Zewen Zhang¹, Sheng Zhou¹, Chunzheng Cao^1,2,*

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2465-2480, 2024, DOI:10.32604/cmc.2024.049605

Abstract The classification of functional data has drawn much attention in recent years. The main challenge is representing infinite-dimensional functional data by finite-dimensional features while utilizing those features to achieve better classification accuracy. In this paper, we propose a mean-variance-based (MV) feature weighting method for classifying functional data or functional curves. In the feature extraction stage, each sample curve is approximated by B-splines to transfer features to the coefficients of the spline basis. After that, a feature weighting approach based on statistical principles is introduced by comprehensively considering the between-class differences and within-class variations of the… More >

Di Wang, Yuefei Zhu, Jinlong Fei^*, Maohua Guo

CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2253-2276, 2024, DOI:10.32604/cmc.2024.049504

Abstract Website fingerprinting, also known as WF, is a traffic analysis attack that enables local eavesdroppers to infer a user’s browsing destination, even when using the Tor anonymity network. While advanced attacks based on deep neural network (DNN) can perform feature engineering and attain accuracy rates of over 98%, research has demonstrated that DNN is vulnerable to adversarial samples. As a result, many researchers have explored using adversarial samples as a defense mechanism against DNN-based WF attacks and have achieved considerable success. However, these methods suffer from high bandwidth overhead or require access to the target… More >

Kamolthip Ruckwongpatr^1,#, Chirawat Paratthakonkun^2,#, Usanut Sangtongdee^3,4,*, Iqbal Pramukti⁵, Ira Nurmala⁶, Kanokwan Angkasith⁷, Weena Thanachaisakul⁷, Jatuphum Ketchatturat⁸, Mark D. Griffiths⁹, Yi-Kai Kao^10,*, Chung-Ying Lin^1,5,11,12

International Journal of Mental Health Promotion, Vol.26, No.4, pp. 293-302, 2024, DOI:10.32604/ijmhp.2024.047023

Abstract Background: In recent years, there has been increased research interest in both smartphone addiction and social media addiction as well as the development of psychometric instruments to assess these constructs. However, there is a lack of psychometric evaluation for instruments assessing smartphone addiction and social media addiction in Thailand. The present study evaluated the psychometric properties and gender measurement invariance of the Thai version of the Smartphone Application-Based Addiction Scale (SABAS) and Bergen Social Media Addiction Scale (BSMAS). Method: A total of 801 Thai university students participated in an online survey from January 2022 to More >

Yanjing Cao¹, Chenchen Xu^1,2, Qi Li¹, Shan Lu^1,2,*, Jing Xiao^1,*

International Journal of Mental Health Promotion, Vol.26, No.4, pp. 261-269, 2024, DOI:10.32604/ijmhp.2024.043729

Abstract Background: Valid and reliable measures of depressive symptoms are crucial for understanding risk factors, outcomes, and interventions across rural and urban settings. Despite this need, the longitudinal invariance of these measures over time remains understudied. This research explores the structural components of the Center for Epidemiological Studies Depression Scale (CES-D) and examines its consistency across various living environments and temporal stability in a cohort of Chinese teenagers. Method: In the initial phase, 1,042 adolescents furnished demographic details and undertook the CES-D assessment. After a three-month interval, 967 of these participants repeated the CES-D evaluation. The… More >

Talal Albalawi, P. Ganeshkumar^*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3511-3528, 2024, DOI:10.32604/cmc.2024.046396

Abstract The Internet of Things (IoT) is a growing technology that allows the sharing of data with other devices across wireless networks. Specifically, IoT systems are vulnerable to cyberattacks due to its opennes The proposed work intends to implement a new security framework for detecting the most specific and harmful intrusions in IoT networks. In this framework, a Covariance Linear Learning Embedding Selection (CL2ES) methodology is used at first to extract the features highly associated with the IoT intrusions. Then, the Kernel Distributed Bayes Classifier (KDBC) is created to forecast attacks based on the probability distribution More >

Chengsheng Yuan^1,2, Baojie Cui^1,2, Zhili Zhou³, Xinting Li^4,*, Qingming Jonathan Wu⁵

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 899-914, 2024, DOI:10.32604/cmc.2023.045854

Abstract In recent years, deep learning has been the mainstream technology for fingerprint liveness detection (FLD) tasks because of its remarkable performance. However, recent studies have shown that these deep fake fingerprint detection (DFFD) models are not resistant to attacks by adversarial examples, which are generated by the introduction of subtle perturbations in the fingerprint image, allowing the model to make fake judgments. Most of the existing adversarial example generation methods are based on gradient optimization, which is easy to fall into local optimal, resulting in poor transferability of adversarial attacks. In addition, the perturbation added… More >

Yu-Ming Chu¹, Saima Rashid^2,*, Shazia Karim³, Anam Sultan²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1573-1611, 2023, DOI:10.32604/cmes.2023.027724

Abstract The fractional-order Boussinesq equations (FBSQe) are investigated in this work to see if they can effectively improve the situation where the shallow water equation cannot directly handle the dispersion wave. The fuzzy forms of analytical FBSQe solutions are first derived using the Adomian decomposition method. It also occurs on the sea floor as opposed to at the functionality. A set of dynamical partial differential equations (PDEs) in this article exemplify an unconfined aquifer flow implication. This methodology can accurately simulate climatological intrinsic waves, so the ripples are spread across a large demographic zone. The Aboodh… More >

Ashaduzzaman Sagar¹ , Md. Sabibul Haque¹, Md. Alamgir Hossain¹, Md. Nesar Uddin¹, Jannat E. Tajkia¹, Md. Ashik Mia¹, Toufika Hossain Shabi², Md. Solaiman Ali Fakir¹, Md. Abdul Kader^3,4,5, Walid Soufan⁶, Md. Atikur Rahman⁷, Muhammad Aamir Iqbal⁸, Mohammad Sohidul Islam⁹, Ayman El Sabagh^10,*, A. K. M. Zakir Hossain^1,*

Phyton-International Journal of Experimental Botany, Vol.92, No.8, pp. 2349-2368, 2023, DOI:10.32604/phyton.2023.028974

Abstract Salt stress is one of the major limitations to modern agriculture that negatively influences plant growth and productivity. Salt tolerant cultivar can provide excellent solution to enhance stress tolerance with plant fitness to unfavorable environments. Therefore, this study was aimed to screen salt tolerant sorghum genotypes through evaluating of different morphological, biochemical, and physiological attributes in response to salinity stress. In this study, we have been evaluated total six sorghum genotypes including Hybrid sorgo, Debgiri, BD-703, BD-706, BD-707, and BD-725 under salt stress (12 dS m⁻¹ NaCl). The response variables included length and weight of root… More >

Ming Cheng¹, Shiming Li^1,3,*, Yuhe Wang¹, Guohui Zhou¹, Peng Han¹, Yan Zhao²

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2527-2555, 2023, DOI:10.32604/cmc.2023.036427

Abstract To address the problem of network security situation assessment in the Industrial Internet, this paper adopts the evidential reasoning (ER)algorithm and belief rule base (BRB) method to establish an assessment model. First, this paper analyzes the influencing factors of the Industrial Internet and selects evaluation indicators that contain not only quantitative data but also qualitative knowledge. Second, the evaluation indicators are fused with expert knowledge and the ER algorithm. According to the fusion results, a network security situation assessment model of the Industrial Internet based on the ER and BRB method is established, and the… More >

Prasanalakshmi Balaji^1,*, B. Sri Revathi², Praveetha Gobinathan³, Shermin Shamsudheen³, Thavavel Vaiyapuri⁴

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2275-2291, 2022, DOI:10.32604/cmc.2022.028560

Abstract Recently medical image classification plays a vital role in medical image retrieval and computer-aided diagnosis system. Despite deep learning has proved to be superior to previous approaches that depend on handcrafted features; it remains difficult to implement because of the high intra-class variance and inter-class similarity generated by the wide range of imaging modalities and clinical diseases. The Internet of Things (IoT) in healthcare systems is quickly becoming a viable alternative for delivering high-quality medical treatment in today’s e-healthcare systems. In recent years, the Internet of Things (IoT) has been identified as one of the… More >