Mohamed Abouhawwash^1,2, S. Sridevi³, Suma Christal Mary Sundararajan⁴, Rohit Pachlor⁵, Faten Khalid Karim⁶, Doaa Sami Khafaga^6,*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 239-253, 2023, DOI:10.32604/csse.2023.037812

Abstract One of the significant health issues affecting women that impacts their fertility and results in serious health concerns is Polycystic ovarian syndrome (PCOS). Consequently, timely screening of polycystic ovarian syndrome can help in the process of recovery. Finding a method to aid doctors in this procedure was crucial due to the difficulties in detecting this condition. This research aimed to determine whether it is possible to optimize the detection of PCOS utilizing Deep Learning algorithms and methodologies. Additionally, feature selection methods that produce the most important subset of features can speed up calculation and enhance the effectiveness of classifiers. In… More >

Mahima Dahiya^*, Nitin Nitin

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4183-4201, 2023, DOI:10.32604/cmc.2023.032430

Abstract Intrusion detection is critical to guaranteeing the safety of the data in the network. Even though, since Internet commerce has grown at a breakneck pace, network traffic kinds are rising daily, and network behavior characteristics are becoming increasingly complicated, posing significant hurdles to intrusion detection. The challenges in terms of false positives, false negatives, low detection accuracy, high running time, adversarial attacks, uncertain attacks, etc. lead to insecure Intrusion Detection System (IDS). To offset the existing challenge, the work has developed a secure Data Mining Intrusion detection system (DataMIDS) framework using Functional Perturbation (FP) feature selection and Bengio Nesterov Momentum-based… More >

V. Joseph Raymond^1,2,*, R. Jeberson Retna Raj¹

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2413-2429, 2023, DOI:10.32604/iasc.2023.030527

Abstract In recent days the usage of android smartphones has increased extensively by end-users. There are several applications in different categories banking/finance, social engineering, education, sports and fitness, and many more applications. The android stack is more vulnerable compared to other mobile platforms like IOS, Windows, or Blackberry because of the open-source platform. In the Existing system, malware is written using vulnerable system calls to bypass signature detection important drawback is might not work with zero-day exploits and stealth malware. The attackers target the victim with various attacks like adware, backdoor, spyware, ransomware, and zero-day exploits and create threat hunts on… More >

Qidai Lin¹, Ying Gong^2,*, Yizhi Shi¹, Changsen Feng², Youbing Zhang²

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.3, pp. 929-944, 2022, DOI:10.32604/cmes.2022.020752

Abstract The integrated energy systems, usually including electric energy, natural gas and thermal energy, play a pivotal role in the energy Internet project, which could improve the accommodation of renewable energy through multi-energy complementary ways. Focusing on the regional integrated energy system composed of electrical microgrid and natural gas network, a fault risk warning method based on the improved RelieF-softmax method is proposed in this paper. The raw data-set was first clustered by the K-maxmin method to improve the preference of the random sampling process in the RelieF algorithm, and thereby achieved a hierarchical and non-repeated sampling. Then, the improved RelieF… More >

Xiaohua Chen^1,*, Caifu Lan¹, Honghao Zheng², Wang Li¹, Chao Zhao¹, Wenjun Dang³

Energy Engineering, Vol.119, No.4, pp. 1439-1452, 2022, DOI:10.32604/ee.2022.018208

Abstract For oil pipeline in mountain areas, high hydrostatic pressure in the pipeline may cause error-opening of pressure relief valves, and oil is discharged from the pipeline to the pressure relief tanks, bringing spilling-over risk of the pressure relief tanks. Therefore, simulating the error-opening situations of the pressure relief valves and investigating the oil discharge process are necessary for checking the possibility of the spilling-over accident and then proposing measures to improve the pressure relief system. This research focuses on a continuous undulating oil pipeline with large elevation difference and a station along this pipeline, which is named B station in… More >

Alaa Khalid Alduraibi^*

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1295-1309, 2022, DOI:10.32604/iasc.2022.026601

Abstract With technological advancements, deep machine learning can assist doctors in identifying the brain mass or tumor using magnetic resonance imaging (MRI). This work extracts the deep features from 18-pre-trained convolutional neural networks (CNNs) to train the classical classifiers to categorize the brain MRI images. As a result, DenseNet-201, EfficientNet-b0, and DarkNet-53 deep features trained support vector machine (SVM) model shows the best accuracy. Furthermore, the ReliefF method is applied to extract the best features. Then, the fitness function is defined to select the number of nearest neighbors of ReliefF algorithm and feature vector size. Finally, the particle swarm optimization algorithm… More >

Xiaoxia Zhu^1,2,*, Xu Guo², Yishu Teng^1,*, John Gershenson³

International Journal of Mental Health Promotion, Vol.23, No.2, pp. 289-302, 2021, DOI:10.32604/IJMHP.2021.013691

Abstract When the global outbreak of new coronary pneumonia broke out in 2020, online public opinion events triggered by cultural differences among overseas students had come into the public view. To further explore the relationship between the cultural alienation of overseas students and their own happiness, this study takes visualization and analysis of positive, negative sentiment analysis of Weibo netizens’ comment data in the “Xu Kexin Incident” as the starting point, on the basis of introducing cultural alienation, stress relief methods, and cultural intelligence, combining gender and social ability, social relations and other individual attributes, designed a questionnaire to investigate 502… More >

Chunlei Zhang^1,2,3,*, Y. P. Chugh², Ruimin Feng⁴, Yong Zhang⁵, Wei Shen¹, Jingke Wu¹, Yushun Yang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.127, No.1, pp. 135-157, 2021, DOI:10.32604/cmes.2021.014665

Abstract Extraction of a protective coal seam (PVCS)-below or above a coal seam to be mined with the potential of coal and gas outburst risk-plays an important role not only in decreasing the stress field in the surrounding rock mass but also in increasing the gas desorption capacity and gas flow permeability in the protected coal seam (PTCS). The PVCS is mined to guarantee the safe mining of the PTCS. This study has numerically evaluated the stress redistribution effects using FLAC3D model for a longwall face in Shanxi Province. The effects of mining depth, mining height and inter-burden rock mass properties… More >

Caixia Wang², Xiao Huang^1,*, Hongqing Chen², Weijie Liang²

Journal of Renewable Materials, Vol.9, No.7, pp. 1239-1252, 2021, DOI:10.32604/jrm.2021.014746

Abstract Currently, people pay more and more attention to the transitional resettlement of victims after various natural disasters. There is an urgent need for a large number of temporary houses to resettle the victims after natural disasters. Disaster-relief temporary houses (DTHs) played an important role in the post-disaster resettlement in the past, which can not only be produced on a large scale, but also can be quickly and conveniently erected, which were the main means to solve the problem of transitional resettlement. However, due to their temporary nature, there was no extra energy consuming system installed in the DTHs generally. Hence… More >

Jiahui Pan^1,6,*, Jianhao Zhang¹, Fei Wang^1,6, Wuhan Liu², Haiyun Huang^3,6, Weishun Tang³, Huijian Liao⁴, Man Li⁵, Jianhui Wu¹, Xueli Li², Dongming Quan², Yuanqing Li^3,6

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 53-71, 2021, DOI:10.32604/iasc.2021.015970

Abstract In this paper, an automatic sleep scoring system based on electroencephalogram (EEG) and electrooculogram (EOG) signals was proposed for sleep stage classification and depression detection. Our automatic sleep stage classification method contained preprocessing based on independent component analysis, feature extraction including spectral features, spectral edge frequency features, absolute spectral power, statistical features, Hjorth features, maximum-minimum distance and energy features, and a modified ReliefF feature selection. Finally, a support vector machine was employed to classify four states (awake, light sleep [LS], slow-wave sleep [SWS] and rapid eye movement [REM]). The overall accuracy of the Sleep-EDF database reached 90.10 ± 2.68% with… More >