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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

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

An efficient machine learning framework for optimizing hyperspectral data analysis in detecting adulterated honey

10.11591/ijeecs.v39.i3.pp1776-1786
Ashwini N. Yeole , Guru Prasad M. S. , Santosh Kumar
Honey adulteration detection involves employing spectral data, often utilizing machine learning (ML) techniques, to identify the presence of impurities or additives in honey. This study aims to explore ML models through the collection of a hyperspectral honey dataset with limited samples and 128 features. Three distinct feature selection (FS) methods i.e., Boruta, repeated incremental pruning to produce error reduction (RIPPER), and gain ratio attribute evaluator (GRAE) are applied to extract important features for decision-making. Then, the feature-selected dataset is classified through four effective ML algorithms, such as support vector machine (SVM), random forest (RF), logistic regression (LR), and decision tree (DT). Accuracy, F1-score, Kappa Statistics, and Matthews correlation coefficient (MCC) are the performance metrics used to assess the results of ML algorithms. RIPPER FS technique gave the best results by improving its accuracy values from 79.05% (primary data) to 91.89% (augmented data) for the RF classifier model and 74.93% (primary data) to 91.89% (augmented data) for the DT classifier model. These detailed examinations of the experiments demonstrate that proper finetuning of the ML methods can play a vital role in optimizing hyperspectral data analysis for detecting adulteration levels in honey samples.
Volume: 39
Issue: 3
Page: 1776-1786
Publish at: 2025-09-01

Solar cell-based garden light automation for environmentally friendly technology learning

10.11591/ijpeds.v16.i3.pp1457-1471
Afrizal Mayub , Fahmizal Fahmizal , Lazfihma Lazfihma
This research aims to: 1) Produce a prototype design for a solar cell-based automatic garden lighting system; 2) Determine the relationship between current, power, and voltage and light intensity; 3) Describe the feasibility of an environmentally friendly technology practicum guidebook; and 4) Describe teacher and student responses to the environmentally friendly technology practice guidebook. This research is R&D type Analysis, Design, Development, Implementation and Evaluation (ADDIE) Analysis, design, development, implementation and evaluation. The research sample used 44 class IX students at MTS Rahmatullah. According to students, aspects of teaching materials, aspects of content, and difficulty of teaching materials at school are inadequate at 84.25%, 80% and 82.5%. Student interest in environmentally friendly technology practicum guidebooks was 84.25%. The higher the light intensity, the higher the current, power, and voltage. Expert validation shows; the prototype of an automatic garden lighting system based on solar cells and a practical guidebook on environmentally friendly technology are very suitable for use (89.14% and 90.75%). The use of environmentally friendly technology practicum guidebooks increased students' critical thinking skills in the high category (N-Gain = 0.7937) and received responses from teachers and students in the "almost all" category (91.50% and 89.9%).
Volume: 16
Issue: 3
Page: 1457-1471
Publish at: 2025-09-01

Islanding detection of integrated DG system using rate of change of frequency over reactive power

10.11591/ijpeds.v16.i3.pp1637-1644
B. V. Seshu Kumari , Ambati Giri Prasad , S. Sai Srilakshmi , Karri Sairamakrishna Buchireddy , Ch. Rami Reddy
This paper offers a passive islanding detection method that is effective for distributed generation. When a distributed generator (DG) keeps a location powered even when access to the external electrical grid is lost, this circumstance is referred to as islanding. The power distribution system currently includes distributed generators (DGs), which provide inexpensive electricity and have fewer environmental impacts. Sometimes, these DGs continue to supply the nearby loads because of line outages and islands made by system separations. As a result, there are scenarios with unacceptable power quality. The islanding is identified if the result of the rate of change of frequency over reactive power exceeds the threshold value. The MATLAB test results from this study demonstrate the effectiveness of the suggested approach for different islanding and non-islanding scenarios.
Volume: 16
Issue: 3
Page: 1637-1644
Publish at: 2025-09-01

Wireless charging Class-E inverter for zero-voltage switching over coupling coefficient range

10.11591/ijpeds.v16.i3.pp1752-1764
Anon Namin , Chuchat Donloei , Ekkachai Chaidee
A novel and practical methodology is presented in this study for designing contactless wireless energy systems using resonant-mode Class-E converters, aiming to sustain efficient soft-transition switching under various levels of magnetic coupling, even under coil misalignment. The approach integrates the wireless power transfer (WPT) circuit with the inverter’s series resonant network and analytically derives the relationship between the coupling coefficient and impedance phase angle to identify zero voltage switching (ZVS) conditions. A key contribution is the use of the maximum expected coupling coefficient as a critical design point to ensure ZVS across practical variations. A complete step-by-step design procedure is provided. Simulation and experimental results confirm that the inverter achieves and maintains ZVS for coupling values in the range 0 < k ≤ kdesigned, with efficiencies reaching up to 95%. This work supports the advancement of soft-switching inverter design to enable robust and efficient WPT systems under practical misalignment conditions.
Volume: 16
Issue: 3
Page: 1752-1764
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

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

Enhancement of power quality of grid integrated photo voltaic system using active power filter

10.11591/ijpeds.v16.i3.pp2017-2029
Praveen Kamat , Anant Naik
The world's population's energy needs are growing daily, while at the same time, fossil fuels are being reduced at an alarming rate. Fossil fuel burning also increases pollution and causes global warming. Renewable energies are now being extensively used to generate electricity, so the dependence on fossil fuels is considerably reduced. Among the primary sources of alternative energy used to create power is photovoltaic (PV) technology. A grid connected PV system is the most widely recommended. When PV is linked to the grid, two main issues are the maximum power that can be taken out of it and the quality of the electricity placed into it. With the help of neural networks, the maximum power point tracking (MPPT) technology has been developed to increase the PV array's power harvesting. An active power filter (APF) had been created and analyzed using Instantaneous Reactive Power Theory, including the Chebyshev II low-pass filter. As required by IEEE 519, the total harmonic distortion (THD) with injected source current has been confirmed well within 5%. These results demonstrate that this method is a simple and efficient way to inject harmonic-free currents into the grid.
Volume: 16
Issue: 3
Page: 2017-2029
Publish at: 2025-09-01

Improving electrical energy efficiency through hydroelectric power and turbine optimization at the El Oued water demineralization plant in Algeria

10.11591/ijpeds.v16.i3.pp1881-1896
Khaled Miloudi , Ali Medjghou , Ala Eddine Djokhrab , Mosbah Laouamer , Souheib Remha , Yacine Aoun
This paper presents an investigation into the energy potential of the Albian aquifer in the Algerian Sahara at the El Oued water demineralization plant, focusing on its capacity to generate electrical power due to its high-pressure and high-temperature water reserves. We designed and implemented a turbine-generator system to convert hydraulic energy into electricity, achieving an average annual energy output of 1,804,560 kWh, which translates to a financial gain of approximately 345,888,600 DZD per year from energy savings. The selection of a Francis turbine was justified based on its efficiency, which ranges from 90% to 95%, and the system design was simulated using MATLAB-Simulink, demonstrating its robustness and effectiveness in managing the electrical network parameters. Our economic analysis indicates a high return on investment, confirming the feasibility of utilizing the Albian aquifer as a strategic asset for clean and reliable energy production in the region.
Volume: 16
Issue: 3
Page: 1881-1896
Publish at: 2025-09-01

Performance evaluation of multicarrier quadrature phase shift keying-based system under noisy channel conditions

10.11591/ijaas.v14.i3.pp693-701
Deepa Narayana Reddy , Aishwarya Nagaraju , Deepti Hosakere Prabhakara , Deekshitha Beeraganahalli Srinivas , Gandlaparthi Navyatha
A comprehensive analysis of quadrature phase shift keying (QPSK) modulation in both single input single output (SISO) and multiple input multiple output (MIMO) systems is conducted using MATLAB. The investigation focuses on evaluating QPSK performance with metrics such as signal-to-noise ratio (SNR) and bit error rate (BER) across diverse channel conditions. Furthermore, the study extends to encompass the integration of QPSK with orthogonal frequency division multiplexing (OFDM), with a particular emphasis on assessing spectral efficiency and error rate implications. To validate the accuracy of the simulations, QPSK and QPSK-OFDM configurations are implemented on the WiComm-T hardware platform, enabling a direct comparison of real-world performance metrics against simulation results. By offering practical insights and recommendations for the deployment of robust communication systems, this research underscores the inherent advantages of integrating OFDM with QPSK across both SISO and MIMO configurations.
Volume: 14
Issue: 3
Page: 693-701
Publish at: 2025-09-01

A hybrid features based malevolent domain detection in cyberspace using machine learning

10.11591/ijaas.v14.i3.pp916-927
Saleem Raja Abdul Samad , Pradeepa Ganesan , Amna Salim Rashid Al-Kaabi , Justin Rajasekaran , Murugan Singaravelan , Peerbasha Shebbeer Basha
The rise of social media has changed modern communication, placing information at our fingertips. While these developments have made our lives easier, they have also increased cybercrime. Cyberspace has become a refuge for modern cybercriminals to conduct destructive actions. Most cyberattacks are carried out through malicious links shared on social media platforms, emails, or messaging services. These attacks can have serious consequences for individuals and organizations, including financial losses, sensitive data breaches, and damage to reputation. Early identification and blocking of such links are crucial to protecting internet users and securing cyberspace. Current research uses machine learning (ML) algorithms to detect malicious hyperlinks based on observed patterns in uniform resource locators (URLs) or web content. However, cyberattack tactics are constantly changing. To address this challenge, this paper introduces a robust method that performs a fine-grained analysis of URLs for classification. Lexical and n-gram features are examined separately, with URL n-grams represented using Word2Vec embeddings. The results from hybrid feature sets are combined using a logistic regression (LR) model to increase overall classification accuracy. This robust method allows the system to use both the structural components of the URL and the fine-grained patterns obtained by the n-grams.
Volume: 14
Issue: 3
Page: 916-927
Publish at: 2025-09-01

Haystack-based Facebook’s data storage architecture: store, directory, and cache

10.11591/ijaas.v14.i3.pp671-681
Tole Sutikno , Ahmad Heryanto , Laksana Talenta Ahmad
Haystack is Facebook's unique way of managing large amounts of user-generated content like photos. The architecture prioritizes performance, reliability, and scalability to overcome network-attached storage system bottlenecks. Haystack speeds data access and ensures data integrity during hardware failures by using physical and logical volumes. This study examines the architecture of Facebook's Haystack data storage system and its effects on scalability and efficiency in handling large photo data. According to the study, the store, directory, and cache functions work together to reduce input/output (I/O) operations and improve metadata processing, which traditional network-attached storage systems cannot do. Haystack manages massive photo data storage and retrieval, solving network-attached storage (NAS) limitations. It balances throughput and latency by minimizing disk operations and optimizing metadata processing. Each store, directory, and cache contribute to this ecosystem. The Haystack architecture reduces disk operations and metadata processing bottlenecks with distributed caching. A cache allows instant access to frequently requested images and balances read and write operations across the system. We should study advanced storage system architectures based on Facebook's Haystack architecture. This could involve investigating faster metadata processing algorithms, using artificial intelligence (AI) to improve fault detection and repair systems, and assessing the economic impact of distributed caches.
Volume: 14
Issue: 3
Page: 671-681
Publish at: 2025-09-01

Deep learning for image classification of submersible pump impeller

10.11591/ijaas.v14.i3.pp838-848
Phan Nguyen Ky Phuc , Doan Huu Chanh , Trong Hieu Luu
This study presented a deep learning-based model in the submersible pump impellers quality inspection process. The proposed method aimed to relieve worker workload, automate the system, as well as increase the accuracy in defect detection and classification. The proposed approach aims to be implemented on systems with low investment cost and limited resources, i.e., small single-board computers, enabling flexible deployment in industrial environments. The model consisted of three convolutional neural network (CNN) models, i.e., visual geometry group 16 (VGG16), ResNet50, and a custom model. The outputs of three networks were either synthesized later through an ensemble stage or used separately. A graphical user interface (GUI) was also developed for real-time inspection and user-friendly interaction. The approach achieved up to 99.8% accuracy in identifying defects, including surface scratches, corrosion, and geometric irregularities. The proposed method improved the quality assurance process by reducing manual inspection efforts. Future research could explore advanced techniques like anomaly detection to further enhance system performance and versatility.
Volume: 14
Issue: 3
Page: 838-848
Publish at: 2025-09-01

Dissolved organic matter released from paper trash in water during ultraviolet irradiation: impacts on trihalomethane formation

10.11591/ijaas.v14.i3.pp869-877
Teguh Budi Prijanto , Nia Yuniarti Hasan , Kahar Kahar , Muammar Qadafi , Wisnu Prayogo
When exposed to ultraviolet (UV) light, paper trash could release dissolved organic matter (DOM) as a disinfection byproduct (DBP) precursor in water. This study was undertaken to assess the regulated DBPs, trihalomethanes-4 (THM4) generation potential, and estimated cytotoxicity of paper trash soaked in water during UV radiation. The UV irradiation was carried out at 1, 6, 12, 24, and 48 hours. The released organic material was determined using ultraviolet-visible (UV-Vis) adsorption at wavelengths ranging from 200 to 700 nm. Chlorination was carried out for 24 hours to determine THM4 formation potentials. According to the research findings, the longer the radiation period, the more THM4 species are formed in plain paper samples. On the other hand, the production of trichloromethane (TCM) on paper samples containing writing decreased as the UV radiation period increased. THM4 levels reached 103.12 and 150.57 µg/L for plain and writing paper samples, respectively. UV absorbance at 272 nm (A272) shows a 92% association with THM4 production, making it suitable as an initial characterization approach. Paper trash pollution in water could form carcinogenic DBPs, THM4, if used as a water source in a water treatment plant using chlorine disinfection.
Volume: 14
Issue: 3
Page: 869-877
Publish at: 2025-09-01
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