| 1. |
- Baldoni, R., et al.
(författare)
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An embedded middleware platform for pervasive and immersive environments for-all
- 2009
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Ingår i: 2009 6th IEEE Annual Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks Workshops, SECON Workshops 2009. - : IEEE. - 9781424439386 ; , s. 161-163
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Konferensbidrag (refereegranskat)abstract
- Embedded systems are specialized computers used in larger systems or machines to control equipments such as automobiles, home appliances, communication, control and office machines. Such pervasivity is particularly evident in immersive realities, i.e., scenarios in which invisible embedded systems need to continuously interact with human users, in order to provide continuous sensed information and to react to service requests from the users themselves. The SM4All project investigates an innovative middleware platform for inter-working of smart embedded services in immersive and person-centric environments, through the use of composability and semantic techniques for dynamic service reconfiguration. This is applied to the challenging scenario of private houses and home-care assistance in presence of users with different abilities and needs (e.g., young, able-bodied, aged and disabled). This paper presentes a brief overview of the SM4All system architecture.
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| 2. |
- Li, Fei, et al.
(författare)
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Proactive Service Discovery in Pervasive Environments
- 2010
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Ingår i: Proceedings of the 7th ACM International Conference on Pervasive Services (ICPS). ; , s. 126-133
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Konferensbidrag (refereegranskat)abstract
- Pervasive environments are characterized by rich and dy-namic context, where users need to be continuously informed about services relevant to their current context. Implicit discovery requests, triggered by changes of user context, avail-able services, or user preferences are prevalent in such environments.This paper proposes a proactive service discovery approach for pervasive environments to address these implicit requests. Services and user preferences are described by a formal context model, which effectively captures the dynamics of context and the relationship between services and users. Based on the model, we propose a proactive discovery algorithm to continuously present the most relevant services to the user in response to changes of context, services or user preferences. Numeric coding methods are applied in different phases of the algorithm to improve its performance. A proactive service discovery system is proposed and the context model is grounded in a smart home environment. Experimental results show that our approach can efficiently provide the user with up-to-date information about useful services.
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| 3. |
- Li, F., et al.
(författare)
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Unsupervised context-aware user preference mining
- 2013
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Ingår i: Proceeding of Workshop on Activity Context-Aware System Architectures at the 27th AAAI Conference on Artificial Intelligence. - 9781577356165 ; , s. 36-43
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Konferensbidrag (refereegranskat)abstract
- In pervasive environments, users are situated in rich context and can interact with their surroundings through various services. To improve user experience in such environments, it is essential to find the services that satisfies user preferences in certain context. Thus the suitability of discovered services is highly dependent on how much the context-aware system can understand users' current context and preferred activities. In this paper, we propose an unsupervised learning solution for mining user preferences from the user's past context. To cope with the high dimensionality and heterogeneity of context data, we propose a subspace clustering approach that is able to find user preferences identified by different feature sets. The results of our approach are validated by a series of experiments.
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| 4. |
- Rasch, Katharina
(författare)
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An unsupervised recommender system for smart homes
- 2014
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Ingår i: Journal of Ambient Intelligence and Smart Environments. - 1876-1364 .- 1876-1372. ; 6:1, s. 21-37
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Tidskriftsartikel (refereegranskat)abstract
- Inhabitants of today's smarter homes struggle with complicated user interfaces and inflexible home configurations. The proposed smart home recommender system addresses these issues by continuously interpreting the user's current situation and recommending services that fit the user's habits, i.e. automate some action that the user would want to perform anyway. With these recommendations it is possible to build much simpler user interfaces that highlight the most interesting choices currently available. Configuration becomes much more flexible, since the recommender system automatically learns user habits. Evaluations on two smart home datasets show that the algorithm produces correct recommendations with 61% and 73% accuracy, respectively.
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| 5. |
- Rasch, Katharina, et al.
(författare)
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Automatic description of context-altering services through observational learning
- 2012
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Ingår i: Pervasive Computing. - Berlin, Heidelberg : Springer Berlin/Heidelberg. - 9783642312045 ; , s. 461-477
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Konferensbidrag (refereegranskat)abstract
- Understanding the effect of pervasive services on user context is critical to many context-aware applications. Detailed descriptions of context-altering services are necessary, and manually adapting them to the local environment is a tedious and error-prone process. We present a method for automatically providing service descriptions by observing and learning from the behavior of a service with respect to its environment. By applying machine learning techniques on the observed behavior, our algorithms produce high quality localized service descriptions. In a series of experiments we show that our approach, which can be easily plugged into existing architectures, facilitates context-awareness without the need for manually added service descriptions.
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| 6. |
- Rasch, Katharina, 1982-, et al.
(författare)
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Context-driven personalized service discovery in pervasive environments
- 2011
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Ingår i: World wide web (Bussum). - MA, USA : Kluwer Academic Publishers Hingham. - 1386-145X .- 1573-1413. ; 14:4, s. 295-319
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Tidskriftsartikel (refereegranskat)abstract
- Pervasive environments are characterized by a large number of embedded devices offering their services to the user .Which of the available services are of most interest to the user considerably depends on the user’s current context. User context is often rich and very dynamic; making an explicit, user-driven discovery of services impractical. Users in such environments would instead like to be continuously informed about services relevant to them. Implicit discovery requests triggered by changes in the context are therefore prevalent. This paper proposes a proactiveservice discovery approach for pervasive environments addressing these implicit requests. Services and user preferences are described by a formal context modelcalled Hyperspace Analogue to Context, which effectively captures the dynamics of context and the relationship between services and context. Based on the model, we propose a set of algorithms that can continuously present the most relevant services to the user in response to changes of context, services or user preferences. Numeric coding methods are applied to improve the algorithms’ performance. The algorithms are grounded in a context-driven service discovery system that automatically reacts to changes in the environment. New context sources and services can be dynamically integrated into the system. A client for smart phones continuously informs users about the discovery results. Experiments show, that the system can efficiently provide the user with continuous, up-to-date information about the most useful services in real time.
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| 7. |
- Rasch, Katharina, 1982-
(författare)
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Plug and play context-awareness for pervasive environments
- 2011
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Pervasive environments are physical environments interwoven with a rich set of embedded sensors, actuators and displays offering their services to the user. The considerable amount of computing technology in such environments should be as unobtrusive as possible, aiding the user in everyday activities instead of being distracting. Context-awareness, i.e. the adaptiveness of the environment to the current situation of the user, is of tremendous importance for achieving the desired unobtrusiveness. This licentiate dissertation begins by looking at one aspect of pervasive systems where user experience can be considerably improved through context-awareness: of the thousands of services that may be available in a pervasive environment, only a small percentage will be of interest to the user in any given situation. Instead of having to issue explicit service discovery requests, users would like to be continuously informed about services relevant to them, depending on their current context and their preferences. In this dissertation a proactive service discovery approach for pervasive environments is proposed that addresses these implicit discovery requests. Services and user preferences are described by a formal context model which can effectively capture the dynamics of context and the relationship between services and context. Based on this model a set of algorithms is described that can continuously identify the services most relevant to the user in near real time. Proactive service discovery presumes detailed descriptions of user preferences and service capabilities. Manually providing this information is tedious and error-prone, hindering the adoption of the technology by non-expert users. In the second part of this dissertation it is shown how user preferences can instead be automatically identified by studying the user's interaction with the system. Furthermore an approach is presented for automatically providing service descriptions by observing the conditions under which services are executed and the typical effects they induce in the environment. By applying machine-learning techniques such as subspace clustering and classification on the observed data, these approaches are able to produce high-quality descriptions for both user preferences and service capabilities, without any need for manual annotation. Based on these results it is shown how discovery and learning algorithms can be seamlessly integrated into existing pervasive environments to provide plug and play context-awareness.
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| 8. |
- Rasch, Katharina, 1982-
(författare)
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Smart assistants for smart homes
- 2013
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The smarter homes of tomorrow promise to increase comfort, aid elderly and disabled people, and help inhabitants save energy. Unfortunately, smart homes today are far from this vision – people who already live in such a home struggle with complicated user interfaces, inflexible home configurations, and difficult installation procedures. Under these circumstances, smart homes are not ready for mass adoption.This dissertation addresses these issues by proposing two smart assistants for smart homes. The first assistant is a recommender system that suggests useful services (i.e actions that the home can perform for the user). The recommended services are fitted to the user’s current situation, habits, and preferences. With these recommendations it is possible to build much simpler user interfaces that highlight the most interesting choices currently available. Configuration becomes much more flexible: since the recommender system automatically learns user habits, user routines no longer have to be manually described. Evaluations with two smart home datasets show that the correct service is included in the top five recommendations in 90% of all cases.The second assistant addresses the difficult installation procedures. The unique feature of this assistant is that it removes the need for manually describing device functionalities (such descriptions are needed by the recommender system). Instead, users can simply plug in a new device, begin using it, and let the installation assistant identify what the device is doing. The installation assistant has minimal requirements for manufacturers of smart home devices and was successfully integrated with an existing smart home. Evaluations performed with this smart home show that the assistant can quickly and reliably learn device functionalities.
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| 9. |
- Rasch, Katharina, et al.
(författare)
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The Chemomentum Data Services - A Flexible Solution for Data Handling in UNICORE
- 2008
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Ingår i: EURO-PAR 2008 WORKSHOPS - PARALLEL PROCESSING. - Berlin, Heidelberg : Springer Berlin Heidelberg. ; , s. 84-93
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Konferensbidrag (refereegranskat)abstract
- This paper introduces the Chemomentum data services, a UNICORE-based flexible solution for managing large amounts of data and metadata produced in a Grid. In order to store and manage the increasing amounts of data produced in Grid environments, a highly scalable and distributed Grid storage system is needed. However, the simple storage of data is not enough. To allow a comfortable browsing and retrieving of the data, it is crucial that files are indexed and augmented with metadata. This paper analyses integrated solutions that already provide these functionalities for their features and shortcomings. Incorporating the conclusions drawn from the examination, an architecture for a revised data management solution is presented. This system provides the means to store files with augmenting extensible metadata. It allows also to browse through data using metadata, handle ontologies and transparently access external data sources. In the current stage, most of these functionalities are implemented and running in a distributed environment.
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| 10. |
- Schuller, Bernd, et al.
(författare)
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Chemomentum - UNICORE 6 Based Infrastructure for Complex Applications in Science and Technology
- 2008
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Ingår i: Euro-Par 2007 Workshops. - Berlin, Heidelberg : Springer Berlin Heidelberg. ; , s. 82-93
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Konferensbidrag (refereegranskat)abstract
- Chemomentum, Grid Services based Environment to enable Innovative Research, is an end-user focused approach to exploit Grid computing for diverse application domains. Building on top of UNICORE 6, we are designing and implementing a flexible, user-friendly Grid system focussing on high-performance processing of complex application workflows and management of data, metadata and knowledge. This paper outlines Chemomentum vision, application scenarios, technical challenges, software architecture and design of the system.
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| 11. |
- Seifert, Frank, et al.
(författare)
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Tempo Induction by Stream-Based Evaluation of Musical Events
- 2006
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Ingår i: ISMIR 2006. ; , s. 344-345
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Konferensbidrag (refereegranskat)abstract
- We present an approach for tempo induction that is based on a more perception-oriented analysis of inter-onset intervals. Therefore we utilize auditory grouping concepts and define some rules for their formation. Finally, we show preliminary results that confirm our aim of improving the quality of tempo induction by reducing the amount of perceptually irrelevant data.
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