Multidimensional Approach Research Articles

Enhancing Automatic Vehicle Number Plate Recognition Systems: A Multidimensional Approach to Improve Efficiency and Applicability

Real Time Number Plate Recognition System is an image processing technology which uses number (license) plate to identify the vehicle. The objective is to design an efficient automatic authorized vehicle identification system by using the vehicle number plate. No plate help for movement of traffic securely without any collision. They can reduce the number of accidents on roads like pedestrian accident and right-angle collision of two cars. Number plate recognition (NPR) can be used in various fields such as vehicle tracking, traffic monitoring, automatic payment of tolls on highways or bridges, surveillance systems, tolls collection points, and parking management systems. The developed system first detects the vehicle and then captures the vehicle image. Vehicle number plate region is localized using Neural Network(rcnn) then image segmentation is done on the image. Character recognition technique is used for the character extraction from the plate. The system is implemented and simulated in python, and its performance is tested on real image. Automatic vehicle detection and recognition is a key technique in most of traffic related applications and is an active research topic in the image processing domain. Different methods, techniques and algorithms have been developed for vehicle detection and recognitions but they are not very useful for parking system. In this project we aim to make an application which will help for society and mostly for corporation buldings in each state for doing their work very efficiently and in very small time. Live camera feeds are the primary input we give the system. On the main gate is a camera. When a car or bike passes in front of the camera, the camera reads the number plate number. Using an OCR algorithm, this vehicle can be determined to be authorized or not. If the car is not allowed in the premises the notification will be activated. authorized popup will be on if the vehicle is authorized

A STUDY ON THE IMPACT OF PAYROLL ON EMPLOYEE’S FINANCIAL WELLNESS IN CODEBOARD TECHNOLOGY PRIVATE LTD

This study explores how payroll deductions impact employee financial wellness at Code Board Technology. It assesses their influence on perceived income stability, financial stress, attitudes, and disposable income. The research adopts a multidimensional approach, evaluating savings behavior, debt management, budgeting skills, stress levels, and overall satisfaction. Various deduction types are examined, including taxes, insurance premiums, retirement contributions, and loan repayments. Data from 148 employees were analyzed using various statistical tests and tools. The findings shed light on challenges and perceptions related to deductions, suggesting implications for enhancing both employee financial wellness and organizational practices.

Toward Sustainable Urban Mobility: A Multidimensional Ontology-Based Framework for Assessment and Consensus Decision-Making Using DS-AHP

Urban mobility is a critical aspect of sustainable urban development, with significant environmental, social, and economic implications. Assessing the sustainability of urban mobility systems in order to create more carbon neutral, liveable, healthier, and sustainable cities and neighborhoods for the future requires a multidimensional approach that integrates diverse factors. However, the lack of a unified assessment framework poses challenges in comparing and evaluating different urban mobility projects. This article proposes an ontology for assessing the sustainability of urban mobility systems. This ontology is based on a multidimensional approach that integrates knowledge from experts in transportation engineering, urban planning, environmental science, and social sciences to incorporate existing sustainability indicators and frameworks, as well as domain-specific knowledge. A consensus approach based on Dempster–Shäfer (DS) and Analytic Hierarchy Process (AHP) methods is proposed to account for uncertainties and to allow for the consideration of preferences and ill judgment. Through a case study in Romania, the authors demonstrated the applicability of the proposal to provide a comprehensive and flexible framework for assessing urban mobility sustainability. The proposed ontology provides a valuable tool for policymakers, urban planners, and transportation engineers to make informed decisions towards sustainable urban mobility, and the sensitivity analysis is carried out to demonstrate the robustness of the proposed framework. It has potential for iterative validation and feedback from domain experts, and can serve as a foundation for future research.

Exploring the association between the Arabic version of the Traffic Locus of Control, driving behavior, and road traffic crashes: A multidimensional approach.

The Traffic Locus of Control scale (T-LOC) serves as a measure of drivers' personality attributes, providing insights into their perceptions of potential causes of road traffic crashes (RTCs). This study meticulously evaluated the psychometric properties of the Arabic version of T-LOC (T-LOC-A) among Lebanese drivers. Additionally, the study aimed to explore associations between the T-LOC scale and various driving variables, including driver behavior, accident involvement, and traffic offenses. A cross-sectional study was conducted among Lebanese drivers using a face-to-face approach. The validation of the Arabic version of T-LOC (T-LOC-A) occurred through a two-stage process: translating and culturally adapting T-LOC in the first stage, and testing its psychometric properties in the second stage. Data were collected using a comprehensive self-reported questionnaire in Arabic, covering demographic and travel-related variables, risk involvement, and measures such as the Driver Behavior Questionnaire (DBQ) and T-LOC. Exploratory factor analysis and confirmatory factor analysis were performed to scrutinize the factorial structure of T-LOC. Pearson correlation and chi-square tests were used for continuous and categorical variables, respectively. Two logistic regression analyses were executed to probe associations between T-LOC and involvement in road traffic crashes (RTCs) and T-LOC subscales with the occurrence of traffic offenses. The study included 568 drivers, predominantly male (69%) and aged between 30 and 49 years (42.1%). The findings revealed that T-LOC-A exhibited robust psychometric properties, with excellent reliabilities (α = 0.85) and adherence to the original four-factor structure, encompassing self (α = 0.88), other drivers (α = 0.91), vehicle/environment (α = 0.86), and fate (α = 0.66). The multidimensional structure was statistically supported by favorable fit indices. Gender differences revealed men attributing responsibility to other drivers, while women leaned towards fate and luck beliefs. Regarding driver behavior, the "other drivers" and self-dimensions of T-LOC-A correlated positively with aggressive violations. The fate dimension showed positive associations with aggressive violations and lapses. The "other drivers" subscale correlated positively with errors, and the vehicle/environment subscale with lapses. External T-LOC factors were positively associated with accident involvement, while the "LOC self" factor emerged as a protective element. In terms of traffic offenses, "LOC fate" displayed a positive association, while the "LOC self" factor showed a protective effect. In conclusion, the Arabic T-LOC is a reliable and valuable instrument, suggesting potential improvements in driving safety by addressing drivers' locus of control perceptions.

Population, carbon dioxide emissions and renewable energy consumption nexus: New insights from Vietnam

This academic paper investigates the intricate relationships among population dynamics, carbon dioxide (CO2) emissions and renewable energy consumption in Vietnam. The study used the Autoregressive Distributed Lag approach and fixed panel data method to examine the nexus between population, CO2 emissions and renewable energy consumption in Vietnam. The data is collected at the World Bank from 2000 to 2023. As the nation undergoes rapid economic development and urbanization, understanding the nexus between population growth, environmental impact and the transition to renewable energy sources becomes crucial. The study employs a multidimensional analytical approach that integrates demographic trends, environmental science and energy economics to unveil novel evidence into the complex interplay of these factors. The significant findings indicate a positive trajectory in renewable energy consumption, with notable contributions from solar, wind and hydropower sources. Concurrently, population growth, particularly in urban centres, correlates with increased CO2 emissions, emphasizing the role of demographic shifts in environmental impact. Policy implications derived from these results underscore the need for integrated strategies. Targeted policies promoting renewable energy in urban centres, incentivizing cleaner industrial practices and fostering community engagement emerge as crucial avenues for sustainable development. In essence, this study contributes valuable insights into the dynamic relationships among population dynamics, CO2 emissions and renewable energy consumption in Vietnam, offering a foundation for evidence-based policymaking and guiding future research endeavours in sustainable development.

University Libraries in Türkiye: Past to Present - A Comprehensive Analysis

University libraries play a vital role in the academic landscape by providing a wide range of essential support and services to their members. From research materials and academic resources to access to cutting-edge technology and expert staff, these libraries are at the forefront of fostering a culture of learning, collaboration, and innovation both within their physical spaces and online. Their importance extends beyond the academic environment, as they are also expected to contribute to the development of their respective countries by providing the resources and tools necessary to support a strong and thriving knowledge economy. The objective of this research is to provide a detailed analysis of the situation and challenges experienced by university libraries in Türkiye. This study utilized descriptive and documentary scanning methods to analyze and interpret data obtained from a wide range of both domestic and foreign literature, as well as official primary documents and media. The scope of the study was determined by historical, managerial, legal, and technological problems faced by Türkiye’s university libraries. To ensure systematic integrity, the study grouped various dimensions thought to have a direct or indirect impact on university libraries in Türkiye under different headings. These headings, which constitute the scope of the study, include: “Legislation, organization, and administrative structure”; “Policy, regulations, and standards”; “Budget, building, collection management, human resources, user-related matters, and other relevant issues”; “Collaborations”, and “Information and communication technologies”. By taking into account the historical context, this study aims to offer a comprehensive understanding of the issues that these libraries have faced and continue to face in the present day. The findings of this research indicate that the challenges encountered by university libraries in the past have yet to be effectively addressed and resolved. The study’s methodical, multifaceted, and multidimensional approach to evaluating university libraries, both in the historical context and current situation, presents a unique perspective. The comprehensive and in-depth evaluation process applied in this study is unparalleled and distinguishes it from prior studies in the field. This approach provides a holistic view of university libraries, allowing for a more detailed and accurate assessment of their overall performance.

Community-based education and child development work for migrant children in China: a multi-dimensional citizenship approach

The primary focus of this article is to investigate the impact of community-based efforts to provide education and child development programs and service in China’s migrant communities, specifically as it pertains to the prospects of addressing sociocultural and socioeconomic inequalities in education and child development in urban China. Building on frameworks of dimensions of citizenship, this article examines the work of migrant educator-activists who provide community-based education and child development service in Beijing’s migrant communities. Their efforts to address inequalities in child development for migrant children enrich the understanding of citizenship in the Chinese context.

Transformations of the Russian Labor Market: First and Second Waves

The research significance is determined because over the past three years the Russian labor market has gone through two waves of transformations. The COVID-19 epidemic caused the first wave of transformations, which continued until the end of 2021. The second one, caused by introducing sanctions against Russia, began in February 2022 and continued to this day. The subject of the study is the functioning parameters of the Russian labor market and the major new trends in its development. The paper aims to identify problem areas in the labor market and analyze measures for its development. It also examines the reform of the public employment service and improvement of labor legislation. Information sources: Russian and foreign scientific publications, specialized studies, as well as official open data from the state bodies. The scientific novelty of the study lies in the multidimensional approach to the analysis of the Russian labor market transformation in two waves, trends and for its outlooks growth.

A multifaceted approach to identifying and managing juvenile delinquency by integrating psycho-physiological indicators.

To understand and treat juvenile delinquency, the study explores the relevance of psycho-physiological indicators. It also emphasizes the necessity for thorough research to minimize the gap existing between psycho-physiological measurements and conventional psychosocial components. The study focuses on the relevance of personality features, habituation, and autonomic arousal required to monitor the proper management of delinquent conduct. Through the integration of biological, psychological, and social elements into a multidimensional approach, researchers can uncover novel insights and create cutting-edge therapies for youths who are at risk of delinquent behavior. The study proposes to develop a comprehensive framework that considers biological antecedents in addition to conventional metrics to reach the root cause of delinquency; thereby drawing special attention to current literature and research that emphasizes the psycho-physiological correlates of delinquency. By examining the complex interactions between stress, physiology, emotions, behavior, and social structures, the study highlights the intricacy of delinquent conduct and the necessity for adopting a multifaceted strategy to fully address the problematic areas. Future research paths are emphasized, with a focus on the significance of longitudinal studies, moderating and mediating variables, and creative treatment techniques. By utilizing psycho-physiological markers and psychosocial traits, researchers can tailor intervention strategies to meet individual needs effectively. Early identification of psycho-physiological deficits in children is crucial for implementing successful behavior modification techniques and promoting the well-being of future generations. This is expected to help the government agencies to save time and public money.

Exploring Resilience Among Midlife and Older Sexual Minority and Heterosexual Adults: A Multidimensional Analysis.

Research on resilience in sexual minority midlife and older adults is limited. Using a multidimensional approach, this study examined trait resilience (optimism), resilience as a dynamic process (perceived control), and relational resilience (social support), analyzing their roles in physical and mental health among sexual minority adults. Analyzing data from MIDUS 2 and MIDUS Refresher, we examined a sample of 492 participants, comprising 164 sexual minority and 328 propensity-matched heterosexual individuals. Among sexual minority participants, perceived control was associated with fewer chronic conditions and optimism with lower depressed affect. Among heterosexual participants, perceived control was associated with both outcomes. Subgroup analyses found variations, particularly among lesbian and bisexual women. Resilience measures were not associated with the health outcomes for gay or bisexual men. This study highlighted the complex roles of trait resilience and dynamic resilience processes in association with health outcomes among sexual minority midlife and older adults across diverse subgroups.

How consumers evaluate costs in complex services: the case of mutual fund fees

PurposeIn modern societies, consumer well-being is dependent on choices regarding complex services, such as investments, health care, insurance and lending. However, evaluating costs of such services is often difficult for consumers due to a combination of limited cognitive resources and complexity of the service. The purpose of this study is to empirically examine to what extent three specific consequences of complexity influence consumer tendencies to make mistakes when evaluating the costs (or price) of complex services.Design/methodology/approachThree studies were conducted (survey: n = 153, experiment: n = 332 and conjoint analysis: n = 225), all focusing on how consumers evaluate costs in the complex mutual fund setting.FindingsThe authors find that consumers struggle with estimating and using cost information in decision-making in the complex services setting. Consumers of complex services frequently underestimate the costs over the long-term, may see costs as a signal of service quality and are susceptible to influence from presentation formats when evaluating costs.Research limitations/implicationsThe study investigates mutual funds, which is one example of a complex service. In order to get a full picture of how consumers deal with costs in complex setting, future research needs to expand this focus to other types of complex services.Practical implicationsThe results have implications for both marketers of complex services and policymakers. For marketers, this paper highlights that competing with a low-cost strategy may be difficult in the complex services setting as consumers may lack the ability to actually evaluate what they pay over the long term. For policymakers, increased simplification of prices may be an attractive option. However, it is important that this simplification is done in a way that increases the possibility to compare prices.Originality/valueAs complexity influences several aspects of decision-making, an understanding of how consumers evaluate costs in complex settings is dependent on taking a multidimensional research approach. This paper makes a novel contribution to the literature on pricing by showing that consumers struggle with multiple aspects when evaluating costs in complex contexts. Understanding these effects is important to policy, as well as to research on the cognitive value of simplicity that is currently gaining traction in marketing research.

Does social protection reach those left behind: empirical evidence from Botswana using multidimensional poverty approaches

ABSTRACT Social protection policies are important for advancing the United Nations 2030 Agenda for Sustainable Development, especially the call to leave no one behind. We employ multidimensional poverty measures to identify those left behind. Using data from the 2015/16 Botswana Multi-Topic Household Survey, this study compares the targeting performance of selected social assistance programmes according to: (a) the specific programme eligibility criteria; (b) the monetary poverty measure; and (c) the multidimensional poverty index. The overall results reveal high inclusion and exclusion error rates among most programmes, indicating that they perform poorly in reaching their intended beneficiaries. The results also reveal high under-coverage rates irrespective of the poverty measure used. However, when the programmes are ranked according to leakage rates, the results differ across the two poverty measures. Relying on the monetary poverty measure alone may send inadequate information to policymakers tasked with reforming Botswana’s national social protection policy.

Spatial Multi-Omics in Alzheimer’s Disease: A Multi-Dimensional Approach to Understanding Pathology and Progression

Alzheimer’s Disease (AD) presents a complex neuropathological landscape characterized by hallmark amyloid plaques and neurofibrillary tangles, leading to progressive cognitive decline. Despite extensive research, the molecular intricacies contributing to AD pathogenesis are inadequately understood. While single-cell omics technology holds great promise for application in AD, particularly in deciphering the understanding of different cell types and analyzing rare cell types and transcriptomic expression changes, it is unable to provide spatial distribution information, which is crucial for understanding the pathological processes of AD. In contrast, spatial multi-omics research emerges as a promising and comprehensive approach to analyzing tissue cells, potentially better suited for addressing these issues in AD. This article focuses on the latest advancements in spatial multi-omics technology and compares various techniques. Additionally, we provide an overview of current spatial omics-based research results in AD. These technologies play a crucial role in facilitating new discoveries and advancing translational AD research in the future. Despite challenges such as balancing resolution, increasing throughput, and data analysis, the application of spatial multi-omics holds immense potential in revolutionizing our understanding of human disease processes and identifying new biomarkers and therapeutic targets, thereby potentially contributing to the advancement of AD research.

Multidimensional Cross-Country Measurement of Climate Change Perceptions

ABSTRACT Understanding public perceptions of climate change is crucial for more targeted communication and better-informed policymaking. Moreover, the perceptions of climate change encompass different aspects and thus need to be defined and measured using a multidimensional approach. In this paper, we introduce the Climate Perceptions Index (CPI), a composite measure that comprehensively assesses the public perceptions of climate change, based on a sample of over 100 thousand active Facebook users across 107 countries. We construct the CPI as an aggregate of three distinct dimensions that quantify the awareness of climate change, risk perception, and commitment to action. The results show that the extent of climate change perceptions varies significantly across countries and across dimensions. Countries with the highest and lowest scores globally can be found in almost all regions, and across all levels of socio-economic development. Furthermore, we analyze the relationships between the CPI dimensions and find that the influence of risk perception on commitment to action is the strongest at the lowest levels of climate change awareness. This highlights the possibility of climate change risk normalization at higher levels of awareness, and further shows that effective policies and strategies must not only focus on raising knowledge about climate change, but also overcome the normalization of its threats.

Networkwide Traffic State Forecasting Using Exogenous Information: A Multi-Dimensional Graph Attention-Based Approach

Traffic-state forecasting is crucial for traffic management and control strategies, as well as user- and system-level decision-making in the transportation network. While traffic forecasting has been approached with a variety of techniques over the last couple of decades, most approaches simply rely on endogenous traffic variables for state prediction, despite the evidence that exogenous factors can significantly affect traffic conditions. This paper proposes a multidimensional spatiotemporal graph attention-based traffic-prediction approach (M-STGAT), which predicts traffic based on past observations of speed, along with lane-closure events, temperature, and visibility across a large transportation network. The approach is based on a graph attention network architecture, which learns based on the structure of the transportation network on which these variables are observed. Numerical experiments are performed using traffic-speed and lane-closure data from the Caltrans Performance Measurement System (PeMS) and corresponding weather data from the National Oceanic and Atmospheric Administration (NOOA) Automated Surface Observing Systems (ASOS). The numerical experiments implement three alternative models which do not allow for multidimensional input, along with two alternative multidimensional models, based on the literature. The M-STGAT outperforms the five alternative models in validation and testing with the primary data set, as well as for one transfer data set across all three prediction horizons for all error measures. However, the model’s transferability varies for the remaining two transfer data sets, which may require further investigation. The results demonstrate that M-STGAT has the most consistently low error values across all transfer data sets and prediction horizons.

Multidimensional Approach to Combating the Shadow Economy: Theory and Practice

This article presents a detailed analysis of multi-level strategies to combat the shadow economy on the example of Uzbekistan. The study delves into the theoretical aspects of the problem, identifying the factors contributing to the shadow sector, and discusses the need for integrated co-operation between government structures, business and society. The article offers practical recommendations, including improving the legislative framework and strengthening the law enforcement system. The authors draw attention to successful cases of implementing technological tools aimed at increasing the transparency of financial flows. The article also covers socio-cultural measures, including educational initiatives aimed at fostering intolerant attitudes towards the shadow economy. Based on data on the dynamics of Uzbekistan's economy, it is emphasized that a multidimensional approach can effectively reduce the shadow economy and promote sustainable economic growth.

Multidimensional Approach to Exploring Neighborhood Determinants and Symptom Severity Among Individuals With Psychosis

ImportanceThe impact of cumulative exposure to neighborhood factors on psychosis, depression, and anxiety symptom severity prior to specialized services for psychosis is unknown.ObjectiveTo identify latent neighborhood profiles based on unique combinations of social, economic, and environmental factors, and validate profiles by examining differences in symptom severity among individuals with first episode psychosis (FEP).Design, Setting, and ParticipantsThis cohort study used neighborhood demographic data and health outcome data for US individuals with FEP receiving services between January 2017 and August 2022. Eligible participants were between ages 14 and 40 years and enrolled in a state-level coordinated specialty care network. A 2-step approach was used to characterize neighborhood profiles using census-tract data and link profiles to mental health outcomes. Data were analyzed March 2023 through October 2023.ExposuresEconomic and social determinants of health; housing conditions; land use; urbanization; walkability; access to transportation, outdoor space, groceries, and health care; health outcomes; and environmental exposure.Main Outcomes and MeasuresOutcomes were Community Assessment of Psychic Experiences 15-item, Patient Health Questionnaire 9-item, and Generalized Anxiety Disorder 7-item scale.ResultsThe total sample included 225 individuals aged 14 to 36 years (mean [SD] age, 20.7 [4.0] years; 152 men [69.1%]; 9 American Indian or Alaska Native [4.2%], 13 Asian or Pacific Islander [6.0%], 19 Black [8.9%], 118 White [55.1%]; 55 Hispanic ethnicity [26.2%]). Of the 3 distinct profiles identified, nearly half of participants (112 residents [49.8%]) lived in urban high-risk neighborhoods, 56 (24.9%) in urban low-risk neighborhoods, and 57 (25.3%) in rural neighborhoods. After controlling for individual characteristics, compared with individuals residing in rural neighborhoods, individuals residing in urban high-risk (mean estimate [SE], 0.17 [0.07]; P = .01) and urban low-risk neighborhoods (mean estimate [SE], 0.25 [0.12]; P = .04) presented with more severe psychotic symptoms. Individuals in urban high-risk neighborhoods reported more severe depression (mean estimate [SE], 1.97 [0.79]; P = .01) and anxiety (mean estimate [SE], 1.12 [0.53]; P = .04) than those in rural neighborhoods.Conclusions and RelevanceThis study found that in a cohort of individuals with FEP, baseline psychosis, depression, and anxiety symptom severity differed by distinct multidimensional neighborhood profiles that were associated with where individuals reside. Exploring the cumulative effect of neighborhood factors improves our understanding of social, economic, and environmental impacts on symptoms and psychosis risk which could potentially impact treatment outcomes.

Incorporating Fine-Grained Linguistic Features and Explainable AI into Multi-Dimensional Automated Writing Assessment

With the flourishing development of corpus linguistics and technological revolutions in the AI-powered age, automated essay scoring (AES) models have been intensively developed. However, the intricate relationship between linguistic features and different constructs of writing quality has yet to be thoroughly investigated. The present study harnessed computational analytic tools and Principal Component Analysis (PCA) to distill and refine linguistic indicators for model construction. Findings revealed that both micro-features and their combination with aggregated features robustly described writing quality over aggregated features alone. Linear and non-linear models were thus developed to explore the associations between linguistic features and different constructs of writing quality. The non-linear AES model with Random Forest Regression demonstrated superior performance over other benchmark models. Furthermore, SHapley Additive exPlanations (SHAP) was employed to pinpoint the most powerful linguistic features for each rating trait, enhancing the model’s transparency through explainable AI (XAI). These insights hold the potential to substantially facilitate the advancement of multi-dimensional approaches toward writing assessment and instruction.

Dual career through the eyes of university student-athletes in the Republic of Kosovo.

The successful combination of a sports career and education, known as the dual career, requires cooperation and a multi-dimensional approach. Although extensive research has been conducted on dual career programs and services in developed countries, there is limited information available on the dual-career phenomenon in developing countries. This study aimed to explore the dual career experiences of university student-athletes in the Republic of Kosovo. A 30-item online survey was distributed to student-athletes, addressing various aspects of the dual career. A total of 121 student-athletes (males: 63.6%; females: 36.4%) voluntarily participated in the survey. These student-athletes represented 13 different sports, with 102 (84.3%) participating in team and 19 (15.7%) in individual sports. Between individual and team sports no significant differences were found regarding university and sports engagement, and the time required to travel from the university to the training venue, whereas a significant difference (p = 0.019) emerged for the time needed to travel from home to the training venue. Significant differences (p < 0.05) were found between university majors in terms of sports engagement. The present findings highlight a lack of familiarity with dual career programs among student-athletes (89.3%) and the need for dual-career policies at the university (16.5%), sport (9.9%), and national (13.2%) levels. Student-athletes faced various challenges, mainly related to limited leisure time (62.8%), academic overload (60.3%), frequent absence from classes (59.6%), and financial uncertainty (35.5%). Recommended improvements included increased financial support (66.1%), the availability of sports facilities at or near the university (48.8%), greater educational flexibility (26.4%), tutoring services at the university (25.6%), and sports clubs (19%) levels, as well as improved communication regarding existing initiatives and legal aspects (53.7% and 47.1%, respectively). The study also identified parents (98.3%), coaches (86%), and siblings (60.3%) as important sources of support for student-athletes at personal, sports, and university levels. In conclusion, to enhance the potential of future student-athletes in the Republic of Kosovo, relevant stakeholders in sports and higher education should collaborate closely and implement programs and services based on international best practices for dual-career support.

Development of a market-driven training model for rural women in Iran by using a qualitative paradigm.

Training programs aimed at empowering rural women in Kurdistan, Iran, have fallen short of their goals. This study offers a unique understanding of how contextual factors and cultural nuances impact the effectiveness of market-driven training programs for rural women in Kurdistan. This study explored factors affecting the effectiveness of market-driven training programs for rural women in Kurdistan. A qualitative approach using grounded theory methodology was employed. Interviews were conducted with 23 key informants, including rural women and experts. Data analysis with MAXQDA software identified seven categories and a core category related to market-driven training. The study revealed that successful implementation of market-driven training hinges on various external and internal factors. These include access to markets, facilities, and funding, along with effective monitoring of business activities. Additionally, rural community culture and the purchasing power of women were identified as key intervening conditions impacting program success. When implemented effectively, market-driven training programs have the potential to empower women, reduce rural migration, and improve product quality. The research suggests that future training programs should adopt a multi-dimensional approach that addresses the identified factors to achieve sustainable positive outcomes for rural women in Kurdistan.