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  • Open Access

    ARTICLE

    Eighteen-Element Antenna for Metal-Rimmed Smartphone Sub-6 GHz LTE42 Band Applications

    Saqer S. Alja’Afreh1,*, Mallak H. Alshamaileh1, Eqab Almajali2, Jawad Yousaf3, Amir Altaf4

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3181-3198, 2022, DOI:10.32604/cmc.2022.029863

    Abstract Due to the limited space and large mutual coupling levels, the design of sub-6 GHz massive Multi-Input Multi-Output (m-MIMO) smartphone antenna system attracts antennas’ designers and engineers worldwide. Therefore, this paper presents 18-element m-MIMO antenna system that covers the long-term evolution 42 (LTE42) frequency band (3.4–3.6 GHz) for the fifth generation (5G) applications in metallic frame smartphones. The proposed array system is etched on the long sides of a metal rim of the mobile chassis symmetrically, which is electrically connected to the system ground plane with zero ground clearance. A low-profile frame of height 7 mm (λ/12.3) is symmetrically placed… More >

  • Open Access

    ARTICLE

    Adversarial Training Against Adversarial Attacks for Machine Learning-Based Intrusion Detection Systems

    Muhammad Shahzad Haroon*, Husnain Mansoor Ali

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3513-3527, 2022, DOI:10.32604/cmc.2022.029858

    Abstract Intrusion detection system plays an important role in defending networks from security breaches. End-to-end machine learning-based intrusion detection systems are being used to achieve high detection accuracy. However, in case of adversarial attacks, that cause misclassification by introducing imperceptible perturbation on input samples, performance of machine learning-based intrusion detection systems is greatly affected. Though such problems have widely been discussed in image processing domain, very few studies have investigated network intrusion detection systems and proposed corresponding defence. In this paper, we attempt to fill this gap by using adversarial attacks on standard intrusion detection datasets and then using adversarial samples… More >

  • Open Access

    ARTICLE

    Cuckoo Optimized Convolution Support Vector Machine for Big Health Data Processing

    Eatedal Alabdulkreem1, Jaber S. Alzahrani2, Majdy M. Eltahir3, Abdullah Mohamed4, Manar Ahmed Hamza5,*, Abdelwahed Motwakel5, Mohamed I. Eldesouki6, Mohammed Rizwanullah5

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3039-3055, 2022, DOI:10.32604/cmc.2022.029835

    Abstract Big health data collection and storing for further analysis is a challenging task because this knowledge is big and has many features. Several cloud-based IoT health providers have been described in the literature previously. Furthermore, there are a number of issues related to time consumed and overall network performance when it comes to big data information. In the existing method, less performed optimization algorithms were used for optimizing the data. In the proposed method, the Chaotic Cuckoo Optimization algorithm was used for feature selection, and Convolutional Support Vector Machine (CSVM) was used. The research presents a method for analyzing healthcare… More >

  • Open Access

    ARTICLE

    Manta Ray Foraging Optimization with Machine Learning Based Biomedical Data Classification

    Amal Al-Rasheed1, Jaber S. Alzahrani2, Majdy M. Eltahir3, Abdullah Mohamed4, Anwer Mustafa Hilal5,*, Abdelwahed Motwakel5, Abu Sarwar Zamani5, Mohamed I. Eldesouki6

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3275-3290, 2022, DOI:10.32604/cmc.2022.029823

    Abstract The biomedical data classification process has received significant attention in recent times due to a massive increase in the generation of healthcare data from various sources. The developments of artificial intelligence (AI) and machine learning (ML) models assist in the effectual design of medical data classification models. Therefore, this article concentrates on the development of optimal Stacked Long Short Term Memory Sequence-to-Sequence Autoencoder (OSAE-LSTM) model for biomedical data classification. The presented OSAE-LSTM model intends to classify the biomedical data for the existence of diseases. Primarily, the OSAE-LSTM model involves min-max normalization based pre-processing to scale the data into uniform format.… More >

  • Open Access

    ARTICLE

    An AOP-Based Security Verification Environment for KECCAK Hash Algorithm

    Hassen Mestiri1,2,3,*, Imen Barraj1,4,5, Mohsen Machhout3

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 4051-4066, 2022, DOI:10.32604/cmc.2022.029794

    Abstract Robustness of the electronic cryptographic devices against fault injection attacks is a great concern to ensure security. Due to significant resource constraints, these devices are limited in their capabilities. The increasing complexity of cryptographic devices necessitates the development of a fast simulation environment capable of performing security tests against fault injection attacks. SystemC is a good choice for Electronic System Level (ESL) modeling since it enables models to run at a faster rate. To enable fault injection and detection inside a SystemC cryptographic model, however, the model’s source code must be updated. Without altering the source code, Aspect-Oriented Programming (AOP)… More >

  • Open Access

    ARTICLE

    Aortic Dissection Diagnosis Based on Sequence Information and Deep Learning

    Haikuo Peng1, Yun Tan1,*, Hao Tang2, Ling Tan2, Xuyu Xiang1, Yongjun Wang2, Neal N. Xiong3

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2757-2771, 2022, DOI:10.32604/cmc.2022.029727

    Abstract Aortic dissection (AD) is one of the most serious diseases with high mortality, and its diagnosis mainly depends on computed tomography (CT) results. Most existing automatic diagnosis methods of AD are only suitable for AD recognition, which usually require preselection of CT images and cannot be further classified to different types. In this work, we constructed a dataset of 105 cases with a total of 49021 slices, including 31043 slices expert-level annotation and proposed a two-stage AD diagnosis structure based on sequence information and deep learning. The proposed region of interest (RoI) extraction algorithm based on sequence information (RESI) can… More >

  • Open Access

    ARTICLE

    Face Mask Recognition for Covid-19 Prevention

    Trong Hieu Luu1, Phan Nguyen Ky Phuc2,*, Zhiqiu Yu3, Duy Dung Pham1, Huu Trong Cao1

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3251-3262, 2022, DOI:10.32604/cmc.2022.029663

    Abstract In recent years, the COVID-19 pandemic has negatively impacted all aspects of social life. Due to ease in the infected method, i.e., through small liquid particles from the mouth or the nose when people cough, sneeze, speak, sing, or breathe, the virus can quickly spread and create severe problems for people’s health. According to some research as well as World Health Organization (WHO) recommendation, one of the most economical and effective methods to prevent the spread of the pandemic is to ask people to wear the face mask in the public space. A face mask will help prevent the droplet… More >

  • Open Access

    ARTICLE

    Research on the Design Method of Equipment in Service Assessment Subjects

    Jianhua Luo, Yuhang Zhou*, Hua Li, Xi Chen, Xigong Xia

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2473-2484, 2022, DOI:10.32604/cmc.2022.029640

    Abstract Combined with equipment activities such as combat readiness, training, exercises and management, it is proposed that the design of equipment in-service assessment subjects should follow the principles of combination, stage and operability. Focusing on the design of equipment in-service assessment subjects, a design method for in-service assessment subjects based on the combination of trial and training mode is proposed. Based on the actual use of high-equipment use management and training and the established indicator system, the army’s bottom-level equipment activity subjects and bottom-level assessments are combined. The indicators are mapped and analyzed. Through multiple rounds of iterations, the mapping relationship… 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

    Encryption Algorithm for Securing Non-Disclosure Agreements in Outsourcing Offshore Software Maintenance

    Atif Ikram1,2,*, Masita Abdul Jalil1, Amir Bin Ngah1, Nadeem Iqbal2, Nazri Kama4, Azri Azmi4, Ahmad Salman Khan3, Yasir Mahmood3,4, Assad Alzayed5

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3827-3845, 2022, DOI:10.32604/cmc.2022.029609

    Abstract Properly created and securely communicated, non-disclosure agreement (NDA) can resolve most of the common disputes related to outsourcing of offshore software maintenance (OSMO). Occasionally, these NDAs are in the form of images. Since the work is done offshore, these agreements or images must be shared through the Internet or stored over the cloud. The breach of privacy, on the other hand, is a potential threat for the image owners as both the Internet and cloud servers are not void of danger. This article proposes a novel algorithm for securing the NDAs in the form of images. As an agreement is… More >

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