Building a diversity featured search system by fusing existing tools

This paper describes our diversity featured retrieval system which are built for the task of ImageCLEFPhoto 2008. Two existing tools are used: Solr and Carrot. We have experimented with different settings of the system to see how the performance changes. The results suggest that the system can indeed increase diversity of the retrieved results and keep the precision about the same

Creating a test collection to evaluate diversity in image retrieval

This paper describes the adaptation of an existing test collection for image retrieval to enable diversity in the results set to be measured. Previous research has shown that a more diverse set of results often satisfies the needs of more users better than standard document rankings. To enable diversity to be quantified, it is necessary to classify images relevant to a given theme to one or more sub-topics or clusters. We describe the challenges in building (as far as we are aware) the first test collection for evaluating diversity in image retrieval. This includes selecting appropriate topics, creating sub-topics, and quantifying the overall effectiveness of a retrieval system. A total of 39 topics were augmented for cluster-based relevance and we also provide an initial analysis of assessor agreement for grouping relevant images into sub-topics or clusters

Overview of the 2005 cross-language image retrieval track (ImageCLEF)

The purpose of this paper is to outline efforts from the 2005 CLEF crosslanguage image retrieval campaign (ImageCLEF). The aim of this CLEF track is to explore the use of both text and content-based retrieval methods for cross-language image retrieval. Four tasks were offered in the ImageCLEF track: a ad-hoc retrieval from an historic photographic collection, ad-hoc retrieval from a medical collection, an automatic image annotation task, and a user-centered (interactive) evaluation task that is explained in the iCLEF summary. 24 research groups from a variety of backgrounds and nationalities (14 countries) participated in ImageCLEF. In this paper we describe the ImageCLEF tasks, submissions from participating groups and summarise the main fndings

Direct detection of electron backscatter diffraction patterns.

We report the first use of direct detection for recording electron backscatter diffraction patterns. We demonstrate the following advantages of direct detection: the resolution in the patterns is such that higher order features are visible; patterns can be recorded at beam energies below those at which conventional detectors usefully operate; high precision in cross-correlation based pattern shift measurements needed for high resolution electron backscatter diffraction strain mapping can be obtained. We also show that the physics underlying direct detection is sufficiently well understood at low primary electron energies such that simulated patterns can be generated to verify our experimental data

Embracing virtual outpatient clinics in the era of COVID-19

The response to the COVID-19 pandemic has raised the profile and level of interest in the use, acceptability, safety and effectiveness of virtual outpatient consultations and telemedicine. These models of care are not new but a number of challenges have so far hindered widespread take up and endorsement of these ways of working. With the response to the COVID-19 pandemic, remote and virtual working and consultation have become the default. This paper explores our experience of and learning from virtual and remote consultation and questions how this experience can be retained and developed for the future

Attitudes to Reading and Writing and their Links with Social Mobility 1914-2014: An Evidence Review

This review has drawn on a range of literature, archive material, family interviews and data gathered using social media to explore attitudes to reading and writing and their links with social mobility from 1914 to the present day. It identifies the many ways in which families read for pleasure and identifies ways in which Booktrust’s activity might be developed

Applying machine learning algorithms in estimating the performance of heterogeneous, multi-component materials as oxygen carriers for chemical-looping processes

Heterogeneous, multi-component materials such as industrial tailings or by-products, along with naturally occurring materials, such as ores, have been intensively investigated as candidate oxygen carriers for chemical-looping processes. However, these materials have highly variable compositions, and this strongly influences their chemical-looping performance. Here, using machine learning techniques, we estimate the performance of heterogeneous, multi-component materials as oxygen carriers for chemical-looping. Experimental data for 19 manganese ores chosen as potential chemical-looping oxygen carriers were used to create a so-called training database. This database has been used to train several supervised artificial neural network models (ANN), which were used to predict the reactivity of the oxygen carriers with different fuels and the oxygen transfer capacity with only the knowledge of reactor bed temperature, elemental composition, and mechanical properties of the manganese ores. This novel approach explores ways of dealing with the training dataset, learning algorithms and topology of ANN models to achieve enhanced prediction precision. Stacked neural networks with a bootstrap resampling technique have been applied to achieve high precision and robustness on new input data, and the confidence intervals were used to assess the precision of these predictions. The current results indicate that the best trained ANNs can produce highly accurate predictions for both the training database and the unseen data with the high coefficient of determination (R2 = 0.94) and low mean absolute error (MAE = 0.057). We envision that the application of these ANNs and other machine learning algorithms will accelerate the development of oxygen carrying materials for a range of chemical-looping applications and offer a rapid screening tool for new potential oxygen carriers