Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (6)
  • Open Access


    Numerical Study of the Biomechanical Behavior of a 3D Printed Polymer Esophageal Stent in the Esophagus by BP Neural Network Algorithm

    Guilin Wu1,2, Shenghua Huang1, Tingting Liu3, Zhuoni Yang3, Yuesong Wu2, Guihong Wei1, Peng Yu1,*, Qilin Zhang4, Jun Feng4, Bo Zeng5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2709-2725, 2024, DOI:10.32604/cmes.2023.031399

    Abstract Esophageal disease is a common disorder of the digestive system that can severely affect the quality of life and prognosis of patients. Esophageal stenting is an effective treatment that has been widely used in clinical practice. However, esophageal stents of different types and parameters have varying adaptability and effectiveness for patients, and they need to be individually selected according to the patient’s specific situation. The purpose of this study was to provide a reference for clinical doctors to choose suitable esophageal stents. We used 3D printing technology to fabricate esophageal stents with different ratios of… More >

  • Open Access


    Estimation of Weibull Distribution Parameters for Wind Speed Characteristics Using Neural Network Algorithm

    Musaed Alrashidi*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1073-1088, 2023, DOI:10.32604/cmc.2023.036170

    Abstract Harvesting the power coming from the wind provides a green and environmentally friendly approach to producing electricity. To facilitate the ongoing advancement in wind energy applications, deep knowledge about wind regime behavior is essential. Wind speed is typically characterized by a statistical distribution, and the two-parameters Weibull distribution has shown its ability to represent wind speeds worldwide. Estimation of Weibull parameters, namely scale and shape parameters, is vital to describe the observed wind speeds data accurately. Yet, it is still a challenging task. Several numerical estimation approaches have been used by researchers to obtain c and… More >

  • Open Access


    Micro Calcification Detection in Mammogram Images Using Contiguous Convolutional Neural Network Algorithm

    P. Gomathi1,*, C. Muniraj2, P. S. Periasamy3

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1887-1899, 2023, DOI:10.32604/csse.2023.028808

    Abstract The mortality rate decreases as the early detection of Breast Cancer (BC) methods are emerging very fast, and when the starting stage of BC is detected, it is curable. The early detection of the disease depends on the image processing techniques, and it is used to identify the disease easily and accurately, especially the micro calcifications are visible on mammography when they are 0.1 mm or bigger, and cancer cells are about 0.03 mm, which is crucial for identifying in the BC area. To achieve this micro calcification in the BC images, it is necessary… More >

  • Open Access


    Deriving Driver Behavioral Pattern Analysis and Performance Using Neural Network Approaches

    Meenakshi Malik1, Rainu Nandal1,*, Surjeet Dalal2, Vivek Jalglan3, Dac-Nhuong Le4,5

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 87-99, 2022, DOI:10.32604/iasc.2022.020249

    Abstract It has been observed that driver behavior has a direct and considerable impact upon factors like fuel consumption, environmentally harmful emissions, and public safety, making it a key consideration of further research in order to monitor and control such related hazards. This has fueled our decision to conduct a study in order to arrive at an efficient way of analyzing the various parameters of driver behavior and find ways and means of positively impacting such behavior. It has been ascertained that such behavioral patterns can significantly impact the analysis of traffic-related conditions and outcomes. In… More >

  • Open Access


    Developing a Recognition System for Classifying COVID-19 Using a Convolutional Neural Network Algorithm

    Fawaz Waselallah Alsaade1, Theyazn H. H. Aldhyani2,*, Mosleh Hmoud Al-Adhaileh3

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 805-819, 2021, DOI:10.32604/cmc.2021.016264

    Abstract The COVID-19 pandemic poses an additional serious public health threat due to little or no pre-existing human immunity, and developing a system to identify COVID-19 in its early stages will save millions of lives. This study applied support vector machine (SVM), k-nearest neighbor (K-NN) and deep learning convolutional neural network (CNN) algorithms to classify and detect COVID-19 using chest X-ray radiographs. To test the proposed system, chest X-ray radiographs and CT images were collected from different standard databases, which contained 95 normal images, 140 COVID-19 images and 10 SARS images. Two scenarios were considered to… More >

  • Open Access


    Application of the Fuzzy Neural Network Algorithm in the Exploration of the Agricultural Products E-Commerce Path

    Shuangying Liu1, Weidong Zhang2,*

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 569-575, 2020, DOI:10.32604/iasc.2020.013935

    Abstract The constant development of computer technology has greatly facilitated our life. In the past, the agricultural products trade and agricultural products business model were an offline development, through face-to-face transactions. However, with the continuous application of Internet technology, we also have a new exploration on the e-commerce path of agricultural products. The fuzzy neural network algorithm was used to study the electronic commerce path of agricultural products and helped us to carry out the exploration computation of the electronic commerce path of agricultural products. And good calculation results have been obtained. Through our testing of More >

Displaying 1-10 on page 1 of 6. Per Page