• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.123-139
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• 2019

The Korean NPL market was formed by the government and foreign capital shortly after the 1997 IMF crisis. However, this market is short-lived, as the bad debt has started to increase after the global financial crisis in 2009 due to the real economic recession. NPL has become a major investment in the market in recent years when the domestic capital market's investment capital began to enter the NPL market in earnest. Although the domestic NPL market has received considerable attention due to the overheating of the NPL market in recent years, research on the NPL market has been abrupt since the history of capital market investment in the domestic NPL market is short. In addition, decision-making through more scientific and systematic analysis is required due to the decline in profitability and the price fluctuation due to the fluctuation of the real estate business. In this study, we propose a prediction model that can determine the achievement of the benchmark yield by using the NPL market related data in accordance with the market demand. In order to build the model, we used Korean NPL data from December 2013 to December 2017 for about 4 years. The total number of things data was 2291. As independent variables, only the variables related to the dependent variable were selected for the 11 variables that indicate the characteristics of the real estate. In order to select the variables, one to one t-test and logistic regression stepwise and decision tree were performed. Seven independent variables (purchase year, SPC (Special Purpose Company), municipality, appraisal value, purchase cost, OPB (Outstanding Principle Balance), HP (Holding Period)). The dependent variable is a bivariate variable that indicates whether the benchmark rate is reached. This is because the accuracy of the model predicting the binomial variables is higher than the model predicting the continuous variables, and the accuracy of these models is directly related to the effectiveness of the model. In addition, in the case of a special purpose company, whether or not to purchase the property is the main concern. Therefore, whether or not to achieve a certain level of return is enough to make a decision. For the dependent variable, we constructed and compared the predictive model by calculating the dependent variable by adjusting the numerical value to ascertain whether 12%, which is the standard rate of return used in the industry, is a meaningful reference value. As a result, it was found that the hit ratio average of the predictive model constructed using the dependent variable calculated by the 12% standard rate of return was the best at 64.60%. In order to propose an optimal prediction model based on the determined dependent variables and 7 independent variables, we construct a prediction model by applying the five methodologies of discriminant analysis, logistic regression analysis, decision tree, artificial neural network, and genetic algorithm linear model we tried to compare them. To do this, 10 sets of training data and testing data were extracted using 10 fold validation method. After building the model using this data, the hit ratio of each set was averaged and the performance was compared. As a result, the hit ratio average of prediction models constructed by using discriminant analysis, logistic regression model, decision tree, artificial neural network, and genetic algorithm linear model were 64.40%, 65.12%, 63.54%, 67.40%, and 60.51%, respectively. It was confirmed that the model using the artificial neural network is the best. Through this study, it is proved that it is effective to utilize 7 independent variables and artificial neural network prediction model in the future NPL market. The proposed model predicts that the 12% return of new things will be achieved beforehand, which will help the special purpose companies make investment decisions. Furthermore, we anticipate that the NPL market will be liquidated as the transaction proceeds at an appropriate price.

• 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.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.

• Journal of Life Science
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• v.22 no.7
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• pp.871-879
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• 2012

Polyploids are a potentially important germplasm source in seedless citrus breeding program. Seedlessness is one of the most promising traits of commercial mandarin breeds that mandarin triploid hybrids possess permanently. The formation of new constant triploid hybrids can be recovered through diploid species hybridization from the fusion of divalent gametes at low frequencyor intra-and inter-ploidy crosses. However, extensive breeding work based on small $F_1$ hybrid seeds developed is impossible without a very effective aseptic methodology and ploidy event. In this study, in vitro embryo culture was employed to recover natural hybrids from monoembryonic diploid, open-pollinated mandarin. Flow cytometry was used to determine ploidy level. A total of 10,289 seeds were extracted from 792 fruits having approximately 13 seeds per fruit. Average frequency of small seeds developed was 7.1%, while the average frequency of small seeds per fruit were: 8.9% for 'Clementine' 10.2% for 'Harehime' 2.6% for 'Kamja' 3.1% for 'Pyunkyool' 2.8% for 'Sadookam' and 7.0% for 'Wilking' mandarin. Average size of a perfect seed was $49.52{\pm}0.07mm^2$ ('Clementine') while the small seed measured $7.95{\pm}0.04mm^2$ ('Clementine'), which was about 1/6 smaller than the perfect seed. In total, 731 small seeds were obtained and all of them contained only one embryo per seed. The efficiency of 'Clementine' was 14 times higher than 'Wilking' and more than 109 times higher than 'Pyunkyool'. The basic information on spontaneous polyploidy provides for the hybridization of constant triploids and increases the efficiency of conventional cross.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.65 no.3
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• pp.231-240
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• 2020

This research was conducted to evaluate the physicochemical properties, antioxidant components, and their activities for more taking advantage of small redbean cultivars. Seed size, 100 seeds weight, and hardness on the 8 cultivars were measured. The free sugar and crude protein contents were evaluated using HPLC and protein analyzer, respectively. Amylose content, antioxidant components, and activities were analyzed by spectrophotometer. The range of 100 seeds weight and hardness were 12.55-18.81 g and 9,527.38-14,341.25 gf, respectively. Total free sugar, amylose, and crude protein were showed 22.49-31.07 mg/g, 13.53-15.67%, and 21.27-23.30%, respectively. The cultivar 'Hongeon' was higher antioxidant component and activity more than others. In clustering the cultivars based on the results, the tree showed four major clades. The 'Huinnarae' group was high in total free sugar and amylose content. The 'Hongeon' group were high in 100 seeds weight, antioxidant component. and activity, while amylose content was lower than that in the other groups. The results of the cultivars can be utilized for research of functional materials. The findings of this study will provide valuable information for expansion of functional food industry related on small redbean.

• Journal of Food Hygiene and Safety
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• v.33 no.1
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• pp.1-11
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• 2018

It is ten years since the Good Agricultural Practices (GAP) certification system was implemented in Korea, and the government aims to acquire GAP certification up to 25% of the total agricultural areas by 2022. As of the end of 2017, 6.3% of the total cultivated area and 8.1% of the total farm households were certified, which is slower than expected. The purpose of this study was to investigate the causes of the GAP accreditation through the surveys and on site inspections of the GAP certified farmers and to propose the development plans according to the problems analysis of the current system in order to expand the GAP certification. Certified farmers recognized the need for agricultural safety and hygiene, but there were a lot of nonconformities regarding practical practices. This is due to the ambiguity of the certification standards and the wrong ways in the training method for the producers. GAP certification is slow to expand to farmers and low consumer awareness is considered a structural problem of GAP certification system, and improvement measures are needed accordingly. It is necessary to convert the state-led GAP certification system into a state-led private certification system. It is necessary for the government to focus on policy, research and follow-up management. In addition, it is necessary to establish a separate organization in the form of a contribution organization for the certification, education, and public relations. In addition, long-term plan must be established and systematically carried out. It is necessary to integrate too many certification agencies compared to the farming scale of Korea, and it is necessary to realize the application fee for realizing the financial independence of the certification body and correct certification work. In addition, inspector qualification standards should be strengthened and training system should be improved to nurture high quality inspectors. Simplified certification standards based on statutes need to be subdivided into practical action plans. In order to improve the GAP certification system, it is necessary to have a discussion through a committee composed of specialists from industry and academia, and it will be possible to contribute to the safety of the food of the people through the production of safe by drawing concrete development plans.

• Science of Emotion and Sensibility
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• v.9 no.1
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• pp.49-61
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• 2006

The present mobile phone industry has significant effect on the domestic economy and has taken root as the core item that has the responsibility to lead the Korean economy for a considerable period of time. As the mobile phone market becomes gigantic, the mobile phone is being used by people in broader age bracket, and functions or designs preferred by people of various age are getting more diverse. Like that, as the mobile phone has greater effect on and meaning in our daily lives, consumers of mobile phone have growing expectation of the mobile phone Now, the core function of voice communication via the mobile phone is not a great concern to consumers. But the function, such as more convenient and friendly information input and output, processing and storage, and the design, which is more sophisticated and optimized for the user environment, are being demanded, not just the simple voice communication. And as the modern design is getting more similar to the objects of traditional high art consumed by consumers every day, the aesthetic aspect of design can play an important role, as the factor that differentiates the product, in creating new value which forms the spiritual and emotional value of human beings to improve the quality of living, and in addition, the willingness of consumers to buy is determined by the design that they prefer the most. Like that, a new design of mobile phone based on a new dimension and preferred by the consumers the most is urgently required to be developed by shedding light on the factors related to the preference of consumers on the basis of the analysis on the aesthetic aspect, which can be said to be the most critical factor in the design process. Therefore, this study aims to identity the common preference and different factors of aesthetic aspects through the analysis on the aesthetic aspects of the mobile phone preferred by users among countries, and figure out the formative artistic factors of aesthetic aspects that are considered to be important, in order to propose the guideline on the aesthetic aspect of mobile phone that can be applied to the design of mobile phone practically.

• Journal of Technology Innovation
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• v.24 no.1
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• pp.143-167
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• 2016

The purpose of this study is to analyze changes of innovation activities and their performance in pre-IPO and post-IPO of KOSDAQ IPO listed companies in medical and pharmaceutical fields, which require high R&D investment, from 2000 to 2005 in Korea. The innovation efficiencies of the IPO companies were measured before and after three years based on the DEA model. The financial data and patent information of the listed company during total 6 years, which were 3 years before IPO and 3 years after IPO, were collected. The main results of this research are as follows. First, it took an average 12.86 years until IPO in the start-up of the IPO companies in the pharmaceutical sector, and innovation was on average more active than the IPO before. R&D investment was higher than the IPO before, and the number of the applied patent during 3 years after IPO was 16.67 which was increased from 8.43 during 3 years before IPO. In addition, the average scope of technology of the IPO companies was expanded from 11 to 22 technology fields during previous 3 year and after 3 year each, and financial growth after IPO was lower than the previous IPO. Second, the financial performance of R&D investment and the performance of patent activity were weakened in the efficiency after the IPO, and the integrated performance from the patenting activities and the R&D investment was decreased after the IPO. Finally, the efficiency of the financial performance of the patenting activity was lower than the efficiency of the financial performance of the patent and R&D investment and patent activities under the R&D investment. In particular, the inefficiency of the firms' patenting activities performance after the IPO was caused by the decreasing return to scale, according to the results of this study. This results implicate that the expansion of R&D investments through the IPO had not lead to the financial performance of the market, and that the overall inefficiency since the IPO is due to the inefficiencies at the stage for the outcome of innovation activity rather than the output obtained through the R&D investments that appear to lead the performance of the market.

• Korean Journal of Environment and Ecology
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• v.22 no.3
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• pp.207-220
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• 2008

Tourism in the natural environment grows significantly and in many tropical countries it becomesthe important earning of the nations. Nevertheless, tourism impact to environment and cultural values has become the threats to the sustainability and competitiveness of such industry. Therefore, the appropriate planning and management of tourism destination sites where environmentally and culturally fragile are needed in order to increase economic benefits, sustain local culture and conserve environment in balance. The aims of the paper are to examine tourism practices, to determine socio-cultural and natural resources, and to assess local people perception to cultural landscape and its future tourism development in order to formulate the appropriate strategies to achieve sustainable tourism. A case study was carried out at Tengger highland, Bromo Tengger Semeru National Park(BTSNP) East Java. Official documents were gathered and interviews with several key persons had conducted to determine recent status of tourism, resources capital and the existence of local people. Semi-structured interviews and questionnaires were carried out at Tenggerese villages to explore local people perspectives to tourism development, culture preservation, and cultural landscape conservation issues. It is followed by descriptive analysis of vegetation to assess the recent status of environments based on vegetation information. Our findings reveals that tourism grows significantly at BTSNP, and Tengger Caldera as spiritual and cultural sites for local people become the centre for tourism activities. The abundance cultural and natural resources are the significant capital for sustainable tourism. Tenggerese argues that tourism should be planned to provide benefits to local people, preserve tradition and able to conserve nature in order to ensure the living sustainability of Tenggerese. The overall result of the study provide general feature of recent status of the cultural and natural resources as well as positive society perception in order to establish a strategy for sustainable tourism in cultural landscape.

• Journal of Environmental Health Sciences
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• v.40 no.6
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• pp.454-468
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• 2014

Objectives: This study was conducted to investigate the actual condition of the farm work environment and personal protective equipment as part of the effort to improve livestock work for the safety and health of poultry farmers and provide basic data for establishing plans to improve and develop personal protective equipment. Methods: For this purpose, a questionnaire survey on general information about stables, the poultry work environment, accidents, the wearing of work clothes and personal protective equipment, and the level of awareness related to personal protective equipment was conducted among 148 poultry farmers. Results: As a result, it was found that poultry workplace environment was exposed to such risks as fine dusts; organic dusts; poisonous gases; odorous substances; chicken excrement; contact with chickens, bacteria or viruses; and accidents related to machine operation. Thirteen percent of respondents suffered severe respiratory diseases, and the most frequently injured sites due to accidents were the hands (25.7%), knees (23.8%), arms (17.3%), and head (10.9%). The most frequent type of accident was collisions between the body and obstacles or machinery during movement (36.4%), followed by erroneous machine operation such as feeders and electric shocks (8.5%). Regarding the wearing of work clothes and personal protective equipment, 51.7% of the respondents wore worn-out clothing or everyday clothes, whereas only 32.0% wore work clothes. The percentage of farmers who wore proper protective equipment for the work environment during poultry work was 48.4%. The most frequently used type of protective equipment was boots (38.9%), followed by mask (36.7%), gloves (36.3%), appropriate work clothes (22.6%), quarantine clothes (17.6%), helmets (13.4%), and goggles (12.6%). The rate of wearing goggles was low because they were considered inconvenient and lowered work efficiency. Furthermore, they purchased everyday products available on the market for their personal protective equipment which were not appropriate for maintaining safety in an actual harmful environment and its consequent risks. As a result of the survey of the awareness level related to personal protective equipment, their levels of awareness of accidents and attitude proved to be average or higher, but the practice of wearing protective equipment and the level of knowledge and management of personal protective equipment were lower. Conclusion: This survey found that the wearing status of personal protective equipment among poultry farmers was insufficient even though they were exposed to risks. Most respondents were aware of the necessity of wearing personal protective equipment and of the potential for accidents, but they did not wear proper protective equipment. Their wearing rate was low due to a lack of knowledge about protective equipment, as well as the inconvenience of wearing it. Therefore there is a need to improve and develop specialized personal protective equipment for respiration, hands, and eyes, as well as work clothes that can protect farmers from major harmful matter that is generated in the poultry workplace. Based on the results of this investigation, we will conduct further studies on the required performance and design directions of personal protective equipment while collecting more objective data through field-oriented assessments.