For biomedical engineering university courses and further education in fields of personal and on-the-job training e. g. for clinical engineers, an interactive computer based learning and training system is in progress...
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ISBN:
(纸本)9783540892076
For biomedical engineering university courses and further education in fields of personal and on-the-job training e. g. for clinical engineers, an interactive computer based learning and training system is in progress. the software system thERAGNOSOS is designed for interdisciplinary application in selected fields of biomedical engineering: medical terminology for biomedical engineers, medical imaging, electrical activation in human heart, modelling and simulation, cerebral autoregulation and lung function diagnosis and mechanical ventilation. application for blended learning reached positive response among students and teachers.
this paper presents a generic unsupervised learning based solution to unexpected event detection from a static uncalibrated camera. the system can be represented into a probabilistic framework in which the detection i...
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ISBN:
(纸本)9789898111692
this paper presents a generic unsupervised learning based solution to unexpected event detection from a static uncalibrated camera. the system can be represented into a probabilistic framework in which the detection is achieved by a likelihood based decision. We propose an original method to approximate the likelihood function using a sparse vector machine based model. this model is then used to detect efficiently unexpected events online. Moreover, features used are based on optical flow orientation within image blocks. the resulting application is able to learn automatically expected optical flow orientations from training video sequences and to detect unexpected orientations (corresponding to unexpected event) in a near real-time frame rate. Experiments show that the algorithm can be used in various applications like crowd or traffic event detection.
the distributed clustering algorithm is used to cluster the distributed datasets without necessarily downloading all the data into a single place. Many applications can benefit from frizzy clustering, where each objec...
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Approach for multiple pattern extraction from obtained individual clusters is presented in this paper. Pattern extraction supports the end users in understanding the cluster concept. Pattern discovery approach uses re...
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this paper presents two recent machinelearning techniques namely Model Tree (MT) and Gene Expression Programming (GEP) to predict suspended sediment Loads (SSL) in river. MT is a kind of decision tree, which has the ...
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Rough Set (RS) and Support Vector machine(SVM) have gradually been becoming hot spots in the territory of artificial intelligence, machinelearning and data mining research. In this paper, RS and SVM theories have bee...
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ISBN:
(纸本)9781424438655
Rough Set (RS) and Support Vector machine(SVM) have gradually been becoming hot spots in the territory of artificial intelligence, machinelearning and data mining research. In this paper, RS and SVM theories have been discussed, a new hybrid RS-SVM model was proposed based on the attribute reduction of RS and the classification principles of SVM, which has been analyzed its possibility of application in competency assessment and has been applied in competency assessment. Firstly, the attribute reduction of RS has been applied as preprocessor to delete redundant attributes and conflicting objects without losing efficient information. then, an SVM classification model is built to make a forecast. Finally,compared the RS-SVM model with neural network model or grade regression model. Empirical results shown that RS-SVM model obtains good classification performance, and it highly reduces the complexity in the process of SVM classification and prevents the over-fit of training model in a certain extent.
this paper introduces the concepts of asking point and expected answer type as variations of the question focus. they are of particular importance for QA over semistructured data, as represented by Topic Maps, OWL or ...
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the proceedings contain 28 papers. the topics discussed include: cross-lingual ontology mapping - an investigation of the impact of machine translation;modeling common real-word relations using triples extracted from ...
ISBN:
(纸本)3642108709
the proceedings contain 28 papers. the topics discussed include: cross-lingual ontology mapping - an investigation of the impact of machine translation;modeling common real-word relations using triples extracted from n-grams;supporting the development of data wrapping ontologies;a conceptual model for a web-scale entity name system;repairing the missing is-a structure of ontologies;entity resolution in texts using statistical learning and ontologies;an effective similarity propagation method for matching ontologies without sufficient or regular linguistic information;merging and ranking answers in the semantic web: the wisdom of crowds;lode: linking open descriptions of events;a semantic Wiki based light-weight web application model;guidelines for the specification and design of large-scale semantic applications;and semantic-linguistic feature vectors for search: unsupervised construction and experimental validation.
this paper deals with a real-time scheduling method for holonic manufacturing systems (HMS). In the previous paper, a real-time scheduling method based on utility values has been proposed and applied to the HMS. In th...
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ISBN:
(纸本)9783642036668
this paper deals with a real-time scheduling method for holonic manufacturing systems (HMS). In the previous paper, a real-time scheduling method based on utility values has been proposed and applied to the HMS. In the proposed method, all the job holons and the resource holons firstly evaluate the utility values for the cases where the holon selects the individual candidate holons for the next machining operations. the coordination holon secondly determine a suitable combination of the resource holons and the job holons which carry out the next machining operations, based on the utility values. Multi-agent reinforcement learning is newly proposed and implemented to the job holons and the resource holons, in order to improve their capabilities for evaluating the utility values of the candidate holons. the individual job holons and resource holons evaluate the suitable utility values according to the status of the HMS, by applying the proposed learning method.
Human electroencephalograph (EEG) data driven animation is often used in neurofeedback systems for concentration training in children and adults. Visualization of the time-series data could be used in neurofeedback an...
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ISBN:
(纸本)9783642018107
Human electroencephalograph (EEG) data driven animation is often used in neurofeedback systems for concentration training in children and adults. Visualization of the time-series data could be used in neurofeedback and for the data analysis. the paper proposes a novel method of 3D mapping of EEG data and describes visualization system VisBrain that was developed for EEG data analysis. We employed a concept of a dynamic 3D volumetric shape for showing how the electrical signal changes through time. For the shape, a time-dependent solid blobby object was used. this object is defined using implicit functions. Besides just a visual comparison, we propose to apply set-theoretic ("Boolean") operations to the moving shapes to isolate activities common for both of them per time point, as well as those that are unique for either one. the advantages of the method are demonstrated with real EEG experiments examples. New emerging applications of EEG data driven animation in e-learning, games, entertainment, and medical applications are discussed.
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