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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141-150 订阅

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Traffic Bottleneck Reconstruction LIDAR Orthoimages: A RANSAC Algorithm Feature Extraction 3rd

Traffic Bottleneck Reconstruction LIDAR Orthoimages: A RANSA...

引用

3rd international conference of Reliable Information and Communication Technology (IRICT)

作者： Sakib, Md. Nazmus Rahman, Md. Ashiqur World Univ Bangladesh Plot 13-ARd 5 Dhaka 1205 Bangladesh

ISBN: (纸本)9783319990071;9783319990064

This study attempts a solution for autonomous vehicles to avoid immediate collision due to close proximity between cars. Since LIDAR sensors are widely used for capturing images in autonomous car industry, we depict a scope of using RANSAC algorithm and linear regression to reconstruct the orthoimages to escape traffic bottleneck as well as avoid collision. It is found that LIDAR sensors can't suggests much detail in close distance, and cameras don't perform well in conditions with low light or glare images. dataset is collected from KITTI (Karlsruhe Institute of Technology) containing compressed pixels. Significance resultants focus on error reduction followed by feature extraction simulated with MATLAB. The findings excludes large scale of data size to implement and project in T-way testing for determining strength as well as capability of resultants.

关键词： Autonomous vehicle RANSAC algorithm LIDAR sensor Orthoimage reconstruction Linear regression analysis Traffic bottleneck

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A Model for Addressing Quality Issues in Big data 3rd

A Model for Addressing Quality Issues in Big Data

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3rd international conference of Reliable Information and Communication Technology (IRICT)

作者： Onyeabor, Grace Amina Ta'a, Azman Univ Utara Malaysia Coll Arts & Sci Sch Comp Sintok 06010 Kedah Malaysia Fed Univ Technol Minna Nigeria

ISBN: (纸本)9783319990071;9783319990064

Big data (BD) is everywhere and quite a lot of benefits have been derived from its usage by different organizations. Notwithstanding, there are still numerous technical and research challenges that must be tackled to comprehend and gain its full potential. The major challenges of BD are not just its processing, storage and analytics, there are also challenges associated with it that run across the BD value chain such as the data collection phase, integration and the enforcement of quality. This paper propose a DQ transformation model to evaluate BD quality from the data collection phase through to the visualization phase involving both data-driven and process-driven quality evaluation by assessing the quality of data itself first then assessing the process quality. This is still an ongoing research and hopefully will be experimented using specific data Quality Dimensions (DQDs) like completeness, consistency, accuracy and timeliness with process quality dimensions such as Throughput, response time, latency with their corresponding metrics.

关键词： Big data data Quality data Quality Dimensions

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Big data Analytics in the Malaysian Public Sector: The Determinants of Value Creation 3rd

Big Data Analytics in the Malaysian Public Sector: The Deter...

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3rd international conference of Reliable Information and Communication Technology (IRICT)

作者： Wahdain, Esmat A. Baharudin, Ahmad Suhaimi Ahmad, Mohammad Nazir Univ Sains Malaysia USM Sch Comp Sci Gelugor 11800 Penang Malaysia Hadhramout Univ Coll Comp & Informat Technol Mukalla Yemen Univ Kebangsaan Malaysia Inst Visual Informat Bangi Selangor Malaysia

ISBN: (纸本)9783319990071;9783319990064

Big data analytics is a crucial pillar of organisational success. Today's organisations need to leverage the troves of big data to achieve competitive advantage over their competitors. This is only possible by extracting valuable meaning from the vast amount of data. Big data analytics is the tool used for this value extraction. This research in progress aims to help Malaysian public organisations leverage the BDA capabilities to improve their performance and provide better services for citizens. The research proposed a modified DELTA model, and after exploratory interviews with MAMPU officials, factors believed to be highly influential in the Malaysian context were added such as knowledge sharing and job turnover.

关键词： Big data analytics Malaysia Public sector MAMPU

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Biometric Based Signature Authentication Scheme for Cloud Healthcare data Security 3rd

Biometric Based Signature Authentication Scheme for Cloud He...

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3rd international conference of Reliable Information and Communication Technology (IRICT)

作者： Thangarasu, Gunasekar Dominic, P. D. D. Subramanian, Kayalvizhi Smiley, Sajitha Linton Univ Coll Mantin Negeri Sembilan Malaysia Univ Teknol PETRONAS Seri Iskandar Perak Malaysia

ISBN: (纸本)9783319990071;9783319990064

Cloud computing is a recent and fastest growing area of development in healthcare. Cloud-based healthcare management services are considered as an effective way to manage the data related to healthcare. However, the major problem associated with the healthcare management service is data security. It leads to tax, bank, insurance and medical fraudulence. Hence, retrieval of data onto more secured access is required to improve the security of medical records of healthcare services. In this research, proposed a biometric based signature authentication scheme with neural network for cloud healthcare data security. The neural network is used in this scheme for the accuracy of retrieving the clinical data onto the cloud. The neural network acquires biometric signature through biometric sensor processed with quality checker for effective authentication. This network also has support in terms of statistical learning of the clinical datasets. After various experiments, it is concluded that the proposed method provides faster results with higher sensitivity, specificity with accuracy.

关键词： Biometric Healthcare Neural network data security Hadoop MapReduce

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An privacy preserving and multi-copy supporting pdp algorithm and its application in component testing tool 19

An privacy preserving and multi-copy supporting pdp algorith...

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3rd High Performance computing and Cluster Technologies conference, HPCCT 2019 and the 2nd international conference on Big data and Artificial Intelligence, BDAI 2019

作者： Shi, Yan Zhang, Guozheng Li, Shuyu Computing Technique Research Institute Aviation Industry Corporation of China Xi'an710065 China School of Computer Science Shaanxi Normal University Xi'an710119 China

ISBN: (纸本)9781450371858

Aiming at the problem of malicious data deletion or tampering in the untrusted server-side storage, an improved PDP (Provable data Possession) algorithm supporting privacy protection and multiple copies is proposed in the paper. BLS signature and encrypted copies with random mask are adopted in the algorithm. The implementation of the algorithm is described in detail. Experimental results show that the proposed algorithm achieves better performance compared with the MR-PDP algorithm proposed by Cutmola [6]. Finally, the algorithm is applied in a component testing tool to verify the integrity of component source files before component downloading and deployment. © 2019 Association for computing Machinery.

关键词： Digital storage

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A Fuzz Logic-Based Cloud computing Provider's Evaluation and Recommendation Model 3rd

A Fuzz Logic-Based Cloud Computing Provider's Evaluation and...

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3rd international conference of Reliable Information and Communication Technology (IRICT)

作者： Hasan, Mohd Hilmi Aziz, Norshakirah A. Akhir, Emelia Akashah P. Burhan, Nur Zarith Natasya Mohd Razali, Razulaimi Univ Teknol PETRONAS Comp & Informat Sci Dept Ctr Res Data Sci Seri Iskandar 32610 Perak Malaysia Univ Teknol MARA Bandar Tun Razak 26400 Pahang Malaysia

ISBN: (纸本)9783319990071;9783319990064

The growing number of cloud computing providers has made the selection process difficult and time consuming. This motivates many research to propose cloud computing recommendation system. However, generating an overall rating of a provider based on accumulation of several performance parameters involves uncertainties especially when the computation comprises network-related performance parameters. Hence, this paper proposes a fuzzy logic-based model that evaluates providers based on downlink, uplink and latency parameters, and determines the best provider. The model was constructed based on historical data of the real cloud computing providers implementation. The model was compared against non-fuzzy model, and it showed that the proposed fuzzy logic-based model is better in terms of accuracy. This work implies faster and accurate selection of cloud computing provider.

关键词： Cloud computing provider's recommendation Recommendation system Fuzzy logic recommendation Fuzzy recommendation system

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An Efficient Message Filtering Strategy Based on Asynchronous ADMM with L1 Regularization 3

An Efficient Message Filtering Strategy Based on Asynchronou...

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2019 3rd international conference on data Mining, Communications and Information Technology, DMCIT 2019

作者： Zhang, Jiafeng School of Computer Engineering and Science Shanghai University Shanghai200444 China

With the increment of data scale, distributed machine learning has received more and more attention. However, as the data grows, the dimension of the dataset will increase rapidly, which leads to the increment of the communication traffic in the distributed computing cluster and decreases the performance of the distributed algorithms. This paper proposes a message filtering strategy based on asynchronous alternating direction method of multipliers (ADMM), which can effectively reduce the communication time of the algorithm while ensuring the convergence of the algorithm. In this paper, a soft threshold filtering strategy based on L1 regularization is proposed to filter the parameter of master node, and a gradient truncation filtering strategy is proposed to filter the parameter of slave node. Besides, we update the algorithm asynchronously to reduce the waiting time of the master node. Experiments on large-scale sparse data show that our algorithm can effectively reduce the traffic of messages and make the algorithm reach convergence in a shorter time. © 2019 Published under licence by IOP Publishing Ltd.

关键词： Cluster computing

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Traffic Prediction for Intelligent Transportation System using Machine Learning

Traffic Prediction for Intelligent Transportation System usi...

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r Engineering: Machine Learning and Internet of Things (ICETCE), 2020 3rd international conference on

作者： Gaurav Meena Deepanjali Sharma Mehul Mahrishi Department of Computer Science Central University of Rajasthan Ajmer Rajasthan India Department of Information Technology Swami Keshvanand Institute of Technology Jaipur Rajasthan India

ISBN: (数字)9781728116839

ISBN: (纸本)9781728116846

This paper aims to develop a tool for predicting accurate and timely traffic flow Information. Traffic Environment involves everything that can affect the traffic flowing on the road, whether it's traffic signals, accidents, rallies, even repairing of roads that can cause a jam. If we have prior information which is very near approximate about all the above and many more daily life situations which can affect traffic then, a driver or rider can make an informed decision. Also, it helps in the future of autonomous vehicles. In the current decades, traffic data have been generating exponentially, and we have moved towards the big data concepts for transportation. Available prediction methods for traffic flow use some traffic prediction models and are still unsatisfactory to handle real-world applications. This fact inspired us to work on the traffic flow forecast problem build on the traffic data and *** is cumbersome to forecast the traffic flow accurately because the data available for the transportation system is insanely huge. In this work, we planned to use machine learning, genetic, soft computing, and deep learning algorithms to analyse the big-data for the transportation system with much-reduced complexity. Also, Image Processing algorithms are involved in traffic sign recognition, which eventually helps for the right training of autonomous vehicles.

关键词： Machine learning algorithms Machine learning Prediction algorithms Roads Support vector machines

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The integrated development of "Internet + government service" and government institutional reform 2019

The integrated development of "Internet + government service...

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3rd international conference on Management Engineering, software Engineering and Service sciences, ICMSS 2019

作者： Li, Xian Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)9781450361897

On October 18, 2017, General Secretary Xi Jinping repeatedly mentioned the words "Internet, network power, digital China" in the report of the 19th National Congress of the Communist Party of China, fully reflecting the important significance of "Internet plus, cloud computing and the application of big data" in the national strategic level. at the same time, further proposes major measures to deepen the institutional reform of the party and government organs. Therefore, this paper focuses on the two hot issues raised by the 19th National Congress and discusses the intrinsic relationship between the two. The organic development strategy, institutional mechanism, management technology, put forward suggestions for further improvement, with a view to providing reference for government reform and innovation. © 2019 Association for computing Machinery.

关键词： computing power

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Proposed Mechanism Based on Genetic Algorithm to Find the Optimal Multi-hop Path in Wireless Sensor Networks 3rd

Proposed Mechanism Based on Genetic Algorithm to Find the Op...

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3rd international conference of Reliable Information and Communication Technology (IRICT)

作者： Al-Shalabi, Mohammed Anbar, Mohammed Wan, Tat-Chee Univ Sains Malaysia Natl Adv IPv6 Ctr NAV6 Gelugor 11800 Penang Malaysia Univ Sains Malaysia Comp Sci Dept Gelugor 11800 Penang Malaysia

ISBN: (纸本)9783319990071;9783319990064

In widespread wireless sensor networks, where the cluster heads (CHs) and the base station (BS) are far from each other, data transmission is considered a critical factor because of its influence on the network efficiency in terms of power consumption and lifetime. Direct transmission problem, when a CH sends its data directly to the BS, causes a rapid drain of energy in CHs that are far from the BS. Several studies have been proposed to address this problem by finding intermediate nodes between the CH and the BS, but they suffer from many problems such as the complexity and considering just one parameter to select the intermediate nodes. This paper proposed a new mechanism to find the optimal multi-hop path for data transmission from a CH to the BS by utilizing the Genetic Algorithm (GA). The proposed mechanism aims to increase the network lifetime by reducing the consumed energy in the data transmission process.

关键词： LEACH protocol Genetic Algorithm data transmission Multi-hop path

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