Azuwa Ali¹, Mohd Najib Mohd Yasin^2,*, Ismahayati Adam², Ali H. Rambe³, Mohd Haizal Jamaludin⁴, Hasliza A Rahim², Corhan Cengiz⁵, Mohd Ibrahim Shapiai Abd. Razak⁶

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 313-325, 2023, DOI:10.32604/cmc.2023.031706

Abstract This paper proposes a new dielectric resonator antenna (DRA) design that can generate circularly polarized (CP) triple-band signals. A triple-band CP DRA antenna fed by a probe feed system is achieved with metal strips structure on side of DRA structure. The design start with conventional rectangular DRA with F shaped metal strips on DRA structure alongside the feed. Then, the F metal strip is enhanced by extending the length of the metal strip to obtain wider impedance bandwidth. Further improvement on the antenna performance is observed by improvised the conventional DRA structure. The method of removing part of DRA bottom… More >

Rehana Ghulam¹, Sammar Fatima¹, Tariq Ali¹, Nazir Ahmad Zafar¹, Abdullah A. Asiri², Hassan A. Alshamrani^2,*, Samar M. Alqhtani³, Khlood M. Mehdar⁴

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1333-1349, 2023, DOI:10.32604/cmc.2023.031695

Abstract Human brain consists of millions of cells to control the overall structure of the human body. When these cells start behaving abnormally, then brain tumors occurred. Precise and initial stage brain tumor detection has always been an issue in the field of medicines for medical experts. To handle this issue, various deep learning techniques for brain tumor detection and segmentation techniques have been developed, which worked on different datasets to obtain fruitful results, but the problem still exists for the initial stage of detection of brain tumors to save human lives. For this purpose, we proposed a novel U-Net-based Convolutional… More >

Khlood Shinan^1,2, Khalid Alsubhi², M. Usman Ashraf^3,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 693-714, 2023, DOI:10.32604/cmc.2023.031641

Abstract The number of botnet malware attacks on Internet devices has grown at an equivalent rate to the number of Internet devices that are connected to the Internet. Bot detection using machine learning (ML) with flow-based features has been extensively studied in the literature. Existing flow-based detection methods involve significant computational overhead that does not completely capture network communication patterns that might reveal other features of malicious hosts. Recently, Graph-Based Bot Detection methods using ML have gained attention to overcome these limitations, as graphs provide a real representation of network communications. The purpose of this study is to build a botnet… More >

Saif Saad Hameed, Ismail Taha Ahmed^*, Omar Munthir Al Okashi

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 327-340, 2023, DOI:10.32604/cmc.2023.031622

Abstract Biometric recognition refers to the identification of individuals through their unique behavioral features (e.g., fingerprint, face, and iris). We need distinguishing characteristics to identify people, such as fingerprints, which are world-renowned as the most reliable method to identify people. The recognition of fingerprints has become a standard procedure in forensics, and different techniques are available for this purpose. Most current techniques lack interest in image enhancement and rely on high-dimensional features to generate classification models. Therefore, we proposed an effective fingerprint classification method for classifying the fingerprint image as authentic or altered since criminals and hackers routinely change their fingerprints… More >

Fatemeh Sadeghi¹, Omid Rostami², Myung-Kyu Yi³, Seong Oun Hwang^3,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 751-768, 2023, DOI:10.32604/cmc.2023.031519

Abstract Real-time detection of Covid-19 has definitely been the most widely-used world-wide classification problem since the start of the pandemic from 2020 until now. In the meantime, airspace opacities spreads related to lung have been of the most challenging problems in this area. A common approach to do on that score has been using chest X-ray images to better diagnose positive Covid-19 cases. Similar to most other classification problems, machine learning-based approaches have been the first/most-used candidates in this application. Many schemes based on machine/deep learning have been proposed in recent years though increasing the performance and accuracy of the system… More >

Swaleha Zubair¹, Anjani Kumar Singha¹, Nitish Pathak², Neelam Sharma³, Shabana Urooj^4,*, Samia Rabeh Larguech⁴

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2005-2019, 2023, DOI:10.32604/cmc.2023.031481

Abstract Deep learning is the process of determining parameters that reduce the cost function derived from the dataset. The optimization in neural networks at the time is known as the optimal parameters. To solve optimization, it initialize the parameters during the optimization process. There should be no variation in the cost function parameters at the global minimum. The momentum technique is a parameters optimization approach; however, it has difficulties stopping the parameter when the cost function value fulfills the global minimum (non-stop problem). Moreover, existing approaches use techniques; the learning rate is reduced during the iteration period. These techniques are monotonically… More >

Mohamed Amine Ouamri^1,2, Reem Alkanhel^3,*, Cedric Gueguen¹, Manal Abdullah Alohali⁴, Sherif S. M. Ghoneim⁵

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 453-467, 2023, DOI:10.32604/cmc.2023.031450

Abstract With the rapid development of emerging 5G and beyond (B5G), Unmanned Aerial Vehicles (UAVs) are increasingly important to improve the performance of dense cellular networks. As a conventional metric, coverage probability has been widely studied in communication systems due to the increasing density of users and complexity of the heterogeneous environment. In recent years, stochastic geometry has attracted more attention as a mathematical tool for modeling mobile network systems. In this paper, an analytical approach to the coverage probability analysis of UAV-assisted cellular networks with imperfect beam alignment has been proposed. An assumption was considered that all users are distributed… More >

Yu Fan^1,6, Jingbing Li^1,2,*, Uzair Aslam Bhatti^1,2, Chunyan Shao¹, Cheng Gong¹, Jieren Cheng^3,5, Yenwei Chen⁴

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1279-1302, 2023, DOI:10.32604/cmc.2023.031445

Abstract Medical images are a critical component of the diagnostic process for clinicians. Although the quality of medical photographs is essential to the accuracy of a physician’s diagnosis, they must be encrypted due to the characteristics of digital storage and information leakage associated with medical images. Traditional watermark embedding algorithm embeds the watermark information into the medical image, which reduces the quality of the medical image and affects the physicians’ judgment of patient diagnosis. In addition, watermarks in this method have weak robustness under high-intensity geometric attacks when the medical image is attacked and the watermarks are destroyed. This paper proposes… More >

Mehdi Jamei¹, Nadjem Bailek^2,*, Kada Bouchouicha³, Muhammed A. Hassan⁴, Ahmed Elbeltagi⁵, Alban Kuriqi⁶, Nadhir Al-Ansar⁷, Javier Almorox⁸, El-Sayed M. El-kenawy^9,10

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1625-1640, 2023, DOI:10.32604/cmc.2023.031406

Abstract Solar energy represents one of the most important renewable energy sources contributing to the energy transition process. Considering that the observation of daily global solar radiation (GSR) is not affordable in some parts of the globe, there is an imperative need to develop alternative ways to predict it. Therefore, the main objective of this study is to evaluate the performance of different hybrid data-driven techniques in predicting daily GSR in semi-arid regions, such as the majority of Spanish territory. Here, four ensemble-based hybrid models were developed by hybridizing Additive Regression (AR) with Random Forest (RF), Locally Weighted Linear Regression (LWLR),… More >

Anwer Mustafa Hilal^1,2,*, Aisha Hassan Abdalla Hashim¹, Heba G. Mohamed³, Mohamed K. Nour⁴, Mashael M. Asiri⁵, Ali M. Al-Sharafi⁶, Mahmoud Othman⁷, Abdelwahed Motwakel²

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 607-621, 2023, DOI:10.32604/cmc.2023.031371

Abstract Cybersecurity-related solutions have become familiar since it ensures security and privacy against cyberattacks in this digital era. Malicious Uniform Resource Locators (URLs) can be embedded in email or Twitter and used to lure vulnerable internet users to implement malicious data in their systems. This may result in compromised security of the systems, scams, and other such cyberattacks. These attacks hijack huge quantities of the available data, incurring heavy financial loss. At the same time, Machine Learning (ML) and Deep Learning (DL) models paved the way for designing models that can detect malicious URLs accurately and classify them. With this motivation,… More >