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TELKOMNIKA (Telecommunication Computing Electronics and Control)
Published by Universitas Ahmad Dahlan
ISSN : 16936930     EISSN : 23029293     DOI : 10.12928
Core Subject : Science,
Computer Science & IT
Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of submissions that TELKOMNIKA has received during the last few months the duration of the review process can be up to 14 weeks. Communication Engineering, Computer Network and System Engineering, Computer Science and Information System, Machine Learning, AI and Soft Computing, Signal, Image and Video Processing, Electronics Engineering, Electrical Power Engineering, Power Electronics and Drives, Instrumentation and Control Engineering, Internet of Things (IoT)
Arjuna Subject : Ilmu Komputer (semua kategori) - Aplikasi Ilmu Komputer
Articles 64 Documents
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Search results for , issue "Vol 15, No 1: March 2017" : 64 Documents clear
Open-circuit Fault Diagnosis for Grid-connected NPC Inverter based on Independent Component Analysis and Neural Network Xiaofeng Wan; Hailin Hu; Yunjun Yu; Liping Kang; Fanpeng Zeng
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i1.3677

Abstract

This paper is under in-depth investigation due to suspicion of possible plagiarism on a high similarity indexAn open circuit (O-C) fault detection method for grid-connected neutral-point-clamped (NPC) inverter based on independent component analysis (ICA) and neural network (NN) is proposed in this paper. A NN classifier is applied to the fault diagnosis of NPC inverter. The ICA is utilized for the three phase current feature extraction. The ICA reduces the number of NN input neuron. A lower dimensional input space reduces the noise and the training time of NN, the ICA algorithm improves the mapping performance. The proposed algorithm is evaluated with simulation test set. The overall classification performance of the proposed network is more than 97%. The simulation results show that the proposed algorithm performs satisfactorily to fault location.
Device Discovery Schemes for Energy-efficient Cluster Head Rotation in D2D Bhaskara Narottama; Arfianto Fahmi; Budi Syihabuddin; Desti Madya Saputri; Patricius Evander Christy; Obed Rhesa Ludwiniananda
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i1.4676

Abstract

 In this paper, novel device discovery approaches for the Cluster Head Rotation, which is a state-of-the-art method for the Device-to-Device communication, are proposed. The device discovery is the process to detect and to include new devices in the Device-to-Device communication. The proposed device discovery is aimed to attain energy efficiency for the communication devices. We propose two schemes for the device discovery: eNB-assisted and independent device discovery. Compared to previous work, the proposed device discovery is utilizing the cluster head rotation method, to achieve better energy efficiency. In this work, several simulations were performed and discussed for both schemes. In the first simulation, the device energy consumption is examined. After that, the number of devices that get rejected is studied. The device discovery processes in multi cluster head scenario, which is Cluster Head Rotation, are examined in this paper. The result of the simulation shows that eNB-assisted device discovery can provide better energy efficiency. Also, the number of rejected devices of the eNB-assisted device discovery is slightly lower than independent device discovery.
Potential Usage Estimation of Ground Water using Spatial Association Rule Mining Suci Sri Utami Sutjipto; Imas Sukaesih Sitanggang; Baba Barus
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i1.4750

Abstract

The utilization of ground water in the long term will lead to a number of negative impacts on groundwater resources and the environment, such as the decrease of groundwater level, seawater intrusion, land subsidence as well as scarcity of ground water. Furthermore, the use of ground water has directly affected the consumption pattern of Regional Water Company Bogor City (PDAM) customers. This study aims to determine the patterns and characteristics of PDAM customers in the utilization of ground water by using spatial association rule mining, so it can help PDAM to approximate the increase of customers that utilize ABT and the losses incurred. This research shows that as many as 53.362 (41.27%) PDAM customers that have the potential to use groundwater. The said customers are featured by several characteristics, such as being active customers, with monthly water bill of less than Rp. 53.358 and are not close to river.
A Novel Text Classification Method Using Comprehensive Feature Weight Jian Liu; Weisheng Wu
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i1.4303

Abstract

Currently, since the categorical distribution of short text corpus is not balanced, it is difficult to obtain accurate classification results for long text classification. To solve this problem, this paper proposes a novel method of short text classification using comprehensive feature weights. This method takes into account the situation of the samples in the positive and negative categories, as well as the category correlation of words, so as to improve the existing feature weight calculation method and obtain a new method of calculating the comprehensive feature weight. The experimental result shows that the proposed method is significantly higher than other feature-weight methods in the micro and macro average value, which shows that this method can greatly improve the accuracy and recall rate of short text classification.
Back-stepping Control of Free-Floating Space Robot based on Adaptive Neural Network Wang Cao; Lin Senhai; Ye Xiaoping; Jiang Jie; Zhang Wenhui
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i1.4588

Abstract

Trajectory tracking control problems of the free-floating space robot are considered by the paper, back-stepping control method based on adaptive neural network is put forward. The complex system is decomposed into several simple sub-systems. The control laws are designed by derived, so that closed-loop stability can be obtained by each subsystem; Because of the influence of interference and the measurement level limitation, accurate mathematical model is difficult to be obtained. Neural network controller of good nonlinear approximation ability is designed to compensate the uncertainty of system model. Adaptive learning laws are designed to ensure that weights can be adjusted online real-time. The system uniformly ultimately bounded (UUB) is proved based on the Lyapunov theory. Simulation experiments show that the control method can fast track the desired trajectory, and has a good application value for space robotic manipulators with uncertainty.
A Dynamic Programming Approach to Energy-Efficient Scheduling on Multi-FPGA based Partial Runtime Reconfigurable Systems Chao Jing; Qi Song
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i1.3878

Abstract

This paper has been studied an important issue of energy-efficient scheduling on multi-FPGA systems. The main challenges are integral allocation, reconfiguration overhead and exclusiveness and energy minimization with deadline constraint. To tackle these challenges, based on the theory of dynamic programming, we have designed and implemented an energy-efficient scheduling on multi-FPGA systems. Differently, we have presented a MLPF algorithm for task placement on FPGAs. Finally, the experimental results have demonstrated that the proposed algorithm can successfully accommodate all tasks without violation of the deadline constraint. Additionally, it gains higher energy reduction 13.3% and 26.3% than that of Particle Swarm Optimization and fully balanced algorithm, respectively.
Measurement Straight Leg Raise for Low Back Pain Based Grayscale Depth Tavipia Rumambi; Hustinawaty Hustinawaty; Sarifuddin Madenda; Eri Prasetyo Wibowo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i1.4291

Abstract

Spinal disorders are the most frequent cause of pain and lower part of the spine, which is often called Low Back Pain.Straight Leg Raise Test  can provide important information to detect the cause of LBP. Straight Leg Raise test conducted by physican with a goniometer required accurately reading angle when your feet up. But this can be overcome with Kinect can detect motion and displays images and depth data. Methodological includes image acquisition method using RGB and Grayscale depth, skeleton tracking, feature extraction detection Straight Leg Raise . The proposed algorithm describes a method for estimating the data triangulation angle Straight Leg Raise by Kinect. Results measurement if   the positive Low Back Pain below 60 degrees there is a tendency to suffer from one of the causes of Low Back Pain. The results can be stored in the database as medical history and used to monitor the progress of therapy
Reliability Evaluation of Low-voltage Switchgear Based on Maximum Entropy Principle Zhang Zhigang; Wang Jingqin; Wang Li; Wang Meng
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i1.4255

Abstract

In this paper, based on the definition of two-parameter joint entropy and the maximum entropy principle, a method was proposed to determine the prior distribution by using the maximum entropy method in the reliability evaluation of low-voltage switchgear. The maximum entropy method takes kinds of priori information as different constraints. The optimal prior distribution was selected by maximizing entropy under these constraints, which not only contains the known prior information but also tries to avoid the introduction of other assumption information. Based on non-parametric bootstrap method, the hyper-parameters of prior distribution is obtained by two-order moment of prior information. Finally, with the bootstrap method, the prior distribution robustness and the posterior robustness were analyzed, and the posterior mean time between failures for the low-voltage switchgear was estimated.
A Robot Collision Avoidance Method Using Kinect and Global Vision Haibin Wu; Jianfeng Huang; Xiaoning Yang; Jinhua Ye; Sumei He
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i1.3566

Abstract

This paper introduces a robot collision avoidance method using Kinect and global vision to improve the industrial robot’s security. Global vision is installed above the robot, and a combination of the background-difference method and the Otsu algorithm are used. Human skeleton detection is then introduced to detect the location information of the human body. The collided objects are classified into nonhuman and human obstacle which is further categorized into the human head and non-head areas such as the arm. The Kalman filter is used to predict the human gesture. The human joints danger index is used to evaluate the risk level of the human on the basis of human body joints and robot’s motion information. Finally, a motion control strategy is adopted in view of obstacle categories and the human joint danger index. Results show that the proposed method can effectively improve robot’s security in real time.
Layout Optimization of Microsatellite Components Using Genetic Algorithm Mohammad Mukhayadi; Irman Hermadi; Soewarto Hardhienata
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 15, No 1: March 2017
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v15i1.3872

Abstract

The placement of satellite components usually belongs to non-deterministic polynomial-time hard (NP-hard) problems that in terms of computational complexity is very difficult to solve. This problem is normally known as layout optimization problem (LOP). In this study the layout of microsatellite components has to meet the requirements set by mission payloads, launcher and spacecraft attitude control. The novel scheme is to find the various possibilities of optimal layout using genetic algorithms combined with order-based positioning technique (OPT). Each component has a given index and then placed in a container based on specific order of placements in accordance with a bottom-left (BL) algorithm that is already established. The placement order is generated by the genetic algorithm which explore various possibilities to obtain a sequence that brings the best solution.

Page 3 of 7 | Total Record : 64

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