• Proceedings of the Korea Society for Simulation Conference
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• 2003.11a
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• pp.95-103
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• 2003

Event notification service is a event-based messaging middle ware service needed for various vertical domains, such as, business applications, distributed system management, and web service integration. In this paper, we investigate the architecture of an event notification service that includes a subject-based event dissemination service and a flexible message communication service. The event dissemination service is in charge of transferring events asynchronously but speedy according to the subjects of events and their environmental knowledge. It also includes content-based message filtering. The message communication service provides a common communication infrastructure supporting variety types of messages and variety of protocols. Depending on application domains and situation, we can re-configurate the communication infrastructure in order to optimize the efficiency and usability. This paper shows the performance analysis of our event notification service with various types of message formats and protocols.

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.538-555
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• 2015

Event detection based on using features from a static grid can give poor results from the viewpoint of two main aspects: the position of the camera and the position of the event that is occurring in the scene. The former causes problems when training and test events are at different distances from the camera to the actual position of the event. The latter can be a source of problems when training events take place in any position in the scene, and the test events take place in a position different from the training events. Both issues degrade the accuracy of the static grid method. Therefore, this work proposes a method called a dynamic grid for event detection, which can tackle both aspects of the problem. In our experiment, we used the dynamic grid method to detect four types of event patterns: implosion, explosion, two-way, and one-way using a Multimedia Analysis and Discovery (MAD) pedestrian dataset. The experimental results show that the proposed method can detect the four types of event patterns with high accuracy. Additionally, the performance of the proposed method is better than the static grid method and the proposed method achieves higher accuracy than the previous method regarding the aforementioned aspects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3498-3512
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• 2021

This article describes how events that make up text stories can be represented and extracted. We also address the results from our simple experiment on extracting and clustering events in terms of emotions, under the assumption that different emotional events can be associated with the classified clusters. Each emotion cluster is based on Plutchik's eight basic emotion model, and the attributes of the NLTK-VADER are used for the classification criterion. While comparisons of the results with human raters show less accuracy for certain emotion types, emotion types such as joy and sadness show relatively high accuracy. The evaluation results with NRC Word Emotion Association Lexicon (aka EmoLex) show high accuracy values (more than 90% accuracy in anger, disgust, fear, and surprise), though precision and recall values are relatively low.

• Journal of Korea Game Society
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• v.20 no.1
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• pp.47-56
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• 2020

The purpose of this study is to analyze visual environmental elements of game space by play-event in adventure games. We extracted common six types of play-event through exploring ten representative adventure games and organized three types of space structure and four types of object as the criteria of analysis. Based on the criteria, we embodied the characteristics of visual environmental elements by performing direct playing and monitoring. As a result, we verified that the story intended and the gameplay induced by the play-event are closely related to visual environmental elements.

• Journal of Sport and Applied Science
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• v.3 no.1
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• pp.1-14
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• 2019

Numerous types of sporting events have been hosted in Korea during the last decades. Sport events produce various types of data, and there is a clear necessity of storing and utilizing this information. From this background, the purpose of this study is to draw complex sports categories from international sport events life cycles in order to categorize standards of knowledges management system. This study utilized qualitative methods: expert groups discussion for overall life cycle steps and in-depth interviews for detail life cycle steps. The results show that there are several life cycle steps: bidding, preparation, operation, evaluation, post management steps. To be more specific, for the bidding step, there are check, plan, implementing detail phase; and the preparation step is based on event preparation Basis Build, event preparation implementation, test and supplementation phases. For the operation step, event operation system switch, event operation during the period, finish operation phases are deducted. Evaluation and post management step do not have detail phases. Efforts to store and utilize knowledge can be one of the starting points to make the operation of sport events efficiently.

• The Journal of Industrial Distribution & Business
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• v.12 no.5
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• pp.47-58
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• 2021

Purpose - Current research aimed at exploring the effect differences between the two types of processing product information such as the imagining and the considering on psychological product ownership which could influence the intent to purchase or use the product, and focused on identifying the interaction effects of activated memory information type and advertising information type on each of the information processing types. Research design, data, and methodology - This study divided the information processing types into imagining and considering, and the consumer's memories were divided into autobiographical or episodic and semantic memory. The advertising information was approached in each of event information being together with the product and product feature information. At empirical study, 2(two types of memory activation: episodic and semantic memory activation) ∗ 2(two types of advertising information: event-focused and product feature-focused advertising information) between-subjects design was used to make four types of questionnaire according to the type of experimental groups. Through the survey platform, 'questionnaire stars' of 'WeChat' in China, 219 questionnaire data were collected for empirical study. The structural equation model in AMOS 26 and Anova were used to verify hypotheses. Results - First, the ownership affected the usage intent positively. Second, the imagining did not affect the psychological ownership but did directly affect the usage intention, and the considering affected the ownership positively. Third, the episodic memory activation positively influenced the imagining and negatively affected the considering, whereas the semantic memory activation positively influenced the considering and negatively affected the imagining. Fourth, event-advertising information increased the effects of the activated episodic memory on the imagining, and feature-advertising information increased the effects of the activated semantic memory on the considering. Conclusions - marketers should develop and advertise their product-related event message to trigger the imaging that directly increase the intent to purchase or use their product, when consumers are under the activation of their episodic memory. And marketers should advertise their product feature-related message to trigger the considering that could induce consumers' ownership for their product to increase the intent to purchase or use their product, when they are under the activation of their semantic memory.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.46.2-46.2
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• 2021

We present solar event auto detection using deep-learning-based object detection algorithms and DeepSDO event dataset. DeepSDO event dataset is a new detection dataset with bounding boxed as ground-truth for three solar event (coronal holes, sunspots and prominences) features using Solar Dynamics Observatory data. To access the reliability of DeepSDO event dataset, we compared to HEK data. We train two representative object detection models, the Single Shot MultiBox Detector (SSD) and the Faster Region-based Convolutional Neural Network (R-CNN) with DeepSDO event dataset. We compared the performance of the two models for three solar events and this study demonstrates that deep learning-based object detection can successfully detect multiple types of solar events. In addition, we provide DeepSDO event dataset for further achievements event detection in solar physics.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.201-208
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• 2005

Event notification service is a event-based messaging middleware service needed for various vertical domains, such as, business applications, distributed system management, and web service integration. In this paper, we investigate the architecture of an event notification service that includes a subject-based event dissemination service and a flexible message communication service. The event dissemination service is in charge of transferring events asynchronously but speedy according to the subjects of events and their environmental knowledge. It also includes content-based message filtering. The message communication service provides a common communication infrastructure supporting variety types of messages and variety of protocols. Depending on application domains and situation, we can re-configurate the communication infrastructure in order to optimize the efficiency and usability. This paper shows the performance analysis of our event notification service with various types of message formats and protocols.

• Journal of Korean Theatre Studies Association
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• no.48
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• pp.549-569
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• 2012

Since 1995, the Local autonomy era has opened, local festivals have been increasing throughout the country. Traditional culture festivals are also increasing. Performing traditional culture festivals is effective for maintenance and transmission of traditional culture as well as creation and nurturing of local culture. They are also effective promoting local economy. Depending on realization level of character, place and costume based on historic research, traditional culture festivals are classified as the "Representation event" or the "Reenactment event". But there are two problems. The first is unexacting classification method for festival types made by Central government yearly. The second is unable to meet one of two goals which are protecting traditional culture and stimulating local economy throughout increasing tourists. The purpose of this study is to suggest improvement of classification method for festival types, and to offer two suggestions for ensure successful local festivals. First of all, I suggest advanced classification method for festival types. For more sophisticated collection process of national festival status, local government department should ensure purpose of festivals, and central government department should add 3 steps to existing process. For example professional committee for judgement of festival types should be founded for consulting of local and central government department. The second suggestion is reinforcement of historic research for the Representation of traditional culture event. The representation of traditional culture should focus on protection of tradition, and could be perfect by continuous historic research. The last suggestion is cooperation with local governments each other for the Reenactment of traditional culture event. The Reenactment of traditional culture should focus on promoting local economy by increasing tourists. So local governments who have similar traditional events should cooperate to get preventing loss of resource and overcome weakness of promoting.

• Journal of information and communication convergence engineering
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• v.5 no.3
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• pp.233-238
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• 2007

An approach to identify Chinese event types is proposed in this paper which combines a good feature selection policy and a Maximum Entropy (ME) model. The approach not only effectively alleviates the problem that classifier performs poorly on the small and difficult types, but improve overall performance. Experiments on the ACE2005 corpus show that performance is satisfying with the 83.5% macro - average F measure. The main characters and ideas of the approach are: (1) Optimal feature set is built for each type according to local feature selection, which fully ensures the performance of each type. (2) Positive and negative features are explicitly discriminated and combined by using one - sided metrics, which makes use of both features' advantages. (3) Wrapper methods are used to search new features and evaluate the various feature subsets to obtain the optimal feature subset.