How to ... be a reflective practitioner.

Sustainable Development Goals

Proceedings of world academy of science, engineering and technology, vol 8

The Wealth of Knowledge: Intellectual Capital and the Twenty‐First Century Organization

This paper addresses the problem of path prediction for multiple interacting agents in a scene, which is a crucial step for many autonomous platforms such as self-driving cars and social robots. We present \textit{SoPhie}; an interpretable framework based on Generative Adversarial Network (GAN), which leverages two sources of information, the path history of all the agents in a scene, and the scene context information, using images of the scene. To predict a future path for an agent, both physical and social information must be leveraged. Previous work has not been successful to jointly model physical and social interactions. Our approach blends a social attention mechanism with a physical attention that helps the model to learn where to look in a large scene and extract the most salient parts of the image relevant to the path. Whereas, the social attention component aggregates information across the different agent interactions and extracts the most important trajectory information from the surrounding neighbors. SoPhie also takes advantage of GAN to generates more realistic samples and to capture the uncertain nature of the future paths by modeling its distribution. All these mechanisms enable our approach to predict socially and physically plausible paths for the agents and to achieve state-of-the-art performance on several different trajectory forecasting benchmarks.

SoPhie: An Attentive GAN for Predicting Paths Compliant to Social and Physical Constraints.

In the rapidly developing space of novel technologies that combine sensing and semantic technologies, research on smart products has the potential of establishing a research field in itself. In this paper, we synthesize existing work in this area in order to define and characterize smart products. We then reflect on a set of challenges that semantic technologies are likely to face in this domain. Finally, in order to initiate discussion in the workshop, we sketch an initial comparison of smart products and semantic sensor networks from the perspective of knowledge technologies.

Position paper on realizing smart products : challenges for semantic web technologies

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Position paper on realizing smart products: challenges for semantic web technologies

Purpose – The purpose of this paper is to create new ideas for assistive technology products at home, especially products utilizing robotic consumer appliances available in the homes of elderly people. The work was founded on a reported increase in household robots as well as an ageing population in the industrialized world. Design/methodology/approach – Technology should be something that is perceived as belonging to our own world that fits our daily practices. Earlier studies show that in addition to cleaning functions, new household robots could change home routines and people's relationship to them. Taking the previous studies as a starting point, the paper proposes a vacuum cleaner robot as a platform for developing pervasive safety services and describe implementation of a conceptual prototype which brings the feeling of safety to an older person and their relatives by assisting in case of accidents. Moreover, the results are presented of an empirical evaluation of the prototype with end-users. Find...

An assistive household robot – doing more than just cleaning

Cooking assistant is an application that needs to find a trade-off between providing efficient help to the users (e.g., reminding them to stir a meal if it is about to burn) and avoiding users' annoyance. This trade-off may vary in different contexts, such as cooking alone or in a group, cooking new or known recipe etc. The results of the user study, presented in this paper, show which features of a multimodal interface users perceive as socially acceptable or unacceptable in different situations, and how this perception depends on user's age.

Designing socially acceptable multimodal interaction in cooking assistants

Data mining is the process of extracting hidden knowledge from data. As more data is gathered, data mining is becoming an increasingly important tool to transform this data into information. Visualization is central to data mining. Information visualization is the process of turning abstract data into a visual shape easily understood by the user, making it possible for him/her to generate new knowledge about the relations between the data. Ontologies represent a shared meaning of a domain and they can be used to describe almost any kind of domain concepts explicitly including their terms, attributes, values and relationships facilitating the communication between people and application systems. Leveraging the power of semantic technologies, ontology based data mining and recent trends in information visualization, this work presents the approach towards the management of multi-dimensional often temporal heterogeneous home data.

Julia Kantorovitch

Papers

Position paper on realizing smart products : challenges for semantic web technologies

Position paper on realizing smart products: challenges for semantic web technologies

An assistive household robot – doing more than just cleaning

Designing socially acceptable multimodal interaction in cooking assistants

Ontology driven data mining and information visualization for the networked home