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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 63 Documents
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Search results for , issue "Vol 33, No 1: January 2024" : 63 Documents clear
Retinal lesions classification for diabetic retinopathy using custom ResNet-based classifier Silpa Ajith Kumar; James Satheesh Kumar
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp405-415

Abstract

Failure to diagnose and treat retinal illnesses on time might lead to irreversible blindness. The focus is on three common retinal lesions associated with diabetic retinopathy (DR): microaneurysms (MAs), haemorrhages, and exudates. The proposed solution leverages deep learning, employing a customized residual network (ResNet) based classifier trained on real-time retinal images meticulously annotated and graded by ophthalmologists. Annotation noise was a significant obstacle addressed by downsampling and augmenting the data. Compared to cutting-edge techniques, this one performs better with test-set accuracy of 93.34% across all classes. This approach holds great promise for enhancing early detection and treatment of DR by automating the recognition of these vital retinal abnormalities. The ability to automatically classify these symptoms can aid clinicians in making more precise diagnosis and starting treatments sooner. This research shows that deep learning-based approaches are highly effective, especially when combined with a customised ResNet-based classifier and thorough pre-processing steps. We observed that this method provides the ability to better the lives of patients and lower the rate of permanent blindness resulting from retinal disorders.
An improved secured cloud data using dynamic rivest-shamir-adleman key Ugbedeojo Musa; Marion O. Adebiyi; Francis Bukie Osang; Abayomi Aduragba Adebiyi; Ayodele Ariyo Adebiyi
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp433-441

Abstract

Encryption methods had been widely used for secure data transmission and communication in both public and private organizations against intruders. Rivest-shamir-adleman (RSA) encryption algorithm is one of the most popular and efficient encryption schemes that has been in used for decades. Due to technological advancement and innovation, there is a threat to this algorithm. It is believed that introduction of quantum computer will break RSA algorithm easily. In view of this, it is pertinent to research into how RSA algorithm could be strengthened against all adversaries. This research aim at protecting client/server communication and file sharing by generating dynamic public and private keys. The proposed method was implemented in visual basic.net 2008. The result shows that dynamic keys do not affect the performance of the system and it is capable of protecting communication and file sharing between client/server. As the key generated keeps changing at an interval, it will difficult for most advance computer to factor any of the keys before another key is generated. This is the basis of the security of the proposed system.
Homogenous and multilayer electromagnetics models for estimating skin reflectance Amani Yousef Owda; Majdi Owda
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp82-92

Abstract

Reflectance measurements of human skin are widely limited over the millimeter wave (MMW) band in literature. This is due to the cost and technical difficulties of the experimental setup. This paper proposes homogenous and multilayer skin models for estimating the reflectance of the forearm and palm of the hand skin over the MMW band 30-100 GHz. The simulation results demonstrate that the differences in reflectance between the homogenous and multilayer models of forearm skin are limited to 0.014, indicating that the thin stratum corneum (SC) layer in the multilayer skin models has a minimal impact on the interaction with MMW of the forearm skin. However, in the palm of hand skin, there is a substantial difference in reflectance calculations between the homogenous and the multilayer skin models in the range of 0.099 to 0.143. These differences are attributed to the presence of a thick SC layer in the palm of the hand. Thus, the simulation results suggested that two-layer should be used for the palm of hand skin as it better captures the reflectance characteristics of this region. The importance of having those models are in calculating the skin reflectance that can be used for the non-invasive diagnosis of skin conditions.
Penguin search with Harris-Hawk optimization algorithm to improve clustering performance in wireless network Chitra Sabapathy Ranganathan; Rajeshkumar Sampathrajan
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp190-197

Abstract

Integrating optimal search algorithm concepts across the wireless core and cluster structure enables next-generation wireless networks to effectively provide reliable low-delay communications and connectivity for internet of things (IoT) devices. This article describes penguin search with the Harris-Hawk optimization algorithm (PHHO) to improve clustering performance in wireless networks. The penguin search optimization algorithm (PSO) algorithm computes the fitness value for feature selection from the database. Harris-Hawk optimization (HHO) algorithm to reduce the time and energy required for network transmission. This mechanism builds the clusters based on node communication range. The node direction, node mobility, node bandwidth availability, and energy parameters to decide the cluster head (CH) by applying the HHO algorithm. This approach uses a PSO algorithm fitness function to select the feature subset to minimize error and overhead in the network. Using a network simulator (NS)-3, this method assesses and chooses the most efficient way for data transmission, and the result is compared to a baseline mechanism.
Bayesian K-means clustering based quality of experience aware multimedia video streaming Manjunatha Peddareddygari Bayya Reddy; Sheshappa Shagathur Narayanappa
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp612-621

Abstract

Media streaming is an essential approach for delivering multimedia information from the source distributor to the end-user through the Internet. Along with the development of more number of users and the spread of mobile devices, the availability and diversity of multimedia applications has also increased. Multimedia users primarily prioritize quality of experience (QoE), as they seek to access multimedia content with high availability and enjoy smooth video streaming in the shortest possible time. The impact of video delivery plays a significant role in QoE, which is efficiently made by delivering the content through a specialized content delivery network architecture. In this research, a Bayesian K-means clustering algorithm is proposed for the identification of QoE in multimedia video streaming. In this multimedia video streaming, the Amazon Prime video dataset is utilized for determining the performance of the proposed model. The proposed method is developed from the ‘Patching Up’ the video quality problem (PatchVQ) model, the from patches to pictures (PaQ-2-PiQ) model is utilized for the spatial feature extraction, and 3D ResNet-18 is utilized for temporal feature extraction. The proposed Bayesian K-means achieved a QoE reward function of 5,237.42 and 5841.36 as well as a fairness reward function of 5,841.36 and 8,732.08 at the speed of 1,500 kB/s and 2,000 kB/s respectively.
Application of remote monitoring of biosignals and geolocation with a Wearable for patients with sequelae of the coronavirus Santiago Linder Rubiños Jimenez; Mario Alberto Garcia Perez; Eduardo Nelson Chávez Gallegos; Linett Angélica Velasquez Jimenez; Niko Alain Alarcon Cueva; Mauro Bernardo Sanchez Cabrera
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp135-150

Abstract

Several patients who have overcome coronavirus disease (COVID-19) have been left with cardiovascular and pulmonary sequelae and most medical centers lack a remote monitoring system for each patient that notifies them of any complications during rehabilitation. The objective of this research was to implement a Wearable that monitors the patient's health and alerts in case of detecting any anomaly. For this reason, a Wearable was developed that displays the patient's heart rate, oxygen saturation level and body temperature on the Light Emitting Diode (LCD) and the application mobile, sending an alert and geolocation message if anomalies are detected in vital signs. The standard deviation of heart rate, temperature and oxygen saturation was obtained, which was 1.4930, 0.1558 and 0.4364 in the rest stage, respectively, and 6.3442, 0.2365 and 0.9186 in the physical activity stage respectively with a maximum duration of 42 hours and 52 minutes of battery, managing to send alert messages and store the information in the cloud, which allows to conclude that the Wearable can facilitate the management of the database and the location of the patient, that the measurement error increases with physical activity, and that battery life varies with the number of biosignal readings per hour.
Impact of low molecular weight acid and moisture on the thermal ageing properties of palm oil Muhammad Muzamil Mustam; Norhafiz Azis; Jasronita Jasni; Rasmina Halis; Mohd Aizam Talib; Nur Aqilah Mohamad; Zaini Yaakub
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp10-19

Abstract

This study examines the effect of low molecular weight acid (LMA), moisture and oxygen on the thermal ageing characteristics of refined, bleached, and deodorised palm oil (RBDPO). The paper moisture was varied between 0.5% and 3.5%. The oil was initially subjected to 0.2 g of LMA and 20 mbar of oxygen pressure. The thermal ageing experiment was performed at 120 °C and 140 °C for 28 days. Several dielectric and physiochemical parameters were measured which included dielectric dissipation factor, relative permittivity, resistivity, moisture in oil, acidity, and thermogravimetric analysis (TGA). It is found that LMA and moisture in paper do not affect the relative permittivity of RBDPO and mineral oil (MO). The dielectric dissipation factor of RBDPO and MO reveals slight increment trends within the ageing time. The decrements of resistivities occur after 7 days of ageing for both RBDPO and MO while only RBDPO shows decrement trend of moisture in oil. The ageing patterns of relative permittivities, dielectric dissipation factors and resistivities for RBDPO are similar to MO. The increment of acidity for RBDPO is more apparent that MO throughout the ageing time. All RBDPOs are more resistant to ageing than MO based on the TGA.
Sizing and analysis of a standalone photovoltaics system for a three-bedroom residence in Nigeria Chibuike Peter Ohanu; Godson Nnamdi Egbo; Tole Sutikno
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp1-9

Abstract

The intermittency of electricity supply from conventional sources, increase in fuel prices and constant emission of greenhouse gases by non-renewable energy sources are major challenges faced by energy users. Energy from reneweable sources have advantages over the traditional (non-renewable) sources of energy. This paper presents the sizing and analysis of a standalone photovoltaic (PV) system for a 3-bedroom residence situated at Obollo-Nsukka (6.876°N, 7.403°E, 389 m) in Nigeria. The energy requirements of such a residence are 8.14 kWh/day and analysis have shown that the cost of constructing the PV system is ₦2,838,040 Nigeria naira (NGN). The cost of maintaining such a system within a lifetime of 20 years is between 159,328 NGN/year to 1,895,918 NGN/year. Comparing the levelized cost of energy (LCOE) of enugu electricity distribution company (EEDC) which is 66.5 NGN/kWh to the LCOE of the standalone PV system which is between 102,124 NGN/kWh to 419 NGN/kWh it was found out that the cost of electricity from the PV system is more than that of the conventional grid. The PV system provides feasible solution to the intermittency issues of the conventional grid in Nigeria. Hence, this technology only technically viable for residential electrification purposes in Nigeria.
Enhancing hate speech detection in Indonesian using abusive words lexicon Endang Wahyu Pamungkas; Dian Purworini; Divi Galih Prasetyo Putri; Sohail Akhtar
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp450-462

Abstract

Hate speech is a major challenge in Indonesia, a diverse country with multiple languages and a dynamic online landscape. This research explores the phenomenon of hate speech and its detection, particularly in language contexts with limited resources. We introduce a new abusive words lexicon, created by collecting words from various sources, adapted for Indonesian, Javanese and Sundanese. Our study investigates the practical implementation of this lexicon. We conducted extensive experiments using different datasets and machine learning models, aiming to improve hate speech detection. The results consistently show a positive impact of the lexicon, which significantly improves detection, especially in languages with fewer resources. But this research paves the way for further exploration. The lexicon can be expanded, broadening its scope. Additionally, we suggest investigating more sophisticated models, such as transformerbased models, to more effectively detect hate speech. In a world where hate speech is a growing problem, our research provides valuable insights and tools to combat it effectively in Indonesia and other countries.
A new conjugate gradient for unconstrained optimization problems and its applications in neural networks Alaa Luqman Ibrahim; Mohammed Guhdar Mohammed
Indonesian Journal of Electrical Engineering and Computer Science Vol 33, No 1: January 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v33.i1.pp93-100

Abstract

We introduce a novel efficient and effective conjugate gradient approach for large-scale unconstrained optimization problems. The primary goal is to improve the conjugate gradient method's search direction in order to propose a new, more active method based on the modified vector , which is dependent on the step size of Barzilai and Borwein. The suggested algorithm features the following traits: (i) The ability to achieve global convergence; (ii) numerical results for large-scale functions show that the proposed algorithm is superior to other comparable optimization methods according to the number of iterations (NI) and the number of functions evaluated (NF); and (iii) training neural networks is done to improve their performance.

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