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31,456 Article Results

Computer aided diagnosis for breast cancer based on the gabor filter technique

10.11591/ijece.v10i5.pp5235-5242
Mohammed Y. Kamil
The most prominent reason for the death of women all over the world is breast cancer. Early detection of cancer helps to lower the death rate. Mammography scans determine breast tumors in the first stage. As the mammograms have slight contrast, thus, it is a blur to the radiologist to recognize micro growths. A computer-aided diagnostic system is a powerful tool for understanding mammograms. Also, the specialist helps determine the presence of the breast lesion and distinguish between the normal area and the mass. In this paper, the Gabor filter is presented as a key step in building a diagnostic system. It is considered a sufficient method to extract the features. That helps us to avoid tumor classification difficulties and false-positive reduction. The linear support vector machine technique is used in this system for results classification. To improve the results, adaptive histogram equalization pre-processing procedure is employed. Mini-MIAS database utilized to evaluate this method. The highest accuracy, sensitivity, and specificity achieved are 98.7%, 98%, 99%, respectively, at the region of interest (30×30). The results have demonstrated the efficacy and accuracy of the proposed method of helping the radiologist on diagnosing breast cancer.
Volume: 10
Issue: 5
Page: 5235-5242
Publish at: 2020-10-01

Determining damages in ceramic plates by using discrete wavelet packet transform and support vector machine

10.11591/ijece.v10i5.pp4759-4769
Mehmet Yumurtaci , Gokhan Gokmen , Tahir Cetin Akinci
In this study, an analysis was conducted by using discrete wavelet packet transform (DWPT) and support vector machine (SVM) methods to determine undamaged and cracked plates. The pendulum was used to land equal impacts on plates in this experimental study. Sounds, which emerge from plates as a result of the impacts applied to undamaged and cracked plates, are sound signals used in the analysis and DWPT of these sound signals were obtained with 128 decompositions for feature extraction. The first four components, reflecting the characteristics of undamaged and cracked plates within these 128 components, were selected for enhancing the performance of the classifier and energy values were used as feature vectors. In the study, the SVM model was created by selecting appropriate C and γ parameters for the classifier. Undamaged and cracked plates were seen to be successfully identified by an analysis of the training and testing phases. Undamaged and cracked statuses of the plates that are undamaged and have the analysis had identified different cracks. The biggest advantage of this analysis method used is that it is high-precision, is relatively low in cost regarding experimental equipment and requires hardware.
Volume: 10
Issue: 5
Page: 4759-4769
Publish at: 2020-10-01

International Telecommunication Union-Radiocommunication Sector P.837-6 and P.837-7 performance to estimate Indonesian rainfall

10.12928/telkomnika.v18i5.14316
Marzuki; Andalas University Marzuki , Dea Kurnia; University of Andalas Harysandi , Rini; University of Andalas Oktaviani , Lisna; University of Andalas Meylani , Mutya; Andalas University Vonnisa , Harmadi; Andalas University Harmadi , Hiroyuki; Kyoto University Hashiguchi , Toyoshi; Shimane University Shimomai , L.; Informazione e Bioingegneria Luini , Sugeng; Indonesian Agency for Meteorological, Climatological and Geophysics Nugroho , Muzirwan; National Institute of Aeronautics and Space Muzirwan , Nor Azlan Mohd; Universiti Teknikal Malaysia Melaka (UTeM) Aris
This work evaluated the performance of International Telecommunication Union-Radiocommunication Sector (ITU-R) P.837-6 and P.837-7 models (Annex 1) to estimate one-minute rainfall rates in Indonesia. In addition to the default ITU-R P.837-6, the input of ITU-R P.837-6 is also modified using data which has better spatial resolution, i.e. a combination of Tropical Rainfall Measuring Mission (TRMM) 3A25 and 3B43 (ITU-R+3A25+3B43), 3B42 and 3B43 (ITU-R+3B42+3B43), Global Satellite Mapping of Precipitation (ITU-R+GSMaP), and Global Precipitation Measurement (ITU-R+GPM). Among the five test sites, the default ITU-R P.837-6 and ITU-R+3A25+3B43 could predict one-minute rainfall rates at two locations accurately. The ITU-R P.837-7 exhibited a marginally better performance for sites that had a high percentage of very heavy rain, particularly at large (1%) and small (0.001%) percentages of time exceeded. The spatial distribution of rainfall rate produced by ITU-R P.837-7 and ITU-R+3A25+3B43 was closer to the pattern demonstrated by recent satellite precipitation measurements.
Volume: 18
Issue: 5
Page: 2292-2303
Publish at: 2020-10-01

Abnormal activity detection in surveillance video scenes

10.12928/telkomnika.v18i5.16634
Jwan Jamal; Al-Mustansiriyah University Ali , Narjis Mezaal; Al-Mustansiriyah University Shati , Methaq; Al-Mustansiriyah University Talib Gaata
Automated detection of abnormal activity assumes a significant task in surveillance applications. This paper presents an intelligent framework video surveillance to detect abnormal human activity in an academic environment that takes into account the security and emergency aspects by focusing on three abnormal activities (falling, boxing and waving). This framework designed to consist of the two essential processes: the first one is a tracking system that can follow targets with identify sets of features to understand human activity and measure descriptive information of each target. The second one is a decision system that can realize if the activity of the target track is "normal" or "abnormal” then energizing alarm when recognized abnormal activities.
Volume: 18
Issue: 5
Page: 2447-2453
Publish at: 2020-10-01

Development and testing of a thai website accessibility evaluation tool

10.11591/ijece.v10i5.pp4900-4909
Kewalin Angkananon , Mike Wald , Piyabud Ploadaksorn
This paper deals with the important problem that there is no help with the accessibility evaluations of Thailand’s web by developing and evaluating a new method and tool online, WebThai2Access, with experts, developers, and users with disabilities. This tool was evaluated by 30 developers, 30 hearing impaired people, 30 visually impaired people, and 30 elderly people. The developers evaluated the websites whereas experimental tasks were given to each disabled group based on the problems they had accessing web information. The developers found WebThai2Access very usable and the 15 test criteria were reliable for evaluating websites. The lower and upper 95% limits for confidence ratings of developers were minus or plus 10% for YouTube and Pantip websites and minus or plus 3% with the blind association website. The 95% lower and upper limits of confidence were minus or plus 5% for hearing impaired users, minus or plus 2% for elderly users and minus or plus 0% for visually impaired users. The results therefore showed WebThai2Access was reliable and accessible for developers whose evaluations reasonably well predicted website accessibility for users with disabilities.
Volume: 10
Issue: 5
Page: 4900-4909
Publish at: 2020-10-01

Improving data quality using a deep learning network

10.11591/ijeecs.v20.i1.pp306-312
Chulhyun Hwang , Kyouhwan Lee , Hoekyung Jung
IoT data is collected in real time and is treated as highly reliable data because of its high precision. However, it often exhibits incomplete values for reasons such as sensor aging and failure, poor operating environment, and communication problems. The characteristics of IoT data transmitted with high precision and time series are suitable to use LSTM, which is one kind of RNN. In this paper, when applying LSTM to data quality improvement in IoT environment where data are collected simultaneously from several sensors, it is suggested that it is effective to construct LSTM individually for each sensor accuracy.
Volume: 20
Issue: 1
Page: 306-312
Publish at: 2020-10-01

On-chip ultra low power optical wake-up receiver for wireless sensor nodes targeting structural health monitoring

10.12928/telkomnika.v18i5.13378
Chia Yee; Universiti Teknikal Malaysia Melaka (UTeM) Saw , Yan Chiew; Universiti Teknikal Malaysia Melaka (UTeM) Wong , Ser Lee; Universiti Teknikal Malaysia Melaka (UTeM) Loh , Haoyu; Zhejiang Ocean University Zhang
Wireless sensor network (WSN) consists of distributed nodes deployed for monitoring the physical conditions and organizing collected data at the central control unit. Power consumption is the challenges in WSN as the network consists of wireless sensor nodes becomes denser. By utilizing WSN and visible light technology, a simple health monitoring system design can be approached that are smaller in size, faster and lower power consumption. This work focuses on design a low power optical wake-up receiver to reduce the energy consumption of each node in WSN. A wake-up receiver is designed to be always-on for detecting incoming signal and switches on the stand by protocol controller and WSN network for data transmission process. The characteristic of optical transmission and functional circuit of a wake-up receiver has been investigated. A low power optical wake-up receiver has been designed in 180nm Silterra CMOS process technology. The proposed wake-up receiver consumes only 443pW in standby mode and 1.89nW in active mode. The proposed optical wake-up receiver drastically reduces the power consumption by more than one third compared to other wake-up receivers which could be a milestone in the medical field if successfully conducted.
Volume: 18
Issue: 5
Page: 2257-2264
Publish at: 2020-10-01

Multiverse optimisation based technique for solving economic dispatch in power system

10.11591/ijeecs.v20.i1.pp485-491
Muhammad Haziq Suhaimi , Ismail Musirin , Muzaiyanah Hidayab , Shahrizal Jelani , Mohd Helmi Mansor
Economic dispatch (ED) is one of the many important components in a power system operation. It is designed to calculate the exact amount of power generation needed to ensure a minimum cost of generation. A power system with multiple generators should be running under an economic condition. The operating cost has to be minimised for any feasible load demand. The increase of power demand is getting higher throughout the year. Economic dispatch is used to schedule and control all output of the fossil-fuel or coal-generators to satisfy the system load demand at a minimum cost. This paper presents the multiverse optimisation (MVO) for solving the economic dispatch in a power system. The proposed Multiverse optimisation engine developed in this study is implemented on the IEEE 30-Bus reliability test system (RTS). It has five generators, all of which are denoted as the control variables for the optimisation process. To reveal the superiority of MVO, a similar process was conducted using evolutionary programming (EP). Results from both techniques were compared, and it was revealed that MVO had outperformed EP in terms of reduced cost of generation for the system.
Volume: 20
Issue: 1
Page: 485-491
Publish at: 2020-10-01

Algorithm performance comparison for earthquake signal recognition on smartphone’s accelerometer

10.12928/telkomnika.v18i5.14708
Hapsoro Agung; School of Meteorology, Climatology, and Geophysics Nugroho , Haryas Subyantara; School of Meteorology, Climatology, and Geophysics Wicaksana , Hariyanto; School of Meteorology, Climatology, and Geophysics Hariyanto , Rista H.; School of Meteorology, Climatology, and Geophysics Virgianto
Micro-electro-mechanical-system accelerometer is able to detect acceleration signal caused by earthquake. Such type of accelerometer is also used by smartphones. There are few algorithms that can be used to recognize the type of acceleration signal from smartphone. This study aims to find signal recognition algorithm in order to consider the most proper algorithm for earthquake signal detection. The initial stage of designing the recognizer is data collection for each type of signal classification. The next step is to apply a highpass filter to separate the signals collected from the gravitational acceleration signal. The signal is divided into several segments. The system will extract features of each signal segment in the time and frequency domain. Each signal segment is then classified according to the type of signal using the classifier through a series of training data processes. The classifier which has the highest accuracy value is exported into the new input signal modeling. As the result, fine K-NN algorithm has the highest level of accuracy in the classification. The fine K-NN algorithm has an accuracy rate of 99.75% in the classification of human activity signals and earthquake signals with a memory capacity of 6,044 kilobytes and processing time of 15.93 seconds. This algorithm has the best classifier criteria compared to decision tree, support vector machine and linear discriminant analysis algorithms.
Volume: 18
Issue: 5
Page: 2505-2516
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

Pulse shaping methods for inter carrier interference reduction in OFDM system

10.12928/telkomnika.v18i5.13840
N. M. A. E. D.; Udayana University Wirastuti , Ni Putu Lintang; Bali Towerindo Sentra Plc. Anggitiadewi , Nyoman; Udayana University Pramaita
The weakness of the orthogonal freuency division multiplexing (OFDM) system is susceptible to the existence of carrier frequency offset (CFO) which causes the emergence of inter carrier interference (ICI) which causes a degradation of performance OFDM systems. This study aims to apply the suggested rectangular (REC) pulse and improved sinc-power (ISP) pulse shaping methods on OFDM system and determines ICI reduction with the effects of CFO over flat fading Rayleigh channels. The performance of each pulse shaping method is evaluated and compared based on parameter ICI power vs. normalized frequency offset, signal to interference ratio (SIR) vs. normalized frequency offset and bit error rate (BER) vs. energy bit per noise (Eb/No). The simulation result in terms of BER vs. Eb/No indicated that REC and ISP pulse shaping has better performance dealing with ICI reduction compared to OFDM system no applied pulse shaping. In addition, the ISP is able to mitigate ICI better than REC.
Volume: 18
Issue: 5
Page: 2276-2283
Publish at: 2020-10-01

Designing and configuring context-aware semantic web applications

10.12928/telkomnika.v18i5.15277
Haider Hadi; Al-Mansour University College (MUC) Abbas , Suha Sahib; Ministry of Higher Education Oleiwi , Haider Rasheed; Baghdad College of Economic Sciences University Abdulshaheed
Context-aware services are attracting attention of world as the use of web services are rapidly growing. We designed an architecture of context-aware semantic web which provides on demand flexibility and scalability in extracting and mining the research papers from well-known digital libraries i.e. ACM, IEEE and SpringerLink. This paper proposes a context-aware administrations system, which supports programmed revelation and incorporation of setting dependent on Semantic Web administrations. This work has been done using the python programming language with a dedicated library for the semantic web analysis named as “Cubic-Web” on any defined dataset, in our case as we have used a dataset for extracting and studying several publications to measure the impact of context aware semantic web application on the results. We have found the average recall and averge accuracy for all the context aware research journals in our research work. Moreover, as this study is limited journal documents, other future studies can be approached by examining different types of publications using this advance research. An efficient system has been designed considering the parameters of research article meta-data to find out the papers from the web using semantic web technology. Parameters like year of publication, type of publication, number of contributors, evaluation methods and analysis method used in publication. All this data has been extracted using the designed context-aware semantic web technology.
Volume: 18
Issue: 5
Page: 2549-2559
Publish at: 2020-10-01

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
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