Fangming Bi^{1, 2}, Xuanyi Fu^{1, 2}, Wei Chen^{1, 2, 3, *}, Weidong Fang⁴, Xuzhi Miao^{1, 2}, Biruk Assefa^{1, 5}

CMC-Computers, Materials & Continua, Vol.62, No.1, pp. 199-216, 2020, DOI:10.32604/cmc.2020.06258

Abstract Aiming at the defects of the traditional fire detection methods, which are caused by false positives and false negatives in large space buildings, a fire identification detection method based on video images is proposed. The algorithm first uses the hybrid Gaussian background modeling method and the RGB color model to perform fire prejudgment on the video image, which can eliminate most non-fire interferences. Secondly, the traditional regional growth algorithm is improved and the fire image segmentation effect is effectively improved. Then, based on the segmented image, the dynamic and static features of the fire flame More >

Yue Li¹, Guangquan Xu^2,3, Hequn Xian^1,*, Longlong Rao³, Jiangang Shi^4,*

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 637-647, 2019, DOI:10.31209/2019.100000118

Abstract In order to prevent the spread of Android malware and protect privacy information from being compromised, this study proposes a novel multidimensional hybrid features extraction and analysis method for Android malware detection. This method is based primarily on a multidimensional hybrid features vector by extracting the information of permission requests, API calls, and runtime behaviors. The innovation of this study is to extract greater amounts of static and dynamic features information and combine them, that renders the features vector for training completer and more comprehensive. In addition, the feature selection algorithm is used to further More >

Tao Li¹, Lingyun Wang¹, Yin Chen^1,*, Yongjun Ren¹, Lei Wang¹, Jinyue Xia²

Journal on Artificial Intelligence, Vol.1, No.2, pp. 59-68, 2019, DOI:10.32604/jai.2019.06346

Abstract In order to solve the problem that real-time face recognition is susceptible to illumination changes, this paper proposes a face recognition method that combines Local Binary Patterns (LBP) and Embedded Hidden Markov Model (EHMM). Face recognition method. The method firstly performs LBP preprocessing on the input face image, then extracts the feature vector, and finally sends the extracted feature observation vector to the EHMM for training or recognition. Experiments on multiple face databases show that the proposed algorithm is robust to illumination and improves recognition rate. More >

Jinlai Yang^1,2,3, Liangru Wu^1,2,3,*, Yanhong Pan^1,2,3, Hao Zhong^1,2,3

Journal of Renewable Materials, Vol.7, No.11, pp. 1209-1219, 2019, DOI:10.32604/jrm.2019.07896

Abstract A novel fluorescent composition was firstly isolated from natural winter fresh Moso bamboo shoots, and its optical properties were fully investigated by fluorescence spectroscopy. It could emit strong blue light both in solid and solution state, providing high fluorescence intensity in ethanol. The solution’s concentration and addition of water greatly affected the fluorescence intensity, high concentration and addition of much water could quench fluorescence. Apoptosis results showed that the fluorescent extract (0-25 mg/L) could not induce apoptosis of Hela cells. Confocal fluorescent microscopic imaging in human hepatocellular carcinoma cells (HepG2) was realized using the fluorescent More >

Lingya Meng^{1, *}, Cuiwei Liu², Liping Fang², Yuxing Li², Juntao Fu³

Sound & Vibration, Vol.53, No.4, pp. 111-128, 2019, DOI:10.32604/sv.2019.03835

Abstract When acoustic method is used in leak detection for natural gas pipelines, the external interferences including operation of compressor and valve, pipeline knocking, etc., should be distinguished with acoustic leakage signals to improve the accuracy and reduce false alarms. In this paper, the technologies of extracting characteristics of acoustic signals were summarized. The acoustic leakage signals and interfering signals were measured by experiments and the characteristics of time-domain, frequency-domain and time-frequency domain were extracted. The main characteristics of time-domain are mean value, root mean square value, kurtosis, skewness and correlation function, etc. The features in More >

Xiaoying Chen^{1, 2, *}, Shijun Zhao², Xiaolei Wang², Xuejin Sun², Jing Feng², Nan Ye³

CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 861-875, 2019, DOI:10.32604/cmc.2019.06230

Abstract It is important to extract texture feature from the ground-base cloud image for cloud type automatic detection. In this paper, a new method is presented to capture the contour edge, texture and geometric structure of cloud images by using Contourlet and the power spectrum analysis algorithm. More abundant texture information is extracted. Cloud images can be obtained a multiscale and multidirection decomposition. The coefficient matrix from Contourlet transform of ground nephogram is calculated. The energy, mean and variance characteristics calculated from coefficient matrix are composed of the feature information. The frequency information of the data More >

Junya Sakurai¹, Junya Inoue^2,3,4, Masahiko Demura^4,*, Yoichi Mototake⁵, Masato Okada^4,5, Masayoshi Yamazaki⁴

The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.2, pp. 128-128, 2019, DOI:10.32604/icces.2019.05408

Abstract According to the inherent creep strength concept proposed by Kimura et al., microstructural strengthening effect is expiring after a long-term creep deformation at high temperature. In the region, the solid solution hardening effect becomes dominant so that the rupture time is expected to be a simple function of chemical composition and test conditions. In fact, they found that there was a linear relationship between logarithm rupture time and the amount of Mo for the carbon steel JIS STB410. They also found the positive correlations of Cr and Mn to the logarithmic rupture time. However, it… More >

Engozogho Anris Starlin Peguy^1,2, Bikoro Bi Athomo Arsene^1,2, Vidal Marcia⁵, Denaud Louis⁴, Safou Tchiama Rodrigue^2,3, Charrier Bertrand¹

Journal of Renewable Materials, Vol.7, No.6, pp. 517-522, 2019, DOI:10.32604/jrm.2019.04051

Abstract In order to promote convenient strategies for the utilization of wood wastes from aucoumea klaineana pierre (okoume) timber industry, various chemical analysis were carried out on samples from different origins. Total extractives content of the bark, sapwood and heartwood of okoume were evaluated. thermogravimetric analyses were performed and the stiasny number was calculated. it was found that the bark was richer in fatty acid of high molecular weight while the sapwood was rich in fatty acid of low molecular weight. the condensed tannins content varied according to the origin and the part of the tree. More >

Princy Matlani^1,*, Manish Shrivastava¹

CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.3, pp. 427-458, 2019, DOI:10.32604/cmes.2019.04985

Abstract Real-time wild smoke detection utilizing machine based identification method is not produced proper accuracy, and it is not suitable for accurate prediction. However, various video smoke detection approaches involve minimum lighting, and it is required for the cameras to identify the existence of smoke particles in a scene. To overcome such challenges, our proposed work introduces a novel concept like deep VGG-Net Convolutional Neural Network (CNN) for the classification of smoke particles. This Deep Feature Synthesis algorithm automatically generated the characteristics for relational datasets. Also hybrid ABC optimization rectifies the problem related to the slow… More >

Jun Sun¹, Yan Li¹, Yatian Shen^1,*, Wenke Ding¹, Xianjin Shi¹, Lei Zhang¹, Xiajiong Shen¹, Jing He²

Journal of Information Hiding and Privacy Protection, Vol.1, No.2, pp. 69-75, 2019, DOI:10.32604/jihpp.2019.06357

Abstract Relation extraction is an important task in NLP community. However, some models often fail in capturing Long-distance dependence on semantics, and the interaction between semantics of two entities is ignored. In this paper, we propose a novel neural network model for semantic relation classification called joint self-attention bi-LSTM (SA-Bi-LSTM) to model the internal structure of the sentence to obtain the importance of each word of the sentence without relying on additional information, and capture Long-distance dependence on semantics. We conduct experiments using the SemEval-2010 Task 8 dataset. Extensive experiments and the results demonstrated that the More >