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Kabir Fardad¹, Bahman Najafi¹, Sina Faizollahzadeh Ardabili¹, Amir Mosavi^2,3, Shahaboddin Shamshirband,^4,5,*, Timon Rabczuk²
CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 381-392, 2018, DOI:10.3970/cmc.2018.01803
Abstract Glycyrrhiza glabra, Mint, Cuminum cyminum, Lavender and Arctium medicinal are considered as edible plants with therapeutic properties and as medicinal plants in Iran. After extraction process of medicinal plants, residual wastes are not suitable for animal feed and are considered as waste and as an environmental threat. At present there is no proper management of waste of these plants and they are burned or buried. The present study discusses the possibility of biogas production from Glycyrrhiza Glabra Waste (GGW), Mentha Waste (MW), Cuminum Cyminum Waste (CCW), Lavender Waste (LW) and Arctium Waste (AW). 250 g… More >

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1477

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Qijun Wu¹, Limin Han¹, Lingxuan Wang², Xun Gong^3,*
CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 393-403, 2018, DOI:10.3970/cmc.2018.01740
Abstract We optimized the ground-state stable configuration of CoS molecule in different external radiation fields (0-0.04 atomic units (a.u.)) at the basis set level of 6-311G++ (d, p) using the B3LYP density functional theory. On this basis, the molecular structure, total energy, energy gap, and the intensities of infrared ray (IR) spectra, Raman spectra, and ultraviolet-visible (UV-Vis) absorption spectra of CoS molecule were computed using the same method. The results showed that the molecular structure changed greatly under the effect of the external radiation fields and had significant dependency on the radiation fields. The total energy More >

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2256

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1348

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Xuewen Zhang¹, Zhonghao Li¹, Gongshen Liu^1,*, Jiajun Xu¹, Tiankai Xie², Jan Pan Nees¹
CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 405-417, 2018, DOI:10.3970/cmc.2018.02527
Abstract As a main distributed computing system, Spark has been used to solve problems with more and more complex tasks. However, the native scheduling strategy of Spark assumes it works on a homogenized cluster, which is not so effective when it comes to heterogeneous cluster. The aim of this study is looking for a more effective strategy to schedule tasks and adding it to the source code of Spark. After investigating Spark scheduling principles and mechanisms, we developed a stratifying algorithm and a node scheduling algorithm is proposed in this paper to optimize the native scheduling More >

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1495

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Shengqun Fang¹, Zhiping Cai^1,*, Wencheng Sun¹, Anfeng Liu², Fang Liu³, Zhiyao Liang⁴, Guoyan Wang⁵
CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 419-433, 2018, DOI:10.3970/cmc.2018.02289
Abstract By using efficient and timely medical diagnostic decision making, clinicians can positively impact the quality and cost of medical care. However, the high similarity of clinical manifestations between diseases and the limitation of clinicians’ knowledge both bring much difficulty to decision making in diagnosis. Therefore, building a decision support system that can assist medical staff in diagnosing and treating diseases has lately received growing attentions in the medical domain. In this paper, we employ a multi-label classification framework to classify the Chinese electronic medical records to establish corresponding relation between the medical records and disease… More >

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1578

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Jixin Liu^1,*, Ning Sun^1,2, Xiaofei Li¹, Guang Han¹, Haigen Yang¹, Quansen Sun³
CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 435-446, 2018, DOI:10.3970/cmc.2018.02177
Abstract Rare bird has long been considered an important in the field of airport security, biological conservation, environmental monitoring, and so on. With the development and popularization of IOT-based video surveillance, all day and weather unattended bird monitoring becomes possible. However, the current mainstream bird recognition methods are mostly based on deep learning. These will be appropriate for big data applications, but the training sample size for rare bird is usually very short. Therefore, this paper presents a new sparse recognition model via improved part detection and our previous dictionary learning. There are two achievements in More >

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2675

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1357

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Ming Wan¹, Jiangyuan Yao^2,*, Yuan Jing¹, Xi Jin^3,4
CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 447-463, 2018, DOI:10.3970/cmc.2018.02195
Abstract As the main communication mediums in industrial control networks, industrial communication protocols are always vulnerable to extreme exploitations, and it is very difficult to take protective measures due to their serious privacy. Based on the SDN (Software Defined Network) technology, this paper proposes a novel event-based anomaly detection approach to identify misbehaviors using non-public industrial communication protocols, and this approach can be installed in SDN switches as a security software appliance in SDN-based control systems. Furthermore, aiming at the unknown protocol specification and message format, this approach first restructures the industrial communication sessions and merges More >

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2755

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1487

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Meijuan Wang^1,2,*, Jian Wang¹, Lihong Guo^1,3, Lein Harn⁴
CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 465-482, 2018, DOI:10.3970/cmc.2018.02568
Abstract In the era of big data, the conflict between data mining and data privacy protection is increasing day by day. Traditional information security focuses on protecting the security of attribute values without semantic association. The data privacy of big data is mainly reflected in the effective use of data without exposing the user’s sensitive information. Considering the semantic association, reasonable security access for privacy protect is required. Semi-structured and self-descriptive XML (eXtensible Markup Language) has become a common form of data organization for database management in big data environments. Based on the semantic integration nature More >

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2818

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1338

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Xintao Duan^1,*, Haoxian Song¹, Chuan Qin², Muhammad Khurram Khan³
CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 483-493, 2018, DOI:10.3970/cmc.2018.01798
Abstract In this paper, we propose a novel coverless image steganographic scheme based on a generative model. In our scheme, the secret image is first fed to the generative model database, to generate a meaning-normal and independent image different from the secret image. The generated image is then transmitted to the receiver and fed to the generative model database to generate another image visually the same as the secret image. Thus, we only need to transmit the meaning-normal image which is not related to the secret image, and we can achieve the same effect as the More >

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3019

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1524

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Yang Du¹, Zhaoxia Yin^1,2,*, Xinpeng Zhang³
CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 495-507, 2018, DOI:10.3970/cmc.2018.02440
Abstract This paper proposes a lossless and high payload data hiding scheme for JPEG images by histogram modification. The most in JPEG bitstream consists of a sequence of VLCs (variable length codes) and the appended bits. Each VLC has a corresponding RLV (run/length value) to record the AC/DC coefficients. To achieve lossless data hiding with high payload, we shift the histogram of VLCs and modify the DHT segment to embed data. Since we sort the histogram of VLCs in descending order, the filesize expansion is limited. The paper’s key contribution includes: Lossless data hiding, less filesize More >

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2298

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1528

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Zhenguo Gao¹, Shixiong Xia¹, Yikun Zhang¹, Rui Yao^1,*, Jiaqi Zhao¹, Qiang Niu¹, Haifeng Jiang²
CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 509-521, 2018, DOI:10.3970/cmc.2018.02634
Abstract The colour feature is often used in the object tracking. The tracking methods extract the colour features of the object and the background, and distinguish them by a classifier. However, these existing methods simply use the colour information of the target pixels and do not consider the shape feature of the target, so that the description capability of the feature is weak. Moreover, incorporating shape information often leads to large feature dimension, which is not conducive to real-time object tracking. Recently, the emergence of visual tracking methods based on deep learning has also greatly increased… More >

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2744

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1395

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Lizhi Xiong^1,*, Yunqing Shi²
CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 523-539, 2018, DOI:10.3970/cmc.2018.01791
Abstract Advanced cloud computing technology provides cost saving and flexibility of services for users. With the explosion of multimedia data, more and more data owners would outsource their personal multimedia data on the cloud. In the meantime, some computationally expensive tasks are also undertaken by cloud servers. However, the outsourced multimedia data and its applications may reveal the data owner’s private information because the data owners lose the control of their data. Recently, this thought has aroused new research interest on privacy-preserving reversible data hiding over outsourced multimedia data. In this paper, two reversible data hiding… More >

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1393

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Lingyun Xiang^1,2, Yan Li², Wei Hao^3,*, Peng Yang⁴, Xiaobo Shen⁵
CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 541-559, 2018, DOI:10.3970/cmc.2018.03510
Abstract For protecting the copyright of a text and recovering its original content harmlessly, this paper proposes a novel reversible natural language watermarking method that combines arithmetic coding and synonym substitution operations. By analyzing relative frequencies of synonymous words, synonyms employed for carrying payload are quantized into an unbalanced and redundant binary sequence. The quantized binary sequence is compressed by adaptive binary arithmetic coding losslessly to provide a spare for accommodating additional data. Then, the compressed data appended with the watermark are embedded into the cover text via synonym substitutions in an invertible manner. On the More >

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1593