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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301-310 订阅

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A Power and Performance Aware Routing Algorithm for Fat Tree Networks 3

A Power and Performance Aware Routing Algorithm for Fat Tree...

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IEEE 3rd international conference on Big data Security on Cloud (BigdataSecurity) / 3rd IEEE international conference on High Performance and Smart computing (HPSC) / 2nd IEEE international conference on Intelligent data and Security (IDS)

作者： Gao, Yongqiang Yu, Lei Inner Mongolia Univ Coll Comp Sci Hohhot Peoples R China

ISBN: (纸本)9781509062966

data center energy consumption has become one of the top concerns in designing and operating large-scale data centers as cloud service providers such as Amazon, Google, IBM and Microsoft have begun to establish more data centers in response to growing requests in clouds. In recent years, extensive efforts have been put into the research of reducing the energy consumption of servers. With the improvement of sever energy efficiency, the energy consumption of data center network, which could account for 10%-20% of the total energy expenditure of a data center, has emerged as a substantial issue. Modern data center networks often use a fat-tree network topology because of its high bisection bandwidth. In this paper, we develop a power and performance aware routing algorithm for fat tree networks that dynamically consolidate network flows and turn off unused network switches in order to reduce network energy consumption while meeting the network performance requirement.

关键词： data center network power routing fat tree network best-worst ant system

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Objective smoking: Towards smoking detection using smartwatch sensors 3rd

Objective smoking: Towards smoking detection using smartwatc...

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3rd international conference on Biomedical and Health Informatics, ICBHI 2017

作者： Maramis, C. Kilintzis, V. Scholl, P. Chouvarda, I. Lab of Computing & Medical Informatics Department of Medicine Aristotle University of Thessaloniki KEDIP Building University Campus Thessaloniki Greece Embedded Systems Department of Computer Science University of Freiburg Freiburg Germany

ISBN: (纸本)9789811074189

Smoking is arguably one of the most harmful lifestyle behaviors with well-known relations to dozens of diseases. As a consequence, smoking monitoring and cessation support have been popular targets for the emerging field of Behavioral Informatics. Although smoking monitoring has been attempted in the past (e.g., self-reporting), the revolution of smart wearable devices has provided the necessary tools for developing truly objective and unobtrusive smoking detection methods applicable in real-life settings. This work takes the first step towards the development of such a method using smartwatch inertial sensory data, with the end-goal of integrating the proposed method in a novel just-in-time intervention for smoking cessation. The paper explores the detection of smoking instances and the constituting puffs from 3-axis gyroscope data that are routinely acquired by any Android Wear smartphone. The feasibility of the method is tested on actual real-life data, yielding very promising preliminary results. © Springer Nature Singapore Pte Ltd. 2018.

关键词： Android (operating system)

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Message from the CCIoT-2017 Symposium Chairs

Proceedings - 2017 IEEE International Conference on Internet...

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Proceedings - 2017 IEEE international conference on Internet of Things, IEEE Green computing and Communications, IEEE Cyber, Physical and Social computing, IEEE Smart data, iThings-GreenCom-CPSCom-Smartdata 2017 2018年 2018-January卷 1xxvi页

作者： Miao, Wang Najjari, Noushin Wang, Haozhe Zhao, Zhiwei University of Exeter United Kingdom University of Electronic Science and Technology of China China

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Fuzzy entropy based feature selection for website user classification in EDoS defense 3rd

Fuzzy entropy based feature selection for website user class...

引用

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

作者： Bhingarkar, Sukhada Shah, Deven MIT College of Engineering Pune Pune India Thakur College of Engineering and Technology Mumbai India

ISBN: (纸本)9789811086595

Economic Denial of Sustainability (EDoS) attack is one of the major web security attacks performed on cloud hosted websites that exploits cloud’s utility model by fraudulently consuming metered resources such as network bandwidth. In such attack, the malicious traffic imitates to be legitimate and hence goes undetected. A way to defend against such attack is to analyze the browsing behavior of the users and classify them. A training dataset to be used for this classification includes some features that are fuzzy which may lead to incorrect results. Hence, there is a need of feature selection mechanism that selects only important features from the feature set and discards the irrelevant one. This paper proposes to use fuzzy entropy based feature selection for classification of website users in EDoS defense. To evaluate the performance, the classification is done with and without doing feature selection. The classification accuracy shows that the proposed approach is capable of producing more accurate results with fewer features than original feature space. © Springer Nature Singapore Pte Ltd. 2018.

关键词： data mining

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data Model Logger - data Discovery for Extract-Transform-Load 19

Data Model Logger - Data Discovery for Extract-Transform-Loa...

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19th IEEE international conference on High Performance computing and Communications (HPCC) / 15th IEEE international conference on Smart City (SmartCity) / 3rd IEEE international conference on data science and Systems (DSS)

作者： Madhikermi, Manik Buda, Andrea Dave, Bhargav Framling, Kary Aalto Univ Sch Sci POB 15400 FI-00076 Espoo Finland

ISBN: (纸本)9781538625880

Information Systems (ISs) are fundamental to streamline operations and support processes of any modern enterprise. Being able to perform analytics over the data managed in various enterprise ISs is becoming increasingly important for organisational growth. Extract, Transform, and Load (ETL) are the necessary pre-processing steps of any data mining activity. Due to the complexity of modern IS, extracting data is becoming increasingly complicated and time-consuming. In order to ease the process, this paper proposes a methodology and the results of a pilot implementation, that aims to simplify data extraction process by leveraging the end-users' knowledge and understanding of the specific IS.

关键词： ETL database Trigger Reverse Engineering data Warehouse Information System Information Retrieval Process Mapping data Discovery

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Message from the GreenCom-2017 Workshop/Symposium Chairs

Proceedings - 2017 IEEE International Conference on Internet...

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作者： Yassein, Muneer Bani Yang, Shusen Huang, Haojun Jordan University of Science and Technology Jordan Xian Jiaotong University China Wuhan University China

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A text mining based literature analysis for learning theories and computer science education 3rd

A text mining based literature analysis for learning theorie...

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

作者： Hodhod, Rania Fleenor, Hillary Columbus State University ColumbusGA31907 United States

ISBN: (纸本)9783319648606

Text mining has been successfully used to discover interesting patterns and extract useful information from analyzing massive text data exists on the internet, books and other text sources. Computer science education has become an initiative for The National science Foundation (NSF) and the White House Office of science and Technology Policy (OSTP) in the United States. Finding the right tools and technologies that can support that initiative and help students succeed and do well while studying computer science is a plus. Although the literature is rich with research for computer science education, there is no clear guide on the use of learning theories to design educational games to teach computer science. Text mining can analyze the literature to find trends for designing educational games for computer science education, in addition to identifying existing gaps. The paper presents the results from analyzing 204 papers to discover the current state of research related to computer science education, using Voyant, a text mining tool. Analysis of results should provide an insight on how learning theories have been considered/used in computer science education and guide future research through identifying what learning theories need to be considered in designing educational games to teach computer science topics, such as data structures. © 2018, Springer international Publishing AG.

关键词： data structures

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Efficient Asynchronous Communication Between Virtual Machines in Embedded Systems 19

Efficient Asynchronous Communication Between Virtual Machine...

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作者： Wang, Rui Xu, Libin Bai, Yuebin Wang, Zhongzhao Yang, Hailong Zhang, Lijun Beihang Univ Sch Comp Sci & Engn Beijing Peoples R China Sci & Technol Commun Networks Lab Shijiazhuang Hebei Peoples R China

ISBN: (纸本)9781538625880

Embedded virtualization systems become increasingly important in the light of mobile computing era. Current OKL4 technology has overcome some limitations of plain virtualization by introducing microkernel approach but also imposes several concerns including incomplete IPC (InterProcess Communication). With this in mind, in this paper a novel asynchronous communication mechanism to optimize original OKL4 IPC mechanism is proposed. The mechanism is able to effectively deal with concurrent communication requests between any virtual machines (VMs) by generating multiple event channels and providing a complete management mechanism. Further, a shared-memory-based bulk data transfer mechanism based on asynchronous communication mechanism is proposed to enrich OKL4 primitive data exchange approaches. In the end, the promising experiment results prove the feasibility and effectiveness of the mechanisms.

关键词： embedded virtualization OKL4 asynchronous communication multiple channel bulk data transfer

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An Efficient Type-Agnostic Approach for Finding Sub-sequences in data 19

An Efficient Type-Agnostic Approach for Finding Sub-sequence...

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作者： Chapuis, Bertil Garbinato, Benoit Andritsos, Periklis Univ Lausanne Lausanne Switzerland Univ Toronto Toronto ON Canada

ISBN: (纸本)9781538625880

In this paper, we present an efficient type-agnostic approach for finding sub-sequences in data, such as text documents or GPS trajectories. Our approach relies on data deduplication for creating an inverted index. In contrast with existing data deduplication techniques that split raw sequences of characters arbitrarily, our approach preserves the semantics of the original sequence via the notion of token and can be used to index normalized data. When compared to indexing methods that preserve the semantics and operate on normalized data, our method increases the relevance of the inverted index, reduces its size and improves its performances. As data normalization is generally not used beyond the scope of textual data, we introduce a framework that helps identify the extent to which data should be normalized regardless of its type. On this basis, we demonstrate with a dataset made of GPS trajectories that our method can be used agnostically: it can be used to index and query data of a completely different type. Finally, we show that the resulting spatial-index is characterized by a better discrimination than classic spatial-indexing approaches.

关键词： Semantics Trajectory Global Positioning System Indexing conferences Dictionaries

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Big data Model of Security Sharing Based on Blockchain 3

Big Data Model of Security Sharing Based on Blockchain

引用

3rd international conference on Big data computing and Communications (BIGCOM)

作者： Li Yue Huang Junqin Qin Shengzhi Wang Ruijin Univ Elect Sci & Technol China Chengdu Sichuan Peoples R China

ISBN: (纸本)9781538633496

The rise of big data age in the Internet has led to the explosive growth of data size. However, trust issue has become the biggest problem of big data, leading to the difficulty in data safe circulation and industry development. The blockchain technology provides a new solution to this problem by combining non-tampering, traceable features with smart contracts that automatically execute default instructions. In this paper, we present a credible big data sharing model based on blockchain technology and smart contract to ensure the safe circulation of data resources.

关键词： big data blockchain smart contract data sharing

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