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  • Open Access

    ARTICLE

    Assessment of Seismic Damage in Nativity Church in Bethlehem Using Pushover Analysis

    Belal Almassri1,*, Ali Safiyeh2

    Structural Durability & Health Monitoring, Vol.15, No.4, pp. 349-366, 2021, DOI:10.32604/sdhm.2021.016889

    Abstract This study focuses on advanced finite element (FE) analyses on The Church of Nativity located in Bethlehem (Palestine), one of the most historic structures in the world. To ensure the model quality, a 3D FE model was created using two types of typical commercial software, DIANA FEA and SAP2000. From analyses, one of the expected behaviors for this kind of masonry structure “low modal period” was found. The seismic behavior of the church was studied using pushover analyses, which were conducted using DIANA FEA. The first unidirectional mass proportional load pattern was created in both directions, X-direction as a longitudinal… More >

  • Open Access

    ARTICLE

    Sub-1 GHz Network-Based Wireless Bridge-Monitoring System: Feature and Verification

    Li Hui1,*, Faress Hraib2, Mohammad Rahman3, Miguel Vicente4, Riyadh Hindi3

    Structural Durability & Health Monitoring, Vol.15, No.4, pp. 281-297, 2021, DOI:10.32604/sdhm.2021.016495

    Abstract Traditional bridge monitoring systems often require wired connections between sensors, a data acquisition system, and data center. The use of extension wires, conduits, and other costly accessories can dramatically increase the total cost of bridge monitoring. With the development of wireless technologies and the notable cost benefits, many researchers have been integrating wireless networks into bridge monitoring system. In this study, a wireless bridge monitoring system has been developed based on the Sub-1 GHz network. The main functional components of this system include sensors, wireless nodes, gateway and data center. Wireless nodes can convert analog signals obtained from the sensors… More >

  • Open Access

    ARTICLE

    Experimental Study on Compressive Strength of Recycled Aggregate Concrete under High Temperature

    Mohammad Akhtar1, Abdulsamee Halahla2, Amin Almasri3,*

    Structural Durability & Health Monitoring, Vol.15, No.4, pp. 335-348, 2021, DOI:10.32604/sdhm.2021.015988

    Abstract This research aims to study the effect of elevated temperature on the compressive strength evolution of concrete made with recycled aggregate. Demolished building concrete samples were collected from four different sites in Saudi Arabia, namely from Tabuk, Madina, Yanbu, and Riyadh. These concretes were crushed and recycled into aggregates to be used to make new concrete samples. These samples were tested for axial compressive strength at ages 3, 7, 14, and 28 days at ambient temperature. Samples of the same concrete mixes were subjected to the elevated temperature of 300°C and tested for compressive strength again. The experimental result reveals… More >

  • Open Access

    ARTICLE

    A QR Data Hiding Method Based on Redundant Region and BCH

    Ying Zhou*, Weiwei Luo

    Journal on Big Data, Vol.3, No.3, pp. 127-133, 2021, DOI:10.32604/jbd.2021.019236

    Abstract In recent years, QR code has been widely used in the Internet and mobile devices. It is based on open standards and easy to generate a code, which lead to that anyone can generate their own QR code. Because the QR code does not have the ability of information hiding, any device can access the content in QR code. Thus, hiding the secret data in QR code becomes a hot topic. Previously, the information hiding methods based on QR code all use the way of information hiding based on image, mostly using digital watermarking technology, and not using the coding… More >

  • Open Access

    ARTICLE

    CTSF: An End-to-End Efficient Neural Network for Chinese Text with Skeleton Feature

    Hengyang Wang, Jin Liu*, Haoliang Ren

    Journal on Big Data, Vol.3, No.3, pp. 119-126, 2021, DOI:10.32604/jbd.2021.017184

    Abstract The past decade has seen the rapid development of text detection based on deep learning. However, current methods of Chinese character detection and recognition have proven to be poor. The accuracy of segmenting text boxes in natural scenes is not impressive. The reasons for this strait can be summarized into two points: the complexity of natural scenes and numerous types of Chinese characters. In response to these problems, we proposed a lightweight neural network architecture named CTSF. It consists of two modules, one is a text detection network that combines CTPN and the image feature extraction modules of PVANet, named… More >

  • Open Access

    ARTICLE

    WMA: A Multi-Scale Self-Attention Feature Extraction Network Based on Weight Sharing for VQA

    Yue Li, Jin Liu*, Shengjie Shang

    Journal on Big Data, Vol.3, No.3, pp. 111-118, 2021, DOI:10.32604/jbd.2021.017169

    Abstract Visual Question Answering (VQA) has attracted extensive research focus and has become a hot topic in deep learning recently. The development of computer vision and natural language processing technology has contributed to the advancement of this research area. Key solutions to improve the performance of VQA system exist in feature extraction, multimodal fusion, and answer prediction modules. There exists an unsolved issue in the popular VQA image feature extraction module that extracts the fine-grained features from objects of different scale difficultly. In this paper, a novel feature extraction network that combines multi-scale convolution and self-attention branches to solve the above… More >

  • Open Access

    ARTICLE

    Survey on Research of RNN-Based Spatio-Temporal Sequence Prediction Algorithms

    Wei Fang1,2,*, Yupeng Chen1, Qiongying Xue1

    Journal on Big Data, Vol.3, No.3, pp. 97-110, 2021, DOI:10.32604/jbd.2021.016993

    Abstract In the past few years, deep learning has developed rapidly, and many researchers try to combine their subjects with deep learning. The algorithm based on Recurrent Neural Network (RNN) has been successfully applied in the fields of weather forecasting, stock forecasting, action recognition, etc. because of its excellent performance in processing Spatio-temporal sequence data. Among them, algorithms based on LSTM and GRU have developed most rapidly because of their good design. This paper reviews the RNN-based Spatiotemporal sequence prediction algorithm, introduces the development history of RNN and the common application directions of the Spatio-temporal sequence prediction, and includes precipitation nowcasting… More >

  • Open Access

    ARTICLE

    Pressure-Induced Instability Characteristics of a Transient Flow and Energy Distribution through a Loosely Bent Square Duct

    Sreedham Chandra Adhikari1, Ratan Kumar Chanda1, Sidhartha Bhowmick1, Rabindra Nath Mondal1, Suvash Chandra Saha2,*

    Energy Engineering, Vol.119, No.1, pp. 429-451, 2022, DOI:10.32604/EE.2022.018145

    Abstract Due to widespread applications of the bent ducts in engineering fields such as in chemical, mechanical, bio-mechanical and bio-medical engineering, scientists have paid considerable attention to invent new characteristics of fluid flow in a bent duct (BD). In the ongoing study, a spectral-based numerical technique is applied to explore flow characteristics and energy distribution through a loosely bent square duct (BSD) of small curvature. Flow is accelerated due to combined action of the non-dimensional parameters; the Grashof number Gr (=1000), the curvature (=0.001), and the Prandtl number Pr (=7.0) over a wide domain of the Dean number . Fortran code… More >

  • Open Access

    ARTICLE

    Inferential Statistics and Machine Learning Models for Short-Term Wind Power Forecasting

    Ming Zhang, Hongbo Li, Xing Deng*

    Energy Engineering, Vol.119, No.1, pp. 237-252, 2022, DOI:10.32604/EE.2022.017916

    Abstract The inherent randomness, intermittence and volatility of wind power generation compromise the quality of the wind power system, resulting in uncertainty in the system's optimal scheduling. As a result, it's critical to improve power quality and assure real-time power grid scheduling and grid-connected wind farm operation. Inferred statistics are utilized in this research to infer general features based on the selected information, confirming that there are differences between two forecasting categories: Forecast Category 1 (0–11 h ahead) and Forecast Category 2 (12–23 h ahead). In z-tests, the null hypothesis provides the corresponding quantitative findings. To verify the final performance of… More >

  • Open Access

    ARTICLE

    Effects of Spark Energy on Spark Plug Fault Recognition in a Spark Ignition Engine

    A. A. Azrin1,*, I. M. Yusri1,2, M. H. Mat Yasin3, A. Zainal4

    Energy Engineering, Vol.119, No.1, pp. 189-199, 2022, DOI:10.32604/EE.2022.017843

    Abstract The increasing demands for fuel economy and emission reduction have led to the development of lean/diluted combustion strategies for modern Spark Ignition (SI) engines. The new generation of SI engines requires higher spark energy and a longer discharge duration to improve efficiency and reduce the backpressure. However, the increased spark energy gives negative impacts on the ignition system which results in deterioration of the spark plug. Therefore, a numerical model was used to estimate the spark energy of the ignition system based on the breakdown voltage. The trend of spark energy is then recognized by implementing the classification method. Significant… More >

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