Shengting Wu¹, Yuling Liu^1,*, Jingwen Wang², Qi Li¹

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1207-1222, 2019, DOI:10.32604/cmc.2019.05835

Abstract Sentiment analysis is a research hot spot in the field of natural language processing and content security. Traditional methods are often difficult to handle the problems of large difference in sample distribution and the data in the target domain is transmitted in a streaming fashion. This paper proposes a sentiment analysis method based on Kmeans and online transfer learning in the view of fact that most existing sentiment analysis methods are based on transfer learning and offline transfer learning. We first use the Kmeans clustering algorithm to process data from one or multiple source domains and select the data similar… More >

Xin Li^1,2, Yanchun Liang^1,2, Minghao Zhao^1,2, Chong Wang^1,2,3, Yu Jiang^1,2,*

CMC-Computers, Materials & Continua, Vol.60, No.3, pp. 1073-1085, 2019, DOI:10.32604/cmc.2019.05929

Abstract In recent years, extreme weather events accompanying the global warming have occurred frequently, which brought significant impact on national economic and social development. The ocean is an important member of the climate system and plays an important role in the occurrence of climate anomalies. With continuous improvement of sensor technology, we use sensors to acquire the ocean data for the study on resource detection and disaster prevention, etc. However, the data acquired by the sensor is not enough to be used directly by researchers, so we use the Generative Adversarial Network (GAN) to enhance the ocean data. We use GAN… More >

Weiwei Liu¹, Yang Tang², Fei Yang², Yi Dou³, Jin Wang^4,*

CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 813-834, 2019, DOI:10.32604/cmc.2019.06754

Abstract Electric vehicles (EVs) are recognized as one of the most promising technologies worldwide to address the fossil fuel energy resource crisis and environmental pollution. As the initial work of EV charging station (EVCS) construction, site selection plays a vital role in its whole life cycle. In this paper, a multi-objective optimization model for the location layout of EVCSs is established when considering various factors such as user demand, investment cost, soil locations, the emergency charging mileage limit, the actual road condition and service network reliability. The model takes the minimum investment cost and the minimum user charging cost as the… More >

Tao Shen^1,*, Yukari Nagai¹, Chan Gao²

CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 641-651, 2019, DOI:10.32604/cmc.2019.04885

Abstract Building structure is like the skeleton of the building, it bears the effects of various forces and forms a supporting system, which is the material basis on which the building depends. Hence building structure design is a vital part in architecture design, architects often explore novel applications of their technologies for building structure innovation. However, such searches relied on experiences, expertise or gut feeling. In this paper, a new design method for the optimal building frame column design based on the genetic algorithm is proposed. First of all, in order to construct the optimal model of the building frame column,… More >

Zhao Dou¹, Gang Xu^1,*, Xiubo Chen¹, Kaiguo Yuan²

CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 335-347, 2019, DOI:10.32604/cmc.2019.04159

Abstract Rational participants want to maximize their benefits. The protocol with rational participants will be more realistic than the protocol with honest, semi-honest and dishonest participants. We research the rational non-hierarchical quantum state sharing in this paper. General steps of some known quantum state sharing protocol are summarized. Based on these steps, a new rational protocol is proposed. It means that lots of common protocols could be modified to rational protocols. Our protocol is widely applicable. Analyses show that the proposed protocol is rational and secure. It is also all-win for agents. Furthermore, number of deceiving agents is considered to redefine… More >

Ma Ning^1,*, Jianhe Guan¹, Pingzeng Liu², Ziqing Zhang³, Gregory M. P. O’Hare⁴

CMC-Computers, Materials & Continua, Vol.58, No.1, pp. 215-227, 2019, DOI:10.32604/cmc.2019.03763

Abstract With the rapid development of China’s economy, the scale of the city has been continuously expanding, industrial enterprises have been increasing, the discharge of multiple pollutants has reached the top of the world, and the environmental problems become more and more serious. The air pollution problem is particularly prominent. Air quality has become a daily concern for people. In order to control air pollution, it is necessary to grasp the air quality situation in an all-round way. It is necessary to evaluate air quality. Accurate results of air quality evaluation can help people know more about air quality. In this… More >

Wenjun Yang¹, Pingping Dong^1,2,*, Wensheng Tang¹, Xiaoping Lou¹, Hangjun Zhou³, Kai Gao⁴, Haodong Wang⁵

CMC-Computers, Materials & Continua, Vol.57, No.2, pp. 205-222, 2018, DOI:10.32604/cmc.2018.03726

Abstract Multipath TCP (MPTCP) is the most significant extension of TCP that enables transmission via multiple paths concurrently to improve the resource usage and throughput of long flows. However, due to the concurrent multiple transfer (CMT) in short flow trans-mission, the congestion window (cwnd) of each MPTCP subflow is too small and it may lead to timeout when a single lost packet cannot be recovered through fast retransmission. As a result, MPTCP has even worse performance for short flows compared to regular TCP. In this paper, we take the first step to analyze the main reason why MPTCP has the diminished… More >

Chuanlong Li^1,2,*, Yumeng Jiang³, Marta Cheslyar¹

CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 313-324, 2018, DOI: 10.3970/cmc.2018.03950

Abstract Deep neural network has proven to be very effective in computer vision fields. Deep convolutional network can learn the most suitable features of certain images without specific measure functions and outperform lots of traditional image processing methods. Generative adversarial network (GAN) is becoming one of the highlights among these deep neural networks. GAN is capable of generating realistic images which are imperceptible to the human vision system so that the generated images can be directly used as intermediate medium for many tasks. One promising application of using GAN generated images would be image concealing which requires the embedded image looks… More >

Shuaiwei Zhang¹, Xiaoyuan Yang^1,*, Weidong Zhong¹, Yujuan Sun²

CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 325-338, 2018, DOI:10.3970/cmc.2018.03611

Abstract As one of the typical method for side channel attack, DPA has become a serious trouble for the security of encryption algorithm implementation. The potential capability of DPA attack induces researchers making a lot of efforts in this area, which significantly improved the attack efficiency of DPA. However, most of these efforts were made based on the hypothesis that the gathered power consumption data from the target device were stable and low noise. If large deviation happens in part of the power consumption data sample, the efficiency of DPA attack will be reduced rapidly. In this work, a highly efficient… More >

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 transmission of the secret image.… More >