Loc Vu-Quoc¹ and Shaofan Li²

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.3, pp. 1075-1075, 2021, DOI:10.32604/cmes.2021.018780

Abstract This article has no abstract. More >

Xudong Wang^1,2, Changqing Miao^1,2,*, Mao Yang^1,2, Youliang Ding^1,2

Structural Durability & Health Monitoring, Vol.15, No.4, pp. 299-316, 2021, DOI:10.32604/sdhm.2021.017526

Abstract This study presents an investigation on the fatigue analysis of four types of details on orthotropic steel decks (OSDs) for a cable-stayed super-wide steel box girder bridge based on finite-element analysis (FEA) with vehicle transverse distribution model (VTDM). A high-fidelity 3D FE model verified by the static load test is established to satisfy the fatigue analysis accuracy. The stress behavior of super-wide steel box girders under the vehicle load at different lane locations is investigated. Then, considering the effect of VTDM, the fatigue life analysis of four typical details is performed using the Miner cumulative damage rule. The results show… More >

S. Kalyani^*, K. Venkata Rao, A. Mary Sowjanya

Structural Durability & Health Monitoring, Vol.15, No.4, pp. 317-334, 2021, DOI:10.32604/sdhm.2021.016975

Abstract Internet of Things systems generate a large amount of sensor data that needs to be analyzed for extracting useful insights on the health status of the machine under consideration. Sensor data of all possible states of a system are used for building machine learning models. These models are further used to predict the possible downtime for proactive action on the system condition. Aircraft engine data from run to failure is used in the current study. The run to failure data includes states like new installation, stable operation, first reported issue, erroneous operation, and final failure. In the present work, the… More >

Belal Almassri^1,*, 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 >

Li Hui^1,*, 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 >

Mohammad Akhtar¹, Abdulsamee Halahla², Amin Almasri^3,*

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 >

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 >

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 >

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 >

Wei Fang^1,2,*, 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 >