Open Access
ARTICLE
Kabir Fardad1, Bahman Najafi1, Sina Faizollahzadeh Ardabili1, Amir Mosavi2,3, 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 of these plants with TS… More >
Open Access
ARTICLE
Qijun Wu1, Limin Han1, Lingxuan Wang2, Xun Gong3,*
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 of CoS molecule grew slightly… More >
Open Access
ARTICLE
Xuewen Zhang1, Zhonghao Li1, Gongshen Liu1,*, 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 strategy of Spark. In this… More >
Open Access
ARTICLE
Shengqun Fang1, Zhiping Cai1,*, 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 categories, and compare this method… More >
Open Access
ARTICLE
Jixin Liu1,*, Ning Sun1,2, 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 our work: (1) after the… More >
Open Access
ARTICLE
Ming Wan1, Jiangyuan Yao2,*, Yuan Jing1, Xi Jin3,4
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 the payloads from industrial communication… More >
Open Access
ARTICLE
Meijuan Wang1,2,*, Jian Wang1, Lihong Guo1,3, 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 of XML data, this paper… More >
Open Access
ARTICLE
Xintao Duan1,*, 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 transmission of the secret image.… More >
Open Access
ARTICLE
Yang Du1, Zhaoxia Yin1,2,*, 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 expansion in identical pay-load and… More >
Open Access
ARTICLE
Zhenguo Gao1, Shixiong Xia1, Yikun Zhang1, Rui Yao1,*, 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 the demand for computing resources… More >
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