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28,188 Article Results

Torque sharing function optimization for switched reluctance motor control using ant colony optimization algorithm

10.11591/ijpeds.v16.i3.pp1537-1551
Dhiyaa Mohammed Ismael , Thamir Hassan Atyia
Switched reluctance motors (SRMs) are gaining popularity in industrial and automotive applications due to their robust design, fault tolerance, and high torque density, particularly in wide-speed-range operations. However, SRM performance is often limited by torque ripple, speed oscillations, and inefficiencies, which can lead to mechanical stress, vibration, and acoustic noise. Addressing these challenges requires the effective optimization of control strategies. This study aims to enhance the performance of SRM drives by employing an ant colony optimization (ACO) algorithm to optimize the torque sharing function (TSF). The proposed method iteratively tunes TSF parameters to minimize torque ripple and improve speed stability under varying operating conditions. Simulation results demonstrate significant improvements: torque ripple is reduced from a range of –20 Nm to 10 Nm without optimization to below 10 Nm with ACO-based optimization. Similarly, current peaks decrease from 60 A to 5.5 A, ensuring smoother motor operation and enhanced efficiency. Comparative analysis confirms that the ACO-based TSF provides superior tracking of speed set points, reduced mechanical stress, and improved reliability, making it well-suited for high performance applications in both industrial and automotive sectors.
Volume: 16
Issue: 3
Page: 1537-1551
Publish at: 2025-09-01

Optimization of two-stage DTMOS operational transconductance amplifier with Firefly algorithm

10.11591/ijpeds.v16.i3.pp1417-1428
Udari Gnaneshwara Chary , Swathi Mummadi , Kakarla Hari Kishore
This paper presents a methodology for optimizing dynamic threshold MOSFET (DTMOS) two-stage operational transconductance amplifiers (OTAs) tailored for biomedical applications through the utilization of the Firefly algorithm. The optimization process focuses on enhancing key performance metrics such as gain, bandwidth, and power efficiency, which are critical for biomedical signal processing, neural interfaces, and wearable healthcare devices. The methodology encompasses circuit architecture definition, Firefly algorithm implementation, fitness evaluation, and result analysis. The optimization results reveal a significant enhancement in performance metrics. Specifically, the number of transistors in the design is 25. The initial overall gain was 76.65 V/V, with a power efficiency (µ) of 1.6. After optimization, the overall gain was significantly improved to 84.029 dB using the Firefly algorithm, demonstrating superior performance compared to existing algorithms. The power efficiency (µ) was also enhanced to 1.702, underscoring the efficiency improvements achieved through optimization. Simulation results and statistical analysis confirm that the Firefly algorithm effectively achieves optimal configurations, improving the robustness of OTA designs against parameter variations. These enhancements validate the algorithm's efficacy in addressing power-performance trade-offs and its suitability for diverse biomedical applications. Physical prototyping of the optimized design further demonstrates real-world functionality, underscoring its practical applicability.
Volume: 16
Issue: 3
Page: 1417-1428
Publish at: 2025-09-01

Machine learning techniques for solar energy generation prediction in photovoltaic systems

10.11591/ijpeds.v16.i3.pp2055-2062
J. Sumithra , J. C. Vinitha , M. J. Suganya , M. Anuradha , P. Sivakumar , R. Balaji
For photovoltaic (PV) systems to be as effective and dependable as they possibly can be, it is vital to make an accurate prediction of the amount of power that will be generated by the sun. Using machine learning, it is now much simpler to forecast the amount of solar energy that will be generated. These approaches are more accurate and are able to adapt to the ever changing conditions of the nature of the environment. We take a look at the most recent machine learning algorithms for predicting solar energy and examine their methodology, as well as their strengths and drawbacks, in this paper. Using performance metrics like root mean squared error (RMSE), mean absolute error (MAE), and mean squared error (MSE) makes it possible to evaluate important algorithms like support vector machines, decision trees, and linear regression. The results show that machine learning could help make predictions more accurate, lower the amount of uncertainty in operations, and help people make decisions in real time for PV systems. The study also points out important areas where research is lacking and suggests ways to move forward with the use of machine learning in systems that produce renewable energy.
Volume: 16
Issue: 3
Page: 2055-2062
Publish at: 2025-09-01

DC bus control strategy and implications for voltage source converter system

10.11591/ijpeds.v16.i3.pp1505-1515
Haider Fadel , Ahmed Abdulredha Ali , Mustafa Jameel Hameed
Significantly, the use of power electronic devices in residential and industrial settings has grown significantly in the last several years. Recent advancements in power semiconductors and microelectronics may be the main reason of their growing use in power systems for filtering, conditioning, and compensating. Additionally, the proliferation of semiconductor switches appropriate for high-power applications, and the enhancement of microelectronics enable mixed signal processing and control mechanisms. Furthermore, the concentration on renewable energy sources within the electric utility industry has emphasized the incorporation of power electronic converters into power systems. The operation and control of the regulated DC-voltage power port are examined in this work, a key part in different applications, such as STATCOM, dual mode HVDC converter systems, and aerodynamic wind energy converters with adaptive-speed optimization, emphasizing its significance in upholding a stable voltage level throughout the DC bus. The research also highlights the importance of power electronic converters within contemporary power systems, emphasizing their crucial role in facilitating effective and reliable power distribution. The obtained simulation results confirmed the efficacy of feed forward compensation in stabilizing the voltage responses of the DC bus.
Volume: 16
Issue: 3
Page: 1505-1515
Publish at: 2025-09-01

Photovoltaic energy harvesting for the power supply of medical devices

10.11591/ijpeds.v16.i3.pp1962-1969
Hamza Abu Owida , Basem Abu Izneid , Nidal Turab
The increasing demand for sustainable and reliable power sources in portable and implantable medical devices has led to growing interest in photovoltaic (PV) energy harvesting. Traditional power sources, such as batteries, are limited by finite energy capacity and frequent replacement or recharging needs, particularly in implantable devices where surgical intervention is required for battery replacement. Photovoltaic energy harvesting, which converts light into electrical energy, offers a promising alternative, especially in environments with consistent light exposure. This review provides an in-depth analysis of the advancements in PV technologies for powering medical devices. It covers various types of PV materials, design innovations, and the integration of energy storage systems. Additionally, the review highlights the application of PV systems in both external and implantable medical devices, while addressing critical challenges such as ensuring biocompatibility, optimizing performance in low-light conditions, and miniaturizing PV systems for implantation. The potential of PV energy harvesting to improve device longevity and reduce the need for invasive procedures is emphasized. This review concludes by outlining the current challenges and future directions needed to achieve widespread clinical adoption, aiming to contribute to the development of sustainable power solutions in healthcare.
Volume: 16
Issue: 3
Page: 1962-1969
Publish at: 2025-09-01

A model predictive control strategy for enhance performance of totem-pole PFC rectifier

10.11591/ijpeds.v16.i3.pp1687-1700
Le Chau Duy , Nguyen Dinh Tuyen
This paper proposed a simple but effective finite control set-based model predictive control (FCS-MPC) method to control a totem-pole bridgeless boost PFC rectifier (TBBR). The control algorithm selects from the possible switching states an appropriate one that fulfills a predefined cost function. This method also successfully eliminates the zero-crossing current distortion so that the grid current can synchronize well with the grid voltage. The theoretical analysis was presented and verified by simulation. Finally, a 3.3 kW/400 Vdc prototype was fabricated and investigated through various working conditions to realize the effectiveness of the proposed control strategy. Both simulation and experimental results show that the proposed control method can ensure accurate control of DC link output voltage and sinusoidal input current with unity power factor.
Volume: 16
Issue: 3
Page: 1687-1700
Publish at: 2025-09-01

An analytical technique for failure analysis and reliability assessment of grid daily outage performance in distributed power system

10.11591/ijpeds.v16.i3.pp1852-1864
Jacob Kehinde Ogunjuyigbe , Evans Chinemezu Ashigwuike , Kafayat Adeyemi , Ngang Bassey Ngang , Timothy Oluwaseun Araoye , Isaac Ojochogwu Onuh , Benson Stephen Adole , Solomon Bala Okoh , Iboi Endurance
This paper modeled and analyzed the reliability performance of the 132/33 kV substation in Abuja, Nigeria through the historical data collected from the APO substation using MATLAB 2021b. The probability distribution model was applied to determine the daily feeder’s outage using Reliability, availability, mean time to repair (MTR), Failure rate, distribution indices, and mean time between failures (MTBF). Due to the application of smart energy meters, the use of prepaid energy meters has helped to regulate energy demand, reduce network overloading especially during peak hours, and minimize the cost of energy consumed. There are more forced failures in the distribution system due to the switchgear and Transformer failures. There are more forced failures in the distribution system since 2013, which caused a reduction in the number of interruptions even with an increase in several customers linked to the transmission network. The result shows that the system was most available in the year 2015 with an average service availability index (ASAI) value of 98.9971%. The system was least available in year 2011 with an ASAI value of 98.6558%. The paper recommended that there should be interconnections between different feeders through proper configuration of switches or reclosers, to reduce failure occurrence in the network.
Volume: 16
Issue: 3
Page: 1852-1864
Publish at: 2025-09-01

Variable frequency drive based on full-bridge class D for single-phase induction motor

10.11591/ijpeds.v16.i3.pp1701-1710
Budi Pramono Jati , Jenny Putri Hapsari , Muhamad Haddin , Sri Arttini Dwi Prasetyowati
The issue with induction motors lies in speed regulation, which can be addressed by adjusting the motor voltage; however, this affects torque. In contrast, a variable frequency drive (VFD) changes the motor frequency while maintaining a constant voltage. A VFD controller with constant sinusoidal voltage and adjustable frequency can be implemented using an Arduino and a class D full-bridge MOSFET amplifier inverter. This paper discusses the electronic speed control (ESC) of induction motors using VFD regulation, demonstrating how changes in frequency affect motor speed. The system involves an induction motor controlled by a VFD comprising three main components: an AC-to-DC converter, a class-D full-bridge MOSFET inverter, and a variable-frequency sinusoidal signal source. VFDs operate with constant voltage and variable frequency. This method includes the design and testing of VFD hardware and software. The VFD components include: a class-D full-bridge switching inverter, a sinusoidal signal frequency generator (30–70 Hz), an Arduino with custom software, an SMPS power supply, and a step-up transformer. The results indicate that the class-D full-bridge inverter can effectively regulate motor speed through VFD control. The motor speed is almost directly proportional to the frequency: at 30 Hz, the speed is 860 RPM; at 50 Hz, 1472 RPM; and at 70 Hz, 2035 RPM.
Volume: 16
Issue: 3
Page: 1701-1710
Publish at: 2025-09-01

Improvement direct torque control of induction motor using robust intelligence artificial ANFIS speed controller

10.11591/ijpeds.v16.i3.pp1552-1565
Laoufi Abdelhaq , Chergui Moulay-Idriss , Soufiane Chekroun
This paper proposes a study aimed at improving the conventional direct torque control (DTC) technique applied to induction motors (IM). The primary aim is to reduce the harmonic distortions and fluctuations associated with the electrical current, flux variations, and generated torque, while ensuring accurate speed reference tracking and ensuring optimal dynamic performance of the drive, especially under variable speed conditions. To achieve this, we introduce an intelligent control system that utilizes a hybrid neuro-fuzzy inference model (ANFIS), through the application of the back propagation method. The DTC-ANFIS technique is compared with the traditional DTC-PI method and simulated using MATLAB/Simulink in different scenarios. The obtained results reveal a significant improvement in performance over DTC-PI, with superior results over a wide speed range.
Volume: 16
Issue: 3
Page: 1552-1565
Publish at: 2025-09-01

Impact of leadership approaches and appraisal practices on hospital workforce and environment

10.11591/ijphs.v14i3.26182
Subodh S. Satheesh , Anila Cholleti
Hospital appraisal practices can directly impact workforce-based outcomes, including work performance, retention rate, and physical and emotional well-being. This study aimed to evaluate the effectiveness of performance appraisals and leadership approaches on the overall job satisfaction of the workforce in healthcare settings. A descriptive cross-sectional method was employed to collect data from 258 randomly selected health workforce from different private hospitals in Bangalore, India. A structured questionnaire was used to evaluate the appraisal process, leadership approaches, and sentiments. SPSS version 26 and Python 3.13 were used for statistical analysis. Most of the participants (62.2%) had a good understanding of the performance appraisal process, viewing it as essential for professional growth (95%) and work quality (96.5%). However, 53.8% felt that appraisal requirements were poorly communicated, with 58.9% reporting common unfair practices. Over half of them (56.3%) acknowledged their manager's influence, but only 43.6% expressed moderate satisfaction. This study found that despite the good understanding of the performance appraisal among the study participants, the lack of communication and the unethical work environment contributed to dissatisfaction. Thus, organizations should develop a more transparent, fair, and employee-centric appraisal system to enhance job satisfaction, workforce stability, and overall patient care quality.
Volume: 14
Issue: 3
Page: 1412-1418
Publish at: 2025-09-01

Relationship between employment changes and psychosocial discomfort during the COVID-19 pandemic

10.11591/ijphs.v14i3.25746
María Teresa Solís-Soto , María Soledad Burrone , Armando Basagoitia , Luna Rojas , Paulina Valenzuela , Catalina Barrientos , Fabiola Molina , Daniela Valdés , Silvina Arrosi , Silvina Ramos , Paulina Rincón , Loreto Villagran Valenzuela
Due to the COVID-19 pandemic and the containment and prevention measures established at the global and national level, daily life activities were affected, deepening inequities in Chile and impacting the population's mental health. The study's objective was to analyze the relationship between working conditions and psychological distress during the COVID-19 pandemic in Chile. For this, a cross-sectional study was implemented using an anonymous and self-administered online questionnaire, reaching a final sample size of 784 people ≥18 years. The questionnaire explored sociodemographics, work, income, and psychological distress information. We computed logistic regression models to assess risk factors associated with psychological discomfort. Data showed that higher percentage of women dedicate more hours per week to household chores, caring for other people, and accompanying schoolwork than men. More than half of the participants (55%) reported psychological discomfort, with household income reduction as the main risk factor. Our results reflect the impact of the COVID-19 pandemic in Chile, with a severe decrease in household income, a risk factor for psychological discomfort. It is important to implement strategies to protect mental health during health emergencies, considering more vulnerable populations.
Volume: 14
Issue: 3
Page: 1201-1209
Publish at: 2025-09-01

Quality of life among peri menopausal and post-menopausal women from rural area of Western India

10.11591/ijphs.v14i3.26055
Sanjana Maniktalla , Jayashree Sachin Gothankar , Arvinder Pal Singh Narula
Menopause, remains a poorly investigated topic holding increased taboo. In addition to symptoms categorized under vasomotor, vaginal, energy, food and insomnia, it is linked to occurrence of various medical comorbidities. Understanding the status of menopause symptoms and awareness will help provide insight on how it influences women’s quality of life. Objective was to assess the association of menopause on attributes of sleep, energy, memory, work, leisure and everyday activities affecting quality of life. This was a community based cross-sectional study conducted over three months in randomly selected villages under rural field practice area of private medical college in Maharashtra. Data was collected during health camps along with house visits. Research tool containing socio-demographic, menopausal status and quality of life components was used targeting women aged 40-65 years. Logistic regression analysis was used to find odds ratio and adjusted odds ratio respectively for menopausal symptoms with associated attributes at 5% level of significance and 95% CI. Results showed the mean age of women was 48.16 years ±8.4 SD, by which 57% had fully attained menopause and it was associated with significant changes in sleep, memory and physical relations. This study lays emphasis on the fact that menopause period is associated with sleep and memory disturbances as well as physical relations in rural women. It also highlights on the poor knowledge and attitude pertaining to menopause in a rural setup.
Volume: 14
Issue: 3
Page: 1347-1356
Publish at: 2025-09-01

Assessment of depression, malnutrition and co-morbidities of geriatric individuals in rural areas of Bangladesh

10.11591/ijphs.v14i3.26155
Mst. Umme Hafsa Begum , Md. Nazrul Islam , Afsana Akter , Lima Akter , Mst. Trisha Akter , Md. Abul Hasnat , Mst. Rokshana Rabeya
In rural Bangladesh, elderly populations face distinct health challenges, with depression, malnutrition, and co-morbidities significantly impacting their well-being. This cross-sectional study evaluated 384 older adults across four divisions of Bangladesh using the geriatric depression scale (GDS-15), mini nutritional assessment (MNA), and Katz Index of activities of daily living (ADL). Depression was found among 62.8% of respondents. About 13.0% of participants were malnourished, and 51.8% were at risk of malnutrition. Self reported hypertension (47.1%), arthritis (46.4%), dental problems (43.5%), and insomnia (37.0%) were profound among respondents. The risk of dementia, anorexia, cardiovascular disease, and hypertension was higher among males than females. Geriatric depression was significantly higher in the elderly who were residing in a nuclear family than their counterparts (AOR = 2.114; 95% CI = 1.328-3.365). Additionally, being unemployed was identified as an independent predictor of GD (AOR = 1.992, 95% CI: 1.070 3.709, p = .030). The higher prevalence of depression and risk of malnutrition highlight the pressing requirement for well-coordinated and comprehensive healthcare strategies. The development of multifaceted approaches, incorporating mental health services, nutritional interventions, and socioeconomic support, would enhance elders' well-being.
Volume: 14
Issue: 3
Page: 1620-1628
Publish at: 2025-09-01

Prevalence and health literacy on high blood pressure among late adulthood individuals in Northeast Thailand: a cross sectional study

10.11591/ijphs.v14i3.24980
Kittipong Sornlorm , Arunrat Puncha Glingasorn
High blood pressure (HBP) is a leading risk factor for atherosclerotic cardiovascular disease and mortality. This study aimed to identify health literacy and other characteristics associated with HBP among late adults in Thailand. A cross-sectional study was conducted with 1,345 adults aged 35-59 years from Health Centers 7, 8, 9, and 10 in Northeast Thailand. Descriptive statistics and a generalized linear mixed model (GLMM) were used to determine the adjusted odds ratio (Adj. OR) and 95% confidence interval (CI). Results showed a prevalence of HBP at 24.76% (95% CI: 22.52-27.13). Multivariable analysis revealed a significant association between HBP and health literacy in finding health information (Adj. OR = 1.59, 95% CI: 1.28-1.96, p-value<0.001), as well as judging health information (Adj. OR = 1.34, 95% CI: 1.04-1.73, p-value=0.024). Additionally, history of smoking (Adj. OR=2.04, 95% CI: 1.29-3.24, p-value = 0.002), comorbidity (Adj. OR = 2.20, 95% CI: 1.76-2.74, p-value <0.001), physical activity (Adj. OR = 1.67, 95% CI: 1.28-2.16, p-value <0.001), and body mass index (Adj. OR = 2.21, 95% CI: 1.14-4.26, p-value=0.018) were found to be associated with HBP. Poor health literacy increases the risk of HBP. Relevant authorities must evaluate the group context and develop a suitable health literacy model.
Volume: 14
Issue: 3
Page: 1576-1584
Publish at: 2025-09-01

Attitude as a mediator between socio-ecological factors and non-communicable disease management: a study protocol

10.11591/ijphs.v14i3.25308
Azrin Shah Abu Bakar , Haliza Abdul Rahman , Ahmad Iqmer Nashriq Mohd Nazan
Non-communicable diseases (NCDs) have risen in Malaysia, and people with low socioeconomic status are more vulnerable to NCDs. Previous studies on the management of non-communicable disease have focused on aspects of socioeconomic factors, individual factors, and psychosocial factors. However, there is limited information on socio-ecological factors (e.g. intrapersonal, interpersonal, organizational, community, and societal factors) and their direct and indirect effect of socio-ecological factors on non-communicable disease management mediated by attitude has not been investigated. Thus, this study aimed to investigate the role of attitude as a mediator between socio-ecological factors and non-communicable disease management among support staff in Putrajaya, Malaysia. A cross-sectional study using cluster random sampling will be conducted at selected Ministries, in Putrajaya Malaysia. The questionnaire will assess respondents’ background information, knowledge of non-communicable disease, attitude towards preventing non-communicable disease and chronic illness resources survey (CIRS) to measure socio-ecological factors. Descriptive and inferential statistics will be used in data analysis using SPSS and SEM with AMOS software. The findings will provide a theoretical model for understanding the various factors that determine towards non-communicable disease management through mediation of attitude.
Volume: 14
Issue: 3
Page: 1387-1393
Publish at: 2025-09-01
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