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检索条件"任意字段=3rd International Conference on Soft Computing in Data Science, SCDS 2017"

共 694 条记录，以下是261-270 订阅

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Parameter optimization of support vector machine using dragonfly algorithm 3rd

Parameter optimization of support vector machine using drago...

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3rd international conference on Advanced Intelligent Systems and Informatics, AISI 2017

作者： Tharwat, Alaa Gabel, Thomas Hassanien, Aboul Ella Faculty of Computer Science and Engineering Frankfurt University of Applied Sciences Frankfurt am Main Germany Faculty of Computers and Information Cairo University Giza Egypt Cairo Egypt

ISBN: (纸本)9783319648606

Support Vector Machine (SVM) parameters such as penalty and kernel parameters have a great influence on the complexity and accuracy of the classification model. In this paper, Dragonfly algorithm (DA) has been proposed to optimize the parameters of SVM;thus, the classification error can be decreased. To evaluate the proposed model (DA-SVM), the experiment adopted six standard datasets which are obtained from UCI machine learning data repository. For verification, the results of the DA-SVM algorithm are compared with two well-known optimization algorithms, namely, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). The experimental results demonstrated that the proposed model is capable to find the optimal values of the SVM parameters and avoids the local optima problem. © 2018, Springer international Publishing AG.

关键词： Support vector machines

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Traffic Paralysis Alarm System Based on Strong Associated Subnet 3rd

引用

3rd international conference on Human Centered computing (HCC)

作者： Yu, Chen Zhu, Shaohui Chen, Hanhua Zhang, Ruiguo Zhou, Jiehan Jin, Hai Huazhong Univ Sci & Technol Cluster & Grid Comp Lab Big Data Technol & Syst Lab Serv Comp Technol & Syst LabSch Comp Sci & Techn Wuhan 430074 Hubei Peoples R China Siemens Ltd Beijing Peoples R China Univ Oulu Oulu Finland

ISBN: (纸本)9783319745213;9783319745206

Urban traffic congestion is a major problem for urban transportation management all over the world. However, traditional research focuses only on detection and description of urban traffic situations, which are not enough for improving urban traffic conditions. In this paper, we distinguish two types of traffic congestion: traffic paralysis and traffic jams. The former is the state that traffic is almost stagnant in a large area and on many roads, and it will take a long time before recovering the normal traffic flow. In comparison, a traffic jam has less negative effect on traffic flow and recovers easily. According to this, we propose a traffic paralysis alarm system based on strong associated subnet to alert traffic paralysis incidents. The system orients to city road network, mines association rules between road segments, constructs the strong associated subnets and detects traffic anomalies with floating car GPS data. We analyze two parameters of our proposed system with a true dataset generated by over 2000 taxicabs in Zhuhai and explain our system with a simulation experiment on VISSIM.

关键词： Traffic paralysis Association rule Strong associated subnet Alarm

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Methodology of Selecting the Hadoop Ecosystem Configuration in Order to Improve the Performance of a Plagiarism Detection System 3rd

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3rd international KEYSTONE conference (IKC)

作者： Sobecki, Andrzej Kepa, Marcin Gdansk Univ Technol Ul G Narutowicza 11-12 PL-80233 Gdansk Poland

ISBN: (纸本)9783319744971;9783319744964

The plagiarism detection problem involves finding patterns in unstructured text documents. Similarity of documents in this approach means that the documents contain some identical phrases with defined minimal length. The typical methods used to find similar documents in digital libraries are not suitable for this task (plagiarism detection) because found documents may contain similar content and we have not any warranty that they contain any of identical phrases. The article describes an example method of searching for similar documents contains identical phrases in big documents repositories, and presents a problem of selecting storage and computing platform suitable for presented method using in plagiarism detection systems. In the article we present comparison of the mentioned above method implementations using two computing platforms: KASKADA and Hadoop with different configurations in order to test and compare their performance and scalability. The method using the default tools available on the Hadoop platform i.e. HDFS and Apache Spark offers worse performance than the method implemented on the KASKADA platform using the NFS (Network File System) and the processing model Master/Slave. The advantage of the Hadoop platform increases with the use of additional data structures (hash-map) and tools offered on this platform, i.e. HBase (NoSQL). The tools integrated with the Hadoop platform provide a possibility of creating efficient and a scalable method for finding similar documents in big repositories. The KASKADA platform offers efficient tools for analysing data in real-time processes i.e. when there is no need to compare the input data to a large collection of information (patterns) and to use the advanced data structures. The Contribution of this article is the comparison of the two computing and storage platforms in order to achieve better performance of the method used in the plagiarism detection system to find similar documents containing identical phrases

关键词： data structures

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Automatic arabic ontology construction framework: An insectivore’s animal case study 3rd

Automatic arabic ontology construction framework: An insecti...

引用

3rd international conference on Advanced Intelligent Systems and Informatics, AISI 2017

作者： Fadl, Dalia Abbas, Safia Aref, Mostafa Computer Science Department Faculty of Computers and Information Sciences Ain Shams University Cairo Egypt

ISBN: (纸本)9783319648606

Arabic is the official language of millions of people in the Middle East and northern African countries. Arabic ontology is the foundation of the formulation of Arabic Semantic Web. Surprisingly, little has been done in the field of computerized language and lexical resources. This paper introduces a framework that generates an Arabic Ontology from a semi-structured data (XML documents associated with graph schema), in which, XML schema is created and utilized in the graph schema development (XSG). Finally, the paper provides a case study, insectivore’s case, where the developed Arabic ontology is applied. The results consist of 143 words, 10 Concepts, 10 elements and 20 relations. The generated ontology is evaluated using data-driven evaluation method and tree based mining. 65% of the source XML documents have been included in the insectivore’s case study. This result can be refined more to reach satisfying results. © 2018, Springer international Publishing AG.

关键词： Ontology

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A sugeno-mamdani fuzzy system based soft computing approach towards sensor node localization with optimization 3rd

A sugeno-mamdani fuzzy system based soft computing approach ...

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3rd international conference on Next Generation computing Technologies, NGCT 2017

作者： Kumar, Abhishek Saini, Bhawana Faculty- IT iNurture Education Solutions Private Limited Bangalore560052 India

ISBN: (纸本)9789811086595

Localization implies determining or tracking the position of sensor nodes accurately within the deployment area. Most of the localization approaches involve use of some deployed nodes whose position coordinates are already known to us (using Geographical Positioning System (GPS) or some other method) called landmarks or anchors. As fuzzy systems are apt at handling imprecise and uncertain values, this study attempts to leverage the imprecision and uncertainty handling ability of soft computing techniques such as Fuzzy Logic. An aggregated Mamdani- Sugeno Fuzzy Inference System based localization approach has been proposed using triangular membership functions. One input Received Signal Strength Indicator (RSSI), 5 rules and one output (weight) model has been implemented. The output weight indicated the proximity of a particular anchor to an unknown node. The weight was then used in weighted centroid to compute the estimated position of the unknown sensor node. The solution was optimized using Gauss Newton method. The accuracy of the proposed scheme was 50% to 90% better than centroid, weighted centroid and some other works done using soft computing techniques. A coverage of almost 97–98% can be achieved in least computational time. The average processing time of the proposed technique was approximately 1.5 s. The number of anchors required to localize the nodes is also extremely less. Furthermore, being computationally simple, the algorithm does not require any extra hardware and can be implemented in pure decentralized manner. This study also offers new insights into how optimization techniques such as Gauss Newton method can be used to significantly improve the localization accuracy and to solve the problem of localization in large scale sensor networks where number of sensor nodes are in range of thousands. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Sensor nodes

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Enhanced secure transmission of data in wireless body area network for health care applications 3rd

Enhanced secure transmission of data in wireless body area n...

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3rd international conference on Next Generation computing Technologies, NGCT 2017

作者： Kumar, Sumit Tomar, Anurag Singh Chaurasiya, Sandip K. School of Computer Science and Engineering College of Engineering Studies University of Petroleum and Energy Studies Dehradun India

ISBN: (纸本)9789811086595

The advent of new technologies like cloud computing, Internet of Things and Wireless Body Area Networks (WBAN) have largely promoted the e-healthcare management. E-healthcare eases the life of patients in society and provides them freedom from going to hospital physically on regular intervals. Presently, E-healthcare is facing the challenges including authenticity and privacy of information during transmission. To maintain secrecy of messages knapsack cryptosystem have been applied in WBAN. For authentication of data transmitted in WBAN, we have recommended a modified and improved recovery based digital signature scheme with batch verification of messages that improve the performance of underlying algorithm in terms of computation. Proposed algorithm does not require computing one way hash for digital signature generation. Security analysis of proposed work has been presented to validate the privacy and security of message against various attacks. The results demonstrate performance improvement in digital signature verification scheme. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Authentication

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Collective behavior aware collaborative caching for mobile edge computing 1

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3rd international conference on Smart computing and Communications, SmartCom 2018

作者： Jiang, Hao Huang, Hehe Jiang, Ying Wang, Yuan Zeng, Yuanyuan Zhou, Chen School of Electronic Information Wuhan University Wuhan China School of Data and Computer Science Sun Yat-Sen University Guangzhou China China Ship Development and Design Center Wuhan China

ISBN: (数字)9783030057558

ISBN: (纸本)9783030057541

In Mobile Edge computing (MEC) paradigm, popular and repetitive content can be cached and offloaded from nearby MEC server in order to reduce the backhaul overload. Due to hardware limitation of MEC devices, collaboration among MEC servers can greatly improve the cache performance. In this paper, we propose a Collective Behavior aware Collaborative Caching (CBCC) method. At first, we propose to discover the collective behavior of users by using content-location similarity network fusion algorithm. our analysis is based on real dataset of usage detail records and explore the heterogeneity and predictability of collective behavior during content access. Based on it, we propose a collaborative relationship model that relies on the collective behavior. Then, the collaborative caching placement is formulated by solving a multi-objective optimization problem. Our simulations are based on the real dataset from cellular systems. The numerical results show that the proposed method achieves performance gains in terms of both hit rate and transmission cost. © 2018, Springer Nature Switzerland AG.

关键词： Mobile edge computing

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The evaluation of web based academic progress information system using heuristic evaluation and user experience questionnaire (UEQ) 3

The evaluation of web based academic progress information sy...

引用

3rd international conference on Informatics and computing, ICIC 2018

作者： Paramitha, A.A. Istri Ita Dantes, Gede Rasben Indrawan, Gede Computer Science Department Ganesha University of Education Bali Indonesia

ISBN: (纸本)9781538669204

This research is aimed to evaluate the interface and user experience of SIsKa, and then to give recommendation of the system interface. SIsKA is a web-based information system which is developed to thesis management computer science department of post graduate students Ganesha University of education. This evaluation is aimed to identify the problems faced by the users when using the system and measure the respond of the user when interacting through the system. The interface evaluation is done by means of heuristic evaluation technic;meanwhile the evaluation of user experience is done by means of User Experience Questionnaire. In the heuristic evaluation done by three evaluators, it is found that there are 40 violations over the 10 Nielsen's principal. Based on the UEQ result, it is found that in 20 SIsKA users, the average score for each aspect are: attractiveness aspect is 1,59, perspicuity aspect is 1,75, efficiency aspect is 1,64, dependability aspect is 1,40, stimulation aspect is 1,56, and novelty aspect is 1,10. After comparing the average score in dataset product of UEQ data Analysis Tool, it is found that the attractiveness, perspicuity, efficiency, and novelty aspects of SIsKA are categorized as good. The dependability aspect is categorized as above average, and stimulation aspect is categorized as excellent. The recommendation of interface of SIsKA users is focused on 10 most severe problems found in heuristic evaluation. This recommendation is done in the form of wireframe, so it will be easier to draw the real framework of the website. The result of this research can be used as the suggestion and reference for the SIsKA developers to improve the quality of SIsKA particularly on the system interface. © 2018 IEEE.

关键词： User interfaces

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Event data analysis in large virtualized environment 3rd

Event data analysis in large virtualized environment

引用

3rd international conference on Cognitive computing and Information Processing, CCIP 2017

作者： Bharath, M.B. Ashoka, D.V. EMC Software and Services India Pvt. Ltd Bangalore India JSS Academy of Technical Education Bangalore India

ISBN: (纸本)9789811090585

Monitoring large virtualized datacenter is a daunting task. Around 3 to 3.5 million of events/alerts are received annually from 90+ customers, managed by our organization. Global command centers process these events in real-time and takes an appropriate necessary action for each of those alerts. One of the challenging tasks is to extract useful analytical details out of this large dataset. Attempts to run analytics on this event data poses a problem like heterogeneous source, unstructured data without any centralized repository to collect these events etc. These three issues are the same classic issues face by any "Big data" analysis. To address this issues a novel unified framework is built. This paper focus on big data problems and the solution proposed to address event data analysis in large virtualized environment as a use case. Along with this detailed design and implementation of the proposed solution with resulting report details are also discussed. © 2018, Springer Nature Singapore Pte Ltd.

关键词： data Analytics

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Hybrid optimization in big data: Error detection and data repairing by big data cleaning using CSO-GSA 3rd

Hybrid optimization in big data: Error detection and data re...

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3rd international conference on Cognitive computing and Information Processing, CCIP 2017

作者： Rama Satish, K.V. Kavya, N.P. RNS Institute of Technology Bengaluru India

ISBN: (纸本)9789811090585

data cleaning is an important process in the history of data acquisition, data storage, data management and data analytics, and is still go through rapid development. In fact, cleaning of data is considered as a very important challenging task in the Big data era, due to the exponential growth of data in terms volume and variety of data in most of the applications. This paper focus to prove an accurate data extraction system in different ways of data cleaning, i.e., error detection methods and data repairing algorithms. To achieve the accuracy of data extraction and improve the quality of data, this paper proposes a hybrid Cuckoo Search Optimization along with Gravitational Search algorithm (CSO-GSA) which is used to effectively detect the error from the data received by the source file and repairs the data before delivering it. Through the experiment on the MATLAB platform, it is exhibits the proposed approach to bringing down the time for error detection and correction in huge data sets with acceptable error detecting accuracy. © 2018, Springer Nature Singapore Pte Ltd.

关键词： Big data

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