Emad Ul Haq Qazi^1,*, Tanveer Zia¹, Muhammad Imran², Muhammad Hamza Faheem¹

Intelligent Automation & Soft Computing, Vol.38, No.3, pp. 225-240, 2023, DOI:10.32604/iasc.2023.041181

Abstract Deep learning is considered one of the most efficient and reliable methods through which the legitimacy of a digital image can be verified. In the current cyber world where deepfakes have shaken the global community, confirming the legitimacy of a digital image is of great importance. With the advancements made in deep learning techniques, now we can efficiently train and develop state-of-the-art digital image forensic models. The most traditional and widely used method by researchers is convolution neural networks (CNN) for verification of image authenticity but it consumes a considerable number of resources and requires a large dataset for training.… More >

Mehdi Hassan¹, Shuanghu Fang^1,*, Muhammad Rizwan², Asma Seemi Malik³, Iqra Mushtaque⁴

International Journal of Mental Health Promotion, Vol.26, No.1, pp. 1-9, 2024, DOI:10.32604/ijmhp.2023.043096

Abstract This study examined the effects of financial stress, parental expectation and test anxiety on suicidal ideation in pre-medical students. For this purpose, a cross-sectional research design was used, and data were collected through a non-probability sampling technique. The sample consisted of 425 pre-medical students. Our results indicate a strong and positive association between parental expectation and suicidal ideation (β = 0.272; t = 3.573; p < 0.000). Likewise, entrance test exam anxiety has a positive association with suicidal ideation among pre-medical students (β = 0.394; t = 3.933; p < 0.000). Lastly, there is a significant and positive association between… More >

Cheng Peng¹, Siwei Cheng², Min Sun¹, Chao Ren¹, Jun Song¹, Haibo Huang^2,*

Sound & Vibration, Vol.58, pp. 25-46, 2024, DOI:10.32604/sv.2024.046940

Abstract The Noise, Vibration, and Harshness (NVH) experience during driving is significantly influenced by the sound insulation performance of the car floor acoustic package. As such, accurate and efficient predictions of its sound insulation performance are crucial for optimizing related noise reduction designs. However, the complex acoustic transmission mechanisms and difficulties in characterizing the sound absorption and insulation properties of the floor acoustic package pose significant challenges to traditional Computer-Aided Engineering (CAE) methods, leading to low modeling efficiency and prediction accuracy. To address these limitations, a hierarchical multi-objective decomposition system for predicting the sound insulation performance of the floor acoustic package… More >

YANG LI^1,2, JIAN LIU^1,3,*, YUEDI HU^1,2, CHENGZHI CONG^1,2, YIMING CHEN^1,2, QIAO ZHOU^1,2

BIOCELL, Vol.48, No.1, pp. 9-19, 2024, DOI:10.32604/biocell.2023.045862

Abstract Rheumatoid arthritis (RA) is a prevalent autoimmune disease whose main features include chronic synovial inflammation, bone destruction, and joint degeneration. Neutrophils are often considered to be the first responders to inflammation and are a key presence in the inflammatory milieu of RA. Neutrophil extracellular traps (NETs), a meshwork of DNA-histone complexes and proteins released by activated neutrophils, are widely involved in the pathophysiology of autoimmune diseases, especially RA, in addition to playing a key role in the neutrophil innate immune response. NETs have been found to be an important source of citrullinated autoantigen antibodies and inflammatory factor release, which can… More > Graphic Abstract

Liang Zeng^1,2, Junyang Shi¹, Yanyan Li¹, Shanshan Wang^1,2,*, Weigang Li³

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 375-392, 2024, DOI:10.32604/cmc.2023.045803

Abstract The job shop scheduling problem is a classical combinatorial optimization challenge frequently encountered in manufacturing systems. It involves determining the optimal execution sequences for a set of jobs on various machines to maximize production efficiency and meet multiple objectives. The Non-dominated Sorting Genetic Algorithm III (NSGA-III) is an effective approach for solving the multi-objective job shop scheduling problem. Nevertheless, it has some limitations in solving scheduling problems, including inadequate global search capability, susceptibility to premature convergence, and challenges in balancing convergence and diversity. To enhance its performance, this paper introduces a strengthened dominance relation NSGA-III algorithm based on differential evolution… More >

Junpeng Wu^1,2,*, Zhenpeng Liu², Xingfan Jiang², Xinguang Tao², Ye Zhang³

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 677-694, 2024, DOI:10.32604/cmc.2023.045759

Abstract The current existing problem of deep learning framework for the detection and segmentation of electrical equipment is dominantly related to low precision. Because of the reliable, safe and easy-to-operate technology provided by deep learning-based video surveillance for unmanned inspection of electrical equipment, this paper uses the bottleneck attention module (BAM) attention mechanism to improve the Solov2 model and proposes a new electrical equipment segmentation mode. Firstly, the BAM attention mechanism is integrated into the feature extraction network to adaptively learn the correlation between feature channels, thereby improving the expression ability of the feature map; secondly, the weighted sum of CrossEntropy… More >

Sijia Zhu^1,*, Pinxiu Wang², Ke Shen¹

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 283-302, 2024, DOI:10.32604/cmc.2023.045506

Abstract This paper proposes a new network structure, namely the ProNet network. Retinal medical image segmentation can help clinical diagnosis of related eye diseases and is essential for subsequent rational treatment. The baseline model of the ProNet network is UperNet (Unified perceptual parsing Network), and the backbone network is ConvNext (Convolutional Network). A network structure based on depth-separable convolution and 1 × 1 convolution is used, which has good performance and robustness. We further optimise ProNet mainly in two aspects. One is data enhancement using increased noise and slight angle rotation, which can significantly increase the diversity of data and help… More >

Lujuan Deng, Boyi Liu^*, Zuhe Li

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1157-1170, 2024, DOI:10.32604/cmc.2023.042150

Abstract Multimodal sentiment analysis aims to understand people’s emotions and opinions from diverse data. Concatenating or multiplying various modalities is a traditional multi-modal sentiment analysis fusion method. This fusion method does not utilize the correlation information between modalities. To solve this problem, this paper proposes a model based on a multi-head attention mechanism. First, after preprocessing the original data. Then, the feature representation is converted into a sequence of word vectors and positional encoding is introduced to better understand the semantic and sequential information in the input sequence. Next, the input coding sequence is fed into the transformer model for further… More >

Junhui Li¹, Haotian Zhang¹, Cuiping Li^1,*, Xingxu Zhu¹, Ruitong Liu², Fangwei Duan², Yongming Peng³

Energy Engineering, Vol.121, No.2, pp. 291-313, 2024, DOI:10.32604/ee.2023.027593

Abstract In the existing power system with a large-scale hydrogen storage system, there are problems such as low efficiency of electric-hydrogen-electricity conversion and single modeling of the hydrogen storage system. In order to improve the hydrogen utilization rate of hydrogen storage system in the process of participating in the power grid operation, and speed up the process of electric-hydrogen-electricity conversion. This article provides a detailed introduction to the mathematical and electrical models of various components of the hydrogen storage unit, and also establishes a charging and discharging efficiency model that considers the temperature and internal gas partial pressure of the hydrogen… More >

Yujing Ma^1,*, Leilei Chen^2,3, Haojie Lian^3,4, Zhongwang Wang^2,3

The International Conference on Computational & Experimental Engineering and Sciences, Vol.28, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.010585

Abstract An efficient method of moments (MoM) based on polynomial chaos expansion(PCE) is applied to quickly calculate the electromagnetic scattering problems. The triangle basic functions are used to discretize the surface integral equations. The PCE is utilized to accelerate the MoM by constructing a surrogate model for univariate and bivariate analysis[1]. The mathematical expressions of the surrogate model for the radar cross-section (RCS) are established by considering uncertain parameters such as bistatic angle, incident frequency, and dielectric constant[2,3]. By using the example of a scattering cylinder with analytical solution, it is verified that the MoM accelerated by PCE presents a considerable… More >