Fulin Li¹, Chuanyi Wang^1,*, Xiaoguang Yue²

International Journal of Mental Health Promotion, Vol.24, No.2, pp. 169-187, 2022, DOI:10.32604/ijmhp.2022.020034

Abstract Background: Doctoral students have much higher risk of anxiety or depression than general population. Doctoral students worldwide are facing varying degrees of mental health risks. Method: Based on the survey data of 6,812 doctoral students worldwide in Nature in 2019, Probit and Logit models are used to explore the correlation between the fit of doctoral education and training process and the mental health of doctoral students. Results: (1) The training environment fit of doctoral students has a significant positive impact on their mental health. (2) The academic profession fit of doctoral students has a significant positive impact on their mental… More >

Zhiyuan Sun^1,2, Fabian Herold^3,4, Kelong Cai^1,2, Qian Yu⁵, Xiaoxiao Dong^1,2, Zhimei Liu^1,2, Jinming Li⁶, Aiguo Chen^1,2,* , Liye Zou^7,*

International Journal of Mental Health Promotion, Vol.24, No.2, pp. 143-158, 2022, DOI:10.32604/ijmhp.2022.020075

Abstract In recent years evidence has emerged suggesting that Mini-basketball training program (MBTP) can be an effective intervention method to improve social communication (SC) impairments and restricted and repetitive behaviors (RRBs) in preschool children suffering from autism spectrum disorder (ASD). However, there is a considerable degree if interindividual variability concerning these social outcomes and thus not all preschool children with ASD profit from a MBTP intervention to the same extent. In order to make more accurate predictions which preschool children with ASD can benefit from an MBTP intervention or which preschool children with ASD need additional interventions to achieve behavioral improvements,… More >

Sukanta Ghosh¹, Amar Singh¹, Kavita^2,*, N. Z. Jhanjhi³, Mehedi Masud⁴, Sultan Aljahdali⁴

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4257-4274, 2022, DOI:10.32604/cmc.2022.023414

Abstract Automatic plant classification through plant leaf is a classical problem in Computer Vision. Plants classification is challenging due to the introduction of new species with a similar pattern and look-a-like. Many efforts are made to automate plant classification using plant leaf, plant flower, bark, or stem. After much effort, it has been proven that leaf is the most reliable source for plant classification. But it is challenging to identify a plant with the help of leaf structure because plant leaf shows similarity in morphological variations, like sizes, textures, shapes, and venation. Therefore, it is required to normalize all plant leaves… More >

Abdossaleh Zar¹, Fatemeh Ahmadi¹, Forouzan Karimi^2,*, Mozhgan Ahmadi³, Roger Ramsbottom⁴

Molecular & Cellular Biomechanics, Vol.19, No.1, pp. 51-59, 2022, DOI:10.32604/mcb.2022.018345

Abstract The effect of resistance training and a herbal supplement on muscular signaling pathways are limited. We investigated the expression of IL-6, Gp130, JAK and STAT after resistance training, and Spirulina platensis supplementation in animal muscle. Thirty-two male Sprague Dawley rats (weight: 290 ± 20 g, and 9 weeks of age) were divided into four groups: control (CO; n = 8), Spirulina platensis supplementation (SP; n = 8), resistance exercise (RE; n = 8), and Spirulina platensis + resistance exercise (SP + RE; n = 8). The resistance exercise group trained five sessions each week for eight weeks. Spirulina 200 mg… More >

S. Lakshmi Durga¹, Ch. Rajeshwari¹, Khalid Hamed Allehaibi², Nishu Gupta^3,*, Nasser Nammas Albaqami⁴, Isha Bharti⁵, Ahmad Hoirul Basori⁶

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 1-19, 2022, DOI:10.32604/iasc.2022.022536

Abstract In recent years, the demand for smart wireless communication technology has increased tremendously, and it urges to extend internet services globally with high reliability, less cost and minimal delay. In this connection, low earth orbit (LEO) satellites have played prominent role by reducing the terrestrial infrastructure facilities and providing global coverage all over the earth with the help of satellite internet of things (SIoT). LEO satellites provide wide coverage area to dynamically accessing network with limited resources. Presently, most resource allocation schemes are designed only for geostationary earth orbit (GEO) satellites. For LEO satellites, resource allocation is challenging due to… More >

R. Kanthavel^1,*, R. Dhaya²

Computer Systems Science and Engineering, Vol.42, No.1, pp. 257-269, 2022, DOI:10.32604/csse.2022.021606

Abstract Osteoarthritis is the most common class of arthritis that involves tears down the soft cartilage between the joints of the knee. The regeneration of this cartilage tissue is not possible, and thus physicians typically suggest therapeutic measures to prevent further deterioration over time. Normally, bringing about joint replacement is a remedial course of action. Expose itself in joint pain recognized with a normal X-ray. Deep learning plays a vital role in predicting the early stages of osteoarthritis by using the MRI pictures of muscles of the knee muscle. It can be used to accurately measure the shape and texture of… More >

Wei Jiang^1,*, Gang He²

Molecular & Cellular Biomechanics, Vol.18, No.4, pp. 221-229, 2021, DOI:10.32604/mcb.2021.017050

Abstract Tennis service is an important part of winning a match. This study analyzed the mechanics of tennis serving speed and divided ten tennis players into two groups. One group carried out conventional training, while the other group carried out auxiliary training on shoulders through elastic band besides conventional training. The actions were photographed by cameras and analyzed. The results showed that the throwing height and hitting point height of the two groups improved after the experiment, and p < 0.05 in the comparison between Groups A and B; the ball deflection angle reduced after throwing, but the improvement of Group B was… More >

Zilong Jin^1,2, Chengbo Zhang¹ , Kan Yao³ , Dun Cao⁴ , Seokhoon Kim⁵, Yuanfeng Jin^6,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5991-6005, 2022, DOI:10.32604/cmc.2022.021498

Abstract

Cognitive radio devices can utilize the licensed channels in an opportunistic manner to solve the spectrum scarcity issue occurring in the unlicensed spectrum. However, these cognitive radio devices (secondary users) are greatly affected by the original users (primary users) of licensed channels. Cognitive users have to adjust operation parameters frequently to adapt to the dynamic network environment, which causes extra energy consumption. Energy consumption can be reduced by predicting the future activity of primary users. However, the traditional prediction-based algorithms require large historical data to achieve a satisfying precision accuracy which will consume a lot of time and memory space.… More >

Shubha Sumesh¹, John Yearwood¹, Shamsul Huda¹ and Shafiq Ahmad^2,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4503-4521, 2022, DOI:10.32604/cmc.2022.015474

Abstract

Clinical Study and automatic diagnosis of electrocardiogram (ECG) data always remain a challenge in diagnosing cardiovascular activities. The analysis of ECG data relies on various factors like morphological features, classification techniques, methods or models used to diagnose and its performance improvement. Another crucial factor in the methodology is how to train the model for each patient. Existing approaches use standard training model which faces challenges when training data has variation due to individual patient characteristics resulting in a lower detection accuracy. This paper proposes an adaptive approach to identify performance improvement in building a training model that analyze global training… More >

Nebojsa Bacanin¹, Khaled Alhazmi^2,*, Miodrag Zivkovic¹, K. Venkatachalam³, Timea Bezdan¹, Jamel Nebhen⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4199-4215, 2022, DOI:10.32604/cmc.2022.020449

Abstract In the domain of artificial neural networks, the learning process represents one of the most challenging tasks. Since the classification accuracy highly depends on the weights and biases, it is crucial to find its optimal or suboptimal values for the problem at hand. However, to a very large search space, it is very difficult to find the proper values of connection weights and biases. Employing traditional optimization algorithms for this issue leads to slow convergence and it is prone to get stuck in the local optima. Most commonly, back-propagation is used for multi-layer-perceptron training and it can lead to vanishing… More >