• Journal of Navigation and Port Research
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• v.34 no.10
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• pp.781-786
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• 2010

In this study, a new concept of ocean transport system, called the mobile harbor serving for a short distance transport of containers with cargo handling cranes between mother containerships and coastal ports, is introduced. Instead of direct berthing a very large containership at the coastal port, Mobile Harbor is moving to the offshore mooring basin with enough water depth condition. Therefore, investigation of the coastal environment, technical condition and limitation of the domestic trade ports for the application of Mobile Harbor, is essential process. To figure out the accessibility of mobile harbor, the environmental conditions, the cargo handling capacity and marine traffic volume and flow pattern has been analyzed with the tools for marine traffic simulation and virtual navigation aids system. The most proper Mobile Harbor mooring areas among trade ports of the south and east coast are selected by analyzing the obtained information and evaluating its application: (1) Under natural environmental conditions such as air and sea weather, three candidate areas are selected such as Masan port, Ulsan port, and Busan(New port) port. (2) Under marine traffic and appropriateness of water facilities, three candidate areas are selected as Mokpo port, Busan(New port) port, and Donghae & Mookho port (3) For a region-based analysis considering handling capacity and the local managed trade ports in vicinity, three candidate areas are selected as Busan region, Yosu & KwangYang region, and Mokpo region. Through this study, the basic guideline for selection of optimum trade port and offshore mooring basin for mothership and Mobile Harbor is recommended. In order to apply the Mobile Harbor to the real water, navigaton aids as the virtual route identification with AIS must be introduced for maritime safety in the vicinity of Mobile Harbor area which berthing and cargo handling is being conducted.

• Journal of the Korean Society of Groundwater Environment
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• v.5 no.2
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• pp.88-100
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• 1998

Since fractures may serve as major conduits of groundwater flow in crystalline rocks, characterization of conductive fractures is especially important for interpretation of flow system. In this study, characterization of fractures to investigate hydraulically conductive fractures in gneisses at an abandoned mine area was performed. The orientation, width, length, movement sense, infilling materials, spacing, aperture, roughness of both joints and faults and intersection and connectivity to other joints were measured on outcrops. In addition, characteristics of subsurface fractures were examined by core logging in five boreholes, of which the orientations were acquired by acoustic televiewer logging from three boreholes. The dominant fracture sets were grouped from outcrops; GSet 1: N50-82$^{\circ}$E/55-90$^{\circ}$SE, GSet 2: N2-8$^{\circ}$E/56-86$^{\circ}$SE, GSet 3: N46-72$^{\circ}$W/60-85$^{\circ}$NE, GSet 4:Nl2-38$^{\circ}$W/15-40$^{\circ}$SW and from subsurface; HSet 1: N50-90$^{\circ}$E/55-90$^{\circ}$SE, HSet 2: N10-30$^{\circ}$E/50-70$^{\circ}$SE, HSet 3: N20-60$^{\circ}$W/50-80$^{\circ}$NE, HSet 4: N10-50$^{\circ}$E/$\leq$40$^{\circ}$NW. Among them, GSet 1, GSet 3 and HSet 1, HSet 3 are the most intensely developed fracture sets in the study area. The mean fracture spacings of HSet 1 are 30-47cm and code 1 fractures, such as faults and open fractures, comprise 21.0-42.9 percent of the whole fractures in each borehole. HSet 3 shows the mean fracture spacings of 55-57cm and the ratio of code 1 fractures is 15.4-26.9 percent. In spite of the mean fracture spacing of 239cm, code 1 fractures of HSet 4 have the highest ratio of 54.5 percent. From the fact that faults or open fractures have high hydraulic conductivity, it can be inferred that the three fracture sets of N55-85$^{\circ}$E/50-80$^{\circ}$SE, N20-60$^{\circ}$W/50-75$^{\circ}$NE and N10-30$^{\circ}$E/$\leq$30$^{\circ}$NW from a fracture system of relatively high conductivity. It is indirectly verified with geophysical loggings and constant injection tests performed in the boreholes.

• Food Science and Preservation
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• v.21 no.5
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• pp.618-626
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• 2014

The physicochemical characteristics and consumer perceptions of two Fuji cultivars (Fuji and Royal Fuji) with six different size groups (3D: 30~39, 4D: 40~49, 5D: 50~59, 6D: 60~69, 7D: 70~79, and 8D: 80~89 apples/15 kg) were investigated to identify the ideal size and the drivers of consumer acceptability of apples. For the physicochemical characteristics, the weight, volume, specific volume, L, a, and b colors, hardness, pH, acidity, and brix of apples were measured. A total of 100 consumers were asked to mark the intensity of the characteristics (size, redness, glossiness, surface roughness, apple odor, apple flavor, sweetness, sourness, hardness, crunchiness, and toughness) to determine the ideal characteristics of apples before they were asked to taste the apple products. The consumers evaluated the apple samples in terms of their appearance, odor, flavor, texture, and overall acceptability; the consumers' intent to purchase such apples and willingness to pay for them; and the intensity of the aforementioned characteristics. Compared to the ideal characteristics of apples, the actual apple samples were rated low in their apple odor, apple flavor, acidity, sweetness, hardness, and crispness. The ideal size of the apples was between 4D and 5D. Their overall acceptability was highly affected by their flavor, followed by their texture, odor, and appearance. The acceptability of the appearance was highly correlated with the glossiness (r = 0.80), volume, weight, redness (r = 0.73), and size (r = 0.72). The consumer acceptability of the apples increased with the decreased pH and the increased Brix, hardness, and color b values of the peeled apples. The apple flavor, sweetness, hardness, crispiness, juiciness, and toughness during mastication were noted as sensory drivers of consumer acceptability.

• Research in Community and Public Health Nursing
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• v.12 no.1
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• pp.288-298
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• 2001

This article makes an attempt to evaluate the extent of developing community health nursing knowledge and to suggest the direction of developing a body of knowledge henceforth through the results of analysis for contents and outcomes of all literatures. which have been published in the Journal related to community health nursing. Refer to the following for the result of this article. 1. The total number of literatures analyzed amounted to 100 pieces in Journal of community health nursing society. 78 in Journal of industrial nursing society, 134 in Journal of school health society. 40 in Journal of home care nursing society. 2. Journal of community health nursing society Health needs and educational-behavioral diagnoses, which are more concrete nursing assessments and diagnoses. formed the main current(54%) of articles published in Journal of community health nursing society since 1992. There was a quantitative growth as well as a qualitative advance. Through a classification by the type of a body of knowledge. It was found that the knowledge providing nursing practice with bases, commanded an overwhelming majority(71.8%). Also, Researches on systemic supports for nursing practice are showing a tendency to increase. 3. Journal of industrial nursing society 52.6% of research papers presented in Journal of industrial nursing society dealt with health problem of workers. assessment of risk factors, diagnosis of health behaviors. Because of the beginning of an industrial nursing, the domain of nursing management to establish the role and task, work condition, training. documentary system made up 23 percent of research, subjects. A knowledge providing nursing practice with bases have a majority, 69.2%. In addition. the subject concerning a systemic support and quality assurance was scarce but continuously presented. 4. Journal of school health society The major point of this journal is the identification of health problems and risk factors which belong to assessment and diagnosis domain(56.8%) regardless of year, Because of the interdisciplinary characteristic. The knowledge on quality assurance of nursing practice is relatively rare. But, articles related to a systemic support is plentiful. 5. Journal of home care nursing society In its infancy, there was a large number of papers concerning need assessment and diagnosis, Comparing others, this journal has introduced a good many of articles related to program management. delivery system. service fee, etc that belong to domain of systemic support for nursing practice. 6. It is showing definitely that quantity and extent of research have grown for a short period. See the analysis in terms of nursing process, studies related to the domain of assessment and diagnosis command an absolute majority regardless of kinds of journal. Although articles referring to program management and implementation is increasing in number, it is scarce to evaluate a nursing program and grope for an improvement. Also, program development based on a theoretical framework is little. Therefore much more scientific effort to ensure profession should be executed. 7. In the methodological aspect, longitudinal study needs to be carried out so that we could show the evidence based nursing theory. To develop a more general theory, we have to conduct a study of various subjects and improve a validity of tools through a repeat test. In addition, the effort for interdisciplinary cooperation is needed.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.5 no.1
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• pp.11-18
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• 2002

Purpose: It is known that lactoferrin serves as a source of iron for H. pylori in gastric mucosa. This study was undertaken to investigate the relationship between lactoferrin and H. pylori infection coexistent with iron-deficiency anemia by determining the lactoferrin levels in gastric biopsy specimens, and by locating the major sites of lactoferrin expression, according to the presence or absence of iron-deficiency anemia. Methods: Fifty-five adolescents that underwent gastroduodenoscopy were divided into three groups: NL (n=19) for normal controls, HP (n=15) for patients with H. pylori, and IDA (n=21) for patients with H. pylori gastritis and coexisting iron-deficiency anemia. Histopathologic features were graded from to marked on the basis of the Updated Sydney System. The gastric mucosal levels of lactoferrin were measured by immunoassay. Immunohistochemical technique was used to allow identification of the location and quantification of the lactoferrin expression. Results: Lactoferrin levels in the antrum increased significantly, in proportion to, H. pylori density, polymorphonuclear cell infiltration, and chronic inflammation in the histologic specimens. Patients in the HP and IDA groups showed significantly increased mucosal levels of lactoferrin compared with that observed in the normal group (p=0.0001). The lactoferrin level in IDA group tended to be higher than that in the HP group (p=0.2614). The major sites of lactoferrin expression by immunohistochemistry were in glands and neutrophils within epithelium. Lactoferrin was stained weakly in NL, and strongly in HP and IDA. Conclusion: The lactoferrin sequestration in the gastric mucosa of IDA was remarkable, and this finding seems to give a clue that leads to the clarification of the mechanism by which H. pylori infection contributes to iron-deficiency anemia.

• Journal of the Korean Applied Science and Technology
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• v.18 no.1
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• pp.67-77
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• 2001

In search for several fatty acid with unusual structure in vegetable oils, we have found that unknown peaks were shown on GLC in the analysis of fatty acids of the lipids from the pulp of ripened jujube (Zizypus jujuba var. inermis) fruits. These fatty acids were identified as a series of cis-monoenoic acids with ${\omega}-5$ double bond system such as $C_{14:1{\omega}5}$, $C_{16:1{\omega}5}$ and $C_{18:1{\omega}5}$, including ${\omega}-7$ fatty acid as $C_{16:1{\omega}7}$ and $C_{18:1{\omega}7}$, by GLC, solid-phase extraction silver ion-column chromatographic, GLC-mass spectrometric and IR techniques. First of all, total fatty acid methyl esters were resolved into saturated and branched fatty acid, monoenoic acid, dienoic acid, and trienoic acid fraction, respectively, with 100% dichloromethane (DCM), DCM/acetone (9:1, v/v) 100% acetone, and acetone/ acetonitrile (97:3, v/v) solvent system. Unknown fatty acids were included in the monoenoic fraction and were confirmed to have cis-configuration by IR. Picolinyl esters of monoenoic fatty acids gave distinct molecular ion peak and dominant diagnostic peaks, for example, m/z 317, 220 and 260 fragment for $cis-C_{14:1{\omega}5}$, m/z 345, m/z 248 and 288 fragment for $cis-C_{16:1{\omega}5}$ and m/z 373, m/z 276 and 316 fragment for $cis-C_{18:1{\omega}5}$. In this way the occurrence of $cis-C_{16:1{\omega}7}$ and $cis-C_{18:1{\omega}7}$ could be deduced from the appearance of prominent fragments as m/z 345, 220 and 260, and m/z 373, 248 and 280. Level of total ${\omega}-5$ fatty acids amounted to about 30% in the fatty acid composition with the predominance of $C_{16:1{\omega}5}$ $ (18.7{\sim}25.0%)$, in the semi-ripened and/or ripened samples collected in September 14 ($C_{16:1{\omega}5}$ ; 18.7%, $C_{14:1{\omega}5}$ ; 3.6% and $C_{18:1{\omega}5}$ ; 3.0%), September 22 ($C_{16:1{\omega}5}$ ; 25.0%, $C_{14:1{\omega}5}$ ; 1.4% and $C_{18:1{\omega}5}$ ; 2.6%), and October $7 (C_{16:1{\omega}5}$ ; 24.7%, $C_{14:1{\omega}5}$ ; 7.7% and $C_{18:1{\omega}5}$ ; 2.5%). However, the lipids extracted from unripened jujube in July and August contain these unusual fatty acids as low as negligible. It could be observed that the level of ${\omega}-5$ fatty acids in the pulps increased sharply with an elapse of ripening time of jujube fruits. Other monoenoic fatty acids with ${\omega}-7$ series, $C_{16:1{\omega}7}$ (palmitoleic acid) and $C_{18:1{\omega}7}$ (cis-vaccenic acid) could be detected. And in the lipids of the kernel and leaf of jujube, none of ${\omega}-5$ fatty acids could be detected.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.6
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• pp.904-911
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• 2015

The objective of this study was to investigate the quality characteristics of traditional wine using an radio-frequency identification (RFID) system annexed to a fermenter. In this study, we proposed an RFID-based data transmission scheme for monitoring fermentation of traditional alcoholic beverages. The pH, total acidity, total sugar, soluble sugar, free sugar, alcohol content, and organic acids of were investigated and subjected to fermentation of traditional alcoholic beverages three times. The pH ranged from 7.98, 7.95, and 7.68 at day 0, decreased drastically to 3.31~2.96 at day 2, and then slowly increased to the end point, finally reaching 3.34 at day 20. Acidity tended to increase quickly with time, especially for all samples after day 2. The fermentation environment induced a sudden increase acidity in reactants and indicated a low pH. The total sugars during fermentation quickly decreased to the range of 20.3, 22.43, and 19.2% at day 2, and the slope of reduction steadily decreased to 5.1, 6.1, and 4.8% at day 10. On the other hand, the alcohol content showed the reverse trend as total sugars. The alcohol content also showed the same pattern as total acids, showing the highest alcohol content of 17.3% (v/v) on day 20. In this study on traditional wine fermentation using an RFID system, we showed that pH, soluble sugar, and alcohol content can be adopted as key indicators for quality control and standardization of traditional wine manufacturing.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.10-20
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• 2019

Irregular rainfall caused by climate change, in combination with non-point pollution, can cause water systems worldwide to suffer from frequent eutrophication and algal blooms. This type of water pollution is more common in agricultural prone to water system inflow of non-point pollution. Therefore, in this study, the correlation between Unmanned Aerial Vehicle(UAV) multi-spectral images and total phosphorus, total nitrogen, and chlorophyll-a with indirect association of algal blooms, was analyzed to identify the usability of UAV image to identify water quality characteristics in agricultural streams. The analysis the vegetation index Normalized Differences Index (NDVI), the Normalized Differences Red Edge(NDRE), and the Chlorophyll Index Red Edge(CIRE) for the detection of multi-spectral images and algal blooms collected from the target regions Yang cheon and Hamyang Wicheon. The analysis of the correlation between image values and water quality analysis values for the water sampling points, total phosphorus at a significance level of 0.05 was correlated with the CIRE(0.66), and chlorophyll-a showed correlation with Blue(-0.67), Green(-0.66), NDVI(0.75), NDRE (0.67), CIRE(0.74). Total nitrogen was correlated with the Red(-0.64), Red edge (-0.64) and Near-Infrared Ray(NIR)(-0.72) wavelength at the significance level of 0.05. The results of this study confirmed a significant correlations between multi-spectral images collected through UAV and the factors responsible for water pollution, In the case of the vegetation index used for the detection of algal bloom, the possibility of identification of not only chlorophyll-a but also total phosphorus was confirmed. This data will be used as a meaningful data for counterplan such as selecting non-point pollution apprehensive area in agricultural area.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.1-17
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• 2019

Because stock price forecasting is an important issue both academically and practically, research in stock price prediction has been actively conducted. The stock price forecasting research is classified into using structured data and using unstructured data. With structured data such as historical stock price and financial statements, past studies usually used technical analysis approach and fundamental analysis. In the big data era, the amount of information has rapidly increased, and the artificial intelligence methodology that can find meaning by quantifying string information, which is an unstructured data that takes up a large amount of information, has developed rapidly. With these developments, many attempts with unstructured data are being made to predict stock prices through online news by applying text mining to stock price forecasts. The stock price prediction methodology adopted in many papers is to forecast stock prices with the news of the target companies to be forecasted. However, according to previous research, not only news of a target company affects its stock price, but news of companies that are related to the company can also affect the stock price. However, finding a highly relevant company is not easy because of the market-wide impact and random signs. Thus, existing studies have found highly relevant companies based primarily on pre-determined international industry classification standards. However, according to recent research, global industry classification standard has different homogeneity within the sectors, and it leads to a limitation that forecasting stock prices by taking them all together without considering only relevant companies can adversely affect predictive performance. To overcome the limitation, we first used random matrix theory with text mining for stock prediction. Wherever the dimension of data is large, the classical limit theorems are no longer suitable, because the statistical efficiency will be reduced. Therefore, a simple correlation analysis in the financial market does not mean the true correlation. To solve the issue, we adopt random matrix theory, which is mainly used in econophysics, to remove market-wide effects and random signals and find a true correlation between companies. With the true correlation, we perform cluster analysis to find relevant companies. Also, based on the clustering analysis, we used multiple kernel learning algorithm, which is an ensemble of support vector machine to incorporate the effects of the target firm and its relevant firms simultaneously. Each kernel was assigned to predict stock prices with features of financial news of the target firm and its relevant firms. The results of this study are as follows. The results of this paper are as follows. (1) Following the existing research flow, we confirmed that it is an effective way to forecast stock prices using news from relevant companies. (2) When looking for a relevant company, looking for it in the wrong way can lower AI prediction performance. (3) The proposed approach with random matrix theory shows better performance than previous studies if cluster analysis is performed based on the true correlation by removing market-wide effects and random signals. The contribution of this study is as follows. First, this study shows that random matrix theory, which is used mainly in economic physics, can be combined with artificial intelligence to produce good methodologies. This suggests that it is important not only to develop AI algorithms but also to adopt physics theory. This extends the existing research that presented the methodology by integrating artificial intelligence with complex system theory through transfer entropy. Second, this study stressed that finding the right companies in the stock market is an important issue. This suggests that it is not only important to study artificial intelligence algorithms, but how to theoretically adjust the input values. Third, we confirmed that firms classified as Global Industrial Classification Standard (GICS) might have low relevance and suggested it is necessary to theoretically define the relevance rather than simply finding it in the GICS.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.17-32
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• 2021

Speaker recognition is generally divided into speaker identification and speaker verification. Speaker recognition plays an important function in the automatic voice system, and the importance of speaker recognition technology is becoming more prominent as the recent development of portable devices, voice technology, and audio content fields continue to expand. Previous speaker recognition studies have been conducted with the goal of automatically determining who the speaker is based on voice files and improving accuracy. Speech is an important sociolinguistic subject, and it contains very useful information that reveals the speaker's attitude, conversation intention, and personality, and this can be an important clue to speaker recognition. The final ending used in the speaker's speech determines the type of sentence or has functions and information such as the speaker's intention, psychological attitude, or relationship to the listener. The use of the terminating ending has various probabilities depending on the characteristics of the speaker, so the type and distribution of the terminating ending of a specific unidentified speaker will be helpful in recognizing the speaker. However, there have been few studies that considered speech in the existing text-based speaker recognition, and if speech information is added to the speech signal-based speaker recognition technique, the accuracy of speaker recognition can be further improved. Hence, the purpose of this paper is to propose a novel method using speech style expressed as a sentence-final ending to improve the accuracy of Korean speaker recognition. To this end, a method called sentence sequencing that generates vector values by using the type and frequency of the sentence-final ending appearing in the utterance of a specific person is proposed. To evaluate the performance of the proposed method, learning and performance evaluation were conducted with a actual drama script. The method proposed in this study can be used as a means to improve the performance of Korean speech recognition service.