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  • Open Access


    Efficient Crack Severity Level Classification Using Bilayer Detection for Building Structures

    M. J. Anitha1,*, R. Hemalatha2

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 1183-1200, 2023, DOI:10.32604/csse.2023.031888

    Abstract Detection of cracks at the early stage is considered as very constructive since precautionary steps need to be taken to avoid the damage to the civil structures. Moreover, identifying and classifying the severity level of cracks is inevitable in order to find the stability of buildings. Hence, this paper proposes an efficient strategy to classify the cracks into fine, medium, and thick using a novel bilayer crack detection algorithm. The bilayer crack detection algorithm helps in extracting the requisite features from the crack for efficient classification. The proposed algorithm works well in the dark background and connects the discontinued cracks… More >

  • Open Access


    An Optimal Method for Speech Recognition Based on Neural Network

    Mohamad Khairi Ishak1, Dag Øivind Madsen2,*, Fahad Ahmed Al-Zahrani3

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1951-1961, 2023, DOI:10.32604/iasc.2023.033971

    Abstract Natural language processing technologies have become more widely available in recent years, making them more useful in everyday situations. Machine learning systems that employ accessible datasets and corporate work to serve the whole spectrum of problems addressed in computational linguistics have lately yielded a number of promising breakthroughs. These methods were particularly advantageous for regional languages, as they were provided with cutting-edge language processing tools as soon as the requisite corporate information was generated. The bulk of modern people are unconcerned about the importance of reading. Reading aloud, on the other hand, is an effective technique for nourishing feelings as… More >

  • Open Access


    Machine Learning Based Diagnosis for Diabetic Retinopathy for SKPD-PSC

    M. P. Thiruvenkatasuresh1,*, Surbhi Bhatia2, Shakila Basheer3, Pankaj Dadheech4

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1767-1782, 2023, DOI:10.32604/iasc.2023.033711

    Abstract The study aimed to apply to Machine Learning (ML) researchers working in image processing and biomedical analysis who play an extensive role in comprehending and performing on complex medical data, eventually improving patient care. Developing a novel ML algorithm specific to Diabetic Retinopathy (DR) is a challenge and need of the hour. Biomedical images include several challenges, including relevant feature selection, class variations, and robust classification. Although the current research in DR has yielded favourable results, several research issues need to be explored. There is a requirement to look at novel pre-processing methods to discard irrelevant features, balance the obtained… More >

  • Open Access


    Research on Federated Learning Data Sharing Scheme Based on Differential Privacy

    Lihong Guo*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5069-5085, 2023, DOI:10.32604/cmc.2023.034571

    Abstract To realize data sharing, and to fully use the data value, breaking the data island between institutions to realize data collaboration has become a new sharing mode. This paper proposed a distributed data security sharing scheme based on C/S communication mode, and constructed a federated learning architecture that uses differential privacy technology to protect training parameters. Clients do not need to share local data, and they only need to upload the trained model parameters to achieve data sharing. In the process of training, a distributed parameter update mechanism is introduced. The server is mainly responsible for issuing training commands and… More >

  • Open Access


    A Review of Device-Free Indoor Positioning for Home-Based Care of the Aged: Techniques and Technologies

    Geng Chen1,*, Lili Cheng1, Rui Shao1, Qingbin Wang1, Shuihua Wang2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 1901-1940, 2023, DOI:10.32604/cmes.2023.024901

    Abstract With the development of urbanization, the problem of neurological diseases brought about by population aging has gradually become a social problem of worldwide concern. Aging leads to gradual degeneration of the central nervous system, shrinkage of brain tissue, and decline in physical function in many elderlies, making them susceptible to neurological diseases such as Alzheimer’s disease (AD), stroke, Parkinson’s and major depressive disorder (MDD). Due to the influence of these neurological diseases, the elderly have troubles such as memory loss, inability to move, falling, and getting lost, which seriously affect their quality of life. Tracking and positioning of elderly with… More > Graphic Abstract

    A Review of Device-Free Indoor Positioning for Home-Based Care of the Aged: Techniques and Technologies

  • Open Access


    Liver Tumors Segmentation Using 3D SegNet Deep Learning Approach

    G. Nallasivan1,*, V. Ramachandran2, Roobaea Alroobaea3, Jasem Almotiri4

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1655-1677, 2023, DOI:10.32604/csse.2023.030697

    Abstract An ultrasonic filter detects signs of malignant tumors by analysing the image’s pixel quality fluctuations caused by a liver ailment. Signs of malignant growth proximity are identified in an ultrasound filter through image pixel quality variations from a liver’s condition. Those changes are more common in alcoholic liver conditions than in other etiologies of cirrhosis, suggesting that the cause may be alcohol instead of liver disease. Existing Two-Dimensional (2D) ultrasound data sets contain an accuracy rate of 85.9% and a 2D Computed Tomography (CT) data set of 91.02%. The most recent work on designing a Three-Dimensional (3D) ultrasound imaging system… More >

  • Open Access


    Improved Soil Quality Prediction Model Using Deep Learning for Smart Agriculture Systems

    P. Sumathi1,*, V. V. Karthikeyan2, M. S. Kavitha3, S. Karthik3

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 1545-1559, 2023, DOI:10.32604/csse.2023.027580

    Abstract Soil is the major source of infinite lives on Earth and the quality of soil plays significant role on Agriculture practices all around. Hence, the evaluation of soil quality is very important for determining the amount of nutrients that the soil require for proper yield. In present decade, the application of deep learning models in many fields of research has created greater impact. The increasing soil data availability of soil data there is a greater demand for the remotely avail open source model, leads to the incorporation of deep learning method to predict the soil quality. With that concern, this… More >

  • Open Access


    Failure Prediction for Scientific Workflows Using Nature-Inspired Machine Learning Approach

    S. Sridevi*, Jeevaa Katiravan

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 223-233, 2023, DOI:10.32604/iasc.2023.031928

    Abstract Scientific workflows have gained the emerging attention in sophisticated large-scale scientific problem-solving environments. The pay-per-use model of cloud, its scalability and dynamic deployment enables it suited for executing scientific workflow applications. Since the cloud is not a utopian environment, failures are inevitable that may result in experiencing fluctuations in the delivered performance. Though a single task failure occurs in workflow based applications, due to its task dependency nature, the reliability of the overall system will be affected drastically. Hence rather than reactive fault-tolerant approaches, proactive measures are vital in scientific workflows. This work puts forth an attempt to concentrate on… More >

  • Open Access


    Impact of Portable Executable Header Features on Malware Detection Accuracy

    Hasan H. Al-Khshali1,*, Muhammad Ilyas2

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 153-178, 2023, DOI:10.32604/cmc.2023.032182

    Abstract One aspect of cybersecurity, incorporates the study of Portable Executables (PE) files maleficence. Artificial Intelligence (AI) can be employed in such studies, since AI has the ability to discriminate benign from malicious files. In this study, an exclusive set of 29 features was collected from trusted implementations, this set was used as a baseline to analyze the presented work in this research. A Decision Tree (DT) and Neural Network Multi-Layer Perceptron (NN-MLPC) algorithms were utilized during this work. Both algorithms were chosen after testing a few diverse procedures. This work implements a method of subgrouping features to answer questions such… More >

  • Open Access


    A Consistent Time Level Implementation Preserving Second-Order Time Accuracy via a Framework of Unified Time Integrators in the Discrete Element Approach

    Tao Xue1, Yazhou Wang2, Masao Shimada2, David Tae2, Kumar Tamma2,*, Xiaobing Zhang1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1469-1487, 2023, DOI:10.32604/cmes.2022.021616

    Abstract In this work, a consistent and physically accurate implementation of the general framework of unified second-order time accurate integrators via the well-known GSSSS framework in the Discrete Element Method is presented. The improved tangential displacement evaluation in the present implementation of the discrete element method has been derived and implemented to preserve the consistency of the correct time level evaluation during the time integration process in calculating the algorithmic tangential displacement. Several numerical examples have been used to validate the proposed tangential displacement evaluation; this is in contrast to past practices which only seem to attain the first-order time accuracy… More >

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