Kamlendra Vikram¹, Uvaraja Ragavendran², Kanak Kalita^1,*, Ranjan Kumar Ghadai³, Xiao-Zhi Gao⁴

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1771-1784, 2021, DOI:10.32604/cmc.2020.013946

Abstract In this work, diamond-like carbon (DLC) thin film coatings are deposited on silicon substrates by using plasma-enhanced chemical vapour deposition (PECVD) technique. By varying the hydrogen (H₂) flow rate, CH₄−Argon (Ar) flow rate and deposition temperature (T_d) as per a Box-Behnken experimental design (BBD), 15 DLC deposition experiments are carried out. The Young’s modulus (E) and the coefficient of friction (COF) for the DLCs are measured. By using a second-order polynomial regression approach, two metamodels are built for E and COF, that establish them as functions of H₂ flow rate, CH₄-Ar flow rate and T_d. A non-dominated sorting genetic algorithm… More >

Ali Saadon Al-Ogaili^1,*, Ameer Alhasan², Agileswari Ramasamy¹, Marayati Binti Marsadek¹, Tengku Juhana Tengku Hashim¹, Ammar Al-Sharaa³, Mastura Binti Aadam³, Lukman Audah²

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2141-2164, 2021, DOI:10.32604/cmc.2020.013440

Abstract The Coronavirus (COVID-19) pandemic is considered as a global public health challenge. To contain this pandemic, different measures are being taken globally. The Internet of Things (IoT) has been represented as one of the most important schemes that has been considered to fight the spread of COVID-19 in the world, practically Malaysia. In fact, there are many sectors in Malaysia would be transformed into smart services by using IoT technologies, particularly energy, transportation, healthcare sectors. This manuscript presents a comprehensive review of the IoT technologies that are being used currently in Malaysia to accelerate the measures against COVID-19. These IoT… More >

Srinath Doss¹, Jothi Paranthaman², Suseendran Gopalakrishnan³, Akila Duraisamy³, Souvik Pal⁴, Balaganesh Duraisamy⁵, Chung Le Van^6,*, Dac-Nhuong Le⁷

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1577-1594, 2021, DOI:10.32604/cmc.2020.012379

Abstract In the healthcare system, the Internet of Things (IoT) based distributed systems play a vital role in transferring the medical-related documents and information among the organizations to reduce the replication in medical tests. This datum is sensitive, and hence security is a must in transforming the sensational contents. In this paper, an Evolutionary Algorithm, namely the Memetic Algorithm is used for encrypting the text messages. The encrypted information is then inserted into the medical images using Discrete Wavelet Transform 1 level and 2 levels. The reverse method of the Memetic Algorithm is implemented when extracting a hidden message from the… More >

Taoze Sun, Wei Tan, Yujie Yang, Hongna Mu^*

Phyton-International Journal of Experimental Botany, Vol.90, No.1, pp. 171-178, 2021, DOI:10.32604/phyton.2020.013668

Abstract Pinus elliottii is an exotic afforestation pine extensively distributed in southern parts of China. In order to understand whether endophytic fungi can affect seedling growth of P. elliottii, Piriformospora indica (Pi), Funnelifcrmis mosseae (Fm), and Diversispora tortuosa (Dt) were inoculated respectively, and the non-inoculated group was set as control. The growth indexes, the contents of soluble sugar and soluble protein, and plant endogenous hormone levels in the leaves of P. elliottii, were analyzed. The results showed that Fm, Dt and Pi colonized the P. elliottii roots to form mycorrhizal structure and chlamydospores arranged in beads respectively. Three fungal inoculants exhibited… More >

Sabeen Tahir^*, Sheikh Tahir Bakhsh, Rayed AlGhamdi

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 733-749, 2021, DOI:10.32604/cmc.2020.013261

Abstract Medical Internet of Things (MIoTs) is a collection of small and energyefficient wireless sensor devices that monitor the patient’s body. The healthcare networks transmit continuous data monitoring for the patients to survive them independently. There are many improvements in MIoTs, but still, there are critical issues that might affect the Quality of Service (QoS) of a network. Congestion handling is one of the critical factors that directly affect the QoS of the network. The congestion in MIoT can cause more energy consumption, delay, and important data loss. If a patient has an emergency, then the life-critical signals must transmit with… More >

Gia Nhu Nguyen^1,2, Nin Ho Le Viet^1,2, Gyanendra Prasad Joshi³, Bhanu Shrestha^4,*

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 551-562, 2021, DOI:10.32604/cmc.2020.012441

Abstract Fog computing in the Internet of Health Things (IoHT) is promising owing to the increasing need for energy- and latency-optimized health sector provisioning. Additionally, clinical data (particularly, medical image data) are a delicate, highly protected resource that should be utilized in an effective and responsible manner to fulfil consumer needs. Herein, we propose an energy-effi- cient fog-based IoHT with a tunicate swarm-optimization-(TSO)-based lightweight Simon cipher to enhance the energy efficiency at the fog layer and the security of data stored at the cloud server. The proposed Simon cipher uses the TSO algorithm to select the optimal keys that will minimize… More >

Abdul Waheed^1,2,*, Naila Habib Khan³, Mahdi Zareei⁴, Shahab Ul Islam⁵, Latif Jan^5,6, Arif Iqbal Umar¹, Ehab Mahmoud Mohamed^7,8

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 359-372, 2021, DOI:10.32604/cmc.2020.012196

Abstract Congestion control is one of the main obstacles in cyberspace traffic. Overcrowding in internet traffic may cause several problems; such as high packet hold-up, high packet dropping, and low packet output. In the course of data transmission for various applications in the Internet of things, such problems are usually generated relative to the input. To tackle such problems, this paper presents an analytical model using an optimized Random Early Detection (RED) algorithm-based approach for internet traffic management. The validity of the proposed model is checked through extensive simulation-based experiments. An analysis is observed for different functions on internet traffic. Four… More >

Abdelsalam Aldawoud^*, Fatma Elzahraa Hosny, Rasha Mdkhana

Energy Engineering, Vol.117, No.6, pp. 381-395, 2020, DOI:10.32604/EE.2020.011863

Abstract The opportunities for energy savings by retrofitting of the existing school buildings in the United Arab Emirates (UAE) are significant because of their excessive energy consumption and space cooling demand. In this research, energy modeling and simulation are utilized with the use of Design Builder software to examine the influence of various retrofitting measures of air-conditioning (A/C) system and building envelope components on the energy use. Several combined measures are implemented and assessed to achieve the main goal of this research of selecting the best course of action to reduce cooling energy consumption for existing school buildings in the UAE.… More >

Weiwen Kong¹, Baowei Wang^1,2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 849-863, 2020, DOI:10.32604/cmes.2020.012818

Abstract Internet of Things (IoT) is a network that connects things in a special union. It embeds a physical entity through an intelligent perception system to obtain information about the component at any time. It connects various objects. IoT has the ability of information transmission, information perception,andinformationprocessing.Theairqualityforecastinghasalways been an urgent problem, which affects people’s quality of life seriously. So far, many air quality prediction algorithms have been proposed, which can be mainly classifed into two categories. One is regression-based prediction, the other is deep learning-based prediction. Regression-based prediction is aimed to make use of the classical regression algorithm and the various… More >

Soukaina Mjahed^1,*, Khadija Bouzaachane¹, Ahmad Taher Azar^2,3, Salah El Hadaj¹, Said Raghay¹

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 459-494, 2020, DOI:10.32604/cmes.2020.010791

Abstract This paper focuses on the unsupervised detection of the Higgs boson particle using the most informative features and variables which characterize the “Higgs machine learning challenge 2014” data set. This unsupervised detection goes in this paper analysis through 4 steps: (1) selection of the most informative features from the considered data; (2) definition of the number of clusters based on the elbow criterion. The experimental results showed that the optimal number of clusters that group the considered data in an unsupervised manner corresponds to 2 clusters; (3) proposition of a new approach for hybridization of both hard and fuzzy clustering… More >