• The KIPS Transactions:PartB
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• v.10B no.7
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• pp.769-776
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• 2003

DNA computing has used to solve MCP (Maximal Clique Problem). However, when current DNA computing is applied to MCP. it can't efficiently express vertices and edges and it has a problem that can't look for solutions, by misusing wrong restriction enzyme. In this paper we proposed ACO (Algorithm for Code Optimization) that applies DNA coding method to DNA computing to solve MCP's problem. We applied ACO to MCP and as a result ACO could express DNA codes of variable lengths and generate codes without unnecessary vertices than Adleman's DNA computing algorithm could. In addition, compared to Adleman's DNA computing algorithm, ACO could get about four times as many as Adleman's final solutions by reducing search time and biological error rate by 15%.

• Korean Journal of Occupational Health Nursing
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• v.17 no.2
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• pp.155-165
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• 2008

Purpose: The purpose of this study was to investigate the condition, recognition of breast feeding of 273 nurses. Method: Data was collected using a structured questionnaire form April to June 2007. The subjects were 273 nurses in Kyunggido. The data analysis was done with descriptive statistics, $x^2$-test procedures using SPSS/WIN 12.0 PC. Result: There are 23.9% of child day care center, 5.2% of rest room for women, 16.8% of breast feeding room in workplace. Rate of breast-feeding practice was 78.4% of nurses. The reasons why they could not perform the breast-feeding include mother's job(45.4%), lacking breast milk(25.8%). The characteristics of nurses found to be related breast-feeding include age, number of employers. Conclusion: The results showed that the rest supports of the work environment was insufficient to perform breast-feeding in the workplace. These results suggest that nursing intervention for employed mother's breast-feeding practice behavior promotion should focus on characteristics influencing factors on workplace. Also, efficient breast-feeding education program for employed mothers should be developed by continuous qualitative researches based on breast-feeding experiences of employed mothers.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.1
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• pp.20-28
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• 1989

The recognition of partially occluded objects is of prime importance for industrial machine vision applications and to solve real provlems in factory automation. This paper describes a method tc solve the problem of occlusion in a two dimensional scene. The technique consists of three steps: searching of border, extracting of line segments and clustering of hypotheses by matching probability. Computer simulation results have been tested for 20 scenes contained the 80 models, and have obtained 95% of properly correct recognition rate on the average.

• The Journal of the Acoustical Society of Korea
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• v.18 no.8
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• pp.3-8
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• 1999

Previous variable vocabulary speech recognition systems with context-independent acoustic modeling, could not represent the effect of neighboring phonemes. To solve this problem, we use allophone-based context-dependent acoustic model. This paper describes the method to improve acoustic model of the system effectively. Acoustic model is improved by using allophone clustering technique that uses entropy as a similarity measure and the optimal allophone model is generated by changing the number of allophones. We evaluate performance of the improved system by using Phonetically Optimized Words(POW) DB and PC commands(PC) DB. As a result, the allophone model composed of six hundreds allophones improved the recognition rate by 13% from the original context independent model m POW test DB.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.378-390
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• 2015

Image projectors can turn any surface into a display. Integrating a surface projection with a user interface transforms it into an interactive display with many possible applications. Hand gesture interfaces are often used with projector-camera systems. Hand detection through color image processing is affected by the surrounding environment. The lack of illumination and color details greatly influences the detection process and drops the recognition success rate. In addition, there can be interference from the projection system itself due to image projection. In order to overcome these problems, a gesture interface based on depth images is proposed for projected surfaces. In this paper, a depth camera is used for hand recognition and for effectively extracting the area of the hand from the scene. A hand detection and finger tracking method based on depth images is proposed. Based on the proposed method, a touch interface for the projected surface is implemented and evaluated.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.54-61
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• 2008

This paper proposes a new algorithm for detecting and recognizing overlapped objects among a stack of arbitrarily located objects using a signature representation scheme. The proposed algorithm consists of two processes of detecting overlap of objects and of determining the boundary between overlapping objects. To determine overlap of objects, in the first step, the edge image of object region is extracted and those areas in the object region are considered as the object areas if an area is surrounded by a closed edge. For each object, its signature image is constructed by measuring the distances of those edge points from the center of the object, along the angle axis, which are located at every angle with reference to the center of the object. When an object is not overlapped, its features which consist of the positions and angles of outstanding points in the signature are searched in the database to find its corresponding model. When an object is overlapped, its features are partially matched with those object models among which the best matching model is selected as the corresponding model. The boundary among the overlapping objects is determined by projecting the signature to the original image. The performance of the proposed algorithm has been tested with the task of picking the top or non-overlapped object from a stack of arbitrarily located objects. In the experiment, a recognition rate of 98% has been achieved.

• The Journal of the Acoustical Society of Korea
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• v.19 no.1
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• pp.67-72
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• 2000

Particularly based on the signal bias removal(SBR) algorithm for compensating the corrupted speech, this paper presents a new algorithm which is independent of environments, minimizes the amount of computation, and is readily applicable to the conventional recognition system. To this end, a multiple-bias algorithm and a partial codebook search algorithm have been added to the conventional SBR algorithm. The simulation results show that combining the two algorithms proposed in this paper provides a reduction of computation time to 1/8 times as well as an improvement of the recognition rate from 77.58% of the conventional system to 81.32%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.12
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• pp.1465-1474
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• 1992

This paper describes a new overlapped object recognition method using extended local features. At first, we extract the extended local features consisting of corners, arcs, parallel-lines, and corner-arcs from the images consisting of model objects. Based on the extended local features we construct a knowledge-base. In order to match objects, we also extract the extended local features from the input image, and then check the compatibility between the extracted features and the features in the knowledge-base. From the set of compatible features, we compute geometric transforms. If any geometric transforms are clustered, we generate the hypothesis of the objects as the centers of the clusters, and then verify the hypothesis by a reverse geometric transform. An experiment shows that the proposed method increases the recognition rate and the accuracy as compared with existing methods.

• Journal of Korea Society of Industrial Information Systems
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• v.25 no.1
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• pp.13-23
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• 2020

In this paper, we propose a quantization parameter determination method for face depth image encoding in order to minimize an impact on a face recognition accuracy. When a face depth image is compressed through quantization in H.264/AVC, differential quantization parameters are assigned according to an accuracy of ellipsoid modeling prediction and an importance degree of a unit block in extracting facial features. The simulation results show that the face recognition success rates are improved by up to 6% at the same compression rates through the proposed compression rate determination method.

• Journal of Korean society of Dental Hygiene
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• v.7 no.4
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• pp.509-519
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• 2007

The purpose of this study was to take inforamtion to increase support on water fluoridation primary school teachers in Jinhae. The survey was done by self-administration method to primary school teachers 88 at non-fluoridated area in Jinhae. The date was analysed using the SPSS 10.1 program. The results are as follows : The mean percentage of the respondents using the tap water and purified water for drinking was 51.1% and 33.3%, respectively. Recognition rate of water fluoridation was 64.8%, 33.3% of the respondents knew about water fluoridation from mass mesdia. 62.5% of the respondents agreed with water fluoridation. 76.1% of the respondents knew that the purpose of water fluoridation was the prevention of dental caries. 72.7% of the respondents agreed with continuous water fluoridation. 70.5% of the recognized about safety of water fluoridation. 72.7% of the respondents agreed with decision of professional group for the performance of water fluoridation. In order to secure residents' support for the continuation of the adjusted water fluoridation program and to reinforce the education for safety and economical efficiency for the residents through systemic education.