Qiang Li^1,2,*, Pan Chen¹, Lihong Gao¹, Dan Meng¹, Jinjie Zou¹

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 465-481, 2023, DOI:10.32604/cmes.2022.020300

Abstract Monopiles are the most common foundation form of offshore wind turbines, which bear the vertical load, lateral load and bending moment. It remains uncertain whether the applied vertical load increases the lateral deflection of the pile. This paper investigated the influence of vertical load on the behaviour of monopiles installed in the sand under combined load using three-dimensional numerical methods. The commercial software PLAXIS was used for simulations in this paper. Monopiles were modelled as a structure incorporating linear elastic material behaviour and soil was modelled using the Hardening-Soil (HS) constitutive model. The monopiles under vertical load, lateral load and… More >

Farah Mohammad^*, Saad Al-Ahmadi

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 623-639, 2023, DOI:10.32604/cmc.2023.032552

Abstract

There exists various neurological disorder based diseases like tumor, sleep disorder, headache, dementia and Epilepsy. Among these, epilepsy is the most common neurological illness in humans, comparable to stroke. Epilepsy is a severe chronic neurological illness that can be discovered through analysis of the signals generated by brain neurons and brain Magnetic resonance imaging (MRI). Neurons are intricately coupled in order to communicate and generate signals from human organs. Due to the complex nature of electroencephalogram (EEG) signals and MRI’s the epileptic seizures detection and brain related problems diagnosis becomes a challenging task. Computer based techniques and machine learning models… More >

Fayez AlFayez^*

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2165-2176, 2023, DOI:10.32604/csse.2023.026238

Abstract The paper addresses the challenge of transmitting a big number of files stored in a data center (DC), encrypting them by compilers, and sending them through a network at an acceptable time. Face to the big number of files, only one compiler may not be sufficient to encrypt data in an acceptable time. In this paper, we consider the problem of several compilers and the objective is to find an algorithm that can give an efficient schedule for the given files to be compiled by the compilers. The main objective of the work is to minimize the gap in the… More >

Jian Qiang Wang¹, Wei Fang^1,2,*, Victor S. Sheng³

Journal of New Media, Vol.4, No.2, pp. 73-84, 2022, DOI:10.32604/jnm.2022.027040

Abstract Brain-Computer Interface (BCI) technology is a way for humans to explore the mysteries of the brain and has applications in many areas of real life. People use this technology to capture brain waves and analyze the electroencephalograph (EEG) signal for feature extraction. Take the medical field as an example, epilepsy disease is threatening human health every moment. We propose a convolutional neural network SECNN-LSTM framework based on the attention mechanism can automatically perform feature extraction and analysis on the collected EEG signals of patients to complete the prediction of epilepsy diseases, overcoming the problem that the disease requires long time… More >

Jian Liu¹, Yipeng Du¹, Xiang Wang^1,*, Wuguang Yue², Jim Feng³

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1995-2011, 2022, DOI:10.32604/cmc.2022.029073

Abstract Epilepsy is a common neurological disease and severely affects the daily life of patients. The automatic detection and diagnosis system of epilepsy based on electroencephalogram (EEG) is of great significance to help patients with epilepsy return to normal life. With the development of deep learning technology and the increase in the amount of EEG data, the performance of deep learning based automatic detection algorithm for epilepsy EEG has gradually surpassed the traditional hand-crafted approaches. However, the neural architecture design for epilepsy EEG analysis is time-consuming and laborious, and the designed structure is difficult to adapt to the changing EEG collection… More >

Manar Ahmed Hamza^1,*, Noha Negm², Shaha Al-Otaibi³, Amel A. Alhussan⁴, Mesfer Al Duhayyim⁵, Fuad Ali Mohammed Al-Yarimi², Mohammed Rizwanullah¹, Ishfaq Yaseen¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4541-4555, 2022, DOI:10.32604/cmc.2022.027048

Abstract Machine learning (ML) becomes a familiar topic among decision makers in several domains, particularly healthcare. Effective design of ML models assists to detect and classify the occurrence of diseases using healthcare data. Besides, the parameter tuning of the ML models is also essential to accomplish effective classification results. This article develops a novel red colobuses monkey optimization with kernel extreme learning machine (RCMO-KELM) technique for epileptic seizure detection and classification. The proposed RCMO-KELM technique initially extracts the chaotic, time, and frequency domain features in the actual EEG signals. In addition, the min-max normalization approach is employed for the pre-processing of… More >

Yong Chen¹, Chao Xu^1,*, Jing Selena He², Sheng Xiao³, Fanfan Shen¹

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5251-5272, 2022, DOI:10.32604/cmc.2022.026750

Abstract With the continuous expansion of software applications, people's requirements for software quality are increasing. Software defect prediction is an important technology to improve software quality. It often encodes the software into several features and applies the machine learning method to build defect prediction classifiers, which can estimate the software areas is clean or buggy. However, the current encoding methods are mainly based on the traditional manual features or the AST of source code. Traditional manual features are difficult to reflect the deep semantics of programs, and there is a lot of noise information in AST, which affects the expression of… More >

Zhiqiu Yu^*, Shuo-Yan Chou

Computer Systems Science and Engineering, Vol.42, No.3, pp. 963-984, 2022, DOI:10.32604/csse.2022.023129

Abstract With the widespread of new energy vehicles, charging piles have also been continuously installed and constructed. In order to make the number of piles meet the needs of the development of new energy vehicles, this study aims to apply the method of system dynamics and combined with the grey prediction theory to determine the parameters as well as to simulate and analyze the ratio of vehicles to chargers. Through scenario analysis, it is predicted that by 2030, this ratio will gradually decrease from 1.79 to 1. In order to achieve this ratio as 1:1, it is necessary to speed up… More >

S. Beatrice^*, Janaki Meena

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 331-347, 2022, DOI:10.32604/iasc.2022.023666

Abstract Discovering the information about several disorders prevailing in brain and neurology is by no means a new scientific technique. A neurological disorder of any human being can be analyzed using EEG (Electroencephalography) signal from the electrode’s output. Epilepsy (spontaneous recurrent seizure) detection is usually carried out by the physicians using a visual scanning of the signals produced by EEG, which is onerous and may be inaccurate. EEG signal is often used to determine epilepsy, for its merits, such as non-invasive, portable, and economical, can exhibit superior temporal tenacity. This paper surveys the existing artifact removal methods. It puts a new-fangled… More >

Yousheng Deng, Chengpu Peng^*, Jialin Su, Lingtao Li, Liqing Meng, Long Li

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 1135-1148, 2022, DOI:10.32604/cmes.2022.018349

Abstract Moso bamboo has the advantages of high short-term strength and reproducibility, appropriating for temporary supporting structure of shallow foundation pit. According to the displacement of the pile top from an indoor model test, the reliability of the supporting effect of the moso bamboo pile was analyzed. First, the calculation formula of reliability index was deduced based on the mean-value first-order second-moment (MVFOSM)method and probability theory under ultimate limit state and serviceability limit state. Then, the dimensionless bias factor (the ratio of the measured value to the calculated value) was introduced to normalize the displacement. The mathematical characteristics of the displacement… More >