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29,287 Article Results

On the Comparison of Line Spectral Frequencies and Mel-Frequency Cepstral Coefficients Using Feedforward Neural Network for Language Identification

10.11591/ijeecs.v10.i1.pp168-175
Teddy Surya Gunawan , Mira Kartiwi
Of the many audio features available, this paper focuses on the comparison of two most popular features, i.e. line spectral frequencies (LSF) and Mel-Frequency Cepstral Coefficients. We trained a feedforward neural network with various hidden layers and number of hidden nodes to identify five different languages, i.e. Arabic, Chinese, English, Korean, and Malay. LSF, MFCC, and combination of both features were extracted as the feature vectors. Systematic experiments have been conducted to find the optimum parameters, i.e. sampling frequency, frame size, model order, and structure of neural network. The recognition rate per frame was converted to recognition rate per audio file using majority voting. On average, the recognition rate for LSF, MFCC, and combination of both features are 96%, 92%, and 96%, respectively. Therefore, LSF is the most suitable features to be utilized for language identification using feedforward neural network classifier.
Volume: 10
Issue: 1
Page: 168-175
Publish at: 2018-04-01

Improved Key Frame Extraction using Discrete Wavelet Transform with Modified Threshold Factor

10.12928/telkomnika.v16i2.7692
Hussein Ali; University of Technology Aldelfy , Mahmood Hamza; University of Technology Al-Mufraji , Thamir; University of Technology R. Saeed
Video summarization used for a different application like video object recognition and classification. In video processing, numerous frames containing similar information, this leads to time consumption and slow processing speed and complexity. By using key frames reducing the amount of memory needed for video data processing and complexity greatly. In this paper key frame extraction of Arabic isolated word using discrete wavelet transform (DWT) with modified threshold factor is proposed with different bases. The results for different wavelet basis db, sym and coif show the best result for numbers of key frames at the threshold factor value (0.75).
Volume: 16
Issue: 2
Page: 567-572
Publish at: 2018-04-01

Automatic Segmentation of Brachial Artery based on Fuzzy C-Means Pixel Clustering from Ultrasound Images

10.11591/ijece.v8i2.pp638-643
Joonsung Park , Doo Heon Song , Hosung Nho , Hyun-Min Choi , Kyung-Ae Kim , Hyun Jun Park , Kwang Baek Kim
Automatic extraction of brachial artery and measuring associated indices such as flow-mediated dilatation and Intima-media thickness are important for early detection of cardiovascular disease and other vascular endothelial malfunctions. In this paper, we propose the basic but important component of such decision-assisting medical software development – noise tolerant fully automatic segmentation of brachial artery from ultrasound images. Pixel clustering with Fuzzy C-Means algorithm in the quantization process is the key component of that segmentation with various image processing algorithms involved. This algorithm could be an alternative choice of segmentation process that can replace speckle noise-suffering edge detection procedures in this application domain.
Volume: 8
Issue: 2
Page: 638-643
Publish at: 2018-04-01

A Real Time Vein Detection System

10.11591/ijeecs.v10.i1.pp129-137
Kazi Istiaque Ahmed , Mohamed Hadi Habaebi , Md Rafiqul Islam
Blood veins detection process can be cumbersome for nurses and medical practioners when it comes to special overweight type of patients.This simple routine procedure can lead the process into an extreme calamity for these patients. In this paper, we emphasized on a process for the detection of the vein in real time using the consecrations of Matlab to prevent or at least reduce the number of inescapable calamity for patients during the infusion of a needle by phlebotomy or doctor in everyday lives. Hemoglobin of the blood tissues engrossed the Near Infrared (NIR) illuminated light and Night vision camera is used to capture the scene and enhance the vein pattern clearly using Contrast Limited Adaptive Histogram Equalization (CLAHE) method. This simple approach can successfully also lead to localizing bleeding spots, clots from stroke …etc among other things.
Volume: 10
Issue: 1
Page: 129-137
Publish at: 2018-04-01

Editorial: Scientific Writing Workshop on TELKOMNIKA Editors and Authors Meeting (TEAM)

10.12928/telkomnika.v16i2.3773
Tole; Universitas Ahmad Dahlan Sutikno
In this year, TELKOMNIKA is organizing scientific writing workshop series for improving manuscript quality which is called as “Scientific Writing Workshop on TELKOMNIKA Editors and Authors Meeting (TEAM)”. This workshop is aimed at developing scientific writing skills to both editing and proofreading for preparing final manuscript. Editing covers reread manuscript which includes content, overall structure, clarity, style and citations to see whether the manuscript is well-organized and the transitions between paragraphs are smooth. Proofreading is the final stage of the editing process, focusing on surface errors such as misspellings and mistakes in grammar and punctuation. This process is just as important as any other aspect of writing. The process is instrumental in getting ideas across in an accessible and logical manner.
Volume: 16
Issue: 2
Page: 463-464
Publish at: 2018-04-01

Driver Behaviour State Recognition based on Speech

10.12928/telkomnika.v16i2.8416
Norhaslinda; Universiti Teknologi MARA Kamaruddin , Abdul Wahab; International Islamic University Malaysia Abdul Rahman , Khairul Ikhwan; Universiti Teknologi MARA Mohamad Halim , Muhammad Hafiq Iqmal; Universiti Teknologi MARA Mohd Noh
Researches have linked the cause of traffic accident to driver behavior and some studies provided practical preventive measures based on different input sources. Due to its simplicity to collect, speech can be used as one of the input. The emotion information gathered from speech can be used to measure driver behavior state based on the hypothesis that emotion influences driver behavior. However, the massive amount of driving speech data may hinder optimal performance of processing and analyzing the data due to the computational complexity and time constraint. This paper presents a silence removal approach using Short Term Energy (STE) and Zero Crossing Rate (ZCR) in the pre-processing phase to reduce the unnecessary processing. Mel Frequency Cepstral Coefficient (MFCC) feature extraction method coupled with Multi-Layer Perceptron (MLP) classifier are employed to get the driver behavior state recognition performance. Experimental results demonstrated that the proposed approach can obtain comparable performance with accuracy ranging between 58.7% and 76.6% to differentiate four driver behavior states, namely; talking through mobile phone, laughing, sleepy and normal driving. It is envisaged that such approach can be extended for a more comprehensive driver behavior identification system that may acts as an embedded warning system for sleepy driver.
Volume: 16
Issue: 2
Page: 852-861
Publish at: 2018-04-01

Vehicle Accident Report Application for Solving Traffic Problems and Reduce the Ratio of Pollution using Case Study: Kuwait City

10.11591/ijeecs.v10.i1.pp380-391
Abdulrahman Alkandari , Samer Moein
Minor traffic accidents have become a major problem facing the road users in the recent years, according to the statistics from the Ministry of Interior (MOI) in Kuwait there were recorded 80,388 accidents by the year 2014. Accidents not only affect the mobility but also contribute to air pollution and slow down economic growth. These effects are the result of the seriously extended trips travel time due to accumulated vehicles queue. In some accidents cases, the lost time waiting for the arrival of the traffic officers and filling up the accident report could take up to 45 minutes. The new idea of Vehicle Accident Report application (I-VAR) concept developed by the research team would reduce the waiting time up to 3 minutes (93% savings), which would increase the level of service of the segment of a roadway. In addition, the study will be discussed four major situations on some of the busiest roads in Kuwait. Specifically, gas emissions and cost estimation. Improve the pollution obviously, by using the (I-VAR) application for the minor accidents there is an amount of 360,776,460 K.D would be saved yearly from the Kuwait government funds. It is a consequence of the huge savings in alleviating traffic congestion and generally produces more saver and efficient travel conditions.
Volume: 10
Issue: 1
Page: 380-391
Publish at: 2018-04-01

Deduplication Analysis of Products In Digital Marketing

10.11591/ijeecs.v10.i1.pp392-399
P. Amudhavalli , N. Rajalakshmi , K.S. Sindhu
As Digital Marketing is becoming more popular, the number of customer’s interpretation on brands is increasing promptly which makes it firmer for companies to evaluate their brand image and to digital market their products on the web. The Forensic Analysis is used to determine and analyze patterns of fraudulent activities on images. Pixel Analysis and Least square support vector machine are used to compare and associate the scores acquired from the images into one result per tweet. We selected these techniques to compare and find the accuracy of the Digital Marketing images with the received product’s images to identify the fraudulent activities on images in Digital Marketing. As the result of this project the customer can identify whether the received product is exactly what is given in the online purchase website.
Volume: 10
Issue: 1
Page: 392-399
Publish at: 2018-04-01

Predicting the Spread of Acacia Nilotica Using Maximum Entropy Modeling

10.12928/telkomnika.v16i2.6894
Budi Arif; Universitas Singaperbangsa Karawang Dermawan , Yeni; Bogor Agricultural University Herdiyeni , Lilik Budi; Bogor Agriculturan University Prasetyo , Agung; The Ministry of Environment and Forestry Siswoyo
Acacia nilotica planted in Baluran National Park aims to prevent the spread of fire from savanna to teak forest became developed into invasive and led to a decrease in the quality and quantity of savannas. Therefore, it is required to predict the spread of A. nilotica to minimize the impacts of invasion on savanna area. The study aims to identify environmental factors which affect spread of A. nilotica. Furthermore, the spread of A. nilotica is predicted using Maximum Entropy. Maximum Entropy is efficient model since it uses presence-only data while the most of other models use presence and absence data. The experimental results reveal six environmental factors, including elevation, slope, NDMI, NDVI, distance from the river, and temperature were identified affecting the spread of A. nilotica. The most dominant environmental factors were elevation and temperature with 40% and 39.6% contributions. Maximum Entropy performed well in predicting the spread of A. nilotica, it was indicated by AUC value of 0.938.
Volume: 16
Issue: 2
Page: 703-712
Publish at: 2018-04-01

Bayesian Segmentation in Signal with Multiplicative Noise Using Reversible Jump MCMC

10.12928/telkomnika.v16i2.7510
Suparman; Universitas Ahmad Dahlan Suparman , Michel; Signal and Communications Group, ENSEEIHT Doisy
This paper proposes the important issues in signal segmentation. The signal is disturbed by multiplicative noise where the number of segments is unknown. A Bayesian approach is proposed to estimate the parameter. The parameter includes the number of segments, the location of the segment, and the amplitude. The posterior distribution for the parameter does not have a simple equation so that the Bayes estimator is not easily determined. Reversible Jump Markov chain Monte Carlo (MCMC) method is adopted to overcome the problem. The Reversible Jump MCMC method creates a Markov chain whose distribution is close to the posterior distribution. The performance of the algorithm is shown by simulation data. The result of this simulation shows that the algorithm works well. As an application, the algorithm is used to segment a Synthetic Aperture Radar (SAR) signal. The advantage of this method is that the number of segments, the position of the segment change, and the amplitude are estimated simultaneously.
Volume: 16
Issue: 2
Page: 673-680
Publish at: 2018-04-01

Fuzzified Single Phase Automatic Sequential Reactive Power Compensation with Minimized Switches

10.12928/telkomnika.v16i2.9024
K.; Multimedia University Shashikumar , C.; Multimedia University Venkataseshaiah , K. S.; Multimedia University Sim
The current rapid growth in IoT technology facilitates the effortless implementation of bidirectional remote monitoring and control system implementation in homes and buildings. We have modeled an actual non-intrusive PnP sequential SVC prototype hardware and wireless FLC automation software design on a real single phase home appliances system as load modeling. In addition, we have also designed a novel Unidirectional MOSFET Switched Capasitor model (UniMosSC) which enables us to reduce the hardware cost and increase the life span of SVC due it uses minimum switching devices. The system we have designed is able to correct the power factor at the root of the problem at each appliance. Due to complexity of appliance clustering and overlapping clusters, we implemented fuzziness in the system for more reliability in computations. The system could be used in homes or buildings resulting in electricity bill reduction, saving dollars and cents.
Volume: 16
Issue: 2
Page: 889-899
Publish at: 2018-04-01

Design and Analysis of Ku/K-band Circular SIW Patch Antenna using 3D EM-based Artificial Neural Networks

10.12928/telkomnika.v16i2.8011
Mohammed; Aboubekr Belkaid University of Tlemcen Chetioui , Abdelhakim; Aboubekr Belkaid University of Tlemcen Boudkhil , Nadia; Aboubekr Belkaid University of Tlemcen Benabdellah , Nasreddine; Aboubekr Belkaid University of Tlemcen Benahmed
Substrate Integrated Waveguide (SIW) antennas are considered as main radiators for RF and microwave wireless systems due to their low profile, low cost and soft integration with the other devices. The gain of a SIW patch antenna may be enhanced using different techniques such as Artificial Neural Networks (ANN) by modifying the antenna’s geometry with high efficiency comparing to electromagnetic techniques that take more time. This paper describes a novel structure of a circular SIW patch antenna design using a tree-dimensional electromagnetic (3D-EM) simulation based on ANN model which is developed as an accurate tool for synthesizing the forward side and then analyzing the reverse side of the problem. In this work, ANN algorithms are used for training the samples to provide precise geometrical dimensions of the SIW patch antenna with high accuracy for the target requirements. The antenna is designed to operate in Ku and K frequency bands, resonate at 16.10 GHz and 19.81 GHz respectively and show good performance resulting in low return losses of less than -10dB to -29dB for the selective frequency bands.
Volume: 16
Issue: 2
Page: 594-599
Publish at: 2018-04-01

Quality Translation Enhancement Using Sequence Knowledge and Pruning in Statistical Machine Translation

10.12928/telkomnika.v16i2.8687
Media A.; Sampoerna University Ayu , Teddy; Sampoerna University Mantoro , Jelita; Surya University Asean
Machine translation has two important parts, a learning process which followed by a translation process. Unfortunately, most of the translation process requires complex operations and in-depth knowledge of the languages in order to give a good quality translation. This study proposes a better approach, which does not require in-depth knowledge of the linguistic properties of the languages, but it produces a good quality translation. This study evaluated 28 different parameters in IRSTLM language modeling, which resulting 270 millions experiments, and proposes a sequence evaluation mechanism based on a maximum evaluation of each parameter in producing a good quality translation based on NIST and BLEU. The parallel corpus and statistical machine learning for English and Bahasa Indonesia were used in this study. The pruning process, user interface, and the personalization of translation have a very important role in implementing of this machine translation. The result is quite promising. It shows that pruning process increases of the translation process time. The particular sequence knowledge/value parameter in translation process has a better performance than the other method using in-depth linguistic knowledge approaches. All these processes, including the process of parsing from a stand-alone mode to an online mode, are also discussed in detail.
Volume: 16
Issue: 2
Page: 718-727
Publish at: 2018-04-01

Breast Mass Segmentation Using a Semi-automatic Procedure Based on Fuzzy C-means Clustering

10.12928/telkomnika.v16i2.6193
Moustapha Mohamed; Chouaib Doukkali University Saleck , Abdelmajid El; Chouaib Doukkali University Moutaouakkil , Mohammed; Chouaib Doukkali University Moucouf , Maksi; Hospital Mohamed V Bouchaib , Hani; Hospital Mohamed V Samira , Jamaldine; Hospital Mohamed V Zineb
Mammography is the primary modality that helped in the early detection and diagnosis of women breast diseases. Further, the process of extracting the masses in mammogram represents a challenging task facing the radiologists, due to problems such as fuzzy or speculated borders, low contrast and the presence of intensity inhomogeneities. Aims to help the radiologists in the diagnosis of breast cancer, many approaches have been conducted to automatically segment the masses in mammograms. Towards this aim, in this paper, we present a new approach for extraction of tumors from region-of-interest (ROI) using the algorithm of Fuzzy C-Means (FCM) setting two clusters for semi-automated segmentation. The proposed method meant to select as input data the set of pixels that enable to get the meaningful information required to segment the masses with high accuracy. This could be accomplished through eliminating unnecessary pixels, which influence on this process through separating it outside of the input data using an optimal threshold given by monitoring the change of clusters rate during the process of threshold decrementing. The proposed methodology has successfully segmented the masses, with an average sensitivity of 82.02% and specificity of 98.23%.
Volume: 16
Issue: 2
Page: 665-672
Publish at: 2018-04-01

Exergy Assessment of Photovoltaic Thermal with V-groove Collector Using Theoretical study

10.12928/telkomnika.v16i2.8433
Muhammad; The National University of Malaysia Zohri , Nurato; Mercu Buana University Nurato , Lalu Darmawan; College Computer Information Management (STMIK) Mataram Bakti , Ahmad; The National University of Malaysia Fudholi
The solution of the environmental problems because of fuel fossil is to use new and renewable energy. There are many studies about energy analysis of solar collector with v-groove but exergy analysis of photovoltaic thermal system with v-groove is still less especially by theoretical study. Photovoltaic thermal with v-groove collector has been conducted the exergy analysis by theoretical assessment. The matrix inversion methods were used to analyze the energy balance equation. The theoretical assessment was conducted under the solar intensity of 385 W/m2, 575 W/m2, and 875 W/m2 and mass flow rate between 0.01 and 0.05 kg/s. The maximum exergy efficiency and exergy of PVT system with v-groove collector were 17.80% and 86.32 Watt at the solar intensity of 875 W/m2.
Volume: 16
Issue: 2
Page: 550-557
Publish at: 2018-04-01
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