• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.357-359
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• 2022

Autonomous decision-making is key to safe and efficient marine autonomy, as global marine industry comprises over 90 percent of the world's cargo transportation. Challenges of the real-world validation in the aquatic domain limits the wide-spread of ASVs despite their promising societal impacts. We propose and demonstrate the real-world validation platform and comprehensive algorithm steps. Such a framework will serve as a more explainable and reliable decision-making system of ASVs as well as autonomous vehicles in other domains.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.1-10
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• 2020

Blockchain enabled Decentralized Autonomous Organization (DAO), a new form of organization with conveying its core value - trust. Token holders who are participating DAO's governance share their thoughts, information, and ideas in online forum. But it is problem that chronological form of DAO's online forum makes token holders hard to find crucial information, meaning that many of them might not understand what is happening discussion. In this paper, we studied not only a decision making process which feature is iteration, visualization, and applicable to DAO with 6 steps in total but also a decision making tool which is based on the process of this paper. The tool has features to help participants such as voting model, visualization features which gives guidance to them for their decision during the process. Our experiment showed that the process and tool is somewhat reasonable, and the information during the process is effective for participants. This work is expected to be applied to current DAOs to make a decision among the token holders.

• Journal of Agricultural Extension & Community Development
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• v.12 no.2
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• pp.257-270
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• 2005

The purposes of this study were to explore the differences of decision making in farming settlement and to analyze attributes for vocational decision making of rural youth. The study was carried out by literature review and questionnaire. To analyze vocational decision making of rural youth, the data were collected from 196 rural youth by stratified random sampling. The SPSSWIN/ver10 was used for analyzing data with frequency, percentage, t-test ANOVA and factor analysis. The major findings of this study were as follows; 1) Rural youth decided to become farmers at the middle and high school stage for farming succession and eco-friendly life orientation. 2) Youth parents were the major source of influence on their rural youth to settle in farming. 3) Rural youth with high economic status, upper academic achievement and university graduation showed higher autonomous decision making and lower heteronomous decision making. 4) Rural youth with low economic status and low academic achievement showed unstable vocational decision making. 5) The study suggested that rural youth with unstable decision making should get more educational opportunities and supports.

• Journal of KIISE:Software and Applications
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• v.30 no.12
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• pp.1220-1227
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• 2003

To perform rational decision-making, autonomous agents need considerable computational resources. When other agents are present in the environment, these demands are even more severe. In these settings, it may be difficult for the agent to decide what to do in an acceptable time in multiagent situations that involve many agents. These problems motivate us to investigate ways in which the agents can be equipped with flexible decision-making procedures that enable them to function in a variety of situations in which decision-making time is important. The flexible decision-making methods explicitly consider a tradeoff between decision quality and computation time. Our framework limits resources used for agent deliberation and produces results that are not necessarily optimal, but provide autonomous agents with the best decision under time pressure. We validate our framework with experiments in a simulated anti-air defense domain. The experiments show that compiled rules reduce computation time while offering good performance.

• Journal of applied mathematics & informatics
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• v.41 no.5
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• pp.973-988
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• 2023

In real-life scenarios, we may have to deal with real numbers or numbers in intervals or a combination of both to solve multi-criteria decision-making (MCDM) problems. Also, we may come across a situation where we must combine this interval and actual number membership values into a single real number. The most significant factor in combining these membership values into a single value is by using aggregation operators or scoring algorithms. To overcome such a situation, we suggest the cubic hypersoft set (CHSS) concept as a workaround. Ultimately, this makes it simple for the decision-maker to obtain information without misconceptions. The primary aim of this study is to establish some operational laws for the cubic hypersoft set, present the fundamental properties of aggregation operators and propose an algorithm by using the technique of order of preference by similarity to the ideal solution (TOPSIS) technique based on correlation coefficients to analyze the stress-coping skills of workers.

• Journal of the HCI Society of Korea
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• v.14 no.2
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• pp.21-29
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• 2019

Take-over requests in semi-autonomous cars must be handled properly in the case of road obstacles or curved roads in order to avoid accidents. In these situations, situation awareness and appropriate decision making are essential for distracted drivers. This study used a driving simulator to investigate the components of auditory-visual information systems that affect safety, workload, and trust. Auditory information consisted of either voice guidance providing situation awareness for the take-over or a beep sound that only alerted the driver. Visual information consisted of either a screen showing how to maneuver the vehicle or only an icon indicating a take-over situation. By providing auditory information that increased situation awareness and visual information that aided decision making, trust and safety increased, while workload decreased. These results suggest that the levels of situation awareness and decision making ability affect trust, safety, and workload for drivers.

• Asia Marketing Journal
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• v.20 no.2
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• pp.65-83
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• 2018

Technological advances are bringing autonomous vehicles to the ever-evolving transportation system. Anticipating adoption of these technologies by users is essential to vehicle manufacturers for making more precise production and marketing strategies. The research investigates regulatory focus and consumer innovativeness with consumers' adoption of autonomous vehicles (AVs) and to consumers' subsequent willingness to pay for AVs. An online questionnaire was fielded to confirm predictions, and regression analysis was conducted to verify the model's validity. The results show that a promotion focus does not have a significantly positive effect on the automation level at which consumers will adopt AVs, but a prevention focus has a significantly positive effect on conditional AV adoption. Consumer innovativeness, consumers' novelty-seeking have a significantly positive relationship with high and full AV adoption, and consumers' independent decision-making has a significantly positive effect on full AV adoption. The higher the level of automation at which a consumer adopts AVs, the higher the willingness to pay for them. Finally, using a neural network and decision tree analyses, we show methods with which to describe three categories for potential adopters of AVs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.165-167
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• 2011

Autonomous robots are intelligent machines that are capable of performing task in the world themselves with little or no human intervention. One of the main reason autonomous robots gained popularity in human's world is their ability to perform task with high degree of precision, accuracy and also consistency. One of the most studied fields in autonomous robot is the ability of decision making in robots. To tackle the ability of robots to make decision, this paper proposed an Autonomous Maze Solving Robot that is able to solve a maze using the optimum solution. The maze and the design of the robot are in compliance with IEEE Micromouse competition rules and regulation. Micromouse is an autonomous maze solving robot that shall be able to explore a maze on its own from a predefined starting location and find the optimum path to reach the predefined goal in the maze without human's intervention.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.124-127
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• 1997

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment. For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows. When the environmental condition changes, a robot selects an appropriate behavior strategy. And its behavior strategy is simulated and suppressed by other robot using communication. Finally much simulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idiotopic network hypothesis. And it is used for decision making of optimal swarm strategy.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1196-1203
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• 2004

Autonomous agents need considerable computational resources to perform rational decision-making. The complexity of decision-making becomes prohibitive when large number of agents are present and when decisions have to be made under time pressure. One of approaches in time-critical domains is to respond to an observed condition with a predefined action. Although such a system may be able to react very quickly to environmental conditions, predefined plans are of less value if a situation changes and re-planning is needed. In this paper we investigate strategies intended to tame the computational burden by using off-line computation in conjunction with on-line reasoning. We use performance profiles computed off-line and the notion of urgency (i.e., the value of time) computed on-line to choose the amount of information to be included during on-line deliberation. This method can adjust to various levels of real-time demands, but incurs some overhead associated with iterative deepening. We test our framework with experiments in a simulated anti-air defense domain. The experiments show that the off-line performance profiles and the on-line computation of urgency are effective in time-critical situations.