• Applied Biological Chemistry
• /
• v.5
• /
• pp.7-21
• /
• 1964

가잠(家蠶)(Bombyx mori)의 잠체(蠶體), 용체 및 견사선(絹絲腺)(후부(後部))에서 phenol법(法)으로 RNA를 추출(抽出)하여 RNA의 nucleotide 조성(組成)(mole ratio)을 살피는 한편, 견사선(絹絲腺)(후부(後部))에서 초원심법(超遠沈法)으로 r-RNA, s-RNA를 분리(分離)하여 이에 대(對)한 nucleotide조성(組成)을 조사(調査)하고 또 가잠견사선(家蠶絹絲腺)과 비교(比較)할 목적(目的)으로 거미 방적선(紡績腺)의 t-RNA를 분리(分離)하여 nucleotide성분(成分)을 측정(測定)하여 다음과 같은 결과(結果)를 얻었다. 1) 잠란(蠶卵)에 있어서 이것을 마수(磨粹), 탈지(脫脂) 후(後) lysozyme을 작용(作用)시키고 10% NaCl용액(溶液)으로 가열(加熱) 추출(抽出)하는 새방법(方法)을 고찰(考察)하여 RNA의 추출(抽出)이 극난(極難)한 잠란(蠶卵)에서 RNA를 분리(分離)하는데 성공(成功)하였다. 2) 가잠란(家蠶卵), 잠체(蠶體), 용체 및 견사선(絹絲腺)(후부(後部))의 t-RNA nucleotide 조성(組成)은 다음과 같다. 시료(試料) $\frac{G+C}{A+U}$ $\frac{G+U}{A+C}$ $\frac{Pu}{Py}$ 가잠란(家蠶卵)의 RNA 1.14 1.24 0.99 가잠체(家蠶體)의 RNA 1.40 1.36 0.80 용체의 RNA 1.40 1.33 1.35 후부견사선(後部絹絲腺)의 RNA 1.05 1.32 1.15 이로서 잠체(蠶體). 용체 및 견사선(絹絲腺)의 Pu/Py는 각각(各各) 차이(差異)가 있으나 G+U/A+C는 3자간(者間)에 1.3의 거이 동일(同一)한 수치(數値)를 보여주고 있다. G+C/A+U는 잠체(蠶體)와 용체에 있어서 동일(同一)하나 견사선(絹絲腺)의 그것과는 차이(差異)가 있다. 한편 잠란(蠶卵)에 있어서는 Pu/Py, G+C/A+U, G+U/A+C가 각각(各各) 잠체(蠶體), 용체 및 견사선(絹絲腺)에 있어서와 현저(顯著)한 차이(差異)를 보여주고 있다. G+C/A+U가 1.3이나 되는 RNA의 base ratio를 가진 생물(生物)에 관(關)해서는 아직 보고(報告)된 바 없고 다만 본논문(本論文)의 가잠(家蠶)에 관(關)한 RNA와 속편(續編)인 각종(各種) 패류(貝類) RNA의 nucleotide 조성(組成)에서 모두 1.3에 가까운 수치(數値)를 보여주고 있다. 3) 견사선(絹絲腺)(후부(後部)) t-RNA와 거미 방적선(紡績腺)의 t-RNA의 nucleotide molar ratio 및 견사선(絹絲腺)의 r-RNA, s-RNA nucleotide 조성(組成)은 다음과 같다. 재료(材料) $\frac{G+C}{A+U}$ $\frac{G+U}{A+C}$ $\frac{Pu}{Py}$ 가잠견사선(家蠶絹絲腺)(후부(後部)의 t-RNA 1.05 1.32 1.15의 r-RNA 1.12 1.30 1.20의 s-RNA 1.55 1.33 0.65 지주방적선(蜘蛛紡績腺)의 t-RNA 1.35 1.24 1.16 즉(卽) 가잠견사선(家蠶絹絲腺)(후부(後部))과 거미방적선(紡績腺)의 t-RNA nucleotide 조성(組成)은 Pu/Py가 1.15와 1.16으로서 거이 동일(同一)하지만 G+C/A+U, G+U/A+C에 차이(差異)가 있음을 보았다. 한편 가잠견사선(家蠶絹絲腺)(후부(後部)) r-RNA와 s-RNA의 Pu/Py와 G+C/A+U는 현저(顯著)한 차이(差異)가 있고, G+U/A+C에 있어서는 1.3으로서 거이 동일(同一)한 수치(數値)를 보여주고 있다. 4. 이상(以上)과 같이 잠체(蠶體)에 관(關)한 RNA의 nucleotide 조성(組成)은 소위(所謂) GC-type로서, 현재(現在)까지 문헌(文獻)에 보고(報告)된 각종(各種) 생물(生物)의 RNA의 base ratio에 관(關)하여 비교(比較) 검토(檢討)하였으며, RNA의 nucleotide ratio의 차이(差異)의 의의(意義)에 대(對)하여 고찰(考察)하였다.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.26 no.2
• /
• pp.69-84
• /
• 1984

This study was carried out to investigate the time distribution of single storms and to establish the model of storm patterns in korea. Rainfall recording charts collected from 42 metheorological stations covering the Korean peninsula were analyzed. A single storm was defined as a rain period seperated from preceding and succeeding rainfall by 6 hours and more. Among the defined single storms, 1199 storms exceeding total rainfall of 80 mm were qualified for the study. Storm patterns were cklassified by quartile classification method and the relationship between cummulative percent of rainfalls and cummulative storm time was established for each quartile storm group. Time distribution models for each stations were prepared through the various analytical and inferential procedures. Obtained results are summarized as follows: 1. The percentile frequency of quartile storms for the first to the fourth quartile were 22.0%, 26.5%, 28.9% and 22.6%, respectively. The large variation of percentile frequency was show between the same quartile storms. The advanced type storm pattern was predominant in the west coastal type storm patterns predominantly when compared to the single storms with small total rainfalls. 3. The single storms with long storm durations tended to show delayed type storm patterns predominantly when compared to the single storms with short storm durations. 4. The percentile time distribution of quartile storms for 42 rin gaging stations was estimated. Large variations were observed between the percentiles of time distributions of different stations. 5. No significant differences were generally found between the time distribution of rainfalls with greater total rainfall and with less total rainfall. This fact suggests that the size of the total rainfall of single storms was not the main factor affecting the time distribution of heavy storms. 6. Also, no significant difference were found between the time distribution of rainfalls with long duration and with short duration. The fact indicates that the storm duration was no the main factor affecting the time distribution of heavy storms. 7. In Korea, among all single storms, 39.0% show 80 to 100mm of total rainfall which stands for the mode of the frequency distribution of total rainfalls. The median value of rainfalls for all single storms from the 42 stations was 108mm. The shape of the frequency distribution of total rainfalls showed right skewed features. No significant differences were shown in the shape of distribution histograms for total rainfall of quartile storms. The mode of rainfalls for the advanced type quartile storms was 80~100mm and their frequencies were 39~43% for respective quartiles. For the delayed type quartile storms, the mode was 80~100mm and their frequencies were 36!38%. 8. In Korea, 29% of all single storms show 720 to 1080 minutes of storm durations which was the highest frequency in the frequency distribution of storm durations. The median of the storm duration for all single storms form 42 stations was 1026 minutes. The shape of the frequency distribution was right skewed feature. For the advanced type storms, the higher frequency of occurrence was shown by the single storms with short durations, whereas for the delayed type quartile storms, the higher frequency was shown gy the long duration single storms. 9. The total rainfall of single storms was positively correlated to storm durations in all the stations throughout the nation. This fact was also true for most of the quartile storms. 10. The third order polynomial regression models were established for estimating the time distribution of quartile storms at different stations. The model test by relative error method resulted good agreements between estimated and observed values with the relative error of less than 0.10 in average.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.3 no.1
• /
• pp.22-29
• /
• 2001

In Korean high yielding varieties developed by crosses between indica and japonica rice, the most limiting factor for yield may be attributed to the less number of the tillers in the unit area. The goals of this study is to find out the effect of the temperature factors as well as cultural practices on the development and increase of tillers of Dasanbyeo, the high yielding indica crossed japonica cultivar. The effect of temperature was examined under controlled phytotron condition with 6 levels of temperature, 15, 17, 19, 22, 24 and 26$^{\circ}C$, respectively, For the experiment, the leading japonica variety in Korea, Hwaseongbyeo, was used for the check cultivar for the comparison with Dasanbyeo. The high temperature also accelerated the initiation and termination of tiller development. The cultivar difference in the speed of tiller development was observed, for example, more rapid development of tiller in Dasanbyeo than in Hwaseongbyeo was observed at the high temperature range of 24-26$^{\circ}C$, while the vice versa phenomena was observed at lower temperature range of 17-22$^{\circ}C$. The first secondary tiller of Dasanbyeo was observed on the 16, 17, 23, 27 and 38 days after transplanting (DAT) at 26$^{\circ}C$, 24$^{\circ}C$, 22$^{\circ}C$, 19$^{\circ}C$, and 17$^{\circ}C$, respectively. Those of Hwaseongbyeo was 19-22, and 26 DAT at 19-26$^{\circ}C$ and 17$^{\circ}C$, respectively. The last effective tiller of Dasanbyeo was observed on 27-33 DAT for the primary tiller, 20-41 DAT for the secondary tiller. Those of Hwaseongbyeo were 23-40 DAT for primary tiller, and 24-40 DAT for the secondary tiller, and 24-40 DAT for the secondary tiller.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.3 no.1
• /
• pp.44-54
• /
• 2001

This study was conducted to estimate microclimate of natural deciduous forest in national forest of Pyungchang, Kangwon province and to investigate the effects of the microclimatic conditions on the periodic annual increment of diameter by site types. In this study, site was first classified by nine types considering both elevation (higher than 1,000 m, 700∼1,000 m, and lower than 700 m) and topographical conditions (ridge, slope and valley). For each of site types, diameter growth was measured by using increment borer and periodic annual increment of diameter was then analyzed. A topoclimatological technique, for estimating microclimatic conditions, which make use of empirical relationships between the topographical factor and the climatic normals in the study area was applied to produce monthly mean, maximum and minimum temperatures, relative humidity, precipitation and hours of sunshine. From these monthly estimtes, 17 weather variables such as warmth index, coldness index, index of aridity etc. which affect the diameter growth were computed for each of site types. The periodic annual increment of diameter was then correlated with and regressed on the 17 weather variables to examine effects of microclimatic conditions on the diameter growth by site types. From the correlation analysis, it was found that the diameter growth by site types was positively correlated with all of 17 weather variables except the warmth index. Especially, the conditions such as high relative humidity and large amount of sunshine hours provide favorable environment for the growth of diameter. On the other hand, it was also found that diameter growth was negatively iufluenced by warmth index. According to the regression analysis, the periodic annual increment of diameter could be well predicted by index of aridity and mean relative humidity for the growing season.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.6 no.4
• /
• pp.218-234
• /
• 2004

Recent warm winters were evaluated for a possible shifting of the northern limit for winter barley cultivation in Korea. Therefore, safe zones for winter barley cultivation were reclassified based on the average and minimum January air temperature in recent years. The results are as follows: By analysis of mean values of January average air temperatures for 30 years (1971-2000), the northern limits for safe cultivation of hulled, naked, and malting barley were Ganghwa - Icheon - Chungju - Chunyang - Goseong, Cheonan - Geumsan - Mungyeong - Andong - Sokcho, and Gwangju - Jangheung - Sancheong - Pohang - Uljin lines, respectively. Meanwhile, based on the January average air temperature of 14 years (1987-2000) with warmer winters, the safe cultivation zone of winter barley shifted northward of the normal (1971-2000). So, the northern limits for hulled, naked, and malting barley were Pocheon - Chuncheon - Wonju - Yangpyeong - Chunyang, Ganghwa - Icheon - Chungju - Uiseong - Goseong, and Gunsan - Suncheon - Jinju - Miryang - Yeongdeok - Uljin lines, respectively. Winter barley cultivars with the strongest tolerance to low temperature can be grown up to the adjacent areas of Taebaek Mountains (that is, Inje, Hongcheon, Jecheon, and Taebaek areas). Based on January mean air temperatures of 10-year return period for 30 years (1971-2000), the northern limits for hulled and naked barley were Boryeong - Namwon - Geochang - Gumi - Goseong and Seocheon - Jeongeup - Hapcheon - Yeongdeok - Sokcho lines, respectively. It ~ppears that malting barley can be cultivated only at southern coastal areas (that is, Busan, Tongyeong, Yeosu, and Wando areas). On the other hand, based on the weather conditions of 14 years (1987-2000) with warmer winters, the northern limits for hulled, naked, and malting barley were Ganghwa - Icheon - Yeongju - Goseong, Seosan - Namwon - Mungyeong - Andong - Sokcho, and Gwangju - Jangheung - Sacheon - Ulsan - Uljin lines, respectively. The northern limit for winter barley cultivars including Olbori with the strongest tolerance to low temperature was the Ganghwa - Wonju - Chungju - Chunyang - Goseong line.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.13 no.3
• /
• pp.148-156
• /
• 2011

The purpose of this study is to analyze the patterns of forest fire possibly related with Asian dust event and carry out a correlation analysis between forest fire occurrence and existence or not of the Asian dust event during dry seasons i.e. February to May in 2000 to 2008. To study the correlation of forest fire and Asian dust, we surveyed information of Asian dust observations, forest fire statistics, fire danger rating index, weather data such as temperature, relative humidity and wind speed of the day occurring the forest fire. As a consequence of analysis, the regional frequency of Asian dust was the highest in Gyeonggi and Chungbuk divisions. Frequencies of forest fire occurrence by the Asian dust events were the highest in the day before three days of the Asian dust event. The highest frequent regions of forest fire occurrence were district of boundary line between Gyeonggi and Western of Gangwon, Chungbuk and Gyeonbuk inland. The correlation between forest fire and fire danger rating index showed the high correlation with the day before three days and after three days of the Asian dust event. These correlation coefficients were 0.50038 and 0.53978 to 1% significance level. The result of analysis between the frequency of forest fire occurrence and wind speed had a highly negative relationship at all the Asian dust days, the day before and after three days. The correlation coefficients had been -0.58623 to -0.61245 to 1% significance level. Relative humidity showed a little of negative relationship with forest fire occurrence in -0.2568(p ${\leq}$ 0.01) for the Asian dust day and -0.35309(p ${\leq}$ 0.01) for next three days. Moreover, at the day before three days of Asian dust events, it was -0.23701 to 1% significance level. However, the mean temperature did not correlate with frequency of forest fire occurrence by Asian dust events at all.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.10 no.3
• /
• pp.82-93
• /
• 2008

In order to ensure a standardized data analysis of the eddy covariance measurements, Hong and Kim's quality control program has been updated and used to process eddy covariance data measured at two levels on the main flux tower at Gwangneung site from January to May in 2005. The updated program was allowed to remove outliers automatically for $CO_2$ and latent heat fluxes. The flag system consists of four quality groups(G, D, B and M). During the study period, the missing data were about 25% of the total records. About 60% of the good quality data were obtained after the quality control. The number of record in G group was larger at 40m than at 20m. It is due that the level of 20m was within the roughness sublayer where the presence of the canopy influences directly on the character of the turbulence. About 60% of the bad data were due to low wind speed. Energy balance closure at this site was about 40% during the study period. Large imbalance is attributed partly to the combined effects of the neglected heat storage terms, inaccuracy of ground heat flux and advection due to local wind system near the surface. The analysis of wind direction indicates that the frequent occurrence of positive momentum flux was closely associated with mountain valley wind system at this site. The negative $CO_2$ flux at night was examined in terms of averaging time. The results show that when averaging time is larger than 10min, the magnitude of calculated $CO_2$ fluxes increases rapidly, suggesting that the 30min $CO_2$ flux is influenced severely by the mesoscale motion or nonstationarity. A proper choice of averaging time needs to be considered to get accurate turbulent fluxes during nighttime.

• Cartoon and Animation Studies
• /
• s.39
• /
• pp.321-348
• /
• 2015

The purpose of this study was to find a system and a progression principle in orchestral piece based on the outcome after comparatively analyzing the orchestral operation technique in "Battle for The Glory" out of the background music in the animation "Dragon Quest IV" by Koichi Sugiyama(1931~), who is a leading runner of Japan's animation music, based on functional parts daccord & Instrumentation Pattern, Rhythm Pattern, Voicing Pattern, and harmonic ratio by progression section devised by the writer. As a result, first, five themes in this music have specific instrumentation pattern, respectively. In a passage that is shown exposition, reprise, and representation in theme, the unity was emphasized by maintaining the same instrumentation pattern. On the contrary to this, a passage of being suggested new theme is being used the exchange method and addition & subtraction in musical instrument in order to strengthen diversity. Second, the voicing pattern is forming the vertical contrasting relationship of "thinness-thickness" on the whole. However, the diversity is being intensified that is changed into the structure of "thickness-thinness" in the third theme and of "thinness-thickness" that has two melodies in the fourth theme. Third, the rhythm pattern is forming the vertical contrasting relationship of "big-small" on the whole. However, the fifth theme is being given diversity with being changed into the structure of "small-big." Fourth, the harmony by progression section from the horizontal perspective is shown to be high in the proportion of unity in the section of being repeated and represented the theme and to be high in the proportion of diversity in the section of being suggested new theme. In this study, the balanced orchestral operation technique through the operation technique, which was used in this work, is what extracts the relationship of diverse proportions in the horizontal progression section based on the technique of vertical perspective. In this aspect, this analytical study is desired to be positioned as a new paradigm in establishing a theoretical system and an educational method in orchestration.

• Journal of Intelligence and Information Systems
• /
• v.21 no.3
• /
• pp.79-99
• /
• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of Intelligence and Information Systems
• /
• v.18 no.1
• /
• pp.125-141
• /
• 2012

These days, the malicious attacks and hacks on the networked systems are dramatically increasing, and the patterns of them are changing rapidly. Consequently, it becomes more important to appropriately handle these malicious attacks and hacks, and there exist sufficient interests and demand in effective network security systems just like intrusion detection systems. Intrusion detection systems are the network security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. Conventional intrusion detection systems have generally been designed using the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. However, they cannot handle new or unknown patterns of the network attacks, although they perform very well under the normal situation. As a result, recent studies on intrusion detection systems use artificial intelligence techniques, which can proactively respond to the unknown threats. For a long time, researchers have adopted and tested various kinds of artificial intelligence techniques such as artificial neural networks, decision trees, and support vector machines to detect intrusions on the network. However, most of them have just applied these techniques singularly, even though combining the techniques may lead to better detection. With this reason, we propose a new integrated model for intrusion detection. Our model is designed to combine prediction results of four different binary classification models-logistic regression (LOGIT), decision trees (DT), artificial neural networks (ANN), and support vector machines (SVM), which may be complementary to each other. As a tool for finding optimal combining weights, genetic algorithms (GA) are used. Our proposed model is designed to be built in two steps. At the first step, the optimal integration model whose prediction error (i.e. erroneous classification rate) is the least is generated. After that, in the second step, it explores the optimal classification threshold for determining intrusions, which minimizes the total misclassification cost. To calculate the total misclassification cost of intrusion detection system, we need to understand its asymmetric error cost scheme. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, total misclassification cost is more affected by FNE rather than FPE. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 10,000 samples from them by using random sampling method. Also, we compared the results from our model with the results from single techniques to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell R4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on GA outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that the proposed model outperformed all the other comparative models in the total misclassification cost perspective. Consequently, it is expected that our study may contribute to build cost-effective intelligent intrusion detection systems.