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Faiza Qayyum¹, Faisal Jamil¹, Shabir Ahmad², Do-Hyeun Kim^1,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2091-2105, 2022, DOI:10.32604/cmc.2022.019898
（This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
Abstract Renewable energy resources are deemed a potential energy production source due to their cost efficiency and harmless reaction to the environment, unlike non-renewable energy resources. However, they often fail to meet energy requirements in unfavorable weather conditions. The concept of Hybrid renewable energy resources addresses this issue by integrating both renewable and non-renewable energy resources to meet the required energy load. In this paper, an intelligent cost optimization algorithm is proposed to maximize the use of renewable energy resources and minimum utilization of non-renewable energy resources to meet the energy requirement for a nanogrid infrastructure. An actual data set comprising… More >

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J. Sampathkumar^*, N. Malmurugan
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2107-2123, 2022, DOI:10.32604/cmc.2022.019983
Abstract Wireless Sensor Network is considered as the intermediate layer in the paradigm of Internet of things (IoT) and its effectiveness depends on the mode of deployment without sacrificing the performance and energy efficiency. WSN provides ubiquitous access to location, the status of different entities of the environment and data acquisition for long term IoT monitoring. Achieving the high performance of the WSN-IoT network remains to be a real challenge since the deployment of these networks in the large area consumes more power which in turn degrades the performance of the networks. So, developing the robust and QoS (quality of services)… More >

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Rahul Sharma¹, Amar Singh¹, Kavita², N. Z. Jhanjhi³, Mehedi Masud⁴, Emad Sami Jaha⁵, Sahil Verma^2,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2125-2140, 2022, DOI:10.32604/cmc.2022.020017
Abstract Indian agriculture is striving to achieve sustainable intensification, the system aiming to increase agricultural yield per unit area without harming natural resources and the ecosystem. Modern farming employs technology to improve productivity. Early and accurate analysis and diagnosis of plant disease is very helpful in reducing plant diseases and improving plant health and food crop productivity. Plant disease experts are not available in remote areas thus there is a requirement of automatic low-cost, approachable and reliable solutions to identify the plant diseases without the laboratory inspection and expert's opinion. Deep learning-based computer vision techniques like Convolutional Neural Network (CNN) and… More >

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Zafar Iqbal^1,2, Muhammad Aziz-ur Rehman¹, Nauman Ahmed^1,2, Ali Raza^3,4, Muhammad Rafiq⁵, Ilyas Khan^6,*, Kottakkaran Sooppy Nisar⁷
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2141-2157, 2022, DOI:10.32604/cmc.2022.013906
（This article belongs to this Special Issue: Mathematical aspects of the Coronavirus Disease 2019 (COVID-19): Analysis and Control)
Abstract In this article, a brief biological structure and some basic properties of COVID-19 are described. A classical integer order model is modified and converted into a fractional order model with as order of the fractional derivative. Moreover, a valued structure preserving the numerical design, coined as Grunwald–Letnikov non-standard finite difference scheme, is developed for the fractional COVID-19 model. Taking into account the importance of the positivity and boundedness of the state variables, some productive results have been proved to ensure these essential features. Stability of the model at a corona free and a corona existing equilibrium points is investigated on… More >

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Sayed Mahmoud^*, Alaa Salman
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2159-2173, 2022, DOI:10.32604/cmc.2022.022357
Abstract Reinforced concrete (RC) as a material is most commonly used for buildings construction. Several floor systems are available following the structural and architectural requirements. The current research study provides cost and input energy comparisons of RC office buildings of different floor systems. Conventional solid, ribbed, flat plate and flat slab systems are considered in the study. Building models in three-dimensional using extended three-dimensional analysis of building systems (ETABS) and in two-dimensional using slab analysis by the finite element (SAFE) are developed for analysis purposes. Analysis and design using both software packages and manual calculations are employed to obtain the optimum… More >

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834

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Ayman Abd-Elhamed^1,2,*, Mohamed Fathy³, Khaled M. Abdelgaber¹
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2175-2190, 2022, DOI:10.32604/cmc.2022.021899
（This article belongs to this Special Issue: Artificial Intelligence and Machine Learning Algorithms in Real-World Applications and Theories)
Abstract The capability of piles to withstand horizontal loads is a major design issue. The current research work aims to investigate numerically the responses of laterally loaded piles at working load employing the concept of a beam-on-Winkler-foundation model. The governing differential equation for a laterally loaded pile on elastic subgrade is derived. Based on Legendre-Galerkin method and Runge-Kutta formulas of order four and five, the flexural equation of long piles embedded in homogeneous sandy soils with modulus of subgrade reaction linearly variable with depth is solved for both free- and fixed-headed piles. Mathematica, as one of the world's leading computational software,… More >

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887

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Iqra Afzal¹, Fiaz Majeed¹, Muhammad Usman Ali², Shahzada Khurram³, Akber Abid Gardezi⁴, Shafiq Ahmad⁵, Saad Aladyan⁵, Almetwally M. Mostafa⁶, Muhammad Shafiq^7,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2191-2207, 2022, DOI:10.32604/cmc.2022.022711
Abstract In this era of electronic health, healthcare data is very important because it contains information about human survival. In addition, the Internet of Things (IoT) revolution has redefined modern healthcare systems and management by providing continuous monitoring. In this case, the data related to the heart is more important and requires proper analysis. For the analysis of heart data, Electrocardiogram (ECG) is used. In this work, machine learning techniques, such as adaptive boosting (AdaBoost) is used for detecting normal sinus rhythm, atrial fibrillation (AF), and noise in ECG signals to improve the classification accuracy. The proposed model uses ECG signals… More >

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865

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Kazim Ali^1,*, Adnan N. Qureshi¹, Ahmad Alauddin Bin Arifin², Muhammad Shahid Bhatti³, Abid Sohail³, Rohail Hassan⁴
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2209-2224, 2022, DOI:10.32604/cmc.2022.020111
Abstract These days, deep learning and computer vision are much-growing fields in this modern world of information technology. Deep learning algorithms and computer vision have achieved great success in different applications like image classification, speech recognition, self-driving vehicles, disease diagnostics, and many more. Despite success in various applications, it is found that these learning algorithms face severe threats due to adversarial attacks. Adversarial examples are inputs like images in the computer vision field, which are intentionally slightly changed or perturbed. These changes are humanly imperceptible. But are misclassified by a model with high probability and severely affects the performance or prediction.… More >

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Faizan Rasheed¹, Kok-Lim Alvin Yau², Rafidah Md Noor³, Yung-Wey Chong^4,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2225-2247, 2022, DOI:10.32604/cmc.2022.022952
（This article belongs to this Special Issue: Artificial Intelligence Enabled Intelligent Transportation Systems)
Abstract This paper investigates the use of multi-agent deep Q-network (MADQN) to address the curse of dimensionality issue occurred in the traditional multi-agent reinforcement learning (MARL) approach. The proposed MADQN is applied to traffic light controllers at multiple intersections with busy traffic and traffic disruptions, particularly rainfall. MADQN is based on deep Q-network (DQN), which is an integration of the traditional reinforcement learning (RL) and the newly emerging deep learning (DL) approaches. MADQN enables traffic light controllers to learn, exchange knowledge with neighboring agents, and select optimal joint actions in a collaborative manner. A case study based on a real traffic… More >

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Noha E. El-Attar^1,*, Sahar F. Sabbeh^1,2, Heba Fasihuddin², Wael A. Awad³
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2249-2269, 2022, DOI:10.32604/cmc.2022.022673
Abstract The outbreak of Covid-19 has taken the lives of many patients so far. The symptoms of COVID-19 include muscle pains, loss of taste and smell, coughs, fever, and sore throat, which can lead to severe cases of breathing difficulties, organ failure, and death. Thus, the early detection of the virus is very crucial. COVID-19 can be detected using clinical tests, making us need to know the most important symptoms/features that can enhance the decision process. In this work, we propose a modified multilayer perceptron (MLP) with feature selection (MLPFS) to predict the positive COVID-19 cases based on symptoms and features… More >

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Farhad Bin Ashraf¹, Touhidul Alam^2,*, Md Tarikul Islam³, Mandeep Jit Singh³, Norbahiah Binti Misran³, Mohammad Tariqul Islam³
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2271-2284, 2022, DOI:10.32604/cmc.2022.021751
Abstract In this paper, the design and performance analysis of an Inkjet-printed metamaterial loaded monopole antenna is presented for wireless local area network (WLAN) and worldwide interoperability for microwave access (WiMAX) applications. The proposed metamaterial structure consists of two layers, one is rectangular tuning fork-shaped antenna, and another layer is an inkjet-printed metamaterial superstate. The metamaterial layer is designed using four split-ring resonators (SRR) with an H-shaped inner structure to achieve negative-index metamaterial properties. The metamaterial structure is fabricated on low-cost photo paper substrate material using a conductive ink-based inkjet printing technique, which achieved dual negative refractive index bands of 2.25–4.25… More >

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Hajira Saleem¹, Faisal Riaz¹, Asadullah Shaikh², Khairan Rajab^2,3, Adel Rajab^2,*, Muhammad Akram², Mana Saleh Al Reshan²
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2285-2302, 2022, DOI:10.32604/cmc.2022.022726
Abstract Deep learning techniques, particularly convolutional neural networks (CNNs), have exhibited remarkable performance in solving vision-related problems, especially in unpredictable, dynamic, and challenging environments. In autonomous vehicles, imitation-learning-based steering angle prediction is viable due to the visual imagery comprehension of CNNs. In this regard, globally, researchers are currently focusing on the architectural design and optimization of the hyperparameters of CNNs to achieve the best results. Literature has proven the superiority of metaheuristic algorithms over the manual-tuning of CNNs. However, to the best of our knowledge, these techniques are yet to be applied to address the problem of imitation-learning-based steering angle prediction.… More >

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Hatim G. Zaini^*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2303-2314, 2022, DOI:10.32604/cmc.2022.021998
（This article belongs to this Special Issue: Artificial Intelligence and Machine Learning Algorithms in Real-World Applications and Theories)
Abstract This paper gives and analyses data-driven prediction models for the energy usage of appliances. Data utilized include readings of temperature and humidity sensors from a wireless network. The building envelope is meant to minimize energy demand or the energy required to power the house independent of the appliance and mechanical system efficiency. Approximating a mapping function between the input variables and the continuous output variable is the work of regression. The paper discusses the forecasting framework FOPF (Feature Optimization Prediction Framework), which includes feature selection optimization: by removing non-predictive parameters to choose the best-selected feature hybrid optimization technique has been… More >

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Tengfei Tu^1,2, Wei Yin³, Hua Zhang^1,2,*, Xingyu Zeng¹, Xiaoxiang Deng¹, Yuchen Zhou¹, Xu Liu⁴
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2315-2331, 2022, DOI:10.32604/cmc.2022.022540
Abstract The Internet Control Message Protocol (ICMP) covert tunnel refers to a network attack that encapsulates malicious data in the data part of the ICMP protocol for transmission. Its concealment is stronger and it is not easy to be discovered. Most detection methods are detecting the existence of channels instead of clarifying specific attack intentions. In this paper, we propose an ICMP covert tunnel attack intent detection framework ICMPTend, which includes five steps: data collection, feature dictionary construction, data preprocessing, model construction, and attack intent prediction. ICMPTend can detect a variety of attack intentions, such as shell attacks, sensitive directory access,… More >

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Mohammad B. Khan¹, Abdul R. Khan^2,*, Hasan Alkahtani²
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2333-2346, 2022, DOI:10.32604/cmc.2022.020623
（This article belongs to this Special Issue: Pervasive Computing and Communication: Challenges, Technologies & Opportunities)
Abstract Architectures based on the data flow computing model provide an alternative to the conventional Von-Neumann architecture that are widely used for general purpose computing. Processors based on the data flow architecture employ fine-grain data-driven parallelism. These architectures have the potential to exploit the inherent parallelism in compute intensive applications like signal processing, image and video processing and so on and can thus achieve faster throughputs and higher power efficiency. In this paper, several data flow computing architectures are explored, and their main architectural features are studied. Furthermore, a classification of the processors is presented based on whether they employ either… More >

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Malini M. Patil^1,*, P. M. Rekha¹, Arun Solanki², Anand Nayyar^3,4, Basit Qureshi⁵
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2347-2361, 2022, DOI:10.32604/cmc.2022.021447
Abstract In the past few decades, climatic changes led by environmental pollution, the emittance of greenhouse gases, and the emergence of brown energy utilization have led to global warming. Global warming increases the Earth's temperature, thereby causing severe effects on human and environmental conditions and threatening the livelihoods of millions of people. Global warming issues are the increase in global temperatures that lead to heat strokes and high-temperature-related diseases during the summer, causing the untimely death of thousands of people. To forecast weather conditions, researchers have utilized machine learning algorithms, such as autoregressive integrated moving average, ensemble learning, and long short-term… More >

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834

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Mohd Anul Haq^*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2363-2381, 2022, DOI:10.32604/cmc.2022.023059
（This article belongs to this Special Issue: Artificial Intelligence and Machine Learning Algorithms in Real-World Applications and Theories)
Abstract Water received in rainfall is a crucial natural resource for agriculture, the hydrological cycle, and municipal purposes. The changing rainfall pattern is an essential aspect of assessing the impact of climate change on water resources planning and management. Climate change affected the entire world, specifically India’s fragile Himalayan mountain region, which has high significance due to being a climatic indicator. The water coming from Himalayan rivers is essential for 1.4 billion people living downstream. Earlier studies either modeled temperature or rainfall for the Himalayan area; however, the combined influence of both in a long-term analysis was not performed utilizing Deep… More >

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Md. Mushfiqur Rahman^1,*, Md. Shabiul Islam¹, Mohammad Tariqul Islam², Samir Salem Al-Bawri³, Wong Hin Yong¹
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2383-2399, 2022, DOI:10.32604/cmc.2022.022150
（This article belongs to this Special Issue: Advances in 5G Antenna Designs and Systems)
Abstract In this paper, a unit cell of a single-negative metamaterial structure loaded with a meander line and defected ground structure (DGS) is investigated as the principle radiating element of an antenna. The unit cell antenna causes even or odd mode resonances similar to the unit cell structure depending on the orientation of the microstrip feed used to excite the unit cell. However, the orientation which gives low-frequency resonance is considered here. The unit cell antenna is then loaded with a meander line which is parallel to the split bearing side and connects the other two sides orthogonal to the split… More >

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Xiaojun Pan¹, Haiying Li², Xiaoyi Li¹, Li Xu¹, Yanbin Sun^1,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2401-2417, 2022, DOI:10.32604/cmc.2022.021020
Abstract Supervisory control and data acquisition systems (SCADAs) play an important role in supervising and controlling industrial production with the help of programmable logic controllers (PLCs) in industrial control systems (ICSs). A PLC receives the control information or program from a SCADA to control the production equipment and feeds the production data back to the SCADA. Once a SCADA is controlled by an attacker, it may threaten the safety of industrial production. The lack of security protection, such as identity authentication and encryption for industrial control protocols, increases the potential security risks. In this paper, we propose a PLC protection system… More >

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G. Parthasarathy^1,*, S. Sathiya Devi²
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2419-2434, 2022, DOI:10.32604/cmc.2022.019805
Abstract Recommender system is a tool to suggest items to the users from the extensive history of the user's feedback. Though, it is an emerging research area concerning academics and industries, where it suffers from sparsity, scalability, and cold start problems. This paper addresses sparsity, and scalability problems of model-based collaborative recommender system based on ensemble learning approach and enhanced clustering algorithm for movie recommendations. In this paper, an effective movie recommendation system is proposed by Classification and Regression Tree (CART) algorithm, enhanced Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) algorithm and truncation method. In this research paper, a new… More >

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Simon Crase^1,2, Benjamin Hall², Suresh N. Thennadil^3,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2435-2458, 2022, DOI:10.32604/cmc.2022.022414
Abstract Cluster analysis in spectroscopy presents some unique challenges due to the specific data characteristics in spectroscopy, namely, high dimensionality and small sample size. In order to improve cluster analysis outcomes, feature selection can be used to remove redundant or irrelevant features and reduce the dimensionality. However, for cluster analysis, this must be done in an unsupervised manner without the benefit of data labels. This paper presents a novel feature selection approach for cluster analysis, utilizing clusterability metrics to remove features that least contribute to a dataset's tendency to cluster. Two versions are presented and evaluated: The Hopkins clusterability filter which… More >

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Sonali Dash¹, Sahil Verma^2,*, Kavita², N. Z. Jhanjhi³, Mehedi Masud⁴, Mohammed Baz⁵
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2459-2476, 2022, DOI:10.32604/cmc.2022.020904
Abstract Segmentation of vessel in retinal fundus images is a primary step for the clinical identification for specific eye diseases. Effective diagnosis of vascular pathologies from angiographic images is thus a vital aspect and generally depends on segmentation of vascular structure. Although various approaches for retinal vessel segmentation are extensively utilized, however, the responses are lower at vessel's edges. The curvelet transform signifies edges better than wavelets, and hence convenient for multiscale edge enhancement. The bilateral filter is a nonlinear filter that is capable of providing effective smoothing while preserving strong edges. Fast bilateral filter is an advanced version of bilateral… More >

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756

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Amina Bibi¹, Muhamamd Attique Khan¹, Muhammad Younus Javed¹, Usman Tariq², Byeong-Gwon Kang³, Yunyoung Nam^3,*, Reham R. Mostafa⁴, Rasha H. Sakr⁵
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2477-2495, 2022, DOI:10.32604/cmc.2022.018917
（This article belongs to this Special Issue: Recent Advances in Deep Learning for Medical Image Analysis)
Abstract Background: In medical image analysis, the diagnosis of skin lesions remains a challenging task. Skin lesion is a common type of skin cancer that exists worldwide. Dermoscopy is one of the latest technologies used for the diagnosis of skin cancer. Challenges: Many computerized methods have been introduced in the literature to classify skin cancers. However, challenges remain such as imbalanced datasets, low contrast lesions, and the extraction of irrelevant or redundant features. Proposed Work: In this study, a new technique is proposed based on the conventional and deep learning framework. The proposed framework consists of two major tasks: lesion segmentation… More >

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Mohammad Alamgeer¹, Fahd N. Al-Wesabi^2,3,*, Huda G. Iskandar^3,4, Imran Khan⁵, Nadhem Nemri⁶, Mohammad Medani⁶, Mohammed Abdullah Al-Hagery⁷, Ali Mohammed Al-Sharafi^3,8
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2497-2513, 2022, DOI:10.32604/cmc.2022.018591
Abstract Content authentication, integrity verification, and tampering detection of digital content exchanged via the internet have been used to address a major concern in information and communication technology. In this paper, a text zero-watermarking approach known as Smart-Fragile Approach based on Soft Computing and Digital Watermarking (SFASCDW) is proposed for content authentication and tampering detection of English text. A first-level order of alphanumeric mechanism, based on hidden Markov model, is integrated with digital zero-watermarking techniques to improve the watermark robustness of the proposed approach. The researcher uses the first-level order and alphanumeric mechanism of Markov model as a soft computing technique… More >

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Usman Ali^1,2, Mohd Yamani Idna Idris^1,3,*, Jaroslav Frnda⁴, Mohamad Nizam Bin Ayub¹, Roobaea Alroobaea⁵, Fahad Almansour⁶, Nura Modi Shagari¹, Insaf Ullah⁷, Ihsan Ali¹
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2515-2532, 2022, DOI:10.32604/cmc.2022.019800
（This article belongs to this Special Issue: Next - Generation Secure Solutions for Wireless Communications, IoT and SDNs)
Abstract Industrial internet of things (IIoT) is the usage of internet of things (IoT) devices and applications for the purpose of sensing, processing and communicating real-time events in the industrial system to reduce the unnecessary operational cost and enhance manufacturing and other industrial-related processes to attain more profits. However, such IoT based smart industries need internet connectivity and interoperability which makes them susceptible to numerous cyber-attacks due to the scarcity of computational resources of IoT devices and communication over insecure wireless channels. Therefore, this necessitates the design of an efficient security mechanism for IIoT environment. In this paper, we propose a… More >

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Md. Amanath Ullah¹, Touhidul Alam^2,3, Ali F. Almutairi^4,*, Mohammad Tariqul Islam⁵
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2533-2542, 2022, DOI:10.32604/cmc.2022.021852
Abstract This paper reveals a new design of UHF CubeSat antenna based on a modified Planar Inverted F Antenna (PIFA) for CubeSat communication. The design utilizes a CubeSat face as the ground plane. There is a gap of 5 mm beneath the radiating element that facilitates the design providing with space for solar panels. The prototype is fabricated using Aluminum metal sheet and measured. The antenna achieved resonance at 419 MHz. Response of the antenna has been investigated after placing a solar panel. Lossy properties of solar panels made the resonance shift about 20 MHz. This design addresses the frequency shifting… More >

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Ala’ A. Eshmawi¹, Hesham Alhumyani², Sayed Abdel Khalek³, Rashid A. Saeed², Mahmoud Ragab⁴, Romany F. Mansour^5,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2543-2557, 2022, DOI:10.32604/cmc.2022.021833
Abstract Sentiment analysis or Opinion Mining (OM) has gained significant interest among research communities and entrepreneurs in the recent years. Likewise, Machine Learning (ML) approaches is one of the interesting research domains that are highly helpful and are increasingly applied in several business domains. In this background, the current research paper focuses on the design of automated opinion mining model using Deer Hunting Optimization Algorithm (DHOA) with Fuzzy Neural Network (FNN) abbreviated as DHOA-FNN model. The proposed DHOA-FNN technique involves four different stages namely, preprocessing, feature extraction, classification, and parameter tuning. In addition to the above, the proposed DHOA-FNN model has… More >

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Imran Ahmed¹, Iqbal Khan¹, Misbah Ahmad¹, Awais Adnan¹, Hanan Aljuaid^2,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2559-2577, 2022, DOI:10.32604/cmc.2022.021259
（This article belongs to this Special Issue: Security and Privacy issues for various Emerging Technologies and Future Trends)
Abstract The Internet of Things (IoT) has been transformed almost all fields of life, but its impact on the healthcare sector has been notable. Various IoT-based sensors are used in the healthcare sector and offer quality and safe care to patients. This work presents a deep learning-based automated patient discomfort detection system in which patients’ discomfort is non-invasively detected. To do this, the overhead view patients’ data set has been recorded. For testing and evaluation purposes, we investigate the power of deep learning by choosing a Convolution Neural Network (CNN) based model. The model uses confidence maps and detects 18 different… More >

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Taher M. Ghazal^1,2,*, Mohammad Kamrul Hasan¹, Siti Norul Huda Abdullah¹, Khairul Azmi Abubakkar¹, Mohammed A. M. Afifi²
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2579-2597, 2022, DOI:10.32604/cmc.2022.019706
Abstract Smart healthcare applications depend on data from wearable sensors (WSs) mounted on a patient’s body for frequent monitoring information. Healthcare systems depend on multi-level data for detecting illnesses and consequently delivering correct diagnostic measures. The collection of WS data and integration of that data for diagnostic purposes is a difficult task. This paper proposes an Errorless Data Fusion (EDF) approach to increase posture recognition accuracy. The research is based on a case study in a health organization. With the rise in smart healthcare systems, WS data fusion necessitates careful attention to provide sensitive analysis of the recognized illness. As a… More >

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Muhammad Ibrahim¹, Faisal Jamil², YunJung Lee¹, DoHyeun Kim^2,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2599-2616, 2022, DOI:10.32604/cmc.2022.019534
（This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
Abstract In recent times, the evolution of blockchain technology has got huge attention from the research community due to its versatile applications and unique security features. The IoT has shown wide adoption in various applications including smart cities, healthcare, trade, business, etc. Among these applications, fitness applications have been widely considered for smart fitness systems. The users of the fitness system are increasing at a high rate thus the gym providers are constantly extending the fitness facilities. Thus, scheduling such a huge number of requests for fitness exercise is a big challenge. Secondly, the user fitness data is critical thus securing… More >

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Muhammad Usman Younus^1,*, Rabia Shafi², Ammar Rafiq³, Muhammad Rizwan Anjum⁴, Sharjeel Afridi⁵, Abdul Aleem Jamali⁶, Zulfiqar Ali Arain⁷
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2617-2631, 2022, DOI:10.32604/cmc.2022.022236
（This article belongs to this Special Issue: Application of Machine-Learning in Computer Vision)
Abstract The development of multimedia content has resulted in a massive increase in network traffic for video streaming. It demands such types of solutions that can be addressed to obtain the user's Quality-of-Experience (QoE). 360-degree videos have already taken up the user's behavior by storm. However, the users only focus on the part of 360-degree videos, known as a viewport. Despite the immense hype, 360-degree videos convey a loathsome side effect about viewport prediction, making viewers feel uncomfortable because user viewport needs to be pre-fetched in advance. Ideally, we can minimize the bandwidth consumption if we know what the user motion… More >

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Baowei Wang^1,2,3,*, Weishen Wang¹, Peng Zhao¹, Naixue Xiong⁴
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2633-2652, 2022, DOI:10.32604/cmc.2022.022291
Abstract Most of the existing zero-watermark schemes for medical images are only appropriate for a single grayscale image. When they protect a large number of medical images, repeating operations will cause a significant amount of time and storage costs. Hence, this paper proposes an efficient zero-watermark scheme for multiple color medical images based on quaternion generalized Fourier descriptor (QGFD). Firstly, QGFD is utilized to compute the feature invariants of each color image, then the representative features of each image are selected, stacked, and reshaped to generate a feature matrix, which is then binarized to get a binary feature image. Copyright information… More >

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Shabir Ahmad, Faheem Khan, Taeg Keun Whangbo^*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2653-2666, 2022, DOI:10.32604/cmc.2022.022821
（This article belongs to this Special Issue: Machine Learning Empowered Secure Computing for Intelligent Systems)
Abstract Serious games have recently enticed many researchers due to their wide range of capabilities. A serious game is a mean of gaming for a serious job such as healthcare, education, and entertainment purposes. With the advancement in the Internet of Things, new research directions are paving the way in serious games. However, the internet connectivity of players in Internet-of-things-enabled serious games is a matter of concern and has been worth investigating. Different studies on topologies, frameworks, and architecture of communication technologies are conducted to integrate them with serious games on machine and network levels. However, the Internet of things, whose… More >

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J. P. Shri Tharanyaa^1,*, D. Sharmila², R. Saravana Kumar³
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2667-2681, 2022, DOI:10.32604/cmc.2022.019889
Abstract With the emergence of the Internet of things (IoT), embedded systems have now changed its dimensionality and it is applied in various domains such as healthcare, home automation and mainly Industry 4.0. These Embedded IoT devices are mostly battery-driven. It has been analyzed that usage of Dynamic Random-Access Memory (DRAM) centered core memory is considered the most significant source of high energy utility in Embedded IoT devices. For achieving the low power consumption in these devices, Non-volatile memory (NVM) devices such as Parameter Random Access Memory (PRAM) and Spin-Transfer Torque Magnetic Random-Access Memory (STT-RAM) are becoming popular among main memory… More >

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Sohail Abbas¹, Zahid Raza², Nida Siddiqui², Faheem Khan³, Taegkeun Whangbo^3,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2683-2695, 2022, DOI:10.32604/cmc.2022.023003
（This article belongs to this Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
Abstract Wireless Sensor Network (WSN) is considered to be one of the fundamental technologies employed in the Internet of things (IoT); hence, enabling diverse applications for carrying out real-time observations. Robot navigation in such networks was the main motivation for the introduction of the concept of landmarks. A robot can identify its own location by sending signals to obtain the distances between itself and the landmarks. Considering networks to be a type of graph, this concept was redefined as metric dimension of a graph which is the minimum number of nodes needed to identify all the nodes of the graph. This… More >

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Aisha Muhammad^1,5, Mohammed A. H. Ali^2,*, Sherzod Turaev³, Ibrahim Haruna Shanono^4,5, Fadhl Hujainah⁶, Mohd Nashrul Mohd Zubir², Muhammad Khairi Faiz², Erma Rahayu Mohd Faizal¹, Rawad Abdulghafor⁸
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2697-2719, 2022, DOI:10.32604/cmc.2022.020873
Abstract This paper presents a development of a novel path planning algorithm, called Generalized Laser simulator (GLS), for solving the mobile robot path planning problem in a two-dimensional map with the presence of constraints. This approach gives the possibility to find the path for a wheel mobile robot considering some constraints during the robot movement in both known and unknown environments. The feasible path is determined between the start and goal positions by generating wave of points in all direction towards the goal point with adhering to constraints. In simulation, the proposed method has been tested in several working environments with… More >

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Ahmed Hammoodi¹, Lukman Audah¹ , Laith Al-Jobouri^2,*, Mazin Abed Mohammed³, Mustafa S. Aljumaily⁴
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2721-2738, 2022, DOI:10.32604/cmc.2022.020091
Abstract OFDM based waveforms are considered as the main part of the latest cellular communications standard (namely 5G). Many inherited problems from the OFDM-Based LTE are still under investigation. Getting rid of the out of band emissions is one of these problems. Ensuring low out of band emission (OOBE) is deemed as one of the most critical challenges to support development of future technologies such as 6G and beyond. Universal Filtered Multi Carrier (UFMC) has been considered as one of the candidate waveforms for the 5G communications due to its robustness against Inter Carrier Interference (ICI) and the Inter Symbol Interference… More >

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Muhammad Sajjad¹, Tauqeer Safdar Malik¹, Shahzada Khurram², Akber Abid Gardezi³, Fawaz Alassery⁴, Habib Hamam⁵, Omar Cheikhrouhou⁶, Muhammad Shafiq^7,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2739-2753, 2022, DOI:10.32604/cmc.2022.022706
Abstract Many patients have begun to use mobile applications to handle different health needs because they can better access high-speed Internet and smartphones. These devices and mobile applications are now increasingly used and integrated through the medical Internet of Things (mIoT). mIoT is an important part of the digital transformation of healthcare, because it can introduce new business models and allow efficiency improvements, cost control and improve patient experience. In the mIoT system, when migrating from traditional medical services to electronic medical services, patient protection and privacy are the priorities of each stakeholder. Therefore, it is recommended to use different user… More >

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Rehman Ullah Khan^1,*, Woei Sheng Wong¹, Insaf Ullah², Fahad Algarni³, Muhammad Inam Ul Haq⁴, Mohamad Hardyman bin Barawi¹, Muhammad Asghar Khan²
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2755-2772, 2022, DOI:10.32604/cmc.2022.022471
（This article belongs to this Special Issue: Soft Computing and Machine Learning for Predictive Data Analytics)
Abstract The deaf-mutes population is constantly feeling helpless when others do not understand them and vice versa. To fill this gap, this study implements a CNN-based neural network, Convolutional Based Attention Module (CBAM), to recognise Malaysian Sign Language (MSL) in videos recognition. This study has created 2071 videos for 19 dynamic signs. Two different experiments were conducted for dynamic signs, using CBAM-3DResNet implementing ‘Within Blocks’ and ‘Before Classifier’ methods. Various metrics such as the accuracy, loss, precision, recall, F1-score, confusion matrix, and training time were recorded to evaluate the models’ efficiency. Results showed that CBAM-ResNet models had good performances in videos… More >

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Jinrong Hu¹, Lujin Li¹, Ying Fu¹, Maoyang Zou¹, Jiliu Zhou¹, Shanhui Sun^2,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2773-2788, 2022, DOI:10.32604/cmc.2022.017916
Abstract Deformable medical image registration plays a vital role in medical image applications, such as placing different temporal images at the same time point or different modality images into the same coordinate system. Various strategies have been developed to satisfy the increasing needs of deformable medical image registration. One popular registration method is estimating the displacement field by computing the optical flow between two images. The motion field (flow field) is computed based on either gray-value or handcrafted descriptors such as the scale-invariant feature transform (SIFT). These methods assume that illumination is constant between images. However, medical images may not always… More >

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F. Kavin^1,*, R. Senthilkumar²
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2789-2806, 2022, DOI:10.32604/cmc.2022.021577
Abstract The main aim of this work is to design a suitable Fractional Order Proportionl Integral Derivative (FOPID) controller with Chaotic Whale Optimization Algorithm (CWOA) for a RO desalination system. Continuous research on Reverse Osmosis (RO) desalination plants is a promising technique for satisfaction with sustainable and efficient RO plants. This work implements CWOA based FOPID for the simulation of reverse osmosis (RO) desalination process for both servo and regulatory problems. Mathematical modeling is a vital constituent of designing advanced and developed engineering processes, which helps to gain a deep study of processes to predict the performance, more efficiently. Numerous approaches… More >

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768

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Reem Alkanhel¹, Abid Ali^2,3, Faisal Jamil⁴, Muzammil Nawaz², Faisal Mehmood⁵, Ammar Muthanna^6,7,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2807-2825, 2022, DOI:10.32604/cmc.2022.019766
（This article belongs to this Special Issue: Artificial Intelligence Convergence Networks Leveraging Software-Defined Networking)
Abstract Although the Software-Defined Network (SDN) is a well-controlled and efficient network but the complexity of open flow switches in SDN causes multiple issues. Many solutions have been proposed so far for the prevention of errors and mistakes in it but yet, there is still no smooth transmission of pockets from source to destination specifically when irregular movements follow the destination host in SDN, the errors include packet loss, data compromise etc. The accuracy of packets received at their desired destination is possible if networks for pockets and hosts are monitored instead of analysis of network snapshot statistically for the state,… More >

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802

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Pradeep Kumar Singh¹, Pijush Kanti Dutta Pramanik¹, Madhumita Sardar¹, Anand Nayyar^2,3,*, Mehedi Masud⁴, Prasenjit Choudhury¹
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2827-2846, 2022, DOI:10.32604/cmc.2022.020437
Abstract A collaborative filtering-based recommendation system has been an integral part of e-commerce and e-servicing. To keep the recommendation systems reliable, authentic, and superior, the security of these systems is very crucial. Though the existing shilling attack detection methods in collaborative filtering are able to detect the standard attacks, in this paper, we prove that they fail to detect a new or unknown attack. We develop a new attack model, named Obscure attack, with unknown features and observed that it has been successful in biasing the overall top-N list of the target users as intended. The Obscure attack is able to… More >

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Prachi Agrawal¹, Khalid Alnowibet², Ali Wagdy Mohamed^3,4,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2847-2868, 2022, DOI:10.32604/cmc.2022.023126
（This article belongs to this Special Issue: Artificial Intelligence and Machine Learning Algorithms in Real-World Applications and Theories)
Abstract This paper presents a novel application of metaheuristic algorithms for solving stochastic programming problems using a recently developed gaining sharing knowledge based optimization (GSK) algorithm. The algorithm is based on human behavior in which people gain and share their knowledge with others. Different types of stochastic fractional programming problems are considered in this study. The augmented Lagrangian method (ALM) is used to handle these constrained optimization problems by converting them into unconstrained optimization problems. Three examples from the literature are considered and transformed into their deterministic form using the chance-constrained technique. The transformed problems are solved using GSK algorithm and… More >

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N. S. Ishak¹, F. C. Seman^2,*, N. Zainal³, N. A. Awang⁴
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2869-2882, 2022, DOI:10.32604/cmc.2022.022694
（This article belongs to this Special Issue: Antennas for Biomedical and Healthcare Applications)
Abstract Sugar is important in daily food intake since it is used as food preservative and sweetener. Therefore, is important to analyze the influence of sugar on the spectroscopic properties of the sample. Terahertz spectroscopy is proven to be useful and an efficient method for sugar detection as well as for future food quality industry. However, the lack of detection sensitivity in Terahertz Spectroscopy has prevented it from being used in a widespread spectroscopic analysis technology. In this paper, Frequency Selective Surface (FSS) using the Terahertz Spectroscopy Time Domain Spectrum (THz-TDS) which operates at terahertz frequency range has been demonstrated for… More >

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Lelisa Adeba Jilcha¹, Jin Kwak^2,*
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2883-2899, 2022, DOI:10.32604/cmc.2022.023167
Abstract In the contemporary world, digital content that is subject to copyright is facing significant challenges against the act of copyright infringement. Billions of dollars are lost annually because of this illegal act. The current most effective trend to tackle this problem is believed to be blocking those websites, particularly through affiliated government bodies. To do so, an effective detection mechanism is a necessary first step. Some researchers have used various approaches to analyze the possible common features of suspected piracy websites. For instance, most of these websites serve online advertisement, which is considered as their main source of revenue. In… More >

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Alaa Eisa¹, Nora EL-Rashidy², Mohammad Dahman Alshehri^3,*, Hazem M. El-bakry¹, Samir Abdelrazek¹
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2901-2921, 2022, DOI:10.32604/cmc.2022.021342
Abstract At this current time, data stream classification plays a key role in big data analytics due to its enormous growth. Most of the existing classification methods used ensemble learning, which is trustworthy but these methods are not effective to face the issues of learning from imbalanced big data, it also supposes that all data are pre-classified. Another weakness of current methods is that it takes a long evaluation time when the target data stream contains a high number of features. The main objective of this research is to develop a new method for incremental learning based on the proposed ant… More >

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Erkan Erdemir^1,*, Adem Alpaslan Altun²
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2923-2941, 2022, DOI:10.32604/cmc.2022.022797
（This article belongs to this Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
Abstract Metaheuristic algorithms are one of the methods used to solve optimization problems and find global or close to optimal solutions at a reasonable computational cost. As with other types of algorithms, in metaheuristic algorithms, one of the methods used to improve performance and achieve results closer to the target result is the hybridization of algorithms. In this study, a hybrid algorithm (HSSJAYA) consisting of salp swarm algorithm (SSA) and jaya algorithm (JAYA) is designed. The speed of achieving the global optimum of SSA, its simplicity, easy hybridization and JAYA's success in achieving the best solution have given us the idea… More >

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Ahmed R. Abas¹, Ibrahim Elhenawy¹, Mahinda Zidan^2,*, Mahmoud Othman²
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2943-2961, 2022, DOI:10.32604/cmc.2022.021671
Abstract Due to the widespread usage of social media in our recent daily lifestyles, sentiment analysis becomes an important field in pattern recognition and Natural Language Processing (NLP). In this field, users’ feedback data on a specific issue are evaluated and analyzed. Detecting emotions within the text is therefore considered one of the important challenges of the current NLP research. Emotions have been widely studied in psychology and behavioral science as they are an integral part of the human nature. Emotions describe a state of mind of distinct behaviors, feelings, thoughts and experiences. The main objective of this paper is to… More >

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Fan Yang¹, Jie Xu^1,*, Haoliang Wei¹, Meng Ye², Mingzhu Xu¹, Qiuru Fu¹, Lingfei Ren³, Zhengwen Huang⁴
CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2963-2980, 2022, DOI:10.32604/cmc.2022.022810
Abstract Zanthoxylum bungeanum Maxim, generally called prickly ash, is widely grown in China. Zanthoxylum rust is the main disease affecting the growth and quality of Zanthoxylum. Traditional method for recognizing the degree of infection of Zanthoxylum rust mainly rely on manual experience. Due to the complex colors and shapes of rust areas, the accuracy of manual recognition is low and difficult to be quantified. In recent years, the application of artificial intelligence technology in the agricultural field has gradually increased. In this paper, based on the DeepLabV2 model, we proposed a Zanthoxylum rust image segmentation model based on the FASPP module… More >

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