• Annual Conference of KIPS
• /
• 2022.11a
• /
• pp.727-729
• /
• 2022

본 연구는 2021 게임업계 연쇄 파동을 통해 게임사 이슈 대응에 대한 사용자들의 인식이 바뀐 것에 주목하여 메이플스토리 확률 조작 사건에서 나타난 사용자들의 반응을 토픽모델링으로 분석하였다. 이를 위해 사건의 발단이 된 메이플스토리 테스트 월드 업데이트 내용이 업로드된 2021년 2월 18일 17시를 기점으로 국내 온라인 게임 커뮤니티 중 하나인 인벤의 자유게시판에서 총 10만 개의 게시물을 수집하고 토픽모델링 분석을 실시하였다. 이후 도출된 주제별 주요 단어를 10개씩 확인하여 주제를 정의했다. 각 토픽을 비교하며 관련성을 확인했고 이를 통해 사용자들의 반응을 분석한 결과 확률 조작으로 인한 보상으로 환불을 원하고 있다는 것과 아이템의 확률을 조작했다는 것에 대한 사용자들의 분노, 디렉터 본인의 직접적인 사과문과 사용자와의 소통 요구, 또 다른 게임으로의 이탈을 확인할 수 있었다.

• Environmental and Resource Economics Review
• /
• v.27 no.1
• /
• pp.139-160
• /
• 2018

Using survey data of selected 1,349 individuals nationwide in Korea, we measure the influencing factors for the acceptance of nuclear power and estimates the probability of acceptance under several scenarios with different percentages of monetary compensation. Results of panel probit demonstrate that nuclear risk aversion tendency was found to be higher in case of female, younger age, past experience of extreme event such as an earthquake. However, the residents' residency nearby the nuclear power plant was not related to the risk-aversion tendency. In addition, we found that the nuclear acceptance is improved when the monetary compensation rate is increased. Although the policy demand intended to reduce GHG emissions in South Korea, the expansion of nuclear power is not be easy due to the occurrence of recent strong earthquakes because the risk attitude of an individual is influenced by subjective assessments formed through direct and indirect experiences of natural disasters such as an earthquake. Our results suggest that the opposition to construction of nuclear power plant is expected to be further intensified especially when combined with the experiences of threatening earthquakes. As a result, the debate and policy conflicts of nuclear power plants will consistently continue and large social costs are apparent for the acceptance of nuclear power plant.

• The Journal of the Acoustical Society of Korea
• /
• v.22 no.3
• /
• pp.188-193
• /
• 2003

Regardless of the distribution of the adaptation data in the testing environment, model-based adaptation methods that have so far been reported in various literature incorporates the adaptation data undiscriminatingly in reducing the mismatch between the training and testing environments. When the amount of data is small and the parameter tying is extensive, adaptation based on outlier data can be detrimental to the performance of the recognizer. The distribution of the adaptation data plays a critical role on the adaptation performance. In order to maximally improve the recognition rate in the testing environment using only a small number of adaptation data, supervised weighted training is applied to the structural maximum a posterior (SMAP) algorithm. We evaluate the performance of the proposed weighted SMAP (WSMAP) and SMAP on TIDIGITS corpus. The proposed WSMAP has been found to perform better for a small amount of data. The general idea of incorporating the distribution of the adaptation data is applicable to other adaptation algorithms.

• Journal of IKEEE
• /
• v.14 no.3
• /
• pp.236-243
• /
• 2010

Power quality mitigation devices play an important role in lots of industrial segments. Although there were many devices available in the market, the selection of an appropriate device specially for voltage sags and interruptions mitigation has been a challenge in the utility and customer for several years. It usually depends on technical and economic characteristics of the device. Nevertheless, most mitigation method is selected by rule of thumb or empirical method. In this paper, the life cycle cost analysis for the probabilistic risk assesment of voltage sag mitigation method is performed using either the deterministic or probabilistic approach. The difference between a deterministic and a probabilistic cost analysis approach is illustrated with five different case studies. This paper not only provides a comparison of life cycle costing of various devices but it also indirectly shows the possible savings due to the mitigation of voltage sags in the form of a project balance chart.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.2
• /
• pp.46-56
• /
• 1999

A predictive controller is designed based upon stochastic methods for compensation time-delay effect on a system which has inherent time-delay caused by the spatial separation between controllers and actuators. The predictive controller estimates current outputs through linear prediction methods and probability functions utilizing previous outputs, and minimizes the malicious phenomena caused by the time-delay in precision control systems. To demonstrate effectiveness of this control methodology, we applied this algorithm for the control of a tele-operated DC servomotor. The experimental results show that this predictive controller is superior to the PID controller in terms of convergence-characteristics, and show that this controller expands the maximum allowable time-delay for a system maintaining the stability. Since the proposed predictor does not require models of plants - it requires only stochastic information for outputs --, it is a general scheme which can be applied for the control of systems which are difficult to model or the compensator of PID control.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.40 no.3
• /
• pp.215-221
• /
• 2012

In this paper, we introduce an optimization method to improve pursuit performance of a pursuer in a pursuit-evasion game (PEG). Pursuers build a probability map and employ a hybrid pursuit policy which combines the merits of local-max and global-max pursuit policies to search and capture evaders as soon as possible in a 2-dimensional space. We propose an episodic parameter optimization (EPO) algorithm to learn good values for the weighting parameters of a hybrid pursuit policy. The EPO algorithm is performed while many episodes of the PEG are run repeatedly and the reward of each episode is accumulated using reinforcement learning, and the candidate weighting parameter is selected in a way that maximizes the total averaged reward by using the golden section search method. We found the best pursuit policy in various situations which are the different number of evaders and the different size of spaces and analyzed results.

• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.739-743
• /
• 2008

In this paper, we introduce a method for automatically generating accompaniment music, according to user's input melody. The initial accompaniment chord is generated by analyzing user's input melody. Then next chords are generated continuously based on markov chain probability table in which transition probabilities of each chord are defined. The probability table is learned according to reinforcement learning mechanism using sample data of existing music. Also during playing accompaniment, the probability table is learned and refined using reward values obtained in each status to improve the behavior of playing the chord in real-time. The similarity between user's input melody and each chord is calculated using pitch class histogram. Using our method, accompaniment chords harmonized with user's melody can be generated automatically in real-time.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.17 no.3
• /
• pp.260-267
• /
• 1992

In this paper, the performance of frequency hopped(FH) M-ary frequency shift keyed(MFSK)system is analyzed with the fading channel and the multione famming. In general, the performance degradation of FH/MFSK system is due to the Rayleigh fading and the multitone jamming environment. In order to improve the system performance. the time diversity is used. When the time diversity is applied to the Rayleigh fading and the mulitone jamming, we get around 18dB and 19dB improvements. respectively. And when it is applied to both the Rayleigh fading and the multitone jamming, we get around 4 dB improvement.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.6
• /
• pp.863-870
• /
• 2008

In this paper, a new filtering scheme for vehicle tracking with distorted measurement is presented. This filtering scheme is essential for the implementation of the adaptive cruise control (ACC) system. The proposed method combines the IMM and the probabilistic fuzzy model and is named as the Fuzzy IMM (FIMM). The IMM is employed to recognize the intention of the preceding vehicle. The probabilistic furry model is introduced to compensate the distortion of the range sensor. Finally, a computer simulation is performed to illustrate the validity of the suggested algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.40 no.2
• /
• pp.247-252
• /
• 2015

Adaptive algorithms based on the criterion of zero-error probability (ZEP) have robustness to impulsive noise and their decision feedback (DF) versions are known to compensate effectively for severe multipath channel distortions. However the ZEP-DF algorithm computes several summation operations at each iteration time for each filter section and this plays an obstacle role in practical implementation. In this paper, the ZEP-DF with recursive gradient estimation (RGE) method is proposed and shown to reduce the computational burden of O(N) to a constant which is independent of the sample size N. Also the weight update of the initial state and the steady state is a continuous process without bringing about any propagation of gradient estimation error in DF structure.