• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.121-124
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• 2001

Using ordors with the different concentration of essential oils, e studied the effect of a pleasant olfactory stimulation on physiological responses. we examined psychological response, mental task and changes in cardiac, immunity and EEG in responses to 150times solution (feel easily) and 500times solution (feel with difficulty) which of essential oil (called PCK) were diluted in propylene glycol, and neutral (water). The 150times solution that was felt pleasant produced significant differences (p<0.05) in relative power change of beta activity in the left frontal region (Fp1, F3, F7) of the brain, and heart rate (HR) deceleration after mental task. these results are consistent with substantial research that has documented cardiac and EEG responses to pleasant stimuli. What is more, 150times solution increased the concentration of s-IgA know as an index of immunity.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.85-90
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• 2005

In this paper, firstly we report experimental results on applying information extraction (IE) methodology to the task of summarizing clinical trial design information in focus on ‘Compared Treatment’, ‘Endpoint’ and ‘Patient Population’ from clinical trial MEDLINE abstracts. From these results, we have come to see this problem as one that can be decomposed into a sentence classification subtask and an IE subtask. By classifying sentences from clinical trial abstracts and only performing IE on sentences that are most likely to contain relevant information, we hypothesize that the accuracy of information extracted from the abstracts can be increased. As preparation for testing this theory in the next stage, we conducted an experiment applying state-of-the-art sentence classification techniques to the clinical trial abstracts and evaluated its potential in the original task of the summarization of clinical trial design information.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.447-449
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• 2012

This paper present an intelligent microcontroller based chess playing robot which can play a board game against opponent and calculate its moves in a non-idealized environment. In this work, for the sake of simplicity task is accomplished by using Cartesian coordinate system. Chess playing system has been designed in such a way that it provides an interface between user and robot to control chess movements using RS232. Various algorithms are implemented for interfacing hardware in C++ language. Our main goal is to design a cost effective and highly accurate robot system that consumes minimal power to complete its task.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.87-105
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• 2020

Statistical engineering contains the design of experiments, quality control/management, and reliability engineering. R is a free software environment for statistical computing and graphics that is supported by the R Foundation for Statistical Computing. R package has many functions and libraries for statistical engineering. We can use R package as a useful tool for statistical engineering. This paper shows the applications of R package for statistical engineering and suggests a R Task View for statistical engineering.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.194-203
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• 2008

Iterative learning control (ILC) is a simple and effective method for the control of systems that perform the same task repetitively. ILC algorithm uses the repetitiveness of the task to track the desired trajectory. In this paper, we propose a PID (proportional plus integral and derivative) type ILC update law for control discrete-time single input single-output (SISO) linear time-invariant (LTI) systems, performing repetitive tasks. In this approach, the input of controlled system in current cycle is modified by applying the PID strategy on the error achieved between the system output and the desired trajectory in a last previous iteration. The convergence of the presented scheme is analyzed and its convergence condition is obtained in terms of the PID coefficients. An optimal design method is proposed to determine the PID coefficients. It is also shown that under some given conditions, this optimal iterative learning controller can guarantee the monotonic convergence. An illustrative example is given to demonstrate the effectiveness of the proposed technique.

• Korean Journal of Computational Design and Engineering
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• v.6 no.3
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• pp.157-168
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• 2001

The description of enterprise activities is the basis fur process improvement and information system building. To describe such activities, it is necessary to model the enterprise activities from the abstraction level to the implementation level in a stepwise and integrated form. For this reason, several modeling approaches have been proposed. However, most of them lacked the stepwise or integration aspects although some of them covered overall levels. This study proposes the hierarchical modeling approach for integrating the enterprise activity model from the abstraction level to the implementation level systematically. It is composed of five modeling levels such as function level, process level, task level, document workflow level, and event flow level. This study discusses the definition and characteristics of each level and compare our modeling frame with other modeling methodologies in case study.

• Proceedings of the ESK Conference
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• 1993.10a
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• pp.252-262
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• 1993

The subject on office automation is gradually gaining more improtance due to the fact that the efficiency of office systems contribute to the increase of productivity as much as manufactoring systems themselves. For successful implementation of office automation, one must carefully plan and execute various steps such as the analysis of office tasks, personnel training, workplace design, equipment design, and so on. The previous studies related to the subject has not been concrete enough to be practically helpful for the actual realization of office automation. In this paper, a new analysis method of the office task is proposed. This analysis method is based on the Rasmussen's and Bennette's methods. The Rasmussen's method describes a way of quantifying mental workload while the Bennette's method provides a tool for the analysis of the office task. The posner's and Rouse's methods are also employed for the detailed division of tasks. The method proposed in this paper is believed to be easier for use and expected to be more helpful for us to cope with the clear definition of office tasks that is vital to successful implementation of office automation.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.100-112
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• 1996

This paper presents a design experience of a control language for coordination of a multi-robot system. To effectively program job commands, a Petrinet-type Graphical Robot Language(PGRL) is proposed, where some functions, such as concurrency and synchronization, for coordination among tasks can be easily programmed.In our system, the proposed task commands of PGRL are implemented by employing formal model languages, which are composed of three modules, sensory, data handling, and action module. It is expected that by using our proposed PGRL and formal languages, one can easily describe a job or task, and hence can effectively operate a complex real-time and concurrent system. The control system is being implemented by using VME-based 32-bit microprocessor boards for supervisory, each module controller(arm, hand, leg, sensor data processing module) and a real time multi-tasking operating system(VxWorks). (author). 17 refs., 16 figs., 2 tabs.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.40-47
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• 2022

A reward function suitable for a task is required to manipulate objects through reinforcement learning. However, it is difficult to design the reward function if the ample information of the objects cannot be obtained. In this study, a demonstration-based object manipulation algorithm called stochastic exploration guided by demonstration (SEGD) is proposed to solve the design problem of the reward function. SEGD is a reinforcement learning algorithm in which a sparse reward explorer (SRE) and an interpolated policy using demonstration (IPD) are added to soft actor-critic (SAC). SRE ensures the training of the critic of SAC by collecting prior data and IPD limits the exploration space by making SEGD's action similar to the expert's action. Through these two algorithms, the SEGD can learn only with the sparse reward of the task without designing the reward function. In order to verify the SEGD, experiments were conducted for three tasks. SEGD showed its effectiveness by showing success rates of more than 96.5% in these experiments.

• Design & Manufacturing
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• v.17 no.4
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• pp.57-62
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• 2023

As a representative method for mass production, a multi-cavity type mold capable of simultaneously molding products of the same shape can be applied. It has the advantage of improving the productivity from several times to several tens of times, but it may cause disadvantages which is the quality deviation with each cavity. This study, therefore, has tried to increase the cavity filling balance by using a melt flipper and a flow distance control part in the runner part of the mold. Along with this, the design and manufacturing of air vents during injection molding have been verified through experimental methods to achieve a higher level of multi-cavity filling balance and dimensional accuracy.