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  • Open Access

    ARTICLE

    HgaNets: Fusion of Visual Data and Skeletal Heatmap for Human Gesture Action Recognition

    Wuyan Liang1, Xiaolong Xu2,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1089-1103, 2024, DOI:10.32604/cmc.2024.047861

    Abstract Recognition of human gesture actions is a challenging issue due to the complex patterns in both visual and skeletal features. Existing gesture action recognition (GAR) methods typically analyze visual and skeletal data, failing to meet the demands of various scenarios. Furthermore, multi-modal approaches lack the versatility to efficiently process both uniform and disparate input patterns. Thus, in this paper, an attention-enhanced pseudo-3D residual model is proposed to address the GAR problem, called HgaNets. This model comprises two independent components designed for modeling visual RGB (red, green and blue) images and 3D skeletal heatmaps, respectively. More specifically, each component consists of… More >

  • Open Access

    ARTICLE

    An Adaptive Hate Speech Detection Approach Using Neutrosophic Neural Networks for Social Media Forensics

    Yasmine M. Ibrahim1,2, Reem Essameldin3, Saad M. Darwish1,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 243-262, 2024, DOI:10.32604/cmc.2024.047840

    Abstract Detecting hate speech automatically in social media forensics has emerged as a highly challenging task due to the complex nature of language used in such platforms. Currently, several methods exist for classifying hate speech, but they still suffer from ambiguity when differentiating between hateful and offensive content and they also lack accuracy. The work suggested in this paper uses a combination of the Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO) to adjust the weights of two Multi-Layer Perceptron (MLPs) for neutrosophic sets classification. During the training process of the MLP, the WOA is employed to explore and determine… More >

  • Open Access

    ARTICLE

    An Enhanced Multiview Transformer for Population Density Estimation Using Cellular Mobility Data in Smart City

    Yu Zhou1, Bosong Lin1, Siqi Hu2, Dandan Yu3,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 161-182, 2024, DOI:10.32604/cmc.2024.047836

    Abstract This paper addresses the problem of predicting population density leveraging cellular station data. As wireless communication devices are commonly used, cellular station data has become integral for estimating population figures and studying their movement, thereby implying significant contributions to urban planning. However, existing research grapples with issues pertinent to preprocessing base station data and the modeling of population prediction. To address this, we propose methodologies for preprocessing cellular station data to eliminate any irregular or redundant data. The preprocessing reveals a distinct cyclical characteristic and high-frequency variation in population shift. Further, we devise a multi-view enhancement model grounded on the… More >

  • Open Access

    ARTICLE

    Smartphone-Based Wi-Fi Analysis for Bus Passenger Counting

    Mohammed Alatiyyah*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 875-907, 2024, DOI:10.32604/cmc.2024.047790

    Abstract In the contemporary era of technological advancement, smartphones have become an indispensable part of individuals’ daily lives, exerting a pervasive influence. This paper presents an innovative approach to passenger counting on buses through the analysis of Wi-Fi signals emanating from passengers’ mobile devices. The study seeks to scrutinize the reliability of digital Wi-Fi environments in predicting bus occupancy levels, thereby addressing a crucial aspect of public transportation. The proposed system comprises three crucial elements: Signal capture, data filtration, and the calculation and estimation of passenger numbers. The pivotal findings reveal that the system demonstrates commendable accuracy in estimating passenger counts… More >

  • Open Access

    ARTICLE

    A Lightweight, Searchable, and Controllable EMR Sharing Scheme

    Xiaohui Yang, Peiyin Zhao*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1521-1538, 2024, DOI:10.32604/cmc.2024.047666

    Abstract Electronic medical records (EMR) facilitate the sharing of medical data, but existing sharing schemes suffer from privacy leakage and inefficiency. This article proposes a lightweight, searchable, and controllable EMR sharing scheme, which employs a large attribute domain and a linear secret sharing structure (LSSS), the computational overhead of encryption and decryption reaches a lightweight constant level, and supports keyword search and policy hiding, which improves the high efficiency of medical data sharing. The dynamic accumulator technology is utilized to enable data owners to flexibly authorize or revoke the access rights of data visitors to the data to achieve controllability of… More >

  • Open Access

    REVIEW

    Internet of Things Authentication Protocols: Comparative Study

    Souhayla Dargaoui1, Mourade Azrour1,*, Ahmad El Allaoui1, Azidine Guezzaz2, Abdulatif Alabdulatif3, Abdullah Alnajim4

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 65-91, 2024, DOI:10.32604/cmc.2024.047625

    Abstract Nowadays, devices are connected across all areas, from intelligent buildings and smart cities to Industry 4.0 and smart healthcare. With the exponential growth of Internet of Things usage in our world, IoT security is still the biggest challenge for its deployment. The main goal of IoT security is to ensure the accessibility of services provided by an IoT environment, protect privacy, and confidentiality, and guarantee the safety of IoT users, infrastructures, data, and devices. Authentication, as the first line of defense against security threats, becomes the priority of everyone. It can either grant or deny users access to resources according… More >

  • Open Access

    ARTICLE

    Image Fusion Using Wavelet Transformation and XGboost Algorithm

    Shahid Naseem1, Tariq Mahmood2,3, Amjad Rehman Khan2, Umer Farooq1, Samra Nawazish4, Faten S. Alamri5,*, Tanzila Saba2

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 801-817, 2024, DOI:10.32604/cmc.2024.047623

    Abstract Recently, there have been several uses for digital image processing. Image fusion has become a prominent application in the domain of imaging processing. To create one final image that proves more informative and helpful compared to the original input images, image fusion merges two or more initial images of the same item. Image fusion aims to produce, enhance, and transform significant elements of the source images into combined images for the sake of human visual perception. Image fusion is commonly employed for feature extraction in smart robots, clinical imaging, audiovisual camera integration, manufacturing process monitoring, electronic circuit design, advanced device… More >

  • Open Access

    ARTICLE

    An Ingenious IoT Based Crop Prediction System Using ML and EL

    Shabana Ramzan1, Yazeed Yasin Ghadi2, Hanan Aljuaid3, Aqsa Mahmood1,*, Basharat Ali4

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 183-199, 2024, DOI:10.32604/cmc.2024.047603

    Abstract Traditional farming procedures are time-consuming and expensive as based on manual labor. Farmers have no proper knowledge to select which crop is suitable to grow according to the environmental factors and soil characteristics. This is the main reason for the low yield of crops and the economic crisis in the agricultural sector of the different countries. The use of modern technologies such as the Internet of Things (IoT), machine learning, and ensemble learning can facilitate farmers to observe different factors such as soil electrical conductivity (EC), and environmental factors like temperature to improve crop yield. These parameters play a vital… More >

  • Open Access

    ARTICLE

    MSC-YOLO: Improved YOLOv7 Based on Multi-Scale Spatial Context for Small Object Detection in UAV-View

    Xiangyan Tang1,2, Chengchun Ruan1,2,*, Xiulai Li2,3, Binbin Li1,2, Cebin Fu1,2

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 983-1003, 2024, DOI:10.32604/cmc.2024.047541

    Abstract Accurately identifying small objects in high-resolution aerial images presents a complex and crucial task in the field of small object detection on unmanned aerial vehicles (UAVs). This task is challenging due to variations in UAV flight altitude, differences in object scales, as well as factors like flight speed and motion blur. To enhance the detection efficacy of small targets in drone aerial imagery, we propose an enhanced You Only Look Once version 7 (YOLOv7) algorithm based on multi-scale spatial context. We build the MSC-YOLO model, which incorporates an additional prediction head, denoted as P2, to improve adaptability for small objects.… More >

  • Open Access

    ARTICLE

    Outsmarting Android Malware with Cutting-Edge Feature Engineering and Machine Learning Techniques

    Ahsan Wajahat1, Jingsha He1, Nafei Zhu1, Tariq Mahmood2,3, Tanzila Saba2, Amjad Rehman Khan2, Faten S. Alamri4,*

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 651-673, 2024, DOI:10.32604/cmc.2024.047530

    Abstract The growing usage of Android smartphones has led to a significant rise in incidents of Android malware and privacy breaches. This escalating security concern necessitates the development of advanced technologies capable of automatically detecting and mitigating malicious activities in Android applications (apps). Such technologies are crucial for safeguarding user data and maintaining the integrity of mobile devices in an increasingly digital world. Current methods employed to detect sensitive data leaks in Android apps are hampered by two major limitations they require substantial computational resources and are prone to a high frequency of false positives. This means that while attempting to… More >

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