Since 1960's obstetricians have been using cardiotocography (CTG) to detect possible ongoing hypoxia of the fetus. CTG consists of fetal heart rate (fHR) and uterine contraction (TOCO) monitoring. The evaluation o...
详细信息
Since 1960's obstetricians have been using cardiotocography (CTG) to detect possible ongoing hypoxia of the fetus. CTG consists of fetal heart rate (fHR) and uterine contraction (TOCO) monitoring. The evaluation of the fHR in clinical settings is ruled by FIGO guidelines, which are based on evaluation of macroscopic morphological features derived from the fHR, such as baseline variability. Although upgrades were proposed to the guidelines - none of them is taking into account results achieved by the adult heart rate variability research. In this work, almost complete set of features previously used for fHR description is investigated and the features are assessed based on their statistical significance in the task of distinguishing the records into three FIGO classes. Inter-correlation of the features is also discussed. We assess the features on a large data set and use expert signal evaluation instead of pH values with the aim to give an overall view of the potential usefulness of the features in the clinical settings. We conclude the paper by presenting the best uncorrected feature subset according to the meta-analysis of three different ranking methods.
Acoustic emission (AE) is one of the most important non-destructive testing (NDT) methods for materials and constructions. Using AE testing, the location of a single event (crack) can be classified efficiently into th...
详细信息
Acoustic emission (AE) is one of the most important non-destructive testing (NDT) methods for materials and constructions. Using AE testing, the location of a single event (crack) can be classified efficiently into three typical areas in a ship hull. The problem is a typical classification problem based on the use of features extracted from piezo-sensors' signal. As in most classification problems, the extraction and selection of the most appropriate set of features plays a major role in the overall performance of the system. In this research work we investigate the use of an evolutionary algorithm to extract new features from a set of primitive features in a lower dimensional space through a linear transformation. These features are subsequently fed into a probabilistic neural network (PNN) that performs the classification. In simulation experiments, where a stiffened plate model (SPM) is partially sank into water, the localization rate in noisy environments outperforms a work, where a feature selection phase alone was used before the classification phase. The proposed hybrid computational intelligent approach shows the potential merit of using it in real life situations where the signal is distorted by noise.
This paper introduces a novel approach based on signal processing methods to extract features from speech signals and based on them to detect a specific type of articulation disorders. Articulation, in effect, is the ...
详细信息
This paper introduces a novel approach based on signal processing methods to extract features from speech signals and based on them to detect a specific type of articulation disorders. Articulation, in effect, is the specific and characteristic way that an individual produces the speech sounds. Empirical Mode Decomposition and the Hilbert Huang transform are applied to the speech signal in order to calculate the marginal spectrum of the signal. The marginal spectrum is subsequently subject to a mel-cepstrum like processing to extract features which are fed to a neural network classifier responsible for the identification of the articulation disorder. Our preliminary results suggest that this approach is very promising for the detection of the disorder under study.
A great variety of languages can be designed by different people for different purposes to operate resource spaces. Two fundamental issues are: can we design more operations in addition to existing operations? and, ho...
A great variety of languages can be designed by different people for different purposes to operate resource spaces. Two fundamental issues are: can we design more operations in addition to existing operations? and, how many operations are sufficient or necessary? This paper solves these problems by investigating the theoretical basis for determining how complete a selection capability is provided in a resource operation sublanguage independent of any host language. The result is very useful to the design and analysis of operating languages.
Effective document classification is a long-pursued goal in knowledge management. This paper proposes a novel hybrid approach of semantic representation and statistical measurements. Document is divided into content s...
Effective document classification is a long-pursued goal in knowledge management. This paper proposes a novel hybrid approach of semantic representation and statistical measurements. Document is divided into content segments first. By Formal Concept Analysis (FCA), their semantic links with standard concept identifiers are built up whose weights are calculated statistically. In this way, effective concept fusing and document classification can be achieved. In addition, a semantic overlay for specific documents will be constructed via concept fusing. Experiments show our approach is feasible and effective.
作者:
Hai ZhugeChina Knowledge Grid Research Group
Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China
In the human, society, interconnection environment and systems methodology perspectives, this paper answers the following questions: What are the knowledge Grid and its distinguished features? What are its methodology...
详细信息
In the human, society, interconnection environment and systems methodology perspectives, this paper answers the following questions: What are the knowledge Grid and its distinguished features? What are its methodology and major research issues? These answers are important to the development of this promising area.
The key issue of peer data management systems (PDMSs) is how to efficiently organize and manage distributed resources in P2P networks to accurately route queries from the peer initiating the query to appropriate peers...
详细信息
The key issue of peer data management systems (PDMSs) is how to efficiently organize and manage distributed resources in P2P networks to accurately route queries from the peer initiating the query to appropriate peers to avoid network flooding. This paper proposes a semantic-based PDMS model, called R-Chord, by deploying the resource space model above the Chord overlay for uniformly, normally and effectively organizing and managing resources distributed in P2P networks. Experiments show that, compared to the Chord model, the R-Chord model is more flexible to support semantic-based queries and can significantly decrease the average visiting number of and visiting times on peers for answering queries.
A knowledge flow is invisible but it plays an important role in ordering knowledge exchange in teamwork. It can help achieve effective team knowledge management by modeling, optimizing, monitoring and controlling the ...
详细信息
A knowledge flow is invisible but it plays an important role in ordering knowledge exchange in teamwork. It can help achieve effective team knowledge management by modeling, optimizing, monitoring and controlling the operation of knowledge flow processes. This paper proposes the notion of knowledge energy as the driving cause of forming an autonomous knowledge flow network, and explores the behind principles. Knowing these principles can help team managers and the support systems improve cooperation by monitoring the knowledge energy of nodes, and by evaluating and adjusting knowledge flows. A knowledge flow network management system can be the high layer of the knowledge grid to help improve the efficiency of distributed knowledge-intensive teamwork.
An important obstacle to the success of the Semantic Web is that the establishment of the semantic relationship is labor-intensive. This paper proposes an automatic semantic relationship discovering approach for const...
详细信息
ISBN:
(纸本)1581139128
An important obstacle to the success of the Semantic Web is that the establishment of the semantic relationship is labor-intensive. This paper proposes an automatic semantic relationship discovering approach for constructing the semantic link network. The basic premise of this work is that the semantics of a web page can be reflected by a set of keywords, and the semantic relationship between two web pages can be determined by the semantic relationship between their keyword sets. The approach adopts the data mining algorithms to discover the semantic relationships between keyword sets, and then uses deductive and analogical reasoning to enrich the semantic relationships. The proposed algorithms have been implemented. Experiment shows that the approach is feasible.
The future Web can be imagined as a life network consisting of resource nodes and semantic relationship links between them. Any node has a life span from birth -?adding it to the network -?to death -?removing it from ...
详细信息
ISBN:
(纸本)1581139128
The future Web can be imagined as a life network consisting of resource nodes and semantic relationship links between them. Any node has a life span from birth -?adding it to the network -?to death -?removing it from the network. Through establishing and investigating two types of models for such a network, we obtain the same scale free distribution of semantic links. Simulations and comparisons validate the rationality of the proposed models.
暂无评论