vector machine (SVM) for Binary classification on Spark Machine Learning library (Spark MLlib) and compare the accuracy of prediction and classification respectively. The results show that parallel Chi-Square selection followed by parallel logistic regression and SVM provide better accuracy compared to accuracy obtained with complete set of gene expression data.

关键词： Parallel gene selection Chi-Square Parallel logistic regression Parallel SVM Hadoop map reduce Spark MLlib

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Supporting Microservice Evolution

Supporting Microservice Evolution

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33rd IEEE international conference on Software Maintenance and Evolution (ICSME)

作者： Sampaio, Adalberto R., Jr. Kadiyala, Harshavardhan Hu, Bo Steinbacher, John Erwin, Tony Rosa, Nelson Beschastnikh, Ivan Rubin, Julia Univ Fed Pernambuco Recife PE Brazil Univ British Columbia Vancouver BC Canada IBM Corp Markham ON Canada IBM Corp Armonk NY USA

ISBN: (纸本)9781538609927

Microservices have become a popular pattern for deploying scale-out application logic and are used at companies like Netflix, IBM, and Google. An advantage of using microservices is their loose coupling, which leads to agile and rapid evolution, and continuous re-deployment. However, developers are tasked with managing this evolution and largely do so manually by continuously collecting and evaluating low-level service behaviors. This is tedious, error-prone, and slow. We argue for an approach based on service evolution modeling in which we combine static and dynamic information to generate an accurate representation of the evolving microservice-based system. We discuss how our approach can help engineers manage service upgrades, architectural evolution, and changing deployment trade-offs.

关键词： Containers databases Cloud computing Monitoring Topology data mining

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20th international conference on advanced Computer System, ACS 2016

20th International Conference on Advanced Computer System, A...

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20th international conference on advanced Computer System, ACS 2016

ISBN: (纸本)9783319484280

The proceedings contain 32 papers. The special focus in this conference is on Artificial Intelligence, Multimedia Systems and Software Technologies. The topics include: On Fuzzy RDM-arithmetic;hidden Markov models with affix based observation in the field of syntactic analysis;an experiment on numeric, linguistic and color coded rating scale comparison;comparison of RDM complex interval arithmetic and rectangular complex arithmetic;homogeneous ensemble selection - experimental studies;deterministic method for the prediction of time series;a study on directionality in the Ulam square with the use of the Hough transform;real-time system of delivering water-capsule for firefighting;subject-specific methodology in the frequency scanning phase of SSVEP-based BCI;S-boxes cryptographic properties from a statistical angle;data scheme conversion proposal for information security monitoring systems;non-standard certification models for pairing based cryptography;the use of the objective digital image quality assessment criterion indication to create panoramic photographs;accuracy of high-end and self-build eye-tracking systems;mouth features extraction for emotion analysis;parallel facial recognition system based on 2DHMM;system of acoustic assistance in spatial orientation for the blind;performance and energy efficiency in distributed computing;the approach to web services composition;loop nest tiling for image processing and communication applications;the method of evaluating the usability of the website based on logs and user preferences and ontology-based approaches to big data analytics.

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1st international conference on data Engineering and Communication Technology, ICDECT 2016

1st International Conference on Data Engineering and Communi...

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1st international conference on data Engineering and Communication Technology, ICDECT 2016

ISBN: (纸本)9789811016776

The proceedings contain 80 papers. The special focus in this conference is on data Engineering and Communication Technology. The topics include: Experimental analysis on big data in IOT-based architecture;morphology based approach for number plate extraction;tracking pointer based approach for iceberg query evaluation;performance evaluation of shortest path routing algorithms in real road networks;an outlook in some aspects of hybrid decision tree classification approach;content search quaternary look-up table architecture;exhaust gas emission analysis of automotive vehicles using FPGA;comparative analysis of android malware detection techniques;developing secure cloud storage system using access control models;a multilevel clustering using multi-hop and Multihead in VANET;significance of frequency band selection of MFCC for text-independent speaker identification;analytical study of miniaturization of microstrip antenna for bluetooth/WiMax;novel all-optical encoding and decoding scheme for code preservation;improvisation in frequent pattern mining technique;detailed survey on attacks in wireless sensor network;an approach to protect confidential data in cloud environment;issues with DCR and NLSR in named-based routing protocol;priority dissection supervision for intrusion detection in wireless sensor networks;mining frequent quality factors of software system using apriori algorithm;algorithm for the enumeration and identification of kinematic chains;communication device for differently abled people;a prototype model;an adaptive mapreduce scheduler for scalable heterogeneous systems and multiple home automation on raspberry pi.

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Minimal Coflow Routing and Scheduling in OpenFlow-based Cloud Storage Area Networks 10

Minimal Coflow Routing and Scheduling in OpenFlow-based Clou...

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10th IEEE international conference on Cloud computing (CLOUD)

作者： Chiu, Chui-Hui Singh, Dipak Kumar Wang, Qingyang Lee, Kisung Park, Seung-Jong Louisiana State Univ Ctr Computat & Technol Div Comp Sci & Engn Baton Rouge LA 70803 USA

ISBN: (纸本)9781538619933

Researches affirm that coflow scheduling/routing substantially shortens the average application inner communication time in data center networks(DCNs). The commonly desirable critical features of existing coflow scheduling/routing framework includes (1) coflow scheduling, (2) coflow routing, and (3) per-flow rate-limiting. However, to provide the 3 features, existing frameworks require customized computing frameworks, customized operating systems, or specific external commercial monitoring frameworks on software-defined networking(SDN) switches. These requirements defer or even prohibit the deployment of coflow scheduling/routing in production DCNs. In this paper, we design a coflow scheduling and routing framework, MinCOF which has minimal requirements on hosts and switches for cloud storage area networks(SANs) based on OpenFlow SDN. MinCOF accommodates all critical features of coflow scheduling/routing from previous works. The deployability in production environment is especially taken into consideration. The OpenFlow architecture is capable of processing the traffic load in a cloud SAN. Not necessary requirements for hosts from existing frameworks are migrated to the mature commodity OpenFlow 1.3 Switch and our coflow scheduler. Transfer applications on hosts only need slight enhancements on their existing connection establishment and progress reporting functions. Evaluations reveal that MinCOF decreases the average coflow completion time (CCT) by 12.94% compared to the latest OpenFlow-based coflow scheduling and routing framework.

关键词： Application-aware Networks data Center Networks Software-defined Networking OpenFlow Coflow Scheduling Storage Area Networks Cloud computing

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Performance analysis of triaxial accelerometer for activity recognition

Performance analysis of triaxial accelerometer for activity ...

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international conference on advanced computing, ICAC

作者： M. Poorani V. Vaidehi P. Varalakshmi Department of Electronics MIT Anna University Chennai India School of Computing and Engineering VIT Chennai India Department of Computer Technology MIT Anna University Chennai India

ISBN: (纸本)9781509058891

Human Activity Recognition (HAR) based on accelerometer has become an important mobile application. Activity recognition however depends on X, Y, Z the Cartesian coordinate parameters. There are several approaches for activity recognition. Popular methods of activity recognition using accelerometer reading includes machine learning approach, rule based data mining approach, fuzzy inference approach etc. This paper compares activity recognition based on temporal pattern mining and ANFIS method for wearable sensor accelerometer and mobile accelerometer readings. Though the existing activity recognition using body worn accelerometer gives better accuracy it is found to be costly and consume more power. Hence this paper proposes an ANFIS based activity recognition with the available accelerometer in mobile phone.

关键词： Activity recognition Accelerometers data mining Hidden Markov models Mobile handsets Wearable sensors Feature extraction

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