Raheem Ogla^1,*, Eman Shakar Mahmood¹, Rasha I. Ahmed¹, Abdul Monem S. Rahma²

CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 3075-3096, 2023, DOI:10.32604/cmc.2023.039818

Abstract The transmission of video content over a network raises various issues relating to copyright authenticity, ethics, legality, and privacy. The protection of copyrighted video content is a significant issue in the video industry, and it is essential to find effective solutions to prevent tampering and modification of digital video content during its transmission through digital media. However, there are still many unresolved challenges. This paper aims to address those challenges by proposing a new technique for detecting moving objects in digital videos, which can help prove the credibility of video content by detecting any fake objects inserted by hackers. The… More >

Nizar Faisal Alkayem¹, Maosen Cao^2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.4, pp. 1-1, 2023, DOI:10.32604/icces.2023.09367

Abstract Structural damage identification is a key engineering technique that attempts to ensure structural reliability. In this regard, one of the major intelligent approaches is the inverse analysis of structural damage using metaheuristics. By considering the recent achievements, an efficient hybrid objective function that combines the modal kinetic energy and modal strain energy is developed. The objective function aims to extract maximum modal information from the structure and overcome noisy conditions. Moreover, the original methods are usually vulnerable to the associated high multimodality and uncertainty of the inverse problem. Therefore, the particle swarm algorithm (PSO) mechanism is combined with another newly… More >

Guohui Song^1,2, Yongbin Wang^1,*, Jianfei Li¹, Hongbin Hu¹

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1621-1641, 2023, DOI:10.32604/cmc.2023.040095

Abstract Predicting the popularity of online news is essential for news providers and recommendation systems. Time series, content and meta-feature are important features in news popularity prediction. However, there is a lack of exploration of how to integrate them effectively into a deep learning model and how effective and valuable they are to the model’s performance. This work proposes a novel deep learning model named Multiple Features Dynamic Fusion (MFDF) for news popularity prediction. For modeling time series, long short-term memory networks and attention-based convolution neural networks are used to capture long-term trends and short-term fluctuations of online news popularity. The… More >

Youngeun An, Jimin Lee, EunSang Bak^*, Sungbum Pan^*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1817-1832, 2023, DOI:10.32604/cmc.2023.039460

Abstract Emotion recognition based on facial expressions is one of the most critical elements of human-machine interfaces. Most conventional methods for emotion recognition using facial expressions use the entire facial image to extract features and then recognize specific emotions through a pre-trained model. In contrast, this paper proposes a novel feature vector extraction method using the Euclidean distance between the landmarks changing their positions according to facial expressions, especially around the eyes, eyebrows, nose, and mouth. Then, we apply a new classifier using an ensemble network to increase emotion recognition accuracy. The emotion recognition performance was compared with the conventional algorithms… More >

Mingqiang Zhou^*, Mengjiao Li, Zhiyuan Qian, Kunpeng Li

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2443-2460, 2023, DOI:10.32604/cmc.2023.038675

Abstract Role-based network embedding aims to embed role-similar nodes into a similar embedding space, which is widely used in graph mining tasks such as role classification and detection. Roles are sets of nodes in graph networks with similar structural patterns and functions. However, the role-similar nodes may be far away or even disconnected from each other. Meanwhile, the neighborhood node features and noise also affect the result of the role-based network embedding, which are also challenges of current network embedding work. In this paper, we propose a Role-based network Embedding via Quantum walk with weighted Features fusion (REQF), which simultaneously considers… More >

Mehdi Hassan^1,2, Safdar Ali³, Jin Young Kim^2,*, Muhammad Sanaullah⁴, Hani Alquhayz⁵, Khushbakht Safdar⁶

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1643-1663, 2023, DOI:10.32604/cmc.2023.038578

Abstract Breast cancer resistance protein (BCRP) is an important resistance protein that significantly impacts anticancer drug discovery, treatment, and rehabilitation. Early identification of BCRP substrates is quite a challenging task. This study aims to predict early substrate structure, which can help to optimize anticancer drug development and clinical diagnosis. For this study, a novel intelligent approach-based methodology is developed by modifying the ResNet101 model using transfer learning (TL) for automatic deep feature (DF) extraction followed by classification with linear discriminant analysis algorithm (TLRNDF-LDA). This study utilized structural fingerprints, which are exploited by DF contrary to conventional molecular descriptors. The proposed in… More >

XIAOFENG LI¹, JINYANG ZHENG², JINFENG ZHU³, XIN HUANG⁴, HUANHUAN ZHU⁵, BINGDI CHEN^6,*

BIOCELL, Vol.47, No.8, pp. 1771-1781, 2023, DOI:10.32604/biocell.2023.028343

Abstract Circulating tumor cells (CTCs) are neoplastic cells that are detached from primary tumors and enter circulation. Enumeration and characterization of CTCs are of significance in cancer diagnosis, prognosis, and treatment monitoring. CTC survival in the bloodstream is a limiting step for the development of metastases in distant organs. Recent technological advances, especially in single-cell molecular analyses have uncovered heterogeneous CTC survival mechanisms. Undergoing epithelial-to-mesenchymal transition (EMT), increasing stem cell-like properties, and forming cell clusters enable CTCs to adapt to the harsh microenvironment of the circulation. Expressing and releasing several immunosuppressive molecules help CTCs escape from anti-cancer immune mechanisms. This review… More >

Ahmed Silik^1,2,7, Xiaodong Wang³, Chenyue Mei³, Xiaolei Jin³, Xudong Zhou⁴, Wei Zhou⁴, Congning Chen⁴, Weixing Hong^1,2, Jiawei Li^1,2, Mingjie Mao^1,2, Yuhan Liu^1,2, Mohammad Noori^5,6,*, Wael A. Altabey^8,*

Structural Durability & Health Monitoring, Vol.17, No.4, pp. 257-281, 2023, DOI:10.32604/sdhm.2023.023617

Abstract Damage detection is an important area with growing interest in mechanical and structural engineering. One of the critical issues in damage detection is how to determine indices sensitive to the structural damage and insensitive to the surrounding environmental variations. Current damage identification indices commonly focus on structural dynamic characteristics such as natural frequencies, mode shapes, and frequency responses. This study aimed at developing a technique based on energy Curvature Difference, power spectrum density, correlation-based index, load distribution factor, and neutral axis shift to assess the bridge deck condition. In addition to tracking energy and frequency over time using wavelet packet… More > Graphic Abstract

Safdar Khan¹, Muhammad Attique Khan², Jamal Hussain Shah^1,*, Faheem Shehzad², Taerang Kim³, Jae-Hyuk Cha³

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2337-2360, 2023, DOI:10.32604/csse.2023.040410

Abstract Human Suspicious Activity Recognition (HSAR) is a critical and active research area in computer vision that relies on artificial intelligence reasoning. Significant advances have been made in this field recently due to important applications such as video surveillance. In video surveillance, humans are monitored through video cameras when doing suspicious activities such as kidnapping, fighting, snatching, and a few more. Although numerous techniques have been introduced in the literature for routine human actions (HAR), very few studies are available for HSAR. This study proposes a deep convolutional neural network (CNN) and optimal featuresbased framework for HSAR in video frames. The… More >

Ghoroub Talal Bostaji^*, Emad Sami Jaha

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1571-1591, 2023, DOI:10.32604/csse.2023.039701

Abstract Human recognition technology based on biometrics has become a fundamental requirement in all aspects of life due to increased concerns about security and privacy issues. Therefore, biometric systems have emerged as a technology with the capability to identify or authenticate individuals based on their physiological and behavioral characteristics. Among different viable biometric modalities, the human ear structure can offer unique and valuable discriminative characteristics for human recognition systems. In recent years, most existing traditional ear recognition systems have been designed based on computer vision models and have achieved successful results. Nevertheless, such traditional models can be sensitive to several unconstrained… More >