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All Journal Journal of Robotics and Control (JRC) International Journal of Community Service
Ali Selamat
Faculty of Computing, Universiti Teknologi Malaysia
Religion Aerospace Engineering Humanities Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mechanical Engineering Public Health Social Sciences Other

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A Recurrent Deep Architecture for Enhancing Indoor Camera Localization Using Motion Blur Elimination Alam, Muhammad S.; Mohamed, Farhan B.; Selamat, Ali; Hossain, AKM B.
Journal of Robotics and Control (JRC) Vol 5, No 4 (2024)
Publisher : Universitas Muhammadiyah Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18196/jrc.v5i4.21930

Abstract

Rapid growth and technological improvements in computer vision have enabled indoor camera localization. The accurate camera localization of an indoor environment is challenging because it has many complex problems, and motion blur is one of them. Motion blur introduces significant errors, degrades the image quality, and affects feature matching, making it challenging to determine camera pose accurately. Improving the camera localization accuracy for some robotic applications is still necessary. In this study, we propose a recurrent neural network (RNN) approach to solve the indoor camera localization problem using motion blur reduction. Motion blur in an image is detected by analyzing its frequency spectrum. A low-frequency component indicates motion blur, and by investigating the direction of these low-frequency components, the location and amount of blur are estimated. Then, Wiener filtering deconvolution removes the blur and obtains a clear copy of the original image. The performance of the proposed approach is evaluated by comparing the original and blurred images using the peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). After that, the camera pose is estimated using recurrent neural architecture from deblurred images or videos. The average camera pose error obtained through our approach is (0.16m, 5.61◦). In two recent research, Deep Attention and CGAPoseNet, the average pose error is (19m, 6.25◦) and (0.27m, 9.39◦), respectively. The results obtained through the proposed approach improve the current research results. As a result, some applications of indoor camera localization, such as mobile robots and guide robots, will work more accurately.
Optimizing STEM Learning in SDN Bringinan with Interactive PhET Technology Arifin, Rizal; Sudarno, Sudarno; Winardi, Yoyok; Desriyanti, Desriyanti; Adi Mustiko, Vijay; Johari, Norhasnidawani; Selamat, Ali
International Journal Of Community Service Vol. 4 No. 4 (2024): November 2024
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijcs.v4i4.298

Abstract

This program aimed to enhance STEM education at SDN Bringinan, Jambon, Ponorogo, by integrating PhET Interactive Simulations. The program focused on two main topics: energy transfer and energy transformations. Students from grades 4, 5, and 6 were divided into groups and guided by facilitators to explore these concepts using PhET. The program began with problem identification through discussions with the school's Principal and teachers, followed by careful planning and execution over two sessions in August 2024. The first session introduced students to heat transfer, while the second focused on energy transformations. Post-session evaluations showed that students successfully understood and applied these concepts, identifying energy sources, converters, and users, and explaining the process of energy transformations. The success of the program suggests the effectiveness of interactive technology like PhET in improving students' comprehension of complex scientific concepts, highlighting a valuable approach for future educational initiatives.
Enhancing Teacher Competency In Using Technology-Based Interactive Learning Media Through Wordwall Training At Tsanawiyah Dharut Thalibin Widaningrum, Ida; Puji Astuti, Indah; Nurfitri, Khoiru; Rahmatika Az-Zahra, Rifqi; Mustikasari, Dyah; Selamat, Ali; Widiyahseno, Bambang
International Journal Of Community Service Vol. 4 No. 4 (2024): November 2024
Publisher : CV. Inara

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51601/ijcs.v4i4.785

Abstract

This community service focuses on training teachers to use technology-based interactive learning media, especially the Wordwall platform, for Tsanawiyah Dharut Thalibin, Sampung, Ponorogo, and East Java. This training aims to improve teachers' skills in creating interactive digital worksheets to overcome student boredom and increase active participation in learning. The training was carried out in several stages, starting from problem identification and planning to evaluation. The results of this training showed that most teachers had not previously used technology-based learning media. After the training, teachers can use the Wordwall platform to create interactive learning activities, such as quizzes and games, which are expected to increase student engagement and create a more dynamic learning atmosphere. The evaluation showed increased teachers' understanding and skills in interactive learning media.
Co-Authors Adi Mustiko, Vijay Alam, Muhammad S. Arifin, Rizal Bambang Widiyahseno, Bambang Desriyanti, Desriyanti Dyah Mustikasari Hossain, AKM B. Ida Widaningrum, Ida Johari, Norhasnidawani Mohamed, Farhan B. Nurfitri, Khoiru Puji Astuti, Indah Rahmatika Az-Zahra, Rifqi Sudarno Sudarno Winardi, Yoyok