Tong Li¹, Shibin Zhang^{1, *}, Jinyue Xia²

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 401-438, 2020, DOI:10.32604/cmc.2020.010551

Abstract Generative adversarial network (GAN) is one of the most promising methods for unsupervised learning in recent years. GAN works via adversarial training concept and has shown excellent performance in the fields image synthesis, image super-resolution, video generation, image translation, etc. Compared with classical algorithms, quantum algorithms have their unique advantages in dealing with complex tasks, quantum machine learning (QML) is one of the most promising quantum algorithms with the rapid development of quantum technology. Specifically, Quantum generative adversarial network (QGAN) has shown the potential exponential quantum speedups in terms of performance. Meanwhile, QGAN also exhibits some problems, such as barren… More >

Bo Xiao¹, Yinghang Jiang², Qi Liu^{2, 5, *}, Xiaodong Liu³, Mingxu Sun^{4, *}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 389-399, 2020, DOI:10.32604/cmc.2020.06092

Abstract MEMS accelerometers are widely used in various fields due to their small size and low cost, and have good application prospects. However, the low accuracy limits its range of applications. To ensure data accuracy and safety we need to calibrate MEMS accelerometers. Many authors have improved accelerometer accuracy by calculating calibration parameters, and a large number of published calibration methods have been confusing. In this context, this paper introduces these techniques and methods, analyzes and summarizes the main error models and calibration procedures, and provides useful suggestions. Finally, the content of the accelerometer calibration method needs to be overcome. More >

Lili He^{1, 2}, Zhiwei Cai^{1, 2}, Dantong Ouyang^{1, 2}, Changshuai Wang^{1, 2}, Yu Jiang^{1, 2}, Chong Wang^{1, 2, 3}, Hongtao Bai^{1, 2, *}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 373-388, 2020, DOI:10.32604/cmc.2020.09860

Abstract In view of the satellite cloud-derived wind inversion has the characteristics of large scale, intensive computing and time-consuming serial inversion algorithm is very difficult to break through the bottleneck of efficiency. We proposed a parallel acceleration scheme of cloud-derived wind inversion algorithm based on MPI cluster parallel technique in this paper. The divide-and-conquer idea, assigning winds vector inversion tasks to each computing unit, is identified according to a certain strategy. Each computing unit executes the assigned tasks in parallel, namely divide-and-rule the inversion task, so as to reduce the efficiency bottleneck of long inversion time caused by serial time accumulation.… More >

Muhammad Waqas^{1, 2}, Shanshan Tu^{1, 3, *}, Sadaqat Ur Rehman¹, Zahid Halim², Sajid Anwar², Ghulam Abbas², Ziaul Haq Abbas⁴, Obaid Ur Rehman⁵

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 359-371, 2020, DOI:10.32604/cmc.2020.09821

Abstract Security threats to smart and autonomous vehicles cause potential consequences such as traffic accidents, economically damaging traffic jams, hijacking, motivating to wrong routes, and financial losses for businesses and governments. Smart and autonomous vehicles are connected wirelessly, which are more attracted for attackers due to the open nature of wireless communication. One of the problems is the rogue attack, in which the attacker pretends to be a legitimate user or access point by utilizing fake identity. To figure out the problem of a rogue attack, we propose a reinforcement learning algorithm to identify rogue nodes by exploiting the channel state… More >

Senbo Chen^{1, 3, *}, Wenan Tan^{1, 2}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 345-358, 2020, DOI:10.32604/cmc.2020.09807

Abstract The problem of influence maximizing in social networks refers to obtaining a set of nodes of a specified size under a specific propagation model so that the aggregation of the node-set in the network has the greatest influence. Up to now, most of the research has tended to focus on monolayer network rather than on multiplex networks. But in the real world, most individuals usually exist in multiplex networks. Multiplex networks are substantially different as compared with those of a monolayer network. In this paper, we integrate the multi-relationship of agents in multiplex networks by considering the existing and relevant… More >

Junxiang Wang^{1, *}, Lin Huang¹, Ying Zhang¹, Yonghong Zhu¹, Jiangqun Ni², Yunqing Shi³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 325-344, 2020, DOI:10.32604/cmc.2020.09784

Abstract To measure the security for hot searched reversible data hiding (RDH) technique, especially for the common-used histogram-shifting based RDH (denoted as HS-RDH), several steganalysis schemes are designed to detect whether some secret data has been hidden in a normal-looking image. However, conventional steganalysis schemes focused on the previous RDH algorithms, i.e., some early spatial/pixel domain-based histogram-shifting (HS) schemes, which might cause great changes in statistical characteristics and thus be easy to be detected. For recent improved methods, such as some adaptive prediction error (PE) based embedding schemes, those conventional schemes might be invalid, since those adaptive embedding mechanism would effectively… More >

Liang Yang^{1, *}, Daojian Zeng², Jianhua Yan³, Yaozhang Sai¹

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 313-323, 2020, DOI:10.32604/cmc.2020.09809

Abstract The Synthetic Aperture Radar (SAR) raw data generator is required to the evaluation of focusing algorithms, moving target analysis, and hardware design. The time-domain SAR simulator can generate the accurate raw data but it needs much time. The frequency-domain simulator not only increases the efficiency but also considers the trajectory deviations of the radar. In addition, the raw signal of the extended scene included static and moving targets can be generated by some frequency-domain simulators. However, the existing simulators concentrate on the raw signal simulation of the static extended scene and moving targets at uniform speed mostly. As for the… More >

Jiangheng Kou¹, Mingxing He^{1, *}, Ling Xiong¹, Zihang Ge², Guangmin Xie¹

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 297-312, 2020, DOI:10.32604/cmc.2020.09758

Abstract With the development of communication technologies, various mobile devices and different types of mobile services became available. The emergence of these services has brought great convenience to our lives. The multi-server architecture authentication protocols for mobile cloud computing were proposed to ensure the security and availability between mobile devices and mobile services. However, most of the protocols did not consider the case of hierarchical authentication. In the existing protocol, when a mobile user once registered at the registration center, he/she can successfully authenticate with all mobile service providers that are registered at the registration center, but real application scenarios are… More >

Yan Liu¹, Wenyuan Fang¹, Qiang Wei^{1, *}, Yuan Zhao¹, Liang Wang²

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 273-295, 2020, DOI:10.32604/cmc.2020.09659

Abstract Code defects can lead to software vulnerability and even produce vulnerability risks. Existing research shows that the code detection technology with text analysis can judge whether object-oriented code files are defective to some extent. However, these detection techniques are mainly based on text features and have weak detection capabilities across programs. Compared with the uncertainty of the code and text caused by the developer’s personalization, the programming language has a stricter logical specification, which reflects the rules and requirements of the language itself and the developer’s potential way of thinking. This article replaces text analysis with programming logic modeling, breaks… More >

Xiaoyan Zhao^{1, *}, Shuwen Chen², Lin Zhou³, Ying Chen^{3, 4}

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 253-271, 2020, DOI:10.32604/cmc.2020.09848

Abstract Microphone array-based sound source localization (SSL) is a challenging task in adverse acoustic scenarios. To address this, a novel SSL algorithm based on deep neural network (DNN) using steered response power-phase transform (SRP-PHAT) spatial spectrum as input feature is presented in this paper. Since the SRP-PHAT spatial power spectrum contains spatial location information, it is adopted as the input feature for sound source localization. DNN is exploited to extract the efficient location information from SRP-PHAT spatial power spectrum due to its advantage on extracting high-level features. SRP-PHAT at each steering position within a frame is arranged into a vector, which… More >