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Journal : TELKOMNIKA (Telecommunication Computing Electronics and Control)

Particle Filter with Integrated Multiple Features for Object Detection and Tracking Muhammad Attamimi; Takayuki Nagai; Djoko Purwanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 6: December 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i6.9466

Abstract

Considering objects in the environments (or scenes), object detection is the first task needed to be accomplished to recognize those objects. There are two problems needed to be considered in object detection. First, a single feature based object detection is difficult regarding types of the objects and scenes. For example, object detection that is based on color information will fail in the dark place. The second problem is the object’s pose in the scene that is arbitrary in general. This paper aims to tackle such problems for enabling the object detection and tracking of various types of objects in the various scenes. This study proposes a method for object detection and tracking by using a particle filter and multiple features consisting of color, texture, and depth information that are integrated by adaptive weights. To validate the proposed method, the experiments have been conducted. The results revealed that the proposed method outperformed the previous method, which is based only on color information.
Design of Electronic Nose System Using Gas Chromatography Principle and Surface Acoustic Wave Sensor Anifatul Faricha; Suwito Suwito; M. Rivai; M.A. Nanda; Djoko Purwanto; Rizki Anhar R.P.
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 4: August 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i4.7127

Abstract

Most gases are odorless, colorless and also hazard to be sensed by the human olfactory system. Hence, an electronic nose system is required for the gas classification process. This study presents the design of electronic nose system using a combination of Gas Chromatography Column and a Surface Acoustic Wave (SAW). The Gas Chromatography Column is a technique based on the compound partition at a certain temperature. Whereas, the SAW sensor works based on the resonant frequency change. In this study, gas samples including methanol, acetonitrile, and benzene are used for system performance measurement. Each gas sample generates a specific acoustic signal data in the form of a frequency change recorded by the SAW sensor. Then, the acoustic signal data is analyzed to obtain the acoustic features, i.e. the peak amplitude, the negative slope, the positive slope, and the length. The Support Vector Machine (SVM) method using the acoustic feature as its input parameters are applied to classify the gas sample. Radial Basis Function is used to build the optimal hyperplane model which devided into two processes i.e., the training process and the external validation process. According to the result performance, the training process has the accuracy of 98.7% and the external validation process has the accuracy of 93.3%. Our electronic nose system has the average sensitivity of 51.43 Hz/mL to sense the gas samples.
Performance Evaluation of MMA7260QT and ADXL345 on Self Balancing Robot Hany Ferdinando; Handry Khoswanto; Djoko Purwanto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 11, No 1: March 2013
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v11i1.876

Abstract

A self balancing robot (SBR) controller needs to detect platform inclination. For this purpose, an accelerometer is used. From various types of accelerometer, we can divide into digital and analog ones. The problem is how to select the right type for the SBR. This paper evaluates the performance of the ADXL345, 3-axis digital output accelerometer and the MMA7260QT, 3-axis analog output accelerometer. The Arduino is used to read data from the sensor and send it to PC for plotting. Both sensors use the lowest sensitivity. The sensors are evaluated with three criteria, i.e. stationary, dynamical response and collaborating with ITG3200 3-axis gyroscope for Kalman filter fusion. For stationary criterion, the ADXL345 is better than the other sensor for all stationary position. For dynamical response, both sensors suffer from the noise due to acceleration of the platform. The sensors do not only sense the gravity but also the acceleration of the platform when it is moved. But the noise level for the ADXL345 is lower than the other. Using Kalman filter makes both sensors show good performance for a SBR application. If three criteria are combined with hardware aspect, then the authors recommend using the ADXL345. Besides, it has several useful features to handle abrupt acceleration.
Electronic Nose using Gas Chromatography Column and Quartz Crystal Microbalance Muhammad Rivai; Djoko Purwanto; Hendro Juwono; Hari Agus Sujono
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 9, No 2: August 2011
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v9i2.703

Abstract

The conventional electronic nose usually consists of an array of dissimilar chemical sensors such as quartz crystal microbalance (QCM) combined with pattern recognition algorithm such as Neural network. Because of parallel processing, the system needs a huge number of sensors and circuits which may emerge complexity and inter-channel crosstalk problems. In this research, a new type of odor identification which combines between gas chromatography (GC) and electronic nose methods has been developed. The system consists of a GC column and a 10-MHz quartz crystal microbalance sensor producing a unique pattern for an odor in time domain. This method offers advantages of substantially reduced size, interferences and power consumption in comparison to existing odor identification system. Several odors of organic compounds were introduced to evaluate the selectivity of the system. Principle component analysis method was used to visualize the classification of each odor in two-dimensional space. This system could resolve common organic solvents, including molecules of different classes (aromatic from alcohols) as well as those within a particular class (methanol from ethanol) and also fuels (premium from pertamax). The neural network can be taught to recognize the odors tested in the experiment with identification rate of 85 %. It is therefore the system may take the place of human nose, especially for poisonous odor evaluations. 
Multiple Moving Obstacles Avoidance of Service Robot using Stereo Vision Widodo Budiharto; Ari Santoso; Djoko Purwanto; Achmad Jazidie
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 9, No 3: December 2011
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v9i3.733

Abstract

In this paper, we propose a multiple moving obstacles avoidance using stereo vision for service robots in indoor environments. We assume that this model of service robot is used to deliver a cup to the recognized customer from the starting point to the destination.  The contribution of this research is a new method for multiple moving obstacle avoidance with Bayesian approach using stereo camera.  We have developed and introduced 3 main modules to recognize faces, to identify multiple moving obstacles and to maneuver of robot. A group of people who is walking  will be tracked as a multiple moving obstacle, and  the speed, direction, and distance of the moving obstacles is  estimated by a stereo camera in order that the robot can maneuver to avoid the collision.  To overcome the inaccuracies of vision sensor, Bayesian approach is used for estimate the absense and direction of obstacles. We present the results of the experiment of the service robot called Srikandi III which uses our proposed method and we also evaluate its performance. Experiments shown that our proposed method working well, and Bayesian approach proved increasing the estimation perform for absence and direction of moving obstacle.
Co-Authors Achmad Jazidie Adrie Sentosa Ainuddin, Emha Amelia Kusuma Indriastuti Amelia Kusuma Indriastuti, Amelia Anas Maulidi Utama Anda Ferwira Andri Widihandoko Andrian, Muhammad Yunus Anifatul Faricha Arhamsyah Arhamsyah, Arhamsyah Ari Santoso Ari Santoso Ari Santoso Astria Nur Irfansyah Attamimi, Muhammad Bima Sena Bayu Dewantara Budi Tri Cahyana, Budi Tri Budiman, Fajar Chastine Fatichah Dermawan, Dimas Imam Devy Kuswidiastuti Diah Kusumawati, Diah Elfrin P. Hsb. Enny Zulaika EPF Eko Yulipriyono, EPF Epf. Eko Yulipriyono Felix Gunawan Furqan Aliyuddien Gangsarestu, Muhammad Soleh Garudio Kusuma Aji Handry Khoswanto Hani Avrilyantama Hany Ferdinando Hari Agus Sujono Harianto Harianto Haris Hariza Ekarinda Helmy Widyantara Hendra Kusuma Hendro Juwono Irfansyah, Astria Nur Ismiyati Ismiyati Jamhari Jamhari Kami Hari Basuki Kami Hari Basuki Kelvin Liusiani Kusuma, Hendra Siswanto M. Rivai Mannarul Hidayah Muchammad Ainur Fahd Muchammad Ainur Fahd Muhammad Attamimi Muhammad Hilman Fatoni Muhammad Ichlasul Salik Muhammad Rivai Muhammad Rivai Muhammad Rivai Muhammad Yunus Andrian Muharom, Syahri Nanda, Muhammad Achirul Naysila, Novita Prajna Wirya Kencana Putra Purbaningtyas, Retno Utami Putra, Karisma Trinanda Rahayu, Vidya Windi Retno Tri Wahyuni Rinne Nintasari Riza Agung Rizki Anhar R.P. Ronny Mardianto Ronny Mardiyanto, Ronny Rudy Dikairono Ruth Johana Hutagalung Setiawardhana Setiawardhana Setiawardhana Sonny H. Suryani, Santy Diah Suwito Suwito Takayuki Nagai Taufiq, Husen Totok Mujiono, Totok Tri Arief Sardjono Try Yuliandre Pajar Uroidhi, Ali Wahyudi Kushardjoko Widodo Budiharto Widodo Budiharto Widodo Budiharto Yunardi, Riky Tri