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2017 Asia-Pacific Computational Intelligence and Information Technology Conference

作者： Tien-Wen Sung You-Te Lu Chia-Jung Lee Yuan-Hsun Liao Chyun-Chyi Chen Fujian Provincial Key Laboratory of Big Data Mining and Applications College of Information Science and EngineeringFujian University of Technology Department of Information and Communication Southern Taiwan University of Science and Technology Department of Information Management Tainan University of Technology Department of Management Information System Far East University

Although online examination for e-learning is widely realized *** the production of question bank is *** paper proposes an assessment authoring tool to assist teachers in creating reusable test question *** items conforms to the IMS Question and Test Interoperability(QTI) specification and are easy to share,reuse,exchange,and access across distributed learning management systems(LMS).System design and implementation were presented in this paper for sharing and contributing development experiences to related works.

关键词： System IMS Authoring tool of sharable question items based on QTI specification for e-learning assessment

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Strategy intervention for the evolution of fairness

arXiv

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arXiv 2017年

作者： Zhang, Yanling Fu, Feng Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Department of Mathematics Dartmouth College HanoverNH United States Department of Biomedical Data Science Geisel School of Medicine Dartmouth College HanoverNH United States

Masses of experiments have shown individual preference for fairness which seems irrational. The reason behind it remains a focus for research. The effect of spite (individuals are only concerned with their own relative standing) on the evolution of fairness has attracted increasing attention from experiments, but only has been implicitly studied in one evolutionary model. The model did not involve high-offer rejections, which have been found in the form of non-monotonic rejections (rejecting offers that are too high or too low) in experiments. Here, we introduce a high offer and a non-monotonic rejection in structured populations of finite size, and use strategy intervention to explicitly study how spite influences the evolution of fairness: five strategies are in sequence added into the competition of a fair strategy and a selfish strategy. We find that spite promotes fairness, altruism inhibits fairness, and the non-monotonic rejection can cause fairness to overcome selfishness, which cannot happen without high-offer rejections. Particularly for the group-structured population with seven discrete strategies, we analytically study the effect of population size, mutation, and migration on fairness, selfishness, altruism, and spite. A larger population size cannot change the dominance of fairness, but it promotes altruism and inhibits selfishness and spite. Intermediate mutation maximizes selfishness and fairness, and minimizes spite;intermediate mutation maximizes altruism for intermediate migration and minimizes altruism otherwise. The existence of migration inhibits selfishness and fairness, and promotes altruism;sufficient migration promotes spite. Our study may provide important insights into the evolutionary origin of fairness. Copyright © 2017, The Authors. All rights reserved.

关键词： Population statistics

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Preface

Advances in Intelligent Systems and Computing

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Advances in Intelligent Systems and Computing 2018年 579卷 V页

作者： Lin, Jerry Chun-Wei Pan, Jeng-Shyang Chu, Shu-Chuan Chen, Chien-Ming School of Computer Science and Technology Harbin Institute of Technology Shenzhen Graduate School ShenzhenGuangdong China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology FuzhouFujian China School of Computer Science Engineering and Mathematics Flinders University Bedford Park SA Australia

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A dynamic data correction algorithm based on polynomial smooth support vector machine

A dynamic data correction algorithm based on polynomial smoo...

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2016 International Conference on Machine Learning and Cybernetics, ICMLC 2016

作者： Pu, Dong-Mei Gao, Da-Qi Yuan, Yu-Bo Department of Computer Science and Engineering East China University of Science and Technology Shanghai200237 China Key Laboratory of Oceanographic Big Data Mining and Application of Zhejiang Province Zhejiang Ocean University Zhoushan Zhejiang316022 China

ISBN: (纸本)9781509003891

data quality plays an important role in modern intelligent information system and is crucial to any data analysis task. Many imperfection-handling techniques avoid overfitting or simply remove offending portions of the data. data correction can help to retain and recover as much information as possible from the original data resources. In this paper, we proposed a novel technique based on polynomial smooth support vector machine. The quadratic polynomial and the first degree of polynomial as the support vector machine smooth functions are investigated. At the same time, the function was used as smooth function to calculate compensation values. In order to show the procedures of our algorithm, some necessary steps need to be considered. Firstly, the original data are normalized, so as to eliminate experimental effects of dimensional problems. Secondly, the three different kinds of smooth functions need to be analysed mathematically. The difference measure are calculated to make sure the results of correction through different data correction models. The results of given noised data sets can show that the proposed the data correction method based on polynomial smooth support vector machine is effectiveness. © 2016 IEEE.

关键词： data mining

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BeCFI: Detecting hidden control flow with performance monitoring counters

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International Journal of High Performance Computing and Networking 2016年第5-6期9卷 470-479页

作者： Zhou, Hong Wei Shi, Wen Chang Yuan, Jin Hui Li, Fu Lin Institute of Electronic Technology Information Engineering University Zhengzhou China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Renmin University of China Beijing China

Most of existing control flow integrity efforts target keeping intended control flow in good integrity. However, they fail to expose hidden control flow that may be introduced by the execution of rootkits, ROP gadgets, etc. To overcome the challenge, we propose an innovative approach BeCFI to detect hidden control flow based on cross-view principle. Since modern processors are capable of observing the execution of all branch instructions, BeCFI obtains the hardware view with the support of performance monitoring counters (PMCs). To obtain software view, we build a software-based counter by compiler-patching and binary-overwriting, and monitor the execution of branch instructions with software-based counters. If a control transfer only appears in hardware view, BeCFI considers that it is hidden control transfer. We have developed a prototype system on Intel x86 Linux kernel. Our evaluations show BeCFI is capable of detecting the hidden control flow introduced by kernel rootkits and ROP attacks. Furthermore our performance tests demonstrate that BeCFI incurs an acceptable overhead. Copyright © 2016 Inderscience Enterprises Ltd.

关键词： Malware

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Differentially private density estimation via Gaussian mixtures model

Differentially private density estimation via Gaussian mixtu...

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International Workshop on Quality of Service

作者： Yuncheng Wu Yao Wu Hui Peng Juru Zeng Hong Chen Cuiping Li Renmin University of China Beijing P.R. China Ministry of Education Key Laboratory of Data Engineering and Knowledge Engineering

ISBN: (纸本)9781509026357

Density estimation can construct an estimate of the probability density function from the observed data. However, such a function may compromise the privacy of individuals. A notable paradigm for offering strong privacy guarantees in data analysis is differential privacy. In this paper, we propose DPGMM, a parametric density estimation algorithm using Gaussian mixtures model (GMM) under differential privacy. GMM is a well-known model that could approximate any distribution and can be solved via Expectation-Maximization (EM) algorithm. The main idea of DPGMM is to add two extra steps after getting the estimated parameters in the M step of each iteration. The first step is the noise adding step, which injects calibrated noise to the estimated parameters according to their L 1 -sensitivities and privacy budgets. The second step is the post-processing step, which post-processes those noisy parameters that might break their intrinsic characteristics. Extensive experiments using both real and synthetic datasets evaluate the performance of DPGMM, and demonstrate that the proposed method outperforms a state-of-art approach.

关键词： Privacy Gaussian distribution Estimation data privacy Covariance matrices Noise measurement data analysis

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A Real-Time Routing Algorithm for End-to-End Communication Networks with QoS Requirements 3

A Real-Time Routing Algorithm for End-to-End Communication N...

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3rd International Conference on Computing Measurement Control and Sensor Network, CMCSN 2016

作者： Hung, Mao-Hsiung Wang, Chia-Hung He, Yao College of Information Science and Engineering Fujian University of Technology No.3 Xueyuan Road University-Town-Minhou-Fuzhou-City350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian Province China

ISBN: (纸本)9781509010936

A real-time end-to-end routing algorithm is developed in this paper for multi-class communication networks with quality of service (QoS) requirements. The proposed algorithm is performed by means of a two-stage procedure. At the initial stage, we predetermine all possible end-to-end paths for preparing a routing database. Through a simple procedure at the second stage, we identify suitable paths statifing the QoS requirements upon connection requests. Numerical experiment showed that the algorithm is an executable and fast method to select end-to-end routing paths in real-time operation process. © 2016 IEEE.

关键词： Routing algorithms

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Reverse Nearest Neighbor Heat Maps: A Tool for Influence Exploration

Reverse Nearest Neighbor Heat Maps: A Tool for Influence Exp...

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IEEE International Conference on data engineering

作者： Yu Sun Rui Zhang Andy Yuan Xue Jianzhong Qi Xiaoyong Du Department of Computing and Information Systems University of Melbourne Renmin University of China and Key Laboratory of Data Engineering and Knowledge Engineering MOE

ISBN: (纸本)9781509020218

We study the problem of constructing a reverse nearest neighbor (RNN) heat map by finding the RNN set of every point in a two-dimensional space. Based on the RNN set of a point, we obtain a quantitative influence (i.e., heat) for the point. The heat map provides a global view on the influence distribution in the space, and hence supports exploratory analyses in many applications such as marketing and resource management. To construct such a heat map, we first reduce it to a problem called Region Coloring (RC), which divides the space into disjoint regions within which all the points have the same RNN set. We then propose a novel algorithm named CREST that efficiently solves the RC problem by labeling each region with the heat value of its containing points. In CREST, we propose innovative techniques to avoid processing expensive RNN queries and greatly reduce the number of region labeling operations. We perform detailed analyses on the complexity of CREST and lower bounds of the RC problem, and prove that CREST is asymptotically optimal in the worst case. Extensive experiments with both real and synthetic data sets demonstrate that CREST outperforms alternative algorithms by several orders of magnitude.

关键词： Heating Radio frequency Indexes

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Search Result Diversification Based on Query Facets

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Journal of Computer Science & Technology 2015年第4期30卷 888-901页

作者：胡莎窦志成王晓捷文继荣 School of Information Renmin University of China Beijing 100872 China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Beijing 100872 China

In search engines, different users may search for different information by issuing the same query. To satisfy more users with limited search results, search result diversification re-ranks the results to cover as many user intents as possible. Most existing intent-aware diversification algorithms recognize user intents as subtopics, each of which is usually a word, a phrase, or a piece of description. In this paper, we leverage query facets to understand user intents in diversification, where each facet contains a group of words or phrases that explain an underlying intent of a query. We generate subtopics based on query facets and propose faceted diversification approaches. Experimental results on the public TREC 2009 dataset show that our faceted approaches outperform state-of-the-art diversification models.

关键词： query intent query facet search result diversification

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An automatic colonies counting based on piecewise circle fitting

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Journal of Information Hiding and Multimedia Signal Processing 2017年第3期8卷 660-669页

作者： Luo, San-Ding Zou, Zheng Tian, Guang-Ya Pan, Jeng-Shyang Liu, Shi-Jian School of Information Science and Engineering Central South University No.932 Lushannan Road ChangshaHunan410005 China School of Information Science and Engineering Fujian University of Technology No.3 Xueyuan Road University Town Minhou FuzhouFujian350118 China The Key Laboratory of Big Data Mining and Applications of Fujian Province Fujian University of Technology No.3 Xueyuan Road University Town Minhou FuzhouFujian350118 China

And counting the total number of bacterial colonies on agar plates can offer essential indicator for microorganism survival rates. However, manual counting is time-consuming while for computer-aided colony counting, the adhesive colonies usually make the colonies counting challenging. To improve the accuracy and efficiency, we pro- pose a fully automatic counting method. Firstly, a color identification process is used for distinguishing the colonies with different color. Secondly, according to the curvature characteristic along the colony boundary, a segments extraction strategy is used for finding the proper split points. Thirdly, piecewise fitting algorithm ranks candidate circles by confidence, and removes the redundant candidate circles to separate touching colonies. Once the circles are determined, all the colonies are marked by corresponding circles. Our method demonstrates a new way of using circle fitting for accurately separating the touching colonies. The experimental results demonstrated that our method is better than two other most cited methods in accuracy and consuming time. © 2017.

关键词： Circle fitting Clustering Colonies counting Colony segmentation Petri dish

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