• Journal of the Korean Institute of Landscape Architecture
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• v.36 no.3
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• pp.1-8
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• 2008

The purpose of this study is to understand the conflicts that occurred in the rural village's joint management project. This study examined the perception of conflicts among people working in agricultural related fields. A questionnaire survey was given to collected data from people who participated in nation-wide resrvice training course programs. The content of the questionnaire consisted of the factors of conflict in a rural village and the details recognized by general farmers. The data was collected from October 15 to 23, 2007. 206 samples were used for final analysis from a total of 240 samples. Frequency analysis and T-test between variables were conducted by SPSS 14.0. The results suggest that farmers have a negative perception of the business partnership. Proposal for business partnerships should be avoided because of the conflicts between partners. Accordingly, as farmers don't recognize that their joint project is a business partnership, the likehood of a conflict in the agricultural joint business operation and management is contained. Conflicts mainly exist between a village leader and villagers. The main reasons for conflicts are a lack of interest and lack of communal homogeneity, and lack of methodology to share the benefit of business. It will be necessary to understand the aspects of future conflicts in order to manage joint projects ill agricultural experience villages.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.5
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• pp.547-553
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• 2016

Black carbon (BC) contained in particulate matter (PM) originating from the exhaust gases of ships' diesel engines has been receiving great attention as a cause of glacial melting and warming in the polar regions. In this study, we took samples from various locations of PM emitted from the training ship (T/S) HANBADA's main engine, in cooperation with the Korea Maritime and Ocean University. We analyzed the structure and characteristics of these samples using high-resolution transmission electron microscopy (HR-TEM) and applied our findings as fundamental research for developing PM reduction technology. We also employed our results to determine appropriate preemptive action to meet upcoming PM/BC regulations. In addition, we confirmed the emission trend of pollutants from exhaust gases under various engine operating conditions using an exhaust gas analyzer. Results obtained from the analysis of HR-TEM images showed that the structure of the PM is chain-like wispy agglomerates consisting of a number of individual spherical particles. As the sampling location was moved away from the turbo charger (T/C) towards the funnel, more condensates were observed at a low temperature and the molecular structure of the PM lost its characteristic BC structure as an amorphous structure gradually appeared. Furthermore, through the analysis of exhaust gases, we predicted a decrease in PM concentration in the exhaust stream as engine rpm increase.

• The Korean Journal of Emergency Medical Services
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• v.12 no.3
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• pp.43-53
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• 2008

Purpose : This study was designed to examine physiological changes in the body of rescuers conduct CPR according to the 2005 new guideline from American Heart Association. The ratio of artificial respiration has changed from 15 : 2 into 30 : 2 in 2005. The researcher tried to know the correlation between the physiological changes and the accuracy of CPR. Method : The examinees of this study were 26 students (Dept. of Emergency Medical Service). After the training, participants conducted 10 minute CPR and soon after the CPR, their vital signs were checked, and lactic acid and concentration of ammonia were analysed from their blood samples. Questionnaires to ask their subjective fatigue level were filled out after blood samples and 10 minute - CPR was performed. Results : 1) After the CPR, concentrations of ammonia were $149.71{\mu}{\ell}/d{\ell}$ and $162.17{\mu}{\ell}/d{\ell}$ in 15 : 2 and 30 : 2, respectively. The number was higher in 30 : 2 but it wan not statistically meaningful (p = .493). Log value of lactic acid was a little higher in 30 : 2 with 42 log($mmol/{\ell}$) and 54 log($mmol/{\ell}$) in 15 : 2 and 30 : 2, respectively but it was not statistically meaningful (p = .113). 2) Blood pressure in 15 : 2 and 30 : 2 were 118.50 mmHg and 125.08 mmHg while pulse in two different cases were 96.14 and 97.25, showing no statistically significant differences (blood pressure : p = .155, pulse : p = .841). 3) Subjective fatigue was a bit high in 30 : 2 with 5.93 and 6.92 points in 15 : 2 and 30 : 2 respectively but it was not statistically meaningful (p = .142). 4) In the 10 minute CPR, respiration accuracy was 96.21% in 15 : 2 and 94.79% in 30 : 2. There was no statistical significances between the two(p = .225). In the meanwhile, chest compression accuracy was 92.57% in 15 : 2 and 91.83% in 30 : 2. From the beginning to the end of chest compression, there showed no difference(p = .425). the type of CPR did not influence upon the accuracy of chest compression(p = .756). Conclusion : In the CPR conducted by skilled rescuers for 10 minutes, there were no statistically meaningful differences between 15 : 2 and 30 : 2 in the concentration of fatigue element in a blood, subjective fatigue, vital signs and accuracy of CPR. Therefore, 30 : 2 CPR recommended by American Heart Association need to be recommended and performed in scene size up.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.4924-4931
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• 2011

This research performed to evaluate a production processes reporting by the HACCP system of green vegetable juice products, containing lactic acid bacteria, stage of processing raw materials agricultural products and production facilities of general bacteria and pathogenic micro organism. General bacteria are found from four samples of storage of agricultural products at process stage and water was detected 8.67~14.67 CFU/ml. However, all samples were detected less than 105 CFU/ml as a legal standards after the process of UV sterilization. For the outcome of experiment of E.coli, E.coli O157:H7, B.cereus, L.moonocytogenes, Salmonella spp, Staph.aureus as the food poisoning bacterial, E.coli was detected until UV pre-step process in storage process and B.cereus was detected partly till 1st washing. Since all bacterial, Yeast and Mold are detected in main materials, pre-control method is a necessary to establish for decreasing with a number of initial bacteria of main materials and it is considered to establish the effective ways of washing and sterilization such as production facilities for cross contamination prevention of bacteria and Sthaphylococcus. Based on above results, the process of UV sterilization should be managed with CCP as an important process to reduce or eliminate the general and food poisoning bacterial of green vegetable juice products, including lactic acid bacteria. Therefore, it is considered to need an exhaustive HACCP plan such as control manual of UV sterilization, solution method, verification, education and training and record management.

• Advances in nano research
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• v.16 no.4
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• pp.375-394
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• 2024

The extensive utilization of concrete has given rise to environmental concerns, specifically concerning the depletion of river sand. To address this issue, waste deposits can provide manufactured-sand (MS) as a substitute for river sand. The objective of this study is to explore the application of machine learning techniques to facilitate the production of manufactured-sand concrete (MSC) containing stone nano-powder through estimating the splitting tensile strength (STS) containing compressive strength of cement (CSC), tensile strength of cement (TSC), curing age (CA), maximum size of the crushed stone (Dmax), stone nano-powder content (SNC), fineness modulus of sand (FMS), water to cement ratio (W/C), sand ratio (SR), and slump (S). To achieve this goal, a total of 310 data points, encompassing nine influential factors affecting the mechanical properties of MSC, are collected through laboratory tests. Subsequently, the gathered dataset is divided into two subsets, one for training and the other for testing; comprising 90% (280 samples) and 10% (30 samples) of the total data, respectively. By employing the generated dataset, novel models were developed for evaluating the STS of MSC in relation to the nine input features. The analysis results revealed significant correlations between the CSC and the curing age CA with STS. Moreover, when delving into sensitivity analysis using an empirical model, it becomes apparent that parameters such as the FMS and the W/C exert minimal influence on the STS. We employed various loss functions to gauge the effectiveness and precision of our methodologies. Impressively, the outcomes of our devised models exhibited commendable accuracy and reliability, with all models displaying an R-squared value surpassing 0.75 and loss function values approaching insignificance. To further refine the estimation of STS for engineering endeavors, we also developed a user-friendly graphical interface for our machine learning models. These proposed models present a practical alternative to laborious, expensive, and complex laboratory techniques, thereby simplifying the production of mortar specimens.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.299-308
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• 2007

Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.

• Korean Journal of Soil Science and Fertilizer
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• v.32 no.4
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• pp.383-397
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• 1999

For sites to be investigated, the results of such an investigation can be used in determining foals for cleanup, quantifying risks, determining acceptable and unacceptable risk, and developing cleanup plans t hat do not cause unnecessary delays in the redevelopment and reuse of the property. To do this, it is essential that an appropriately detailed study of the site be performed to identify the cause, nature, and extent of contamination and the possible threats to the environment or to any people living or working nearby through the analysis of samples of soil and soil gas, groundwater, surface water, and sediment. The migration pathways of contaminants also are examined during this phase. Key aspects of cost-effective site assessment to help standardize and accelerate the evaluation of contaminated soils at sites are to provide a simple step-by-step methodology for environmental science/engineering professionals to calculate risk-based, site-specific soil levels for contaminants in soil. Its use may significantly reduce the time it takes to complete soil investigations and cleanup actions at some sites, as well as improve the consistency of these actions across the nation. To achieve the effective site assessment, it requires the criteria for choosing the type of standard and setting the magnitude of the standard come from different sources, depending on many factors including the nature of the contamination. A general scheme for site-specific assessment consists of sequential Phase I, II, and III, which is defined by workplan and soil screening levels. Phase I are conducted to identify and confirm a site's recognized environmental conditions resulting from past actions. If a Phase 1 identifies potential hazardous substances, a Phase II is usually conducted to confirm the absence, or presence and extent, of contamination. Phase II involve the collection and analysis of samples. And Phase III is to remediate the contaminated soils determined by Phase I and Phase II. However, important factors in determining whether a assessment standard is site-specific and suitable are (1) the spatial extent of the sampling and the size of the sample area; (2) the number of samples taken: (3) the strategy of taking samples: and (4) the way the data are analyzed. Although selected methods are recommended, application of quantitative methods is directed by users having prior training or experience for the dynamic site investigation process.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.65-70
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• 1991

A hybrid model which uses a probabilistic model and a MLP(multi layer perceptron) model for pattern recognition of EMG(electromyogram) signals is proposed in this paper. MLP model has problems which do not guarantee global minima of error due to learning method and have different approximation grade to bayesian probabilities due to different amounts and quality of training data, the number of hidden layers and hidden nodes, etc. Especially in the case of new test data which exclude design samples, the latter problem produces quite different results. The error probability of probabilistic model is closely related to the estimation error of the parameters used in the model and fidelity of assumtion. Generally, it is impossible to introduce the bayesian classifier to the probabilistic model of EMG signals because of unknown priori probabilities and is estimated by MLE(maximum likelihood estimate). In this paper we propose the method which get the MAP(maximum a posteriori probability) in the probabilistic model by estimating the priori probability distribution which minimize the error probability using the MLP. This method minimize the error probability of the probabilistic model as long as the realization of the MLP is optimal and approximate the minimum of error probability of each class of both models selectively. Alocating the reference coordinate of EMG signal to the outside of the body make it easy to suit to the applications which it is difficult to define and seperate using internal body coordinate. Simulation results show the benefit of the proposed model compared to use the MLP and the probabilistic model seperately.

• Korean Journal of Human Ecology
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• v.12 no.3
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• pp.303-319
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• 2003

This study was designed to examine the extent of job-related stress and job satisfaction and factors affecting job satisfaction of educare center teachers. Special attention was given to the differences due to the various organizational types of educare centers. Two hundred and twenty two public and private educare center teachers of C city were drawn as samples of this study. Self-administered questionnaire method containing items (m job-related stress, Job satisfaction and socio-demographic background was employed and the data were analyzed with SPSSWlN using descriptive statistics, factor analysis and regression analysis. Findings suggested that the major job-related stresses were related to work experiences, working hours, and the number of on-the-job training opportunities. Work place characteristics such as the total number of children in the class, working hours and wage also affected the level of Job satisfaction. Additionally significant statistical differences were found on the job-related stress and the job satisfaction between teachers in public and private educare centers. In the question of the effect of job-related stress on the job satisfaction, job-related stress explained 12% of work-satisfaction, 33% of satisfaction related to the current working place. Accordingly it was possible to draw a conclusion that educare center teachers' job-related stresses. were not ascribed by personal characteristics but by work-related factors such a, poor administrative support low wage and the overwhelming task related stressors The main stressor of job satisfaction was poor administrative support. Differences on job-related stress and job satisfaction_between among teachers of public and private unit were distinctive throughout the study. These results, implicate that workshops are recommended to help diminish the job-related stress among educare center teachers. It is imperative that enhanced work benefits and improved working environment will in turn enhance the quality of services in educare centers.

• Journal of the Korea Society of Computer and Information
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• v.21 no.5
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• pp.79-89
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• 2016

In this paper, we proposed the object classification method using genetic and dynamic random forest consisting of optimal combination of unit tree. The random forest can ensure good generalization performance in combination of large amount of trees by assigning the randomization to the training samples and feature selection, etc. allocated to the decision tree as an ensemble classification model which combines with the unit decision tree based on the bagging. However, the random forest is composed of unit trees randomly, so it can show the excellent classification performance only when the sufficient amounts of trees are combined. There is no quantitative measurement method for the number of trees, and there is no choice but to repeat random tree structure continuously. The proposed algorithm is composed of random forest with a combination of optimal tree while maintaining the generalization performance of random forest. To achieve this, the problem of improving the classification performance was assigned to the optimization problem which found the optimal tree combination. For this end, the genetic algorithm methodology was applied. As a result of experiment, we had found out that the proposed algorithm could improve about 3~5% of classification performance in specific cases like common database and self infrared database compare with the existing random forest. In addition, we had shown that the optimal tree combination was decided at 55~60% level from the maximum trees.