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INDONESIA
Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Published by IAES Indonesia Section and Partners
ISSN : 20893272     EISSN : -     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality articles dedicated to all aspects of the latest outstanding developments in the field of electrical engineering. Its scope encompasses the engineering of Telecommunication and Information Technology, Applied Computing & Computer, Instrumentation & Control, Electrical (Power), Electronics, and Informatics.
Arjuna Subject : -
Articles 783 Documents
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Bat Algorithm for Solving Dynamic Economic Emission Dispatch Problem Hardiansyah, Hardiansyah
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 6, No 3: September 2018
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v6i3.512

Abstract

This paper proposes a new meta-heuristic search algorithm, called Bat Algorithm (BA). Bat algorithm is an optimization technique motivated by the echolocation behavior of natural bats in finding their foods. The proposed algorithm is presented to solve the dynamic economic emission dispatch (DEED) problem. As emission minimization is conflicting with minimum cost of generation, the DEED problem becomes a multi-objective optimization problem with conflicting objectives. The proposed algorithm is validated on 5-unit generation system for a 24 h time interval. The results proved the efficiency of the proposed method when compared with the other optimization algorithms reported in the literature.
Resource Efficient Single Precision Floating Point Multiplier Using Karatsuba Algorithm Gowreesrinivas V K; Samundiswary P
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 6, No 3: September 2018
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v6i3.532

Abstract

In floating point arithmetic operations, multiplication is the most required operation for many signal processing and scientific applications. 24-bit length mantissa multiplication is involved to obtain the floating point multiplication final result for two given single precision floating point numbers. This mantissa multiplication plays the major role in the performance evaluation in respect of occupied area and propagation delay. This paper presents the design and analysis of single precision floating point multiplication using karatsuba algorithm with vedic multiplier with the considering of modified 2x1 multiplexers and modified 4:2 compressors in order to overcome the drawbacks in the existing techniques. Further, the performance analysis of single precision floating point multiplier is analyzed in terms of area and delay using Karatsuba Algorithm with different existing techniques such as 4x1 multiplexers and 3:2 compressors and modified techniques such as 2x1 multiplexers, 4:2 compressors. From the simulation results, it is observed that single precision floating point multiplication with karatsuba algorithm using modified 4:2 compressor with XOR-MUX logic provides better performance with efficient usage of resources such as area and delay than that of existing techniques. All the blocks involved for floating point multiplication are coded with Verilog and synthesized using Xilinx ISE Simulator.
Open Source EEG Platform with Reconfigurable Features for Multiple-Scenarios Juan Manuel Lopez; Fabian Gonzalez; Juan Carlos Bohorquez; Jorge Bohorquez; Mario Andres Valderrama; Fredy Segura-Quijano
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 6, No 3: September 2018
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v6i3.556

Abstract

Electroencephalogram (EEG) acquisition systems are widely used as diagnostic and research tools. This document shows the implementation of a reconfigurable family of three affordable 8-channels, 24 bits of resolution, EEG acquisition systems intended for a wide variety of research purposes. The three devices offer a modular design and upgradability, permitting changes in the firmware and software. Due to the nature of the Analog Front-End (AFE) used, no high-pass analog filters were implemented, allowing the capture of very low frequency components. Two systems of the family, called “RF-Brain” and “Bluetooth-Brain”, were designed to be light and wireless, planned for experimentation where movement of the subject cannot be restricted. The sample rate in these systems can be configured up to 2000 samples per second (SPS) for the RF-Brain and 250 SPS for the Bluetooth-Brain when the 8 channels are used. If fewer channels are required, the sampling frequency can be higher (up to 4 kSPS or 2 kSPS for 1 channel for RF-Brain and Bluetooth-Brain respectively). The third system, named “USB-Brain”, is a wired device designed for purposes requiring high sampling frequency acquisition and general purpose ports, with sampling rates up to 4 kSPS.
Blind Signal Separation Algorithm for Acoustic Echo Cancellation Haengwoo Lee
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 6, No 3: September 2018
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v6i3.583

Abstract

This paper is to the blind signal separation algorithm applied to acoustic echo cancellation. This algorithm doesn’t degrade the performance of echo cancellation even in the double-talk. In the closed echo environment, the mixing model of acoustic signals has multi-channel, so the convolutive blind signal separation method is applied. And the mixing coefficients are computed by using the feedback model without directly calculating the separation coefficients. The coefficient updating is performed by iterative computations based on the second-order statistical properties, thus estimating the near-end speech. Many simulations have been performed to verify the performance of the proposed blind signal separation. Simulation results show that the proposed acoustic echo canceller operates safely regardless of double-talk, and the PESQ is improved by 0.6 point compared with the general adaptive FIR filter structure.
Graphene Nanoribbon Simulator of Vacancy Defects On Electronic Structure Kien Liong Wong; Mohamad Azri Sufi Mahadzir; Wee Khang Chong; Mohd Shahrizal Rusli; Cheng Siong Lim; Michael Loong Peng Tan
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 6, No 3: September 2018
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v6i3.576

Abstract

Graphene Nanoribbon Simulator (GNRSIM) is developed using MATLAB Graphical User Interface Development Environment to study the electronics properties of graphene nanoribbons (GNRs). The main focus of this research is the simulation effects of single vacancy 1 in graphene nanoribbons lattices on electronic structure. The band structure and density of states are explored by using tight binding approximation where a Hamiltonian operator with nearest-neighbor interactions is introduced. The simulator has a wide range of input parameters where user can select armchair or zigzag GNR. The size of the lattices namely width and length can be varied. The location of the vacancy defect can be pinpoint by providing the row and column of the missing atom. The limitation of GNRSIM at present is that it can only accept a single atom vacancy. GNRSIM is able to be executed as a standalone application software in understanding the fundamental properties of semiconductor material and device engineering through ab-initio calculations.
Implementation of Modified AES as Image Encryption Scheme Heidilyn V Gamido; Ariel M Sison; Ruji P Medina
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 6, No 3: September 2018
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v6i3.490

Abstract

Since images have bigger size than text, a faster encryption algorithm is needed to provide higher security in digital images. The paper presents a modified AES algorithm that address the requirement in image encryption. The modified algorithm used bit permutation in replacement of MixColumns to reduce the computational requirement of the algorithm in encrypting images. Results of the study show that the modified algorithm exhibited faster encryption and decryption time in images. The modified algorithm also achieved a good result in the key sensitivity analysis, histogram analysis, information entropy, the correlation coefficient of adjacent pixels, Number of Pixel Change Rate and Unified Average Change Intensity making the modified algorithm resistant to statistical and differential attack.
Comparative Study of Type-1 and Type-2 Fuzzy System in Decision Support System Humaira Humaira; Yance Sonatha; Cipto Prabowo; Hidra Amnur; Rita Afyenni
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 6, No 3: September 2018
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v6i3.391

Abstract

This study compares the Type-1 Fuzzy and Interval Type-2 Fuzzy in Decision Support System (DSS). Particular case studied in this paper deals with supplier selection for development of new product. DSS is developed to recommend a decision to provide assessment criteria on the supplier. All the type of membership functions and rules between these systems are equally applied. It is shown that  in Type-2 Fuzzy can manage the level of uncertainty in decision making. In general, both systems have a surface resemblance. The result shows that type-2 Fuzzy based decision making with a level of uncertainty is able to provide alternative decisions.
Big Data in Smart-Cities: Current Research and Challenges Debajyoti Pal; Tuul Triyason; Praisan Padungweang
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 6, No 4: December 2018
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v6i4.543

Abstract

Smart-cities are an emerging paradigm containing heterogeneous network infrastructure, ubiquitous sensing devices, big-data processing and intelligent control systems. Their primary aim is to improve the quality of life of the citizens by providing intelligent services in a wide variety of aspects like transportation, healthcare, entertainment, environment, and energy. In order to provide such services, the role of big-data and its analysis is extremely important as it enables to obtain valuable insights into the large data generated by the smart-cities.  In this article, we investigate the state-of-art research efforts directed towards big-data analytics in a smart-city context. Specifically, first we present a big-data centric taxonomy for the smart-cities to bring forth a generic overview of the importance of big-data paradigm in a smart-city environment. This is followed by the presentation of a top-level snapshot of the commonly used big-data analytical platforms. Due to the heterogeneity of data being collected by the smart-cities, often with conflicting processing requirements, suitable analytical techniques depending upon the data type are also suggested. In addition to this, a generic four-tier big-data framework comprising of the sensing hub, storage hub, processing hub and application hub is also proposed that can be applied in any smart-city context. This is complemented by providing the common big-data applications in a smart-city and presentation of ten selected case studies of smart-cities across the globe. Finally, the open challenges are highlighted in order to give future research directions.
Internet of Things Based Smart Health Monitoring of Industrial Standard Motors Gayathri R.; Shriram K Vasudevan
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 6, No 4: December 2018
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (450.115 KB) | DOI: 10.52549/ijeei.v6i4.492

Abstract

The Industry 4.0 vision provides recommendations how companies can ease the challenges.  In an industrial environment, it is beneficial to  have a predictive approach to make smart industry using IoT. The Predictive approach includes automating the maintenance activities of machines which help to deliver safety, performance, customer experience, capacity, cost efficiency and sustainability of the key business assets.  It helps to improve work force safety which reduces the need to access the infrastructure, develop technologies to enable activities to be remotely controlled from safe areas and automate processes to remove manual tasks and helps to increase infrastructure reliability.  It also improves the precision and accuracy of data collection, introducing data analytics, removing human bias, improving reproducibility.  This will improve information about asset condition, inform inspection and repair schedules based  on asset risks. By implementing predictive and preventive maintenance, one can improve equipment life and avoid any unplanned maintenance activity and thus reducing unscheduled downtime.  We in this work have an unit which could be easily attached to the motor units and this does not demand any wiring to carried out. The sensor monitor signals from the motor, accurately measuring key parameters at regular interval of time, as desired.  And, the data is sent to the cloud, which in our case is adafruit.  From there, the data is analysed and it produces meaningful information. The  server then sends alert message to the users about critical data of machine.   This will help in fixing any technical issue with ease without incurring much delay.
Fast Denoising Filter for MRI using Parallel Approach Oza, Shraddha Dinesh; Joshi, Kalyani Rajiv
Indonesian Journal of Electrical Engineering and Informatics (IJEEI) Vol 6, No 4: December 2018
Publisher : IAES Indonesian Section

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52549/ijeei.v6i4.596

Abstract

Real time medical image processing is necessary in the domain of remote medical care, diagnostics and surgery. To provide fast MRI diagnostics especially for neuro imaging, the research work proposes CUDA GPU based fast denoising filter with a parallel approach. Bilateral filter is the most suitable candidate for denoising, as it has unique ability to retain contours of soft tissue structures of the brain. The work proposes improvised memory optimization techniques for the GPU implementation to achieve superior performance in terms of speed up when compared with existing work. For a 64Megapixel brain MR image, shared memory approach gives speed up of 256.5 while texture memory usage with tiling approach stands the next in speedup with 42.16 over its CPU counterpart. The results indicate that in spite of increase in image size, the execution time of the filter does not increase beyond 500msec keeping the performance real time.

Page 20 of 79 | Total Record : 783

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