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  • Open Access

    ARTICLE

    Multiple-Object Tracking Using Histogram Stamp Extraction in CCTV Environments

    Ye-Yeon Kang1, Geon Park1, Hyun Yoo2, Kyungyong Chung1,*

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.043566

    Abstract Object tracking, an important technology in the field of image processing and computer vision, is used to continuously track a specific object or person in an image. This technology may be effective in identifying the same person within one image, but it has limitations in handling multiple images owing to the difficulty in identifying whether the object appearing in other images is the same. When tracking the same object using two or more images, there must be a way to determine that objects existing in different images are the same object. Therefore, this paper attempts to determine the same object… More >

  • Open Access

    ARTICLE

    Nuclei Segmentation in Histopathology Images Using Structure-Preserving Color Normalization Based Ensemble Deep Learning Frameworks

    Manas Ranjan Prusty1, Rishi Dinesh2, Hariket Sukesh Kumar Sheth2, Alapati Lakshmi Viswanath2, Sandeep Kumar Satapathy2,3,*

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.042718

    Abstract This paper presents a novel computerized technique for the segmentation of nuclei in hematoxylin and eosin (H&E) stained histopathology images. The purpose of this study is to overcome the challenges faced in automated nuclei segmentation due to the diversity of nuclei structures that arise from differences in tissue types and staining protocols, as well as the segmentation of variable-sized and overlapping nuclei. To this extent, the approach proposed in this study uses an ensemble of the UNet architecture with various Convolutional Neural Networks (CNN) architectures as encoder backbones, along with stain normalization and test time augmentation, to improve segmentation accuracy.… More >

  • Open Access

    ARTICLE

    Research on Human Activity Recognition Algorithm Based on LSTM-1DCNN

    Yuesheng Zhao1, Xiaoling Wang1,*, Yutong Luo2,*, Muhammad Shamrooz Aslam3

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.040528

    Abstract With the rapid advancement of wearable devices, Human Activities Recognition (HAR) based on these devices has emerged as a prominent research field. The objective of this study is to enhance the recognition performance of HAR by proposing an LSTM-1DCNN recognition algorithm that utilizes a single triaxial accelerometer. This algorithm comprises two branches: one branch consists of a Long and Short-Term Memory Network (LSTM), while the other parallel branch incorporates a one-dimensional Convolutional Neural Network (1DCNN). The parallel architecture of LSTM-1DCNN initially extracts spatial and temporal features from the accelerometer data separately, which are then concatenated and fed into a fully… More >

  • Open Access

    ARTICLE

    Analyzing the Impact of Blockchain Models for Securing Intelligent Logistics through Unified Computational Techniques

    Mohammed S. Alsaqer1, Majid H. Alsulami2,*, Rami N. Alkhawaji3, Abdulellah A. Alaboudi2

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.042379

    Abstract Blockchain technology has revolutionized conventional trade. The success of blockchain can be attributed to its distributed ledger characteristic, which secures every record inside the ledger using cryptography rules, making it more reliable, secure, and tamper-proof. This is evident by the significant impact that the use of this technology has had on people connected to digital spaces in the present-day context. Furthermore, it has been proven that blockchain technology is evolving from new perspectives and that it provides an effective mechanism for the intelligent transportation system infrastructure. To realize the full potential of the accurate and efficacious use of blockchain in… More >

  • Open Access

    ARTICLE

    Heart Disease Prediction Using Convolutional Neural Network with Elephant Herding Optimization

    P. Nandakumar, R. Subhashini*

    Computer Systems Science and Engineering, Vol., , DOI:10.32604/csse.2023.042294

    Abstract Heart disease is a major cause of death for many people in the world. Each year the death rate of people affected with heart disease increased a lot. Machine learning models have been widely used for the prediction of heart disease from the different University of California Irvine (UCI) Machine Learning Repositories. But, due to certain data, it predicts less accurately, whereas, for large data, its sub-model deep learning is used. Our literature work has identified that only traditional methods are used for the prediction of heart disease. It will produce less accuracy. To produce more efficacy, Euclidean Distance was… More >

  • Open Access

    ARTICLE

    Numerical Study on the Effect of Vortex Generators on the Aerodynamic Drag of a High-Speed Train

    Tian Li1,2,*, Hao Liang1, Zerui Xiang2, Jiye Zhang1

    FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.043618

    Abstract A relatively high aerodynamic drag is an important factor that hinders the further acceleration of high-speed trains. Using the shear stress transport (SST) k-ω turbulence model, the effect of various vortex generator types on the aerodynamic characteristics of an ICE2 (Inter-city Electricity) train has been investigated. The results indicate that the vortex generators with wider triangle, trapezoid, and micro-ramp arranged on the surface of the tail car can significantly change the distribution of surface pressure and affect the vorticity intensity in the wake. This alteration effectively reduces the resistance of the tail car. Meanwhile, the micro-ramp vortex generator with its… More > Graphic Abstract

    Numerical Study on the Effect of Vortex Generators on the Aerodynamic Drag of a High-Speed Train

  • Open Access

    ARTICLE

    Analysis of Calcined Red Mud Properties and Related Mortar Performances

    Zhengfan Lyu1,3, Yulin Li2,3, Mengmeng Fan1,3,*, Yan Huang1, Chenguang Li2

    FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.043512

    Abstract Red mud (RM) is a low-activity industrial solid waste, and its utilization as a resource is currently a hot topic. In this study, the micro characteristics of red mud at different calcination temperatures were analyzed using X-ray diffraction and scanning electron microscopy. The performance of calcined red mud was determined through mortar strength tests. Results indicate that high-temperature calcination can change the mineral composition and microstructure of red mud, and increase the surface roughness and specific surface area. At the optimal temperature of 700°C, the addition of calcined red mud still leads to a decrease in mortar strength, but its… More > Graphic Abstract

    Analysis of Calcined Red Mud Properties and Related Mortar Performances

  • Open Access

    ARTICLE

    A Numerical Study on the Effect of the Backflow Hole Position on the Performances of a Self-Priming Pump

    Dongwei Wang1,*, Lijian Cao1, Weidong Wang2, Jiajun Hu1

    FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.042654

    Abstract A self-priming pump is a centrifugal pump that has the ability to prime itself. Typically, its performance depends on the configuration of its reflux hole. In this study, the ANSYS FLUENT software is used to investigate the effects of three different radial positions of the reflux hole on gas-liquid two-phase distribution, pressure pulsation, and imp during self-priming. The research results indicate that: (1) The effective channel size for the reflux liquid to enter the volute varies depending on the location of the reflux hole. The effect of the impeller rotation on the reflux liquid becomes more obvious as the setting… More >

  • Open Access

    ARTICLE

    Analysis and Optimization of the Electrohydraulic Forming Process of Sinusoidal Corrugation Tubes

    Da Cai, Yinlong Song, Hao Jiang, Guangyao Li, Junjia Cui*

    FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.025833

    Abstract Aluminum alloy thin-walled structures are widely used in the automotive industry due to their advantages related to light weight and crashworthiness. They can be produced at room temperature by the electrohydraulic forming process. In the present study, the influence of the related parameters on the forming quality of a 6063 aluminum alloy sinusoidal corrugation tube has been assessed. In particular, the orthogonal experimental design (OED) and central composite design (CCD) methods have been used. Through the range analysis and variance analysis of the experimental data, the influence degree of wire diameter (WD) and discharge energy (DE) on the forming quality… More >

  • Open Access

    ARTICLE

    Investigative Review of Design Techniques of Parabolic Trough Solar Collectors

    Roba Tarek AbdelFatah*, Irene S. Fahim, Mohamed Mahran Kasem

    Frontiers in Heat and Mass Transfer, Vol., , DOI:10.32604/fhmt.2023.044706

    Abstract Parabolic trough solar collectors (PTCs) are among the most cost-efficient solar thermal technologies. They have several applications, such as feed heaters, boilers, steam generators, and electricity generators. A PTC is a concentrated solar power system that uses parabolic reflectors to focus sunlight onto a tube filled with heattransfer fluid. PTCs performance can be investigated using optical and thermal mathematical models. These models calculate the amount of energy entering the receiver, the amount of usable collected energy, and the amount of heat loss due to convection and radiation. There are several methods and configurations that have been developed so far; however,… More > Graphic Abstract

    Investigative Review of Design Techniques of Parabolic Trough Solar Collectors

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