Quantitative analysis and detection of abnormalities for electroencephalogram (EEG) recordings during evoked activities are essential for clinical diagnosis on neurological disorders. However, the process of interpret...
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Quantitative analysis and detection of abnormalities for electroencephalogram (EEG) recordings during evoked activities are essential for clinical diagnosis on neurological disorders. However, the process of interpreting EEG is time consuming and requires experienced electroencephalographers (EEGers). In this study, a method of automatic EEG interpretation during hyperventilation was proposed. The purpose is to provide a quantitative interpretation of EEG which is able to conform to EEGers' visual inspection. The final integrated results of automatic interpretation were compared with EEGers' evaluation, and showed high consistence.
This paper explores the issues surrounding the use of audio in learning and offers an alternative to podcasting. It considers the practicalities of enabling students to generate their own audio recordings and the pote...
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This paper explores the issues surrounding the use of audio in learning and offers an alternative to podcasting. It considers the practicalities of enabling students to generate their own audio recordings and the potential to enhance and personalise learning in a self directed way that suits their individual learning styles. There is some discussion of hardware and its accessibility, cost and ease of use as well as protocols on what audio can/cannot be recorded or shared amongst students. The paper explores different types of scenario where recording can be used beneficially and uses real student case studies to demonstrate its efficacy, as perceived by the students. There is also particular emphasis on the benefits to specific student groups, including those with English as an additional language or students with learning difficulties. In summary the paper gives evidence of how student generated audio can be embedded into the curriculum and the benefits it can bring.
Recently we develop two kinds of approaches, that is, the super-exponential method (SEM) and the eigenvector method (EVM), of which both can achieve the blind deconvolution for MIMO-IIR systems. It is shown that these...
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ISBN:
(纸本)9781424420780
Recently we develop two kinds of approaches, that is, the super-exponential method (SEM) and the eigenvector method (EVM), of which both can achieve the blind deconvolution for MIMO-IIR systems. It is shown that these methods are closely related each other. Based on this fact, we propose a new SEM incorporated with the EVM. Simulation results will be presented for showing the validity of the proposed method.
We present a new control strategy for a VTOL aerial robot. A kinematics control law is derived using Astolfi's discontinuous control, after introducing a chained form transformation with one generator and three ch...
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This paper deals with a computational model of emotions and its application for cooperative benevolent agents. A stochastic emotion model based on Markov theory is adapted to perform their well organized tasks to achi...
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A fuzzy coach-player system is here improved as an instruction system with voice interface. However, this system deals with some fuzziness included in voice instructions and introduces hierarchical instructions, which...
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An optical system of off-axis digital holography for imaging the Jones vector of an object wave is improved, and a Faraday rotator for the reference wave is also newly constructed. To evaluate the accuracy of the pola...
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This chapter reports the development of a real time 3D sensor system and a new concept based on space decomposition by encoding its operational space using limited number of laser spots. The sensor system uses the ric...
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Multi-robot task allocation, cooperation and interaction among the members of a team are very complex topics that need to be explored more. A task can be accomplished by a multi-robot team with required performance an...
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Data for human sleep study may be affected by internal and external influences. The recorded sleep data contains complex and stochastic factors, which increase the difficulties for the computerized sleep stage determi...
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Data for human sleep study may be affected by internal and external influences. The recorded sleep data contains complex and stochastic factors, which increase the difficulties for the computerized sleep stage determination techniques to be applied for clinical practice. The aim of this study is to develop an automatic sleep stage determination system which is optimized for variable sleep data. The main methodology includes two modules: expert knowledge database construction and automatic sleep stage determination. Visual inspection by a qualified clinician is utilized to obtain the probability density function of parameters during the learning process of expert knowledge database construction. Parameter selection is introduced in order to make the algorithm flexible. Automatic sleep stage determination is manipulated based on conditional probability. The result showed close agreement comparing with the visual inspection by clinician. The developed system can meet the customized requirements in hospitals and institutions.
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