• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.1-27
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• 2017

It is known that the economic sentiment index and macroeconomic indicators are closely related because economic agent's judgment and forecast of the business conditions affect economic fluctuations. For this reason, consumer sentiment or confidence provides steady fodder for business and is treated as an important piece of economic information. In Korea, private consumption accounts and consumer sentiment index highly relevant for both, which is a very important economic indicator for evaluating and forecasting the domestic economic situation. However, despite offering relevant insights into private consumption and GDP, the traditional approach to measuring the consumer confidence based on the survey has several limits. One possible weakness is that it takes considerable time to research, collect, and aggregate the data. If certain urgent issues arise, timely information will not be announced until the end of each month. In addition, the survey only contains information derived from questionnaire items, which means it can be difficult to catch up to the direct effects of newly arising issues. The survey also faces potential declines in response rates and erroneous responses. Therefore, it is necessary to find a way to complement it. For this purpose, we construct and assess an index designed to measure consumer economic sentiment index using sentiment analysis. Unlike the survey-based measures, our index relies on textual analysis to extract sentiment from economic and financial news articles. In particular, text data such as news articles and SNS are timely and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. There exist two main approaches to the automatic extraction of sentiment from a text, we apply the lexicon-based approach, using sentiment lexicon dictionaries of words annotated with the semantic orientations. In creating the sentiment lexicon dictionaries, we enter the semantic orientation of individual words manually, though we do not attempt a full linguistic analysis (one that involves analysis of word senses or argument structure); this is the limitation of our research and further work in that direction remains possible. In this study, we generate a time series index of economic sentiment in the news. The construction of the index consists of three broad steps: (1) Collecting a large corpus of economic news articles on the web, (2) Applying lexicon-based methods for sentiment analysis of each article to score the article in terms of sentiment orientation (positive, negative and neutral), and (3) Constructing an economic sentiment index of consumers by aggregating monthly time series for each sentiment word. In line with existing scholarly assessments of the relationship between the consumer confidence index and macroeconomic indicators, any new index should be assessed for its usefulness. We examine the new index's usefulness by comparing other economic indicators to the CSI. To check the usefulness of the newly index based on sentiment analysis, trend and cross - correlation analysis are carried out to analyze the relations and lagged structure. Finally, we analyze the forecasting power using the one step ahead of out of sample prediction. As a result, the news sentiment index correlates strongly with related contemporaneous key indicators in almost all experiments. We also find that news sentiment shocks predict future economic activity in most cases. In almost all experiments, the news sentiment index strongly correlates with related contemporaneous key indicators. Furthermore, in most cases, news sentiment shocks predict future economic activity; in head-to-head comparisons, the news sentiment measures outperform survey-based sentiment index as CSI. Policy makers want to understand consumer or public opinions about existing or proposed policies. Such opinions enable relevant government decision-makers to respond quickly to monitor various web media, SNS, or news articles. Textual data, such as news articles and social networks (Twitter, Facebook and blogs) are generated at high-speeds and cover a wide range of issues; because such sources can quickly capture the economic impact of specific economic issues, they have great potential as economic indicators. Although research using unstructured data in economic analysis is in its early stages, but the utilization of data is expected to greatly increase once its usefulness is confirmed.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.109-125
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• 2020

The Ministry of National Defense is pushing for the Defense Acquisition Program to build strong defense capabilities, and it spends more than 10 trillion won annually on defense improvement. As the Defense Acquisition Program is directly related to the security of the nation as well as the lives and property of the people, it must be carried out very transparently and efficiently by experts. However, the excessive diversification of laws and regulations related to the Defense Acquisition Program has made it challenging for many working-level officials to carry out the Defense Acquisition Program smoothly. It is even known that many people realize that there are related regulations that they were unaware of until they push ahead with their work. In addition, the statutory statements related to the Defense Acquisition Program have the tendency to cause serious issues even if only a single expression is wrong within the sentence. Despite this, efforts to establish a sentence comparison system to correct this issue in real time have been minimal. Therefore, this paper tries to propose a "Comparison System between the Statement of Military Reports and Related Laws" implementation plan that uses the Siamese Network-based artificial neural network, a model in the field of natural language processing (NLP), to observe the similarity between sentences that are likely to appear in the Defense Acquisition Program related documents and those from related statutory provisions to determine and classify the risk of illegality and to make users aware of the consequences. Various artificial neural network models (Bi-LSTM, Self-Attention, D_Bi-LSTM) were studied using 3,442 pairs of "Original Sentence"(described in actual statutes) and "Edited Sentence"(edited sentences derived from "Original Sentence"). Among many Defense Acquisition Program related statutes, DEFENSE ACQUISITION PROGRAM ACT, ENFORCEMENT RULE OF THE DEFENSE ACQUISITION PROGRAM ACT, and ENFORCEMENT DECREE OF THE DEFENSE ACQUISITION PROGRAM ACT were selected. Furthermore, "Original Sentence" has the 83 provisions that actually appear in the Act. "Original Sentence" has the main 83 clauses most accessible to working-level officials in their work. "Edited Sentence" is comprised of 30 to 50 similar sentences that are likely to appear modified in the county report for each clause("Original Sentence"). During the creation of the edited sentences, the original sentences were modified using 12 certain rules, and these sentences were produced in proportion to the number of such rules, as it was the case for the original sentences. After conducting 1 : 1 sentence similarity performance evaluation experiments, it was possible to classify each "Edited Sentence" as legal or illegal with considerable accuracy. In addition, the "Edited Sentence" dataset used to train the neural network models contains a variety of actual statutory statements("Original Sentence"), which are characterized by the 12 rules. On the other hand, the models are not able to effectively classify other sentences, which appear in actual military reports, when only the "Original Sentence" and "Edited Sentence" dataset have been fed to them. The dataset is not ample enough for the model to recognize other incoming new sentences. Hence, the performance of the model was reassessed by writing an additional 120 new sentences that have better resemblance to those in the actual military report and still have association with the original sentences. Thereafter, we were able to check that the models' performances surpassed a certain level even when they were trained merely with "Original Sentence" and "Edited Sentence" data. If sufficient model learning is achieved through the improvement and expansion of the full set of learning data with the addition of the actual report appearance sentences, the models will be able to better classify other sentences coming from military reports as legal or illegal. Based on the experimental results, this study confirms the possibility and value of building "Real-Time Automated Comparison System Between Military Documents and Related Laws". The research conducted in this experiment can verify which specific clause, of several that appear in related law clause is most similar to the sentence that appears in the Defense Acquisition Program-related military reports. This helps determine whether the contents in the military report sentences are at the risk of illegality when they are compared with those in the law clauses.

• Restorative Dentistry and Endodontics
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• v.32 no.3
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• pp.248-259
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• 2007

The aim of this research was to study the effect of intermittent polymerization on marginal adaptation by comparing the marginal adaptation of intermittently polymerized composite to that of continuously polymerized composite. The materials used for this study were Pyramid (Bisco Inc., Schaumburg, U.S.A.) and Heliomolar (Ivoclar Vivadent, Liechtenstein) . The experiment was carried out in class II MOD cavities prepared in 48 extracted human maxillary premolars. The samples were divided into 4 groups by light curing method: group 1- continuous curing (60s light on with no light off), group 2-intermittent curing (cycles of 3s with 2s light on & 1s light off for 90s); group 3- intermittent curing (cycles of 2s with 1s light on & 1s light off for 120s); group 4- intermittent curing (cycles of 3s with 1s light on & 2s light off for 180s). Consequently the total amount of light energy radiated was same in all the groups. Each specimen went through thermo-mechanical loading (TML) which consisted of mechanical loading (720,000 cycles, 5.0 kg) with a speed of 120 rpm for 100hours and thermocycling (6000 thermocycles of alternating water of $50^{\circ}C$ and $55^{\circ}C$). The continuous margin (CM) (%) of the total margin and regional margins, occlusal enamel (OE), vertical enamel (VE), and cervical enamel (CE) was measured before and after TML under a $\times200$ digital light microscope. Three-way ANOVA and Duncan's Multiple Range Test was performed at 95% level of confidence to test the effect of 3 variables on CM (%) of the total margin: light curing conditions, composite materials and effect of TML. In each group, One-way ANOVA and Duncan's Multiple Range Test was additionally performed to compare CM (%) of regions (OE, VE CE). The results indicated that all the three variables were statistically significant (p < 0.05). Before TML, in groups using Pyramid, groups 3 and 4 showed higher CM (%) than groups 1 and 2, and in groups using Heliomolar. groups 3 and 4 showed higher CM (%) than group 1 (p < 0.05). After TML, in both Pyramid and Heliomo)ar groups, group 3 showed higher CM (%) than group 1 (p < 0.05) CM (%) of the regions are significantly different in each group (p < 0.05). Before TML, no statistical difference was found between groups within the VE and CE region. In the OE region, group 4 of Pyramid showed higher CM (%) than group 2, and groups 2 and 4 of Heliomolar showed higher CM (%) than group 1 (p < 0.05). After TML, no statistical difference was found among groups within the VE and CE region. In the OE region, group 3 of Pyramid showed higher CM (%) than groups 1 and 2, and groups 2,3 and 4 of Heliomolar showed higher CM (%) than group 1 (p < 0.05). It was concluded that intermittent polymerization may be effective in reducing marginal gap formation.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.36 no.3
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• pp.26-36
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• 2018

This study aims to examine the characteristics of landscape through the analysis of location and the landscape of Gugok while also conducting the empirical study through the literature review, field study, and digital analysis of the Okgung Gugok. Oksan Gugok is a set of songs set in Ogsan Creek(玉山川)or Jagyese Creek(紫溪川, 紫玉山), which flows in front of the Oksan Memorial Hall(李彦迪), which is dedicated to the Lee Eong-jeok (李彦迪). We first ascertained the location and configuration of Oksan Gogok. Second, we confirmed the accurate location of Oksan Gogok by utilizing the digital topographic map of Oksan Gogok which was submitted by Google Earth Pro and Geographic Information Center as well as the length of the longitude of the gravel measured by the Trimble Juno SB GPS. Through the study of the literature and the field investigation, The results of the study are as follows. First, Yi Eonjeok was not a direct composer of Oksan Gugok, nor did he produce "Oksan Gugokha(Music)". Lee Ia-sung(李野淳), the ninth Youngest Son of Tweo-Kye, Hwang Lee, visited the "Oksan Gugokha" in the spring of 1823(Sunjo 23), which was the 270th years after the reign of Yi Eonjeok. At this time, receiving the proposal of Ian Sung, Lee Jung-eom(李鼎儼), Lee Jung-gi(李鼎基), and Lee Jung-byeong(李鼎秉), the descendants of Ian Sung set up a song and created Oksan Gugok Music. And the Essay of Oksan Travel Companions writted by Lee Jung-gi turns out being a crucial data to describe the situation when setting up the Ok-San Gugok. Second, In the majority of cases, Gogok Forest is a forest managed by a Confucian Scholar, not run by ordinary people. The creation of "Oksan Bugok Music" can be regarded as an expression of pride that the descendants of Yi Eonjeok and Lee Hwang, and next generation of several Confucian scholars had inherited traditional Neo-Confucian. Third, Lee Jung-eom's "Oksan Donghaengki" contains a detailed description of the "Oksan Gugokha" process and the process of creating a song. Fourth, We examined the location of one to nine Oksan songs again. In particular, eight songs and nine songs were located at irregular intervals, and eight songs were identified as $36^{\circ}01^{\prime}08.60^{{\prime}{\prime}}N$, $129^{\circ}09^{\prime}31.20^{{\prime}{\prime}}E$. Referring to the ancient kingdom of Taojam, the nine-stringed Sainam was unbiased as a lower rock where the two valleys of the East West congregate. The location was estimated at $36^{\circ}01^{\prime}19.79^{{\prime}{\prime}}N$, $129^{\circ}09^{\prime}30.26^{{\prime}{\prime}}E$. Fifth, The landscape elements and landscapes presented in Lee Jung-eom's "Oksan Gugokha" were divided into form, semantic and climatic elements. As a result, Lee Jung-eom's Cho Young-gwan was able to see the ideal of mountain water and the feeling of being idle in nature as well as the sense of freedom. Sixth, After examining the appearance of the elements and the frequency of the appearance of the landscape, 'water' and 'mountain' were the absolute factors that emphasized the original curved environment at the mouth of Lee Jung-eom. Therefore, there was gugokga can gauge the fresh ideas(神仙思想)and retreat ever(隱居思想). This inherent harmony between the landscape as well as through the mulah any ideas that one with nature and meditation, Confucian tube.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.14 no.4
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• pp.1-10
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• 2011

This study was conducted to compare the growth of Zoysia japonica depending on different soil treatments in Saemangeum sea dike, which is filled with dredged soil. Zoysia japonica was planted using sod-pitching method on the control plot. On plots which were treated with forest soil and soil improvement, Zoysia japonica seeds were sprayed mechanically. Sixteen months after planting, coverage rate, leaf length, leaf width, and root length were measured and analyzed. Also, three Zoysia japonica samples per plot were collected to analyze nutrient contents. Coverage rate was 100% in B treatment plot(dredged soil+$40kg/m^3$ soil improvement+forest soil), in C treatment plots (dredged soil+$60kg/m^3$ soil improvement+forest soil), and D treatment plots (dredged soil+$60kg/m^3$ soil improvement), while only 43% of the soil surface was covered with Zoysia japonica on control plots. The width of the leaf on C treatment plots (3.79mm) was the highest followed by D treatment (3.49mm), B treatment (2.40mm) and control plots (1.97mm). Leaf and root length of D treatment was 30.18cm and 13.18cm, which were highest among different treatments. The leaf length of D treatment was highest followed by C, B, and A treatments. The root length of D treatment was highest followed by C, A, and B treatments. The nitrogen and phosphate contents of the above ground part of Zoysia japonica were highest in C treatment, followed by D, B, and A treatments. The nitrogen and phosphate contents of the underground part of Zoysia japonica were highest in D treatment, followed by C, A, and B treatments. C and D treatments showed the best results in every aspect of grass growth. The results of this study could be used to identify the cost effective way to improve soil quality for soil surface fixation on reclaimed areas using grass species.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.22 no.1
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• pp.135-166
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• 1977

Some biochemical features of varietal variation in seed protein and their implications for soybean breeding for high protein were pursued employing 86 soybean varieties of Korea, Japan, and the U.S.A. origins. Also, studied comparatively was the temporal pattern of protein components accumulation during seed development characteristic to the high protein variety. Seed protein content of the 86 soybean varieties varied 34.4 to 50.6%. Non-existence of variety having high content of both protein and oil, or high protein content with average oil content as well as high negative correlation between the content of protein and oil (r=-0.73$^{**}$) indicate strongly a great difficulty to breed high protein variety while conserving oil content. The total content of essential amino acids varied 32.82 to 36.63% and the total content of sulfur-containing amino acids varied 2.09 to 2.73% as tested for 12 varieties differing protein content from 40.0 to 50.6%. The content of methionine was positively correlated with the content of glutamic acid, which was the major amino acid (18.5%) in seed protein of soybean. In particular, the varieties Bongeui and Saikai ＃20 had high protein content as well as high content of sulfur-containing amino acids. The content of lysine was negatively correlated with that of isoleucine, but positively correlated with protein content. The content of alanine, valine or leucine was correlated positively with oil content. The seed protein of soybean was built with 12 to 16 components depending on variety as revealed on disc acrylamide gel electrophoresis. The 86 varieties were classified into 11 groups of characteristic electrophoretic pattern. The protein component of Rm=0.14(b) showed the greatest varietal variation among the components in their relative contents, and negative correlation with the content of the other components, while the protein component of Rm=0.06(a) had a significant, positive correlation with protein content. There was sequential phases of rapid decrease, slow increase and stay in the protein content during seed development. Shorter period and lower rate of decrease followed by longer period and higher rate of increase in protein content during seed development was of characteristic to high protein variety together with earlier and continuous development at higher rate of the protein component a. Considering the extremely low methionine content of the protein component a, breeding for high protein content may result in lower quality of soybean protein.n.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.21 no.1
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• pp.136-179
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• 1976

Effects of seeding pattern and rate on the yield and some agronomic characters of barley under different cultural conditions were observed at Suweon, Daejeon and Jinju during the barley growing season from 1972 to 1974. Plant height and culm length were increased by dense seeding, shading, heavy fertilization, moving location down to the lower latitude. The tiller number per plant, dry matter weight, leaf number on main stem, percentage of valid tillers, RGR, NAR, and $R_{A}$ were increased by heavy fertilization, sparse seeding, reduced furrow width and drilling likewise the length, width and angle of leaf. The newer cultivar had higher RGR and NAR. The higher yielding cultivars had higher potential for carbohydrate assimilating ability. Straw weight and grain yield were increased by dense seeding, reduced furrow width, drilling, heavier fertilization and moving the location to the south, and then decreased by shading and late seeding. High yield increase by drilling was found in late seeding. The optimum seeding rate for the yield increase were 15l/10a for furrow and 25l/10a for drilling. The spike number type cultivars were favourable for the sparse seeding and the spike weight type cultivars seemed to be suitable to the dense seeding, The repeatability of days to heading due to location and fertilizer level was higher than that of seeding time and seeding method. Repeatability of culm length was extremly high in seeding method and comparatively high in fertilizer level while low in location. The repeatability of yield due to location and seeding methods was comparatively high, but the tendency was different along with different cultivars. Also the repeatability of yield due to the fertilizer level was generally high except cultivar Haganemngi.

• Applied Biological Chemistry
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• v.22 no.4
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• pp.198-209
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• 1979

L-Tyrosine, 2-chloro-L-tyrosine, 2-bromo-L-tyrosine, and 2-iodo-L-tyrosine were synthesized by ${\beta}-tyrosinase$ obtained from cells of Escherichia intermedia A-21, through the reversal of the ${\alpha},{\beta}-elimination$ reaction, and their molecular structures were analyzed by element analysis, NMR spectroscopy, mass spectrometry and IR spectroscopy. Rates of synthesis and hydrolysis of halogenated tyrosines by ${\beta}-tyrosinase$, inhibition of the enzyme activity by halogenated phenols, and effects of addition of m-bromophenol on the synthesis of 2-bromotyrosine were determined. The results obtained were as follows: 1) In the synthesis of halogenated tyrosines, the yield of 2-chlorotyrosine from m-chlorophenol were approximately 15 per cent, that of 2-bromotyrosine from m-bromophenol 13.8 per cent, and that of 2-iodotyrosine from m-iodophenol 9.8 per cent. 2) Rate of synthesis of halogenated tyrosines by ${\beta}-tyrosinase$ was slower than that of tyrosine and the rates were decreased in the order of chlorine, bromine and iodine, that is, by increasing the atomic radius. Relative rate of 2-chlorotyrosine synthesis was determined to be 28.2, that of 2-bromotyrosine to be 8.13, and that of 2-iodotyrosine to be 0.98, respectively, against 100 of tyrosine. However 3-iodotyrosine was not synthesized by the enzyme. 3) The relative rate of 2-chlorotyrosine hydrolysis by ${\beta}-tyrosinase$ was 70.7, that of 2-bromotyrosine was 39.0, and that of 2-iodotyrosine was 12.6 against 100 of tyrosine, respectively. The rate of hydrolysis appeared to be decreased in the order of chlorine, bromine and iodine, that is, by increasing the atomic radius or by decreasing the electronegativity. But 3-iodotyrosine was not hydrolyzed by the enzyme. 4) The activity of ${\beta}-tyrosinase$ was inhibited by phenol markedly. Of the halogenated phenols, o-, or m-chlorophenol and o-bromophenol gave marked inhibition on the enzyme action, however inhibition by iodophenol was not strong. Plotting by Lineweaver-Burk method, a mixed-type inhibition by m-chlorophenol was observed and its Ki value was found to be $5.46{\times}10^{-4}M$. 5) During the synthesizing reaction of 2-bromotyrosine by the enzyme, sequential addition of substrate which was m-bromophenol with time intervals and in a small amount resulted in better yield of the product. 6) The halogenated tyrosines which were produced by ${\beta}-tyrosinase$ from pyruvate, ammonia and m-halogenated phenols were analysed to determine their molecular structures by element analysis, NMR spectroscopy, mass spectrometry, and IR spectroscopy. The result indicated that they were 2-chloro-L-tyrosine, 2-bromo-L-tyrosine, and 2-iodo-L-tyrosine, respectively.

• Applied Biological Chemistry
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• v.7
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• pp.92-104
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• 1966

For the purpose of the better dietary management and to empahsize of importance in nutrition education for 552 students at the dormitories, College of Agriculture, Seoul National University, the dietary survey was conducted for each consecutive seven days, from March 7th to 13th at the boy's dormitory, from March 14th to 20th at the girl's dormitory, respectively. In comparison the average caloric and nutrient intake per caput per day at the both, girl's and boy's dormitory with the recommended dietary allowances for age of 25, the intake of calories and all nutrients except riboflavin were over the allowances for the boy, while the caloric intake by the girl was considerablly below the allowance. But it is meant that only 150 calories was actually deficient in comparison with the figure of the average energy consumption determined for the girls at the dormitory of the Sook-myung Woman's University, whose pattern of living was quite similar to those of the girls at this college. Except iron and ascorbic acid, all other nutrients were deficient for the girls. The calories in the form of protein of a diet taken by the boy was 12.9% and that by the girl was 12.8%. Protein quality of the diet taken by boy scored 70 while that by the girl scored 79. NDp Cal% of the diet taken by the boy was 7 and that by the girl was figured out to be 8. Therefore, calculated reference protein taken by the boy was 55.8 grams and that by the girl was 36.9%. Though it is generally recommended that at least 1/3 of the protein should come from animal sources, it was apparent by this survey that providing 1/5 of the protein from animal sources with remaining part of high quality vegetable protein foods in the adequate mixed diet would give satisfactory results for both girl and boy students. This was clearly demonstrated by the recommended reference protein and NDp Cal% met. Significant difference between boys and girls in the average consumption of seasonings was found. In consumption per day of seasonings, boy used 1.5 grams of red pepper powder which means they used 15 times more of red pepper than girls did. Kochujang was used 13 grams by boy-students which was as high as 21 times of that of the girl. Total salt intake by the boy was 34 grams while the girl consummed 23 grams. It is obviously recognized that boys prefer more peppery and salty flavor than girls do. To reduce the amount of protein consummed and to improve the quality of protein food, increase of riboflavin rich food and increase of fat intake in place of grain intake are recommendable to the boy. For the girl's diet, consumption of grains, particularly more intake of barley mal· be recommendable to meet the B group of vitamins allowances as well as the caloric allowance. The use of more servings of yellow green vegetables is needed to the girl.