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  • Open Access

    EDITORIAL

    Introduction for the Special Issue on Beyond the Hypes of Geospatial Big Data: Theories, Methods, Analytics, and Applications

    Qianxin Wang1,*, Allison Kealy2, Shengjie Zhai3

    CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.2, pp. 245-247, 2019, DOI:10.32604/cmes.2019.06589

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    A Data-Intensive FLAC3D Computation Model: Application of Geospatial Big Data to Predict Mining Induced Subsidence

    Yaqiang Gong1,2, Guangli Guo1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.2, pp. 395-408, 2019, DOI:10.32604/cmes.2019.03686

    Abstract Although big data are widely used in various fields, its application is still rare in the study of mining subsidence prediction (MSP) caused by underground mining. Traditional research in MSP has the problem of oversimplifying geological mining conditions, ignoring the fluctuation of rock layers with space. In the context of geospatial big data, a data-intensive FLAC3D (Fast Lagrangian Analysis of a Continua in 3 Dimensions) model is proposed in this paper based on borehole logs. In the modeling process, we developed a method to handle geospatial big data and were able to make full use of borehole logs. The effectiveness… More >

  • Open Access

    ARTICLE

    Exploring Urban Population Forecasting and Spatial Distribution Modeling with Artificial Intelligence Technology

    Yan Zou1,2,3,*, Shaoliang Zhang1, Yanhai Min1

    CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.2, pp. 295-310, 2019, DOI:10.32604/cmes.2019.03873

    Abstract The high precision population forecasting and spatial distribution modeling are very important for the theory and application of population sociology, city planning and Geo-Informatics. However, the two problems need to be solved for providing the high precision population information. One is how to improve the population forecasting precision of small area (e.g., street scale); another is how to improve the spatial resolution of urban population distribution model. To solve the two problems, some new methods are proposed in this contribution. (1) To improve the precision of small area population forecasting, a new method is developed based on the fade factor… More >

  • Open Access

    ARTICLE

    Hierarchical Geographically Weighted Regression Model

    Fengchang Xue1, 2, *

    Journal of Quantum Computing, Vol.1, No.1, pp. 9-20, 2019, DOI:10.32604/jqc.2019.05954

    Abstract In spatial analysis, two problems of the scale effect and the spatial dependence have been plagued scholars, the first law of geography presented to solve the spatial dependence has played a good role in the guidelines, forming the Geographical Weighted Regression (GWR). Based on classic statistical techniques, GWR model has ascertain significance in solving spatial dependence and spatial non-uniform problems, but it has no impact on the integration of the scale effect. It does not consider the interaction between the various factors of the sampling scale observations and the numerous factors of possible scale effects, so there is a loss… More >

  • Open Access

    ARTICLE

    Binaural Sound Source Localization Based on Convolutional Neural Network

    Lin Zhou1,*, Kangyu Ma1, Lijie Wang1, Ying Chen1,2, Yibin Tang3

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 545-557, 2019, DOI:10.32604/cmc.2019.05969

    Abstract Binaural sound source localization (BSSL) in low signal-to-noise ratio (SNR) and high reverberation environment is still a challenging task. In this paper, a novel BSSL algorithm is proposed by introducing convolutional neural network (CNN). The proposed algorithm first extracts the spatial feature of each sub-band from binaural sound signal, and then combines the features of all sub-bands within one frame to assemble a two-dimensional feature matrix as a grey image. To fully exploit the advantage of the CNN in extracting high-level features from the grey image, the spatial feature matrix of each frame is used as input to train the… More >

  • Open Access

    ARTICLE

    Novel Approach for Automatic Region of Interest and Seed Point Detection in CT Images Based on Temporal and Spatial Data

    Zhe Liu1, Charlie Maere1,*, Yuqing Song1

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 669-686, 2019, DOI:10.32604/cmc.2019.04590

    Abstract Accurately finding the region of interest is a very vital step for segmenting organs in medical image processing. We propose a novel approach of automatically identifying region of interest in Computed Tomography Image (CT) images based on temporal and spatial data . Our method is a 3 stages approach, 1) We extract organ features from the CT images by adopting the Hounsfield filter. 2)We use these filtered features and introduce our novel approach of selecting observable feature candidates by calculating contours’ area and automatically detect a seed point. 3) We use a novel approach to track the growing region changes… More >

  • Open Access

    ARTICLE

    A Lie-Group Adaptive Method to Identify the Radiative Coefficients in Parabolic Partial Differential Equations

    Chein-Shan Liu1, Chih-Wen Chang2

    CMC-Computers, Materials & Continua, Vol.25, No.2, pp. 107-134, 2011, DOI:10.3970/cmc.2011.025.107

    Abstract We consider two inverse problems for estimating radiative coefficients α(x) and α(x, y), respectively, in Tt(x, t) = Txx(x, t)-α(x)T(x, t), and Tt(x, y, t) = Txx(x, y, t) + Tyy(x, y, t)-α(x, y)T(x, y, t), where a are assumed to be continuous functions of space variables. A Lie-group adaptive method is developed, which can be used to find a at the spatially discretized points, where we only utilize the initial condition and boundary conditions, such as those for a typical direct problem. This point is quite different from other methods, which need the overspecified final time data. Three-fold advantages… More >

  • Open Access

    ARTICLE

    Gender-Specific Multi-Task Micro-Expression Recognition Using Pyramid CGBP-TOP Feature

    Chunlong Hu1,*, Jianjun Chen1, Xin Zuo1, Haitao Zou1, Xing Deng1, Yucheng Shu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.118, No.3, pp. 547-559, 2019, DOI:10.31614/cmes.2019.04032

    Abstract Micro-expression recognition has attracted growing research interests in the field of compute vision. However, micro-expression usually lasts a few seconds, thus it is difficult to detect. This paper presents a new framework to recognize micro-expression using pyramid histogram of Centralized Gabor Binary Pattern from Three Orthogonal Panels (CGBP-TOP) which is an extension of Local Gabor Binary Pattern from Three Orthogonal Panels feature. CGBP-TOP performs spatial and temporal analysis to capture the local facial characteristics of micro-expression image sequences. In order to keep more local information of the face, CGBP-TOP is extracted based on pyramid sub-regions of the micro-expression video frame.… More >

  • Open Access

    ARTICLE

    Stability Analysis of Cross-channel Excavation for Existing Anchor Removal Project in Subway Construction

    Li Bin1,2,3, Fang Hongyuan1,2,3,*, He Wei4, Sun Bin1

    CMES-Computer Modeling in Engineering & Sciences, Vol.113, No.1, pp. 57-69, 2017, DOI:10.3970/cmes.2017.113.054

    Abstract The cutter head will be stuck when the shield machine pass through the area existing anchor left by foundation construction of surrounding high-rise building. Subsurface excavation method is an efficient way to remove the existed anchor. In this paper, a three-dimensional finite element model is developed to study stability of cross-channel excavation. The time-spatial effects of arch crown settlement, intrados uplift and side wall horizontal convergence are analyzed according to different excavation size, lining thickness and lining order. The results show that the excavation size is the main factor to control the deformation of the surrounding soil, especially in arch… More >

  • Open Access

    ARTICLE

    A Model of the Spatially Dependent Mechanical Properties of the Axon During Its Growth

    J.A. García1,2, J.M. Peña1, S. McHugh2, A. Jérusalem2,3

    CMES-Computer Modeling in Engineering & Sciences, Vol.87, No.5, pp. 411-432, 2012, DOI:10.3970/cmes.2012.087.411

    Abstract Neuronal growth is a complex process involving many intra- and extracellular mechanisms which are collaborating conjointly to participate to the development of the nervous system. More particularly, the early neocortical development involves the creation of a multilayered structure constituted by neuronal growth (driven by axonal or dendritic guidance cues) as well as cell migration. The underlying mechanisms of such structural lamination not only implies important biochemical changes at the intracellular level through axonal microtubule (de)polymerization and growth cone advance, but also through the directly dependent stress/stretch coupling mechanisms driving them. Efforts have recently focused on modeling approaches aimed at accounting… More >

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