• Journal of Fisheries and Marine Sciences Education
• /
• v.26 no.1
• /
• pp.10-21
• /
• 2014

The aquatic disease inspector is not classified as an occupation in the current Korean Standard Classification of Occupations(KSCO). Therefore, the roll of the aquatic disease inspector in the medical treatment and the prevention against the aquatic organism disease is underestimated. The aquatic disease inspector is in a more disadvantageous position than the pharmacist and the veterinarian. The purpose of this study is to approve the aquatic disease inspector as an occupation in KSCO. The important contents of this study are as follows. In the first place, this study looks around the general requirements of classifying the occupations in KSCO. The aquatic disease inspector satisfies the most general requirements. But, because of the similarities of job between the aquatic disease inspector and the veterinarian, the aquatic disease inspector do not satisfy the requirement for 'the principle of exclusiveness'. In the second place, this study looks around the classification system of KSCO. The classification system of KSCO is consists of multi steps. This study makes the plan for the appropriate occupation classification of the aquatic disease inspector. In the third place, this study looks for the legal methods to classify the aquatic disease inspector as an occupation in KSCO. In order to classify the aquatic disease inspector as an occupation in KSCO, many regulations of the laws about the aquatic disease inspector and the veterinarian are to be amended and the number of the aquatic disease inspectors is to be increased by the innovative measures.

• Journal of the Korea Convergence Society
• /
• v.12 no.4
• /
• pp.23-30
• /
• 2021

An Automated Industry and Occupation Coding System assigns statistical classification code to the enormous amount of natural language data collected from people who write about their industry and occupation. Unlike previous studies that applied information retrieval, we propose a system that does not need an index database and gives proper code regardless of the level of classification. Also, we show our model, which utilized KoBERT that achieves high performance in natural language downstream tasks with deep learning, outperforms baseline. Our method achieves 95.65%, 91.51%, and 97.66% in Occupation/Industry Code Classification of Population and Housing Census, and Industry Code Classification of Census on Basic Characteristics of Establishments. Moreover, we also demonstrate future improvements through error analysis in the respect of data and modeling.

• Journal of Fisheries and Marine Sciences Education
• /
• v.19 no.3
• /
• pp.329-345
• /
• 2007

The purpose of this study was to classify the standard classification of fishery occupations base on KECO(Korean Employment Classification of Occupation) in Korea. The result of this study was as follows. First ranks was fisheries duties, second ranks were classified into five categories. That were administration duties management duties financial affairs duties, social service duties marketing duties individual service duties, construction duties civil engineering duties, machinery duties manufacture duties repairing duties, production duties. Third ranks classify based on second ranks. Administration duties management duties financial affairs duties were classified fishery administration, fishery management, fishery financial affairs. Social service duties marketing duties individual service duties were classified fishery social service, fishery marketing, fishery individual service. Construction duties civil engineering duties were classified fishery construction, fishery civil engineering. Machinery duties manufacture duties repairing duties were classified fishery machinery duties, fishery manufacture, fishery repairing. Production duties were classified fishery processing, marine products, fishery environment. Fourth ranks was classified according to third ranks.

• Journal of Fisheries and Marine Sciences Education
• /
• v.18 no.3
• /
• pp.341-363
• /
• 2006

All industries must be cope with fast technological progress along with the economic changes experience. However, a fishery and ocean industry are something yet to study base data for HRD and classifying occupation. Therefore, this study points to major problems which related useful data of information on the fishery and ocean industry. The purpose of this study is to classify fishery and ocean occupations by KSCO. The study is carried out though review of the literature, field investigation, direct interview and an experts' meeting of 5 field majors. A proposed classification of fishery and ocean occupations is modified on several times by the meeting of experts' group. Finally, a systematic classification of fishery and ocean occupations is as follows. First of all, first rank change from fishing to fishery industry. And the second rank, fishery and ocean occupations were classified into four categories bases on the systematic and comprehensive, as it were production fisheries, fishery products and processing, fishery supplies and infrastructure, fishery services. Each rank of classifying occupation is from two to four steps based on the occupation cluster.

• Journal of Korean Library and Information Science Society
• /
• v.35 no.2
• /
• pp.95-114
• /
• 2004

This study investigates general characteristics and major changes in the Railway Bureau Library(RBL: Choldo Doseogwan) Classification, along with a comparative analysis with other related classifications used at that time. This study can make clear some differences and characteristics of the classification used during the Japanese occupation of Korea and its relation to the major classifications used after the independence of the Korea.

• The Journal of Korean Association of Computer Education
• /
• v.7 no.4
• /
• pp.51-60
• /
• 2004

This paper proposes an automated coding system of Korean standard industry/occupation for census which reduces a lot of cost and labor for manual coding. The proposed system converts natural language responses on survey questionnaires into corresponding numeric codes using information retrieval techniques and document classification algorithm. The system was experimented with 46,762 industry records and occupation 36,286 records using 10-fold cross -validation evaluation method. As experimental results, the system show 87.08% and 66.08% production rates when classifying industry records into level 2 and level 5 codes respectively. The system shows slightly lower performances on occupation code classification. We expect that the system is enough to be used as a semi-automate coding system which can minimize manual coding task or as a verification tool for manual coding results though it has much room to be improved as an automated coding system.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.14 no.12
• /
• pp.6495-6503
• /
• 2013

This paper presents a study on the development of a web-based system for the road occupation permit information management. For the development of this system, the survey of information system related to a road occupation permit, an analysis of road occupation business process, the definition of the road occupation permit data, the development of the system, and the application of the system to the work-related to road occupation permit were conducted consecutively. In an analysis of the road occupation business process, the statutes, such as the road act were investigated, work examples of the road management agent were reviewed, and a survey targeting staff and citizens was carried out. The information classification code to represent the attributes of the data was developed to manage the information in each road occupation permit process, and the metadata was defined considering the hierarchy relationship of the information. The road occupation and access system was developed based on the information classification code and metadata to reflect the user requirements. The System was applied to the Regional Construction and Management Administration and Branch Office belonging to the Ministry of Land, Infrastructure and Transport Affairs. By replacing the business process based on paper documents to the business process based on the information system, it is expected that the service of the civil petition be upgraded and the business process of the road occupation permit be reformed.

• Journal of Preventive Medicine and Public Health
• /
• v.55 no.4
• /
• pp.371-378
• /
• 2022

Objectives: No studies have examined the association between preterm birth rates and socioeconomic factors in Japan using nationwide statistical data. We analyzed the association between preterm birth rates and household occupation using Vital Statistics data. Methods: Aggregated Vital Statistics data from Japan from 2007 to 2019 were obtained from the Ministry of Health, Labour and Welfare. From the data, the number of births according to year, age group, gestational period, number of pregnancies, and household occupation were used in this study. Crude preterm birth rates and preterm birth rates adjusted by maternal age according to household occupation were calculated for each year. Poisson regression analysis was conducted to evaluate the association between household occupation and preterm births. Results: Unemployed households had the highest preterm birth rate, and households with an occupation classification of "full-time worker 2" (an employee at a large company, civil servant, or board member) had the lowest preterm birth rate throughout each period. Poisson regression analysis revealed that unemployed households were statistically significantly associated with a high preterm birth risk. In contrast, the preterm birth rate adjusted by maternal age remained stable throughout each period regardless of household occupation, and preterm birth rates were found not to have increased in recent years in Japan. Conclusions: Unemployed households had higher preterm birth rates than other household occupations. Further studies investigating the characteristics of unemployed households are needed to identify the reasons for this disparity.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.4
• /
• pp.21-29
• /
• 2023

In this paper, we propose an AI-based system for automatically classifying industry and occupation codes in the population census. The accurate classification of industry and occupation codes is crucial for informing policy decisions, allocating resources, and conducting research. However, this task has traditionally been performed by human coders, which is time-consuming, resource-intensive, and prone to errors. Our system represents a significant improvement over the existing rule-based system used by the statistics agency, which relies on user-entered data for code classification. In this paper, we trained and evaluated several models, and developed an ensemble model that achieved an 86.76% match accuracy in industry and 81.84% in occupation, outperforming the best individual model. Additionally, we propose process improvement work based on the classification probability results of the model. Our proposed method utilizes an ensemble model that combines transfer learning techniques with pre-trained models. In this paper, we demonstrate the potential for AI-based systems to improve the accuracy and efficiency of population census data classification. By automating this process with AI, we can achieve more accurate and consistent results while reducing the workload on agency staff.

• Journal of Digital Convergence
• /
• v.17 no.4
• /
• pp.203-210
• /
• 2019

This study analyzed the size and influence factors of annual average health expenditure according to job type. Using data from the Korea Health Panel (2012), the final analysis was conducted on adults aged 20 years or older, excluding the missing data. Data analysis was done by logistic regression analysis to analyze the factors affecting medical expenditure. As a result of the study, Model 1 showed higher expenditure on medical expenses by skilled workers in agriculture and forestry fishery than those in simple labor. Model 2 was analyzed as having a positive effect on the increase of medical expenditure by the simple worker in the sales of the occupation, statistically significant by sex, marriage, income level and chronic disease. Therefore, it would be necessary to establish social security and health care & welfare policies, in order to grasp the disease with a high frequency rate according to occupation status and activate the physical examination and preventive actions.