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INDONESIA
Indonesian Journal of Electrical Engineering and Computer Science
Published by Institute of Advanced Engineering and Science
ISSN : 25024752     EISSN : 25024760     DOI : -
Core Subject :
Arjuna Subject : -
Articles 64 Documents
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Search results for , issue "Vol 15, No 1: July 2019" : 64 Documents clear
Protecting sensitive information utilizing an efficient association representative rule concealing algorithm for imbalance dataset Mylam Chinnappan Babu; Sankaralingam Pushpa
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 1: July 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i1.pp527-534

Abstract

In data mining, discrimination is the detrimental behavior of the people which is extensively studied in human society and economical science. However, there are negative perceptions about the data mining. Discrimination has two categories; one is direct, and another is indirect. The decisions depend on sensitive information attributes are named as direct discrimination, and the decisions which depend on non-sensitive information attributes are called as indirect discrimination which is strongly related with biased sensitive ones. Privacy protection has become another one of the most important problems in data mining investigation.  To overcome the above issues, an Efficient Association Representative Rule Concealing (EARRC) algorithm is proposed to protect sensitive information or knowledge and offer privacy protection with the classification of the sensitive data. Representative rule concealing is one kind of the privacy-preserving mechanisms to hide sensitive association rules. The objective of this paper is to reduce the alternation of the original database and perceive that there is no sensitive association rule is obtained. The proposed method hides the sensitive information by altering the database without modifying the support of the sensitive item. The EARRC is a type of association classification approach which integrates the benefits of both associative classification and rule-based PART (Projective Adaptive Resonance Theory) classification. Based on Experimental computations, proposed EARRC+PART classifier improves 1.06 NMI and 5.66 Accuracy compared than existing methodologies.
Automatic foreground detection based on KDE and binary classification Mohammed Lahraichi; Khalid Housni; Samir Mbarki
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 1: July 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i1.pp517-526

Abstract

In the recent decades, several methods have been developed to extract moving objects in the presence of dynamic background. However, most of them use a global threshold, and ignore the correlation between neighboring pixels. To address these issues, this paper presents a new approach to generate a probability image based on Kernel Density Estimation (KDE) method, and then apply the Maximum A Posteriori in the Markov Random Field (MAP-MRF) based on probability image, so as to generate an energy function, this function will be minimized by the binary graph cut algorithm to detect the moving pixels instead of applying a thresholding step. The proposed method was tested on various video sequences, and the obtained results showed its effectiveness in presence of a dynamic scene, compared to other background subtraction models.
Multistring seven-level quasi Z-source based asymmetrical inverter Ramesh Rahul Jammy; Kirubakaran Annamalai
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 1: July 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i1.pp88-94

Abstract

In this paper, a single-phase multistring seven-level Quasi-Z-source based Asymmetrical Inverter suitable for grid-connected photovoltaic (PV) system is presented. This topology is an upgrade of quasi-Z-source dc-dc (qZs) network and Asymmetrical multilevel inverter (AMLI). The AMLI generates higher number of levels with reduced switch count and number of sources when compared to symmetrical cascaded based MLI. The qZs network acts as an intermediate stage between the low-voltage PV array and AMLI, to enhance the output voltage gain of the inverter. The steady state performance the topology is verified through MATLAB simulation and experimentation. A laboratory prototype model is developed for a capacity of 200W to validate the theoretical studies. Finally, a comparative assessment of the proposed with the existing topologies is presented.
Active contour model for satellitale image combining local and global region based approach Mouri Hayat; Fizazi Hadria
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 1: July 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i1.pp247-257

Abstract

Global and local image information is crucial for accurate segmentation of images with intensity inhomogeneity valuable minute details and multiple objects with various intensities. We propose a region-based active contour model which is able to utilize together local and global image information. The major contribution of this paper is to expand the LIF model which is includes only local image infofmation to a local and global model. The introduction of a new local and global signed pressure force function enables the extraction of accurate local and global image information and extracts multiple objects with several intensities. Several tests performed on some synthetic and real images indicate that our model is effective as well as less sensitivity to the initial contour location and less time compared with the related works.  
Optimising the parameters of a RBFN network for a teaching learning paradigm Pamela Chaudhury; Hrudaya Kumar Tripathy
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 1: July 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i1.pp435-442

Abstract

Academic performance of students has been a concern worldwide. Despite efforts made by educational institutions there has been a rise in poor academic performance. In our research study we have proposed a model to pre-determine the academic performance of students using a Radial Basis Function network (RBFN) using primary data. The proposed model has been developed by using algorithms like differential evolution (DE) and teaching learning based optimization (TLBO). This model can be used by academic institutions to identify the academically weaker students and take preventive steps to reduce the number of academic failures.
Improving bearings-only target state estimation tracking problem by using adaptive and nonlinear kalman algorithms Tammam Khadour; Michel Al Saba; Louay Saleh
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 1: July 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i1.pp190-198

Abstract

Finding the best estimate of the process state from noisy data is the main problem in tracking systems, many efforts and researches have been done to remove this noise. More useful information about the target’s state can be extracted from observations by using a more appropriate model for the target’s motion or using additional sensors. In this paper, we will introduce two methods to improve the estimation of bearing-only target tracking problem in two dimensions (2D). The first method is by adding a third sensor and making a good alignment of those sensors, and at the same time an extended Kalman filter (EKF), unscented Kalman filter (UKF) and cubature Kalman filter (CKF) are implemented. The second method is by applying an adaptive nonlinear Kalman filter (ANKF) for two sensors to solve the problem of measurement variance uncertainty.
Electrocardiogram (ECG) based stress recognition integrated with different classification of age and gender N. S. Nor Shahrudin; K. A. Sidek; A. Z. Jusoh
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 1: July 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i1.pp199-210

Abstract

Good mental health is important in our daily life. A person commonly finds stress as a barrier to enhance an individual’s performance. Be reminded that not all people have the same level of stress because different people have dissimilar problems in their life. In addition, different level of age and gender will affect unequal amount of stress. Electrocardiogram (ECG) signal is an electrical indicator of the heart that can detect changes of human response which relates to our emotions and reactions. Thus, this research proposed a non-intrusive detector to identify stress level for both gender and different classification of age using the ECG. A total of 30 healthy subjects were involved during the data acquisition stage. Data acquisition which initialize ECG data were divided into two conditions; which are normal and stress states. ECG data for normal state only need the participant to breath in and out normally. In other hand, the participants also need to undergo Stroop Colour word test as a stress inducer to represent ECG in stress state. Then, Sgolay filter was selected in the pre-processing stage to remove artifacts in the signal. The process was followed by feature extraction of the ECG signal and finally classified using RR Interval (RRI), different amplitudes of R peaks and Cardioid graph were used to evaluate the performance of the proposed technique. As a result, Class 5 (age range between 50-59 years old) marks the highest changes of stress level rather than other classes, while women are more affected by stress rather than men by showing tremendous percentage changes between normal and stress level over the proposed classifiers. The result proves that ECG signals can be used as an alternative mechanism to recognize stress more efficiently with the integration of gender and age variabilities.
Modified singular spectrum analysis in identifying rainfall trend over peninsular Malaysia S.M. Shaharudin; N. Ahmad; N.H. Zainuddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 1: July 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i1.pp283-293

Abstract

Identifying the local time scale of the torrential rainfall pattern through Singular Spectrum Analysis (SSA) is useful to separate the trend and noise components. However, SSA poses two main issues which are torrential rainfall time series data have coinciding singular values and the leading components from eigenvector obtained from the decomposing time series matrix are usually assesed by graphical inference lacking in a specific statistical measure. In consequences to both issues, the extracted trend from SSA tended to flatten out and did not show any distinct pattern.  This problem was approached in two ways. First, an Iterative Oblique SSA (Iterative O-SSA) was presented to make adjustment to the singular values data. Second, a measure was introduced to group the decomposed eigenvector based on Robust Sparse K-means (RSK-Means). As the results, the extracted trend using modification of SSA appeared to fit the original time series and looked more flexible compared to SSA.
Performance analysis of 5-ary MUSA and SCMA for uplink transmission Esraa Mosleh; Mostafa M. Fouda; Adly S. Tag Eldien; Mohsen M. Tantawy
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 1: July 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i1.pp365-372

Abstract

Multiple access is one of the core technologies of wireless communications, which enables wireless base stations to deal with a large number of different users and provide the service for each of them at the same time.  Meeting the 5G challenges, non-orthogonal multiple access is the main concerned point in 5G technologies. In this paper, two types of non-orthogonal multiple access schemes, namely, 5-ary Multi User Shared Access (MUSA) and Sparse Code Multiple Access (SCMA), are studied. The Bit Error Rate performance (BER) analysis in terms of user overloading for an uplink 5-ary MUSA and SCMA systems are analyzed.
Optimized health parameters using PSO: a cost effective rfid based wearable gadget with less false alarm rate Talha Ahmed Khan; M. Junaid Tahir; Muhammad Alam; Kushsairy A. Kadir; Zeeshan Shahid
Indonesian Journal of Electrical Engineering and Computer Science Vol 15, No 1: July 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v15.i1.pp230-239

Abstract

The motive of contriving the proposed research was originated after recognizing some false alarm in measuring health parameters and practical issues in hospitals for example approachability and presence of patient at designated place for the evaluation of the health parameters like Blood pressure, sugar, body temperature, pulse and some other parameters.  The manual entry of the data into the systems have been become a critical problem. To vanquish this problem, a wearable gadget has been designed, so that a patient can carry it feasibly. Various approaches like Bayesian classifier has been applied to minimize the false alarm. Fuzzy logic, Kalman filtering, extended Kalman filtering, support vector machine, multi-layer perceptron, adaptive neuro fuzzy inference system and cuckoo search have been applied to eliminate the false alarm and give the best optimum solution. Results have proved that PSO worked betted as its convergence time is less than the others algorithms and produced best optimum value for the body vitals. Moreover, PSO has been applied to achieve the best optimal results and to increase the performance.  Monitoring of heart pulse rate and body temperature readings that were recorded in database were then tested and validated by comparing digital thermometer and digital inflator. PSO will converge and give the global best position of data by updating the velocity. Results proved that PSO produced better results by optimizing with better accuracy and precision and can be acknowledged as cost-effective solution.

Page 6 of 7 | Total Record : 64

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