Estimation of High Resolution Sea Surface Salinity Using Multi Satellite Data and Machine Learning (다종 위성자료와 기계학습을 이용한 고해상도 표층 염분 추정)
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- Korean Journal of Remote Sensing
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- v.38 no.5_2
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- pp.747-763
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- 2022
Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.
This study was conducted to estimate genetic parameters for milk production and linear type traits in Holstein dairy cattle in Korea. The data including milk yields, fat yields, protein yields, fat percent, protein percent, somatic score and 15 linear type traits for 10,218 first parity cows collected by Dairy Cattle Improvement Center, National Agricultural Cooperative, Korea, which were calving from January 2009 to April 2013. Genetic and error (co)variances between two traits selected form 19 traits were estimated using bi-trait pairwise analyses with WOMBAT package. The estimated heritabilities for milk yield(MY), fat yield(FY), protein yield(PY), fat percent(FP), protein percent(PP), somatic cell score(SCS), udder depth(UD), udder texture(UT), median suspensory(MS), fore udder attachment(FUA), front teat placement (FTP), rear attachment height(RAH), rear attachment width(RAW), rear teat placement(RTP), front teat length(FTL), foot angle(FA), heel depth(HD), bone quality(BQ), rear legs side view(RLSV), rear legs rear view(RLRV) and locomotion(LC) were 0.128, 0.144, 0.100, 0.273, 0.333, 0.090, 0.179, 0.066, 0.104, 0.109, 0.127, 0.099, 0.059, 0.069, 0.154, 0.014, 0.010, 0.052, 0.065, 0.175 and 0.031, respectively. Among the genetic correlations, UD, UT, FTP, RAW, FTL, FA and RLSV with MY were -0.334, 0.271, 0.445, 0.544, 0.076, -0.281 and -0.228, respectively, and MS, FTP, RTP, FTL, FA, BQ, RLSV, RLRV and LC with PP were -0.147, -0.182, -0.262, -0.136, 0.355, 0.311, 0.135, 0.233 and 0.143, respectively. Especially, MY had the highest positive genetic correlation with RAW (0.544), while SCS had the highest negative genetic correlation with LC (-0.603). FP had negative genetic correlation with most udder traits, whereas, FP had positive genetic correlation with leg and hoof traits (0.056 - 0.355).
This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
The wall shear stress in the vicinity of end-to end anastomoses under steady flow conditions was measured using a flush-mounted hot-film anemometer(FMHFA) probe. The experimental measurements were in good agreement with numerical results except in flow with low Reynolds numbers. The wall shear stress increased proximal to the anastomosis in flow from the Penrose tubing (simulating an artery) to the PTFE: graft. In flow from the PTFE graft to the Penrose tubing, low wall shear stress was observed distal to the anastomosis. Abnormal distributions of wall shear stress in the vicinity of the anastomosis, resulting from the compliance mismatch between the graft and the host artery, might be an important factor of ANFH formation and the graft failure. The present study suggests a correlation between regions of the low wall shear stress and the development of anastomotic neointimal fibrous hyperplasia(ANPH) in end-to-end anastomoses. 30523 T00401030523 ^x Air pressure decay(APD) rate and ultrafiltration rate(UFR) tests were performed on new and saline rinsed dialyzers as well as those roused in patients several times. C-DAK 4000 (Cordis Dow) and CF IS-11 (Baxter Travenol) reused dialyzers obtained from the dialysis clinic were used in the present study. The new dialyzers exhibited a relatively flat APD, whereas saline rinsed and reused dialyzers showed considerable amount of decay. C-DAH dialyzers had a larger APD(11.70
Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.
The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.
In china, six bibliographies of offical historical books are evaluated at the most important things among the systematically-editing bibliographies. These bibliographies would be usful to study the orign of classical sciences and their development, bibliographic research of Chinese classics, bibliographic judgement on genuine books, titles, authors, volumes. They could be refered to research into graving, correcting, and existence of ancient books. therefore, these bibliographies would be applied to estimation the phase of scientific and cultural development. The study of these bibliographies has been not yet made in Korea. This thesis lays its importance on the background of their appearance, their classification norms, organizing system of their catalogue, and comparison between their difference. 1. Editing and compiling of Chilyak (칠약) by Liu Chin (유흠) and official histories played an important role of entering an apperance of historical book's bibliographies. Chilyak has been lost. However, its classification and compiling system of classical books would be traced by Hansoyemunji(한서예문지) of which basic system is similar to Chilyak. It classified books according to their scientific characteristic. If a few books didn't have their own categories, they were combined by the circles parallel to the books' characteristic. With the books classified under the same scientific characteristic, they were again divided into the scientific schools or structures. It also arranged the same kinds of books according to the chronology. The some books wi th duplicate subjects were classified multiplely by their duplicate subject. 2. Ssu-ma Chon's (사마천) The Historical Records (Saki, 사기) and Pan Ku's (반고) The History of the Former Han Dynasty (Hanso, 한서) has also took effects on appearance of historical books' bibliographies. Covering overall history, Saki was structured by the five parts: The basic annals(본기), the chronological tables (표), the documents (서), the hereditary houses (세가), biographies (열전). The basic annals dealt with kings and courts' affairs according to the chronology. The chronological tables was the records of the annals. The documents described overall the social and cultural systems. The hereditary houses recorded courts' meritorious officials and public figures. The biographies showed exemplars of seventy peoples selected by their social status. Pan Ku(반구)'s The History of the Former Han Dynasty(한서) deserved to be called the prototype for the offical histories after Saki's (사기; The Historical Records) apperance. Although it modelled on Saki, it had set up its own cataloguing system. It was organized by four parts; the basic annals (본기), the chronological tables (표), treatises(지), biographies (열전). The documents in the Hanso(한서) was converted into treatises(지). The hereditary houses and biographies were merged. For the first time, the treatise with The Yemunji could operate function for historical bibliographies. 3. There were six historical bibliographies: Hansoyemunji(한서예문지), Susokyongjeokji (수서경적지), Kudangsokyongjeokji(구당서경적지), Shindangsoyemunji (신당서예문지), Songsayemunji (송사예문지), Myongsayemunji (명사예문지). 1) Modelling on Liu Chin's Chilyak except Chipryak(집략), Hansoyemunji divided the characteristic of the books and documents into six parts: Yukrye(육예), Cheja(제자), Shibu(시부), Pyongsoh(병서), Susul(수술), Pangki(방기). Under six parts, there were thirty eight orders in Hansoyemunji. To its own classification, Hansoyemunji applied the Chilyak's theory of classification that the books or documents were managed according to characteristic of sciences, the difference of schools, the organization of sentences. However the overlapped subjects were deleted and unified into one. The books included into an unsuitable subject were corrected and converted into another. The Hansoyemunji consisted of main preface (Taesoh 대서), minor preface (Sosoh 소서) , the general preface (Chongso 총서). It also recorded the introduction of books and documents, the origin of sciences, the outline of subjects, and the establishment of orders. The books classified by the subject had title, author, and volumes. They were rearranged by titles and the chronological publication year. Sometimes author was the first access point to catalogue the books. If it was necessary for the books to take footnotes, detail notes were formed. The Volume number written consecutively to order and subject could clarify the quantity of books. 2) Refering to Classfication System by Seven Norms (칠분법) and Classification System by Four Norms(사분법), Susokyongjeokji(수서경적지) had accomplished the classification by four norms. In fact, its classification largely imitated Wanhyosoh(완효서)'s Chilrok(칠록), Susokyongjeokji's system of classification consisted of four parts-Kyung(경), Sa(사), Cha(자), Chip(칩). The four parts were divided into 40 orders. Its appendix was again divided into two parts, Buddihism and Taiosm. Under the two parts there were fifteen orders. Totally Susokyongjeokji was made of six parts and fifty five orders. In comparison with Hansoyemunji(한서예문지), it clearly showed the conception of Kyung, Sa, Cha, Chip. Especially it deserved to be paid attention that Hansoyemunji laied history off Chunchu(춘추) and removed history to Sabu(사부). However Chabu(사부) put many contrary subjects such as Cheja(제자), Kiye(기예), Sulsu(술수), Sosol(소설) into the same boundary, which committed errors insufficient theoretical basis. Anothor demerit of Susokyongjeokji was that it dealt with Taiosm scriptures and Buddism scriptures at the appendix because they were considered as quasi-religion. Its compilation of bibliographical facts consisted of main preface(Taesoh 대서), minor preface(Sosoh 소서), general preface (Chongsoh 총서), postscript (Husoh 후서). Its bibliological facts mainly focused on the titles. Its recorded authors' birth date and their position. It wrote the lost and existence of books consecutive to total number of books, which revealed total of the lost books in Su Dynasty. 3) Modelling on the basis of Kokumsorok(고분서록) and Naewaekyongrok(내외경록), Kudangsokyongjeokji(구당서경적지) had four parts and fourty five orders. It was estimated as the important role of establishing basic frame of classification by four norms in classification theory's history. However it had also its own limit. Editing and compling orders of Kudangsokyongjeokji had been not progressively changed. Its orders imitated by and large Susokyongjeokji. In Its system of organizing catalogue, with its minor preface and general preface deleting, Kudangsokyongjeokji by titles after orders sometimes broke out confusion because of unclear boundaries between orders. 4) Shindangsoyemunji(신당서예문지), adding 28,469 books to Kudangsokyongjeokji, recorded 82,384 books which were divided by four parts and fourty four orders. In comparison with Kudangkyongjeokj, Sindangsoyemunji corrected unclear order's norm. It merged the analogical norms four orders (for instance, Kohun 고훈 and Sohakryu 소학류) and seperated the different norms four orders (for example, Hyokyong 효경 and Noneuhryu 논어류, Chamwi 참위 and Kyonghaeryu 경해류, Pyonryon 편년 and Wisaryu 위사류). Recording kings' behaviors and speeches (Kikochuryu 기거주류) in the historical parts induced the concept of specfication category. For the first time, part of Chipbu (집부) set up the order of classification norm for historical and literatural books and documents (Munsaryu 문사류). Its editing and compiling had been more simplified than Kudangsokyongjeokji. Introduction was written at first part of bibliographies. Appendants except bibliographic items such subject, author, title, volume number, total were omitted. 5) Songsayemunji(송사예문지) were edited in the basis of combining Puksong(북송) and Namsong(남송), depending on Sabukuksayemunji(사부국사예문지). Generally Songsayemunji had lost a lot of bibliographical facts of many books. They were duplicated and wrongly classified books because it committed an error of the incorrectly annalistic editing. Particularly Namsong showed more open these defaults. Songsayemunji didin't include the books published since the king Youngchong(영종). Its system of classification was more better controlled. Chamwiryu(참위류) in the part of Kyongbu(경부) was omitted. In the part of history(Sabu 사부), recordings of kings' behaviors and speeches more merged in the annals. Historical abstract documents (Sachoryu 사초류) were seperately arranged. In the part of Chabu(자부), Myongdangkyongmaekryu(명당경맥류) and Euisulryu(의술류) were combined. Ohangryu(오행류) were laied off Shikuryu(시구류). In the part of Chipbu(집부), historical and literatural books (Munsaryu 문사류) were independentely arranged. There were the renamed orders; from Wisa(위사) to Paesa(패사), Chapsa (잡사) to Pyolsa(열사), Chapchonki(잡전기) to Chonki(전기), Ryusoh(류서) to Ryusa(류서). Introduction had only main preface. The books of each subject catalogued by title, the volume number, and author and arranged mainly by authors. Annotations were written consecutively after title and the volume number. In the afternote the number of not-treated books were revealed. Difference from Singdangsohyemunji(신당서예문지) were that the concept and boundary of orders became more clearer. It also wrote the number of books consecutive to main subject. 6) Modelling on Chonkyongdangsomok (경당서목), Myongsayemunji(명사예문지) was compiled in the basis of books and documents published in the Ming Danasty. In classification system, Myongsayemunji partly merged and the seperated some orders for it. It also deleted and renamed some of orders. In case of necessity, combining of orders' norm was occured particulary in the part of Sabu(사부) and Chabu(자부). Therefore these merging of orders norm didn't offer sufficient theretical background. For example, such demerits were seen in the case that historical books edited by annals were combined with offical historical ones which were differently compiled and edited from the former. In the part of Chabu(자부), it broke out another confusion that Pubga(법가), Meongga(명가), Mukga(묵가), Chonghweongka's(종횡가) thoughts were classified in the Chapka(잡가). Scriptures of Taiosim and Buddhism were seperated from each other. There were some deleted books such as Mokrokryu(목록류), Paesaryu(패사류) in the part of history (Sabu 사부) and Chosaryu(초사류) in the part of Chipbu(집부). The some in the each orders had been renamed. Imitating compiling system of Songsayemunji(송사예문지), with reffering to its differ-ence, Myongsayemunji(명사예문지) wrote the review and the change of the books by author. The number of not-treated books didn't appear at the total. It also deleted the total following main subject.