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Doll and robot are effective and beneficial non-pharmacological therapies applied in different clinical settings. Doll therapy (DT), principally based in Bowlby's attachment theory, uses an empathy or lifelike baby doll to conduct caring behaviors of it. Robot therapies (RT) use care robots with a friendly attitude and appearance that create emotions and movements that lead to different verbal, motor and emotional reactions. Both DT and RT are person-centred therapies that aim to improve wellbeing of people that suffer from different neurological, psychological and mental health disorders, such as Alzheimer's Disease, autism spectrum disorder, stress or depression, by providing a realistic experience. In this paper, the characteristics of both therapies, their benefits and the possibilities of innovation in the therapeutic field are presented.

[EN] With bore fields for energy extraction and injection, it is often necessary to predict the temperature response to heat loads for many years ahead. Mathematical methods, both analytical and numerical, with different degrees of sophistication, are employed. Often the g-function concept is used, in which the borehole wall is assumed to have a uniform temperature and the heat injected is constant over time. Due to the unavoidable thermal resistance between the borehole wall and the circulating fluid and with varying heat flux along the boreholes, the concept of uniform borehole wall temperature is violated, which distorts heat flow distribution between boreholes. This aspect has often been disregarded. This paper describes improvements applied to a previous numerical model approach. Improvements aim at taking into account the effect of thermal resistance between the fluid and the borehole wall. The model employs a highly conductive material (HCM) embedded in the boreholes and connected to an HCM bar above the ground surface. The small temperature difference occurring within the HCM allows the ground to naturally control the conditions at the wall of all boreholes and the heat flow distribution to the boreholes. The thermal resistance between the fluid and the borehole wall is taken into account in the model by inserting a thermally resistive layer at the borehole wall. Also, the borehole ends are given a hemispherical shape to reduce the fluctuations in the temperature gradients there. The improvements to the HCM model are reflected in a changed distribution of the heat flow to the different boreholes. Changes increase with the number of boreholes. The improvements to the HCM model are further illustrated by predicting fluid temperatures for measured variable daily loads of two monitored GCHP installations. Predictions deviate from measured values with a mean absolute error within 1.1 and 1.6¿K., The Swedish Energy Agency is acknowledged for financing this project. The authors thank Massimo Cimmino (Ecole Polytechnique de Montreal, Canada) for contributing to the generation of a particular solution with his approach.

Indoor positioning technology is commercially available now, however, the positioning accuracy is not sufficient in the current technologies. Currently available indoor positioning technologies differ in terms of accuracy, costs and effort, but have improved quickly in the last couple of years. It has been actively conducted research for estimating indoor location using RSSI (Received Signal Strength Indicator) level of Wi-Fi access points or BLE (Bluetooth Low Energy) tags. WiFi signal is commonly used for the indoor positioning technology. However, It requires an external power source, more setup costs and expensive. BLE is inexpensive, small, have a long battery life and do not require an external energy source. Therefore, using BLE tags we might be able to make the positioning system practical and inexpensive way. In this paper, we investigate such practical type of indoor positioning method based on BLE. BLE RSSI are processed by Multilayer Perceptron(MLP). Also, compass data and walking speed estimation with an extended Kalman filter is used to improve the accuracy. Our preliminary experimental result shows 2.21m error in case of the MLP output. In preliminary experimental results, the proposed approach improved the accuracy of indoor positioning by 21.2%.