Open Access
ARTICLE
Faiza Qayyum1, Faisal Jamil1, Shabir Ahmad2, Do-Hyeun Kim1,*
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 >
Open Access
ARTICLE
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 >
Open Access
ARTICLE
Rahul Sharma1, Amar Singh1, Kavita2, N. Z. Jhanjhi3, Mehedi Masud4, Emad Sami Jaha5, Sahil Verma2,*
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 >
Open Access
ARTICLE
Zafar Iqbal1,2, Muhammad Aziz-ur Rehman1, Nauman Ahmed1,2, Ali Raza3,4, Muhammad Rafiq5, Ilyas Khan6,*, 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 >
Open Access
ARTICLE
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 >
Open Access
ARTICLE
Ayman Abd-Elhamed1,2,*, 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 >
Open Access
ARTICLE
Iqra Afzal1, Fiaz Majeed1, Muhammad Usman Ali2, Shahzada Khurram3, Akber Abid Gardezi4, Shafiq Ahmad5, Saad Aladyan5, Almetwally M. Mostafa6, Muhammad Shafiq7,*
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 >
Open Access
ARTICLE
Kazim Ali1,*, 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 >
Open Access
ARTICLE
Faizan Rasheed1, Kok-Lim Alvin Yau2, Rafidah Md Noor3, Yung-Wey Chong4,*
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 >
Open Access
ARTICLE
Noha E. El-Attar1,*, Sahar F. Sabbeh1,2, 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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