This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbala...This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbalance（QCM） principle,and they could capture different vibration frequency signal values for Chinese spirit identification. For each sensor in an8-channel sensor array, seven characteristic values of the original vibration frequency signal values, i.e., average value（A）,root-mean-square value（RMS）, shape factor value（S_f）, crest factor value（C_f）, impulse factor value（I_f）, clearance factor value（CL_f）, kurtosis factor value（K_v） are first extracted. Then the dimension of the characteristic values is reduced by the principle components analysis（PCA） method. Finally the back propagation（BP） neutral network algorithm is used to recognize Chinese spirits. The experimental results show that the recognition rate of six kinds of Chinese spirits is 93.33% and our proposed new pattern recognition system can identify Chinese spirits effectively.展开更多
We present a new pattern recognition system based on moving average and linear discriminant analysis （LDA）, which can be used to process the original signal of the new polymer quartz piezoelectric crystal air-sensit...We present a new pattern recognition system based on moving average and linear discriminant analysis （LDA）, which can be used to process the original signal of the new polymer quartz piezoelectric crystal air-sensitive sensor system we designed, called the new e-nose. Using the new e-nose, we obtain the template datum of Chinese spirits via a new pattern recognition system. To verify the effectiveness of the new pattern recognition system, we select three kinds of Chinese spirits to test, our results confirm that the new pattern recognition system can perfectly identify and distinguish between the Chinese spirits.展开更多
Deficits in social communication are one of the behavioral signatures of autism spectrum disorder(ASD). Because faces are arguably the most important social stimuli that we encounter in everyday life, investigating th...Deficits in social communication are one of the behavioral signatures of autism spectrum disorder(ASD). Because faces are arguably the most important social stimuli that we encounter in everyday life, investigating the ability of individuals with ASD to process faces is thought to be important for understanding the nature of ASD. However, although a considerable body of evidence suggests that ASD individuals show specific impairments in face processing, a significant number of studies argue otherwise. Through a literature review, we found that this controversy is largely attributable to the different face tests used across different studies. Therefore, a more reliable and valid face test is needed. To this end, we performed a meta-analysis on data gleaned from a variety of face tests conducted on individuals with developmental prosopagnosia(DP) who suffer a selective deficit in face processing. Based on this meta-analysis, we selected an old/new face recognition test that relies on face memory as a standard diagnostic test for measuring specific face processing deficits. This test not only reliably reflects DP individuals' subjective experiences with faces in their daily lives, but also effectively differentiates deficits in face processing from deficits caused by other general problems. In addition, DP individuals' performance in this test predicts their performance in a variety of face tests that examine specific components of face processing(e.g., holistic processing of faces). Finally, this test can be easily administrated and is not overly sensitive to prior knowledge. In summary, this test can be used to evaluate face-processing ability, and it helped to resolve the controversy whether individuals with ASD exhibit face-processing deficits.展开更多
基金Project supported by the National High Technology Research and Development Program of China(Grant No.2013AA030901)the Fundamental Research Funds for the Central Universities,China(Grant No.FRF-TP-14-120A2)
文摘This paper presents a new pattern recognition system for Chinese spirit identification by using the polymer quartz piezoelectric crystal sensor based e-nose. The sensors are designed based on quartz crystal microbalance（QCM） principle,and they could capture different vibration frequency signal values for Chinese spirit identification. For each sensor in an8-channel sensor array, seven characteristic values of the original vibration frequency signal values, i.e., average value（A）,root-mean-square value（RMS）, shape factor value（S_f）, crest factor value（C_f）, impulse factor value（I_f）, clearance factor value（CL_f）, kurtosis factor value（K_v） are first extracted. Then the dimension of the characteristic values is reduced by the principle components analysis（PCA） method. Finally the back propagation（BP） neutral network algorithm is used to recognize Chinese spirits. The experimental results show that the recognition rate of six kinds of Chinese spirits is 93.33% and our proposed new pattern recognition system can identify Chinese spirits effectively.
基金Project supported by the National High Technology Research and Development Program of China(Grant No.2013AA030901)
文摘We present a new pattern recognition system based on moving average and linear discriminant analysis （LDA）, which can be used to process the original signal of the new polymer quartz piezoelectric crystal air-sensitive sensor system we designed, called the new e-nose. Using the new e-nose, we obtain the template datum of Chinese spirits via a new pattern recognition system. To verify the effectiveness of the new pattern recognition system, we select three kinds of Chinese spirits to test, our results confirm that the new pattern recognition system can perfectly identify and distinguish between the Chinese spirits.
基金supported by the 100 Talents Program of Chinese Academy of Sciences,the National Basic Research Program of China(Grant Nos.2010CB833903 and 2011CB505402)the National Natural Science Foundation of China(Grant No.91132703)the Fundamental Research Funds for the Central Universities(Grant No.2009SD-3)
文摘Deficits in social communication are one of the behavioral signatures of autism spectrum disorder(ASD). Because faces are arguably the most important social stimuli that we encounter in everyday life, investigating the ability of individuals with ASD to process faces is thought to be important for understanding the nature of ASD. However, although a considerable body of evidence suggests that ASD individuals show specific impairments in face processing, a significant number of studies argue otherwise. Through a literature review, we found that this controversy is largely attributable to the different face tests used across different studies. Therefore, a more reliable and valid face test is needed. To this end, we performed a meta-analysis on data gleaned from a variety of face tests conducted on individuals with developmental prosopagnosia(DP) who suffer a selective deficit in face processing. Based on this meta-analysis, we selected an old/new face recognition test that relies on face memory as a standard diagnostic test for measuring specific face processing deficits. This test not only reliably reflects DP individuals' subjective experiences with faces in their daily lives, but also effectively differentiates deficits in face processing from deficits caused by other general problems. In addition, DP individuals' performance in this test predicts their performance in a variety of face tests that examine specific components of face processing(e.g., holistic processing of faces). Finally, this test can be easily administrated and is not overly sensitive to prior knowledge. In summary, this test can be used to evaluate face-processing ability, and it helped to resolve the controversy whether individuals with ASD exhibit face-processing deficits.
