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28,428 Article Results

Structural behavior of reinforced soil walls under seismic loads

10.11591/ijaas.v14.i3.pp711-723
Reynaldo Melquiades Reyes Roque , Lincoln Jimmy Fernández Menacho , Brayanm Reynaldo Reyes Huerta , Fabrizio del Carpio Delgado
One of the main engineering challenges has been to design an economical soil retaining structure with high seismic resistance. From this perspective, reinforced soil walls have been developed with a focus on flexibility, in order to efficiently resist the effects of similar historical events in the event of a significant earthquake. The overall objective of this study was to compare the structural behavior of a geogrid-reinforced soil wall (Terramesh® system) under static and pseudo-static loads, and in a seismic environment simulated using the finite element method, in a shopping center in Trujillo, Peru. A case study was conducted using a mixed methodology, both applied and analytical-comparative in scope. Furthermore, the finite element methodology, material constitutive modeling, and dynamic time-history analysis of modal structures were chosen. It was determined that seismic loading can produce a 53.33% increase in deformations compared to the static state; Likewise, the overall safety factor under dynamic conditions tends to decrease by 27.85% compared to the static case. This study demonstrated the scope of geogrid reinforcement (Terramesh® system) through a practical case of a reinforced soil wall, using Plaxis 2D software to compare, estimate, and compare structural behavior in static, dynamic, and simulated environments.
Volume: 14
Issue: 3
Page: 711-723
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

Eco-friendly durable asphalt using maleic-modified rosin ester

10.11591/ijaas.v14.i3.pp793-803
Emma Savitri , Edy Purwanto , Restu Kartiko Wisi , Aloisiyus Yuli Widianto , Reyhan Sava Pratama , Yosafat Gary Tegar Harijono
Asphalt, a crucial component of transportation infrastructure, particularly in regions with high traffic loads and extreme climates, often lacks the necessary elasticity, strength, and durability. Various asphalt modifiers have been explored, but many struggle with cost, thermal stability, and environmental impact. This study, however, investigates maleic-modified rosin ester, a gum rosin derivative, as a sustainable and cost-effective asphalt modifier. The base asphalt was heated to 150-190 °C, sheared at 100 rpm, and combined with 4-20% maleic rosin ester and sulfur. The modified asphalt was subjected to tests, including penetration, softening point, ductility, density, kinematic viscosity, Fourier transform infrared (FTIR), and dynamic shear rheometer (DSR) tests. The results are promising, showing that maleic rosin ester enhances penetration resistance and softening points while maintaining ductility and viscosity within acceptable limits. Chemical analysis confirmed improved adhesion, crosslinking, and thermal stability, making the modified asphalt more deformation-resistant. This suggests that maleic-modified rosin ester is a viable alternative to synthetic polymers, offering improved durability and sustainability. The enhanced durability of the modified asphalt provides confidence in its long-term performance, making it a reliable choice for transportation infrastructure.
Volume: 14
Issue: 3
Page: 793-803
Publish at: 2025-09-01

Evaluating shading effects on photovoltaic modules: Mathematical modeling with ideal, single, and double diodes

10.11591/ijpeds.v16.i3.pp1949-1961
Mohcine Abouyaakoub , Mbarek Chahboun , Ali Ait Ali , Aziz El Mrabet , Hicham Hihi , Souhail Barakat
Among the issues that solar systems face is partial shadowing that can be caused by many factors, such as trees, buildings, or clouds. A shaded module will produce less energy, which reduces the power supplied by a solar system based on PV panels. The purpose of this study is to model and simulate photovoltaic modules based on an ideal single and double diode. After that, we will simulate five configurations formed by nine photovoltaic solar panels: series (S), parallel (P), series-parallel (SP), bridge-link (BL), and total-cross-tied (TCT) under uniform and non-uniform cases (center, diagonal, and frame). These five PV solar configurations are compared in terms of short circuit currents (ISC), open circuit voltages (VOC), peak powers (PMP), the voltage and current values corresponding to maximum power (VMP, IMP), mismatch power loss (MPL), fill factor (FF), efficiency ratio (ER), and overall maximum power (OMP). The six PV configurations are simulated, considering the parameters of the STM6-40/36 PV module.
Volume: 16
Issue: 3
Page: 1949-1961
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

Intelligent control solutions for enhancing dual-fold Luo converter efficiency in EVs

10.11591/ijpeds.v16.i3.pp1789-1800
P. Siva Subramanian , B. Marisekar , P. Mohana Karthiga , R. Ramya
This research proposes the design and application of a smart controller for a dual-fold Luo converter tailored specifically for E-vehicle applications. The dual-fold Luo converter, known for its ability to efficiently step up and step down voltage levels with reduced components, is augmented with a smart control strategy to enhance its performance in the context of electric vehicles. The smart controller utilizes advanced techniques, such as artificial neural networks or fuzzy logic, to adaptively regulate the converter's operation, thereby improving efficiency, transient response, and overall reliability. By leveraging real-time data from the E-vehicle system, the controller dynamically adjusts key parameters to optimize performance under varying load and operating conditions. Key design considerations include the selection and training of the smart controller to achieve desired voltage regulation, efficiency, and robustness in the face of uncertainties inherent in E-vehicle operation. The proposed design methodology is validated through simulation studies, demonstrating superior performance compared to conventional control techniques. The results illustrate the efficacy of the smart controller in enhancing the dynamic response of the dual-fold Luo converter, making it a promising solution for E-vehicle power management systems. This research contributes to the advancement of power electronics in electric transportation, facilitating the development of more efficient and reliable E-vehicle systems in the pursuit of sustainable mobility.
Volume: 16
Issue: 3
Page: 1789-1800
Publish at: 2025-09-01

When studying applied physics: what problems are there, and do pre-service physics teachers need?

10.11591/ijaas.v14.i3.pp650-661
Renol Afrizon , Lilia Ellany Mohtar , Mohd Syahriman Mohd Azmi , Hidayati Hidayati
Applied physics courses are essential for pre-service physics teachers (PsPTs), but they often encounter challenges in pursuing this educational pathway. This study aims to identify the problems and learning elements that PsPTs need in applied physics learning using the McKillip discrepancy model. The data were collected using questionnaires and bibliometric techniques. A total of 23 PsPTs participated in the study. Additionally, 1,000 articles were consulted as a data source. The data analysis uses descriptive statistics and the VOSviewer software. The first finding is primary issues identified in applied physics learning e.g., the difficulty of locating suitable learning resources, the dearth of in-depth physics comprehension, the absence of visualization like augmented reality (AR), the failure to undertake empirical activities in the laboratory, and global warming and climate change topic were pertinent at the high school level, entailed intricate issues, and were abstract. The second finding is a learning module that is integrated with science, technology, engineering, and mathematics (STEM), and AR is needed by PsPTs. Finally, this need has been paramount over the past decade to meet PsPTs' needs. Thus, the needs analysis results serve as an initial reference point for decision-makers to identify elements and develop integrated STEM and AR applied physics learning modules.
Volume: 14
Issue: 3
Page: 650-661
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

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

Analysis of mobile banking adoption in Ghana: do education levels differ?

10.11591/ijaas.v14.i3.pp828-837
Isaac Asampana , Lawrence Kwami Aziale , Henry Matey Akwetey , Hannah Ayaba Tanye
This study investigates the role of educational attainment in mobile banking (m-banking) adoption in Ghana, leveraging data from 598 respondents through a multi-group analysis. By integrating the technology acceptance model (TAM) and the theory of planned behavior (TPB) into a structural equation modelling framework, the research examines key factors such as subjective norms, perceived usefulness, ease of use, trust, and self-efficacy. Results reveal significant differences in adoption behaviors between lower- and higher-educated users. Subjective norms strongly influence higher-educated individuals, while perceived ease of use drives adoption among lower-educated users. Perceived usefulness positively affects higher-educated users but has a negative impact on lower-educated respondents. The findings highlight the moderating effect of education level on the adoption process, offering theoretical and practical insights into targeted strategies for enhancing financial inclusion in developing economies. These results underscore the importance of user segmentation in fostering broader acceptance and utilization of m-banking technologies.
Volume: 14
Issue: 3
Page: 828-837
Publish at: 2025-09-01

Modern research of using alternative energy resources in Azerbaijan

10.11591/ijaas.v14.i3.pp907-915
Ramil Sadigov Ali , Mushkunaz Nazarova Kichmirza , Garayeva Irada Eyvaz , Gunay Mammadova Israphil , Turkan Hasanova Allahverdi , Muhammad Madnee
The article provides a comprehensive analysis of modern trends and prospects for the use of solar batteries in various sectors of the economy and the agricultural sector. The purpose of this article is to analyze the possibility of energy saving for a private residential building in Gobustan using solar energy storage in a greenhouse extension and a heat pump to transfer heat to the heating system. The calculation showed that in the coldest month, December, the potential of solar thermal energy is 15-38% of the required heat demand, depending on the material used in the extension design. In March and April, excess heat is generated, which can be used for hot water supply needs. Thus, for an individual residential building, the use of solar heat accumulated in a greenhouse extension is relevant as an additional source of heat for the heating system. Surface density of solar radiation flux, W/m2: surface density of direct solar radiation flux: 1,680 (November), 1,530 (December), 1,870 (January), 2,730 (February), 3,270 (March), 3,180 (April); Surface density of diffuse solar radiation flux: 650 (November), 450 (December), 480 (January), 680 (February), 1180 (March), 1,830 (April).
Volume: 14
Issue: 3
Page: 907-915
Publish at: 2025-09-01

Self-development moderates the impact of digital literacy and talent on human error

10.11591/ijaas.v14.i3.pp682-692
Achmad Mirza , Isnurhadi Isnurhadi , Muhammad Ichsan Hadjri
Effective public services are important for increasing community satisfaction and organizational credibility. This study aims to explore the influence of digital literacy, underutilized talent, and human error on the effectiveness of public services, with self-development as a moderating variable. This study was conducted with employees of the Trade Office of South Sumatra Province. The research method used was quantitative data analysis, which was performed using partial least squares structural equation modeling (PLS-SEM). The results of this study show that digital literacy and self-development play an important role in reducing human error and increasing the effectiveness of public services. These findings have practical implications for human resource management in the public sector, focusing on improving digital literacy and employee self-development. 
Volume: 14
Issue: 3
Page: 682-692
Publish at: 2025-09-01

Sulphur corrosion in transformer insulating oils: its effects, detection methods, and mitigation strategies

10.11591/ijaas.v14.i3.pp784-792
Nur Izyan Husnina Zulkefli , Sharin Ab Ghani , Mohd Shahril Ahmad Khiar , Imran Sutan Chairul , Nor Hidayah Rahim , Nur Farhana Mohd Azlan
Oil-immersed transformers are subjected to electrical, thermal, and mechanical stresses over time, which inevitably affect the insulating oil and paper insulation. The presence of sulphur corrosion also degrades the insulating oil and paper insulation. Sulphur corrosion in insulating oils has been a prevalent problem for many years, as it culminates in the failure of oil-immersed transformers. The longevity of oil-immersed transformers is dependent on the integrity of the insulating oil and paper insulation, which can deteriorate owing to sulphur corrosion. The occurrence and accumulation of copper sulphide (Cu2S) can result in transformer malfunctions, which is a significant issue for transformer manufacturers and operators. This paper provides a concise overview of the effects of sulphur corrosion, its detection methods, as well as its mitigation strategies. It is believed that this paper will enhance the understanding of sulphur corrosion in insulating oils, provide the best practices for sulphur corrosion management, and serve as guidance on enhancing transformer reliability and performance.
Volume: 14
Issue: 3
Page: 784-792
Publish at: 2025-09-01

Optimizing retail systems: using big data and power business intelligence for performance insights

10.11591/ijaas.v14.i3.pp945-954
Huu Dang Quoc , Ha Le Viet
In the rapid development of information technology, using enterprise data to support timely management decisions is crucial in helping businesses operate effectively and improve competitiveness. This study uses Microsoft power business intelligence (MPBI) to analyze data in retail systems, allowing managers to grasp the business situation in real time, track advanced sales, optimize inventory control, and analyze customer behavior and supply chain visibility. From the data generated by the business, the study uses the streaming extract transform load (ETL) model to support real-time data aggregation, then converts to the MPBI data visualization system to convert data into visual charts, helping businesses easily monitor, track, analyze, and make decisions to promote business activities. The study proposes a data structure to organize retail information storage. It proposes a system of calculation formulas and data synthesis, making integrate and convert tabular data into visual charts. Through analysis of real data from the LH83 retail system, the study shows the feasibility of implementing a data visualization system and the difficulties encountered when businesses want to deploy this model.
Volume: 14
Issue: 3
Page: 945-954
Publish at: 2025-09-01

Comprehensive structured analysis of machine learning in safety models

10.11591/ijaas.v14.i3.pp627-638
Mohd Shukri Abdul Wahab , Syed Tarmizi Syed Shazali , Noor Hisyam Noor Mohamed , Abdul Rani Achmed Abdullah
Machine learning (ML) integration into various industries has revolutionized operations recently, enhancing efficiency and predictive capabilities. However, the rapid adoption of ML models also presents significant safety concerns that are highly demanded. To achieve this, scholarly articles from reputable databases such as Scopus and Web of Science (WoS) focus on studies published between 2022 and 2024, which were extensively searched. The study's flow is based on the PRISMA framework. The database found (n=40) that the final primary data was analyzed. The findings were divided into three themes: i) safety and risk management, ii) ML and artificial intelligence (AI) applications in safety, and iii) smart technology for safety. The conclusion highlights the need for continuous monitoring and updating of the safety protocols to keep in step with the growing ML landscape. This review contributes to the understanding of ML safety. It offers global lessons that can guide future research and policy-making efforts to ensure ML technologies' safe and ethical use.
Volume: 14
Issue: 3
Page: 627-638
Publish at: 2025-09-01
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