A double-decker bus, an elephant and 300 Girl Guides: analyzing 'space' and 'place' in Blue Peter

This article draws upon Karen Lury's definitions of 'space' and 'place' in relation to the BBC children's programme Blue Peter (1958–present). Through an analysis of the Blue Peter studio over the past 53 years, Amanda Beauchamp highlights its evolution from a 'space' to a 'place' within the history of children's television. Her article considers how the Blue Peter studio's 'infinite nature' was achieved, alongside the role it played in creating the programme institution. She addresses the impact of major changes in the studio layout since 2005, when the studio went from being 'tardis-like' to a 'cosy cubbyhole'. Amanda concludes by questioning the impact that this change has had on programme identity and whether the 'place' that pre-2005 Blue Peter took 47 years to create has been compromised.

Evaluation of reach and grasp robot-assisted therapy suggests similar functional recovery patterns on proximal and distal arm segments in sub-acute hemiplegia

This paper provides some additional evidence in support of the hypothesis that robot therapies are clinically beneficial in neurorehabilitation. Although only 4 subjects were included in the study, the design of the intervention and the measures were done so as to minimise bias. The results are presented as single case studies, and can only be interpreted as such due to the study size. The intensity of intervention was 16 hours and the therapy philosophy (based on Carr and Shepherd) was that coordinated movements are preferable to joint based therapies, and that coordinating distal movements (in this case grasps) helps not only to recover function in these areas, but has greater value since the results are immediately transferable to daily skills such as reach and grasp movements.

Machine learning and small robot navigation

Developing successful navigation and mapping strategies is an essential part of autonomous robot research. However, hardware limitations often make for inaccurate systems. This project serves to investigate efficient alternatives to mapping an environment, by first creating a mobile robot, and then applying machine learning to the robot and controlling systems to increase the robustness of the robot system. My mapping system consists of a semi-autonomous robot drone in communication with a stationary Linux computer system. There are learning systems running on both the robot and the more powerful Linux system. The first stage of this project was devoted to designing and building an inexpensive robot. Utilizing my prior experience from independent studies in robotics, I designed a small mobile robot that was well suited for simple navigation and mapping research. When the major components of the robot base were designed, I began to implement my design. This involved physically constructing the base of the robot, as well as researching and acquiring components such as sensors. Implementing the more complex sensors became a time-consuming task, involving much research and assistance from a variety of sources. A concurrent stage of the project involved researching and experimenting with different types of machine learning systems. I finally settled on using neural networks as the machine learning system to incorporate into my project. Neural nets can be thought of as a structure of interconnected nodes, through which information filters. The type of neural net that I chose to use is a type that requires a known set of data that serves to train the net to produce the desired output. Neural nets are particularly well suited for use with robotic systems as they can handle cases that lie at the extreme edges of the training set, such as may be produced by "noisy" sensor data. Through experimenting with available neural net code, I became familiar with the code and its function, and modified it to be more generic and reusable for multiple applications of neural nets.

Resolución 446(XIX): Lugar y fecha del próximo período de sesiones = Resolution 446(XIX): Date and place of next session = Résolution 446(XIX): Lieu et date de la prochaine session

Publicado separadamete en cada idioma

Resolución 21: Fecha y lugar del Segundo Período de Sesiones = Resolution 21: Time and place of Second Session = Résolution 21: Date et lieu de la Deuxième Session

El símbolo E/840/Rev.1 corresponde a la edición bilingüe inglés/francés publicada en 1953