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Hybrid semantic model based on machine learning for sentiment classification of consumer reviews

10.11591/ijai.v14.i3.pp2001-2011
Palaniraj Rajidurai Parvathy , Nagarajan Mohankumar , Rajendran Shobiga , Gour Sundar Mitra Thakur , Mamatha Bandaru , Velusamy Sujatha , Shanmugam Sujatha
Digital information is regularly produced from a variety of sources, including social media and customer service reviews. For the purpose of increasing customer happiness, this written data must be processed to extract user comments. Consumers typically share comments and thoughts about consumable items, technological goods, and services supplied for payment in the modern period of consumerism with simple access to social networking globe. Each object has a plethora of remarks or thoughts that demand special attention due to their sentimental worth, especially in the written portions. The goal of the current project is to do sentiment prediction on the Amazon Electronics, Kindle, and Gift Card datasets. In order to predict sentiment and evaluate utilizing many executions evaluates admitting accuracy, recall, and F1-score, a hybrid soft voting ensemble method that combines lexical and ensemble methodologies is proposed in this study. In addition to calculating a subjectivity score and sentiment score, this study also suggests a non-interpretive sentiment class label that may be used to assess the sign of the evaluations applying suggested method for sentiment categorization. The effectiveness of our suggested ensemble model is examined using datasets from Amazon customer product reviews, and we found an improvement of 2-5% in accuracy compared to the current state-of-the-art ensemble method.
Volume: 14
Issue: 3
Page: 2001-2011
Publish at: 2025-06-01

Influence of community factors on formal care use among older Chinese adults

10.11591/ijphs.v14i2.24703
Zihan Zhang , Chieko Kato
Community plays a pivotal role in older adults' well-being and long-term care issues. This study investigates how community factors, including community support and social participation, with self-assessment of health as an intervening variable, influence the use of formal care. Further, how a community contributes to older adults' well-being has also been discussed. Data was collected from older adults (men 150, women 150, age>60 y/o) and was analyzed by using structural equation modeling (SEM). This study used health as an intervening variable to investigate community factors' influence on formal care use. The results find a significant negative influence of social participation and self-assessment of health on the use of formal care. While community support was not found to influence the use of formal care significantly, both community support and social participation could negatively influence the use of formal care by positively influencing the self-assessment of health. Cohabitation has also been found to influence community support significantly positively. In China, where formal care still needs to be more developed, reducing over-reliance on formal care follows Chinese cultural values and economic considerations. Moreover, older people living alone need to be attended to by the community.
Volume: 14
Issue: 2
Page: 959-966
Publish at: 2025-06-01

The role of family-centered care in enhancing stroke rehabilitation outcomes: an integrative literature review

10.11591/ijphs.v14i2.24847
Fery Agusman Motuho Mendrofa , Dwi Indah Iswanti , I Made Moh. Yanuar Saifudin
Family-centered care (FCC), which emphasizes the involvement of family members as active participants in the care process, represents a significant paradigm within the realm of stroke rehabilitation. This study aimed to locate and synthesize the most recent evidence concerning the advantages, methodologies, and obstacles associated with the integration of FCC in stroke rehabilitation. The approach taken involves conducting an integrative literature review following the guidelines set forth by Whittemore and Knafl. A thorough exploration of four databases including PubMed, CINAHL, Scopus, and PsycINFO, was carried out, focusing on both quantitative and qualitative studies published between January 2012 and December 2022. Inclusion criteria comprised studies involving adult stroke patients undergoing rehabilitation, detailing family-centered interventions, and presenting outcomes for either the patients or their families. Upon the screening process, 25 studies met the inclusion criteria and were included in the analysis. Various strategies have been identified to effectively involve families in the rehabilitation process, such as educational initiatives, collaborative planning for home-based care, and provision of support for caregivers. However, the implementation of FCC faces challenges stemming from factors at the system level, provider level, and patient/family level, in conclusion, the integration of FCC in stroke rehabilitation yields substantial benefits for both patients and caregivers. It is imperative for nurses to engage families as collaborative partners, tailor interventions according to specific requirements, offer assistance to caregivers, and instigate changes at the systemic level.
Volume: 14
Issue: 2
Page: 1031-1039
Publish at: 2025-06-01

Deep learning approaches, platforms, datasets for behaviorbased recognition: a survey

10.11591/ijeecs.v38.i3.pp1880-1895
Yunusa Mohammed Jeddah , Aisha Hassan Abdallah Hashim , Othman Omran Khalifa
Video surveillance is an extensively used tool due to the high rate of atypical behavior and many cameras that enable video capture and storage. Unfortunately, most of these cameras are operator dependent for stored content analysis. This limitation necessitates the provision of an automatic behavior identification system. This behavior identification can be achieved using unsupervised (generative) computer vision methods. Deep learning makes it possible to model human behavior regardless of where they could be. We attempt to classify current research work to report the ongoing trends in human behavior recognition using deep learning algorithms. This paper reviews various aspects, like the ones associated with machine learning and deep learning models, human activity recognition (HAR), deep learning frameworks/tools, abnormal behavior datasets, and a variety of other current trends in the field of automatic learning. All these are to give the researcher a sense of direction in this area.
Volume: 38
Issue: 3
Page: 1880-1895
Publish at: 2025-06-01

Integrating gamification to increase users’ engagement to adhere COVID-19 interventions using extended TAM

10.11591/ijeecs.v38.i3.pp1936-1945
Mohd Hazim Afiq Kalana , Syahrul Nizam Junaini , Suriati Khartini Jali , Yusep Rosmansyah , Atina Putri , Ahmad Alif Kamal
Gamification has shown potential for enhancing motivation and engagement, yet its effectiveness in promoting adherence to COVID-19 preventive measures remains underexplored. With decreasing public attentiveness, this study examines the role of gamification in encouraging compliance with health protocols through an extended technology acceptance model (TAM) and structural equation modeling (SEM). A gamified mobile application was developed, incorporating features such as points, badges, and progress tracking, and was designed to appeal to younger audiences. Data collected from 150 secondary school students in Sarawak, Malaysia, indicated that perceived usefulness, perceived ease of use, and attitude toward the app significantly influenced engagement with COVID-19 preventive measures. Among these factors, perceived usefulness demonstrated the strongest effect on engagement (β = 0.424, t = 4.812, p < 0.001). The findings highlight the potential of gamification to enhance compliance with COVID-19 protocols.
Volume: 38
Issue: 3
Page: 1936-1945
Publish at: 2025-06-01

The omega 3 index: a study on the Portuguese population

10.11591/ijphs.v14i2.24104
Carlos Cardoso , Romina Gomes , João Francisco , Maria Sapatinha , Cláudia Afonso , Narcisa M. Bandarra
The omega-3 index (O3I) is used as a biomarker for cardiovascular disease risk. The factors affecting O3I are not fully understood. A study was conducted in a representative sample of the Portuguese population (1,126 individuals) involving blood sampling for the determination of O3I and answering a questionnaire. Participants were asked to indicate their consumption frequencies and other relevant data. The average O3I of the population was 4.82±2.30%. There was a clear increasing trend of the O3I with higher amounts of consumed seafood, achieving an O3I of ~6% with three or more weekly meals. Age was a major determinant, presenting 50-79 year old males higher O3I values than 18-49. Physical activity led to higher O3I, 5.05±2.39% vs 4.64±2.21%. Smoking caused a lower O3I, 4.38±1.97% vs 4.89±2.34%. Physical activity had a larger effect upon O3I in consumers with high seafood consumption. In elderly (>70 year old), there was an inverse relation between O3I levels and high blood pressure. This study’s findings point to the importance of changing dietary habits in the direction of increasing seafood consumption and combining these nutritional changes with a healthier lifestyle (with more physical activity and no smoking) for a higher O3I and a lower cardiovascular disease incidence.
Volume: 14
Issue: 2
Page: 836-851
Publish at: 2025-06-01

Aerobics research in China: characteristics, hotspots, and evolution visualized

https://ijphs.iaescore.com/index.php/IJPHS/article/view/24889
Wang Yang , Zainal Abidin B Zainuddin
This study utilizes CiteSpace software to visually analyze 679 core journal papers from the CNKI database, exploring the landscape of aerobics research in China. It aims to identify influential authors and institutions while elucidating the evolution of research focus from its early stages to current trends. The primary objective is to explore the characteristics of aerobics research, including hot topics, evolving frontiers, and key developments. By examining titles, keywords, abstracts, and other materials, CiteSpace software provides insights into the scientific knowledge graph, emphasizing influential authors and institutions in aerobics research. The findings reveal a notable shift in focus from early public teaching to current emphasis on competitive aerobics, physical education, and athlete transitions. The research field has expanded to encompass diversified topics, showcasing continuous depth in empirical and theoretical investigations. Three distinct periods are identified in research frontiers: early, middle, and recent stages, each with unique directions and emphases. The study recommends a multi-disciplinary integrated development approach in aerobics research, emphasizing enriched teaching and competition visions, improved regional integration policies, and a comprehensive display of the field’s research and development status. Acknowledging evolving trends and diversification will contribute to a holistic understanding and continued advancement of aerobics research.
Volume: 14
Issue: 2
Page: 967-977
Publish at: 2025-06-01

Analysis of geothermal technology development in the Colombian energy transition to 2050 using system dynamics

10.11591/ijece.v15i3.pp2523-2533
Diego Alberto Carreño , Isaac Dyner , Enrique Ángel Sanint , Andrés Julián Aristizábal
This research analyzes the current and future prospects of geothermal energy in Colombia using a system dynamics model. The study focuses on evaluating geothermal potential linked to hydrothermal systems, surface manifestations like geysers, and areas near volcanoes. The model, projecting up to 2050, offers a comprehensive assessment of national geothermal potential, considering technical, economic, regulatory, and social factors that influence its integration into the energy matrix. Key findings highlight the need for adjustments to the existing regulatory framework, which currently lacks sufficient incentives for geothermal project development. Additionally, the study underscores the importance of implementing stronger government policies and incentives to promote this renewable energy source. Proper social and environmental management, with active involvement of local communities, is also identified as crucial for project success. The system dynamics approach effectively models the complex interrelationships between variables shaping the future of geothermal energy in Colombia. The developed model serves as a novel tool for technological foresight in this strategic field, identifying obstacles and opportunities to unlock Colombia's significant geothermal potential and providing a systemic perspective on this critical issue for the national energy transition.
Volume: 15
Issue: 3
Page: 2523-2533
Publish at: 2025-06-01

Road pavement deformation using remote sensing technique

10.11591/ijaas.v14.i2.pp345-351
Kishan Patel , Rajesh Gujar
The road surface reflects the status of the city’s infrastructure. Road safety and driving comfort can be affected by the rough surface. To minimize road hazards, pavement conditions must be periodically inspected for damaged surfaces. A quick and efficient data collection can be provided by the radar images. For a large spatial coverage, radar image provides a non-destructive data collection technique for analyzing road conditions and classifying distress. The surface distress can be correlated by analyzing the images collected from high-resolution cameras and satellites. This article outlines the applicability of synthetic aperture radar (SAR) and interferometric synthetic aperture radar (InSAR) based images to manage and monitor pavement infrastructure. Therefore, the detection of deteriorating surfaces can be improved by analyzing the radar images timely. The results showed the deficiencies on the surface that can be used to mitigate bad pavement conditions and allow road users to use good road infrastructure with safety and comfort.
Volume: 14
Issue: 2
Page: 345-351
Publish at: 2025-06-01

Bridging technology and healthcare: user acceptance of a surgical site infection system

10.11591/ijaas.v14.i2.pp523-532
Afan Fatkhur Akhmad , Maria Ulfa
Surgical site infections (SSI) continue to be a problem for surgeons, and unfortunately, SSI information systems are underutilized. This study analyzed the user acceptance of the SSI information system based on the extended technology acceptance model (TAM2). A cross-sectional questionnaire-based study. The variables studied intention to use (IU), perceived ease of use (PEOU), demographic factors (FD), subjective norm (SN), Image (I), job relevance (JR), output quality (OQ), result demonstrability (RD), perceived usefulness (PU). Data were collected by filling out questionnaires and then analyzed using smart-partial least squares (PLS). In total, 61 nurses were included. Most respondents are aged 31-35 (26.23%), and most working periods are between 11-15 years (27.87%). There were significant positive effects on SN to PU (β=0.12; p 0.05). This study concluded that PEOU is the most influential variable in the IU the SSI information system.
Volume: 14
Issue: 2
Page: 523-532
Publish at: 2025-06-01

Content based image retrieval using visual geometric group19 with Jaccard similarity measure

10.11591/ijaas.v14.i2.pp430-438
Rajath Arakere Narayanaswamy , Vidyalakshmi Krishne Gowda
Content-based image retrieval (CBIR) is an important research area that focuses on emerging techniques for handling large image collections and enabling efficient retrieval. The main challenge of image retrieval is to extract relevant feature vectors for image description. Therefore, visual geometric group 19 (VGG19) with Jaccard is proposed in this research for CBIR. The VGG19 allows to capture of hierarchical features, and it is appropriate for texture and fine detail characteristics. It enables to production of robust and discriminative feature representations because of numerous convolutional layers. The Jaccard is utilized as a similarity measure among feature vectors by comparing the union and intersection of feature sets. It is helpful to manage sparse and higher-dimensional data that provides a fast and accurate image retrieval process. The Caltech 256 and Corel 1K datasets are considered and it is preprocessed by image resizing and normalization. The raw images are resized to ensure dataset similarity and normalized into the range of 0 and 1. The metrics such as recall, f-measure, and average precision are used to calculate the VGG19-Jaccard performance. The VGG19-Jaccard achieves average precision of 99.0 and 99.8% for Caltech 256 and Corel 1K datasets compared to the two-stage CBIR technique.
Volume: 14
Issue: 2
Page: 430-438
Publish at: 2025-06-01

A review of open-source energy system modeling tools

10.11591/ijaas.v14.i2.pp469-480
Nguyen Binh Khanh , Phuong Le Ngo , Luong Ngoc Giap , Truong Nguyen Tuong An , Trung Bui Tien , Tran The Vinh , Le Van Nghia , Tran Trong Dat
Nowadays, the transition to open markets, the rapid growth of renewable energy sources like wind and solar, and the shift towards electrification in transportation and industry for decarbonization have increased the demand for advanced energy system models with detailed spatial and temporal data. This paper utilizes a comprehensive literature review and selects a representative set of open-source tools for evaluation. A comparative analysis of 17 open-source energy system modeling tools and their commercial alternatives was conducted. The paper analyzes many open-source aspects such as code commits, updates, programming languages, license details, citations, and energy system modeling features such as power flows (PFs), continuation PF, dynamic analysis, short-circuit analysis, contingency analysis, transportation model, optimal PF (OPF), multi-period OPF, unit commitment (UC), investment optimization, and graphic user interface. Based on the results, the paper suggests appropriate tools used for according power/energy system analysis objective: MATPOWER for power system analysis and Python for power system analysis (PyPSA) for energy system analysis.
Volume: 14
Issue: 2
Page: 469-480
Publish at: 2025-06-01

Design of face recognition based effective automated smart attendance system

10.11591/ijeecs.v38.i3.pp2020-2030
Jyoti L. Bangare , Diptee Chikmurge , Karthikeyan Kaliyaperumal , Meenakshi Meenakshi , Sunil L. Bangare , Kishori Kasat , Kantilal Pitambar Rane , Ravi Kishore Veluri , Batyrkhan Omarov , Malik Jawarneh , Abhishek Raghuvanshi
The issue of automatic attendance marking has been successfully resolved in recent years through the utilization of standard biometric approaches. Although this strategy is automated and forward-thinking, its use is hindered by time constraints. Acquiring a thumb impression requires the individual to form a line, which might lead to inconvenience. The innovative visual system utilizes a computer and camera to detect and record students’ attendance based on their facial features. This article presents a face recognition based automatic attendance system. This system includes- image acquisition, image enhancement using histogram equalization, image segmentation by fuzzy C means clustering technique, building classification model using K-nearest neighbour (KNN), support vector machine (SVM) and AdaBoost technique. For experimental work, 500 images of students of a class are selected at random. Accuracy of KNN algorithm in proposed framework is 98.75%. It is higher than the accuracy of SVM (96.25%) and AdaBoost (86.50%). KNN is also performing better on parameters likesensitivity, specificity, precision and F_measure.
Volume: 38
Issue: 3
Page: 2020-2030
Publish at: 2025-06-01

A gamified online learning environment with comprehensive assessments and software integration

10.11591/ijaas.v14.i2.pp416-429
Swati Shilaskar , Shripad Bhatlawande , Rupali Deshpande , Shivam Shinde , Jyoti Madake , Anjali Solanke
The National Achievement Survey (NAS), conducted by the Ministry of Education, India, highlighted a concerning decline in mathematics proficiency among students in Maharashtra as they advance through grades. This trend is further aggravated by the limited availability of online resources in Marathi, hindering their learning progress. To address this, a pilot study was proposed to develop a specialized online platform tailored for Marathi medium students, integrating gamification and artificial intelligence (AI)-driven feedback to enhance engagement and comprehension. The pilot project, conducted at a Marathi medium school with approval from the principal, focused on polynomial division tests for 8th-grade students over four days. Results revealed that despite the easy level test's higher difficulty, students scored higher on the medium level test, possibly due to an adjustment period to the online platform. Notably, some students performed better on the hard-level test, indicating the platform's potential to improve performance. While promising, the study's limitations, including a small sample size, highlight the need for further research with a larger cohort and the integration of automatic suggestions for concept-specific games and assessments in future iterations to optimize the platform's effectiveness.
Volume: 14
Issue: 2
Page: 416-429
Publish at: 2025-06-01

Adaptive hybrid particle swarm optimization and fuzzy logic controller for a solar-wind hybrid power system

10.11591/ijape.v14.i2.pp498-512
G. B. Arjun Kumar , M. Balamurugan , K. N. Sunil Kumar , Ravi Gatti
This paper presents the best modeling and control strategies for a grid-connected hybrid wind-solar power system to maximize energy production. For variable wind speeds, determine the optimal power point using fuzzy logic control, adopt an adaptive hill climb searching method, and compare it with an optimal torque control method for large inertia wind turbine (WT). The role of fuzzy logic controller (FLC) is to adjust the hill climbing search (HCS) technique's step-size according to the operating point. The doubly-fed induction generator (DFIG) control system has two subsystems: rotor-side and grid-side converters. The active and reactive power have been indirectly regulated by adjusting the current on the d-q axis. The rotor side converter (RSC) controllers are responsible for controlling the WTs rotational speed to achieve the maximum power output. The grid side converter (GSC) manages the voltage at the DC link and keeps a unity power factor between the grid and GSC. Optimal hybrid power point tracking technique for use with photovoltaic systems in both constant and variable shade circumstances, based on particle swarm optimization (PSO) and perturb and observe (P&O). The optimal power point tracking (OPPT) approach is compared to three other methods: PSO, P&O, and hybrid P&O-PSO. The model has a total capacity of 2.249 MW, with wind capacity of 2 MW and solar capacity of 0.249 MW, and its efficiency is analyzed.
Volume: 14
Issue: 2
Page: 498-512
Publish at: 2025-06-01
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