• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.379-384
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• 2002

개발적인 측면에서 온라인 게임 환경에서의 NPC(Non Playable Character)들은 환경인식능력, 이동능력, 특수 능력 및 아이템의 소유 배분 등을 원활히 하기 위한 능력들을 소유해야 하며, 게임 환경을 인식, 저장하기 위한 데이터구조와 자신만의 독특한 임무(mission)를 달성하기 위한 계획을 갖고 행위를 해야 한다. 이런 의미에서 NPC는 자신만의 고유한 규칙과 행동 패턴, 그리고 목표(Goal)와 이를 실행하기 위한 계획(plan)을 소유하는 에이전트로 인식되어야 할 것이다. 그러나, 기존 게임의 NPC 제어 구조나 구현 방법은 이러한 요구조건에 부합되지 못한 부분이 많았다. C/C++ 같은 컴퓨터 언어들을 이용한 구현은 NPC의 유연성이나, 행위에 많은 문제점이 있었다. 이들 언어의 switch 문법은 NPC의 몇몇 특정 상태를 묘사하고, 그에 대한 행위를 지정하는 방법으로 사용되었으나, 게임 환경이 복잡해지면서, 더욱더 방대한 코드를 만들어야 했고, 해석하는데 많은 어려움을 주었으며, 동일한 NPC에 다른 행동패턴을 적용시키기도 어려웠다. 또한, 대부분의 제어권을 게임 서버 폭에서 도맡아 함으로써, 서버측에 많은 과부하 요인이 되기도 하였다. 이러한 어려움을 제거하기 위해서 게임 스크립트를 사용하기도 하였지만, 그 또한 단순 반복적인 패턴에 사용되거나, 캐릭터의 속성적인 측면만을 기술 할 수 있을 뿐이었다 이러한 어려움을 해소하기 위해서는 NPC들의 작업에 필요한 지식의 계층적 분화를 해야 하고, 현재 상황과 목표 변화에 적합한 반응을 표현할 수 있는 스크립트의 개발이 필수 적이라 할 수 있다 또한 스크립트의 실행도 게임 서버 측이 아닌 클라이언트 측에서 수행됨으로써, 서버에 걸리는 많은 부하를 줄일 수 있어야 할 것이다. 본 논문에서는, 대표적인 반응형 에이전트 시스템인 UMPRS/JAM을 이용하여, 에이전트 기반의 게임 캐릭터 구현 방법론에 대해 알아본다.퓨터 부품조립을 사용해서 Template-based reasoning 예를 보인다 본 방법론은 검색노력을 줄이고, 검색에 있어 Feasibility와 Admissibility를 보장한다.매김할 수 있는 중요한 계기가 될 것이다.재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having

• The Journal of the Korea Contents Association
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• v.9 no.3
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• pp.361-371
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• 2009

LAMS(learning activity management system)[1] is one of the useful tools for designing and managing effectively the learning activities such as web search, chat, forum, grouping, and board. Even if LAMS has been upgraded to support the methods for making e-Learning contents conveniently, it does not have a method to communicate with external educational contents (EEC) made by external tools like Flash, Java, Visual C++, and so on. LAMS, which has been operated on Web environment, should manage all EECs like video and dynamic educational contents as educational contents in LAMS database. However, the current LAMS does not support the functionalities which can provide information of EECs to LAMS database and can also access any information about EECs from the database yet. In this paper, we propose the communication mechanism between the LAMS and EECs for solving the problem. In special, the mechanism makes many statistical data by using the information, and provides them for reflecting in education, and can control various learning management that was impossible under the original LAMS. Based on the proposed mechanism, teachers using LAMS can make more various educational contents and can manage them in the system.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.103-118
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• 1999

This paper analyzes the performance of symbol timing recovery and equalizer in 8VSB digital terrestrial TV receiver under various multipath signals and proposes equalization techniques which improve indoor reception performance. Data segment sync is used for symbol timing recovery and timing offset is measured for echoes of various delays and amplitudes by using symbol timing detection filter whose pattern is +1. +1. -1. and -1. Measured timing offsets were below 10% for long echoes with more than 5 symbol delay and above 30% for short echoes with around 1 symbol delay. Indoor reception is always more challenging than outdoor reception due to lower signal strength. large and short multipaths. and moving interfering objects. So it is considered to use FSE (Fractionally Spaced Equalizer) which is very robust to timing offset and blind equalizer which can update equalizer tap coefficients even by information data. We compare the performance of conventional DFE (Decision Feedback Equalizer) and FSE-DFE using LMS algorithm and Stop and Go algorithm for the indoor reception. Experiments reveals FSE has excellent performance for large timing offset and Stop and Go algorithm shows good performance for Doppler shift. so we propose to use FSE-DFE structure with Stop and Go algorithm for the reliable indoor reception.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.12
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• pp.60-69
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• 2000

This paper describes a single-chip full-custom implementation of pipelined adaptive decision-feedback equalizer(PADFE) using a 0.25-${\mu}m$ CMOS technology for wide-band wireless digital communication systems. To enhance the throughput rate of ADFE, two pipeline stages are inserted into the critical path of the ADFE by using delayed least-mean-square(DLMS) algorithm. Redundant binary (RB) arithmetic is applied to all the data processing of the PADFE including filter taps and coefficient update blocks. When compared with conventional methods based on two's complement arithmetic, the proposed approach reduces arithmetic complexity, as well as results in a very simple complex-valued filter structure, thus suitable for VLSI implementation. The design parameters including pipeline stage, filter tap, coefficient and internal bit-width, and equalization performance such as bit error rate (BER) and convergence speed are analyzed by algorithm-level simulation using COSSAP. The single-chip PADFE contains about 205,000 transistors on an area of about $1.96\times1.35-mm^2$. Simulation results show that it can safely operate with 200-MHz clock frequency at 2.5-V supply, and its estimated power dissipation is about 890-mW. Test results show that the fabricated chip works functionally well.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.4
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• pp.483-488
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• 2015

This paper implements a long-term monitoring system (LMS) for ship's engine performance analysis (SEPA) based on the web, for the purpose of the communication speed and engine maintenance. This system is composed of a simulator, monitoring module with a multi channel A/D converter, monitoring computer, network attached storage (NAS), RS485 serial and wireless internet communication system. The existing products monitor the information transmitted from pressure sensors installed in the upper parts of each of engines in the local or web computer, but have a delay in the communication speed and errors in long-term monitoring due to the large volume of sampling pressure data. To improve these problems, the monitoring computer saves the sampling pressure data received from the pressure sensors in NAS, monitors the long-term sampling data generated by the sectional down sampling method on a local computer, and transmits them to the web for long-term monitoring. Because this method has one tenth of the original sampling data, it will use memory with small capacity, save communication cost, monitor the long-term sampling data for 30 days, and as a result, make a great contribution to engine maintenance.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.4
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• pp.45-54
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• 2012

Location-based services with GPS positioning technology as a key technology, but recognizing the current location through satellite communication is not possible in an indoor location-aware technology, low-power short-range communication is primarily made of the study. Especially, as Chirp Spread Spectrum(CSS) based location-aware approach for low-power physical layer IEEE802.15.4a is selected as a standard, Ranging distance estimation techniques and data transfer speed enhancements have been more developed. It is known that the distance measured by CSS ranging has quite a lot of noise as well as its bias. However, the noise problem can be adjusted by modeling the non-zero mean noise value by a scaling factor which corresponds to the change of magnitude of a measured distance vector. In this paper, we propose a localization system using the CSS signal to measure distance for a mobile node taken a measurement of the exact coordinates. By applying the extended kalman filter and least mean squares method, the localization system is faster, more stable. Finally, we evaluate the reliability and accuracy of the proposed algorithm's performance by the experiment for the realization of localization system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.413-423
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• 2003

The CMA algorithmis most widely investigated blind algorithm and the most widely used one in practice. But, since nonlinear CM cost function have not closed form solution about the optimum weight. There have been difficultiesto analyze the CMA equalizer's theoretical performance. Recently, Zeng presents the notable theoretical resultabout the MSE of CM-minimizing estimators for the FIR linear channel in the presence of AWGN. Through this method, It wouldbe possible to campare the theoretical performance between CMA and Wiener equalizer in terms of MSE. In this paper, based on Zeng's method, we first calculate the theoretical MSE bound of CMA equalizer in partial response channel which is widely used in HDD, digital VCR such as high-density digital recording.playback systems. We confirmedthis result withthe computer simulation. Except this, we also performedthe theoretical and simulation analysis about the modified CMA equalizer, which was proposed to improve the performance of CMA equalizer in partial response channel. Finally, we compare and evaluate the performance analysis results between CMA and Modified CMA equalizer.

• Journal of Energy Engineering
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• v.22 no.3
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• pp.245-249
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• 2013

This paper attempts to estimate the kerosene demand function in Korea over the period 1981-2012. As the kerosene demand function provides us information on the pattern of consumer's kerosene consumption, it can be usefully utilized in predicting the impact of policy variables such as kerosene price and forecasting the demand for kerosene. We apply least absolute deviations and least median squares estimation methods as a robust approach to estimating the parameters of the kerosene demand function. The results show that short-run price and income elasticities of the kerosene demand are estimated to be -0.468 and 0.409, respectively. They are statisitically significant at the 1% level. The short-run price and income elasticities portray that demand for kerosene is price- and income-inelastic. This implies that the kerosene is indispensable goods to human-being's life, thus the kerosene demand would not be promptly adjusted to responding to price and/or income change. However, long-run price and income elasticities reveal that the demand for kerosene is price- and income-elastic in the long-run.

• Journal of the Korean School Mathematics Society
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• v.24 no.1
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• pp.83-105
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• 2021

In this paper, we analyzed the misconceptions and errors incurred during factorization learning. We also examined whether online individualization classes had a positive effect on students' mathematical achievement. The experiment was conducted for 4 weeks (16 times in total) on middle school juniors in rural areas of Gyeonggi Province, where the influence of private extra education was small. In the class, the 'Google Classroom' was used as a LMS, the video lecture was uploaded to YouTube, and the teacher interacted with the students through "Zoom" and "Facetalk". In the online class situation, students' assignments and test answers were checked in real time through 'Google Classroom', and immediate feedback was provided to the experimental class group's students. However, for the control group students, feedback was provided only to those who desired. A total of 7 achievement evaluations were conducted in the order of pre-test, formative evaluation (5 times), and post-test to confirm the change in students' ability improvement and achievement. Through the formative evaluation analysis, it was possible to grasp the types of errors and misconceptions that occured during the factorization process. Students' errors were divided into four types: theorem or definition distortion error, functional errors such as calculation, operation, and manipulation, errors that do not verify the solution, and no response. As a result of ANCOVA, the two groups did not show any difference from the 1st to 4th formative assessment. However, the 5th formative assessment and post-test showed statistically significant differences, confirming that online individualization classes contributed to improvemed achievement.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.523-533
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• 2022

During the COVID-19 pandemic, the use of video classes and real-time online education has increased, but the lack of interaction between instructors and learners remains a challenging problem to be resolved. This paper designs and implements a learning support system that utilizes a digital human to improve faculty-student interaction, which plays an important role in increasing the educational effect and satisfaction of real-time online classes. In this paper, a digital human participates in a class as a virtual learner and asks questions raised by other learners through an anonymous chat system to the instructor on behalf of the learners. In addition, as a class facilitator, the digital human analyzes the lecturer's speech in real time and provides it to the learner in the form of a summary of the class, thereby facilitating faculty-student interaction. In order to confirm that the proposed system can be used in actual online real-time classes, we apply our system to Zoom classes. Experimental results show that facilitated Q&A and real-time class summaries are successfully provided through our digital human-based learning support system.