Home / Journals / CMC / Vol.72, No.2, 2022
Special lssues
Table of Content
  • Open AccessOpen Access

    ARTICLE

    Metaheuristic Lightweight Cryptography for Security Enhancement inInternet of Things

    Mahmoud Ragab1,2,3,*, Ehab Bahaudien Ashary4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3009-3023, 2022, DOI:10.32604/cmc.2022.025763
    Abstract The advancements made in Internet of Things (IoT) is projected to alter the functioning of healthcare industry in addition to increased penetration of different applications. However, data security and private are challenging tasks to accomplish in IoT and necessary measures to be taken to ensure secure operation. With this background, the current paper proposes a novel lightweight cryptography method for enhance the security in IoT. The proposed encryption algorithm is a blend of Cross Correlation Coefficient (CCC) and Black Widow Optimization (BWO) algorithm. In the presented encryption technique, CCC operation is utilized to optimize the encryption process of cryptography method.… More >

  • Open AccessOpen Access

    ARTICLE

    Secret Key Optimization for Secure Speech Communications

    Osama S. Faragallah1,*, Mahmoud Farouk2, Hala S. El-Sayed3
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3025-3037, 2022, DOI:10.32604/cmc.2022.019951
    Abstract This paper answers three essential questions for audio speech cryptosystems in time and discrete transform domains. The first question is, what are the best values of sub-keys that must be used to get the best quality and security for the audio cryptosystem in time and discrete transform domains. The second question is the relation between the number of sub-keys, the number of secret keys used, and the audio speech signal block’s size. Finally, how many possible secret keys can be used to get the best quality and security results for the audio speech cryptosystem in time and discrete transform domains.… More >

  • Open AccessOpen Access

    ARTICLE

    Sammon Quadratic Recurrent Multilayer Deep Classifier for Legal Document Analytics

    Divya Mohan*, Latha Ravindran Nair
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3039-3053, 2022, DOI:10.32604/cmc.2022.024438
    Abstract In recent years, machine learning algorithms and in particular deep learning has shown promising results when used in the field of legal domain. The legal field is strongly affected by the problem of information overload, due to the large amount of legal material stored in textual form. Legal text processing is essential in the legal domain to analyze the texts of the court events to automatically predict smart decisions. With an increasing number of digitally available documents, legal text processing is essential to analyze documents which helps to automate various legal domain tasks. Legal document classification is a valuable tool… More >

  • Open AccessOpen Access

    ARTICLE

    Optimal Bidirectional LSTM for Modulation Signal Classification in Communication Systems

    Manar Ahmed Hamza1,*, Siwar Ben Haj Hassine2, Souad Larabi-Marie-Sainte3, Mohamed K. Nour4, Fahd N. Al-Wesabi5,6, Abdelwahed Motwakel1, Anwer Mustafa Hilal1, Mesfer Al Duhayyim7
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3055-3071, 2022, DOI:10.32604/cmc.2022.024490
    Abstract Modulation signal classification in communication systems can be considered a pattern recognition problem. Earlier works have focused on several feature extraction approaches such as fractal feature, signal constellation reconstruction, etc. The recent advent of deep learning (DL) models makes it possible to proficiently classify the modulation signals. In this view, this study designs a chaotic oppositional satin bowerbird optimization (COSBO) with bidirectional long term memory (BiLSTM) model for modulation signal classification in communication systems. The proposed COSBO-BiLSTM technique aims to classify the different kinds of digitally modulated signals. In addition, the fractal feature extraction process takes place by the use… More >

  • Open AccessOpen Access

    ARTICLE

    Fuzzy Hybrid Coyote Optimization Algorithm for Image Thresholding

    Linguo Li1,2, Xuwen Huang2, Shunqiang Qian2, Zhangfei Li2, Shujing Li2,*, Romany F. Mansour3
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3073-3090, 2022, DOI:10.32604/cmc.2022.026625
    Abstract In order to address the problems of Coyote Optimization Algorithm in image thresholding, such as easily falling into local optimum, and slow convergence speed, a Fuzzy Hybrid Coyote Optimization Algorithm (hereinafter referred to as FHCOA) based on chaotic initialization and reverse learning strategy is proposed, and its effect on image thresholding is verified. Through chaotic initialization, the random number initialization mode in the standard coyote optimization algorithm (COA) is replaced by chaotic sequence. Such sequence is nonlinear and long-term unpredictable, these characteristics can effectively improve the diversity of the population in the optimization algorithm. Therefore, in this paper we first… More >

  • Open AccessOpen Access

    ARTICLE

    VPN and Non-VPN Network Traffic Classification Using Time-Related Features

    Mustafa Al-Fayoumi1, Mohammad Al-Fawa’reh2, Shadi Nashwan3,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3091-3111, 2022, DOI:10.32604/cmc.2022.025103
    Abstract The continual growth of the use of technological appliances during the COVID-19 pandemic has resulted in a massive volume of data flow on the Internet, as many employees have transitioned to working from home. Furthermore, with the increase in the adoption of encrypted data transmission by many people who tend to use a Virtual Private Network (VPN) or Tor Browser (dark web) to keep their data privacy and hidden, network traffic encryption is rapidly becoming a universal approach. This affects and complicates the quality of service (QoS), traffic monitoring, and network security provided by Internet Service Providers (ISPs), particularly for… More >

  • Open AccessOpen Access

    ARTICLE

    Analysis and Assessment of Wind Energy Potential of Almukalla in Yemen

    Murad A. A. Almekhlafi1, Fahd N. Al-Wesabi2,3, Majdy M. Eltahir4, Anwer Mustafa Hilal5, Amin M. El-Kustaban6, Abdelwahed Motwakel5, Ishfaq Yaseen5, Manar Ahmed Hamza5,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3113-3129, 2022, DOI:10.32604/cmc.2022.024355
    Abstract Energy is an essential element for any civilized country's social and economic development, but the use of fossil fuels and nonrenewable energy forms has many negative impacts on the environment and the ecosystem. The Republic of Yemen has very good potential to use renewable energy. Unfortunately, we find few studies on renewable wind energy in Yemen. Given the lack of a similar analysis for the coastal city, this research newly investigates wind energy's potential near the Almukalla area by analyzing wind characteristics. Thus, evaluation, model identification, determination of available energy density, computing the capacity factors for several wind turbines and… More >

  • Open AccessOpen Access

    ARTICLE

    Artificial Intelligence Techniques Based Learner Authentication in Cybersecurity Higher Education Institutions

    Abdullah Saad AL-Malaise AL-Ghamdi1, Mahmoud Ragab2,3,4,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3131-3144, 2022, DOI:10.32604/cmc.2022.026457
    Abstract Education 4.0 is being authorized more and more by the design of artificial intelligence (AI) techniques. Higher education institutions (HEI) have started to utilize Internet technologies to improve the quality of the service and boost knowledge. Due to the unavailability of information technology (IT) infrastructures, HEI is vulnerable to cyberattacks. Biometric authentication can be used to authenticate a person based on biological features such as face, fingerprint, iris, and so on. This study designs a novel search and rescue optimization with deep learning based learning authentication technique for cybersecurity in higher education institutions, named SRODL-LAC technique. The proposed SRODL-LAC technique… More >

  • Open AccessOpen Access

    ARTICLE

    Deep Learning Framework for Classification of Emoji Based Sentiments

    Nighat Parveen Shaikh*, Mumtaz Hussain Mahar
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3145-3158, 2022, DOI:10.32604/cmc.2022.024843
    Abstract Recent patterns of human sentiments are highly influenced by emoji based sentiments (EBS). Social media users are widely using emoji based sentiments (EBS) in between text messages, tweets and posts. Although tiny pictures of emoji contains sufficient information to be considered for construction of classification model; but due to the wide range of dissimilar, heterogynous and complex patterns of emoji with similar meanings (SM) have become one of the significant research areas of machine vision. This paper proposes an approach to provide meticulous assistance to social media application (SMA) users to classify the EBS sentiments. Proposed methodology consists upon three… More >

  • Open AccessOpen Access

    ARTICLE

    Safety Helmet Wearing Detection in Aerial Images Using Improved YOLOv4

    Wei Chen1, Mi Liu1,*, Xuhong Zhou2, Jiandong Pan3, Haozhi Tan4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3159-3174, 2022, DOI:10.32604/cmc.2022.026664
    Abstract In construction, it is important to check whether workers wear safety helmets in real time. We proposed using an unmanned aerial vehicle (UAV) to monitor construction workers in real time. As the small target of aerial photography poses challenges to safety-helmet-wearing detection, we proposed an improved YOLOv4 model to detect the helmet-wearing condition in aerial photography: (1) By increasing the dimension of the effective feature layer of the backbone network, the model's receptive field is reduced, and the utilization rate of fine-grained features is improved. (2) By introducing the cross stage partial (CSP) structure into path aggregation network (PANet), the… More >

  • Open AccessOpen Access

    ARTICLE

    An Eco-Friendly Approach for Reducing Carbon Emissions in Cloud Data Centers

    Mohammad Aldossary1,*, Hatem A. Alharbi2
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3175-3193, 2022, DOI:10.32604/cmc.2022.026041
    Abstract Based on the Saudi Green initiative, which aims to improve the Kingdom's environmental status and reduce the carbon emission of more than 278 million tons by 2030 along with a promising plan to achieve net-zero carbon by 2060, NEOM city has been proposed to be the “Saudi hub” for green energy, since NEOM is estimated to generate up to 120 Gigawatts (GW) of renewable energy by 2030. Nevertheless, the Information and Communication Technology (ICT) sector is considered a key contributor to global energy consumption and carbon emissions. The data centers are estimated to consume about 13% of the overall global… More >

  • Open AccessOpen Access

    ARTICLE

    Heart Disease Diagnosis Using the Brute Force Algorithm and Machine Learning Techniques

    Junaid Rashid1, Samina Kanwal2, Jungeun Kim1,*, Muhammad Wasif Nisar2, Usman Naseem3, Amir Hussain4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3195-3211, 2022, DOI:10.32604/cmc.2022.026064
    Abstract Heart disease is one of the leading causes of death in the world today. Prediction of heart disease is a prominent topic in the clinical data processing. To increase patient survival rates, early diagnosis of heart disease is an important field of research in the medical field. There are many studies on the prediction of heart disease, but limited work is done on the selection of features. The selection of features is one of the best techniques for the diagnosis of heart diseases. In this research paper, we find optimal features using the brute-force algorithm, and machine learning techniques are… More >

  • Open AccessOpen Access

    ARTICLE

    Bio-Inspired Numerical Analysis of COVID-19 with Fuzzy Parameters

    F. M. Allehiany1, Fazal Dayan2,3,*, F. F. Al-Harbi4, Nesreen Althobaiti5, Nauman Ahmed2, Muhammad Rafiq6, Ali Raza7, Mawahib Elamin8
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3213-3229, 2022, DOI:10.32604/cmc.2022.025811
    Abstract Fuzziness or uncertainties arise due to insufficient knowledge, experimental errors, operating conditions and parameters that provide inaccurate information. The concepts of susceptible, infectious and recovered are uncertain due to the different degrees in susceptibility, infectivity and recovery among the individuals of the population. The differences can arise, when the population groups under the consideration having distinct habits, customs and different age groups have different degrees of resistance, etc. More realistic models are needed which consider these different degrees of susceptibility infectivity and recovery of the individuals. In this paper, a Susceptible, Infected and Recovered (SIR) epidemic model with fuzzy parameters… More >

  • Open AccessOpen Access

    ARTICLE

    Solving Cauchy Issues of Highly Nonlinear Elliptic Equations Using a Meshless Method

    Chih-Wen Chang*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3231-3245, 2022, DOI:10.32604/cmc.2022.024563
    Abstract In this paper, we address 3D inverse Cauchy issues of highly nonlinear elliptic equations in large cuboids by utilizing the new 3D homogenization functions of different orders to adapt all the specified boundary data. We also add the average classification as an approximate solution to the nonlinear operator part, without requiring to cope with nonlinear equations to resolve the weighting coefficients because these constructions are owned many conditions about the true solution. The unknown boundary conditions and the result can be retrieved straightway by coping with a small-scale linear system when the outcome is described by a new 3D homogenization… More >

  • Open AccessOpen Access

    ARTICLE

    Interest Points Analysis for Internet Forum Based on Long-Short Windows Similarity

    Xinghai Ju1, Jicang Lu1,*, Xiangyang Luo1, Gang Zhou1, Shiyu Wang1, Shunhang Li1, Yang Yang2,3
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3247-3267, 2022, DOI:10.32604/cmc.2022.026698
    Abstract For Internet forum Points of Interest (PoI), existing analysis methods are usually lack of usability analysis under different conditions and ignore the long-term variation, which lead to blindness in method selection. To address this problem, this paper proposed a PoI variation prediction framework based on similarity analysis between long and short windows. Based on the framework, this paper presented 5 PoI analysis algorithms which can be categorized into 2 types, i.e., the traditional sequence analysis methods such as autoregressive integrated moving average model (ARIMA), support vector regressor (SVR), and the deep learning methods such as convolutional neural network (CNN), long-short… More >

  • Open AccessOpen Access

    ARTICLE

    Coyote Optimization Using Fuzzy System for Energy Efficiency in WSN

    Ahmed S. Almasoud1, Taiseer Abdalla Elfadil Eisa2, Marwa Obayya3, Abdelzahir Abdelmaboud4, Mesfer Al Duhayyim5, Ishfaq Yaseen6, Manar Ahmed Hamza6,*, Abdelwahed Motwakel6
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3269-3281, 2022, DOI:10.32604/cmc.2022.024584
    Abstract In recent days, internet of things is widely implemented in Wireless Sensor Network (WSN). It comprises of sensor hubs associated together through the WSNs. The WSN is generally affected by the power in battery due to the linked sensor nodes. In order to extend the lifespan of WSN, clustering techniques are used for the improvement of energy consumption. Clustering methods divide the nodes in WSN and form a cluster. Moreover, it consists of unique Cluster Head (CH) in each cluster. In the existing system, Soft-K means clustering techniques are used in energy consumption in WSN. The soft-k means algorithm does… More >

  • Open AccessOpen Access

    ARTICLE

    Flexible Memristive Devices Based on Graphene Quantum-Dot Nanocomposites

    Sung Won Hwang, Dae-Ki Hong*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3283-3297, 2022, DOI:10.32604/cmc.2022.025931
    Abstract Artificial neural networks (ANNs) are attracting attention for their high performance in various fields, because increasing the network size improves its functioning. Since large-scale neural networks are difficult to implement on custom hardware, a two-dimensional (2D) structure is applied to an ANN in the form of a crossbar. We demonstrate a synapse crossbar device from recent research by applying a memristive system to neuromorphic chips. The system is designed using two-dimensional structures, graphene quantum dots (GQDs) and graphene oxide (GO). Raman spectrum analysis results indicate a D-band of 1421 cm−1 that occurs in the disorder; band is expressed as an atomic… More >

  • Open AccessOpen Access

    ARTICLE

    DWT-SVD Based Image Steganography Using Threshold Value Encryption Method

    Jyoti Khandelwal1, Vijay Kumar Sharma1, Dilbag Singh2,*, Atef Zaguia3
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3299-3312, 2022, DOI:10.32604/cmc.2022.023116
    Abstract Digital image steganography technique based on hiding the secret data behind of cover image in such a way that it is not detected by the human visual system. This paper presents an image scrambling method that is very useful for grayscale secret images. In this method, the secret image decomposes in three parts based on the pixel's threshold value. The division of the color image into three parts is very easy based on the color channel but in the grayscale image, it is difficult to implement. The proposed image scrambling method is implemented in image steganography using discrete wavelet transform… More >

  • Open AccessOpen Access

    ARTICLE

    Scaled Dilation of DropBlock Optimization in Convolutional Neural Network for Fungus Classification

    Anuruk Prommakhot, Jakkree Srinonchat*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3313-3329, 2022, DOI:10.32604/cmc.2022.024417
    Abstract Image classification always has open challenges for computer vision research. Nowadays, deep learning has promoted the development of this field, especially in Convolutional Neural Networks (CNNs). This article proposes the development of efficiently scaled dilation of DropBlock optimization in CNNs for the fungus classification, which there are five species in this experiment. The proposed technique adjusts the convolution size at 35, 45, and 60 with the max-polling size 2 × 2. The CNNs models are also designed in 12 models with the different BlockSizes and KeepProp. The proposed techniques provide maximum accuracy of 98.30% for the training set. Moreover, three accurate models,… More >

  • Open AccessOpen Access

    ARTICLE

    Modeling and Verification of Aircraft Takeoff Through Novel Quantum Nets

    Maryam Jamal1, Nazir Ahmad Zafar2, Atta-ur-Rahman3,*, Dhiaa Musleh3, Mohammed A. Gollapalli4, Sghaier Chabani4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3331-3348, 2022, DOI:10.32604/cmc.2022.025205
    Abstract The formal modeling and verification of aircraft takeoff is a challenge because it is a complex safety-critical operation. The task of aircraft takeoff is distributed amongst various computer-based controllers, however, with the growing malicious threats a secure communication between aircraft and controllers becomes highly important. This research serves as a starting point for integration of BB84 quantum protocol with petri nets for secure modeling and verification of takeoff procedure. The integrated model combines the BB84 quantum cryptographic protocol with powerful verification tool support offered by petri nets. To model certain important properties of BB84, a new variant of petri nets… More >

  • Open AccessOpen Access

    ARTICLE

    Reversible Video Steganography Using Quick Response Codes and Modified ElGamal Cryptosystem

    Ramadhan J. Mstafa1,2,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3349-3368, 2022, DOI:10.32604/cmc.2022.025791
    Abstract The rapid transmission of multimedia information has been achieved mainly by recent advancements in the Internet's speed and information technology. In spite of this, advancements in technology have resulted in breaches of privacy and data security. When it comes to protecting private information in today's Internet era, digital steganography is vital. Many academics are interested in digital video because it has a great capability for concealing important data. There have been a vast number of video steganography solutions developed lately to guard against the theft of confidential data. The visual imperceptibility, robustness, and embedding capacity of these approaches are all… More >

  • Open AccessOpen Access

    ARTICLE

    Finger Vein Authentication Based on Wavelet Scattering Networks

    Amjad Rehman1, Majid Harouni2,*, Maedeh Omidiravesh3, Suliman Mohamed Fati1, Saeed Ali Bahaj4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3369-3383, 2022, DOI:10.32604/cmc.2022.016410
    Abstract Biometric-based authentication systems have attracted more attention than traditional authentication techniques such as passwords in the last two decades. Multiple biometrics such as fingerprint, palm, iris, palm vein and finger vein and other biometrics have been introduced. One of the challenges in biometrics is physical injury. Biometric of finger vein is of the biometrics least exposed to physical damage. Numerous methods have been proposed for authentication with the help of this biometric that suffer from weaknesses such as high computational complexity and low identification rate. This paper presents a novel method of scattering wavelet-based identity identification. Scattering wavelet extracts image… More >

  • Open AccessOpen Access

    ARTICLE

    Optimized Artificial Neural Network Techniques to Improve Cybersecurity of Higher Education Institution

    Abdullah Saad AL-Malaise AL-Ghamdi1, Mahmoud Ragab2,3,4,*, Maha Farouk S. Sabir1, Ahmed Elhassanein5,6, Ashraf A. Gouda4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3385-3399, 2022, DOI:10.32604/cmc.2022.026477
    Abstract Education acts as an important part of economic growth and improvement in human welfare. The educational sectors have transformed a lot in recent days, and Information and Communication Technology (ICT) is an effective part of the education field. Almost every action in university and college, right from the process from counselling to admissions and fee deposits has been automated. Attendance records, quiz, evaluation, mark, and grade submissions involved the utilization of the ICT. Therefore, security is essential to accomplish cybersecurity in higher security institutions (HEIs). In this view, this study develops an Automated Outlier Detection for CyberSecurity in Higher Education… More >

  • Open AccessOpen Access

    ARTICLE

    Ransomware Classification Framework Using the Behavioral Performance Visualization of Execution Objects

    Jun-Seob Kim, Ki-Woong Park*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3401-3424, 2022, DOI:10.32604/cmc.2022.026621
    Abstract A ransomware attack that interrupted the operation of Colonial Pipeline (a large U.S. oil pipeline company), showed that security threats by malware have become serious enough to affect industries and social infrastructure rather than individuals alone. The agents and characteristics of attacks should be identified, and appropriate strategies should be established accordingly in order to respond to such attacks. For this purpose, the first task that must be performed is malware classification. Malware creators are well aware of this and apply various concealment and avoidance techniques, making it difficult to classify malware. This study focuses on new features and classification… More >

  • Open AccessOpen Access

    ARTICLE

    Process Tolerant and Power Efficient SRAM Cell for Internet of Things Applications

    T. G. Sargunam1,2,*, Lim Way Soong1, C. M. R. Prabhu1, Ajay Kumar Singh3
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3425-3446, 2022, DOI:10.32604/cmc.2022.023452
    Abstract The use of Internet of Things (IoT) applications become dominant in many systems. Its on-chip data processing and computations are also increasing consistently. The battery enabled and low leakage memory system at subthreshold regime is a critical requirement for these IoT applications. The cache memory designed on Static Random-Access Memory (SRAM) cell with features such as low power, high speed, and process tolerance are highly important for the IoT memory system. Therefore, a process tolerant SRAM cell with low power, improved delay and better stability is presented in this research paper. The proposed cell comprises 11 transistors designed with symmetric… More >

  • Open AccessOpen Access

    ARTICLE

    Image Encryption Using Multi-Scroll Attractor and Chaotic Logistic Map

    R. Anitha*, B. Vijayalakshmi
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3447-3463, 2022, DOI:10.32604/cmc.2022.021519
    Abstract In the current scenario, data transmission over the network is a challenging task as there is a need for protecting sensitive data. Traditional encryption schemes are less sensitive and less complex thus prone to attacks during transmission. It has been observed that an encryption scheme using chaotic theory is more promising due to its non-linear and unpredictable behavior. Hence, proposed a novel hybrid image encryption scheme with multi-scroll attractors and quantum chaos logistic maps (MSA-QCLM). The image data is classified as inter-bits and intra-bits which are permutated separately using multi scroll attractor & quantum logistic maps to generate random keys.… More >

  • Open AccessOpen Access

    ARTICLE

    Sustainable Energy Management with Traffic Prediction Strategy for Autonomous Vehicle Systems

    Manar Ahmed Hamza1,*, Masoud Alajmi2, Jaber S. Alzahrani3, Siwar Ben Haj Hassine4, Abdelwahed Motwakel1, Ishfaq Yaseen1
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3465-3479, 2022, DOI:10.32604/cmc.2022.026066
    Abstract Recent advancements of the intelligent transportation system (ITS) provide an effective way of improving the overall efficiency of the energy management strategy (EMSs) for autonomous vehicles (AVs). The use of AVs possesses many advantages such as congestion control, accident prevention, and etc. However, energy management and traffic flow prediction (TFP) still remains a challenging problem in AVs. The complexity and uncertainties of driving situations adequately affect the outcome of the designed EMSs. In this view, this paper presents novel sustainable energy management with traffic flow prediction strategy (SEM-TPS) for AVs. The SEM-TPS technique applies type II fuzzy logic system (T2FLS)… More >

  • Open AccessOpen Access

    ARTICLE

    Metaheuristics Algorithm for Tuning of PID Controller of Mobile Robot System

    Harsh Goud1, Prakash Chandra Sharma2, Kashif Nisar3,7,*, Muhammad Reazul Haque4, Ag. Asri Ag. Ibrahim3, Narendra Singh Yadav2, Pankaj Swarnkar5, Manoj Gupta6, Laxmi Chand6
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3481-3492, 2022, DOI:10.32604/cmc.2022.019764
    Abstract Robots in the medical industry are becoming more common in daily life because of various advantages such as quick response, less human interference, high dependability, improved hygiene, and reduced aging effects. That is why, in recent years, robotic aid has emerged as a blossoming solution to many challenges in the medical industry. In this manuscript, meta-heuristics (MH) algorithms, specifically the Firefly Algorithm (FF) and Genetic Algorithm (GA), are applied to tune PID controller constraints such as Proportional gain Kp Integral gain Ki and Derivative gain Kd. The controller is used to control Mobile Robot System (MRS) at the required set… More >

  • Open AccessOpen Access

    ARTICLE

    Dynamic Vehicular Clustering Enhancing Video on Demand Services Over Vehicular Ad-hoc Networks

    M. Almutiq1, L. Sellami1,2,*, B. Alaya1,3
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3493-3510, 2022, DOI:10.32604/cmc.2022.024571
    Abstract Nowadays, video streaming applications are becoming one of the tendencies driving vehicular network users. In this work, considering the unpredictable vehicle density, the unexpected acceleration or deceleration of the different vehicles included in the vehicular traffic load, and the limited radio range of the employed communication scheme, we introduce the “Dynamic Vehicular Clustering” (DVC) algorithm as a new scheme for video streaming systems over vehicular ad-hoc networks (VANET). The proposed algorithm takes advantage of the small cells concept and the introduction of wireless backhauls, inspired by the different features and the performance of the Long Term Evolution (LTE)-Advanced network. Vehicles… More >

  • Open AccessOpen Access

    ARTICLE

    Detection of Lung Tumor Using ASPP-Unet with Whale Optimization Algorithm

    Mimouna Abdullah Alkhonaini1, Siwar Ben Haj Hassine2, Marwa Obayya3, Fahd N. Al-Wesabi2, Anwer Mustafa Hilal4,*, Manar Ahmed Hamza4, Abdelwahed Motwakel4, Mesfer Al Duhayyim5
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3511-3527, 2022, DOI:10.32604/cmc.2022.024583
    Abstract The unstructured growth of abnormal cells in the lung tissue creates tumor. The early detection of lung tumor helps the patients avoiding the death rate and gives better treatment. Various medical image modalities can help the physicians in the diagnosis of disease. Many research works have been proposed for the early detection of lung tumor. High computation time and misidentification of tumor are the prevailing issues. In order to overcome these issues, this paper has proposed a hybrid classifier of Atrous Spatial Pyramid Pooling (ASPP)-Unet architecture with Whale Optimization Algorithm (ASPP-Unet -WOA). To get a fine tuning detection of tumor… More >

  • Open AccessOpen Access

    ARTICLE

    An Efficient Intrusion Detection Framework in Software-Defined Networking for Cybersecurity Applications

    Ghalib H. Alshammri1,2, Amani K. Samha3, Ezz El-Din Hemdan4, Mohammed Amoon1,4, Walid El-Shafai5,6,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3529-3548, 2022, DOI:10.32604/cmc.2022.025262
    Abstract Network management and multimedia data mining techniques have a great interest in analyzing and improving the network traffic process. In recent times, the most complex task in Software Defined Network (SDN) is security, which is based on a centralized, programmable controller. Therefore, monitoring network traffic is significant for identifying and revealing intrusion abnormalities in the SDN environment. Consequently, this paper provides an extensive analysis and investigation of the NSL-KDD dataset using five different clustering algorithms: K-means, Farthest First, Canopy, Density-based algorithm, and Exception-maximization (EM), using the Waikato Environment for Knowledge Analysis (WEKA) software to compare extensively between these five algorithms.… More >

  • Open AccessOpen Access

    ARTICLE

    Blockchain-Based Robust Data Security Scheme in IoT-Enabled Smart Home

    Anusha Vangala1, Ashok Kumar Das1, YoungHo Park2,*, Sajjad Shaukat Jamal3
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3549-3570, 2022, DOI:10.32604/cmc.2022.025660
    Abstract The recent surge in development of smart homes and smart cities can be observed in many developed countries. While the idea to control devices that are in home (embedded with the Internet of Things (IoT) smart devices) by the user who is outside the home might sound fancy, but it comes with a lot of potential threats. There can be many attackers who will be trying to take advantage of this. So, there is a need for designing a secure scheme which will be able to distinguish among genuine/authorized users of the system and attackers. And knowing about the details… More >

  • Open AccessOpen Access

    ARTICLE

    A Fast Algorithm for Mining Top-Rank-k Erasable Closed Patterns

    Ham Nguyen1, Tuong Le2,3,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3571-3583, 2022, DOI:10.32604/cmc.2022.024765
    Abstract The task of mining erasable patterns (EPs) is a data mining problem that can help factory managers come up with the best product plans for the future. This problem has been studied by many scientists in recent times, and many approaches for mining EPs have been proposed. Erasable closed patterns (ECPs) are an abbreviated representation of EPs and can be considered condensed representations of EPs without information loss. Current methods of mining ECPs identify huge numbers of such patterns, whereas intelligent systems only need a small number. A ranking process therefore needs to be applied prior to use, which causes… More >

  • Open AccessOpen Access

    ARTICLE

    Design of Energy Efficient WSN Using a Noble SMOWA Algorithm

    Avishek Banerjee1, Deepak Garg1, Victor Das2, Laxminarayan Sahoo3, Ira Nath4, Vijayakumar Varadarajan5, Ketan Kotecha6,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3585-3600, 2022, DOI:10.32604/cmc.2022.025233
    Abstract In this paper, the establishment of efficient Wireless Sensor Network (WSN) networks has been projected to minimize the consumption of energy using a new Self-adaptive Multi-Objective Weighted Approach (SMOWA) algorithm for solving a multi-objective problem. The Different WSN nodes deployment policies have been proposed and applied in this paper to design an efficient Wireless Sensor Network to minimize energy consumption. After that, the cluster head for each cluster has been selected with the help of the duty cycle. After configuring the WSN networks, the SMOWA algorithms have been developed to obtain the minimum energy consumption for the networks. Energy minimization,… More >

  • Open AccessOpen Access

    ARTICLE

    5G Antenna Gain Enhancement Using a Novel Metasurface

    Mubashir Ashfaq1, Shahid Bashir1,*, Syed Imran Hussain Shah2, Nisar Ahmad Abbasi3, Hatem Rmili4,5, Muhammad Abbas Khan6
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3601-3611, 2022, DOI:10.32604/cmc.2022.025558
    Abstract This article presents a Sub-6 GHz microstrip patch antenna (MPA) with enhanced gain using metamaterial (MTM) superstrate. The source MPA operates at 4.8 GHz and has a peak gain of 5.3 dBi at the resonance frequency. A window-shaped unit cell is designed and investigated through the material wave propagation technique. The unit cell shows an Epsilon Near Zero (ENZ)-Mu Very Large (MVL) behavior around 4.8 GHz. The unit cell has a fourfold geometry which makes it a polarization independent metamaterial. A double layer antenna is designed by placing a 4 × 4 MTM slab as a superstrate above the MPA at a… More >

  • Open AccessOpen Access

    ARTICLE

    Selecting Best Software Vulnerability Scanner Using Intuitionistic Fuzzy Set TOPSIS

    Navneet Bhatt1, Jasmine Kaur2, Adarsh Anand2, Omar H. Alhazmi3,*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3613-3629, 2022, DOI:10.32604/cmc.2022.026554
    Abstract Software developers endeavor to build their products with the least number of bugs. Despite this, many vulnerabilities are detected in software that threatens its integrity. Various automated software i.e., vulnerability scanners, are available in the market which helps detect and manage vulnerabilities in a computer, application, or a network. Hence, the choice of an appropriate vulnerability scanner is crucial to ensure efficient vulnerability management. The current work serves a dual purpose, first, to identify the key factors which affect the vulnerability discovery process in a network. The second, is to rank the popular vulnerability scanners based on the identified attributes.… More >

  • Open AccessOpen Access

    ARTICLE

    AI-based Automated Extraction of Location-Oriented COVID-19 Sentiments

    Fahim K. Sufi1,*, Musleh Alsulami2
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3631-3649, 2022, DOI:10.32604/cmc.2022.026272
    Abstract The coronavirus disease (COVID-19) pandemic has affected the lives of social media users in an unprecedented manner. They are constantly posting their satisfaction or dissatisfaction over the COVID-19 situation at their location of interest. Therefore, understanding location-oriented sentiments about this situation is of prime importance for political leaders, and strategic decision-makers. To this end, we present a new fully automated algorithm based on artificial intelligence (AI), for extraction of location-oriented public sentiments on the COVID-19 situation. We designed the proposed system to obtain exhaustive knowledge and insights on social media feeds related to COVID-19 in 110 languages through AI-based translation,… More >

  • Open AccessOpen Access

    ARTICLE

    Opto-Video Encryption Based on Logistic Adjusted Sine map in FrFT

    Osama S. Faragallah1,*, Ashraf Afifi1, Ibrahim F. Elashry2, Ensherah A. Naeem3, Heba M. El-Hoseny4, Ahmed I. Sallam5, Hala S. El-sayed6
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3651-3663, 2022, DOI:10.32604/cmc.2022.019827
    Abstract In the last few years, videos became the most common form of information transmitted over the internet, and a lot of the traffic is confidential and must be protected and delivered safely to its intended users. This introduces the challenges of presenting encryption systems that can encode videos securely and efficiently at the same time. This paper presents an efficient opto-video encryption system using Logistic Adjusted Sine map (LASM) in the Fractional Fourier Transform (FrFT). In the presented opto-video LASM-based FrFT scheme, the encoded video is split into distinct frames and transformed into optical signals utilizing an optical supply. Each… More >

  • Open AccessOpen Access

    ARTICLE

    Slicing-Based Enhanced Method for Privacy-Preserving in Publishing Big Data

    Mohammed BinJubier1, Mohd Arfian Ismail1, Abdulghani Ali Ahmed2,*, Ali Safaa Sadiq3
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3665-3686, 2022, DOI:10.32604/cmc.2022.024663
    Abstract Publishing big data and making it accessible to researchers is important for knowledge building as it helps in applying highly efficient methods to plan, conduct, and assess scientific research. However, publishing and processing big data poses a privacy concern related to protecting individuals’ sensitive information while maintaining the usability of the published data. Several anonymization methods, such as slicing and merging, have been designed as solutions to the privacy concerns for publishing big data. However, the major drawback of merging and slicing is the random permutation procedure, which does not always guarantee complete protection against attribute or membership disclosure. Moreover,… More >

  • Open AccessOpen Access

    ARTICLE

    Cancellable Multi-Biometric Template Generation Based on Arnold Cat Map and Aliasing

    Ahmed M. Ayoup1,*, Ashraf A. M. Khalaf1, Walid El-Shafai2,3, Fathi E. Abd El-Samie2, Fahad Alraddady4, Salwa M. Serag Eldin4,5
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3687-3703, 2022, DOI:10.32604/cmc.2022.025902
    Abstract The cancellable biometric transformations are designed to be computationally difficult to obtain the original biometric data. This paper presents a cancellable multi-biometric identification scheme that includes four stages: biometric data collection and processing, Arnold's Cat Map encryption, decimation process to reduce the size, and final merging of the four biometrics in a single generated template. First, a 2D matrix of size 128 × 128 is created based on Arnold's Cat Map (ACM). The purpose of this rearrangement is to break the correlation between pixels to hide the biometric patterns and merge these patterns together for more security. The decimation is performed to… More >

  • Open AccessOpen Access

    ARTICLE

    A Deep Learning Approach for Prediction of Protein Secondary Structure

    Muhammad Zubair1, Muhammad Kashif Hanif1,*, Eatedal Alabdulkreem2, Yazeed Ghadi3, Muhammad Irfan Khan1, Muhammad Umer Sarwar1, Ayesha Hanif1
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3705-3718, 2022, DOI:10.32604/cmc.2022.026408
    Abstract The secondary structure of a protein is critical for establishing a link between the protein primary and tertiary structures. For this reason, it is important to design methods for accurate protein secondary structure prediction. Most of the existing computational techniques for protein structural and functional prediction are based on machine learning with shallow frameworks. Different deep learning architectures have already been applied to tackle protein secondary structure prediction problem. In this study, deep learning based models, i.e., convolutional neural network and long short-term memory for protein secondary structure prediction were proposed. The input to proposed models is amino acid sequences… More >

  • Open AccessOpen Access

    ARTICLE

    Improving Association Rules Accuracy in Noisy Domains Using Instance Reduction Techniques

    Mousa Al-Akhras1,2,*, Zainab Darwish2, Samer Atawneh1, Mohamed Habib1,3
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3719-3749, 2022, DOI:10.32604/cmc.2022.025196
    Abstract Association rules’ learning is a machine learning method used in finding underlying associations in large datasets. Whether intentionally or unintentionally present, noise in training instances causes overfitting while building the classifier and negatively impacts classification accuracy. This paper uses instance reduction techniques for the datasets before mining the association rules and building the classifier. Instance reduction techniques were originally developed to reduce memory requirements in instance-based learning. This paper utilizes them to remove noise from the dataset before training the association rules classifier. Extensive experiments were conducted to assess the accuracy of association rules with different instance reduction techniques, namely:… More >

  • Open AccessOpen Access

    ARTICLE

    Genetic Based Approach for Optimal Power and Channel Allocation to Enhance D2D Underlaied Cellular Network Capacity in 5G

    Ahmed. A. Rosas*, Mona Shokair, M. I. Dessouky
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3751-3762, 2022, DOI:10.32604/cmc.2022.025226
    Abstract With the obvious throughput shortage in traditional cellular radio networks, Device-to-Device (D2D) communications has gained a lot of attention to improve the utilization, capacity and channel performance of next-generation networks. In this paper, we study a joint consideration of power and channel allocation based on genetic algorithm as a promising direction to expand the overall network capacity for D2D underlaied cellular networks. The genetic based algorithm targets allocating more suitable channels to D2D users and finding the optimal transmit powers for all D2D links and cellular users efficiently, aiming to maximize the overall system throughput of D2D underlaied cellular network… More >

  • Open AccessOpen Access

    ARTICLE

    Hybrid Deep Learning Enabled Intrusion Detection in Clustered IIoT Environment

    Radwa Marzouk1, Fadwa Alrowais2, Noha Negm3, Mimouna Abdullah Alkhonaini4, Manar Ahmed Hamza5,*, Mohammed Rizwanullah5, Ishfaq Yaseen5, Abdelwahed Motwakel5
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3763-3775, 2022, DOI:10.32604/cmc.2022.027483
    Abstract Industrial Internet of Things (IIoT) is an emerging field which connects digital equipment as well as services to physical systems. Intrusion detection systems (IDS) can be designed to protect the system from intrusions or attacks. In this view, this paper presents a novel hybrid deep learning with metaheuristics enabled intrusion detection (HDL-MEID) technique for clustered IIoT environments. The HDL-MEID model mainly intends to organize the IIoT devices into clusters and enabled secure communication. Primarily, the HDL-MEID technique designs a new chaotic mayfly optimization (CMFO) based clustering approach for the effective choice of the Cluster Heads (CH) and organize clusters. Moreover,… More >

  • Open AccessOpen Access

    ARTICLE

    An Interpretable Artificial Intelligence Based Smart Agriculture System

    Fariza Sabrina1,*, Shaleeza Sohail2, Farnaz Farid3, Sayka Jahan4, Farhad Ahamed5, Steven Gordon6
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3777-3797, 2022, DOI:10.32604/cmc.2022.026363
    Abstract With increasing world population the demand of food production has increased exponentially. Internet of Things (IoT) based smart agriculture system can play a vital role in optimising crop yield by managing crop requirements in real-time. Interpretability can be an important factor to make such systems trusted and easily adopted by farmers. In this paper, we propose a novel artificial intelligence-based agriculture system that uses IoT data to monitor the environment and alerts farmers to take the required actions for maintaining ideal conditions for crop production. The strength of the proposed system is in its interpretability which makes it easy for… More >

  • Open AccessOpen Access

    ARTICLE

    Artificial Intelligence Based Prostate Cancer Classification Model Using Biomedical Images

    Areej A. Malibari1, Reem Alshahrani2, Fahd N. Al-Wesabi3,*, Siwar Ben Haj Hassine3, Mimouna Abdullah Alkhonaini4, Anwer Mustafa Hilal5
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3799-3813, 2022, DOI:10.32604/cmc.2022.026131
    Abstract Medical image processing becomes a hot research topic in healthcare sector for effective decision making and diagnoses of diseases. Magnetic resonance imaging (MRI) is a widely utilized tool for the classification and detection of prostate cancer. Since the manual screening process of prostate cancer is difficult, automated diagnostic methods become essential. This study develops a novel Deep Learning based Prostate Cancer Classification (DTL-PSCC) model using MRI images. The presented DTL-PSCC technique encompasses EfficientNet based feature extractor for the generation of a set of feature vectors. In addition, the fuzzy k-nearest neighbour (FKNN) model is utilized for classification process where the… More >

  • Open AccessOpen Access

    ARTICLE

    Optimized Image Multiplication with Approximate Counter Based Compressor

    M. Maria Dominic Savio1,*, T. Deepa1, N. Bharathiraja2, Anudeep Bonasu3
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3815-3834, 2022, DOI:10.32604/cmc.2022.025924
    Abstract The processor is greatly hampered by the large dataset of picture or multimedia data. The logic of approximation hardware is moving in the direction of multimedia processing with a given amount of acceptable mistake. This study proposes various higher-order approximate counter-based compressor (CBC) using input shuffled 6:3 CBC. In the Wallace multiplier using a CBC is a significant factor in partial product reduction. So the design of 10-4, 11-4, 12-4, 13-4 and 14-4 CBC are proposed in this paper using an input shuffled 6:3 compressor to attain two stage multiplications. The input shuffling aims to reduce the output combination of… More >

  • Open AccessOpen Access

    ARTICLE

    Wavelet Based Detection of Outliers in Volatility Time Series Models

    Khudhayr A. Rashedi1,2,*, Mohd Tahir Ismail1, Abdeslam Serroukh3, S. Al wadi4
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3835-3847, 2022, DOI:10.32604/cmc.2022.026476
    Abstract We introduce a new wavelet based procedure for detecting outliers in financial discrete time series. The procedure focuses on the analysis of residuals obtained from a model fit, and applied to the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) like model, but not limited to these models. We apply the Maximal-Overlap Discrete Wavelet Transform (MODWT) to the residuals and compare their wavelet coefficients against quantile thresholds to detect outliers. Our methodology has several advantages over existing methods that make use of the standard Discrete Wavelet Transform (DWT). The series sample size does not need to be a power of 2 and the… More >

  • Open AccessOpen Access

    ARTICLE

    Developing Check-Point Mechanism to Protect Mobile Agent Free-Roaming Against Untrusted Hosts

    Tarig Mohamed Ahmed*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3849-3862, 2022, DOI:10.32604/cmc.2022.025582
    Abstract Mobile Agent has many benefits over traditional distributed systems such as reducing latency, bandwidth, and costs. Mobile Agent Systems are not fully utilized due to security problems. This paper focuses on mobile agent protection against malicious hosts. A new security mechanism called Checkpoints has been proposed. Checkpoint Mechanism (CPM) aims to protect Mobile Agent against malicious hosts in case of Capturing and Integrity attacks. CPM assumes using a free-roaming mobility mechanism by Mobile agent systems. The main idea behind CPM is to generate multiple versions of Mobile Agent. The multiple version is used to recover Mobile Agent from Capturing and… More >

  • Open AccessOpen Access

    ARTICLE

    Enhance Vertical Handover Security During Execution Phase in Mobile Networks

    Omar Khattab*
    CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3863-3875, 2022, DOI:10.32604/cmc.2022.026102
    Abstract The Vertical Handover (VHO) is one of the most vital features provided for the heterogeneous mobile networks. It allows Mobile Users (MUs) to keep ongoing sessions without disruption while they continuously move between different Radio Access Technologies (RATs) such as Wireless Fidelity (Wi-Fi), Global System for Mobile Communication (GSM), Universal Mobile Telecommunications System (UMTS), Long Term Evolution (LTE) and Fifth Generation (5G). In order to fulfill this goal, the VHO must comply to three main phases: starting of collecting the required information and then passing it for decision phase to obtain the best available RAT for performing VHO by execution… More >

Per Page:

Share Link