Rohit Samkria¹, Mohammed Abd-Elnaby², Rajesh Singh³, Anita Gehlot³, Mamoon Rashid^4,*, Moustafa H. Aly⁵, Walid El-Shafai⁶

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1709-1723, 2021, DOI:10.32604/cmc.2021.018525

Abstract Fault detection of the photovoltaic (PV) grid is necessary to detect serious output power reduction to avoid PV modules’ damage. To identify the fault of the PV arrays, there is a necessity to implement an automatic system. In this IoT and LabVIEW-based automatic fault detection of 3 × 3 solar array, a PV system is proposed to control and monitor Internet connectivity remotely. Hardware component to automatically reconfigure the solar PV array from the series-parallel (SP) to the complete cross-linked array underneath partial shading conditions (PSC) is centered on the Atmega328 system to achieve maximum power. In the LabVIEW environment,… More >

Nahida Islam¹, Fahiba Farhin¹, Ishrat Sultana¹, M. Shamim Kaiser¹, Md. Sazzadur Rahman¹, Mufti Mahmud², A. S. M. Sanwar Hosen³, Gi Hwan Cho^3,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1801-1821, 2021, DOI:10.32604/cmc.2021.018466

Abstract The Internet of Things (IoT) integrates billions of self-organized and heterogeneous smart nodes that communicate with each other without human intervention. In recent years, IoT based systems have been used in improving the experience in many applications including healthcare, agriculture, supply chain, education, transportation and traffic monitoring, utility services etc. However, node heterogeneity raised security concern which is one of the most complicated issues on the IoT. Implementing security measures, including encryption, access control, and authentication for the IoT devices are ineffective in achieving security. In this paper, we identified various types of IoT threats and shallow (such as decision… More >

Mahmoud Ragab^1,2, Ali Algarni³, Adel A. Bahaddad⁴, Romany F. Mansour^5,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2277-2294, 2021, DOI:10.32604/cmc.2021.018000

Abstract Physical health plays an important role in overall well-being of the human beings. It is the most observed dimension of health among others such as social, intellectual, emotional, spiritual and environmental dimensions. Due to exponential increase in the development of wireless communication techniques, Internet of Things (IoT) has effectively penetrated different aspects of human lives. Healthcare is one of the dynamic domains with ever-growing demands which can be met by IoT applications. IoT can be leveraged through several health service offerings such as remote health and monitoring services, aided living, personalized treatment, and so on. In this scenario, Deep Learning… More >

Faisal Mehmood¹, Shabir Ahmad^2,3, Israr Ullah¹, Faisal Jamil¹, DoHyeun Kim^1,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2231-2244, 2021, DOI:10.32604/cmc.2021.017528

Abstract The data being generated by the Internet of Things needs to be stored, monitored, and analyzed for maximum IoT resource utilization. Software Defined Networking has been extensively utilized to address issues such as heterogeneity and scalability. However, for small-scale IoT application, sometimes it is considered an inefficient approach. This paper proposes an alternate lightweight mechanism to the design and implementation of a dynamic virtual network based on user requirements. The key idea is to provide users a virtual interface that enables them to reconfigure the communication flow between the sensors and actuators at runtime. The throughput of the communication flow… More >

Naglaa F. Soliman^1,2, Abeer D. Algarni^1,*, Walid El-Shafai³, Fathi E. Abd El-Samie^1,3, Ghada M. El Banby⁴

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1571-1595, 2021, DOI:10.32604/cmc.2021.016980

Abstract Cancelable biometrics are required in most remote access applications that need an authentication stage such as the cloud and Internet of Things (IoT) networks. The objective of using cancelable biometrics is to save the original ones from hacking attempts. A generalized algorithm to generate cancelable templates that is applicable on both single and multiple biometrics is proposed in this paper to be considered for cloud and IoT applications. The original biometric is blurred with two co-prime operators. Hence, it can be recovered as the Greatest Common Divisor (GCD) between its two blurred versions. Minimal changes if induced in the biometric… More >

Merna Gamal¹, Hala M. Abbas², Nour Moustafa^3,*, Elena Sitnikova³, Rowayda A. Sadek¹

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1823-1837, 2021, DOI:10.32604/cmc.2021.012877

Abstract Intrusion Detection Systems (IDSs) have a great interest these days to discover complex attack events and protect the critical infrastructures of the Internet of Things (IoT) networks. Existing IDSs based on shallow and deep network architectures demand high computational resources and high volumes of data to establish an adaptive detection engine that discovers new families of attacks from the edge of IoT networks. However, attackers exploit network gateways at the edge using new attacking scenarios (i.e., zero-day attacks), such as ransomware and Distributed Denial of Service (DDoS) attacks. This paper proposes new IDS based on Few-Shot Deep Learning, named CNN-IDS,… More >

Jesus Hamilton Ortiz¹, Javier Ferney Castillo García², Osamah Ibrahim Khalaf³, Fernando Velez Varela^2,*, Pedro Jefferson Barragan Baron², Jhon Hadder Guzmán Atehortúa²

Journal on Internet of Things, Vol.3, No.2, pp. 53-63, 2021, DOI:10.32604/jiot.2021.014736

Abstract This work shows the development of a module that performs measurements of electrical variables in a low voltage power transformer. These variables are sent by means of the IEEE802.11 standard, connecting to a database stored in the cloud; associating with the meter IoT concepts, this to allow a client to perform an analysis, monitoring and management of their electrical network. For the construction of this module, non-invasive current sensors connected to a three-phase meter are used and a communication card is used that allows data to be extracted from the meter and sent to the cloud database. This module, to… More >

SULAIMAN A. AL YOUSEF^*

BIOCELL, Vol.45, No.5, pp. 1403-1411, 2021, DOI:10.32604/biocell.2021.015450

Abstract Seeds from soybean collected from different commercial markets were surveyed for seed-borne fungi. Ninetyeight fungal colonies were isolated all over three monthly isolations constituting twenty-two fungal species. The isolated fungi were belonging to the genera: Alternaria, Aspergillus, Cephalosporium, Chaetomium, Cladosporium, Colletotrichum, Curvularia, Fusarium, Macrophomina, Mucor, Penicillium, Rhizoctonia, Rhizopus, Sclerotium, Stemphylium, and Verticillium. Assay of the antifungal activity of four ethanolic extracts of clove, cinnamon, garlic, and mint was carried out against the most common fungal species (Aspergillus flavus, A. niger, Fusarium solani, F. oxysporium, and F. moniliforme), which significantly reduced the growth of tested fungi. Clove extract recorded the highest… More >

Fenni Lv^1,2,#, Sen Wang^3,#, Ruiping Tian¹, Peng Wang², Kang Liu^1,*

Phyton-International Journal of Experimental Botany, Vol.90, No.6, pp. 1645-1660, 2021, DOI:10.32604/phyton.2021.016947

Abstract Villin (VLN) is considered to be one of the most important actin-binding proteins, participates in modulating the actin cytoskeleton dynamics, plays essential role in plant development and resisting adverse environments. However, systematic studies of the VLN gene family have not been reported in cotton (Gossypium). In this study, 14 GhVLNs were identified in G. hirsutum. These GhVLN genes were distributed in 6 A-subgenome chromosomes and 6 D-subgenome chromosomes of the allotetraploid upland cotton and classified into three phylogenetical groups based on the classification model of AtVLNs. In addition, the 14 GhVLN genes have highly conserved gene structure and motif architecture.… More >

Hyun Yoo¹, Ji-Won Baek², Kyungyong Chung^3,*

Intelligent Automation & Soft Computing, Vol.29, No.2, pp. 319-334, 2021, DOI:10.32604/iasc.2021.018115

Abstract With the convergence and development of the Internet of things (IoT) and artificial intelligence, closed-circuit television, wearable devices, and artificial neural networks have been combined and applied to crime prevention and follow-up measures against crimes. However, these IoT devices have various limitations based on the physical environment and face the fundamental problem of privacy violations. In this study, voice data are collected and emotions are classified based on an acoustic sensor that is free of privacy violations and is not sensitive to changes in external environments, to overcome these limitations. For the classification of emotions in the voice, the data… More >