• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.11B
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• pp.1285-1296
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• 2011

Packet classification is one of the basic and important functions of the Internet routers, and it became more important along with new emerging application programs requiring real-time transmission. Since packet classification should be accomplished in line-speed on each incoming input packet for multiple header fields, it becomes one of the challenges in designing Internet routers. Various packet classification algorithms have been proposed to provide the high-speed packet classification. Hierarchical approach achieves effective packet classification performance by significantly narrowing down the search space whenever a field lookup is completed. However, hierarchical approach involves back-tracking problem. In order to solve the problem, set-pruning trie and grid-of-trie algorithms are proposed. However, the algorithm either causes excessive node duplication or heavy pre-computation. In this paper, we propose a smart set-pruning trie which reduces the number of node duplication in the set-pruning trie by the simple merging of the lower-level tries. Simulation result shows that the proposed trie has the reduced number of copied nodes by 2-8% compared with the set-pruning trie.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.5156-5161
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• 2013

In distributed spatial data stream processing, processed tuples of downstream nodes are replicated to the upstream node in order to increase the utilization of distributed nodes and to recover the whole system for the case of system failure. However, while the data input rate increases and multiple downstream nodes share the operation result of the upstream node, the data which stores to output queues as a backup can be lost since the deletion operation delay may be occurred by the delay of the tuple processing of upstream node. In this paper, the adaptive upstream backup scheme based on operation throughput in distributed spatial data stream system is proposed. This method can cut down the average load rate of nodes by efficient spatial operation migration as it processes spatial temporal data stream, and it can minimize the data loss by fluid change of backup mode. The experiments show the proposed approach can prevent data loss and can decrease, on average, 20% of CPU utilization by node monitoring.

• Korean Journal of Cognitive Science
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• v.6 no.2
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• pp.47-79
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• 1995

Since the early age of computer graphics, facial animation has been applied to various fields, and nowadays it has found several novel applications such as virtual reality(for representing virtual agents), teleconference, and man-machine interface.When we want to apply facial animation to the system with multiple participants connected via network, it is hard to animate facial expression as we desire in real-time because of the size of information to maintain an efficient communication.This paper's major contribution is to adapt 'Level-of-Detail'to the facial animation in order to solve the above problem.Level-of-Detail has been studied in the field of computer graphics to reperesent the appearance of complicated objects in efficient and adaptive way, but until now no attempt has mode in the field of facial animation. In this paper, we present a systematic scheme which enables this kind of adaptive control using Level-of-Detail.The implemented system can generate speech synchronized facial expressions with various types of user input such as text, voice, GUI, head motion, etc.

• Journal of the Korean Society for Railway
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• v.13 no.1
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• pp.119-124
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• 2010

Light rail is an electric railway system, characterized by its ability to operate single or multiple car consists (trains) along exclusive rights-of-way at ground level, on aerial structures, in subways or in streets, able to board and discharge passengers at station platforms or at street, track, or car-floor level and normally powered by overhead electrical wires. Depending upon the specific system, the light rail lends some major advantages to urban settings. The evaluation of light rail technology as a potential component of regional transit systems has been the subject of extensive studies throughout the country in the past decade. For the study, feasibility was defined as "the ability of an LRT system to achieve certain level of transportation market in comparison with other transportation alternatives." This paper describes the feasibility study to evaluate a proposed light rail development project. The minimum are those LRT systems that would met to make a project feasible for further evaluation.

• Korean Journal of Remote Sensing
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• v.33 no.1
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• pp.25-35
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• 2017

Spatial downscaling with fine resolution auxiliary variables has been widely applied to predict precipitation at fine resolution from coarse resolution satellite-based precipitation products. The spatial downscaling framework is usually based on the decomposition of precipitation values into trend and residual components. The fine resolution auxiliary variables contribute to the estimation of the trend components. The main focus of this study is on quantitative analysis of impacts of trend component estimates on predictive performance in spatial downscaling. Two regression models were considered to estimate the trend components: multiple linear regression (MLR) and geographically weighted regression (GWR). After estimating the trend components using the two models,residual components were predicted at fine resolution grids using area-to-point kriging. Finally, the sum of the trend and residual components were considered as downscaling results. From the downscaling experiments with time-series Tropical Rainfall Measuring Mission (TRMM) 3B43 precipitation data, MLR-based downscaling showed the similar or even better predictive performance, compared with GWR-based downscaling with very high explanatory power. Despite very high explanatory power of GWR, the relationships quantified from TRMM precipitation data with errors and the auxiliary variables at coarse resolution may exaggerate the errors in the trend components at fine resolution. As a result, the errors attached to the trend estimates greatly affected the predictive performance. These results indicate that any regression model with high explanatory power does not always improve predictive performance due to intrinsic errors of the input coarse resolution data. Thus, it is suggested that the explanatory power of trend estimation models alone cannot be always used for the selection of an optimal model in spatial downscaling with fine resolution auxiliary variables.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.521-532
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• 2006

Recently, many research initiatives have been underway to improve reception performance of ATSC based DTV signal in mobile channel by adopting multiple antennas. In this paper, we propose a new mobile channel model which can be applicable to any array geometry. And then we propose new channel estimation algorithm which uses PN5l1 sequence in field synch. The proposed algorithm is to estimate channel by correlating the input signal in If frequency band and finding maximum peak, which does not need complicated synchronization circuit. Finally, we propose new receiver structures which can be implemented at the front-end of the existing receiver with no modification. With computer simulation, we verify the performance of the proposed model and verify the performance of the receiver structure with computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.89-92
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• 2005

Using natural speech commands for controlling a human-robot is an interesting topic in the field of robotics. In this paper, our main focus is on the verification of a speaker who gives a command to decide whether he/she is an authorized person for commanding. Among possible dynamic features of natural speech, pitch period is one of the most important ones for characterizing speech signals and it differs usually from person to person. However, current techniques of pitch detection are still not to a desired level of accuracy and robustness. When the signal is noisy or there are multiple pitch streams, the performance of most techniques degrades. In this paper, we propose a two-level approach for pitch detection which in compare with standard pitch detection algorithms, not only increases accuracy, but also makes the performance more robust to noise. In the first level of the proposed approach we discriminate voiced from unvoiced signals based on a neural classifier that utilizes cepstrum sequences of speech as an input feature set. Voiced signals are then further processed in the second level using a modified standard AMDF-based pitch detection algorithm to determine their pitch periods precisely. The experimental results show that the accuracy of the proposed system is better than those of conventional pitch detection algorithms for speech signals in clean and noisy environments.

• Journal of Korean Academy of Nursing Administration
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• v.9 no.1
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• pp.103-112
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• 2003

Purpose : This study was designed to describe the economic awareness, economic knowledge, and attitude toward cost-effectiveness in nursing of hospital nurses. Method : The sample included 272 nurses conveniently selected from 5 tertiary care hospitals. Data were collected on general characteristics of nurses, the economic awareness level, the knowledge level of economics, and the attitude toward cost-effectiveness. Data were analyzed using SPSS PC version 10.0. Result : 1) The mean of economic awareness level of hospital nurses was 44.87 (SD=3.53) with a possible range of 5${\sim}$50. The mean of the knowledge level of economics was 58.3 (SD=11.9) with a possible range of 0${\sim}$100. 2) The mean of attitude toward cost-effectiveness in nursing was 39.95 (SD=5.01) with a possible range of 5${\sim}$50, which means moderately positive. 3) Analyzing the relationships between economic awareness level and knowledge level of economics, and attitude toward cost-effectiveness, the knowledge level of economics was positively related with the economic awareness level (r=.192, p=.002) and the attitude (r=.133, p=.029). The economic awareness level was positively related with the attitude (r=.470, p=.000). 4) Backward multiple regression revealed that the linear combination of economic awareness, job position, place of employment, and the presence of CQI committee accounted for 26.1% of the variance in the attitudes toward cost-effectiveness nursing care. Conclusion : Findings reveal that RNs lack basic knowledge of economics and its link to nursing practice, yet, they want a voice in economic decision making. In an effort to fill the void of economic knowledge and respond to nurses' call for greater input, in-service programs and curricula for generic programs must be developed.

• Journal of Korea Port Economic Association
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• v.26 no.3
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• pp.165-174
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• 2010

DEA converts multiple inputs and outputs of a decision unit into a single measure of performance, generally mentioned as relative efficiency. DEA has been applied successfully as a performance evaluation tool in many fields including manufacturing, banks, pharmacies, and hospitals to name a few. This paper applies the input-oriented DEA model, DEA/Window analysis, and Malmquist indices to the 9 regions in Korea to measure the efficiency and productivity. The empirical results show the following findings. First, the super efficiency indicate that efficiency of Group 2 is greater than Group 1. Second, Malmquist indices show that productivity of Group 2 is less than Group 1. Third, DEA/Window of Group2 show that Chungnam is most stable, while Jeonnam is most unstable.

• Journal of the Korea Society of Computer and Information
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• v.7 no.4
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• pp.8-15
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• 2002

This Paper proposes designing and implementing the database system storing the medical images. This system collects the medical image when doctors operate and diagnose the patients using the endoscope in the orthopedics, then stores the medical image data to database. Therefore. system avoids duplicated medical data, retrieves and updates the medical data effectively. The medical image data can be shared to the multiple users and application programs. This system consists of the five components. that is, the input module acquiring the medical image from the endoscope. the modulo storing the medical image. the database design and implementation storms the patient's disease history and the medical image data, user friendly interface design and implementation, and the simple data retrieval engine. The features of the system are followed. The image catcher program using DirectShow is portable any image catcher board And because the image catcher algorithm is implemented as a public module, The throughput can be increased during the development of video and audio contents on internet.