• Title/Summary/Keyword: large-scale development project

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Optimization of 3D ResNet Depth for Domain Adaptation in Excavator Activity Recognition

  • Seungwon SEO;Choongwan KOO
    • International conference on construction engineering and project management
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    • 2024.07a
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    • pp.1307-1307
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    • 2024
  • Recent research on heavy equipment has been conducted for the purposes of enhanced safety, productivity improvement, and carbon neutrality at construction sites. A sensor-based approach is being explored to monitor the location and movements of heavy equipment in real time. However, it poses significant challenges in terms of time and cost as multiple sensors should be installed on numerous heavy equipment at construction sites. In addition, there is a limitation in identifying the collaboration or interference between two or more heavy equipment. In light of this, a vision-based deep learning approach is being actively conducted to effectively respond to various working conditions and dynamic environments. To enhance the performance of a vision-based activity recognition model, it is essential to secure a sufficient amount of training datasets (i.e., video datasets collected from actual construction sites). However, due to safety and security issues at construction sites, there are limitations in adequately collecting training dataset under various situations and environmental conditions. In addition, the videos feature a sequence of multiple activities of heavy equipment, making it challenging to clearly distinguish the boundaries between preceding and subsequent activities. To address these challenges, this study proposed a domain adaptation in vision-based transfer learning for automated excavator activity recognition utilizing 3D ResNet (residual deep neural network). Particularly, this study aimed to identify the optimal depth of 3D ResNet (i.e., the number of layers of the feature extractor) suitable for domain adaptation via fine-tuning process. To achieve this, this study sought to evaluate the activity recognition performance of five 3D ResNet models with 18, 34, 50, 101, and 152 layers, which used two consecutive videos with multiple activities (5 mins, 33 secs and 10 mins, 6 secs) collected from actual construction sites. First, pretrained weights from large-scale datasets (i.e., Kinetic-700 and Moment in Time (MiT)) in other domains (e.g., humans, animals, natural phenomena) were utilized. Second, five 3D ResNet models were fine-tuned using a customized dataset (14,185 clips, 60,606 secs). As an evaluation index for activity recognition model, the F1 score showed 0.881, 0.689, 0.74, 0.684, and 0.569 for the five 3D ResNet models, with the 18-layer model performing the best. This result indicated that the activity recognition models with fewer layers could be advantageous in deriving the optimal weights for the target domain (i.e., excavator activities) when fine-tuning with a limited dataset. Consequently, this study identified the optimal depth of 3D ResNet that can maintain a reliable performance in dynamic and complex construction sites, even with a limited dataset. The proposed approach is expected to contribute to the development of decision-support systems capable of systematically managing enhanced safety, productivity improvement, and carbon neutrality in the construction industry.

Exploratory Correlation Analysis among Age Identity, Proximity of Clothing to Self, and Self-Actualization for Older Persons in the United States (미국 노년층의 의복의 자아 근접성, 나이 정체성, 자아실현 사이의 상호연관성 분석)

  • Lee, Young-A
    • Journal of the Korean Society of Clothing and Textiles
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    • v.33 no.12
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    • pp.1897-1909
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    • 2009
  • This large-scale research project contributes to the theory development in the importance of clothing to the self and in the way that older persons might age successfully by fulfilling the need for self-actualization by incorporating a primary resource environment, such as clothing into their self-system. This paper presents one research objective from a lager project that explores the correlations among the Proximity of Clothing to Self (PCS), age identity (subjective or perceived age), and self-actualization (the highest level of human needs). A mail survey design was applied to this study. In November 2004, two questionnaires, Clothing: A Resource for Successful Aging? (to measure PCS, age identity, and demographic variables) and Personal Orientation Inventory (to measure self-actualization), were sent to 1,700 older persons in the U.S. and 195 completed usable questionnaires were returned (12% response rate). This research discovered that the age identity of older persons did not relate with PCS except for those 85 years and over. There were negative correlations among subscales of PCS and self-actualization. This result can be interpreted as that an older person who has not met the highest level of needs yet, can use clothing as a facilitator or need satisfier to meet a higher level of Self-Actualization (SA). Correlation analyses also revealed that older persons in the age category of 75 to 84 years were different from those in the category of 65 to 74 years and 85 years and over. This result implies that older persons in this age category are undergoing more psychological transitions than those in other categories. Further research is necessary to explore the relationship of several SA subscales with various clothing variables such as clothing interest, clothing involvement, or clothing satisfaction.

Classification of Landscape Type on Land and Evaluation of Site-suitability Based on It (토지의 경관유형분류와 이에 기초한 입지타당성 평가)

  • Ra, Jung-Hwa;Ku, Ji-Na;Lee, Hyun-Taek;Cho, Hyun-Ju
    • Journal of the Korean Institute of Landscape Architecture
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    • v.39 no.5
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    • pp.57-75
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    • 2011
  • The purpose of this study is to find ways of evaluating the suitability of sites being considered for development of different types of parks in the vicinity of yangmock-myun kyoung buk, where a large project(as large as about14.0$km^2$) has been planned. The results are as follows. Three surveys for selecting the assessment indicators were performed. ${\cdot}$ The first survey analyzed the importance of 23 selected assessment indicators based on a review of existing literature review and an on-the-spot research. ${\cdot}$ The second survey selected assessment indicators for each park type. ${\cdot}$ The third survey computed additive values of selected assessment indicators by the park types. It used a method of standardizing the average importance of indicators by making their sum equal to 10. These additive values were then multiplied by each grade of indicators to make a final evaluation. An evaluation of the site-suitability of park types was performed twice. The purpose of the first evaluation was to figure out how much each type met the minimum requirements targeted for all landscape types. The minimum requirements were derived by using a relative comparison between the standard of value rating of the assessment indicators, which was over the medium magnitude on the importance analysis, and the result of field research. A second evaluation estimated the targeted sites that met the minimum requirements. Value ratings of second assessment indicators were quantitatively divided as 1 to 3 grade and the evaluation scores were added, giving an additive value for each assessment indicator. The evaluation score on each park type was rated on a scale of 1 to 3 according to their averages, (from lowest to highest). Since this evaluation model of the site suitability on park types only focused on the 'face' of space in this study, additional analysis is necessary for setting the evaluation model and incorporating the overall impact of space, network connection and other factors, considering 'spot', 'line' and 'face' aspects of space.

Bankruptcy Forecasting Model using AdaBoost: A Focus on Construction Companies (적응형 부스팅을 이용한 파산 예측 모형: 건설업을 중심으로)

  • Heo, Junyoung;Yang, Jin Yong
    • Journal of Intelligence and Information Systems
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    • v.20 no.1
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    • pp.35-48
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    • 2014
  • According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

DEVELOPMENT OF STATEWIDE TRUCK TRAFFIC FORECASTING METHOD BY USING LIMITED O-D SURVEY DATA (한정된 O-D조사자료를 이용한 주 전체의 트럭교통예측방법 개발)

  • 박만배
    • Proceedings of the KOR-KST Conference
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    • 1995.02a
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    • pp.101-113
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    • 1995
  • 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.

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Limitations of National Responsibility and its Application on Marine Environmental Pollution beyond Borders -Focused on the Effects of China's Three Gorges Dam on the Marine Environment in the East China Sea- (국경을 넘는 해양환경오염에 대한 국가책임과 적용의 한계 -중국의 산샤댐 건설로 인한 동중국해 해양환경 영향을 중심으로-)

  • Yang, Hee Cheol
    • Ocean and Polar Research
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    • v.37 no.4
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    • pp.341-356
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    • 2015
  • A nation has a sovereign right to develop and use its natural resources according to its policies with regard to development and the relevant environment. A nation also has an obligation not to harm other countries or damage environments of neighboring countries as consequences of such actions of developments or use of natural resources. However, international precedents induce a nation to take additional actions not to cause more damages from the specific acts causing environmental damages beyond national borders, when such acts have economic and social importance. That is to say that there is a tendency to resolve such issues in a way to promote the balance between the mutual interests by allowing such actions to continue. A solution to China's Three Gorges Dam dilemma based on a soft law approach is more credible than relying on a good faith approach of national responsibilities and international legal proceedings since the construction and operation of the dam falls within the category of exercising national sovereign rights. If a large scale construction project such as the Three Gorges Dam or operation of a nuclear power plant causes or may cause environmental damage beyond the border of a nation engaged in such an undertaking, countries affected by this undertaking should jointly monitor the environmental effects in a spirit of cooperation rather than trying to stop the construction and should seek cooperative solutions of mutual understanding to establish measures to prevent further damages. If China's Three Gorges Dam construction and operation cause or contain the possibility of causing serious damages to marine environment, China cannot set aside its national responsibility to meet international obligations if China is aware of or knows about the damage that has occurred or may occur but fail to prevent, minimize, reverse or eliminate additional chances of such damages, or fails to put in place measures in order to prevent the recurrence of such damages. However, Korea must be able to prove a causal relationship between the relevant actions and resulting damages if it is to raise objections to the construction or request certain damage-prevention actions against crucial adverse effects on the marine environment out of respect for China's right to develop resources and acts of use thereof. Therefore, it is essential to cumulate continuous monitoring and evaluations information pertaining to marine environmental changes and impacts or responses of affected waters as well as acquisition of scientific baseline data with observed changes in such baseline. As China has adopted a somewhat nonchalant attitude toward taking adequate actions to protect against marine pollution risks or adverse effects caused by the construction and operation of China's Three Gorges Dam, there is a need to persuade China to adopt a more active stance and become involved in the monitoring and co-investigation of the Yellow Sea in order to protect the marine environment. Moreover, there is a need to build a regular environmental monitoring system that includes the evaluation of environmental effects beyond borders. The Espoo Convention can serve as a mechanism to ease potential conflicts of national interest in the Northeast Asian waters where political and historical sensitivities are acute. Especially, the recent diplomatic policy advanced by Korea and China can be implemented as an important example of gentle cooperation as the policy tool of choice is based on regional cooperation or cooperation between different regions.

A Study on Comparative Analysis of Socio-economic Impact Assessment Methods on Climate Change and Necessity of Application for Water Management (기후변화 대응을 위한 발전소 온배수 활용 양식업 경제성 분석)

  • Lee, Sangsin;Kim, Shang Moon;Um, Gi Jeung
    • Journal of Korean Society of societal Security
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    • v.4 no.2
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    • pp.73-78
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    • 2011
  • In order to resolve the problem of change in global climate which is worsening as days go by and to preemptively cope with strengthened restriction on carbon emission, the government enacted 'Framework Act on Low Carbon Green Growth' in 2010 and selected green technology and green industry as new national growth engines. For this reason, the necessity to use the un-utilized waste heat across the whole industrial system has become an issue, and studies on and applications of recycling in the agricultural and fishery fields such as cultivation of tropical crops and flatfishes by utilizing the waste heat and thermal effluent generated by large industrial complexes including power plants are being actively carried out. In this study, we looked into the domestic and overseas examples of having utilized waste heat abandoned in the form of power plant thermal effluent, and carried out economic efficiency evaluation of sturgeon aquaculture utilizing thermal effluent of Yeongwol LNG Combined Cycle Power Plant in Gangwon-do. In this analysis, we analyzed the economic efficiency of a model business plan divided into three steps, starting from a small scale in order to minimize the investment risk and financial burden, which is then gradually expanded. The business operation period was assumed to be 10 years (2012~2021), and the NVP (Net Present Value) and economic efficiency (B/C) for the operation period (10 years) were estimated for different loan size by dividing the size of external loan by stage into 80% and 40% based on the basic statistics secured through a site survey. Through the result of analysis, we can see that reducing the size of the external loan is an important factor in securing greater economic efficiency as, while the B/C is 1.79 in the case the external loan is 80% of the total investment, it is presumed to be improved to 1.81 when the loan is 40%. As the findings of this study showed that the economic efficiency of sturgeon aquaculture utilizing thermal effluent of power plant can be secured, it is presumed that regional development project items with high added value can be derived though this, and, in addition, this study will greatly contribute to reinforcement of the capability of local governments to cope with climate change.

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Ginseng Research in Natural Products Research Institute (NPRI) and the Pharmaceutical Industry Complex in Gaesong (생약연구소의 인삼연구와 약도개성)

  • Park, Ju-young
    • Journal of Ginseng Culture
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    • v.3
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    • pp.54-73
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    • 2021
  • The Natural Products Research Institute (NPRI, 生藥硏究所), an institution affiliated with Keijo Imperial University (京城帝國大學), was the predecessor of the NPRI at Seoul National University and a comprehensive research institute that focused on ginseng research during the Japanese colonial era. It was established under the leadership of Noriyuki Sugihara (杉原德行), a professor of the second lecture in pharmacology at the College of Medicine in Keijo Imperial University. Prof. Sugihara concentrated on studying Korean ginseng and herbal medicine beginning in 1926 when the second lecture of pharmacology was established. In addition to Prof. Sugihara, who majored in medicine and pharmacology, Kaku Tenmin (加來天民), an assistant professor who majored in pharmacy; Tsutomu Ishidoya (石戶谷勉), a lecturer who majored in agriculture and forestry; and about 36 researchers actively worked in the laboratory before the establishment of the NPRI in 1939. Among these personnel, approximately 14 Korean researchers had basic medical knowledge, derived mostly from specialized schools, such as medical, dental, and pharmaceutical institutions. As part of the initiative to explore the medicinal herbs of Joseon, the number of Korean researchers increased beginning in 1930. This increase started with Min Byung-Ki (閔丙祺) and Kim Ha-sik (金夏植). The second lecture of pharmacology presented various research results in areas covering medicinal plants in Joseon as well as pharmacological actions and component analyses of herbal medicines. It also conducted joint research with variousinstitutions. Meanwhile, in Gaesong (開城), the largest ginseng-producing area in Korea, the plan for the Pharmaceutical Industry Complex was established in 1935. This was a large-scale project aimed at generating profits through research on and the mass production of drugs and the reformation of the ginseng industry under collaboration among the Gaesong Ministry, Kwandong (關東) military forces, Keijo Imperial University, and private organizations. In 1936 and 1938, the Gyeonggi Provincial Medicinal Plant Research Institute (京畿道立 藥用植物硏究所) and the Herb Garden of Keijo Imperial University (京城帝國大學 藥草園) and Pharmaceutical Factory were established, respectively. These institutions merged to become Keijo Imperial University's NPRI, which wasthen overseen by Prof. Sugihara as director. Aside from conducting pharmacological research on ginseng, the NPRI devoted efforts to the development and sale of ginseng-based drugs, such as Sunryosam (鮮麗蔘), and the cultivation of ginseng. In 1941, the Jeju Urban Test Center (濟州島試驗場) was established, and an insecticide called Pancy (パンシ) was produced using Jeju-do medicinal herbs. However, even before research results were published in earnest, Japanese researchers, including Prof. Sugihara, hurriedly returned to Japan in 1945 because of the surrender of Japanese forces and the liberation of Korea. The NPRI was handed over to Seoul National University and led by Prof. Oh Jin-Sup (吳鎭燮), a former medical student at Keijo Imperial University. Scholars such as Woo Lin-Keun (禹麟根) and Seok Joo-Myung (石宙明) worked diligently to deal with the Korean pharmaceutical industry.

A Study on Medium-Sized Enterprises of Japan (일본의 중견기업에 관한 연구 : 현황과 특징, 정책을 중심으로)

  • Kang, Cheol Gu;Kim, Hyun Sung;Kim, Hyun Chul
    • Korean small business review
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    • v.32 no.2
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    • pp.209-223
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    • 2010
  • Korea's business is composed of a few large-sized enterprises (which can be abbreviated as LSE) and a majority of small-sized enterprises (SSE). Although there has been a growing recognition of the need for the development of medium-sized enterprises (MSE) which can serve as a link between SSE and LSE, as yet there has not yet been a consensus on the definition, characteristics and the function of the MSE in Korea. Nowadays, the world is being globalized, and Japan and China are in competition to ne a great economic power. While East Asia is experiencing rapid changes, promoting MSE which can secure flexibility and efficiency through covering up the limitation of LSE and SSE is needed in order to respond the global market which is being specialized. The features of MSE in Japan can be listed as follows. First, the MSE in Japan is developing the company through getting into niche markets which are hard for major companies to enter rather than developing markets in order to compete against major companies directly. While MSEs are endeavoring to build the business firmly in the domestic market, they can possess special and competitive technical skills through trials and errors; so that they can get a chance develop their business through independent business system rather than putting their effort to compete against major companies. Second, from the MSEs with competitive edge in the market, there are many contributions to the national exportation. Those MSEs produce in domestic and maintain the quality of high price products which need cutting-edge technology, while they relocate the low and middle priced goods to the country where manufacturing costs are low, so that they can maintain the price competitiveness. Third, the industrial structure in Japan is formed from dual structure between major companies and small sized companies. In other words, in Japan's industrial structure which are composed of subcontract structure, this dual structure has taken a major role of small sized companies' growth and manufacturing businesses' international competitive power. Forth, MSE in Japan adopt a strategy of putting their value on qualitative scale growth rather than quantitative scale growth. In this paper, the case of Japanese MSE is analyzed. Along with its long history of Industrialization, Japan has a corporate environment where the SSEs can develop as a MSE and later a LSE through a full-support system. Among its SSEs, there are a number of world class corporations equipped with a large domestic market, win-win cooperation with the LSEs and an independent technology development. It can also be observed that these SSEs develop into MSEs with sustainable growth potentials. This study will focus on the condition under which the MSEs of Japan have been developed, and how they have survived the competition between SSEs and LSEs. Through this study, this paper attempts to offer solutions to Korea's polarization between the SSE and LSE, while providing the basis for SSEs revitalization. In general, if both extremities phenomenon deepen between LSE and SSE, there are possible fears of occurring disutility in national economy by the monopolization of LSE. For that reason, enterprise group, which can make SSE or MSE compete LSE in some area and ease the monopoly and oligopoly problem, is needed. This awareness has been shared for ages long. Nevertheless, there is no legal definition for MSE in Japan, and there is no definition about the enterprise size or unified view of MSE between scholars, but it is defined differently by each of academical person or research institution and study meeting. For that reason, this paper will organize the definition of MSE in Japan, and then will propose the characteristics of the background which has made MSE secure competitiveness and sustainable growth in global market. This study focus on that because through this process, the positive change to the awareness of MSE can be proposed in Korea and to seek the policy direction for building institutional framework which can make SSE become MES. Through this way, the fundamentals for SSE to become MSE can be managed and some appropriate suggestions which will be able to make MSE enter the global market in the future can also be proposed. Due to these facts, this study is very important and well timed task. In a sense of this way, this study will examine the definition and role of MSE in Japan. after this examination, this study will deal with the status, special feature, and promotion policy for MSE. Through this analysis of MSE in Japan, the foundation which be able to set the desirable role model for MSE in Korea can be proposed. Also, the political implication which is needed to push ahead to contribute to creating employment and economic growth through sustainable growth of MSEs in economic system of Korea can be offered through this study. It has been found that Japan's MSE functions as an indispensable link among various industrial structures by holding a significant position in employment rate, production and value added. Although the MSEs took up less than 1% of the entire number of businesses with 2700 manufacturing firms and 7000 non-manufacturing firms, its employment ratios are about 15%, while taking about 25% of the manufacturing industry's exports. In industries such as machinery and electronics which is considered Japan's major industry, the MSEs showed a higher than average ratio of manufacturing exports and employment rate. It can be analyzed that behind Japan's advantageous industries, close and deeply knit MSEs exist. Although there are no clearly stated policies geared towards the MSEs by the Japanese government, various political measures exist such as the R&D Project and the inducement of cooperation between enterprises which gives room for MSEs to participate in the SSE policies. In relation to these findings, the following practical measures can be considered in order to revitalize Korea's MSEs: First, there is a need for a legal definition of MSE and the incentives to provide legal support for its growth. Second, if a law to support the MSEs is established, it could provide a powerful inducement for the SSE to grow as a MSE, rather than stay as a SSE. Third, there is a need for a strategy of MSEs to establish a stable base in the domestic market and then advance to the global market with the accumulated trial and error and competitiveness. Fourth, the SSE themselves need the spirit of entrepreneurship in order to make the leap to a MSE. Because if nothing is to be changed about the system on the firms that grew, and the parts of the past custom was left to be managed alone, confusion and absence of management can take place. No matter how much tax favors the government will give and no matter how much incentive there could be through the policies, there are limits for industries to higher the ability to propagate. And because of that it is a period where industries need their own innovative skills to reform their firms.