Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (487)
  • Open Access

    ARTICLE

    Defense Against Poisoning Attack via Evaluating Training Samples Using Multiple Spectral Clustering Aggregation Method

    Wentao Zhao1, Pan Li1,*, Chengzhang Zhu1,2, Dan Liu1, Xiao Liu1

    CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 817-832, 2019, DOI:10.32604/cmc.2019.05957

    Abstract The defense techniques for machine learning are critical yet challenging due to the number and type of attacks for widely applied machine learning algorithms are significantly increasing. Among these attacks, the poisoning attack, which disturbs machine learning algorithms by injecting poisoning samples, is an attack with the greatest threat. In this paper, we focus on analyzing the characteristics of positioning samples and propose a novel sample evaluation method to defend against the poisoning attack catering for the characteristics of poisoning samples. To capture the intrinsic data characteristics from heterogeneous aspects, we first evaluate training data More >

  • Open Access

    ARTICLE

    Development of Cloud Based Air Pollution Information System Using Visualization

    SangWook Han1, JungYeon Seo1, Dae-Young Kim2, SeokHoon Kim3, HwaMin Lee3,*

    CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 697-711, 2019, DOI:10.32604/cmc.2019.06071

    Abstract Air pollution caused by fine dust is a big problem all over the world and fine dust has a fatal impact on human health. But there are too few fine dust measuring stations and the installation cost of fine dust measuring station is very expensive. In this paper, we propose Cloud-based air pollution information system using R. To measure fine dust, we have developed an inexpensive measuring device and studied the technique to accurately measure the concentration of fine dust at the user’s location. And we have developed the smartphone application to provide air pollution More >

  • Open Access

    ARTICLE

    A Multi-Feature Weighting Based K-Means Algorithm for MOOC Learner Classification

    Yuqing Yang1,2, Dequn Zhou1,*, Xiaojiang Yang1,3,4

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 625-633, 2019, DOI:10.32604/cmc.2019.05246

    Abstract Massive open online courses (MOOC) have recently gained worldwide attention in the field of education. The manner of MOOC provides a new option for learning various kinds of knowledge. A mass of data miming algorithms have been proposed to analyze the learner’s characteristics and classify the learners into different groups. However, most current algorithms mainly focus on the final grade of the learners, which may result in an improper classification. To overcome the shortages of the existing algorithms, a novel multi-feature weighting based K-means (MFWK-means) algorithm is proposed in this paper. Correlations between the widely More >

  • Open Access

    ARTICLE

    Multiple Kernel Clustering Based on Self-Weighted Local Kernel Alignment

    Chuanli Wang1,2, En Zhu1, Xinwang Liu1, Jiaohua Qin2, Jianping Yin3,*, Kaikai Zhao4

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 409-421, 2019, DOI:10.32604/cmc.2019.06206

    Abstract Multiple kernel clustering based on local kernel alignment has achieved outstanding clustering performance by applying local kernel alignment on each sample. However, we observe that most of existing works usually assume that each local kernel alignment has the equal contribution to clustering performance, while local kernel alignment on different sample actually has different contribution to clustering performance. Therefore this assumption could have a negative effective on clustering performance. To solve this issue, we design a multiple kernel clustering algorithm based on self-weighted local kernel alignment, which can learn a proper weight to clustering performance for… More >

  • Open Access

    ARTICLE

    A Physical Layer Algorithm for Estimation of Number of Tags in UHF RFID Anti-Collision Design

    Zhong Huang1, Jian Su2, Guangjun Wen1, Wenxian Zheng3, Chu Chu1, Yijun Zhang4,*, Yibo Zhang5

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 399-408, 2019, DOI:10.32604/cmc.2019.05876

    Abstract A priori knowledge of the number of tags is crucial for anti-collision protocols in slotted UHF RFID systems. The number of tags is used to decide optimal frame length in dynamic frame slotted ALOHA (DFSA) and to adjust access probability in random access protocols. Conventional researches estimate the number of tags in MAC layer based on statistics of empty slots, collided slots and successful slots. Usually, a collision detection algorithm is employed to determine types of time slots. Only three types are distinguished because of lack of ability to detect the number of tags in More >

  • Open Access

    ARTICLE

    Application of Self-Organizing Feature Map Neural Network Based on K-means Clustering in Network Intrusion Detection

    Ling Tan1,*, Chong Li2, Jingming Xia2, Jun Cao3

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 275-288, 2019, DOI:10.32604/cmc.2019.03735

    Abstract Due to the widespread use of the Internet, customer information is vulnerable to computer systems attack, which brings urgent need for the intrusion detection technology. Recently, network intrusion detection has been one of the most important technologies in network security detection. The accuracy of network intrusion detection has reached higher accuracy so far. However, these methods have very low efficiency in network intrusion detection, even the most popular SOM neural network method. In this paper, an efficient and fast network intrusion detection method was proposed. Firstly, the fundamental of the two different methods are introduced More >

  • Open Access

    ARTICLE

    An Efficient Crossing-Line Crowd Counting Algorithm with Two-Stage Detection

    Zhenqiu Xiao1,*, Bin Yang2, Desy Tjahjadi3

    CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1141-1154, 2019, DOI:10.32604/cmc.2019.05638

    Abstract Crowd counting is a challenging task in crowded scenes due to heavy occlusions, appearance variations and perspective distortions. Current crowd counting methods typically operate on an image patch level with overlaps, then sum over the patches to get the final count. In this paper we describe a real-time pedestrian counting framework based on a two-stage human detection algorithm. Existing works with overhead cameras is mainly based on visual tracking, and their robustness is rather limited. On the other hand, some works, which focus on improving the performances, are too complicated to be realistic. By adopting… More >

  • Open Access

    ARTICLE

    Fuzzy C-Means Algorithm Automatically Determining Optimal Number of Clusters

    Ruikang Xing1,*, Chenghai Li1

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 767-780, 2019, DOI:10.32604/cmc.2019.04500

    Abstract In clustering analysis, the key to deciding clustering quality is to determine the optimal number of clusters. At present, most clustering algorithms need to give the number of clusters in advance for clustering analysis of the samples. How to gain the correct optimal number of clusters has been an important topic of clustering validation study. By studying and analyzing the FCM algorithm in this study, an accurate and efficient algorithm used to confirm the optimal number of clusters is proposed for the defects of traditional FCM algorithm. For time and clustering accuracy problems of FCM More >

  • Open Access

    ARTICLE

    Controlled Secure Direct Communication Protocol via the Three-Qubit Partially Entangled Set of States

    Gang Xu1,2,*, Ke Xiao1,*, Zongpeng Li3, Xin-Xin Niu2,4, Michael Ryan5

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 809-827, 2019, DOI:10.32604/cmc.2019.04400

    Abstract In this paper, we first re-examine the previous protocol of controlled quantum secure direct communication of Zhang et al.’s scheme, which was found insecure under two kinds of attacks, fake entangled particles attack and disentanglement attack. Then, by changing the party of the preparation of cluster states and using unitary operations, we present an improved protocol which can avoid these two kinds of attacks. Moreover, the protocol is proposed using the three-qubit partially entangled set of states. It is more efficient by only using three particles rather than four or even more to transmit one More >

  • Open Access

    ARTICLE

    An Asynchronous Clustering and Mobile Data Gathering Schema Based on Timer Mechanism in Wireless Sensor Networks

    Jin Wang1,2,3, Yu Gao3, Wei Liu3, Wenbing Wu1, Se-Jung Lim4,*

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 711-725, 2019, DOI:10.32604/cmc.2019.05450

    Abstract Recently, Wireless sensor networks (WSNs) have become very popular research topics which are applied to many applications. They provide pervasive computing services and techniques in various potential applications for the Internet of Things (IoT). An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism (ACMDGTM) algorithm is proposed which would mitigate the problem of “hot spots” among sensors to enhance the lifetime of networks. The clustering process takes sensors’ location and residual energy into consideration to elect suitable cluster heads. Furthermore, one mobile sink node is employed to access cluster heads in accordance with More >

Displaying 451-460 on page 46 of 487. Per Page