The topic of this paper is to enhance the semantic information of dialogue through external knowledge graph. Knowledge graph is a graph structure composed of entities and relations between entities. The size change of nodes is used in the graph to indicate the different degrees of mutual influence between nodes.
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EDITORIAL
Yu-Dong Zhang1,*, Zhengchao Dong2, Juan Manuel Gorriz3,4, Carlo Cattani5, Ming Yang6
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 399-401, 2021, DOI:10.32604/cmes.2021.017472
（This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
Abstract This article has no abstract. More >
Open Access
ARTICLE
Zhongqin Bi1, Shiyang Wang1, Yan Chen2,*, Yongbin Li1, Jung Yoon Kim3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 403-426, 2021, DOI:10.32604/cmes.2021.016729
（This article belongs to this Special Issue: Innovation and Application of Intelligent Processing of Data, Information and Knowledge in E-Commerce)
Abstract With the continuous improvement of the e-commerce ecosystem and the rapid growth of e-commerce data, in the context of the e-commerce ecosystem, consumers ask hundreds of millions of questions every day. In order to improve the timeliness of customer service responses, many systems have begun to use customer service robots to respond to consumer questions, but the current customer service robots tend to respond to specific questions. For many questions that lack background knowledge, they can generate only responses that are biased towards generality and repetitiveness. To better promote the understanding of dialogue and generate more meaningful responses, this paper… More >
Open Access
ARTICLE
Juhong Tie1,2,*, Hui Peng2, Jiliu Zhou1,3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 427-445, 2021, DOI:10.32604/cmes.2021.014107
（This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
Abstract The main task of magnetic resonance imaging (MRI) automatic brain tumor segmentation is to automatically segment the brain tumor edema, peritumoral edema, endoscopic core, enhancing tumor core and nonenhancing tumor core from 3D MR images. Because the location, size, shape and intensity of brain tumors vary greatly, it is very difficult to segment these brain tumor regions automatically. In this paper, by combining the advantages of DenseNet and ResNet, we proposed a new 3D U-Net with dense encoder blocks and residual decoder blocks. We used dense blocks in the encoder part and residual blocks in the decoder part. The number… More >
Open Access
REVIEW
Karpagam Sundararajan1, Lalit Garg2,*, Kathiravan Srinivasan4,*, Ali Kashif Bashir3, Jayakumar Kaliappan4, Ganapathy Pattukandan Ganapathy5, Senthil Kumaran Selvaraj6, T. Meena7
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 447-487, 2021, DOI:10.32604/cmes.2021.015528
Abstract Drought is the least understood natural disaster due to the complex relationship of multiple contributory factors. Its beginning and end are hard to gauge, and they can last for months or even for years. India has faced many droughts in the last few decades. Predicting future droughts is vital for framing drought management plans to sustain natural resources. The data-driven modelling for forecasting the metrological time series prediction is becoming more powerful and flexible with computational intelligence techniques. Machine learning (ML) techniques have demonstrated success in the drought prediction process and are becoming popular to predict the weather, especially the… More >
Open Access
REVIEW
Shuxuan Xie, Zengchen Yu, Zhihan Lv*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 489-522, 2021, DOI:10.32604/cmes.2021.016728
Abstract In recent years, the development of artificial intelligence (AI) and the gradual beginning of AI’s research in the
medical field have allowed people to see the excellent prospects of the integration of AI and healthcare. Among
them, the hot deep learning field has shown greater potential in applications such as disease prediction and drug
response prediction. From the initial logistic regression model to the machine learning model, and then to the
deep learning model today, the accuracy of medical disease prediction has been continuously improved, and the
performance in all aspects has also been significantly improved. This article introduces some… More >
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ARTICLE
Baoshou Liu1,2, Xiaolei Yan1, Yangfan Li3, Shiwei Zhou4, Xiaodong Huang3,*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 523-540, 2021, DOI:10.32604/cmes.2021.017211
（This article belongs to this Special Issue: Novel Methods of Topology Optimization and Engineering Applications)
Abstract This paper proposes a new element-based multi-material topology optimization algorithm using a single variable for minimizing compliance subject to a mass constraint. A single variable based on the normalized elemental density is used to overcome the occurrence of meaningless design variables and save computational cost. Different from the traditional material penalization scheme, the algorithm is established on the ordered ersatz material model, which linearly interpolates Young's modulus for relaxed design variables. To achieve a multi-material design, the multiple floating projection constraints are adopted to gradually push elemental design variables to multiple discrete values. For the convergent element-based solution, the multiple… More >
Open Access
ARTICLE
Jiaxiu Dong1,2,3, Jianhua Liu4, Niannian Wang1,2,3,*, Hongyuan Fang1,2,3, Jinping Zhang1, Haobang Hu1,2,3, Duo Ma1,2,3
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 541-564, 2021, DOI:10.32604/cmes.2021.015875
Abstract Nowadays, asphalt road has dominated highways around the world. Among various defects of asphalt road, cracks have been paid more attention, since cracks often cause major engineering and personnel safety incidents. Current manual crack inspection methods are time-consuming and labor-intensive, and most segmentation methods cannot detect cracks at the pixel level. This paper proposes an intelligent segmentation and measurement model based on the modified Mask R-CNN algorithm to automatically and accurately detect asphalt road cracks. The model proposed in this paper mainly includes a convolutional neural network (CNN), an optimized region proposal network (RPN), a region of interest (RoI) Align… More >
Open Access
ARTICLE
Buyu Jia, Siyi Mao, Quansheng Yan, Xiaolin Yu*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 565-582, 2021, DOI:10.32604/cmes.2021.015183
Abstract Research on the lateral vibrational stability of footbridges has attracted increasing attention in recent years. However, this stability contains a series of complex mechanisms, such as nonlinear vibration, random excitation, and random stability. The Lyapunov method is regarded as an effective tool for analyzing random vibrational stability; however, it is a qualitative method and can only provide a binary judgment for stability. This study proposes a new method, IEVIE–SA, which combines the energy method based on the comparison between the input energy and the variation of intrinsic energy (IEVIE) and the stochastic averaging (SA) method. The improved Nakamura model was… More >
Open Access
ARTICLE
W. M. Faizal1,2, N. N. N. Ghazali2,*, C. Y. Khor1, M. Z. Zainon2, Irfan Anjum Badruddin3,4,*, Sarfaraz Kamangar4, Norliza Binti Ibrahim5, Roziana Mohd Razi6
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 583-604, 2021, DOI:10.32604/cmes.2021.015549
Abstract Background: Obstructive sleep apnea is a sleeping disorder that has troubled a sizeable population. There is an
active area of research on obstructive sleep apnea that intends to better understand airflow behaviors and therefore
treat patients more effectively. This paper aims to investigate the airflow characteristics of the upper airway in
an obstructive sleep apnea (OSA) patient under light and heavy breathing conditions by using Turbulent Kinetic
Energy (TKE), an accurate method in expressing the flow concentration mechanisms of sleeping disorders. It is
important to visualize the concentration of flow in the upper airway in order to identify the severity… More >
Open Access
ARTICLE
Haiquan Li1, Qinghui Zhang2,*, Xiaoqian Chen3
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 605-621, 2021, DOI:10.32604/cmes.2021.015747
Abstract Flight load computations (FLC) are generally expensive and time-consuming. This paper studies deep learning (DL)-based surrogate models of FLC to provide a reliable basis for the strength design of aircraft structures. We mainly analyze the influence of Mach number, overload, angle of attack, elevator deflection, altitude, and other factors on the loads of key monitoring components, based on which input and output variables are set. The data used to train and validate the DL surrogate models are derived using aircraft flight load simulation results based on wind tunnel test data. According to the FLC features, a deep neural network (DNN)… More >
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