• Korean Journal of Labor Studies
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• v.23 no.1
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• pp.221-253
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• 2017

This study aims at analyzing the management strategy and performance of companies that have been pursuing Generational Diversity. The management strategies were examined in terms of production, organizational structure and skill development. Performance was then evaluated using Balanced Scorecard (BSC). We selected four Japanese companies that practice Generational Diversity between the younger(age less then 34) and older generation(age older then 65). Our findings suggest the following. The common management strategies of the four companies include 1) creating generation-diverse teams 2) ensuring flexible work arrangements and 3) providing skill training programs. These strategies have yield positive outcomes such as sales increase, cost reduction (financial perspective) and expansion of the market share (customer perspective). Non-financial performance includes improvement of product and service quality (internal business perspective) and skill improvement of both the young and the old workers (learning and growth perspective). This study provides practical implications to domestic companies for their successful management of generational diversity in workplace.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.15-19
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• 2021

In May 2021, a major conflict broke out between Israel and Palestine. Fourteen days after the conflict began, a ceasefire between the two sides was signed with the victory of Defense Forces (IDF). One of the reasons why IDF was able to lead the dispute to victory with the minimum damage in the shortest period of time is that the female workforce in IDF turned on. also, there are currently 33% of the female workforce in IDF, and various tasks are carried out in the field by convergence with male workforce. So, in this study, the examples experienced by IDF will provide clues to overcoming the future challenge of Korea's lack of military service resources.

• Journal of Information Technology Services
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• v.22 no.4
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• pp.97-110
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• 2023

In this study, we propose a technique to automatically generate transfer documents using sensor data from livestock manure transfer systems. The research involves analyzing sensor data and applying machine learning techniques to derive optimized outcomes for livestock manure transfer documents. By comparing and contrasting with existing documents, we present a method for automatic document generation. Specifically, we propose the utilization of Gradient Boosting, a machine learning algorithm. The objective of this research is to enhance the efficiency of livestock manure and liquid byproduct management. Currently, stakeholders including producers, transporters, and processors manually input data into the livestock manure transfer management system during the disposal of manure and liquid byproducts. This manual process consumes additional labor, leads to data inconsistency, and complicates the management of distribution and treatment. Therefore, the aim of this study is to leverage data to automatically generate transfer documents, thereby increasing the efficiency of livestock manure and liquid byproduct management. By utilizing sensor data from livestock manure and liquid byproduct transport vehicles and employing machine learning algorithms, we establish a system that automates the validation of transfer documents, reducing the burden on producers, transporters, and processors. This efficient management system is anticipated to create a transparent environment for the distribution and treatment of livestock manure and liquid byproducts.

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.93-105
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• 2023

In order to transform the traditional aquaculture industry, which is dependent on experience, labor-intensive and natural environment, into future intelligent smart aquaculture, digital aquaculture improves aquaculture reproducibility and efficiency of production process through digitization of the aquaculture industry based on ICT equipments, Data analysis and utilization for promoted to increase the acceptability of aquaculturist. Europe's advanced fisheries countries have achieved rapid growth not only in aquaculture technology but also in the aquaculture equipment industry through digitization that combines information and communication technology with aquaculture farms. However, it is not possible to collect aquacultural data in Korea because it has not secured a Korean aquaculture industry for multi-variety, small-scale production and aquaculturists' refusal of reception for digital transformation. Therefore, this study intends to suggest the development direction of digital aquaculture to convert to intelligent smart aquaculture in the future by analyzing trends and critical technology.

• Korea Trade Review
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• v.41 no.5
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• pp.89-111
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• 2016

The Mega-FTA is intended for emerging economies, including developed economies, to expand economies of scale in a single market. The Bilateral FTA shall take into account the relevant industries and the inter-country related industries to adjust the origin standard and preferential tariff rates. Therefore, certain competitive industries can expect foreign investment and re-investment in the domestic market as well as expansion of the market in the region. However, the mega-FTA should expand the size of the economy under the same preferential tax rates for many Partner countries. The Mega-FTA can maximize the effectiveness of the agreement by making use of the competitive advantages of the participating countries. In the mega-FTA, Cumulative Criteria should be appropriately used as a supplemental standard of origin. The Cumulative Criteria is an important FTA utilization factor that determines the success of the mega-FTA. Using FTA, Korea should export locally produced materials using cheaper labor force in FTA partner country. In addition, in order to prepare the Mega-FTA, which allows full cumulation, it is necessary to encourage the overseas transfer of low-cost structure materials processing industry so that the material suppliers can be transferred to the area where production cost is lower and raw material supply is easier.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.75-75
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• 2022

Traditional agriculture mostly focused on activity in the field, but current agriculture faces problems such as reduction of agricultural inputs, labor shortage and so on. Accordingly, traditional agricultural experiments generally considered the simple treatment effects, but current agricultural experiments need to consider the several and complicate treatment effects. To analyze such several and complicate treatment effects, data collection has the first priority. Remote sensing is a quite effective tool to collect information in agriculture, and recent easier availability of UAVs (Unmanned Aerial Vehicles) enhances the effectiveness. LAI (Leaf Area Index) is one of the most important information for evaluating the condition of crop growth. In this study, we utilized UAV with multispectral camera to evaluate plant-based LAI of sweetcorn in a small-scale field experiment and discussed the feasibility of a new experimental design to analyze the several and complicate treatment effects. The plant-based SR measured by UAV showed the highest correlation coefficient with LAI measured by a canopy analyzer in 2018 and 2019. Application of linear mix model showed that plant-based SR data had higher detection power due to its huge number of data although SR was inferior to evaluate LAI than the canopy analyzer. The distribution of plant-based data also statistically revealed the border effect in treatment plots in the traditional experimental design. These results suggest that remote sensing with UAVs has the advantage even in a small-scale experimental plot and has a possibility to provide a new experimental design if combined with various analytical applications such as plant size, shape, and color.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

• Korean Journal of Agricultural Science
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• v.8 no.2
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• pp.203-211
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• 1981

Mechanization of rice transplanting operation is very important project not only to solve the labor shortage problem at the so-called labor demand peak seasons of the rice transplanting, but also to reduce the production cost of rice by reducing the labor requirements. For these reasons this study was carried out to find the basic data for encourage the project of mechanization of rice transplanting. 381 sample farms were surveyed with questionaries and interviewed with a considerable number of relative personels about the operation, selecting and ownership trend of the rice transplanter. Collected data was analized by computer of Chungnam National University computer center applied to frequencies, cross- tabulation, $x^2$-test. The analized results of this survey are summarized as follows; 1. About 76.09% of the farmers interviewed was individual ownership of rice transplanter but about 52.27% of the farmers who wanted to purchase it in 2 or 3 years supported the cooperative ownership and utilization. This fact suggested that cooperative system of village level should be thoroghly studied. 2. The 93.33% of respondents gave the answer that the yield of rice was not affected by the planting methods between machine and manual. 3. The farmers who had a rice transplanter owned 4- row type rice transplanter with mat type seedling but the 25% of the farmers wanted to purchase it in 2 or 3 years wanted to own a 4 row type rice transplanter with band type seedling. Therefore the introduction of the 4-row type rice transplanter with band type seedling to rural area should be considered again. 4. The percent of farmers who wanted the cooperative system of village level was 49.57-57.83% of the farmers who had it already and wanted to own it in near future. It was strengthened by this fact that seedling nursely work was technically supported by the governmental level.

• Korean Journal of Agricultural Science
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• v.1 no.1
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• pp.59-66
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• 1974

This paper describes how location influences on the development of dairy farming. It compares Chuncheon, which in the mountains, Daejeon, which is a transportation center and on flat ground, and Incheon, which is the gate to Seoul and an industrial city. The results analyzed are summarized as follows : 1. Incheon, due to her vast market, influenced strongly on the development of management. But shortage of roughage for feeds is the critical problem there. 2. Owing to the side job of raising chicks, which involves 92% of dairy farmers there, Chuncheon does not make smooth utilization of vast grass pasture. 3. In Daejeon's case, running orchards concurrently is the problem. 4. There exists no gap in wages between the region. The labor supply is most affluent in Incheon and there is competition with other forms of agriculture in the mountainous area. 5. The full-time employee tends to be skillful in accordance with his career. Family labor has been skillful, but the full-time employee is very fluid and shows varieties of skill. 6. Because of the obscurity of the distribution of labor with other jobs in Chuncheon and Daejeon, many unspecialized men serve. 7. The prices of milk are different in each region. The income of dairy farmers is strongly influenced by the low purchasing price of milk plants, and this is one of the important factors hindering the development of dairy farm ing in Chuncheon.

• 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.