This study investigated effects of video prompting using an iPod Touch to teach recipe-following to four 16-19 year-old youth with intellectual disability and autism in a transition classroom. Target behaviors involved correctly following three multi-step recipes: microwave dinner, brownies, and gelatin. A multiple-probe design across recipes was replicated across participants. After low levels of responding in baseline probes, researchers presented participants with an iPod Touch showing each step of the task using video and with audio narration. Following the video prompting phase, maintenance and home-based generalization probes were conducted. The intervention increased recipe-following performance for all participants. Performance maintained and generalized to youths’ home kitchens. Results are discussed in regards to using video demonstrations in a sequence of prompts.

This study aims to design and validate a nutritional recipe for a snack made of Green Banana (Musa paradisiaca) Peel Flour (GBPF) and to assess the nutritional composition and microbiological quality of the flour. Banana peel, a food industry by-product, is a nutritious, low-cost material available for all year. Banana peel flower could be used as a functional ingredient due to its high fiber content and good functional properties. In general, university students have a deficient dietary fiber intake due to altered dietary patterns; thus, this study was focused on this population. The GBPFs were obtained from the peels of pre-climacteric bananas by fluidized bed (FDB) dryer, after which, microbiological, proximate, and dietary fiber analyses were applied. It was designed the nutritional recipe for the snack taking into account the energy and dietary fiber nutritional requirements of the target population. It could be validated and adjusted the recipe following the methodology of Centro Nacional de Alimentaci n y Nutrici n, concluding with the determination of dietary fiber in the end-product. The dietary fiber, total carbohydrate, protein, total fat and energy contents of the GBPF were as following: 38.7 g, 76.3 g, 5.9 g, 3.6 g, and 361.2 kcal, per 100 g of flour. The snack contained 7.74 g of dietary fiber per serving size, having a good acceptance among the university students' panelists based on an organoleptic test. In conclusion, the GBPF showed great potential as a source of dietary fiber, and it was an excellent source of carbohydrates and other nutrients to a lesser degree. When included as a functional ingredient in the nutritional formulation of a snack, it had an overall positive effect on the product's organoleptic characteristics. / Revisión por pares

Today, many introductory computer science courses rely heavily on a specific programming language to convey fundamental programming concepts. For beginning students, the cognitive capacity required to operate with the syntactic forms of this language may overwhelm their ability to formulate a solution to a program. We recognize that the introductory computer science courses can be more effective if they convey fundamental concepts without requiring the students to focus on the syntax of a programming language. To achieve this, we propose a new teaching method based on the Design Recipe and Code Outlining (DRaCO) processes. Our new pedagogy capitalizes on the algorithmic intuitions of novice students and provides a tool for students to externalize their intuitions using techniques they are already familiar with, rather than with the syntax of a specific programming language. We validate the effectiveness of our new pedagogy by integrating it into an existing CS1 course at California Polytechnic State University, San Luis Obispo. We find that the our newly proposed pedagogy shows strong potential to improve students’ ability to program.

One of the key tasks in the study of the recommendation system is to model the dynamics aspect of a person's preference, i.e. to give sequential recommendations. Markov Chain (MC), which is famous for its capability of learning a transition graph, is the most popular approach to address the task. In previous work, the recommendation system attempts to model the short-term dynamics of the personal preference based on the long-term dynamics, which implies the assumption that the personal preference over a set of items remains same over time. However, in the field of food science, the study of Sensory-Specific Satiety (SSS) shows that the personal preference on food changes along time and previous meals. However, whether such changes follow certain patterns remains unclear. In this paper, a recommendation system is built based on Variable Order Markov Chain (VOMC), which is capable of modeling various lengths of sequential patterns using the suffix tree (ST) search. This recommendation system aims to understand and model the short-term dynamics aspect of the personal preference on food. To evaluate the system, a Food Diary survey is carried to collect users’ meals data over seven days. The results show that this recommendation system can give meaningful recommendations. / En av huvuduppgifterna när det kommer till rekommenderingsplatformar är att modellera kortsidiga dynamiska egenskaper, dvs. användares sekventiella beteenden. Markov Chain (MC), som är mest känd för sin förmåga att lära sig övergångsgrafer, är den mest populära metoden för att ge sig på denna uppgift. I föregående arbeten så har rekommenderingsplatformar ofta tenderat att modellera kortsidig dynamik baserat på långsidig dynamik, t.ex. likheter mellan objekt eller användares relativa preferenser givet olika tillfällen. Att använda den här metoden brukar medföra att användares långsiktiga dynamik, i detta fall personliga smakpreferenser, är alltid densamma. Däremot, så har studien av Sensory-Specific Satiety visat att användares preferenser gällande mat varierar. I detta arbete så undersöks ett rekommenderingssystem som baseras på Variable Order Markov Chain (VOMC) som kan anpassa sig efter den observerade realiseringen genom att använda suffix tree (ST) för att extrahera sekventiella mönster. Detta rekommenderingssystem fokuserar på kortsidig dynamik istället för att kombinera kort- och långsidig dynamik. För att evaluera metoden, en undersökning av vilken mat som konsumeras, under loppet av sju dagar, ges ut för att samla data om vilken mat och i vilken ordning användare konsumerar. I resultaten så visas att det föreslagna rekommenderingsystemet kan ge meningsfulla rekommendationer.

Background: The demand for a sustainable lifestyle is increasing due to the need to tackle rapid climate change. One-third of carbon emissions come from the food industry; reducing emissions from this industry is crucial when fighting climate change. One of the ways to reduce carbon emissions from this industry is by helping consumers adopt sustainable eating habits by consuming eco-friendly food. To help consumers find eco-friendly recipes, we developed a sustainable recipe recommendation system that can recommend relevant and eco-friendly recipes to consumers using little information about their previous food consumption.  Objective: The main objective of this research is to identify (i) the appropriate recommendation algorithm suitable for a dataset that has few training and testing examples, and (ii) a technique to re-order the recommendation list such that a proper balance is maintained between relevance and carbon rating of the recipes. Method: We conducted an experiment to test the performance of a GPT embeddings-based recommendation system, Factorization Machines, and a version of a Graph Neural Network-based recommendation algorithm called PinSage for a different number of training examples and used ROC AUC value as our metric. After finding the best-performing model we experimented with different re-ordering techniques to find which technique provides the right balance between relevance and sustainability. Results: The results from the experiment show that the PinSage and Factorization Machines predict on average whether an item is relevant or not with 75% probability whereas GPT-embedding-based recommendation systems predict with only 55% probability. We also found the performance of PinSage and Factorization Machines improved as the training set size increased. For re-ordering, we found using a loga- rithmic combination of the relevance score and carbon rating of the recipe helped to reduce the average carbon rating of recommendations with a marginal reduction in the ROC AUC score.  Conclusion: The results show that the chosen state-of-the-art recommendation systems: PinSage and Factorization Machines outperform GPT-embedding-based recommendation systems by almost 1.4 times.

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The aim has been to investigate and describe how gender-neutral design, concerning typefaces and colours, can be created. Based on my results I’ve designed a cover for a recipe-book to make it appealing to both women and men. I have been doing my research based on questions such as; Does feminine and masculine design, concerning typefaces and colours exist? And if so what characterizes it? Does gender-neutral design, concerning typefaces and colours exist? And if so what characterizes it? Is it possible to design a cover for a recipe-book in a gender-neutral way, concerning typefaces and colours?The first part of my research consists of a literature study based on keywords such as gender, graphic design, gender theory, typeface, androgynous, visual communication, colour, shape, feminine, masculine, and book design. The second part consists of a empirical study based upon a heterogeneous sample of 311 respondents. The respondents responded to a survey about how they perceived different colours and typefaces from a gender perspective. The result shows that, within the target group I have chosen to focus on, there are colours and typefaces that are perceived as more feminine, masculine or gender-neutral than others. My design of the recipe-book becomes part of showing the results since I have based my design-decisions on the results from the literature study and survey.

The thesis deals with Work Instructions from the Perspective of Text Comprehesion. It gives the description of Work Instructions in general, then focuses on two specific kinds of Instructions - Recipes and Consumer Medicine Information. Information about Vocabulary, Syntactics, Semantics, Coreference and Inferences are involved. There is a research of Text Comprehension in the empirical part of this thesis, it is divided into two parts, one for each kind of Instruction. This thesis draws on findings of Czech and foreign linguists.

Este trabalho procura estabelecer a relação entre a vida nas grandes cidades do Sudeste brasileiro, notadamente no Rio de Janeiro e São Paulo, com a prática e a transmissão do saber culinário ao longo do século XX. O momento de formação da classe média brasileira, a oferta de bens de consumo relacionados à modernidade como o fogão a gás, os aparelhos eletrodomésticos e também os alimentos industrializados, somados ao papel atribuído às mulheres na nova ordem social urbana, criaram uma ruptura no modo como as receitas culinárias eram preparadas e transmitidas. Esta ruptura foi seguida de um novo padrão culinário, que por sua vez afetou os valores e a simbologia que permeiam o ato de cozinhar. / This work seeks to establish the relationship between life in the big cities of the Brazilian Southeast, particularly in Rio de Janeiro and São Paulo, and the practice as well as the way culinary knowledge was shared during the 20th century. The moment of formation of the Brazilian middle class, the availability of consumer goods related to modernity, e.g. the gas stove, appliances and industrialized foods, combined with the role attributed to women in the new urban social order, created a rupture in the way culinary recipes were prepared and passed down from one generation to another. This rupture was followed by a new culinary pattern, which in turn affected the values and the symbology comprised in the cooking act.

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