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  • Open Access

    ARTICLE

    Weighted De-Synchronization Based Resource Allocation in Wireless Networks

    Kimchheang Chhea1, Dara Ron1, Jung-Ryun Lee1,2,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1815-1826, 2023, DOI:10.32604/cmc.2023.032376 - 06 February 2023

    Abstract Considering the exponential growth of wireless devices with data-starving applications fused with artificial intelligence, the significance of wireless network scalability using distributed behavior and fairness among users is a crucial feature in guaranteeing reliable service to numerous users in the network environment. The Kuramoto model is described as nonlinear self-sustained phase oscillators spinning at varying intrinsic frequencies connected through the sine of their phase differences and displays a phase transition at a specific coupling strength, in which a mutual behavior is accomplished. In this work, we apply the Kuramoto model to achieve a weighted fair… More >

  • Open Access

    ARTICLE

    Gastrointestinal Diseases Classification Using Deep Transfer Learning and Features Optimization

    Mousa Alhajlah1, Muhammad Nouman Noor2, Muhammad Nazir2, Awais Mahmood1,*, Imran Ashraf3, Tehmina Karamat4

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2227-2245, 2023, DOI:10.32604/cmc.2023.031890 - 06 February 2023

    Abstract Gastrointestinal diseases like ulcers, polyps’, and bleeding are increasing rapidly in the world over the last decade. On average 0.7 million cases are reported worldwide every year. The main cause of gastrointestinal diseases is a Helicobacter Pylori (H. Pylori) bacterium that presents in more than 50% of people around the globe. Many researchers have proposed different methods for gastrointestinal disease using computer vision techniques. Few of them focused on the detection process and the rest of them performed classification. The major challenges that they faced are the similarity of infected and healthy regions that misleads the… More >

  • Open Access

    ARTICLE

    Lung Cancer Segmentation with Three-Parameter Logistic Type Distribution Model

    Debnath Bhattacharyya1, Eali. Stephen Neal Joshua2, N. Thirupathi Rao2, Yung-cheol Byun3,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1447-1465, 2023, DOI:10.32604/cmc.2023.031878 - 06 February 2023

    Abstract Lung cancer is the leading cause of mortality in the world affecting both men and women equally. When a radiologist just focuses on the patient’s body, it increases the amount of strain on the radiologist and the likelihood of missing pathological information such as abnormalities are increased. One of the primary objectives of this research work is to develop computer-assisted diagnosis and detection of lung cancer. It also intends to make it easier for radiologists to identify and diagnose lung cancer accurately. The proposed strategy which was based on a unique image feature, took into… More >

  • Open Access

    ARTICLE

    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 - 06 February 2023

    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

    ARTICLE

    Adaptive Dynamic Dipper Throated Optimization for Feature Selection in Medical Data

    Ghada Atteia1, El-Sayed M. El-kenawy2,3, Nagwan Abdel Samee1,*, Mona M. Jamjoom4, Abdelhameed Ibrahim5, Abdelaziz A. Abdelhamid6,7, Ahmad Taher Azar8,9, Nima Khodadadi10,11, Reham A. Ghanem12, Mahmoud Y. Shams13

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1883-1900, 2023, DOI:10.32604/cmc.2023.031723 - 06 February 2023

    Abstract The rapid population growth results in a crucial problem in the early detection of diseases in medical research. Among all the cancers unveiled, breast cancer is considered the second most severe cancer. Consequently, an exponential rising in death cases incurred by breast cancer is expected due to the rapid population growth and the lack of resources required for performing medical diagnoses. Utilizing recent advances in machine learning could help medical staff in diagnosing diseases as they offer effective, reliable, and rapid responses, which could help in decreasing the death risk. In this paper, we propose… More >

  • Open Access

    ARTICLE

    TinyML-Based Classification in an ECG Monitoring Embedded System

    Eunchan Kim1, Jaehyuk Kim2, Juyoung Park3, Haneul Ko4, Yeunwoong Kyung5,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1751-1764, 2023, DOI:10.32604/cmc.2023.031663 - 06 February 2023

    Abstract Recently, the development of the Internet of Things (IoT) has enabled continuous and personal electrocardiogram (ECG) monitoring. In the ECG monitoring system, classification plays an important role because it can select useful data (i.e., reduce the size of the dataset) and identify abnormal data that can be used to detect the clinical diagnosis and guide further treatment. Since the classification requires computing capability, the ECG data are usually delivered to the gateway or the server where the classification is performed based on its computing resource. However, real-time ECG data transmission continuously consumes battery and network… More >

  • Open Access

    ARTICLE

    Energy Management System with Power Offering Strategy for a Microgrid Integrated VPP

    Yeonwoo Lee*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2313-2329, 2023, DOI:10.32604/cmc.2023.031133 - 06 February 2023

    Abstract In the context of both the Virtual Power Plant (VPP) and microgrid (MG), the Energy Management System (EMS) is a key decision-maker for integrating Distributed renewable Energy Resources (DERs) efficiently. The EMS is regarded as a strong enabler of providing the optimized scheduling control in operation and management of usage of disperse DERs and Renewable Energy reSources (RES) such as a small-size wind-turbine (WT) and photovoltaic (PV) energies. The main objective to be pursued by the EMS is the minimization of the overall operating cost of the MG integrated VPP network. However, the minimization of… More >

  • Open Access

    ARTICLE

    Automated Brain Hemorrhage Classification and Volume Analysis

    Maryam Wardah1, Muhammad Mateen1,*, Tauqeer Safdar Malik2, Mohammad Eid Alzahrani3, Adil Fahad3, Abdulmohsen Almalawi4, Rizwan Ali Naqvi5

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2283-2299, 2023, DOI:10.32604/cmc.2023.030706 - 06 February 2023

    Abstract Brain hemorrhage is a serious and life-threatening condition. It can cause permanent and lifelong disability even when it is not fatal. The word hemorrhage denotes leakage of blood within the brain and this leakage of blood from capillaries causes stroke and adequate supply of oxygen to the brain is hindered. Modern imaging methods such as computed tomography (CT) and magnetic resonance imaging (MRI) are employed to get an idea regarding the extent of the damage. An early diagnosis and treatment can save lives and limit the adverse effects of a brain hemorrhage. In this case,… More >

  • Open Access

    ARTICLE

    A 37 GHz Millimeter-Wave Antenna Array for 5G Communication Terminals

    Jalal Khan1, Sadiq Ullah1,*, Usman Ali1, Ladislau Matekovits2,3,4, Farooq Ahmad Tahir5, Muhammad Inam Abbasi6

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1317-1330, 2023, DOI:10.32604/cmc.2023.029879 - 06 February 2023

    Abstract This work presents, design and specific absorption rate (SAR) analysis of a 37 GHz antenna, for 5th Generation (5G) applications. The proposed antenna comprises of 4-elements of rectangular patch and an even distribution. The radiating element is composed of copper material supported by Rogers RT5880 substrate of thickness, 0.254 mm, dielectric constant (εr), 2.2, and loss tangent, 0.0009. The 4-elements array antenna is compact in size with a dimension of 8 mm × 20 mm in length and width. The radiating patch is excited with a 50 ohms connector i.e., K-type. The antenna resonates in the frequency band of 37 GHz, that covers the… More >

  • Open Access

    ARTICLE

    Detecting Double JPEG Compressed Color Images via an Improved Approach

    Xiaojie Zhao1, Xiankui Meng1, Ruyong Ren2, Shaozhang Niu2,*, Zhenguang Gao3

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1765-1781, 2023, DOI:10.32604/cmc.2023.029552 - 06 February 2023

    Abstract Detecting double Joint Photographic Experts Group (JPEG) compression for color images is vital in the field of image forensics. In previous researches, there have been various approaches to detecting double JPEG compression with different quantization matrices. However, the detection of double JPEG color images with the same quantization matrix is still a challenging task. An effective detection approach to extract features is proposed in this paper by combining traditional analysis with Convolutional Neural Networks (CNN). On the one hand, the number of nonzero pixels and the sum of pixel values of color space conversion error… More >

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