• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2019.05a
• /
• pp.521-524
• /
• 2019

The design of photobiological active photosensitizing molecular model for photodynamic therapy has been attracted as a research for the development of cancer treatment, and has been interested in the effective method for cancer treatment and the photosensitizer having more stable wavelength. Furthermore, the development of photosensitizer has been already carried out from the first generation molecule to the third one, and the research of smart photosensitizer as the fourth generation has been requested. As a fact, the selective killing of the only cancer cell is very difficult problem, and the present photodynamic therapy has the problem of killing of the normal cell. So, I have designed the new modelling of photosensitizer having the smart recognizing unit and the magnetic nanoparticle as well as having the several effective recognizing unit. In particular, the new model design of the photosensitizer having lanthanide metal has suggested for the development of photodynamic therapy. The model design of these new photosensitizing molecules will be introduced in the poster section for the new turning point of the development of photosensitizer.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.617-619
• /
• 2021

Since Manchu characters are written vertically and are connected without spaces within a word, a preprocessing process is required to separate the character area and the units that make up the characters before recognizing the characters. In this paper, we describe a preprocessing method that extracts the character area and cuts off the unit of the character. Unlike existing research that presupposes a method of recognizing each word or character unit, or recognizing the remaining part after removing the stem of a continuous character, this method cuts the character into each recognizable unit. It can be applied to the method of recognizing letters by combining the units. Through an experiment, the effectiveness of this method was verified.

• Proceedings of the KIEE Conference
• /
• 2002.11c
• /
• pp.411-413
• /
• 2002

In this paper we researched about the ultrasonic cane which aids the blind to walk. We used ultrasonic in recognizing the object and implemented pulse counting method in measuring the distance. The distance measuring system consists of transmitter unit, receiver unit and micro-processor. We used broadband ultrasonic sensors in transmitter unit and receiver unit. The blind is able to recognize the distance between obstacles and himself as it used a vibration system.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.27 no.6
• /
• pp.861-870
• /
• 1990

A method of recognizing objects is proposed that uses a concept of modified incremental circle transform. The modified incremental circle transform, which maps bundaries of an object into an unit circle, represnets efficiently the shape of the boundaries detected in digitized binary images of the objects. It is proved that modified incremental circle transform of object, which is invariant under object translation, rotation, and size, can be used as feature information for recognizing two dimensional polygonal object efficiently.

• Journal of Korean Elementary Science Education
• /
• v.26 no.5
• /
• pp.551-557
• /
• 2007

The purpose of this study was to examine the questions in the 'Matter' units of elementary science textbooks under the 7th curriculum. For the analysis, a total of 338 questions were extracted from 15 units. Six criteria (recalling, recognizing, predictive, applied, divergent, and evaluative question) were reconstructed for textbook question analysis based on Blosser(1973)'s question category system for science. The results were as follows. First, there were more closed (recalling, recognizing, predictive, or applied) questions (72.2%) than open (divergent or evaluative) questions (27.8%) in elementary science textbooks. Second, cognitive-memory (recalling or recognizing) question type was the most frequently asked in all grade levels. Open (divergent or evaluative) questions increased according to grade level whereas convergent (predictive or applied) questions decreased. Third, question types were applied based on the characteristics of each unit rather than on children's developmental characteristics. Educational implications were discussed based on the results.

• Proceedings of the KIEE Conference
• /
• 1987.07b
• /
• pp.1061-1064
• /
• 1987

This paper describes the procedure of recognizing the On-line Korean characters which are written on a graphic tablet. The effective recognition of primitives is performed by the use of stroke unit proceeding instead of coordinate unit under the base of definition of characteristic points which are fit to Korean character through the application of the characteristics of korean characters & input data on graphic tablet.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2004.05a
• /
• pp.409-412
• /
• 2004

Plot Units는 이야기를 형성하는 줄거리 또는 줄거리에 나오는 여러 사건을 하나로 구성하여 표현하는 단위이다. 한편, 개연규칙은 문장간 구성성분들의 개연적인 결속성을 나타낸다. 이러한 결속은 개연사슬로 나타낼 수 있다. 개연사슬은 개념을 연결하는 어휘들과 그 연결을 설명하는 관계들의 목록이다. 이중에서 기능관계순열로는 해당 개연규칙을 보다 개념적으로 설명할 수 있다. 본 논문에서는 이러한 기능관계순열을 분석하고 Plot Units과 비교해 보았다. 실험을 통하여 주어진 기능관계순열이 Plot Units의 어떤 유형에 해당하는지 알 수 있었다.

• Journal of the Korean Society of Industry Convergence
• /
• v.27 no.1
• /
• pp.183-193
• /
• 2024

Recurrent Neural Network technology that learns past patterns and predicts future patterns using technology for recognizing and classifying objects is being applied to various industries, economies, and languages. And research for practical use is making a lot of progress. However, research on the application of Recurrent Neural Networks for evaluating and predicting the safety of mechanical structures is insufficient. Accurate detection of external load applied to the outside is required to evaluate the safety of mechanical structures. Learning of Recurrent Neural Networks for this requires a large amount of load data. This study applied the Gated Recurrent Unit technique to examine the possibility of load learning and investigated the possibility of applying a stacked Auto Encoder as a way to secure load data. In addition, the usefulness of learning mechanical loads was analyzed with the Gated Recurrent Unit technique, and the basic setting of related functions and parameters was proposed to secure accuracy in the recognition and prediction of loads.

• KIISE Transactions on Computing Practices
• /
• v.23 no.5
• /
• pp.316-321
• /
• 2017

We analyze the online Hangul handwriting recognition problem (HHR) and present solutions based on recurrent neural networks. The solutions are organized according to the three kinds of sequence labeling problem - sequence classifications, segment classification, and temporal classification, with additional consideration of the structural constitution of Hangul characters. We present a stacked gated recurrent unit (GRU) based model as the natural HHR solution in the sequence classification level. The proposed model shows 86.2% accuracy for recognizing 2350 Hangul characters and 98.2% accuracy for recognizing the six types of Hangul characters. We show that the type recognizing model successfully follows the type change as strokes are sequentially written. These results show the potential for RNN models to learn high-level structural information from sequential data.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10b
• /
• pp.61-64
• /
• 1992

In this paper, a visual pattern recognition system is proposed, which can recognize both a pattern and its location. This system, referred to as the expanded neocognitron, has the following capabilities: (1) A higher performance in extraction of features, and (2) A new capability for recognizing the locations of patterns. This system adopts the learning and recognizing mechanism of the neocognitron. First, the ability to classify pattern is enhanced by improving the mechanisms of feature extraction and learning algorithm. Second, the function of detecting the location of each pattern is realized by developing an architecture which does not reduce structure, i.e., the unit density is constant all the way from the input stage to the output stage.