Home / Journals / CMC / Vol.71, No.3, 2022
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  • Open AccessOpen Access

    ARTICLE

    Building a Trust Model for Secure Data Sharing (TM-SDS) in Edge Computing Using HMAC Techniques

    K. Karthikeyan*, P. Madhavan
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4183-4197, 2022, DOI:10.32604/cmc.2022.019802
    Abstract With the rapid growth of Internet of Things (IoT) based models, and the lack amount of data makes cloud computing resources insufficient. Hence, edge computing-based techniques are becoming more popular in present research domains that makes data storage, and processing effective at the network edges. There are several advanced features like parallel processing and data perception are available in edge computing. Still, there are some challenges in providing privacy and data security over networks. To solve the security issues in Edge Computing, Hash-based Message Authentication Code (HMAC) algorithm is used to provide solutions for preserving More >

  • Open AccessOpen Access

    ARTICLE

    Adaptive Runtime Monitoring of Service Level Agreement Violations in Cloud Computing

    Sami Ullah Khan1, Babar Nazir1, Muhammad Hanif2,*, Akhtar Ali3, Sardar Alam1, Usman Habib4
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4199-4220, 2022, DOI:10.32604/cmc.2022.020852
    (This article belongs to the Special Issue: AI for Wearable Sensing--Smartphone / Smartwatch User Identification / Authentication)
    Abstract The cloud service level agreement (SLA) manage the relationship between service providers and consumers in cloud computing. SLA is an integral and critical part of modern era IT vendors and communication contracts. Due to low cost and flexibility more and more consumers delegate their tasks to cloud providers, the SLA emerges as a key aspect between the consumers and providers. Continuous monitoring of Quality of Service (QoS) attributes is required to implement SLAs because of the complex nature of cloud communication. Many other factors, such as user reliability, satisfaction, and penalty on violations are also… More >

  • Open AccessOpen Access

    ARTICLE

    Automated Deep Learning Empowered Breast Cancer Diagnosis Using Biomedical Mammogram Images

    José Escorcia-Gutierrez1,*, Romany F. Mansour2, Kelvin Beleño3, Javier Jiménez-Cabas4, Meglys Pérez1, Natasha Madera1, Kevin Velasquez1
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4221-4235, 2022, DOI:10.32604/cmc.2022.022322
    Abstract Biomedical image processing is a hot research topic which helps to majorly assist the disease diagnostic process. At the same time, breast cancer becomes the deadliest disease among women and can be detected by the use of different imaging techniques. Digital mammograms can be used for the earlier identification and diagnostic of breast cancer to minimize the death rate. But the proper identification of breast cancer has mainly relied on the mammography findings and results to increased false positives. For resolving the issues of false positives of breast cancer diagnosis, this paper presents an automated… More >

  • Open AccessOpen Access

    ARTICLE

    SSABA: Search Step Adjustment Based Algorithm

    Fatemeh Ahmadi Zeidabadi1, Ali Dehghani2, Mohammad Dehghani3, Zeinab Montazeri4, Štěpán Hubálovský5, Pavel Trojovský3,*, Gaurav Dhiman6
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4237-4256, 2022, DOI:10.32604/cmc.2022.023682
    (This article belongs to the Special Issue: AI-Aided Innovative Cryptographic Techniques for Futuristic Secure Computing Systems)
    Abstract Finding the suitable solution to optimization problems is a fundamental challenge in various sciences. Optimization algorithms are one of the effective stochastic methods in solving optimization problems. In this paper, a new stochastic optimization algorithm called Search Step Adjustment Based Algorithm (SSABA) is presented to provide quasi-optimal solutions to various optimization problems. In the initial iterations of the algorithm, the step index is set to the highest value for a comprehensive search of the search space. Then, with increasing repetitions in order to focus the search of the algorithm in achieving the optimal solution closer… More >

  • Open AccessOpen Access

    ARTICLE

    SVM and KNN Based CNN Architectures for Plant Classification

    Sukanta Ghosh1, Amar Singh1, Kavita2,*, N. Z. Jhanjhi3, Mehedi Masud4, Sultan Aljahdali4
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4257-4274, 2022, DOI:10.32604/cmc.2022.023414
    Abstract Automatic plant classification through plant leaf is a classical problem in Computer Vision. Plants classification is challenging due to the introduction of new species with a similar pattern and look-a-like. Many efforts are made to automate plant classification using plant leaf, plant flower, bark, or stem. After much effort, it has been proven that leaf is the most reliable source for plant classification. But it is challenging to identify a plant with the help of leaf structure because plant leaf shows similarity in morphological variations, like sizes, textures, shapes, and venation. Therefore, it is required… More >

  • Open AccessOpen Access

    ARTICLE

    Adaptive Fuzzy Logic Controller for Harmonics Mitigation Using Particle Swarm Optimization

    Waleed Rafique1, Ayesha Khan2, Ahmad Almogren3, Jehangir Arshad1, Adnan Yousaf4, Mujtaba Hussain Jaffery1, Ateeq Ur Rehman5, Muhammad Shafiq6,*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4275-4293, 2022, DOI:10.32604/cmc.2022.023588
    Abstract An excessive use of non-linear devices in industry results in current harmonics that degrades the power quality with an unfavorable effect on power system performance. In this research, a novel control technique-based Hybrid-Active Power-Filter (HAPF) is implemented for reactive power compensation and harmonic current component for balanced load by improving the Power-Factor (PF) and Total–Hormonic Distortion (THD) and the performance of a system. This work proposed a soft-computing technique based on Particle Swarm-Optimization (PSO) and Adaptive Fuzzy technique to avoid the phase delays caused by conventional control methods. Moreover, the control algorithms are implemented for… More >

  • Open AccessOpen Access

    ARTICLE

    Binary Fruit Fly Swarm Algorithms for the Set Covering Problem

    Broderick Crawford1,*, Ricardo Soto1, Hanns de la Fuente Mella1, Claudio Elortegui1, Wenceslao Palma1, Claudio Torres-Rojas1, Claudia Vasconcellos-Gaete2, Marcelo Becerra1, Javier Peña1, Sanjay Misra3
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4295-4318, 2022, DOI:10.32604/cmc.2022.023068
    (This article belongs to the Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
    Abstract Currently, the industry is experiencing an exponential increase in dealing with binary-based combinatorial problems. In this sense, metaheuristics have been a common trend in the field in order to design approaches to solve them successfully. Thus, a well-known strategy consists in the use of algorithms based on discrete swarms transformed to perform in binary environments. Following the No Free Lunch theorem, we are interested in testing the performance of the Fruit Fly Algorithm, this is a bio-inspired metaheuristic for deducing global optimization in continuous spaces, based on the foraging behavior of the fruit fly, which… More >

  • Open AccessOpen Access

    ARTICLE

    Unified FPGA Design for the HEVC Dequantization and Inverse Transform Modules

    Turki M. Alanazi, Ahmed Ben Atitallah*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4319-4335, 2022, DOI:10.32604/cmc.2022.022988
    Abstract As the newest standard, the High Efficiency Video Coding (HEVC) is specially designed to minimize the bitrate for video data transfer and to support High Definition (HD) and ULTRA HD video resolutions at the cost of increasing computational complexity relative to earlier standards like the H.264. Therefore, real-time video decoding with HEVC decoder becomes a challenging task. However, the Dequantization and Inverse Transform (DE/IT) are one of the computationally intensive modules in the HEVC decoder which are used to reconstruct the residual block. Thus, in this paper, a unified hardware architecture is proposed to implement… More >

  • Open AccessOpen Access

    ARTICLE

    An EFSM-Based Test Data Generation Approach in Model-Based Testing

    Muhammad Luqman Mohd-Shafie1,*, Wan Mohd Nasir Wan Kadir1, Muhammad Khatibsyarbini1, Mohd Adham Isa1, Israr Ghani1, Husni Ruslai2
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4337-4354, 2022, DOI:10.32604/cmc.2022.023803
    Abstract Testing is an integral part of software development. Current fast-paced system developments have rendered traditional testing techniques obsolete. Therefore, automated testing techniques are needed to adapt to such system developments speed. Model-based testing (MBT) is a technique that uses system models to generate and execute test cases automatically. It was identified that the test data generation (TDG) in many existing model-based test case generation (MB-TCG) approaches were still manual. An automatic and effective TDG can further reduce testing cost while detecting more faults. This study proposes an automated TDG approach in MB-TCG using the extended… More >

  • Open AccessOpen Access

    ARTICLE

    Parking Availability Prediction with Coarse-Grained Human Mobility Data

    Aurora Gonzalez-Vidal1, Fernando Terroso-Sáenz2,*, Antonio Skarmeta1
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4355-4375, 2022, DOI:10.32604/cmc.2022.021492
    Abstract Nowadays, the anticipation of parking-space demand is an instrumental service in order to reduce traffic congestion levels in urban spaces. The purpose of our work is to study, design and develop a parking-availability predictor that extracts the knowledge from human mobility data, based on the anonymized human displacements of an urban area, and also from weather conditions. Most of the existing solutions for this prediction take as contextual data the current road-traffic state defined at very high temporal or spatial resolution. However, access to this type of fine-grained location data is usually quite limited due… More >

  • Open AccessOpen Access

    ARTICLE

    Enhance Egocentric Grasp Recognition Based Flex Sensor Under Low Illumination

    Chana Chansri, Jakkree Srinonchat*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4377-4389, 2022, DOI:10.32604/cmc.2022.024026
    Abstract Egocentric recognition is exciting computer vision research by acquiring images and video from the first-person overview. However, an image becomes noisy and dark under low illumination conditions, making subsequent hand detection tasks difficult. Thus, image enhancement is necessary to make buried detail more visible. This article addresses the challenge of egocentric hand grasp recognition in low light conditions by utilizing the flex sensor and image enhancement algorithm based on adaptive gamma correction with weighting distribution. Initially, a flex sensor is installed to the thumb for object manipulation. The thumb placement that holds in a different More >

  • Open AccessOpen Access

    ARTICLE

    Efficient Data Compression of ECG Signal Based on Modified Discrete Cosine Transform

    Ashraf Mohamed Ali Hassan1, Mohammed S. Alzaidi2, Sherif S. M. Ghoneim2,3,*, Waleed El Nahal4
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4391-4408, 2022, DOI:10.32604/cmc.2022.024044
    Abstract This paper introduced an efficient compression technique that uses the compressive sensing (CS) method to obtain and recover sparse electrocardiography (ECG) signals. The recovery of the signal can be achieved by using sampling rates lower than the Nyquist frequency. A novel analysis was proposed in this paper. To apply CS on ECG signal, the first step is to generate a sparse signal, which can be obtained using Modified Discrete Cosine Transform (MDCT) on the given ECG signal. This transformation is a promising key for other transformations used in this search domain and can be considered… More >

  • Open AccessOpen Access

    ARTICLE

    PSO Based Multi-Objective Approach for Controlling PID Controller

    Harsh Goud1, Prakash Chandra Sharma2, Kashif Nisar3, Ag. Asri Ag. Ibrahim3,*, Muhammad Reazul Haque4, Narendra Singh Yadav2, Pankaj Swarnkar5, Manoj Gupta6, Laxmi Chand6
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4409-4423, 2022, DOI:10.32604/cmc.2022.019217
    Abstract CSTR (Continuous stirred tank reactor) is employed in process control and chemical industries to improve response characteristics and system efficiency. It has a highly nonlinear characteristic that includes complexities in its control and design. Dynamic performance is compassionate to change in system parameters which need more effort for planning a significant controller for CSTR. The reactor temperature changes in either direction from the defined reference value. It is important to note that the intensity of chemical actions inside the CSTR is dependent on the various levels of temperature, and deviation from reference values may cause… More >

  • Open AccessOpen Access

    ARTICLE

    Explainable Artificial Intelligence Solution for Online Retail

    Kumail Javaid1, Ayesha Siddiqa2, Syed Abbas Zilqurnain Naqvi2, Allah Ditta3, Muhammad Ahsan2, M. A. Khan4, Tariq Mahmood5, Muhammad Adnan Khan6,*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4425-4442, 2022, DOI:10.32604/cmc.2022.022984
    Abstract Artificial intelligence (AI) and machine learning (ML) help in making predictions and businesses to make key decisions that are beneficial for them. In the case of the online shopping business, it’s very important to find trends in the data and get knowledge of features that helps drive the success of the business. In this research, a dataset of 12,330 records of customers has been analyzed who visited an online shopping website over a period of one year. The main objective of this research is to find features that are relevant in terms of correctly predicting… More >

  • Open AccessOpen Access

    ARTICLE

    Traffic Priority-Aware Medical Data Dissemination Scheme for IoT Based WBASN Healthcare Applications

    Muhammad Anwar1, Farhan Masud2, Rizwan Aslam Butt3, Sevia Mahdaliza Idrus4,*, Mohammad Nazir Ahmad5, Mohd Yazid Bajuri6
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4443-4456, 2022, DOI:10.32604/cmc.2022.022826
    Abstract Wireless Body Area Sensor Network (WBASN) is an automated system for remote health monitoring of patients. WBASN under umbrella of Internet of Things (IoT) is comprised of small Biomedical Sensor Nodes (BSNs) that can communicate with each other without human involvement. These BSNs can be placed on human body or inside the skin of the patients to regularly monitor their vital signs. The BSNs generate critical data as it is related to patient's health. The data traffic can be classified as Sensitive Data (SD) and Non-sensitive Data (ND) packets based on the value of vital… More >

  • Open AccessOpen Access

    ARTICLE

    Gauss Gradient and SURF Features for Landmine Detection from GPR Images

    Fatma M. El-Ghamry1,2, Walid El-Shafai2, Mahmouad I. Abdalla1, Ghada M. El-Banby3, Abeer D. Algarni4,*, Moawad I. Dessouky2, Adel S. Elfishawy2, Fathi E. Abd El-Samie2,4, Naglaa F. Soliman1,4
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4457-4487, 2022, DOI:10.32604/cmc.2022.022328
    Abstract Recently, ground-penetrating radar (GPR) has been extended as a well-known area to investigate the subsurface objects. However, its output has a low resolution, and it needs more processing for more interpretation. This paper presents two algorithms for landmine detection from GPR images. The first algorithm depends on a multi-scale technique. A Gaussian kernel with a particular scale is convolved with the image, and after that, two gradients are estimated; horizontal and vertical gradients. Then, histogram and cumulative histogram are estimated for the overall gradient image. The bin values on the cumulative histogram are used for More >

  • Open AccessOpen Access

    ARTICLE

    Machine Learning-Based Predictions on the Self-Heating Characteristics of Nanocomposites with Hybrid Fillers

    Taegeon Kil1, D. I. Jang1, H. N. Yoon1, Beomjoo Yang2,*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4487-4502, 2022, DOI:10.32604/cmc.2022.020940
    Abstract A machine learning-based prediction of the self-heating characteristics and the negative temperature coefficient (NTC) effect detection of nanocomposites incorporating carbon nanotube (CNT) and carbon fiber (CF) is proposed. The CNT content was fixed at 4.0 wt.%, and CFs having three different lengths (0.1, 3 and 6 mm) at dosage of 1.0 wt.% were added to fabricate the specimens. The self-heating properties of the specimens were evaluated via self-heating tests. Based on the experiment results, two types of artificial neural network (ANN) models were constructed to predict the surface temperature and electrical resistance, and to detect More >

  • Open AccessOpen Access

    ARTICLE

    Atmospheric Convection Model Based Digital Confidentiality Scheme

    Noor Munir1, Majid Khan1,*, Mohammad Mazyad Hazzazi2, Amer Aljaedi3, Sajjad Shaukat Jamal2, Iqtadar Hussain4
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4503-4522, 2022, DOI:10.32604/cmc.2022.021077
    Abstract Nonlinear dynamics is a fascinating area that is intensely affecting a wide range of different disciplines of science and technology globally. The combination of different innovative topics of information security and high-speed computing has added new visions into the behavior of complex nonlinear dynamical systems which uncovered amazing results even in the least difficult nonlinear models. The generation of complex actions from a very simple dynamical method has a strong relation with information security. The protection of digital content is one of the inescapable concerns of the digitally advanced world. Today, information plays an important… More >

  • Open AccessOpen Access

    ARTICLE

    A Real-Time Oral Cavity Gesture Based Words Synthesizer Using Sensors

    Palli Padmini1, C. Paramasivam1, G. Jyothish Lal2, Sadeen Alharbi3,*, Kaustav Bhowmick4
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4523-4554, 2022, DOI:10.32604/cmc.2022.022857
    Abstract The present system experimentally demonstrates a synthesis of syllables and words from tongue manoeuvers in multiple languages, captured by four oral sensors only. For an experimental demonstration of the system used in the oral cavity, a prototype tooth model was used. Based on the principle developed in a previous publication by the author(s), the proposed system has been implemented using the oral cavity (tongue, teeth, and lips) features alone, without the glottis and the larynx. The positions of the sensors in the proposed system were optimized based on articulatory (oral cavity) gestures estimated by simulating… More >

  • Open AccessOpen Access

    ARTICLE

    Use of Local Region Maps on Convolutional LSTM for Single-Image HDR Reconstruction

    Seungwook Oh, GyeongIk Shin, Hyunki Hong*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4555-4572, 2022, DOI:10.32604/cmc.2022.022086
    (This article belongs to the Special Issue: Application of Machine-Learning in Computer Vision)
    Abstract Low dynamic range (LDR) images captured by consumer cameras have a limited luminance range. As the conventional method for generating high dynamic range (HDR) images involves merging multiple-exposure LDR images of the same scene (assuming a stationary scene), we introduce a learning-based model for single-image HDR reconstruction. An input LDR image is sequentially segmented into the local region maps based on the cumulative histogram of the input brightness distribution. Using the local region maps, SParam-Net estimates the parameters of an inverse tone mapping function to generate a pseudo-HDR image. We process the segmented region maps More >

  • Open AccessOpen Access

    ARTICLE

    Transfer Learning-based Computer-aided Diagnosis System for Predicting Grades of Diabetic Retinopathy

    Qaisar Abbas1,*, Mostafa E. A. Ibrahim1,2, Abdul Rauf Baig1
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4573-4590, 2022, DOI:10.32604/cmc.2022.023670
    (This article belongs to the Special Issue: Innovative Technology For Machine Intelligence)
    Abstract Diabetic retinopathy (DR) diagnosis through digital fundus images requires clinical experts to recognize the presence and importance of many intricate features. This task is very difficult for ophthalmologists and time-consuming. Therefore, many computer-aided diagnosis (CAD) systems were developed to automate this screening process of DR. In this paper, a CAD-DR system is proposed based on preprocessing and a pre-train transfer learning-based convolutional neural network (PCNN) to recognize the five stages of DR through retinal fundus images. To develop this CAD-DR system, a preprocessing step is performed in a perceptual-oriented color space to enhance the DR-related… More >

  • Open AccessOpen Access

    ARTICLE

    SBOOSP for Massive Devices in 5G WSNs Using Conformable Chaotic Maps

    Chandrashekhar Meshram1,*, Agbotiname Lucky Imoize2,3, Sajjad Shaukat Jamal4, Amer Aljaedi5, Adel R. Alharbi5
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4591-4608, 2022, DOI:10.32604/cmc.2022.022642
    Abstract The commercialization of the fifth-generation (5G) wireless network has begun. Massive devices are being integrated into 5G-enabled wireless sensor networks (5G WSNs) to deliver a variety of valuable services to network users. However, there are rising fears that 5G WSNs will expose sensitive user data to new security vulnerabilities. For secure end-to-end communication, key agreement and user authentication have been proposed. However, when billions of massive devices are networked to collect and analyze complex user data, more stringent security approaches are required. Data integrity, non-repudiation, and authentication necessitate special-purpose subtree-based signature mechanisms that are pretty… More >

  • Open AccessOpen Access

    ARTICLE

    Profiling Casualty Severity Levels of Road Accident Using Weighted Majority Voting

    Saba Awan1, Zahid Mehmood2,*, Hassan Nazeer Chaudhry3, Usman Tariq4, Amjad Rehman5, Tanzila Saba5, Muhammad Rashid6
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4609-4626, 2022, DOI:10.32604/cmc.2022.019404
    Abstract To determine the individual circumstances that account for a road traffic accident, it is crucial to consider the unplanned connections amongst various factors related to a crash that results in high casualty levels. Analysis of the road accident data concentrated mainly on categorizing accidents into different types using individually built classification methods which limit the prediction accuracy and fitness of the model. In this article, we proposed a multi-model hybrid framework of the weighted majority voting (WMV) scheme with parallel structure, which is designed by integrating individually implemented multinomial logistic regression (MLR) and multilayer perceptron… More >

  • Open AccessOpen Access

    ARTICLE

    Metaheuristic Optimization Algorithm for Signals Classification of Electroencephalography Channels

    Marwa M. Eid1,*, Fawaz Alassery2, Abdelhameed Ibrahim3, Mohamed Saber4
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4627-4641, 2022, DOI:10.32604/cmc.2022.024043
    Abstract Digital signal processing of electroencephalography (EEG) data is now widely utilized in various applications, including motor imagery classification, seizure detection and prediction, emotion classification, mental task classification, drug impact identification and sleep state classification. With the increasing number of recorded EEG channels, it has become clear that effective channel selection algorithms are required for various applications. Guided Whale Optimization Method (Guided WOA), a suggested feature selection algorithm based on Stochastic Fractal Search (SFS) technique, evaluates the chosen subset of channels. This may be used to select the optimum EEG channels for use in Brain-Computer Interfaces More >

  • Open AccessOpen Access

    ARTICLE

    Skeleton Split Strategies for Spatial Temporal Graph Convolution Networks

    Motasem S. Alsawadi*, Miguel Rio
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4643-4658, 2022, DOI:10.32604/cmc.2022.022783
    Abstract Action recognition has been recognized as an activity in which individuals’ behaviour can be observed. Assembling profiles of regular activities such as activities of daily living can support identifying trends in the data during critical events. A skeleton representation of the human body has been proven to be effective for this task. The skeletons are presented in graphs form-like. However, the topology of a graph is not structured like Euclidean-based data. Therefore, a new set of methods to perform the convolution operation upon the skeleton graph is proposed. Our proposal is based on the Spatial… More >

  • Open AccessOpen Access

    ARTICLE

    Hybrid In-Vehicle Background Noise Reduction for Robust Speech Recognition: The Possibilities of Next Generation 5G Data Networks

    Radek Martinek1, Jan Baros1, Rene Jaros1, Lukas Danys1,*, Jan Nedoma2
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4659-4676, 2022, DOI:10.32604/cmc.2022.019904
    Abstract This pilot study focuses on employment of hybrid LMS-ICA system for in-vehicle background noise reduction. Modern vehicles are nowadays increasingly supporting voice commands, which are one of the pillars of autonomous and SMART vehicles. Robust speaker recognition for context-aware in-vehicle applications is limited to a certain extent by in-vehicle background noise. This article presents the new concept of a hybrid system, which is implemented as a virtual instrument. The highly modular concept of the virtual car used in combination with real recordings of various driving scenarios enables effective testing of the investigated methods of in-vehicle More >

  • Open AccessOpen Access

    ARTICLE

    Drone-based AI/IoT Framework for Monitoring, Tracking and Fighting Pandemics

    Abdelhamied A. Ateya1,2, Abeer D. Algarni1, Andrey Koucheryavy3, Naglaa. F. Soliman1,2,*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4677-4699, 2022, DOI:10.32604/cmc.2022.021850
    Abstract Since World Health Organization (WHO) has declared the Coronavirus disease (COVID-19) a global pandemic, the world has changed. All life's fields and daily habits have moved to adapt to this new situation. According to WHO, the probability of such virus pandemics in the future is high, and recommends preparing for worse situations. To this end, this work provides a framework for monitoring, tracking, and fighting COVID-19 and future pandemics. The proposed framework deploys unmanned aerial vehicles (UAVs), e.g.; quadcopter and drone, integrated with artificial intelligence (AI) and Internet of Things (IoT) to monitor and fight… More >

  • Open AccessOpen Access

    ARTICLE

    Modified UNet Model for Brain Stroke Lesion Segmentation on Computed Tomography Images

    Batyrkhan Omarov1,2,3, Azhar Tursynova1,*, Octavian Postolache4, Khaled Gamry5, Aidar Batyrbekov5, Sapargali Aldeshov6,7, Zhanar Azhibekova9, Marat Nurtas5,8, Akbayan Aliyeva6, Kadrzhan Shiyapov10,11
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4701-4717, 2022, DOI:10.32604/cmc.2022.020998
    Abstract The task of segmentation of brain regions affected by ischemic stroke is help to tackle important challenges of modern stroke imaging analysis. Unfortunately, at the moment, the models for solving this problem using machine learning methods are far from ideal. In this paper, we consider a modified 3D UNet architecture to improve the quality of stroke segmentation based on 3D computed tomography images. We use the ISLES 2018 (Ischemic Stroke Lesion Segmentation Challenge 2018) open dataset to train and test the proposed model. Interpretation of the obtained results, as well as the ideas for further… More >

  • Open AccessOpen Access

    ARTICLE

    Plant Identification Using Fitness-Based Position Update in Whale Optimization Algorithm

    Ayman Altameem1, Sandeep Kumar2, Ramesh Chandra Poonia3, Abdul Khader Jilani Saudagar4,*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4719-4736, 2022, DOI:10.32604/cmc.2022.022177
    (This article belongs to the Special Issue: Recent advancements in Environment Sustainability, AgriFood using applied artificial intelligence in Multimedia Systems)
    Abstract Since the beginning of time, humans have relied on plants for food, energy, and medicine. Plants are recognized by leaf, flower, or fruit and linked to their suitable cluster. Classification methods are used to extract and select traits that are helpful in identifying a plant. In plant leaf image categorization, each plant is assigned a label according to its classification. The purpose of classifying plant leaf images is to enable farmers to recognize plants, leading to the management of plants in several aspects. This study aims to present a modified whale optimization algorithm and categorizes More >

  • Open AccessOpen Access

    ARTICLE

    Graphene-Based RFID Tag Antenna for Vehicular Smart Border Passings

    Prach Asavanarakul, Amnoiy Ruengwaree*, Suwat Sakulchat
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4737-4748, 2022, DOI:10.32604/cmc.2022.023743
    Abstract Globalization has opened practically every country in the globe to tourism and commerce today. In every region, the volume of vehicles traveling through border crossings has increased significantly. Smartcards and radio frequency identification (RFID) have been proposed as a new method of identifying and authenticating passengers, products, and vehicles. However, the usage of smartcards and RFID tag cards for vehicular border crossings continues to suffer security and flexibility challenges. Providing a vehicle's driver a smartcard or RFID tag card may result in theft, loss, counterfeit, imitation, or vehicle transmutation. RFID sticker tags would replace RFID… More >

  • Open AccessOpen Access

    ARTICLE

    E-mail Spam Classification Using Grasshopper Optimization Algorithm and Neural Networks

    Sanaa A. A. Ghaleb1,3,4, Mumtazimah Mohamad1, Syed Abdullah Fadzli1, Waheed A.H.M. Ghanem2,3,4,*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4749-4766, 2022, DOI:10.32604/cmc.2022.020472
    Abstract Spam has turned into a big predicament these days, due to the increase in the number of spam emails, as the recipient regularly receives piles of emails. Not only is spam wasting users’ time and bandwidth. In addition, it limits the storage space of the email box as well as the disk space. Thus, spam detection is a challenge for individuals and organizations alike. To advance spam email detection, this work proposes a new spam detection approach, using the grasshopper optimization algorithm (GOA) in training a multilayer perceptron (MLP) classifier for categorizing emails as ham More >

  • Open AccessOpen Access

    ARTICLE

    Mobile Devices Interface Adaptivity Using Ontologies

    Muhammad Waseem Iqbal1, Muhammad Raza Naqvi2, Muhammad Adnan Khan3,4, Faheem Khan5, T. Whangbo5,*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4767-4784, 2022, DOI:10.32604/cmc.2022.023239
    Abstract Currently, many mobile devices provide various interaction styles and modes which create complexity in the usage of interfaces. The context offers the information base for the development of Adaptive user interface (AUI) frameworks to overcome the heterogeneity. For this purpose, the ontological modeling has been made for specific context and environment. This type of philosophy states to the relationship among elements (e.g., classes, relations, or capacities etc.) with understandable satisfied representation. The context mechanisms can be examined and understood by any machine or computational framework with these formal definitions expressed in Web ontology language (WOL)/Resource… More >

  • Open AccessOpen Access

    ARTICLE

    A New Hybrid SARFIMA-ANN Model for Tourism Forecasting

    Tanzila Saba1, Mirza Naveed Shahzad2,*, Sonia Iqbal2,3, Amjad Rehman1, Ibrahim Abunadi1
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4785-4801, 2022, DOI:10.32604/cmc.2022.022309
    Abstract Many countries developed and increased greenery in their country sights to attract international tourists. This planning is now significantly contributing to their economy. The next task is to facilitate the tourists by sufficient arrangements and providing a green and clean environment; it is only possible if an upcoming number of tourists’ arrivals are accurately predicted. But accurate prediction is not easy as empirical evidence shows that the tourists’ arrival data often contains linear, nonlinear, and seasonal patterns. The traditional model, like the seasonal autoregressive fractional integrated moving average (SARFIMA), handles seasonal trends with seasonality. In… More >

  • Open AccessOpen Access

    REVIEW

    Milestones of Wireless Communication Networks and Technology Prospect of Next Generation (6G)

    Mohammed H. Alsharif1, Md. Sanwar Hossain2, Abu Jahid3, Muhammad Asghar Khan4, Bong Jun Choi5,*, Samih M. Mostafa6,7
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4803-4818, 2022, DOI:10.32604/cmc.2022.023500
    Abstract Since around 1980, a new generation of wireless technology has arisen approximately every 10 years. First-generation (1G) and second-generation (2G) began with voice and eventually introduced more and more data in third-generation (3G) and became highly popular in the fourth-generation (4G). To increase the data rate along with low latency and mass connectivity the fifth-generation (5G) networks are being installed from 2020. However, the 5G technology will not be able to fulfill the data demand at the end of this decade. Therefore, it is expected that 6G communication networks will rise, providing better services through… More >

  • Open AccessOpen Access

    ARTICLE

    Robust Watermarking of Screen-Photography Based on JND

    Siyu Gu1, Jin Han1,*, Xingming Sun1,2, Yi Cao1,3
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4819-4833, 2022, DOI:10.32604/cmc.2022.023955
    Abstract With the popularity of smartphones, it is often easy to maliciously leak important information by taking pictures of the phone. Robust watermarking that can resist screen photography can achieve the protection of information. Since the screen photo process can cause some irreversible distortion, the currently available screen photo watermarks do not consider the image content well and the visual quality is not very high. Therefore, this paper proposes a new screen-photography robust watermark. In terms of embedding region selection, the intensity-based Scale-invariant feature transform (SIFT) algorithm used for the construction of feature regions based on… More >

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    ARTICLE

    Hydrodynamics and Heat Transfer Analysis of Airflow in a Sinusoidally Curved Channel

    Abid. A. Memon1, M. Asif Memon1, Kaleemullah Bhatti1, Thanin Sitthiwirattham2,*, Nichaphat Patanarapeelert3
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4835-4853, 2022, DOI:10.32604/cmc.2022.023912
    Abstract For heat transfer enhancement in heat exchangers, different types of channels are often tested. The performance of heat exchangers can be made better by considering geometry composed of sinusoidally curved walls. This research studies the modeling and simulation of airflow through a units long sinusoidally curved wavy channel. For the purpose, two-dimensional Navier Stokes equations along with heat equations are under consideration. To simulate the fluid flow problem, the finite element-based software COMSOL Multiphysics is used. The parametric study for Reynolds number from to and the period of vibration P from to are observed. The surface… More >

  • Open AccessOpen Access

    ARTICLE

    Fuzzy Control Based Resource Scheduling in IoT Edge Computing

    Samah Alhazmi, Kailash Kumar*, Soha Alhelaly
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4855-4870, 2022, DOI:10.32604/cmc.2022.024012
    Abstract Edge Computing is a new technology in Internet of Things (IoT) paradigm that allows sensitive data to be sent to disperse devices quickly and without delay. Edge is identical to Fog, except its positioning in the end devices is much nearer to end-users, making it process and respond to clients in less time. Further, it aids sensor networks, real-time streaming apps, and the IoT, all of which require high-speed and dependable internet access. For such an IoT system, Resource Scheduling Process (RSP) seems to be one of the most important tasks. This paper presents a… More >

  • Open AccessOpen Access

    ARTICLE

    Efficient Computer Aided Diagnosis System for Hepatic Tumors Using Computed Tomography Scans

    Yasmeen Al-Saeed1,2, Wael A. Gab-Allah1, Hassan Soliman1, Maysoon F. Abulkhair3, Wafaa M. Shalash4, Mohammed Elmogy1,*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4871-4894, 2022, DOI:10.32604/cmc.2022.023638
    Abstract One of the leading causes of mortality worldwide is liver cancer. The earlier the detection of hepatic tumors, the lower the mortality rate. This paper introduces a computer-aided diagnosis system to extract hepatic tumors from computed tomography scans and classify them into malignant or benign tumors. Segmenting hepatic tumors from computed tomography scans is considered a challenging task due to the fuzziness in the liver pixel range, intensity values overlap between the liver and neighboring organs, high noise from computed tomography scanner, and large variance in tumors shapes. The proposed method consists of three main More >

  • Open AccessOpen Access

    ARTICLE

    Smart Bubble Sort: A Novel and Dynamic Variant of Bubble Sort Algorithm

    Mohammad Khalid Imam Rahmani*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4895-4913, 2022, DOI:10.32604/cmc.2022.023837
    Abstract In the present era, a very huge volume of data is being stored in online and offline databases. Enterprise houses, research, medical as well as healthcare organizations, and academic institutions store data in databases and their subsequent retrievals are performed for further processing. Finding the required data from a given database within the minimum possible time is one of the key factors in achieving the best possible performance of any computer-based application. If the data is already sorted, finding or searching is comparatively faster. In real-life scenarios, the data collected from different sources may not… More >

  • Open AccessOpen Access

    ARTICLE

    Hybridization of CNN with LBP for Classification of Melanoma Images

    Saeed Iqbal1,*, Adnan N. Qureshi1, Ghulam Mustafa2
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4915-4939, 2022, DOI:10.32604/cmc.2022.023178
    Abstract Skin cancer (melanoma) is one of the most aggressive of the cancers and the prevalence has significantly increased due to increased exposure to ultraviolet radiation. Therefore, timely detection and management of the lesion is a critical consideration in order to improve lifestyle and reduce mortality. To this end, we have designed, implemented and analyzed a hybrid approach entailing convolutional neural networks (CNN) and local binary patterns (LBP). The experiments have been performed on publicly accessible datasets ISIC 2017, 2018 and 2019 (HAM10000) with data augmentation for in-distribution generalization. As a novel contribution, the CNN architecture More >

  • Open AccessOpen Access

    ARTICLE

    5G Smart Mobility Management Based Fuzzy Logic Controller Unit

    Chafaa Hamrouni1,*, Slim Chaoui2
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4941-4953, 2022, DOI:10.32604/cmc.2022.023732
    Abstract In the paper, we propose a fuzzy logic controller system to be implemented for smart mobility management in the 5G wireless communication network. Mobility management is considered as a main issue for all-IP mobile networks future generation. As a network-based mobility management protocol, Internet Engineering Task Force developed the Proxy Mobile IPv6 (PMIPv6) in order to support the mobility of IP devices, and many other results were presented to reduce latency handover and the amount of PMIPv6 signaling, but it is not enough for the application needs in real-time. The present paper describes an approach More >

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    ARTICLE

    Man Overboard Detection System Using IoT for Navigation Model

    Hüseyin Gürüler1, Murat Altun1, Faheem Khan2, Taegkeun Whangbo2,*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4955-4969, 2022, DOI:10.32604/cmc.2022.023556
    (This article belongs to the Special Issue: Machine Learning Empowered Secure Computing for Intelligent Systems)
    Abstract Security measures and contingency plans have been established in order to ensure human safety especially in the floating elements like ferry, ro-ro, catamaran, frigate, yacht that are the vehicles services for the purpose of logistic and passenger transport. In this paper, all processes in the event of Man overboard (MOB)are initiated for smart transportation. In MOB the falling person is totally dependent on the person who first saw the falling person. The main objective of this paper is to develop a solution to this significant problem. If a staff member or a passenger does not… More >

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    ARTICLE

    Text Encryption Using Pell Sequence and Elliptic Curves with Provable Security

    Sumaira Azhar1, Naveed Ahmed Azam2,*, Umar Hayat1
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4971-4988, 2022, DOI:10.32604/cmc.2022.023685
    Abstract The demand for data security schemes has increased with the significant advancement in the field of computation and communication networks. We propose a novel three-step text encryption scheme that has provable security against computation attacks such as key attack and statistical attack. The proposed scheme is based on the Pell sequence and elliptic curves, where at the first step the plain text is diffused to get a meaningless plain text by applying a cyclic shift on the symbol set. In the second step, we hide the elements of the diffused plain text from the attackers. More >

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    ARTICLE

    Optimized Ensemble Algorithm for Predicting Metamaterial Antenna Parameters

    El-Sayed M. El-kenawy1,2, Abdelhameed Ibrahim3,*, Seyedali Mirjalili4,5, Yu-Dong Zhang6, Shaima Elnazer7,8, Rokaia M. Zaki9,10
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4989-5003, 2022, DOI:10.32604/cmc.2022.023884
    (This article belongs to the Special Issue: Artificial Intelligence and Machine Learning Algorithms in Real-World Applications and Theories)
    Abstract Metamaterial Antenna is a subclass of antennas that makes use of metamaterial to improve performance. Metamaterial antennas can overcome the bandwidth constraint associated with tiny antennas. Machine learning is receiving a lot of interest in optimizing solutions in a variety of areas. Machine learning methods are already a significant component of ongoing research and are anticipated to play a critical role in today's technology. The accuracy of the forecast is mostly determined by the model used. The purpose of this article is to provide an optimal ensemble model for predicting the bandwidth and gain of… More >

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    ARTICLE

    Brain Tumor Detection and Segmentation Using RCNN

    Maham Khan1, Syed Adnan Shah1, Tenvir Ali2, Quratulain2, Aymen Khan2, Gyu Sang Choi3,*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5005-5020, 2022, DOI:10.32604/cmc.2022.023007
    (This article belongs to the Special Issue: Machine Learning Applications in Medical, Finance, Education and Cyber Security)
    Abstract Brain tumors are considered as most fatal cancers. To reduce the risk of death, early identification of the disease is required. One of the best available methods to evaluate brain tumors is Magnetic resonance Images (MRI). Brain tumor detection and segmentation are tough as brain tumors may vary in size, shape, and location. That makes manual detection of brain tumors by exploring MRI a tedious job for radiologists and doctors’. So an automated brain tumor detection and segmentation is required. This work suggests a Region-based Convolution Neural Network (RCNN) approach for automated brain tumor identification… More >

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    ARTICLE

    Perceptual Image Outpainting Assisted by Low-Level Feature Fusion and Multi-Patch Discriminator

    Xiaojie Li1, Yongpeng Ren1, Hongping Ren1, Canghong Shi2, Xian Zhang1, Lutao Wang1, Imran Mumtaz3, Xi Wu1
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5021-5037, 2022, DOI:10.32604/cmc.2022.023071
    Abstract Recently, deep learning-based image outpainting has made greatly notable improvements in computer vision field. However, due to the lack of fully extracting image information, the existing methods often generate unnatural and blurry outpainting results in most cases. To solve this issue, we propose a perceptual image outpainting method, which effectively takes the advantage of low-level feature fusion and multi-patch discriminator. Specifically, we first fuse the texture information in the low-level feature map of encoder, and simultaneously incorporate these aggregated features reusability with semantic (or structural) information of deep feature map such that we could utilize More >

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    ARTICLE

    Security Threat and Vulnerability Assessment and Measurement in Secure Software Development

    Mamoona Humayun1, NZ Jhanjhi2,*, Maram Fahhad Almufareh1, Muhammad Ibrahim Khalil3
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5039-5059, 2022, DOI:10.32604/cmc.2022.019289
    Abstract Security is critical to the success of software, particularly in today's fast-paced, technology-driven environment. It ensures that data, code, and services maintain their CIA (Confidentiality, Integrity, and Availability). This is only possible if security is taken into account at all stages of the SDLC (Software Development Life Cycle). Various approaches to software quality have been developed, such as CMMI (Capability maturity model integration). However, there exists no explicit solution for incorporating security into all phases of SDLC. One of the major causes of pervasive vulnerabilities is a failure to prioritize security. Even the most proactive… More >

  • Open AccessOpen Access

    ARTICLE

    Energy-Efficient Scheduling for a Cognitive IoT-Based Early Warning System

    Saeed Ahmed1,2, Noor Gul1,3, Jahangir Khan4, Junsu Kim1, Su Min Kim1,*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5061-5082, 2022, DOI:10.32604/cmc.2022.023639
    (This article belongs to the Special Issue: Artificial Intelligence Convergence Healthcare System Leveraging Blockchain Networks)
    Abstract Flash floods are deemed the most fatal and disastrous natural hazards globally due to their prompt onset that requires a short prime time for emergency response. Cognitive Internet of things (CIoT) technologies including inherent characteristics of cognitive radio (CR) are potential candidates to develop a monitoring and early warning system (MEWS) that helps in efficiently utilizing the short response time to save lives during flash floods. However, most CIoT devices are battery-limited and thus, it reduces the lifetime of the MEWS. To tackle these problems, we propose a CIoT-based MEWS to slash the fatalities of… More >

  • Open AccessOpen Access

    ARTICLE

    Fruits and Vegetables Freshness Categorization Using Deep Learning

    Labiba Gillani Fahad1, Syed Fahad Tahir2,*, Usama Rasheed1, Hafsa Saqib1, Mehdi Hassan2, Hani Alquhayz3
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5083-5098, 2022, DOI:10.32604/cmc.2022.023357
    Abstract The nutritional value of perishable food items, such as fruits and vegetables, depends on their freshness levels. The existing approaches solve a binary class problem by classifying a known fruit\vegetable class into fresh or rotten only. We propose an automated fruits and vegetables categorization approach that first recognizes the class of object in an image and then categorizes that fruit or vegetable into one of the three categories: pure-fresh, medium-fresh, and rotten. We gathered a dataset comprising of 60K images of 11 fruits and vegetables, each is further divided into three categories of freshness, using… More >

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    ARTICLE

    Sum Rate Maximization-based Fair Power Allocation in Downlink NOMA Networks

    Mohammed Abd-Elnaby*
    CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5099-5116, 2022, DOI:10.32604/cmc.2022.022020
    (This article belongs to the Special Issue: Intelligent Computing Techniques for Communication Systems)
    Abstract Non-orthogonal multiple access (NOMA) has been seen as a promising technology for 5G communication. The performance optimization of NOMA systems depends on both power allocation (PA) and user pairing (UP). Most existing researches provide sub-optimal solutions with high computational complexity for PA problem and mainly focuses on maximizing the sum rate (capacity) without considering the fairness performance. Also, the joint optimization of PA and UP needs an exhaustive search. The main contribution of this paper is the proposing of a novel capacity maximization-based fair power allocation (CMFPA) with low-complexity in downlink NOMA. Extensive investigation and… More >

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