The eigenvalues of some liquid drop fingerprints are of high similarity, which decreases the recognition accuracy rates of BP neural network. In order to solve this problem, recognition method based on cluster analysis and BP neural network is proposed in this paper. Cluster analysis is used to classify liquid samples according to the similarity of eigenvalues and narrow the recognition range for samples under study. The experimental results have proved that this method is able to increase the recognition accuracy rate from 83.42% to 99.83%.

Previous studies have shown that learners with different native language backgrounds have common difficulties in learning Chinese affricates but demonstrate in various patterns. While few studies investigated this issue of native Urdu speakers. To address the production of Chinese affricates /ts/ and /tsʰ/ by native Urdu speakers, speech materials, produced by two groups of subjects with different Chinese proficiency, were selected from the BLCU-SAIT speech corpus. The error rate and error types of their production of Chinese affricates /ts/ and /tsʰ/ have been discussed after transcription and data analysis. The results show that though there are no counterparts of Chinese affricates /ts/ and /tsʰ/ in Urdu, the error and the acquisition pattern of these two affricates, to some extent, affected by individual differences of their roles in Urdu except universal similarities and differences between two languages. The findings of this study shed some light on second language learning and teaching.

Among various pattern recognition methods used for liquid identification, the method based on neural network has the advantages of robustness and fault tolerance, which can study and adapt to the uncertain system. The waveform analysis is exploited for feature extraction of the liquid droplet fingerprint (LDF) in this paper, and the liquid identification is carried out by means of BP and RBF neural network. The experimental results proved that the recognition rate is excellent in both of these two methods. In condition that the training data is limited, RBF network is better than BP network in recognition speed and rate.

Our aim is to explore the brain stereotaxic method of aquatic animal-robots. [Methods] Carps were anesthetized by Eugenol. The carp skulls and brain were observed by the method of anatomy. Carp brain structure and size were obtained by three-dimension images which were structured by CT. The brain stereotaxic method was confirmed by setting up a 3 d coordinate system of brain and dividing carp skull surface into 8 location areas. The 3 d coordinate system of brain was built according to the principle of brain stereotaxic coordinates, the bony marks and the characteristics of carp skull. And the 8 location areas were used for implanting electrodes. Stimulating electrodes were implanted into cerebral motor areas by the application of brain stereotaxic method. [Results] The carp-robot went forward and turned successfully by controlling in underwater experiment. [Conclusion] The results showed that the brain stereotaxic method is feasible and reliable for carp-robot.

This study, based on corpus materials, investigates the “voice onset time” (VOT) of Mandarin word-initial stops in isolated syllables according to the effect of vowel contexts produced by native and nonnative speakers. Here, 1250 monosyllables of word-initial plosives /p/, /t/, /k/, /p[Formula: see text]/, /t[Formula: see text]/, and /k[Formula: see text]/ were uttered in combination with the vowels /a/, /i/, and /u/ in four tone contexts except /ki/ and /k[Formula: see text]i/ that are phonetically illegal in Mandarin by 20 participants (10 native Chinese speakers and 10 Urdu learners of Chinese). Results show that for native Chinese speakers, the VOTs of aspirated stops followed by the high vowels /i/ and /u/ are significantly longer than those followed by the low vowel /a/, and unaspirated stops followed only by the high back vowel /u/ are significantly longer than those followed by the low vowel /a/. For native Urdu speakers, the mean VOTs of word-initial stops in Mandarin monosyllables have no significant effect for both aspirated and unaspirated ones in combination with different vowels. Understanding the results of this study will be of assistance to second language learning and teaching.