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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 51 Documents
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Search results for , issue "Vol 14, No 3: September 2016" : 51 Documents clear
GPU CUDA accelerated Image Inpainting using Fourth Order PDE equation Edwin Prananta; Pranowo Pranowo; Djoko Budianto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3412

Abstract

This paper describes the technique to accelerate inpainting process using fourth order PDE equation using GPU CUDA. Inpainting is the process of filling in missing parts of damaged images based on information gleaned from surrounding areas. It uses the GPU computation advantage to process PDE equation into parallel process. Fourth order PDE will be solved using parallel computation in GPU. This method can speed up the computation time up to 36x using NVDIA GEFORCE GTX 670.
Optimization of Hydrogen-fueled Engine Ignition Timing Based on L-M Neural Network Algorithm Lijun Wang; Yuan Liu; Yahui Liu; Wei Wang; Yanan Zhao; Zhenzhong Yang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.2756

Abstract

In view of the improvement measures of the optimization control algorithm for the ignition system of the hydrogen-fueled engine, the L-M neural network algorithm, Powell neural network algorithm and the traditional BP neural network algorithm are used to optimize the ignition system. The results showed that L-M algorithm not only can accurately predict the hydrogen-fueled engine ignition timing, but also has high precision, high convergence speed, a simple model and other outstanding advantages in the training process, which can greatly reduce the workload of human engine bench tests. Only a small amount of engine bench test is carried out, and the obtained sample data can be used to predict the ignition timing under the whole working conditions. The mean square error of the optimization results based on L-M algorithm arrives at 0.0028 after 100 times of calculation, the maximum value of absolute error arrives at 0.2454, and the minimum value of absolute error arrives at 0.00426.
A Comprehensive Test Approach on High-Power Low-Noise Intermodulation Distortion Lei Wang; Jingyi Zhang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3715

Abstract

With the shortage of wireless communication bandwidth resource, the radio interferences occur so frequently. Currently, effcient frequency allocation algorithm designing and Intermoduation Distortion (IMD) suppression are two means to rationally improve the bandwidth resource. Therefore, four comprehensive approaches named stimulus isolation, channel crosstalk isolation; spectrum slight offset and Auto Level Control (ALC) leak control are proposed respectively to avoid the restriction of the periphery system’s noise and dynamic range of measurement instruments. Moreover, the high power and low noise detection approach, the auxiliary components amelioration and the measurement system improvement are analyzed. Finally, utilizing Silicon-On-Insulator (SOI) Radio Frequency (RF) switch as the carrier to do the experiment based on Advantest 93K tester. Experiment results show that the comprehensive optimized approaches can keep the whole system to less than -150 dBm (nearly 170 dBc) low noise range under the large signal cases. The actual intermodulation distortion signal could be rejected and sampled in precise accuracy which is nearly 20% improved. What’s more, the approaches are also beneficial to the expansion of the industrial multi-site test.
A Comparison of Retweet Prediction Approaches: The Superiority of Random Forest Learning Method Hendra Bunyamin; Tomas Tunys
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3150

Abstract

We consider the following retweet prediction task: given a tweet, predict whether it will be retweeted. In the past, a wide range of learning methods and features has been proposed for this task. We provide a systematic comparison of the performance of these learning methods and features in terms of prediction accuracy and feature importance. Specifically, from each previously published approach we take the best performing features and group these into two sets: user features and tweet features. In addition, we contrast five learning methods, both linear and non-linear. On top of that, we examine the added value of a previously proposed time-sensitive modeling approach. To the authors’ knowledge this is the first attempt to collect best performing features and contrast linear and non-linear learning methods. We perform our comparisons on a single dataset and find that user features such as the number of times a user is listed, number of followers, and average number of tweets published per day most strongly contribute to prediction accuracy across selected learning methods. We also find that a random forest-based learning, which has not been employed in previous studies, achieves the highest performance among the learning methods we consider. We also find that on top of properly tuned learning methods the benefits of time-sensitive modeling are very limited.
Internet Protocol Based Satellite On-Board System Emir Husni; Nazmi Febrian; Angga Putra
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3512

Abstract

The reliability of satellite data communication can be enhanced by designing two subsystems involving data communication among subsystem and data communication between satellie and Ground Station (GS). In this paper, Error Control Coding (ECC) is applied in satellite data communication with Automatic Repeat Request (ARQ) method. Further, bit error checking uses the calculation of 15 bit Cyclic Redundancy Check (CRC) Controller Area Network (CAN) standard. The calculation of CRC is attached in CAN frame over IP communication protocol between primary OBC and secondary OBC. OBC is designed by implementing Triple Modular Redundant system on a Linux-based operating system. The CAN frame over IP simulation with manual input is found to correct all corrupted data. When the simulation uses NetEM, the system corrects 100 % data with 0-10 % value of corruption with maximum time transfer of 84.472 seconds. ION DTN is also found to correct all corrupted data with values from 0 to 2 % and maximum delay at an altitude of 50,000 kilometer orbit using NetEm for TMTC mission. The testing results show that the system will keep carrying out its mission as long as a fault does not occur on all three OBC at the same time.
Prediction Model of Smelting Endpoint of Fuming Furnace Based on Grey Neural Network Song Qiang; WU Yaochun
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3713

Abstract

Since grey theory and neural network could improve prediction precision, the technology of combination prediction was proposed in this study. Then the algorithm was simulated by Matlab using practical data of a fuming furnace. The results reveal that the smelting endpoint of fuming furnace could be accurately predicted with this model by referring to small sample and information. Therefore, GNN model is effective with the advantages of high precision, fewer samples required and simple calculation.
Quasi-Newton Method for Absolute Value Equation Based on Upper Uniform Smoothing Approximation Longquan Yong; Shouheng Tuo
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3785

Abstract

In this paper, an upper uniform smooth approximation function of absolute value function is proposed, and some properties of uniform smooth approximation function are studied. Then, absolute value equation (AVE), Ax - |x| = b, where A is a square matrix whose singular values exceed one, is transformed into smooth optimization problem by using the upper uniform smooth approximation function, and solved by quasi-Newton method. Numerical results in solving given AVE problems demonstrated that our algorithm is valid and superior to lower uniform smooth approximation function.
Flow Fair Sampling Based on Multistage Bloom Filters Liu Yuanzhen; Huang Shurong; Liu Jianzhao
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3648

Abstract

Network traffic distribution is heavy-tailed. Most of network flows are short and carry very few packets, and the number of large flows is small. Traditional random sampling tends to sample more large flows than short ones. However, many applications depend on per-flow traffic other than just large flows. A flow fair sampling based on multistage Bloom filters is proposed. The total measurement interval is divided into n child time intervals. In each child time interval, employ multistage Bloom filters to query the incoming packet’s flow whether exists in flow information table or not, if exists, sample the packet with static sampling rate which is inversely proportional to the estimation flow traffic up to the previous time interval. If it is a new flow’s first packet, create its flow information and insert it into the multistage Bloom filters. The results show that the proposed algorithm is accurate especially for short flows and easy to extend.
Compressive Sensing Algorithm for Data Compression on Weather Monitoring System Rika Sustika; Bambang Sugiarto
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3021

Abstract

Compressive sensing (CS) is new data acquisition algorithm that can be used for compression. CS theory certifies that signals can be recovered from far fewer samples or measurements than Nyquist rate. On this paper, the compressive sensing technique is applied for data compression on our weather monitoring system. On this weather monitoring system, compression using compressive sensing with fewer samples or measurements means minimizing sensing and overall energy cost. Our focus on this paper lies in the selection of matrix for representation basis under which the weather data are sparsely represented. We evaluated three types of representation basis using data from real measurement. By comparing performance of data recovery, result show that DCT (Discrete Cosine Transform) is the best performance on sparsifying weather data
Scalable Nodes Deployment Algorithm for the Monitoring of Underwater Pipeline Muhammad Zahid Abbas; Kamalrulnizam Abu Bakar; Muhammad Ayaz Arshad; Muhammad Tayyab; Mohammad Hafiz Mohamed
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 3: September 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i3.3464

Abstract

Underwater Wireless Linear Sensor Networks (UW-LSNs) possess unique features as compared to the terrestrial sensor networks for pipeline monitoring. Other than long propagation delays for long range underwater pipelines and high error probability, homogeneous node deployment also makes it harder to detect and locate the pipeline leakage efficiently. Determining the exact leakage position with minimum delay stays a major issue where pipelines length is extremely long and expensive to deploy many underwater sensors. In order to tackle the problem of large scale pipeline monitoring and unreliable underwater link quality, many algorithms have been proposed and even some of them provided good solutions for these issues but the scalable nodes deployments still need focus and prime attention. In order to handle the problem of nodes deployment, we therefore propose a dynamic nodes deployment algorithm where every node in the network is assigned location in a quick and efficient way without needing any localization scheme. It provides an option to handle the heterogeneous types of nodes, distribute topology and mechanism in which new nodes are easily added to the network without affecting the existing network performance. The proposed distributed topology algorithm divides the pipeline length into segments and sub-segments in order to manage the higher delay issue. Normally nodes are randomly deployed for the long range underwater pipeline inspection yet it requires some proper dynamic nodes deployment algorithm assigning unique position to each node

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