International Journal of Advances in Applied Sciences
International Journal of Advances in Applied Sciences (IJAAS), p-ISSN 2252-8814, e-ISSN 2722-2594, is a peer-reviewed and open access journal dedicated to publish significant research findings in the field of Applied Sciences, Engineering and Information Technology. The journal is designed to serve researchers, developers, professionals, graduate students and others interested in state-of-the art research activities in applied science, engineering and information technology areas, which cover topics including: applied physics; applied chemistry; applied biology; environmental and earth sciences; electrical & electronic engineering; instrumentation & control; telecommunications & computer science; industrial engineering; materials & manufacturing; mechanical, mechatronics & civil engineering; food, chemical & agricultural engineering; and acoustic & music engineering. IJAAS is published by Intelektual Pustaka Media Utama (IPMU). This journal is ACCREDITED (recognised) by the Ministry of Education, Culture, Research, and Technology, Republic of Indonesia (Decree No: 79/E/KTP/2023). Scopus has indexed articles published in this journal since 2019 issues. If you have access to scopus.com, you can <a href="https://id.elsevier.com/as/authorization.oauth2?platSite=SC%2Fscopus&ui_locales=en-US&scope=openid+profile+email+els_auth_info+els_analytics_info+urn%3Acom%3Aelsevier%3Aidp%3Apolicy%3Aproduct%3Aindv_identity&els_policy=idp_policy_indv_identity_plus&response_type=code&redirect_uri=https%3A%2F%2Fwww.scopus.com%2Fauthredirect.uri%3FtxGid%3D1296069b61a14ad54b64ac4c1cbee01f&state=forceLogin%7CtxId%3D4B6FDB664E7E5E38C50C3A445963F1E2.i-0e06c2e91cabf8067%3A14&authType=SINGLE_SIGN_IN&prompt=login&client_id=SCOPUS&isValidNewDocSearchRedirection=false">click here. Scimagojr also has been indexing it as of 2019. See our Scimagojr profile here. IJAAS Features: Plagiarism: CrossCheck plagiarism powered by iThenticate. DOI: DOI Number is indexed by Crossref. Open Access: Open access provides immediate and unrestricted access to the latest research. Full Archive Available: Every issue of Journal of IJAAS is available online. ISSN Record Information: The ISSN of IJAAS journal is registered at https://portal.issn.org/resource/ISSN/2722-2594 <!--[if mso]> <xml><w:WordDocument xmlns:w="urn:schemas-microsoft-com:office:word"><w:DontUseAdvancedTypographyReadingMail/></w:WordDocument> <o:OfficeDocumentSettings><o:PixelsPerInch>96</o:PixelsPerInch><o:AllowPNG/></o:OfficeDocumentSettings></xml> <![endif]--><!--[if !mso]><!--><!--<![endif]--><!--[if mso ]> <![endif]--> <!--[if mso]> <v:roundrect xmlns:v="urn:schemas-microsoft-com:vml" xmlns:w="urn:schemas-microsoft-com:office:word" href="https://youtu.be/B9lB-4sZNI4?si=o5H0_HS2NaXlxe-Z" style="height:46px;width:210px;v-text-anchor:middle;" arcsize="9%" fillcolor="#3202b6"> <v:stroke dashstyle="Solid" weight="0px" color="#3202b6"/> <w:anchorlock/> <v:textbox inset="0px,0px,0px,0px"> <![endif]-->HOW TO REGISTER<!--[if mso]> </v:textbox></v:roundrect><![endif]--> <!--[if mso]> <v:roundrect xmlns:v="urn:schemas-microsoft-com:vml" xmlns:w="urn:schemas-microsoft-com:office:word" href="https://youtu.be/hQD9-HeNy1k?si=_Q7Dsawb-OEvh2Gl" style="height:46px;width:187px;v-text-anchor:middle;" arcsize="9%" fillcolor="#ff47ce"> <v:stroke dashstyle="Solid" weight="0px" color="#ff47ce"/> <w:anchorlock/> <v:textbox inset="0px,0px,0px,0px"> <![endif]-->HOW TO SUBMIT<!--[if mso]> </v:textbox></v:roundrect><![endif]-->
Institute of Advanced Engineering and Science
COPYRIGHT AND LICENSING AGREEMENT This is to certify that the submitted manuscript is an original work, has not been published previously, and is not being considered for publication elsewhere. Upon acceptance, the article will be published by Intelektual Pustaka Media Utama (IPMU) under the terms of the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0). The authors retain the copyright to the work. We declare that: This manuscript has not been published previously in the same or substantially similar form. It is not currently under review or consideration for publication by any other journal. All necessary permissions have been obtained for the use of any third-party material included in this manuscript. We agree that upon publication, the article will be distributed under the Creative Commons Attribution-ShareAlike 4.0 International License (CC BY-SA 4.0). License Grant We, the authors, retain all copyrights to the submitted article, and grant to IPMU the non-exclusive right to reproduce, publish, translate, and distribute the article in any form or medium, including print and electronic formats. The article may be used, shared, or adapted by others, provided that: Proper attribution is given to the original author(s) and source, A link to the license is included, Any changes are indicated, and Any derivative works are licensed under the same terms (ShareAlike). Full license details: https://creativecommons.org/licenses/by-sa/4.0 Author Responsibility The corresponding author signs for and accepts responsibility for releasing this material on behalf of any and all co-authors. This agreement is to be signed by at least one of the authors who has obtained the consent of the co-author(s), if any. After submission of this agreement signed by the corresponding author, changes in authorship or order of authors will not be accepted. Retained Rights Authors retain all proprietary rights in any process, method, or material described in the work. Authors may distribute or reuse the work for personal or institutional use, or include it in other works, with appropriate credit and under the same license. Authors may deposit the published version of the article in institutional or public repositories.
Comprehensive structured analysis of machine learning in safety models
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.
Copyright (c) 2025 Mohd Shukri Abdul Wahab, Syed Tarmizi Syed Shazali, Noor Hisyam Noor Mohamed, Abdul Rani Achmed Abdullah http://creativecommons.org/licenses/by-sa/4.0
A bibliometric review of lean principles in highway pavement for productivity improvement
A past study of 25 years reveals the positive impact of lean principles on highway pavement productivity. This bibliometric review extracted 389 papers from the Scopus database that revolved around three terms, “lean principles,” “highway pavement,” and “productivity improvement,” and used VOSviewer for scientometric analysis and scientific mapping. Study reveals that addressing this topic on a global scale is of chief significance, given the potential variations in indices of the issue across different countries or provinces. This research undertakes a comprehensive qualitative analysis that highlights diverse indicators that exert influence on the productivity of pavements. Additionally, this analysis also seeks to propose potential avenues for future research within lean construction. An intensive investigation provides four unique clusters of words that have been formed through the process of keyword science mapping within the context of the lean principles, which are road segment, techniques, productivity improvement, and lean. Last but not least, 4 pointers are recommended that will help stakeholders and policymakers assess pavement performance practices, identify areas for improvement, and execute targeted interventions to improve productivity.
Copyright (c) 2025 Pooja P. Gohil, MohammedShakil S. Malek, Deep Shaileshkumar Upadhyaya http://creativecommons.org/licenses/by-sa/4.0
When studying applied physics: what problems are there, and do pre-service physics teachers need?
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.
Copyright (c) 2025 Renol Afrizon, Lilia Ellany Mohtar, Mohd Syahriman Mohd Azmi, Hidayati Hidayati http://creativecommons.org/licenses/by-sa/4.0
Determination of soil salinization by hyperspectral remote sensing in the Shirvan Plain
The determination of soil salinization in the Shirvan Plain, considered the main agricultural zone of Azerbaijan, negatively affects the productivity of agricultural crops. Based on 10 m Sentinel-2 images on Google Earth Engine platforms and by examining SI1, green-red band normalized difference vegetation index (GRNDVI), green normalized difference vegetation index (GNDVI), normalized difference vegetation index (NDVI), and difference vegetation index of the environment (DVI), four remote sensing salinity monitoring index models, S1DI1, S1DI2, S1DI3, and S1DI4, were constructed to extract soil salinity information in the Shirvan Plain in combination with the measured electrical conductivity. The results show that the overall classification accuracy of S1DI1 (SI1-GRNDVI), S1DI2 (SI1-GNDVI), S1DI3 (SI1-NDVI), and S1DI4 (SI1-DVI) models for salinity monitoring are 82.35%, 83.10%, 81.96%, and 79.25%, respectively.
Copyright (c) 2025 Sahib Shukurov Khudaverdi, Aygun Ismayilova Azer, Ramil Sadigov Ali,Maya Karimova Javanshir, Turkan Hasanova Allahverdi, Gunel Asgarova Farhad http://creativecommons.org/licenses/by-sa/4.0
Haystack-based Facebook’s data storage architecture: store, directory, and cache
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.
Copyright (c) 2025 Tole Sutikno, Ahmad Heryanto, Laksana Talenta Ahmad http://creativecommons.org/licenses/by-sa/4.0
Self-development moderates the impact of digital literacy and talent on human error
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.
Copyright (c) 2025 Achmad Mirza, Isnurhadi Isnurhadi, Muhammad Ichsan Hadjri http://creativecommons.org/licenses/by-sa/4.0
Performance evaluation of multicarrier quadrature phase shift keying-based system under noisy channel conditions
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.
Copyright (c) 2025 Deepa Narayana Reddy, Aishwarya Nagaraju, Deepti Hosakere Prabhakara, Deekshitha Beeraganahalli Srinivas, Gandlaparthi Navyatha http://creativecommons.org/licenses/by-sa/4.0
Artificial neural network based sensorless position estimation and direct torque control for stepper motor
This study describes and illustrates how sensorless location estimation is achieved through the application of artificial neural network (ANN) control. Control stepper motor torque directly. Using stepper motors directly leads to a lot of problems; therefore, automated control systems are now commonly preferred. Stepper motors have several drawbacks when used directly, including the potential for steps to occasionally be missing while the motors are running. When physical sensors are not available, the proposed method estimates rotor position and speed using electrical signals and ANN algorithms. Simulation and experiment results demonstrate accurate position estimation (±1.5°) and efficient torque control. The sensorless direct torque control (DTC)-ANN approach increases the performance, reliability, and cost of stepper motors in robotics, computer numerical control (CNC) machines, and 3D printing.
Copyright (c) 2025 Nagasridhar Arise, Thiruveedula Madhu Babu, Srinidhi Gollapudi, Tarun Kumar Dommeti, Abhishek Kummari, Mahith Shambukari http://creativecommons.org/licenses/by-sa/4.0
Structural behavior of reinforced soil walls under seismic loads
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.
Copyright (c) 2025 Reynaldo Melquiades Reyes Roque, Lincoln Jimmy Fernández Menacho, Brayanm Reynaldo Reyes Huerta, Fabrizio del Carpio Delgado http://creativecommons.org/licenses/by-sa/4.0
Autonomous navigation system for a rover with robotic arm using convolutional neural networks
The aim of this project is to design and develop an autonomous rover equipped with a KUKA robotic arm. This mobile vehicle will be able to move autonomously thanks to the use of machine learning techniques. It will also be able to detect and retrieve objects using the KUKA arm. The rover will feature Mecanum wheels for improved maneuverability and will be controlled by a Raspberry Pi 3 board, with machine learning algorithms implemented using TensorFlow and Python. The development process will follow the V-methodology. The use of such an autonomous rover and its manipulative capabilities opens the way to many practical applications, including sampling in dangerous or difficult-to-access environments, search and rescue operations in the event of natural disasters or industrial accidents, and inspection and maintenance of industrial or construction sites. The rover could also be used for educational purposes, enabling students to explore the concepts of robotics and artificial intelligence.
Copyright (c) 2025 Aziz El Mrabet, Hicham Hihi, Mohammed Khalil Laghraib, Mbarek Chahboun, Aymane Amalaoui http://creativecommons.org/licenses/by-sa/4.0
A method classifying the domestic tourist destination base similarity measuring
The classification problem is crucial in business, providing an effective method for supporting search activities in areas such as e-commerce, education, and marketing. This has become especially important in the wake of the COVID-19 pandemic, which has increased the need to promote and stimulate domestic tourism. This research focuses on recommending tourist destinations based on historical search data related to domestic tourism. The study uses techniques like term frequency-inverse document frequency (TF-IDF) weight vector analysis and similarity measures to calculate recommendation scores. Data was collected from various tourism websites, covering destinations across all 63 provinces and cities in Vietnam. Experiments were conducted using three approaches: cosine similarity, the brute force algorithm, and long short-term memory (LSTM) for long-text processing. The results indicate that similarity-based methods produce recommendations that closely match user preferences. For full-sentence queries, the brute force algorithm delivers more accurate results, while LSTM provides faster processing times. These findings offer businesses multiple strategies for improving recommender systems in practical applications.
Copyright (c) 2025 Nguyen Thi Hoi, Tran Thi Nhung, Bui Quang Truong, Nguyen Quang Trung http://creativecommons.org/licenses/by-sa/4.0
An innovative design and development of multilevel inverter for a wind energy conversion system
The drawbacks of fossil fuel-based energy sources, including high costs, pollution, scarcity, and environmental damage, highlight how urgent it is to switch to renewable energy sources. Multilevel inverters (MLIs) are currently required for the production of wind electricity. In this research, to get a reduced harmonic distortion, use 31-level inverter based on shifted carrier-pulse width modulation (SC-PWM) is developed for wind power generation using MATLAB/Simulink. It aids in minimizing the total harmonic distortion (THD) to 3.20, and the output voltage is enhanced by the suggested MLI. Wind energy extraction is optimized by combining with a proportional integral derivative (PID) control system. MATLAB/Simulink has been used to make sure the MLI structure and look into the implementation of wind energy conversion systems using a permanent magnet synchronous generator (PMSG). In order to show that the suggested inverter architecture improves power conversion efficiency and stability in renewable energy systems, the study also examines power efficiency, system dependability, and the viability of large-scale applications. Additionally, the study investigates grid integration, modulation strategies, and switching losses to guarantee increased sustainability, dependability, and efficiency in wind energy applications while lowering operating costs.
Copyright (c) 2025 Rosaiah Mudigondla, Thiruveedula Madhu Babu, Supriya Dachepalli, Anudeep Punjala, Md Yousuf Ali, Bakam Anirudh http://creativecommons.org/licenses/by-sa/4.0
Impulse buying behavior in mobile commerce: a partial least squares structural equation modeling analysis
Efficient online transactions now thrive through websites (e-commerce) and mobile apps (m-commerce). With the growth of m-commerce, marketers aim to boost profits by understanding impulsive buying behavior. This study investigates factors influencing online impulse buying (OIB) in m-commerce by analyzing key variables. Data were gathered via questionnaires from 449 Indonesian consumers who had made digital payments and impulsive purchases using smartphones. The framework includes sales promotion (SP), attractive advertising (EA), and mobile digital payment systems (MDPS) as situational factors; hedonic shopping motivation (HSM) as a motivational factor; and impulsiveness (I) and smartphone addiction (SA) as personal traits. Analysis used partial least squares structural equation modeling (PLS-SEM), with gender, income, and smartphone usage time as control variables. Results show that EA, MDPS, HSM, I, and SA significantly influence OIB, while SP does not. For consumer segmentation, t-distributed stochastic neighbor embedding (t-SNE) outperformed ISOmap and principal component analysis (PCA), achieving a silhouette score of 0.72. A paired t-test (p<0.01) confirmed t-SNE’s superior clustering accuracy. These findings reveal that t-SNE better captures consumer segmentation patterns, helping businesses refine marketing strategies and deepen their understanding of psychological drivers behind impulsive m-commerce purchases.
Copyright (c) 2025 Hery, Winnie Veronica, Andree E. Widjaja, Calandra Alencia Haryani, Riswan E. Tarigan http://creativecommons.org/licenses/by-sa/4.0
Redesign the layout of the raw material warehouse from randomized storage to class-based storage
The company has a problem of ineffectiveness in the layout of the raw material warehouse due to the use of storage methods that ignore factors such as the type, dimensions, and condition of the goods. This reduces the optimal function of the warehouse and increases the time to retrieve goods. This research aims to redesign the suitable and practical layout of the raw material warehouse by considering its form and function, as well as filling methodological gaps from previous research. The method used is class-based storage. Based on ABC analysis, the category with the highest value is class C goods, with 73 units. Meanwhile, from the fast, slow, non-moving (FSN) analysis, class F (fast-moving) goods have the highest frequency of movement, with a movement percentage of 63% for 10 units of goods. The warehouse slotting analysis shows an increase in the number of shelves from nine to 15 shelves with five different shelf models and layout changes in raw material warehouses 1 and 2. The class-based storage method results in a more organized layout, efficient movement of goods, and faster picking time to optimize warehouse functions.
Copyright (c) 2025 Nur Iftitah, Qurtubi, Danang Setiawan, Vembri Noor Helia http://creativecommons.org/licenses/by-sa/4.0
Sulphur corrosion in transformer insulating oils: its effects, detection methods, and mitigation strategies
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.
Copyright (c) 2025 Nur Izyan Husnina Zulkefli, Sharin Ab Ghani, Mohd Shahril Ahmad Khiar, Imran Sutan Chairul, Nor Hidayah Rahim, Nur Farhana Mohd Azlan http://creativecommons.org/licenses/by-sa/4.0
Eco-friendly durable asphalt using maleic-modified rosin ester
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.
Copyright (c) 2025 Emma Savitri, Edy Purwanto, Restu Kartiko Widi, Aloisiyus Yuli Widianto, Reyhan Sava Pratama, Yosafat Gary Tegar Harijono http://creativecommons.org/licenses/by-sa/4.0
ToLatin application acceptability evaluation to support Balinese script transliteration learning
This work supported Indonesia's research focus area on information and communication technology (ICT) content improvement for information data on various forms of local wisdom. As one of the various forms of local wisdom, the Balinese script was supported by the ToLatin application that transliterates Balinese script into Latin text. It has been used to support Balinese script learning at the high school level in Buleleng Regency, Bali, Indonesia. To determine the acceptability of this application, which had not been studied before, a user acceptance evaluation was conducted using a combination of acceptance variables from the technology acceptance model (TAM) and success variables from DeLone & McLean. This study used a quantitative method with data collection through questionnaires from 385 respondents. The data analysis used the importance-performance analysis (IPA) method through suitability, gap, and quadrant analyses. The study results indicated that the acceptability of ToLatin could be more optimal. The suitability analysis revealed an average score of 87.91%, indicating the need for improvement in system quality, particularly the innovative indicator (SysQ3), based on the quadrant analysis. The gap analysis revealed an average score of -0.54 from 7 acceptance variables, indicating the need to improve system performance to meet user expectations.
Copyright (c) 2025 Luh Joni Erawati Dewi, Gede Indrawan, I Made Agus Oka Gunawan, I Wayan Sutaya, Sariyasa http://creativecommons.org/licenses/by-sa/4.0
E-commerce waste management: a systematic review
This paper reviews literature on e-commerce waste management issues and challenges, focusing on potential improvements in Malaysia. It analyzes various sources, including Scopus, Web of Science (WoS), and Google Scholar (GS), using thematic and content analysis based on preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The review highlights the surge in packaging and electronic waste due to increased e-commerce activity. In response, Malaysia has introduced policies promoting sustainable practices, such as eco-friendly packaging, e-waste regulations, and circular economy (CE) principles. Growing consumer awareness has also driven demand for sustainable e-commerce options. However, the key challenge is to reduce waste generation rather than just managing it. Achieving this will require significant efforts to minimize excessive manufacturing and packaging. The review aims to provide insights for stakeholders to support effective waste management and foster sustainability in the e-commerce sector.
Copyright (c) 2025 Mohd. Suhaimi Shamsuddin, Noor Fadhiha Mokhtar, Safiek Mokhlis, Zuha Rosufila Abu Hasan, Najdah Abd Aziz, Mohamad Nizam Yusof http://creativecommons.org/licenses/by-sa/4.0
Analysis of mobile banking adoption in Ghana: do education levels differ?
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.
Copyright (c) 2025 Isaac Asampana, Lawrence Kwami Aziale, Henry Matey Akwetey, Hannah Ayaba Tanye http://creativecommons.org/licenses/by-sa/4.0
Deep learning for image classification of submersible pump impeller
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.
Copyright (c) 2025 Phan Nguyen Ky Phuc, Doan Huu Chanh, Trong Hieu Luu http://creativecommons.org/licenses/by-sa/4.0
Large language models and retrieval-augmented generation-based chatbot for adolescent mental health
Access to fast and efficient information is crucial in today's digital era, especially for teenagers in obtaining mental health services. The manual method used by Youth Information and Counselling Centre (PIK R) to provide mental health information requires significant time and effort. This research presents an AI-based solution by developing a chatbot system using retrieval-augmented generation (RAG) and large language models (LLM). This chatbot is designed to provide accurate and effective mental health information for teenagers throughout the day. An analysis of a dataset consisting of articles on teenage mental health and data from the Alodokter website was used as the basis for the development of this chatbot. The research results show that the chatbot is capable of providing relevant and accurate information, with evaluations using the recall-oriented understudy for gisting evaluation (ROUGE) score method yielding an average of ROUGE-1 with a precision of 87.8%, recall of 83.0%, and F1-measure of 84.0%; ROUGE-2 with a precision of 82.8%, recall of 76.8%, and F1-measure of 78.2%; and ROUGE-L with a precision of 88.0%, recall of 82.6%, and F1-measure of 83.4%. These findings indicate the potential use of chatbots as an effective tool to support the mental health of adolescents.
Copyright (c) 2025 Andi Riansyah, Imam Much Ibnu Subroto, Intan Nur’aini, Ratna Supradewi, Suyanto Suyanto http://creativecommons.org/licenses/by-sa/4.0
Fuzzy logic controller-based protection of direct current bus using solid-state direct current breaker
Low-voltage direct current (LVDC) microgrids are increasingly utilized due to their efficiency and compatibility with distributed energy resources (DERs) and direct current (DC) loads, eliminating the need for multiple energy conversions. However, the protection of LVDC systems presents significant challenges, including high fault currents and the vulnerability of electronic devices. Traditional electromechanical circuit breakers are inadequate due to their slow response times. This work presents a protection approach for the DC bus in LVDC microgrids that combines a fuzzy logic controller (FLC) with a solid-state circuit breaker (SSCB). The FLC is designed to detect and respond to faults rapidly by processing input variables such as current magnitude and rate of change of current. The FLC controls the SSCB, which interrupts fault currents quickly and reliably. The proposed system demonstrates optimized fault-clearing times within milliseconds, significantly enhancing the protection and reliability of LVDC microgrids. This novel solution protects critical electronic components while also ensuring the microgrid's operational integrity. The FLC approach is utilized for optimizing fault-clearing duration within milliseconds.
Copyright (c) 2025 Eswaraiah Giddalur, Askani Jaya Laxmi http://creativecommons.org/licenses/by-sa/4.0
Dissolved organic matter released from paper trash in water during ultraviolet irradiation: impacts on trihalomethane formation
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.
Copyright (c) 2025 Teguh Budi Prijanto, Nia Yuniarti Hasan, Kahar, Muammar Qadafi, Wisnu Prayogo http://creativecommons.org/licenses/by-sa/4.0
Effectiveness of dashboard as a work progress scheduling, monitoring, and decision-making in construction projects
Scheduling, monitoring, and decision-making are important factors in determining the general achievement of sustainable construction. Therefore, this study was conducted to determine the effectiveness of a dashboard as a measuring tool for construction project scheduling, monitoring, and decision-making. A survey with a Likert scale (5 scale) on each viewpoint, including planning, oversight, and independent direction, of 15 respondents from project executors and 7 respondents from supervisors was used as instrumentation. The results showed that the dashboard was evaluated with a value of 92.25 among executors and supervisors linked to product characteristics. Executors also used the scheduling dashboard with a value of 91.73, and the feature of employing the concept for supervision was appropriate as a measuring instrument, scoring 92.15. Furthermore, the final step was the aspect of using the dashboard for decision-making, which was tested and used with a value of 88.14. The use dashboard model is an effective tool for work progress scheduling, monitoring, and decision-making in construction projects.
Copyright (c) 2025 Putri Lynna Adelinna Luthan, Nathanael Sitanggang http://creativecommons.org/licenses/by-sa/4.0
Test rig development for load test of pipe saddle support
Pipe saddle support is a structure commonly used to support horizontal steel pipe. It prevents direct contact between the pipe and the support. Pipe saddle support can experience displacement due to pipe movement and insufficient stress analysis. Given these concerns, conducting a load test is essential to determine the stress on pipe saddle supports. However, a universal testing machine (UTM) is not suitable for this purpose due to the size limitation. Therefore, this study proposed a test rig setup for the pipe saddle support load test. The test rig consists of a portal frame secured by an underground locking system featuring a strong floor. Additionally, an actual pipe is utilized to replicate actual loading conditions on the pipe saddle support. The applied load is measured using a load cell, with a custom-designed bracket to ensure precise load transfer. Finally, the pipe saddle support specimen is bolted to a base support to maintain stability during the load test. Stress analysis using finite element analysis (FEA) demonstrated that the test rig is suitable for conducting load tests on the specimens with a maximum force of 80 kN. FEA confirmed that the test rig operates within a safety factor of 1.3.
Copyright (c) 2025 Muhammad Arif Rayhan, Mohd Shukri Yob, Mohd Juzaila Abd Latif, Ojo Kurdi, Fudhail Abdul Munir http://creativecommons.org/licenses/by-sa/4.0
Numerical study of non-linear twisted blades for tidal turbines improvement
Despite the growing demand for renewable energy, the utilization of tidal energy remains underdeveloped due to efficiency limitations in turbine design. Addressing this gap, this study investigates the performance of horizontal-axis tidal turbines (HATT) by comparing two foil designs, National Advisory Committee for Aeronautics (NACA) 2415 and OptA, to optimize energy extraction efficiency. The research employs computational fluid dynamics (CFD) simulations using OpenFOAM to evaluate the effects of foil modifications and non-linear twist distributions on turbine performance across varying tip speed ratios (TSR). The results indicate that the OptA foil significantly improves turbine performance, achieving a 41.4% increase in torque and a 40.2% increase in power coefficient (CP) at TSR 5, which was identified as the optimal operating condition. The OptA foil enhances velocity distribution, reduces flow separation, and improves vortex behavior, leading to greater efficiency and stability. These findings confirm that foil selection and blade design modifications play a critical role in HATT optimization.
Copyright (c) 2025 Nu Rhahida Arini, Philips Ade Putera Atmojo, Deni Saputra, Dendy Satrio http://creativecommons.org/licenses/by-sa/4.0
Modern research of using alternative energy resources in Azerbaijan
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).
Copyright (c) 2025 Ramil Sadigov Ali, Mushkunaz Nazarova Kichmirza, Garayeva Irada Eyvaz, Gunay Mammadova Israphil, Turkan Hasanova Allahverdi, Muhammad Madnee http://creativecommons.org/licenses/by-sa/4.0
A hybrid features based malevolent domain detection in cyberspace using machine learning
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.
Copyright (c) 2025 Saleem Raja Abdul Samad, Pradeepa Ganesan, Amna Salim Rashid Al-Kaabi, Justin Rajasekaran, Murugan Singaravelan, Peerbasha Shebbeer Basha http://creativecommons.org/licenses/by-sa/4.0
Solar photovoltaic based cascaded multilevel inverter with 33-levels using phase opposition disposition control method
A cascaded multilevel inverter (MLI) tailored for photovoltaic (PV) networks, aiming to improve power quality and support transformer-less operation. The symmetric MLI design is selected for its effectiveness in minimizing harmonics and enhancing fault tolerance in high-power scenarios, where the use of power semiconductor converters can introduce complications. The proposed inverter configuration achieves thirty-three voltage levels, optimizing power quality while using insulated gate bipolar transistor (IGBT) semiconductor switches. The phase opposition disposition (POD) control method is applied to trigger necessary switching signals for the inverter's components. To ensure high output voltage for the MLI, a boost converter is employed, and the overall system is tested with an R load. The effectiveness of the design is validated through MATLAB/Simulink simulations, which demonstrate a notable reduction in total harmonic distortion (THD).
Copyright (c) 2025 Chandolu Sai Deepak, Madhu Babu Thiruveedula, Bandari Rahul Teja, Supe Gowtham, Sthambhampally Vivek, Panuganti Yeshwanth Kumar http://creativecommons.org/licenses/by-sa/4.0
The impact of fast charging technology on battery longevity in electric vehicles
Fast charging technology has revolutionized the electric vehicle (EV) industry by addressing range anxiety and significantly reducing charging times. However, this convenience introduces challenges concerning battery longevity, as high charging currents and elevated temperatures accelerate battery degradation. This paper investigates the mechanisms through which fast charging impacts lithium-ion batteries, including thermal stress, lithium plating, and mechanical wear. It synthesizes findings from various studies, highlighting how fast charging can shorten battery lifespan by up to 20-30% compared to standard charging methods. Strategies to mitigate these effects, such as advanced materials, adaptive charging protocols, and efficient thermal management systems, are discussed. Furthermore, the paper emphasizes the importance of standards and policies to promote sustainable fast charging practices. By balancing charging speed with long-term battery health, the EV industry can achieve widespread adoption while ensuring sustainability. This work aims to provide a comprehensive understanding of the trade-offs associated with fast charging and offers actionable insights for improving EV battery durability.
Copyright (c) 2025 Perattur Nagabushanam, Kalagotla Chenchireddy, Radhika Dora, Thanikanti Sudhakar Babu, Vadthya Jagan, Varikuppala Manohar http://creativecommons.org/licenses/by-sa/4.0
Optimizing retail systems: using big data and power business intelligence for performance insights
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.
Copyright (c) 2025 Huu Dang Quoc, Ha Le Viet http://creativecommons.org/licenses/by-sa/4.0
Pitch extraction using discrete cosine transform based power spectrum method in noisy speech
The pitch period is a key component of many speech analysis research projects. In real-world applications, voice data is frequently gathered in noisy surround- ings, therefore algorithms must be able to manage background noise well in order to estimate pitch accurately. Despite advancements, many state-of–the-art algorithms struggle to deliver adequate results when faced with low signal-to- noise ratios (SNRs) in processing noisy speech signals. This research proposes an effective concept specifically designed for speech processing applications, particularly in noisy conditions. To achieve this goal, we introduce a fundamen- tal frequency extraction algorithm designed to tolerate non-stationary changes in the amplitude and frequency of the input signal. In order to improve the extrac- tion accuracy, we also use a cumulative power spectrum (CPS) based on discrete cosine transform (DCT) rather than conventional power spectrum. We enhance extraction accuracy of our method by utilizing shorter sub-frames of the input signal to mitigate the noise characteristics present in speech signals. According to the experimental results, our proposed technique demonstrates superior per- formance in noisy conditions compared to other existing state-of-the-art meth- ods without utilizing any kind of post-processing techniques.
Copyright (c) 2025 Humaira Sunzida, Nargis Parvin, Jafrin Akter Jeba, Sulin Chi, Md. Shiplu Ali, Moinur Rahman, Md. Saifur Rahman http://creativecommons.org/licenses/by-sa/4.0
Therapeutic potential of alpha-linolenic acid from Sacha Inchi oil in cervical cancer: an in vitro study on HeLa cells
This study investigated the potential of alpha-linolenic acid (ALA) from Sacha Inchi oil as a therapeutic agent for cervical cancer through an in vitro study on HeLa cells. Cervical cancer is one of the most common types of cancer in women, which is often caused by human papillomavirus (HPV) infection. Although chemotherapy therapy is one of the main methods in cancer treatment, this approach often causes side effects and drug resistance. ALA, which is one of the main components of Sacha Inchi oil, is known to have antioxidant and anti-cancer activities. In this study, Sacha Inchi oil was analyzed using liquid chromatography-high resolution mass spectrometry (LC-HRMS) for identification of its active components. Cytotoxic assays were performed using the MTT method on HeLa cells, which showed that ALA significantly inhibited cancer cell viability at low concentrations, with low IC50 values compared to the positive control compound cisplatin. These results suggest that ALA has potential as an effective anti-cancer agent against cervical cancer cells. This study concludes that ALA from Sacha Inchi oil can be a strong candidate in the development of safer and more effective cervical cancer therapy.
Copyright (c) 2025 Adi Permadi, Mutiara Wilson Putri, Muhammad Ali Akbar http://creativecommons.org/licenses/by-sa/4.0
Searchable encryption based on a chaotic system and AES algorithm
Cloud computing provides on-demand access to computing resources, such as storage and processing power. This technology allows businesses to scale efficiently while reducing infrastructure costs. However, protecting the security and privacy of data has grown to be a top priority. This is where enhancing cloud security with searchable encryption (SE) is crucial. SE effectively secures users’ sensitive data while preserving searchability on the cloud server side. It enables the cloud server to search via encrypted data without disclosing information in plaintext data. SE uses different encryption methods to encrypt data before uploading it to servers. The advanced encryption standard (AES) is a common algorithm for encrypting this data. In this paper, a novel SE method has been presented. The technique exploits the properties of the chaotic map to generate an AES key, which makes the AES algorithm more secure for encrypting the searchable index and uploaded files. We implement and test our method with real data from files. The experimental results show that the proposed method can significantly satisfy a higher level of security as compared to other schemes.
Copyright (c) 2025 Fairouz Sherali, Falah Sarhan http://creativecommons.org/licenses/by-sa/4.0