• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.12
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• pp.2541-2546
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• 2009

In the anti-collision scheme proposed by EPCglobal Class-1 Gen-2 standard, the frame size for a query round is determined by Q-algorithm. In the Q-algorithm, the reader calculates a frame size without estimating the number of tags in it's identification range. It uses only the slot status. Therefore, the Q-algorithm has advantage that the reader's algorithm is simpler than other DFSA algorithms. However, the standard does not define an optimized parameter value for adjusting the frame size. In this paper, we propose the optimized parameter values for minimizing the identification time by various computer simulations.

• The KIPS Transactions:PartC
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• v.9C no.2
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• pp.163-172
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• 2002

Java Card API porvide benifit for development program based on smart card using limmited resource. This APIs does not support arithmetic operations such as modular arithmetic, greatest common divisor calculation, and generation and certification of prime number, which is necessary arithmetic in PKI algorithm implementation. In this paper, we implement class BigInteger acted in the Java Card platform because that Java Card APIs does not support class BigInteger necessary in implementation of PKI algorithm.

• Educational Technology International
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• v.15 no.2
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• pp.71-88
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• 2014

A variety of studies to predict students' performance have been conducted since educational data such as web-log files traced from Learning Management System (LMS) are increasingly used to analyze students' learning behaviors. However, it is still challenging to predict students' learning achievement in blended learning environment where online and offline learning are combined. In higher education, diverse cases of blended learning can be formed from simple use of LMS for administrative purposes to full usages of functions in LMS for online distance learning class. As a result, a generalized model to predict students' academic success does not fulfill diverse cases of blended learning. This study compares two blended learning classes with each prediction model. The first blended class which involves online discussion-based learning revealed a linear regression model, which explained 70% of the variance in total score through six variables including total log-in time, log-in frequencies, log-in regularities, visits on boards, visits on repositories, and the number of postings. However, the second case, a lecture-based class providing regular basis online lecture notes in Moodle show weaker results from the same linear regression model mainly due to non-linearity of variables. To investigate the non-linear relations between online activities and total score, RF (Random Forest) was utilized. The results indicate that there are different set of important variables for the two distinctive types of blended learning cases. Results suggest that the prediction models and data-mining technique should be based on the considerations of diverse pedagogical characteristics of blended learning classes.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.49-54
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• 2024

Data imbalance is a common issue encountered in classification problems, stemming from a significant disparity in the number of samples between classes within the dataset. Such data imbalance typically leads to problems in classification models, including overfitting, underfitting, and misinterpretation of performance metrics. Methods to address this issue include resampling, augmentation, regularization techniques, and adjustment of loss functions. In this paper, we focus on loss function adjustment, particularly comparing the performance of various configurations of loss functions (Cross Entropy, Balanced Cross Entropy, two settings of Focal Loss: 𝛼 = 1 and 𝛼 = Balanced, Asymmetric Loss) on Multi-Class black-box video data with imbalance issues. The comparison is conducted using the I3D, and R3D_18 models.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.1
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• pp.61-68
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• 2010

In this work, a reduced size 20W quasi class-E Power Amplifier(PA) with defected ground structure load-network is presented for WCDMA base station application. Harmonic impedances required for the class E operation are satisfied by applying the dumbbell and the asymmetric spiral DGS. Open impedance for 2nd harmonic frequency which has the highest power and nearly short impedances for other higher order harmonics are provided by the proposed DGS load-network. The maximum Power Added Efficiency(PAE) of 70.2 % at the output power of 43.1 dBm with the saturated power gain of 12.7 dB is achieved by the proposed quasi class-E PA, which is comparable to the performance of the reference class-E PA. Total size of the proposed class-E PA is only $50{\times}50\;mm^2$ and much smaller than the conventional class-E PA that is loaded with a number of open stubs.

• The korean journal of orthodontics
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• v.35 no.6 s.113
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• pp.420-432
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• 2005

Bolton analysis is widely used to predict tooth size discrepancy. but its accuracy has been challenged. The purpose of this study was to describe true anterior tooth size discrepancies among orthodontic patients and to evaluate the factors that affect true anterior tooth size discrepancies. The subjects consisted of 80 patients with varying malocclusions (Class I. Class II. Class III. and Class III surgery) who were treated orthodontically. Pre-treatment models. set-up models from post-treatment models. and lateral cephalometric radiographs were analyzed The results were as follows. The means. the standard deviations. and ranges of anterior Bolton ratio in the present study were somewhat higher than those of Bolton's samples and Korean normal samples. The number of patients showing maxillary deficiency was larger than that of patients showing maxillary excess in view of true anterior discrepancies. There was a significant difference between anterior Bolton discrepancy from pre-treatment models and true anterior discrepancy from set-up models (p < 0.05) There was no significant difference in true anterior discrepancies among malocclusion groups (p > 0.05). And there was also no significant difference between the male and female groups (p> 0.05). Overbite and the incisal edge thickness of maxillary anterior teeth have little relationship with true anterior discrepancies. Multiple regression analysis showed that true anterior discrepancy was mainly determined by anterior Bolton ratio, upper incisor to occlusal plane angle after treatment. interincisal angle after treatment. and upper right lateral incisor width.

• Journal of the Korean Geographical Society
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• v.46 no.6
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• pp.707-723
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• 2011

The purpose of this study was to quantitatively evaluate the effectiveness of learning management systems (LMS) in the physical geography class. The study adopted the experimental design and three classes participated in this study. The first class was controlled using only classroom lectures, the second class used PPT slides along with the classroom lectures, and the third class used online video clips along with the lectures. The experiments were conducted from the Spring Semester 2007 to the Spring Semester 2008 for the introductory physical geography course. The study results showed that online learning tools help students improve academic performance and their attitudes towards the class and the instructor. Compared to simple PowerPoint slides, voice recording attached to the visual lecture slide materials enhanced students' motivation. Class lectures with lecture slides did not improve students' scores. However, when the visual materials were combined with voice recording, the number of internet access to online class materials increased, and class attendance and students' final grades were improved. Based on the results, the instructional design model that combines classroom and online learning was suggested.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.157-168
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• 2023

Image segmentation and supervised classification techniques are widely used to monitor the ground surface using high-resolution remote sensing images. In order to classify various objects, a process of defining a class corresponding to each object and selecting samples belonging to each class is required. Existing methods for extracting class samples should select a sufficient number of samples having similar intensity characteristics for each class. This process depends on the user's visual identification and takes a lot of time. Representative samples of the class extracted are likely to vary depending on the user, and as a result, the classification performance is greatly affected by the class sample extraction result. In this study, we propose an image classification technique that minimizes user intervention when extracting class samples by applying the histogram back-projection technique and has consistent intensity characteristics of samples belonging to classes. The proposed classification technique using histogram back-projection showed improved classification accuracy in both the experiment using hue subchannels of the hue saturation value transformed image from Compact Advanced Satellite 500-1 imagery and the experiment using the original image compared to the technique that did not use histogram back-projection.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.475-486
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• 2006

Space time series data can be viewed either as a set of time series collected simultaneously at a number of spatial locations or as sets of spatial data collected at a number of time points. The major purpose of this article is to formulate a class of space time autoregressive moving average (STARMA) model, to discuss some of the their statistical properties such as model identification approaches, some procedure for estimation and the predictions. For illustration, we apply this STARMA model to the mumps data. The data set of mumps cases consists of the number of cases of mumps reported from twelve states monthly over the years 1969-1988.

• Journal of the Korea Computer Industry Society
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• v.2 no.10
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• pp.1301-1308
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• 2001

In this paper, some interesting aspects of Grzegorczyk classes $\xi\sum{n}$, n$\geq$0 & $\sum$= { 1, 2 } of word-theoretic primitive recursive functions are observed including the classes of its corresponding predicates ($\xi\sum{n}$)* In particular, the small classes $\xi\sum{n}$($n\leq2$) are very incomparable to the corresponding small classes $\xi\sum{n}$ where $\xi\sum{n}$ is the number-theoretic Grzegorczyk classes. As one of some interesting aspects of the small classes, we show that the equivalence problem in $\xi\sum{0}$is undecidable.