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  • Open Access

    ARTICLE

    Brain Tumor Classification Using Image Fusion and EFPA-SVM Classifier

    P. P. Fathimathul Rajeena1,*, R. Sivakumar2

    Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2837-2855, 2023, DOI:10.32604/iasc.2023.030144

    Abstract An accurate and early diagnosis of brain tumors based on medical imaging modalities is of great interest because brain tumors are a harmful threat to a person’s health worldwide. Several medical imaging techniques have been used to analyze brain tumors, including computed tomography (CT) and magnetic resonance imaging (MRI). CT provides information about dense tissues, whereas MRI gives information about soft tissues. However, the fusion of CT and MRI images has little effect on enhancing the accuracy of the diagnosis of brain tumors. Therefore, machine learning methods have been adopted to diagnose brain tumors in recent years. This paper intends… More >

  • Open Access

    ARTICLE

    A Double Threshold Energy Detection-Based Neural Network for Cognitive Radio Networks

    Nada M. Elfatih1, Elmustafa Sayed Ali1,5, Maha Abdelhaq2, Raed Alsaqour3,*, Rashid A. Saeed4

    Computer Systems Science and Engineering, Vol.45, No.1, pp. 329-342, 2023, DOI:10.32604/csse.2023.028528

    Abstract

    In cognitive radio networks (CoR), the performance of cooperative spectrum sensing is improved by reducing the overall error rate or maximizing the detection probability. Several optimization methods are usually used to optimize the number of user-chosen for cooperation and the threshold selection. However, these methods do not take into account the effect of sample size and its effect on improving CoR performance. In general, a large sample size results in more reliable detection, but takes longer sensing time and increases complexity. Thus, the locally sensed sample size is an optimization problem. Therefore, optimizing the local sample size for each cognitive… More >

  • Open Access

    ARTICLE

    A Novel Segment White Matter Hyperintensities Approach for Detecting Alzheimer

    Antonitta Eileen Pious1,*, U. K. Sridevi2

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2715-2726, 2023, DOI:10.32604/csse.2023.026582

    Abstract Segmentation has been an effective step that needs to be done before the classification or detection of an anomaly like Alzheimer’s on a brain scan. Segmentation helps detect pixels of the same intensity or volume and group them together as one class or region, where in that particular region of interest (ROI) can be concentrated on, rather than focusing on the entire image. In this paper White Matter Hyperintensities (WMH) is taken as a strong biomarker that supports and determines the presence of Alzheimer’s. As the first step a proper segmentation of the lesions has to be carried out. As… More >

  • Open Access

    ARTICLE

    Adaptive Sub-Threshold Voltage Level Control for Voltage Deviate-Domino Circuits

    C. Arun Prasath1,*, C. Gowri Shankar2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1767-1781, 2023, DOI:10.32604/iasc.2023.028758

    Abstract Leakage power and propagation delay are two significant issues found in sub-micron technology-based Complementary Metal-Oxide-Semiconductor (CMOS)-based Very Large-Scale Integration (VLSI) circuit designs. Positive Channel Metal Oxide Semiconductor (PMOS) has been replaced by Negative Channel Metal Oxide Semiconductor (NMOS) in recent years, with low dimension-switching changes in order to shape the mirror of voltage comparator. NMOS is used to reduce stacking leakage as well as total exchange. Domino Logic Circuit is a powerful and versatile digital programmer that gained popularity in recent years. In this study regarding Adaptive Sub Threshold Voltage Level Control Problem, the researchers intend to solve the contention… More >

  • Open Access

    ARTICLE

    Fin Field Effect Transistor with Active 4-Bit Arithmetic Operations in 22 nm Technology

    S. Senthilmurugan1,*, K. Gunaseelan2

    Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1323-1336, 2023, DOI:10.32604/iasc.2023.027650

    Abstract A design of a high-speed multi-core processor with compact size is a trending approach in the Integrated Circuits (ICs) fabrication industries. Because whenever device size comes down into narrow, designers facing many power density issues should be reduced by scaling threshold voltage and supply voltage. Initially, Complementary Metal Oxide Semiconductor (CMOS) technology supports power saving up to 32 nm gate length, but further scaling causes short severe channel effects such as threshold voltage swing, mobility degradation, and more leakage power (less than 32) at gate length. Hence, it directly affects the arithmetic logic unit (ALU), which suffers a significant power… More >

  • Open Access

    ARTICLE

    A Sea Ice Recognition Algorithm in Bohai Based on Random Forest

    Tao Li1, Di Wu1, Rui Han2, Jinyue Xia3, Yongjun Ren4,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3721-3739, 2022, DOI:10.32604/cmc.2022.029619

    Abstract As an important maritime hub, Bohai Sea Bay provides great convenience for shipping and suffers from sea ice disasters of different severity every winter, which greatly affects the socio-economic and development of the region. Therefore, this paper uses FY-4A (a weather satellite) data to study sea ice in the Bohai Sea. After processing the data for land removal and cloud detection, it combines multi-channel threshold method and adaptive threshold algorithm to realize the recognition of Bohai Sea ice under clear sky conditions. The random forests classification algorithm is introduced in sea ice identification, which can achieve a certain effect of… More >

  • Open Access

    ARTICLE

    Detection and Classification of Hemorrhages in Retinal Images

    Ghassan Ahmed Ali1, Thamer Mitib Ahmad Al Sariera2,*, Muhammad Akram1, Adel Sulaiman1, Fekry Olayah1

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1601-1616, 2023, DOI:10.32604/csse.2023.026119

    Abstract Damage of the blood vessels in retina due to diabetes is called diabetic retinopathy (DR). Hemorrhages is the first clinically visible symptoms of DR. This paper presents a new technique to extract and classify the hemorrhages in fundus images. The normal objects such as blood vessels, fovea and optic disc inside retinal images are masked to distinguish them from hemorrhages. For masking blood vessels, thresholding that separates blood vessels and background intensity followed by a new filter to extract the border of vessels based on orientations of vessels are used. For masking optic disc, the image is divided into sub-images… More >

  • Open Access

    ARTICLE

    Cervical Cancer Detection Based on Novel Decision Tree Approach

    S. R. Sylaja Vallee Narayan1,*, R. Jemila Rose2

    Computer Systems Science and Engineering, Vol.44, No.2, pp. 1025-1038, 2023, DOI:10.32604/csse.2023.022564

    Abstract Cervical cancer is a disease that develops in the cervix’s tissue. Cervical cancer mortality is being reduced due to the growth of screening programmers. Cervical cancer screening is a big issue because the majority of cervical cancer screening treatments are invasive. Hence, there is apprehension about standard screening procedures, as well as the time it takes to learn the results. There are different methods for detecting problems in the cervix using Pap (Papanicolaou-stained) test, colposcopy, Computed Tomography (CT), Magnetic Resonance Image (MRI) and ultrasound. To obtain a clear sketch of the infected regions, using a decision tree approach, the captured… More >

  • Open Access

    ARTICLE

    Edge Detection of COVID-19 CT Image Based on GF_SSR, Improved Multiscale Morphology, and Adaptive Threshold

    Shouming Hou1, Chaolan Jia1, Kai Li1, Liya Fan2, Jincheng Guo3,*, Mackenzie Brown4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 81-94, 2022, DOI:10.32604/cmes.2022.019006

    Abstract Edge detection is an effective method for image segmentation and feature extraction. Therefore, extracting weak edges with the inhomogeneous gray of Corona Virus Disease 2019 (COVID-19) CT images is extremely important. Multiscale morphology has been widely used in the edge detection of medical images due to its excellent boundary detection accuracy. In this paper, we propose a weak edge detection method based on Gaussian filtering and singlescale Retinex (GF_SSR), and improved multiscale morphology and adaptive threshold binarization (IMSM_ATB). As all the CT images have noise, we propose to remove image noise by Gaussian filtering. The edge of CT images is… More >

  • Open Access

    ARTICLE

    A Steganography Based on Optimal Multi-Threshold Block Labeling

    Shuying Xu1, Chin-Chen Chang1, Ji-Hwei Horng2,*

    Computer Systems Science and Engineering, Vol.44, No.1, pp. 721-739, 2023, DOI:10.32604/csse.2023.026046

    Abstract Hiding secret data in digital images is one of the major research fields in information security. Recently, reversible data hiding in encrypted images has attracted extensive attention due to the emergence of cloud services. This paper proposes a novel reversible data hiding method in encrypted images based on an optimal multi-threshold block labeling technique (OMTBL-RDHEI). In our scheme, the content owner encrypts the cover image with block permutation, pixel permutation, and stream cipher, which preserve the in-block correlation of pixel values. After uploading to the cloud service, the data hider applies the prediction error rearrangement (PER), the optimal threshold selection… More >

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