this paper presents a novel parallel algorithm to synthesize textures in patches. It decomposes the synthesis process into two steps by the chessboard pattern, withthe first step to place patches in the black grids, ...
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Context-awareness refers to computing systems that are able to sense and to comprehend their environment in order to adapt themselves in dependence to the available and relevant contextual information they depend upon...
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ISBN:
(纸本)9780769539294
Context-awareness refers to computing systems that are able to sense and to comprehend their environment in order to adapt themselves in dependence to the available and relevant contextual information they depend upon. Gathering such contextual information involves real world entities such as sensors, which, for various reasons, are often prone to certain degrees of uncertainty and inaccuracy. Nevertheless, high quality context information plays a vital role in ensuring correct system behavior as well as dynamic system and service adaptation. thus, a set of indicators is required which allows determining the quality of contextual information, which is commonly known as Quality of Context (QoC). One of the most relevant parameter of the QoC is the Probability of Correctness (PoC), which expresses the level of confidence, that the contextual information sensed, are in fact correct or not. In this paper, we propose an approach for measuring the PoC of context information by firstly analyzing the nature of context information and, secondly, revisiting the concept of Quality of Context also discussing other QoC parameters. Finally, we present a novel approach for quantifying the PoC for specific context information and evaluate the proposed method on a concrete case study.
Practical intelligence is gained by doing. In this project we offer a technique which allows software agents and humans to learn by doing. the human trainer, that is the domain expert, directly interacts withthe syst...
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Humans can learn in a matter of seconds to associate a response R with a stimulus S, following simple verbal instructions, e.g. "Press the right button when you see a green light". this involves establishing...
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this paper presents a method for performing a robust association between the apneas and hypopneas recorded on a polysomnogram and the desaturations they cause. It is based on a structural algorithm that takes advantag...
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ISBN:
(纸本)9783642024801
this paper presents a method for performing a robust association between the apneas and hypopneas recorded on a polysomnogram and the desaturations they cause. It is based on a structural algorithm that takes advantage of the fuzzy set theory to represent the medical knowledge on which it relies. the method aims to generate information that could serve as a starting point for gaining a deeper insight into the Sleep Apnea-Hypopnea Syndrome by means of data mining techniques. this has led to a sacrifice of sensitivity for specificity. We have validated our proposal over 37 hours of polysomnographic recordings. 88% of the hypoventilations present in the recordings were associated withthe desaturations they caused, presenting a rate of false associations of 0.86%.
Ontology design patterns were proposed in order to assist the ontology engineering task, providing models of specific construction representing a particular form of knowledge. Various kinds of patterns have since been...
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Ontology design patterns were proposed in order to assist the ontology engineering task, providing models of specific construction representing a particular form of knowledge. Various kinds of patterns have since been introduced and classes of patterns identified. Detecting these patterns in existing ontologies is needed in various scenarios, for example the detection of the the two parts of an alignment pattern in an ontology matching scenario, or the detection of an anti-pattern in an optimization scenario. In this paper we present a novel method for the detection of logical patterns in ontologies. this method is based on both SPARQL, as the underlying language for retrieving patterns, and a lexical heuristic constraining the query. It extends our previous works on ontology patterns modeling and detection. We describe an algorithm computing a tokenbased similarity measure used as the lexical heuristic. We conduct an experiment on a large number of Web ontologies, obtaining interesting measures on the usage frequency of three selected patterns.
this paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. the proposed algo...
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this paper presents a new approach to content-based image retrieval by using dynamic indexing and guided search in a hierarchical structure, and extending data mining and data warehousing techniques. the proposed algorithms include: a wavelet-based scheme for multiple image feature extraction, the extension of a conventional data warehouse and an image database to an image data warehouse for dynamic image indexing, an image data schema for hierarchical image representation and dynamic image indexing, a statistically based feature selection scheme to achieve flexible similarity measures, and a feature component code to facilitate query processing and guide the search for the best matching. A series of case studies are reported, which include a wavelet-based image color hierarchy, classification of satellite images, tropical cyclone patternrecognition, and personal identification using multi-level palmprint and face features.
Identifying the pattern support distribution (PSD) in datasets is useful for many data mining tasks, such as market basket analysis. the support of a pattern is the frequency of its occurrence in a dataset. Calculatin...
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ISBN:
(纸本)9780769532424
Identifying the pattern support distribution (PSD) in datasets is useful for many data mining tasks, such as market basket analysis. the support of a pattern is the frequency of its occurrence in a dataset. Calculating the distribution of these supports over an entire dataset is computationally expensive;this cost can be reduced by sampling from the dataset and computingthe PSD on a relatively small sample. However, this may miscount patterns and cause significant changes in the distribution identified. Based on the fact that the PSD shows a power-law relationship, in this paper we investigate the influence of sampling on the characteristics of the power-law relationship in the pattern support distribution. We consider sampling effect on this relationship under two assumptions: uniform distribution of pattern supports, and independent identically distributed (i.i.d.) distributions. We experimentally evaluate the influence on data from four real-world transaction datasets.
In this work we describe a new algorithm to mine tree structured data. Our method computes an almost smallest supertree, based upon iteratively employing tree alignment. this supertree is a global pattern, that can be...
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