• 전자공학회논문지B
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• 제28B권7호
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• pp.548-556
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• 1991

In this paper, Korean spoken continuous digits are ercognized using DHMM(Dynamic Hidden Markov Model) and lexical analysis to provide the base of developing voice dialing system. After segmentation by phoneme unit, it is recognized. This system can be divided into the segmentation section, the design of standard speech section, the recognition section, and the lexical analysis section. In the segmentation section, it is segmented using the ZCR, O order LPC cepstrum, and Ai, parameter of voice speech dectaction, which is changed according to time. In the standard speech design section, 19 phonemes or syllables are trained by DHMM and designed as a standard speech. In the recognition section, phomeme stream are recognized by the Viterbi algorithm.In the lexical decoder section, finally recognized continuous digits are outputed. This experiment shiwed the recognition rate of 85.1% using data spoken 7 times of 21 classes of 7 continuous digits which are combinated all of the occurence, spoken by 10 man.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1989년도 추계학술대회 논문집 학회본부
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• pp.481-483
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• 1989

This paper is concentrated on the recognition of Korean Digits. The speech signals of each of digits are fed into computer through the 18 bandpass filters, AD converter. Spectrum input data are analyzed and used. BASIC program language is used for recognition performance and the result of recognition is outputed to computer screen and printer. In this paper, the strength and weakness of filter-bank analysis method is described and the technique of real-time recognition is argued. In this experiment, Ratio of recognition for speaker dependent recognition was about 97% and recognition time was also satisfied. Therefore, A way of speaker independent recognition will be presented and using for special communication in the future.

• 한국임상수의학회지
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• 제9권2호
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• pp.367-372
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• 1992

To investigate the effect of neck collars for the protection of self-mutilation, attainable sites of the body in dogs with collars and durability of collars were examined for 7 days. The collars used in the present experiment were hand made plastic basket collar, IASIS$\^$R/ ( heat moldable plastics), commerical plastic and cardboard collars The hand made plastic basket collar was made of basket which could buy at any supermarkets. The dogs with hand made plastic basket collar and IASIS$\^$R/ which was cast from the neck to the scapular region could lick only on digits of the forelimb. However, the dogs with commercial plastic and cardboard collars could lick not only the digits of forelimb but femur and digits of the hindlimb. It was suggested that hand made plastic basket collar was superior to the other collars in easiness of putting, durability, protection of self mutilation and economy.

• 대한수학회보
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• 제51권5호
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• pp.1325-1337
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• 2014

In this paper we study the sequences defined by the last and the last non-zero digits of $n^n$ in base b. For the sequence given by the last digits of $n^n$ in base b, we prove its periodicity using different techniques than those used by W. Sierpinski and R. Hampel. In the case of the sequence given by the last non-zero digits of $n^n$ in base b (which had been studied only for b = 10) we show the non-periodicity of the sequence when b is an odd prime power and when it is even and square-free. We also show that if $b=2^2{^s}$ the sequence is periodic and conjecture that this is the only such case.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1995년도 제12회 음성통신 및 신호처리 워크샵 논문집 (SCAS 12권 1호)
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• pp.69-72
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• 1995

In this paper, a new approach for Korean connected digits recognition using the spatio-temporal neural network is reported. The data of seven digits phone numbers are used in the recognition of connected words, and in the initial experiment, digit recognition rate of 28% was achieved. In this paper, to increase recognition rate, two different approaches are analyzed. In the first system, to compensate the STNN's own defect and to emphasize the Korean word's phonic characters, the starting point of phone is pointed by comparing the average magnitude and zero-crossing rate and the ending point is pointed by comparing only zero-crossing rate. The digit recoginiton rate increased to 61%. Also, in the second system, to consider fact that same word's phone is varied severally, the number of STNN's of each word is increased from one to five, and then the varied same word's phones can be included to the increased STNN's. The digit recogniton rate of connected words increased to 89%.

• 품질경영학회지
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• 제19권1호
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• pp.163-169
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• 1991

This paper studies computer programming for Two-Way Layout with Multiple Observations - Fixed Model using the subroutines of the former paper. The following items are considered in the PC computer programming: * significant digits in the computation of Sum of Squares * containing the necessary F-distribution values in the program * including the necessary estimation after the Analysis of Variance * following the rules of KS A 0021 in rounding off digits etc. The running results of Analysis of Variation Table and Estimations of a fictitious example is added with the parts of PC program. It should be mentioned that the main purpose of this paper is in the arousing of the discussion about significant digits concept in the PC computer programming for various kinds of Statistical Methods.

• Archives of Reconstructive Microsurgery
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• 제25권2호
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• pp.60-64
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• 2016

Segmental amputation of the digits and hand has been described as a contraindication for replantation because of poor results. We report the results of replantation for a patient who experienced multi-segment amputation of the hand. A 39-year-old man presented six hours after an accident, while using a straw cutter, that caused a multi-segment amputation of the entire palm and digits. The replantation surgery took 18 hours. We observed the patient gain satisfactory function of the hand. For replantation of a multi-segment amputation, connecting as many blood vessels as possible without tension is most important.

• 정보학연구
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• 제9권4호
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• pp.65-74
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• 2006

The back propagation of neural networks has the problems of falling into local minimum and delay of the speed by the iterative learning. An algorithm to solve the problem and improve the speed of the learning was already proposed in[8], which updates the learning parameter related with the connection weight. In this paper, we propose the algorithm generating initial weight to improve the efficiency of the algorithm by offering the difference between the input vector and the target signal to the generating function of initial weight. The algorithm proposed here can classify more than 98.75% of the handwritten digits and this rate shows 30% more effective than the other previous methods.

• 반도체디스플레이기술학회지
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• 제19권4호
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• pp.130-134
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• 2020

This paper proposes a new method for the digit recognition on a 7-segment display. The proposed method uses morphological processing that dilates segments of digits and connects them into strokes. The digits are extracted by connected component analysis and finally, template matching method recognizes the extracted digits. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. Experiments were conducted by using various 7-segment LED displays and 7-segment mono LCD displays. The results show that the proposed method is successful for the digit recognition on the 7-segment displays.

• 센서학회지
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• 제30권1호
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• pp.15-19
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• 2021

Image processing is one of the major techniques that are used for computer vision. Nowadays, researchers are using machine learning and deep learning for the aforementioned task. In recent years, digit recognition tasks, i.e., automatic meter recognition approach using electric or water meters, have been studied several times. However, two major issues arise when we talk about previous studies: first, the use of the deep learning technique, which includes a large number of parameters that increase the computational cost and consume more power; and second, recent studies are limited to the detection of digits and not storing or providing detected digits to a database or mobile applications. This paper proposes a system that can detect the digital number of meter readings using a lightweight deep neural network (DNN) for low power consumption and send those digits to an Android mobile application in real-time to store them and make life easy. The proposed lightweight DNN is computationally inexpensive and exhibits accuracy similar to those of conventional DNNs.