• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.71-88
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• 2017

Language models were originally developed for speech recognition and language processing. Using a set of example sentences, a language model predicts the next word or character based on sequential input data. N-gram models have been widely used but this model cannot model the correlation between the input units efficiently since it is a probabilistic model which are based on the frequency of each unit in the training set. Recently, as the deep learning algorithm has been developed, a recurrent neural network (RNN) model and a long short-term memory (LSTM) model have been widely used for the neural language model (Ahn, 2016; Kim et al., 2016; Lee et al., 2016). These models can reflect dependency between the objects that are entered sequentially into the model (Gers and Schmidhuber, 2001; Mikolov et al., 2010; Sundermeyer et al., 2012). In order to learning the neural language model, texts need to be decomposed into words or morphemes. Since, however, a training set of sentences includes a huge number of words or morphemes in general, the size of dictionary is very large and so it increases model complexity. In addition, word-level or morpheme-level models are able to generate vocabularies only which are contained in the training set. Furthermore, with highly morphological languages such as Turkish, Hungarian, Russian, Finnish or Korean, morpheme analyzers have more chance to cause errors in decomposition process (Lankinen et al., 2016). Therefore, this paper proposes a phoneme-level language model for Korean language based on LSTM models. A phoneme such as a vowel or a consonant is the smallest unit that comprises Korean texts. We construct the language model using three or four LSTM layers. Each model was trained using Stochastic Gradient Algorithm and more advanced optimization algorithms such as Adagrad, RMSprop, Adadelta, Adam, Adamax, and Nadam. Simulation study was done with Old Testament texts using a deep learning package Keras based the Theano. After pre-processing the texts, the dataset included 74 of unique characters including vowels, consonants, and punctuation marks. Then we constructed an input vector with 20 consecutive characters and an output with a following 21st character. Finally, total 1,023,411 sets of input-output vectors were included in the dataset and we divided them into training, validation, testsets with proportion 70:15:15. All the simulation were conducted on a system equipped with an Intel Xeon CPU (16 cores) and a NVIDIA GeForce GTX 1080 GPU. We compared the loss function evaluated for the validation set, the perplexity evaluated for the test set, and the time to be taken for training each model. As a result, all the optimization algorithms but the stochastic gradient algorithm showed similar validation loss and perplexity, which are clearly superior to those of the stochastic gradient algorithm. The stochastic gradient algorithm took the longest time to be trained for both 3- and 4-LSTM models. On average, the 4-LSTM layer model took 69% longer training time than the 3-LSTM layer model. However, the validation loss and perplexity were not improved significantly or became even worse for specific conditions. On the other hand, when comparing the automatically generated sentences, the 4-LSTM layer model tended to generate the sentences which are closer to the natural language than the 3-LSTM model. Although there were slight differences in the completeness of the generated sentences between the models, the sentence generation performance was quite satisfactory in any simulation conditions: they generated only legitimate Korean letters and the use of postposition and the conjugation of verbs were almost perfect in the sense of grammar. The results of this study are expected to be widely used for the processing of Korean language in the field of language processing and speech recognition, which are the basis of artificial intelligence systems.

• Progress in Medical Physics
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• v.23 no.1
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• pp.15-25
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• 2012

The aim of this study is to evaluate plan quality and dose accuracy for Volumetric Modulated Arc Therapy (VMAT) on the TG-119 and is to investigate the effects on variation of the selectable optimization parameters of VMAT. VMAT treatment planning was implemented on a Varian iX linear accelerator with ARIA record and verify system (Varian Mecical System Palo Alto, CA) and Oncentra MasterPlan treatment planning system (Nucletron BV, Veenendaal, Netherlands). Plan quality and dosimetric accuracy were evaluated by effect of varying a number of arc, gantry spacing and delivery time for the test geometries provided in TG-119. Plan quality for the target and OAR was evaluated by the mean value and the standard deviation of the Dose Volume Histograms (DVHs). The ionization chamber and $Delta^{4PT}$ bi-planar diode array were used for the dose evaluation. For treatment planning evaluation, all structure sets closed to the goals in the case of single arc, except for the C-shape (hard), and all structure sets achieved the goals in the case of dual arc, except for C-shape (hard). For the variation of a number of arc, the simple structure such as a prostate did not have the difference between single arc and dual arc, whereas the complex structure such as a head and neck showed a superior result in the case of dual arc. The dose distribution with gantry spacing of $4^{\circ}$ was shown better plan quality than the gantry spacing of $6^{\circ}$, but was similar results compared with gantry spacing of $2^{\circ}$. For the verification of dose accuracy with single arc and dual arc, the mean value of a relative error between measured and calculated value were within 3% and 4% for point dose and confidence limit values, respectively. For the verification on dose accuracy with the gantry intervals of $2^{\circ}$, $4^{\circ}$ and $6^{\circ}$, the mean values of relative error were within 3% and 5% for point dose and confidence limit values, respectively. In the verification of dose distribution with $Delta^{4PT}$ bi-planar diode array, gamma passing rate was $98.72{\pm}1.52%$ and $98.3{\pm}1.5%$ for single arc and dual arc, respectively. The confidence limit values were within 4%. The smaller the gantry spacing, the more accuracy results were shown. In this study, we performed the VMAT QA based on TG-119 procedure, and demonstrated that all structure sets were satisfied with acceptance criteria. And also, the results for the selective optimization variables informed the importance of selection for the suitable variables according to the clinical cases.

• Sleep Medicine and Psychophysiology
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• v.9 no.1
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• pp.34-40
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• 2002

Objectives: The gold standard for diagnosing obstructive sleep apnea syndrome (OSAS) is nocturnal polysomnography (NPSG). This is rather expensive and somewhat inconvenient, however, and consequently simpler and cheaper alternatives to NPSG have been proposed. Oximetry is appealing because of its widespread availability and ease of application. In this study, we have evaluated whether oximetry alone can be used to diagnose or screen OSAS. The diagnostic performance of an analysis algorithm using arterial oxygen saturation ($SaO_2$) base on 'dip index', mean of $SaO_2$, and CT90 (the percentage of time spent at $SaO_2$<90%) was compared with that of NPSG. Methods: Fifty-six patients referred for NPSG to the Division of Sleep Studies at Seoul National University Hospital, were randomly selected. For each patient, NPSG with oximetry was carried out. We obtained three variables from the oximetry data such as the dip index most linearly correlated with respiratory disturbance index (RDI) from NPSG, mean $SaO_2$, and CT90 with diagnosis from NPSG. In each case, sensitivity, specificity and positive and negative predictive values of oximetry data were calculated. Results: Thirty-nine patients out of fifty-six patients were diagnosed as OSAS with NPSG. Mean RDI was 17.5, mean $SaO_2$ was 94.9%, and mean CT90 was 5.1%. The dip index [4%-4sec] was most linearly correlated with RDI (r=0.861). With dip index [4%-4sec]${\geq}2$ as diagnostic criteria, we obtained sensitivity of 0.95, specificity of 0.71, positive predictive value of 0.88, and negative predictive value of 0.86. Using mean $SaO_2{\leq}97%$, we obtained sensitivity of 0.95, specificity of 0.41, positive predictive value of 0.79, and negative predictive value of 0.78. Using $CT90{\geq}5%$, we obtained sensitivity of 0.28, specificity of 1.00, positive predictive value of 1.00, and negative predictive value of 0.38. Conclusions: The dip index [4%-4sec] and mean $SaO_2{\leq}97%$ obtained from nocturnal oximetry data are helpful in diagnosis of OSAS. CT90${\leq}$5% can be also used in excluding OSAS.

• Economic and Environmental Geology
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• v.35 no.5
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• pp.379-393
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• 2002

Within the Boseong-Jangheung area of Korea, five hydrothermal gold (-silver) quartz vein deposits occur. They have the characteristic features as follows: the relatively gold-rich nature of e1ectrurns; the absence of Ag-Sb( -As) sulfosalt mineral; the massive and simple mineralogy of veins. They suggest that gold mineralization in this area is correlated with late Jurassic to Early Cretaceous, mesothermal-type gold deposits in Korea. Fluid inclusion data show that fluid inclusions in stage I quartz of the mine area homogenize over a wide temperature range of 200$^{\circ}$ to 460$^{\circ}$C with salinities of 0.0 to 13.8 equiv. wt. % NaCI. The homogenization temperature of fluid inclusions in stage II calcite of the mine area ranges from 150$^{\circ}$ to 254$^{\circ}$C with salinities of 1.2 to 7.9 equiv. wt. % NaCI. This indicates a cooling of the hydrothermal fluid with time towards the waning of hydrothermal activity. Evidence of fluid boiling including CO2 effervescence indicates that pressures during entrapment of auriferous fluids in this area range up to 770 bars. Calculated sulfur isotope composition of auriferous fluids in this mine area (${\delta}^34S$_{{\Sigma}S}$$\textperthousand$) indicates an igneous source of sulfur in auriferous hydrothermal fluids. Within the Sobaegsan Massif, two representative mesothermal-type gold mine areas (Youngdong and Boseong-Jangheung areas) occur. The ${\delta}^34S values of sulfide minerals from Youngdong area range from -6.6 to 2.3$\textperthousand$ (average=-1.4$\textperthousand$, N=66), and those from BoseongJangheung area range from -0.7 to 3.6$\textperthousand$ (average=1.6$\textperthousand$, N=39). These i)34S values of both areas are comparatively lower than those of most Korean metallic ore deposits (3 to 7TEX>$\textperthousand$). And, within the Sobaegsan Massif, the ${\delta}^34S values of Youngdong area are lower than those of Boseong-Jangheung area. It is inferred that the difference of ${\delta}^34S values within the Sobaegsan Massif can be caused by either of the following mechanisms: (1) the presence of at least two distinct reservoirs (both igneous, with ${\delta}^34S values of < -6 $\textperthousand$ and 2$\pm$2 %0) for Jurassic mesothermal-type gold deposits in both areas; (2) different degrees of the mixing (assimilation) of 32S-enriched sulfur (possibly sulfur in Precambrian pelitic basement rocks) during the generation and/or subsequent ascent of magma; and/or (3) different degrees of the oxidation of an H2S-rich, magmatically derived sulfur source ${\delta}^34S = 2$\pm$2$\textperthousand$) during the ascent to mineralization sites. According to the observed differences in ore mineralogy (especially, iron-bearing ore minerals) and fluid inclusions of quartz from the mesothermal-type deposits in both areas, we conclude that pyrrhotite-rich, mesothermal-type deposits in the Youngdong area formed from higher temperatures and more reducing fluids than did pyrite(-arsenopyrite)-rich mesothermal-type deposits in the Boseong-Jangheung area. Therefore, we prefer the third mechanism than others because the ${\delta}^34S values of the Precambrian gneisses and Paleozoic sedimentary rocks occurring in both areas were not known to the present. In future, in order to elucidate the provenance of ore sulfur more systematically, we need to determine ${\delta}^34S values of the Precambrian metamorphic rocks and Paleozoic sedimentary rocks consisting the basement of the Korean Peninsula including the Sobaegsan Massif.

• The Journal of Korean Society for Radiation Therapy
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• v.32
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• pp.17-29
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• 2020

Purpose: The purpose of this work was to investigate the dosimetric impact of mixed energy partial arc technique on prostate cancer VMAT. Materials and Methods: This study involved prostate only patients planned with 70Gy in 30 fractions to the planning target volume (PTV). Femoral heads, Bladder and Rectum were considered as oragan at risk (OARs). For this study, mixed energy partial arcs (MEPA) were generated with gantry angle set to 180°~230°, 310°~50° for 6MV arc and 130°~50°, 310°~230° for 15MV arc. Each arc set the avoidance sector which is gantry angle 230°~310°, 50°~130° at first arc and 50°~310° at second arc. After that, two plans were summed and were analyzed the dosimetry parameter of each structure such as Maximum dose, Mean dose, D2%, Homogeneity index (HI) and Conformity Index (CI) for PTV and Maximum dose, Mean dose, V70Gy, V50Gy, V30Gy, and V20Gy for OARs and Monitor Unit (MU) with 6MV 1 ARC, 6MV, 10MV, 15MV 2 ARC plan. Results: In MEPA, the maximum dose, mean dose and D2% were lower than 6MV 1 ARC plan(p<0.0005). However, the average difference of maximum dose was 0.24%, 0.39%, 0.60% (p<0.450, 0.321, 0.139) higher than 6MV, 10MV, 15MV 2 ARC plan, respectively and D2% was 0.42%, 0.49%, 0.59% (p<0.073, 0.087, 0.033) higher than compared plans. The average difference of mean dose was 0.09% lower than 10MV 2 ARC plan, but it is 0.27%, 0.12% (p<0.184, 0.521) higher than 6MV 2 ARC, 15MV 2 ARC plan, respectively. HI was 0.064±0.006 which is the lowest value (p<0.005, 0.357, 0.273, 0.801) among the all plans. For CI, there was no significant differences which were 1.12±0.038 in MEPA, 1.12±0.036, 1.11±0.024, 1.11±0.030, 1.12±0.027 in 6MV 1 ARC, 6MV, 10MV, 15MV 2 ARC, respectively. MEPA produced significantly lower rectum dose. Especially, V70Gy, V50Gy, V30Gy, V20Gy were 3.40, 16.79, 37.86, 48.09 that were lower than other plans. For bladder dose, V30Gy, V20Gy were lower than other plans. However, the mean dose of both femoral head were 9.69±2.93, 9.88±2.5 which were 2.8Gy~3.28Gy higher than other plans. The mean MU of MEPA were 19.53% lower than 6MV 1 ARC, 5.7% lower than 10MV 2 ARC respectively. Conclusion: This study for prostate radiotherapy demonstrated that a choice of MEPA VMAT has the potential to minimize doses to OARs and improve homogeneity to PTV at the expense of a moderate increase in maximum and mean dose to the femoral heads.

• The Korean Journal of Nuclear Medicine Technology
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• v.25 no.2
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• pp.35-40
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• 2021

Purpose Glomerular filtration rate(GFR) is an important indicator for the diagnosis, treatment, and follow-up of kidney disease and is also used by healthy individuals for drug use and evaluating kidney function in donors. The gold standard method of the GFR test is to measure by continuously injecting the inulin which is extrinsic marker, but it takes a long time and the test method is complicated. so, the method of measuring the serum concentration of creatinine is used. Estimated glomerular filtration rate (eGFR) is used instead. However, creatinine is known to be affected by age, gender, muscle mass, etc. eGFR formulas that are currently used include the Cockroft-Gault formula, the modification of diet in renal disease (MDRD) formula, and the chronic kidney disease epidemilogy collaboration (CKD-EPI) formula for adults. For children, the Schwartz formula is used. Measurement of GFR using ⁵¹Cr-EDTA (diethylenetriamine tetraacetic acid), ^99mTc-DTPA (diethylenetriamine pentaacetic acid) can replace inulin and is currently in use. Therefore, We compared the GFR measured using ^99mTc-DTPA with the eGFR using CKD-EPI formula. Materials and Methods For 200 kidney transplant donors who visited Asan medical center.(96 males, 104 females, 47.3 years ± 12.7 years old) GFR was measured using plasma(Two-plasma-sample-method, TPSM) obtained by intravenous administration of ^99mTc-DTPA(0.5mCi, 18.5 MBq). eGFR was derived using CKD-EPI formula based on serum creatinine concentration. Results GFR average measured using ^99mTc-DTPA for 200 kidney transplant donors is 97.27±19.46(ml/min/1.73m²), and the eGFR average value using the CKD-EPI formula is 96.84±17.74(ml/min/1.73m²), The concentration of serum creatinine is 0.84±0.39(mg/dL). Regression formula of ^99mTc-DTPA GFR for serum creatinine-based eGFR was Y = 0.5073X + 48.186, and the correlation coefficient was 0.698 (P<0.01). Difference (%) was 1.52±18.28. Conclusion The correlation coefficient between the ^99mTc-DTPA and the eGFR derived on serum creatinine concentration was confirmed to be moderate. This is estimated that eGFR is affected by external factors such as age, gender, and muscle mass and use of formulas made for kidney disease patients. By using ^99mTc-DTPA, we can provide reliable GFR results, which is used for diagnosis, treatment and observation of kidney disease, and kidney evaluation of kidney transplant patients.

• Journal of Preventive Medicine and Public Health
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• v.30 no.1 s.56
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• pp.45-59
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• 1997

It has been known that there is a tracking phenomenon in the level of serum lipids. However, no study has been performed to examine the change and tracking of serum lipids in Korean adolescents. The purpose of this study is to examine the changes of serum lipids in Korean adolescents from 12 to 16 years of age, and to examine whether or not there is a tracking phenomenon in serum lipids level during the period. In 1992 serum lipids(total cholesterol(TC), triglyceride(TG), LDL cholesterol(LDL-C), HDL cholesterol(HDL-C)) were measured in 318 males, 365 females who were 12 years of age in Kangwha county, Korea. These participants have been followed up to 1996 and serum lipids level were examined in 1994 and 1996. Among the participants 162 males and 147 females completed all three examinations in fasting state. To examine the effect of eliminating adolescents with incomplete data, we compared serum lipids, blood pressure and anthropometric measures at baseline between adolescents with complete follow-up and adolescents who were withdrawn. To examine the change of serum lipids we compared mean values of serum lipids according to age in males and females. Repeated analysis of variance was used to test the change according to age. We used three methods to examine the existence of tracking. First, we analyzed the trends in serum lipids over 4-year period within quartile groups formed on the basis of the first-year serum lipids level to see whether or not the relative ranking of the mean serum lipids among the quartile groups remained in the same group for 4-year period. Second, we quantified the degree of tracking by calculating Spearman's rank correlation coefficient between every tests. Third, the persistence extreme quartile method was used. This method divides the population into quartile groups according to the initial level of blood lipids and then calculates the percent of the subjects who stayed in the same group at follow-up measurement. The decreases in levels were noted during 4 years for TC, LDL-C, primarily for boys. The level of HDL-C decreased between baseline and first follow-up for both sexes. Tracking, as measured by both correlation coefficients and persistence extreme quartiles, was evident for all of the lipids. The correlation coefficients of TC between baseline and 4 years later in boys and girls were 0.55 and 0.68, respectively. And the corresponding values for HDL-C were 0.58 and 0.69. More than 50% of adolescents who belonged to the highest quartile group in TC, HDL-C and LDL-C at the baseline were remained at the same group at the examination performed 2 years later for both sexes. The probabilities of remaining at the same group were more than 35% when examined 4 years later. The tracking phenomenon of TG was less evident compared with the other lipids. Percents of girls who stayed at the same group 2 years later and 4 years later were 42.9% and 25.7%, respectively. It was evident that serum lipid levels tracked in Korean adolescents. Researches with longer follow-up would be needed in the future to investigate the long-term change of lipids from adolescents to adults.

• Journal of the Korean Wood Science and Technology
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• v.2 no.2
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• pp.8-12
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• 1974

1. If one unity is given to the prongs whose ends touch each other for estimating the internal stresses occuring in it, the internal stresses which are developed in the open prongs can be evaluated by the ratio to the unity. In accordance with the above statement, an equation was derived as follows. For employing this equation, the prongs should be made as shown in Fig. I, and be measured A and B' as indicated in Fig. l. A more precise value will result as the angle (J becomes smaller. $CH=\frac{(A-B') (4W+A) (4W-A)}{2A[(2W+(A-B')][2W-(A-B')]}{\times}100%$ where A is thickness of the prong, B' is the distance between the two prongs shown in Fig. 1 and CH is the value of internal stress expressed by percentage. It precision is not required, the equation can be simplified as follows. $CH=\frac{A-B'}{A}{\times}200%$ 2. Under scheduled drying condition III the kiln, when the weight of a sample board is constant, the moisture content of the shell of a sample board in the case of a normal casehardening is lower than that of the equilibrium moisture content which is indicated by the Forest Products Laboratory, U. S. Department of Agriculture. This result is usually true, especially in a thin sample board. A thick unseasoned or reverse casehardened sample does not follow in the above statement. 3. The results in the comparison of drying rate with five different kinds of wood given in Table 1 show that the these drying rates, i.e., the quantity of water evaporated from the surface area of I centimeter square per hour, are graded by the order of their magnitude as follows. (1) Ginkgo biloba Linne (2) Diospyros Kaki Thumberg. (3) Pinus densiflora Sieb. et Zucc. (4) Larix kaempheri Sargent (5) Castanea crenata Sieb. et Zucc. It is shown, for example, that at the moisture content of 20 percent the highest value revealed by the Ginkgo biloba is in the order of 3.8 times as great as that for Castanea crenata Sieb. & Zucc. which has the lowest value. Especially below the moisture content of 26 percent, the drying rate, i.e., the function of moisture content in percentage, is represented by the linear equation. All of these linear equations are highly significant in testing the confficient of X i. e., moisture content in percentage. In the Table 2, the symbols are expressed as follows; Y is the quantity of water evaporated from the surface area of 1 centimeter square per hour, and X is the moisture content of the percentage. The drying rate is plotted against the moisture content of the percentage as in Fig. 2. 4. One hundred times the ratio(P%) of the number of samples occuring in the CH 4 class (from 76 to 100% of CH ratio) within the total number of saplmes tested to those of the total which underlie the given SR ratio is measured in Table 3. (The 9% indicated above is assumed as the danger probability in percentage). In summarizing above results, the conclusion is in Table 4. NOTE: In Table 4, the column numbers such as 1. 2 and 3 imply as follows, respectively. 1) The minimum SR ratio which does not reveal the CH 4, class is indicated as in the column 1. 2) The extent of SR ratio which is confined in the safety allowance of 30 percent is shown in the column 2. 3) The lowest limitation of SR ratio which gives the most danger probability of 100 percent is shown in column 3. In analyzing above results, it is clear that chestnut and larch easly form internal stress in comparison with persimmon and pine. However, in considering the fact that the revers, casehardening occured in fir and ginkgo, under the same drying condition with the others, it is deduced that fir and ginkgo form normal casehardening with difficulty in comparison with the other species tested. 5. All kinds of drying defects except casehardening are developed when the internal stresses are in excess of the ultimate strength of material in the case of long-lime loading. Under the drying condition at temperature of $170^{\circ}F$ and the lower humidity. the drying defects are not so severe. However, under the same conditions at $200^{\circ}F$, the lower humidity and not end coated, all sample boards develop severe drying defects. Especially the chestnut was very prone to form the drying defects such as casehardening and splitting.