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Search Results (18)
  • Open Access


    Secure Transmission of Compressed Medical Image Sequences on Communication Networks Using Motion Vector Watermarking

    Rafi Ullah1,*, Mohd Hilmi bin Hasan1, Sultan Daud Khan2, Mussadiq Abdul Rahim3

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3283-3301, 2024, DOI:10.32604/cmc.2024.046305

    Abstract Medical imaging plays a key role within modern hospital management systems for diagnostic purposes. Compression methodologies are extensively employed to mitigate storage demands and enhance transmission speed, all while upholding image quality. Moreover, an increasing number of hospitals are embracing cloud computing for patient data storage, necessitating meticulous scrutiny of server security and privacy protocols. Nevertheless, considering the widespread availability of multimedia tools, the preservation of digital data integrity surpasses the significance of compression alone. In response to this concern, we propose a secure storage and transmission solution for compressed medical image sequences, such as… More >

  • Open Access


    An Optimized Chinese Filtering Model Using Value Scale Extended Text Vector

    Siyu Lu1, Ligao Cai1, Zhixin Liu2, Shan Liu1, Bo Yang1, Lirong Yin3, Mingzhe Liu4, Wenfeng Zheng1,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 1881-1899, 2023, DOI:10.32604/csse.2023.034853

    Abstract With the development of Internet technology, the explosive growth of Internet information presentation has led to difficulty in filtering effective information. Finding a model with high accuracy for text classification has become a critical problem to be solved by text filtering, especially for Chinese texts. This paper selected the manually calibrated Douban movie website comment data for research. First, a text filtering model based on the BP neural network has been built; Second, based on the Term Frequency-Inverse Document Frequency (TF-IDF) vector space model and the doc2vec method, the text word frequency vector and the More >

  • Open Access


    Symbiotic Organisms Search with Deep Learning Driven Biomedical Osteosarcoma Detection and Classification

    Abdullah M. Basahel1, Mohammad Yamin1, Sulafah M. Basahel2, Mona M. Abusurrah3, K.Vijaya Kumar4, E. Laxmi Lydia5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 133-148, 2023, DOI:10.32604/cmc.2023.031786

    Abstract Osteosarcoma is one of the rare bone cancers that affect the individuals aged between 10 and 30 and it incurs high death rate. Early diagnosis of osteosarcoma is essential to improve the survivability rate and treatment protocols. Traditional physical examination procedure is not only a time-consuming process, but it also primarily relies upon the expert’s knowledge. In this background, the recently developed Deep Learning (DL) models can be applied to perform decision making. At the same time, hyperparameter optimization of DL models also plays an important role in influencing overall classification performance. The current study… More >

  • Open Access


    Photovoltaic Models Parameters Estimation Based on Weighted Mean of Vectors

    Mohamed Elnagi1, Salah Kamel2, Abdelhady Ramadan2, Mohamed F. Elnaggar3,4,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5229-5250, 2023, DOI:10.32604/cmc.2023.032469

    Abstract Renewable energy sources are gaining popularity, particularly photovoltaic energy as a clean energy source. This is evident in the advancement of scientific research aimed at improving solar cell performance. Due to the non-linear nature of the photovoltaic cell, modeling solar cells and extracting their parameters is one of the most important challenges in this discipline. As a result, the use of optimization algorithms to solve this problem is expanding and evolving at a rapid rate. In this paper, a weIghted meaN oF vectOrs algorithm (INFO) that calculates the weighted mean for a set of vectors… More >

  • Open Access


    Motion Enhanced Model Based on High-Level Spatial Features

    Yang Wu1, Lei Guo1, Xiaodong Dai1, Bin Zhang1, Dong-Won Park2, Ming Ma1,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5911-5924, 2022, DOI:10.32604/cmc.2022.031664

    Abstract Action recognition has become a current research hotspot in computer vision. Compared to other deep learning methods, Two-stream convolutional network structure achieves better performance in action recognition, which divides the network into spatial and temporal streams, using video frame images as well as dense optical streams in the network, respectively, to obtain the category labels. However, the two-stream network has some drawbacks, i.e., using dense optical flow as the input of the temporal stream, which is computationally expensive and extremely time-consuming for the current extraction algorithm and cannot meet the requirements of real-time tasks. In… More >

  • Open Access


    Image Captioning Using Detectors and Swarm Based Learning Approach for Word Embedding Vectors

    B. Lalitha1,*, V. Gomathi2

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 173-189, 2023, DOI:10.32604/csse.2023.024118

    Abstract IC (Image Captioning) is a crucial part of Visual Data Processing and aims at understanding for providing captions that verbalize an image’s important elements. However, in existing works, because of the complexity in images, neglecting major relation between the object in an image, poor quality image, labelling it remains a big problem for researchers. Hence, the main objective of this work attempts to overcome these challenges by proposing a novel framework for IC. So in this research work the main contribution deals with the framework consists of three phases that is image understanding, textual understanding and… More >

  • Open Access


    Effects of two vectors on the expression of the NbNAC1 transcription factor and preparation of its polyclonal antibody


    BIOCELL, Vol.46, No.9, pp. 2123-2131, 2022, DOI:10.32604/biocell.2022.020229

    Abstract The NAC (NAM, ATAF, and CUC) superfamily is one of the largest plant-specific families containing transcription factors. An increasing number of studies suggest that NAC1 is involved in plants response to different biotic and abiotic stimulis. Nicotiana benthamiana is a widely used system for evaluating plant-pathogen interactions. In order to study the biochemical function of NbNAC1, NbNAC1 protein and antibody are essential. Therefore, we focused on developing a prokaryotic expression system for producing the Nicotiana benthamiana NbNAC1 protein of in Escherichia coli and the preparation of its polyclonal antibody. Firstly, we constructed two different molecular weight prokaryotic expression More >

  • Open Access


    Effective Classification of Synovial Sarcoma Cancer Using Structure Features and Support Vectors

    P. Arunachalam1, N. Janakiraman1, Junaid Rashid2, Jungeun Kim2,*, Sovan Samanta3, Usman Naseem4, Arun Kumar Sivaraman5, A. Balasundaram6

    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2521-2543, 2022, DOI:10.32604/cmc.2022.025339

    Abstract In this research work, we proposed a medical image analysis framework with two separate releases whether or not Synovial Sarcoma (SS) is the cell structure for cancer. Within this framework the histopathology images are decomposed into a third-level sub-band using a two-dimensional Discrete Wavelet Transform. Subsequently, the structure features (SFs) such as Principal Components Analysis (PCA), Independent Components Analysis (ICA) and Linear Discriminant Analysis (LDA) were extracted from this sub-band image representation with the distribution of wavelet coefficients. These SFs are used as inputs of the Support Vector Machine (SVM) classifier. Also, classification of PCA… More >

  • Open Access


    Historical Arabic Images Classification and Retrieval Using Siamese Deep Learning Model

    Manal M. Khayyat1,2, Lamiaa A. Elrefaei2,3, Mashael M. Khayyat4,*

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 2109-2125, 2022, DOI:10.32604/cmc.2022.024975

    Abstract Classifying the visual features in images to retrieve a specific image is a significant problem within the computer vision field especially when dealing with historical faded colored images. Thus, there were lots of efforts trying to automate the classification operation and retrieve similar images accurately. To reach this goal, we developed a VGG19 deep convolutional neural network to extract the visual features from the images automatically. Then, the distances among the extracted features vectors are measured and a similarity score is generated using a Siamese deep neural network. The Siamese model built and trained at… More >

  • Open Access


    Insider Threat Detection Based on NLP Word Embedding and Machine Learning

    Mohd Anul Haq1, Mohd Abdul Rahim Khan1,*, Mohammed Alshehri2

    Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 619-635, 2022, DOI:10.32604/iasc.2022.021430

    Abstract The growth of edge computing, the Internet of Things (IoT), and cloud computing have been accompanied by new security issues evolving in the information security infrastructure. Recent studies suggest that the cost of insider attacks is higher than the external threats, making it an essential aspect of information security for organizations. Efficient insider threat detection requires state-of-the-art Artificial Intelligence models and utility. Although significant have been made to detect insider threats for more than a decade, there are many limitations, including a lack of real data, low accuracy, and a relatively low false alarm, which… More >

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