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  • 1
    Online Resource
    Online Resource
    Egypts Presidential Specialized Council for Education and Scientific Research ; 2019
    In:  Menoufia Journal of Electronic Engineering Research Vol. 28, No. 1 ( 2019-12-01), p. 78-82
    In: Menoufia Journal of Electronic Engineering Research, Egypts Presidential Specialized Council for Education and Scientific Research, Vol. 28, No. 1 ( 2019-12-01), p. 78-82
    Type of Medium: Online Resource
    ISSN: 1687-1189
    Language: English
    Publisher: Egypts Presidential Specialized Council for Education and Scientific Research
    Publication Date: 2019
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  • 2
    Online Resource
    Online Resource
    Institute of Electrical and Electronics Engineers (IEEE) ; 2021
    In:  IEEE Access Vol. 9 ( 2021), p. 67874-67889
    In: IEEE Access, Institute of Electrical and Electronics Engineers (IEEE), Vol. 9 ( 2021), p. 67874-67889
    Type of Medium: Online Resource
    ISSN: 2169-3536
    Language: Unknown
    Publisher: Institute of Electrical and Electronics Engineers (IEEE)
    Publication Date: 2021
    detail.hit.zdb_id: 2687964-5
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  • 3
    In: Frontiers in Public Health, Frontiers Media SA, Vol. 10 ( 2022-12-1)
    Abstract: The brain tumor is an urgent malignancy caused by unregulated cell division. Tumors are classified using a biopsy, which is normally performed after the final brain surgery. Deep learning technology advancements have assisted the health professionals in medical imaging for the medical diagnosis of several symptoms. In this paper, transfer-learning-based models in addition to a Convolutional Neural Network (CNN) called BRAIN-TUMOR-net trained from scratch are introduced to classify brain magnetic resonance images into tumor or normal cases. A comparison between the pre-trained InceptionResNetv2, Inceptionv3, and ResNet50 models and the proposed BRAIN-TUMOR-net is introduced. The performance of the proposed model is tested on three publicly available Magnetic Resonance Imaging (MRI) datasets. The simulation results show that the BRAIN-TUMOR-net achieves the highest accuracy compared to other models. It achieves 100%, 97%, and 84.78% accuracy levels for three different MRI datasets. In addition, the k -fold cross-validation technique is used to allow robust classification. Moreover, three different unsupervised clustering techniques are utilized for segmentation.
    Type of Medium: Online Resource
    ISSN: 2296-2565
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2022
    detail.hit.zdb_id: 2711781-9
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  • 4
    In: Micromachines, MDPI AG, Vol. 14, No. 2 ( 2023-02-03), p. 380-
    Abstract: This article presents the circularly polarized antenna operating over 28 GHz mm-wave applications. The suggested antenna has compact size, simple geometry, wideband, high gain, and offers circular polarization. Afterward, two-port MIMO antenna are designed to get Left Hand Circular Polarization (LHCP) and Right-Hand Circular Polarization (RHCP). Four different cases are adopted to construct two-port MIMO antenna of suggested antenna. In case 1, both of the elements are placed parallel to each other; in the second case, the element is parallel but the radiating patch of second antenna element are rotated by 180°. In the third case, the second antenna element is placed orthogonally to the first antenna element. In the final case, the antenna is parallel but placed in the opposite end of substrate material. The S-parameters, axial ratio bandwidth (ARBW) gain, and radiation efficiency are studied and compared in all these cases. The two MIMO systems of all cases are designed by using Roger RT/Duroid 6002 with thickness of 0.79 mm. The overall size of two-port MIMO antennas is 20.5 mm × 12 mm × 0.79 mm. The MIMO configuration of the suggested CP antenna offers wideband, low mutual coupling, wide ARBW, high gain, and high radiation efficiency. The hardware prototype of all cases is fabricated to verify the predicated results. Moreover, the comparison of suggested two-port MIMO antenna is also performed with already published work, which show the quality of suggested work in terms of various performance parameters over them.
    Type of Medium: Online Resource
    ISSN: 2072-666X
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2620864-7
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  • 5
    In: Heat Transfer, Wiley, Vol. 51, No. 5 ( 2022-07), p. 3999-4011
    Abstract: In this paper, the effectiveness of ferrofluid as a working fluid for solar flat plate collectors (FPCs) is studied. A mini‐ferrofluid‐based solar FPC is designed and tested under laboratory conditions. The thermal performance of the designed solar FPC is evaluated under different conditions and it is observed that it provides higher efficiency for the case of ferrofluid in the presence of a magnetic field. The thermal efficiency is observed to increase by 54% for ferrofluid in presence of a magnetic field as compared to no magnetic field. The thermal efficiency is observed to increase further with the increase in the magnetic field. The increase in thermal efficiency is attributed to the combined effects of higher thermal conductivity and magnetohydrodynamics of ferrofluid, which result in higher convective heat transfer from the riser tube walls into ferrofluid. The higher heat transfer for ferrofluid with a magnetic field is established by calculating the Nusselt number numerically using COMSOL. Simulation results show an increase in Nusselt number for ferrofluid with magnetic field and hence higher thermal efficiency for the solar FPC. The designed FPC provides simple modifications to conventional FPCs to use ferrofluid with magnetic field for higher thermal efficiencies.
    Type of Medium: Online Resource
    ISSN: 2688-4534 , 2688-4542
    URL: Issue
    Language: English
    Publisher: Wiley
    Publication Date: 2022
    detail.hit.zdb_id: 3021752-0
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