Articles

Access the latest knowledge in applied science, electrical engineering, computer science and information technology, education, and health.

Advanced Search
Filter Icon

Filters article

Years

FAQ Arrow
Single Year
Range Year
0
0

Source Title

FAQ Arrow

Authors

FAQ Arrow

31,456 Article Results

Comparative assessment of knowledge, attitude, and practice toward self-medication among health and non-health students at Daffodil International University, Dhaka (2022–2023)

10.11591/ijphs.v15i1.26866
Md. Mizanur Rahman , Md. Jahir Alam , Ms Tamanna Khatun , Chaity Sutar , Shabnaz Akter , As-Ad Din Mahmood , Sher Mostafa Sadiq Khan
Self-medication, a popular self-care practice, is common throughout the world and is responsible for serious health complications. The present investigation assessed the knowledge, attitudes, and practices of self-medication among healthcare and non-healthcare students at Daffodil International University, Savar, Dhaka, Bangladesh. A cross-sectional survey of 240 students from the Pharmacy and Environmental Science Departments, ages 19 to 24, was carried out between October 2022 and January 2023. Socio-demographics, knowledge, attitudes, information sources, common medications, and diseases treated were all covered in the pre-tested questionnaire used to gather data. SPSS v16.0 with correlations and descriptive statistics was used for the analysis. Among 240 participants, 50.8% were health science students and 49.2% were non-health science students; 45.8% were male, and 54.2% were female. Most (74.2%, p < 0.01) were aged 21-22 years, mainly in the 4th year (43.3%, p < 0.001). Knowledge analysis showed 37.5% knew over-the-counter (OTC) drugs (p < 0.001) and 55% supported self-medication for minor illness. Common conditions treated were headache (49.2%), fever (23.3%), and cold (16.7%). Painkillers were the most used drugs (39.2%), with family members as the main source of advice (50%). Knowledge had a significant correlation with health science students (p < 0.001). Attitudes revealed 70% used self-medication in the last 6 months; 67.5% discouraged peers, 55.8% reused prescriptions, 73.3% read leaflets, and 61.2% consulted doctors for adverse effects. Previous experiences (74.2%) were the main reason for self-medication. Self-medication is widespread among university students. Health science students demonstrated better knowledge and awareness against self medication while contrasted to non-healthcare students. Awareness programs are needed for all groups.
Volume: 15
Issue: 1
Page: 266-273
Publish at: 2026-03-05

Emotional experiences of Indonesian health science students with self-harm: a phenomenological study

10.11591/ijphs.v15i1.26841
Meidiana Dwidiyanti , Geovanny Serviam Permana Putri Rahamitu , Luky Dwiantoro , Nur Setiawati Dewi , Sri Padma Sari , Alifia Dian Yusriana
Health students often face academic pressure and interpersonal conflicts that can affect their emotional regulation, thereby increasing the risk of self-harm behavior. This study aimed to explore the emotional experiences of health students who have engaged in self-harm through a phenomenological approach. A total of 8 participants (aged 18-25 years) who had engaged in self-harm and came from various health study programs participated in in-depth interviews lasting 45-70 minutes. The results of the study reveal three main themes: i) psychosocial stress as a trigger for negative emotions, ii) the role of social support in the recovery process, and iii) coping mechanisms and the need for professional intervention. These findings reveal emotional dynamics that have not been widely explored in the context of health students in Indonesia, particularly how self-harm is perceived as a strategy to control excessive emotional intensity. This study makes a new contribution by highlighting the need for interventions based on emotional regulation and increased social support that are appropriate to the subjective experiences of health students. Interventions based on empathy and psychological approaches that are more sensitive to the cultural context of the campus are the main recommendations.
Volume: 15
Issue: 1
Page: 283-296
Publish at: 2026-03-05

Calgary family intervention model enhances dietary compliance and knowledge in T2DM patient

10.11591/ijphs.v15i1.26901
Muhtar Muhtar , Aniharyati Aniharyati , Julhana Julhana , Fadlurahmi Fadlurahmi , Muhammad Arifki Zainaro , Martiningsih Martiningsih
The urgency was in developing a more holistic and sustainable approach to supporting type 2 diabetes mellitus (T2DM) patients. This study evaluated the effectiveness of the Calgary Family Intervention Model (CFIM) in improving dietary adherence and knowledge in patients with T2DM. This study used a quantitative method with a quasi-experimental design, involving 280 patients with type 2 diabetes mellitus at the Bolo Community Health Center from January to October 2025. The sample was divided into two groups: intervention (CFIM education) and control (booklet). Data were collected using a valid and reliable questionnaire to measure knowledge and dietary adherence. Data analysis was performed using the Wilcoxon and Mann-Whitney tests. The analysis showed significant results, with the mean knowledge score in the intervention group increasing from 4.84±1.235 to 8.98±2.851 (p < 0.05), while in the control group, it increased from 4.64±1.120 to 7.06±1.219. For dietary adherence, the intervention group showed an increase from 27.00±6.518 to 61.38±7.171 (p = 0.000), compared to the control group, which increased from 27.28±5.592 to 49.44±10.194(p < 0.05). The implications of these results have the potential to strengthen the family-based health intervention model and improve the overall well-being of T2DM patients. This study contributes significantly to family nursing practice by demonstrating the efficacy of the CFIM in enhancing dietary adherence and knowledge among patients with T2DM.
Volume: 15
Issue: 1
Page: 150-159
Publish at: 2026-03-05

Hepatotoxicity effect of alcoholic beverages on histology and IL-6 gene detection in Rattus norvegicus using polymerase chain reaction

10.11591/ijphs.v15i1.27001
Fitria Diniah Janah Sayekti , Vector Stephen Dewangga , Muhammad Taufiq Qurrohman
The liver is an organ that has an important role in metabolic and detoxification processes. Alcohol consumption will cause metabolic disorders in the liver and can cause changes in histological structures. Interleukin-6 has a profound role in liver pathology and plays an important role in the body's defense mechanism, and contributes to the manifestation of tissue damage. This study was an experimental study using 20 Rattus norvegicus treated with 25% alcohol, and a normal treatment only given distilled water. Histological observations were carried out on each preparation in 5 fields of view. The hepatotoxicity effect of alcohol was observed based on the presence of cell degeneration and necrosis in histological preparations stained with hematoxylin eosin. IL-6 detection with polymerase chain reaction was analyzed qualitatively using electrophoresis. Based on the statistical test results, the sig. (2 tailed) of 0.00 < 0.05 so that it can be seen that there is a significant difference in histological results between the normal control group without treatment and the group induced by alcohol. The administration of alcoholic beverages with 25% ethanol content in vivo for 21 days causes necrosis and bleeding around the hepatocyte cells. IL-6 overview appeared to be stronger in the group with alcohol-induced drinking, it could indicate that giving alcohol causes a higher inflammatory response. This study provides scientific evidence that alcohol consumption significantly damages the liver. Further research can be conducted to increase the sample size and quantitatively assess IL-6 expression.
Volume: 15
Issue: 1
Page: 190-196
Publish at: 2026-03-05

Analysis of the implementation of the healthy Indonesia program policy with a family approach

10.11591/ijphs.v15i1.26855
Abdul Haris , M. Rizki Aditya
This study evaluates the implementation of the Healthy Indonesia Program Family Approach to improve public health and identify inhibiting and supporting factors. This qualitative research employs a case study approach to investigate healthcare dynamics at the Tambora Community Health Center in Bima City, Indonesia. Twelve informants were purposively selected. Data collection involved in-depth interviews, direct observation, and document review, allowing for a multifaceted perspective. An interactive analysis model by Miles and Huberman was used for data analysis, incorporating data collection, reduction, and presentation iteratively. Results showed that 85% of implementing staff had been trained, but there was a shortage of field surveyors, and family visit coverage only reached 72%, below the national target of 80%. Although the average healthy family index of 0.65 indicates adequate results, the main challenges lie in clean living behavior and nutritious diets. The program for mothers giving birth in health facilities reached 95%, but awareness of improving the management of chronic diseases, such as hypertension and tuberculosis, remained low, with treatment fulfillment at 65% and 70%, respectively. The conclusions highlight the need for adaptation strategies and continuous evaluation for the Healthy Indonesia Program to be successful across communities.
Volume: 15
Issue: 1
Page: 232-241
Publish at: 2026-03-05

Strengthening intensive care training in response to COVID-19: lessons for medical education

10.11591/ijphs.v15i1.22918
Mochamat Helmi , Djayanti Sari , Yenny Sulistyowati , Andreasta Meliala , Tjahja Nurrobi , Tugas Ratmono , Laksono Trisnantoro
Frequent updates to clinical guidelines during the COVID-19 pandemic have posed significant challenges for audit processes, quality improvement, and the preparedness of healthcare professionals, particularly in intensive care settings. This study aimed to explore the impact of COVID-19-related demands on medical education and training from the perspective of healthcare teams working in intensive care units (ICUs) in Indonesia during the first wave of the pandemic. A qualitative design was employed using semi-structured interviews and focus group discussions with medical personnel directly involved in the care of COVID-19 patients at national referral hospitals. Purposive sampling was applied to recruit participants, including general practitioners, interns, residents, anesthesiologists, and ICU consultants. A total of 66 participants were included across eight focus group discussions, each consisting of eight to nine participants. Data collection continued until thematic saturation was achieved. Transcripts were analyzed using content analysis to identify key themes and subthemes. The analysis revealed five major themes: i) the need for continuous upgrading of knowledge and competencies, ii) the importance of innovative education and training approaches, iii) the role of professional organizations, iv) challenges encountered during training implementation, and v) time constraints. These findings highlight the urgent need for adaptive, continuous, and technology-supported training strategies to strengthen intensive care workforce preparedness during public health emergencies.
Volume: 15
Issue: 1
Page: 23-31
Publish at: 2026-03-05

Effects of soy plus zinc supplementation on growth and kidney health in Wistar rats: Implications for childhood stunting prevention

10.11591/ijphs.v15i1.26895
Yuniastini Yuniastini , Purwati Purwati , Antun Rahmadi , Sulastri Sulastri , Wien Wiratmoko , Iradah Lia Prasetio , Hendri Busman , Muhammad Al Hafidz , Fannia Khairani Mz , Mohammad Hafid Hak
Zinc deficiency can cause growth and health problems, whereas protein from soy sources contributes to essential nutritional intake. This study aimed to evaluate the effects of soy plus zinc (SPZ) supplementation on growth and kidney health in Wistar rats. This study used a randomized controlled trial design with 24 rats divided into five treatment groups, including a control group. SPZ supplementation was administered daily for 14 days with varying zinc doses (0.020 mg and 0.035 mg per gram of body weight) and palatability enhancement using vanilla flavoring. Data obtained through measurements of initial and final body weights and kidney weights were analyzed using ANOVA to determine significant differences between groups. The results showed that SPZ supplementation positively contributed to growth, as evidenced by a significant increase in the final weight of rats compared to their initial weight (p < 0.05). Histological analysis of the kidneys indicated no visible structural damage, and the average increase in kidney weight was approximately 26.5%. The combination of soy and zinc in SPZ was shown to have a synergistic effect that benefits the development and kidney health of rats, demonstrating its potential application in the context of animal nutrition.
Volume: 15
Issue: 1
Page: 140-149
Publish at: 2026-03-05

A novel single-switch DC-DC converter using the coupled inductor with ultra-high voltage gain

10.11591/ijpeds.v17.i1.pp476-486
Kim-Anh Nguyen , Thai Anh Au Tran , Xuan Khanh Ho , Duong Thach Pham
This paper presents an extremely high step-up DC-DC converter using a quadratic topology and a coupled inductor (CI). The proposed converter (PC) utilizes a single switch, simplifying the control strategy and reducing switching losses. A passive clamp circuit recycles leakage energy, reducing voltage stress (VS) on the MOSFET and enabling the implementation of a low on-state resistance switch for higher efficiency. Additionally, the quadratic structure and passive clamp circuit contribute to higher voltage gain (VG) and better performance. The converter’s operating principles, steady-state analysis, and component selection criteria are discussed in detail. The influence of magnetizing inductance, duty cycle, and parasitic components on the VG is also investigated, along with the system’s dynamic response under input voltage and load variations to ensure stable operation. A comparative evaluation with existing converters highlights its advantages. The PC is verified through SIMPLIS simulations, where key performance metrics such as VG and switching stress are analyzed. Furthermore, a hardware prototype with a power rating of 300 W is built to confirm the theory and showcase the converter’s performance. Experimental results demonstrate high efficiency, stable operation, and substantial VG, validating the converter’s feasibility for renewable energy systems (RES).
Volume: 17
Issue: 1
Page: 476-486
Publish at: 2026-03-01

A new boost LED driver

10.11591/ijpeds.v17.i1.pp602-616
Dzhunusbekov Erlan , Orazbayev Sagi
Reducing the cost, increasing efficiency, and improving the reliability of LED drivers are critical due to the widespread adoption of LED lighting. This paper presents a research study on a novel boost LED driver designed to minimize voltage pulsations across power switches, thereby reducing dynamic losses in all power components. A small number of Schottky diodes were used to reduce conduction losses. To reduce switching losses in semiconductors, a quasi-resonant switching (QRS) at zero current was implemented for driving transistors. The operating principle is analyzed using computer modeling and validated experimentally in critical conduction mode (CrCM). In the initial evaluation, one version of the proposed driver achieved a high efficiency of up to 98.7% at 120 W input power. Additionally, the size and value of the main inductor were significantly reduced. The proposed driver provides an efficient and scalable solution for high-power LED lighting. Lower dynamic losses and reduced impulse voltages create opportunities for integrating the control circuit and power switches into a single chip.
Volume: 17
Issue: 1
Page: 602-616
Publish at: 2026-03-01

Design and improvement of dynamic performance of solar-powered BLDC motor for electric vehicles in agricultural applications

10.11591/ijpeds.v17.i1.pp168-179
Savitri Medegar , M. Sasikala
One of the most pressing environmental problems is the rapid increase in the production of greenhouse gases by transportation vehicles. This paper looks into SPEVs, or solar-powered electric vehicles. The answer to the problems of transportation-related pollution and fuel usage. In an electric vehicle, the power comes from a battery that may be charged by solar panels or any other external power source. By making use of the perturb and observe (P&O) maximum power point tracking (MPPT) controller, one can achieve maximum power. The DC voltage that the photovoltaic module produces is amplified when it is fed into a voltage source inverter (VSI) via this enhanced output. The tool for the job here is a buck-boost converter. To power their wheels, EVs rely on brushless direct current (BLDC) motors and variable speed inverters (VSIs), which transform DC power from solar panels into AC power. We compare the efficiency of electric vehicles (EVs) attained by raising converter voltages and battery state of charge (SoC) using a PI controller, and we look at the performance of photovoltaic (PV) and brushless linear direct current (BLDC) motors. We use MATLAB/Simulink to do the validation.
Volume: 17
Issue: 1
Page: 168-179
Publish at: 2026-03-01

Fuzzy logic direct torque control of induction motors using three-level NPC inverter

10.11591/ijpeds.v17.i1.pp180-194
Jamila Chennane , Lahcen Ouboubker , Mohamed Akhsassi
Induction motor drives are extensively used for their robustness and efficiency, but precise control remains difficult under dynamic conditions. Conventional direct torque control offers a simple structure and fast response, but is limited by torque ripple, flux distortion, and poor low-speed performance. This paper proposes a fuzzy logic-based direct torque control (FDTC) combined with a three-level neutral point clamped (NPC) inverter. A fuzzy inference system (FIS) replaces the hysteresis comparators and switching table, while speed regulation is improved using a PI-fuzzy controller. MATLAB/Simulink simulations under speed variations and load disturbances demonstrate reduced torque and flux ripples, smoother flux trajectories, improved current waveforms, and faster transient response compared with classical DTC. These results confirm that the FDTC–NPC approach provides a robust and efficient solution for advanced applications such as industrial automation, renewable energy, and electric vehicles.
Volume: 17
Issue: 1
Page: 180-194
Publish at: 2026-03-01

High efficient DC-AC inverter for low wireless power transfer applications

10.11591/ijpeds.v17.i1.pp453-464
Kyrillos K. Selim , Hanem Saied Ebrahem Torad , Mostafa R. A. Eltokhy , Hesham F. A. Hamed , Mohamed Elzalik
The inverter's simplicity is an important aspect that must be considered especially for electronic devices, as adding the number of power switches increases the complexity and overall cost of the inverter. This work proposes an inverter design that converts DC into AC power. It receives 12 VDC as an input voltage, and it is composed of a boost converter that converts an input voltage of 5-20 VDC to an output voltage of 4-30 VDC and a pulse width modulation controller to produce a square wave with a frequency of 100 kHz to drive the switching MOSFET. The designed inverter can be operated on different loads ranging from 50 Ω to 1000 Ω, tested in both simulations and experimentally. The design was optimized by the LT Spice simulator. The proposed inverter has operating frequencies ranging from 40 kHz to 110 kHz, taking into account different loads. The obtained results showed that both simulation and experimental results converged, whereas the highest efficiency was 96.96% at 55 kHz at a fixed load of 100 Ω. On the other hand, the maximum achieved efficiency when the load was sweeping was 80% at a load of 50 Ω at a fixed frequency of 100 kHz.
Volume: 17
Issue: 1
Page: 453-464
Publish at: 2026-03-01

A framework for robust PID controller design: an optimization-based approach for inductive loads

10.11591/ijpeds.v17.i1.pp359-369
Ali Abderrazak Tadjeddine , Miloud Kamline , Latifa Smail , Soumia Djelaila , Hafidha Reriballah
This paper presents a comprehensive comparative study of proportional-integral-derivative (PID) controller tuning methodologies for inductive load applications across three representative scenarios. We systematically evaluate classical methods (Ziegler-Nichols, internal model control) against global optimization algorithms (genetic algorithm (GA), particle swarm optimization (PSO)) applied to resistor-resistor-inductor (RRL) circuit models. Results demonstrate that PSO achieves superior performance for moderate-to-slow systems, reducing settling time by 84% while completely eliminating overshoot compared to Ziegler-Nichols. The algorithm automatically discovers optimal PI controller structures, simplifying implementation. However, for ultra-fast systems (time constants < 1 ms), internal model control proves more reliable, achieving 0.84 ms settling with only 0.16% overshoot. Optimized controllers demonstrate exceptional robustness, maintaining stability under ±50% parameter variations and effectively rejecting disturbances. This research provides engineers with a scenario-based framework for method selection, moving beyond heuristic tuning to achieve previously unattainable performance levels. The findings establish optimization-based tuning as a systematic, reliable approach for high-performance control system design in industrial applications.
Volume: 17
Issue: 1
Page: 359-369
Publish at: 2026-03-01

Machine learning based models for solar energy

10.11591/ijpeds.v17.i1.pp752-764
Dalila Cherifi , Abdeldjalil Dahbi , Mohamed Lamine Sebbane , Bassem Baali , Ahmed Yassine Kadri , Messaouda Chaib
Photovoltaic (PV) technology is one of the most promising forms of renewable energy. However, power generation from PV technologies is highly dependent on variable weather conditions, which are neither constant nor controllable, which can affect grid stability. Accurate forecasting of PV power production is essential to ensure reliable operation within the power system. The primary challenge of this study is to accurately predict photovoltaic energy production, considering that weather conditions, such as irradiance, temperature, and wind speed, are random variables. The key contribution of this article is developing a machine learning model to predict the energy production of a real PV power plant in Algeria. Using real measurements sourced from the Center of Renewable Energy Development (CDER) in Adrar, Algeria, in 2021. The data are from two PV power plants located in harsh desert climate conditions. The results presented in this study offer a comparison of several predictive methods applied to real-world data from a PV power plant situated in the Saharan Region. Our findings reveal that the artificial neural network (ANN) model yields the most accurate predictions of 94.96%, with the smallest prediction error: root mean square (RMSE) and mean absolute error (MAE) are 7.78% and 3.80%, respectively.
Volume: 17
Issue: 1
Page: 752-764
Publish at: 2026-03-01

Application of machine learning for production optimization and predictive maintenance in an iron processing plant

10.11591/ijpeds.v17.i1.pp765-776
Lakhdari Lahcen , Mohamed Habbab , Alhachemi Moulay Abdellah
The modern metallurgical industry requires advanced solutions for process optimization, cost reduction, and predictive maintenance. This paper proposes a unified simulation-based framework using machine learning (ML) to jointly address production optimization and maintenance prediction in a virtual iron processing environment. Several ML models, including random forest (RF), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), support vector machine (SVM), and k-nearest neighbors (k-NN), were evaluated on synthetic datasets representing production, maintenance, and transport processes. A reproducible methodology was adopted, including preprocessing, time-aware data splitting, and cross-validation to prevent information leakage. Model performance was assessed using F1-score, area under the receiver operating characteristic curve (AUC), and regression metrics. Tree-based models achieved near-perfect classification performance (AUC ≈ 1, precision and recall > 0.99), while light gradient boosting machine (LightGBM) and CatBoost provided the best regression accuracy. Feature importance analysis using SHapley Additive exPlanations (SHAP) identified vibration and temperature as key maintenance indicators. Although based on simulation, the framework is designed for integration with supervisory control and data acquisition (SCADA) and the Industrial Internet of Things (IIoT), supporting real-time industrial deployment and alignment with operational key performance indicators.
Volume: 17
Issue: 1
Page: 765-776
Publish at: 2026-03-01
1 2 3
...
2097 2098
Show 120 of 2098

Discover Our Library

Embark on a journey through our expansive collection of articles and let curiosity lead your path to innovation.

Explore Now
Library 3D Ilustration