• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.6
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• pp.853-860
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• 2022

The purpose of this study is to suggest an improvement plan for the calculation method of the engineer standard wage rate (ESWR) and to compute a reasonable ESWR. To this end, an adequacy review of theESWR calculation criteria was conducted along with an extensive engineering industry survey. The survey results were analyzed using an effective response sample of 748 companies out of 1,000 survey samples extracted by stratifying the 5,879 survey population. The main results were as follows. ①When calculating the engineering service fee, the prime contractor's engineer wage is suitable for the ESWR. The ESWR can be estimated by the formula 'average wage÷[1-proportion of subcontract orders×(1-subcontract rate)].' ② The field survey showed that the number of monthly working days was 20.35-20.54 days at 99 % confidence interval, which was significantly different from the current standard (22 days). In addition, as a result of a legal review of the ESWR criteria, it was found that the number of working days should be calculated in accordance with the Labor Standards Act after 2022. ③ Applying government guidelines, the time difference between the wage survey and the ESWR application can be corrected by the past ESWR increase rate for a specific period. ④ Using modeling based on the analysis above, the current ESWR was 13.5-14.5 % lower than the appropriate level. A lower ESWR was driven by the non-reflection of subcontract structure (4.1 %), overestimation of monthly work days (6.8-7.8 %), and application of past wage (2.6 %). The proposed model is expected to be widely used in policy making, as it can provide a useful framework for calculating the standard wage rate in similar industries as well as calculating appropriate engineering fees.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.334-346
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• 2022

There is a lack of knowledge and information on the understanding and application of the Process Safety Management (PSM) system, recognized as a major cause of industrial accidents in small-and medium-sized workplaces. Hence, it is necessary to prepare a protocol to secure the practical and continuous levels of implementation for PSM and eliminate human errors through tracking management. However, insufficient research has been conducted on this. Therefore, this study investigated and analyzed the various violations in the administrative measures, based on the regulations announced by the Ministry of Employment and Labor, in approximately 200 small-and medium-sized PSM workplaces with fewer than 300 employees across in korea. This study intended to contribute to the prevention of major industrial accidents by developing a facility maintenance web program that removed human errors in small-and medium-sized workplaces. The major results are summarized as follows. First, It accessed the web via a QR code on a smart device to check the equipment's specification search function, cause of failure, and photos for the convenience of accessing the program, which made it possible to make requests for the it inspection and maintenance in real time. Second, it linked the identification of the targets to be changed, risk assessment, worker training, and pre-operation inspection with the program, which allowed the administrator to track all the procedures from start to finish. Third, it made it possible to predict the life of the equipment and verify its reliability based on the data accumulated through the registration of the pictures for improvements, repairs, time required, cost, etc. after the work was completed. It is suggested that these research results will be helpful in the practical and systematic operation of small-and medium-sized PSM workplaces. In addition, it can be utilized in a useful manner for the development and dissemination of a facility maintenance web program when establishing future smart factories in small-and medium-sized PSM workplaces under the direction of the government.

• Journal of the Korean Society of International Agriculture
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• v.23 no.5
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• pp.475-484
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• 2011

International price of cereal has been dramatically increasing for the past few years. This price hike amplified the importance of food self-sufficiency in numerous countries due to the fact that food security is directly proportional to food self-sufficiency. In this study, we conducted a survey to provide useful information of Cambodia's agricultural environment to possible Korean agricultural investors and as to highlight Cambodia as a strong candidate for the establishment of Korea's foreign base for cereal production. The survey conducted includes information regarding Cambodia's agricultural environment and investment circumstances including the political, economical and other contributing factors affecting agricultural investment in Cambodia. Seventy percent of the Cambodia's total population engage in agriculture and this comprises about 30% of the country's GDP. This statistics reflects the possibility of Cambodia's poverty alleviation which proves that agriculture in Cambodia is the driving force for the improvement of the country's economy. In addition, low labor cost, fertile land, abundant water resources, like the Tonle sap lake and the Mekong river, and unreclaimed lands are the strong points that could attract agricultural investors to Cambodia. Poor infrastructure, irrigation systems, law reforms, including social and cultural differences may be the biggest setbacks for the acceleration of Cambodia's agriculture development. However, the Cambodian government is open and willing to make adjustments for Cambodia to be both foreign and domestic agricultural investor-friendly, expecting that it will boost its country's agricultural development. Making the best out of this opportunity, the coordination of KOICA with Korean agricultural investors in building infrastructures and with the help of the KOPIA program for the transfer of agricultural technology will benefit both countries and will play an important role in Cambodia's agriculture.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.669-681
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• 2023

Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R²)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm², relative error (RE)≤17.9% and validation of R²≥0.56, RMSE≤1.41 ㎍/cm², RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R²=0.80, RMSE=0.94 ㎍/cm², RE=13.9%, and validation showed R²=0.57, RMSE=1.40 ㎍/cm², RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.

• Journal of the Korea Institute of Building Construction
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• v.24 no.2
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• pp.273-284
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• 2024

This study investigates the impact of international oil price fluctuations on overseas construction orders secured by domestic and foreign companies. The analysis employs statistical data spanning the past 20 years, encompassing international oil prices, overseas construction orders from domestic firms, and new overseas construction orders from the top 250 global construction companies. The correlation between these variables is assessed using correlation coefficients(R), determination coefficients(R²), and p-values. The results indicate a strong positive correlation between international oil prices and overseas construction orders. The correlation coefficient between domestic overseas construction orders and oil prices is found to be 0.8 or higher, signifying a significant influence. Similarly, a high correlation coefficient of 0.76 is observed between oil prices and new orders from leading global construction companies. Further analysis reveals a particularly strong correlation between oil prices and overseas construction orders in Asia and the Middle East, potentially due to the prevalence of oil-related projects in these regions. Additionally, a high correlation is observed between oil prices and orders for industrial facilities compared to architectural projects. This suggests an increase in plant construction volumes driven by fluctuations in oil prices. Based on these findings, the study proposes an entry strategy for navigating oil price volatility and maintaining competitiveness in the overseas construction market. Key recommendations include diversifying project locations and supplier bases; utilizing hedging techniques for exchange rate risk management, adapting to local infrastructure and market conditions, establishing local partnerships and securing skilled local labor, implementing technological innovations and digitization at construction sites to enhance productivity and cost reduction The insights gained from this study, coupled with the proposed overseas expansion strategies, offer valuable guidance for mitigating risks in the global construction market and fostering resilience in response to international oil price fluctuations. This approach is expected to strengthen the competitiveness of domestic and foreign construction firms seeking success in the international arena.

• KDI Journal of Economic Policy
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• v.12 no.3
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• pp.27-45
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• 1990

Two opposing views prevail regarding the economic impact of rural out-migration on the rural areas of origin. The optimistic neoclassical view argues that rapid rural out-migration is not detrimental to the income and welfare of the rural areas of origin, whereas Lipton (1980) argues the opposite. We developed our own alternative model for rural to urban migration, appropriate for rapidly developing economies such as Korea's. This model, which adopts international trade theories of nontraded goods and Dutch Disease to rural to urban migration issues, argues that rural to urban migration is caused mainly by two factors: first, the unprofitability of farming, and second, the decrease in demand for rural nontraded goods and the increase in demand for urban nontraded goods. The unprofitability of farming is caused by the increase in rural wages, which is induced by increasing urban wages in booming urban manufacturing sectors, and by the fact that the cost increases in farming cannot be shifted to consumers, because farm prices are fixed worldwide and because the income demand elasticity for farm products is very low. The demand for nontraded goods decreases in rural and increases in urban areas because population density and income in urban areas increase sharply, while those in rural areas decrease sharply, due to rapid rural to urban migration. Given that the market structure for nontraded goods-namely, service sectors including educational and health facilities-is mostly in monopolistically competitive, and that the demand for nontraded goods comes only from local sources, the urban service sector enjoys economies of scale, and can thus offer services at cheaper prices and in greater variety, whereas the rural service sector cannot enjoy the advantages offered by scale economies. Our view concerning the economic impact of rural to urban migration on rural areas of origin agrees with Lipton's pessimistic view that rural out-migration is detrimental to the income and welfare of rural areas. However, our reasons for the reduction of rural income are different from those in Lipton's model. Lipton argued that rural income and welfare deteriorate mainly because of a shortage of human capital, younger workers and talent resulting from selective rural out-migration. Instead, we believe that rural income declines, first, because a rapid rural-urban migration creates a further shortage of farm labor supplies and increases rural wages, and thus reduces further the profitability of farming and, second, because a rapid rural-urban migration causes a further decline of the rural service sectors. Empirical tests of our major hypotheses using Korean census data from 1966, 1970, 1975, 1980 and 1985 support our own model much more than the neoclassical or Lipton's models. A kun (county) with a large out-migration had a smaller proportion of younger working aged people in the population, and a smaller proportion of highly educated workers. But the productivity of farm workers, measured in terms of fall crops (rice) purchased by the government per farmer or per hectare of irrigated land, did not decline despite the loss of these youths and of human capital. The kun having had a large out-migration had a larger proportion of the population in the farm sector and a smaller proportion in the service sector. The kun having had a large out-migration also had a lower income measured in terms of the proportion of households receiving welfare payments or the amount of provincial taxes paid per household. The lower incomes of these kuns might explain why the kuns that experienced a large out-migration had difficulty in mechanizing farming. Our policy suggestions based on the tests of the currently prevailing hypotheses are as follows: 1) The main cause of farming difficulties is not a lack of human capital, but the in­crease in production costs due to rural wage increases combined with depressed farm output prices. Therefore, a more effective way of helping farm economies is by increasing farm output prices. However, we are not sure whether an increase in farm output prices is desirable in terms of efficiency. 2) It might be worthwhile to attempt to increase the size of farmland holdings per farm household so that the mechanization of farming can be achieved more easily. 3) A kun with large out-migration suffers a deterioration in income and welfare. Therefore, the government should provide a form of subsidization similar to the adjustment assistance provided for international trade. This assistance should not be related to the level of farm output. Otherwise, there is a possibility that we might encourage farm production which would not be profitable in the absence of subsidies. 4) Government intervention in agricultural research and its dissemination, and large-scale social overhead projects in rural areas, carried out by the Korean government, might be desirable from both efficiency and equity points of view. Government interventions in research are justified because of the problems associated with the appropriation of knowledge, and government actions on large-scale projects are justified because they required collective action.

• Korean Journal of Weed Science
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• v.13 no.4
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• pp.210-233
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• 1993

The herbicide has become indispensable as much as nitrogen fertilizer in Korean agriculture from 1970 onwards. It is estimated that in 1991 more than 40 herbicides were registered for rice crop and treated to an area 1.41 times the rice acreage ; more than 30 herbicides were registered for field crops and treated to 89% of the crop area ; the treatment acreage of 3 non-selective foliar-applied herbicides reached 2,555 thousand hectares. During the last 25 years herbicides have benefited the Korean farmers substantially in labor, cost and time of farming. Any herbicide which causes crop injury in ordinary uses is not allowed to register in most country. Herbicides, however, can cause crop injury more or less when they are misused, abused or used under adverse environments. The herbicide use more than 100% of crop acreage means an increased probability of which herbicides are used wrong or under adverse situation. This is true as evidenced by that about 25% of farmers have experienced the herbicide caused crop injury more than once during last 10 years on authors' nationwide surveys in 1992 and 1993 ; one-half of the injury incidences were with crop yield loss greater than 10%. Crop injury caused by herbicide had not occurred to a serious extent in the 1960s when the herbicides fewer than 5 were used by farmers to the field less than 12% of total acreage. Farmers ascribed about 53% of the herbicidal injury incidences at their fields to their misuses such as overdose, careless or improper application, off-time application or wrong choice of the herbicide, etc. While 47% of the incidences were mainly due to adverse natural conditions. Such misuses can be reduced to a minimum through enhanced education/extension services for right uses and, although undesirable, increased farmers' experiences of phytotoxicity. The most difficult primary problem arises from lack of countermeasures for farmers to cope with various adverse environmental conditions. At present almost all the herbicides have"Do not use!" instructions on label to avoid crop injury under adverse environments. These "Do not use!" situations Include sandy, highly percolating, or infertile soils, cool water gushing paddy, poorly draining paddy, terraced paddy, too wet or dry soils, days of abnormally cool or high air temperature, etc. Meanwhile, the cultivated lands are under poor conditions : the average organic matter content ranges 2.5 to 2.8% in paddy soil and 2.0 to 2.6% in upland soil ; the canon exchange capacity ranges 8 to 12 m.e. ; approximately 43% of paddy and 56% of upland are of sandy to sandy gravel soil ; only 42% of paddy and 16% of upland fields are on flat land. The present situation would mean that about 40 to 50% of soil applied herbicides are used on the field where the label instructs "Do not use!". Yet no positive effort has been made for 25 years long by government or companies to develop countermeasures. It is a really sophisticated social problem. In the 1960s and 1970s a subside program to incoporate hillside red clayish soil into sandy paddy as well as campaign for increased application of compost to the field had been operating. Yet majority of the sandy soils remains sandy and the program and campaign had been stopped. With regard to this sandy soil problem the authors have developed a method of "split application of a herbicide onto sandy soil field". A model case study has been carried out with success and is introduced with key procedure in this paper. Climate is variable in its nature. Among the climatic components sudden fall or rise in temperature is hardly avoidable for a crop plant. Our spring air temperature fluctuates so much ; for example, the daily mean air temperature of Inchon city varied from 6.31 to $16.81^{\circ}C$ on April 20, early seeding time of crops, within${\times}$2Sd range of 30 year records. Seeding early in season means an increased liability to phytotoxicity, and this will be more evident in direct water-seeding of rice. About 20% of farmers depend on the cold underground-water pumped for rice irrigation. If the well is deep over 70m, the fresh water may be about $10^{\circ}C$ cold. The water should be warmed to about $20^{\circ}C$ before irrigation. This is not so practiced well by farmers. In addition to the forementioned adverse conditions there exist many other aspects to be amended. Among them the worst for liquid spray type herbicides is almost total lacking in proper knowledge of nozzle types and concern with even spray by the administrative, rural extension officers, company and farmers. Even not available in the market are the nozzles and sprayers appropriate for herbicides spray. Most people perceive all the pesticide sprayers same and concern much with the speed and easiness of spray, not with correct spray. There exist many points to be improved to minimize herbicidal phytotoxicity in Korea and many ways to achieve the goal. First of all it is suggested that 1) the present evaluation of a new herbicide at standard and double doses in registration trials is to be an evaluation for standard, double and triple doses to exploit the response slope in making decision for approval and recommendation of different dose for different situation on label, 2) the government is to recognize the facts and nature of the present problem to correct the present misperceptions and to develop an appropriate national program for improvement of soil conditions, spray equipment, extention manpower and services, 3) the researchers are to enhance researches on the countermeasures and 4) the herbicide makers/dealers are to correct their misperceptions and policy for sales, to develop database on the detailed use conditions of consumer one by one and to serve the consumers with direct counsel based on the database.

• Journal of Intelligence and Information Systems
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• v.27 no.3
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• pp.231-252
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• 2021

Artificial intelligence (AI) is a key technology that will change the future the most. It affects the industry as a whole and daily life in various ways. As data availability increases, artificial intelligence finds an optimal solution and infers/predicts through self-learning. Research and investment related to automation that discovers and solves problems on its own are ongoing continuously. Automation of artificial intelligence has benefits such as cost reduction, minimization of human intervention and the difference of human capability. However, there are side effects, such as limiting the artificial intelligence's autonomy and erroneous results due to algorithmic bias. In the labor market, it raises the fear of job replacement. Prior studies on the utilization of artificial intelligence have shown that individuals do not necessarily use the information (or advice) it provides. Algorithm error is more sensitive than human error; so, people avoid algorithms after seeing errors, which is called "algorithm aversion." Recently, artificial intelligence has begun to be understood from the perspective of the augmentation of human intelligence. We have started to be interested in Human-AI collaboration rather than AI alone without human. A study of 1500 companies in various industries found that human-AI collaboration outperformed AI alone. In the medicine area, pathologist-deep learning collaboration dropped the pathologist cancer diagnosis error rate by 85%. Leading AI companies, such as IBM and Microsoft, are starting to adopt the direction of AI as augmented intelligence. Human-AI collaboration is emphasized in the decision-making process, because artificial intelligence is superior in analysis ability based on information. Intuition is a unique human capability so that human-AI collaboration can make optimal decisions. In an environment where change is getting faster and uncertainty increases, the need for artificial intelligence in decision-making will increase. In addition, active discussions are expected on approaches that utilize artificial intelligence for rational decision-making. This study investigates the impact of artificial intelligence on decision-making focuses on human-AI collaboration and the interaction between the decision maker personal traits and advisor type. The advisors were classified into three types: human, artificial intelligence, and human-AI collaboration. We investigated perceived usefulness of advice and the utilization of advice in decision making and whether the decision-maker's personal traits are influencing factors. Three hundred and eleven adult male and female experimenters conducted a task that predicts the age of faces in photos and the results showed that the advisor type does not directly affect the utilization of advice. The decision-maker utilizes it only when they believed advice can improve prediction performance. In the case of human-AI collaboration, decision-makers higher evaluated the perceived usefulness of advice, regardless of the decision maker's personal traits and the advice was more actively utilized. If the type of advisor was artificial intelligence alone, decision-makers who scored high in conscientiousness, high in extroversion, or low in neuroticism, high evaluated the perceived usefulness of the advice so they utilized advice actively. This study has academic significance in that it focuses on human-AI collaboration that the recent growing interest in artificial intelligence roles. It has expanded the relevant research area by considering the role of artificial intelligence as an advisor of decision-making and judgment research, and in aspects of practical significance, suggested views that companies should consider in order to enhance AI capability. To improve the effectiveness of AI-based systems, companies not only must introduce high-performance systems, but also need employees who properly understand digital information presented by AI, and can add non-digital information to make decisions. Moreover, to increase utilization in AI-based systems, task-oriented competencies, such as analytical skills and information technology capabilities, are important. in addition, it is expected that greater performance will be achieved if employee's personal traits are considered.

• Korean Journal of Animal Reproduction
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• v.24 no.1
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• pp.1-18
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• 2000

Eighty dairy farms in Palmers ton North area in New Zealand were surveyed on 1) general characteristics (10 Questions), 2) milk yield and feed supplementary (7 questions), 3) reproductive efficiencies (12 questions) and 4) reproductive disorders (12 questions) by mail questions from February to July, 1998. Among those 4 items from 38 dairy farms (47.5%), especially in items 1) and 2), overall dairy farming situation, supplementary feeding and milk yields were surveyed and analyzed for Korean dairy farmers (especially in Cheju island) to have better understanding or higher economical gains. The results were as follows. 1. In dairy experience, 21 (45%) among 38 dairy farms surveyed were answered that farming less than 15 years, 15~19 year, 20~25 years and over 26 years experience were 3 (7.9%), 7 (18.4%), 6 (15.8%) and 5 (13.2%) which generally showed longer experience compare to Korean dairy farming situation. In survey of labour input and business goal of dairy farming, self-managing farms, sharemilkers, unpaid family manpowering farms, manager running farms, farms with hired worker, farms with part time helper and other type was 21 (55.3%), 10 (26.3%), 2 (3.5%), 3 (5.3%), 18 (31.6%), 2 (3.5%), and 1 (1.8%), respectively. 2. Analyzing pasture and tillable land, pasture according to feeding scale (200, 300 and 400 heads) were 56, 90 and 165.3 ha, and tillable lands were 51, 78 and 165 ha which showed some differences among feeding scale. In recording methods in 38 farms replied, 36 (95%) dairy handbook and 23 (70%) dual methods taking farms were higher than that of 10 (26.3%) computer and 15(39.5%) well-recorder methods. 3. Dairy waste processing facilities in environmental field were almost perfect except of metropolitan area, and so no problem was developed in its control so far. Hence, 26 farm (68.4%) of pond system was higher rather than those in 8 (21.2%) of using as organic manure after storing feces of dairy cattle, 1(2.6%) bunker system and 3 (7.9%) other type farms. 4. In milking facilities, 33 farms (86.9%) of Harringbone types were higher than those in 3 (7.9%) of Walkthrough types, 1 (2.6%) of Rotary system and other types. Although the construction facilities was not enough, this system show the world-leveled dairy country to attempted to elevate economic gains using the advantage of climatic condition. 5. In milking day and yearly yield per head, average 275 milking days and 87 drying days were longer than that of 228 average milking days in New Zealand. Annual total milk yield per head and milk solid (ms) was 3,990 kg and approximately 319 kg. Dairy milk solid (ms) per head, milk yield, fat percentage was 1.2 kg, 15.5 kg and average 4.83% which was much higher than in other country, and milk protein was average 3.75%. 6. In coclusion, Palmerstone North has been a center of dairy farming in New Zealand for the last 21 years. Their dairy farming history is 6~9 year longer than ours and the average number of milking cows per farm is 355, which is much greater than that (35) of Korea. They do not have dairy barn, but only milking parlors. Cows are taken care of by family 0.5 persons), are on a planned calving schedule in spring (93%) and milked for 240~280 days a year, avoiding winter. Cows are dried according to milk yield and body condition score. This management system is quite different from that of Korean dairy farms. Cows are not fed concentrates, relying entirely on pasture forages and the average milk yield per cow is 3,500 kg, which is about 1/2 milk yield of Korean dairy farms. They were bred to produce high fat milk with an average of 4.5%. Their milk production cost is the lowest in the world and the country's economy relies heavily on milk production. We Korean farmers may try to increase farming size, decreasing labor and management costs.