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  • Open Access

    ARTICLE

    A Real-Time Automatic Translation of Text to Sign Language

    Muhammad Sanaullah1,*, Babar Ahmad2, Muhammad Kashif2, Tauqeer Safdar2, Mehdi Hassan3, Mohd Hilmi Hasan4, Norshakirah Aziz4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2471-2488, 2022, DOI:10.32604/cmc.2022.019420 - 27 September 2021

    Abstract Communication is a basic need of every human being; by this, they can learn, express their feelings and exchange their ideas, but deaf people cannot listen and speak. For communication, they use various hands gestures, also known as Sign Language (SL), which they learn from special schools. As normal people have not taken SL classes; therefore, they are unable to perform signs of daily routine sentences (e.g., what are the specifications of this mobile phone?). A technological solution can facilitate in overcoming this communication gap by which normal people can communicate with deaf people. This… More >

  • Open Access

    ARTICLE

    Deterministic and Stochastic Fractional-Order Hastings-Powell Food Chain Model

    Moustafa El-Shahed1,*, Asmaa M. Al-Dububan2

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2277-2296, 2022, DOI:10.32604/cmc.2022.019314 - 27 September 2021

    Abstract In this paper, a deterministic and stochastic fractional-order model of the tri-trophic food chain model incorporating harvesting is proposed and analysed. The interaction between prey, middle predator and top predator population is investigated. In order to clarify the characteristics of the proposed model, the analysis of existence, uniqueness, non-negativity and boundedness of the solutions of the proposed model are examined. Some sufficient conditions that ensure the local and global stability of equilibrium points are obtained. By using stability analysis of the fractional-order system, it is proved that if the basic reproduction number , the predator More >

  • Open Access

    ARTICLE

    Secure Watermarking Scheme for Color DICOM Images in Telemedicine Applications

    Kamred Udham Singh1, Hatem Salem Abu-Hamatta2, Abhishek Kumar3, Achintya Singhal4, Mamoon Rashid5,*, A. K. Bashir6

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2525-2542, 2022, DOI:10.32604/cmc.2022.019302 - 27 September 2021

    Abstract Teleradiology plays a vital role in the medical field, which permits transmitting medical and imaging data over a communication network. It ensures data reliability and provides convenient communication for clinical interpretation and diagnostic purposes. The transmission of this medical data over a network raises the problems of legal, ethical issues, privacy, and copyright authenticity. The copyright protection of medical images is a significant issue in the medical field. Watermarking schemes are used to address these issues. A gray-level or binary image is used as a watermark frequently in color image watermarking schemes. In this paper,… More >

  • Open Access

    ARTICLE

    Privacy-Enhanced Data Deduplication Computational Intelligence Technique for Secure Healthcare Applications

    Jinsu Kim1, Sungwook Ryu2, Namje Park1,3,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4169-4184, 2022, DOI:10.32604/cmc.2022.019277 - 27 September 2021

    Abstract A significant number of cloud storage environments are already implementing deduplication technology. Due to the nature of the cloud environment, a storage server capable of accommodating large-capacity storage is required. As storage capacity increases, additional storage solutions are required. By leveraging deduplication, you can fundamentally solve the cost problem. However, deduplication poses privacy concerns due to the structure itself. In this paper, we point out the privacy infringement problem and propose a new deduplication technique to solve it. In the proposed technique, since the user’s map structure and files are not stored on the server, More >

  • Open Access

    ARTICLE

    Artificial Intelligence in Medicine: Real Time Electronic Stethoscope for Heart Diseases Detection

    Batyrkhan Omarov1,2,*, Nurbek Saparkhojayev2, Shyrynkyz Shekerbekova3, Oxana Akhmetova1, Meruert Sakypbekova1, Guldina Kamalova3, Zhanna Alimzhanova1, Lyailya Tukenova3, Zhadyra Akanova4

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2815-2833, 2022, DOI:10.32604/cmc.2022.019246 - 27 September 2021

    Abstract Diseases of the cardiovascular system are one of the major causes of death worldwide. These diseases could be quickly detected by changes in the sound created by the action of the heart. This dynamic auscultations need extensive professional knowledge and emphasis on listening skills. There is also an unmet requirement for a compact cardiac condition early warning device. In this paper, we propose a prototype of a digital stethoscopic system for the diagnosis of cardiac abnormalities in real time using machine learning methods. This system consists of three subsystems that interact with each other (1)… More >

  • Open Access

    ARTICLE

    Land-Cover Classification and its Impact on Peshawar’s Land Surface Temperature Using Remote Sensing

    Shahab Ul Islam1, Saifullah Jan2, Abdul Waheed3,4,*, Gulzar Mehmood5, Mahdi Zareei6, Faisal Alanazi7

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4123-4145, 2022, DOI:10.32604/cmc.2022.019226 - 27 September 2021

    Abstract Spatial and temporal information on urban infrastructure is essential and requires various land-cover/land-use planning and management applications. Besides, a change in infrastructure has a direct impact on other land-cover and climatic conditions. This study assessed changes in the rate and spatial distribution of Peshawar district’s infrastructure and its effects on Land Surface Temperature (LST) during the years 1996 and 2019. For this purpose, firstly, satellite images of bands7 and 8 ETM+(Enhanced Thematic Mapper) plus and OLI (Operational Land Imager) of 30 m resolution were taken. Secondly, for classification and image processing, remote sensing (RS) applications… More >

  • Open Access

    ARTICLE

    Engagement Detection Based on Analyzing Micro Body Gestures Using 3D CNN

    Shoroog Khenkar1,*, Salma Kammoun Jarraya1,2

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2655-2677, 2022, DOI:10.32604/cmc.2022.019152 - 27 September 2021

    Abstract This paper proposes a novel, efficient and affordable approach to detect the students’ engagement levels in an e-learning environment by using webcams. Our method analyzes spatiotemporal features of e-learners’ micro body gestures, which will be mapped to emotions and appropriate engagement states. The proposed engagement detection model uses a three-dimensional convolutional neural network to analyze both temporal and spatial information across video frames. We follow a transfer learning approach by using the C3D model that was trained on the Sports-1M dataset. The adopted C3D model was used based on two different approaches; as a feature More >

  • Open Access

    ARTICLE

    Realistic Smile Expression Recognition Approach Using Ensemble Classifier with Enhanced Bagging

    Oday A. Hassen1,*, Nur Azman Abu1, Zaheera Zainal Abidin1, Saad M. Darwish2

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2453-2469, 2022, DOI:10.32604/cmc.2022.019125 - 27 September 2021

    Abstract A robust smile recognition system could be widely used for many real-world applications. Classification of a facial smile in an unconstrained setting is difficult due to the invertible and wide variety in face images. In this paper, an adaptive model for smile expression classification is suggested that integrates a fast features extraction algorithm and cascade classifiers. Our model takes advantage of the intrinsic association between face detection, smile, and other face features to alleviate the over-fitting issue on the limited training set and increase classification results. The features are extracted taking into account to exclude… More >

  • Open Access

    ARTICLE

    Diffusion Based Channel Gains Estimation in WSN Using Fractional Order Strategies

    Nasir Mahmud Khokhar1, Muhammad Nadeem Majeed2, Syed Muslim Shah3,*

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2209-2224, 2022, DOI:10.32604/cmc.2022.019120 - 27 September 2021

    Abstract In this study, it is proposed that the diffusion least mean square (LMS) algorithm can be improved by applying the fractional order signal processing methodologies. Application of Caputo’s fractional derivatives are considered in the optimization of cost function. It is suggested to derive a fractional order variant of the diffusion LMS algorithm. The applicability is tested for the estimation of channel parameters in a distributed environment consisting of randomly distributed sensors communicating through wireless medium. The topology of the network is selected such that a smaller number of nodes are informed. In the network, a… More >

  • Open Access

    ARTICLE

    Multiclass Cucumber Leaf Diseases Recognition Using Best Feature Selection

    Nazar Hussain1, Muhammad Attique Khan1, Usman Tariq2, Seifedine Kadry3,*, MuhammadAsfand E. Yar4, Almetwally M. Mostafa5, Abeer Ali Alnuaim6, Shafiq Ahmad7

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3281-3294, 2022, DOI:10.32604/cmc.2022.019036 - 27 September 2021

    Abstract Agriculture is an important research area in the field of visual recognition by computers. Plant diseases affect the quality and yields of agriculture. Early-stage identification of crop disease decreases financial losses and positively impacts crop quality. The manual identification of crop diseases, which are mostly visible on leaves, is a very time-consuming and costly process. In this work, we propose a new framework for the recognition of cucumber leaf diseases. The proposed framework is based on deep learning and involves the fusion and selection of the best features. In the feature extraction phase, VGG (Visual… More >

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