• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.143-151
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• 2010

Fingerprint classification is a step to increase the efficiency of an 1:N fingerprint recognition system and plays a role to reduce the matching time of fingerprint and to increase accuracy of recognition. It is difficult to classify fingerprints, because the ridge pattern of each fingerprint class has an overlapping characteristic with more than one class, fingerprint images may include a lot of noise and an input condition is an exceptional case. In this paper, we propose a novel approach to design a stochastic model and to accomplish fingerprint classification using a directional characteristic of fingerprints for an effective classification of various qualities. We compute the directional value by searching a fingerprint ridge pixel by pixel and extract a directional characteristic by merging a computed directional value by fixed pixels unit. The modified Markov model of each fingerprint class is generated using Markov model which is a stochastic information extraction and a recognition method by extracted directional characteristic. The weight list of classification model of each class is decided by analyzing the state transition matrixes of the generated Markov model of each class and the optimized value which improves the performance of fingerprint classification using GA (Genetic Algorithm) is estimated. The performance of the optimized classification model by GA is superior to the model before the optimization by the experiment result of applying the fingerprint database of various qualities to the optimized model by GA. And the proposed method effectively achieved fingerprint classification to exceptional input conditions because this approach is independent of the existence and nonexistence of singular points by the result of analyzing the fingerprint database which is used to the experiments.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.587-599
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• 2023

As climate change increasesthe frequency and risk of flooding in major cities around theworld, the importance ofsimulation technology that can quickly and accurately analyze high-resolution 2D flooding information in large-scale areasis emerging. The physically-based approaches based on the Shallow Water Equations (SWE) often requires huge computer resources hindering high-resolution flood prediction. This study investigated the theoretical background of Weighted Cellular Automata 2D (WCA2D), which simulates spatio-temporal changes offlooding using transition rules and weight-based system, and assessed feasibility to simulate pluvial flooding in the urbancatchment, theOncheon-cheon catchmentinBusan, SouthKorea.Inaddition,the computation performancewas compared by applying versions using OpenComputing Language (OpenCL) andOpenMulti-Processing (OpenMP) parallel computing techniques. Simulationresultsshowed that the maximuminundation depthmap by theWCA2Dmodel cansimilarly reproduce historical inundation maps. Also, it can precisely simulate spatio-temporal changes of flooding extent in the urban catchment with complex topographic characteristics. For computation efficiency, parallel computing schemes, theOpenCLandOpenMP, improved the computation by about 8~14 and 5~6 folds respectively, compared to the sequential computation.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.73-80
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• 2023

The recent steep increase in the minimum hourly wage has increased the burden of labor costs, and the share of unmanned stores is increasing in the aftermath of COVID-19. As a result, theft crimes targeting unmanned stores are also increasing, and the "Just Walk Out" system is introduced to prevent such thefts, and LiDAR sensors, weight sensors, etc. are used or manually checked through continuous CCTV monitoring. However, the more expensive sensors are used, the higher the initial cost of operating the store and the higher the cost in many ways, and CCTV verification is difficult for managers to monitor around the clock and is limited in use. In this paper, we would like to propose an AI image processing fusion algorithm that can solve these sensors or human-dependent parts and detect customers who perform abnormal behaviors such as theft at low costs that can be used in unmanned stores and provide cloud-based notifications. In addition, this paper verifies the accuracy of each algorithm based on behavior pattern data collected from unmanned stores through motion capture using mediapipe, object detection using YOLO, and fusion algorithm and proves the performance of the convergence algorithm through various scenario designs.

• Journal of IKEEE
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• v.25 no.3
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• pp.493-500
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• 2021

In this paper, we propose the development of deep learning structure to improve quality of polygonal containers. The deep learning structure consists of a convolution layer, a bottleneck layer, a fully connect layer, and a softmax layer. The convolution layer is a layer that obtains a feature image by performing a convolution 3x3 operation on the input image or the feature image of the previous layer with several feature filters. The bottleneck layer selects only the optimal features among the features on the feature image extracted through the convolution layer, reduces the channel to a convolution 1x1 ReLU, and performs a convolution 3x3 ReLU. The global average pooling operation performed after going through the bottleneck layer reduces the size of the feature image by selecting only the optimal features among the features of the feature image extracted through the convolution layer. The fully connect layer outputs the output data through 6 fully connect layers. The softmax layer multiplies and multiplies the value between the value of the input layer node and the target node to be calculated, and converts it into a value between 0 and 1 through an activation function. After the learning is completed, the recognition process classifies non-circular glass bottles by performing image acquisition using a camera, measuring position detection, and non-circular glass bottle classification using deep learning as in the learning process. In order to evaluate the performance of the deep learning structure to improve quality of polygonal containers, as a result of an experiment at an authorized testing institute, it was calculated to be at the same level as the world's highest level with 99% good/defective discrimination accuracy. Inspection time averaged 1.7 seconds, which was calculated within the operating time standards of production processes using non-circular machine vision systems. Therefore, the effectiveness of the performance of the deep learning structure to improve quality of polygonal containers proposed in this paper was proven.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.5
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• pp.74-86
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• 2015

The purpose of this study was to deduce the landscape evaluation indices that can be applied from the preparation for the registration of major national farm/fishery heritages to post-management. For this purpose, the Delphi survey was performed on experts. From August to November in 2014, the primary open survey, secondary open survey, and tertiary closed survey were performed to gather opinions from 28 experts, 25 experts, and 29 experts, respectively. As a result, the landscape evaluation indices for farm/fishery heritage consisted of five areas of evaluation, ten items of evaluation, and 40 indices of evaluation. The areas of evaluation were rurality, authenticity, aesthetics, tourism potentials, and locality. Rurality was classified into rurality of farm/fishery towns and nostalgia. Authenticity was classified into objective authenticity and existential authenticity. Aesthetics was classified into attractiveness and harmony. Tourism potentials were classified into value of resources and value of usability. Locality was divided into physical originality and cultural identity. The study made the following findings: first, the general grounds of farm/fishery landscape evaluation cannot be applied when evaluating the quality of landscapes of farm/fishery heritage, as their value as a cultural heritage should be considered. Second, the new indices valued emotional factors in addition to the physical factors considered by the existing farm/fishery landscapes. The new indices involved a more expanded concept of landscapes as it also considers everyday or temporary activities, including the farm/fishery activities of local people or participation in festivals and experience programs. Third, farm/fishery heritage focuses on the lives of local people, as it involves both the synchronic and the diachronic perspectives to see what is currently visible and what is no longer visible. This brings into consideration not only the farms and the natural environments but also their relationships with the villages, especially the residential areas. Finally, the indices reflected both the farm/fishery heritage's value as cultural heritage and its value for tourism. They derived temporary and dynamic landscapes, including the trading activities of local specialty markets in relation to the production landscapes. However, further studies should be conducted as this study could not rate the relative importance of indices or compare the total scores of landscapes without the weight of each item.

• The Journal of Korean society of community based occupational therapy
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• v.10 no.1
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• pp.39-49
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• 2020

Objective : The aim of this study was to investigate the care burden and life quality in family caregivers of community-dwelling patients using home mechanical ventilator(HMV) in Yeognam region. Methods : Survey performed to family caregivers of the patients using HMV in Yeognam region, Korea. The questionnaire is composed with patient care and the burden on caring. Korean version of Short Form Zarit Burden Interview(K-ZBI-12) and 3-Level version of EuroQol-5 Dimension applying Korean weight(KEQ-5D-3L) were also investigated. Statistical significance was accepted for p<.05. Results : A total 98 out of 150 questionnaires were analyzed. The K-ZBI-12(33.08±10.34) had a correlation with KEQ-5D-3L(0.71±0.25) negatively(p=.038). Patients' age, duration of HMV, financial burden and professional caregivers' care time had correlations with K-ZBI-12 positively(p<.05). KEQ-5D-3L correlated duration of HMV negatively(p=.017). Invasive ventilator group had lower KEQ-5D-3L than the non-invasive ventilator group(p=.008). K-ZBI-12 was lower in more than one caregiver care of patients than in one(p=.001). Conclusion : This study revealed high care burden and low quality of life in family caregivers of the patients with HMV in Yeongnam region, Korea. Efforts are needed to continually identify the needs of patients and their families, and the socioeconomic support and medical services associated with HMV.

• Journal of the Korean Institute of Landscape Architecture
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• v.39 no.3
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• pp.98-106
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• 2011

This study was performed with the purpose of providing basic data for the improvement of zoning regulations of urban nature park by analyzing the present problem which occurred during last 6 years from the year of 2005 when the program was introduced for the first time. The study was processed first by the analysis of the cases of problems evoked by citizens, second the other problems was delineated by interviews of officials, at last the validity of all of the problems was verified by a group of professionals through delphi method. The results can be summarized as follows. 1. In relation to the designation and management of urban national park areas, designation criteria, designation process, maintenance, laws and regulations and 20 other items were found to be problematic. After Delphi method, 5 items were removed and 2 added. The results showed that there were 17 problematic items in total. 2. Regarding the problem of criteria for designation, which are, lack of priority(weights), lack of objectivity due to the difficulty to use quantitative evaluation method, incompatibility for contaminated land environmental impact assessment, incompatibility of land suitability assessment, lack of detailed field survey standards, lack of national park area standards, and 6 other items. 3. Regarding the problem of designation process, which are, the occurrence of civil appeals for designating a new national park, the needs of feasibility study on the urban national park areas constructed before urban national park guidelines came out, lack of a comprehensive review of the boundaries set when determining national park area management plan, poor temporal and financial conditions for an accurate field survey, and 4 other items. 4. Regarding the problem of maintenance management, which are, lack of management system in each space, lack of effectiveness of Urban Nature Park Area Management Plan among master plans for park and green areas, the occurrence of dual managers due to dual natures such as purpose area and city park, lack of professional manpower to manage park areas, and 4 other items. 5. Regarding the problems of regulation guidelines, which are, lack of separate urban park area management plan, incompatibility of the permitted facilities in the park to the park area standards, lack of feasibility study on urban park areas, and 3 other items.

• Journal of Nutrition and Health
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• v.42 no.1
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• pp.38-47
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• 2009

The purpose of the study was to develop an eating habit checklist for screening elementary school children at risk of inadequate micronutrient intake. Eating habits, food intake, and anthropometric data were collected from 142 children (80 boys and 62 girls) in the $4^{th}$ to $6^{th}$ grades of elementary schools. Percentage of Recommended Intakes (RI) and Mean Adequacy Ratio (MAR) of six micronutrients; vitamin A, riboflavin, vitamin C, calcium, iron, zinc, and the number of nutrients the children consumed below EAR among the six nutrients were used as indices to detect the risk of inadequate micronutrient intake. Pearson correlation coefficients were calculated between eating habit scores and inadequate micronutrient intake indices in order to select questions included in the checklist. Meal frequency, enough time for breakfast, regularity of dinner, appetite, eating frequencies of Kimchi, milk, fruits and beans showed significant correlations with indices of inadequate micronutrient intake. Stepwise regression analysis was performed to give each item a different weight by prediction strength. To determine the cut-off point of the test score, sensitivity, specificity, and positive predictive values were calculated. The 8-item checklist with test results from 0 to 12 points was developed, and those with equal or higher than 6 points were diagnosed as high-risk group of inadequate micronutrient intake, and those with 4 or 5 points were diagnosed as moderate-risk group. Among our subjects 14.1% was diagnosed as high-risk group, and 30.3% as moderate-risk group. The proportions of the subjects who consumed below EAR of all micronutrients but vitamin C were highest in the high-risk group, and there were significant differences in the proportions of the subjects with intake below EAR of all micronutrients except vitamin B6 among the three groups. This checklist will provide a useful screening tool to identify children at risk of inadequate micronutrient intake.

• Journal of Nutrition and Health
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• v.42 no.5
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• pp.486-495
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• 2009

The purpose of this study was to analyze the performance evaluation index for a salt reduction project. Questionnaires were developed in order to investigate salt reduction programs nationwide. The evaluation index and programs were analyzed through the case study of a salt reduction program in public health centers. The validity of the salt reduction program's evaluation index was determined based on study of the Delphi survey and on discussion with nutrition and health care professionals. The Delphi survey showed that daily salt intake was the most valid nutritional evaluation index. Stroke mortality and stomach cancer mortality were good health care evaluation indexes. The method for measuring salt intake that had the greatest validity was a 24-hour urine collection. However, 24-hour urine collection had the lowest score for ease of performance. The combined scores of validity and ease of performance showed that the survey method for dietary attitude and dietary behavior, dietary frequency analysis (DFQ 15), and a salty taste assessment, in that order, were proper methods. The high reliability of the salty taste assessment indicated that the percentage of the population that exhibits proper salt intake (2,000 mg sodium or less daily) and the percentage of the population that consumes low-salt diets as nutritional evaluation indexes also will be helpful to evaluate performance of salt reduction programs.

• Science of Emotion and Sensibility
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• v.13 no.1
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• pp.47-60
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• 2010

Most of the researches about classification usually have used kNN(k-Nearest Neighbor), SVM(Support Vector Machine), which are known as learn-based model, and Bayesian classifier, NNA(Neural Network Algorithm), which are known as statistics-based methods. However, there are some limitations of space and time when classifying so many web pages in recent internet. Moreover, most studies of classification are using uni-gram feature representation which is not good to represent real meaning of words. In case of Korean web page classification, there are some problems because of korean words property that the words have multiple meanings(polysemy). For these reasons, LSA(Latent Semantic Analysis) is proposed to classify well in these environment(large data set and words' polysemy). LSA uses SVD(Singular Value Decomposition) which decomposes the original term-document matrix to three different matrices and reduces their dimension. From this SVD's work, it is possible to create new low-level semantic space for representing vectors, which can make classification efficient and analyze latent meaning of words or document(or web pages). Although LSA is good at classification, it has some drawbacks in classification. As SVD reduces dimensions of matrix and creates new semantic space, it doesn't consider which dimensions discriminate vectors well but it does consider which dimensions represent vectors well. It is a reason why LSA doesn't improve performance of classification as expectation. In this paper, we propose new LSA which selects optimal dimensions to discriminate and represent vectors well as minimizing drawbacks and improving performance. This method that we propose shows better and more stable performance than other LSAs' in low-dimension space. In addition, we derive more improvement in classification as creating and selecting features by reducing stopwords and weighting specific values to them statistically.