R. Sowmyalakshmi¹, T. Jayasankar^1,*, V. Ayyem Pillai², Kamalraj Subramaniyan³, Irina V. Pustokhina⁴, Denis A. Pustokhin⁵, K. Shankar⁶

CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 1751-1767, 2021, DOI:10.32604/cmc.2021.016825

Abstract Internet of Things (IoT) paves a new direction in the domain of smart farming and precision agriculture. Smart farming is an upgraded version of agriculture which is aimed at improving the cultivation practices and yield to a certain extent. In smart farming, IoT devices are linked among one another with new technologies to improve the agricultural practices. Smart farming makes use of IoT devices and contributes in effective decision making. Rice is the major food source in most of the countries. So, it becomes inevitable to detect rice plant diseases during early stages with the… More >

Shankarnarayanan Nalini^1,*, Nagappan Krishnaraj², Thangaiyan Jayasankar³, Kalimuthu Vinothkumar⁴, Antony Sagai Francis Britto⁵, Kamalraj Subramaniam⁶, Chokkalingam Bharatiraja⁷

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1117-1128, 2021, DOI:10.32604/cmc.2021.012431

Abstract Precision Agriculture is a concept of farm management which makes use of IoT and networking concepts to improve the crop. Plant diseases are one of the underlying causes in the decrease in the number of quantity and quality of the farming crops. Recognition of diseases from the plant images is an active research topic which makes use of machine learning (ML) approaches. A novel deep neural network (DNN) classification model is proposed for the identification of paddy leaf disease using plant image data. Classification errors were minimized by optimizing weights and biases in the DNN… More >

D. Venugopal¹, T. Jayasankar^2,*, N. Krishnaraj³, S. Venkatraman⁴, N. B. Prakash⁵, G. R. Hemalakshmi⁵

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 27-38, 2021, DOI:10.32604/iasc.2021.015205

Abstract Comprehensive evaluation of common complex diseases associated with common gene mutations is currently a hot area of human genome research into causative new developments. A multi-fractal analysis of the genome is performed by placing the entire DNA sequence into smaller fragments and using the chaotic game representation and systematic methods to calculate the general dimensional spectrum of each fragment. This is a time consuming process as it uses floating point to represent large data sets and requires processing time. The proposed Regressive Multi-Array Deep Neural Classifier (RMDNC) system is implemented to reduce the computation time,… More >

Pinjie Xu², Ce Li^1,2,*, Liguo Zhang^3,4, Feng Yang^1,2, Jing Zheng^1,5, Jingwu Feng²

Journal on Artificial Intelligence, Vol.1, No.1, pp. 9-18, 2019, DOI:10.32604/jai.2019.06157

Abstract Detecting the underground disease is very crucial for the roadbed health monitoring and maintenance of transport facilities, since it is very closely related to the structural health and reliability with the rapid development of road traffic. Ground penetrating radar (GPR) is widely used to detect road and underground diseases. However, it is still a challenging task due to data access anywhere, transmission security and data processing on cloud. Cloud computing can provide scalable and powerful technologies for large-scale storage, processing and dissemination of GPR data. Combined with cloud computing and radar detection technology, it is More >

Somayeh Hessam¹, Shaghayegh Vahdat¹, Irvan Masoudi Asl^2,*, Mahnaz Kazemipoor³, Atefeh Aghaei⁴, Shahaboddin Shamshirband,^5,6,*, Timon Rabczuk⁷

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 11-26, 2019, DOI:10.32604/cmc.2019.06472

Abstract In recent years, Parkinson's Disease (PD) as a progressive syndrome of the nervous system has become highly prevalent worldwide. In this study, a novel hybrid technique established by integrating a Multi-layer Perceptron Neural Network (MLP) with the Biogeography-based Optimization (BBO) to classify PD based on a series of biomedical voice measurements. BBO is employed to determine the optimal MLP parameters and boost prediction accuracy. The inputs comprised of 22 biomedical voice measurements. The proposed approach detects two PD statuses: 0-disease status and 1- good control status. The performance of proposed methods compared with PSO, GA, More >