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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 9,174 Documents
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Development of mini smart multipurpose vehicle for organic rice harvesting Kanchana Daoden; Sureeporn Sringam; Supanat Nicrotha; Thanawat Sornnen
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp152-159

Abstract

This research aimed to develop the mini smart multipurpose vehicle (MSMPv) innovative from the conventional agriculture tractor for three objectives. The novel automatic gear modified technique for the MSMPv is proposed, then an idea to enhance peripheral capability through a hitch system. The final purpose is to support the farmer's ability to follow organic agriculture regulations on the issue of contaminated tools and machinery, especially in the rules related to contamination of equipment or machines that cannot share with conventional agricultural production. The organic rice crop plot of Nong Bua Lamphu Province in Thailand has been set to the case study. Here, farmers faced problems; lack of labour, production under an organic system that does not permit chemicals, and limited harvesting. According to the existing technology, this research has developed a typical farm tractor used in the country by inventing a manual transmission engine to an automatic transmission and accessories such as remote control, GPS, camera, and sensors. Thus, the development of this organic rice harvesting prototype should be an approach that provides both the opportunity to raise the self-reliance concept and enhance the knowledge of the development of innovative tools for farmers simultaneously.
Linear frequency modulated reverberation suppression using time series models Jami Venkata Suman; Mamidipaka Hema; Bandi Jagadeesh
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1395-1401

Abstract

When active radar and sonar systems are used for target detection and tracking, boosting target detection, and tracking efficiency is the most important challenge in real-time reverberation. To eliminate reverberation when transmitting linear frequency modulated (LFM) signals, this study employs time series techniques such as autoregressive (AR), moving average (MA), and autoregressive moving average (ARMA). The primary purpose of this research is to whiten LFM reverberation by transforming it to a fractional domain using the fractional Fourier transform (FrFT). The LFM reverberation is a highly coloured noise whose frequency fluctuates according to the stationary hitting frequency. As a reference signal, the proposed methods make use of the adjacent signal block. The effectiveness of FrFT-based AR, MA, and ARMA pre-whitening for LFM reverberation reduction was assessed, and the results were presented.
Low-cost nitrogen dioxide monitoring station based on metal oxide sensor and cellular network Rady Purbakawaca; Arief Sabdo Yuwono; Husin Alatas; I Dewa Made Subrata
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp105-115

Abstract

Air pollution has a negative impact on the environment and human health. Meanwhile, the number of conventional air quality monitoring stations is minimal due to high procurement and operational costs. This study proposes a nitrogen dioxide (NO2) pollutant measurement system using the metal oxide sensor (MOX) sensor and cellular network for data transmission in the measurement area. A calibration curve is used to measure NO2 levels based on the sensor's internal resistance changes. Measurement data of NO2 concentration, air temperature, relative humidity, and geospatial information are compiled and sent via global positioning system (GSM), general packet radio service (GPRS) radio communication with transmission intervals of every minute. The database server processes the data and displays it on the web application. System testing results at the Tugu Kujang Bogor at 15:38:00-16:38:00 September 23, 2021, showed that the concentration of NO2 ranged from 0.16-0.52ppm with an average of 270 ppb with an AQI of 133 in the unhealthy category for the sensitive group. The measured NO2 levels are outside the range of the NO2 concentration database in the industrial areas of Bogor and Jakarta for the 2016-2020 period. Therefore, this system provides an excellent opportunity to obtain real-time measurement data in the field.
Girth aware normalized min sum decoding algorithm for shorter length low density parity check codes Abdelilah Kadi; Hajar El Ouakili; Rachid El Alami; Said Najah
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1692-1700

Abstract

Recently, short block codes are in great demand due to the emergent applications requiring the transmission of a short data unit and can guarantee speedy communication, with a minimum of latency and complexity which are among the technical challenges in today’s wireless services and systems. In the context of channel coding using low density parity check (LDPC) codes, the shorter length LDPC block codes are more likely to have short cycles with lengths of 4 and 6. The effect of the cycle with the minimum size is that this one prevents the propagation of the information in the Tanner graph during the iterative process. Therefore, the message decoded by short block code is assumed to be of poor quality due to short cycles. In this work, we present a study of the evolution of the messages on check nodes during the iterative decoding process when using the LDPC decoding algorithm normalized min sum (NMS), to see the destructive effect of short cycles and justify the effectiveness of the girth aware normalized min sum (GA-NMS) decoding LDPC codes algorithm in terms of correction of the errors, particularly for the codes with short cycles 4 and 6. In addition to this, the GA-NMS algorithm is evaluated in terms of bit error rate performance and convergence behavior, using wireless regional area networks (WRAN) LDPC code, which is considered as a short block code.
Low power residue number system using lookup table decomposition and finite state machine based post computation Balaji Morasa; Padmaja Nimmagadda
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp127-134

Abstract

In this paper, memory optimization and architectural level modifications are introduced for realizing the low power residue number system (RNS) with improved flexibility for electroencephalograph (EEG) signal classification. The proposed RNS framework is intended to maximize the reconfigurability of RNS for high-performance finite impulse response (FIR) filter design. By replacing the existing power-hungry RAM-based reverse conversion model with a highly decomposed lookup table (LUT) model which can produce the results without using any post accumulation process. The reverse conversion block is modified with an appropriate functional unit to accommodate FIR convolution results. The proposed approach is established to develop and execute pre-calculated inverters for various module sets. Therefore, the proposed LUT-decomposition with RNS multiplication-based post-accumulation technology provides a high-performance FIR filter architecture that allows different frequency response configuration elements. Experimental results shows the superior performance of decomposing LUT-based direct reverse conversion over other existing reverse conversion techniques adopted for energy-efficient RNS FIR implementations. When compared with the conventional RNS FIR design with the proposed FSM based decomposed RNS FIR, the logic elements (LEs) were reduced by 4.57%, the frequency component is increased by 31.79%, number of LUTs is reduced by 42.85%, and the power dissipation was reduced by 13.83%.
Applying reinforcement learning for random early detection algorithm in adaptive queue management systems Ayman Basheer Yousif; Hassan Jaleel Hassan; Gaida Muttasher
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1684-1691

Abstract

Recently, the use of internet has been increased all around the hose, the companies, government departments and the video games and so on. Thus, this increased the traffic used in the networks, which generated congestion issues and sent packet drop in the nodes. To solve this problem, certain algorithms are used. The Active queue management is one of the most important algorithms that helps with this issue. For an effective network management, the RL was used, and it will adapt with the parameters of algorithms. Where the suggested algorithm deep Q-networks (DQN) depends on the reinforcement learning (RL) to reduce the drop and delay. Also, the random early detection (RED) (an active queue management (AQM) algorithm) was adopted based on the NS3 situation.
Spam detection by using machine learning based binary classifier Mohd Fadzil Abdul Kadir; Ahmad Faisal Amri Abidin; Mohamad Afendee Mohamed; Nazirah Abdul Hamid
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 1: April 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i1.pp310-317

Abstract

Because of its ease of use and speed compared to other communication applications, email is the most commonly used communication application worldwide. However, a major drawback is its inability to detect whether mail content is either spam or ham. There is currently an increasing number of cases of stealing personal information or phishing activities via email. This project will discuss how machine learning can help in spam detection. Machine learning is an artificial intelligence application that provides the ability to automatically learn and improve data without being explicitly programmed. A binary classifier will be used to classify the text into two different categories: spam and ham. This research shows the machine learning algorithm in the Azure-based platform predicts the score more accurately compared to the machine learning algorithm in visual studio, hybrid analysis and JoeSandbox cloud.
Unbalance compensation topology for railway application based on pulse width modulation alternating current chopper Ismail Mir; Anas Benslimane; Jamal Bouchnaif; Badreddine Lahfaoui
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i3.pp1235-1246

Abstract

This paper focuses the study on the design of a new topology of unbalance compensators adopted by railway operators in the substations of high-speed railway lines, this compensation structure based on the concept of alternating current (AC)-chopper controlled impedance (CCI). The present document describes the CCI compensator in terms of the components constituting this structure, the installation of CCI to limit the unbalance factor according to the limit imposed by the moroccan energy provider (ONEE), and the calculation of the power losses generated by the CCI and the comparison with other topologies such as voltage source inverter STATCOM (VSI) and current source inverter STATCOM (CSI). The modelization of the compensator and the results were established using MATLAB/Simulink software by exploiting real data provided by the moroccan railway office (ONCF).
Improving the quality of service in wireless sensor networks using an enhanced routing genetic protocol for four objectives Mahmoud Moshref; Rizik Al-Sayyed; Saleh Al-Sharaeh
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp1182-1196

Abstract

Multi-objective algorithms are used to achieve high performance for quality of service (QoS) in wireless sensor networks (WSNs) is an important field for researchers because these algorithms improve two or more conflicting objectives and present the best trade-off between the conflicting objectives to solve multi-objective problems (MOPs). Previous research proposed an algorithm that relies on non-dominated sorting genetic algorithm 3 (NSGA-III), namely enhanced non-dominated sorting genetic routing algorithm (ENSGRA). This algorithm is used to optimise three objectives, which include number of worked sensors, energy consuming and node covering area. The fourth objective, which is node load balancing, is added in the current research. Such an addition aims to improve node distribution around cluster heads and decrease network congestion, thus decreasing energy consumption and increasing network lifetime. The ENSGRA algorithm is compared with multi-objective multi-step particle swarm optimisation (MOMSPSO), non-dominated sorting genetic algorithm 2 (NSGA-II), and NSGA-III. The proposed algorithm ENSGRA exceed to MOMSPSO, NSGA-II, and NSGA-III in the proposed QoS model in the final outcomes, as the proposed approach achieved (38%) average combination (optimisation) percentage. Which is the highest percentage over other methods.
Medicine prediction based on doctor’s degree: a data mining approach Md Shohel Arman; Kaushik Sarker; Asif Khan Shakir; Shah Fahad Hossain; Afia Hasan
Indonesian Journal of Electrical Engineering and Computer Science Vol 26, No 2: May 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v26.i2.pp1125-1134

Abstract

The effective use of information mining in profoundly unmistakable fields like e-business, promoting and retail has prompted its application in different enterprises. There is an absence of powerful investigation devices to find concealed connections and patterns in information. This examination paper expects to give a review of ebb and flow systems of learning revelation in databases utilizing information mining strategies that are being used in today’s therapeutic research especially in medicine prediction. Correlation, Chi-square and Euclidean distance feature selections are used to select features and showing the comparison of the result between K-Nearest neighbors, Naïve Bayes, decision tree, artificial neural network. The result uncovers that decision tree beats and sometime Bayesian grouping is having comparative precision as of choice tree. The analysis of performance can be done in such as doctor’s degrees may vary the diseases medicine.

Page 654 of 918 | Total Record : 9174

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