TELKOMNIKA (Telecommunication Computing Electronics and Control)
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)
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Multi Facial Blurring using Improved Henon Map
Saparudin Saparudin;
Ghazali Sulong;
Muhammed Ahmed Saleh
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/telkomnika.v12i4.359
Generally, full encryption is applied on the entire image to obscure the faces. However, it suffers in overhead, speed and time. Alternatively, selective encryption can be used to encrypt only the sensitive part of the image such as human faces. This paper proposes a new encryption algorithm using enhanced Henon chaotic map to conceal the faces. This technique involves three steps: face detection, encryption and decryption. Experiments have been performed to evaluate security such as histogram, sensitivity and statistical analysis, and results reveal that the proposed method provides high security with entropy and correlation close to ideal values.
Large Crowd Count Based on Improved SURF Algorithm
Haining Zhang;
Huanbo Gao
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/telkomnika.v12i4.362
This paper uses an analysis of Speeded up Robust Feature (SURF), based on the method of Linear Interpolation for camera distortion calibration, for high-density crowd counting. The eigenvalues are built on the Gray Level Co-occurrence Matrix (GLCM) features and the SURF features. Though the method of linear interpolation, weight values are interpolated to reduce the error, which is caused by camera distortion calibration. The optimized crowd’s feature vector can be got then. Through the method of support vector regression, the crowd’s number can be forecast by training model. The experiment result shows that the method of this paper has a higher accuracy than the previous methods.
Intelligent Interface for Knowledge Based System
Nyoman Bogi Aditya Karna;
Iping Supriana;
Ulfa Maulidevi
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/telkomnika.v12i4.413
Every Knowledge Based System has their own knowledge formalism depends on the problem to be solved, goal to be achieved, and proposed solution. This means every knowledge contained in the system will differ from one system to another. This was also meant that this knowledge cannot be used by other system, which in return makes every system must start with a learning phase from the start. One of the solutions to overcome this problem is by providing a unified model that can accept all type of knowledge which guarantees automatic interaction between Knowledge Based System. Interaction in this paper is defined as knowledge sharing, integration, and transfer from one system to another. This research provides the model and conducts the test on interaction capability. This research contributes for accelerating a new Knowledge Based System establishment because it does not need a knowledge initialization.
Pre-Timed and Coordinated Traffic Controller Systems Based on AVR Microcontroller
Freddy Kurniawan;
Denny Dermawan;
Okto Dinaryanto;
Mardiana Irawati
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/telkomnika.v12i4.497
The major weaknesses of traffic controllers in Indonesia are unable to accommodate the variety of traffic volume and unable to be coordinated. To solve the problem, a pre-timed and coordinated traffic controller system is build. The system consists of a master and a local controller. Each controller has a database containing signal-timing plans that would be allocated to manage vehicle flows. To synchronize the signal-timing, the master controller sends the synchronization data to the local controller wirelessly and the local controller shifts the end of a cycle by adding or subtracting the green interval of any phases. The transition time for synchronization only takes one to several cycles. The algorithm for controlling the traffic including coordination can be done by an AVR microcontroller. Memory usage of the microcontroller is lower than 10% meanwhile the CPU utilization is no more than 1%, thus the systems could be widely developed.
Feature Selection Method Based on Improved Document Frequency
Wei Zheng;
Guohe Feng
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/telkomnika.v12i4.536
Feature selection is an important part of the process of text classification, there is a direct impact on the quality of feature selection because of the evaluation function. Document frequency (DF) is one of several commonly methods used feature selection, its shortcomings is the lack of theoretical basis on function construction, it will tend to select high-frequency words in selecting. To solve the problem, we put forward a improved algorithm named DFM combined with class distribution of characteristics and realize the algorithm with programming, DFM were compared with some feature selection method commonly used with experimental using support vector machine, as text classification .The results show that, when feature selection, the DFM methods performance is stable at work and is better than other methods in classification results.
Dynamic DEMATEL Group Decision Approach Based on Intuitionistic Fuzzy Number
Hui Xie;
Wanchun Duan;
Yonghe Sun;
Yuanwei Du
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/telkomnika.v12i4.787
With respect to the problems of aggregation about group experts’ information and dynamic decision in DEMATEL(decision making trial and evaluation laboratory), a dynamic DEMATEL group expert decision-making method on intuitionistic fuzzy number(IFN) is presented. Firstly using IFN instead of original point estimates to reflect the experts’ preference, the group experts’ information are integrated horizontally at each period. Then the aggregation information at different periods are aggregated vertically again by dynamic intuitionistic fuzzy weighted averaging (DIFWA) operator so as to obtain the dynamic intuitionistic fuzzy DEMATEL total relation matrix. Thirdly, through the analysis of center and reason degree, the positions of the various factors in the system are clear and definite, and the inner structure of system has been revealed. Finally, the feasibility and practicability of the proposed method is shown through an illustrative example of a process of course selection in a school.
Cost Forecasting Model of Transmission Project based on the PSO-BP Method
Yan Lu;
Dongxiao Niu;
Bingjie Li;
Min Yu
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/telkomnika.v12i4.439
In order to solve being sensitive to the initial weights, slow convergence, being easy to fall into local minimum and other problems of the BP neural network, this paper introduces the Particle Swarm Optimization (PSO) algorithm into the Artificial Neural Network training, and construct a BP neural network model optimized by the particle swarm optimization. This method can speed up the convergence and improve the prediction accuracy. Through the analysis of the main factors on the cost of transmission line project, dig out the path and lead factors, topography and meteorological factors, the tower and the tower base materials and other factors. Use the PSO-BP model for the cost forecasting of transmission line project based on historical project data. The result shows that the method can predict the cost effectively. Compared with the traditional BP neural network, the method can predict with higher accuracy, and can be generalized and applied in cost forecasting of actual projects.
Spectrum Comparative Study of Commutation Failure and Short-Circuit Fault in UHVDC Transmission System
Shi-long Chen;
Jun-xiang Rong;
Gui-hong Bi;
Xing-wang Li;
Rui-rui Cao
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/telkomnika.v12i4.300
When commutation failure occurs in UHVDC transmission system, the transient process of DC voltage and current are similar to grounding short-circuit fault. In order to differentiate them effectively, the paper introduces mathematical morphology methods to analysis the spectrum of transient current. Base on Yunnan-Guangzhou kV UHVDC transmission system, the paper simulates the commutation failure and DC line short-circuit fault under different fault conditions in PSCAD/EMTDC. By modified morphology filter, the transient signal of DC () is decomposed into six scales, and morphological characteristics of aerial mode component of is analyzed under different scales. The simulation results show that when DC line short-circuit faults occurs, wherever in the rectifier side, in the DC transmission line midpoint or in the inverter side, the aerial mode component of have more high frequency weight in ~ and decays gradually; When commutation failures, which are caused by the inverter side AC system single-phase grounding fault, phase to phase fault, three phase grounding fault or the inverter side transformer ratio increased, the aerial mode component of have less frequency weight in.
Trusted Node-Based Algorithm to Secure Home Agent NATed IPv4 Network from IPv6 Routing Header Attacks
Mohamed Shenify
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/telkomnika.v12i4.540
Providing a secure mobile communication in mixed IPv4/IPv6 networks is a challenging task. One of the most critical vulnerabilities associated with the IPv6 protocol is the routing header that potentially may be exploited by attackers to bypass the security. This paper discusses an algorithm to secure home agent network from the routing header vulnerability, where the home agent network uses IPv4 Network Address Translation (NAT) router. The algorithm also takes into account multi-hops destination in the routing header. Verification was done through implementation of the algorithm at the Home Agent modul in a testbed network. The experimental results show that the proposed algorithm provides secure communication between Correspondent nodes and Mobile Nodes that moved into the NATed network without causing a significance filtering delay.
Image Deblurring via an Adaptive Dictionary Learning Strategy
Lei Li;
Ruiting Zhang;
Jiangmin Kan;
Wenbin Li
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 12, No 4: December 2014
Publisher : Universitas Ahmad Dahlan
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DOI: 10.12928/telkomnika.v12i4.532
Recently, sparse representation has been applied to image deblurring. The dictionary is the fundamental part of it and the proper selection of dictionary is very important to achieve super performance. The global learned dictionary might achieve inferior performances since it could not mine the specific information such as the texture and edge which is contained in the blurred image. However, it is a computational burden to train a new dictionary for image deblurring which requires the whole image (or most parts) as input; training the dictionary on only a few patches would result in over-fitting. To address the problem, we instead propose an online adaption strategy to transfer the global learned dictionary to a specific image. In our deblurring algorithm, the sparse coefficients, latent image, blur kernel and the dictionary are updated alternatively. And in every step, the global learned dictionary is updated in an online form via sampling only a few training patches from the target noisy image. Since our adaptive dictionary exploits the specific information, our deblurring algorithm shows superior performance over other state-of-the-art algorithms.