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  • Open Access

    ARTICLE

    Paragraph Vector Representation Based on Word to Vector and CNN Learning

    Zeyu Xiong1,*, Qiangqiang Shen1, Yijie Wang1, Chenyang Zhu2

    CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 213-227, 2018, DOI:10.3970/cmc.2018.01762

    Abstract Document processing in natural language includes retrieval, sentiment analysis, theme extraction, etc. Classical methods for handling these tasks are based on models of probability, semantics and networks for machine learning. The probability model is loss of semantic information in essential, and it influences the processing accuracy. Machine learning approaches include supervised, unsupervised, and semi-supervised approaches, labeled corpora is necessary for semantics model and supervised learning. The method for achieving a reliably labeled corpus is done manually, it is costly and time-consuming because people have to read each document and annotate the label of each document. Recently, the continuous CBOW model… More >

  • Open Access

    ARTICLE

    Binary Image Steganalysis Based on Distortion Level Co-Occurrence Matrix

    Junjia Chen1, Wei Lu1,2,*, Yuileong Yeung1, Yingjie Xue1, Xianjin Liu1, Cong Lin1,3, Yue Zhang4

    CMC-Computers, Materials & Continua, Vol.55, No.2, pp. 201-211, 2018, DOI:10.3970/cmc.2018.01781

    Abstract In recent years, binary image steganography has developed so rapidly that the research of binary image steganalysis becomes more important for information security. In most state-of-the-art binary image steganographic schemes, they always find out the flippable pixels to minimize the embedding distortions. For this reason, the stego images generated by the previous schemes maintain visual quality and it is hard for steganalyzer to capture the embedding trace in spacial domain. However, the distortion maps can be calculated for cover and stego images and the difference between them is significant. In this paper, a novel binary image steganalytic scheme is proposed,… More >

  • Open Access

    ARTICLE

    Investigation of the Short-Time Photodissociation Dynamics of Furfural in S2 State by Resonance Raman and Quantum Chemistry Calculations

    Kemei Pei1,*, Yueben Dong1, Lei Chen1

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 189-200, 2018, DOI:10.3970/cmc.2018.055.189

    Abstract Raman (resonance Raman, FT-Raman), IR and UV-visible spectroscopy and quantum chemistry calculations were used to investigate the photodissociation dynamics of furfural in S2 state. The resonance Raman(RR) spectra indicate that the photorelaxation dynamics for the S0→S2 excited state is predominantly along nine motions: C=O stretch ν5 (1667 cm-1), ring C=C antisymmetric stretch ν6 (1570 cm-1), ring C=C symmetric stretch ν7 (1472 cm-1), C2-O6-C5 symmetric stretch/C1-H8 rock in plane ν8 (1389 cm-1), C3-C4 stretch/ C1-H8 rock in plane ν9 (1370 cm-1), C5-O6 stretch in plane ν12 (1154 cm-1), ring breath ν13 (1077 cm-1), C3-C4 stretch ν14 (1020 cm-1), C3-C2-O6 symmetric stretch… More >

  • Open Access

    ARTICLE

    Early Stage of Oxidation on Titanium Surface by Reactive Molecular Dynamics Simulation

    Liang Yang1,2, Caizhuang Wang3,*, Shiwei Lin2,*, Yang Cao2, Xiaoheng Liu1

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 177-188, 2018, DOI:10.3970/cmc.2018.055.177

    Abstract Understanding of metal oxidation is very critical to corrosion control, catalysis synthesis, and advanced materials engineering. Metal oxidation is a very complex phenomenon, with many different processes which are coupled and involved from the onset of reaction. In this work, the initial stage of oxidation on titanium surface was investigated in atomic scale by molecular dynamics (MD) simulations using a reactive force field (ReaxFF). We show that oxygen transport is the dominant process during the initial oxidation. Our simulation also demonstrate that a compressive stress was generated in the oxide layer which blocked the oxygen transport perpendicular to the Titanium… More >

  • Open Access

    ARTICLE

    Electronic Structure and Physical Characteristics of Dioxin Under External Electric Field

    Wenyi Yin1,2, Xiangyun Zhang1,2,†, Bumaliya Abulimiti3,*, Yuzhu Liu1,2,*, Yihui Yan1,2, Fengbin Zhou1,2, Feng Jin4

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 165-176, 2018, DOI:10.3970/cmc.2018.055.165

    Abstract Dioxin is a highly toxic and caustic substance, which widely existed in the atmosphere, soil and water with tiny particles. Dioxin pollution has become a major problem that concerns the survival of mankind, which must be strictly controlled. The bond length, bond angle, energy, dipole moment, orbital energy level distribution of dioxin under the external field are investigated using DFT (density functional theory) on basis set level of B3LYP/6-31G (d, p). The results indicate that with the increase of the electric field, the length of one Carbon-Oxygen bond increases while another Carbon-Oxygen bond decreases. The energy gradually decreases with the… More >

  • Open Access

    ARTICLE

    Steganography Using Reversible Texture Synthesis Based on Seeded Region Growing and LSB

    Qili Zhou1, Yongbin Qiu1, Li Li1,*, Jianfeng Lu1, Wenqiang Yuan1, Xiaoqing Feng2, Xiaoyang Mao3

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 151-163, 2018, DOI:10.3970/cmc.2018.055.151

    Abstract Steganography technology has been widely used in data transmission with secret information. However, the existing steganography has the disadvantages of low hidden information capacity, poor visual effect of cover images, and is hard to guarantee security. To solve these problems, steganography using reversible texture synthesis based on seeded region growing and LSB is proposed. Secret information is embedded in the process of synthesizing texture image from the existing natural texture. Firstly, we refine the visual effect. Abnormality of synthetic texture cannot be fully prevented if no approach of controlling visual effect is applied in the process of generating synthetic texture.… More >

  • Open Access

    ARTICLE

    Modelling the Roles of Cewebrity Trust and Platform Trust in Consumers’ Propensity of Live-Streaming: An Extended TAM Method

    Donghui Li1, Guozheng Zhang1,*, Zeng Xu1, Yong Lan1, Yongdong Shi2, Zhiyao Liang2, Haiwen Chen3

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 137-150, 2018, DOI:10.3970/cmc.2018.055.137

    Abstract Live streaming is a booming industry in China, involving an increasing number of Internet users. Previous studies show that trust is a cornerstone to develop e-commerce. Trust in the streaming industry is different from that of other e-commerce areas. There are two major dimensions of trust in the live streaming context: platform trust and cewebrity trust, which are both important for customers to adopt and reuse a specific live streaming service. We collected questionnaire data from 520 participates who have used live streaming services in China. We model the collected data and identified factors that can influence users’ propensity by… More >

  • Open Access

    ARTICLE

    Adversarial Learning for Distant Supervised Relation Extraction

    Daojian Zeng1,3, Yuan Dai1,3, Feng Li1,3, R. Simon Sherratt2, Jin Wang3,*

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 121-136, 2018, DOI:10.3970/cmc.2018.055.121

    Abstract Recently, many researchers have concentrated on using neural networks to learn features for Distant Supervised Relation Extraction (DSRE). These approaches generally use a softmax classifier with cross-entropy loss, which inevitably brings the noise of artificial class NA into classification process. To address the shortcoming, the classifier with ranking loss is employed to DSRE. Uniformly randomly selecting a relation or heuristically selecting the highest score among all incorrect relations are two common methods for generating a negative class in the ranking loss function. However, the majority of the generated negative class can be easily discriminated from positive class and will contribute… More >

  • Open Access

    ARTICLE

    An Abnormal Network Flow Feature Sequence Prediction Approach for DDoS Attacks Detection in Big Data Environment

    Jieren Cheng1,2, Ruomeng Xu1,*, Xiangyan Tang1, Victor S. Sheng3, Canting Cai1

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 95-119, 2018, DOI:10.3970/cmc.2018.055.095

    Abstract Distributed denial-of-service (DDoS) is a rapidly growing problem with the fast development of the Internet. There are multitude DDoS detection approaches, however, three major problems about DDoS attack detection appear in the big data environment. Firstly, to shorten the respond time of the DDoS attack detector; secondly, to reduce the required compute resources; lastly, to achieve a high detection rate with low false alarm rate. In the paper, we propose an abnormal network flow feature sequence prediction approach which could fit to be used as a DDoS attack detector in the big data environment and solve aforementioned problems. We define… More >

  • Open Access

    ARTICLE

    Localization Algorithm of Indoor Wi-Fi Access Points Based on Signal Strength Relative Relationship and Region Division

    Wenyan Liu1, Xiangyang Luo1,*, Yimin Liu1, Jianqiang Liu2, Minghao Liu1, Yun Q. Shi3

    CMC-Computers, Materials & Continua, Vol.55, No.1, pp. 71-93, 2018, DOI:10.3970/cmc.2018.055.071

    Abstract Precise localization techniques for indoor Wi-Fi access points (APs) have important application in the security inspection. However, due to the interference of environment factors such as multipath propagation and NLOS (Non-Line-of-Sight), the existing methods for localization indoor Wi-Fi access points based on RSS ranging tend to have lower accuracy as the RSS (Received Signal Strength) is difficult to accurately measure. Therefore, the localization algorithm of indoor Wi-Fi access points based on the signal strength relative relationship and region division is proposed in this paper. The algorithm hierarchically divide the room where the target Wi-Fi AP is located, on the region… More >

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