• Journal of Physiology & Pathology in Korean Medicine
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• v.22 no.6
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• pp.1347-1353
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• 2008

Pulse condition is the essential division for conducting pulse diagnosis which is one of the most fundamental and important diagnostics in traditional Korean/Chinese medicine. We studied the pulse condition referred to classics of traditional medicine for a full understanding in present time and come to a conclusion like below. The reference to pulse condition was concluded to 'twenty four pulse conditions' which is the fundamental conception generally accepted in present age since it had first mentioned in "Huangdi Neijing" and after it had passed through "Nanjing", "pulse pattern identification-chapter of normal pulse"of Zhang Zhongjing and reached "Maijing"of Wang Shuhe. Although medical partitioners had different views to some extent about pulse condition, there were no significant differences in the main theoretical frame. Even though there had been a diversity of opinions on the classification of pulse-condition between various medical practitioners, the method of Dae-dae and the method of systematic endeavored by Zhou Xueting and Zhou Xuehai who were medical scholars in the Ch'ing dynasty have been a criterion for the classification of pulse-condition up to date. We were able to recognize that the change of pulse condition caused by pathological situation should be compared to physiological pulse condition for detecting the deficiency and excess by researching the analyzing methods of pulse condition mentioned in the "Lingshu", and the book of Hua Shou and Zhou Xuehai). To sum up, first normal pulse which is the physiological pulse condition should be a standard for detecting physiological pulse condition. Secondly, Zhou Xueting insisted that relaxed pulse should be a standard pulse condition for detecting normal pulse.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.7
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• pp.1346-1367
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• 2011

As the size of camera modules is decreasing and as the computing performance of portable devices is improving, taking photos has become a part of daily life. However, existing photo management programs and products that manage such photos still require extensive user effort to facilitate the sharing and browsing of images. It is especially difficult for novice users to manage and share photos. In this paper, we develop a round-robin concept-driven user preference feedback mechanism for achieving direct photo sharing, instant display, and easy management using optimized user controls and user preference-driven classification. Compared with commercial photo management systems, our proposed solution provides new features: optimized user controls, direct sharing and instant display, and user preference feedback driven classification. These new features boost the round-robin concept-driven user preference feedback. This paper proposes a photo finder that automatically searches for photos in storage spaces or cameras. The proposed photo finder relies on user preference feedback to share photos by leveraging user preferences, and the round-robin connection transmits photos to the family's digital photo frame or web album by arbiter. The proposed method saves time and spares users the effort required for photo management. Moreover, this method does not merely direct photo sharing and simple photo management, but it also increases the satisfaction level of users viewing the photos.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.653-662
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• 2002

Fingerprint recognition is a task to find a matching pattern in a database for a specific persons fingerprint. To accomplish this task, preprocessing, classification, and matching steps are taken for a large-scale fingerprint database but only the matching step is taken without classification for a small-scale database. The primary matching method is based on minutiae (ridge ending point, bifurcation). This matching method, however, requires a very complex computation to extract minutiae and match minutiae-to-minutiae accurately due to translation, rotation, nonlinear deformation of fingerprint and occurrence of spurious minutiae. In addition, this method requires a laborious preprocessing step in order to improve the quality of fingerprint Images. This paper proposes a new simple method to eliminate these problems. With this method, Gabor variance is used instead of minutiae for fingerprint recognition. The Gabor variance is computed from Gabor features that result from filtering a fingerprint image through Gabor filter. In this paper, this method is described and its test result is shown, demonstrating the potential of using this new method for fingerprint recognition.

• ETRI Journal
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• v.36 no.5
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• pp.714-720
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• 2014

In this paper, we propose the use of data-driven probabilistic utterance-level decision logic to improve Weighted Finite State Transducer (WFST)-based endpoint detection. In general, endpoint detection is dealt with using two cascaded decision processes. The first process is frame-level speech/non-speech classification based on statistical hypothesis testing, and the second process is a heuristic-knowledge-based utterance-level speech boundary decision. To handle these two processes within a unified framework, we propose a WFST-based approach. However, a WFST-based approach has the same limitations as conventional approaches in that the utterance-level decision is based on heuristic knowledge and the decision parameters are tuned sequentially. Therefore, to obtain decision knowledge from a speech corpus and optimize the parameters at the same time, we propose the use of data-driven probabilistic utterance-level decision logic. The proposed method reduces the average detection failure rate by about 14% for various noisy-speech corpora collected for an endpoint detection evaluation.

• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.117-120
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• 1993

In this paper, we explore the possibility of URAN(Universally Reconstructable Artificial Neural-network) VLSI chip for speech recognition. URAN, a newly developed analog-digital hybrid neural chip, is discussed in respects to its input, output, and weight accuracy and their relations to its performance on speaker independent digit recognition. Multi-layer perceptron(MLP) nets including a large frame input layer are used to recognize a digit syllable at a forward retrieval. The simulation results using the full and limited floating precision computations for the input, output, and weight variables of the network give the comparable classification performance. An MLP with piecewise linear hidden and output units is also trained successfully using low accuracy computation.

• Journal of the Korean Institute of Landscape Architecture
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• v.26 no.1
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• pp.59-69
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• 1998

This research was conducted to suggest some directions for desirable urban green space planning through 1) establishing a new classification system by examining the existing concept, problems and characteristics of green space and 2) defining the essence of green space environment and finding some analytical and evaluative methods through a clear establishment of functions, indicators of green space. An analytical technique of green space, in which the coexistent relationship of human and other organisms was emphasized, was tried in order to realize urban green space planning. Based on the relevancy between green space and human being, green space was classified into green space for existence green space for utility, green space for both of existence and utility. The ratio of green covered, the ratio of greenery within the frame of vision, and the ratio of green volume in green space for existence was used as analytic and evaluative indicators.

• Journal of the Korean Institute of Landscape Architecture
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• v.25 no.3
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• pp.56-65
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• 1997

This research was conducted to suggest some directions for desirable urban green space planning through 1) establishing a new classification system by examining the existing concept, problems and characteristics of green space and 2) defining the essence of green space environment and finding some analytical and evaluative methods through a clear establishment of functions, indicators of green space. In the research, measurements of the amount of green space was accompanied with measurements of green covered space, green volume, and the structure of greenery within the frame of vision. As result, three-dimensional measurement was possible, three-dimensional measurement was possible, which turned out to be more effective than the existing 2-dimensional measuring method. It is found that the ratio of green covered space is to proportional to the ratio of green volume in this study. Therefore in green space planning process it is desirable to consider the ratio of green volume all together.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.287-289
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• 2005

This paper presents a hybrid neural network system which used a Self-Organizing Map and Multilayer Perceptron for the problem of Malay syllables speech recognition. The novel idea in this system is the usage of a two-dimension Self-organizing feature map as a sequential mapping function which transform the phonetic similarities or acoustic vector sequences of the speech frame into trajectories in a square matrix where elements take on binary values. This property simplifies the classification task. An MLP is then used to classify the trajectories that each syllable in the vocabulary corresponds to. The system performance was evaluated for recognition of 15 Malay common syllables. The overall performance of the recognizer showed to be 91.8%.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.11
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• pp.114-125
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• 1997

This paper presents a method that automatically recognizes dimension sets from the mechanical drawings, and that classifies 6 types dimension sets according to functional purpose. In the proposed method, the object and closed-loop symbols are separated from the character-free drawings. Then object lines and interpretation lines are vectorized. And, after recognizing dimension sets(consistings of arrowhead, shape line, tail lines, extension lines, text-string, and feature control frame), we classify recognized dimension sets as horizontal, vertical, angular, diametral, radial, and leader dimension sets. Finally the proposed method converts classified dimension sets into AutoCAD data by using AutoLisp language. By using the methods of geometric modeling, the proposed method readily recognized and classifies dimension sets from complex drawings. Experimetnal results are presented, which are obtained by applying the proposed method to drawings drawn in compliance with the KS drafting standard.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3534-3549
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• 2020

The traditional method of smoke image recognition has low accuracy. For this reason, we proposed an algorithm based on the good group of IMFOA which is GMFOA to optimize the parameters of SVM. Firstly, we divide the motion region by combining the three-frame difference algorithm and the ViBe algorithm. Then, we divide it into several parts and extract the histogram of oriented gradient and volume local binary patterns of each part. Finally, we use the GMFOA to optimize the parameters of SVM and multiple kernel learning algorithms to Classify smoke images. The experimental results show that the classification ability of our method is better than other methods, and it can better adapt to the complex environmental conditions.