A Resource Space Model is a semantic model to organize, locate and operate Web resources in a multidimensional resource space. It’s easy for users to understand the resource space and locate resources in it because a...
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A Resource Space Model is a semantic model to organize, locate and operate Web resources in a multidimensional resource space. It’s easy for users to understand the resource space and locate resources in it because a resource space is constructed based on the classification semantics. In general, resource spaces models are manually designed and constructed based on domain knowledge and resource analysis. Human factors, such as personal opinions, knowledge level and design skill, will influence the design result of a resource space. To reduce the difficulties of the manual design and ease the designing process, this work studies the issues of automated creation of a resource space and proposes a general method to automatically construct resource spaces from XML files.
MapReduce provided a novel computing model for complex job decomposition and sub-tasks management to support cloud computing with large distributed data sets. However, its performance is significantly influenced by th...
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This paper explores heterogeneous semantic data in Web 1.0, Semantic Web and Web 2.0 for topicspecific crawling and search. A statistical Semantic Association Model (SAM) is proposed to support semantic interoperabili...
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This paper explores heterogeneous semantic data in Web 1.0, Semantic Web and Web 2.0 for topicspecific crawling and search. A statistical Semantic Association Model (SAM) is proposed to support semantic interoperability among four different models of thesauruses, categories, ontologies, and folksonomies. Based on this model, a focused crawling and semantic search framework is developed. In focused crawling of potentially related textual and semantic data, URLs are ordered before crawling and irrelevant Web pages are filtered out after crawling according to SAM-based semantic relevance ranking. In order that the retrieved results are more semantically related to the user queries, approaches of SAM-based semantic query expansion and meta-search result aggregation are designed. Experiments show that the proposed model and framework effectively integrates both keyword data and heterogeneous semantic data for topic-specific crawling and search.
SVM (Support Vector Machines) is a novel algorithm of machine learning which is based on SLT (Statistical Learning Theory). It can solve the problem characterized by nonlinear, high dimension, small sample and local m...
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This paper surveys research on the Resource Space Model RSM. RSM is a classification-based, multi-dimensional and content-based space model for efficiently and effectively managing various resources. As a non-relation...
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This paper surveys research on the Resource Space Model RSM. RSM is a classification-based, multi-dimensional and content-based space model for efficiently and effectively managing various resources. As a non-relational data model, it has a rather complete theoretical basis and has significant applications in faceted search and the future cyber-physical society. Applications in picture resources and email resources are introduced.
With tremendous research progress in biomedical sensors and sensor networks, there is an increasingly need for employing new data processing technologies that are capable of online analysis of the streaming medica...
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With tremendous research progress in biomedical sensors and sensor networks, there is an increasingly need for employing new data processing technologies that are capable of online analysis of the streaming medical sensor data, which is a typical health monitoring scenario. This paper describes using the data stream management system (DSMS) in developing ubiquitous health monitoring application. We propose the system architecture suitable for simultaneously processing streaming data from heterogeneous sources and performing different monitoring tasks planned by clinicians. A pilot heart rate variability (HRV) monitor with a graphical user interface is developed based on Borealis and several tasks are implemented, including monitoring Rmssd, MeanHR (mean heart rate), and pNN50. Results of the test runs in the lab environment show the usefulness and potential of DSMS in performing intelligent real-time medical data processing.
People often feel the limitation of time to read the continuously increasing articles they need to read. It is a grand challenge to handle the explosion of articles. To understand how humans read articles and get the ...
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People often feel the limitation of time to read the continuously increasing articles they need to read. It is a grand challenge to handle the explosion of articles. To understand how humans read articles and get the meaning is the basis of improving the efficiency of reading articles. The underlying semantic links between language units of different granularities reflect some basic semantics. Sentence is the basic language unit for accurately indicating semantics. By defining concepts and the dependent set of sentences, and constructing the semantic link network of dependent sentences and semantic link network of concepts, this paper proposes the textual semantic lens with a set of functions for helping people comprehend articles. Integrating with the semantic link networks of articles, the semantic lens can help people efficiently read large-scale articles.
In a Bluetooth Low Energy (BTLE) piconet, the master node controls the channel access by a simple polling scheme. Due to an absence of coordination among independent master nodes while accessing the wireless medium, d...
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In a Bluetooth Low Energy (BTLE) piconet, the master node controls the channel access by a simple polling scheme. Due to an absence of coordination among independent master nodes while accessing the wireless medium, devices will encounter high packet interference if many piconets are simultaneously operating in the same area. In this paper, we propose two schemes in the converged BTLE and cellular network, one is based on bad channel prediction for the BTLE piconets, and the other is based on frequency hopping sequences transformation. We compare the performance of the proposed algorithms with original scheme in the form of channel collision probability and new signaling overhead. The simulation results show that the proposed schemes can reduce channel collision probability significantly and simultaneously the new signaling overhead introduced to the downlink is not large.
Wind shear is recognized by a major hazard during takeoff and landing of aircraft, which can be detected by airborne forward-looking weather radar. A high-fidelity wind shear model constructed by the Computational Flu...
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Wind shear is recognized by a major hazard during takeoff and landing of aircraft, which can be detected by airborne forward-looking weather radar. A high-fidelity wind shear model constructed by the Computational Fluid Dynamics software has been implemented in this study. The model is reasonably representative of the downward wind falling to the ground during the mature phase of the microburst wind shear. The results of the radar echo signal simulation based on the above wind shear model show that the distribution of the velocities has an obvious horizontal "S" shape. The simulated results demonstrate the typical characteristic of the microburst wind shear.
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