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28,188 Article Results

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

Relationship between shift work and the risk of colorectal cancer among Moroccan women

10.11591/ijphs.v14i3.25572
Hamza Elbaylek , Soumia Ammor
Colorectal cancer (CRC) is a public health problem worldwide, and also in Morocco, with 7.9% of new cancer cases. Dietary factors have been linked to CRC risk; however, several modifiable risk factors have not been studied in Morocco. This study aimed to explore the association between shift work and the risk of colorectal cancer among Moroccan women. A case-control study was conducted at CHU Mohamed VI Marrakech, involving 165 cases and 165 controls. Data were collected using a self-administered questionnaire. For general characteristics, we used the Chi-square test for categorical variables and student’s t-test or Mann-Whitney U for continuous variables to select confounding factors, we ran logistic regression analysis to estimate odds ratios and 95% confidence intervals. Findings from our study show an increased risk of CRC for rotating shift workers ORb:1.74 (95% CI:1.05-2.91) (p-value = 0.01). When stratified by tumor location, night shift work was correlated with an increased risk of rectal cancer, while stratified by age, rotating shift work was also correlated with an increased risk of CRC among those aged 45 to 65 years ORb: 2.18 (95% CI:1.03-4.79) (p-value = 0.048). Findings from this study may be helpful for future research in Morocco and North African countries.
Volume: 14
Issue: 3
Page: 1109-1118
Publish at: 2025-09-01

Empowering breastfeeding mothers: How self-directed learning boosts confidence-unveiling the two-round Delphi method

10.11591/ijphs.v14i3.25965
Dewi Ariani , Respati Suryanto Dradjat , Kumboyono Kumboyono , Lilik Zuhriyah
Promoting breastfeeding self-efficacy through self-directed learning requires behavior, goal setting, and self-reinforcement. This research aims to collect insights from health professionals on strategies for improving maternal confidence in breastfeeding using self-directed learning and existing knowledge. An in-depth exploration through a two-round Delphi method rooted in the self-efficacy theory of self-directed learning for breastfeeding mothers was conducted, involving expert input and an extensive literature review. Four key documents were identified, each undergoing rigorous expert rating to ensure quality. Six essential elements for health professionals to guide breastfeeding mothers were established, focusing on lactation physiology, successful initiation, confidence building, adversity management, cultural beliefs, and public breastfeeding. Three crucial topics, including prior knowledge, personal attributes, and autonomous processes, were designed to enhance self-efficacy through self-directed learning. In conclusion, the study emphasizes the vital role of health professionals in supporting mothers through comprehensive breastfeeding guidance and encouraging self-directed learning.
Volume: 14
Issue: 3
Page: 1256-1266
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

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 ±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

Assessment of depression, malnutrition and co-morbidities of geriatric individuals in rural areas of Bangladesh

10.11591/ijphs.v14i3.26155
Mst. Umme Hafsa Begum , Md. Nazrul Islam , Afsana Akter , Lima Akter , Mst. Trisha Akter , Md. Abul Hasnat , Mst. Rokshana Rabeya
In rural Bangladesh, elderly populations face distinct health challenges, with depression, malnutrition, and co-morbidities significantly impacting their well-being. This cross-sectional study evaluated 384 older adults across four divisions of Bangladesh using the geriatric depression scale (GDS-15), mini nutritional assessment (MNA), and Katz Index of activities of daily living (ADL). Depression was found among 62.8% of respondents. About 13.0% of participants were malnourished, and 51.8% were at risk of malnutrition. Self reported hypertension (47.1%), arthritis (46.4%), dental problems (43.5%), and insomnia (37.0%) were profound among respondents. The risk of dementia, anorexia, cardiovascular disease, and hypertension was higher among males than females. Geriatric depression was significantly higher in the elderly who were residing in a nuclear family than their counterparts (AOR = 2.114; 95% CI = 1.328-3.365). Additionally, being unemployed was identified as an independent predictor of GD (AOR = 1.992, 95% CI: 1.070 3.709, p = .030). The higher prevalence of depression and risk of malnutrition highlight the pressing requirement for well-coordinated and comprehensive healthcare strategies. The development of multifaceted approaches, incorporating mental health services, nutritional interventions, and socioeconomic support, would enhance elders' well-being.
Volume: 14
Issue: 3
Page: 1620-1628
Publish at: 2025-09-01

Philippine traditional herbal remedies for hypertension

10.11591/ijphs.v14i3.25625
Meliza Parba , Cesar G. Demayo
Certain areas of the Philippines continue to rely on traditional non-pharmacological approaches, such as herbal medicine, for hypertension treatment, a significant public health problem globally. Therefore, a systematic review of plants used in the Philippines to treat hypertension, based on the PRISMA flow diagram, was carried out. Relevant ethnobotanical studies were retrieved from databases such as Google Scholar, ScienceDirect, and PubMed. Following the eligibility screening, 36 ethnobotanical studies were included. The majority of the studies included in this review came from Region XIII (CARAGA), Region VI (Western Visayas), and Region X (Northern Mindanao). The most prevalent plant family and species were Poaceae (12 species) and Cymbopogon citratus (DC.) Stapf. (16 citations), respectively. Leaves were the most common plant parts utilized while decoction was the most frequently mentioned mode of preparation. Oral administration was the most widely used form of administration. This review highlights medicinal plants with potential antihypertensive properties. It underscores the need to conduct a systematic review of their pharmacological properties to determine which have been scientifically validated and are most effective against hypertension.
Volume: 14
Issue: 3
Page: 1585-1594
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

Artificial neural network based sensorless position estimation and direct torque control for stepper motor

10.11591/ijaas.v14.i3.pp702-710
Nagasridhar Arise , Thiruveedula Madhu Babu , Srinidhi Gollapudi , Tarun Kumar Dommeti , Abhishek Kummari , Mahith Shambukari
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.
Volume: 14
Issue: 3
Page: 702-710
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

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

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

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

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

Supportive work environment for people with Down syndrome in Malaysia: a cross-sectional study

10.11591/ijphs.v14i3.25124
Md Mizanur Rahman , Chuong Hock Ting , Razitasham Safii , Rosalia Saimon , Yoke Yong Chen , Sharifa Ezat Wan Puteh , Abg Safuan Adenan
Understanding organizational culture, knowledge of employment rights, and positive attitudes towards people with disabilities is crucial for creating inclusive workplaces. This Malaysian study compared the perspectives of employers, employees, and community members with disabilities using a cross-sectional design and convenience sampling of 595 respondents. Data on demographics, organizational culture, legislative knowledge, and attitudes were collected via a validated survey and analyzed using descriptive statistics, one-way analysis of variance (ANOVA), and multiple linear regression in JAMOVI and SPSS, with a p-value<.05 indicating significance. The study found a moderately supportive organizational culture for employing people with disabilities, with the highest scores in supportive work environments and inclusive culture. Employers and employees perceived greater top management commitment and inclusivity than community members with Down syndrome. Legislative knowledge and positive attitudes significantly shaped perceptions of a supportive and inclusive workplace. Muslim participants reported greater support and disability-accommodating human resource (HR) practices than those of other religions. The findings underscore the need for targeted training and awareness programs on disability rights to enhance inclusivity among all stakeholders in Malaysia.
Volume: 14
Issue: 3
Page: 1489-1498
Publish at: 2025-09-01
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