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28,188 Article Results

A method classifying the domestic tourist destination base similarity measuring

10.11591/ijaas.v14.i3.pp740-750
Nguyen Thi Hoi , Tran Thi Nhung , Bui Quang Truong , Nguyen Quang Trung
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.
Volume: 14
Issue: 3
Page: 740-750
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

A bibliometric review of lean principles in highway pavement for productivity improvement

10.11591/ijaas.v14.i3.pp639-649
Pooja P. Gohil , MohammedShakil S. Malek , Deep Shaileshkumar Upadhyaya
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.
Volume: 14
Issue: 3
Page: 639-649
Publish at: 2025-09-01

The impact of fast charging technology on battery longevity in electric vehicles

10.11591/ijaas.v14.i3.pp936-944
Perattur Nagabushanam , Kalagotla Chenchireddy , Radhika Dora , Thanikanti Sudhakar Babu , Vadthya Jagan , Varikuppala Manohar
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.
Volume: 14
Issue: 3
Page: 936-944
Publish at: 2025-09-01

Test rig development for load test of pipe saddle support

10.11591/ijaas.v14.i3.pp886-893
Muhammad Arif Rayhan , Mohd Shukri Yob , Mohd Juzaila Abd Latif , Ojo Kurdi , Fudhail Abdul Munir
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.
Volume: 14
Issue: 3
Page: 886-893
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

Solar photovoltaic based cascaded multilevel inverter with 33-levels using phase opposition disposition control method

10.11591/ijaas.v14.i3.pp928-935
Chandolu Sai Deepak , Madhu Babu Thiruveedula , Bandari Rahul Teja , Supe Gowtham , Sthambhampally Vivek , Panuganti Yeshwanth Kumar
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). 
Volume: 14
Issue: 3
Page: 928-935
Publish at: 2025-09-01

Five-Tier BI architecture with tuned decision trees for e-commerce prediction

10.11591/ijeecs.v39.i3.pp1633-1641
Thiruneelakandan Arjunan , Umamageswari A.
In recent times, remarkable performance has been shown by large language models (LLMs) in a range of natural language processing (NLP) such as questioning, responding, document production, and translating languages. In today's competitive business landscape, understanding consumer behaviour in online buying is crucial for the success of e-commerce platforms. The work proposes a novel Five-Tier service-oriented BI architecture (FSOBIA) that leverages advanced tuned decision tree (ATDT) techniques for predicting online buying behaviour. The proposed FSOBIA offers e-commerce platforms a scalable and adaptable solution for gaining insights into consumer preferences and making informed business decisions. The goal of FSOBIA's design and implementation is to meet the needs of evolving users and quicker service. Experimental evaluations on real-world datasets in FSOBIA achieved over 95% prediction accuracy, outperforming traditional models: Decision trees (82%), and XGBoost (91%), while offering better scalability and computational efficiency.
Volume: 39
Issue: 3
Page: 1633-1641
Publish at: 2025-09-01

Exploring the impact of artificial intelligence driven solutions on early detection of cardiac arrest

10.11591/ijeecs.v39.i3.pp1938-1945
Tejashree Venkatesha , Saravana Kumar Sundararajan
The advancement of medical science and technology has yet not evolved up with a concrete solution towards early detection of cardiac arrest from practical deployment. It is noted that artificial intelligence (AI) has been proving a potential contributor to address this state of diagnosis emergency. In current era of research work, there has been various implementation model and review work has been carried out towards advocating AI for determining early onset of cardiac arrest; however, there are various contradiction and shortcoming which is quite challenging to be extracted. Hence, the current manuscript presents a review of existing methodology by presenting core taxonomies of recent AI-methods towards early detection of cardiac arrest. Various standard dataset has been studied too to find associated advantages and limitation that restrict the actual potential of AI to prediction. The outcome presents novel highlights of research gap, trade-off, and crisp highlights of effectiveness of existing AI approaches as a study contribution.
Volume: 39
Issue: 3
Page: 1938-1945
Publish at: 2025-09-01

Localization and mapping of autonomous wheel mobile robot using Google cartographer

10.11591/ijra.v14i3.pp322-331
Qory Hidayati , Novendra Setyawan , Amrul Faruq , Muhammad Irfan , Nur Kasan , Fitri Yakub
COVID-19 has become a world concern because of the spread and number of cases that have befallen the world. Medical workers are the first exposed group because they have direct contact with patients. So, a vehicle is needed to replace tasks such as logistics, delivery, and patient waste transportation. An autonomous wheeled mobile robot (AWMR) is a wheeled robot capable of moving freely from one place to another. AWMR is required to have good navigation and trajectory control skills. The purpose of this study is to develop an AWMR navigation system model based on the simultaneous localization and mapping (SLAM) algorithm, accurately in a dynamic environment. With this research, developing a good navigation and trajectory method for AWMR, in the future, it can be applied to produce an AWMR platform for multipurpose. This research was conducted in two stages of development. The first year is the research that is currently being carried out, focused on sensor modeling, designing SLAM-based navigation models, and making navigation system testbeds. This research produces a trajectory navigation and control system that can be implemented on an AWMR platform for the purposes of logistics, transportation, and patient waste in hospitals.
Volume: 14
Issue: 3
Page: 322-331
Publish at: 2025-09-01

SCADA system in water storage tanks with NI vision LabVIEW

10.11591/ijra.v14i3.pp381-392
Kartika Kartika , Misriana Misriana , M. Fathan Naqi , Asran Asran , Misbahul Jannah , Arnawan Hasibuan , Suryati Suryati
Advances in technology have driven the need for efficient water management systems. This study presents a SCADA-based water management system that integrates LabVIEW and Arduino to monitor and regulate water levels and flow rates in a storage tank. The system uses an HC-SRF04 ultrasonic sensor for water level measurement with 99.77% accuracy and an HX710 pressure sensor, which achieves 98.54% accuracy. The LabVIEW interface displays real-time data, giving users an intuitive view of system performance. A proportional integral derivative (PID) algorithm optimizes the water pump through pulse width modulation (PWM), achieving water flow rate control. The Ziegler-Nichols method tunes the PID parameters to Kp = 16.59, Ti = 1.102, and Td = 0.2755. This tuning ensures the system maintains a consistent target flow rate of 4 liters per minute (L/min) with minimal variation. Initial testing showed a 2.5% overshoot but stabilized at the desired flow rate within 10 seconds, indicating effective control. This SCADA system reduces water and energy waste by enabling continuous real-time monitoring and control. The system provides accurate data through a LabVIEW interface, ensuring effective and informed operational decisions. This robust solution supports efficient water management for industrial and environmental applications, contributing to sustainability and resource optimization.
Volume: 14
Issue: 3
Page: 381-392
Publish at: 2025-09-01

Robot Gaussian-historical relocalization: inertial measurement unit-LiDAR likelihood field matching

10.11591/ijra.v14i3.pp438-450
Ye-Ming Shen , Min Kang , Jia-Qiang Yang , Zhong-Hou Cai
Robot localization is a foundational technology for autonomous navigation, enabling task execution and adaptation to dynamic environments. However, failure to return to the correct pose after power loss or sudden displacement (the “kidnapping” problem) can lead to critical system failures. Existing methods often suffer from slow relocalization, high computational cost, and poor robustness to dynamic obstacles. We propose a novel inertial measurement unit (IMU)-LiDAR fusion relocalization framework based on Gaussian historical constraints and adaptive likelihood field matching. By incorporating IMU-derived yaw constraints and modeling historical poses within a 3σ Gaussian region, our method effectively narrows the LiDAR search space. Curvature and normal vector-based feature extraction reduces point cloud volume by 50–70%, while dynamic obstacle filtering via multi-frame differencing and neighborhood validation enhances robustness. An adaptive spiral search strategy further refines pose estimation. Compared to ORB-SLAM3 and adaptive Monte Carlo localization (AMCL), our method maintains comparable accuracy while significantly reducing relocalization time and CPU usage. Experimental results show a relocalization success rate of 84%, average time of 1.68 seconds, and CPU usage of 38.4%, demonstrating high efficiency and robustness in dynamic environments.
Volume: 14
Issue: 3
Page: 438-450
Publish at: 2025-09-01

Multi-robot coverage algorithm in complex terrain based on improved bio-inspired neural network

10.11591/ijra.v14i3.pp348-360
Fangfang Zhang , Mengdie Duan , Jianbin Xin , Jinzhu Peng
Biological neural network (BNN) algorithms have become popular in coverage search in recent years. However, its edge activity values are weak, and it is simple to fall into a local optimum at a late stage of coverage. When applied to complex environments, the 3D BNN network structure has high computational and storage complexity. In order to solve the above problems, we propose an algorithm for multi-robot cooperative coverage of complex terrain based on an improved BNN. The algorithm models the complex terrain using a 2.5-dimensional (2.5D) elevation map. Combining the dual-layer BNN network with the 2.5D elevation map, we propose an elevation value priority mechanism. This mechanism lets the robot make elevation-based decisions and prioritizes higher terrain areas. The dual neural network's first layer plans the robot's path in normal mode. The second network layer helps the robot escape the local optimum. Finally, the algorithm's full coverage effect in complex terrains and the speed of covering high terrain are verified by simulations. The experiments show that our algorithm preferentially covers high points of the region and eventually covers 100% of complex terrain. Compared with other algorithms, our algorithm covers more efficiently and takes fewer steps than others. The speed of covering high terrain areas has increased by 34.51%.
Volume: 14
Issue: 3
Page: 348-360
Publish at: 2025-09-01

Energy efficient clustering and routing method for Internet of Things

10.11591/ijra.v14i3.pp418-428
Bhawna Ahlawat , Anil Sangwan
The Internet of Things is crucial in monitoring environmental conditions in remote areas, but it faces significant challenges related to energy consumption, which affects network longevity and coverage. Clustering has proven effective in prolonging the life of sensor networks. Adaptive clustering in wireless sensor networks allows for more effective cluster organization via real-time rearranging of sensor nodes according to important parameters, which include energy levels and the distance between them. Fruit fly algorithm (FFA) and ant colony optimization (ACO) are emerging as encouraging techniques for creating clusters and establishing paths, respectively. This paper describes the use of the FFA to make the clustering process better by selecting the best cluster head and reducing energy consumption. This paper proposes a novel solution that integrates ACO for establishing paths with FFA for clustering. This method is tested in both homogeneous and heterogeneous settings using MATLAB, comparing its performance with two existing algorithms: low energy adaptive clustering hierarchy (LEACH) and biogeography-based optimization algorithm (BOA). According to the findings, the suggested algorithm performs noticeably better than BOA and LEACH in the context of coverage area and network service period, especially in heterogeneous settings.
Volume: 14
Issue: 3
Page: 418-428
Publish at: 2025-09-01

An Internet of Things based mobile-controlled robot with emergency parking system

10.11591/ijra.v14i3.pp370-380
Abdul Kareem , Varuna Kumara , Vishwanath Madhava Shervegar , Karthik S. Shetty , Manvith Devadig , Mahammad Shamma , Kiran Maheshappa
This paper presents an Internet of Things (IoT) based mobile-controlled car with an emergency parking system that integrates advanced functionalities to enhance safety and user convenience, utilizing the ESP32 microcontroller as its core. The system allows users to control the car remotely via a mobile application, leveraging Wi-Fi connectivity for seamless communication. Key features include LED indicators for various operations such as reversing, left and right turns, and brake activation, ensuring clear signaling in real-time. The innovative emergency parking system detects obstacles or emergencies using sensors and halts the vehicle automatically, reducing the risk of accidents. The car's lightweight, energy-efficient design, combined with the versatility of the ESP32, ensures a responsive and reliable operation. Additionally, the system provides an intuitive user interface through the mobile app, enabling precise control and real-time feedback. The proposed system is faster in response compared to the existing systems. Moreover, the proposed system consumes less energy, and hence, it uses the battery more efficiently, extending the time of operation. Lower power consumption ensures longer operation time, reducing the need for frequent charging and making the system more practical. This paper demonstrates the integration of IoT and embedded systems to create a smart vehicle solution suitable for various applications, including robotics, automation, and personal transport. Its cost-effectiveness and scalability make it a viable choice for both hobbyists and developers.
Volume: 14
Issue: 3
Page: 370-380
Publish at: 2025-09-01
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