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Fahd N. Al-Wesabi^1,2,*, Imran Khan³, Saleem Latteef Mohammed⁴, Huda Farooq Jameel⁴, Mohammad Alamgeer⁵, Ali M. Al-Sharafi⁶, Byung Seo Kim⁷
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1-15, 2022, DOI:10.32604/cmc.2022.018469 - 03 November 2021
Abstract With the rapid development of the next-generation mobile network, the number of terminal devices and applications is growing explosively. Therefore, how to obtain a higher data rate, wider network coverage and higher resource utilization in the limited spectrum resources has become the common research goal of scholars. Device-to-Device (D2D) communication technology and other frontier communication technologies have emerged. Device-to-Device communication technology is the technology that devices in proximity can communicate directly in cellular networks. It has become one of the key technologies of the fifth-generation mobile communications system(5G). D2D communication technology which is introduced into… More >

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Khalid Mahmood Aamir¹, Muhammad Ramzan^1,2, Saima Skinadar¹, Hikmat Ullah Khan³, Usman Tariq⁴, Hyunsoo Lee⁵, Yunyoung Nam^5,*, Muhammad Attique Khan⁶
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 17-33, 2022, DOI:10.32604/cmc.2022.018613 - 03 November 2021
（This article belongs to the Special Issue: Recent Advances in Deep Learning for Medical Image Analysis)
Abstract This paper focuses on detecting diseased signals and arrhythmias classification into two classes: ventricular tachycardia and premature ventricular contraction. The sole purpose of the signal detection is used to determine if a signal has been collected from a healthy or sick person. The proposed research approach presents a mathematical model for the signal detector based on calculating the instantaneous frequency (IF). Once a signal taken from a patient is detected, then the classifier takes that signal as input and classifies the target disease by predicting the class label. While applying the classifier, templates are designed… More >

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Parneet Kaur¹, Yogesh Kumar¹, Shakeel Ahmed^2,*, Abdulaziz Alhumam², Ruchi Singla³, Muhammad Fazal Ijaz⁴
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 35-50, 2022, DOI:10.32604/cmc.2022.017681 - 03 November 2021
Abstract Automatic License Plate Recognition (ALPR) systems are important in Intelligent Transportation Services (ITS) as they help ensure effective law enforcement and security. These systems play a significant role in border surveillance, ensuring safeguards, and handling vehicle-related crime. The most effective approach for implementing ALPR systems utilizes deep learning via a convolutional neural network (CNN). A CNN works on an input image by assigning significance to various features of the image and differentiating them from each other. CNNs are popular for license plate character recognition. However, little has been reported on the results of these systems with More >

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Seungwoon Lee¹, Woogeun Kil¹, Byeong-hee Roh^1,*, SJ Kim², Jin-suk Kang³
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 51-69, 2022, DOI:10.32604/cmc.2022.019635 - 03 November 2021
Abstract There have been numerous works proposed to merge augmented reality/mixed reality (AR/MR) and Internet of Things (IoT) in various ways. However, they have focused on their specific target applications and have limitations on interoperability or reusability when utilizing them to different domains or adding other devices to the system. This paper proposes a novel architecture of a convergence platform for AR/MR and IoT systems and services. The proposed architecture adopts the oneM2M IoT standard as the basic framework that converges AR/MR and IoT systems and enables the development of application services used in general-purpose environments More >

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A. F. Mohamed^1,2, J. Abu Alsoud¹, Mujahed Al-Dhaifallah^3,*, Hegazy Rezk^4,5, Mohamed K. Hassan^1,6
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 71-83, 2022, DOI:10.32604/cmc.2022.019257 - 03 November 2021
Abstract In power plants, flue gases can cause severe corrosion damage in metallic parts such as flue ducts, heat exchangers, and boilers. Coating is an effective technique to prevent this damage. A robust fuzzy model of the surface roughness (R_a and R_z) of flue gas ducts coated by protective composite coating from epoxy and nanoparticles was constructed based on the experimental dataset. The proposed model consists of four nanoparticles (ZnO, ZrO₂, SiO₂, and NiO) with 2%, 4%, 6%, and 8%, respectively. Response surface methodology (RSM) was used to optimize the process parameters and identify the optimal conditions for… More >

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1432

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Nadia H. Alsulami^1,*, Amani T. Jamal¹, Lamiaa A. Elrefaei²
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 85-108, 2022, DOI:10.32604/cmc.2022.019450 - 03 November 2021
（This article belongs to the Special Issue: Recent Advances in Deep Learning, Information Fusion, and Features Selection for Video Surveillance Application)
Abstract Lip-reading technologies are rapidly progressing following the breakthrough of deep learning. It plays a vital role in its many applications, such as: human-machine communication practices or security applications. In this paper, we propose to develop an effective lip-reading recognition model for Arabic visual speech recognition by implementing deep learning algorithms. The Arabic visual datasets that have been collected contains 2400 records of Arabic digits and 960 records of Arabic phrases from 24 native speakers. The primary purpose is to provide a high-performance model in terms of enhancing the preprocessing phase. Firstly, we extract keyframes from… More >

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Sathish Babu Pandu^1,*, A. Sagai Francis Britto², Pudi Sekhar³, P. Vijayarajan⁴, Amani Abdulrahman Albraikan⁵, Fahd N. Al-Wesabi⁶, Mesfer Al Duhayyim⁷
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 109-124, 2022, DOI:10.32604/cmc.2022.021015 - 03 November 2021
Abstract Solar energy has gained attention in the past two decades, since it is an effective renewable energy source that causes no harm to the environment. Solar Irradiation Prediction (SIP) is essential to plan, schedule, and manage photovoltaic power plants and grid-based power generation systems. Numerous models have been proposed for SIP in the literature while such studies demand huge volumes of weather data about the target location for a lengthy period of time. In this scenario, commonly available Artificial Intelligence (AI) technique can be trained over past values of irradiance as well as weather-related parameters… More >

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1293

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Muhammad Shahid Bhatti^1,*, Azmat Ullah¹, Rohaya Latip², Abid Sohail¹, Anum Riaz¹, Rohail Hassan³
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 125-141, 2022, DOI:10.32604/cmc.2022.020083 - 03 November 2021
（This article belongs to the Special Issue: Computational Models for Pro-Smart Environments in Data Science Assisted IoT Systems)
Abstract Text classification of low resource language is always a trivial and challenging problem. This paper discusses the process of Urdu news classification and Urdu documents similarity. Urdu is one of the most famous spoken languages in Asia. The implementation of computational methodologies for text classification has increased over time. However, Urdu language has not much experimented with research, it does not have readily available datasets, which turn out to be the primary reason behind limited research and applying the latest methodologies to the Urdu. To overcome these obstacles, a medium-sized dataset having six categories is… More >

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Anwer Mustafa Hilal¹, Badria Sulaiman Alfurhood², Fahd N. Al-Wesabi^3,4, Manar Ahmed Hamza^1,*, Mesfer Al Duhayyim⁵, Huda G. Iskandar^4,6
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 143-157, 2022, DOI:10.32604/cmc.2022.021502 - 03 November 2021
Abstract Smart city promotes the unification of conventional urban infrastructure and information technology (IT) to improve the quality of living and sustainable urban services in the city. To accomplish this, smart cities necessitate collaboration among the public as well as private sectors to install IT platforms to collect and examine massive quantities of data. At the same time, it is essential to design effective artificial intelligence (AI) based tools to handle healthcare crisis situations in smart cities. To offer proficient services to people during healthcare crisis time, the authorities need to look closer towards them. Sentiment… More >

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Dezheng Zhang^1,2, Qi Jia^1,2, Shibing Yang^1,2, Xinliang Han², Cong Xu³, Xin Liu^1,4, Yonghong Xie^1,2,*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 159-170, 2022, DOI:10.32604/cmc.2022.017295 - 03 November 2021
Abstract Syndrome differentiation is the core diagnosis method of Traditional Chinese Medicine (TCM). We propose a method that simulates syndrome differentiation through deductive reasoning on a knowledge graph to achieve automated diagnosis in TCM. We analyze the reasoning path patterns from symptom to syndromes on the knowledge graph. There are two kinds of path patterns in the knowledge graph: one-hop and two-hop. The one-hop path pattern maps the symptom to syndromes immediately. The two-hop path pattern maps the symptom to syndromes through the nature of disease, etiology, and pathomechanism to support the diagnostic reasoning. Considering the… More >

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T. Jeslin^1,*, J. Arul Linsely²
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 171-182, 2022, DOI:10.32604/cmc.2022.020255 - 03 November 2021
（This article belongs to the Special Issue: Advanced signal acquisition and processing for Internet of Medical Things)
Abstract Brain cancer is the premier reason for cancer deaths all over the world. The diagnosis of brain cancer at an initial stage is mediocre, as the radiologist is ineffectual. Different experiments have been conducted and demonstrated clearly that the algorithms for nodule segmentation are unsuccessful. Therefore, the research has consolidated incremental clustering focused on superpixel segmentation as an appropriate optimization approach for the accurate segmentation of pulmonary nodules. The key aim of the research is to refine brain CT images to accurately distinguish tumors and the segmentation of small-scale anomalous nodules in the brain region.… More >

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1268

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Afiya Kiran¹, Ahmad Karim^2,*, Yasser Obaid Alharbi³, Diaa Mohammed Uliyan³
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 183-197, 2022, DOI:10.32604/cmc.2022.021860 - 03 November 2021
Abstract Wireless Sensor Networks (WSNs) can be termed as an auto-configured and infrastructure-less wireless networks to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure and motion etc. WSNs may comprise thousands of Internet of Things (IoT) devices to sense and collect data from its surrounding, process the data and take an automated and mechanized decision. On the other side the proliferation of these devices will soon cause radio spectrum shortage. So, to facilitate these networks, we integrate Cognitive Radio (CR) functionality in these networks. CR can sense the unutilized spectrum of licensed users… More >

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1318

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Abdelhameed Ibrahim^1,*, Hattan F. Abutarboush², Ali Wagdy Mohamed^3,4, Mohamad Fouad¹, El-Sayed M. El-kenawy^5,6
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 199-213, 2022, DOI:10.32604/cmc.2022.021886 - 03 November 2021
（This article belongs to the Special Issue: Artificial Intelligence and Machine Learning Algorithms in Real-World Applications and Theories)
Abstract Metamaterial Antenna is a special class of antennas that uses metamaterial to enhance their performance. Antenna size affects the quality factor and the radiation loss of the antenna. Metamaterial antennas can overcome the limitation of bandwidth for small antennas. Machine learning (ML) model is recently applied to predict antenna parameters. ML can be used as an alternative approach to the trial-and-error process of finding proper parameters of the simulated antenna. The accuracy of the prediction depends mainly on the selected model. Ensemble models combine two or more base models to produce a better-enhanced model. In… More >

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Talha Imtiaz Baig^1,*, Yaser Daanial Khan¹, Talha Mahboob Alam², Bharat Biswal³, Hanan Aljuaid⁴, Durdana Qaiser Gillani⁵
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 215-230, 2022, DOI:10.32604/cmc.2022.021849 - 03 November 2021
（This article belongs to the Special Issue: Machine Learning Applications in Medical, Finance, Education and Cyber Security)
Abstract Lysine Lipoylation is a protective and conserved Post Translational Modification (PTM) in proteomics research like prokaryotes and eukaryotes. It is connected with many biological processes and closely linked with many metabolic diseases. To develop a perfect and accurate classification model for identifying lipoylation sites at the protein level, the computational methods and several other factors play a key role in this purpose. Usually, most of the techniques and different traditional experimental models have a very high cost. They are time-consuming; so, it is required to construct a predictor model to extract lysine lipoylation sites. This… More >

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ARTICLE

Emad M. Ahmed^1,*, Mohamed A. Ahmed¹, Ziad M. Ali^2,3, Imran Khan⁴
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 231-254, 2022, DOI:10.32604/cmc.2022.022005 - 03 November 2021
Abstract The operation complexity of the distribution system increases as a large number of distributed generators (DG) and electric vehicles were introduced, resulting in higher demands for fast online reactive power optimization. In a power system, the characteristic selection criteria for power quality disturbance classification are not universal. The classification effect and efficiency needs to be improved, as does the generalization potential. In order to categorize the quality in the power signal disturbance, this paper proposes a multi-layer severe learning computer auto-encoder to optimize the input weights and extract the characteristics of electric power quality disturbances.… More >

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R. Krishnaswamy^1,*, B. Sivakumar², B. Viswanathan³, Fahd N. Al-Wesabi^4,5, Marwa Obayya⁶, Anwer Mustafa Hilal⁷
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 255-268, 2022, DOI:10.32604/cmc.2022.021995 - 03 November 2021
Abstract Automatic biomedical signal recognition is an important process for several disease diagnoses. Particularly, Electrocardiogram (ECG) is commonly used to identify cardiovascular diseases. The professionals can determine the existence of cardiovascular diseases using the morphological patterns of the ECG signals. In order to raise the diagnostic accuracy and reduce the diagnostic time, automated computer aided diagnosis model is necessary. With the advancements of artificial intelligence (AI) techniques, large quantity of biomedical datasets can be easily examined for decision making. In this aspect, this paper presents an intelligent biomedical ECG signal processing (IBECG-SP) technique for CVD diagnosis.… More >

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ARTICLE

Abdullah Shoukat¹, Muhammad Ali Mughal^1,*, Saifullah Younus Gondal¹, Farhana Umer², Tahir Ejaz³, Ashiq Hussain¹
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 269-285, 2022, DOI:10.32604/cmc.2022.021575 - 03 November 2021
（This article belongs to the Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
Abstract Transmission line is a vital part of the power system that connects two major points, the generation, and the distribution. For an efficient design, stable control, and steady operation of the power system, adequate knowledge of the transmission line parameters resistance, inductance, capacitance, and conductance is of great importance. These parameters are essential for transmission network expansion planning in which a new parallel line is needed to be installed due to increased load demand or the overhead line is replaced with an underground cable. This paper presents a method to optimally estimate the parameters using… More >

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Hafifah Ab Hamid¹, Nazrul Anuar Nayan^1,*, Mohd Zubir Suboh¹, Nurin Izzati Mohamad Azizul¹, Mohamad Nazhan Mohd Nizar¹, Amilia Aminuddin², Mohd Shahrir Mohamed Said³, Saharuddin Ahmad⁴
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 287-304, 2022, DOI:10.32604/cmc.2022.021987 - 03 November 2021
（This article belongs to the Special Issue: Advances in Artificial Intelligence and Machine learning in Biomedical and Healthcare Informatics)
Abstract Hyperuricemia is an alarming issue that contributes to cardiovascular disease. Uric acid (UA) level was proven to be related to pulse wave velocity, a marker of arterial stiffness. A hyperuricemia prediction method utilizing photoplethysmogram (PPG) and arteriograph by using machine learning (ML) is proposed. From the literature search, there is no available papers found that relates PPG with UA level even though PPG is highly associated with vessel condition. The five phases in this research are data collection, signal preprocessing including denoising and signal quality indexes, features extraction for PPG and SDPPG waveform, statistical analysis… More >

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T. Gopalakrishnan¹, Periakaruppan Sudhakaran², K. C. Ramya³, K. Sathesh Kumar⁴, Fahd N. Al-Wesabi^5,6,*, Manal Abdullah Alohali⁷, Anwer Mustafa Hilal⁸
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 305-320, 2022, DOI:10.32604/cmc.2022.020914 - 03 November 2021
Abstract Muscular Dystrophy (MD) is a group of inherited muscular diseases that are commonly diagnosed with the help of techniques such as muscle biopsy, clinical presentation, and Muscle Magnetic Resonance Imaging (MRI). Among these techniques, Muscle MRI recommends the diagnosis of muscular dystrophy through identification of the patterns that exist in muscle fatty replacement. But the patterns overlap among various diseases whereas there is a lack of knowledge prevalent with regards to disease-specific patterns. Therefore, artificial intelligence techniques can be used in the diagnosis of muscular dystrophies, which enables us to analyze, learn, and predict for… More >

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1352

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Jaehwan Lee, Suhwan Kwak, Seungwoo Park, Sangoh Park^*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 321-338, 2022, DOI:10.32604/cmc.2022.021237 - 03 November 2021
Abstract Recently, the importance of vehicle safety supporting system has been highlighted as autonomous driving and platooning has attracted the researchers. To ensure driving safety, each vehicle must broadcast a basic safety message (BSM) every 100 ms. However, stable BSM exchange is difficult because of the changing environment and limited bandwidth of vehicular wireless communication. The increasing number of vehicles on the road increases the competition to access wireless networks for BSM exchange; this increases the packet collision rate. An increased packet collision rate impairs the transmission and reception of BSM information, which can easily cause… More >

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1392

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Alaa A. K. Ismaeel^1,2, Essam H. Houssein³, Amir Y. Hassan⁴, Mokhtar Said^5,*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 339-353, 2022, DOI:10.32604/cmc.2022.021517 - 03 November 2021
Abstract Renewable energy is a safe and limitless energy source that can be utilized for heating, cooling, and other purposes. Wind energy is one of the most important renewable energy sources. Power fluctuation of wind turbines occurs due to variation of wind velocity. A wind cube is used to decrease power fluctuation and increase the wind turbine’s power. The optimum design for a wind cube is the main contribution of this work. The decisive design parameters used to optimize the wind cube are its inner and outer radius, the roughness factor, and the height of the… More >

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1097

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ARTICLE

Jakkrit Onshaunjit, Jakkree Srinonchat^*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 355-367, 2022, DOI:10.32604/cmc.2022.017698 - 03 November 2021
Abstract An ideal printed circuit board (PCB) defect inspection system can detect defects and classify PCB defect types. Existing defect inspection technologies can identify defects but fail to classify all PCB defect types. This research thus proposes an algorithmic scheme that can detect and categorize all 14-known PCB defect types. In the proposed algorithmic scheme, fuzzy c-means clustering is used for image segmentation via image subtraction prior to defect detection. Arithmetic and logic operations, the circle hough transform (CHT), morphological reconstruction (MR), and connected component labeling (CCL) are used in defect classification. The algorithmic scheme achieves More >

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1436

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Noor Gul^1,2, Saeed Ahmed^1,3, Atif Elahi⁴, Su Min Kim¹, Junsu Kim^1,*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 369-387, 2022, DOI:10.32604/cmc.2022.022260 - 03 November 2021
（This article belongs to the Special Issue: Artificial Intelligence Convergence Networks Leveraging Software-Defined Networking)
Abstract Since the introduction of the Internet of Things (IoT), several researchers have been exploring its productivity to utilize and organize the spectrum assets. Cognitive radio (CR) technology is characterized as the best aspirant for wireless communications to augment IoT competencies. In the CR networks, secondary users (SUs) opportunistically get access to the primary users (PUs) spectrum through spectrum sensing. The multipath issues in the wireless channel can fluster the sensing ability of the individual SUs. Therefore, several cooperative SUs are engaged in cooperative spectrum sensing (CSS) to ensure reliable sensing results. In CSS, security is… More >

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Muhammad Shahid Bhatti^1,*, Saman Azhar¹, Abid Sohail¹, Mohammad Hijji², Hamna Ayemen¹, Areesha Ramzan¹
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 389-406, 2022, DOI:10.32604/cmc.2022.021384 - 03 November 2021
（This article belongs to the Special Issue: Computational Models for Pro-Smart Environments in Data Science Assisted IoT Systems)
Abstract In the age of the internet, social media are connecting us all at the tip of our fingers. People are linkedthrough different social media. The social network, Twitter, allows people to tweet their thoughts on any particular event or a specific political body which provides us with a diverse range of political insights. This paper serves the purpose of text processing of a multilingual dataset including Urdu, English, and Roman Urdu. Explore machine learning solutions for sentiment analysis and train models, collect the data on government from Twitter, apply sentiment analysis, and provide a python More >

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Muhammad Basit Umair¹, Zeshan Iqbal¹, Muhammad Bilal², Jamel Nebhen⁴, Tarik Adnan Almohamad³, Raja Majid Mehmood^5,*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 407-422, 2022, DOI:10.32604/cmc.2022.020727 - 03 November 2021
（This article belongs to the Special Issue: Green IoT Networks using Machine Learning, Deep Learning Models)
Abstract Internet of Things (IoT) defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central location. These IoT devices are connected to a network therefore prone to attacks. Various management tasks and network operations such as security, intrusion detection, Quality-of-Service provisioning, performance monitoring, resource provisioning, and traffic engineering require traffic classification. Due to the ineffectiveness of traditional classification schemes, such as port-based and payload-based methods, researchers proposed machine learning-based traffic classification systems based on shallow neural networks. Furthermore, machine learning-based models incline to misclassify… More >

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ARTICLE

Anurag Jain¹, Kusum Yadav², Hadeel Fahad Alharbi², Shamik Tiwari^1,*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 423-438, 2022, DOI:10.32604/cmc.2022.020238 - 03 November 2021
（This article belongs to the Special Issue: Emerging Trends and Real-World Applications of Intelligent Computing Techniques)
Abstract Corona is a viral disease that has taken the form of an epidemic and is causing havoc worldwide after its first appearance in the Wuhan state of China in December 2019. Due to the similarity in initial symptoms with viral fever, it is challenging to identify this virus initially. Non-detection of this virus at the early stage results in the death of the patient. Developing and densely populated countries face a scarcity of resources like hospitals, ventilators, oxygen, and healthcare workers. Technologies like the Internet of Things (IoT) and artificial intelligence can play a vital… More >

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1303

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Sultan H. Almotiri^*, Mohammed A. Al Ghamdi
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 439-455, 2022, DOI:10.32604/cmc.2022.021012 - 03 November 2021
（This article belongs to the Special Issue: Intelligent Computing Techniques for Communication Systems)
Abstract The identification of an effective network which can efficiently meet the service requirements of the target, while maintaining ultimate performance at an increased level is significant and challenging in a fully interconnected wireless medium. The wrong selection can contribute to unwanted situations like frustrated users, slow service, traffic congestion issues, missed and/or interrupted calls, and wastefulness of precious network components. Conventional schemes estimate the handoff need and cause the network screening process by a single metric. The strategies are not effective enough because traffic characteristics, user expectations, network terminology and other essential device metrics are… More >

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Milos Mravik¹, T. Vetriselvi², K. Venkatachalam^3,*, Marko Sarac¹, Nebojsa Bacanin¹, Sasa Adamovic¹
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 457-471, 2022, DOI:10.32604/cmc.2022.020687 - 03 November 2021
Abstract At present, the prevalence of diabetes is increasing because the human body cannot metabolize the glucose level. Accurate prediction of diabetes patients is an important research area. Many researchers have proposed techniques to predict this disease through data mining and machine learning methods. In prediction, feature selection is a key concept in preprocessing. Thus, the features that are relevant to the disease are used for prediction. This condition improves the prediction accuracy. Selecting the right features in the whole feature set is a complicated process, and many researchers are concentrating on it to produce a… More >

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Arfat Ahmad Khan¹, Chitapong Wechtaisong^1,*, Faizan Ahmed Khan², Nadeem Ahmad³
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 473-487, 2022, DOI:10.32604/cmc.2022.020903 - 03 November 2021
Abstract Environmental monitoring is essential for accessing and avoiding the undesirable situations in industries along with ensuring the safety of workers. Moreover, inspecting and monitoring of environmental parameters by humans lead to various health concerns, which in turn brings to the requirement of monitoring the environment by robotics. In this paper, we have designed and implemented a cost-efficient robotic vehicle for the computation of various environmental parameters such as temperature, radiation, smoke, and pressure with the help of sensors. Furthermore, the robotic vehicle is designed in such a way that it can be dually controlled by… More >

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R. D. Pubudu L. Indrasiri¹, Ernesto Lee², Vaibhav Rupapara³, Furqan Rustam⁴, Imran Ashraf^5,*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 489-515, 2022, DOI:10.32604/cmc.2022.019636 - 03 November 2021
Abstract Malicious traffic detection over the internet is one of the challenging areas for researchers to protect network infrastructures from any malicious activity. Several shortcomings of a network system can be leveraged by an attacker to get unauthorized access through malicious traffic. Safeguard from such attacks requires an efficient automatic system that can detect malicious traffic timely and avoid system damage. Currently, many automated systems can detect malicious activity, however, the efficacy and accuracy need further improvement to detect malicious traffic from multi-domain systems. The present study focuses on the detection of malicious traffic with high… More >

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1802

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WooHyun Park¹, Nawab Muhammad Faseeh Qureshi^2,*, Dong Ryeol Shin¹
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 517-535, 2022, DOI:10.32604/cmc.2022.021421 - 03 November 2021
（This article belongs to the Special Issue: Big Data Security Using Artificial Intelligence-based Approaches)
Abstract Spam mail classification considered complex and error-prone task in the distributed computing environment. There are various available spam mail classification approaches such as the naive Bayesian classifier, logistic regression and support vector machine and decision tree, recursive neural network, and long short-term memory algorithms. However, they do not consider the document when analyzing spam mail content. These approaches use the bag-of-words method, which analyzes a large amount of text data and classifies features with the help of term frequency-inverse document frequency. Because there are many words in a document, these approaches consume a massive amount… More >

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REVIEW

Haykel Marouani^1,2, Omar Al-mutiri^1,*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 537-571, 2022, DOI:10.32604/cmc.2022.020098 - 03 November 2021
Abstract The study of optimization methods for reliability–redundancy allocation problems is a constantly changing field. New algorithms are continually being designed on the basis of observations of nature, wildlife, and humanity. In this paper, we review eight major evolutionary algorithms that emulate the behavior of civilization, ants, bees, fishes, and birds (i.e., genetic algorithms, bee colony optimization, simulated annealing, particle swarm optimization, biogeography-based optimization, artificial immune system optimization, cuckoo algorithm and imperialist competitive algorithm). We evaluate the mathematical formulations and pseudo-codes of each algorithm and discuss how these apply to reliability–redundancy allocation problems. Results from a More >

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Najib Ahmed Mohammed¹, Ali Mohammed Mansoor^1,*, Rodina Binti Ahmad¹, Saaidal Razalli Bin Azzuhri²
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 573-592, 2022, DOI:10.32604/cmc.2022.020462 - 03 November 2021
Abstract Mission critical Machine-type Communication (mcMTC), also referred to as Ultra-reliable Low Latency Communication (URLLC), has become a research hotspot. It is primarily characterized by communication that provides ultra-high reliability and very low latency to concurrently transmit short commands to a massive number of connected devices. While the reduction in physical (PHY) layer overhead and improvement in channel coding techniques are pivotal in reducing latency and improving reliability, the current wireless standards dedicated to support mcMTC rely heavily on adopting the bottom layers of general-purpose wireless standards and customizing only the upper layers. The mcMTC has… More >

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Lihua Zhu¹, Yan Zhang¹, Yu Wang^1,*, Cheire Cheng²
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 593-609, 2022, DOI:10.32604/cmc.2022.022053 - 03 November 2021
Abstract In nowadays society, the safety of the elderly population is becoming a pressing concern, especially for those who live alone. There might be daily risks such as accidental falling or treatment attack on them. Aiming at these problems, indoor positioning could be a critical way to monitor their states. With the rapidly development of the imaging techniques, wearable and portable cameras are very popular, which could be set on human individual. And in view of the advantages of the visual positioning, the authors propose a binocular visual positioning algorithm to real-timely locate the elderly indoor.… More >

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Samir Salem Al-Bawri¹, Mohammad Tariqul Islam^2,*, Kabir Hossain^3,4, Thennarasan Sabapathy^3,4, Muzammil Jusoh^3,4
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 611-628, 2022, DOI:10.32604/cmc.2022.021244 - 03 November 2021
Abstract This paper presents a textile-based C-shaped split-ring resonators (SRR) metamaterial (MTM) unit cells with an electrical tunability function. The proposed MTM was composed of two symmetrical C-shaped SRR combined with a central diagonal metal bar, whereas the RF varactor diode is placed on the backside of the splitted ground plane. Stopband behavior of single and array MTM unit cells were analyzed while the achieved negative index physical characteristics were widely studies. Though four different MTM arrays (i.e., 1 × 1, 1 × 2, 2 × 1, and 2 × 2) were analyzed in simulation, a 2… More >

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1172

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Savita Khurana¹, Gaurav Sharma², Neha Miglani³, Aman Singh⁴, Abdullah Alharbi⁵, Wael Alosaimi⁵, Hashem Alyami⁶, Nitin Goyal^7,*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 629-649, 2022, DOI:10.32604/cmc.2022.021884 - 03 November 2021
Abstract COVID-19, being the virus of fear and anxiety, is one of the most recent and emergent of various respiratory disorders. It is similar to the MERS-COV and SARS-COV, the viruses that affected a large population of different countries in the year 2012 and 2002, respectively. Various standard models have been used for COVID-19 epidemic prediction but they suffered from low accuracy due to lesser data availability and a high level of uncertainty. The proposed approach used a machine learning-based time-series Facebook NeuralProphet model for prediction of the number of death as well as confirmed cases… More >

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A. Devipriya¹, P. Prabu², K. Venkatachalam³, Ahmed Zohair Ibrahim^4,*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 651-666, 2022, DOI:10.32604/cmc.2022.020820 - 03 November 2021
Abstract This research article proposes an automatic frame work for detecting COVID -19 at the early stage using chest X-ray image. It is an undeniable fact that coronovirus is a serious disease but the early detection of the virus present in human bodies can save lives. In recent times, there are so many research solutions that have been presented for early detection, but there is still a lack in need of right and even rich technology for its early detection. The proposed deep learning model analysis the pixels of every image and adjudges the presence of… More >

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1242

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Anwer Mustafa Hilal^1,*, Lamia Osman Widaa², Fahd N. Al-Wesabi³, Mohammad Medani³, Manar Ahmed Hamza¹, Mesfer Al Duhayyim⁴
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 667-681, 2022, DOI:10.32604/cmc.2022.021338 - 03 November 2021
Abstract The emergence of Beyond 5G (B5G) and 6G networks translated personal and industrial operations highly effective, reliable, and gainful by speeding up the growth of next generation Internet of Things (IoT). Industrial equipment in 6G encompasses a huge number of wireless sensors, responsible for collecting massive quantities of data. At the same time, 6G network can take real-world intelligent decisions and implement automated equipment operations. But the inclusion of different technologies into the system increased its energy consumption for which appropriate measures need to be taken. This has become mandatory for optimal resource allocation in… More >

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1168

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K. S. Bhuvaneshwari¹, J. Uma², K. Venkatachalam³, Mehedi Masud⁴, Mohamed Abouhawwash^5,6,*, T. Logeswaran⁷
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 683-695, 2022, DOI:10.32604/cmc.2022.021477 - 03 November 2021
Abstract Air pollution is one of the major concerns considering detriments to human health. This type of pollution leads to several health problems for humans, such as asthma, heart issues, skin diseases, bronchitis, lung cancer, and throat and eye infections. Air pollution also poses serious issues to the planet. Pollution from the vehicle industry is the cause of greenhouse effect and CO2 emissions. Thus, real-time monitoring of air pollution in these areas will help local authorities to analyze the current situation of the city and take necessary actions. The monitoring process has become efficient and dynamic… More >

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1381

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Imran Khan¹, Fahd N. Al-Wesabi², Marwa Obayya³, Anwer Mustafa Hilal⁴, Manar Ahmed Hamza⁴, Mohammed Rizwanullah⁴, Fahad Ahmed Al-Zahrani⁵, Hirofumi Amano⁶, Samih M. Mostafa^7,*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 697-715, 2022, DOI:10.32604/cmc.2022.021847 - 03 November 2021
Abstract With the rapid development of wireless communication technology, the spectrum resources are increasingly strained which needs optimal solutions. Cognitive radio (CR) is one of the key technologies to solve this problem. Spectrum sensing not only includes the precise detection of the communication signal of the primary user (PU), but also the precise identification of its modulation type, which can then determine the a priori information such as the PU’ service category, so as to use this information to make the cognitive user (CU) aware to discover and use the idle spectrum more effectively, and improve the… More >

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1117

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Siti Hajar Khairuddin, Mohd Hilmi Hasan^*, Emilia Akashah P. Akhir, Manzoor Ahmed Hashmani
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 717-734, 2022, DOI:10.32604/cmc.2022.020666 - 03 November 2021
（This article belongs to the Special Issue: Future Generation of Artificial Intelligence and Intelligent Internet of Things)
Abstract Fuzzy inference system (FIS) is a process of fuzzy logic reasoning to produce the output based on fuzzified inputs. The system starts with identifying input from data, applying the fuzziness to input using membership functions (MF), generating fuzzy rules for the fuzzy sets and obtaining the output. There are several types of input MFs which can be introduced in FIS, commonly chosen based on the type of real data, sensitivity of certain rule implied and computational limits. This paper focuses on the construction of interval type 2 (IT2) trapezoidal shape MF from fuzzy C Means… More >

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Muhammad Ahmad^1,*, M. Arfan Jaffar¹, Fawad Nasim¹, Tehreem Masood¹, Sheeraz Akram²
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 735-752, 2022, DOI:10.32604/cmc.2022.019691 - 03 November 2021
Abstract

Due to limited depth-of-field of digital single-lens reflex cameras, the scene content within a limited distance from the imaging plane remains in focus while other objects closer to or further away from the point of focus appear as blurred (out-of-focus) in the image. Multi-Focus Image Fusion can be used to reconstruct a fully focused image from two or more partially focused images of the same scene. In this paper, a new Fuzzy Based Hybrid Focus Measure (FBHFM) for multi-focus image fusion has been proposed. Optimal block size is very critical step for multi-focus image fusion.

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1134

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Muhammad Samiullah¹, Waqar Aslam¹, Arif Mehmood¹, Muhammad Saeed Ahmad², Shafiq Ahmad³, Adel M. Al-Shayea³, Muhammad Shafiq^4,*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 753-769, 2022, DOI:10.32604/cmc.2022.020432 - 03 November 2021
Abstract Smart and interconnected devices can generate meaningful patient data and exchange it automatically without any human intervention in order to realize the Internet of Things (IoT) in healthcare (HIoT). Due to more and more online security and data hijacking attacks, the confidentiality, integrity and availability of data are considered serious issues in HIoT applications. In this regard, lightweight block ciphers (LBCs) are promising in resource-constrained environment where security is the primary consideration. The prevalent challenge while designing an LBC for the HIoT environment is how to ascertain platform performance, cost, and security. Most of the… More >

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1059

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Muhammad Waqas Nadeem, Hock Guan Goh^*, Vasaki Ponnusamy, Yichiet Aun
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 771-789, 2022, DOI:10.32604/cmc.2022.021669 - 03 November 2021
（This article belongs to the Special Issue: Machine Learning Empowered Secure Computing for Intelligent Systems)
Abstract Software-defined network (SDN) becomes a new revolutionary paradigm in networks because it provides more control and network operation over a network infrastructure. The SDN controller is considered as the operating system of the SDN based network infrastructure, and it is responsible for executing the different network applications and maintaining the network services and functionalities. Despite all its tremendous capabilities, the SDN face many security issues due to the complexity of the SDN architecture. Distributed denial of services (DDoS) is a common attack on SDN due to its centralized architecture, especially at the control layer of… More >

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P. N. Palanisamy^*, N. Malmurugan
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 791-808, 2022, DOI:10.32604/cmc.2022.019921 - 03 November 2021
Abstract In recent years, deep neural networks have become a fascinating and influential research subject, and they play a critical role in video processing and analytics. Since, video analytics are predominantly hardware centric, exploration of implementing the deep neural networks in the hardware needs its brighter light of research. However, the computational complexity and resource constraints of deep neural networks are increasing exponentially by time. Convolutional neural networks are one of the most popular deep learning architecture especially for image classification and video analytics. But these algorithms need an efficient implement strategy for incorporating more real… More >

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1352

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Abdulsamad A. AL-Marghilani^*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 809-824, 2022, DOI:10.32604/cmc.2022.021185 - 03 November 2021
（This article belongs to the Special Issue: Intelligent Big Data Management and Machine Learning Techniques for IoT-Enabled Pervasive Computing)
Abstract Presently, suspect prediction of crime scenes can be considered as a classification task, which predicts the suspects based on the time, space, and type of crime. Performing digital forensic investigation in a big data environment poses several challenges to the investigational officer. Besides, the facial sketches are widely employed by the law enforcement agencies for assisting the suspect identification of suspects involved in crime scenes. The sketches utilized in the forensic investigations are either drawn by forensic artists or generated through the computer program (composite sketches) based on the verbal explanation given by the eyewitness… More >

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Mesfer Al Duhayyim¹, Marwa Obayya², Fahd N. Al-Wesabi^3,4, Anwer Mustafa Hilal^5,*, Mohammed Rizwanullah⁵, Majdy M. Eltahir⁶
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 825-842, 2022, DOI:10.32604/cmc.2022.021490 - 03 November 2021
Abstract With technological advancements in 6G and Internet of Things (IoT), the incorporation of Unmanned Aerial Vehicles (UAVs) and cellular networks has become a hot research topic. At present, the proficient evolution of 6G networks allows the UAVs to offer cost-effective and timely solutions for real-time applications such as medicine, tracking, surveillance, etc. Energy efficiency, data collection, and route planning are crucial processes to improve the network communication. These processes are highly difficult owing to high mobility, presence of non-stationary links, dynamic topology, and energy-restricted UAVs. With this motivation, the current research paper presents a novel… More >

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Zhang Nan¹, Li Wenjing^1,*, Liu Zhu¹, Li Zhi¹, Liu Yumin¹, Nurun Nahar²
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 843-854, 2022, DOI:10.32604/cmc.2022.017504 - 03 November 2021
Abstract With the continuous evolution of smart grid and global energy interconnection technology, amount of intelligent terminals have been connected to power grid, which can be used for providing resource services as edge nodes. Traditional cloud computing can be used to provide storage services and task computing services in the power grid, but it faces challenges such as resource bottlenecks, time delays, and limited network bandwidth resources. Edge computing is an effective supplement for cloud computing, because it can provide users with local computing services with lower latency. However, because the resources in a single edge… More >

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Visvasam Devadoss Ambeth Kumar¹, Chetan Swarup², Indhumathi Murugan¹, Abhishek Kumar³, Kamred Udham Singh⁴, Teekam Singh⁵, Ramu Dubey^6,*
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 855-869, 2022, DOI:10.32604/cmc.2022.021582 - 03 November 2021
（This article belongs to the Special Issue: Applications of Machine Learning for Big Data)
Abstract Cardio Vascular disease (CVD), involving the heart and blood vessels is one of the most leading causes of death throughout the world. There are several risk factors for causing heart diseases like sedentary lifestyle, unhealthy diet, obesity, diabetes, hypertension, smoking and consumption of alcohol, stress, hereditary factory etc. Predicting cardiovascular disease and improving and treating the risk factors at an early stage are of paramount importance to save the precious life of a human being. At present, the highly stressful life with bad lifestyle activities causes heart disease at a very young age. The main… More >

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1526

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Samira Mujkic^1,*, Suad Kasapovic¹, Mohammed Abuibaid²
CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 871-888, 2022, DOI:10.32604/cmc.2022.021441 - 03 November 2021
（This article belongs to the Special Issue: Radio Networks for new Disruptive Digital Services in Fourth Industrial Revolution)
Abstract This paper investigates the resource optimization problem for a multi-cell massive multiple-input multiple-output (MIMO) network in which each base station (BS) is equipped with a large number of antennas and each base station (BS) adapts the number of antennas to the daily load profile (DLP). This paper takes into consideration user location distribution (ULD) variation and evaluates its impact on the energy efficiency of load adaptive massive MIMO system. ULD variation is modeled by dividing the cell into two coverage areas with different user densities: boundary focused (BF) and center focused (CF) ULD. All cells… More >

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