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Hydrothermal synthesis and defect-driven optical characterization of CdS nanoparticles for semiconductor and solar applications

10.11591/ijape.v15.i1.pp440-448
Deepti Bhargava , R. K. N. R. Manepalli , M. C. Rao , P. Venkata Ramana Rao , N. S. Subba Rao , A. Narendra Babu , P. Sree Brahmanandam
Nanoparticles (NPs) play a crucial role in advancing technology, particularly by enhancing the performance of energy storage in semiconductor applications. The synthesis of NPs with reduced particle size and increased surface area, along with a higher number of active sites, facilitates improved ion diffusion, making them highly suitable for such applications. Various methods have been employed to reduce the size of NPs, depending on factors such as purity and controlled composition. The present study focuses on controlling both the size and composition of cadmium sulfide (CdS) NPs, aiming to achieve a high surface-to-volume ratio. These NPs were synthesized using a hydrothermal method in a high-pressure autoclave. The evaluation of the synthesized inorganic CdS-NPs for technological applications requires experimental validation of their characteristics, including particle size, energy band gap, thermal stability, temperature response, as well as optical and electronic properties. The results obtained using the proposed methods reveal a bandgap of 2.28 eV, a hexagonal wurtzite structure with an average crystallite size of 10.26 nm, reduced effective mass, and an intense absorption peak at a higher wavelength. These characteristics indicate that the synthesized CdS nanoparticles are suitable for various applications, including high-power semiconductors, solar energy harvesting, optoelectronic devices, and materials for energy and electrical engineering.
Volume: 15
Issue: 1
Page: 440-448
Publish at: 2026-03-01

A bibliometric review of critical chain project management in construction

10.11591/ijaas.v15.i1.pp272-280
Dhiraj S. Bachwani , MohammedShakil S. Malek , Deep Shaileshkumar Upadhyaya , Neetu Yadav
This study offers an extensive bibliometric analysis of critical chain project management (CCPM) research over the past twenty years, seeking to elucidate the discipline’s developmental trajectory and pinpoint emerging research frontiers. A comprehensive review of the literature revealed fundamental principles of CCPM, highlighting essential components such as buffer management strategies and resource-constrained scheduling methodologies. This initial analysis established the theoretical framework for the quantitative study and facilitated the identification of suitable metrics to integrate both foundational theories and contemporary advancements in CCPM scholarship. The study examined approximately 1,800 academic publications, including journal articles, conference proceedings, review papers, and book chapters published from 2000-2022, obtained from the Scopus database. The analytical framework encompassed various bibliometric dimensions, including performance metrics, relationship indicators, conceptual frameworks, publication characteristics, and VOSviewer network analysis, as essential elements of the data examination process. The developed framework has two main goals: it helps researchers find important publications, potential collaborators, and new areas of research, and it gives practitioners a structured place to store information about how to use CCPM methods in complicated projects with few resources.
Volume: 15
Issue: 1
Page: 272-280
Publish at: 2026-03-01

A novel 9-level fourfold-boost switched capacitor inverter (N9L-FBSCI) configuration utilizing fewer components and optimized active switches

10.11591/ijape.v15.i1.pp132-140
N. Subhashchandrabose , I. Kumaraswamy
Multilevel inverter (MLI) topologies are more important in high-voltage applications where the most common design tends to have significant disadvantages, including being very component when it comes to the switch voltage stress, control scheme, and also not self-voltage balanced. These problems lead to higher cost, lower efficiency, and lower reliability. This paper will therefore develop a new nine-level fourfold-boost switched capacitor inverter (N9L-FBSCI) without increasing the number of components but ensures greater voltage gains and ease of use. It uses only one DC source, eight active switches, and two capacitors with a self-balancing mechanism of the voltage, avoiding extra balancing of the voltage. A four fold voltage gain is achieved using fewer switching devices per stage and less blocking voltage to control across switches. An efficient control is achieved by a level-shifted phase disposition PWM (LS-PDPWM) technique. Analytical and comparative testing against recent MLI design proves that the topology proposed has better voltage boosting and efficiency using the least number of components. Simulation and experimental verification prove the practical efficiency of the N9L-FBSCI, which can achieve a 400 V peak output with low total harmonic distortion. The topology has a high potential in renewable and industrial fields with cost effective high performance. Experimental and simulation data support an output voltage of 400 V at an output load current of 2 A with RL loading (100 Ω, 100 mH) delivering 400 W power output. The efficiency in the case of the inverter reaches its peak at 97.84% and voltage and current total harmonic distortion (THD) of 16% and 6%, correspondingly. The present proposed N9L-FBSCI has a better voltage gain and fewer components than available nine-level topologies without altering the delight of the wave position.
Volume: 15
Issue: 1
Page: 132-140
Publish at: 2026-03-01

Extending battery life and reducing charging costs in electric vehicles through converter selection for on-board chargers

10.11591/ijape.v15.i1.pp14-22
Jangam Kishore Babu , Ganney Poorna Chandra Rao , Puvvula Venkata Rama Krishna , Swathi Karike , Sailaja Kethireddy , Sareddy Venkata Rami Reddy , B. Nagi Reddy , Rekha Rangam
The electric vehicle (EV) sector is among the quickly expanding industries today. Global commitment to reducing pollution levels promotes interest in EVs. Fuel combustion engines emit around 10% of the globe's greenhouse gas emissions, which exacerbate the greenhouse effect. The emissions from electric vehicles are 17–27% less than those from internal combustion engines. The short battery life, high cost of charging, and lack of charging stations are some disadvantages of electric vehicles. The goal of this study is to suggest the ideal converter for the on-board charger (OBC), one that can extend battery life by lowering charging current at extremes of state of charge (SOC) and lower charging costs by increasing power factor (PF). The current control range than the isolated converter using transformers. Lastly, an analysis of the MATLAB/Simulink output findings is conducted to verify the effectiveness of the suggested OBC design with a non-isolated converter.
Volume: 15
Issue: 1
Page: 14-22
Publish at: 2026-03-01

High impedance fault discrimination in microgrid power system using stacking ensemble approach

10.11591/ijape.v15.i1.pp98-109
Arangarajan Vinayagam , Raman Mohandas , Meyyappan Chindamani , Bhadravathi Gavirangapa Sujatha , Soumya Mishra , Arivoli Sundaramurthy
High impedance (HI) faults in microgrid (MG) power systems are non-linear, intermittent, and have low fault current magnitudes, making them challenging to detect by typical protective systems. Consequently, it is imperative to implement a sophisticated protection system that is dependent on the precision of fault detection. In this study, a stacking ensemble classifier (SEC) is proposed to discriminate HI fault from other transients within a photovoltaic (PV) generated MG power system. The MG model is simulated with the introduction of faults and transients. The features of data set from event signals are generated using the discrete wavelet transform (DWT) technique. The dataset is used to train the individual classifiers (Naïve Bayes (NB), decision tree J48 (DTJ), and K-nearest neighbors (KNN)) at initial and meta learner in the final stage of SEC. The SEC outperforms other classification methods with respect to accuracy of classification, rate of success in detecting HI fault, and performance measures. The outcomes of the classification study conducted under standard test conditions (STC) of solar PV and the noisy environment of event signals clearly demonstrate that the SEC is more dependable and performs better than the individual base classification approaches.
Volume: 15
Issue: 1
Page: 98-109
Publish at: 2026-03-01

Blade number and angle effect the archimedes spiral wind turbine performance

10.11591/ijape.v15.i1.pp393-402
Rosadila Febritasari , Muhammad Ibnul Abidin
The efficiency and performance of Archimedes spiral wind turbine (ASWT) are affected by the design and number of turbine blades which can convert the kinetic energy of the wind into mechanical energy to turn a generator that can produce electricity as much as possible in low wind speed. This study aims to obtain the optimal ASWT design in low wind speed in terms of aerodynamic performance. The method is conducted by numerically computational fluid dynamics (CFD) simulation on the fixed-opening angle and the blades number variations. The results show that the smallest C_D value is -2.18 at the 65° of opening angle, the largest C_L value at the 45° of opening angle is 0.37, and the largest C_M value is 0.61 at the 65° of opening angle and 4 blades. Therefore, it can be concluded that the Archimedes wind turbine with 4 blades and 65° pitch is the optimal.
Volume: 15
Issue: 1
Page: 393-402
Publish at: 2026-03-01

Current state of production of аlternative energy on the Absheron Peninsula

10.11591/ijape.v15.i1.pp37-45
Ramil Sadigov Ali , Nazila Alverdiyeva Farman , Gunay Mammadova Israphil , Vusala Isaqova Gudrat , Turkan Hasanova Allahverdi , Muhammad Madnee
The article is devoted to the study of the relationship between sustainable development and the introduction of innovative technologies, and the formation of smart cities. The Azerbaijan Republic is a land-poor country and has exhausted most of its natural resources. Therefore, the use of renewable energy sources and scientific research in this direction are important and topical issues for the country's scientists. Wind demand: in 10 months (from January to October) showed 3.000 GWh-4.000 GWh in Absheron (2020-2024 years). Since bioenergy can be produced in any weather, it is more reliable than solar and wind energy in Azerbaijan's regions. Seasonal variations in the availability of agricultural residues can lead to uneven energy production and create difficulties in ensuring a constant supply. The study is innovative given the importance of non-competition with food production, as well as the unique environmental, economic, and technological implications of each biofuel production method.
Volume: 15
Issue: 1
Page: 37-45
Publish at: 2026-03-01

Google Play review analysis on Sharia pawnshop applications in Indonesia

10.11591/ijaas.v15.i1.pp86-98
Azhar Alam , Adityo Wiwit Kurniawan , Muhammad Sholahuddin
Digital transformation opens opportunities for Sharia pawnshops to develop innovative application-based services following Sharia principles. This study analyzes the perception and experience of users of the Sharia pawnshop application on the Google Play Store using a netnography approach. It collects and analyzes 395 user reviews between June and December 2024, which consist of 219 positive reviews and 176 negative reviews. The analysis shows that 59.82% of users gave positive reviews regarding satisfaction with using the application, especially regarding transaction security and ease of use. As many as 17.35% of positive reviews emphasized the benefits of the application in transforming Islamic financial services. The main challenges identified included update system problems (35.23%), technical and server problems (30.11%), and registration complexity (5.68%). There was also a discrepancy between numerical ratings and review content. Important concerns include service problems (9.66%) and limited choice of Islamic banks (5.11%). This research provides important insights for the development of digital Islamic finance applications in the future, especially in the aspects of improving technological infrastructure, simplifying processes, and improving the quality of customer service. The results of this study contribute to a better understanding of user needs in the context of the digitization of Islamic financial services in Indonesia.
Volume: 15
Issue: 1
Page: 86-98
Publish at: 2026-03-01

State evolution approach for the axion conversion probability in magnetosphere of a neutron star

10.11591/ijaas.v15.i1.pp355-371
Bilal Ahmad , Shehreyar Ali
Neutron stars (NS), with their extreme gravitational and magnetic fields, provide an exceptional astrophysical laboratory for studying axion dark matter (DM). Through the Primakoff effect, axions can convert into photons within the magnetospheres of NS, a process that may produce observable radio and X-ray signals. In this work, we investigate axion-photon conversion using a novel, time-dependent state evolution formalism, moving beyond the commonly used stationary-path approximations. We derive a generic analytical expression for the conversion probability and calculate the associated radiated power. Our analysis demonstrates that this approach allows NS to strongly constrain the axion-photon coupling constant, reaching sensitivities of gaγγ ≃ 10−14 −10−15 GeV−1 for axion masses of ma ≃ 10−3 −10−10 eV. These results establish a new pathway to constrain gaγ via NS observations. Future campaigns using powerful observatories like the James Webb Space Telescope (JWST), Green Bank Telescope (GBT), and More Karoo Array Telescope (MeerKAT) array will be ideally suited to probe the distinct spectral signatures predicted by our model across multiple frequency domains.
Volume: 15
Issue: 1
Page: 355-371
Publish at: 2026-03-01

Remote procedure call communication and control of autonomous mobile robot for indoor smart waste monitoring

10.11591/ijra.v15i1.pp89-98
Ashaari Yusof , Abdullah Man , Azmi Ibrahim , Mohamed Ashraf Husni Zai , Md. Jakir Hossen
The integration of autonomous mobile robots (AMRs) and Internet of Things (IoT) technology has revolutionized various industries, including smart waste management (SWM). In this paper, the implementation of a customized remote procedure call (RPC) methodology was successfully demonstrated. This methodology facilitated control and monitoring of AMRs for smart indoor waste management to collect and dispose waste, monitor bin threshold levels and report relevant parameters to a cloud-based platform. Key operational parameters from the AMR and the smart bins via assembled user smart dashboard ensures seamless user monitoring for indoor waste management. Our findings underscore the relevance of RPC in advancing smart waste management technologies, contributing to operational efficiency and sustainability.
Volume: 15
Issue: 1
Page: 89-98
Publish at: 2026-03-01

Car selection in games using multi-objective optimization by ratio analysis based on player achievement

10.11591/csit.v7i1.p30-45
Caesar Nafiansyah Putra , Fresy Nugroho , Mochamad Imamudin , Dwi Pebrianti , Jehad Abdelhamid Hammad , Tri Mukti Lestari , Dian Maharani , Alfina Nurrahman
The selection menu in some racing games usually uses a random system for vehicle selection. However, this random feature generally randomizes the selection of the index without considering factors that support the player's abilities. Therefore, this study aims to develop a racing game that can suggest vehicles that have been adjusted to the player's performance. Vehicle recommendations are made using the multi-objective optimization on the basis of ratio analysis (MOORA) method as its method. The MOORA calculation ranks vehicles based on criteria such as mileage, fuel efficiency, speed, agility, and others collected in previous games. The results of this study show the effectiveness of using the MOORA method in recommending vehicles that match the player's skills, thereby improving the overall player experience. In addition, the usability test produced a system usability scale (SUS) score of 82.4, so it is included in the very good category.
Volume: 7
Issue: 1
Page: 30-45
Publish at: 2026-03-01

Analysis of congestion management using generation rescheduling with augmented Mountain Gazelle optimizer

10.11591/ijict.v15i1.pp57-65
Chidambararaj Natarajan , Aravindhan Karunanithy , S. Jothika , R. P. Linda Joice
This study presents an original blockage of the executive’s approach utilizing age rescheduling with the augmented mountain gazelle optimizer (AMGO). Enlivened by the versatility of mountain gazelles, AMGO is applied to enhance age plans for a reasonable power framework situation. The strategy successfully mitigates clogs, taking into account functional imperatives, market elements, and vulnerabilities. Recreation results show AMGO’s heartiness, seriousness, and proficiency in contrast with existing strategies. Notwithstanding its heartiness in blockage the board, the AMGO presents a state-of-the-art versatile element, enlivened by the spryness of mountain gazelles, empowering constant changes in accordance with developing power framework conditions and contrasted and genetic algorithms and PSO. The review adds to propelling streamlining methods for clogging the executives, offering a promising device for improving power framework, unwavering quality and productivity.
Volume: 15
Issue: 1
Page: 57-65
Publish at: 2026-03-01

Enhancing intellectual property rights management through blockchain integration

10.11591/ijict.v15i1.pp111-119
Raghavan Sheeja , Sherwin Richard R. , Shreenidhi Kovai Sivabalan , Srinivas Madhavan
The generational improvement has significantly converted several industries, and the area of intellectual property rights (IPR) isn’t any exception. IPRs, being as important as they are, need to be securely managed in some way. Blockchain, with its decentralized and immutable nature, gives a promising answer for enhancing the management of intellectual property (IP). This paper explores the strategic integration of blockchain generation for the control of IPR. The proposed system consists of a complete system, from registration and validation to predictive evaluation and royalty distribution, all facilitated through clever contracts. The use of zero-knowledge proofs guarantees the safety and confidentiality of sensitive information. The paper discusses the advantages and future implications of implementing this type of device.
Volume: 15
Issue: 1
Page: 111-119
Publish at: 2026-03-01

Classification and regression tree model for diabetes prediction

10.11591/ijict.v15i1.pp207-216
Farah Najidah Noorizan , Nur Anida Jumadi , Li Mun Ng
Diabetes mellitus is characterized by excessive blood glucose that occurs when the pancreas malfunctions while producing insulin. High blood glucose levels can cause chronic damage to organs, particularly the eyes and kidneys. Diabetes prediction models traditionally use a variety of machine learning (ML) algorithms by combining data from the glucose levels, patient health parameters, and other biomarkers. Prior research on diabetes prediction using various algorithms, such as support vector machine (SVM) and decision tree (DT) models, demonstrates an accuracy rate of approximately 70%, which is relatively modest. Therefore, in this study, a classification and regression tree (CART) multiclassifier model has been proposed to improve the accuracy of diabetes prediction, which is based on three classes: non-diabetic, pre-diabetic, and diabetic. The study involved data preprocessing steps, hyperparameter tuning, and evaluation of performance metrics. The model achieved 97% accuracy while utilizing the value of 5 for the number of leaves per node, the value of 10 for the maximum number of splits, and deviance as the split criterion, which also resulted in a precision of 98%, recall of 97%, and F1-score of 98%, showing that the proposed multiclassifier model can accurately predict diabetes. In conclusion, the proposed CART model with the best hyperparameter setting can enable the highest accuracy in predicting diabetes classes.
Volume: 15
Issue: 1
Page: 207-216
Publish at: 2026-03-01

Reputation-enhanced two-way hybrid algorithm for detecting attacks in WSN

10.11591/ijict.v15i1.pp428-437
Divya Bharathi Selvaraj , Veni Sundaram
Wireless sensor networks (WSNs) are susceptible to a variety of attacks, such as data tampering attacks, blackhole attacks, and grayhole attacks, that can affect the reliability of communication. We proposed a reputationenhanced two-way hybrid algorithm (RCHA) that uses cryptographic hash functions and reputation-based trust management to detect and de-escalate attacks accurately. The RCHA algorithm implements two hash functions RACE integrity primitives’ evaluation message digest (RIPEMD) and secure hash algorithm (SHA-3), to initiate the integrity check for the entire packet sent across the network. Every node in the WSN tracks a reputation score for each neighbor the node is connected to, and this score is dynamically updated based on the behavior of each neighbor. If a neighboring node’s reputation drops below a threshold, the node is sent a maliciousness designation. At that time, the node will broadcast an alert message to its neighboring nodes and begin to reroute its data through one of its trusted neighbors to ensure the reliability of the communication. The simulation results reported that the RCHA algorithm improved the accuracy of the attack detection rate and the number of packets delivered compared to traditional attack detection methods. The RCHA algorithm was able to maintain low computational and energy overhead for the WSN, making it an attractive option for a resource-constrained application in a WSN. Given the trends towards more collaborative networks, the reputation mechanism in the RCHA algorithm improves the overall reliability and capabilities of the WSN, regardless of adversaries.
Volume: 15
Issue: 1
Page: 428-437
Publish at: 2026-03-01
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