title: Machine learning-based prediction of young’s modulus in Ti-Alloys

authors: Dinibutun, Seza

abstract: This study explores the use of machine learning to predict the experimental Young’s modulus of titanium alloys based on their mechanical and microstructural properties. Several regression models were developed and compared, including Random Forest, XGBoost, CatBoost, Multi-Layer Perceptron, and a Stacking Regressor. Among these, Random Forest, XGBoost and CatBoost achieved the most accurate results with R<sup>2</sup> values above 0.85. To improve interpretability, SHapley Additive exPlanations were applied to examine which input features most strongly influenced the predictions. The results showed that yield strength, hardness, and the molybdenum equivalent parameter (moe) were among the most influential descriptors. While yield strength and hardness were positively associated with the predicted values, higher moe values corresponded to lower predicted Young’s modulus. This study focuses on the prediction of Young’s modulus, a comparatively less explored elastic property in Ti-alloy machine learning studies and combines systematic model comparison with SHAP-based interpretability to provide physically consistent insights into feature–property relationships.

text: Machine learning-based prediction of young’s modulus in Ti-Alloys This study explores the use of machine learning to predict the experimental Young’s modulus of titanium alloys based on their mechanical and microstructural properties. Several regression models were developed and compared, including Random Forest, XGBoost, CatBoost, Multi-Layer Perceptron, and a Stacking Regressor. Among these, Random Forest, XGBoost and CatBoost achieved the most accurate results with R<sup>2</sup> values above 0.85. To improve interpretability, SHapley Additive exPlanations were applied to examine which input features most strongly influenced the predictions. The results showed that yield strength, hardness, and the molybdenum equivalent parameter (moe) were among the most influential descriptors. While yield strength and hardness were positively associated with the predicted values, higher moe values corresponded to lower predicted Young’s modulus. This study focuses on the prediction of Young’s modulus, a comparatively less explored elastic property in Ti-alloy machine learning studies and combines systematic model comparison with SHAP-based interpretability to provide physically consistent insights into feature–property relationships.

year: 2026-02-19

title: New Zealand outdoor recreation benefits

authors: Kaval, Pamela

subjects: non-market valuation

abstract: Millions of people participate in outdoor recreation activities in New Zealand every year. Economic recreation studies in the country concentrate mostly on market values. Market values only present part of the outdoor recreation benefit; while non-market values represent the other part. In this study, a meta-analysis is used to determine the non-market benefit of recreation. Results show non-market benefits from outdoor recreation to be over five billion dollars annually, exceeding market benefits of approximately four billion. New Zealand non-market values were then compared to those from a United States recreation database and results were favourably similar.

text: New Zealand outdoor recreation benefits Millions of people participate in outdoor recreation activities in New Zealand every year. Economic recreation studies in the country concentrate mostly on market values. Market values only present part of the outdoor recreation benefit; while non-market values represent the other part. In this study, a meta-analysis is used to determine the non-market benefit of recreation. Results show non-market benefits from outdoor recreation to be over five billion dollars annually, exceeding market benefits of approximately four billion. New Zealand non-market values were then compared to those from a United States recreation database and results were favourably similar.

year: 2007-08

title: Nga Wahi Ipurangi - Digital Places

authors: Reilly, Alan Howard

subjects: mLearning

abstract: The Waipa district, unbeknown to many New Zealanders, is home to some of the country’s most significant historical sites and stories.  As a Learning Experiences Outside the Classroom (LEOTC) educator, one of my roles is facilitating the understanding of these places and stories with school students.  
Currently, historical sites of national significance in this area are geographically hard to recognise, and have little or no physical interpretation. The ability of students to learn at these sites relies heavily on the educator’s oratory abilities.  Recent development in mobile technology can now provide access to interpretive internet-based content anytime, anywhere and this research investigates potential for mobile technology to be used as a tool to provide meaningful learning experiences that connect students to our unique history in the environment that these events actually took place in.
This research compares different mobile learning methods’ effectiveness in increasing student understanding and retention of social history content. A mobile learning (mLearning) programme was created for the purpose of this research, with the internet-hosted content divided equally between 3 mobile learning methods and one presenter-based method. 
Three groups consisting of Yr 5-6, Yr 7-8 and Yr 9-10 school students participated in the programme. Students completed multi-choice tests before, immediately after and 4 months following the trial programme. The multi choice results were used to compare improvement in student understanding and retention. Focus group interviews were conducted immediately and 4 months after the trial and were used to explore students metacognitive reflections of the learning methods used. 
The results of the study suggest that the mobile audio method was the most effective at increasing student understanding of the learning content and also had the highest level of content retention.  Results also suggest that environmental and technological distraction may have negatively influenced the effectiveness of the two visual mobile learning methods. Distraction may account for the differences between the learning methods effectiveness suggested by the multi-choice testing. Focus group interviews indicate the importance of mobile learning in an authentic context.
Discussion around the reduction, and where possible, elimination of the identified distractions; appropriateness and feasibility of new programme development including: game/trail based mLearning; the importance of authentic contexts for Māori students; student involvement in design; student-centred methods; connection to the classroom; and the relevance of social media are explored.
This research provides a clear direction for future programme development, aligning with the Ministry of Education’s LEOTC review priorities that emphasise raising student achievement for priority students; improving student engagement; and innovative, future focused learning.

text: Nga Wahi Ipurangi - Digital Places The Waipa district, unbeknown to many New Zealanders, is home to some of the country’s most significant historical sites and stories.  As a Learning Experiences Outside the Classroom (LEOTC) educator, one of my roles is facilitating the understanding of these places and stories with school students.  
Currently, historical sites of national significance in this area are geographically hard to recognise, and have little or no physical interpretation. The ability of students to learn at these sites relies heavily on the educator’s oratory abilities.  Recent development in mobile technology can now provide access to interpretive internet-based content anytime, anywhere and this research investigates potential for mobile technology to be used as a tool to provide meaningful learning experiences that connect students to our unique history in the environment that these events actually took place in.
This research compares different mobile learning methods’ effectiveness in increasing student understanding and retention of social history content. A mobile learning (mLearning) programme was created for the purpose of this research, with the internet-hosted content divided equally between 3 mobile learning methods and one presenter-based method. 
Three groups consisting of Yr 5-6, Yr 7-8 and Yr 9-10 school students participated in the programme. Students completed multi-choice tests before, immediately after and 4 months following the trial programme. The multi choice results were used to compare improvement in student understanding and retention. Focus group interviews were conducted immediately and 4 months after the trial and were used to explore students metacognitive reflections of the learning methods used. 
The results of the study suggest that the mobile audio method was the most effective at increasing student understanding of the learning content and also had the highest level of content retention.  Results also suggest that environmental and technological distraction may have negatively influenced the effectiveness of the two visual mobile learning methods. Distraction may account for the differences between the learning methods effectiveness suggested by the multi-choice testing. Focus group interviews indicate the importance of mobile learning in an authentic context.
Discussion around the reduction, and where possible, elimination of the identified distractions; appropriateness and feasibility of new programme development including: game/trail based mLearning; the importance of authentic contexts for Māori students; student involvement in design; student-centred methods; connection to the classroom; and the relevance of social media are explored.
This research provides a clear direction for future programme development, aligning with the Ministry of Education’s LEOTC review priorities that emphasise raising student achievement for priority students; improving student engagement; and innovative, future focused learning.

year: 2013