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An extensive review of energy storage system for the residential renewable energy system
M. S. A. Mustaza;
M. A. M. Ariff;
Sofia Najwa Ramli
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v18.i1.pp242-250
Energy storage system (ESS) plays a prominent role in renewable energy (RE) to overcome the intermittent of RE energy condition and improve energy utilization in the power system. However, ESS for residential applications requires specific and different configuration. Hence, this review paper aims to provide information for system builders to decide the best setup configuration of ESS for residential application. In this paper, the aim is to provide an insight into the critical elements of the energy storage technology for residential application. The update on ESS technology, battery chemistry, battery charging, and monitoring system and power inverter technology are reviewed. Then, the operation, the pro, and cons of each variant of these technologies are comprehensively studied. This paper suggested that the ESS for residential ESS requires NMC battery chemistry because it delivers an all-rounded performance as compared to other battery chemistries. The four-stages constant current (FCC) charging technique is recommended because of the fast charging capability and safer than other charging techniques reviewed. Next, the battery management system (BMS) is recommended to adapt in advance machine learning method to estimate the state of charge (SOC), state of health (SOH) and internal temperature (IT) to increase the safety and prolong the lifespan of the batteries. Finally, these recommendations and solutions aimed to improve the utilization of RE energy in power system, especially in residential ESS application and offer the best option that is available on the shelf for the residential ESS application in the future.
A review on vehicle to vehicle communication system applications
Hussein Ali Ameen;
Abd Kadir Mahamad;
Sharifah Saon;
Danial Md. Nor;
Kareem Ghazi
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v18.i1.pp188-198
The field of automated vehicle technology is developing rapidly developing. While it is likely to be many years before self-driving cars are commercially viable and used in a wide range of conditions by the general public, technological advances are speeding along the automated technology continuum towards this destination. Automated vehicle technologies troth with significant social benefits such as reduced injuries and deaths, increased road efficiency, mobility. Automated vehicles can improve traffic safety, balance traffic flows, maximize road usage by offering driver warnings and/or assuming vehicle control in dangerous situations, as well as provide motorists with the best end-to-end transportation experience and reduce emissions, which are the most important goals of modern smart traffic control infrastructures. Exchanging data and integration of such systems with Vehicle-to-Vehicle (V2V) may be a keystone to successful readying of vehicular ad-hoc networks (VANETs) and will simply be the following step of this evolution, with dynamic period of time data exchange between all the players of the traffic dominant system and fostering cooperative urban quality. One of the applications of this concept is to provide vehicles and roads with the ability to make road time more enjoyable and also to make roads safer. These applications are typical examples of what an Intelligent Transportation System (ITS) is called, whose objective is to improve security by using new information and communication technologies (NTIC). In this paper, we will focus on the study of the main component in ITS systems and present a review of the major V2V benefits related to driver safety by focusing primarily on the recent developments of these systems.
Denoising of MRI images using fast NLM
Vandana Hanchate;
Kalyani Joshi
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v18.i1.pp135-141
Denoising of image is a very crucial step which should retain fine details but should remove noise. Making the difference between noise and actual edge related data is very difficult. NLM filter helps to make a differentiation between image data and noise data. Its weight function decides the weightage of the neighboring pixel depending upon the similarity with the pixel to process. It helps to retain the edges and avoid it from smoothening. This paper discusses the implementation of NLM filter using hardware platform Spartan 6. After implementaion of this on FPGA, not only denoise the image but preseve edges and there is a tremendous saving in time compared to its matlab implementation. Denoised image performance is calculated using various objective metrics such as MSE, PSNR, SSIM, PFOM etc. FPGA implementation shows clearly the advntages over its matlab implementation.
Foreign exchange prediction based on indices and commodities price using convolutional neural network
Rian Rassetiadi;
Suharjito Suharjito
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v18.i1.pp494-501
The level of accuracy in predicting is the key in conducting forex trading activities in gaining profits. Some predictions are made only by using historical currency data to be predicted, this makes predictions less accurate because they do not consider external influences. This study examines external factors that can influence the results of predictions, by looking for the relationship between the value of indices such as NTFSE and S & P 500 and the value of commodities such as gold and silver to the prediction process of EUR / USD. Prediction carried out using a deep learning algorithm with the Convolutional Neural Network method uses 2 1-dimensional convolution layers with ReL activation. The data used is the value of Open, High, Low and Close prices on forex, indices and commodities which are combined into one with the close forex value target for the next 5 days. Testing of EUR / USD test data only gets MSE results of 0.00081894. While the results of testing of the combined test data between EUR / USD, indices and commodities producing MSE vary between 0.00068717 to 0.0109606 where the best combination is a combination of FTSE 100 and Natural Gas values. So it can be concluded that other factors included in predicting have an influence on the results obtained.
Retina blood vessel extraction based on kirsch’s template method
Nur Syazlin Zolkifli;
Ain Nazari;
Mohd Marzuki Mustafa;
Wan NurShazwani Wan Zakaria;
Nor Surayahani Suriani;
Wan Nur Hafsha Wan Kairuddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v18.i1.pp318-325
Analysis on the retina blood vessels from fundus images have been widely used in the medical community to detect the disorder condition in the blood vessels. An automated tracing of retina blood vessel can help to provide valuable computer-assisted diagnosis for the ophthalmic disorders. Thus, it helps to reduce the time for the ophthalmologist to analyses and diagnose the result of the fundus image of patient. The purpose of this research is to build an algorithm to trace the retina blood vessels. The method to be used in this research consist of two parts which are the pre-processing part and the feature extraction by using the Kirsch’s template. Combining the pre-processing at the early stage and feature extraction at the next stage is applied to extract the edges of the blood vessels. The proposed algorithm was verified by using two online databases, DRIVE and HRF to validate the performance measures. Hence, proposed method is capable to extract the retina blood vessel and give the accuracy of 0.7917, the sensitivity of 0.9077 and the specificity of 0.7215. In conclusion, the extraction of the blood vessels is highly recommended as the early screening stage for the eye diseases beneficially.
Robust control of a UPFC system with H~ control technique
Maamar Benyamina;
Mohamed Bouhamida;
Tayeb Allaoui;
Rachid Taleb;
Mouloud Denai
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v18.i1.pp533-543
FACTS (Flexible AC Transmission Systems) technology has now been accepted as a potential solution to the stability problem and load flow. The Unified Power Flow Controller (UPFC) is considered to be the most powerful and versatile among all FACTS devices. This paper presents the control of a UPFC system using Hinf robust control technique. A simulation study using Matlab/Simulink is presented to the performance of this control strategy and the robustness with respect to variations of the system parameters such as the inductance of the transmission line.
A new modification nonlinear conjugate gradient method with strong wolf-powell line search
Chergui Ahmed;
Bouali Tahar
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v18.i1.pp525-532
The conjugate gradient method has played a special role in solving large-scale unconstrained Optimization problems. In this paper, we propose a new family of CG coefficients that possess sufficient descent conditions and global convergence properties this CG method is similar to (Wei et al) [7]. Global convergence result is established under Strong Wolf-Powell line search. Numerical results to find the optimum solution of some test functions show the new proposed formula has the best result in CPU time and the number of iterations, and the number of gradient evaluations when it comparing with FR, PRP, DY, and WYL
Detection of partially overlapped masses in mammograms
Mustafa Haitham Alhabib;
Omar Haitham Alhabib
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v18.i1.pp235-241
Breast cancer remains one of the major causes of cancer deaths among women. For decades, screening mammography has been one of the most common methods for early cancer detection and diagnosis. Digital mammography images are created by applying a small burst of x-rays that pass through the breast to a solid-state detector, which transmits the electronic signals to a computer to form a digital image. However, due to projection, some mass areas may be partially covered, which makes them difficult to be interprated. This paper addresses the issue of potential mass regions being distorted by other normal breast tissues, which will negatively affect some of the features being extracted from the mass and in turn deteriorate the classification accuracy. The goal was to estimate the overlapped parts of the mass border using Euclidean distance in order to give more accurate results in next stages. The presented method achieved 95.744% region sensitivity at 0.333 False Positive per Image (FPI), outperforming other researches in this branch of mammography analysis.
Internet of things-based (IoT) inventory monitoring refrigerator using arduino sensor network
jessica Velasco;
Leandro Alberto;
Henrick Dave Ambatali;
Marlon Canilang;
Vincent Daria;
Jerome Bryan Liwanag;
Gilfred Allen Madrigal
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v18.i1.pp508-515
This study presents a system that combines a conventional refrigerator, microcontrollers and a smart phone to create an inventory monitoring that can monitor the stocks inside the refrigerator wirelessly by accessing an Android application. The developed refrigerator uses a sensor network system that is installed in a respective compartment inside the refrigerator. Each sensor will transmit data to the microcontrollers, such as Arduino Yun and Arduino Uno, which are interconnected by the I2C communications. All data and images will be processed to provide the user an Internet of Things application through the cloud-based website Temboo. Temboo will have access to send data to the Dropbox. A smartphone is connected to the Dropbox where all the data and images are stored. The user can monitor the stocks or contents of the refrigerator wirelessly using an Android Application.
A study of packet scheduling algorithms in long term evolution-advanced
Mohd Mueen Ul Islam Mattoo;
Huda Adibah Mohd Ramli
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science
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DOI: 10.11591/ijeecs.v18.i1.pp516-524
The allocation of radio resources is one of the most critical functions performed by the Radio Resource Management (RRM) mechanisms in the downlink Long Term Evolution – Advanced (LTE-Advanced). Packet scheduling concerns itself with allocation of these radio resources in an intelligent manner such that system throughput/capacity can be maximized whilst the required multimedia Quality of Service (QoS) is met. Majority of the previous studies of packet scheduling algorithms for LTE-Advanced did not take the effect of channel impairments into account. However, in real world the channel impairments cannot be obliterated completely and have a direct impact on the packet scheduling performance. As such, this work studies the impact of channel impairments on packet scheduling performance in a practical downlink LTE-Advanced. The simulation results obtained demonstrate the efficacy of RM2 scheduling algorithm over other scheduling algorithms in maximizing the system capacity and is more robust on the effect of the cellular channel impairments.