Recipe popularity prediction in Finnish social media by machine learning models

Abstract. In recent times, the internet has emerged as a primary source of cooking inspiration, eating experiences and food social gathering with a majority of individuals turning to online recipes, surpassing the usage of traditional cookbooks. However, there is a growing concern about the healthiness of online recipes. This thesis focuses on unraveling the determinants of online recipe popularity by analyzing a dataset comprising more than 5000 recipes from Valio, one of Finland’s leading corporations. Valio’s website serves as a representation of diverse cooking preferences among users in Finland. Through examination of recipe attributes such as nutritional content (energy, fat, salt, etc.), food preparation complexity (cooking time, number of steps, required ingredients, etc.), and user engagement (the number of comments, ratings, sentiment of comments, etc.), we aim to pinpoint the critical elements influencing the popularity of online recipes. Our predictive model-Logistic Regression (classification accuracy and F1 score are 0.93 and 0.9 respectively)- substantiates the existence of pertinent recipe characteristics that significantly influence their rates. The dataset we employ is notably influenced by user engagement features, particularly the number of received ratings and comments. In other words, recipes that garner more attention in terms of comments and ratings tend to have higher rates values (i.e., more popular). Additionally, our findings reveal that a substantial portion of Valio’s recipes falls within the medium health Food Standards Agency (FSA) score range, and intriguingly, recipes deemed less healthy tend to receive higher average ratings from users. This study advances our comprehension of the factors contributing to the popularity of online recipes, providing valuable insights into contemporary cooking preferences in Finland as well as guiding future dietary policy shift.Reseptin suosion ennustaminen suomalaisessa sosiaalisessa mediassa koneoppimismalleilla. Tiivistelmä. Internet on viime aikoina noussut ensisijaiseksi inspiraation lähteeksi ruoanlaitossa, ja suurin osa ihmisistä on siirtynyt käyttämään verkkoreseptejä perinteisten keittokirjojen sijaan. Huoli verkkoreseptien terveellisyydestä on kuitenkin kasvava. Tämä opinnäytetyö keskittyy verkkoreseptien suosioon vaikuttavien tekijöiden selvittämiseen analysoimalla yli 5000 reseptistä koostuvaa aineistoa Suomen johtavalta maitotuoteyritykseltä, Valiolta. Valion verkkosivujen reseptit edustavat monipuolisesti suomalaisten käyttäjien ruoanlaittotottumuksia. Tarkastelemalla reseptin ominaisuuksia, kuten ravintoarvoa (energia, rasva, suola, jne.), valmistuksen monimutkaisuutta (keittoaika, vaiheiden määrä, tarvittavat ainesosat, jne.) ja käyttäjien sitoutumista (kommenttien määrä, arviot, kommenttien mieliala, jne.), pyrimme paikantamaan kriittiset tekijät, jotka vaikuttavat verkkoreseptien suosioon. Ennustava mallimme — Logistic Regression (luokituksen tarkkuus 0,93 ja F1-pisteet 0,9 ) — osoitti merkitsevien reseptiominaisuuksien olemassaolon. Ne vaikuttivat merkittävästi reseptien suosioon. Käyttämiimme tietojoukkoihin vaikuttivat merkittävästi käyttäjien sitoutumisominaisuudet, erityisesti vastaanotettujen arvioiden ja kommenttien määrä. Toisin sanoen reseptit, jotka saivat enemmän huomiota kommenteissa ja arvioissa, olivat yleensä suositumpia. Lisäksi selvisi, että huomattava osa Valion resepteistä kuuluu keskitason terveyspisteiden alueelle (arvioituna FSA Scorella), ja mielenkiintoisesti, vähemmän terveellisiksi katsotut reseptit saavat käyttäjiltä yleensä korkeamman keskiarvon. Tämä tutkimus edistää ymmärrystämme verkkoreseptien suosioon vaikuttavista tekijöistä ja tarjoaa arvokasta näkemystä nykypäivän ruoanlaittotottumuksista Suomessa

A preliminary study of micro-gestures:dataset collection and analysis with multi-modal dynamic networks

Abstract. Micro-gestures (MG) are gestures that people performed spontaneously during communication situations. A preliminary exploration of Micro-Gesture is made in this thesis. By collecting recorded sequences of body gestures in a spontaneous state during games, a MG dataset is built through Kinect V2. A novel term ‘micro-gesture’ is proposed by analyzing the properties of MG dataset. Implementations of two sets of neural network architectures are achieved for micro-gestures segmentation and recognition task, which are the DBN-HMM model and the 3DCNN-HMM model for skeleton data and RGB-D data respectively. We also explore a method for extracting neutral states used in the HMM structure by detecting the activity level of the gesture sequences. The method is simple to derive and implement, and proved to be effective. The DBN-HMM and 3DCNN-HMM architectures are evaluated on MG dataset and optimized for the properties of micro-gestures. Experimental results show that we are able to achieve micro-gesture segmentation and recognition with satisfied accuracy with these two models. The work we have done about the micro-gestures in this thesis also explores a new research path for gesture recognition. Therefore, we believe that our work could be widely used as a baseline for future research on micro-gestures

Electronic Imaging & the Visual Arts. EVA 2019 Florence

The Publication is following the yearly Editions of EVA FLORENCE. The State of Art is presented regarding the Application of Technologies (in particular of digital type) to Cultural Heritage. The more recent results of the Researches in the considered Area are presented. Information Technologies of interest for Culture Heritage are presented: multimedia systems, data-bases, data protection, access to digital content, Virtual Galleries. Particular reference is reserved to digital images (Electronic Imaging & the Visual Arts), regarding Cultural Institutions (Museums, Libraries, Palace - Monuments, Archaeological Sites). The International Conference includes the following Sessions: Strategic Issues; New Science and Culture Developments & Applications; New Technical Developments & Applications; Cultural Activities – Real and Virtual Galleries and Related Initiatives, Access to the Culture Information. One Workshop regards Innovation and Enterprise. The more recent results of the Researches at national and international level are reported in the Area of Technologies and Culture Heritage, also with experimental demonstrations of developed Activities

A Modular and Open-Source Framework for Virtual Reality Visualisation and Interaction in Bioimaging

Life science today involves computational analysis of a large amount and variety of data, such as volumetric data acquired by state-of-the-art microscopes, or mesh data from analysis of such data or simulations. The advent of new imaging technologies, such as lightsheet microscopy, has resulted in the users being confronted with an ever-growing amount of data, with even terabytes of imaging data created within a day. With the possibility of gentler and more high-performance imaging, the spatiotemporal complexity of the model systems or processes of interest is increasing as well. Visualisation is often the first step in making sense of this data, and a crucial part of building and debugging analysis pipelines. It is therefore important that visualisations can be quickly prototyped, as well as developed or embedded into full applications. In order to better judge spatiotemporal relationships, immersive hardware, such as Virtual or Augmented Reality (VR/AR) headsets and associated controllers are becoming invaluable tools. In this work we present scenery, a modular and extensible visualisation framework for the Java VM that can handle mesh and large volumetric data, containing multiple views, timepoints, and color channels. scenery is free and open-source software, works on all major platforms, and uses the Vulkan or OpenGL rendering APIs. We introduce scenery's main features, and discuss its use with VR/AR hardware and in distributed rendering. In addition to the visualisation framework, we present a series of case studies, where scenery can provide tangible benefit in developmental and systems biology: With Bionic Tracking, we demonstrate a new technique for tracking cells in 4D volumetric datasets via tracking eye gaze in a virtual reality headset, with the potential to speed up manual tracking tasks by an order of magnitude. We further introduce ideas to move towards virtual reality-based laser ablation and perform a user study in order to gain insight into performance, acceptance and issues when performing ablation tasks with virtual reality hardware in fast developing specimen. To tame the amount of data originating from state-of-the-art volumetric microscopes, we present ideas how to render the highly-efficient Adaptive Particle Representation, and finally, we present sciview, an ImageJ2/Fiji plugin making the features of scenery available to a wider audience.:Abstract Foreword and Acknowledgements Overview and Contributions Part 1 - Introduction 1 Fluorescence Microscopy 2 Introduction to Visual Processing 3 A Short Introduction to Cross Reality 4 Eye Tracking and Gaze-based Interaction Part 2 - VR and AR for System Biology 5 scenery — VR/AR for Systems Biology 6 Rendering 7 Input Handling and Integration of External Hardware 8 Distributed Rendering 9 Miscellaneous Subsystems 10 Future Development Directions Part III - Case Studies C A S E S T U D I E S 11 Bionic Tracking: Using Eye Tracking for Cell Tracking 12 Towards Interactive Virtual Reality Laser Ablation 13 Rendering the Adaptive Particle Representation 14 sciview — Integrating scenery into ImageJ2 & Fiji Part IV - Conclusion 15 Conclusions and Outlook Backmatter & Appendices A Questionnaire for VR Ablation User Study B Full Correlations in VR Ablation Questionnaire C Questionnaire for Bionic Tracking User Study List of Tables List of Figures Bibliography Selbstständigkeitserklärun

Handbook of Vascular Biometrics

This open access handbook provides the first comprehensive overview of biometrics exploiting the shape of human blood vessels for biometric recognition, i.e. vascular biometrics, including finger vein recognition, hand/palm vein recognition, retina recognition, and sclera recognition. After an introductory chapter summarizing the state of the art in and availability of commercial systems and open datasets/open source software, individual chapters focus on specific aspects of one of the biometric modalities, including questions of usability, security, and privacy. The book features contributions from both academia and major industrial manufacturers

Ciência de dados na era da agricultura digital: anais.

Estes anais contêm o texto completo dos trabalhos apresentados no XI Congresso Brasileiro de Agroinformática (SBIAgro 2017), o qual foi promovido pela Embrapa Informática Agropecuária e pela Faculdade de Engenharia Agrícola, Instituto de Computação e pelo Centro de Pesquisas Meteorológicas e Climáticas Aplicadas à Agricultura da Universidade Estadual de Campinas (Unicamp). Esta edição do evento foi realizada no Centro de Convenções e na Casa do Lago da Unicamp, localizados na cidade de Campinas (SP). O propósito do evento foi o de reunir pesquisadores, professores, estudantes, empresários e funcionários de empresas para discutir o tema da informática aplicada à agricultura, além de promover um ambiente propício para o surgimento de novos relacionamentos, projetos e negócios.Organizadores: Jayme Garcia Arnal Barbedo, Maria Fernanda Moura, Luciana Alvim Santos Romani, Thiago Teixeira Santos, Débora Pignatari Drucker. SBIAgro 2017