• Journal of Applied Reliability
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• v.10 no.1
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• pp.39-56
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• 2010

Statistical process control (SPC) is a powerful technique for monitoring, managing, analysing and improving the process performance. However, its has limitations such as lack of engineering, statistical skill and training, and lesser importance of activity. To solve the problems, this study proposes an intelligent SPC system using specified agents which are derived through analysis and evaluation of the SPC activities. The activities investigated by the relevant researches are categorized as collection, process analysis, diagnosis, detection, cause analysis and rule generation. Also, the evaluation criteria are established as feasibility of automation, frequency, level and time. The requirements of the agent functions are derived by the evaluation, and the types of customized agents are as data collection, store, analysis, diagnosis, monitoring, alarm and reporting. A prototype SPC system represents that the functions of the proposed agents are successfully validated.

• Food Science of Animal Resources
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• v.43 no.4
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• pp.580-593
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• 2023

The purpose of this study was to analyze whether seawater has positive effects on appearance characteristics, such as CIE a^*, and to determine the gas composition concentration that is suitable for maintaining it. Pork hind meat was cured with four types of curing agent for 5 d at 4℃. The different curing agents comprised the control salt, control nitrite pickling salt (CN), treatment brine, and treatment bittern (BT). The cured hams were cooked at 65℃ for 4 h and packaged at O₂:N₂ gas ratios of 7:3, 8:2, and 9:1 for 3 wk. The physicochemical properties were assessed immediately after heating the sample, and the color properties were measured after a 3 wk storage period. Based on the correlation results of the physicochemical properties, BT had a higher curing and cooking yield than the other treatments, owing to its high salinity. Results of color properties for BT (7:3) and CN (8:2) showed similar color CIE L^*, CIE a^* chroma, and hue angle values. Therefore, BT can be said to be a sous-vide curing agent suitable for preserving the color of ham, and a high nitrogen concentration of 30% helps to maintain the appearance of seawater sous-vide ham.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.3
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• pp.71-84
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• 2024

Artificial intelligence can be cited as a key linkage technology for expanding drones' application fields, and drones combined with artificial intelligence are expected to improve drones' operational capabilities based on algorithms that can solve complex tasks through learning. The purpose of this study is to analyze various latest research cases that apply deep reinforcement learning to drones to solve limitations for performing swarm flight and to propose a new research direction that applies them to multi-agent communication optimization technology. The process of the research is to investigate and analyze the methods for efficient operation of control and communication technologies required for swarm flight to be successful, and to apply algorithms that have the advantage of exchanging richer feedback between agents and having less learning than conventional methods when learning deep reinforcement learning algorithms. It is expected that the efficiency and performance of learning communication protocols optimized for swarm flight will be improved, which will increase the efficiency of mission performance when exploring or scouting large areas through swarm flight in the future.

• The Plant Pathology Journal
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• v.22 no.3
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• pp.278-282
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• 2006

Bacillus vallismortis EXTN-1, a biocontrol agent in cucumber, tomato and potato was tested in rice pathosystem against rice fungal pathogens viz. Magnaporthe grisea, Rhizoctonia solani and Cochliobolus miyabeanus. Apart from increasing the yield in the bacterized plants (11.6-12.6% over control), the study showed that EXTN1 is effective in bringing about disease suppression against all the tested fungal pathogens. EXTN-l treatment resulted in 52.11% reduction in rice blast, 83.02% reduction in sheath blight and 11.54% decrease in brown spot symptoms. As the strain is proven as an inducer for systemic resistance based on PR gene expression in Arabidopsis and tobacco models, it is supposed that a similar mechanism works in rice, bringing about disease suppression. The strain could be used as a potent biocontrol and growth-promoting agent in rice cropping system.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.333-342
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• 2004

This paper presents a framework for the self-organization of swarm systems based on coupled nonlinear oscillators (CNOs). In this scheme, multiple agents in a swarm self-organize to flock and arrange themselves as a group using CNOs, which are able to keep a certain distance by the attractive and repulsive forces among different agents. A theoretical approach of flocking behavior by CNOs and a design guideline of CNO parameters are proposed. Finally, the formation scenario for cooperative multi-agent groups is investigated to demonstrate group behaviors such as aggregation, migration, homing and so on. The task for each group in this scenario is to perform a series of processes such as gathering into a whole group or splitting into two groups, and then to return to the base while avoiding collision with agents in different groups and maintaining the formation of each group.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.571-573
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• 2020

현재의 센서네트워크 환경은 자원사용의 효율화를 위한 제어시스템의 지원이 필수적으로 요구된다. 본 논문은 이동에이전트 기반의 데이터 획득기능, Zigbee 기반 데이터 통신기능, 연산 및 능동규칙 처리기능 등을 지원하는 분산제어 프레임워크를 제안함으로써, 센서네트워크 환경에서 무선방식의 분산된 장치들의 자율제어를 통한 효율적 분산제어시스템 구축에 적용하도록 한다. 제안 프레임워크는 환경 변화, 사용자의 행동 변화 및 이상 패턴 탐지 등에 따른 최적 제어를 기반으로 하는 스마트 전력서비스 개발과 수요자의 요구에 자율적 지능적으로 반응하는 수요반응 서비스 개발에 적용이 가능하다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.735-745
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• 2023

The purpose of this study is to examine how the control of an agent according to a driver's social status affects user experience factors in a multi-user environment of self-driving vehicles. We conducted a user study where participants viewed four scenarios (route changing/parking x accepting/declining a fellow passenger's command) and answered a survey, followed by a post-hoc interview. Results showed that either the routing scenario or accepting a passenger's command scenario had higher usefulness (convenience, effectiveness, efficiency) than their counterparts. Regardless of the car owner's social status, participants rated AI agents more positively when they met their goals effectively. They also stressed that vehicle owners should always be in control of their agents. This study can provide guidelines for designing future autonomous driving scenarios where an agent interacts with a driver, and passengers.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.465-470
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• 2012

This paper proposes a distributed autonomous control method of swarm robot behavior strategy based on artificial immune system and an optimization strategy for artificial immune system. The behavior strategies of swarm robot in the system are depend on the task distribution in environment and we have to consider the dynamics of the system environment. In this paper, the behavior strategies divided into dispersion and aggregation. For applying to artificial immune system, an individual of swarm is regarded as a B-cell, each task distribution in environment as an antigen, a behavior strategy as an antibody and control parameter as a T-cell respectively. The executing process of proposed method is as follows: When the environmental condition changes, the agent selects an appropriate behavior strategy. And its behavior strategy is stimulated and suppressed by other agent using communication. Finally much stimulated strategy is adopted as a swarm behavior strategy. In order to decide more accurately select the behavior strategy, the optimized parameter learning procedure that is represented by stimulus function of antigen to antibody in artificial immune system is required. In this paper, particle swarm optimization algorithm is applied to this learning procedure. The proposed method shows more adaptive and robustness results than the existing system at the viewpoint that the swarm robots learning and adaptation degree associated with the changing of tasks.

• Journal of Digital Contents Society
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• v.4 no.2
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• pp.139-146
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• 2003

This paper explains the design and implementation of the ERA(Error Recovery Agent). ERA is a system that is suitable for detecting, sharing and recovering software error based on multimedia distance education system. This system consists of an ED, ES, and ER. ED detects an error by hooking techniques. ES is an agent which is an error sharing system for distributed multimedia distance education system. We propose how an error application can be treated and recovered as 'media' in a multimedia collaborative environment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.9-11
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• 2022

Applying Reinforcement Learning in everyday applications and varied environments has proved the potential of the of the field and revealed pitfalls along the way. In robotics, a learning agent takes over gradually the control of a robot by abstracting the navigation model of the robot with its inputs and outputs, thus reducing the human intervention. The challenge for the agent is how to implement a feedback function that facilitates the learning process of an MDP problem in an environment while reducing the time of convergence for the method. In this paper we will implement a reward shaping system avoiding sparse rewards which gives fewer data for the learning agent in a ROS environment. Reward shaping prioritizes behaviours that brings the robot closer to the goal by giving intermediate rewards and helps the algorithm converge quickly. We will use a pseudocode implementation as an illustration of the method.