• Journal of the Korean association of regional geographers
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• v.13 no.1
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• pp.54-67
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• 2007

This paper aims to explore the characteristics of regional embeddedness of Korean firms in Daren City, China, with special reference to management practices. To achieve this goal, I attempt to analyze the type and structure of the firm, the structure of decision-making, labor practices, and the inter-organizational networks with the government, trade associations and the business supporting agencies. The major purpose of the investment in Daren by Korean firms is to penetrate and expand the local market. In line with this, the structure of decision-making by Korean firms tends to become increasingly autonomous, especially in terms of employment and marketing. However, the decision-making related to finance and accounting tends to be still highly controlled upon the headquarter in Korea. In addition, it is shown that Korean firms make a great effort to sustain the cooperative relationships with the local society and the local government.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.635-642
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• 2002

There is a rapidly growing demand for the intellectualization of information technology. Especially, in the area of KDD (Knowledge Discovery in Database) which should make an optimal decision of finding knowledge from a large amount of data, the demand is enormous. A large volume of Knowledge Base should be efficiently managed for a more intellectual choice. This study is proposing a Hybrid SOM for an efficient search and renewal of knowledge base, which combines a self-study nerve network, Self-Organization Map with a probable distribution theory in order to get knowledge needed for decision-making management from the Knowledge Base. The efficient knowledge base management through this proposed method is carried out by a stimulation test. This test confirmed that the proposed Hybrid SOM can manage with efficiency Knowledge Base.

• Journal of Navigation and Port Research
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• v.47 no.6
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• pp.430-436
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• 2023

Study on Changes in Vessel Traffic Services Due to Introduction of Maritime Autonomous Surface ShipsThe development of technologies related to Maritime Autonomous Surface Ships (MASS) has been actively progressing since the mid-2010s, focusing on themes such as collision avoidance, route planning, digital twin, and communication technologies. On the other hand, research on land-based infrastructure connected with MASS, such as logistics systems, port facilities, and vessel traffic services, has relatively received less attention. This study analyzed impact of emergence of MASS on existing vessel traffic service operations and proposed changes in control operations to prepare for its impact. To do this, current vessel traffic service operations were analyzed and elements of MASS technology that could affect vessel traffic control were identified. A survey was conducted among vessel traffic controllers to identify items related to the control of MASS. Results analyzed using the AHP method showed that preparation for emergency response and communication methods with MASS were the most important. Based on this, we were able to derive detailed plans for basic MASS control procedures and emergency response procedures based on data communication within maritime traffic control areas. MASS control procedures proposed in this study are expected to be used as a solution to resolve issues related to traffic safety of MASS in coastal areas.

• Journal of Advanced Navigation Technology
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• v.26 no.5
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• pp.312-318
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• 2022

Currently, the Republic of Korea is facing the problem of a decrease in military service resources due to the demographic cliff, and is pursuing military restructuring and changes in the military force structure in order to respond to this. In this situation, the Army is pushing forward the deployment of a drone-bot combat system that will lead the future battlefield. The battlefield of the future will be changed into an integrated battlefield concept that combines command and control, surveillance and reconnaissance, and precision strike. According to these changes, unmanned combat system, including dronebots, will be widely applied to combat situations that are high risk and difficult for humans to perform in actual combat. In this paper, as one of the countermeasures to these changes, autonomous behavior software with a BDI architecture-based decision-making system was developed. The autonomous behavior software applied a framework structure to improve applicability to multiple models. Its function was verified in a PC-based environment by assuming that the target UAV is a battalion-level surveillance and reconnaissance UAV.

• Current Industrial and Technological Trends in Aerospace
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• v.4 no.2
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• pp.55-67
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• 2006

20세기에 탄생한 동력비행기는 인간의 이동능력을 비약적으로 향상시켰다. 인류의 미개척지였던 항공분야의 발전은 지속적인 기술개발을 통해 더 빨리, 더 멀리, 더 높이 향하기 위해서 계속 나아가고 있다. 이러한와중에 최근에 괄목할 만한 성장을 이룬 컴퓨터와 소프트웨어 산업의 발전은 비행임무에 따라 위험성이 높거나, 사람이 하기 힘든 반복적이고 지루한 비행을 대신하기위한 로봇 비행체 즉, 무인항공기의 개발을 가능하게 하였다. 무인항공기의 탄생 초기에는 조종사의 희생을 줄이기 위해 군사 분야에서 주로 사용되었으나, 산림감시나 해안정찰, 기상관측, 재난관측, 조난자 수색 등 민수분야의 임무로 점차 활동영역이 넓혀지고 있다. 현재 무인항공기에 탑재된 인공지능의 수준은 안정된 비행이 가능하도록 하는 자동조종(autopilot)과 주어진 비행경로를 추종하기위한 항법유도(Navigation & Guidance)정도이며, 비행 중 발생하는 비상상황에 대처하기 위한 의사판단은 지상의 조종자에 의해 결정된다. 앞으로는 계획되지 않은 상황을 맞이했을 때 무인기 스스로 판단하여 경로를 변경하고, 동시에 여러 무인기들과 협력하여 임무를 수행함으로써 임무효율을 높이는 방향으로 인공지능의 수준이 향상될 것이다. 본 논문에서는 최근의 무인항공기 개발추세와 이들 무인기에 고려되고 있는 제어기에 대해 살펴보고, 향후 무인항공기에 적용될 자율비행 알고리듬과 제어기 시스템의 개발동향에 대해 고찰하였다.

• Journal of the Korea Institute of Military Science and Technology
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• v.27 no.6
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• pp.772-783
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• 2024

The emergence of MUCS(Manned-Unmanned Complex System), incorporating numerous robots surpassing human's control capabilities, is inevitable on future battlefields and necessitates revolutionary robot operation technology. Since MUCS should be structured over the current command and control networks in Korean military binding its constituent elements ranging from small echelons to joint forces, various types of MUCS configurations and manned-unmanned teaming(MUM-T) types are also defined. Then a methodology for robot collaboration with aiming at real-time situation response is proposed. The method is basing on the situational response decision-making model in order to operate multiple robots cooperatively in respond to serial events occurring in real-time using the concept of control measure which is the origin/object triggering a task. In addition, a set of decision-making rules is devised and compared to decisions optimized by the model. Through illustrative experiments the suggested method is checked to be viable for realizing MUM-T and operating multiple robots in MUCSs.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.256-265
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• 2021

Ground, sea and air mobility, such as vehicles, ships, and airplanes, are generally operated by people. Based on the innovative development of autonomous decision-making systems and artificial intelligence (AI) following the recent fourth industrial revolution, research and development on maritime autonomous surface ships (MASS) is been actively performed around the world. Before the realization of the commercialization of MASS in international maritime transport, it is urgent to clarify the characteristics of this ship and its international legal status. This paper aims to analyze the concern of whether a ship without crew members will eventually be operated as a fully unmanned ship or can be recognized as a ship under international law as the number of crew members is gradually reduced owing to the development stage of autonomous ships. Consequently, based on the United Nations Convention on the Law of the Sea (UNCLOS) and the regulations of the International Maritime Organization (IMO), it was found that MASS has the same international legal status as general ships. In addition this paper presents the working principles of enacting and revising the IMO Conventions and international legal measures necessary for the safe operation of MASS.

• Informatization Policy
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• v.25 no.2
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• pp.20-45
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• 2018

This study aims to find the factors of Internet overdependence in adults, through the decision tree analysis model, which is a data mining method using National Information Society Agency's raw data from the survey on Internet overdependence in 2016. As a result of the decision tree analysis, a total 16 nodes of Internet overdependence risk groups were identified. The main predicated variables were the amount of time spent per smart media usage in weekdays; amount of time spent per smart media usage in weekends; experiences of purchasing cash items; percentage of using smart media for leisure; negative personality; percentage of using smart media for information search and utilization; and awareness on good functions of the Internet, all of which in order had greater impact on the risk groups. Users in the highest risk node spent the smart media for more than 5 minutes per use and less than 5~10 minutes in weekdays, had experiences of cash item purchase, and had lower level of awareness on the good functions of the Internet. The analysis led to the following recommendations: First, even a short-time use has higher chances of causing Internet overdependence, and therefore, guidelines need to be developed based on research on the usage behavior rather than the usage time. Second, self-regulation is required because factors that affect overindulgence in games, such as the cash items, increase Internet overdependence. Third, using the Internet for leisure causes higher risk of overdependence and therefore, other means of leisure should be recommended.

• The Korean Society of Law and Medicine
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• v.23 no.2
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• pp.67-96
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• 2022

"Aid in Dying" means that when a decision-making patient suffers from an incurable disease, a drug that can speed up death is prescribed by a doctor and used to lead to death. Since the suspension of life-sustaining treatment was institutionalized based on human dignity and patient autonomy, the question of whether assisted death can be legally justified in relation to the right to receive medical help to shorten one's life to die with dignity has recently been actively discussed. In Korea, since the suspension of life-sustaining treatment was institutionalized by the enactment of the Life-sustaining Treatment Decision Act in 2016, an amendment to the Life-sustaining Treatment Act was recently proposed to legalize Aid in Dying. The global trend is that human "Right to Die" is discussed in the division of life and death, from the suspension of life-sustaining treatment to assisted death, and again in the order of euthanasia. In this paper, we started discussing dignified death and institutionalized patients' right to self-determination, looked at the controversy in the United States, which legislated assisted death in many states since the 2000s, and analyzed the main contents of California's End of Life Option Act and the data after enforcement. The strict requirements for Aid in Dying, such as voluntary confirmation of patients' intentions and doctors' obligation to provide information, and the results of California's Aid in dying system, composed of relatively diverse races, were reviewed.

• 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.