cover
Article Per Year (5 Year)
All
Home Page
OAI Link
Editorial Team
Contact
Reviewer
Google Scholar
Contact Name
Tole Sutikno
Contact Email
ijece@iaesjournal.com
Phone
-
Journal Mail Official
ijece@iaesjournal.com
Editorial Address
-
Location
Kota yogyakarta,
Daerah istimewa yogyakarta
INDONESIA
International Journal of Electrical and Computer Engineering
Published by Institute of Advanced Engineering and Science
ISSN : 20888708     EISSN : 27222578     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Electrical and Computer Engineering (IJECE, ISSN: 2088-8708, a SCOPUS indexed Journal, SNIP: 1.001; SJR: 0.296; CiteScore: 0.99; SJR & CiteScore Q2 on both of the Electrical & Electronics Engineering, and Computer Science) is the official publication of the Institute of Advanced Engineering and Science (IAES). The journal is open to submission from scholars and experts in the wide areas of electrical, electronics, instrumentation, control, telecommunication and computer engineering from the global world.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 111 Documents
 8   9   10   11   12 
Search results for , issue "Vol 14, No 1: February 2024" : 111 Documents clear
Remote sensing in the analysis between forest cover and COVID-19 cases in Colombia Henao-Céspedes, Vladimir; Garcés-Gómez, Yeison Alberto
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp732-740

Abstract

This article explores the relationship between forest cover and coronavirus disease 2019 (COVID-19) cases in Colombia using remote sensing techniques and data analysis. The study focuses on the CORINE land cover methodology's five main land cover categories: artificial territory, agricultural territories, forests and semi-natural areas, humid areas, and water surfaces. The research methodology involves several phases of the unified method of analytical solutions for data mining (ASUM-DM). Data on COVID-19 cases and forest cover are collected from the Colombian National Institute of Health and Advanced Land Observation Satellite (ALOS PALSAR), respectively. Land cover data is processed using QGIS software. The results indicate an inverse relationship between forest cover and COVID-19 cases, as evidenced by Pearson's index ρ of -0.439 (p-value <0.012). In addition, a negative correlation is observed between case density and forests and semi-natural areas, one of the land cover categories. The findings of this study suggest that higher forest cover is associated with lower numbers of COVID-19 cases in Colombia. The results could potentially inform government organizations and policymakers in implementing strategies and policies for forest conservation and the inclusion of green areas in densely populated urban areas.
Wearable with integrated piezoelectric energy harvester for geolocation of people with Alzheimer's Linder Rubiños Jimenez, Santiago; Herber Grados Gamarra, Juan; Nelson Chávez Gallegos, Eduardo; Angélica Velasquez Jimenez, Linett; Junior Grados Espinoza, Herbert; Christian Pesantes Arriola, Genaro
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp497-508

Abstract

Alzheimer's is a progressive disease that affects memory, causing disorientation in the patient, which causes them to lose themselves, generating anguish in families who have to resort to expensive searches. The objective of this research was to implement a device that can remotely provide the location of the Alzheimer's patient over a long period to relatives for greater security. For this, in this research, a mobile application was developed that receives information from a wearable that applies the internet of things using ong-range wide area technology to show the patient's real-time location and uses piezoelectrics for greater battery autonomy. The real-time location of the person and the radius of the safe zone in the application were obtained as results, the received signal strength indicator value where the signal was excellent or good had a value of -30 to -89 dB between 0 to 400 meters and the battery discharge time was 11 hours and 44 minutes. It was concluded that the application is interactive, that the piezoelectric system increased the autonomy of the wearable, and that the long-range wide area (LoRa) technology allowed monitoring of the patient's location with great precision at 400 meters.
Hierarchal attribute based cryptographic model to handle security services in cloud environment: a new model Rajarao, Banavathu; Sreenivasulu, Meruva
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp1102-1111

Abstract

The sharing of information in the cloud is a unique element of the environment, but there is a risk that the information may land with the wrong people. To counterattack this problem, security-associated methodologies were used to secure the information that was readily available to clients. Despite the lack of benefits, this provides productive/adaptability and dependability in access control strategies between clients in the sharing of information. The novel hierarchal attribute-based cryptographic security model (NHACSM) is being proposed to provide adaptability, versatility, and access control in sharing information in the appropriate climate. This model allows clients to share information in a hierarchal way, allowing for a productive assessment of access control strategy and improved security. The NHACSM method is used to reduce the total time values for different user instances compared to conventional approaches, for example, attribute-set-based encryption (ASBE), key-policy attribute-based encryption (KP-ABE), and ciphertext-policy attribute-based encryption (CP-ABE). With respect to 10 instances existing methods achieve 2.7, 2.5, and 2.3 respectively, and also compared to 20, 30, 40, and 50 instances, our proposed method is low. The encryption and decryption time evaluation values and performance evaluation of different approaches, ASBE, CP-ABE, were taken into account when increasing the user instance.
Novel control strategy for the global model of wind turbine El Fadili, Yattou; Berrada, Youssef; Boumhidi, Ismail
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp258-267

Abstract

This paper presents a new nonlinear control for the overall model of a three-blade horizontal axis variable speed wind turbine (VSWT) including mechanical and electrical parts, with the aim of improving its performance and making it more profitable. The proposed control is an extension of the classical sliding mode control (SMC) by converting its sliding surface into a sliding sector. The classical SMC approach is widely used for nonlinear systems due to its stability against parameter variation, it is robustness against modeling uncertainties, its good results against external disturbances, and its ease of implementation in real time. Unfortunately, the SMC has a major drawback related to the chattering phenomenon. This phenomenon is due to the utility of a higher switching gain in the case of large uncertainties, it causes high-frequency oscillations once the sliding regime is reached, and it can cause a loss of accuracy by influencing the input control variables. This is the reason that aims to develop a new control law to eliminate the chattering and to guarantee stability, which is demonstrated by the Lyapunov theory. The effectiveness of the developed control is compared with the SMC and is illustrated by numerical simulations using MATLAB toolboxes.
Transformations for non-destructive evaluation of brix in mango by reflectance spectroscopy and machine learning Paiva-Peredo, Ernesto; Gonzales-Rodriguez, Diego; Trujillo Herrera, William; Soria Quijaite, Juan Jesús; Quispe-Arpasi, Diana; Paulino, Christian Ovalle
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp532-546

Abstract

Mango is a very popular climacteric fruit in America and Europe. Among the internal properties of the mango, total soluble solids (TSS) are an adequate indicator to estimate the quality of mango, however, the measurement of this indicator requires destructive tests. Several research have addressed similar issues; they have made use of pre-processing transformations without making it clear which of them is statistically better. Here, we created a new spectral database to build machine learning (ML) models. We analyzed a total of 18 principal component regression (PCR) models and 18 partial least squared regression (PLSR) models, where 4 types of transformations, 3 different feature extractors, and 3 different pre-processing techniques are combined. The research proposes a double cross validation (CV) both to determine the optimal number of components and to obtain the final metrics. The best model had a root mean square error (RMSE) of 1.1382 °Brix and a RMSE on the transformed scale of 0.5140. The best model used 4 components, used y2 transformation, reflectance R as the independent variable and MSC as a pre-processing technique.
EksPy: a new Python framework for developing graphical user interface based PyQt5 Kirsan, Aidil Saputra; Takano, Kosuke; Zebada Mansurina, Sallie Trixie
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp520-531

Abstract

This study introduces EksPy Python framework, a novel framework designed for developing graphical user interface (GUI) applications in Python. EksPy framework is built on PyQt5, which is a collection of Python bindings for the Qt libraries, and it provides a user-friendly and intuitive interface. The comparative analysis of EksPy framework with existing frameworks such as Tkinter and PyQt highlights its notable features, including ease of use, rapid development, enhanced performance, effective database management, and the model-view-controller (MVC) concept. The experimental results illustrate that EksPy framework requires less code and enhances code readability, thereby facilitating better understanding and efficient development. Additionally, EksPy framework offers a modern and customizable appearance, surpassing Tkinter’s capabilities. Furthermore, it incorporates a built-in object-relational mapping (ORM) feature to simplify database interactions and adheres to the MVC architectural pattern. In conclusion, EksPy Python framework emerges as a powerful, user-friendly, and efficient framework for GUI application development in Python.
An efficient unused integrated circuits detection algorithm for parallel scan architecture Sathyanarayana, Rekha; Kanathur Ramaswamy, Nataraj; Srikantaswamy, Mallikarjunaswamy; Kanathur Ramaswamy, Rekha
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp469-478

Abstract

In recent days, many integrated circuits (ICs) are operated parallelly to increase switching operations in on-chip static random access memory (SRAM) array, due to more complex tasks and parallel operations being executed in many digital systems. Hence, it is important to efficiently identify the long-duration unused ICs in the on-chip SRAM memory array layout and to effectively distribute the task to unused ICs in SRAM memory array. In the present globalization, semiconductor supply chain detection of unused SRAM in large memory arrays is a very difficult task. This also results in reduced lifetime and more power dissipation. To overcome the above-mentioned drawbacks, an efficient unused integrated circuits detection algorithm (ICDA) for parallel scan architecture is proposed to differentiate the ‘0’ and ‘1’ in a larger SRAM memory array. The proposed architecture avoids the unbalancing of ‘0’ and ‘1’ concentrations in the on-chip SRAM memory array and also optimizes the area required for the memory array. As per simulation results, the proposed method is more efficient in terms of reliability, the detection rate in both used and unused ICs and reduction of power dissipation in comparison to conventional methods such as backscattering side-channel analysis (BSCA) and network attached storage (NAS) algorithm.
A novel multi-biometric technique for verification of secure e-document Ali, Ammar Mohammed; Farhan, Alaa Kadhim
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp662-671

Abstract

Extracting unique and distinctive traits is one of the most important challenges that researchers face, who rely on biometrics to extract exceptional traits for an individual. A large amount of biometric evidence that can be identified and found in various research has been done. In this paper, a biometrics system is proposed that combines the benefits of fingerprinting and uses a novel strategy to combine it with the image-based fingerprint vein feature set. The proposed system is fast and performs effective personal identification by combining both features. The features extracted from the venous print and fingerprint are matched to the nearest neighbors of the authorized person forms to verify the identity of the person. Several experiments have been performed on selected datasets to evaluate the performance of the new biometrics system. The obtained results prove that our proposed system is superior to biometric systems that use the feature of single biometrics. However, our goal is to set up an algorithm that is inexpensive in terms of time complexity while keeping it at the required security levels.
Machine learning for real-time prediction of complications induced by flexible uretero-renoscopy with laser lithotripsy Baidada, Chafik; Hrimech, Hamid; Aatila, Mustapha; Lachgar, Mohamed; Ommane, Younes
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp971-982

Abstract

It is not always easy to predict the outcome of a surgery. Peculiarly, when talking about the risks associated to a given intervention or the possible complications that it may bring about. Thus, predicting those potential complications that may arise during or after a surgery will help minimize risks and prevent failures to the greatest extent possible. Therefore, the objectif of this article is to propose an intelligent system based on machine learning, allowing predicting the complications related to a flexible uretero-renoscopy with laser lithotripsy for the treatment of kidney stones. The proposed method achieved accuracy with 100% for training and, 94.33% for testing in hard voting, 100% for testing and 95.38% for training in soft voting, with only ten optimal features. Additionally, we were able to evaluted the machine learning model by examining the most significant features using the shpley additive explanations (SHAP) feature importance plot, dependency plot, summary plot, and partial dependency plots.
Deep learning with filtering for defect characterization in pulsed thermography based non-destructive testing Selvan, Sethu Selvi; Delanthabettu, Sharath; Murugesan, Menaka; Balasubramaniam, Venkatraman
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp1027-1040

Abstract

Pulsed thermography is widely used for non-destructive testing of various materials. The temperature profile obtained after pulse heating is used to characterize the underlying defects in an object. In this paper, the automation of the process of defect visualization and depth quantification in pulsed thermography through various deep learning algorithms is reported. Stainless steel plate with artificial defects is considered for analysis. The raw temperature data is smoothed using moving average, Savitzky-Golay and quadratic regression filters to reduce noise. Thermal signal reconstruction, the conventional method to eliminate noise, is also used for generating filtered datasets. Defect visualization refers to identifying and locating the defects in an image sample and Mask region convolutional neural network (Mask R-CNN) is considered for not just detecting the defects but also locating them on the image. The located defects are utilized for depth estimation using the following networks-multi-layer perceptron (MLP), long short-term memory (LSTM) and gated recurrent units (GRU). The input to the networks is the temperature contrast characteristics which symbolizes the difference in temperature over defective and non-defective areas measured over 250 time points and output of the networks is the estimated depth. The study shows that LSTM based approach provides the least percentage error of 5.5% and is a very suitable approach for automation of defect characterization in pulsed thermography.

Page 11 of 12 | Total Record : 111

 8   9   10   11   12 

Filter by Year

2024 2024


Reset
Filter By Issues
All Issue Vol 16, No 1: February 2026 Vol 15, No 6: December 2025 Vol 15, No 5: October 2025 Vol 15, No 4: August 2025 Vol 15, No 3: June 2025 Vol 15, No 2: April 2025 Vol 15, No 1: February 2025 Vol 14, No 6: December 2024 Vol 14, No 5: October 2024 Vol 14, No 4: August 2024 Vol 14, No 3: June 2024 Vol 14, No 2: April 2024 Vol 14, No 1: February 2024 Vol 13, No 6: December 2023 Vol 13, No 5: October 2023 Vol 13, No 4: August 2023 Vol 13, No 3: June 2023 Vol 13, No 2: April 2023 Vol 13, No 1: February 2023 Vol 12, No 6: December 2022 Vol 12, No 5: October 2022 Vol 12, No 4: August 2022 Vol 12, No 3: June 2022 Vol 12, No 2: April 2022 Vol 12, No 1: February 2022 Vol 11, No 6: December 2021 Vol 11, No 5: October 2021 Vol 11, No 4: August 2021 Vol 11, No 3: June 2021 Vol 11, No 2: April 2021 Vol 11, No 1: February 2021 Vol 10, No 6: December 2020 Vol 10, No 5: October 2020 Vol 10, No 4: August 2020 Vol 10, No 3: June 2020 Vol 10, No 2: April 2020 Vol 10, No 1: February 2020 Vol 9, No 6: December 2019 Vol 9, No 5: October 2019 Vol 9, No 4: August 2019 Vol 9, No 3: June 2019 Vol 9, No 2: April 2019 Vol 9, No 1: February 2019 Vol 8, No 6: December 2018 Vol 8, No 5: October 2018 Vol 8, No 4: August 2018 Vol 8, No 3: June 2018 Vol 8, No 2: April 2018 Vol 8, No 1: February 2018 Vol 7, No 6: December 2017 Vol 7, No 5: October 2017 Vol 7, No 4: August 2017 Vol 7, No 3: June 2017 Vol 7, No 2: April 2017 Vol 7, No 1: February 2017 Vol 6, No 6: December 2016 Vol 6, No 5: October 2016 Vol 6, No 4: August 2016 Vol 6, No 3: June 2016 Vol 6, No 2: April 2016 Vol 6, No 1: February 2016 Vol 5, No 6: December 2015 Vol 5, No 5: October 2015 Vol 5, No 4: August 2015 Vol 5, No 3: June 2015 Vol 5, No 2: April 2015 Vol 5, No 1: February 2015 Vol 4, No 6: December 2014 Vol 4, No 5: October 2014 Vol 4, No 4: August 2014 Vol 4, No 3: June 2014 Vol 4, No 2: April 2014 Vol 4, No 1: February 2014 Vol 3, No 6: December 2013 Vol 3, No 5: October 2013 Vol 3, No 4: August 2013 Vol 3, No 3: June 2013 Vol 3, No 2: April 2013 Vol 3, No 1: February 2013 Vol 2, No 6: December 2012 Vol 2, No 5: October 2012 Vol 2, No 4: August 2012 Vol 2, No 3: June 2012 Vol 2, No 2: April 2012 Vol 2, No 1: February 2012 Vol 1, No 2: December 2011 Vol 1, No 1: September 2011 More Issue