Zhao-Jun Zhang¹, Wen-Wei Wang^1,2,*, Jing-Shui Zhen¹, Bo-Cheng Li¹, De-Cheng Cai¹, Yang-Yang Du¹, Hui Huang²

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 105-123, 2025, DOI:10.32604/sdhm.2024.052506 - 15 November 2024

Abstract This study aimed to investigate the moment redistribution in continuous glass fiber reinforced polymer (GFRP)-concrete composite slabs caused by concrete cracking and steel bar yielding in the negative bending moment zone. An experimental bending moment redistribution test was conducted on continuous GFRP-concrete composite slabs, and a calculation method based on the conjugate beam method was proposed. The composite slabs were formed by combining GFRP profiles with a concrete layer and supported on steel beams to create two-span continuous composite slab specimens. Two methods, epoxy resin bonding, and stud connection, were used to connect the composite… More >

Qi Zhang^1,2,4,5, Zhixin Chen³, Yang Wu^4,*, Guoqi Xiang², Guang Wen¹, Xuegang Zhang², Yongchun Xie², Guangchun Yang²

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 593-619, 2024, DOI:10.32604/cmes.2023.046319 - 16 April 2024

Abstract Although there is currently no unified standard theoretical formula for calculating the contact stress of cylindrical gears with a circular arc tooth trace (referred to as CATT gear), a mathematical model for determining the contact stress of CATT gear is essential for studying how parameters affect its contact stress and building the contact stress limit state equation for contact stress reliability analysis. In this study, a mathematical relationship between design parameters and contact stress is formulated using the Kriging Metamodel. To enhance the model’s accuracy, we propose a new hybrid algorithm that merges the genetic… More >

Lindah Sawe^*, Joyce Gikandi, John Kamau, David Njuguna

Journal of Cyber Security, Vol.6, pp. 25-39, 2024, DOI:10.32604/jcs.2023.045859 - 11 January 2024

Abstract Phishing emails have experienced a rapid surge in cyber threats globally, especially following the emergence of the COVID-19 pandemic. This form of attack has led to substantial financial losses for numerous organizations. Although various models have been constructed to differentiate legitimate emails from phishing attempts, attackers continuously employ novel strategies to manipulate their targets into falling victim to their schemes. This form of attack has led to substantial financial losses for numerous organizations. While efforts are ongoing to create phishing detection models, their current level of accuracy and speed in identifying phishing emails is less… More >

YANG GU^1,#,*, MINGGUANG BI^2,#, DEHUI CHEN³, NING NI⁴, JIANMING CHEN^1,*

BIOCELL, Vol.47, No.9, pp. 2069-2080, 2023, DOI:10.32604/biocell.2023.029989 - 28 September 2023

Abstract Background: The underlying mechanism of sciatic nerve injury (SNI) is a common motor functional disorder, necessitates further research. Methods: A rat model of SNI was established, with the injury group subjected to compressive injury of the right sciatic nerve exposed at the midpoint of the thigh and the sham surgery group undergoing the same surgical procedure. An oxygen-glucose deprivation model was employed to simulate in vitro SNI in PC12 cells. Following data acquisition and quality control, differentially expressed proteins (DEPs) in each model were identified through differential analysis, and enrichment analysis was used to explore the… More >

Wenxin Chen^1,#, Jie Wu^1,2,#, Long Li^3,*, Shiyong Wu^4,*

International Journal of Mental Health Promotion, Vol.25, No.8, pp. 949-959, 2023, DOI:10.32604/ijmhp.2023.030072 - 06 July 2023

Abstract Background: University students’ ego-identity, an essential component of their psychological development and mental health, has widely attracted the attention of policymakers, schools, and parents. Method: A total of 298 Chinese vocational pathway undergraduates were recruited, and a conditional process analysis model was adopted to explore the interaction mechanism of ego-identity. Results: The results suggest that the ego-identity of Chinese vocational pathway undergraduates is significantly affected by interaction anxiousness, academic resilience, and cultural intelligence. (1) Interaction anxiousness significantly and positively predicts ego-identity. (2) Academic resilience positively and partially mediates the effect of interaction anxiousness on ego-identity. (3) Cultural intelligence… More >

Meilin Wu^1,2, Lianggui Tang^1,2,*, Qingda Zhang^1,2, Ke Yan^1,2

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 179-198, 2023, DOI:10.32604/iasc.2023.036684 - 29 April 2023

Abstract As COVID-19 poses a major threat to people’s health and economy, there is an urgent need for forecasting methodologies that can anticipate its trajectory efficiently. In non-stationary time series forecasting jobs, there is frequently a hysteresis in the anticipated values relative to the real values. The multilayer deep-time convolutional network and a feature fusion network are combined in this paper’s proposal of an enhanced Multilayer Deep Time Convolutional Neural Network (MDTCNet) for COVID-19 prediction to address this problem. In particular, it is possible to record the deep features and temporal dependencies in uncertain time series, More >

Mingyong Li¹, Lirong Tang¹, Longfei Ma¹, Honggang Zhao¹, Jinyu Hu¹, Yan Wei^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2349-2371, 2023, DOI:10.32604/cmes.2023.022604 - 23 November 2022

Abstract The learning status of learners directly affects the quality of learning. Compared with offline teachers, it is difficult for online teachers to capture the learning status of students in the whole class, and it is even more difficult to continue to pay attention to students while teaching. Therefore, this paper proposes an online learning state analysis model based on a convolutional neural network and multi-dimensional information fusion. Specifically, a facial expression recognition model and an eye state recognition model are constructed to detect students’ emotions and fatigue, respectively. By integrating the detected data with the More >

Anwer Mustafa Hilal^1,*, Eatedal Alabdulkreem², Jaber S. Alzahrani³, Majdy M. Eltahir⁴, Mohamed I. Eldesouki⁵, Ishfaq Yaseen¹, Abdelwahed Motwakel¹, Radwa Marzouk⁶

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1129-1143, 2023, DOI:10.32604/csse.2023.030080 - 03 November 2022

Abstract Biomedical image processing is widely utilized for disease detection and classification of biomedical images. Tongue color image analysis is an effective and non-invasive tool for carrying out secondary detection at anytime and anywhere. For removing the qualitative aspect, tongue images are quantitatively inspected, proposing a novel disease classification model in an automated way is preferable. This article introduces a novel political optimizer with deep learning enabled tongue color image analysis (PODL-TCIA) technique. The presented PODL-TCIA model purposes to detect the occurrence of the disease by examining the color of the tongue. To attain this, the More >

Ashit Kumar Dutta¹, S. Srinivasan², S. N. Kumar³, T. S. Balaji^4,5, Won Il Lee⁶, Gyanendra Prasad Joshi⁷, Sung Won Kim^8,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5563-5576, 2022, DOI:10.32604/cmc.2022.027707 - 21 April 2022

Abstract Due to the advances of intelligent transportation system (ITSs), traffic forecasting has gained significant interest as robust traffic prediction acts as an important part in different ITSs namely traffic signal control, navigation, route mapping, etc. The traffic prediction model aims to predict the traffic conditions based on the past traffic data. For more accurate traffic prediction, this study proposes an optimal deep learning-enabled statistical analysis model. This study offers the design of optimal convolutional neural network with attention long short term memory (OCNN-ALSTM) model for traffic prediction. The proposed OCNN-ALSTM technique primarily pre-processes the traffic… More >

Yanhua Lu¹, Xuehui Gong^2,*, Andrew Byron Kipnis³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5481-5497, 2022, DOI:10.32604/cmc.2022.027089 - 21 April 2022

Abstract Combined with the energy consumption data of individual buildings in the logistics group of Yangtze University, the analysis model scheme of energy consumption of individual buildings in the university is studied by using Back Propagation (BP) neural network to solve nonlinear problems and have the ability of global approximation and generalization. By analyzing the influence of different uses, different building surfaces and different energy-saving schemes on the change of building energy consumption, the grey correlation method is used to determine the main influencing factors affecting each building energy consumption, including uses, building surfaces and energy-saving… More >