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Human movement pattern can be a valuable information for rehabilitation therapy, sport medicine and elderly people monitoring, but acquisition of them through multi-cite accelerormeters would result in uncomfortable wearing and complex data processing. In this paper, method of using a single waist-fixed accelerometer to detect human movement pattern was investigated and evaluated. 10 subjects were...
On-body sensing has enabled scalable and unobtrusive activity recognition for context-aware wearable computing. Common methods for activity recognition are based on supervised learning requiring substantial amounts of labeled training data. Obtaining accurate and detailed annotations of activities is a great challenge for these approaches preventing their applicability in real-world settings. This...
This paper continues to explore the potential of newly introduced Fuzzy Gaussian Inference (FGI). It aims at constructing fuzzy membership functions by modelling hidden probability distributions underlying human motions. A fuzzy rule-based system has been employed to assist boxing motion classification from natural human Motion Capture data. In this experiment, FGI alone is able to recognise seven...
Network defense is an elusive art. The arsenal to defend our devices from attack is constantly lagging behind the latest methods used by attackers to break into them and subsequently into our networks. To counteract this trend, we developed a distributed, scalable approach that harnesses the power of collaborative end-host detectors or sensors. Simulation results reveal order of magnitude improvements...
Classification is an important technique in the field of Data Mining and Machine Learning. The classifier can predict the class of unknown data based on their given attribute values. In ubiquitous computing environment, a great deal information can be obtained from various sensors. However, with the time going on, new sensor may be recruited. The recruited new sensors may bring new outcomes to the...
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