• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.10-19
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• 2007

In this paper, Class-1 Air-interface protocols of EPCglobal applied to RFID system in UHF band are analyzed, and the standard anticollision algorithms are realized. Also, the improved anticollision algorithms of the Class-1 Generation-1 and Generation-2 protocol are proposed and the performances of anticollision algorithms are compared. As the results, reduction ratio of total tag recognition time of the improved Generation-1 algorithm is 54.5% for 100 tags and 63.4% for 1000 tags with respect to standard algorithm, respectively. And the reduction ratio of the improved Generation-2 algorithm is 7.9% for 100 tags and 11.7% for 1000 tags. Total recognition times of the improved algorithms are shorter than those of standard algorithms according to increasing the number of tag. Therefore, the improved anticollision algorithm proposed in this paper is the advanced method improving the performance of tag recognition in the RFID system.

• The Journal of Korean Institute for Practical Engineering Education
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• v.3 no.1
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• pp.25-31
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• 2011

These days, almost all of the embedded systems have microprocessors or micro-controllers in them as their brains. So microprocessor related subjects become very important and most engineering departments have those kinds of subjects in their curriculums with practice hours. However, in most universities in Korea, the number of students in a class is more than 40 and only one teaching assistant is assigned to the class. So it is very hard job to find out an appropriate method to evaluate the students' achievements in their practice hours fairly. In this study, the author introduces some suggestions for the evaluation of the students' achievements in microprocessor practice courses. In addition to it, the author also introduces some guidelines for contents of microprocessor related subjects.

• Bulletin of the Korean Chemical Society
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• v.35 no.7
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• pp.2057-2064
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• 2014

Thermochemical sulfate reduction (TSR) was conducted in autoclave on the system of crude oil and $MgSO_4$ at different temperatures. Gas chromatography pulsed flame photometric detector (GC-PFPD) was used to detected the composition of organic sulfur compounds in oil phase products. The results of the analysis indicate that with increased temperature, the contents of organic sulfur compounds with high molecular weight and thermal stability, such as benzothiophenes and dibenzothiophenes, gradually became dominated. In order to gain greater insight into the formation and distribution of organic sulphur compounds from TSR, positive ion electrospray Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was used in detecting the detailed elemental composition and distribution of them. The mass spectra showed that the mass range of sulfur compounds was 200-550 Da. Four sulfur class species, $S_1$, $N_1S_1$, $O_1S_1$ and $O_2S_1$, were assigned in the positive-ion spectrum. Among the identified sulfur compounds, the $S_1$ class species was dominant. The most abundant $S_1$ class species increase associated with the DBE value and carbon number increasing which also indicates the evolution of organic sulfur compounds in TSR is from the labile series to the stable one. In pure blank pyrolysis experiments with crude oil cracking without TSR, different composition and distribution of organic sulfur compounds in oil phase products were seen from mass spectra in order to evaluate their pyrolysis behaviors without $MgSO_4$. FT-IR and XRD were used in analyzing the products of solid phases. Two distinct crystallographic phases MgO and $MgSO_4$ are found to coexist in the products which demonstrated the transformation of inorganic sulfur compounds into organosulfur compounds exist in TSR.

• Journal of The Korean Astronomical Society
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• v.40 no.4
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• pp.99-106
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• 2007

Statistical analyses were performed to investigate the relative success and accuracy of daily maximum X-ray flux (MXF) predictions, using both multilinear regression and autoregressive time-series prediction methods. As input data for this work, we used 14 solar activity parameters recorded over the prior 2 year period (1989-1990) during the solar maximum of cycle 22. We applied the multilinear regression method to the following three groups: all 14 variables (G1), the 2 so-called 'cause' variables (sunspot complexity and sunspot group area) showing the highest correlations with MXF (G2), and the 2 'effect' variables (previous day MXF and the number of flares stronger than C4 class) showing the highest correlations with MXF (G3). For the advanced three days forecast, we applied the autoregressive timeseries method to the MXF data (GT). We compared the statistical results of these groups for 1991 data, using several statistical measures obtained from a $2{\times}2$ contingency table for forecasted versus observed events. As a result, we found that the statistical results of G1 and G3 are nearly the same each other and the 'effect' variables (G3) are more reliable predictors than the 'cause' variables. It is also found that while the statistical results of GT are a little worse than those of G1 for relatively weak flares, they are comparable to each other for strong flares. In general, all statistical measures show good predictions from all groups, provided that the flares are weaker than about M5 class; stronger flares rapidly become difficult to predict well, which is probably due to statistical inaccuracies arising from their rarity. Our statistical results of all flares except for the X-class flares were confirmed by Yates' $X^2$ statistical significance tests, at the 99% confidence level. Based on our model testing, we recommend a practical strategy for solar X-ray flare predictions.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.1
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• pp.59-64
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• 2015

In this paper, we found the usefulness of the deep belief network (DBN) in the fields of brain-computer interface (BCI), especially in relation to imagined speech. In recent years, the growth of interest in the BCI field has led to the development of a number of useful applications, such as robot control, game interfaces, exoskeleton limbs, and so on. However, while imagined speech, which could be used for communication or military purpose devices, is one of the most exciting BCI applications, there are some problems in implementing the system. In the previous paper, we already handled some of the issues of imagined speech when using the International Phonetic Alphabet (IPA), although it required complementation for multi class classification problems. In view of this point, this paper could provide a suitable solution for vowel classification for imagined speech. We used the DBN algorithm, which is known as a deep learning algorithm for multi-class vowel classification, and selected four vowel pronunciations:, /a/, /i/, /o/, /u/ from IPA. For the experiment, we obtained the required 32 channel raw electroencephalogram (EEG) data from three male subjects, and electrodes were placed on the scalp of the frontal lobe and both temporal lobes which are related to thinking and verbal function. Eigenvalues of the covariance matrix of the EEG data were used as the feature vector of each vowel. In the analysis, we provided the classification results of the back propagation artificial neural network (BP-ANN) for making a comparison with DBN. As a result, the classification results from the BP-ANN were 52.04%, and the DBN was 87.96%. This means the DBN showed 35.92% better classification results in multi class imagined speech classification. In addition, the DBN spent much less time in whole computation time. In conclusion, the DBN algorithm is efficient in BCI system implementation.

• Journal of Korean Elementary Science Education
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• v.30 no.4
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• pp.468-481
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• 2011

This research is to observe and analyze the student interactions when inquiry problems were generated along with the students by using asynchronous discussion methods with the class bulletin board. For this research, 10 students from a single class of 6th grade were selected. The subject students were divided into 2 groups by cognitive levels. After the students were submitted the 4 problem situations for 1 week each, the discussion process was analyzed. The research results are as follows. First, the analysis of the step by step interactive discussion showed that several students answered for the question from a single student while discussing first for the question and answer in a form of a question with many multiple answers without any connections with the previously asked questions. At the end of the discussion, one to two students answered to a question by taking turns and the type of discussion changed to one question - one answer type by answering to the person who spoke prior to the next. Second, the discussion took place with the students in the transitional stage speaking in time in order, to provide comments to the bottom of the linear form and students in the formal operational stage students speaking in temporal order, regardless of the number of comments in the direction of the radiation(mind map) forms. The individual comment speaking rates were similar in the two groups so the students were able to speak indiscriminately.

• School Mathematics
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• v.12 no.4
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• pp.507-530
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• 2010

The purpose of this study was to help teachers for their teaching practice by analyzing the excellent lesson videos. To analyze the lesson videos between teacher and students, the researchers classified excellent lesson classes into four types as 'Discourse type', 'Representation type', 'Operation type' and 'Complex type' by mathematical communication pattern and kept close watch each lesson videos. Mathematical communication of the best discourse type classroom was analyzed in terms of questioning, explaining, and the sources of mathematical ideas. As a result, the number of Discourse type classes was 6. Operation type classes were 16 owing to characteristic of elementary class. Representation type class was 1 and Complex type class was 1. The Classes excluding Operation type was more planned by teachers. Teachers need to know about mathematical communication accurately because they designed just 5 lesson plan considering mathematical communication of students and only one of the lessons has the intellectual purpose of communication. Furthermore teachers should reflect questioning for student-to-student in their lesson plan.

• Journal of Korean Elementary Science Education
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• v.26 no.3
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• pp.252-259
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• 2007

The purpose of this study was to examine the status and science teachers' perceptions of classes for those gifted in science in elementary school. For this purpose, a number of questions were posed to teachers : 27-item-questionnaires were given to 38 teachers of students gifted in science in elementary schools located in Incheon province. The results of this study were as follows : 1. most elementary teachers were in charge of classes containing students gifted in science, but this was the case with only a few secondary teachers. Therefore, it appears to be more necessary to educate elementary teachers who majored in science content and gifted education. 2. In addition, most teachers had positive perceptions of the needs, attitudes and environments needed for gifted education. Most of them attended 60-hour training programs on gifted education. They thought that it was helpful in understanding the characteristics of gifted students, but they wanted to learn more about actual pedagogical methods through such programs. 3. The teaching methods used in classes for those gifted in science were mainly experimental activities, but there were few opportunities for creative problem solving and project learning. This may be due to limited class time of about one hour every two weeks in this class. 4. When the materials used in class were first developed, they mainly used materials made by the city board of education and selected the theme of interest by themselves. Therefore, there may be problems of duplication of materials or systems regarding the science contents for one year. 5. Furthermore, the themes of the materials used were mostly related in terms of the contents of textbooks than more generally. When planning and managing the classes for those gifted in science, the above points should be considered in order to improve the education of those students gifted in science.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.53-60
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• 2012

Nearest-neighbor classification predicts the class of an input data with the most frequent class among the near training data of the input data. Even though nearest-neighbor classification doesn't have a training stage, all of the training data are necessary in a predictive stage and the generalization performance depends on the quality of training data. Therefore, as the training data size increase, a nearest-neighbor classification requires the large amount of memory and the large computation time in prediction. In this paper, we propose a prototype selection algorithm that predicts the class of test data with the new set of prototypes which are near-boundary training data. Based on Tomek links and distance metric, the proposed algorithm selects boundary data and decides whether the selected data is added to the set of prototypes by considering classes and distance relationships. In the experiments, the number of prototypes is much smaller than the size of original training data and we takes advantages of storage reduction and fast prediction in a nearest-neighbor classification.

• Journal of Intelligence and Information Systems
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• v.14 no.3
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• pp.133-154
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• 2008

The data imbalance problem which can be uncounted in data mining classification problems typically means that there are more or less instances in a class than those in other classes. In order to solve the data imbalance problem, there has been proposed a number of techniques based on re-sampling with replacement, adjusting decision thresholds, and adjusting the cost of the different classes. In this paper, we study the feasibility of the combination usage of the techniques previously proposed to deal with the data imbalance problem, and suggest a combination method using genetic algorithm to find the optimal combination ratio of the techniques. To improve the prediction accuracy of a minority class, we determine the combination ratio based on the F-value of the minority class as the fitness function of genetic algorithm. To compare the performance with those of single techniques and the matrix-style combination of random percentage, we performed experiments using four public datasets which has been generally used to compare the performance of methods for the data imbalance problem. From the results of experiments, we can find the usefulness of the proposed method.