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41st European conference on Information Retrieval, ECIR 2019

作者： Beel, Joeran Collins, Andrew Kopp, Oliver Dietz, Linus W. Knoth, Petr School of Computer Science and Statistics ADAPT Centre Trinity College Dublin Dublin Ireland Digital Content and Media Sciences Division National Institute of Informatics Tokyo Japan IPVS University of Stuttgart Stuttgart Germany Department of Informatics Technical University of Munich Garching Germany Knowledge Media Institute The Open University London United Kingdom

ISBN: (纸本)9783030157180

We introduce the first ‘living lab’ for scholarly recommender systems. This lab allows recommender-system researchers to conduct online evaluations of their novel algorithms for scholarly recommendations, i.e., recommendations for research papers, citations, conferences, research grants, etc. Recommendations are delivered through the living lab’s API to platforms such as reference management software and digital libraries. The living lab is built on top of the recommender-system as-a-service Mr. DLib. Current partners are the reference management software JabRef and the CORE research team. We present the architecture of Mr. DLib’s living lab as well as usage statistics on the first sixteen months of operating it. During this time, 1,826,643 recommendations were delivered with an average click-through rate of 0.21%. © Springer Nature Switzerland AG 2019.

关键词： Recommender systems

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LSTM-BA: DDoS Detection Approach Combining LSTM and Bayes

LSTM-BA: DDoS Detection Approach Combining LSTM and Bayes

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international conference on Advanced Cloud and Big Data (CBD)

作者： Yan Li Yifei Lu Nanjing University of Science and Technology Nanjing China

The development of cyberspace brings both opportunities and threats, among which Distributed Denial of service (DDoS) is one of the most destructive attacks. A mass of DDoS attack detection methods have been proposed. But more or less there are some problems, either the construction process is complex, or low accuracy, or poor generalization ability. To overcome these problems, in this paper, we propose a new DDoS detection method which combines the Long Short Term Memory (LSTM) and Bayes approach, referred to as LSTM-BA. Through LSTM method, we can identify parts of DDoS attacks with high confidence outputs from LSTM module. For those outputs with low confidence, we further use Bayes method for the second judgment to improve the accuracy. Our proposed method has been validated using publicly available datasets of ISCX2012. The results demonstrate that LSTM-BA has a better performance. More exactly, LSTM-BA achieves 98.15% detection accuracy, which is improved by 0.16% compared with the state-of-the-art method.

关键词： computer crime Machine learning computer architecture Logic gates Bayes methods Feature extraction Microprocessors

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Web-Based Cataract Detection system Using Deep Convolutional Neural Network

Web-Based Cataract Detection System Using Deep Convolutional...

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international conference of the IEEE Nigeria computer Chapter (NigeriaComputConf)

作者： Musa Yusuf Samuel Theophilous Jadesola Adejoke Annah B. Hassan Computer Science Department Bingham University Karu Nigeria

The alarming cases of cataract within the last decade and the projection of cataract cases within the next few decades call for urgent intervention by early diagnosis. Formal ways of detecting cataract such as physical examination, tests and diagnosis are clinic and professional bound. Hence the need for automation process. Some works have been done on computer Aided Diagnosis (CAD) of cataract with tools such as Expert systems, which are limited to their knowledgebase thus inaccurate. Early diagnosis of cataract enables quick intervention and treatment. This paper presents a web-based computer Aided Diagnostic for cataract detection system using Convolutional Neural Network that can be used by any nonprofessional outside the clinic environment. The systems model trained on a data set of 100 eye images using transfer learning which were retrieved from google image search results of “normal human eyes” and “human eye cataract”. It utilized ImageNet model developed in ILSVRC2012 using the Convolutional Neural Network classifier and transferred its knowledge using Transfer learning to train a new model. The new model gained the ability to classify eye images into “Normal” and “Cataractious”. The system was designed to take images as inputs and achieved a Sensitivity of 69%, a Specificity of 86%, Precision of 86%, F-Score of 56% and AUC of 84.56%. Its accuracy score was 78% which was influenced using the model trained during the ImageNet image classification using deep convolutional neural network.

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Internet of building equipment system based on thread network and methods for managing end devices 4

Internet of building equipment system based on thread networ...

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4th IEEE international conference on computer and Communications, ICCC 2018

作者： Shen, Bin Zhang, Guiqing Wang, Ming Li, Chengdong School of Computer Science and Technology Shandong Jianzhu University Jinan China School of Information and Electrical Engineering Shandong Jianzhu University Jinan China

ISBN: (纸本)9781538683392

In order to solve the internal networking, remote communication and optimization control of the end devices in the Internet of Building Equipment, this paper presents an Internet of Building Equipment system based on the Thread network and a series of methods for managing end devices. In this system the single point of failure can be effectively avoided both within the intranet and from the intranet to Internet, and the whole communication process from end devices to the remote server is based on the Internet Protocol and the User Datagram Protocol, without the need for gateways to carry out the protocol conversion. This paper also proposes a method of persisting bidirectional communication between each end device and the server, by which the server can send control commands to end devices at any time. Finally, based on the communication capability among end devices, this paper puts forward an optimization control method for end devices to save energy, or to improve the comfort and security of the occupants' environment. © 2018 IEEE.

关键词： Internet of things

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computer-ASSISTED NON-INVASIVE DIABETES MELLITUS DETECTION system VIA FACIAL KEY BLOCK ANALYSIS 15

COMPUTER-ASSISTED NON-INVASIVE DIABETES MELLITUS DETECTION S...

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international conference on Wavelet Analysis and Pattern Recognition (ICWAPR)

作者： Shu, Ting Zhang, Bob Tang, Yuan-Yan Univ Macao Deparment Comp & Infoimat Sci Fac Scince & Technol Taipa Macao Peoples R China

ISBN: (纸本)9781538652183

A computer-assisted Non-invasive Diabetes Mellitus Detection system through facial key block analysis is designed and developed in this paper. There are four main steps in our system: facial image capture through a non-invasive device, automatic location of the key blocks based on the positions of the two pupils, key block texture feature extraction using Local Binary Pattern with cell-size 21, and classification with Support Vector Machines. In the first step of this system, a specially designed facial image capture device has been developed to capture the facial image of each patient in a standard designed environment. According to Traditional Chinese Medicine theory, various facial regions can reflect the health status of different inner organs. Based on this, four key blocks are located automatically using the positions of the two pupils and used in Diabetes Mellitus detection instead of employing the whole facial image. For the last two steps, an experiment which selects the best value of Local Binary Pattern cell-size and the better classifier of two traditional classifiers (k-Nearest Neighbors and Support Vector Machines) is implemented and its results are applied in this system. In order to test the system performance, the facial images of 200 volunteers consisting of 100 Diabetes Mellitus patients and 100 healthy persons are captured and analyzed through this system. Based on the test result, the computer-assisted Non-invasive Diabetes Mellitus Detection system through facial key block analysis is proven to be effective and efficient at distinguishing Diabetes Mellitus from Healthy patients in real time.

关键词： Disease detection system Diabetes mellitus Facial key block analysis Local binary pattern Support vector machines

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Behind the benefits of using an automated exercise creation system 22

Behind the benefits of using an automated exercise creation ...

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22nd international conference on Knowledge-Based and Intelligent Information and Engineering systems (KES)

作者： Saastamoinen, Kalle Rissanen, Antti Natl Def Univ Dept Mil Technol POB 7 FI-00861 Helsinki Finland

Exercises are an essential part of learning university-level mathematics. Automated assessments provide an easy and flexible way to create new exercises for students. Moreover, students' performances may be monitored in real time. In 2012, we started to test a mathematical exercise creation system originally created in Lappeenranta University of Technology (LUT). The functionality of this system was jointly piloted by LUT and the National Defence University (NDU). The system was tested in the NDU basic mathematics course with 137 cadets. We show in this article that students who used the automated exercise system scored better on examinations than the students from the previous and following year who could not use the system. A statistical summary of the students' results is presented at the end of this paper to support this conclusion. We will also compare this system to the other systems in the market and consider whether it makes sense for universities to develop this kind of system or whether it is simply a waste of time and money. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： computer-managed exercise test mathematics analysis

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Guest Editor's Introduction to the Special Issue on Security and Privacy on Clouds

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IEEE TRANSACTIONS ON CLOUD COMPUTING 2018年第2期6卷 301-302页

作者： Qiu, Meikang Kung, Sun-Yuan Columbia Univ Elect Engn Dept 1322 Mudd Bldg500 W 120th St New York NY 10027 USA Princeton Univ Dept Elect Engn E Quad B230 Princeton NJ 08544 USA

The fifteen papers in this special section focus on cloud computer security and privacy. The emerging paradigm of cloud computing provides a new way to address the constraints of limited energy, capabilities, and resources. Researchers and practitioners have embraced cloud computing as a new approach that has the potential for a profound impact in our daily life and world economy. However, security and privacy protection is a critical concern in the development and adoption of cloud computing. To avoid system fragility and defend against vulnerabilities exploration from cyber attacker, various cyber security techniques and tools have been developed for cloud systems.

关键词： Special issues and sections Cloud computing Privacy computer security computer architecture Encryption

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The system supervising and warning the agricultural meteorological disaster of zhejiang based on WebGIS 7

The system supervising and warning the agricultural meteorol...

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7th international conference on Agro-Geoinformatics, Agro-Geoinformatics 2018

作者： Guo, Fenfen Yao, Yiping Xiao, Jingjing Jin, Zhifeng Yuan, Dehui Wang, Zhihai Second Institute of Oceanography State Oceanic Administration Hangzhou China Zhejiang Meteorological Bureau Zhejiang Climate Center Hangzhou China

ISBN: (纸本)9781538650387

The monitoring and warning system of main agro-meteorological disasters in Zhejiang Province is researched and developed herein based on technology of WebGIS. According to SOA and B/S structure, the system is constructed on *** development platform by using C# and Java computer language, and applied in in Zhejiang Meteorological Department as a subsystem of 'Zhejiang Modern Agricultural Meteorology Business system'. © 2018 IEEE.

关键词： Meteorology

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systematic Resource Allocation in Cloud RAN with Caching as a service under Two Timescales

Systematic Resource Allocation in Cloud RAN with Caching as ...

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作者： Tang, Jianhua Quek, Tony Q. S. Chang, Tsung-Hui Shim, Byonghyo Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Normal University Changsha410081 China Institute of New Media and Communications Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore487372 Singapore Department of Electronic Engineering Kyung Hee University Yongin17104 Korea Republic of School of Science and Engineering Chinese University of Hong Kong Shenzhen518172 China Shenzhen Research Institute of Big Data Shenzhen518172 China Department of Electrical and Computer Engineering Institute of New Media and Communications Seoul National University Seoul08826 Korea Republic of

Recently, cloud radio access network (C-RAN) with caching as a service (CaaS) was proposed to merge the functionalities of communication, computing, and caching (CCC) together. In this paper, we dissect the interactions of CCC in C-RAN with CaaS from two dimensions: physical resource dimension and time dimension. In the physical resource dimension, we identify how to segment the baseband unit (BBU) pool resources (i.e., computation and storage) into different types of virtual machines (VMs). In the time dimension, we address how the long-term resource segmentation in the BBU pool impacts on the short-term transmit beamforming at the remote radio heads. We formulate the problem as a stochastic mixed-integer nonlinear programming (SMINLP) to minimize the system cost, including the server cost, VM cost and wireless transmission cost. After a series of approximation, including sample average approximation, successive convex approximation, and semidefinite relaxation, the SMINLP is approximated as a global consensus problem. The alternating direction method of multipliers (ADMM) is utilized to obtain the solution in a parallel fashion. Simulation results verify the convergence of our proposed algorithm, and also confirm that the proposed scheme is more cost-saving than that without considering the integration of CCC. © 1972-2012 IEEE.

关键词： Integer programming

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China's Efforts to Information service for Visual-Impaired People 16th

China's Efforts to Information Service for Visual-Impaired P...

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16th international conference on computers Helping People with Special Needs (ICCHP)

作者： Gu, Chunbin Bu, Jiajun Song, Shuyi Yu, Zhi Li, Liangcheng Han, Meng Tang, Lizhen Zhejiang Univ Coll Comp Sci Zhejiang Prov Key Lab Serv Robot Alibaba Zhejiang Univ Joint Inst Frontier Technol Hangzhou 310027 Zhejiang Peoples R China China Braille Press Beijing 100050 Peoples R China

ISBN: (纸本)9783319942742;9783319942735

In China, there are more than 13 million visual-impaired people, which obtain information by touching and hearing rather than vision. To help them access to information more conveniently, many efforts have been made in China: Firstly, it provides digital resources by building China Digital Library for Visual Impairment;Secondly, it develops a software called Sunshine Screen Reader to help visual-impaired people search through the computer;Also, it promotes SunshineReader, a portable device, to enable visual-impaired people obtain information from electronic documents and printed text. All these efforts achieve demonstrable results in narrowing down the gap between visual-impaired people and information. Generally speaking, most information can be accessed by CDLVI, Sunshine Screen Reader and SunshineReader.

关键词： Visual-impaired people Information service Assistive technology

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