Search results for "computer.software_genre"
showing 10 items of 3858 documents
Editor Definition Language and Its Implementation
2001
Universal graphical editor definition language based on logical metamodel extended by presentation classes is proposed. Implementation principles of this language, based on Graphical Diagramming Engine are described.
System aspects of sharing a virtual reality
1998
We have recently held the second annual "System Aspects of Sharing a Virtual Reality" workshop, in conjunction with CVE '98 (see report in this issue). The single-day format allowed for twelve presentations plus discussion, which are summarized below. The topics addressed were: designing systems to cope with network limitations; managing communication and information; the construction of systems and toolkits; issues of presentation and user interaction; and application development and evaluation.
Hyplets - Multi Exception Level Kernel towards Linux RTOS
2018
This paper presents the concept of a Multi-Exception level operating system. We add a hypervisor awareness to the Linux kernel and execute code in hyp exception level. We do that through the use of Hyplets. Hyplets are an innovative way to code interrupt service routines under ARM. Hyplets provide high performance, security, running time predictability, an RPC mechanism and a possible solution for the priority inversion problem. Hyplets uses special features of ARM8va hypervisor memory architecture.
A novel scheme for privacy preserving in RBAC
2013
Role Based Access Control (RBAC) Model has been proved to be quite useful and has drawn a lot of research interest over the last fifteen years. In this paper we discuss general context-aware RBAC model. We analyze potential privacy threats associated with use of context-aware RBAC and propose a novel scheme that provides privacy-preserving for access models based on RBAC.
Spoken conversational context improves query auto-completion in web search
2021
Web searches often originate from conversations in which people engage before they perform a search. Therefore, conversations can be a valuable source of context with which to support the search process. We investigate whether spoken input from conversations can be used as a context to improve query auto-completion. We model the temporal dynamics of the spoken conversational context preceding queries and use these models to re-rank the query auto-completion suggestions. Data were collected from a controlled experiment and comprised conversations among 12 participant pairs conversing about movies or traveling. Search query logs during the conversations were recorded and temporally associated…
Structural Knowledge Extraction from Mobility Data
2016
Knowledge extraction has traditionally represented one of the most interesting challenges in AI; in recent years, however, the availability of large collections of data has increased the awareness that “measuring” does not seamlessly translate into “understanding”, and that more data does not entail more knowledge. We propose here a formulation of knowledge extraction in terms of Grammatical Inference (GI), an inductive process able to select the best grammar consistent with the samples. The aim is to let models emerge from data themselves, while inference is turned into a search problem in the space of consistent grammars, induced by samples, given proper generalization operators. We will …
A Approach to Clinical Proteomics Data Quality Control and Import
2011
International audience; Biomedical domain and proteomics in particular are faced with an increasing volume of data. The heterogeneity of data sources implies heterogeneity in the representation and in the content of data. Data may also be incorrect, implicate errors and can compromise the analysis of experiments results. Our approach aims to ensure the initial quality of data during import into an information system dedicated to proteomics. It is based on the joint use of models, which represent the system sources, and ontologies, which are use as mediators between them. The controls, we propose, ensure the validity of values, semantics and data consistency during import process.
CheS-Mapper - Chemical Space Mapping and Visualization in 3D
2012
Abstract Analyzing chemical datasets is a challenging task for scientific researchers in the field of chemoinformatics. It is important, yet difficult to understand the relationship between the structure of chemical compounds, their physico-chemical properties, and biological or toxic effects. To that respect, visualization tools can help to better comprehend the underlying correlations. Our recently developed 3D molecular viewer CheS-Mapper (Chemical Space Mapper) divides large datasets into clusters of similar compounds and consequently arranges them in 3D space, such that their spatial proximity reflects their similarity. The user can indirectly determine similarity, by selecting which f…
Stochastic model predicts evolving preferences in the Iowa gambling task
2014
Learning under uncertainty is a common task that people face in their daily life. This process relies on the cognitive ability to adjust behavior to environmental demands. Although the biological underpinnings of those cognitive processes have been extensively studied, there has been little work in formal models seeking to capture the fundamental dynamic of learning under uncertainty. In the present work, we aimed to understand the basic cognitive mechanisms of outcome processing involved in decisions under uncertainty and to evaluate the relevance of previous experiences in enhancing learning processes within such uncertain context. We propose a formal model that emulates the behavior of p…
Learning Behavioral Rules from Multi-Agent Simulations for Optimizing Hospital Processes
2021
Hospital processes are getting more and more complex, starting from the creation of therapy plans over intra-hospital transportation up to the coordination of patients and staff members. In this paper, multi-agent simulations will be used to optimize the coordination of different kinds of individuals (like patients and doctors) in a hospital process. But instead of providing results in form of optimized schedules, here, behavioral rules for the different individuals will be learned from the simulations, that can be exploited by the individuals to optimize the overall process. As a proof-of-concept, the approach will be demonstrated in different variants of a hospital optimization scenario, …