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INDONESIA
Emerging Science Journal
Published by Ital Publication
ISSN : 26109182     EISSN : -     DOI : -
Core Subject : Social,
Environmental Science
Emerging Science Journal is not limited to a specific aspect of science and engineering but is instead devoted to a wide range of subfields in the engineering and sciences. While it encourages a broad spectrum of contribution in the engineering and sciences. Articles of interdisciplinary nature are particularly welcome.
Arjuna Subject : -
Articles 12 Documents
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Search results for , issue "Vol 7, No 6 (2023): December" : 12 Documents clear
Trajectory Tracking Control of a Mobile Robot using Neural Networks Darwin Trujillo; Luis A. Morales; Danilo Chávez; David F. Pozo
Emerging Science Journal Vol 7, No 6 (2023): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2023-07-06-01

Abstract

This paper presents a novel soft computing-based machine learning technique designed to enhance the trajectory tracking capabilities of mobile robots through the application of neural networks. The goal of this approach is to enhance the accuracy and overall performance of trajectory tracking without the need for manual gain recalibration, which is a tedious and time-consuming task for the designer when setting up the robot. This improvement is achieved by creating a kinematic controller based on neural networks, which are constructed using the kinematic model of the robot. In the initial phase, the controller requires gains defined by the designer. Subsequently, during the application phase, the backpropagation algorithm is used to dynamically adjust the gains of the neural network, aiming to minimize the closed-loop error. One of the key innovations introduced by this controller is the potential for automatic online gain tuning, thereby eliminating the need for a pre-learning phase, typically required by traditional neural controllers. To validate the effectiveness of this approach, the results are systematically analyzed and compared against those obtained using a conventional kinematic controller. Performance metrics reveal the improved precision in trajectory tracking achieved by the controller, with reduced effort, highlighting the performance enhancements in different trajectories. Doi: 10.28991/ESJ-2023-07-06-01 Full Text: PDF
Bridging Sustainable Bank Performance through Fintech and Enacted Norms Steph Subanidja; Fangky A. Sorongan; Mercurius B. Legowo
Emerging Science Journal Vol 7, No 6 (2023): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2023-07-06-017

Abstract

Since the launch of green banking, the Government Authority still needs to accommodate enacted norms and fintech in measuring sustainable bank performance. Empirically, this study aims to reveal the impact of variables and business drivers on sustainable bank performance. This research uses a quantitative approach through path analysis. By analysing 70 out of 78 bank managers or directors who are members of the National Banking Association as respondents, this study states that business drivers, fintech, and enacted norms encourage sustainable bank performance improvement. In addition, fintech and enacted norms are suitable as moderating and exogenous variables for sustainable bank performance, but the variables are not endogenous variables for business drivers. In addition, fintech and enacted norms can bridge the achievement of sustainable bank performance. The originality of this research is that enacted norms and fintech are the moderating variables in realising bank sustainability. The research suggests that enacted norms should be one of the new dimensions in measuring bank sustainability, and the existence of fintech could be an integral part of realising sustainable bank performance. Doi: 10.28991/ESJ-2023-07-06-017 Full Text: PDF

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