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

共 696 条记录，以下是421-430 订阅

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Discovering the City: Crowdsourcing and Personalized Urban Paths Across Cultural Heritage 1

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3rd international conference on Smart Objects and Technologies for Social Good, GOODTECHS 2017

作者： Delnevo, Giovanni Melis, Andrea Mirri, Silvia Monti, Lorenzo Prandini, Marco Department of Electrical Electronic and Information Engineering "Guglielmo Marconi" Universitá di Bologna Bologna Italy Department of Computer Science and Engineering Universitá di Bologna Bologna Italy Interdepartmental Centre for Industrial ICT Research - CIRI ICT Universitá di Bologna Bologna Italy

ISBN: (数字)9783319761114

ISBN: (纸本)9783319761107

Travel planners and mobile applications related to cultural heritage can play an interesting role in the development of smart cities, when they are integrated each other, engaging the user in? touristic and entertainment activities, letting him/her be a source of cultural resources. This paper focuses on a microservices-based architecture, defined with the aim of providing support in computing personalized urban paths across cultural heritage places and in sharing multimedia resources about points of interest. A prototype of mobile application has been implemented on the basis of such architecture, showing the feasibility of the proposed approach thanks to personas and related scenarios. © ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering 2018.

关键词： Crowdsourcing

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Advanced Fully Homomorphic Encryption Scheme over Real Numbers 4

Advanced Fully Homomorphic Encryption Scheme over Real Numbe...

引用

4th IEEE international conference on Cyber Security and Cloud computing, CSCloud 2017 and 3rd IEEE international conference of Scalable and Smart Cloud, SSC 2017

作者： Gai, Keke Qiu, Meikang Li, Yujun Liu, Xiao-Yang Department of Computer Science Pace University New YorkNY10038 United States School of Automation and Information Engineering Xian University of Technology Shaanxi710048 China Department of Electrical Engineering Columbia University New YorkNY10027 United States

ISBN: (纸本)9781509066438

The broad implementation of cloud computing have led to a dramatically growing in exchanging and using data throughout multiple parties. The main problem restricting the implementation of cloud computing is that users lack controls in cloud systems, from which security and privacy concerns become a major issue for cloud users. Logically, an applicable Fully Homomorphic Encryption (FHE) scheme is an effective solution to protecting data throughout the data usage lifecycle in the cloud system, due to the full control on users' own. However, there is no efficacious FHE scheme developed yet for meeting practical demands by the reason of either unqualified accuracy rate or intolerable latency time. Focus on this issue, we propose an advanced FHE scheme designed for operating real numbers, which is named as Full Homomorphic Encryption over Real Numbers (FHE-RN). Our approach has superb performances in both accuracy and efficiency, which has been proved by our experimental evaluations. © 2017 IEEE.

关键词： Cryptography

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Adaptive sink transmission and relocation to extend the network lifetime of wireless sensor network 3

Adaptive sink transmission and relocation to extend the netw...

引用

3rd international conference on Advances in computing, Communication and Automation (Fall), ICACCA 2017

作者： Pant, Sonu Kumar, Ramesh Singh, Ajeet Department of Computer Science and Engineering GBPEC Pauri Ghurdauri India

ISBN: (纸本)9781509064038

Modern improvement in micro manufacturing technology authorized wireless communication to evolution of low power, low cost and multitasking sensor nodes. Multiple sensing applications take place sincerity as an outcome. It include environmental monitoring, disaster management, object tracking, battlefield surveillance, intrusion detection, etc. In a wireless sensor network (WSN) when data sensed and passed from one sensor to another, there arise a problem of limited battery power. Sink relocation is a method for extend the network lifetime of a WSN. In this paper a new approach of adaptive sink transmission and relocation (AST-EASR) introduces to extend the network lifetime of WSN. Our proposed method categorized in two way, sink transmission and relocation. Sink transmission operation performed by checking the receive signal strength using of heterogeneous lower energy consumption. Other side the task of sink relocation performed by grid based sensing (prior for advance node). Simulation results show that our proposed AST-EASR maximized the network lifetime of WSN as compare to conventional approaches like, energy aware sink relocation (EASR) and one-step moving scheme. © 2017 IEEE.

关键词： Energy utilization

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Rare event prediction using similarity majority under-sampling technique 3rd

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3rd international conference on soft computing in data science, scds 2017

作者： Li, Jinyan Fong, Simon Hu, Shimin Chu, Victor W. Wong, Raymond K. Mohammed, Sabah Dey, Nilanjan Department of Computer Information Science University of Macau China School of Computer Science and Engineering Nanyang Technological University Singapore Singapore School of Computer Science and Engineering University of New South Wales Sydney Australia Department of Computer Science Lakehead University Thunder Bay Canada Department of Information Technology Techno India College of Technology Kolkata India

ISBN: (纸本)9789811072413

In data mining it is not uncommon to be confronted by imbalanced classification problem in which interesting samples are rare. Having too many ordinary but too few rare samples as training data, will mislead the classifier to become over-fitted by learning too much from majority class samples and become under-fitted lacking recognizing power for minority class samples. In this research work, a novel rebalancing technique that under-samples (reduce by sampling) the majority class size for subsiding the imbalanced class distributions without synthesizing extra training samples, is studied. This simple method is called Similarity Majority Under-Sampling Technique (SMUTE). By measuring the similarity between each majority class sample and its surrounding minority class samples, SMUTE effectively discriminates the majority and minority class samples with consideration of not changing too much of the underlying non-linear mapping between the input variables and the target classes. Two experiments are conducted and reported in this paper: one is an extensive performance comparison of SMUTE with the states-of-the-arts using generated imbalanced data;the other is the use of real data representing a case of natural disaster prevention where accident samples are rare. SMUTE is found to be working favourably well over other methods in both cases. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Disaster prevention

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Analyzing Movie Scripts as Unstructured Text 3

Analyzing Movie Scripts as Unstructured Text

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3rd IEEE international conference on Big data computing Service and Applications (BigdataService)

作者： Lee, Seong-Ho Yu, Hye-Yeon Cheong, Yun-Gyung Sungkyunkwan Univ Coll Software Suwon South Korea

ISBN: (纸本)9781509063185

This paper describes our initial attempt to analyze movie scripts for understanding patterns and narrative flow that can be present in storytelling. We collected movie scripts, processed the data using simple natural language processing and machine learning techniques. The result suggests that analyzing big movie script may reveal patterns related to narrative structure.

关键词： movie script scenario data analysis narrative

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Multiservice product comparison system with improved reliability in big data broadcasting 3

Multiservice product comparison system with improved reliabi...

引用

3rd IEEE international conference on science Technology, Engineering and Management, ICONSTEM 2017

作者： Sindoori, K. B. Apoorva Karthikeyan, L. Sivakumar, S. Abirami, G. Durai, Ramesh Babu Department of Information Technology Dhanalakshmi College of Engineering Chennai India Information Technology Dhanalakshmi College of Engineering Chennai India Electrical and Electronics Engineering Dhanalakshmi College of Engineering Chennai India

ISBN: (纸本)9781509048557

Big-data computing is a new critical challenge for the Information and Communication industry. There are large numbers of datasets in petabyte scale where researchers and engineers are dealing with. The distribution of data from one data center to another is difficult. The objective of minimizing the completion time of the BD broadcasting problem can be managed to a single source node. The BD broadcasting problem is solved using the Lock Step Broadcast Tree (LSBT) algorithm. To reduce the complication of the original data broadcasting problem we model it as Lock Step Broadcast Tree (LSBT). To overcome the problem, it allows data to be divided into chunks and sent in a pipeline fashion. The BD broadcasting problem how the nodes may obtain the given massive data cooperatively in a minimum amount of total transmission time. The data transmission in big-data computing is significant factor for the job completion time. This approach lowers the computational complexity and takes least amount of time for completion than other efficient solutions in the literature survey. © 2017 IEEE.

关键词： Locks (fasteners)

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Cloud-Based Video Course Recording Model for WE-TUTOR 14

Cloud-Based Video Course Recording Model for WE-TUTOR

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14th international Symposium on Pervasive Systems, Algorithms and Networks (I-SPAN) / 11th international conference on Frontier of Computer science and Technology (FCST) / 3rd international Symposium of Creative computing (ISCC)

作者： Li, Qing Sheng Li, Jian-Ping Zhejiang Univ Media & Commun Sch Elect & Informat Hangzhou Zhejiang Peoples R China Univ Bradford Fac Engn & Informat Bradford BD7 1DQ W Yorkshire England

ISBN: (纸本)9781538608401

A cloud-based video course recording model is proposed in this paper to record and deal with classroom information in the learning management system (LMS). In the developed model, a new foundations key frame description technology (FKD) has been developed. A cloud-based key frame description library (CKDL) has been improved to raise the speed of retrieval. At the same time, a novel approach has been developed to store the foundations key frame of video course and a related extracting technique has been built to show the transferred video on the client. The results and experiments has demonstrated that the proposed model is effective in frame based video retrieval in the system of WE-TUTOR

关键词： multimedia data integration streaming media flipped classroom cloud computing online course

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Gender and age classification of human faces for automatic detection of anomalous human behaviour 3

Gender and age classification of human faces for automatic d...

引用

3rd IEEE international conference on Cybernetics, CYBCONF 2017

作者： Wang, Xiaofeng Mohd Ali, Azliza Angelov, Plamen School of Information Science and Technology Northwest University Xi'an China Faculty of Computing and Mathematical Sciences Universiti Teknologi MARA Shah Alam Selangor40450 Malaysia School of Computing and Communications InfoLab21 Lancaster University LancasterLA1 4WA United Kingdom

ISBN: (纸本)9781538622018

In this paper, we introduce an approach to classify gender and age from images of human faces which is an essential part of our method for autonomous detection of anomalous human behaviour. Human behaviour is often uncertain, and sometimes it is affected by emotion or environment. Automatic detection can help to recognise human behaviour which later can assist in investigating suspicious events. Central to our proposed approach is the recently introduced transfer learning. It was used on the basis of deep learning and successfully applied to image classification area. This paper is a continuous study from previous research on heterogeneous data in which we use images as supporting evidence. We present a method for image classification based on a pre-trained deep model for feature extraction and representation followed by a Support Vector Machine classifier. Because very few data sets with labels of gender and age exist of face images, we build one dataset named GAFace and applied our proposed method to this dataset achieving excellent results and robustness (gender classification: 90.33% and age classification: 80.17% accuracy) approaching human performance. © 2017 IEEE.

关键词： Image classification

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An Improved Straggler Identification Scheme for data-Intensive computing on Cloud Platforms 4

An Improved Straggler Identification Scheme for Data-Intensi...

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4th IEEE international conference on Cyber Security and Cloud computing, CSCloud 2017 and 3rd IEEE international conference of Scalable and Smart Cloud, SSC 2017

作者： Dai, Wei Ibrahim, Ibrahim Bassiouni, Mostafa Department of Electrical and Computer Engineering United States Department of Computer Science University of Central OrlandoFL United States

ISBN: (纸本)9781509066438

One of the challenges faced by data-intensive computing is the problem of stragglers, which can significantly increase the job completion time. Various proactive and reactive straggler mitigation techniques have been developed to address the problem. The straggler identification scheme is a crucial part of the straggler mitigation techniques, as only when stragglers are detected not only correctly but also early enough, the improvement in job completion time can make a real difference. Although the classical standard deviation method is a widely adopted straggler identification scheme, it is not an ideal solution due to certain inherent limitations. In this paper, we present Tukey's method, another statistical method for outlier detection, which is more suitable for the identification of stragglers for two reasons. First, it is robust to extreme observations from stragglers. Second, it can identify stragglers and, more importantly, start speculative execution earlier than the standard deviation method. Our extensive simulation results confirm that Tukey's method can remarkably outperform the standard deviation method. © 2017 IEEE.

关键词： Statistics

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Accurate Camera Calibration using Iteratively Optimized Algorithm of Control Points 14

Accurate Camera Calibration using Iteratively Optimized Algo...

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作者： Liu, JunJie Liu, YongHuai Zhu, XiangYuan ZhaoQing Univ Sch Comp Sci Zhaoqing Guangdong Peoples R China Aberystwyth Univ Dept Comp Sci Aberystwyth SY23 3DB Dyfed Wales

ISBN: (纸本)9781538608401

Camera calibration and image correction is an important step for most of the computer vision tasks, like 3D metric measurement and multi-view stereo. In this paper, we propose a novel algorithm for camera calibration and image correction. It considers the inaccuracy of 3D pattern (like chessboard) and the lens distortion effect on the feature point detection. After each iteration, the estimated parameters are used to undistorted the images to have better feature detection. The established 3D-2D points are more accurate for further camera calibration. A comparative study based on synthetic data, real image and data from our 3D scanner corrupted by reasonable levels of noise shows that the proposed algorithm successfully calibrated, corrected the distorted images and precisely reconstructed the captured laser stripes in 3D space.

关键词： Iteration Calibration Camera Calibration Iteration

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