
Asia Pacific Academy of Science Pte. Ltd. (APACSCI) specializes in international journal publishing. APACSCI adopts the open access publishing model and provides an important communication bridge for academic groups whose interest fields include engineering, technology, medicine, computer, mathematics, agriculture and forestry, and environment.

As China's pillar industry, the property market has suffered a considerable impact in recent years, with a decline in turnover and many developers at risk of bankruptcy. As one of the most concerned factors for stakeholders, housing prices need to be predicted more objectively and accurately to minimize decision-making errors by developers and consumers. Many prediction models in recent years have been unfriendly to consumers due to technical difficulties, high data demand, and varying factors affecting house prices in different regions. A uniform model across the country cannot capture local differences accurately, so this study compares and analyses the fitting effects of multiple machine learning models using February 2024 new building data in Changsha as an example, aiming to provide consumers with a simple and practical reference for prediction methods. The modeling exploration applies several regression techniques based on machine learning algorithms, such as Stepwise regression, Robust regression, Lasso regression, Ridge regression, Ordinary Least Squares (OLS) regression, Extreme Gradient Boosted regression (XGBoost), and Random Forest (RF) regression. These algorithms are used to construct forecasting models, and the best-performing model is selected by conducting a comparative analysis of the forecasting errors obtained between these models. The research found that machine learning is a practical approach to property price prediction, with least squares regression and Lasso regression providing relatively more convincing results.
Ethno-education: Health education based on cultural diversity cultural diversity
Vol 5, Issue 1, 2024
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Abstract
Introduction: In a multicultural country such as Colombia, ethnoeducation is an important component of health education, because it promotes the quality of life of ethnic minorities based on the community’s potential, practices, habits, experiences and approaches that promote overall health awareness. The purpose of this article is to perform a narrative review on the background of ethnoeducation and its impact on health. The development of inter-cultural skills among students in health fields would enable the future professional to perform their roles with adequate cultural relevance, respecting the values, traditions and history of the communities. Topics discussed: Worldwide, ethnoeducation has been highly relevant, and some international organizations have worked on its implementation for decades. In Colombia, several legal and regulatory instruments have been developed to implement ethnoeducation. However, close to 86% of the ethnic populations do not have access to education in accordance with the established principles. The importance of ethnoeducation has been highlighted in several countries in that it has achieved positive results such as a reduction of morbidity and mortality through educational activities that promote health and help prevent diseases. To achieve this, it is essential that the planned activities be integrated into the communities’ cultural perceptions. Conclusion: Although local, national and international guidelines have been established, ethnoeducation continues to be a challenge. It is necessary to increase efforts in order for ethnoeducation to achieve the objectives that have been set out from a theoretical perspective.
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Copyright (c) 2024 Hernández-Martínez Alejandro, Cuartas-Agudelo Yuban Sebastián, Herrera-Almanza Laura, Roldan-Tabares Mabel Dahiana, Martínez-Sánchez Lina María

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Prof. Mehmet Cetin
Kastamonu University,
Turkey