• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8A
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• pp.794-804
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• 2008

In this paper, we analyze the performance of probabilistic slotted anti-collision algorithm used in EPCglobal Class-1 Generation-2 (Gen2). To increase throughput and system efficiency, and to decrease tag identification time and collision ratio, we propose new tag anti-collision algorithms, which are FAFQ (fired adjustable flamed Q) algorithm and AAFQ (adaptive adjustable framed Q) algorithm, by using QueryAdjust command. We also propose grouping method based on Gen2 to improve the efficiency of tag identification. The simulation results show that all the proposed algorithms outperform Q algorithm, and AAFQ algorithm performs the best. That is, AAFQ has an increment of 5% of system efficiency and a decrement of 4.5% of collision ratio. For FAFQ and AAFQ algorithm, the performance of grouping method is similar to that of ungrouping method. However, for Q algorithm in Gen2, grouping method can increase throughput and system efficiency, and decrease tag identification time and collision ratio compared with ungrouping method.

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1431-1438
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• 2004

Reinforcement learning learns policies for accomplishing a task's goal by experience through interaction between agent and environment. Q-learning, basis algorithm of reinforcement learning, has the problem of curse of dimensionality and slow learning speed in the incipient stage of learning. In order to solve the problems of Q-learning, new function approximation methods suitable for reinforcement learning should be studied. In this paper, to improve these problems, we suggest Fuzzy Q-Map algorithm that is based on online fuzzy clustering. Fuzzy Q-Map is a function approximation method suitable to reinforcement learning that can do on-line teaming and express uncertainty of environment. We made an experiment on the mountain car problem with fuzzy Q-Map, and its results show that learning speed is accelerated in the incipient stage of learning.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1299-1302
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• 2003

In this paper, we propose new method which can provide user the path to the target place efficiently. It stores the state of roads to target place as the form of Q-table and finds the proper path using Q-table.0-table is updated by the information about real traffic which is reported by users. This method can provides the proper path, using less storage and less computation time than the conventional method which stores entire road traffic information and finds the path by graph search algorithm.

• Communications for Statistical Applications and Methods
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• v.10 no.2
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• pp.433-443
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• 2003

In this study, we provide a comparison of multivariate Q-techniques in the up-to-date versions of SAS, SPSS, Minitab and S-plus well known to those who study statistics. We can analyze data through the direct Input method(command) in SAS and use of menu method in SPSS, Minitab and S-plus. The analysis performance method is chosen by the high frequency of use. Widely we compare with each Q-techniques form according to input data, input option, statistical chart and statistical output.

• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.187-191
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• 2000

In the analysis of repeated measurements, multivariate regression models that account for the correlations among the observations from the same subject are widely used. Like the usual univariate regression models, these multivariate regression models also need some model diagnostic procedures. In this paper, we propose a simple graphical method to detect outliers and to investigate the goodness of model fit in repeated measures data. The graphical method is based on the quantile-quantile(Q-Q) plots of the $X^2$ distribution and the standard normal distribution. We also propose diagnostic measures to detect influential observations. The proposed method is illustrated using two examples.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.94-96
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• 2009

In this paper, we present the Q-learning method for adaptive traffic signal control on the basis of multi-agent technology. The structure is composed of sixphase agents and one intersection agent. Wireless communication network provides the possibility of the cooperation of agents. As one kind of reinforcement learning, Q-learning is adopted as the algorithm of the control mechanism, which can acquire optical control strategies from delayed reward; furthermore, we adopt dynamic learning method instead of static method, which is more practical. Simulation result indicates that it is more effective than traditional signal system.

• Geophysics and Geophysical Exploration
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• v.21 no.1
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• pp.54-60
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• 2018

The data acquired from seismic exploration can be used to detect the existence of oil and gas resources through appropriate processing and interpretation. The seismic attributes indicating the existence of resources are extracted from amplitude information, where the Q-factor representing intrinsic attenuation plays an useful role of hydrocarbon indicator. So, the accuracy of Q-factor estimation is very important to investigate the existence of resources. In this study, we calculated the Q-factor and analyzed the error rate through a numerical example. To mimic real data, random noise was added to the synthetic data. With the noise-added data, the Q-factor was estimated and the error rate was analyzed by using the spectral ratio method (SRM) and peak frequency shift method (PFSM). Both methods provided a relatively accurate Q-factor when the signal-to-noise ratio was 90 dB. However, the peak frequency shift method (PFSM) produced better results than the spectral ratio method (SRM) as the level of random noise increased.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.103-113
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• 2021

In this study, the Q method is used to investigate the types of perceptions of liberal arts education perceived by college students and to investigate the characteristics of each type. 33 Q samples were extracted from the Q population collected through literature research, open questionnaires, and deep interviews. Q classification was conducted for 27 students of A University located in B City. The data was analyzed using the QUANL program. In the research, the types of awareness of liberal arts education were derived as "pursuit of various experiences", "pursuit of practical studies", "pursuit of accident expansion", and "pursuit of social change". The results of this study re-establish the meaning of liberal arts education in university education and suggest that it is necessary to consider various educational contents and teaching learning methods.

• The Korean Journal of Ecology
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• v.17 no.4
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• pp.471-484
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• 1994

The forest vegetation types and their structural characteristics in Mt. $Mud\v{u}ng$ were investigated by classification method and ordination method. The forest was classified into 7 communities by ristic composition table: Quercus monogolica community, Q. serrata community, Q.acutissima community, Q.variabilis community, Q.dentata community, Pinus densiflora community and Frainus mandshurica community. Considering the moisture gradient, two kinds of distributuin pattern were shown as follows; F. mandshurica, Q. acturissima, Platycarya strobilacea and Staphylea bumalda were distribute at moist habitats, while Q. monogolica, P. densiflora and Q.variabilis at dry habitats. In continuum analysis, each population occupied different distribution area but it was continuously overlapped. On the successional trends of tree species, it is postulated that Q. mongolica species might dominate the altitudinal zone over 700m.

• Journal of the Korean Data and Information Science Society
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• v.9 no.1
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• pp.11-18
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• 1998

In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using the correlation coefficient(r). So, the measurement for agreement was determined by Bland & Altman's method recently. In this article, we will analyse the measurement for agreement by using Q-Q plot and by applying Bland and Altman's method through graph. And we will show characteristics for these techniques.