85 10 900 https://urss.warwick.ac.uk/files/original/cc5fcdaceaa8863e62ac443131b77d3e.pdf a6b0f9ac364fa637572418c2e10a730b 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 An introduction to cyclotomic polynomials and modified Cauchy-Mirimano(CLM) polynomials Meta Tags Meta tags cyclotomic polynomial 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 Yiming Liao Contributor An entity responsible for making contributions to the resource Miles Reid Subject The topic of the resource Mathematics Title A name given to the resource An introduction to cyclotomic polynomials and modified Cauchy-Mirimano(CLM) polynomials Date A point or period of time associated with an event in the lifecycle of the resource 2024 https://urss.warwick.ac.uk/files/original/2c67bd86268fa950f3ceb264230b7b7c.pdf 7ef34b3010e193acca75d4e54992a192 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 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 Unlocking the Future: Blockchain & Uniswap V3 Subject The topic of the resource Warwick Business School Creator An entity primarily responsible for making the resource Yiming Zhou and Guanda Chen Date A point or period of time associated with an event in the lifecycle of the resource 2023 Analytics. Liquidity Blockchain Business Data FinTech Guanda Chen Trading behaviours Uniswap V3 Yiming Zhou https://urss.warwick.ac.uk/files/original/92ea65d41daabef114ff8b1d1966bbb4.pdf 493105631245b2b7d284c0c1d4065305 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 Purpose – This study examines the suitability of hard versus soft clustering approaches for customer segmentation across distinct business model types. Specifically, it evaluates whether homogeneous marketing treatment implied by K-means is justified in subscription and singular transaction contexts, and whether Fuzzy C-means (FCM) offers a more appropriate representation of behavioural overlap. Methodology – Using the RFM (Recency–Frequency–Monetary) framework, the study applies both K-means and FCM to two datasets: the Online Retail dataset (transaction model) and the Customer Churn dataset (subscription model). RFM metrics were adapted for subscription contexts to reflect product interactions rather than discrete purchases. Clustering performance was assessed through the silhouette score (K-means) and fuzzy partition coefficient (FCM), following a consistent CRISP-DM process for data preparation, modelling, and evaluation. Findings – Results indicate a reversal of theoretical expectations. The subscription dataset exhibited considerable behavioural overlap, with weak cluster separation, challenging the assumption of homogeneous treatment. Conversely, the transaction dataset displayed moderately strong partitions, suggesting that standardisation of product attributes may reduce behavioural heterogeneity. These findings highlight that clustering suitability depends not only on business model type but also on contextual factors such as product standardisation and tier design. Originality – This study is the first to align the selection of hard versus soft clustering methods with business model typologies and to adapt RFM metrics for subscription contexts. By integrating FCM as a diagnostic tool for testing the validity of homogeneous treatment assumptions, it addresses a critical gap in behavioural segmentation research and provides a practical decision framework for guiding clustering choice. Meta Tags Meta tags Customer segmentation, Machine learning, Clustering, Business analytics, Customer behaviour, Business model 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 Hard vs. Soft Clustering for RFM Segmentation: A Joint Evaluation of Method Suitability Across Singular Transaction and Subscription Business Models Creator An entity primarily responsible for making the resource Ying Ting Chan https://urss.warwick.ac.uk/files/original/1ae459601a278b3bcd18f0a69a98685b.pdf ab270c87883dca633644a80e5a80b8a1 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 Arts 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 The Cinematic Space of Los Angeles in La La Land (2016) – The Tension between Reality and Fantasy Subject The topic of the resource Film & Television Studies Description An account of the resource In Los Angles, there was an exceptionally close interaction between cinema and the built environment. In their form and function, the largest movie studios resembled and were often described as, cities in themselves, being part and not part of their surroundings (Sheil, 2012). La La Land (Damien Chazelle, 2016) was shot in LA, and explicitly announces its concern with the city in its title, plot and themes. It is also a film that portrays the close relationships between the movie studio and the city space. Creator An entity primarily responsible for making the resource Yinglun Wang Date A point or period of time associated with an event in the lifecycle of the resource 2022 City Film LA Los Angeles Space https://urss.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://urss.warwick.ac.uk/files/original/f339e06f7253279522b28eb65211a5ad.pdf caf958f1203b3052a58d274d8bf3fa5a 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 Boundary, Sexuality and Mobility: A Study of Chinese Queer Studying in the UK Subject The topic of the resource Politics and International Studies Creator An entity primarily responsible for making the resource Yiran Huang Date A point or period of time associated with an event in the lifecycle of the resource 2023 Asian studies gender studies Immigrant studies Politics and International Studies Yiran Huang https://urss.warwick.ac.uk/files/original/2e3bf90ef38fcf8042b860586b795da7.pdf f807b7d8cc88b684ee494dfaf4f6cb86 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 Imagine that when a virus enters our body, our immune system is activated, and some cells start to track and kill the virus. Here is an interesting question: How do the cells know which direction is the correct one, given that the movement of the virus is totally random? My project will use differential equations, particularly stochastic differential equations, to explain this phenomenon and numerical methods that rely on computers to predict the potential future movement of the cells. Meta Tags Meta tags PDEs, numerical methods, stochastic differential equations, finite element method 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 Yiyang Hu Contributor An entity responsible for making contributions to the resource Dr Björn Stinner Subject The topic of the resource Mathematics Title A name given to the resource Differential Equations in Cell Motility: Applications of Numerical Methods in the Real World Date A point or period of time associated with an event in the lifecycle of the resource 2025 https://urss.warwick.ac.uk/files/original/898367e798b9ae5aaed708bd37d78039.pdf a46bcd30b050493a4ece918f5d03923f 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/. Title A name given to the resource Scheme Theory of Curves and Quadratic Forms Subject The topic of the resource Mathematics Creator An entity primarily responsible for making the resource Yorgos Kontoyiannis Date A point or period of time associated with an event in the lifecycle of the resource 2023 Geometry Mathematics Schemes Yorgos Kontoyiannis https://urss.warwick.ac.uk/files/original/d8574afe93a2826c331f50969144f4e1.pdf a7ea7aeb3dd90b6d5d7fbf7c520a9c3f 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 Bayesian Predictive Densities with Recursive Conditional Copula Online Updates Subject The topic of the resource Statistics Creator An entity primarily responsible for making the resource Yuanhe Zhang David Huk Date A point or period of time associated with an event in the lifecycle of the resource 2023 Bayesian Statistics Deep Learning Machine learning Statistics Yuanhe Zhang David Huk https://urss.warwick.ac.uk/files/original/f4fc79d5b9e4575a064f110caabf8fb3.pdf ed1c4f06f62b408f5a7a28f6715d5b6c 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 Presentation Meta Tags Meta tags Tag 1 :The function of TrPM2 on Neuronal Cell ---if it signal to PGE2; Tag 2 :determine the specific roles of TRPA1, TRPV1, and TRPM2 in mediating the response to PGE2. 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 The function of TrPM2 on Neuronal Cell Creator An entity primarily responsible for making the resource Yuemeng Chen 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 2024 Contributor An entity responsible for making contributions to the resource Xuming Zhang anti-inflammatory Disease Immunity inflammation neuronal Cell rPM2