درخت حوزه‌های تخصصی

The success of economic programs, with the company's strategy, is an integrated and coordinated set of interventions and programs that are used to exploit core competencies and gain competitive advantage. So people in an organization are important assets that are able to convert from visible assets into optimal productive resources to meet the needs of the organization. Therefore, this article attempts to propose the interaction of two priority and effective categories on the performance of the organization, namely strategic management of human resources and supply chain management, by setting strategic priorities and indicators of interest in them by providing a syntactic scientific model and framework. Based on this, with the help of hypercompilation, he analyzed the variables of reliability, flexibility, social contexts, skill contexts, emotional conditions, level of maturity and individual maturity in the form of a conceptual model, which analyzed the hypotheses extracted from it showed that the issues examined in the field of strategic human resource managementhave a meaningful relationship with the strategic bias of the supply chain in economics and finance. The most important strategies for conveying a sense of commitment to continuous interaction between the supplier and the successful human resources and creating an independent personality for the set of efficient suppliers were counted by human resources

This study aims to explore the experiences and benefits of inclusive sports programs for students with disabilities, focusing on their physical, social, emotional, and educational development. The objective is to understand how these programs impact participants and identify key themes that illustrate their benefits and challenges. A qualitative research design was employed, utilizing semi-structured interviews to gather data from a diverse group of participants. The sample included 29 individuals: 15 students with disabilities, 6 teachers and coaches, and 8 parents of students with disabilities. Interviews were conducted in person or via video conferencing, recorded, and transcribed for thematic analysis. The data were coded and analyzed to identify recurring themes and patterns, with theoretical saturation guiding the final sample size. The analysis revealed four main themes: physical benefits, social benefits, emotional and psychological benefits, and educational and developmental benefits. Participants reported significant improvements in physical fitness, skill development, and health. Social benefits included enhanced social integration, communication skills, and a sense of belonging. Emotional and psychological benefits encompassed increased emotional well-being, psychological resilience, and reduced anxiety. Educational benefits included better academic performance, life skills, and career skills development. These findings align with previous studies highlighting the multifaceted benefits of inclusive sports programs. Inclusive sports programs significantly enhance the physical, social, emotional, and educational well-being of students with disabilities. The study underscores the importance of designing inclusive programs that accommodate diverse needs, providing adequate training for educators and coaches, and fostering a supportive environment. Future research should aim to include larger and more diverse samples, incorporate quantitative measures, and explore the long-term impacts of these programs to further refine and maximize their benefits.

Several research investigations have indicated that asset returns exhibit notable skewness and kurtosis, which have a substantial impact on the utility function of investors. Additionally, it has been observed that Average Value-at-Risk (AVaR) provides a more accurate estimation of risk compared to variance. This study focuses on the computational challenge associated with portfolio optimization in an uncertain context, employing the Mean-AVaR-skewness-kurtosis paradigm.The uncertainty around the total return is con-sidered and analyzed in the context of the challenge of selecting an optimal portfolio. The concepts of Value-at-Risk (VaR), Average Value-at-Risk (AVaR), skewness, and kurtosis are initially introduced to describe uncertain variables. These concepts are then further explored to identify and analyse relevant aspects within specific distributions. The outcomes of this study will convert the existing models into deterministic forms and uncertain mean-AVaR-skewness-kurtosis optimization models for portfolio selection. These models are designed to cater to the demands of investors and mitigate their apprehensions.

The widespread adoption of Android phones has heightened concerns about user privacy. This research presents an Adaptive Privacy Management System (APMS) that integrates Machine Learning (ML) models with Differential Privacy techniques to enhance privacy protection. The APMS monitors application behavior and employs ML algorithms to detect anomalies and enable context-aware privacy enforcement. Differential Privacy ensures that sensitive data remains protected through the addition of noise and privacy-preserving computations. Experimental results demonstrate that the APMS achieves a 92.5% accuracy rate in detecting the privacy leakage. The anomaly detection model, using Random Forest, shows high accuracy (92.5%), recall (89.5%), and precision (73.9%), effectively identifying both normal and anomalous behaviors. Additionally, the impact of noise on data utility, controlled by the privacy budget (ε), is manageable. The results show that APMS is a robust system for safeguarding user confidential information, contributing to a more secure and privacy-centric Android ecosystem.