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28,188 Article Results

Evaluating the development and cutting capacity of a one-square computer numeric controlled milling machine

10.11591/ijra.v14i3.pp451-462
Oluwaseun Kayode Ajayi , Ayodele Temitope Oyeniran , Shengzhi Du , Babafemi Olamide Malomo , Kolawole Oluwaseun Alao , Quadri Ayomide Omotosho , Marvellous Oluwadamilare Fawole , Ayomide Isaiah Lasaki , Godwin Thompson
Traditional subtractive technology is rapidly losing significance with the advent of digital manufacturing technologies, which offer affordable machining with high accuracy and repeatability. Computer numeric controlled (CNC) machining has been around for a while; however, it has been costly to own one. Since the concept of CNC machining is now broadly understood and open-source software is available for control, designers can make use of available local materials to develop cheaper CNC machines. Hence, this presents the evaluation of the design and development of a one-square-meter CNC milling machine. The control was implemented on Arduino Uno, while open-source Universal G-code Sender (UGS) and G-code reference block library (GRBL) were used for the G-code generation and machine control, respectively. The built CNC was calibrated and tested on wood and plastic materials, and the resulting products were acceptable in accuracy up to Β±0.02 mm in the first trial, but attained perfect accuracy by the third trial. Multiple tests repeatedly showed that accuracy was maintained. Since the machine is reconfigurable, future work entails automation and incorporating laser cutting capabilities into the machine.
Volume: 14
Issue: 3
Page: 451-462
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 β€œkidnapping” 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 3Οƒ 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

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

LoRa-enabled remote-controlled surveillance robot for monitoring and navigation in disaster response missions

10.11591/ijra.v14i3.pp311-321
Anita Gehlot , Rajesh Singh , Rahul Mahala , Mahim Raj Gupta , Vivek Kumar Singh
Rescue missions must be conducted within a strict timeframe, and the safety of all rescuers and civilians is prioritized. The proposed system aims to design a remote-operated aerial surveillance robot for disaster-affected areas for search and rescue missions. Real-time video transmission and RS-232 long-range communication enable operators to navigate rough environments and monitor data collected in real-time. This powerful tool ensures the protection of human life while collecting accurate and meaningful data. Cloud storage for data and surveillance strengthens the system, preventing part failure and fostering collaboration among users. This is a significant step towards using Internet of Things systems alongside remote-controlled robots in disaster response. The robot's key contribution to disaster management is identifying the environment, addressing issues of no visibility, complicated terrains, and speed. Its modification and expansion capabilities make it useful in armed surveillance, industrial monitoring, and environmental studies, making it an important innovation for many other fields.
Volume: 14
Issue: 3
Page: 311-321
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

Hybrid deep learning and active contour for segmenting hazy images

10.11591/ijra.v14i3.pp429-437
Firhan Azri Ahmad Khairul Anuar , Jenevy Jone , Raja Farhatul Aiesya Raja Azhar , Abdul Kadir Jumaat
Image segmentation seeks to distinguish the foreground from the background for further analysis. A recent study presented a new active contour model (ACM) for image segmentation, termed Gaussian regularization selective segmentation (GRSS). This interactive ACM is effective for segmenting certain objects in images. However, a weakness of the GRSS model becomes apparent when utilized on hazy images, as it is not intended for such conditions and produces inadequate outcomes. This paper introduces a new ACM for segmenting hazy images that hybridizes a pretrained deep learning model, namely DehazeNet, with the GRSS model. Specifically, the haze-free images are estimated using DehazeNet, which fuses the information with the GRSS model. The new formulation, designated as GRSS with DehazeNet (GDN), is addressed via the calculus of variations and executed in MATLAB software. The segmentation accuracy was evaluated by calculating Error, Jaccard, and Dice metrics, while efficiency was determined by measuring processing time. Despite the increased processing time, numerical experiments demonstrated that the GDN model achieved higher accuracy, as indicated by the lower error and higher Jaccard and Dice than the GRSS model. The GDN model can potentially be formulated in the vector-valued image domain in the future.
Volume: 14
Issue: 3
Page: 429-437
Publish at: 2025-09-01

Boost efficiency performance through the enhancement of duty cycle based MPPT algorithm

10.11591/ijape.v14.i3.pp541-550
Ahmed Badawi , I. M. Elzein , Walid Alqaisi , Al Hareth Zyoud
The use of direct power control (DPC) has become popular as an effective control strategy for pulse width modulated (PWM) converters. The incremental conductance algorithm (INC) is utilized to control the duty cycle (D) in tracking the optimal point to increase power efficiency in wind energy conversion systems (WECS). WECS parameters are adjusted to achieve unity power factor, allowing the system to extract maximum power (π‘ƒπ‘šπ‘Žπ‘₯) from WECS. Simulation results show that wind speed has a significant impact on the captured power, with a proportional relationship between wind speed and power. Control strategies are employed to optimize the (D) to reach the desired operating point. A DC-DC boost converter is connected to WECS, where the (D) controls the MOSFET to maintain π‘‰π‘œπ‘’π‘‘ at the optimal level on the DC link. Various wind speed profiles are simulated in this study to evaluate system efficiency, especially under conditions of rapid wind speed fluctuations. The controller based on (D) demonstrates superior tracking performance through the DC link, ensuring that π‘‰π‘œπ‘’π‘‘ remains at an optimal level.
Volume: 14
Issue: 3
Page: 541-550
Publish at: 2025-09-01

Effect of DC link capacitor short-circuit on an inverter fed induction motor performance

10.11591/ijape.v14.i3.pp631-639
Cheikh Oudaa , Ethmane Isselem Arbih Mahmoud , Mohamed Amine Khelif , Ahmed Mohamed Yahya , Bendiabdellah Azeddine , Abdel Kader Mahmoud
Induction motors are widely used in industrial power plants because of their durability, reliability and high performance under different operating conditions of the electrical system. It is also important to note that most of these motors are controlled by variable frequency drives. By adjusting the drive parameters, the motor can be managed according to design. The reliability of motor control systems based on variable speed drives is therefore crucial for industrial applications. Unlike induction motors, the power supply components of these electrical machines are delicate and susceptible to faults. To enhance the performance of the control-motor system, it is essential for researchers to understand how faults affect the drive system as a whole. In this context, this paper addresses short-circuit faults in the intermediate circuit capacitor of an induction motor driven by an inverter. The simulation results of these capacitors faults are presented, and their impact on the behavior of the rectifier, the inverter, and the induction motor is analyzed and interpreted.
Volume: 14
Issue: 3
Page: 631-639
Publish at: 2025-09-01

Exploring the role of swimming in enhancing diet-based weight loss programs for athletes

10.11591/ijphs.v14i3.25330
Cherkaoui Sidi Hassan , Mouane Nezha
This study explores the synergistic effects of customized dietary strategies and aerobic exercise, specifically swimming, on achieving weight loss while preserving muscle mass in athletes. The research highlights the importance of a holistic approach to weight management, integrating personalized diet plans with tailored exercise regimens. The study segmented participants into two groups, one following a standard diet for weight maintenance and another adhering to a similar diet augmented by regular swimming sessions aimed at weight loss. Results indicate that the diet-plus-swimming group exhibited significantly greater reductions in weight and body mass index (BMI) compared to the diet-only group, suggesting that incorporating swimming enhances the effectiveness of dietary interventions. These findings emphasize the potential of combining physical activities such as swimming with dietary modifications to achieve optimal weight management outcomes, providing a comprehensive approach to athlete health management. The study also underscores the need for personalized strategies that consider individual characteristics and preferences to support sustainable weight loss and improved health outcomes.
Volume: 14
Issue: 3
Page: 1452-1458
Publish at: 2025-09-01

Thai E-sarn dance on balance and muscle strength in elderly women with falls risk

10.11591/ijphs.v14i3.25067
Warangkana Chompoopan , Worawut Chompoopan , Saowaluk Seedaket , Duangruedee Chotklang , Siratorn Pongjan , Tivapron Kombusadee
The risk of falls, which is a significant contributor to mortality among the elderly population, is increasing due to declining balance and muscle strength. A quasi-experimental design was used in this study to examine the effects of traditional Thai E-sarn on balance and muscle strength in older women living in the community. The experimental or control group consisted of 35 people. The experimental group participated in a 12-week fitness regimen utilizing Thai E-sarn. The control group avoided participating in any type of physical activity. The experimental group exhibited notable enhancements in their balance, muscle strength, and health parameters as compared to the control group. In the experimental group, the timed up and go test (TUG) score was reduced by 1.91 seconds (95%CI: 0.67 to 3.16), p=0.003, while the 30-second chair stand test (30CST) increased by 3.15 (95%CI: 1.24 to 5.04), p<0.002. Systolic blood pressure dropped by 6.58 mmHg, diastolic by 5.57, and heart rate by 5.29 beats per minute. These findings suggest regular Thai E-sarn dance may improve balance, muscle strength, and all other parameters. Additional investigation is required to elucidate the impact of exercise on enhancing the general health of older adults.
Volume: 14
Issue: 3
Page: 1267-1275
Publish at: 2025-09-01

Global stability of SEIM tuberculosis model with two infection phases and medication effects

10.11591/ijphs.v14i3.25899
Jovian Dian Pratama , Anindita Henindya Permatasari
Tuberculosis (TB), caused by mycobacterium tuberculosis (MTB), remains a significant global health issue, leading to high morbidity and mortality rates despite being a preventable and curable disease. The dynamics of TB transmission and the effects of treatment are critical to improving disease management. This study aims to analyze the global stability of a susceptible, exposed, infected, medicated (SEIM) model for TB transmission, incorporating the effects of medication and infection phases on disease progression. A deterministic SEIM model is proposed, dividing the population into four compartments: susceptible, exposed, infected, and medicated. The model accounts for treatment effects, including non-permanent immunity and the potential dormancy of MTB. Stability analysis was conducted using Lyapunov functions to evaluate equilibrium points, and the basic reproduction number (β„œ0) was derived to determine disease dynamics. The analysis reveals that when β„œ0 < 1, the system is globally asymptotically stable at the non-endemic equilibrium, indicating disease eradication. Conversely, when β„œ0 >1, the system converges to the endemic equilibrium, signifying sustained transmission within the population. These findings highlight the critical role of treatment and infection dynamics in controlling TB spread. The SEIM model provides a comprehensive framework for understanding TB transmission dynamics and emphasizes the importance of reducing (β„œ0) through effective public health interventions. Further research is recommended to validate the model with empirical data and explore its applicability in different epidemiological settings.
Volume: 14
Issue: 3
Page: 1137-1150
Publish at: 2025-09-01

Knowledge, attitudes, and practices of nurses caring for surgical cerebral aneurysm patients in a Thai Tertiary Hospital

10.11591/ijphs.v14i3.25981
Palama Sobut , Boonyada Wongpimoln , Supattra Pleaynongkhae , Kitiyarat Hanlue , Sattawas Udonsat
Ruptured cerebral aneurysm after surgery is a critical condition that necessitates vigilant monitoring and early detection of complications by staff nurses. Therefore, an appropriate level of skill and knowledge related to the management of patients undergoing surgery is crucial for nurses to support these patients. The current research aimed to examine KAP indicators (knowledge, attitude, and practice) among nurses in this context, making use of a cross-sectional study design involving the participation of 111 staff nurses selected randomly from one tertiary hospital located in the northeast of Thailand. The study was carried out during February – June 2024, making use of a survey to acquire demographic data along with a questionnaire to measure the KAP indicators. Data were analyzed using the Spearman correlation coefficient and Pearson correlation coefficient. The finding revealed that the overall KAP score on caring patients with ruptured cerebral aneurysm undergoing surgery was high. However, the correlation observed between knowledge/attitude/age/duration of experience for caring patients with ruptured cerebral aneurysm undergoing surgery and practice was shown to be both positive and significant (p<0.05). Therefore, nurse administrators should implement a comprehensive knowledge training system, enhance specialized training, and improve nursing practices for these patients. This will help to ensure that staff nurses achieve a high level of KAP in providing optimal care for these patients.
Volume: 14
Issue: 3
Page: 1561-1568
Publish at: 2025-09-01
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