Modular product development for mass customization

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Use of machine learning techniques in the Kansei engineering synthesis phase

Una de las principales metodologías para el diseño emocional de productos es la ingeniería Kansei. En esta técnica se pretende relacionar las propiedades del producto o servicio con las sensaciones percibidas por los usuarios. Una aplicación clásica de esta metodología requiere distintas fases entre la que se encuentran la elección del dominio del diseño, la definición del espacio semántico y de propiedades, la síntesis, la validación y la construcción del modelo. La popularización de las técnicas de inteligencia artificial, entre las que se encuentra el aprendizaje automático, ha llevado a muchos autores a utilizar estas herramientas en la fase de síntesis. En este trabajo se analizan las principales herramientas de aprendizaje automático usadas en la fase de síntesis de ingeniería kansei, así como la adecuación de su uso, en base al espacio de propiedades previamente definido.Kansei engineering is one of the main methodologies for the emotional design of products. This technique aims to relate the properties of the product or service to the sensations perceived by users. A classic application of this methodology requires different phases, among which are the choice of the product domain, the definition of the semantic space and properties, the elaboration of the synthesis, the validation and the construction of the model and validation. The popularization of artificial intelligence techniques, including machine learning, has led many authors to use these mathematical models in the synthesis phase. This paper analyses the main machine learning tools used in the synthesis phase of kansei engineering, as well as the relevance of their use, based on the property space previously described

Backwards is the way forward: feedback in the cortical hierarchy predicts the expected future

Clark offers a powerful description of the brain as a prediction machine, which offers progress on two distinct levels. First, on an abstract conceptual level, it provides a unifying framework for perception, action, and cognition (including subdivisions such as attention, expectation, and imagination). Second, hierarchical prediction offers progress on a concrete descriptive level for testing and constraining conceptual elements and mechanisms of predictive coding models (estimation of predictions, prediction errors, and internal models)

Affective design using machine learning : a survey and its prospect of conjoining big data

Customer satisfaction in purchasing new products is an important issue that needs to be addressed in today’s competitive markets. Consumers not only need to be solely satisfied with the functional requirements of a product, and they are also concerned with the affective needs and aesthetic appreciation of the product. A product with good affective design excites consumer emotional feelings so as to buy the product. However, affective design often involves complex and multi-dimensional problems for modelling and maximising affective satisfaction of customers. Machine learning is commonly used to model and maximise the affective satisfaction, since it is effective in modelling nonlinear patterns when numerical data relevant to the patterns is available. This article presents a survey of commonly used machine learning approaches for affective design when two data streams namely traditional survey data and modern big data are used. A classification of machine learning technologies is first provided which is developed using traditional survey data for affective design. The limitations and advantages of each machine learning technology are also discussed and we summarize the uses of machine learning technologies for affective design. This review article is useful for those who use machine learning technologies for affective design. The limitations of using traditional survey data are then discussed which is time consuming to collect and cannot fully cover all the affective domains for product development. Nowadays, big data related to affective design can be captured from social media. The prospects and challenges in using big data are discussed so as to enhance affective design, in which very limited research has so far been attempted. This article provides guidelines for researchers who are interested in exploring big data and machine learning technologies for affective design

Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input. A survey of NLG is timely in view of the changes that the field has undergone over the past decade or so, especially in relation to new (usually data-driven) methods, as well as new applications of NLG technology. This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of relatively recent research topics that have arisen partly as a result of growing synergies between NLG and other areas of artificial intelligence; (c) draw attention to the challenges in NLG evaluation, relating them to similar challenges faced in other areas of Natural Language Processing, with an emphasis on different evaluation methods and the relationships between them.Comment: Published in Journal of AI Research (JAIR), volume 61, pp 75-170. 118 pages, 8 figures, 1 tabl

The role of sensescapes in tourist experiences in rural areas

Tese de doutoramento, Turismo, Faculdade de Economia, Universidade do Algarve, 2013The sensory appealing of destinations has recently been in focus as an important dimension in the process of facilitating positive and memorable tourist experiences. Particularly, the countryside embraces local resources rich in multi-sensory effects that could be explored in the planning and marketing of stimulating tourist experiences addressed to segments of tourists suitable for sustainable local development. Despite being well documented that the so-called five senses – sight, hearing, smell, taste, and touch – influence human perception, memory, and behavior, research following a holistic approach to all modalities of sensory experiences in tourism, specifically in rural destinations, is still scarce. In this light, this thesis encloses four studies aiming to explore the role of sensescapes in tourist experiences in rural areas. The first study explores the conceptualization of the sensory dimension of tourist experiences by discussing its theoretical underpinnings. The second study presents a conceptual framework intended to support the appropriateness of the research on sensory experiences as perceived by tourists and resulting contribute to marketing sustainable sensory-themed tourist experiences in rural destinations. Subsequently, study three shows through a questionnaire presented to tourists in rural lodgings in Southwest Portugal that reported sensory experiences could be used to capture meaningful sensory-based themes adequate for segmenting tourists and tangibilize tourist offerings based on sensory experiences. Study four uses a two-step process of data collection, conducted in loco and six months after the tourists’ visit to Southwest Portugal, revealing that richer sensory tourist experiences may have an important role in the long-term memory of individuals’ experiences, potentiating favorable tourist behavior with respect to rural destinations loyalty. Overall, the results corroborate the importance of the sensory dimension for individuals’ likelihood of having a positive and memorable tourist experience, as well as the potential of using sensory stimuli in marketing tourist experiences in rural destinations.A importância dos cinco sentidos humanos – visão, audição, olfato, paladar e tato – no marketing de experiências turísticas positivas e memoráveis tem vindo a ser enfatizada no âmbito da investigação em turismo. Particularmente, a vulnerabilidade e riqueza multissensorial dos recursos endógenos oferecidos nas áreas rurais (ex. fauna, flora, gastronomia), com características divergentes do ambiente urbano e potenciadoras de atividades ligadas à natureza e à vida rural, justificam um estudo atento da experiência sensorial turística em destinos rurais. Neste contexto, é evidenciado o papel dos sentidos humanos no planeamento e marketing de experiências turísticas especialmente dirigidas a segmentos de turistas que potenciem o desenvolvimento sustentável das áreas rurais. Apesar de estar bem documentada na literatura a influência de todos os sentidos na perceção, memória e comportamento dos indivíduos, e por consequência no comportamento de consumo, assiste-se a uma escassez de estudos que abordem a importância dos cinco sentidos na experiência turística de uma forma holística, particularmente em destinos rurais. Assim, para além da paisagens visuais, que têm sido mais estudadas, diversos autores sugerem que a investigação na área do turismo inclua também as experiências auditivas, olfativas, gastronómicas e táteis. Desta forma, a presente tese compreende quatro estudos com o objetivo de explorar o papel da dimensão sensorial da experiência turística em áreas rurais, com uma abordagem póspositivista e uma perspetiva de marketing. O primeiro estudo contribui para a conceptualização da dimensão sensorial da experiência turística, através da discussão de uma revisão de literatura multidisciplinar, assim como para a identificação de tópicos de investigação pouco explorados com potencial interessante para investigação futura. O segundo estudo apresenta um instrumento conceptual com o objetivo de mostrar a relevância do estudo de experiências sensoriais relatadas por turistas e o respetivo contributo na definição de temas multissensoriais adequados ao marketing de experiência turísticas em destinos rurais. O terceiro artigo é de natureza empírica e revela, através de um questionário aplicado a turistas que pernoitaram em alojamentos de espaço rural da Costa Alentejana e Vicentina de Portugal, que o estudo de experiências sensoriais relatadas por visitantes xiiié adequado ao processo de segmentação de turistas e na definição de uma oferta turística com base em experiências multissensoriais em áreas rurais. No caso particular em estudo, quatro temas sensoriais são sugeridos através de uma análise de correspondência múltiplas, traduzindo-se em quatro segmentos de turistas com perfis distintos, com base nas atividades desenvolvidas no destino e nas motivações dos participantes para a escolha do destino de férias. Os quatro temas identificados dizem respeito a experiências especificamente rurais, experiências globais do destino com especial foco nas atividades relacionadas com a praia, experiências de natureza e experiências de natureza espiritual. O quarto estudo é empírico e recorre a dados recolhidos junto de turistas in loco, assim como seis meses após a visita ao Sudoeste de Portugal. Os resultados permitem concluir que experiências sensorialmente mais ricas têm um papel importante na memória a longo-prazo de experiências turísticas, promovendo um comportamento mais favorável dos visitantes em relação aos destinos rurais, no que diz respeito à recomendação e revisita por parte de turistas, o que sugere uma ligação entre a dimensão sensorial da experiência turística em destinos rurais e a fidelização ao destino. No geral, os resultados permitem corroborar a importância dos sentidos para os indivíduos viverem uma experiência turística positiva e memorável, assim como o potential do uso de estímulos sensoriais no marketing de experiências turísticas em ambientes rurais