Auditory perception is one of the most important functions for robotics applications. Microphone arrays are widely used for auditory perception in which the spatial structure of microphones is usually known. In practi...
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The flame-made (5/5) pure ZnO and WO 3 -doped ZnO nanoparticles containing 0.25, 0.50, and 0.75 mol% of WO 3 were successfully synthesized by flame spray pyrolysis (FSP). These materials were studied for NO 2 , CO an...
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The flame-made (5/5) pure ZnO and WO 3 -doped ZnO nanoparticles containing 0.25, 0.50, and 0.75 mol% of WO 3 were successfully synthesized by flame spray pyrolysis (FSP). These materials were studied for NO 2 , CO and H 2 gas sensing at different gas concentrations and operating temperatures ranging from 300-400°C in dry air. The crystalline phase, morphology and size of the nanoparticles were characterized by XRD, BET, TEM, SEM and EDS in order to correlate physical properties with gas sensing performance. The gas-sensing results showed that WO 3 doping significantly enhanced NO 2 gas-sensing performance of ZnO nanoparticles. In addition, 0.5 mol% is found to be an optimal WO 3 concentration which gives the highest sensitivity towards NO 2 .
In this paper,we prove the optimality of disturbance-affine control policies in the context of onedimensional,box-constrained,multi-stage robust *** results cover the finite horizon case,with minimax(worstcase) object...
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In this paper,we prove the optimality of disturbance-affine control policies in the context of onedimensional,box-constrained,multi-stage robust *** results cover the finite horizon case,with minimax(worstcase) objective,and convex state costs plus linear control *** proof methodology,based on techniques from polyhedral geometry,is elegant and conceptually simple,and entails efficient algorithms for the case of piecewise affine state costs,when computing the optimal affine policies can be done by solving a single linear program.
A statistical parametric approach to speech synthesis based HMMs has grown in popularity over the last few years. In this approach, spectrum, excitation, and duration of speech are simultaneously modeled by context-de...
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A statistical parametric approach to speech synthesis based HMMs has grown in popularity over the last few years. In this approach, spectrum, excitation, and duration of speech are simultaneously modeled by context-dependent HMMs, and speech waveforms are generated from the HMMs themselves. Since December 2002, we have publicly released an opensource software toolkit named "HMM-based speech synthesis system (HTS)" to provide a research and development toolkit for statistical parametric speech synthesis. This paper describes recent developments of HTS in detail, as well as future release plans.
We investigated 0.01-0.08 Hz low-frequency fluctuations of BOLD-fMRI signals in the face and object-responsive regions during the resting-state and during face or object viewing tasks. By comparing the effects of the ...
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We propose an automatic and precise moving-object extraction method for use in video streams that can also be used for 3-D system applications. The method generates a statistical model for each pixel using several fra...
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We propose an automatic and precise moving-object extraction method for use in video streams that can also be used for 3-D system applications. The method generates a statistical model for each pixel using several frames, and then uses it to generate trimap images. After manually initializing a frame, unknown regions are automatically determined either background or foreground for the rest of frames. The key technology proposed is an adaptive training scheme, which estimates detection thresholds locally through the algorithm, followed by matting approaches using an iterative process and weighted statistical distance minimization. Experiments demonstrate outperformance of our method for both indoor and outdoor video streams, and also for 3-D modeling and representation.
Recently, there are many studies on brain computer interface (BCI) system and some use EEG response at oddball paradigms. The aim of this paper is to extract feature (i.e. P300 response) from the EEG signals to improv...
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Recently, there are many studies on brain computer interface (BCI) system and some use EEG response at oddball paradigms. The aim of this paper is to extract feature (i.e. P300 response) from the EEG signals to improve the spelling system. We propose the method to analyze the averaged EEG signal concerned time and spatial. It is confirmed that the processing period with feature extraction is able to be shortened by averaging multi-channels. Effective information is obtained from the EEG signal near of the center part.
QGENIE is a specialized interface to GENIE, a decision modeling environment developed by the Decision Systems Laboratory, University of Pittsburgh. QGENIE allows for rapid construction of graphical models in which all...
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QGENIE is a specialized interface to GENIE, a decision modeling environment developed by the Decision Systems Laboratory, University of Pittsburgh. QGENIE allows for rapid construction of graphical models in which all variables are propositional, almost no numerical probabilities are displayed at the user interface, and degrees of truth of propositions are displayed by means of node colors. All numerical parameters, such as prior probability distributions over variables and strengths of influences between variables, are entered by means of graphical sliders. While the underlying computations are all numerical and based on Bayesian updating, QGENIE makes the impression of a qualitative, ¿order of magnitude¿ type system that aids rapid model building and an approximate analysis of systems.
This paper presents a comprehensive study on a number of hybrid test vector compression methods for VLSI circuit testing. In the proposed approaches, a software program is loaded into the on-chip processor memory alon...
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This paper presents a comprehensive study on a number of hybrid test vector compression methods for VLSI circuit testing. In the proposed approaches, a software program is loaded into the on-chip processor memory along with the compressed test data sets. To minimize on-chip storage besides testing time, the test data volume is first reduced by compaction in a hybrid manner before downloading into the processor. The methods utilize a set of adaptive coding techniques for realizing lossless compression. The compaction program need not be loaded into the embedded processor, as only the decompression of test data is required for the automatic test equipment. The developed schemes necessitate minimal hardware overhead, while the on-chip embedded processor can be reused for normal operation on completion of testing. As an extension of the earlier works, this paper also reports further results on studies of the problem and demonstrates the feasibility of the suggested methodologies with simulation results on ISCAS 85 combinational and ISCAS 89 full scan sequential benchmark circuits.
This paper presents a certified confidence model which aims to ensure credibility for information exchanged among agents which inhabit an open environment. Generally speaking, the proposed environment shows a supplier...
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