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p-Index From 2020 - 2025
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All Journal JISKa (Jurnal Informatika Sunan Kalijaga) Journal of Engineering and Technological Sciences
Chang, Shyang-Jye
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Aerospace Engineering Automotive Engineering Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Library & Information Science

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Revitalizing Art with Technology: A Deep Learning Approach to Virtual Restoration Putranti, Nurrohmah Endah; Chang, Shyang-Jye; Raffiudin, Muhammad
JISKA (Jurnal Informatika Sunan Kalijaga) Vol. 10 No. 1 (2025): January 2025
Publisher : UIN Sunan Kalijaga Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14421/jiska.2025.10.1.87-99

Abstract

This study evaluates CycleGAN's performance in virtual painting restoration, focusing on color restoration and detail reproduction. We compiled datasets categorized by art styles and conditions to achieve accurate restorations without altering original reference materials. Various paintings and those with a yellow filter, to create effective training datasets for CycleGAN. The model utilized cycle consistency loss and advanced data augmentation techniques. We assessed the results using PSNR, SSIM, and Color Inspector metrics, focusing on Claude Monet's Nasturtiums in a Blue Vase and Hermann Corrodi's Prayers at Dawn. The findings demonstrate superior color recovery and preservation of intricate details compared to other methods, confirmed through quantitative and qualitative evaluations. Key contributions include employing CycleGAN for art restoration, model evaluation, and framework development. Practical implications extend to art conservation, digital library enhancement, art education, and broader access to restored works. Future research may explore dataset expansion, complex architectures, interdisciplinary collaboration, automated evaluation tools, and improved technologies for real-time restoration applications. In conclusion, CycleGAN holds promise for digital art conservation, with ongoing efforts aimed at integrating across fields for effective cultural preservation.
Design and Application of a Kirigami-Based Soft Robotic Gripper using Finite Element Analysis Gomes, Efrem Olivio; Chang, Shyang-Jye; Saputra, Ilham
Journal of Engineering and Technological Sciences Vol. 57 No. 4 (2025): Vol. 57 No. 4 (2025): August
Publisher : Directorate for Research and Community Services, Institut Teknologi Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.5614/j.eng.technol.sci.2025.57.4.3

Abstract

The demand for adaptable and efficient soft robotic grippers has grown due to their potential applications in industries such as food handling, manufacturing, and logistics. This study explores a Kirigami-based soft robotic gripper, designed to handle a wide range of objects with minimal risk of damage. The gripper utilizes a Kirigami-inspired structure combined with Liquid Silicone Rubber (LSR CN-251), chosen for its flexibility, durability, and food-safe properties. Finite element analysis was conducted to analyze the gripper’s mechanical performance under tensile forces ranging from 0.1 N to 4.3 N, focusing on stress distribution and deformation. Experimental validation was performed to verify the simulated results and assess the gripper’s performance in real-world scenarios. The simulations revealed predictable stress distribution and controlled deformation, with experimental tests demonstrating the gripper’s successful handling of delicate items, irregular objects, heavier item, and others. The Kirigami structure’s passive force distribution enabled a secure yet gentle grip, minimizing the risk of damage. The gripper’s adaptability, flexibility, and lightweight construction were confirmed in these tests. Manufactured from food-safe LSR, the gripper presents a cost-effective and efficient alternative to traditional pneumatic or jamming-based grippers. Limitations in the experimental setup, such as the restricted range of the uArm Swift Pro, were noted, and future research should explore dynamic performance under real-world conditions, enhance the range of motion, and integrate sensory feedback for improved precision.
Co-Authors Gomes, Efrem Olivio Putranti, Nurrohmah Endah Raffiudin, Muhammad Saputra, Ilham