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Journal : International Journal of Electrical and Computer Engineering

Intelligent Robotics Navigation System: Problems, Methods, and Algorithm Siti Nurmaini; Bambang Tutuko
International Journal of Electrical and Computer Engineering (IJECE) Vol 7, No 6: December 2017
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (611.098 KB) | DOI: 10.11591/ijece.v7i6.pp3711-3726

Abstract

This paper set out to supplement new studies with a brief and comprehensible review of the advanced development in the area of the navigation system, starting from a single robot, multi-robot, and swarm robots from a particular perspective by taking insights from these biological systems. The inspiration is taken from nature by observing the human and the social animal that is believed to be very beneficial for this purpose. The intelligent navigation system is developed based on an individual characteristic or a social animal biological structure. The discussion of this paper will focus on how simple agent’s structure utilizes flexible and potential outcomes in order to navigate in a productive and unorganized surrounding. The combination of the navigation system and biologically inspired approach has attracted considerable attention, which makes it an important research area in the intelligent robotic system. Overall, this paper explores the implementation, which is resulted from the simulation performed by the embodiment of robots operating in real environments.
Inverse kinematic analysis of 4 DOF pick and place arm robot manipulator using fuzzy logic controller Tresna Dewi; Siti Nurmaini; Pola Risma; Yurni Oktarina; Muhammad Roriz
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1118.067 KB) | DOI: 10.11591/ijece.v10i2.pp1376-1386

Abstract

The arm robot manipulator is suitable for substituting humans working in tomato plantation to ensure tomatoes are handled efficiently. The best design for this robot is four links with robust flexibility in x, y, and z-coordinates axis. Inverse kinematics and fuzzy logic controller (FLC) application are for precise and smooth motion. Inverse kinematics designs the most efficient position and motion of the arm robot by adjusting mechanical parameters. The FLC utilizes data input from the sensors to set the right position and motion of the end-effector. The predicted parameters are compared with experimental results to show the effectiveness of the proposed design and method. The position errors (in x, y, and z-axis) are 0.1%, 0.1%, and 0.04%. The rotation errors of each robot links (θ1, θ2, and θ3) are 0%, 0.7% and 0.3%. The FLC provides the suitable angle of the servo motor (θ4) responsible in gripper motion, and the experimental results correspond to FLC’s rules-based as the input to the gripper motion system. This setup is essential to avoid excessive force or miss-placed position that can damage tomatoes. The arm robot manipulator discussed in this study is a pick and place robot to move the harvested tomatoes to a packing system.
Intelligent Sensing Using Metal Oxide Semiconductor Based-on Support Vector Machine for Odor Classification Nyayu Latifah Husni; Siti Nurmaini; Irsyadi Yani; Ade Silvia
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 6: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1148.853 KB) | DOI: 10.11591/ijece.v8i6.pp4133-4147

Abstract

Classifying odor in real experiment presents some challenges, especially the uncertainty of the odor concentration and dispersion that can lead to a difficulty in obtaining an accurate datasets. In this study, to enhance the accuracy, datasets arrangement based on MOS sensors parameters using SVM approach for odor classification is proposed. The sensors are tested to determine the sensors' time response, sensors' peak duration, sensors' sensitivity, and sensors' stability when applied to the various sources at different range. Three sources were used in experimental test, namely: ethanol, methanol, and acetone. The gas sensors characteristics are analyzed in open sampling method to see the sensors' performance in real situation. These performances are considered as the base of choosing the position in collecting the datasets. The sensors in dynamic experiment have average of precision of 93.8-97.0%, the accuracy 93.3-96.7%, and the recall 93.3-96.7%. This values indicates that the collected datasets can support the SVM in improving the intelligent sensing when conducting odor classification work.
Enhancing ultrasound image quality using deep structure of residual network Sapitri, Ade Iriani; Nurmaini, Siti; Rachmatullah, Muhammad Naufal; Darmawahyuni, Annisa; Firdaus, Firdaus; Islami, Anggun; Tutuko, Bambang; Arum, Akhiar Wista
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i4.pp3779-3794

Abstract

Ultrasonography, a medical imaging technique, is often affected by various types of noise and low brightness, which can result in low image quality. These drawbacks can significantly impede accurate interpretation and hinder effective medical diagnoses. Therefore, improving image quality is an essential aspect of the field of ultrasound systems. This study aims to enhance the quality of ultrasound images using deep learning (DL). The experiment is conducted using a custom dataset consisting of 2,175 infant heart ultrasound images collected from Indonesian hospitals, and the model is subsequently generalized using other datasets. We propose enhanced deep residual network combined convolutional neural networks (EDR-CNNs) to improve the image quality. After the enhancement process, our model achieved peak signal-to-noise ratio (PSNR) and structural similarity index metrics (SSIM) scores of 38.35 and 0.92 respectively, outperforming other methods. The benchmarking with other ultrasound medical images indicates that our proposed model produces good performance, as evidenced by higher PSNR, lower SSIM, a decrease in mean square error (MSE), and a lower contrast improvement index (CII). In conclusion, this study encapsulates the forthcoming trends in advancing low-illumination image enhancement, along with exploring the prevailing challenges and potential directions for further research.
Co-Authors A. Darmawahyuni A. I. Sapitri Ade Iriani Sapitri Ade Iriani Sapitri Ade Iriani Sapitri Ade Silvia Ade Silvia Ade Silvia Handayani Aditya Aditya Aditya, Aditya Agung Juli Anda Agus Triadi Agus Triadi Agus Triadi Ahmad Zarkasi Ahmad Zarkasi Ahmad Zarkasi Ahmad Zarkasih Akhiar Wista Arum Andre Herviant Juliano Anggun Islami Anggun Islami Annisa Darmawahyuni Ardy Hidayat Arief Cahyo Utomo Armansyah, Risky Arnaldo, Muhammad Arum, Akhiar Wista Aulia Rahman Thoharsin B. Tutuko Bambang Tutuko Bambang Tutuko Bayu Wijaya Putra Benedictus Wicaksono Widodo Bhakti Yudho Suprapto Bhakti Yudho Suprapto Bhakti Yudho Suprapto Cindy Kesty Darmawahyuni, Annisa Darmawahyuni, Annisa Deris Stiawan Dewi, Kemala Dewi, Tresna Dian Palupi Rini Dian Palupi Rini Dian Palupi Rini Dimas Budianto Dinda Lestarini Dodo Zaenal Abidin Dwi Mei Rita Sari Ekawati Prihatini Erliza Yuniarti Fachrudin Abdau Fahreza, Irvan Falah Yuridho Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus, Firdaus Firsandaya Malik, Reza Ganesha Ogi GITA FADILA FITRIANA Hadipurnawan Satria Hanif Habibie Supriansyah Huda Ubaya Huda Ubaya Huda Ubaya Husnawati Husnawati Husnawati Husnawati Husnawati Husni, Nyayu Latifah Husni, Nyayu Latifah Irfannuddin Irfannuddin Irsyadi Yani Irvan Fahreza Iryadi Yani Iryadi Yani, Iryadi Isdwanta, Rendy Islami, Anggun Jasmir Jasmir Jasmir Jasmir Jordan Marcelino Kemala Dewi Khairunnisa, Cholidah Zuhroh Krisna Murti Kurniawan, Anggy Tias Kurniawan, Anggy Tyas Legiran Legiran M. Hashim, Siti Zaiton M. N. Rachmatullah M. Naufal Rachmatullah Maharani, Masayu Nadila Marcelino, Jordan Masayu Nadila Maharani Mira Afrina Muhamad Akbar Muhammad Afif Muhammad Anshori Muhammad Arnaldo Muhammad Fachrurrozi Muhammad Fachrurrozi Muhammad Irham Rizki Fauzi Muhammad Naufal Rachmatullah Muhammad Naufal, Muhammad Muhammad Roriz Muhammad Taufik Roseno, Muhammad Taufik Muzakkie, Mufida Nadia Ayu Oktabella, nadia ayu oktabella Novi Yusliani Nurqolbiah, Fatihani Nuswil Bernolian Nuswil Bernolian Nyayu Latifah Husni Nyayu Latifah Husni, Nyayu Latifah Oky Budiyarti Osvari Arsalan Passa, Rahma Satila Patiyus Agustiansyah PATIYUS AGUSTIANSYAH, PATIYUS Pola Risma PP Aditya, PP, Aditya, PP Pratama, Jimiria Putri Mirani Rachmamtullah, Muhammad Naufal Radiyati Umi Partan Radiyati Umi Partan Radiyati Umi Partan Radiyati Umi Partan, Radiyati Umi Rahma Satila Passa Rendy Isdwanta Renny Amalia Pratiwi Reza Firsandaya Malik Reza Firsandaya Malik Ria Nova Ricy Firnando Ricy Firnando Ricy Firnando Rizal Sanif Rizki Kurniati Rossi Passarella Sahat Pangidoan Samsuryadi Samsuryadi Saparudin Saparudin Saparudin, Saparudin Sapitri, Ade Iriani Saputra, Tommy Sari, Dwi Mei Rita Sarifah Putri Raflesia Sarifah Putri Raflesia, Sarifah Putri Sastradinata, Irawan Sigit Prasetyo Noprianto Siti Zaiton Siti Zaiton M. Hashim Soedjana, Hardi Siswo Sri Desy Siswanti Suci Dwi Lestari Suci Dwi Lestari Suhandono, Nugroho Sukemi Sukemi Sukemi Sukemi Sukemi Sukman Tulus Putra Sutarno Sutarno Syamsul Arifin Syaputra, Hadi Tio Artha Nugraha Tresna Dewi Tresna Dewi Tri Undari Triadi, Agus Triadi, Agus Varindo Ockta Keneddi Putra Velia Yuliza Winda Kurnia Sari Wisnu Adi Putra Yani, Iryadi Yesi Novaria Kunang Yurni Oktarina Zaqqi Yamani