Home / Journals / CMC / Vol.71, No.1, 2022
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  • Open AccessOpen Access

    ARTICLE

    A Hybrid Deep Learning Scheme for Multi-Channel Sleep Stage Classification

    Wei Pei1, Yan Li1, Siuly Siuly1,*, Peng Wen2
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 889-905, 2022, DOI:10.32604/cmc.2022.021830
    (This article belongs to this Special Issue: Advances in Artificial Intelligence and Machine learning in Biomedical and Healthcare Informatics)
    Abstract Sleep stage classification plays a significant role in the accurate diagnosis and treatment of sleep-related diseases. This study aims to develop an efficient deep learning based scheme for correctly identifying sleep stages using multi-biological signals such as electroencephalography (EEG), electrocardiogram (ECG), electromyogram (EMG), and electrooculogram (EOG). Most of the prior studies in sleep stage classification focus on hand-crafted feature extraction methods. Traditional hand-crafted feature extraction methods choose features manually from raw data, which is tedious, and these features are limited in their ability to balance efficiency and accuracy. Moreover, most of the existing works on sleep staging are either single… More >

  • Open AccessOpen Access

    ARTICLE

    Clustering Indoor Location Data for Social Distancing and Human Mobility to Combat COVID-19

    Yuan Ai Ho1, Chee Keong Tan1,*, Yin Hoe Ng2
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 907-924, 2022, DOI:10.32604/cmc.2022.021756
    (This article belongs to this Special Issue: Application of Artificial Intelligence, Internet of Things, and Learning Approach for Learning Process in COVID-19/Industrial Revolution 4.0)
    Abstract The world is experiencing the unprecedented time of a pandemic caused by the coronavirus disease (i.e., COVID-19). As a countermeasure, contact tracing and social distancing are essential to prevent the transmission of the virus, which can be achieved using indoor location analytics. Based on the indoor location analytics, the human mobility on a site can be monitored and planned to minimize human’s contact and enforce social distancing to contain the transmission of COVID-19. Given the indoor location data, the clustering can be applied to cluster spatial data, spatio-temporal data and movement behavior features for proximity detection or contact tracing applications.… More >

  • Open AccessOpen Access

    ARTICLE

    Identification of Anomalous Behavioral Patterns in Crowd Scenes

    Muhammad Asif Nauman*, Muhammad Shoaib
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 925-939, 2022, DOI:10.32604/cmc.2022.022147
    Abstract Real time crowd anomaly detection and analyses has become an active and challenging area of research in computer vision since the last decade. The emerging need of crowd management and crowd monitoring for public safety has widen the countless paths of deep learning methodologies and architectures. Although, researchers have developed many sophisticated algorithms but still it is a challenging and tedious task to manage and monitor crowd in real time. The proposed research work focuses on detection of local and global anomaly detection of crowd. Fusion of spatial-temporal features assist in differentiation of feature trained using Mask R-CNN with Resnet101… More >

  • Open AccessOpen Access

    ARTICLE

    Course Evaluation Based on Deep Learning and SSA Hyperparameters Optimization

    Alaa A. El-Demerdash, Sherif E. Hussein, John FW Zaki*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 941-959, 2022, DOI:10.32604/cmc.2022.021839
    Abstract Sentiment analysis attracts the attention of Egyptian Decision-makers in the education sector. It offers a viable method to assess education quality services based on the students’ feedback as well as that provides an understanding of their needs. As machine learning techniques offer automated strategies to process big data derived from social media and other digital channels, this research uses a dataset for tweets' sentiments to assess a few machine learning techniques. After dataset preprocessing to remove symbols, necessary stemming and lemmatization is performed for features extraction. This is followed by several machine learning techniques and a proposed Long Short-Term Memory… More >

  • Open AccessOpen Access

    ARTICLE

    Analysis of Flow Structure in Microturbine Operating at Low Reynolds Number

    Mohamed Omri1,*, Yusuf Al-Turki2, Ahmed A. Alghamdi1, Amrid Amnache3, Luc G. Fréchette3
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 961-977, 2022, DOI:10.32604/cmc.2022.021406
    (This article belongs to this Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
    Abstract In this paper, three-dimensional flows in laminar subsonic cascades at relatively low Reynolds numbers (Re < 2500) are presented, based on numerical calculations. The stator and rotor blade designs are those for a MEMS-based Rankine microturbine power-plant-on-a-chip with 109-micron chord blades. Blade passage calculations in 3D were done for different Reynolds numbers, tip clearances (from 0 to 20%) and incidences (0° to 15°) to determine the impact of aerodynamic conditions on the flow patterns. These conditions are applied to a blade passage for a stationary outer casing. The 3D blade passage without tip clearance indicates the presence of two large… More >

  • Open AccessOpen Access

    ARTICLE

    Data Warehouse Design for Big Data in Academia

    Alex Rudniy*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 979-992, 2022, DOI:10.32604/cmc.2022.016676
    Abstract This paper describes the process of design and construction of a data warehouse (“DW”) for an online learning platform using three prominent technologies, Microsoft SQL Server, MongoDB and Apache Hive. The three systems are evaluated for corpus construction and descriptive analytics. The case also demonstrates the value of evidence-centered design principles for data warehouse design that is sustainable enough to adapt to the demands of handling big data in a variety of contexts. Additionally, the paper addresses maintainability-performance tradeoff, storage considerations and accessibility of big data corpora. In this NSF-sponsored work, the data were processed, transformed, and stored in the… More >

  • Open AccessOpen Access

    ARTICLE

    Polarization Insensitive Broadband Zero Indexed Nano-Meta Absorber for Optical Region Applications

    Ismail Hossain1, Md Samsuzzaman2, Ahasanul Hoque3, Mohd Hafiz Baharuddin3, Norsuzlin Binti Mohd Sahar1, Mohammad Tariqul Islam3,*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 993-1009, 2022, DOI:10.32604/cmc.2022.021435
    Abstract Broadband response metamaterial absorber (MMA) remains a challenge among researchers. A nanostructured new zero-indexed metamaterial (ZIM) absorber is presented in this study, constructed with a hexagonal shape resonator for optical region applications. The design consists of a resonator and dielectric layers made with tungsten and quartz (Fused). The proposed absorbent exhibits average absorption of more than 0.8972 (89.72%) within the visible wavelength of 450–600 nm and nearly perfect absorption of 0.99 (99%) at 461.61 nm. Based on computational analysis, the proposed absorber can be characterized as ZIM. The developments of ZIM absorbers have demonstrated plasmonic resonance characteristics and a perfect… More >

  • Open AccessOpen Access

    ARTICLE

    Takagi–Sugeno Fuzzy Modeling and Control for Effective Robotic Manipulator Motion

    Izzat Al-Darraji1,2, Ayad A. Kakei2, Ayad Ghany Ismaeel3, Georgios Tsaramirsis4, Fazal Qudus Khan5, Princy Randhawa6, Muath Alrammal4, Sadeeq Jan7,*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1011-1024, 2022, DOI:10.32604/cmc.2022.022451
    Abstract Robotic manipulators are widely used in applications that require fast and precise motion. Such devices, however, are prompt to nonlinear control issues due to the flexibility in joints and the friction in the motors within the dynamics of their rigid part. To address these issues, the Linear Matrix Inequalities (LMIs) and Parallel Distributed Compensation (PDC) approaches are implemented in the Takagy–Sugeno Fuzzy Model (T-SFM). We propose the following methodology; initially, the state space equations of the nonlinear manipulator model are derived. Next, a Takagy–Sugeno Fuzzy Model (T-SFM) technique is used for linearizing the state space equations of the nonlinear manipulator.… More >

  • Open AccessOpen Access

    ARTICLE

    Heat Transfer of Casson Fluid over a Vertical Plate with Arbitrary Shear Stress and Exponential Heating

    Dolat Khan1, Gohar Ali1, Arshad Khan2, Ilyas Khan3,*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1025-1034, 2022, DOI:10.32604/cmc.2022.012635
    Abstract The basic objective of this work is to study the heat transfer of Casson fluid of non-Newtonian nature. The fluid is considered over a vertical plate such that the plate exhibits arbitrary wall shear stress at the boundary. Heat transfers due to exponential plate heating and natural convection are due to buoyancy force. Magnetohydrodynamic (MHD) analysis in the occurrence of a uniform magnetic field is also considered. The medium over the plate is porous and hence Darcy’s law is applied. The governing equations are established for the velocity and temperature fields by the usual Boussinesq approximation. The problem is first… More >

  • Open AccessOpen Access

    ARTICLE

    OTP-Based Software-Defined Cloud Architecture for Secure Dynamic Routing

    Tae Woo Kim1, Yi Pan2, Jong Hyuk Park1,*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1035-1049, 2022, DOI:10.32604/cmc.2022.015546
    (This article belongs to this Special Issue: Emerging Trends in Cyber Security for Communication Networks)
    Abstract In the current era, anyone can freely access the Internet thanks to the development of information and communication technology. The cloud is attracting attention due to its ability to meet continuous user demands for resources. Additionally, Cloud is effective for systems with large data flow such as the Internet of Things (IoT) systems and Smart Cities. Nonetheless, the use of traditional networking technology in the cloud causes network traffic overload and network security problems. Therefore, the cloud requires efficient networking technology to solve the existing challenges. In this paper, we propose one-time password-based software-defined cloud architecture for secure dynamic routing… More >

  • Open AccessOpen Access

    ARTICLE

    A Novel Cryptocurrency Prediction Method Using Optimum CNN

    Syed H. Hasan1, Syeda Huyam Hasan2, Mohammed Salih Ahmed3, Syed Hamid Hasan4,*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1051-1063, 2022, DOI:10.32604/cmc.2022.020823
    (This article belongs to this Special Issue: Innovations in Artificial Intelligence using Data Mining and Big Data)
    Abstract In recent years, cryptocurrency has become gradually more significant in economic regions worldwide. In cryptocurrencies, records are stored using a cryptographic algorithm. The main aim of this research was to develop an optimal solution for predicting the price of cryptocurrencies based on user opinions from social media. Twitter is used as a marketing tool for cryptoanalysis owing to the unrestricted conversations on cryptocurrencies that take place on social media channels. Therefore, this work focuses on extracting Tweets and gathering data from different sources to classify them into positive, negative, and neutral categories, and further examining the correlations between cryptocurrency movements… More >

  • Open AccessOpen Access

    ARTICLE

    A Quantum Algorithm for Evaluating the Hamming Distance

    Mohammed Zidan1,2,*, Manal G. Eldin3, Mahmoud Y. Shams4, Mohamed Tolan5,6, Ayman Abd-Elhamed2,7, Mahmoud Abdel-Aty8
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1065-1078, 2022, DOI:10.32604/cmc.2022.020103
    (This article belongs to this Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
    Abstract We present a novel quantum algorithm to evaluate the hamming distance between two unknown oracles via measuring the degree of entanglement between two ancillary qubits. In particular, we use the power of the entanglement degree based quantum computing model that preserves at most the locality of interactions within the quantum model structure. This model uses one of two techniques to retrieve the solution of a quantum computing problem at hand. In the first technique, the solution of the problem is obtained based on whether there is an entanglement between the two ancillary qubits or not. In the second, the solution… More >

  • Open AccessOpen Access

    ARTICLE

    Optimized Stacked Autoencoder for IoT Enabled Financial Crisis Prediction Model

    Mesfer Al Duhayyim1, Hadeel Alsolai2, Fahd N. Al-Wesabi3,4, Nadhem Nemri3, Hany Mahgoub3, Anwer Mustafa Hilal5, Manar Ahmed Hamza5,*, Mohammed Rizwanullah5
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1079-1094, 2022, DOI:10.32604/cmc.2022.021199
    Abstract Recently, Financial Technology (FinTech) has received more attention among financial sectors and researchers to derive effective solutions for any financial institution or firm. Financial crisis prediction (FCP) is an essential topic in business sector that finds it useful to identify the financial condition of a financial institution. At the same time, the development of the internet of things (IoT) has altered the mode of human interaction with the physical world. The IoT can be combined with the FCP model to examine the financial data from the users and perform decision making process. This paper presents a novel multi-objective squirrel search… More >

  • Open AccessOpen Access

    ARTICLE

    Evolutionary Algorithm Based Task Scheduling in IoT Enabled Cloud Environment

    R. Joshua Samuel Raj1, M. Varalatchoumy2, V. L. Helen Josephine3, A. Jegatheesan4, Seifedine Kadry5, Maytham N. Meqdad6, Yunyoung Nam7,*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1095-1109, 2022, DOI:10.32604/cmc.2022.021859
    Abstract Internet of Things (IoT) is transforming the technical setting of conventional systems and finds applicability in smart cities, smart healthcare, smart industry, etc. In addition, the application areas relating to the IoT enabled models are resource-limited and necessitate crisp responses, low latencies, and high bandwidth, which are beyond their abilities. Cloud computing (CC) is treated as a resource-rich solution to the above mentioned challenges. But the intrinsic high latency of CC makes it nonviable. The longer latency degrades the outcome of IoT based smart systems. CC is an emergent dispersed, inexpensive computing pattern with massive assembly of heterogeneous autonomous systems.… More >

  • Open AccessOpen Access

    ARTICLE

    Cardiovascular Disease Prediction Among the Malaysian Cohort Participants Using Electrocardiogram

    Mohd Zubir Suboh1,2, Nazrul Anuar Nayan1,3,*, Noraidatulakma Abdullah4,5, Nurul Ain Mhd Yusof4, Mariatul Akma Hamid4, Azwa Shawani Kamalul Arinfin4, Syakila Mohd Abd Daud4, Mohd Arman Kamaruddin4, Rosmina Jaafar1, Rahman Jamal4
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1111-1132, 2022, DOI:10.32604/cmc.2022.022123
    (This article belongs to this Special Issue: Computational Models for Pro-Smart Environments in Data Science Assisted IoT Systems)
    Abstract A comprehensive study was conducted to differentiate cardiovascular disease (CVD) subjects from non-CVD subjects using short recording electrocardiogram (ECG) of 244 Malaysian adults in The Malaysian Cohort project. An automated peak detection algorithm to detect nine fiducial points of electrocardiogram (ECG) was developed. Forty-eight features were extracted in both time and frequency domains, including statistical features obtained from heart rate variability and Poincare plot analysis. These include five new features derived from spectrum counts of five different frequency ranges. Feature selection was then made based on p-value and correlation matrix. Selected features were used as input for five classifiers of… More >

  • Open AccessOpen Access

    ARTICLE

    Covid-19 CT Lung Image Segmentation Using Adaptive Donkey and Smuggler Optimization Algorithm

    P. Prabu1, K. Venkatachalam2, Ala Saleh Alluhaidan3,*, Radwa Marzouk4, Myriam Hadjouni5, Sahar A. El_Rahman5,6
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1133-1152, 2022, DOI:10.32604/cmc.2022.020919
    Abstract COVID’19 has caused the entire universe to be in existential health crisis by spreading globally in the year 2020. The lungs infection is detected in Computed Tomography (CT) images which provide the best way to increase the existing healthcare schemes in preventing the deadly virus. Nevertheless, separating the infected areas in CT images faces various issues such as low-intensity difference among normal and infectious tissue and high changes in the characteristics of the infection. To resolve these issues, a new inf-Net (Lung Infection Segmentation Deep Network) is designed for detecting the affected areas from the CT images automatically. For the… More >

  • Open AccessOpen Access

    ARTICLE

    Deep Deterministic Policy Gradient to Regulate Feedback Control Systems Using Reinforcement Learning

    Jehangir Arshad1, Ayesha Khan1, Mariam Aftab1, Mujtaba Hussain1, Ateeq Ur Rehman2, Shafiq Ahmad3, Adel M. Al-Shayea3, Muhammad Shafiq4,*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1153-1169, 2022, DOI:10.32604/cmc.2022.021917
    Abstract Controlling feedback control systems in continuous action spaces has always been a challenging problem. Nevertheless, reinforcement learning is mainly an area of artificial intelligence (AI) because it has been used in process control for more than a decade. However, the existing algorithms are unable to provide satisfactory results. Therefore, this research uses a reinforcement learning (RL) algorithm to manage the control system. We propose an adaptive speed control of the motor system based on depth deterministic strategy gradient (DDPG). The actor-critic scenario using DDPG is implemented to build the RL agent. In addition, a framework has been created for traditional… More >

  • Open AccessOpen Access

    ARTICLE

    Design of Human Adaptive Mechatronics Controller for Upper Limb Motion Intention Prediction

    R. Joshua Samuel Raj1,*, J. Prince Antony Joel2, Salem Alelyani3, Mohammed Saleh Alsaqer3, C. Anand Deva Durai4
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1171-1188, 2022, DOI:10.32604/cmc.2022.021667
    Abstract Human Adaptive Mechatronics (HAM) includes human and computer system in a closed loop. Elderly person with disabilities, normally carry out their daily routines with some assistance to move their limbs. With the short fall of human care takers, mechatronics devices are used with the likes of exoskeleton and exosuits to assist them. The rehabilitation and occupational therapy equipments utilize the electromyography (EMG) signals to measure the muscle activity potential. This paper focuses on optimizing the HAM model in prediction of intended motion of upper limb with high accuracy and to increase the response time of the system. Limb characteristics extraction… More >

  • Open AccessOpen Access

    ARTICLE

    Intelligent Disease Diagnosis Model for Energy Aware Cluster Based IoT Healthcare Systems

    Wafaa Alsaggaf1,*, Felwa Abukhodair1, Amani Tariq Jamal2, Sayed Abdel-Khalek3, Romany F. Mansour4
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1189-1203, 2022, DOI:10.32604/cmc.2022.022469
    Abstract In recent days, advancements in the Internet of Things (IoT) and cloud computing (CC) technologies have emerged in different application areas, particularly healthcare. The use of IoT devices in healthcare sector often generates large amount of data and also spent maximum energy for data transmission to the cloud server. Therefore, energy efficient clustering mechanism is needed to effectively reduce the energy consumption of IoT devices. At the same time, the advent of deep learning (DL) models helps to analyze the healthcare data in the cloud server for decision making. With this motivation, this paper presents an intelligent disease diagnosis model… More >

  • Open AccessOpen Access

    ARTICLE

    Deep Learning Based Audio Assistive System for Visually Impaired People

    S. Kiruthika Devi*, C. N. Subalalitha
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1205-1219, 2022, DOI:10.32604/cmc.2022.020827
    Abstract Vision impairment is a latent problem that affects numerous people across the globe. Technological advancements, particularly the rise of computer processing abilities like Deep Learning (DL) models and emergence of wearables pave a way for assisting visually-impaired persons. The models developed earlier specifically for visually-impaired people work effectually on single object detection in unconstrained environment. But, in real-time scenarios, these systems are inconsistent in providing effective guidance for visually-impaired people. In addition to object detection, extra information about the location of objects in the scene is essential for visually-impaired people. Keeping this in mind, the current research work presents an… More >

  • Open AccessOpen Access

    ARTICLE

    Dynamic Encryption and Secure Transmission of Terminal Data Files

    Ruchun Jia1,*, Yang Xin2, Bo Liu3, Qin Qin4
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1221-1232, 2022, DOI:10.32604/cmc.2022.019318
    Abstract Data is the last defense line of security, in order to prevent data loss, no matter where the data is stored, copied or transmitted, it is necessary to accurately detect the data type, and further clarify the form and encryption structure of the data transmission process to ensure the accuracy of the data, so as to prevent data leakage, take the data characteristics as the core, use transparent encryption and decryption technology as the leading, and According to the data element characteristics such as identity authentication, authority management, outgoing management, file audit and external device management, the terminal data is… More >

  • Open AccessOpen Access

    ARTICLE

    An Improved Evolutionary Algorithm for Data Mining and Knowledge Discovery

    Mesfer Al Duhayyim1, Radwa Marzouk2,3, Fahd N. Al-Wesabi4, Maram Alrajhi5, Manar Ahmed Hamza6,*, Abu Sarwar Zamani6
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1233-1247, 2022, DOI:10.32604/cmc.2022.021652
    Abstract Recent advancements in computer technologies for data processing, collection, and storage have offered several chances to improve the abilities in production, services, communication, and researches. Data mining (DM) is an interdisciplinary field commonly used to extract useful patterns from the data. At the same time, educational data mining (EDM) is a kind of DM concept, which finds use in educational sector. Recently, artificial intelligence (AI) techniques can be used for mining a large amount of data. At the same time, in DM, the feature selection process becomes necessary to generate subset of features and can be solved by the use… More >

  • Open AccessOpen Access

    ARTICLE

    Feature Model Configuration Reuse Scheme for Self-Adaptive Systems

    Sumaya Alkubaisi1,*, Said Ghoul2, Oguz Ata1
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1249-1262, 2022, DOI:10.32604/cmc.2022.019434
    (This article belongs to this Special Issue: Application of Big Data Analytics in the Management of Business)
    Abstract Most large-scale systems including self-adaptive systems utilize feature models (FMs) to represent their complex architectures and benefit from the reuse of commonalities and variability information. Self-adaptive systems (SASs) are capable of reconfiguring themselves during the run time to satisfy the scenarios of the requisite contexts. However, reconfiguration of SASs corresponding to each adaptation of the system requires significant computational time and resources. The process of configuration reuse can be a better alternative to some contexts to reduce computational time, effort and error-prone. Nevertheless, systems’ complexity can be reduced while the development process of systems by reusing elements or components. FMs… More >

  • Open AccessOpen Access

    ARTICLE

    Bilateral Coupled Epsilon Negative Metamaterial for Dual Band Wireless Communications

    Md Mhedi Hasan1, Mohammad Tariqul Islam1,*, Md Moniruzzaman1, Mohd Hafiz Baharuddin1, Norsuzlin Binti Mohd Sahar2, Md Samsuzzaman3
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1263-1281, 2022, DOI:10.32604/cmc.2022.021388
    Abstract This work presents a dual band epsilon negative (ENG) metamaterial with a bilateral coupled split ring resonator (SRR) for use in C and X band wireless communication systems. The traditional split-ring resonator (SRR) has been amended with this engineered structure. The proposed metamaterial unit cell is realized on the 1.6 mm thick FR-4 printed media with a dimension of 10 × 10 mm2. The resonating patch built with a square split outer ring. Two interlinked inner rings are coupled vertically to the outer ring to extend its electrical length as well as to tune the resonance frequency. Numerical simulation is… More >

  • Open AccessOpen Access

    ARTICLE

    Dynamic Audio-Visual Biometric Fusion for Person Recognition

    Najlaa Hindi Alsaedi*, Emad Sami Jaha
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1283-1311, 2022, DOI:10.32604/cmc.2022.021608
    Abstract Biometric recognition refers to the process of recognizing a person’s identity using physiological or behavioral modalities, such as face, voice, fingerprint, gait, etc. Such biometric modalities are mostly used in recognition tasks separately as in unimodal systems, or jointly with two or more as in multimodal systems. However, multimodal systems can usually enhance the recognition performance over unimodal systems by integrating the biometric data of multiple modalities at different fusion levels. Despite this enhancement, in real-life applications some factors degrade multimodal systems’ performance, such as occlusion, face poses, and noise in voice data. In this paper, we propose two algorithms… More >

  • Open AccessOpen Access

    ARTICLE

    Design of Nonlinear Components Over a Mordell Elliptic Curve on Galois Fields

    Hafeez ur Rehman1,*, Tariq Shah1, Amer Aljaedi2, Mohammad Mazyad Hazzazi3, Adel R. Alharbi2
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1313-1329, 2022, DOI:10.32604/cmc.2022.022224
    Abstract Elliptic curve cryptography ensures more safety and reliability than other public key cryptosystems of the same key size. In recent years, the use of elliptic curves in public-key cryptography has increased due to their complexity and reliability. Different kinds of substitution boxes are proposed to address the substitution process in the cryptosystems, including dynamical, static, and elliptic curve-based methods. Conventionally, elliptic curve-based S-boxes are based on prime field but in this manuscript; we propose a new technique of generating S-boxes based on mordell elliptic curves over the Galois field . This technique affords a higher number of possibilities to generate… More >

  • Open AccessOpen Access

    ARTICLE

    Ultra-Wideband Annular Ring Fed Rectangular Dielectric Resonator Antenna for Millimeter Wave 5G Applications

    Abinash Gaya1, Mohd. Haizal Jamaluddin1,*, Ayman A. Althuwayb2
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1331-1348, 2022, DOI:10.32604/cmc.2022.022041
    (This article belongs to this Special Issue: Advances in 5G Antenna Designs and Systems)
    Abstract In this article an ultra-wideband rectangular Dielectric Resonator Antenna is designed for millimeter wave 5G frequency band applications. Indoor 5G communications require antenna system with wide bandwidth and high efficiency to enhance the throughput in the channel. To fulfill such requirements a Dielectric Resonator Antenna (DRA) is designed here which has achieved an ultra-wide bandwidth of 20.15% (22.32–27.56 GHz) which is 5.24 GHz of bandwidth centered at 26 GHz as resonating frequency. This covers the complete band 30 (24.3–27.5 GHz) of 5G spectrum. 26 and 28 GHz are considered as most popular frequencies in millimeter wave 5G communications. The aperture… More >

  • Open AccessOpen Access

    ARTICLE

    Parametric Study of Hip Fracture Risk Using QCT-Based Finite Element Analysis

    Hossein Bisheh1,2, Yunhua Luo1,3, Timon Rabczuk2,*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1349-1369, 2022, DOI:10.32604/cmc.2022.018262
    Abstract Various parameters such as age, height, weight, and body mass index (BMI) influence the hip fracture risk in the elderly which is the most common injury during the sideways fall. This paper presents a parametric study of hip fracture risk based on the gender, age, height, weight, and BMI of subjects using the subject-specific QCT-based finite element modelling and simulation of single-leg stance and sideways fall loadings. Hip fracture risk is estimated using the strain energy failure criterion as a combination of bone stresses and strains leading to more accurate and reasonable results based on the bone failure mechanism. Understanding… More >

  • Open AccessOpen Access

    ARTICLE

    Denoising Letter Images from Scanned Invoices Using Stacked Autoencoders

    Samah Ibrahim Alshathri1,*, Desiree Juby Vincent2, V. S. Hari2
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1371-1386, 2022, DOI:10.32604/cmc.2022.022458
    Abstract Invoice document digitization is crucial for efficient management in industries. The scanned invoice image is often noisy due to various reasons. This affects the OCR (optical character recognition) detection accuracy. In this paper, letter data obtained from images of invoices are denoised using a modified autoencoder based deep learning method. A stacked denoising autoencoder (SDAE) is implemented with two hidden layers each in encoder network and decoder network. In order to capture the most salient features of training samples, a undercomplete autoencoder is designed with non-linear encoder and decoder function. This autoencoder is regularized for denoising application using a combined… More >

  • Open AccessOpen Access

    ARTICLE

    An Integrated Deep Learning Framework for Fruits Diseases Classification

    Abdul Majid1, Muhammad Attique Khan1, Majed Alhaisoni2, Muhammad Asfand E. yar3, Usman Tariq4, Nazar Hussain1, Yunyoung Nam5,*, Seifedine Kadry6
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1387-1402, 2022, DOI:10.32604/cmc.2022.017701
    (This article belongs to this Special Issue: Recent Advances in Deep Learning and Saliency Methods for Agriculture)
    Abstract Agriculture has been an important research area in the field of image processing for the last five years. Diseases affect the quality and quantity of fruits, thereby disrupting the economy of a country. Many computerized techniques have been introduced for detecting and recognizing fruit diseases. However, some issues remain to be addressed, such as irrelevant features and the dimensionality of feature vectors, which increase the computational time of the system. Herein, we propose an integrated deep learning framework for classifying fruit diseases. We consider seven types of fruits, i.e., apple, cherry, blueberry, grapes, peach, citrus, and strawberry. The proposed method… More >

  • Open AccessOpen Access

    ARTICLE

    SMOTEDNN: A Novel Model for Air Pollution Forecasting and AQI Classification

    Mohd Anul Haq*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1403-1425, 2022, DOI:10.32604/cmc.2022.021968
    (This article belongs to this Special Issue: Artificial Intelligence and Machine Learning Algorithms in Real-World Applications and Theories)
    Abstract Rapid industrialization and urbanization are rapidly deteriorating ambient air quality, especially in the developing nations. Air pollutants impose a high risk on human health and degrade the environment as well. Earlier studies have used machine learning (ML) and statistical modeling to classify and forecast air pollution. However, these methods suffer from the complexity of air pollution dataset resulting in a lack of efficient classification and forecasting of air pollution. ML-based models suffer from improper data pre-processing, class imbalance issues, data splitting, and hyperparameter tuning. There is a gap in the existing ML-based studies on air pollution due to improper data… More >

  • Open AccessOpen Access

    ARTICLE

    Effective Video Summarization Approach Based on Visual Attention

    Hilal Ahmad1, Habib Ullah Khan2, Sikandar Ali3,*, Syed Ijaz Ur Rahman1, Fazli Wahid3, Hizbullah Khattak4
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1427-1442, 2022, DOI:10.32604/cmc.2022.021158
    (This article belongs to this Special Issue: Application of Machine-Learning in Computer Vision)
    Abstract Video summarization is applied to reduce redundancy and develop a concise representation of key frames in the video, more recently, video summaries have been used through visual attention modeling. In these schemes, the frames that stand out visually are extracted as key frames based on human attention modeling theories. The schemes for modeling visual attention have proven to be effective for video summaries. Nevertheless, the high cost of computing in such techniques restricts their usability in everyday situations. In this context, we propose a method based on KFE (key frame extraction) technique, which is recommended based on an efficient and… More >

  • Open AccessOpen Access

    ARTICLE

    Novel Image Encryption and Compression Scheme for IoT Environment

    Mesfer Al Duhayyim1, Fahd N. Al-Wesabi2, Radwa Marzouk3, Manar Ahmed Hamza4, Anwer Mustafa Hilal4,*, Majdy M. Eltahir2
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1443-1457, 2022, DOI:10.32604/cmc.2022.021873
    Abstract Latest advancements made in the processing abilities of smart devices have resulted in the designing of Intelligent Internet of Things (IoT) environment. This advanced environment enables the nodes to connect, collect, perceive, and examine useful data from its surroundings. Wireless Multimedia Surveillance Networks (WMSNs) form a vital part in IoT-assisted environment since it contains visual sensors that examine the surroundings from a number of overlapping views by capturing the images incessantly. Since IoT devices generate a massive quantity of digital media, it is therefore required to save the media, especially images, in a secure way. In order to achieve security,… More >

  • Open AccessOpen Access

    ARTICLE

    Autism Spectrum Disorder Prediction by an Explainable Deep Learning Approach

    Anupam Garg1, Anshu Parashar1, Dipto Barman2, Sahil Jain3, Divya Singhal3, Mehedi Masud4, Mohamed Abouhawwash5,6,*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1459-1471, 2022, DOI:10.32604/cmc.2022.022170
    (This article belongs to this Special Issue: Applications of Intelligent Systems in Computer Vision)
    Abstract Autism Spectrum Disorder (ASD) is a developmental disorder whose symptoms become noticeable in early years of the age though it can be present in any age group. ASD is a mental disorder which affects the communicational, social and non-verbal behaviors. It cannot be cured completely but can be reduced if detected early. An early diagnosis is hampered by the variation and severity of ASD symptoms as well as having symptoms commonly seen in other mental disorders as well. Nowadays, with the emergence of deep learning approaches in various fields, medical experts can be assisted in early diagnosis of ASD. It… More >

  • Open AccessOpen Access

    ARTICLE

    Deep Learning Enabled Predictive Model for P2P Energy Trading in TEM

    Pudi Sekhar1, T. J. Benedict Jose2, Velmurugan Subbiah Parvathy3, E. Laxmi Lydia4, Seifedine Kadry5, Kuntha Pin6, Yunyoung Nam7,*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1473-1487, 2022, DOI:10.32604/cmc.2022.022110
    Abstract With the incorporation of distributed energy systems in the electric grid, transactive energy market (TEM) has become popular in balancing the demand as well as supply adaptively over the grid. The classical grid can be updated to the smart grid by the integration of Information and Communication Technology (ICT) over the grids. The TEM allows the Peer-to-Peer (P2P) energy trading in the grid that effectually connects the consumer and prosumer to trade energy among them. At the same time, there is a need to predict the load for effectual P2P energy trading and can be accomplished by the use of… More >

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    ARTICLE

    Design of Automatic Batch Calibration and Correction System for IMU

    Lihua Zhu1, Qifan Yun1, Zhiqiang Wu1,*, Cheire Cheng2
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1489-1501, 2022, DOI:10.32604/cmc.2022.022091
    Abstract Thanks to its light weight, low power consumption, and low price, the inertial measurement units (IMUs) have been widely used in civil and military applications such as autopilot, robotics, and tactical weapons. The calibration is an essential procedure before the IMU is put in use, which is generally used to estimate the error parameters such as the bias, installation error, scale factor of the IMU. Currently, the manual one-by-one calibration is still the mostly used manner, which is low in efficiency, time-consuming, and easy to introduce mis-operation. Aiming at this issue, this paper designs an automatic batch calibration method for… More >

  • Open AccessOpen Access

    ARTICLE

    Piezoresistive Prediction of CNTs-Embedded Cement Composites via Machine Learning Approaches

    Jinho Bang1, SongEe Park2, Haemin Jeon2,*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1503-1519, 2022, DOI:10.32604/cmc.2022.020485
    (This article belongs to this Special Issue: Applications of Machine Learning for Big Data)
    Abstract Conductive cementitious composites are innovated materials that have improved electrical conductivity compared to general types of cement, and are expected to be used in a variety of future infrastructures with unique functionalities such as self-heating, electromagnetic shielding, and piezoelectricity. In the present study, machine learning methods that have been recently applied in various fields were proposed for the prediction of piezoelectric characteristics of carbon nanotubes (CNTs)-incorporated cement composites. Data on the resistivity change of CNTs/cement composites according to various water/binder ratios, loading types, and CNT content were considered as training values. These data were applied to numerous machine learning techniques… More >

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    ARTICLE

    Software Defect Prediction Harnessing on Multi 1-Dimensional Convolutional Neural Network Structure

    Zuhaira Muhammad Zain1,*, Sapiah Sakri1, Nurul Halimatul Asmak Ismail2, Reza M. Parizi3
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1521-1546, 2022, DOI:10.32604/cmc.2022.022085
    Abstract Developing successful software with no defects is one of the main goals of software projects. In order to provide a software project with the anticipated software quality, the prediction of software defects plays a vital role. Machine learning, and particularly deep learning, have been advocated for predicting software defects, however both suffer from inadequate accuracy, overfitting, and complicated structure. In this paper, we aim to address such issues in predicting software defects. We propose a novel structure of 1-Dimensional Convolutional Neural Network (1D-CNN), a deep learning architecture to extract useful knowledge, identifying and modelling the knowledge in the data sequence,… More >

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    ARTICLE

    Switched-Beam Optimization for an Indoor Visible Light Communication Using Genetic Algorithm

    Ladathunya Pumkaew, Monthippa Uthansakul*, Peerapong Uthansakul
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1547-1566, 2022, DOI:10.32604/cmc.2022.022556
    Abstract Nowadays, Visible Light Communication (VLC) is an attractive alternative technology for wireless communication because it can use some simple Light Emitting Diodes (LEDs) instead of antennas. Typically, indoor VLC is designed to transmit only one dataset through multiple LED beams at a time. As a result, the number of users per unit of time (throughput) is relatively low. Therefore, this paper proposes the design of an indoor VLC system using switched-beam technique through computer simulation. The LED lamps are designed to be arranged in a circular array and the signal can be transmitted through the beam of each LED lamp… More >

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    ARTICLE

    Energy Aware Metaheuristic Optimization with Location Aided Routing Protocol for MANET

    E. Ahila Devi1, K. C. Ramya2, K. Sathesh Kumar3, Sultan Ahmad4, Seifedine Kadry5, Hyung Ju Park6, Byeong-Gwon Kang6,*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1567-1580, 2022, DOI:10.32604/cmc.2022.022539
    Abstract A mobile ad hoc network (MANET) involves a group of wireless mobile nodes which create an impermanent network with no central authority and infrastructure. The nodes in the MANET are highly mobile and it results in adequate network topology, link loss, and increase the re-initialization of the route discovery process. Route planning in MANET is a multi-hop communication process due to the restricted transmission range of the nodes. Location aided routing (LAR) is one of the effective routing protocols in MANET which suffers from the issue of high energy consumption. Though few research works have focused on resolving energy consumption… More >

  • Open AccessOpen Access

    ARTICLE

    Relation-Aware Entity Matching Using Sentence-BERT

    Huchen Zhou1, Wenfeng Huang1, Mohan Li1,*, Yulin Lai2
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1581-1595, 2022, DOI:10.32604/cmc.2022.020695
    Abstract A key aspect of Knowledge fusion is Entity Matching. The objective of this study was to investigate how to identify heterogeneous expressions of the same real-world entity. In recent years, some representative works have used deep learning methods for entity matching, and these methods have achieved good results. However, the common limitation of these methods is that they assume that different attribute columns of the same entity are independent, and inputting the model in the form of paired entity records will cause repeated calculations. In fact, there are often potential relations between different attribute columns of different entities. These relations… More >

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    ARTICLE

    Defocus Blur Segmentation Using Local Binary Patterns with Adaptive Threshold

    Usman Ali, Muhammad Tariq Mahmood*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1597-1611, 2022, DOI:10.32604/cmc.2022.022219
    (This article belongs to this Special Issue: Machine Learning Empowered Secure Computing for Intelligent Systems)
    Abstract Enormous methods have been proposed for the detection and segmentation of blur and non-blur regions of the images. Due to the limited available information about blur type, scenario and the level of blurriness, detection and segmentation is a challenging task. Hence, the performance of the blur measure operator is an essential factor and needs improvement to attain perfection. In this paper, we propose an effective blur measure based on local binary pattern (LBP) with adaptive threshold for blur detection. The sharpness metric developed based on LBP used a fixed threshold irrespective of the type and level of blur, that may… More >

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    ARTICLE

    Gain Enhancement of Dielectric Resonator Antenna Using Electromagnetic Bandgap Structure

    Amor Smida1,2,*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1613-1623, 2022, DOI:10.32604/cmc.2022.022289
    (This article belongs to this Special Issue: Advances in 5G Antenna Designs and Systems)
    Abstract High gain antennas are highly desirable for long-range wireless communication systems. In this paper, a compact, low profile, and high gain dielectric resonator antenna is proposed, fabricated, experimentally tested, and verified. The proposed antenna system has a cylindrical dielectric resonator antenna with a height of 9 mm and a radius of 6.35 mm as a radiating element. The proposed dielectric resonator antenna is sourced with a slot while the slot is excited with a rectangular microstrip transmission line. The microstrip transmission line is designed for a 50 Ω impedance to provide maximum power to the slot. As a result, the… More >

  • Open AccessOpen Access

    ARTICLE

    Dynamic Automated Infrastructure for Efficient Cloud Data Centre

    R. Dhaya1,*, R. Kanthavel2
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1625-1639, 2022, DOI:10.32604/cmc.2022.022213
    Abstract We propose a dynamic automated infrastructure model for the cloud data centre which is aimed as an efficient service stipulation for the enormous number of users. The data center and cloud computing technologies have been at the moment rendering attention to major research and development efforts by companies, governments, and academic and other research institutions. In that, the difficult task is to facilitate the infrastructure to construct the information available to application-driven services and make business-smart decisions. On the other hand, the challenges that remain are the provision of dynamic infrastructure for applications and information anywhere. Further, developing technologies to… More >

  • Open AccessOpen Access

    ARTICLE

    Hybrid Cuckoo Search Algorithm for Scheduling in Cloud Computing

    Manoj Kumar*, Suman
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1641-1660, 2022, DOI:10.32604/cmc.2022.021793
    (This article belongs to this Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
    Abstract Cloud computing has gained widespread popularity over the last decade. Scheduling problem in cloud computing is prejudiced due to enormous demands of cloud users. Meta-heuristic techniques in cloud computing have exhibited high performance in comparison to traditional scheduling algorithms. This paper presents a novel hybrid Nesterov Accelerated Gradient-based Cuckoo Search Algorithm (NAGCSA) to address the scheduling issue in cloud computing. Nesterov Accelerated Gradient can address trapping at local minima in CSA by updating the position using future approximation. The local search in the proposed algorithm is performed by using Nesterov Accelerated Gradient, while the global search is performed by using… More >

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    ARTICLE

    Decoding of Factorial Experimental Design Models Implemented in Production Process

    Borislav Savkovic1, Pavel Kovac1, Branislav Dudic2,3,*, Michal Gregus2
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1661-1675, 2022, DOI:10.32604/cmc.2022.021642
    Abstract The paper deals with factorial experimental design models decoding. For the ease of calculation of the experimental mathematical models, it is convenient first to code the independent variables. When selecting independent variables, it is necessary to take into account the range covered by each. A wide range of choices of different variables is presented in this paper. After calculating the regression model, its variables must be returned to their original values for the model to be easy recognized and represented. In the paper, the procedures of simple first order models, with interactions and with second order models, are presented, which… More >

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    ARTICLE

    Decagonal C-Shaped CSRR Textile-Based Metamaterial for Microwave Applications

    Kabir Hossain1,2, Thennarasan Sabapathy1,2,*, Muzammil Jusoh1,2, Ping Jack Soh1,3, Samir Salem Al-Bawri4, Mohamed Nasrun Osman1,2, Hasliza A. Rahim1,2, Danai Torrungrueng5, Prayoot Akkaraekthalin6
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1677-1693, 2022, DOI:10.32604/cmc.2022.022227
    Abstract This paper introduces a decagonal C-shaped complementary split-ring resonator (CSRR) textile-based metamaterial (MTM). The overall size of the proposed sub-wavelength MTM unit cell is 0.28λ0 × 0.255λ0 at 3 GHz. Its stopband behaviour was first studied prior analysing the negative index properties of the proposed MTM. It is worth noting that in this work a unique way the experiments were completed. For both simulations and measurements, the proposed MTM exhibited negative-permittivity and negative-refractive index characteristics with an average bandwidth of more than 3 GHz (considering 1.7 to 8.2 GHz as the measurements were carried out within this range). In simulations, the MTM… More >

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    ARTICLE

    Lightweight Key Management Scheme Using Fuzzy Extractor for Wireless Mobile Sensor Network

    Eid Rehman1, Ibrahima Kalil Toure2, Kashif Sultan3, Muhammad Asif4, Muhammad Habib1, Najam Ul Hasan5, Oh-Young Song6,*, Aaqif Afzaal Abbasi1
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1695-1712, 2022, DOI:10.32604/cmc.2022.021641
    Abstract

    The mature design of wireless mobile sensor network makes it to be used in vast verities of applications including from home used to the security surveillance. All such types of applications based on wireless mobile sensor network are generally using real time data, most of them are interested in real time communication directly from cluster head of cluster instead of a base station in cluster network. This would be possible if an external user allows to directly access real time data from the cluster head in cluster wireless mobile sensor network instead of accessing data from base station. But this… More >

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    ARTICLE

    IoT with Evolutionary Algorithm Based Deep Learning for Smart Irrigation System

    P. Suresh1,*, R. H. Aswathy1, Sridevi Arumugam2, Amani Abdulrahman Albraikan3, Fahd N. Al-Wesabi4, Anwer Mustafa Hilal5, Mohammad Alamgeer6
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1713-1728, 2022, DOI:10.32604/cmc.2022.021789
    Abstract In India, water wastage in agricultural fields becomes a challenging issue and it is needed to minimize the loss of water in the irrigation process. Since the conventional irrigation system needs massive quantity of water utilization, a smart irrigation system can be designed with the help of recent technologies such as machine learning (ML) and the Internet of Things (IoT). With this motivation, this paper designs a novel IoT enabled deep learning enabled smart irrigation system (IoTDL-SIS) technique. The goal of the IoTDL-SIS technique focuses on the design of smart irrigation techniques for effectual water utilization with less human interventions.… More >

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    ARTICLE

    DNNBoT: Deep Neural Network-Based Botnet Detection and Classification

    Mohd Anul Haq, Mohd Abdul Rahim Khan*
    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1729-1750, 2022, DOI:10.32604/cmc.2022.020938
    (This article belongs to this Special Issue: Advanced IoT Industrial Solutions and Cyber Security Threats in Communication Networks)
    Abstract The evolution and expansion of IoT devices reduced human efforts, increased resource utilization, and saved time; however, IoT devices create significant challenges such as lack of security and privacy, making them more vulnerable to IoT-based botnet attacks. There is a need to develop efficient and faster models which can work in real-time with efficiency and stability. The present investigation developed two novels, Deep Neural Network (DNN) models, DNNBoT1 and DNNBoT2, to detect and classify well-known IoT botnet attacks such as Mirai and BASHLITE from nine compromised industrial-grade IoT devices. The utilization of PCA was made to feature extraction and improve… More >

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