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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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Multiplatform system oriented to telemedicine Elizabeth Arelli Liñan Espinoza; Erich Jordy Echevarría Carpio; Laberiano Andrade-Arenas
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1687-1699

Abstract

The research arises from the need that was seen in people in recent years due to COVID-19, since remote medical care was required to avoid contagion, that it was developed with the Flutter tool and it is oriented towards telemedicine, which provides a medical evaluation service between patients and doctors. For the development of the methodology, the agile methodology of extreme programming "XP" was implemented, since it is of great help for the development of the system, the proto-types, and their different phases, since, compared to other methodologies, XP was the that gave more results in less time, which allowed us to have a faster development. The objective of the research is to implement a multiplatform system oriented to expert telemedicine. It has been possible to develop a basic demonstration of the system that would be the video calls, one of the most important functions of the entire system, and its operation has been effective as has been demonstrated in the results of this project, in which it was carried out carried out a survey of 50 questions and 95% agreed with the multiplatform system, since it would be of great help for several people.
Variational selective segmentation model for intensity inhomogeneous image Tammie Christy Saibin; Abdul Kadir Jumaat
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 1: January 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i1.pp277-285

Abstract

Variational selective image segmentation models aim to extract a particular object in an image depending on a set of user-defined prior points. The current model suffers from high computational costs due to the traditional total variation function that results in a slow segmenting process. In addition, it is not designed to segment images with intensity inhomogeneities. In this research, we formulate a new variational selective image segmentation model based on the Gaussian function. A Gaussian function is proposed to replace the traditional total variation function to regularize the variational level set function. To segment images with intensity inhomogeneities, the local image fitting idea was in corporate into the formulation. The efficiency of the proposed model was then assessed by recording the computation time while the accuracy was measured using Jaccard and Dice similarity values. Numerical experiments using synthetic, natural, and medical images demonstrate that the proposed model is about 6 times faster than the existing model, while the Jaccard and Dice values are about 11% and 7% higher, respectively, compared to the existing model. In the future, this research can be extended further into a 3-dimensional modeling and vector-valued image framework.
Missing values imputation in Arabic datasets using enhanced robust association rules Awsan Salem; Nurul Akmar Emran; Azah Kamilah Muda; Zahriah Sahri; Abdulrazzak Ali
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp1067-1075

Abstract

Missing value (MV) is one form of data completeness problem in massive datasets. To deal with missing values, data imputation methods were proposed with the aim to improve the completeness of the datasets concerned. Data imputation's accuracy is a common indicator of a data imputation technique's efficiency. However, the efficiency of data imputation can be affected by the nature of the language in which the dataset is written. To overcome this problem, it is necessary to normalize the data, especially in non-Latin languages such as the Arabic language. This paper proposes a method that will address the challenge inherent in Arabic datasets by extending the enhanced robust association rules (ERAR) method with Arabic detection and correction functions. Iterative and Decision Tree methods were used to evaluate the proposed method in an experiment. Experiment results show that the proposed method offers a higher data imputation accuracy than the Iterative and Decision Tree methods.
Quantification of retinal artery-vein ratio for vascular disease diagnosis using spatial U-Net Lakshmi Kala Pampana; Manjula Sri Rayudu
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1404-1411

Abstract

The retinal vascular morphological caliber changes reveal the signs of systemic health disorder and life threat diseases such as cardio and cerebral diseases. The quantitative vascular parameters like narrowed arteries, widened venules, reduced artery-vein ratio (AVR) have been associated with aforesaid disorders and diseases. Hence the quantitative biomarker AVR is important parameter in diagnosing variety of diseases. The accurate quantification of AVR be possible if and only if accurate classification of arteries and vein is done. In this paper, we proposed a deep learning based robust vessel segmentation and classification algorithm based on spatial U-Net and the accuracy of the algorithm is 97.8%. In the quantification process, this algorithm is applied on region of interest (RoI) of a fundus image and measured the AVR values using central retinal artery equivalent (CRAE) and central retinal vein equivalent (CRVE). The experimentation is carried on the digital retinal images for vessel extraction (DRIVE) dataset. The outcome of this work is the AVR observed to be >0.4 in normal retinal case and AVR value <0.4 for unhealthy case.
Passively Q-switched erbium doped fiber laser based on graphene and carbon nanotube saturable absorbers Mahroof Mohamed Mafroos; Husni Hani Jameela Sapingi; Azura Hamzah
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 1: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i1.pp227-233

Abstract

A passively Q-switched erbium-doped fiber laser (EDFL) was experimented on by employing graphene, single walled carbon nanotubes (SWCNT) and multi-walled carbon nanotube (MWCNT) saturable absorbers (SA). The SA film was obtained by embedding the graphene, SWCNT and MWCNT into polyvinyl alcohol (PVA). The graphene SA was prepared by dipping a PVA thin film into the graphene solution while carbon nanotubes SAs were prepared using the casting method and placed in the ring cavity to produce a stable pulse laser. Graphene, SWCNT and MWCNT SAs were operating at wavelengths of 1558.92 nm, 1557.98 nm and 1558.51 nm, respectively, whereas the continuous wave was 1560.72 nm at the input pump power of 56 mW. The pulse energy, output power, repetition rate and pulse width were compared in graphene, SWCNT and MWCNT SAs. The shortest pulse width retrieved in graphene, SWCNT and MWCNT were 3.90 µs, 3.62 µs 4.43 µs and produced at the repetition rate of 115.00 kHz, 130.70 kHz, and 89.13 kHz, respectively. In comparison to graphene and SWCNT SAs, MWCNT SAs exhibit the best performance in terms of output power of 2.19 mW and high pulse energy of 24.57 nJ in passively Q-switched EDFL.
A quad-port multiple-input-multiple-output system for underlay or interweave cognitive radio Laith Wajeeh Abdullah; Qasim Hadi Kareem; Adheed Hasan Sallomi
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 3: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i3.pp1480-1495

Abstract

This paper presents a four-element frequency reconfigurable antenna system that is novel in terms of gathering both underlay and interweave cognitive radio in a single multiple input, multiple output (MIMO) design. Built on a 50×38×0.8 mm3 Rogers RT/Duroid 5880 substrate, this system is constructed of two scanning elements to sense ultra-wide band (UWB) with controllable band notching capabilities and two elements act as communication antennas. Eighteen MIMO modes can be provided depending on the state of the five positive-intrinsic-negative (PIN) diodes in each sensing antenna and the four PIN diodes in each communication antenna. These include a scanning UWB mode, fourteen modes to notch WiMax/Cband/wireless local area network (WLAN)/Xband/ITU in single/dual/triple/quad band rejection states and three interweave modes where each targeting one of the regions of WiMax/Cband/WLAN. Simulated by CST v.10; results like input reflection coefficient and realized gain verify system's capability to work in each operation mode. Moreover, mutual coupling, envelope correlation coefficient and diversity gain all evidence the performance of the proposed system as a MIMO system. Results, simple and compact profile, wide and flexile range of MIMO operation modes in line with the novelty to handle both underlay and interweave cognitive radio all nominate this system as promising to fulfill the needs of modern wireless communications.
An electric power generation improvement for small Savonius wind turbines under low-speed wind Kwanjai Nachaiyaphum; Chonlatee Photong
Indonesian Journal of Electrical Engineering and Computer Science Vol 29, No 2: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v29.i2.pp618-625

Abstract

Savonius wind turbines have advantages of self-rotating at low speed wind, high starting torque, and less noise generation. However, they have low electric power generation capacity. This paper presents electric power generation improvement for small Savonius wind turbines when operating at low-speed wind of 1-6 m/s by using optimal Bach-type blades, twist blades and a wind tunnel. The turbine prototypes with the optimum diameter and height of 32 cm were developed with 3 different blade types: conventional semicircular blades, Bach-type blades and twisted 15° blades and a wind tunnel. The experimental results showed that the Savonius wind turbine with Bach-type generated highest electric voltage, which was 19.3% and 7.6% higher compared to conventional blades and twisted 15° blades. The additional wind tunnel could improve electric power generation efficiency by approximately 21.4% compared to the turbines without the tunnels.
A bio inspired maximum power point tracking controller for PV systems under partial shading conditions Titri Sabrina; Azli Hadjer; Izeboudjen Nouma; Larbes Cherif
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 3: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i3.pp1425-1436

Abstract

Maximum power point tracking (MPPT) is a technique used in extracting the maximum power from a photovoltaic panel (PV) under different weather conditions. The last decade has witnessed a wide variety of algorithm based on MPPT controllers, ranging from simple to more complexe ones. Each of them has its own advantage and disadvantage. Hence, it is crutial to propose methods that are both simple and effective to track and maintain the MPPT of a PV system, even under partial shading conditions. In this study, we propose a new bio inspired method namely seagull optimization algorithm (SOA) for solving the MPPT problem in a PV system. To evaluate the proposed SOA _MPPT performance in terms of accuracy, convergence and stability, a simulation methodology is used. First, by tunning the appropriate parameters, then, we consider the following scenarios: rapid change of solar irradiation, temperature, and three patterns to test partial shading effect. The results are compared with latest bio-inspired methods, namely, particle swarm optimization (PSO), Bat optimisation algorithm (BAT) and fire fly algorithm (FA). The obtained results confirm the effectiveness and robustness of the proposed controller compared to existing conventional and bio inspired controllers.
Using a new coefficient conjugate gradient method for solving unconstrained optimization problems Ranen M. Sulaiman; Basim A. Hassan
Indonesian Journal of Electrical Engineering and Computer Science Vol 27, No 3: September 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v27.i3.pp1642-1648

Abstract

The conjugate gradient technique is a numerical solution strategy for finding minimization in mathematics. We present a simple, straightforward, efficient, and resilient conjugate gradient technique in this study. To address the convergence difficulty and descent property, the new technique is built on the quadratic model. Under some assumptions, the new improved approach meets the convergence characteristics and the adequate descent criterion. The suggested unique strategy is substantially more efficient than the classic FR method, according to our numerical analysis. The number of function evaluations, iterations and restarts are all included in the numerical results. The computational efficiency of the proposed approach is proved by comparative results.
The different approach for supercapacitor modelling in the perspective of self-discharge study Muhammad Abdul Jabbar Bin Abu Bakar; Muhammad Izuan Fahmi; Shamshul Bahar Yaakob; Liew Hui Fang; Muhammad Zaid Aihsan
Indonesian Journal of Electrical Engineering and Computer Science Vol 28, No 2: November 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v28.i2.pp663-673

Abstract

Supercapacitor is a relatively new type of electric component used to store energy compared to a battery. Supercapacitor charge and discharge cycle are faster compared to the battery along with higher power density which increase its application in recent years. However, supercapacitors have quite high self-discharge compared to batteries. This makes energy stored in supercapacitor decrease faster over time when not in use. Various study has been done towards the self-discharge behavior of SC which is both experimentally and in simulation. The simulation is done by various methods and models which have been proposed by previous researchers. Most of the methods that have been used were based on the Equivalent Circuit Model as it is the easiest method available. However, there is still another method proposed such as the Fractional-order model. This paper will review some of the methods and models used to study self-discharge behavior.

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