• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.163-168
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• 2002

The voting algorithm for action selection performs self-improvement by Reinforcement learning algorithm in the dynamic environment. The proposed voting algorithm improves the navigation of the robot by adapting the eligibility of the behaviors and determining the Command Set Generator (CGS). The Navigator that using a proposed voting algorithm corresponds to the CGS for giving the weight values and taking the reward values. It is necessary to decide which Command Set control the mobile robot at given time and to select among the candidate actions. The Command Set was learnt online by means as Q-learning. Action Selector compares Q-values of Navigator with Heterogeneous behaviors. Finally, real-world experimentation was carried out. Results show the good performance for the selection on command set as well as the convergence of Q-value.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.8
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• pp.89-97
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• 2022

The e-commerce market faces significant credit risks due to the complexity of the industry and information asymmetries. Therefore, credit risk has started to stymie the growth of e-commerce. However, there is no reliable system for evaluating the creditworthiness of e-commerce companies. Therefore, this paper constructs a credit risk evaluation index system that comprehensively considers the online and offline behavior of online retail enterprises, including 15 indicators that reflect online credit risk and 15 indicators that reflect offline credit risk. This paper establishes an integration method based on a fuzzy integral support vector machine, which takes the factor analysis results of the credit risk evaluation index system of online retail enterprises as the input and the credit risk evaluation results of online retail enterprises as the output. The classification results of each sub-classifier and the importance of each sub-classifier decision to the final decision have been taken into account in this method. Select the sample data of 1500 online retail loan customers from a bank to test the model. The empirical results demonstrate that the proposed method outperforms a single SVM and traditional SVMs aggregation technique via majority voting in terms of classification accuracy, which provides a basis for banks to establish a reliable evaluation system.

• Asian Journal for Public Opinion Research
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• v.8 no.2
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• pp.67-104
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• 2020

Fake news and disinformation provoked heated arguments during Taiwan's 2018 local election. Most significantly, concerns grew that Beijing was attempting to sway the island's politics armed with a new "Russian-style influence campaign" weapon (Horton, 2018). To investigate the speculated effects of the "onslaught of misinformation," an online survey with 1068 randomly selected voters was conducted immediately after the election. Findings confirmed that false news affected Taiwanese voters' judgment of the news and their voting decisions. More than 50% of the voters cast their votes without knowing the correct campaign news. In particular, politically neutral voters, who were the least able to discern fake news, tended to vote for the China-friendly Kuomintang (KMT) candidates. Demographic analysis further revealed that female voters tended to be more likely to believe fake news during the election period compared to male voters. Younger or lower-income voters had the lowest levels of discernment of fake news. Further analyses and the implications of these findings for international societies are deliberated in the conclusion.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.1
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• pp.8-16
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• 2014

We consider the visual barcode recognition problem in a noisy video data setup. Unlike most existing single-frame recognizers that require considerable user effort to acquire clean, motionless and blur-free barcode signals, we eliminate such extra human efforts by proposing a robust video-based barcode recognition algorithm. We deal with a sequence of noisy blurred barcode image frames by posing it as an online filtering problem. In the proposed dynamic recognition model, at each frame we infer the blur level of the frame as well as the digit class label. In contrast to a frame-by-frame based approach with heuristic majority voting scheme, the class labels and frame-wise noise levels are propagated along the frame sequences in our model, and hence we exploit all cues from noisy frames that are potentially useful for predicting the barcode label in a probabilistically reasonable sense. We also suggest a visual barcode tracking approach that efficiently localizes barcode areas in video frames. The effectiveness of the proposed approaches is demonstrated empirically on both synthetic and real data setup.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.468-481
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• 2018

This study aims to empirically investigate how users' online engagement behaviors predict their uses of paid contents. To this end, the data from the 2016 Korean Media Panel Survey, which has been conducted annually by the Korea Information Society Development Institute(KISDI), were analyzed. Major findings(N=8.313) were as follows. First, the active type of online engagement(e.g., posting, commenting), which contributes to direct creation of online contents, was the most powerful predictor to explain the DV. On the other hand, relatively passive actions of user engagement(e.g., sharing, endorsing, voting) turned out to have no significant effects on the uses of paid contents, just as personality traits and online privacy concerns did. Based on these results, it is recommended that online contents or platform service providers should try to establish clearly-targeted marketing strategies, after thoroughly collecting and analyzing the data of users' various online behaviors.

• Journal of the Semiconductor & Display Technology
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• v.19 no.2
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• pp.1-10
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• 2020

Blockchain enabled Decentralized Autonomous Organization (DAO), a new form of organization with conveying its core value - trust. Token holders who are participating DAO's governance share their thoughts, information, and ideas in online forum. But it is problem that chronological form of DAO's online forum makes token holders hard to find crucial information, meaning that many of them might not understand what is happening discussion. In this paper, we studied not only a decision making process which feature is iteration, visualization, and applicable to DAO with 6 steps in total but also a decision making tool which is based on the process of this paper. The tool has features to help participants such as voting model, visualization features which gives guidance to them for their decision during the process. Our experiment showed that the process and tool is somewhat reasonable, and the information during the process is effective for participants. This work is expected to be applied to current DAOs to make a decision among the token holders.

• The Journal of the Korea Contents Association
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• v.17 no.1
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• pp.426-435
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• 2017

Since online betting occurs on online where anybody can access through internet, thus, the online gambling market has been expanding. Domestic illegal gambling market size is 4 times bigger than that of legal gambling market, and illegal online betting market is rapidly growing as well. Currently online gambling does exist domestically in form of Sports promotion voting rights, also known as, Toto and Proto and internet lottery. However, the need for other types of online gambling to be permitted, expanded and managed has been suggested. This research has analyzed online gambling users, online gambling addicts and general population's awareness on expansion and operation of online gambling, contraction measures of illegal online gambling and operation measures in case of permitted expansion of online gambling. The result of this research's analysis showed that each group has significantly different awareness level on positive and negative effects of permitting online gambling's expansion. Also, it showed that each group has significantly different awareness on permitting expansion of racing betting as a legal gambling item. Since it is the proven fact that illegal online gambling users could turn into legal users and that users could use the service more positively if online gambling is legalized through allowance and expansion process; one could expect the positive effects from permitting expansion of online gambling.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.652-654
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• 2005

베이지안 네트워크의 파라메터 학습은 주어진 평가 척도에 따라 데이터의 훈련집합에 가장 잘 부합되는 네트워크 파라메터를 구하는 것으로, 베이지안 네트워크 설계에 드는 시간과 노력을 줄이기 위해 연구되어 왔다. 본 논문에서는 불완전한 데이터로부터 온라인으로 베이지안 네트워크의 파라메터를 학습하는 방법을 제안한다. 제안하는 방법은 불완전한 데이터로부터 학습이 가능하도록 하여 학습의 유연성을 높이고, 온라인 학습을 통해 사용자 또는 환경의 변화를 잘 모델링한다. Choen 등이 제안한 온라인 파라메터 학습 방법인 Voting EM 알고리즘과 비교 실험 결과, 제안하는 방법의 유용성을 확인할 수 있었다.

• Journal of information and communication convergence engineering
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• v.22 no.1
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• pp.7-13
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• 2024

User preferences and ratings may be anticipated by recommendation systems, which are widely used in social networking, online shopping, healthcare, and even energy efficiency. Constructing trustworthy recommender systems for various applications, requires the analysis and mining of vast quantities of user data, including demographics. This study focuses on holding elections with vague voter and candidate preferences. Collaborative user ratings are used by filtering algorithms to provide suggestions. To avoid information overload, consumers are directed towards items that they are more likely to prefer based on the profile data used by recommender systems. Better interactions between governments, residents, and businesses may result from studies on recommender systems that facilitate the use of e-government services. To broaden people's access to the democratic process, the concept of "e-democracy" applies new media technologies. This study provides a framework for an electronic voting advisory system that uses machine learning.

• Korean journal of communication and information
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• v.42
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• pp.79-106
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• 2008

Based on the third-person effect hypothesis, this study conducted a nation-wide online survey to assess how Korean voters perceived the mass media's effect on the candidates' image and voting behavior during the 17th presidential election. The research results showed that the voters tended to perceive that the mass media such as newspaper, television and the Internet had a greater effect on others than on themselves with regards to the formation of the three candidates' images. The third-person effect on the voting behavior was also revealed differently in terms of the medium according to age and political tendency of the voters. For instance, the younger and liberal voters were likely to see newspaper as having a greater influence on other voters' choice of candidate, while the older voters saw TV as having a greater effect on other voters. The conservative tendency did not affect the perception of the voters at all. Another noteworthy result was that personal characteristics of the candidates' images such as appearances and communication skills did not affect the voters' behaviors in the election process.