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Hyun Kyu Shin¹, Yong Han Ahn², Sang Hyo Lee³, Ha Young Kim^4,*
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 911-928, 2019, DOI:10.32604/cmc.2019.08269
Abstract Compressive strength of concrete is a significant factor to assess building structure health and safety. Therefore, various methods have been developed to evaluate the compressive strength of concrete structures. However, previous methods have several challenges in costly, time-consuming, and unsafety. To address these drawbacks, this paper proposed a digital vision based concrete compressive strength evaluating model using deep convolutional neural network (DCNN). The proposed model presented an alternative approach to evaluating the concrete strength and contributed to improving efficiency and accuracy. The model was developed with 4,000 digital images and 61,996 images extracted from video More >

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I-Ching Hsu^1,*
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 929-950, 2019, DOI:10.32604/cmc.2019.07876
Abstract Considering cloud computing from an organizational and end user computing point of view, it is a new paradigm for deploying, managing and offering services through a shared infrastructure. Current development of cloud computing applications, however, are the lack of a uniformly approach to cope with the heterogeneous information fusion. This leads cloud computing to inefficient development and a low potential reuse. This study addresses these issues to propose a novel Web 2.0 Mashups as a Service, called WMaaS, which is a fundamental cloud service model. The WMaaS is developed based on a XML-based Mashups Architecture More >

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Duyen Le Hien Nguyen¹, Dieu Thi Thanh Do², Jaehong Lee², Timon Rabczuk³, Hung Nguyen-Xuan^1,4,*
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 951-977, 2019, DOI:10.32604/cmc.2019.08001
Abstract We in this paper exploit time series algorithm based deep learning in forecasting damage mechanics problems. The methodologies that are able to work accurately for less computational and resolving attempts are a significant demand nowadays. Relied on learning an amount of information from given data, the long short-term memory (LSTM) method and multi-layer neural networks (MNN) method are applied to predict solutions. Numerical examples are implemented for predicting fracture growth rates of L-shape concrete specimen under load ratio, single-edge-notched beam forced by 4-point shear and hydraulic fracturing in permeable porous media problems such as storage-toughness More >

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K. A. Gepreel^1,2, A. M. S. Mahdy^1,2,*, M. S. Mohamed^1,3, A. Al-Amiri⁴
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 979-994, 2019, DOI:10.32604/cmc.2019.07701
Abstract In this paper, we study the approximate solutions for some of nonlinear Biomathematics models via the e-epidemic SI1I2R model characterizing the spread of viruses in a computer network and SIR childhood disease model. The reduced differential transforms method (RDTM) is one of the interesting methods for finding the approximate solutions for nonlinear problems. We apply the RDTM to discuss the analytic approximate solutions to the SI1I2R model for the spread of virus HCV-subtype and SIR childhood disease model. We discuss the numerical results at some special values of parameters in the approximate solutions. We use More >

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Mamouni El Mamoun^1,*, Zennaki Mahmoud¹, Sadouni Kaddour¹
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 995-1008, 2019, DOI:10.32604/cmc.2019.08081
Abstract Using Support Vector Machine (SVM) requires the selection of several parameters such as multi-class strategy type (one-against-all or one-against-one), the regularization parameter C, kernel function and their parameters. The choice of these parameters has a great influence on the performance of the final classifier. This paper considers the grid search method and the particle swarm optimization (PSO) technique that have allowed to quickly select and scan a large space of SVM parameters. A comparative study of the SVM models is also presented to examine the convergence speed and the results of each model. SVM is More >

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1386

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S. R. Vij^1,*, D. Mukhopadhyay², A. J. Agrawal³
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1009-1024, 2019, DOI:10.32604/cmc.2019.08417
Abstract We all negotiate, formally or informally, in jobs, in day today lives and outcomes of negotiations affect those processes of life. Although negotiation is an intrinsic nature of human psyche, it is very complex phenomenon to implement using computing and internet for the various purposes in E Commerce. Automation of negotiation process poses unique challenges for computer scientists and researchers, so here we study how negotiation can be modeled and analyzed mathematically, what can be different techniques and strategies or set of rules/protocols to be implemented and how they can be relevantly implemented. We are… More >

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Muhammad Shoaib Arif¹, Ali Raza¹, Wasfi Shatanawi^{2, 3, *}, Muhammad Rafiq⁴, Mairaj Bibi⁵
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1025-1043, 2019, DOI:10.32604/cmc.2019.08405
Abstract We are presenting the numerical analysis for stochastic SLBR model of computer virus over the internet in this manuscript. We are going to present the results of stochastic and deterministic computer virus model. Outcomes of the threshold number C* hold in stochastic computer virus model. If C*<1 then in such a condition virus controlled in the computer population while C*>1 shows virus spread in the computer population. Unfortunately, stochastic numerical techniques fail to cope with large step sizes of time. The suggested structure of the stochastic non-standard finite difference scheme (SNSFD) maintains all diverse characteristics More >

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1326

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Lubna Alhenak¹, Manar Hosny^1,*
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1045-1074, 2019, DOI:10.32604/cmc.2019.08355
Abstract In recent years, the volume of information in digital form has increased tremendously owing to the increased popularity of the World Wide Web. As a result, the use of techniques for extracting useful information from large collections of data, and particularly documents, has become more necessary and challenging. Text clustering is such a technique; it consists in dividing a set of text documents into clusters (groups), so that documents within the same cluster are closely related, whereas documents in different clusters are as different as possible. Clustering depends on measuring the content (i.e., words) of… More >

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ARTICLE

Youngseok Park¹, Hyunsang Choi¹, Sanghyun Cho¹, Young-Gab Kim^2,*
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1075-1090, 2019, DOI:10.32604/cmc.2019.08520
Abstract The speech recognition technology has been increasingly common in our lives. Recently, a number of commercial smart speakers containing the personal assistant system using speech recognition came out. While the smart speaker vendors have been concerned about the intelligence and the convenience of their assistants, but there have been little mentions of the smart speakers in security aspects. As the smart speakers are becoming the hub for home automation, its security vulnerabilities can cause critical problems. In this paper, we categorize attack vectors and classify them into hardware-based, network-based, and software-based. With the attack vectors, More >

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3460

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ARTICLE

Jiarui Zhang¹, Gang Wang^2,*, Siyuan Tong¹
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1091-1104, 2019, DOI:10.32604/cmc.2019.05907
Abstract Aiming at the problem of gate allocation of transit flights, a flight first service model is established. Under the constraints of maximizing the utilization rate of gates and minimizing the transit time, the idea of “first flight serving first” is used to allocate the first time, and then the hybrid algorithm of artificial fish swarm and simulated annealing is used to find the optimal solution. That means the fish swarm algorithm with the swallowing behavior is employed to find the optimal solution quickly, and the simulated annealing algorithm is used to obtain a global optimal… More >

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ARTICLE

Dongjie Zhu¹, Yuhua Wang¹, Chuiju You^2,*, Jinming Qiu^2,3, Ning Cao², Chenjing Gong⁴, Guohua Yang⁵, Helen Min Zhou⁶
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1105-1115, 2019, DOI:10.32604/cmc.2019.06041
Abstract With the rapid development of the mobile Internet, users generate massive data in different forms in social network every day, and different characteristics of users are reflected by these social media data. How to integrate multiple heterogeneous information and establish user profiles from multiple perspectives plays an important role in providing personalized services, marketing, and recommendation systems. In this paper, we propose Multi-source & Multi-task Learning for User Profiles in Social Network which integrates multiple social data sources and contains a multi-task learning framework to simultaneously predict various attributes of a user. Firstly, we design More >

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1273

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Xuting Duan^1,2,3, Jingyi Wei^1,2,3, Daxin Tian^1,2,3,*, Jianshan Zhou^1,2,3,4, Haiying Xia⁵, Xin Li⁶, Kunxian Zheng^1,2,3
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1117-1128, 2019, DOI:10.32604/cmc.2019.05578
Abstract In vehicle ad-hoc networks (VANETs), the proliferation of wireless communication will give rise to the heterogeneous access environment where network selection becomes significant. Motivated by the self-adaptive paradigm of cellular attractors, this paper regards an individual communication as a cell, so that we can apply the revised attractor selection model to induce each connected vehicle. Aiming at improving the Quality of Service (QoS), we presented the bio-inspired handover decision-making mechanism. In addition, we employ the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) for any vehicle to choose an access network. This More >

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1312

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ARTICLE

Tiantian Tan^1,*, Baosheng Wang¹, Yong Tang¹, Xu Zhou¹, Jingwen Han²
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1129-1144, 2019, DOI:10.32604/cmc.2019.06051
Abstract During system development, implementation and operation, vulnerability database technique is necessary to system security; there are many vulnerability databases but a lack of quality standardization and general evaluation method are needed. this paper summarized current international popular vulnerability databases, systematically introduced the present situation of current vulnerability databases, and found the problems of vulnerability database technology, extracted common metrics by analyzing vulnerability data of current popular vulnerability databases, introduced 4 measure indexes: the number scale of vulnerabilities, the independence level, the standardization degree and the integrity of vulnerability description, proposed a method for vulnerability database More >

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1921

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ARTICLE

Shibin Zhang^1,*, Yan Chang¹, Lili Yan¹, Zhiwei Sheng¹, Fan Yang¹, Guihua Han¹, Yuanyuan Huang¹, Jinyue Xia²
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1145-1174, 2019, DOI:10.32604/cmc.2019.05668
Abstract This paper summarizes the state of art in quantum communication networks and trust management in recent years. As in the classical networks, trust management is the premise and foundation of quantum secure communication and cannot simply be attributed to security issues, therefore the basic and importance of trust management in quantum communication networks should be taken more seriously. Compared with other theories and techniques in quantum communication, the trust of quantum communication and trust management model in quantum communication network environment is still in its initial stage. In this paper, the core technologies of establishing More >

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Longqing Zhang¹, Liping Bai^1,*, Xinwei Zhang², Yanghong Zhang², Feng Sun², Changcheng Chen²
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1175-1187, 2019, DOI:10.32604/cmc.2019.06075
Abstract Based on the two-dimensional relation table, this paper studies the missing values in the sample data of land price of Shunde District of Foshan City. GeoDa software was used to eliminate the insignificant factors by stepwise regression analysis; NORM software was adopted to construct the multiple imputation models; EM algorithm and the augmentation algorithm were applied to fit multiple linear regression equations to construct five different filling datasets. Statistical analysis is performed on the imputation data set in order to calculate the mean and variance of each data set, and the weight is determined according… More >

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1122

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ARTICLE

Wei Song^1,2,*, Jing Yu³, Xiaobing Zhao^1,2, Antai Wang⁴
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1189-1204, 2019, DOI:10.32604/cmc.2019.06361
Abstract In the current era of multimedia information, it is increasingly urgent to realize intelligent video action recognition and content analysis. In the past few years, video action recognition, as an important direction in computer vision, has attracted many researchers and made much progress. First, this paper reviews the latest video action recognition methods based on Deep Neural Network and Markov Logic Network. Second, we analyze the characteristics of each method and the performance from the experiment results. Then compare the emphases of these methods and discuss the application scenarios. Finally, we consider and prospect the More >

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ARTICLE

Yanfen Guo^1,2, Zhe Cui^1,*, Zhipeng Yang³, Xi Wu², Shaahin Madani⁴
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1205-1215, 2019, DOI:10.32604/cmc.2019.06029
Abstract Since the spatial resolution of diffusion weighted magnetic resonance imaging (DWI) is subject to scanning time and other constraints, its spatial resolution is relatively limited. In view of this, a new non-local DWI image super-resolution with joint information method was proposed to improve the spatial resolution. Based on the non-local strategy, we use the joint information of adjacent scan directions to implement a new weighting scheme. The quantitative and qualitative comparison of the datasets of synthesized DWI and real DWI show that this method can significantly improve the resolution of DWI. However, the algorithm ran More >

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1335

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ARTICLE

Donghui Li¹, Cong Shen^2,*, Xiaopeng Dai¹, Xinghui Zhu¹, Jian Luo¹, Xueting Li¹, Haiwen Chen³, Zhiyao Liang⁴
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1217-1231, 2019, DOI:10.32604/cmc.2019.06354
Abstract Data fusion can effectively process multi-sensor information to obtain more accurate and reliable results than a single sensor. The data of water quality in the environment comes from different sensors, thus the data must be fused. In our research, self-adaptive weighted data fusion method is used to respectively integrate the data from the PH value, temperature, oxygen dissolved and NH3 concentration of water quality environment. Based on the fusion, the Grubbs method is used to detect the abnormal data so as to provide data support for estimation, prediction and early warning of the water quality. More >

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ARTICLE

Maojun Zhang^1,2, Jiajin Yao¹, Zhonghang Xia³, Jiangxia Nan^1,*, Cuiqing Zhang¹
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1233-1244, 2019, DOI:10.32604/cmc.2019.06118
Abstract It is well known that economic policy uncertainty prompts the volatility of the high-yield bond market. However, the correlation between economic policy uncertainty and volatility of high-yield bonds is still not clear. In this paper, we employ GARCH-MIDAS models to investigate their correlation with US economic policy uncertainty index and S&P high-yield bond index. The empirical studies show that mixed volatility models can effectively capture the realized volatility of high-yield bonds, and economic policy uncertainty and macroeconomic factors have significant effects on the long-term component of high-yield bonds volatility. More >

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1234

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Ce Li^1,2,*, Xinyu Shang², Liguo Zhang^3,4, Feng Yang^1,2, Jing Zheng^1,5, Xianlei Xu¹
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1245-1260, 2019, DOI:10.32604/cmc.2019.06159
Abstract Pipeline defect detection systems collect the videos from cameras of pipeline robots, however the systems always analyzed these videos by offline systems or humans to detect the defects of potential security threats. The existing systems tend to reach the limit in terms of data access anywhere, access security and video processing on cloud. There is in need of studying on a pipeline defect detection cloud system for automatic pipeline inspection. In this paper, we deploy the framework of a cloud based pipeline defect detection system, including the user management module, pipeline robot control module, system More >

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1324

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ARTICLE

Yatian Shen¹, Yan Li¹, Jun Sun^1,*, Wenke Ding¹, Xianjin Shi¹, Lei Zhang¹, Xiajiong Shen¹, Jing He²
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1261-1269, 2019, DOI:10.32604/cmc.2019.06104
Abstract On Twitter, people often use hashtags to mark the subject of a tweet. Tweets have specific themes or content that are easy for people to manage. With the increase in the number of tweets, how to automatically recommend hashtags for tweets has received wide attention. The previous hashtag recommendation methods were to convert the task into a multi-class classification problem. However, these methods can only recommend hashtags that appeared in historical information, and cannot recommend the new ones. In this work, we extend the self-attention mechanism to turn the hashtag recommendation task into a sequence More >

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1446

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ARTICLE

Chuiju You¹, Dongjie Zhu^2,*, Yundong Sun², Anshan Ye³, Gangshan Wu⁴, Ning Cao¹, Jinming Qiu¹, Helen Min Zhou⁵
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1271-1283, 2019, DOI:10.32604/cmc.2019.06133
Abstract With the rapid development of social network, public opinion monitoring based on social networks is becoming more and more important. Many platforms have achieved some success in public opinion monitoring. However, these platforms cannot perform well in scalability, fault tolerance, and real-time performance. In this paper, we propose a novel social-network-oriented public opinion monitoring platform based on ElasticSearch (SNES). Firstly, SNES integrates the module of distributed crawler cluster, which provides real-time social media data access. Secondly, SNES integrates ElasticSearch which can store and retrieve massive unstructured data in near real time. Finally, we design subscription More >

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1691

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ARTICLE

Liang Ding^1,*, Lunjie Li¹, Jianghong Han¹, Yuqi Fan^2,*, Donghui Hu¹
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1285-1304, 2019, DOI:10.32604/cmc.2019.06160
Abstract Botnets often use domain generation algorithms (DGA) to connect to a command and control (C2) server, which enables the compromised hosts connect to the C2 server for accessing many domains. The detection of DGA domains is critical for blocking the C2 server, and for identifying the compromised hosts as well. However, the detection is difficult, because some DGA domain names look normal. Much of the previous work based on statistical analysis of machine learning relies on manual features and contextual information, which causes long response time and cannot be used for real-time detection. In addition,… More >

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ARTICLE

Yongyun Zhu¹, Tao Zhang^1,*, Mohan Li², Di Wang¹, Shaoen Wu³
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1305-1321, 2019, DOI:10.32604/cmc.2019.06406
Abstract The observation vectors in traditional coarse alignment contain random noise caused by the errors of inertial instruments, which will slow down the convergence rate. To solve the above problem, a real-time noise reduction method, sliding fixed-interval least squares (SFI-LS), is devised to depress the noise in the observation vectors. In this paper, the least square method, improved by a sliding fixed-interval approach, is applied for the real-time noise reduction. In order to achieve a better-performed coarse alignment, the proposed method is utilized to de-noise the random noise in observation vectors. First, the principles of proposed More >

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1129

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Bing Hu¹, Feng Xiang², Fan Wu³, Jian Liu⁴, Zhe Sun¹, Zhixin Sun^1,*
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1323-1344, 2019, DOI:10.32604/cmc.2019.06414
Abstract To cope with the arbitrariness of the network delays, a novel method, referred to as the composite particle filter approach based on variational Bayesian (VB-CPF), is proposed herein to estimate the clock skew and clock offset in wireless sensor networks. VB-CPF is an improvement of the Gaussian mixture kalman particle filter (GMKPF) algorithm. In GMKPF, Expectation-Maximization (EM) algorithm needs to determine the number of mixture components in advance, and it is easy to generate overfitting and underfitting. Variational Bayesian EM (VB-EM) algorithm is introduced in this paper to determine the number of mixture components adaptively More >

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ARTICLE

Wenchen He^1,*, Shaoyong Guo¹, Yun Liang², Rui Ma³, Xuesong Qiu¹, Lei Shi⁴
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1345-1364, 2019, DOI:10.32604/cmc.2019.06669
Abstract With the popularization of terminal devices and services in Internet of things (IoT), it will be a challenge to design a network resource allocation method meeting various QoS requirements and effectively using substrate resources. In this paper, a dynamic network slicing mechanism including virtual network (VN) mapping and VN reconfiguration is proposed to provide network slices for services. Firstly, a service priority model is defined to create queue for resource allocation. Then a slice including Virtual Network Function (VNF) placement and routing with optimal cost is generated by VN mapping. Next, considering temporal variations of More >

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1242

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Yu Sun^1,2,*, Qiyuan Gao³, Xiaofan Du³, Zhao Gu³
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1365-1375, 2019, DOI:10.32604/cmc.2019.06294
Abstract In this advanced age, when smart phones are the norm, people utilize social networking, online shopping, and even private information storage through smart phones. As a result, identity authentication has become the most critical security activity in this period of the intelligent craze. By analyzing the shortcomings of the existing authentication methods, this paper proposes an identity authentication method based on the behavior of smartphone users. Firstly, the sensor data and touch-screen data of the smart phone users are collected through android programming. Secondly, the eigenvalues of this data are extracted and sent to the More >

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1282

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ARTICLE

Shen Li¹, Fang Liu^1,*, Jiayue Liang¹, Zhenhua Cai¹, Zhiyao Liang²
CMC-Computers, Materials & Continua, Vol.61, No.3, pp. 1377-1389, 2019, DOI:10.32604/cmc.2019.06402
Abstract With the rapid development of artificial intelligence, face recognition systems are widely used in daily lives. Face recognition applications often need to process large amounts of image data. Maintaining the accuracy and low latency is critical to face recognition systems. After analyzing the two-tier architecture “client-cloud” face recognition systems, it is found that these systems have high latency and network congestion when massive recognition requirements are needed to be responded, and it is very inconvenient and inefficient to deploy and manage relevant applications on the edge of the network. This paper proposes a flexible and… More >

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