Investigating machine learning methods in recommender systems

This thesis investigates the use of machine learning in improving predictions of the top K* product purchases at a particular a retailer. The data used for this research is a freely-available (for research) sample of the retailer’s transactional data spanning a period of 102 weeks and consisting of several million observations. The thesis consists of four key experiments: 1. Univariate Analysis of the Dataset: The first experiment, which is the univariate analysis of the dataset, sets the background to the following chapters. It provides explanatory insight into the customers’ shopping behaviour and identifies the drivers that connect customers and products. Using various behavioural, descriptive and aggregated features, the training dataset for a group of customers is created to map their future purchasing actions for one specific week. The test dataset is then constructed to predict the purchasing actions for the forthcoming week. This constitutes a univariate analysis and the chapter is an introduction to the features included in the subsequent algorithmic processes. 2. Meta-modelling to predict top K products: The second experiment investigates the improvement in predicting the top K products in terms of precision at K (or precision@K) and Area Under Curve (AUC) through meta-modelling. It compares combining a range of common machine learning algorithms of a supervised nature within a meta-modelling framework (where each generated model will be an input to a secondary model) with any single model involved, field benchmark or simple model combination method. 3. Hybrid method to predict repeated, promotion-driven product purchases in an irregular testing environment: The third experiment demonstrates a hybrid methodology of cross validation, modelling and optimization for improving the accuracy of predicting the products the customers of a retailer will buy after havingbought them at least once with a promotional coupon. This methodology is applied in the context of a train and test environment with limited overlap - the test data includes different coupons, different customers and different time periods. Additionally this chapter uses a real life application and a stress-test of the findings in the feature engineering space from experiment 1. It also borrows ideas from ensemble (or meta) modelling as detailed in experiment 2. 4. The StackNet model: The fourth experiment proposes a framework in the form of a scalable version of [Wolpert 1992] stacked generalization being extended through cross validation methods to many levels resembling in structure a fully connected feedforward neural network where the hidden nodes represent complex functions in the form of machine learning models of any nature. The implementation of the model is made available in the Java programming language. The research contribution of this thesis is to improve the recommendation science used in the grocery and Fast Moving Consumer Goods (FMCG) markets. It seeks to identify methods of increasing the accuracy of predicting what customers are going to buy in the future by leveraging up-to-date innovations in machine learning as well as improving current processes in the areas of feature engineering, data pre-processing and ensemble modelling. For the general scientific community this thesis can be exploited to better understand the type of data available in the grocery market and to gain insights into how to structure similar machine learning and analytical projects. The extensive, computational and algorithmic framework that accompanies this thesis is also available for general use as a prototype to solve similar data challenges. References: Wolpert, D. H. (1992). Stacked generalization. Neural networks, 5(2), 241-259. Yang, X., Steck, H., Guo, Y., & Liu, Y. (2012). On top-k recommendation using social networks. In Proceedings of the sixth ACM conference on Recommender systems (pp. 67-74). ACM

Microencapsulated phase change materials in solar-thermal conversion systems:understanding geometry-dependent heating efficiency and system reliability

The performance of solar-thermal conversion systems can be improved by incorporation of nanocarbon-stabilized microencapsulated phase change materials (MPCMs). The geometry of MPCMs in the microcapsules plays an important role for improving their heating efficiency and reliability. Yet few efforts have been made to critically examine the formation mechanism of different geometries and their effect on MPCMs-shell interaction. Herein, through changing the cooling rate of original emulsions, we acquire MPCMs within the nanocarbon microcapsules with a hollow structure of MPCMs (h-MPCMs) or solid PCM core particles (s-MPCMs). X-ray photoelectron spectroscopy and atomic force microscopy reveals that the capsule shell of the h-MPCMs is enriched with nanocarbons and has a greater MPCMs-shell interaction compared to s-MPCMs. This results in the h-MPCMs being more stable and having greater heat diffusivity within and above the phase transition range than the s-MPCMs do. The geometry-dependent heating efficiency and system stability may have important and general implications for the fundamental understanding of microencapsulation and wider breadth of heating generating systems

Microcapsules Prepared via Pickering Emulsion Polymerization for Multifunctional Coatings

Micro/nanocontainer-based self-healing coatings have achieved enormous interest in scientific community during the last decade. However, the search for multifunctional micro/nanocontainers still has research challenge, especially for the micro/nanocontainers with dual functionality (both anticorrosion and antimicrobial). Here, a novel type of microcapsules with antimicrobial shell and anticorrosion core was prepared by the Pickering emulsion polymerization technique. Dimethyloctadecyl [3-(trimethoxysilyl) propyl] ammonium chloride (QC18) and linseed oil were encapsulated as the antimicrobial and the anticorrosion agents, respectively. The results of local electrochemical impedance spectroscopy (LEIS) at 10 Hz demonstrated corrosion suppression in the scratched area of coatings doped with multifunctional microcapsules. Additionally, the QC18modified microcapsules exhibited high antibacterial performance, showing over 90 % antimicrobial efficacy against gram-positive bacteria. This type of dual-functional coating might guide future design of micro/nanocontainer-based self-healing paint formulations

Marine Strategy Framework Directive - Descriptor 2, Non-Indigenous Species, Delivering solid recommendations for setting threshold values for non-indigenous species pressure on European seas

Marine Non-Indigenous Species (NIS) are animals and plants introduced accidently or deliberately into the European seas, originating from other seas of the globe. About 800 marine non-indigenous species (NIS) currently occur in the European Union national marine waters, several of which have negative impacts on marine ecosystem services and biodiversity. Under the Marine Strategy Framework Directive (MSFD) Descriptor 2 (D2), EU Member States (MSs) need to consider NIS in their marine management strategies. The Descriptor D2 includes one primary criterion (D2C1: new NIS introductions), and two secondary criteria (D2C2 and D2C3). The D2 implementation is characterized by a number of issues and uncertainties which can be applicable to the Descriptor level (e.g. geographical unit of assessment, assessment period, phytoplanktonic, parasitic, oligohaline NIS, etc.), to the primary criterion D2C1 level (e.g. threshold values, cryptogenic, questionable species, etc), and to the secondary criteria D2C2 and D2C3. The current report tackles these issues and provides practical recommendations aiming at a smoother and more efficient implementation of D2 and its criteria at EU level. They constitute a solid operational output which can result in more comparable D2 assessments among MSs and MSFD regions/subregions. When it comes to the policy-side, the current report calls for a number of different categories of NIS to be reported in D2 assessments, pointing the need for the species to be labelled/categorised appropriately in the MSFD reporting by the MSs. These suggestions are proposed to be communicated to the MSFD Working Group of Good Environmental Status (GES) and subsequently to the Marine Strategy Coordination Group (MSCG) of MSFD. Moreover, they can serve as an input for revising the Art. 8 Guidelines

Non-indigenous species refined national baseline inventories: A synthesis in the context of the European Union's Marine Strategy Framework Directive

Refined baseline inventories of non-indigenous species (NIS) are set per European Union Member State (MS), in the context of the Marine Strategy Framework Directive (MSFD). The inventories are based on the initial assessment of the MSFD (2012) and the updated data of the European Alien Species Information Network, in collaboration with NIS experts appointed by the MSs. The analysis revealed that a large number of NIS was not reported from the initial assessments. Moreover, several NIS initially listed are currently considered as native in Europe or were proven to be historical misreportings. The refined baseline inventories constitute a milestone for the MSFD Descriptor 2 implementation, providing an improved basis for reporting new NIS introductions, facilitating the MSFD D2 assessment. In addition, the inventories can help MSs in the establishment of monitoring systems of targeted NIS, and foster cooperation on monitoring of NIS across or within shared marine subregions.Henn Ojaveer and Maiju Lehtiniemi wish to acknowledge the project COMPLETE (Completing management options in the Baltic Sea region to reduce risk of invasive species introduction by shipping), co-financed by the European Union's funding Programme Interreg Baltic Sea Region (European Regional Development Fund). João Canning-Clode was supported by a starting grant in the framework of the 2014 FCT Investigator Programme (IF/01606/2014/CP1230/CT0001) and wish to acknowledge the support of Fundação para a Ciência e Tecnologia (FCT), through the strategic project UID/MAR/04292/2019 granted to MARE

Non-indigenous species refined national baseline inventories : A synthesis in the context of the European Union's Marine Strategy Framework Directive

Refined baseline inventories of non-indigenous species (NIS) are set per European Union Member State (MS), in the context of the Marine Strategy Framework Directive (MSFD). The inventories are based on the initial assessment of the MSFD (2012) and the updated data of the European Alien Species Information Network, in collaboration with NIS experts appointed by the MSs. The analysis revealed that a large number of NIS was not reported from the initial assessments. Moreover, several NIS initially listed are currently considered as native in Europe or were proven to be historical misreportings. The refined baseline inventories constitute a milestone for the MSFD Descriptor 2 implementation, providing an improved basis for reporting new NIS introductions, facilitating the MSFD D2 assessment. In addition, the inventories can help MSs in the establishment of monitoring systems of targeted NIS, and foster cooperation on monitoring of NIS across or within shared marine subregions. Highlights • Refined MSFD baseline inventories of non-indigenous species (NIS) are set in EU. • The inventories are given per EU Member State (MS) and MSFD subregion up to 2012. • The NIS lists provide a basis for reporting new NIS introductions in EU after 2012. • Our work constitutes a milestone for the MSFD Descriptor 2 implementation

Exploring Environmental and Economic Costs and Benefits of a Forest-Based Circular Economy: A Literature Review

The role of a forest sector in the transition to a circular economy (CE) is critical. Therefore, the purpose of this study is to summarize the main findings of the most important published articles and to provide insights on the interdisciplinary space at the interface of concepts related to a forest-based CE. Moreover, it attempts to assess the challenges raised from adopting the CE in forest sector. Through a systematic literature review, 69 scientific publications were selected and evaluated by two sights: (i) a descriptive analysis and (ii) a cluster analysis of the keywords related to the forest-based CE. The study highlights the need for additional survey on optimizing the interaction between forest ecosystem services and circular economy. Further discussion is also needed about the relations of the key factors associated with the forest-based circular economy, as they emerged from the cluster analysis and the co-occurrence network map