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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 27, No 1: July 2022" : 64 Documents clear
Spectral efficiency and performance improvement of coherent optical transmission system Muthanna Ali Kadhim; Ali Yousif Fattah; Atheer Alaa Sabri
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp290-300

Abstract

This paper presents an orthogonal frequency division multiplexing (OFDM) for a long-haul optical transmission system with high-rate transferability to alleviate dispersion effects. In addition, we suggest combining polarization division multiplexing (PDM) with coherent OFDM (CO-OFDM) to increase spectral efficiency (SE). Based on OptiSystem (2021) version 18.0" software package, a 100 Gbps single-channel PDM-CO-OFDM transmission system is investigated using different modulation formats; bipolar phase keying (BPSK), quadrature phase shift keying (QPSK), Eight-Phase-Shift Keying modulators (8-PSK), and quadrature amplitude modulation (16-QAM). A 60 km span of standard single-mode fiber (SSMF) cable is employed in this investigation. The system's performance and spectral efficiency have been evaluated by comparing against the different modulation schemes. The outcomes that were got show that the BPSK modulation scheme has the longest transmission distance and requires a lesser level of optical signal to noise ratio (OSNR) at the receiver side. Concerning spectral efficiency, 16-QAM outperforms the others. Farther, the impact of employing ultra-low loss and large effective area fiber in reducing loss and nonlinear effects in the optical channel for 16-QAM modulation formats is examined. The result found that the system with advanced fiber has superior performance than the SSMF. The bit error rate (BER) of 0.033 (20% concatenated forward error correction (FEC) threshold) is used as a baseline.
Field programmable gate arrays implementation of different standard deviation estimation techniques Serwan Ali Bamerni; Ahmed Kh. Al-Sulaifanie
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp118-130

Abstract

Additive white Gaussian noise level estimation has found its application in many fields such as biomedical signal processing, communication system, and image processing. Many methods have been proposed with different output accuracy, system complexity, power consumption, and speed. In this paper, three of the most well-known and largely used algorithms (median based, root mean square (RMS) based, and P84 based methods) have been implemented and investigated in a full comparison between them to find their advantage and disadvantage, and the suitability of each method for a specific application. The three designs are created using Xilinx system generator (XSG) and implemented on Xilinx field programmable gate arrays (FPGA) development board with Zynq series "XC7Z020-1CLG484", to evaluate the design's performance and the results are discussed in the paper.
Integrated framework studying contribution of information system to firm performance Ansar Daghouri; Khalifa Mansouri
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp375-385

Abstract

The main purpose of this paper is to study the correlation between information system (IS) success and firm performance based on two evaluation models already construct. The first model allowed to define the criteria and sub-criteria for evaluating the firm performance and the second model consisted of evaluating the IS success. Our contribution is to formalize a decision-making process based on the criteria of the two models as well as the weights generated by the implementation of the analytic hierarchy process (AHP) method to construct the influence diagrams that will allow us to trace the causal links between the two models. This approach has been implemented in three sectors chosen according to their use of information systems. The results obtained confirmed that the evaluation models are sectorial and therefore even the influence diagrams, hence the difficulty of studying the contribution of the IS success in achieving the firm performance with a general and generic approach.
Short-term uncleaned signal to noise threshold ratio based end-to-end time domain speech enhancement in digital hearing aids Padmaja Nimmagadda; Kondru Ayyappa Swamy; Samuda Prathima; Sushma Chintha; Zachariah Callottu Alex
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp131-138

Abstract

This paper presents the improvements in the combined solution for the noise estimation and the speech enhancement in digital hearing aids in time domain. This study focuses on the single channel statistical temporal speech enhancement using adaptive Wiener filtering. In this technique, the noise is updated based on the short-term uncleaned signal to noise threshold ratio (ST-USNTR) of the frame. It works best if and only if the back ground noise level is low compared to that of speech of interest. We considered the time domain algorithms in order to consider the time varying nature of speech signal. The performance of the proposed algorithm is evaluated for speech signal with seven ty pes of noises and three signal to noise ratios (SNR) levels in each type of noise. From the results, it is clear that the basic level of adaptive speech enhancement is obtained using statistical parameters of noisy speech without the need for reference input.
Olive trees cases classification based on deep convolutional neural network from unmanned aerial vehicle imagery Noor Abdulhafed Sehree; Abdulsattar Mohammed Khidhir
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp92-101

Abstract

Unmanned aerial vehicles (UAVs) are one of the various aerial remote sensing platforms with ease of use and cost-effectiveness it can deliver high-resolution imaging, obtained using a variety of sensors. Photogrammetric data is derived by the use of unmanned aerial systems (UAS, which consists of a UAV, sensor(s), and base station). As a result of these types, vegetation monitoring is conceivable. Deep neural networks have had a lot of success with image classification tasks, especially in the remote sensing field. In this paper, we demonstrate how deep neural networks can be used to classify olive trees status from aerial images. We have addressed a multi-class classification problem. In this work five different neural network architectures: VGG16, ResNet50, MobileNet, Xception, and VGG19 had been compared. Transfer learning had been accomplished using training of the fully connected layer(s) at the end of the deep learning layers. We used metrics such as accuracy, precision, recall, and confusion metric to evaluate the results. With accuracy, our model achieves the best results using ResNet50 with an accuracy is (97.2%).
Augmentation of contextual knowledge based on domain dominant words for IoT applications interoperability Prakash Shanmurthy; Poongodi Thangamuthu; Balamurugan Balusamy; Seifedine Kadry
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp504-512

Abstract

Semantic web technology is adapted to the internet of things (IoT) for web - based applications to globally connect the services. Web ontology language (OWL) domain ontology is a powerful machine - readable language for domain knowledge representation. The developer stored the IoT application relevant ontology in a repository or catalogue. Hence, IoT application - related ontology files are available for reus e, but many of the IoT application - relevant ontology files are publicly not available or inaccessible. The proposed idea is to extract the contextual knowledge of IoT applications that contain inaccessible ontology files. The context - wise specific domain I oT applications are not obtainable, hence respective ontology - based research papers are identified and their frequent terms are computed. The selected contextual dominant frequent terms from the transport domain are passed into the skip - gram flavour of wor d2vector modelled n atural language processing ( NLP ) corpus which produces most similar terms. The domain experts select the appropriate terms to annotate in OWL ontology for contextual knowledge augmentation. Finally, 1422 contextual terms were generated b ased on dominant terms of selected IoT applications.
Economic-emission load dispatch for power system operation using enhanced sunflower optimization Hazwani Mohd Rosli; Syahirah Abd Halim; Lilik Jamilatul Awalin; Seri Mastura Mustaza
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp1-10

Abstract

Conventional thermal power plant uses limited sources of gas, fuel or coal which contributes to the rise of air pollution. Thus, it is crucial to efficiently use the natural sources and minimize the emissions of greenhouse gases and other pollutants. This paper presents an optimal economic dispatch considering three factors which are cost of generation, loss of power transmission and amount of emission for an efficient operation of power generation. Enhanced sunflower optimization (ESFO) algorithm is applied to determine the solution for three different cases: economic load dispatch, emission load dispatch and economic-emission load dispatch. The optimal solution based on the minimum generation cost and emission is obtained for the IEEE 6-unit test system using MATLAB software
Internet of things based mobile application to improve citizen security Yulihño Ochante-Huamaccto; Francis Robles-Delgado; Fernando Sierra-Liñan; Michael Cabanillas-Carbonell
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp386-394

Abstract

Citizen insecurity is a social problem that has increased considerably around the world. To combat it, in this research a mobile application based on IOT has been developed with the objective of mapping crimes and incident alerts to improve citizen security. Scrum methodology was used and a significant improvement can be seen with respect to the following indicators: number of reports of dangerous places, with an increase of 102.7%; the second indicator: number of reports by type of crime, with an increase of 25.34%; and the indicator: response time to attention, with an increase of 23.5%. It is determined that there is a significant positive influence of the mobile application developed to improve citizen security.
Blending of three-dimensional geometric model shapes Seng-Beng Ng; Kok-Why Ng; Rahmita Wirza O.K. Rahmat; Yih-Jian Yoong
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp102-109

Abstract

Three-dimensional (3D) geometric model shapes blending method can create various in-between models from two inputs of models shapes. Though, many blended shapes are implausible due to different inputs of model type, inappropriate matching-parts, improper parts-segmentation, and non-tally number of segmentation parts. are crucial and should be taken into account. The objective of this paper is to study the strengths and weaknesses of some prominent shapes blending methods and the 3D reconstruction methods. An interpolated shape blending program using the Laplacian-based contraction and Slinky-based segmentation method is developed to illustrate the critical problems arise in the shape blending process. Output results are to be compared with some prominent existing methods and one will observe the potential research direction in the blending research work
IoT-based communal garbage monitoring system for smart cities Nur Latif Azyze Mohd Shaari Azyze; Ida Syafiza Md Isa; Thomas See Chin
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 1: July 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i1.pp37-43

Abstract

In Malaysia, approximately 38,000 metric tons of garbage are generated due to human daily activities. This is due to the growing population in the urban area, hence increasing the tendency of overflowing garbage due to the insufficient space in the garbage container. In addition, the tight schedule of the garbage collection allows the spreading of the toxic odor as the garbage start to rotten up, hence leading to air pollution. Therefore, a systematic waste management system is important to provide a healthy and clean environment to the community. In this work, a communal garbage monitoring system has been developed to notify the administrator of the status of the container. Besides monitoring the level of garbage, the system is also designed to monitor the temperature, humidity, and air quality of the garbage container. These monitored data will be uploaded at the cloud for real-time monitoring. Compared to the other work, a real test-bed implementation has been conducted considering different types of waste including food waste, paper, bottles and metal; to determine the accuracy of the developed system. The results show that the system has high reliability and high accuracy with 96% for food waste and 98% for other types of waste.

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