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25,002 Article Results

Image Denoising Based on Artificial Bee Colony and BP Neural Network

10.12928/telkomnika.v13i2.1433
Junping; Henan Vocational and Technical Institute Wang , Dapeng; Henan Vocational and Technical Institute Zhang
Image is often subject to noise pollution during the process of collection, acquisition and transmission, noise is a major factor affecting the image quality, which has greatly impeded people from extracting information from the image. The purpose of image denoising is to restore the original image without noise from the noise image, and at the same time maintain the detailed information of the image as much as possible. This paper, by combining artificial bee colony algorithm and BP neural network, proposes the image denoising method based on artificial bee colony and BP neural network (ABC-BPNN), ABC-BPNN adopts the “double circulation” structure during the training process, after specifying the expected convergence speed and precision, it can adjust the rules according to the structure, automatically adjusts the number of neurons, while the weight of the neurons and relevant parameters are determined through bee colony optimization. The simulation result shows that the algorithm proposed in this paper can maintain the image edges and other important features while removing noise, so as to obtain better denoising effect.
Volume: 13
Issue: 2
Page: 614-623
Publish at: 2015-06-01

Guaranteed Cost Control for Uncertain Neutral Systems with a Minimal Order Observer

10.12928/telkomnika.v13i2.875
Erwin; School of Electrical Engineering Susanto , Junartho; School of Electrical Engineering, Telkom University Halomoan , Mitsuaki; Department of Mechanical Systems Engineering, Kumamoto University Ishitobi
This paper presents a design scheme of a minimal order observer-based guaranteed cost controller for uncertain neutral systems, in which some state variables can not be measured. The uncertainties are assumed to be norm-bounded. The initial state is assumed unknown but their mean and covariance are assumed known. A sufficient condition for robust stability analysis and robust stabilization are derived via linear matrix inequalities (LMIs). To show the advantage of the proposed method, a numerical example is given.
Volume: 13
Issue: 2
Page: 518-527
Publish at: 2015-06-01

Unambiguous Sine-phased BOC(kn,n) Signal Acquisition Based on Combined Correlation Functions

10.12928/telkomnika.v13i2.1469
Deng; Beijing University of Posts and Telecommunications Zhongliang , Xi; Beijing University of Posts and Telecommunications Yue , Yin; Beijing University of Posts and Telecommunications Lu
Galileo and GPS have been developing their new signals in recent years. Multiplexed Binary Offset Carrier (MBOC) is the final implementation of Galileo E1 and GPS L1C, which is the multiplexing of BOC(1,1) and BOC(6,1). Therefore, it is helpful to satisfy the demand that the new signals must be compatible with GPS BPSK signal. BOC(kn,n) modulation will provide better track performance and higher positioning accuracy. However, the main drawback of the BOC modulated signal is that its autocorrelation has multiple side peaks around the main peak. This paper will focus on a family of signals: sine-phased BOC(kn,n). We are trying to explore a new method to cancel the side peaks of BOC(kn,n) autocorrelation, making use of two kinds of correlation functions. One is the correlation of the incoming signal and the sine-phased BOC(kn,n) modulated spreading code(PRN code multiplied by subcarrier), and the other is the correlation of the incoming signal and the PRN code only. Two kinds of correlation function are separated into several sub-correlations. Sub-correlations have less side peaks which are in different code delays. Corresponding parts of two sub-correlations will be combined to cancel the side peaks separately, and finally the new function without side peaks will be acquired after several correlations added together. Simulation results will be given. It is shown that the proposed method is contributed to the side peaks cancellation for unambiguous sine-phased BOC (kn, n) signal acquisition.
Volume: 13
Issue: 2
Page: 502-509
Publish at: 2015-06-01

Comparison of Data Partitioning Schema of Parallel Pairwise Alignment on Shared Memory System

10.12928/telkomnika.v13i2.1415
Auriza Rahmad; Institut Pertanian Bogor Akbar , Heru; Institut Pertanian Bogor Sukoco , Wisnu Ananta; Institut Pertanian Bogor Kusuma
The pairwise alignment (PA) algorithm is widely used in bioinformatics to analyze biological sequence. With the advance of sequencer technology, a massive amount of DNA fragments are sequenced much quicker and cheaper. The alignment algorithm needs to be parallelized to be able to align them in a shorter time. Many previous researches have parallelize PA algorithm using various data partitioning schema, but it is unclear which one is the best. The data partitioning schema is important for parallel PA performance, because this algorithm use dynamic programming technique that needs intense inter-thread communication. In this paper, we compared four partitioning schemas to find the best performing one on shared memory system. Those schemas are: blocked columnwise, rowwise, antidiagonal, and blocked columnwise with manual scheduling and loop unrolling. The last schema gave the best performance of 89% efficiency on 4 threads. This result provided fine-grain parallelism that can be used further to develop parallel multiple sequence alignment (MSA).
Volume: 13
Issue: 2
Page: 694-702
Publish at: 2015-06-01

A Study on TPMS Pre-warning Threshold Algorithm Based on Multi-sensor Data Fusion

https://ijeecs.iaescore.com/index.php/IJEECS/article/view/1501
Wang Gang , Zhao Jiyin
In order to improve the precision of the tire pressure monitoring system, the Bayes method is applied to establish its mathematical model of multi-sensor information fusion. The temperature and pressure in the tire, which are the complementary information, are integrated in the model through analyzing the mechanism of tire burst generated by temperature and pressure. Through the temperature compensation of tire burst pressure threshold value, the false alarm and false negative are avoided to the hilt. The experimental results show that compared with the traditional TPMS, the accuracy of the measuring results of this model is improved and thus the system’s monitoring ability is improved so that the traffic safety is guaranteed. DOI: http://dx.doi.org/10.11591/telkomnika.v14i3.7895 
Volume: 14
Issue: 3
Page: 493-499
Publish at: 2015-06-01

Goal-seeking Behavior-based Mobile Robot Using Particle Swarm Fuzzy Controller

10.12928/telkomnika.v13i2.1111
Andi; Universitas Mercu Buana Adriansyah , Yudhi; Universitas Mercu Buana Gunardi , Badaruddin; Universitas Mercu Buana Badaruddin , Eko; Universitas Mercu Buana Ihsanto
Behavior-based control architecture has successfully demonstrated their competence in mobile robot development. Fuzzy logic system characteristics are suitable to address the behavior design problems. However, there are difficulties encountered when setting fuzzy parameters manually. Therefore, most of the works in the field generate certain interest for the study of fuzzy systems with added learning capabilities. This paper presents the development of fuzzy behavior-based control architecture using Particle Swarm Optimization (PSO). A goal-seeking behaviors based on Particle Swarm Fuzzy Controller (PSFC) are developed using the modified PSO with two stages of the PSFC process. Several simulations and experiments with MagellanPro mobile robot have been performed to analyze the performance of the algorithm.  The promising results have proved that the proposed control architecture for mobile robot has better capability to accomplish useful task in real office-like environment.
Volume: 13
Issue: 2
Page: 528-538
Publish at: 2015-06-01

Adaptive Energy-aware Cluster Based Routing Protocol for Mobile Ad Hoc Networks

10.12928/telkomnika.v13i2.1438
Fatemeh; Payamnoor University of Sari Hakimifar , Seyed-Amin; Ferdowsi University of Mashhad Hosseini-Seno , Mohammad; Islamic Azad University of Mashhad Hossein Moattar , Thair; Al Baha University Al-Dala’in , Rahmat; Al Baha University Budiarto
Due to the downside characteristics of Mobile Ad hoc Networks (MANETs) such as dynamic topology and energy consumption and control overhead, network clustering is one of the promising solutions. Cluster Based Routing Protocol (CBRP) is a robust and scalable routing protocol for MANETs. Clustering formation algorithm used in CBRP is a variation of simple lowest-ID algorithm in which the node with a lowest ID among its neighbors is elected as the Cluster head. Neglecting mobility and energy for selecting cluster head is one of the weakness points of the algorithm. In order to increase stability of the network and to prevent re-clustering an adaptive energy-aware Cluster Based Routing Protocol (AECBRP) is proposed. Two algorithms have been introduced in AECBRP as enhancement to the CBRP: improving the cluster formation algorithm by considering relative mobility, residual energy and connectivity degree metrics, and add in an efficient cluster maintenance algorithm based on the aggregate energy metric of cluster head. Using NS-2 we evaluate the rate of cluster-head changes, the normalization routing overhead and the packet delivery ratio. Comparisons denote that the proposed AECBRP has better performances with respect to the original CBRP and Cross-CBRP.
Volume: 13
Issue: 2
Page: 711-721
Publish at: 2015-06-01

Simple Screening for High-Risk Pregnancies in Rural Areas Based on an Expert System

10.12928/telkomnika.v13i2.988
Retno; Jenderal Soedirman University Supriyanti , Ahmad; Jenderal Soedirman University Fariz , Teddy; Jenderal Soedirman University Septiana , Eko; Jenderal Soedirman University Murdyantoro , Yogi; Jenderal Soedirman University Ramadhani , Haris Budi; Jenderal Soedirman University Widodo
The high maternal and infant mortality rates in developing countries, especially Indonesia, are quite alarming. There are many factors that cause high mortality numbers; one of them is the delay in handling cases of high‑risk pregnancies. The main problem faced by developing countries is the lack of health facilities, including medical equipment and human resources. This research aims to develop a simple system that can be used to screen high‑risk pregnancies. This system is based on an expert system. The Analytical Hierarchy Process (AHP) method is used in making decisions about potentially high-risk pregnancy patients. Essentially, the system can be used by anyone, anywhere, to carry out early screening of high‑risk pregnancy patients, so that delays in the treatment of these patients can be resolved, because the symptoms of high‑risk pregnancy are known from the beginning. Results indicate that this system shows promise for further development. 
Volume: 13
Issue: 2
Page: 661-669
Publish at: 2015-06-01

Test Generation Algorithm Based on SVM with compressing Sample Space Methods

10.12928/telkomnika.v13i2.1473
Ting; Chengdu University of Information Technology Long , Jiang; Chengdu University of Information Technology Shiqi , Hang; University of Sichuan Luo
Test generation algorithm based on the SVM (support vector machine) generates test signals derived from the sample space of the output responses of the analog DUT. When the responses of the normal circuits are similar to those of the faulty circuits (i.e., the latter have only small parametric faults), the sample space is mixed and traditional algorithms have difficulty distinguishing the two groups. However, the SVM provides an effective result. The sample space contains redundant data, because successive impulse-response samples may get quite close. The redundancy will waste the needless computational load. So we propose three difference methods to compress the sample space. The compressing sample space methods are Equidistant compressional method, k-nearest neighbors method and maximal difference method. Numerical experiments prove that maximal difference method can ensure the precision of the test generation.
Volume: 13
Issue: 2
Page: 578-586
Publish at: 2015-06-01

Design and Simulation of Small Space Parallel Parking Fuzzy Controller

10.12928/telkomnika.v13i2.1258
Qiulin; Hubei University of Technology Sheng , Jie; Hubei University of Technology Min , Xing; Hubei University of Technology Zhang , Zhengwen; Hubei University of Technology Zhang , Yi; Hubei University of Technology Li , Guangya; Hubei University of Technology Liu
Based on the nonlinearity and time-variation of automatic parking path tracking control system, we use fuzzy control theories and methods to explore the control rules to improve fuzzy controllers and design an automobile steering controller. Then we build the simulation experiment platform of an automobile in Simulink to simulate the reversing settings of parallel parking. This paper adopts the Mamdani control rules; the membership function is the Gauss function. This paper verifies the fuzzy controller's kinematic model and the advantages of fuzzy control rules. Simulation results show that the design of the controller allows the automobile to stop into the parking space smaller than the space obtained by planning path, and automatic parking becomes possible in the parking plot. The control system is characterized by small tracking error, fast response and high reliability.
Volume: 13
Issue: 2
Page: 539-546
Publish at: 2015-06-01

Blind Signal Processing Algorithmsbased based on Recursive Gradient Estimation

10.11591/ijece.v5i3.pp548-561
Namyong Kim , Mingoo Kang
Blind algorithms based on the Euclidean distance (ED) between the output distribution function and a set of Dirac delta functions have a heavy computational burden of  due to some double summation operations for the sample size and symbol points. In this paper, a recursive approach to the estimation of the ED and its gradient is proposed to reduce the computational complexity for efficient implementation of the algorithm. The ED of the algorithm is comprised of information potentials (IPs), and the IPs at the next iteration can be calculated recursively based on the currently obtained IPs. Utilizing the recursively estimated IPs, the next step gradient for the weight update of the algorithm can be estimated recursively with the present gradient. With this recursive approach, the computational complexity of gradient calculation has only . The simulation results show that the proposed gradient estimation method holds significantly reduced computational complexity keeping the same performance as the block processing method
Volume: 5
Issue: 3
Page: 548-561
Publish at: 2015-06-01

Determining Trust Scope Attributes Using Goodness of Fit Test: A Survey

10.12928/telkomnika.v13i2.649
Titin; Institut Teknologi Bandung Pramiyati , Iping; Institiut Teknologi Bandung Supriana , Ayu; Institiut Teknologi Bandung Purwarianti
Indonesian, as one of the countries with high number of internet users has the potential to serve as the place with great information resources. However, these resources must be accompanied by the availability of dependable information. Information trustworthiness can be obtained by assessing the confidence level (trust) of the source of information. This can be determined by using trust scope attributes. Hence, in this study, we intended to establish the trust scope attributes by means of utilizing the ones contained in the User Profile provided by social media; in this case Facebook, Google+, Twitter, and Linkedin. We carried out the research by conducting four stages namely data collection, attributes grouping, attribute selection, and surveys. A survey was then distributed to 257 randomly selected respondents (divided into two clusters: civilians and military officers) to seek for their opinions in terms of what attributes were considered to be crucial in defining the believability of an information source. Chi-square Goodness of fit Test was conducted to compare observed data with data we would expect to obtain. The results of the research suggested that there was similar judgment in terms of dictating source of information trustworthiness chosen by the research participants with the attributes provided by trust scope category. In this research, both civilians and military officer clusters concurrently perceived that educational background was the most dependable attribute.
Volume: 13
Issue: 2
Page: 654-660
Publish at: 2015-06-01

An Image Registration Method Based on Wavelet Transform and Ant Colony Optimization

10.12928/telkomnika.v13i2.1432
Dapeng; Henan Vocational and Technical Institute Zhang , Jiayan; Henan Vocational and Technical Institute Li
Image registration, as one of the basic tasks of image processing, is the process to register two images about the same objective or background which are acquired in different times, different sensors, different perspectives and different shooting conditions. In the image registration, because of the problems that the image information is complicated, they have strong correlation and incompleteness, inaccuracy and non-construction occur in different levels in the processing, to apply the method of computational intelligence information processing in the image registration can have better results than the traditional computation methods. This paper proposes an image registration method based on wavelet decomposition and ant colony optimization, which divides the process of image registration into coarse registration and refined registration through wavelet decomposition technique. In the coarse registration, the transformation parameter value of the image approximation component is acquired through ant colony optimization while the changing parameter value of the original image is obtained by the ant colony search method in the refined registration. The simulation experiment shows that this registration method has the characteristics of anti-noise, fast speed, high accuracy and high registration success rate.
Volume: 13
Issue: 2
Page: 604-613
Publish at: 2015-06-01

Research on Beef Skeletal Maturity Determination Based on Shape Description and Neural Network

10.12928/telkomnika.v13i2.1468
Xiangyan; Xi’an Technological University Meng , Yumiao; Xi’an Technological University Ren , Haixian; Xi’an Technological University Pan
Physiological maturity is an important indicator for beef quality. In traditional method, the maturity grade is determined by subjectively evaluating the degree of cartilage ossification at the tips of the dorsal spine of the thoracic vertebrae. This paper uses the computer vision to replace the artificial method for extracting object (cartilage and bone) regions. Hu invariant moments of object region were calculated as the regional shape characteristic parameters. A trained Hopfield neural network model was used for recognizing cartilage and bone area in thoracic vertebrae image based on minimum Euclidean distance. The result showed that the accuracy of network recognition for cartilage and bone region was 92.75% and 87.68%, respectively. For automatically maturity prediction, the accuracy of prediction was 86%. Algorithm proposed in this paper proved the image description and neural network modeling was an effective method for extracting image feature regions.
Volume: 13
Issue: 2
Page: 730-738
Publish at: 2015-06-01

Water Model Study on Removing Inclusion from Molten Steel by Bubble Attachment in RH Degasser

10.12928/telkomnika.v13i2.999
Chunjie; University of Science and Technology Liaoning Yang , Fuping; University of Science and Technology Liaoning Tang , Minggang; University of Science and Technology Liaoning Shen
In this paper, a water model is established, at geometric similarity ratio of 1:4, to simulate a real 180-t RH vacuum refining device. Removing inclusion from molten steel by bubble attachment in RH degasser is analyzed using the water model. The effects of variables such as bubble size, treatment time, life-gas flow rate, amount and time of NaHCO3 addition are investigated by using high speed video and image-process software.
Volume: 13
Issue: 2
Page: 670-677
Publish at: 2015-06-01
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