Jinxing Li¹, Jun Zhang^1,*, Yunxia Zhou¹, Zhaoling Zhou¹, Hisham Essawy², Xiaojian Zhou^1,*, Guanben Du¹

Journal of Renewable Materials, Vol.8, No.9, pp. 1019-1032, 2020, DOI:10.32604/jrm.2020.012374 - 03 August 2020

Abstract Simple bio-based abrasive grinding wheel based on thermosetting resin matrix was developed starting with condensed tannin and furfuryl alcohol, which are mainly derived from forest and agricultural products like tree barks, wheat and crops. Fourier transform infrared spectra (FTIR) signified the acidic conditions are quiet efficient for the reaction of furfuryl alcohol, urea and glyoxal all together and the -CH₂-NH- and -CH₂-O-CH(OH)- groups are predominating in cross-linking of the tannin-furfuryl alcohol-urea-glyoxal (TFUG) resin. The strengthening contribution of the tannin was also confirmed by the preservation of its distinct crystallinity using X-ray diffraction (XRD). Differential scanning calorimetry… More >

Jianjun He^*, Ruifeng Wang, Yefeng Yin, Jian Chen, Chaoran Guo

Energy Engineering, Vol.117, No.4, pp. 185-193, 2020, DOI:10.32604/EE.2020.011181 - 31 July 2020

Abstract TPG-RED (Thermal Power Generation Based on Reverse Electrodialysis) was studied to explore the new method of solar thermal power generating based on Reverse Electrodialysis (RED) in this paper. RED is a process that transfers the salinity gradient between sea water and fresh water to electricity. TPGRED has combined RED with thermal power generation to transfer thermal energy from solar to electricity which has many advantages of huge available temperature range, sustainability, non-pollution, simple structure, and so on. Respectively, using “1 mol/L H₂SO₄ solution—0.0001 mol/L H₂SO₄ solution” and “1 mol/L Na₂SO₄ solution—0.0001 mol/L Na₂SO₄ solution” as the working… More >

Leilei Geng¹, Chaoran Cui¹, Qiang Guo¹, Sijie Niu², Guoqing Zhang³, Peng Fu^{4, *}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 913-928, 2020, DOI:10.32604/cmc.2020.09975 - 23 July 2020

Abstract The multispectral remote sensing image (MS-RSI) is degraded existing multispectral camera due to various hardware limitations. In this paper, we propose a novel core tensor dictionary learning approach with the robust modified Gaussian mixture model for MS-RSI restoration. First, the multispectral patch is modeled by three-order tensor and high-order singular value decomposition is applied to the tensor. Then the task of MS-RSI restoration is formulated as a minimum sparse core tensor estimation problem. To improve the accuracy of core tensor coding, the core tensor estimation based on the robust modified Gaussian mixture model is introduced More >

Weizu Huang¹, Dong Wang^{1, *}, Zuodong Xiao¹, Qiang Yao², Danjie Du³

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 897-912, 2020, DOI:10.32604/cmc.2020.09728 - 23 July 2020

Abstract The vibratory roller is a piece of vital construction machinery in the field of road construction. The unmanned vibratory roller efficiently utilizes the automated driving technology in the vehicle engineering field, which is innovative for the unmanned road construction. This paper develops and implements the autonomous construction system for the unmanned vibratory roller. Not only does the roller have the function of remote-controlled driving, but it also has the capability of autonomous road construction. The overall system design uses the Programmable Logic Controller (PLC) as the kernel controller. It establishes the communication network through multiple More >

Yan Chang^{1, *}, Shibin Zhang¹, Lili Yan¹, Xueyang Li¹, Tian Cao¹, Qirun Wang²

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 879-896, 2020, DOI:10.32604/cmc.2020.010042 - 23 July 2020

Abstract The secure key rate of quantum key distribution (QKD) is greatly reduced because of the untrusted devices. In this paper, to raise the secure key rate of QKD, a device-independent quantum key distribution (DIQKD) protocol is proposed based on hyper-entangled states and Bell inequalities. The security of the protocol is analyzed against the individual attack by an adversary only limited by the no-signaling condition. Based on the formalization of Clauser-Horne Shimony-Holt (CHSH) violation measurement on local correlation, the probability of a secure secret bit is obtained, which is produced by a pair of hyper-entangled particles. More >

Fuquan Huang¹, Zijun Liu¹, Tinghuang Wang¹, Haitai Zhang^{2, *}, Tony Yip³

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 865-878, 2020, DOI:10.32604/cmc.2020.010724 - 23 July 2020

Abstract In order to quickly and accurately locate the fault location of the distribution network and increase the stability of the distribution network, a fault recovery method based on multi-objective optimization algorithm is proposed. The optimization of the power distribution network fault system based on multiagent technology realizes fast recovery of multi-objective fault, solve the problem of network learning and parameter adjustment in the later stage of particle swarm optimization algorithm falling into the local extreme value dilemma, and realize the multi-dimensional nonlinear optimization of the main grid and the auxiliary grid. The system proposed More >

Jinfeng Li¹, Li Feng^{1, *}, Longqing Zhang², Hongning Dai¹, Lei Yang¹, Liwei Tian¹

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 639-651, 2020, DOI:10.32604/cmc.2020.010309 - 23 July 2020

Abstract Fueled by the booming online games, there is an increasing demand for monitoring online games in various settings. One of the application scenarios is the monitor of computer games in school computer labs, for which an intelligent game recognition method is required. In this paper, a method to identify game processes in accordance with private working sets (i.e., the amount of memory occupied by a process but cannot be shared among other processes) is introduced. Results of the W test showed that the memory sizes occupied by the legitimate processes (e.g., the processes of common… More >

Lejun Zhang^{1, 2}, Zhijie Zhang¹, Weizheng Wang³, Rasheed Waqas¹, Chunhui Zhao^{1, 4}, Seokhoon Kim⁵, Huiling Chen^{6, *}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 597-616, 2020, DOI:10.32604/cmc.2020.011554 - 23 July 2020

Abstract As an extension of the traditional encryption technology, information hiding has been increasingly used in the fields of communication and network media, and the covert communication technology has gradually developed. The blockchain technology that has emerged in recent years has the characteristics of decentralization and tamper resistance, which can effectively alleviate the disadvantages and problems of traditional covert communication. However, its combination with covert communication thus far has been mostly at the theoretical level. The BLOCCE method, as an early result of the combination of blockchain and covert communication technology, has the problems of low… More >

Xiaorui Shao¹, Chang Soo Kim^{1, *}, Dae Geun Kim²

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 543-561, 2020, DOI:10.32604/cmc.2020.011108 - 23 July 2020

Abstract Time series classification (TSC) has attracted various attention in the community of machine learning and data mining and has many successful applications such as fault detection and product identification in the process of building a smart factory. However, it is still challenging for the efficiency and accuracy of classification due to complexity, multi-dimension of time series. This paper presents a new approach for time series classification based on convolutional neural networks (CNN). The proposed method contains three parts: short-time gap feature extraction, multi-scale local feature learning, and global feature learning. In the process of short-time… More >

Yiming Huang^{1, *}, Hang Lei¹, Xiaoyu Li^{1, *}, Qingsheng Zhu², Wanghao Ren³, Xusheng Liu^{2, 4}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 445-458, 2020, DOI:10.32604/cmc.2020.010390 - 23 July 2020

Abstract In recent years, an increasing number of studies about quantum machine learning not only provide powerful tools for quantum chemistry and quantum physics but also improve the classical learning algorithm. The hybrid quantum-classical framework, which is constructed by a variational quantum circuit (VQC) and an optimizer, plays a key role in the latest quantum machine learning studies. Nevertheless, in these hybridframework-based quantum machine learning models, the VQC is mainly constructed with a fixed structure and this structure causes inflexibility problems. There are also few studies focused on comparing the performance of quantum generative models with… More >