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28,451 Article Results

Compressive Sensing Algorithm for Data Compression on Weather Monitoring System

10.12928/telkomnika.v14i3.3021
Rika; Indonesian Institute of Sciences (LIPI) Sustika , Bambang; Indonesian Institute of Sciences (LIPI) Sugiarto
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
Volume: 14
Issue: 3
Page: 974-980
Publish at: 2016-09-01

Hybrid Hierarchical Collision Detection Based on Data Reuse

10.12928/telkomnika.v14i3.3590
Jiancai; South China University of Technology Hu , Kejing; South China University of Technology He , Xiaobin; South China University of Technology Lin , Funan; South China University of Technology Lin
To improve the efficiency of collision detection between rigid bodies in complex scenes, this paper proposes a method based on hybrid bounding volume hierarchies for collision detection. In order to improve the simulation performance, the method is based on weighted oriented bounding box and makes dense sampling on the convex hulls of the geometric models. The hierarchical bounding volume tree is composed of many layers. The uppermost layer adopts a cubic bounding box, while lower layers employ weighted oriented bounding box. In the meantime, the data of weighted oriented bounding box is reused for triangle intersection check. We test the method using two scenes. The first scene contains two Buddha models with totally 361,690 triangle facets. The second scene is composed of 200 models with totally 115, 200 triangle facets. The experiments verify the effectiveness of the proposed method.
Volume: 14
Issue: 3
Page: 1077-1082
Publish at: 2016-09-01

Study on Community’s Land Allocation in Long Pahangai District

10.11591/ijeecs.v3.i3.pp564-571
Dito Cahya Renaldi , I Nengah Surati Jaya , Omo Rusdiana
Land use allocation for community has been a crucial process for supporting the spatial allocation either at the regency or provincial level. This study was emphasized on the analysis of land allocation at the district level. The study applied a linear programming approach to optimize the land use in Long Pahangai District then linked with the spatial information. The optimization considered several factors, i.e., land productivity, the degree of erosion and the preference of the community living in the study area. To support the optimization, the availability of land use was determined by considering the land capability using the query tools in the Geographic Information System. The level of land capability applied five constraints, namely, slope, drainage, soil texture, effective depth and erosion. The study found that the optimal allocation of land use in the study area are primary forest of 6,635.11 ha (25.19%), secondary forest of 19,025.7 ha (71.9%), mixed plantation area of 289.61 ha (1.1%), settlement area of 8.3 ha (0.03%) and rice field of 487.35 ha (1.844%). This optimal allocation might increase the community income per capita by approximately 80% from 9,602,000.- to 17,275,171.-/capita/ha/year.  
Volume: 3
Issue: 3
Page: 564-571
Publish at: 2016-09-01

Anomalies Detection Based on the ROC Analysis using Classifiers in Tactical Cognitive Radio Systems: A survey

10.11591/ijai.v5.i3.pp105-116
Ahmed Moumena
Receiver operating characteristic (ROC) curve is an important technique for organizing classifiers and visualizing their performance in tactical systems in the presence of jamming signal. ROC curves are commonly used to evaluate the performance of classifiers for anomalies detection. This paper gives a survey of ROC analysis based on the anomaly detection using classifiers for using them in research. In recent years have been increasingly adopted in the machine learning and data mining research communities. This survey gives definitions of the anomaly detection theory and how to use one ROC curve, what a ROC curve, when we use ROC curves.
Volume: 5
Issue: 3
Page: 105-116
Publish at: 2016-09-01

GPU CUDA accelerated Image Inpainting using Fourth Order PDE equation

10.12928/telkomnika.v14i3.3412
Edwin Prananta , Pranowo; Atma Jaya Yogyakarta University Pranowo , Djoko; Atma Jaya Yogyakarta University Budianto
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.
Volume: 14
Issue: 3
Page: 1009-1015
Publish at: 2016-09-01

Prediction Model of Smelting Endpoint of Fuming Furnace Based on Grey Neural Network

10.12928/telkomnika.v14i3.3713
Song; School of Mechanical Engineering, Anyang Institute of Technology,Henan,China Qiang , WU; School of Mechanical Engineering, Anyang Institute of Technology,Henan,China Yaochun
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.
Volume: 14
Issue: 3
Page: 941-947
Publish at: 2016-09-01

Recognition of Fission Signals Based on Wavelet Analysis and Neural Network

10.12928/telkomnika.v14i3.3544
Li; South West University of Science & Technology Li , Liu Keqi , Hu; Academy of Engineering Physics Gen
Because of the particularity of the uranium components, the nondestructive measuring technique is needed to detect the radioactivity of the component in certain container and identify their property to recognize all kinds of uranium components. This paper establishes a set of samples with the same shape, different weight and abundance of uranium by simulation. Secondly the cross-correlation function of time-relation signal between the source detector and the detector could be calculated. Lastly the result of cross-correlation functions is through micro-wavelet analysis to obtain feature vector which is related to the quality and abundance property of target uranium components. This vector is used to train neural network and help to identify the quality and abundance of unknown uranium components.
Volume: 14
Issue: 3
Page: 1016-1023
Publish at: 2016-09-01

Particle Swarm Optimization Performance: Comparison of Dynamic Economic Dispatch with Dantzig-Wolfe Decomposition

10.12928/telkomnika.v14i3.4054
Mohd Ruddin; Universiti Teknikal Malaysia Melaka Ab Ghani , Saif Tahseen; Ministry of Electricity Hussein , Zanariah; Universiti Teknikal Malaysia Melaka Jano , Tole; Universitas Ahmad Dahlan Sutikno
Economic Dispatch (ED) problem, in practice, is a nonlinear, non-convex type,which has developed gradually into a serious task management goal in the planning phase of the power system. The prime purpose of Dynamic Economic Dispatch (DED) is to minimize generators’ total cost of the power system. DED is to engage the committed generating units at a minimum cost to meet the load demand while fulfilling various constraints. Utilizing heuristic, population-based, and advanced optimization technique, Particle Swarm Optimization (PSO), represents a challenging problem with large dimension in providing a superior solution for DED optimization problem. The feasibility of the PSO method has been demonstrated technically, and economically for two different systems, and it is compared with the Dantzig-Wolfe technique regarding the solution quality and simplicity of implementation. While Dantzig-Wolfe method has its intrinsic drawbacks and positive features, PSO algorithm is the finest and the most appropriate solution. Conventional techniques have been unsuccessful to present compatible solutions to such problems due to their susceptibility to first estimates and possible entrapment into local optima which may complicate computations.
Volume: 14
Issue: 3
Page: 1042-1051
Publish at: 2016-09-01

A Sentiment Knowledge Discovery Model in Twitter’s TV Content Using Stochastic Gradient Descent Algorithm

10.12928/telkomnika.v14i3.2671
Lira; Bogor Institute of Agriculture Ruhwinaningsih , Taufik; Bogor Institute of Agriculture Djatna
The use of social media that the explosive can be a rich source for data mining. Meanwhile, the development of television programs become increased and varied so motivate people to make comments on it’s via social media. Social network contains abundant information which is unstructured, heterogeneous, high dimensional and incremental in nature. Abundant data can be a rich source of information but it is difficult to identify manually. The contributions of this research are to perform preprocessing to address unstructured data, a lot of noise and heterogeneous; find patterns of information and knowledge of social media user activities in the form of positive and negative sentiment on twitter TV content. Some methodologies and techniques are used to perform preprocessing. They are eliminates punctuation and symbols, eliminates number, replace numbers into letters, translation of Alay words, eliminate stop word and Stemming Porter Algorithm. Methodology of this study was used Stochastic Gradient Descent (SGD).The text that has been through preprocessing produces a more structured text, reducing noise and reducing the diversity of text. So, preprocessing affect to the correctly classified istances and processing time. The experiment results reveal that the use of SGD for discovery of the positive and negative sentiment tends to be faster for large data or stream data. Correctly classified instance with a maximum of 88%.
Volume: 14
Issue: 3
Page: 1067-1076
Publish at: 2016-09-01

Quasi-Newton Method for Absolute Value Equation Based on Upper Uniform Smoothing Approximation

10.12928/telkomnika.v14i3.3785
Longquan; Shaanxi University of Technology Yong , Shouheng; Shaanxi University of Technology Tuo
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.
Volume: 14
Issue: 3
Page: 1134-1141
Publish at: 2016-09-01

Medical Image Contrast Enhancement via Wavelet Homomorphic Filtering Transform

10.12928/telkomnika.v14i3.3118
Xinmin; Hunan University of Commerce Zhou , Ying; Tongji University Zheng , Lina; Hunan University of Commerce Tan , Junchan; Hunan University of Commerce Zhao
A novel enhancement algorithm for magnetic resonance (MR) images based on spatial homomorphic filtering transform is proposed in this paper. By this method, the source image is decomposed into different sub-images by dyadic wavelet transform. Homomorphic filtering functions are applied in performing filtering of corresponding sub-band images to attenuate the low frequencies as well as amplify the high frequencies, and a linear adjustment is carried out on the low frequency of the highest level. Later, inverse dyadic wavelet transform is applied to reconstruct the object image. Experiment results on MR images illustrate that the proposed method can eliminate non-uniformity luminance distribution effectively, some subtle tissues can be improved effectually, and some weak sections have not been smoothed by the novel method. 
Volume: 14
Issue: 3
Page: 1203-1212
Publish at: 2016-09-01

Critical Condition in CuInAlSe2 Growth of Solar Cell Absorber

10.12928/telkomnika.v14i3.3644
Sujarwata; Universitas Negeri Semarang Sujarwata , Fianti; Universitas Negeri Semarang Fianti , J.Y.; Yeungnam University Jung , S.H.; Yeungnam University Lee , K.H.; Yeungnam University Kim , M.I.; Lembaga Ilmu Pengetahuan Indonesia Amal
CuInAlSe2 (CIAS) thin films were prepared using pulsed laser deposition (PLD) and selenization. The PLD process utilized a certain kind of stacking order to deposit elemental films on glass substrates, layer by layer, for precursor preparation. They were designed to be Al- and Cu-deficient and selenized using two different heat treatment steps. According to its precursor compositional ratio, stacking order, and heat treatment, each CIAS film showed different properties and a critical condition. The crystalline phases, compositional ratio, morphology, and optical-electrical properties of the CIAS films are discussed here.   
Volume: 14
Issue: 3
Page: 867-872
Publish at: 2016-09-01

A Novel Selective and Sensitive Electrochemical Sensor for Insulin Detection

10.11591/ijeecs.v3.i3.pp496-502
Zulkarnain Zulkarnain , Suprapto Suprapto , Taslim Ersam , Fredy Kurniawan
A novel selective and sensitive electrochemical sensor for insulin detection has been fabricated and investigated. The electrochemical sensor was made from a mixture of silica gel, chitosan and nickel hydroxide (Ni(OH)2) nanoparticles, which was mounted on a silver wire and covered by a glass tube (silica gel/chitosan/Ni(OH)2 nanoparticles paste electrode). The sensor was characterized using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The anodic and cathodic currents of the silica gel/chitosan paste electrode with Ni(OH)2 are 580 mA and -750 mA, respectively. Without Ni(OH)2, however, the currents are 150 mA and -250 mA, respectively. The sensitivity and limit of detection of the silica gel/chitosan/Ni(OH)2 nanoparticle paste electrode for insulin detection are 5573 × 10­5pA/pMcm2 and 0.25 pM, respectively. The sensor also shows good reproducibility of measurement for 35 days with an RSD of 0.29%. The fabricated electrodes also show good reproducibility, with an RSD of 1.39%.
Volume: 3
Issue: 3
Page: 496-502
Publish at: 2016-09-01

Comparison of various channel equalization techniques in OFDM system using different digital modulations

10.11591/ijeecs.v3.i3.pp634-638
Pratima Manhas , M.K. Soni
The nature of future wireless applications requires high data rates and for this OFDM technique is used. OFDM stands for orthogonal frequency division multiplexing and is a type of multi-carrier transmission where all the subcarriers are orthogonal to each other. At high data rates, the channel distortion to the data is very important and it is somewhat impossible to recover the transmitted data with a simple receiver. So a complex receiver structure is needed which uses computationally expensive equalization and channel estimation algorithms to estimate the channel. These estimations can be used within the received data to recover the originally transmitted data. OFDM can simplify the equalization problem by changing the frequency-selective channel into a flat channel. The radio channels in mobile radio systems are usually multipath fading channels that results in intersymbol interference (ISI) in the received signal. To remove ISI from the signal, many kind of equalizers can be used. The need for equalizers arises from the fact that the channel has amplitude and phase dispersion which results in the interference of the transmitted signals with one another which is known as ISI .So, to solve this problem equalizers are designed. Equalizer is intend to work in such a way that Bit Error Rate (BER) should be low and Signal-to-Noise Ratio (SNR) should be high. An equalizer within a receiver compensates for the average range of expected channel amplitude and delay characteristics. This paper deals with the various equalization techniques (LMS, RLS and CMA) used for OFDM system .A comparative analysis of different equalization technique in terms of BER is done using MATLAB Simulink.
Volume: 3
Issue: 3
Page: 634-638
Publish at: 2016-09-01

Multi-Criteria in Discriminant Analysis to Find the Dominant Features

10.12928/telkomnika.v14i3.3472
Arif; University of Trunojoyo Muntasa , Indah Agustien; University of Trunojoyo Siradjuddin , Rima; University of Trunojoyo Tri Wahyuningrum
A crucial problem in biometrics is enormous dimensionality. It will have an impact on the costs involved. Therefore, the feature extraction plays a significant role in biometrics computational. In this research, a novel approach to extract the features is proposed for facial image recognition. Four criteria of the Discriminant Analysis have been modeled to find the dominant features. For each criterion is an objective function, it was derived to obtain the optimum values. The optimum values can be solved by using generalized the Eigenvalue problem associated to the largest Eigenvalue. The modeling results were employed to recognize the facial image by the multi-criteria projection to the original data. The training sets were also processed by using the Eigenface projection to avoid the singularity problem cases. The similarity measurements were performed by using four different methods, i.e. Euclidian Distance, Manhattan, Chebyshev, and Canberra.  Feature extraction and analysis results using multi-criteria have shown better results than the other appearance method, i.e. Eigenface (PCA), Fisherface (Linear Discriminant Analysis or LDA), Laplacianfaces (Locality Preserving Projection or LPP), and Orthogonal Laplacianfaces (Orthogonal Locality Preserving Projection or O-LPP). 
Volume: 14
Issue: 3
Page: 1113-1122
Publish at: 2016-09-01
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