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  • Open Access


    A Novel Improved Bat Algorithm in UAV Path Planning

    Na Lin1, Jiacheng Tang1, Xianwei Li2,3, Liang Zhao1,*

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 323-344, 2019, DOI:10.32604/cmc.2019.05674

    Abstract Path planning algorithm is the key point to UAV path planning scenario. Many traditional path planning methods still suffer from low convergence rate and insufficient robustness. In this paper, three main methods are contributed to solving these problems. First, the improved artificial potential field (APF) method is adopted to accelerate the convergence process of the bat’s position update. Second, the optimal success rate strategy is proposed to improve the adaptive inertia weight of bat algorithm. Third chaos strategy is proposed to avoid falling into a local optimum. Compared with standard APF and chaos strategy in UAV path planning scenarios, the… More >

  • Open Access


    Uncertain Knowledge Reasoning Based on the Fuzzy Multi Entity Bayesian Networks

    Dun Li1, Hong Wu1, Jinzhu Gao2, Zhuoyun Liu1, Lun Li1, Zhiyun Zheng1,*

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 301-321, 2019, DOI:10.32604/cmc.2019.05953

    Abstract With the rapid development of the semantic web and the ever-growing size of uncertain data, representing and reasoning uncertain information has become a great challenge for the semantic web application developers. In this paper, we present a novel reasoning framework based on the representation of fuzzy PR-OWL. Firstly, the paper gives an overview of the previous research work on uncertainty knowledge representation and reasoning, incorporates Ontology into the fuzzy Multi Entity Bayesian Networks theory, and introduces fuzzy PR-OWL, an Ontology language based on OWL2. Fuzzy PR-OWL describes fuzzy semantics and uncertain relations and gives grammatical definition and semantic interpretation. Secondly,… More >

  • Open Access


    Text Detection and Recognition for Natural Scene Images Using Deep Convolutional Neural Networks

    Xianyu Wu1, Chao Luo1, Qian Zhang2, Jiliu Zhou1, Hao Yang1, 3, *, Yulian Li1

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 289-300, 2019, DOI:10.32604/cmc.2019.05990

    Abstract Words are the most indispensable information in human life. It is very important to analyze and understand the meaning of words. Compared with the general visual elements, the text conveys rich and high-level moral information, which enables the computer to better understand the semantic content of the text. With the rapid development of computer technology, great achievements have been made in text information detection and recognition. However, when dealing with text characters in natural scene images, there are still some limitations in the detection and recognition of natural scene images. Because natural scene image has more interference and complexity than… More >

  • Open Access


    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 respectively. Then, the self-organizing feature… More >

  • Open Access


    An Intrusion Detection Algorithm Based on Feature Graph

    Xiang Yu1, Zhihong Tian2, Jing Qiu2,*, Shen Su2,*, Xiaoran Yan3

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 255-274, 2019, DOI:10.32604/cmc.2019.05821

    Abstract With the development of Information technology and the popularization of Internet, whenever and wherever possible, people can connect to the Internet optionally. Meanwhile, the security of network traffic is threatened by various of online malicious behaviors. The aim of an intrusion detection system (IDS) is to detect the network behaviors which are diverse and malicious. Since a conventional firewall cannot detect most of the malicious behaviors, such as malicious network traffic or computer abuse, some advanced learning methods are introduced and integrated with intrusion detection approaches in order to improve the performance of detection approaches. However, there are very few… More >

  • Open Access


    Semantics Analytics of Origin-Destination Flows from Crowd Sensed Big Data

    Ning Cao1,2, Shengfang Li1, Keyong Shen1, Sheng Bin3, Gengxin Sun3,*, Dongjie Zhu4, Xiuli Han5, Guangsheng Cao5, Abraham Campbell6

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 227-241, 2019, DOI:10.32604/cmc.2019.06125

    Abstract Monitoring, understanding and predicting Origin-destination (OD) flows in a city is an important problem for city planning and human activity. Taxi-GPS traces, acted as one kind of typical crowd sensed data, it can be used to mine the semantics of OD flows. In this paper, we firstly construct and analyze a complex network of OD flows based on large-scale GPS taxi traces of a city in China. The spatiotemporal analysis for the OD flows complex network showed that there were distinctive patterns in OD flows. Then based on a novel complex network model, a semantics mining method of OD flows… More >

  • Open Access


    Readability Assessment of Textbooks in Low Resource Languages

    Zhijuan Wang1,2, Xiaobin Zhao1,2, Wei Song1,*, Antai Wang3

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 213-225, 2019, DOI:10.32604/cmc.2019.05690

    Abstract Readability is a fundamental problem in textbooks assessment. For low re-sources languages (LRL), however, little investigation has been done on the readability of textbook. In this paper, we proposed a readability assessment method for Tibetan textbook (a low resource language). We extract features based on the information that are gotten by Tibetan segmentation and named entity recognition. Then, we calculate the correlation of different features using Pearson Correlation Coefficient and select some feature sets to design the readability formula. Fit detection, F test and T test are applied on these selected features to generate a new readability assessment formula. Experiment… More >

  • Open Access


    Graph-Based Chinese Word Sense Disambiguation with Multi-Knowledge Integration

    Wenpeng Lu1,*, Fanqing Meng2, Shoujin Wang3, Guoqiang Zhang4, Xu Zhang1, Antai Ouyang5, Xiaodong Zhang6

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 197-212, 2019, DOI:10.32604/cmc.2019.06068

    Abstract Word sense disambiguation (WSD) is a fundamental but significant task in natural language processing, which directly affects the performance of upper applications. However, WSD is very challenging due to the problem of knowledge bottleneck, i.e., it is hard to acquire abundant disambiguation knowledge, especially in Chinese. To solve this problem, this paper proposes a graph-based Chinese WSD method with multi-knowledge integration. Particularly, a graph model combining various Chinese and English knowledge resources by word sense mapping is designed. Firstly, the content words in a Chinese ambiguous sentence are extracted and mapped to English words with BabelNet. Then, English word similarity… More >

  • Open Access


    Credit Card Fraud Detection Based on Machine Learning

    Yong Fang1, Yunyun Zhang2, Cheng Huang1,*

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 185-195, 2019, DOI:10.32604/cmc.2019.06144

    Abstract In recent years, the rapid development of e-commerce exposes great vulnerabilities in online transactions for fraudsters to exploit. Credit card transactions take a salient role in nowadays’ online transactions for its obvious advantages including discounts and earning credit card points. So credit card fraudulence has become a target of concern. In order to deal with the situation, credit card fraud detection based on machine learning is been studied recently. Yet, it is difficult to detect fraudulent transactions due to data imbalance (normal and fraudulent transactions), for which Smote algorithm is proposed in order to resolve data imbalance. The assessment of… More >

  • Open Access


    Joint Spectrum Partition and Performance Analysis of Full-Duplex D2D Communications in Multi-Tier Wireless Networks

    Yueping Wang1,*, Xuan Zhang2, Yixuan Zhang3

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 171-184, 2019, DOI:10.32604/cmc.2019.06204

    Abstract Full-duplex (FD) has been recognized as a promising technology for future 5G networks to improve the spectrum efficiency. However, the biggest practical impediments of realizing full-duplex communications are the presence of self-interference, especially in complex cellular networks. With the current development of self-interference cancellation techniques, full-duplex has been considered to be more suitable for device-to-device (D2D) and small cell communications which have small transmission range and low transmit power. In this paper, we consider the full-duplex D2D communications in multi-tier wireless networks and present an analytical model which jointly considers mode selection, resource allocation, and power control. Specifically, we consider… More >

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