1,720,954 research outputs found
Controlled Image Generation for Reflecting Eating Habits in Virtual Avatars
Get PDFThis thesis explores the use of AI-based image generation to visualize potential physical changes resulting from adherence to personalized meal plans provided by the Smart Eating Platform. The central goal is to generate realistic image transformations that reflect anticipated changes in body composition, thereby enhancing user engagement and motivation.
To identify suitable image generation techniques, we conducted manual testing of several models and selected two open-source methods, ControlNet and Null-text Inversion, for deeper evaluation. Both were systematically assessed by generating several hundred images using different combinations of input images, prompt templates, and parameters. This evaluation led to the identification of an optimal parameter set for each model.
During the course of the project, OpenAI released the GPT-4o image generation model. Although introduced too late for inclusion in the full evaluation pipeline, it was informally tested and showed superior performance in both realism and fidelity to the original image. As a result, GPT-4o was integrated into the final system alongside the two open-source pipelines.
The full solution consists of a modular system architecture with a Python-based FastAPI backend and a React.js frontend. The backend pipeline handles parameter validation, converts meal plans into descriptive textual prompts (termed "reflection in appearance"), and generates corresponding images using the selected image model. The system supports both OpenAI's GPT-4o and Qwen3 as language backends, and allows users to select between the three image generation pipelines based on their preferences or technical constraints.
A user study with nine participants was conducted to evaluate image quality and prompt adherence. GPT-4o emerged as the most reliable and well-rated model overall. ControlNet outperformed Null-text Inversion in average ratings, although with greater variability. These findings validate the decision to include multiple generation backends, providing both high-fidelity results and privacy-conscious alternatives for local execution.
In summary, this thesis presents a flexible, user-configurable pipeline for meal plan–driven image transformation, contributing a novel motivational tool to the Smart Eating Platform
Wish an instant map!
Get PDFThe aim of this work is to develop a proof-of-concept (POC) for an open-source QGIS plugin capable of translating natural language queries into Overpass-QL to perform spatial, temporal and attributive filtering of OpenStreetMap (OSM) data. The plugin visualises query results directly in QGIS. For example, a query like "All cafés within 50 metres of a fountain in St. Gallen" is processed and rendered as a map. Unlike existing solutions that either require knowledge of Overpass-QL (e.g. QuickOSM) or are proprietary, this plugin aims to make such functionality accessible to non-experts.
The query processing consists of three main steps: (1) geoname recognition and geocoding (e.g. resolving "St. Gallen"), (2) recognition and semantic alignment of spatial entity sets (SES) with OSM attributes (e.g. mapping "café" to `amenity=cafe`), and (3) generation of Overpass-QL queries. Early attempts to implement the plugin using open source models such as LLaMA yielded suboptimal results. Consequently, a fine-tuned OpenAI GPT-4o model was used, resulting in significant improvements in query generation. Geonames were resolved using Photon, an OSM-based geocoder, in addition to OpenAI's assistant, and SES were mapped using semantic similarity analysis with pre-embedded OSM tags.
The finetuned LLMs were evaluated using 100 natural language queries, with the best fine-tuned GPT-4o model achieving a BLEU score of 0.67, significantly outperforming base models and open source alternatives. The exact match rate was 0.09, indicating room for improvement in the generation of perfectly accurate queries. Most of the generated Overpass-QL queries were functional within QGIS, with a high validity rate, although still lacking in semantic precision.
The resulting QGIS plugin, called Wish an Instant Map! (WAIM), was implemented in Python using the two preprocessing steps, together with the finetuned OpenAI LLM. The graphical user interface includes text input for queries, support for current map extents, and an expert mode for editing OverpassQL. While the system has demonstrated feasibility through black-box testing with English language queries, challenges remain, including reliability of generated queries and reliance on proprietary LLMs.
Future improvements can include the development of an OSM thesaurus to improve semantic matching, the integration of structured output for query validation, and the use of larger datasets or larger LLMs to fine-tune open-source models. Despite its limitations, WAIM illustrates the potential for combining AI with geospatial systems
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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