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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 47 Documents
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Search results for , issue "Vol 14, No 1: March 2016" : 47 Documents clear
Research on Particle Filter Based on Neural Network for Receiver Autonomous Integrity Monitoring Ershen Wang; Qing Zhang; Tao Pang; Qu Pingping; Xingkai Li
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.2359

Abstract

This paper is under in-depth investigation due to suspicion of possible plagiarism on a high similarity index.According to the measurement noise feature of GPS receiver and the degeneracy phenomenon of particle filter (PF), in order to alleviate the sample impoverishment problem for PF, GPS receiver autonomous integrity monitoring (RAIM) algorithm based on PF algorithm combining neural network was proposed, which was used to improve the importance state adjustment of particle filter algorithm. The PF algorithm based on neural network is analized. And the test statistic of satellite fault detection is set up. The satellite fault detection is undertaken by checking the cumulative log-likelihood ratio (LLR) of system state of GPS receiver.The proposed algorithm was Validated by the measured real raw data from GPS receiver, which are deliberately contaminated with the bias fault and ramp fault, the simulation results demonstrate that the proposed algorithm can accurately estimate the state of GPS receiver in the case of non-Gaussian measurement noise, effectively detect and isolate fault satellite by establishing log-likelihood ratio statistic for consistency test and improve the accuracy of detection performance.
Co-simulation and Experiment Research on a Novel Erection Mechanism FENG Jiangtao; HUANG Xianxiang; GAO Qinhe; GUO Xiaosong; YAO Xiaoguang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.2538

Abstract

The erection mechanism with movable back hinged bearing is a novel erection mechanism and the form of its moving process is complicated. The novel erection mechanism needs to be extensively tested to prove its value and to ensure it works properly. Kinetic analysis was accomplished and mathematical model of the hydraulic system was acquired. Fuzzy adaptive PID control was adopted for the erection mechanism taking advantage of fuzzy control and PID control. The novel erection mechanism was validated by virtual prototype technology realized by co-simulation method. The mechanical, hydraulic and control models were respectively established in ADAMS, AMESim and Simulink. Experiment was completed on a platform. The results of simulation and experiment indicate that the novel erection mechanism can move based on designed scheme and the control effect of fuzzy adaptive PID control is excellent. The novel erection mechanism has great practical value.
Image Restoration Algorithm Based on Artificial Fish Swarm Micro Decomposition of Unknown Priori Pixel Dan Sui; Fang He
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.2739

Abstract

In this paper, we put forward a new method to holographic reconstruct image that prior information, module matching and edge structure information is unknown. The proposed image holographic restoration algorithm combines artificial fish swarm micro decomposition and brightness compensation. The traditional method uses subspace feature information of multidimensional search method, it is failed to achieve the fine structure information of image texture template matching and the effect is not well. Therefore, it is difficult to holographic reconstruct the unknown pixels. This weakness obstructs the application of image restoration to many fields. Therefore, we builds a structure texture conduction model for the priority determination of the block that to be repaired, then we use subspace feature information multidimensional search method to the confidence updates of unknown pixel. In order to maintain the continuity of damaged region in image, the artificial fish swarm algorithm decomposition model is combined with the image brightness compensation strategy of edge feature. The simulation result shows that it has a good visual effect in image restoration of a priori unknown pixel, recovery time and computation costs are less, the stability and convergence performance is improved.
R-L-MS-L Filter Function for CT Image Reconstruction Huiling Hou; Mingquan Wang; Xiaopeng Wang
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.1831

Abstract

In X-ray computer tomography (CT), convolution back projection is a fundamental algorithm for CT image reconstruction. As filtering plays an important part in convolution back projection, the choice of filter has a direct impact upon the quality of reconstructed images. Aim at improving reconstructed image quality, a new mixed filter based on the idea of “first weighted average then linear mixing” is designed in this article, denoted by R-L-MS-L. Here, R-L filter is relied on to guarantee the spatial resolution of reconstructed image and S-L filter is processed via 3-point weighted averaging to improve the density resolution, thus enhancing the overall reconstruction quality. Gaussian noise of different coefficients is added to the projection data to contrast the noise performance of the new and traditional mixed filters. The simulation and experiment results show that the new filter is better in anti-noise performance and produces reconstructed images with notably improved quality.
Research on Load Balancing in C-RAN with Femtocells Zhanjun Liu; Xia Peng; Yujing He; Qichao Ma
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.2358

Abstract

The traditional load balancing optimization scheme cannot guarantee the user’s QoS in the C-RAN wireless communication networks when all the neighboring macrocells are under the situation of overload. In order to resolve this problem, we implement the femtocell to the macrocell network, which considers the advantages of femtocell, i.e., small coverage, low cost and better signal quality. Therefore, in this paper, the joint load balancing mechanism is proposed to achieve the joint optimization of femtocell and macrocell network by allowing the users of overloaded macrocell to handover to the femtocell. Finally, the simulation results show that the proposed mechanism greatly improves the user satisfaction as well as the resource utilization rate of the femtocell network while decreases the blocking rate and dropping rate.
Determining Process Model Using Time-Based Process Mining and Control-Flow Pattern Riyanarto Sarno; Widyasari Ayu Wibowo; Kartini Kartini; Yutika Amelia; Kelly Rossa
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.3257

Abstract

Determining right model of business process from event log is the purpose of process discovery. However some problems i.e the inability to discover OR, noise and event log incompleteness are emmerged while determining right model of business process. First, OR relation is often discovered as AND relation. Second, noise problem is occured when there are truncated and low frequency traces in event log. Thus control-flow pattern is used to solve issues of same noise relation frequency hence it discovers relation based on transaction function of activity. Consequently, it can refine non noise relation in business process model. Third, incompleteness leads to incorrect discovery of parallel process model; therefore we used Timed-based Process Mining which utilized non-linear dependence to solve the incompleteness. Finally this paper proposed combination of Timed-based Process Mining and control-flow pattern to discover OR and handle same frequency noise and incompleteness. From the experiment in section 3, this proposed method manages to get right process model from event log.
An Autonomic Optimization Model of Multi-Layered Dependability for Intelligent Internet of things Zheng Ruijuan; Zhang Mingchuan; Wu Qingtao; Li Ying; Wei Wangyang; Bai Xiuling
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.2745

Abstract

Accompanying with the speeding up of Internet of things (IOT) construction, the dependability problems become the important factors constraining its all-round development. Based on the multi-level and multidimensional properties of IOT dependability elements, with the overall improving of the dependability index of IOT as the ultimate goal, the dependability elements of the local fine-tuning in each layer, this paper researches the change rule of internal dependability elements in perception layer, network layer and business layer, and adopts perception layer as the example, using the method of linear programming to seek the best proportion of all kinds of dependability elements and the optimal values of the elements, trying to construct a feasible autonomic optimization model for dependability elements of IOT system. Firstly, according to the function features and dependability properties of each layer, and change rules between the dependability index and dependability elements in each layer are analyzed. Secondly, based on the dynamic changes (up or down) of dependability elements in internal environment (that is, three layers in IOT), the ratio relations of dependability elements in each layer are dynamically controlled and adjusted to implement the local optimization, improving the overall autonomic configuration and autonomic adjusting ability of IOT system. At last, example analysis results show that the optimization model proposed in this paper can realize the substantial optimization in each layer of IOT.
An optimized method of partial discharge data retrieval technique for phase resolved pattern Eka Putra Waldi; Aulia Aulia; Ariadi Hazmi; Hairul Abral; Syukri Arief; Mohd Hafizi Ahmad
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.2602

Abstract

The measurement of phase resolved partial discharge requires a gigantic memory capacity to store all the waves of the PD test results. This limitation eventually hinders the testing. It is necessary to optimize on the aspect of memory storage capability to reduce the storage requirements. In light of foregoing, the partial discharge data retrieval techniques with sampling rate methods were used to detect the peak of partial discharge as well as the PD constituent representatives. The optimization process was performed by using integration of oscilloscope and LabVIEW software. The partial discharge data recording can be easily confined to the points of the partial discharge occurrence only. As results, the storage points were reduced by taking wave magnitude associated with PD, thereby resulting in more representative data. Therefore, this optimized method was able to reduce the file size of the test results up to 97 percent of PD original size thereby decreasing the usage of hard disk storage.
Improving the Channel Utilization of Basic Safety Message in VANETs with Superposition Coded Modulation Xiang Li; Chao Wang; Fuqiang Liu; Xiaobo Yin
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.1355

Abstract

In this paper, we propose a broadcast scheme to effectively utilize the scarce and shared wireless medium for vehicular ad-hoc networks (VANETs). By using superposition coded modulation (SCM), information elements that comprise basic safety messages (BSMs) were delivered with different service qualities determined by real-time traffic situations. The optimal power allocation strategy and achievable performance gain of the proposed method were first theoretically analyzed. To apply the proposed method into practice, the hierarchical quadrature amplitude modulation technology was then employed to implement the proposed SCM-based broadcast scheme for VANETs. To evaluate the performance of the proposed method in real-time traffic environments, a joint traffic-communication simulation was further conducted. Results agree that the proposed method extends the coverage of the BSM broadcast while maintaining an acceptable communication reliability to meet the requirement of driving safety.
Detection and Prediction of Peatland Cover Changes Using Support Vector Machine and Markov Chain Model Ulfa Khaira; Imas Sukaesih Sitanggang; Lailan Syaufina
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 14, No 1: March 2016
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v14i1.2400

Abstract

Detection and prediction of peatland cover changes needs to be done in the rapid rate of deforestation in Indonesia. This work applied Support Vector Machine (SVM) and Markov Chain Model on multitemporal satellite data. The study area is located in the Rokan Hilir district, Riau Province. SVM classification technique used to extract information from satellite data for the years 2000, 2004, 2006, 2009 and 2013. The Markov Chain Model was used to predict future peatland cover. The SVM classification result showed that the Kappa accuracy of peatland cover classification is more than 0.92. The non vegetation areas increased to 307% and the sparse vegetation areas increased to 22% between 2000 and 2013, while dense vegetation areas decreased to 61%. Prediction of future land cover by the Markov Chain Model showed that the use of multitemporal satellite data with 3 years interval provides accurate result for predicting peatland cover changes.

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