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23,598 Article Results

Model predictive control with finite constant set for five-level neutral-point clamped inverter fed interior permanent magnet synchronous motor drive of electric vehicle

10.11591/ijece.v14i5.pp5038-5047
Tran Hung Cuong , An Thi Hoai Thu Anh
This paper uses the five-level neutral-point clamped (NPC) inverter to feed an electric vehicle's traction motor-interior permanent magnet synchronous motor (IPMSM). The model predictive control method controls the energy conversion process according to the model with two prediction steps. The advantage of this method is its fast response, which increases the ability to operate the converter with good voltage quality. Model predictive control (MPC) control is a closed-loop strategy with much potential when integrating multiple control objectives; the calculation process is compact without complex modulation. Within the scope of this article, the MPC strategy will be implemented with two control goals for NPC, including output load current and capacitor voltage balance with low switching frequency. The simulation results on MATLAB/Simulink software were performed to verify the proposed algorithm's effectiveness in minimizing the grid current's harmonics and ensuring an uninterrupted power supply.
Volume: 14
Issue: 5
Page: 5038-5047
Publish at: 2024-10-01

The surprising influence of social commerce service quality on purchase intentions mediated by e-commerce

10.11591/ijeecs.v36.i1.pp367-374
Bukky Suwarno , Wawan Dhewanto , Prawira Fajarindra Belgiawan
Social commerce has become a recent phenomenon and is poised to grow rapidly in the next few years. To better address customer behavior on social commerce platforms, it is imperative to acquire a comprehensive understanding of social commerce from the perspective of service quality. The objective of this research is to examine the dimensions of social commerce service quality and to reveal the factors influencing purchase intentions among the expanding user population. This study identified seven critical dimensions of social commerce service quality (website design, fulfilment, customer service, communication, contact, credibility, and security) that influence purchase intention. This research adopts a questionnaire survey method to collect data from social commerce users. Using PLS-SEM, the findings from an empirical analysis, conducted with a sample of 411 social commerce users, demonstrate that all measured dimensions significantly impact the intention to purchase. The findings also demonstrate that e-commerce has considerable influence on customer purchase intention as a partial mediator in social commerce. The findings hold significant implications for social commerce enterprises to increase customer attraction by identifying the motivations behind their purchasing decisions.
Volume: 36
Issue: 1
Page: 367-374
Publish at: 2024-10-01

New droop-based control of parallel voltage source inverters in isolated microgrid

10.11591/ijece.v14i5.pp4856-4868
Timilehin F. Sanni , Ayokunle A. Awelewa , Anthony U. Adoghe , Adeola Balogun , Tobi Somefun
Microgrids, featuring distributed generators like solar energy and hybrid energy storage systems, represent a significant step in addressing challenges related to the greenhouse effect and outdated transmission infrastructures. The operation and control of islanded microgrids, particularly in terms of grid voltage and frequency, rely on the synchronization of multiple parallel inverters connected to the distributed generators. However, to determine the necessary grid parameters for effective control, the presence of circulating currents from unbalanced grid voltages arises as a challenge. This situation necessitates the development of a new approach to achieve phase angle locking for grid synchronization, with the aim of maintaining the voltage within acceptable limits in islanded microgrids. This objective is realized through the creation of a microgrid network model, design of an adaptive filter, utilizing the double second-order generalized integrator–phase-locked loop (DSOGI-PLL), for dynamic voltage transformation. The design is evaluated by simulation using MATLAB/Simulink. The primary goal is to investigate the DSOGI-PLL-based droop control and compare its performance with the conventional synchronous reference frame–phase-locked loop (SRF-PLL) control approach. Notably, the DSOGI-PLL successfully eliminates the ripples in phase angle estimation, consequently enhancing the quality of voltage output in the microgrid.
Volume: 14
Issue: 5
Page: 4856-4868
Publish at: 2024-10-01

An efficient approximate method for solving Bratu’s boundary value problem

10.11591/ijece.v14i5.pp5738-5743
Kamel Al-Khaled , Mahmood Shareef Ajeel , Issam Abu-Irwaq , Hala Al-Khalid
We compute the numerical solution of Bratu’s boundary value problem (BVP). To achieve this, we apply a new and useful approach to solve Bratu’s boundary value problem by using Green’s function and a new integral operator, along with a modified version of the Adomian decomposition method. This process produces solutions that call for the boundary conditions to be applied explicitly. Statistical results demonstrating the robustness and efficiency of the proposed scheme are included. An exact and approximate solution comparison is made with known results. The quantitative outcomes showcase our novel approach’s high numerical precision and consistency across a range of parameter configurations.
Volume: 14
Issue: 5
Page: 5738-5743
Publish at: 2024-10-01

Fuzzy integral tracking control of an activated sludge process

10.11591/ijece.v14i5.pp5083-5093
Mounir Bekaik , Hichem Bouras , Ahmed Sami Hamana
This paper addresses the issue of tracking the output of an activated sludge process using fuzzy integral control. First, the dynamics of the nonlinear process are modeled with a dynamic state space fuzzy model integrating the effect of external disturbances, and then an additional integral state of the output tracking error is introduced to obtain an augmented Takagi-Sugeno (TS) fuzzy model. The TS fuzzy model is able to describe the dynamics of complex nonlinear systems with an excellent degree of accuracy. It is formulated by fuzzy if-then rules which can give local linear representation of the overall nonlinear system. Second, the design of the fuzzy integral control is performed, in which the state feedback gains are obtained by solving linear matrix inequalities (LMI). The objective is to ensure trajectory tracking of an activated sludge process (ASP) by controlling two key variables: the substrate concentration and the level of dissolved oxygen. To assess the performance of the proposed control strategy, a comparative analysis is carried out with a gain scheduling PI (GS-PI) controller. Simulation results are provided to illustrate the effectiveness of the proposed approach. Where, the fuzzy integral control reduces the high energy consumption in water treatment plants.
Volume: 14
Issue: 5
Page: 5083-5093
Publish at: 2024-10-01

Improving magnetic fields in overhead transmission lines using the insulated cross-arm method

10.11591/ijeecs.v36.i1.pp53-63
Matiullah Ahsan , Md Nor Ramdon Baharom , Zainab Zainal , Norain Sahari , Faridah Hanim , Saufi Kamarudin , Rashisham Abd Rahman , Mohd Fairouz Mohd Yousof , Nor Akmal Jamail , Nordiana Azlin Othman
This research study evaluates the effectiveness of the insulated cross-arm (ICA) method in reducing magnetic field (MF) levels in transmission lines. Using Ansys Maxwell finite element method (FEM) software, the study models and analyses the MF distribution in 132 kV and 275 kV overhead transmission lines (OTLs) in Malaysia. The findings reveal that implementing the ICA method can substantially reduce MF levels, improving MF performance by 36% (at 132 kV) and 48% (at 275 kV). These findings have important implications for mitigating potential health risks associated with high MF exposure near transmission lines. Furthermore, the study highlights the potential for future enhancements in ampacity and emphasizes the importance of promoting a health-conscious environment. Field studies, assessments, and investigations into economic feasibility and practical implementation are recommended for further validation and application of the ICA method. Overall, this research study contributes to the knowledge and understanding of reducing MF exposure and improving the efficiency of power transmission systems.
Volume: 36
Issue: 1
Page: 53-63
Publish at: 2024-10-01

Identification of faults in rotating machines using high precision FBG vibration sensor: a case study on PM schemes

10.11591/ijeecs.v36.i1.pp535-547
Dipak Ranjan Nayak , Nilam N. Ghuge , Ambarish G. Mohapatra , Pramod Sharma , Narayan Nayak , Satyapriya Satapathy , Ashish Khanna
Predictive maintenance (PM) is a data-driven approach to performing proactive maintenance by analyzing the condition of the equipment in any industrial setting. The high-precision sensors are widely adapted to meticulously analyze critical maintenance conditions using such a data-driven approach. In a similar context, a fiber brag grating (FBG) sensor is a passive and high-precision sensor that is widely used in industries where conventional sensors are not preferred. Broadly, this article presents four sub elements of the proposed integrated system such as the design of the sensor element, signal processing scheme (SPS), machine learning (ML) model for predicting anomalies, and decision support system (DSS) to suggest maintenance actions. Also, this article highlights an experimental case study on vibration monitoring and analysis of real-time signals for making proactive maintenance decisions. An FBG vibration sensor of center wavelength 1,550 nm is designed and utilized to acquire real-time vibration signatures of a rotating machine under test. A piezoelectric vibration sensor is used with the FBG sensor to compare the vibration response obtained during the test. Pre-processing of raw signals is performed using a moving average filter (MAV) followed by a low pass filter to nullify the effect of noise. To obtain proactive maintenance decisions, a DSS model is prepared by considering the processed vibration signatures. Various maintenance conditions are tested during the experimental analysis and detailed results analysis are presented.
Volume: 36
Issue: 1
Page: 535-547
Publish at: 2024-10-01

A framework for reusable domain specific software component extraction based on demand

10.11591/ijeecs.v36.i1.pp274-281
N Md Jubair Basha , Gopinath Ganapathy , Moulana Mohammed
The majority of organizations use an agile software development methodology. Standard analysis and design processes are abandoned due to the enormous demand of generating the product within time and budget. This may result in a lack of high-quality software while components are not constructively reused. The components are identified at a later stage in the majority of component approaches. To address such challenges, a methodology for extracting demand-based domain-specific software components from the repository was developed. The process for reusing current components is described in depth with various domain-specific components, and the suggested framework is for extracting demand-based reusable domain-specific software components.
Volume: 36
Issue: 1
Page: 274-281
Publish at: 2024-10-01

Detection of elements of personal safety for the prevention of accidents at work with convolutional neural networks

10.11591/ijece.v14i5.pp5824-5833
Maria Claudia Bonfante , Ivan Hernandez , Juan Contreras Montes , Eugenia Arrieta Rodríguez , Alejandro Cama-Pinto
The task of recognizing personal protective elements in workplace environments in real time is fundamental to protecting the employees in case of any accidents. This can be achieved by deploying a convolutional neural network (CNN) algorithm that can efficiently detect protective elements through surveillance devices. Therefore, this work proposes the construction of a model, implementing the you only look once (YOLO) detector, whose architecture has been one of the most tested according to literature review. YOLOv5 and YOLOv7 versions were used and a dataset of 2,000 images for four classes considered. This dataset was collection from various sources and labelled by the authors, of which 80% was used for training, 15% for testing and 5% for model validation. The most important metrics are presented, making a comparison between the models, and finally it was identified that YOLOv7 achieved a higher success rate, which could be considered a more complete solution for occupational health and safety management in companies.
Volume: 14
Issue: 5
Page: 5824-5833
Publish at: 2024-10-01

Performance evaluation of a proposal for spectrum assignment based on combinative distance-based assessment multicriteria strategy

10.11591/ijece.v14i5.pp5308-5318
Cesar Hernandez , Diego Giral , Tania Vaca
Cognitive radio networks offer an alternative to low spectral availability in some frequency bands due to their high demand for frequency channels. This article proposes to improve the spectral assignment based on the combinative distance-based assessment multicriteria algorithm. The metrics obtained are compared with a simple additive weighting algorithm and a RANDOM selection. To establish the algorithm 's performance, five quality-of-service metrics are used: number of handoffs, number of failed handoffs, average bandwidth, average throughput, and cumulative average delay. From the analysis of the results obtained, combinative distance-based assessment (CODAS) presented the best result for the cost metrics with the lowest levels, and for the benefit metrics, the highest levels were obtained.
Volume: 14
Issue: 5
Page: 5308-5318
Publish at: 2024-10-01

User self-efficacy enhances business intelligence tools for organizational agility

10.11591/ijeecs.v36.i1.pp592-602
Radwan Moh’d Al-Dwairi , Maali Al-Khataybeh , Dania Najadat , Adnan Rawashdeh
The primary objective of this paper is to investigate the interplay between individual self-efficacy (SE) and the adoption of business intelligence (BI) tools, and their combined effects on organizational agility and performance. This research offers a novel perspective by examining the relationship between individual SE and BI tools together, which was neglected in the previous research, shedding light on how these factors collectively influence organizational performance and agility. The importance of this study addresses the crucial need for understanding the role of individual capabilities in leveraging BI tools, especially in the context of rapidly changing environments. The study employs a quantitative approach to examine the proposed model. A survey was conducted with 174 respondents from private and public organizations in Jordan. The findings reveal significant and positive impacts of individual experiences, vicarious experiences (VE), and psychological feedback (PS) on SE. Moreover, the study demonstrates that SE significantly and positively influences the utilization of BI tools, consequently affecting organizational agility and performance. The significance of the study findings lies in its ability to bridge the gap between individual capabilities and the effective utilization of BI tools to equip businesses with invaluable insights for enhancing their decision-making processes.
Volume: 36
Issue: 1
Page: 592-602
Publish at: 2024-10-01

Effect of Na-EDTA on electrical characteristics NaCl electrolyte battery charging solar panels

10.11591/ijece.v14i5.pp4846-4855
Dina Maizana , Moranain Mungkin , Habib Satria , Syafii Syafii , Muhammad Fadlan Siregar
This research investigates the problem of Cu-Zn electrode batteries with NaCl electrolyte. Previous studies have indicated problems with the electrolyte and electrodes after charging, such as turbidity and deposits in the electrolyte, as well as corrosion on the electrodes. Consequently, the battery can only be used once due to a decline in its electrical characteristics after the initial charging. Through this research, improvements were made to the electrical characteristics of the battery by adding Na-EDTA to enhance usage efficiency. The research method involved mixing NaCl solution with the highest electrical conductivity, using six pairs of Cu-Zn electrodes arranged in series. The physical conditions of the electrolyte and electrodes were observed, and electrical characteristics were measured. The research results indicate that the use of NaCl+Na-EDTA electrolyte produces a battery voltage of 4.20 volts with a current of 2 Ah and can be used twice. Charging with solar panels can be done in 1 hour, but the frequency is limited to two times.
Volume: 14
Issue: 5
Page: 4846-4855
Publish at: 2024-10-01

A fuzzy logic scheme based on spread rate and population for pandemic vaccine allocation

10.11591/ijece.v14i5.pp5941-5948
Abdul Kareem , Varuna Kumara
This paper deals with a novel decision-making scheme for inferring the allocation of vaccines to the provincial health care authorities by the central health care authority of a country in pandemic scenarios. This novel scheme utilizes a fuzzy logic-based inference scheme that utilizes the spread rate and population of a province as inputs to infer the vaccination rate. The proposed scheme is evaluated on the coronavirus disease (COVID-19) data from six southern states of India during the first week of October 2020, collected from the database maintained by the Government of India. The findings demonstrate that the suggested plan, which takes population and spread rate into account, makes sure that enough vaccination doses are distributed to the provinces with a larger spread rate with a higher priority, and that immunizations are not delayed in provinces with controlled spread rates. Also, in due course, all territories will appropriately distribute enough vaccine supply to control the spread. Therefore, this plan strengthens the efforts to control the pandemic outbreaks by ensuring the proper and balanced delivery of vaccines in a timely, efficient, and objective manner.
Volume: 14
Issue: 5
Page: 5941-5948
Publish at: 2024-10-01

Photovoltaic power prediction using deep learning models: recent advances and new insights

10.11591/ijece.v14i5.pp5926-5940
Basma Saad , Asmaa El Hannani , Abdelhak Aqqal , Rahhal Errattahi
Artificial intelligence (AI) and its application across various domains have sparked significant interest, with each domain presenting distinct characteristics and challenges. In the renewable energies sector, accurate prediction of power output from photovoltaic (PV) panels using AI is crucial for meeting energy demand and facilitating energy management and storage. The field of data analysis has grown rapidly in recent years, with predictive models becoming increasingly popular for forecasting and prediction tasks. However, the accuracy and reliability of these models depend heavily on the quality of data, data preprocessing, model learning and evaluation. In this context, this paper aims to provide an in-depth review of previous research and recent progress in PV solar power forecasting and prediction by identifying and analyzing the most impacting factors. The findings of the literature review are then used to implement a benchmark for PV power prediction using deep learning models in different climates and PV panels. The aim of implementing this benchmark is to gain insights into the challenges and opportunities of PV power prediction and to improve the accuracy, reliability and explainability of predictive models in the future.
Volume: 14
Issue: 5
Page: 5926-5940
Publish at: 2024-10-01

Improving communication between can-sized satellite and ground control station for accuracy of data acquisition

10.11591/ijeecs.v36.i1.pp197-204
Mohd Hakimi Bin Zohari , Lam Hong Yin , Mohd Hezri Bin Mokhtar
The can-sized satellite, ScoreSAT satellite is a small communications satellite. ScoreSAT helps to develop a platform for finding directions and the exact spot where a lack of communications signal occurs, as well as a real-time visual feed for analysis of communication during and after landing. The project focuses on the design of ScoreSAT and provides a real-time system for capturing real-time data during descent. The objective of the real-time system is to improve the accuracy and location of ScoreSAT data collection, which can provide pressure, humidity, temperature, altitude, latitude, and longitude readings. The main components of this platform are the hardware design that comprises the flight controller, GPS module, and telemetry kit, the software design, which are Mission Planner, and the real-time system (RTS). Based on the entire research, the compact design of the ScoreSAT and ground station was developed to provide alternative meteorological parameter monitoring to complement primary meteorology ground observation such as weather station and radiosonde and to enhance the reliability of the remote sensing observation for environmental studies concerning the factors determining the environment and atmospheric.
Volume: 36
Issue: 1
Page: 197-204
Publish at: 2024-10-01
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