15 10 760 https://linen-dog.lnx.warwick.ac.uk/files/original/4fae51d43394e8a1a7a00a06a4b49266.pdf 4932c57732c2ddd9dc4af90c9cc50262 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Social Sciences Subject The topic of the resource Social Sciences Academic Poster An academic poster Abstract The abstract of the paper This research focuses on four economies: Mauritius, the United Kingdom (UK), the United Arab Emirates (UAE) and China. With their distinct economic model, these four strategically chosen countries encompass four distinct perspectives to tackle climate change. This research thus aims to highlight the importance of tailoring environmental policies according to the different countries’ context. It will investigate the conditions that have induced the implementation of such policies and provide context-based ideas for policymakers to leverage these policy benefits for a more sustainable economy. Meta Tags Meta tags Economics, Environment, Sustainability, Climate Change, Comparative Analysis, Policies Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Stephanie LEE YOU VOON Contributor An entity responsible for making contributions to the resource Dr. Samuel Obeng Subject The topic of the resource Philosophy, Politics and Economics Title A name given to the resource Comparative Analysis of Environmental Policies in Four Countries’ Contexts Date A point or period of time associated with an event in the lifecycle of the resource 2025 https://linen-dog.lnx.warwick.ac.uk/files/original/b105b61404833d2ea581709a5c582691.pdf d3add854f69f767fa95f49287db4723f Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Social Sciences Subject The topic of the resource Social Sciences Academic Paper An academic paper Abstract The abstract of the paper For portfolio managers seeking implementable portfolio optimization approaches, it is essential to evaluate the models and select the one that delivers the highest after-cost and risk-adjusted performance. This study compares traditional portfolio optimization models (Mean-Variance Optimization and the Black-Litterman model) with machine learning approaches (Random Forest and XGBoost) using the same dataset. The 30 S&P 500 stocks are randomly selected, and their price data from 2015 to 2024, obtained at a monthly frequency from Yahoo Finance, are split into a training window (2015-2021), a validating window (2022), and a testing window (2023-2024). All investment strategies are long-only, fully invested, and rebalanced monthly. An equally weighted portfolio consisting of all 30 selected stocks, applying a buy-and-hold strategy, serves as the benchmark model. The model comparison involves evaluating risk-adjusted portfolio performance and predictive accuracy. The empirical test results from the testing period show that machine learning models, particularly Random Forest, can add significant value to portfolios and achieve good predictive accuracy, but they are cost-sensitive and unstable. In contrast, traditional models perform relatively poorly but are stable under different cost settings. Meta Tags Meta tags Portfolio Optimization, Investment Management, Machine Learning, Random Forest, XGBoost, Black-Litterman, Mean-Variance Optimization Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Subject The topic of the resource Warwick Business School Date A point or period of time associated with an event in the lifecycle of the resource 2025 Title A name given to the resource Comparative Analysis of Traditional and Machine Learning Portfolio Optimization Models Using Public Financial Data Creator An entity primarily responsible for making the resource Yingqi Wang https://linen-dog.lnx.warwick.ac.uk/files/original/814f33c9073a41e23988795fe75a59ba.pdf c6d16e388eb66c6c4e24effaf987b909 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Social Sciences Subject The topic of the resource Social Sciences Academic Paper An academic paper Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Comparing Environmental Damages of Waterborne Polyurethane Gloves and Traditional Gloves: Lessons for a post-COVID World Subject The topic of the resource Economics Creator An entity primarily responsible for making the resource Yujing Zhang Date A point or period of time associated with an event in the lifecycle of the resource 2022 Air pollution Environment post-COVID waterborne polyurethane gloves https://linen-dog.lnx.warwick.ac.uk/files/original/01ec36dadcf78c1866e5326df73c16d2.ppt 863b1cecbf48628abb54e1e59061eb59 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Mathematics Academic Poster An academic poster Abstract The abstract of the paper This research investigates and compares the predictive performance of two time-series forecasting methods—Auto-Regressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) neural network for stock price prediction. The study uses historical stock price data obtained from Yahoo Finance to evaluate each model’s ability to predict trends. The ARIMA model, implemented using the “statsmodels” library, serves as a traditional statistical benchmark for modelling autocorrelated and stationary data. In contrast, the LSTM model, developed using “TensorFlow/Keras”, represents a modern deep learning approach capable of learning long-term dependencies and complex temporal dynamics. Data were divided into training and testing sets, with the final 15% reserved for out-of-sample evaluation. Model performance was assessed using Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Meta Tags Meta tags machine learning, ARIMA, LSTM, stock prediction Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Ka Ngai Wong Contributor An entity responsible for making contributions to the resource Dr Salimeh Pour Mohammad Title A name given to the resource Comparison of ARIMA and LSTM model on stock price predictions Subject The topic of the resource Mathematics Date A point or period of time associated with an event in the lifecycle of the resource 2025 https://linen-dog.lnx.warwick.ac.uk/files/original/c3547eb28335f413b3e42c9c0dc0a201.pdf 5536d0da08ecf92e2e1518b9a26b1594 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Science, Engineering and Medicine Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Comparison of Photon Dose Calculation Methods in Radiotherapy Subject The topic of the resource Physics Creator An entity primarily responsible for making the resource Ethan McHugo Date A point or period of time associated with an event in the lifecycle of the resource 2022 cancer doese Monte Carlo modelling Radiotherapy treatment Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Science, Engineering and Medicine Hyperlink A link, or reference, to another resource on the Internet. URL https://www.youtube.com/channel/UCXvU_PWWl_9elPU7-2Gj_0Q Meta Tags Meta tags School of Life Sciences, STEM, Biology, Microbiology, Molecular Biology, Evolution, Sporulation, Bacteria, Cell differentiation Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Completely And Utterly Spore-ing Description An account of the resource Podcast created as a public engagement output for the project 'Investigating Genes Responsible For Commitment To Sporulation In A Model Organism'. Creator An entity primarily responsible for making the resource Kit Lovesy Subject The topic of the resource Life Sciences Date A point or period of time associated with an event in the lifecycle of the resource 2025 https://linen-dog.lnx.warwick.ac.uk/files/original/25f4281156066c06e48d5a7c414f3dd2.pdf 0896e00064bfb2898d6c82e5aa9720b9 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Science, Engineering and Medicine Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Computational Study of the Properties of Niobium�doped Strontium Titanate Perovskites Subject The topic of the resource Physics Creator An entity primarily responsible for making the resource Mathys Potel Date A point or period of time associated with an event in the lifecycle of the resource 2023 Chemistry Coding Condensed Matter Engineering HetSys Mathys Potel Physics Warwick Centre for Predictive Modelling (WCPM) https://linen-dog.lnx.warwick.ac.uk/files/original/ff1a5d2ffccf9139575eb624f17dcbcf.pdf e375c68e8fd4a2a7480168231e620448 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Science, Engineering and Medicine Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Computationally Modelling the Solar Wind and CMEs on their Journey to Earth Description An account of the resource Physics Creator An entity primarily responsible for making the resource Jack Watson Date A point or period of time associated with an event in the lifecycle of the resource 2022 coronal mass injections Satellites Solar Space Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Mathematics Academic Poster An academic poster Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Rachel Haddad Title A name given to the resource Connections, Curvature, and Symmetry Subject The topic of the resource Mathematics Date A point or period of time associated with an event in the lifecycle of the resource 2025 Description An account of the resource A Study of G-Invariant Connection and Curvature Geometry on a Frame Bundle over a Symmetric Base Manifold Contributor An entity responsible for making contributions to the resource Max Stolarski https://linen-dog.lnx.warwick.ac.uk/files/original/b15f8038a7ed4527c2ccadc07daa85aa.pdf 33dd05fb270750b8c203fdbfe914284d Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Social Sciences Subject The topic of the resource Social Sciences Academic Paper An academic paper Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Consumers’ WTP to Avoid Unwanted Auto-renewal Contracts Subject The topic of the resource Economics Creator An entity primarily responsible for making the resource Frisk Zhang Date A point or period of time associated with an event in the lifecycle of the resource 2022 auto-renewal consumers contingent valuation contracts subscriptions discrete choice experiment WTP