• Journal of Satellite, Information and Communications
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• v.12 no.1
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• pp.1-5
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• 2017

In this paper, multiuser detector (MUD) based on radial basis function (RBF) is proposed and simulated for a multicode direct sequence/code division multiple access (DS/CDMA) system in a multipath fading channel. The performance of RBF-based MUD is compared with that of many suboptimal multiuser detectors in terms of bit error probability. From the simulation results, it is confirmed that the RBF-based MUD outperforms decorrelating detector, and achieves near-optimum performance under various environments. The results in this paper can be applied to design of MUD for a multicode DS/CDMA system.

• KIISE Transactions on Computing Practices
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• v.24 no.3
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• pp.113-121
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• 2018

Position encoding is a method of applying weights according to position of words that appear in a sentence. Pointer networks is a deep learning model that outputs corresponding index with an input sequence. This model can be applied to coreference resolution using attribute. However, the pointer networks has a problem in that its performance is degraded when the length of input sequence is long. To solve this problem, we proposed two contributions to resolve the coreference. First, we applied position encoding and dynamic position encoding to pointer networks. Second, we stack deeply layers of encoder to make high-level abstraction. As results, the position encoding based stacked pointer networks model proposed in this paper had a CoNLL F1 performance of 71.78%, which was improved by 6.01% compared to vanilla pointer networks.

• Journal of the Korea Society of Computer and Information
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• v.14 no.10
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• pp.159-166
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• 2009

A nature immunity system responds sensitively to an external invasion with various functions in a lot of bodies, besides it there is a function to remember information to have been currently infected. we propose a hybrid model similar to immune system which combine with the antibody which applied genetic algorithm as select antibody and the arbitrary abnormal system call sequence that applied negative selection of a nature immunity system. A proposed model uses an arbitrary abnormal system Kol sequence in order to reduce a positive defect and a negative defect. Data used to experiment are send mail data processed UNM (University of New Maxico). The negative defect that an experiment results proposal model judged system call more abnormal than the existing negative selection to normal system call appeared 0.55% low.

• The KIPS Transactions:PartD
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• v.18D no.1
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• pp.67-80
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• 2011

On an automated business document processing system maintaining financial data, errors on query based retrieval of numbers are critical to overall performance and usability of the system. Automatic spelling correction methods have been emerged and have played important role in development of information retrieval system. However scope of the methods was limited to the symbols, for example alphabetic letter strings, which can be reserved in the form of trainable templates or custom dictionary. On the other hand, numbers, a sequence of digits, are not the objects that can be reserved into a dictionary but a pure markov sequence. In this paper we proposed a new OCR model for spelling correction for numbers using the multiple streams and the context based correction on top of probabilistic information retrieval framework. We implemented the proposed error correction model as a sub-module and integrated into an existing automated invoice document processing system. We also presented the comparative test results that indicated significant enhancement of overall precision of the system by our model.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.49-60
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• 2006

We propose a method to use a state transition model so that the sensing object can be distinguished through classification of signal patterns sensed by a sensor array. Focusing on the design of the model that is able to distinguish the sensed object more exactly, we present an idea in which the modeling elements, 'states' and 'transitions' are defined as each same-sized angle intervals into which the angle interval $(-\frac{\pi}{2},\frac{\pi}{2})$ is divided and the angle differences between adjacent signal values on sampling signal value sequence value sequence sensed from the sensor array in the uniform time interval, respectively. In addition we show the usefulness of our model through experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.786-795
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• 2002

In this paper, we present a histogram and moment-based vidoe scencd change detection technique using hierarchical Hidden Markov Models(HMMs). The proposed method extracts histograms from a low-frequency subband and moments of edge components from high-frequency subbands of wavelet transformed images. Then each HMM is trained by using histogram difference and directional moment difference, respectively, extracted from manually labeled video. The video segmentation process consists of two steps. A histogram-based HMM is first used to segment the input video sequence into three categories: shot, cut, gradual scene changes. In the second stage, a moment-based HMM is used to further segment the gradual changes into a fade and a dissolve. The experimental results show that the proposed technique is more effective in partitioning video frames than the previous threshold-based methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.8
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• pp.1422-1430
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• 2016

Researches for oceans are limited to military purpose such as underwater sound detection and tracking system. Underwater acoustic communications with low-probability-of-interception (LPI) covert characteristics were received much attention recently. Covert communications are conducted at a low received signal-to-noise ratio to prevent interception or detection by an eavesdropper. This paper proposed optimal covert communication model based on direct sequence spread spectrum for underwater environments. Spread spectrum signals may be used for data transmission on underwater acoustic channels to achieve reliable transmission by suppressing the detrimental effect of interference and self-interference due to jamming and multipath propagation. The characteristics of the underwater acoustic channel present special problems in the design of covert communication systems. To improve performance and probability of interception, we applied BCJR(Bahl, Cocke, Jelinek, Raviv) decoding method and the direct sequence spread spectrum technology in low SNR. Also, we compared the performance between conventional model and proposed model based on turbo equalization by simulation and lake experiment.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.4
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• pp.38-47
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• 2020

A parametric study for analytical correction using measurement results was performed to minimize errors in the predictions of column shortening in RC tall building. The parameters of the column shortening analytical correction are the execution standard of analytical correction, the value of the analytical correction, and the measurement location, and the analytical correction models with the parameters were applied to the construction sequence analysis of a 41-story RC building to compare and analyze the correction effect according to the parameter. The reduction ratio of the error value for each floor was compared with the number of corrections and the total corrected value, and it was confirmed that the error tended to be minimized when the execution standard of analytical correction was performed based on a regular interval, when the analysis correction value was corrected by the error value, and when the measurement position was measured every floor. From this, it was confirmed that the most appropriate analytical correction model can be derived by applying multiple analytical correction models to the actual analysis model.

• Journal of the Korean earth science society
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• v.39 no.3
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• pp.260-274
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• 2018

The purpose of this study was to propose curriculum and teaching sequence for seasonal change by exploring a learning progression. For the purpose, 4 steps of construct modeling approach (specifying construct, item design, outcome space, and measurement model) proposed by Wilson (2005) was applied. In the stage of specifying construct, 'length of shadow according to seasons', 'position of constellation according to seasons', 'seasons of the southern hemisphere and northern hemisphere', 'cause and phenomenon of seasonal change' were selected as the subconstructs of seasonal changes, and constructed a construct map showing the level of development from level 1 to level 4 for each subconstruct based on the results of the previous research. In the item design stage, we developed five assessment items consisting of 3 items in the form of C-E (choose and explain) and two items in the form of CR (constructed response), applied it to 383 elementary, middle and high school students. In the outcome space stage, the students' responses to the assessment items were categorized based on the construct map. The categories were classified into 4 levels according to student ability and scores of 1-4 were given. In the measurement model stage, we applied the partial credit model of the Rasch model and compared whether the learning pathway created from the results of students' response coincides with the construct map. Based on the results of the research, we modified the construct map and finally created hypothetical learning progression on seasonal change. Finally, we proposed an orientation of curriculum amendment and effective teaching sequence for seasonal change.

• Journal of Korea Spatial Information System Society
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• v.10 no.2
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• pp.49-62
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• 2008

This paper proposes an indoor location positioning system for the image recognition based LBS. The proposed system is a vision-based location positioning system that is implemented the augmented reality by overlaying the location results with the view of the user. For implementing, the proposed system uses the pattern matching and location model to recognize user location from images taken by a wearable mobile PC with camera. In the proposed system, the system uses the pattern matching and location model for recognizing a personal location in image sequences. The system is estimated user location by the image sequence matching and marker detection methods, and is recognized user location by using the pre-defined location model. To detect marker in image sequences, the proposed system apply to the adaptive thresholding method, and by using the location model to recognize a location, the system can be obtained more accurate and efficient results. Experimental results show that the proposed system has both quality and performance to be used as an indoor location-based services(LBS) for visitors in various environments.