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  • Open Access

    ARTICLE

    2D Minimum Compliance Topology Optimization Based on a Region Partitioning Strategy

    Chong Wang1, Tongxing Zuo1,2, Haitao Han1,2, Qianglong Wang1,2, Han Zhang1, Zhenyu Liu1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 655-683, 2023, DOI:10.32604/cmes.2023.025153

    Abstract This paper presents an extended sequential element rejection and admission (SERA) topology optimization method with a region partitioning strategy. Based on the partitioning of a design domain into solid regions and weak regions, the proposed optimization method sequentially implements finite element analysis (FEA) in these regions. After standard FEA in the solid regions, the boundary displacement of the weak regions is constrained using the numerical solution of the solid regions as Dirichlet boundary conditions. This treatment can alleviate the negative effect of the material interpolation model of the topology optimization method in the weak regions, such as the condition number… More > Graphic Abstract

    2D Minimum Compliance Topology Optimization Based on a Region Partitioning Strategy

  • Open Access

    ARTICLE

    Structural Damage Identification System Suitable for Old Arch Bridge in Rural Regions: Random Forest Approach

    Yu Zhang, Zhihua Xiong*, Zhuoxi Liang, Jiachen She, Chicheng Ma

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 447-469, 2023, DOI:10.32604/cmes.2023.022699

    Abstract A huge number of old arch bridges located in rural regions are at the peak of maintenance. The health monitoring technology of the long-span bridge is hardly applicable to the small-span bridge, owing to the absence of technical resources and sufficient funds in rural regions. There is an urgent need for an economical, fast, and accurate damage identification solution. The authors proposed a damage identification system of an old arch bridge implemented with a machine learning algorithm, which took the vehicle-induced response as the excitation. A damage index was defined based on wavelet packet theory, and a machine learning sample… More >

  • Open Access

    ARTICLE

    Faster Region Based Convolutional Neural Network for Skin Lesion Segmentation

    G. Murugesan1,*, J. Jeyapriya2, M. Hemalatha3, S. Rajeshkannan4

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2099-2109, 2023, DOI:10.32604/iasc.2023.032068

    Abstract The diagnostic interpretation of dermoscopic images is a complex task as it is very difficult to identify the skin lesions from the normal. Thus the accurate detection of potential abnormalities is required for patient monitoring and effective treatment. In this work, a Two-Tier Segmentation (TTS) system is designed, which combines the unsupervised and supervised techniques for skin lesion segmentation. It comprises preprocessing by the median filter, TTS by Colour K-Means Clustering (CKMC) for initial segmentation and Faster Region based Convolutional Neural Network (FR-CNN) for refined segmentation. The CKMC approach is evaluated using the different number of clusters (k = 3,… More >

  • Open Access

    ARTICLE

    Hybrid Convolutional Neural Network for Plant Diseases Prediction

    S. Poornima1,*, N. Sripriya1, Adel Fahad Alrasheedi2, S. S. Askar2, Mohamed Abouhawwash3,4

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2393-2409, 2023, DOI:10.32604/iasc.2023.024820

    Abstract Plant diseases prediction is the essential technique to prevent the yield loss and gain high production of agricultural products. The monitoring of plant health continuously and detecting the diseases is a significant for sustainable agriculture. Manual system to monitor the diseases in plant is time consuming and report a lot of errors. There is high demand for technology to detect the plant diseases automatically. Recently image processing approach and deep learning approach are highly invited in detection of plant diseases. The diseases like late blight, bacterial spots, spots on Septoria leaf and yellow leaf curved are widely found in plants.… More >

  • Open Access

    ARTICLE

    Nucleotide Sequence Assessment of Four ORFs of Citrus Tristeza Virus: Evidence of Recombination

    Adel A. Rezk1,2,*, Hala A. Amin2

    Phyton-International Journal of Experimental Botany, Vol.92, No.3, pp. 691-705, 2023, DOI:10.32604/phyton.2022.024208

    Abstract Citrus Tristeza Virus (CTV), usually occurs in nature as a mixture of genotypes. Six naturally infected citrus (Citrus sinensis) trees grafted on sour orange rootstock were collected from three citrus growing governorates in Egypt (Sharqia, Qalyubia and Garbia). In this study, RT-PCR, Single-Strand Conformation Polymorphism (SSCP) and nucleotide sequence analysis were used for four independent CTV genomic regions (p65, p18, p20, and p23) to detect and assess the sequence and genetic variabilities among CTV Egyptian isolates. RTPCR products (650 bp) for the CTV p23 gene obtained from the selected isolates were used for the SSCP analysis and DNA sequencing. SSCP… More >

  • Open Access

    ARTICLE

    Detection of Copy-Move Forgery in Digital Images Using Singular Value Decomposition

    Zaid Nidhal Khudhair1,4, Farhan Mohamed2, Amjad Rehman3,*, Tanzila Saba3, Saeed Ali bahaj3

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4135-4147, 2023, DOI:10.32604/cmc.2023.032315

    Abstract This paper presents an improved approach for detecting copy-move forgery based on singular value decomposition (SVD). It is a block-based method where the image is scanned from left to right and top to down by a sliding window with a determined size. At each step, the SVD is determined. First, the diagonal matrix’s maximum value (norm) is selected (representing the scaling factor for SVD and a fixed value for each set of matrix elements even when rotating the matrix or scaled). Then, the similar norms are grouped, and each leading group is separated into many subgroups (elements of each subgroup… More >

  • Open Access

    ARTICLE

    Region Centric GL Feature Approximation Based Secure Routing for Improved QoS in MANET

    S. Soundararajan1, R. Prabha2, M. Baskar3,*, T. J. Nagalakshmi4

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 267-280, 2023, DOI:10.32604/iasc.2023.032239

    Abstract Secure routing in Mobile Adhoc Network (Manet) is the key issue now a day in providing secure access to different network services. As mobile devices are used in accessing different services, performing secure routing becomes a challenging task. Towards this, different approaches exist which find the trusted route based on their previous transmission details and behavior of different nodes. Also, the methods focused on trust measurement based on tiny information obtained from local nodes or with global information which are incomplete. However, the adversary nodes are more capable and participate in each transmission not just to steal the data also… More >

  • Open Access

    ARTICLE

    Data-Driven Models for Predicting Solar Radiation in Semi-Arid Regions

    Mehdi Jamei1, Nadjem Bailek2,*, Kada Bouchouicha3, Muhammed A. Hassan4, Ahmed Elbeltagi5, Alban Kuriqi6, Nadhir Al-Ansar7, Javier Almorox8, El-Sayed M. El-kenawy9,10

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1625-1640, 2023, DOI:10.32604/cmc.2023.031406

    Abstract Solar energy represents one of the most important renewable energy sources contributing to the energy transition process. Considering that the observation of daily global solar radiation (GSR) is not affordable in some parts of the globe, there is an imperative need to develop alternative ways to predict it. Therefore, the main objective of this study is to evaluate the performance of different hybrid data-driven techniques in predicting daily GSR in semi-arid regions, such as the majority of Spanish territory. Here, four ensemble-based hybrid models were developed by hybridizing Additive Regression (AR) with Random Forest (RF), Locally Weighted Linear Regression (LWLR),… More >

  • Open Access

    ARTICLE

    Tracking and Analysis of Pedestrian’s Behavior in Public Places

    Mahwish Pervaiz1, Mohammad Shorfuzzaman2, Abdulmajeed Alsufyani2, Ahmad Jalal3, Suliman A. Alsuhibany4, Jeongmin Park5,*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 841-853, 2023, DOI:10.32604/cmc.2023.029629

    Abstract Crowd management becomes a global concern due to increased population in urban areas. Better management of pedestrians leads to improved use of public places. Behavior of pedestrian’s is a major factor of crowd management in public places. There are multiple applications available in this area but the challenge is open due to complexity of crowd and depends on the environment. In this paper, we have proposed a new method for pedestrian’s behavior detection. Kalman filter has been used to detect pedestrian’s using movement based approach. Next, we have performed occlusion detection and removal using region shrinking method to isolate occluded… More >

  • Open Access

    ARTICLE

    The Effects of Water and Fertilizer Coupling on Plant and Soil Nitrogen Characteristics and Fruit Growth of Rabbiteye Blueberry Plants in a Semi-Arid Region in China

    Xiaolan Guo1,2, Di Zhao2, Jinbin Hu3, Delu Wang2,*, Jianbin Wang1, Muhammad Shakeel4

    Phyton-International Journal of Experimental Botany, Vol.92, No.1, pp. 209-223, 2023, DOI:10.32604/phyton.2022.023050

    Abstract

    To evaluate the effects of nitrogen (N) and irrigation coupling on the soil N distribution, plant N utilization, and fruit yield of rabbiteye blueberries (Vaccinium virgatum), a field experiment was designed using two factors (water and fertilizer application) with four levels of irrigation and three levels of fertilization, and a control. Under the different water and fertilizer combinations, N primarily accumulated in the leaves. Irrigation and N application within appropriate ranges (pure N ≤ 29 g/plant and irrigation volume ≤ 2.5 L/plant) significantly improved the blueberry fruit yield. Increases in water and N within these ranges promoted the effective accumulation… More >

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