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  • Open Access

    REVIEW

    Multi-Aspect Critical Assessment of Applying Digital Elevation Models in Environmental Hazard Mapping

    Maan Habib1,*, Ahed Habib2, Mohammad Abboud3

    Revue Internationale de Géomatique, Vol.33, pp. 247-271, 2024, DOI:10.32604/rig.2024.053857 - 07 August 2024

    Abstract Digital elevation models (DEMs) are essential tools in environmental science, particularly for hazard assessments and landscape analyses. However, their application across multiple environmental hazards simultaneously remains in need for a multi-aspect critical assessment to promote their effectiveness in comprehensive risk management. This paper aims to review and critically assess the application of DEMs in mapping and managing specific environmental hazards, namely floods, landslides, and coastal erosion. In this regard, it seeks to promote their utility of hazard maps as key tools in disaster risk reduction and environmental planning by employing high-resolution DEMs integrated with advanced More >

  • Open Access

    PROCEEDINGS

    Hierarchical Multiscale Modeling of Thaw-Induced Landslides in Permafrost

    Shiwei Zhao1,*, Hao Chen2, Jidong Zhao1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.09965

    Abstract With global warming, thaw-induced landslides occur more frequently in permafrost, which not only threaten the safety of infrastructures as general geohazards but also worsen global warming due to carbon release. This work presents a novel computational framework to model thaw-induced landslides from a multiscale perspective. The proposed approach can capture the thermal-mechanical (TM) response of frozen soils at the particulate scale by using discrete element method (DEM). The micromechanics-based TM model is superior to capturing the sudden crash of soil skeletons caused by thaw-induced cementation loss between soil grains. The DEM-simulated TM response is then More >

  • Open Access

    PROCEEDINGS

    Three-Dimensional Numerical Simulation of Large-Scale LandslideGenerated Surging Waves with a GPU‒Accelerated Soil‒Water Coupled SPH Model

    Can Huang1,*, Xiaoliang Wang1, Qingquan Liu1, Huaning Wang2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09824

    Abstract Soil‒water coupling is an important process in landslide-generated impulse waves (LGIW) problems, accompanied by large deformation of soil, strong interface coupling and three-dimensional effect. A meshless particle method, smooth particle hydrodynamics (SPH) has great advantages in dealing with complex interface and multiphase coupling problems. This study presents an improved soil‒water coupled model to simulate LGIW problems based on an open source code DualSPHysics (v4.0). Aiming to solve the low efficiency problem in modeling real large-scale LGIW problems, graphics processing unit (GPU) acceleration technology is implemented into this code. An experimental example, subaerial landslidegenerated water waves,… More >

  • Open Access

    ARTICLE

    Deep Learning Framework for Landslide Severity Prediction and Susceptibility Mapping

    G. Bhargavi*, J. Arunnehru

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1257-1272, 2023, DOI:10.32604/iasc.2023.034335 - 05 January 2023

    Abstract Landslides are a natural hazard that is unpredictable, but we can prevent them. The Landslide Susceptibility Index reduces the uncertainty of living with landslides significantly. Planning and managing landslide-prone areas is critical. Using the most optimistic deep neural network techniques, the proposed work classifies and analyses the severity of the landslide. The selected experimental study area is Kerala’s Idukki district. A total of 3363 points were considered for this experiment using historic landslide points, field surveys, and literature searches. The primary triggering factors slope degree, slope aspect, elevation (altitude), normalized difference vegetation index (NDVI), and… More >

  • Open Access

    ARTICLE

    Analysis of the Mechanisms Underpinning Rainstorm-Induced Landslides

    Shaojie Feng*, Leipeng Liu, Chen Gao, Hang Hu

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.5, pp. 1189-1201, 2023, DOI:10.32604/fdmp.2023.023637 - 30 November 2022

    Abstract The present study considers the damage mechanisms and the rainfall infiltration process responsible for landslide phenomena which originate from accumulation slopes. Accordingly, a physical test model is developed for different slopes and different rainfall conditions. Moreover, a three-dimensional laser scanner and a camera are used to monitor the slope erosion and the landslide dynamic evolution. Using this approach, the time variation curves of volumetric water content, pore water pressure, soil pressure, slope deformation, and damage are determined. The results show that under similar conditions, similar trends of the pore water pressure are achieved for different More > Graphic Abstract

    Analysis of the Mechanisms Underpinning Rainstorm-Induced Landslides

  • Open Access

    ARTICLE

    Application of Smoothed Particle Hydrodynamics (SPH) for the Simulation of Flow-Like Landslides on 3D Terrains

    Binghui Cui1,*, Liaojun Zhang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 357-376, 2023, DOI:10.32604/cmes.2022.022309 - 29 September 2022

    Abstract Flow-type landslide is one type of landslide that generally exhibits characteristics of high flow velocities, long jump distances, and poor predictability. Simulation of its propagation process can provide solutions for risk assessment and mitigation design. The smoothed particle hydrodynamics (SPH) method has been successfully applied to the simulation of two-dimensional (2D) and three-dimensional (3D) flow-like landslides. However, the influence of boundary resistance on the whole process of landslide failure is rarely discussed. In this study, a boundary condition considering friction is proposed and integrated into the SPH method, and its accuracy is verified. Moreover, the… More > Graphic Abstract

    Application of Smoothed Particle Hydrodynamics (SPH) for the Simulation of Flow-Like Landslides on 3D Terrains

  • Open Access

    ARTICLE

    Transforming Hand Drawn Wireframes into Front-End Code with Deep Learning

    Saman Riaz1, Ali Arshad2, Shahab S. Band3,*, Amir Mosavi4

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4303-4321, 2022, DOI:10.32604/cmc.2022.024819 - 21 April 2022

    Abstract The way towards generating a website front end involves a designer settling on an idea for what kind of layout they want the website to have, then proceeding to plan and implement each aspect one by one until they have converted what they initially laid out into its Html front end form, this process can take a considerable time, especially considering the first draft of the design is traditionally never the final one. This process can take up a large amount of resource real estate, and as we have laid out in this paper, by… More >

  • Open Access

    ARTICLE

    Twisted Pair Cable Fault Diagnosis via Random Forest Machine Learning

    N. B. Ghazali1, F. C. Seman1,*, K. Isa1, K. N. Ramli1, Z. Z. Abidin1, S. M. Mustam1, M. A. Haek2, A. N. Z. Abidin2, A. Asrokin2

    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5427-5440, 2022, DOI:10.32604/cmc.2022.023211 - 14 January 2022

    Abstract Applying the fault diagnosis techniques to twisted pair copper cable is beneficial to improve the stability and reliability of internet access in Digital Subscriber Line (DSL) Access Network System. The network performance depends on the occurrence of cable fault along the copper cable. Currently, most of the telecommunication providers monitor the network performance degradation hence troubleshoot the present of the fault by using commercial test gear on-site, which may be resolved using data analytics and machine learning algorithm. This paper presents a fault diagnosis method for twisted pair cable fault detection based on knowledge-based and… More >

  • Open Access

    ARTICLE

    Application of the Navier-Stokes Equations to the Analysis of the Landslide Sediments Permeability and Related Seepage Effects

    Meng Song1,*, Yuncai Liu2, Zhen Wang1

    FDMP-Fluid Dynamics & Materials Processing, Vol.18, No.2, pp. 313-327, 2022, DOI:10.32604/fdmp.2022.017737 - 16 December 2021

    Abstract The purpose of the study is to implement a new model based on the Navier-Stokes equations for the characterization of landslide sediments interacting with a moving fluid. The model is implemented by combining Hypermesh, the LS-DYNA software and MATLAB. The results show that the main factors affecting the permeability of landslide sediments are the genetic mechanism, the structure and composition of materials, material lithology, and stress. The characteristics and mechanism of permeability changes are determined by adjusting the water levels of fluids. It is found that the permeability of landslide sediments increases at the front More >

  • Open Access

    ARTICLE

    Predicting Concrete Compressive Strength Using Deep Convolutional Neural Network Based on Image Characteristics

    Sanghyo Lee1, Yonghan Ahn2, Ha Young Kim3, *

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 1-17, 2020, DOI:10.32604/cmc.2020.011104 - 23 July 2020

    Abstract In this study, we examined the efficacy of a deep convolutional neural network (DCNN) in recognizing concrete surface images and predicting the compressive strength of concrete. A digital single-lens reflex (DSLR) camera and microscope were simultaneously used to obtain concrete surface images used as the input data for the DCNN. Thereafter, training, validation, and testing of the DCNNs were performed based on the DSLR camera and microscope image data. Results of the analysis indicated that the DCNN employing DSLR image data achieved a relatively higher accuracy. The accuracy of the DSLR-derived image data was attributed… More >

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