• 한국음향학회:학술대회논문집
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• 한국음향학회 1998년도 제15회 음성통신 및 신호처리 워크샵(KSCSP 98 15권1호)
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• pp.250-253
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• 1998

In digital communicatioin networks, speech recognition systems conventionally reconstruct speech followed by extracting feature [parameters. In this paper, we consider a useful approach by incorporating speech coding parameters into the speech recognizer. Most speech coders employed in the networks represent line spectral pairs as spectral parameters. In order to improve the recognition performance of the LSP-based speech recognizer, we introduce two different ways: one is to devise weighed distance measures of LSPs and the other is to transform LSPs into a new feature set, named a pseudo-cepstrum. Experiments on speaker-independent connected-digit recognition showed that the weighted distance measures significantly improved the recognition accuracy than the unweighted one of LSPs. Especially we could obtain more improved performance by using PCEP. Compared to the conventional methods employing mel-frequency cepstral coefficients, the proposed methods achieved higher performance in recognition accuracies.

• Journal of Biosystems Engineering
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• 제34권6호
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• pp.454-461
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• 2009

The purpose of this study is to analyze the RFID recognition performance by level of water. A 13.56 MHz RFID management system for packaged liquid food logistics is consisted of antenna, reader, passive type tags, and embedded controller. The tests were conducted at different level of water, distances between tag and antenna, and position of attached tags. To analyze the RFID recognition performance, maximum recognition distances for a container and recognition rates for a logistics made of 27 containers were measured and analyzed. The maximum recognition distance for a container was different depending on position of attached tags, and attached tag at upside position showed a good performance. But, the recognition rate of 27 containers showed a good ability for attached tags at front side position, 30~35 cm distance to antenna, and water level 1. Therefore, to manage packaged liquid food logistics using RFID system, position of attached tag, distances between tag and antenna, and level of water should be considered.

• 한국정보전자통신기술학회논문지
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• 제14권4호
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• pp.314-322
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• 2021

Skeleton-based action recognition has attracted considerable attention in human action recognition. Recent methods for skeleton-based action recognition employ spatiotemporal graph convolutional networks (GCNs) and have remarkable performance. However, most of them have heavy computational complexity for robust action recognition. To solve this problem, we propose a shuffle graph convolutional network (SGCN) which is a lightweight graph convolutional network using pointwise group convolution rather than pointwise convolution to reduce computational cost. Our SGCN is composed of spatial and temporal GCN. The spatial shuffle GCN contains pointwise group convolution and part shuffle module which enhances local and global information between correlated joints. In addition, the temporal shuffle GCN contains depthwise convolution to maintain a large receptive field. Our model achieves comparable performance with lowest computational cost and exceeds the performance of baseline at 0.3% and 1.2% on NTU RGB+D and NTU RGB+D 120 datasets, respectively.

• 한국임상약학회지
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• 제21권2호
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• pp.66-73
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• 2011

The objective of this study was to evaluate the recognition and performance rates about the safety rules on hazardous drugs among the selected pharmacists. The 160 pharmacists working in 4 general hospitals and in the other 4 institutions specialized in the oncology division were surveyed through mail. Among the 137 respondents to the survey (response rate 85.6%), 111 pharmacists (81%) had recognized the terms of 'hazardous drugs'. In categories of vaccines and hormones, the degrees of the recognition rate were much lower than the cytotoxic medications. It was surveyed that the degree of recognition and performance of safety rules on injectable drugs were higher than the disposal and noninjectable medications. The higher recognition rate of the safety rules made the higher degree of performance. These results were expected to provide the incentive for guidelines on handling hazardous drugs based on Korean healthcare system.

• 한국임상보건과학회지
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• 제8권2호
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• pp.1398-1407
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• 2020

Purpose: The purpose of this study is a technical study to understand the relationship between the recognition and performance of core basic nursing skills of nursing college students who are ahead of clinical practice, and satisfaction with their major. Method: The subjects were 208 second-year students enrolled in the four-year nursing department located in J City and C City. General characteristics, characteristics of clinical practice, and recognition of the importance of core basic nursing skills, performance, and satisfaction with majors were investigated. Descriptive statistics, t-test, analysis of variance, multiple regression analysis and IPA are performed for data analysis Results: The results are follows. The results are follows. First, the performance was lower than that of the core basic nursing skills (p<.001). As a result of comparing the importance recognition and performance of the core basic nursing items, the importance recognition was significantly compared to the performance level in all 20 items. It showed high results. Second, it was found that there was a significant positive correlation (r=.40, p<.01) with major satisfaction in core basic nursing performance. Conclusion: These results highlight the need to develop education. It is necessary to establish a learning strategy through various learning guidance methods and self-directed learning that can improve the performance of items with low performance, although recognized as important through the Core Basic Nursing IPA for nursing students who are about to practice clinical practice. It is suggested to do repeated research applied.

• 대한임베디드공학회논문지
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• 제8권4호
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• pp.219-225
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• 2013

This paper presents a method using Maximum-Likelihood Linear Regression (MLLR) adaptation to improve recognition performance of Limabeam algorithm for speech recognition using microphone array. From our investigation on Limabeam algorithm, we can see that the performance of filtering optimization depends strongly on the supporting optimal state sequence and this sequence is created by using Viterbi algorithm trained with HMM model. So we propose an approach using MLLR adaptation for the recognition of speech uttered in a new environment to obtain better optimal state sequence that support for the filtering parameters' optimal step. Experimental results show that the system embedded with MLLR adaptation presents the word correct recognition rate 2% higher than that of original calibrate Limabeam and also present 7% higher than that of Delay and Sum algorithm. The best recognition accuracy of 89.4% is obtained when we use 4 microphones with 5 utterances for adaptation.

• 동력기계공학회지
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• 제15권5호
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• pp.83-90
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• 2011

In general, 20-high Sendzimir mills(ZRM) use small diameter work rolls to provide massive rolling force. Because of small diameter of work rolls, steel strip has a complex shape mixed with quarter, edge and center waves. Especially when the shape of the strip is controlled automatically, the actuator saturation occurs. These problems affect the productivity and quality of products. In this paper, the problems in automatic shape control of ZRM were analyzed. In order to evaluate the problems for the automatic shape control in ZRM, recognition performance was analyzed by comparing the measured shape and the recognized shape. The actuator positions by the shape recognition and the manual operation were compared. From the analysis results, the necessity of the improvement of recognition performance in ZRM is suggested.

• 대한음성학회지:말소리
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• 제50호
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• pp.99-110
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• 2004

The normal transmission characteristics of sound are hardly obtained due to the various noises and structural factors in a running car environment. It is due to the channel distortion of the original source sound recorded by microphones, and it seriously degrades the performance of the speech recognition in real driving environments. In this paper we analyze the degree of intelligibility under the various sound distortion environments by channels according to driving speed with respect to speech transmission index(STI) and compare the STI with rates of speech recognition. We examine the correlation between measures of intelligibility depending on sound pick-up patterns and performance in speech recognition. Thereby we consider the optimal location of a microphone in single channel environment. In experimentation we find that high correlation is obtained between STI and rates of speech recognition.

• Biomolecules & Therapeutics
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• 제16권3호
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• pp.173-178
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• 2008

Several lines of evidence indicate that scopolamine as a nonselective muscarinic antagonist disrupts object recognition performance and spatial working memory when administered systemically. In the present study, we investigated the different effects of scopolamine on acquisition, consolidation, and retrieval phases of object recognition performance and spatial working memory using the object recognition and the Morris water maze tasks in mice. In the acquisition phase test, scopolamine decreased recognition index on object recognition task and the trial 1 to trial 2 differences on Morris water maze task. In the consolidation and retrieval phase tests, scopolamine also decreased recognition index on object recognition task, where as scopolamine did not exhibited any effects on the Morris water maze task.

• 전기학회논문지
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• 제64권9호
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• pp.1347-1355
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• 2015

In this study, we compare the recognition performance using PCA and RBFNNs for introducing robust face recognition system to pose variations based on pose estimation. proposed face recognition system uses Honda/UCSD database for comparing recognition performance. Honda/UCSD database consists of 20 people, with 5 poses per person for a total of 500 face images. Extracted image consists of 5 poses using Multiple-Space PCA and each pose is performed by using (2D)²PCA for performing pose classification. Linear polynomial function is used as connection weight of RBFNNs Pattern Classifier and parameter coefficient is set by using Particle Swarm Optimization for model optimization. Proposed (2D)²PCA-based face pose classification performs recognition performance with PCA, (2D)²PCA and RBFNNs.