• Journal of Preventive Medicine and Public Health
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• v.10 no.1
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• pp.166-175
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• 1977

The author have performed an epidemiological study on the accidental deaths at industry from 1970 to 1975, in order to seek for the preventive measures of industrial accident with the under-standing of its cause and characteristics of the accidental deaths. The obtained results were as follows; 1. Total number of deaths for 6 years were 361 (350 males, 11 females). and the mean death rate was 33.8 per 100,000 industrial workers during 6 years. By the highest as 52.9 was in 1974 and the lowest as 13.7 in 1970. By the industry group, the death rate of Electricity, Gas and Water was 149.3, Construction 83.9 and the lowest was Manufacturing as 18.3. 2. Standardized mortality rate of the cases by the age group showed that 20-29 years old group was 43.0, 40-49 years old group 38.1, 30-39 years old group 32.0, and the lowest as 17.9 was under 19 years old group. 3. The cumulative percentage of the cases by years of service showed that under 6 months was 60.4%, under 1 year 72.9%, under 2 years 83.1%. 4. By the month of occurrence, the highest was 15.8% which occurred in August and the lowest was 5.8% in February. The highest as 19.1% was on Friday and the lowest as 11.9% on Monday by the day of a week. 5. By the causes of accident, car accidents was 28.3%, fall accidents 19.1%, accidents by a crash 9.1% in that order. By the location of injury, head was 44.6%, multiple injuries 33.0%, chest 10.5%, and back was the lowest as 1.9%. The distribution of the cases by nature of injury shelved that cerebral contusion and hemorrhage was 39.4%, fracture and dislocation 33.2%, asphyxia 8.0% in that order. 6. The cumulative percentage of the cases by the duration from injury to death showed that the injuried day was 74.2%, within 3 days after injury 88.5%, within 7 days 96.1%. Therefore most of the cases were occurred within 7 days after injury. 7. Byythe daily mean wages, most of the cases as 91.7% were under 2,000 won, and more 4,000 won was 1.6% merely.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.1-7
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• 2022

The purpose of this study is to discuss the impact of unmanned aerial vehicle service and how to activate it. The discussion on the impact of the introduction of the unmanned aerial vehicle service was examined in terms of economic, environmental, and social acceptance, and a plan to revitalize the industry was presented. In terms of economic impact, if transportation services are increased using unmanned aerial vehicles in the future, road-based transportation cargo may decrease and road movement speed may increase due to reduced road congestion. This can have a positive effect on the increase in the value of land or real estate assets, and it also provides an impact on smart city design. In terms of environmental impact, unmanned aerial vehicles (UAVs) generally move through electricity, so they emit less exhaust gas compared to other existing devices, such as vehicles and railroads, and thus have less environmental impact. However, noise can have a negative impact on the habitat in the presence of wild animals along their migration routes. In terms of social acceptability of unmanned aerial vehicles (UAV) technology, areas that are declining due to the emergence of new services may appear, and at the same time, organizations that create profits may appear, causing conflicts between industries. Therefore, it is essential to form a social consensus on the acceptance of emerging industries. The government should come up with various countermeasures to minimize the negative impact that reflects the characteristics of the unmanned aerial vehicle use service. Just as various systems such as road signs were introduced so that vehicles can be operated on the ground to secure air routes in the mid- to long-term for revitalization of unmanned-based industries, development and establishment of services that should be introduced and applied prior to constructing air routes I need this. In addition, the design and implementation of information collection and operation plans for unmanned air traffic management in Korea and a plan to secure a control system for each region should also be made. This study can contribute to providing ideas for mid- to long-term research on new areas with the development of the unmanned aerial vehicle industry.

• Korean Journal of Weed Science
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• v.30 no.4
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• pp.340-360
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• 2010

The depletion of fossil fuels, ecological problems associated with $CO_2$ emissions climate change, growing world population, and future energy supplies are forcing the development of alternative resources for energy (heat and electricity), transport fuels and chemicals: the replacement of fossil resources with $CO_2$ neutral biomass. Several options exist to cover energy supplies of the future, including solar, wind, and water power; however, chemical carbon source can get from biomass only. When used in combination with environmental friend production and processing technology, the use of biomass can be seen as a sustainable alternative to conventional chemical feedstocks. The biorefinery concept is analogous to today's petroleum refinery, which produce multiple fuels and chemical products from petroleum. A biorefinery is a facility that integrates biomass conversion processes and equipment to produce fuels, power, and value-added chemicals from biomass. Biorefinery is the co-production of a spectrum of bio-based products (food, feed, materials, and chemicals) and energy (fuels, power, and heat) from biomass [definition IEA Bioenergy Task 42]. By producing multiple products, a biorefinery takes advantage of the various components in biomass and their intermediates therefore maximizing the value derived from the biomass feedstocks. A biorefinery could, for example, produce one or several low-volume, but high-value, chemical or nutraceutical products and a low-value, but high-volume liquid transportation fuel such as biodiesel or bioethanol. Future biorefinery may play a major role in producing chemicals and materials as a bridge between agriculture and chemistry that are traditionally produced from petroleum. Industrial biotechnology is expected to significantly complement or replace the current petroleum-based industry and to play an important role.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.6
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• pp.85-96
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• 2018

Developed nations have implemented various policies to reduce greenhouse gases since the 1997 Kyoto Protocol in order to minimize the effects of global warming. Korea should also reduce energy consumption in the industrial sector, and the transportation and building sectors in order to achieve its greenhouse gas reduction target of 37 percent compared to the Business As Usual levels. The government implements various laws and regulations for reducing energy consumption. To reduce energy consumption in the building sector, in particular, the Energy Conservation Design Standards are enforced according to the 'Enforcement Support for Green Building Construction'. The amount of electricity used to maintain room temperature at $28^{\circ}C$ in these buildings have a 30% reduction (measured on the walls and rooftop) in power usage compared to buildings not required to meet these standards. Although the effect of these energy savings on landscaping is proven, this demonstration is not effective for energy saving since it is not a suitable method for the 'Energy Saving Design Standards of Buildings'. For landscaping to be effective as far as a component of energy reduction, the perfusion rate of the building should be calculated based on the thermal conductivity of the component materials for the energy saving designs with respect to the basis of Article 14 of the Green Building Act. Therefore, the purpose of this study is to ensure that the planting-based mats currently being widely used in the landscape industry can have insulating performance suitable for the 'Energy Saving Design Standards' of Buildings according to the 'Enable Green Building Construction Methods'.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.77-97
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• 2010

Market timing is an investment strategy which is used for obtaining excessive return from financial market. In general, detection of market timing means determining when to buy and sell to get excess return from trading. In many market timing systems, trading rules have been used as an engine to generate signals for trade. On the other hand, some researchers proposed the rough set analysis as a proper tool for market timing because it does not generate a signal for trade when the pattern of the market is uncertain by using the control function. The data for the rough set analysis should be discretized of numeric value because the rough set only accepts categorical data for analysis. Discretization searches for proper "cuts" for numeric data that determine intervals. All values that lie within each interval are transformed into same value. In general, there are four methods for data discretization in rough set analysis including equal frequency scaling, expert's knowledge-based discretization, minimum entropy scaling, and na$\ddot{i}$ve and Boolean reasoning-based discretization. Equal frequency scaling fixes a number of intervals and examines the histogram of each variable, then determines cuts so that approximately the same number of samples fall into each of the intervals. Expert's knowledge-based discretization determines cuts according to knowledge of domain experts through literature review or interview with experts. Minimum entropy scaling implements the algorithm based on recursively partitioning the value set of each variable so that a local measure of entropy is optimized. Na$\ddot{i}$ve and Booleanreasoning-based discretization searches categorical values by using Na$\ddot{i}$ve scaling the data, then finds the optimized dicretization thresholds through Boolean reasoning. Although the rough set analysis is promising for market timing, there is little research on the impact of the various data discretization methods on performance from trading using the rough set analysis. In this study, we compare stock market timing models using rough set analysis with various data discretization methods. The research data used in this study are the KOSPI 200 from May 1996 to October 1998. KOSPI 200 is the underlying index of the KOSPI 200 futures which is the first derivative instrument in the Korean stock market. The KOSPI 200 is a market value weighted index which consists of 200 stocks selected by criteria on liquidity and their status in corresponding industry including manufacturing, construction, communication, electricity and gas, distribution and services, and financing. The total number of samples is 660 trading days. In addition, this study uses popular technical indicators as independent variables. The experimental results show that the most profitable method for the training sample is the na$\ddot{i}$ve and Boolean reasoning but the expert's knowledge-based discretization is the most profitable method for the validation sample. In addition, the expert's knowledge-based discretization produced robust performance for both of training and validation sample. We also compared rough set analysis and decision tree. This study experimented C4.5 for the comparison purpose. The results show that rough set analysis with expert's knowledge-based discretization produced more profitable rules than C4.5.