• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1770-1782
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• 2011

A brain-computer interface (BCI) is a communication system that translates brain activity into commands for computers or other devices. In other words, BCIs create a new communication channel between the brain and an output device by bypassing conventional motor output pathways consisting of nerves and muscles. This is particularly useful for facilitating communication for people suffering from paralysis. Due to the low bit rate, it takes much more time to translate brain activity into commands. Especially it takes much time to input characters by using BCI-based typewriters. In this paper, we propose a brain-operated typewriter which is accelerated by a language prediction model. The proposed system uses three kinds of strategies to improve the entry speed: word completion, next-syllable prediction, and next word prediction. We found that the entry speed of BCI-based typewriter improved about twice as much through our demonstration which utilized the language prediction model.

• Conservation Science in Museum
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• v.28
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• pp.1-16
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• 2022

Treatment was performed to conserve the Underwood Typewriter (Hangi 6863) from the collection of the National Hangeul Museum. Since the typewriter was presumably manufactured in the modern or contemporary era and bore patterns of damage such as component loss, corrosion, and paint loss, as well as being made of multiple materials, a condition survey and a scientific analysis were conducted ahead of the conservation treatment in order to carry out appropriate treatments for each material. The analysis confirmed that the typewriter was made of various materials including metal, paint, and rubber, and the conservation treatment was performed in the sequence of removal of contamination, reinforcement, and restoration under conditions where each material was stable. Conservation treatment was completed in a stable state by strengthening the layer of damaged paint and restoring the lost leg. These processes have enabled a better understanding of the materials and characteristics of typewriters manufactured in the early modern era, which is expected to provide basic data for typewriter conservation research to be conducted in the future.

• Journal of Korean Institute of Industrial Engineers
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• v.5 no.1
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• pp.27-44
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• 1979

The purpose of this study is to detect the problems of the Korean typewriter keyboards, and to analyze and compare the standard keyboard with other keyboards. We find that the standard Korean keyboard has a lot of problems in terms of mechanical engineering and human factors engineering and that it is less efficient than Kong's keyboard.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.727-729
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• 1999

We have developed a realtime phonetic typewriter implemented on IBM PC with sound card based on Windows 95. In this system, analyzing of speech signal, learning of neural network, labeling of output neurons and visualizing of recognition results are performed on realtime. The developing environment for speech processing is established by adding various functions, such as editing, saving, loading of speech data and 3-D or gray level displaying of spectrogram. Recognition experimental using Korean phone had a 71.42% for 13 basic consonant and 90.01% for 7 basic vowel accuracy.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.1
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• pp.34-42
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• 2011

In an effort to the practical realization of phonetic typewriter, we concentrate on the classification of consonants in this paper. Since many of consonants do not show periodic behavior in time domain and thus the validity for Fourier analysis of them are not convincing, vector quantization (VQ) via LBG clustering is first performed to check if the feature vectors of MFCC and LPCC are ever meaningful for consonants. Experimental results of VQ showed that it's not easy to draw a clear-cut conclusion as to the validity of Fourier analysis for consonants. For classification purpose, two kinds of neural networks are employed in our study: self organizing map (SOM) and learning vector quantization (LVQ). Results from SOM revealed that some pairs of phonemes are not resolved. Though LVQ is free from this difficulty inherently, the classification accuracy was found to be low. This suggests that, as long as consonant classification by LVQ is concerned, other types of feature vectors than MFCC should be deployed in parallel. However, the combination of MFCC/LVQ was not found to be inferior to the classification of phonemes by language-moded based approach. In all of our work, LPCC worked worse than MFCC.

• Journal of Korean Library and Information Science Society
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• v.12
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• pp.199-232
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• 1985

Word processor having the functions of a typewriter and a computer together have been used as a powerful tools for office automation. The purpose of this study is to find out the possible areas of the word processing a n.0, pplication in the library operations. For the study, the general concept, developmental process, structure, functions, kinds and suggested a n.0, pplicable areas in the library operations of word processor were investigated. Then, the cases of real a n.0, pplications of word processor in the library field were examplified. In conclusion, the areas where word processor can be of benefit to library workers can be summarized as follows, 1) Orders of books and periodical acquisitions, 2) On-line searching, and storage and editing of input as required, 3) Production of catalogues, and abstracting and indexing bulletin, 4) Budget control, circulation control, and serial control.

• MALSORI
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• no.39
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• pp.43-51
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• 2000

The aim of this paper is to present a phonetically oriented keyboard array for the International Korean Phonetic Alphabet (IKPA). IKPA is a phonetic alphabet devised on the basis of Hangout (Korean alphabet) (Lee, 1999). Every computer has a keyboard as its input device and the English keyboard array is hewn as 'QWERTY' system, which represents the first six letters of the second line of the keyboard. This array is a traditional one devised to protect the congestion of the keys of the mechanical typewriter. To improve the anay of the keyboard, another system named 'Dvorak' has been devised. Likewise, a serious attempt has been made by the authors to work out an efficient keyboard for IKPA representing the manner of vowel and consonant classification. In the phonetic keyboard, the consonant symbols are arranged in the left hand side according to the Place and mauler of the articulation and the vowel symbols in the right hand side according to the vowel quadrilateral.

• Annual Conference on Human and Language Technology
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• 2010.10a
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• pp.143-146
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• 2010

뇌-컴퓨터 인터페이스는 뇌에서 발생하는 생체신호를 통하여 컴퓨터나 외부기기를 직접 제어할 수 있는 기술이다. 자발적으로 언어를 생성하지 못하는 환자들을 위하여 뇌-컴퓨터 인터페이스를 이용하여 한국어를 자유롭게 입력할 수 있는 인터페이스에 대한 연구가 필요하다. 본 연구는 의사소통을 위한 뇌-컴퓨터 인터페이스에서 낮은 정보전달률을 개선하기 위해서 음절 n-gram과 어절 n-gram 모델을 이용하여 언어 예측 모델을 구현하였다. 또한 실제 이를 이용한 뇌 컴퓨터 한국어 입력기를 설계하였다, 이는 기존의 뇌-컴퓨터 인터페이스 연구에서 특징 추출이나 기계학습 방법의 성능향상을 위한 연구와는 차별적인 방법이다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.3
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• pp.317-321
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• 2003

A conventional typewriter types letters by hammering a carbon ribbon which is attached at a paper. The laser typing process which write a micro pattern of Chrome on a silicon wafer has been developed. A glass that is coated with 100 nm Chrome (Carbon ribbon) is attached on a silicon wafer (paper). An Nd-Yag laser (hammer) is irradiated on the glass, and the Chrome is transferred on the silicon wafer. Micro patterns are made by controlling laser beam trajectory. The suggested micro pattering can be used at the high density data storage of TeraBit/in$^2$ or at the improvement of productivity of semiconductor manufacturing procedure.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.3 no.4
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• pp.245-250
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• 2002

This paper presents a priori and the local font classification method. The font classification uses ascenders, descenders, and serifs extracted from a word image. The gradient features of those sub-images are extracted, and used as an input to a neural network classifier to produce font classification results. The font classification determines 2-font styles (upright or slant), 3-font groups (serif, sans serif, or typewriter), and 7-font names (PostScript fonts such as Avant Garde, Helvetica, Bookman, New Century Schoolbook, Palatino, Times, or Courier). The proposed a priori and local font classification method allows an OCR system consisting of various font-specific character segmentation tools and various mono-font character recognizers.