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  • Open Access

    ARTICLE

    Methods and Means for Small Dynamic Objects Recognition and Tracking

    Dmytro Kushnir*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3649-3665, 2022, DOI:10.32604/cmc.2022.030016

    Abstract A literature analysis has shown that object search, recognition, and tracking systems are becoming increasingly popular. However, such systems do not achieve high practical results in analyzing small moving living objects ranging from 8 to 14 mm. This article examines methods and tools for recognizing and tracking the class of small moving objects, such as ants. To fulfill those aims, a customized You Only Look Once Ants Recognition (YOLO_AR) Convolutional Neural Network (CNN) has been trained to recognize Messor Structor ants in the laboratory using the LabelImg object marker tool. The proposed model is an extension of the You Only… More >

  • Open Access

    ARTICLE

    Automatic Botnet Attack Identification Based on Machine Learning

    Peng Hui Li1, Jie Xu1,*, Zhong Yi Xu1, Su Chen1, Bo Wei Niu2, Jie Yin1, Xiao Feng Sun1, Hao Liang Lan1, Lu Lu Chen3

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3847-3860, 2022, DOI:10.32604/cmc.2022.029969

    Abstract At present, the severe network security situation has put forward high requirements for network security defense technology. In order to automate botnet threat warning, this paper researches the types and characteristics of Botnet. Botnet has special characteristics in attributes such as packets, attack time interval, and packet size. In this paper, the attack data is annotated by means of string recognition and expert screening. The attack features are extracted from the labeled attack data, and then use K-means for cluster analysis. The clustering results show that the same attack data has its unique characteristics, and the automatic identification of network… More >

  • Open Access

    ARTICLE

    Multi-Mode Frequency Reconfigurable Conformal Antenna for Modern Electronic Systems

    Abir Zaidi1, Esraa Mousa Ali2, Abdullah G. Alharbi3, Salah Ud-Din Khan4, Mohammad Alsharef5, Mohammed S. Alzaidi5, Sherif S. M. Ghoneim5,*

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3861-3877, 2022, DOI:10.32604/cmc.2022.029889

    Abstract The article presents a miniaturized monopole antenna dedicated to modern flexible electronic systems. The antenna combines three fundamental properties in a single structure. Firstly, it is characterized by a compact size compared to the state-of-the-art literature with an overall size of 18 × 18 × 0.254 mm3, secondly, the proposed antenna integrates the reconfigurability function of frequency, produced by means of a Positive-Intrinsic-Negative (PIN) diode introduced into the radiating element. Thus, the antenna is able to switch between different frequencies and different modes, making it suitable to meet the ever-changing demands of communication systems. third, the antenna is equipped by the property of flexibility.… More >

  • 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 >

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