Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (22,212)
  • Open Access

    ARTICLE

    Blood Group Classification System Based on Image Processing Techniques

    S. A. Shaban*, D. L. Elsheweikh

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 817-834, 2022, DOI:10.32604/iasc.2022.019500

    Abstract The present paper proposes a novel system that automatically classifies the eight different blood groups according to the ABO and Rh blood group systems. The proposed system is developed by applying MATLAB’s image processing techniques on the blood sample images. These images are acquired from the laboratory using the slide test. It utilizes a mean filter for removing noise from blood sample images. In addition, the Contrast Limited Adaptive Histogram Equalization (CLAHE) is used for enhancing the image characteristics analysis. The proposed system also utilizes the automated threshold strategy (Otsu’s approach) for obtaining the blood samples binary images. Since, adding… More >

  • Open Access

    ARTICLE

    A Deep Learning to Distinguish COVID-19 from Others Pneumonia Cases

    Sami Gazzah1,*, Rida Bayi2, Soulaimane Kaloun2, Omar Bencharef2

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 677-692, 2022, DOI:10.32604/iasc.2022.019360

    Abstract A new virus called SARS-CoV-2 appeared at the end of space 2019 in Wuhan, China. This virus immediately spread throughout the world due to its highly contagious nature. Moreover, SARS-CoV-2 has changed the way of our life and has caused a huge economic and public health disaster. Therefore, it is urgent to identify positive cases as soon as possible and treat them as isolated. Automatic detection of viruses using computer vision and machine learning will be a valuable contribution to detecting and limiting the spread of this epidemic. The delay introduction of X-ray technology as diagnostic tool limited our ability… More >

  • Open Access

    REVIEW

    A Review on Privacy Preservation of Location-Based Services in Internet of Things

    Raniyah Wazirali*

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 767-779, 2022, DOI:10.32604/iasc.2022.019243

    Abstract Internet of Things (IoT) has become popular with the rapid development of sensing devices, and it offers a large number of services. Location data is one of the most important information required for IoT systems. With the widespread of Location Based Services (LBS) applications, the privacy and security threats are also emerging. Recently, a large number of studies focused on localization and positioning functionalities, however, the risk associated with user privacy has not been sufficiently addressed so far. Therefore, privacy and security of device location in IoT systems is an active area of research. Since LBS is often exposed to… More >

  • Open Access

    ARTICLE

    Employing a Fuzzy Approach for Monitoring Fish Pond Culture Environment

    Wen-Tsai Sung1, Sung-Jung Hsiao2,*

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 987-1006, 2022, DOI:10.32604/iasc.2022.019098

    Abstract This study builds an automatic monitoring system for the fish pond culture environment. The purpose of this study is to reduce culture costs, including those resulting from labor costs and natural disasters, and make it easier for culturists to manage their fish ponds. With the proposed system, physical indicators of water quality are extracted by temperature, dissolved oxygen, and pH sensing modules; the heater, submerged motor pump, air pump, feeding trough, and LED illuminating lamp are controlled to improve the water quality and reduce labor. The wireless sensor network (WSN) is used as the signal transmission architecture between the sensor… More >

  • Open Access

    ARTICLE

    User Interaction Based Recommender System Using Machine Learning

    R. Sabitha1, S. Vaishnavi2,*, S. Karthik1, R. M. Bhavadharini3

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1037-1049, 2022, DOI:10.32604/iasc.2022.018985

    Abstract In the present scenario of electronic commerce (E-Commerce), the in-depth knowledge of user interaction with resources has become a significant research concern that impacts more on analytical evaluations of recommender systems. For staying in aggressive E-Commerce, various products and services regarding distinctive requirements must be provided on time. Moreover, because of the large amount of product information available online, Recommender Systems (RS) are required to analyze the availability of consumers, which improves the decision-making of customers with detailed product knowledge and reduces time consumption. With that note, this paper derives a new model called User Interaction based Recommender System (UI-RS)… More >

  • Open Access

    ARTICLE

    Multi-Model Detection of Lung Cancer Using Unsupervised Diffusion Classification Algorithm

    N. Jayanthi1,*, D. Manohari2, Mohamed Yacin Sikkandar3, Mohamed Abdelkader Aboamer3, Mohamed Ibrahim Waly3, C. Bharatiraja4

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1317-1329, 2022, DOI:10.32604/iasc.2022.018974

    Abstract Lung cancer is a curable disease if detected early, and its mortality rate decreases with forwarding treatment measures. At first, an easy and accurate way to detect is by using image processing techniques on the cancer-affected images captured from the patients. This paper proposes a novel lung cancer detection method. Firstly, an adaptive median filter algorithm (AMF) is applied to preprocess those images for improving the quality of the affected area. Then, a supervised image edge detection algorithm (SIED) is presented to segment those images. Then, feature extraction is employed to extract the mean, standard deviation, energy, contrast, etc., of… More >

  • Open Access

    ARTICLE

    Selecting Dominant Features for the Prediction of Early-Stage Chronic Kidney Disease

    Vinothini Arumugam*, S. Baghavathi Priya

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 947-959, 2022, DOI:10.32604/iasc.2022.018654

    Abstract Nowadays, Chronic Kidney Disease (CKD) is one of the vigorous public health diseases. Hence, early detection of the disease may reduce the severity of its consequences. Besides, medical databases of any disease diagnosis may be collected from the blood test, urine test, and patient history. Nevertheless, medical information retrieved from various sources is diverse. Therefore, it is unadaptable to evaluate numerical and nominal features using the same feature selection algorithm, which may lead to fallacious analysis. Applying machine learning techniques over the medical database is a common way to help feature identification for CKD prediction. In this paper, a novel… More >

  • Open Access

    ARTICLE

    Optimization Based Vector Quantization for Data Reduction in Multimedia Applications

    V. R. Kavitha1,*, M. Kanchana2, B. Gobinathan3, K. R. Sekar4, Mohamed Yacin Sikkandar5

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 853-867, 2022, DOI:10.32604/iasc.2022.018358

    Abstract Data reduction and image compression techniques in the present Internet and multi-media age are essential to increase image and video capacity in relation to memory, network bandwidth use and safe data transmission. There have been a different variety of image compression models with varying compression efficiency and visual image quality in the literature. Vector Quantization (VQ) is a widely used image coding scheme that is designed to generate an efficient coding book that includes a list of codewords that assign the input image vector to a minimum distance of Euclidea. The Linde–Buzo–Gray (LBG) historically widely used model produces the local… More >

  • Open Access

    ARTICLE

    ResNet CNN with LSTM Based Tamil Text Detection from Video Frames

    I. Muthumani1,*, N. Malmurugan2, L. Ganesan3

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 917-928, 2022, DOI:10.32604/iasc.2022.018030

    Abstract Text content in videos includes applications such as library video retrievals, live-streaming advertisements, opinion mining, and video synthesis. The key components of such systems include video text detection and acknowledgments. This paper provides a framework to detect and accept text video frames, aiming specifically at the cursive script of Tamil text. The model consists of a text detector, script identifier, and text recognizer. The identification in video frames of textual regions is performed using deep neural networks as object detectors. Textual script content is associated with convolutional neural networks (CNNs) and recognized by combining ResNet CNNs with long short-term memory… More >

  • Open Access

    ARTICLE

    Optimal Control and Spectral Collocation Method for Solving Smoking Models

    Amr M. S. Mahdy1,*, Mohamed S. Mohamed1, Ahoud Y. Al Amiri2, Khaled A. Gepreel1

    Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 899-915, 2022, DOI:10.32604/iasc.2022.017801

    Abstract In this manuscript, we solve the ordinary model of nonlinear smoking mathematically by using the second kind of shifted Chebyshev polynomials. The stability of the equilibrium point is calculated. The schematic of the model illustrates our proposition. We discuss the optimal control of this model, and formularize the optimal control smoking work through the necessary optimality cases. A numerical technique for the simulation of the control problem is adopted. Moreover, a numerical method is presented, and its stability analysis discussed. Numerical simulation then demonstrates our idea. Optimal control for the model is further discussed by clarifying the optimal control through… More >

Displaying 10811-10820 on page 1082 of 22212. Per Page