Implementation Analysis of Curriculum 2013 Towards Interactive Learning Aspects and Multimedia-Based Learning

This research aims to determine the application of interactive and multimedia-based learning which conducted by the teachers from office administration in state vocational high school 2 Blitar. This research is qualitative research then the subjects are the teachers’ expertise of administrative programs, vice principal of curriculum and students. Data collection techniques used observation, interviews, and documentation. The results of this research are (1) interactive learning have been implemented, (2) Multimedia-Based learning has been implemented, but it is needed for developing the multimedia which used for teaching process.It can be seen that the teacher conducts learning in accordance with interactive learning indicators. The implementation of the curriculum 2013 for aspects of multimedia-based learning has been carried out by teachers by implementing learning that contains multimedia-based learning indicators

Special Issue IEEE International Conference on Pervasive Computing and Communications (PerCom) 2016

The special issue of Pervasive and Mobile Computing published papers from the IEEE International Conference on Pervasive Computing and Communications (PerCom) 2016. The PerCom 2016 call for papers invited contributions on communication, applications, system software, data management, and other aspects related to pervasive computing. The resulting conference program provided insight into the state of the art in pervasive computing through peer-reviewed full and short papers. Out of 168 submissions, 20 full papers and 5 concise contributions were accepted. All invited contributions were required to included at least 30% new content and went through a second peer review process. Ten papers were accepted to the special issue, with a wide range of topics

Sistema de recomendação de serviços para uma cidade inteligente

Cidades Inteligentes são espaços complexos com variedade de informações, no qual os cidadãos podem ter acesso, sejam eles visitantes ou residentes. Denominado de pontos de interesse (POIs) as informações relacionadas a uma cidade, estando estes POIs espalhados ou concentrados no mesmo local. Ao buscar interesses, o usuário utiliza meios tradicionais de pesquisa, que por vezes não retornam exatamente o local ou serviço desejado. Visando melhorar o resultado da busca, foi utilizado um modelo ontológico, através de um estudo de caso, adicionando dados da cidade de Cotiporã/RS. Através deste estudo é possível mostrar que uma das formas de se modelar um sistema de recomendação é com base nas ontologias. Essas melhoram a semântica e criam uma padronização na web para facilitar o compartilhamento do conhecimento. A abordagem desenvolvida tem por objetivo recomendar POIs turísticos e serviços da área da saúde. Para avaliar o protótipo, foram desenvolvidas regras SWRL inferidas utilizando o motor de inferências Pellet, onde, baseado nas preferências do usuário, o protótipo retorna o resultado da busca efetuada através da localização do usuário, apresentando na interface. Com esta proposta é possível continuar o projeto ampliando os filtros de recomendação para outros setores e ampliar o projeto para outras cidades.Smart Cities are complex spaces with a variety of information, which citizens can access, whether they are visitors or residents. Information related to a city is referred to as points of interest (POIs), these POIs being scattered or concentrated in the same location. When seeking interests, the user uses traditional means of research, which sometimes do not return exactly the desired location or service. To improve the search result, an ontological model was used, through a case study, adding data from the city of Cotiporã / RS. Through this study it is possible to show that one of the ways to model a recommendation system is based on ontologies. These improve semantics and create a standardization on the web to facilitate knowledge sharing. The developed approach aims to recommend tourist POIs and health services. To evaluate the prototype, SWRL rules developed using the Pellet inferences engine were developed, where, based on the user's preferences, the prototype returns the search result made through the user's location, presenting it on the interface. With this proposal it is possible to continue the project by expanding the recommendation filters to other sectors and to expand the project to other cities