We present a generative model that efficiently mines transliteration pairs in a consistent fashion in three different settings: unsupervised, semi-supervised, and supervised transliteration mining. The model interpola...
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We present a generative model that efficiently mines transliteration pairs in a consistent fashion in three different settings: unsupervised, semi-supervised, and supervised transliteration mining. The model interpolates two sub-models, one for the generation of transliteration pairs and one for the generation of non-transliteration pairs (i.e., noise). The model is trained on noisy unlabeled data using the EM algorithm. During training the transliteration sub-model learns to generate transliteration pairs and the fixed non-transliteration model generates the noise pairs. After training, the unlabeled data is disambiguated based on the posterior probabilities of the two sub-models. We evaluate our transliteration mining system on data from a transliteration mining shared task and on parallel corpora. For three out of four language pairs, our system outperforms all semi-supervised and supervised systems that participated in the NEWS 2010 shared task. On word pairs extracted from parallel corpora with fewer than 2% transliteration pairs, our system achieves up to 86.7% F-measure with 77.9% precision and 97.8% recall.
This paper describes a 63-participant user study that compares two widely known systems supporting end users in creating trigger-action rules for the Internet of Things and Ambient Intelligence scenarios. The user stu...
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This paper describes a 63-participant user study that compares two widely known systems supporting end users in creating trigger-action rules for the Internet of Things and Ambient Intelligence scenarios. The user study is the first stage of a research agenda that concerns the implementation of a novel conceptual framework for the design and continuous evolution of 'sentient multimedia systems', namely socio-technical systems, where people and many kinds of hardware/software components (sensors, robots, smart devices, web services, etc.) interact with one another through the exchange of multimedia information, to give rise to intelligent, proactive behaviors. The conceptual framework is structured along three layers physical, inference and user - and is based on an information space of events, conditions and actions, linked together in Event-Condition-Action rules and operating according to the interconnection metaphor. The results of the user study have provided some indications for the implementation of the user layer, suggesting which could be the most suitable interaction style for rule design by a community of end users (e.g. a family) and which issues should be addressed in such a wide context.
Motivation: Smoldyn is a spatial and stochastic biochemical simulator. It treats each molecule of interest as an individual particle in continuous space, simulating molecular diffusion, molecule-membrane interactions ...
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Motivation: Smoldyn is a spatial and stochastic biochemical simulator. It treats each molecule of interest as an individual particle in continuous space, simulating molecular diffusion, molecule-membrane interactions and chemical reactions, all with good accuracy. This article presents several new features. Results: Smoldyn now supports two types of rule-based modeling. These are a wildcard method, which is very convenient, and the BioNetGen package with extensions for spatial simulation, which is better for complicated models. Smoldyn also includes new algorithms for simulating the diffusion of surface-bound molecules and molecules with excluded volume. Both are exact in the limit of short time steps and reasonably good with longer steps. In addition, Smoldyn supports single-molecule tracking simulations. Finally, the Smoldyn source code can be accessed through a C/C++ language library interface.
The modeling language ML-rules allows specifying and simulating complex systems biology models at multiple levels of organization. The development of such simulation models involves a wide variety of simulation experi...
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The modeling language ML-rules allows specifying and simulating complex systems biology models at multiple levels of organization. The development of such simulation models involves a wide variety of simulation experiments and the replicability of generated simulation results requires suitable means for documenting simulation experiments. Embedded domain-specific languages, such as SESSL, cater to both requirements. With SESSL, the user can integrate diverse simulation experimentation methods and third-party software components into an executable, readable simulation experiment specification. A newly developed SESSL binding for ML-rules exploits these features of SESSL, opening up new possibilities for executing and documenting simulation experiments with ML-rules models.
This paper describes ImAtHome, an iOS application for smart home configuration and management. This application has been built over the framework HomeKit, made available in iOS, for communicating with and controlling ...
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ISBN:
(纸本)9781891706400
This paper describes ImAtHome, an iOS application for smart home configuration and management. This application has been built over the framework HomeKit, made available in iOS, for communicating with and controlling home automation accessories. Attention has been put on the design of the interaction with such an application, in order to make the interaction style as much coherent as possible with iOS apps and supporting users without programming skills to unwittingly create event-condition action rules that, in other similar systems, are usually defined through "if-then" constructs. The results of a user test demonstrate that ImAtHome is easy to use and well accepted by end users of different age and background.
With the recent widespread adoption of service-oriented architecture, the dynamic composition of services is now a crucial issue in the area of distributed computing. The coordination and execution of composite Web se...
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With the recent widespread adoption of service-oriented architecture, the dynamic composition of services is now a crucial issue in the area of distributed computing. The coordination and execution of composite Web services are today typically conducted by heavyweight centralized workflow engines, leading to an increasing probability of processing and communication bottlenecks and failures. In addition, centralization induces higher deployment costs, such as the computing infrastructure to support the workflow engine, which is not affordable for a large number of small businesses and end-users. In a world where platforms are more and more dynamic and elastic as promised by cloud computing, decentralized and dynamic interaction schemes are required. Addressing the characteristics of such platforms, nature-inspired analogies recently regained attention to provide autonomous service coordination on top of dynamic large scale platforms. In this paper, we propose an approach for the decentralized execution of composite Web services based on an unconventional programming paradigm that relies on the chemical metaphor. It provides a high-level execution model that allows executing composite services in a decentralized manner. Composed of services communicating through a persistent shared space containing control and data flows between services, our architecture allows to distribute the composition coordination among nodes. A proof of concept is given, through the deployment of a software prototype implementing these concepts, showing the viability of an autonomic vision of service composition.
BioNetGen is an open-source software package for rule-based modeling of complex biochemical systems. Version 2.2 of the software introduces numerous new features for both model specification and simulation. Here, we r...
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BioNetGen is an open-source software package for rule-based modeling of complex biochemical systems. Version 2.2 of the software introduces numerous new features for both model specification and simulation. Here, we report on these additions, discussing how they facilitate the construction, simulation and analysis of larger and more complex models than previously possible. Availability and Implementation: Stable BioNetGen releases (Linux, Mac OS/X and Windows), with documentation, are available at http://***. Source code is available at http://***/ruleWorld/bionetgen. Contact: bionetgen. help@*** Supplementary information: Supplementary data are available at Bioinformatics online.
In recent days, a lot of appliances with a processor and communication function are developed along the progress of computer technology. They are expected to support our daily life with their cooperation on home netwo...
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ISBN:
(纸本)9781509016365
In recent days, a lot of appliances with a processor and communication function are developed along the progress of computer technology. They are expected to support our daily life with their cooperation on home network. Since everyone has own lifestyles and demands, building a program on the network by residents themselves is necessary for obtaining appropriate supports. However, it is quite difficult for general people to build an own program. In this study, thus, we propose a method to build a simple program in which appliances cooperate using a colloquial instruction sentence. Our method defines an event and an action of ECA rule, which works on each appliance, by selecting pre-defined clauses in natural language, as well as automatically assigns corresponding appliances. The usability evaluation showed that our method ease a program cooperating appliances.
[Auto Generated] page ACKNOWLEDGMENTS iv LIST OF TABLES vii LIST OF FIGURES viii ABSTRACT x LINTRODUCTION: THE TRIGGERMAN PROJECT 1 1 . 1 rules and Active Databases Overview: 1 L L 1 Integrity Constraint Checking and ...
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[Auto Generated] page ACKNOWLEDGMENTS iv LIST OF TABLES vii LIST OF FIGURES viii ABSTRACT x LINTRODUCTION: THE TRIGGERMAN PROJECT 1 1 . 1 rules and Active Databases Overview: 1 L L 1 Integrity Constraint Checking and Repair: 1 1.1.2 Time and Temporal Issues: 2 1.1.3 Materialized View Maintenance: 3 1.1.4 Advantages and Shortcomings of Existing rule Systems: 4 1.2 Extensibility and Extensible Databases Background: 6 1.3 TriggerMan: 9 1.3.1 The TriggerMan Environment: 11 1.3.2 The TriggerMan Physi
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