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31,456 Article Results

Factors influencing low intension detection rate in a non-invasive EEG-based brain computer interface system

10.11591/ijeecs.v20.i1.pp167-175
Clifford Maswanganyi , Chungling Tu , Pius Owolawi , Shengzhi Du
Motor imagery (MI) responses extracted from the brain in the form of EEG signals have been widely utilized for intention detection in brain computer interface (BCI) systems. However, due to the non-linearity and the non-stationarity of EEG signals, BCI systems suffer from low MI prediction rate with both known and unknown influncing factors. This paper investigates the impact of visual stimulus, feature dimensions and artifacts on MI task detection rate, towards improving MI prediction rate. Three EEG datasets were utilized to facilitate the investigation. Three filters (band-pass, notch and common average reference) and the independent component analysis (ICA) were applied on each datasets, to eliminate the impact of artifact. Three sets of features where extracted from artifact free ICA components, from which more relevant features were selected. Moreover, the selected feature subsets were incorporated into three classifiers, NB, Regression Tree and K-NN to predict four MI and hybrid tasks. K-NN classifier outperformed the other two classifies in each dataset. The highest classification accuracy is obtained in hybrid task EEG dataset. Moreover, accurately predicted EEG classes were applied to a robotic arm control.
Volume: 20
Issue: 1
Page: 167-175
Publish at: 2020-10-01

A novel delay dictionary design for compressive sensing-based time varying channel estimation in OFDM systems

10.12928/telkomnika.v18i5.14223
Maryam K.; Al-Nahrain University Abboud , Bayan M.; Al-Nahrain University Sabbar
Compressive sensing (CS) is a new attractive technique adopted for Linear Time Varying channel estimation. orthogonal frequency division multiplexing (OFDM) was proposed to be used in 4G and 5G which supports high data rate requirements. Different pilot aided channel estimation techniques were proposed to better track the channel conditions, which consumes bandwidth, thus, considerable data rate reduced. In order to estimate the channel with minimum number of pilots, compressive sensing CS was proposed to efficiently estimate the channel variations. In this paper, a novel delay dictionary-based CS was designed and simulated to estimate the linear time varying (LTV) channel. The proposed dictionary shows the suitability of estimating the channel impulse response (CIR) with low to moderate Doppler frequency shifts with acceptable bit error rate (BER) performance.
Volume: 18
Issue: 5
Page: 2284-2291
Publish at: 2020-10-01

Defective ground structure and complimentary split ring resonator loaded compact wideband antenna for radiolocation applications

10.12928/telkomnika.v18i5.15953
Nelapati Ananda; Acharya Nagarjuna University College of Engineering and Technology Rao , Siddaiah; Acharya Nagarjuna University College of Engineering and Technology P.
A wideband compact antenna with wo Bandwidth enhancement techniques intended for radiolocation applications is presented. Defective ground structure (DGS) is used to enhance the bandwidth and complimentary split ring resonator (CSRR) has been used to generate the bandwidth at the lower frequency of the antenna which brings compact nature. A coax feed patch antenna radiating at X-band frequency of 10 GHz is loaded with DGS and CSRR. Proposed antenna with a bandwidth of 3.4 GHz has shown a considerable enhancement in the antenna bandwidth when compared with the antenna with CSRR alone which is having a bandwidth of 1.15 GHz and a basic patch antenna whose bandwidth is 0.91 GHz. Proposed antenna is having omni directional radiation pattern with a gain of 5.01 dB and without any null in the coverage area. A great increase in the current fields can be observed that the field currents by loading the patch and ground with CSRR and DGS respectively. The patch currents have increased from 2.76 v/m to 3.25 v/m and the ground currents have increased from 0v/m to 2.45 v/m. Proposed antenna has been realized and its performance is measured using vector network analyzer, a near match in between the simulated result and measured result is observed.
Volume: 18
Issue: 5
Page: 2328-2334
Publish at: 2020-10-01

Accurate harmonic source identification using S-transform

10.12928/telkomnika.v18i5.5632
Mohd Hatta; Universiti Teknikal Malaysia Melaka Jopri , Abdul Rahim; Universiti Teknikal Malaysia Melaka Abdullah , Rony; Infineon Technologies AG Karim , Srete; University of Osijek Nikolovski , Tole; Universitas Ahmad Dahlan Sutikno , Mustafa; Universiti Teknikal Malaysia Melaka Manap
This paper introduces the accurate identification of harmonic sources in the power distribution system using time-frequency distribution (TFD) analysis, which is S-transform. The S-transform is a very applicable method to represent signals parameters in time-frequency representation (TFR) such as TFR impedance (ZTFR) and the main advantages of S-transform it can provide better frequency resolution for low frequency components and also offers better time resolution for high-frequency components. The identification of multiple harmonic sources are based on the significant relationship of spectral impedances (ZS) that extracted from the ZTFR, consist of the fundamental impedance (Z1) and harmonic impedance (Zh). To verify the accuracy of the proposed method, MATLAB simulations carried out several unique cases on IEEE 4-bus test feeder cases. It is proven that the proposed method is superior, with 100% correct identification of harmonic source location. It is proven that the method is accurate, fast and cost-efficient to localize harmonic sources in the power distribution system.
Volume: 18
Issue: 5
Page: 2708-2717
Publish at: 2020-10-01

Control system of automatic garage using programmable logic controller

10.12928/telkomnika.v18i5.14398
K.; SRM Institute of Science and Technology Selvakumar , R.; SRM Institute of Science and Technology Palanisamy , Patti; SRM Institute of Science and Technology Nikhil , D.; SRM Institute of Science and Technology Karthikeyan , D.; SRM Institute of Science and Technology Selvabharathi
In today’s populated world, urban land availability has become scarce and manual involvement of humans for a proper task makes a work less efficient and less accurate. The garage is one of the workstations which needs to be modernized for enhanced land utilization, energy saving approach and systematic functioning. This goal can only be achieved through the automation of parking systems. We have proposed an automated control system for garage using siemens PLC (programmable logic control)-1200 to control the vehicles. The number plate of the car is recorded through the RFID reader and the parking slot for that particular vehicle is allotted automatically based on the available vacancy. Along with this the parking area is fitted with fire alarm, which will raise if any smoke or fire happens in the location. The total parking cost of each vehicle can be calculated based on the number of hours it has been parked. And the information will be displayed in the SCADA screen. Additionally, instead of the full lightening of the complete place, lightening will be provided only in the direction of movement of the car, preventing wastage of energy.
Volume: 18
Issue: 5
Page: 2654-2664
Publish at: 2020-10-01

Hybrid order characteristics in car-following behavior

10.11591/ijeecs.v20.i1.pp158-166
Chunling Tu , Shengzhi Du
This paper addresses the discovery of an interesting property in car-following processes, which was not reported in the existing literatures. A hybrid order behavior is supported by both experimental data and theoretical simulations. To demonstrate this behavior, the first order and the second order car-following behaviors are defined. Then, by comparing the first and the second order car-following behaviors in the existing analystic models and the real traffic context, this paper finds that a significant amount of the second order car-following processes in real traffic context do not match the existing models and structural mismatches are observed. The popularity and significance of such cases suggest the existence of unmodelled dynamics in the existing methods, that is, the car following behavior should be determined by more factors than the immediate proceeding vehicle. Therefore, the existing car-following models must be improved to accommodate these factors. This forms one of the main values of this paper. This paper then defines the hybrid order car-following behavior and prompts to associate this behavior with the concerned unmodelled dynamics (mismatches between the actual traffic data and the simulation from models). The neural network is employed to model such dynamics. The idea of the proposed hybrid order behavior matches the fact that the car-following behavior is determined by multiple vehicles driving in front of the subject car instead of only the immediate proceeding one. This is valuable because it provides guidance on the improvement of existing car-following models. The neural network model validates that the consideration of multiple vehicles improves the accuracy of car-following modelling.
Volume: 20
Issue: 1
Page: 158-166
Publish at: 2020-10-01

Development of video-based emotion recognition using deep learning with Google Colab

10.12928/telkomnika.v18i5.16717
Teddy Surya; International Islamic University Malaysia Gunawan , Arselan; International Islamic University Malaysia Ashraf , Bob Subhan; Universitas Potensi Utama Riza , Edy Victor; Universitas Potensi Utama Haryanto , Rika; Universitas Potensi Utama Rosnelly , Mira; International Islamic University Malaysia Kartiwi , Zuriati; Universiti Teknologi MARA Janin
Emotion recognition using images, videos, or speech as input is considered as a hot topic in the field of research over some years. With the introduction of deep learning techniques, e.g., convolutional neural networks (CNN), applied in emotion recognition, has produced promising results. Human facial expressions are considered as critical components in understanding one's emotions. This paper sheds light on recognizing the emotions using deep learning techniques from the videos. The methodology of the recognition process, along with its description, is provided in this paper. Some of the video-based datasets used in many scholarly works are also examined. Results obtained from different emotion recognition models are presented along with their performance parameters. An experiment was carried out on the fer2013 dataset in Google Colab for depression detection, which came out to be 97% accurate on the training set and 57.4% accurate on the testing set.
Volume: 18
Issue: 5
Page: 2463-2471
Publish at: 2020-10-01

Automatic sound synthesis using the fly algorithm

10.12928/telkomnika.v18i5.15665
Zainab A.; University of Basrah Abbood , Imad S.; University of Basrah Alshawi , Asaad A.; University of Basrah Alhijaj , Franck P.; Bangor University Vidal
Our study is demonstrated a new type of evolutionary sound synthesis method. This work based on the fly algorithm, a cooperative co-evolution algorithm; it is derived from the Parisian evolution approach. The algorithm has relatively amended the position of individuals (the Flies) represented by 3-D points. The fly algorithm has successfully investigated in different applications, starting with a real-time stereo vision for robotics. Also, the algorithm shows promising results in tomography to reconstruct 3-D images. The final application of the fly algorithm was generating artistic images, such as digital mosaics. In all these applications, the flies’representation started for simple, 3-D points, to complex one, the structure of 9-elements. Our method follows evolutionary digital art with the fly algorithm in representing the pattern of the flies. They represented in a way of having their structure. This structure includes position, colour, rotation angle, and size. Our algorithm has the benefit of graphics processing units (GPUs) to generate the sound waveform using the modern OpenGL shading language.
Volume: 18
Issue: 5
Page: 2439-2446
Publish at: 2020-10-01

The influences of calcium fluoride and silica particles on improving color homogeneity of WLEDs

10.12928/telkomnika.v18i5.13571
Anh-Minh D.; Ton Duc Thang University Tran , Nguyen Doan Quoc; Ton Duc Thang University Anh , Nguyen Thi Phuong; Posts and Telecommunications Institute of Technology Loan
The LEDs lighting device with phosphor ingredient (pcLEDs) is among the most common lighting methods in recent years and evaluated by chromatic uniformity and lighting capacity. Therefore, we introduce the phosphor particles that can improve the scattering efficiency (SEPs) to apply in pcLEDs at 8500 K correlated color temperature (CCT) with the expectation to produce better pcLEDs by enhancing both quantity and quality of emitted light. Combining various materials such as CaF2 and SiO2 with yellow Y3Al5O12:Ce3+ phosphor composition in the pcLEDs simulation created by the LightTools program is the mechanism of this research. The simulated pcLEDs are tested and the results will be verified with Mie-scattering theory. The observation of the simulation leads to the conclusion about the scattering coefficients of SEPs at 455 nm and 595 nm wavelengths. The calculation showed that CaF2 is better for color homogeneity yet suffer from luminous flux deficiency as the concentration gets higher. On the other hand, SiO2 is the scattering enhancement material that can maintain high luminous flux regardless of its concentration. 
Volume: 18
Issue: 5
Page: 2696-2701
Publish at: 2020-10-01

An intrusion detection system for packet and flow based networks using deep neural network approach

10.11591/ijece.v10i5.pp5514-5525
Kaniz Farhana , Maqsudur Rahman , Md. Tofael Ahmed
Study on deep neural networks and big data is merging now by several aspects to enhance the capabilities of intrusion detection system (IDS). Many IDS models has been introduced to provide security over big data. This study focuses on the intrusion detection in computer networks using big datasets. The advent of big data has agitated the comprehensive assistance in cyber security by forwarding a brunch of affluent algorithms to classify and analysis patterns and making a better prediction more efficiently. In this study, to detect intrusion a detection model has been propounded applying deep neural networks. We applied the suggested model on the latest data set available at online, formatted with packet based, flow based data and some additional metadata. The data set is labeled and imbalanced with 79 attributes and some classes having much less training samples compared to other classes. The proposed model is build using Keras and Google Tensorflow deep learning environment. Experimental result shows that intrusions are detected with the accuracy over 99% for both binary and multi-class classification with selected best features. Receiver operating characteristics (ROC) and precision-recall curve average score is also 1. The outcome implies that Deep Neural Networks offers a novel research model with great accuracy for intrusion detection model, better than some models presented in the literature.
Volume: 10
Issue: 5
Page: 5514-5525
Publish at: 2020-10-01

Comparison of search algorithms in Javanese-Indonesian dictionary application

10.12928/telkomnika.v18i5.14882
Yana Aditia; UIN Sunan Gunung Djati Bandung Gerhana , Nur; UIN Sunan Gunung Djati Bandung Lukman , Arief Fatchul; UIN Sunan Gunung Djati Bandung Huda , Cecep Nurul; UIN Sunan Gunung Djati Bandung Alam , Undang; UIN Sunan Gunung Djati Bandung Syaripudin , Devi; UIN Sunan Gunung Djati Bandung Novitasari
This study aims to compare the performance of Boyer-Moore, Knuth morris pratt, and Horspool algorithms in searching for the meaning of words in the Java-Indonesian dictionary search application in terms of accuracy and processing time. Performance Testing is used to test the performance of algorithm implementations in applications. The test results show that the Boyer Moore and Knuth Morris Pratt algorithms have an accuracy rate of 100%, and the Horspool algorithm 85.3%. While the processing time, Knuth Morris Pratt algorithm has the highest average speed level of 25ms, Horspool 39.9 ms, while the average speed of the Boyer Moore algorithm is 44.2 ms. While the complexity test results, the Boyer Moore algorithm has an overall number of n 26n2, Knuth Morris Pratt and Horspool 20n2 each.
Volume: 18
Issue: 5
Page: 2517-2524
Publish at: 2020-10-01

Database techniques for resilient network monitoring and inspection

10.12928/telkomnika.v18i5.14305
Zahraa A.; AlNahrain University Jaaz , Suha Sahib; Ministry of Higher Education Oleiwi , Seba Aziz; Institute of Medical Technology Al-Mansur Sahy , Israa; Baghdad College of Economic Sciences University Albarazanchi
Network connection logs have long been recognized as integral to proper network security, maintenance, and performance management. This paper provides a development of distributed systems and write optimized databases: However, even a somewhat sizable network will generate large amounts of logs at very high rates. This paper explains why many storage methods are insufficient for providing real-time analysis on sizable datasets and examines database techniques attempt to address this challenge. We argue that sufficient methods include distributing storage, computation, and write optimized datastructures (WOD). Diventi, a project developed by Sandia National Laboratories, is here used to evaluate the potential of WODs to manage large datasets of network connection logs. It can ingest billions of connection logs at rates over 100,000 events per second while allowing most queries to complete in under one second. Storage and computation distribution are then evaluated using Elastic-search, an open-source distributed search and analytics engine. Then, to provide an example application of these databases, we develop a simple analytic which collects statistical information and classifies IP addresses based upon behavior. Finally, we examine the results of running the proposed analytic in real-time upon broconn (now Zeek) flow data collected by Diventi at IEEE/ACM Supercomputing 2019.
Volume: 18
Issue: 5
Page: 2412-2420
Publish at: 2020-10-01

Influence of various application types on the performance of LTE mobile networks

10.11591/ijece.v10i5.pp5420-5429
Adel Agamy , Ahmed M. Mohamed
Modern mobile internet networks are becoming heavier and denser. Also it is not regularly planned, and becoming more heterogeneous. The explosive growth in the usage of smartphones poses numerous challenges for LTE cellular networks design and implementation. The performance of LTE networks with bursty and self-similar traffic has become a major challenge. Accurate modeling of the data generated by each connected wireless device is important for properly investigating the performance of LTE networks. This paper presents a mathematical model for LTE networks using queuing theory considering the influence of various application types. Using sporadic source traffic feeding to the queue of the evolved node B and with the exponential service time assumption, we construct a queuing model to estimate the performance of LTE networks. We use the performance model presented in this paper to study the influence of various application categories on the performance of LTE cellular networks. Also we validate our model with simulation using NS3 simulator with different scenarios.
Volume: 10
Issue: 5
Page: 5420-5429
Publish at: 2020-10-01

The efficient interleaving of digital-video-broadcasting-satellite 2nd generations system

10.12928/telkomnika.v18i5.16295
Mohammed Jabbar Mohammed; The University of Babylon Ameen , Hussam Jawad; The University of Babylon Kadhim
The DVB-S2 system is designed as a toolbox to permit the execution of the satellite programs. Interleaver is an essential part of the DVB-S2 system. The current general block interleaver in DVB-S2 is not best, which leads to high BER and maybe not satisfy the requirements of the system. The purpose of this paper is to study the several interleaver types and comparative analyses are done between them to find which of these give better performance. Simulations results obtained prove that the 2D interleavers minimize BER more than other interleavers of DVB-S2. Further, the performance of 2D interleaver is better on a system that required a low SNR.
Volume: 18
Issue: 5
Page: 2362-2370
Publish at: 2020-10-01

Determination of flexibility of workers working time through Taguchi method approach

10.12928/telkomnika.v18i5.13979
Suhaila; Universiti Malaysia Perlis Saidat , Ahmad Kadri; Universiti Malaysia Perlis Junoh , Wan Zuki Azman; Universiti Malaysia Perlis Wan Muhamad , Zainab; Universiti Malaysia Perlis Yahya
Human factor is one of the important elements in manufacturing world, despite their important role in improvement the production flow, they have been neglected while scheduling for many decades. In this paper the researchers taken the human factor throughout their job performance weightage into consideration while using job shop scheduling (JSS) for a factory of glass industry, in order to improving the workers' flexibility. In other hand, the researchers suggested a new sequence of workers' weightage by using Taguchi method, which present the best flexibility that workers can have, while decreasing the total time that the factory need to complete the whole production flow. 
Volume: 18
Issue: 5
Page: 2764-2771
Publish at: 2020-10-01
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