Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (2,554)
  • Open Access

    ARTICLE

    Microscopic Analysis of Cementitious Sand and Gravel Damming Materials

    Ran Wang1, Aimin Gong1,*, Shanqing Shao1, Baoli Qu2, Jing Xu3, Fulai Wang1, Feipeng Liu3,*

    FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.042566

    Abstract The mechanical properties of cementitious sand and gravel damming material have been experimentally determined by means of microscopic SEM (Scanning Electron Microscopy) image analysis. The results show that the combination of fly ash and water can fill the voids in cemented sand and gravel test blocks because of the presence of hydrated calcium silicate and other substances; thereby, the compactness and mechanical properties of these materials can be greatly improved. For every 10 kg/m3 increase in the amount of cementitious material, the density increases by about 2%, and the water content decreases by 0.2%. The amount of cementitious material used… More >

  • Open Access

    ARTICLE

    Gas-Water Production of a Continental Tight-Sandstone Gas Reservoir under Different Fracturing Conditions

    Yan Liu1, Tianli Sun2, Bencheng Wang1,*, Yan Feng2

    FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.041852

    Abstract A numerical model of hydraulic fracture propagation is introduced for a representative reservoir (Yuanba continental tight sandstone gas reservoir in Northeast Sichuan). Different parameters are considered, i.e., the interlayer stress difference, the fracturing discharge rate and the fracturing fluid viscosity. The results show that these factors affect the gas and water production by influencing the fracture size. The interlayer stress difference can effectively control the fracture height. The greater the stress difference, the smaller the dimensionless reconstruction volume of the reservoir, while the flowback rate and gas production are lower. A large displacement fracturing construction increases the fracture-forming efficiency and… More >

  • Open Access

    ARTICLE

    A Novel Fracturing Fluid with High-Temperature Resistance for Ultra-Deep Reservoirs

    Lian Liu1,2, Liang Li1,2, Kebo Jiao1,2,*, Junwei Fang1,2, Yun Luo1,2

    FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.030109

    Abstract Ultra-deep reservoirs play an important role at present in fossil energy exploitation. Due to the related high temperature, high pressure, and high formation fracture pressure, however, methods for oil well stimulation do not produce satisfactory results when conventional fracturing fluids with a low pumping rate are used. In response to the above problem, a fracturing fluid with a density of 1.2~1.4 g/cm3 was developed by using Potassium formatted, hydroxypropyl guanidine gum and zirconium crosslinking agents. The fracturing fluid was tested and its ability to maintain a viscosity of 100 mPa.s over more than 60 min was verified under a shear… More >

  • Open Access

    ARTICLE

    The Turbulent Schmidt Number for Transient Contaminant Dispersion in a Large Ventilated Room Using a Realizable k-ε Model

    Fei Wang, Qinpeng Meng, Jinchi Zhao, Xin Wang, Yuhong Liu, Qianru Zhang*

    FDMP-Fluid Dynamics & Materials Processing, Vol., , DOI:10.32604/fdmp.2023.026917

    Abstract Buildings with large open spaces in which chemicals are handled are often exposed to the risk of explosions. Computational fluid dynamics is a useful and convenient way to investigate contaminant dispersion in such large spaces. The turbulent Schmidt number (Sct) concept has typically been used in this regard, and most studies have adopted a default value. We studied the concentration distribution for sulfur hexafluoride (SF6) assuming different emission rates and considering the effect of Sct. Then we examined the same problem for a light gas by assuming hydrogen gas (H2) as the contaminant. When SF6 was considered as the contaminant… More >

  • Open Access

    CORRECTION

    Correction: Learning-Based Metaheuristic Approach for Home Healthcare Optimization Problem

    Mariem Belhor1,2,3, Adnen El-Amraoui1,*, Abderrazak Jemai2, François Delmotte1

    Computer Systems Science and Engineering, Vol., , DOI:10.32604/csse.2023.048573

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    CFSA-Net: Efficient Large-Scale Point Cloud Semantic Segmentation Based on Cross-Fusion Self-Attention

    Jun Shu1,2, Shuai Wang1,2, Shiqi Yu1,2, Jie Zhang3,*

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.045818

    Abstract Traditional models for semantic segmentation in point clouds primarily focus on smaller scales. However, in real-world applications, point clouds often exhibit larger scales, leading to heavy computational and memory requirements. The key to handling large-scale point clouds lies in leveraging random sampling, which offers higher computational efficiency and lower memory consumption compared to other sampling methods. Nevertheless, the use of random sampling can potentially result in the loss of crucial points during the encoding stage. To address these issues, this paper proposes cross-fusion self-attention network (CFSA-Net), a lightweight and efficient network architecture specifically designed for directly processing large-scale point clouds.… More >

  • Open Access

    ARTICLE

    Software Defect Prediction Method Based on Stable Learning

    Xin Fan1,2,3, Jingen Mao2,3,*, Liangjue Lian2,3, Li Yu1, Wei Zheng2,3, Yun Ge2,3

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.045522

    Abstract The purpose of software defect prediction is to identify defect-prone code modules to assist software quality assurance teams with the appropriate allocation of resources and labor. In previous software defect prediction studies, transfer learning was effective in solving the problem of inconsistent project data distribution. However, target projects often lack sufficient data, which affects the performance of the transfer learning model. In addition, the presence of uncorrelated features between projects can decrease the prediction accuracy of the transfer learning model. To address these problems, this article propose a software defect prediction method based on stable learning (SDP-SL) that combines code… More >

  • Open Access

    ARTICLE

    Multi-Stream Temporally Enhanced Network for Video Salient Object Detection

    Dan Xu*, Jiale Ru, Jinlong Shi

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.045258

    Abstract Video salient object detection (VSOD) aims at locating the most attractive objects in a video by exploring the spatial and temporal features. VSOD poses a challenging task in computer vision, as it involves processing complex spatial data that is also influenced by temporal dynamics. Despite the progress made in existing VSOD models, they still struggle in scenes of great background diversity within and between frames. Additionally, they encounter difficulties related to accumulated noise and high time consumption during the extraction of temporal features over a long-term duration. We propose a multi-stream temporal enhanced network (MSTENet) to address these problems. It… More >

  • Open Access

    ARTICLE

    Facial Image-Based Autism Detection: A Comparative Study of Deep Neural Network Classifiers

    Tayyaba Farhat1,2, Sheeraz Akram3,*, Hatoon S. AlSagri3, Zulfiqar Ali4, Awais Ahmad3, Arfan Jaffar1,2

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.045022

    Abstract Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by significant challenges in social interaction, communication, and repetitive behaviors. Timely and precise ASD detection is crucial, particularly in regions with limited diagnostic resources like Pakistan. This study aims to conduct an extensive comparative analysis of various machine learning classifiers for ASD detection using facial images to identify an accurate and cost-effective solution tailored to the local context. The research involves experimentation with VGG16 and MobileNet models, exploring different batch sizes, optimizers, and learning rate schedulers. In addition, the “Orange” machine learning tool is employed to evaluate classifier performance and automated… More >

  • Open Access

    ARTICLE

    A Measurement Study of the Ethereum Underlying P2P Network

    Mohammad Z. Masoud1, Yousef Jaradat1, Ahmad Manasrah2, Mohammad Alia3, Khaled Suwais4,*, Sally Almanasra4

    CMC-Computers, Materials & Continua, Vol., , DOI:10.32604/cmc.2023.044504

    Abstract This work carried out a measurement study of the Ethereum Peer-to-Peer (P2P) network to gain a better understanding of the underlying nodes. Ethereum was applied because it pioneered distributed applications, smart contracts, and Web3. Moreover, its application layer language “Solidity” is widely used in smart contracts across different public and private blockchains. To this end, we wrote a new Ethereum client based on Geth to collect Ethereum node information. Moreover, various web scrapers have been written to collect nodes’ historical data from the Internet Archive and the Wayback Machine project. The collected data has been compared with two other services… More >

Displaying 641-650 on page 65 of 2554. Per Page