• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.11a
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• pp.675-678
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• 2004

Ozone is usually generated from oxygen gas using a silent discharge apparatus and its concentration is less then 10 mol%. An ozone condensation system is constructed for metal oxide thin film fabrication. Ozone is condensed by the adsorption method, which is widely used for the growth of oxidation thin films such as superconductor. Highly condensed ozone is analyzed by three methods; ultraviolet absorption, thermal decomposition and Q-mass analyzing methods. Thermal decomposition method is most effective in the highly condensed ozone region and its method is superior to Q-mass analyzer for determining ozone concentration because of the simplicity of the method.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.11a
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• pp.579-582
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• 2003

Ozone is usually generated from oxygen gas using a silent discharge apparatus and its concentration is less then 10 mol%. Ozone is condensed by the adsorption method, which is widely used for the growth of oxidation thin films such as superconductor. Highly condensed ozone is analyzed by three methods; ultraviolet absorption, thermal decomposition and Q-mass analyzing methods. Thermal decomposition method is most effective in the highly condensed ozone region and its method is superior to Q-mass analyzer for determining ozone concentration because of the simplicity of the method.

• Journal of Korea Multimedia Society
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• v.11 no.3
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• pp.353-363
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• 2008

A multi-agent system has a longer learning period and larger state-spaces than a sin91e agent system. In this paper, we suggest a new method to reduce the learning time of Nash Q-learning in a multi-agent environment. We apply Macro-actions to Nash Q-learning to improve the teaming speed. In the Nash Q-teaming scheme, when agents select actions, rewards are accumulated like Macro-actions. In the experiments, we compare Nash Q-learning using Macro-actions with general Nash Q-learning. First, we observed how many times the agents achieve their goals. The results of this experiment show that agents using Nash Q-learning and 4 Macro-actions have 9.46% better performance than Nash Q-learning using only 4 primitive actions. Second, when agents use Macro-actions, Q-values are accumulated 2.6 times more. Finally, agents using Macro-actions select less actions about 44%. As a result, agents select fewer actions and Macro-actions improve the Q-value's update. It the agents' learning speeds improve.

• Journal of Pharmaceutical Investigation
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• v.39 no.1
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• pp.1-6
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• 2009

To overcome the stability problem of hydrophilic quantum dot (Q-dot), cellular uptake of hydrophobic instead of hydrophilic Q-dot was studied in the hope to find a simple method to use Q-dot as a cellular imaging probe. Hydrophobic Q-dot and poly-L-lactic acid (PLLA) were co-dissolved in chloroform to prepare stable films. Due to the cellular compatibility of PLLA, adherent cells were cultured on the film to observe the degree of Q-dot uptake and cytotoxicity of the prepared films. The results show that Q-dots were absorbed into NIH3T3 and EMT6 cells. Cellular uptake was also observed when hydrophobic Q-dots were coated directly on a glass plate. PLLA/Q-dot film and Q-dot coated on glass plate did not show major cytotoxicity. In vivo tumor model was also used to show the uptake of Q-dot from the PLLA/Q-dot film to the tumor site.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.1
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• pp.148-154
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• 2005

This paper deals with performance degradations caused by RF I/Q impairments such as amplitude mismatch and phase mismatch in W-CDMA user equipment which uses QPSK(Quadrature Phase Shift Keying) modulation. The impacts of I/Q impairments on the BER(Bit Error Rate) are analyzed by using the variations of adjacent symbol distance. The BER versus amplitude mismatch and phase mismatch with QPSK constellation is reviewed through Matlab simulation. Performance degradation produced by RF I/Q impairments is measured with the implemented RF transceiver and modulation/demodulation test equipments through EVM(Error Vector Magnitude). The minimum performance requirements of amplitude mismatch and phase mismatch in W-CDMA user equipment are presented from the point of hardware implementation and the test method of the impairments is also included.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.45 no.7
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• pp.17-21
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• 2008

As with the binary pseudo-random sequences q-ary m-sequences possess very good properties which make them useful in many applications. So we construct a class of Jacket matrices by applying additive characters of the finite field $F_q$ to entries of all shifts of q-ary m-sequence. In this paper, we generalize a method of obtaining conventional Hadamard matrices from binary PN-sequences. By this way we propose Jacket matrix construction based on q-ary M-sequences.

• Mass Spectrometry Letters
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• v.7 no.2
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• pp.45-49
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• 2016

An UHPLC-ESI-qTOF-MS analytical method was developed for cyclopeptide alkaloids in the seeds of Ziziphus jujuba var. spinosa (Semen Ziziphi Spinosae), which is a commonly used herb in Chinese and Korean traditional medicines. Considering the basicity of cyclopeptide alkaloids, a specific separation method was developed for an UHPLC system. The compounds were detected by DAD and ESI-qTOF-MS, and their fragmentation patterns were also acquired by MS^E technologies. Peak-picking of major compounds was performed with nine previously isolated compounds and two reference standard compounds. Tandem MS fragmentation behaviors of type-Ia and -Ib cyclopeptide alkaloids were investigated with the acquired data to develop a strategy for dereplication of other cyclopeptide alkaloid compounds in Z. jujuba var. spinosa. Two more cyclopeptide alkaloids were tentatively identified with UHPLC-ESI-qTOF-MS using this method.

• Journal of Fisheries and Marine Sciences Education
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• v.25 no.6
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• pp.1294-1305
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• 2013

The aim of this study was to identify the attitude of nursing students' toward death using Q-methodology and to obtain baseline data to improve nursing students' education program on death. Twenty-nine participants at a college classified 40 Q-statements on a one to nine scale. The resultant Q-sort was a matrix representing the participant's operant subjectivity on the issue under consideration. The results of above procedures were analyzed by PQ Method. The results revealed that there are three types of perception about nursing students' attitudes toward the death. The categories were labeled positive-perspective, pain-avoid and preparation-deficiency. Positive-perspective individuals have a positive sense of their life and death. Thus, they would not fear death, believing in an after-life world, while being positive towards donation of intestines after death. Pain-avoid individuals hope life and death without pain. Preparation-deficiency individuals are unprepared to die. In conclusion, this study discovers three types of the perception about nursing students' attitudes toward the perception of death. By identifying the nature of each of these types, this study can be useful to develop efficient strategies for education program on death.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.15-20
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• 2023

Machine learning is comprised of supervised learning, unsupervised learning and reinforcement learning as the type of data and processing mechanism. In this paper, as input and output are unclear and it is difficult to apply the concrete modeling mathematically, reinforcement learning method are applied for crawling robot in this paper. Especially, Q-Learning is the most effective learning technique in model free reinforcement learning. This paper presents a method to implement a crawling robot that is operated by finding the most optimal crawling method through trial and error in a dynamic environment using a Q-learning algorithm. The goal is to perform reinforcement learning to find the optimal two motor angle for the best performance, and finally to maintain the most mature and stable motion about EV3 Crawling robot. In this paper, for the production of the crawling robot, it was produced using Lego Mindstorms with two motors, an ultrasonic sensor, a brick and switches, and EV3 Classroom SW are used for this implementation. By repeating 3 times learning, total 60 data are acquired, and two motor angles vs. crawling distance graph are plotted for the more understanding. Applying the Q-learning reinforcement learning algorithm, it was confirmed that the crawling robot found the optimal motor angle and operated with trained learning, and learn to know the direction for the future research.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.77-82
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• 2004

Reinforcement learning takes reward about selecting action when agent chooses some action and did state transition in Present state. this can be the important subject in reinforcement learning as temporal-credit assignment problems. In this paper, by new meta heuristic method to solve hard combinational optimization problem, examine Ant-Q learning method that is proposed to solve Traveling Salesman Problem (TSP) to approach that is based for population that use positive feedback as well as greedy search. And, suggest Ant-TD reinforcement learning method that apply state transition through diversification strategy to this method and TD-error. We can show through experiments that the reinforcement learning method proposed in this Paper can find out an optimal solution faster than other reinforcement learning method like ACS and Ant-Q learning.