Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (313)
  • Open Access

    ARTICLE

    Leveraging Blockchain with Optimal Deep Learning-Based Drug Supply Chain Management for Pharmaceutical Industries

    Shanthi Perumalsamy, Venkatesh Kaliyamurthy*

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2341-2357, 2023, DOI:10.32604/cmc.2023.040269

    Abstract Due to its complexity and involvement of numerous stakeholders, the pharmaceutical supply chain presents many challenges that companies must overcome to deliver necessary medications to patients efficiently. The pharmaceutical supply chain poses different challenging issues, encompasses supply chain visibility, cold-chain shipping, drug counterfeiting, and rising prescription drug prices, which can considerably surge out-of-pocket patient costs. Blockchain (BC) offers the technical base for such a scheme, as it could track legitimate drugs and avoid fake circulation. The designers presented the procedure of BC with fabric for creating a secured drug supply-chain management (DSCM) method. With this motivation, the study presents a… More >

  • Open Access

    ARTICLE

    Experimental Evaluation of Individual Hotspots of a Multicore Microprocessor Using Pulsating Heat Sources

    Rodrigo Vidonscky Pinto1, Flávio Augusto Sanzovo Fiorelli2,*

    Frontiers in Heat and Mass Transfer, Vol.21, pp. 427-443, 2023, DOI:10.32604/fhmt.2023.041917

    Abstract The present work provides an experimental and numerical procedure to obtain the geometrical position of the hotspots of a microprocessor using the thermal images obtained from the transient thermal response of this processor subject to pulsating stress tests. This is performed by the solution of the steady inverse heat transfer problem using these thermal images, resulting in qualitative heat source distributions; these are analyzed using the mean heat source gradients to identify the elements that can be considered hotspots. This procedure identified that the processor INTEL Core 2 Quad Q8400S contains one hotspot located in the center of its left… More >

  • Open Access

    ARTICLE

    Low-Strain Damage Imaging Detection Experiment for Model Pile Integrity Based on HHT

    Ziyang Jiang1, Ziping Wang1,*, Kan Feng1, Yang Zhang2, Rahim Gorgin1

    Structural Durability & Health Monitoring, Vol.17, No.6, pp. 557-569, 2023, DOI:10.32604/sdhm.2023.042393

    Abstract With the advancement of computer and mathematical techniques, significant progress has been made in the 3D modeling of foundation piles. Existing methods include the 3D semi-analytical model for non-destructive low-strain integrity assessment of large-diameter thin-walled pipe piles and the 3D soil-pile dynamic interaction model. However, these methods have complex analysis procedures and substantial limitations. This paper introduces an innovative and streamlined 3D imaging technique tailored for the detection of pile damage. The approach harnesses the power of an eight-channel ring array transducer to capture internal reflection signals within foundation piles. The acquired signals are subsequently processed using the Hilbert-Huang Transform… More >

  • Open Access

    ARTICLE

    An Improved Lung Cancer Segmentation Based on Nature-Inspired Optimization Approaches

    Shazia Shamas1, Surya Narayan Panda1,*, Ishu Sharma1,*, Kalpna Guleria1, Aman Singh2,3,4, Ahmad Ali AlZubi5, Mallak Ahmad AlZubi6

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1051-1075, 2024, DOI:10.32604/cmes.2023.030712

    Abstract The distinction and precise identification of tumor nodules are crucial for timely lung cancer diagnosis and planning intervention. This research work addresses the major issues pertaining to the field of medical image processing while focusing on lung cancer Computed Tomography (CT) images. In this context, the paper proposes an improved lung cancer segmentation technique based on the strengths of nature-inspired approaches. The better resolution of CT is exploited to distinguish healthy subjects from those who have lung cancer. In this process, the visual challenges of the K-means are addressed with the integration of four nature-inspired swarm intelligent techniques. The techniques… More >

  • Open Access

    ARTICLE

    Optical Based Gradient-Weighted Class Activation Mapping and Transfer Learning Integrated Pneumonia Prediction Model

    Chia-Wei Jan1, Yu-Jhih Chiu1, Kuan-Lin Chen2, Ting-Chun Yao3, Ping-Huan Kuo1,4,*

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2989-3010, 2023, DOI:10.32604/csse.2023.042078

    Abstract Pneumonia is a common lung disease that is more prone to affect the elderly and those with weaker respiratory systems. However, hospital medical resources are limited, and sometimes the workload of physicians is too high, which can affect their judgment. Therefore, a good medical assistance system is of great significance for improving the quality of medical care. This study proposed an integrated system by combining transfer learning and gradient-weighted class activation mapping (Grad-CAM). Pneumonia is a common lung disease that is generally diagnosed using X-rays. However, in areas with limited medical resources, a shortage of medical personnel may result in… More >

  • Open Access

    ARTICLE

    Enhanced 3D Point Cloud Reconstruction for Light Field Microscopy Using U-Net-Based Convolutional Neural Networks

    Shariar Md Imtiaz1, Ki-Chul Kwon1, F. M. Fahmid Hossain1, Md. Biddut Hossain1, Rupali Kiran Shinde1, Sang-Keun Gil2, Nam Kim1,*

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2921-2937, 2023, DOI:10.32604/csse.2023.040205

    Abstract This article describes a novel approach for enhancing the three-dimensional (3D) point cloud reconstruction for light field microscopy (LFM) using U-net architecture-based fully convolutional neural network (CNN). Since the directional view of the LFM is limited, noise and artifacts make it difficult to reconstruct the exact shape of 3D point clouds. The existing methods suffer from these problems due to the self-occlusion of the model. This manuscript proposes a deep fusion learning (DL) method that combines a 3D CNN with a U-Net-based model as a feature extractor. The sub-aperture images obtained from the light field microscopy are aligned to form… More >

  • Open Access

    ARTICLE

    A New Three-Dimensional (3D) Printing Prepress Algorithm for Simulation of Planned Surgery for Congenital Heart Disease

    Vitaliy Suvorov1,2,*, Olga Loboda2, Maria Balakina1, Igor Kulczycki2

    Congenital Heart Disease, Vol.18, No.5, pp. 491-505, 2023, DOI:10.32604/chd.2023.030583

    Abstract Background: Three-dimensional printing technology may become a key factor in transforming clinical practice and in significant improvement of treatment outcomes. The introduction of this technique into pediatric cardiac surgery will allow us to study features of the anatomy and spatial relations of a defect and to simulate the optimal surgical repair on a printed model in every individual case. Methods: We performed the prospective cohort study which included 29 children with congenital heart defects. The hearts and the great vessels were modeled and printed out. Measurements of the same cardiac areas were taken in the same planes and points at… More > Graphic Abstract

    A New Three-Dimensional (3D) Printing Prepress Algorithm for Simulation of Planned Surgery for Congenital Heart Disease

  • Open Access

    REVIEW

    Advances in Research of Molded Pulp for Food Packaging

    Yifan Liu1, Shufeng Ma2, Feijie Wang1, Liqiang Wang1,*

    Journal of Renewable Materials, Vol.11, No.11, pp. 3831-3846, 2023, DOI:10.32604/jrm.2023.028251

    Abstract The molded pulp, a product of three-dimensional papermaking technology, is environmentally friendly and has a low environmental impact due to its ability to decompose quickly in the natural environment after disposal. The application of molded pulp for food packaging can replace or reduce the use of plastic food packaging. Researchers extract fibers from plants for the production of safe and hygienic molded pulp for food packaging, and they also study and enhance the qualities of molded pulp to broaden its use in the food industry. This paper reviews the sources and varieties of plant fiber used in molded pulp for… More > Graphic Abstract

    Advances in Research of Molded Pulp for Food Packaging

  • Open Access

    ARTICLE

    An Improved Jump Spider Optimization for Network Traffic Identification Feature Selection

    Hui Xu, Yalin Hu*, Weidong Cao, Longjie Han

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3239-3255, 2023, DOI:10.32604/cmc.2023.039227

    Abstract The massive influx of traffic on the Internet has made the composition of web traffic increasingly complex. Traditional port-based or protocol-based network traffic identification methods are no longer suitable for today’s complex and changing networks. Recently, machine learning has been widely applied to network traffic recognition. Still, high-dimensional features and redundant data in network traffic can lead to slow convergence problems and low identification accuracy of network traffic recognition algorithms. Taking advantage of the faster optimization-seeking capability of the jumping spider optimization algorithm (JSOA), this paper proposes a jumping spider optimization algorithm that incorporates the harris hawk optimization (HHO) and… More >

  • Open Access

    ARTICLE

    3D Kronecker Convolutional Feature Pyramid for Brain Tumor Semantic Segmentation in MR Imaging

    Kainat Nazir1, Tahir Mustafa Madni1, Uzair Iqbal Janjua1, Umer Javed2, Muhammad Attique Khan3, Usman Tariq4, Jae-Hyuk Cha5,*

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2861-2877, 2023, DOI:10.32604/cmc.2023.039181

    Abstract Brain tumor significantly impacts the quality of life and changes everything for a patient and their loved ones. Diagnosing a brain tumor usually begins with magnetic resonance imaging (MRI). The manual brain tumor diagnosis from the MRO images always requires an expert radiologist. However, this process is time-consuming and costly. Therefore, a computerized technique is required for brain tumor detection in MRI images. Using the MRI, a novel mechanism of the three-dimensional (3D) Kronecker convolution feature pyramid (KCFP) is used to segment brain tumors, resolving the pixel loss and weak processing of multi-scale lesions. A single dilation rate was replaced… More >

Displaying 21-30 on page 3 of 313. Per Page