Journal of Electrical Engineering and Automation - June 2020
Latest Publications


TOTAL DOCUMENTS

54
(FIVE YEARS 54)

H-INDEX

2
(FIVE YEARS 2)

Published By Inventive Research Organization

2582-3051
Updated Saturday, 07 August 2021

2021 ◽  
Vol 3 (3) ◽  
pp. 154-168
Author(s):  
R Vinothkanna ◽  
M Duraipandian

Considerations about the increasing complexity of technological systems have stimulated the interest in hybrid systems that can successfully manage switching behaviour or approach nonlinearity. Hybrid systems are made up of two parts: a constant dynamics component and a switching mechanism. This article investigates the effectiveness of direct and indirect model adaptive control approaches for any common tool for hybrid modelling and approximation nonlinear systems. A reference model may be linear or partially refined, specifies the desired loop system behavior that the adaptive controllers are capable of achieving in the face of unknown system dynamics regardless of the system dynamics. Individual control gains are obtained for each subsystem and it is also carefully tuned to the altered behavior of each system. Through the application of dynamic gain adjustment, singularities in the principle of certainty equivalence are avoided indirectly. The state of the reference model is asymptotically monitored for both techniques by assuming that a shared Lyapunov feature is available for the switched reference model.


2021 ◽  
Vol 3 (2) ◽  
pp. 92-109
Author(s):  
A Pasumpon Pandian

This research article surveys the most recent IoT healthcare system research articles as the integration of IoT models have been extended to healthcare systems, such as health monitoring, fitness routines, and other applications. Extensive research study has been conducted on Internet of Things (IoT) technology to enhance the monitoring efficiency. This research is aimed at investigating the Internet of Things [IoT] architecture with an emphasis on cloud-based applications. The most significant challenges in the Internet of Things [IoT] include different elements such as accuracy and energy consumption, wherein this research is focused on improving the performance of IoT-based medical equipment. In this research, data management techniques for the Internet of Things-based cloud healthcare system are also thoroughly investigated. The performance and limitations of the Internet of Things (IoT) health system are evaluated. The majority of studies are successful in detecting a wide range of markers and correctly predicting illness. The Internet of Things (IoT) health system is being developed as an effective solution to the health concerns of elderly population. The major drawbacks of current systems are their increased energy consumption, reduced availability of resources, and safety concerns resulting from the use of a large number of different pieces of equipment.


2021 ◽  
Vol 3 (2) ◽  
pp. 110-123
Author(s):  
Rajesh Sharma R

Diabetes is a major cause of organ failure in the human body, and it is one of the leading causes of organ failure. As of now, there is no preventive medicine or vaccine for diabetes. As a result, people all around the world are accustomed to living with diabetes for the rest of their lives. Medical practitioners advise diabetic patients to have a healthy lifestyle that includes regular exercise and a well-balanced diet in order to prevent the effects of diabetes from spreading to other organs of the human body. In most cases, the diabetes is spreading like a heredity disease to the infected people and even to children and it can’t be estimated priory. In recent days, the deep learning algorithms are widely used to estimate the forthcoming effects of several problems by using the data mining process. In the proposed work, the performance of deep ANN and back propagation ANN is considered for estimating diabetes from several primary data factors obtained from a publicly available dataset called Pima Indian diabetes dataset.


2021 ◽  
Vol 3 (2) ◽  
pp. 124-137
Author(s):  
P Hengjinda ◽  
Joy Iong-Zong Chen

The harbours using green ports have become a common mode of enabling the use of environment friendly energy consumption. In this paper, two major contributions are made: reduction of energy consumption in the ports by using ships; prediction of energy consumption with respect to a green port. The characteristics that will play a crucial role in energy consumption of ships are considered and a detailed analysis has been performed to predict the energy consumed by the ships. Deep learning methodologies such as, K-Nearest Regression (KNR), Linear Regression (LR), BP Network (BP), Random Forest Regression (RF) and Gradient Boosting Regression (GBR) are used to determine the different characteristics of the ships that are used while the external features of the ports are given as input. To determine the efficiency of the proposed work, k-fold cross validation is also incorporated. Based on feature importance, the crucial features of the algorithm are selected. The influence of different changing aspects on the ship's energy usage is identified, and reduction methods are implemented appropriately. According to the observed data, the most essential factors that may be utilised to estimate energy consumption of the ship are efficiency of facilities, actual weight, deadweight tonnage, and net tonnage. As the efficiency increases, there is also a significant reduction and the power consumption of the ship at the rate of 8% and 32% in port and berth respectively.


2021 ◽  
Vol 3 (2) ◽  
pp. 138-153
Author(s):  
Jennifer S Raj ◽  
G Ranganathan

Due to the global energy crisis and environmental degradation, largely as a result of the increased usage of non-renewable energy sources, researchers have become more interested in exploring alternative energy systems, which may harvest energy from natural sources. This research article provides a comparison between various modeling of piezoelectric elements in terms of power generation for energy harvesting solutions. The energy harvesting can be computed and calculated based on piezoelectric materials and modeling for the specific application. The most common type of environmental energy that may be collected and transformed into electricity for several purposes is Piezoelectric transduction, which is more effective, compared to other mechanical energy harvesting techniques, including electrostatic, electromagnetic, and triboelectric transduction, due to their high electromechanical connection factor and piezoelectric coefficients. As a result of this research, scientists are highly interested in piezoelectric energy collection.


2021 ◽  
Vol 3 (2) ◽  
pp. 65-78
Author(s):  
Bindhu V

A customer relationship management (CRM) system based on Artificial Intelligence (AI) is used to discover critical success factors (CSF) in order to improve the automated business process and deliver better knowledge management (KM). Moreover, different factors contribute towards achieving efficient knowledge management in CRM systems with AI schemes. Identifying the key elements may be accomplished in a variety of ways. For this purpose, Delphi technique, nominal group technique, and brainstorming approach are used. Using the interpretive structural modelling (ISM) approach, ten key variables, significance degree, and interaction are determined. CSFs such as funding, leadership, and support are the most important of the ten variables identified for integrating KM, CRM, and AI. This approach has the potential to significantly improve the business processes.


2021 ◽  
Vol 3 (2) ◽  
pp. 79-91
Author(s):  
Subarna Shakya

Thermal imaging is utilized as a technique in agricultural crop water management due to its efficiency in estimating canopy surface temperature and the ability to predict crop water levels. Thermal imaging was considered as a beneficial integration in Unmanned Aerial Vehicle (UAV) for agricultural and civil engineering purposes with the reduced weight of thermal imaging systems and increased resolution. When implemented on-site, this technique was able to address a number of difficulties, including estimation of water in the plant in farms or fields, while considering officially induced variability or naturally existing water level. The proposed effort aims to determine the amount of water content in a vineyard using the high-resolution thermal imaging. This research work has developed an unmanned aerial vehicle (UAV) that is particularly intended to display high-resolution images. This approach will be able to generate crop water stress index (CWSI) by utilizing a thermal imaging system on a clear-sky day. The measured values were compared to the estimated stomatal conductance (sg) and stem water (s) potential along the Vineyard at the same time. To evaluate the performance of the proposed work, special modelling approach was used to identify the pattern of variation in water level. Based on the observation, it was concluded that both ‘sg’ and ‘s’ value have correlated well with the CWSI value by indicating a great potential to monitor instantaneous changes in water level. However, based on seasonal changes in water status, it was discovered that the recorded thermal images did not correspond to seasonal variations in water status.


2021 ◽  
Vol 3 (1) ◽  
pp. 34-43
Author(s):  
Nayana

Often, coalitions are formed by the hierarchical integrated energy systems (HIESs) and their evolutionary process which is driven by the benefits of stakeholders and consolidate energy consumers and producers. Several literature have failed to analyze the operation of HIES under the impact of multiple coalitions. At the lower level, multiple users, in the middle level, the multiple distributed energy stations (DESs) and at the upper level, one natural gas and one electricity utility company structure is used for analyzing the HIES operation with a trading scheme. The Lagrange function is used for deriving the optimal operation strategy based analytical function for each probable coalition and each market participant comprising of users and the DESs. It is evident from the results that in a single coalition, the profits linked to other DESs will decrease while increasing the profit of one DES with technological enhancements, users show an aversion towards DESs with high generation coefficient while they are attracted to the ones that enable reduction of heat and electricity price. Maintaining their isolation is preferred by high heat and electricity consuming DESs at the same energy price. Other coalitions and their operations are not affected by the change in parameters of one coalition.


Sign in / Sign up

Export Citation Format

Share Document