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31,456 Article Results

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

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

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

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

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

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

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

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

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

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

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

Deep learning for image classification of submersible pump impeller

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

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

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

Therapeutic potential of alpha-linolenic acid from Sacha Inchi oil in cervical cancer: an in vitro study on HeLa cells

10.11591/ijaas.v14.i3.pp966-974
Adi Permadi , Mutiara Wilson Putri , Muhammad Ali Akbar
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.
Volume: 14
Issue: 3
Page: 966-974
Publish at: 2025-09-01

Redesign the layout of the raw material warehouse from randomized storage to class-based storage

10.11591/ijaas.v14.i3.pp773-783
Nur Iftitah , Qurtubi Qurtubi , Danang Setiawan , Vembri Noor Helia
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.
Volume: 14
Issue: 3
Page: 773-783
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

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

Fuzzy logic controller-based protection of direct current bus using solid-state direct current breaker

10.11591/ijaas.v14.i3.pp859-868
Eswaraiah Giddalur , Askani Jaya Laxmi
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.
Volume: 14
Issue: 3
Page: 859-868
Publish at: 2025-09-01
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