• Journal of Korea Game Society
• /
• v.14 no.2
• /
• pp.29-44
• /
• 2014

This Study analyzes gameness in SNS. SNS is not only communication tool for real life but also game like media for the experimental fiction. As the media like games, SNS meets 6 classic game features. After the Tatradic analysis, Expressive and manipulation rules move SNS paidia direction, player's effort and negotiable outcome are obsolesced. Player's attachment is enhanced and in SNS, the tradition of MUD retrieves abstract ground with representative expression. As following result, SNS is able to extend its own area to the player's creative world for the possible. SNS is the media like games.

• The KIPS Transactions:PartB
• /
• v.15B no.4
• /
• pp.365-374
• /
• 2008

In this paper, we propose a model to enrich an ontology by incrementally extending the relations through variations of patterns. In order to generalize initial patterns, combinations of features are considered as candidate patterns. The candidate patterns are used to extract relations from Wikipedia, which are sorted out according to reliability based on corpus frequency. Selected patterns then are used to extract relations, while extracted relations are again used to extend the patterns of the relation. Through making variations of patterns in incremental enrichment process, the range of pattern selection is broaden and refined, which can increase coverage and accuracy of relations extracted. In the experiments with single-feature based pattern models, we observe that the features of lexical, headword, and hypernym provide reliable information, while POS and syntactic features provide general information that is useful for enrichment of relations. Based on observations on the feature types that are appropriate for each syntactic unit type, we propose a pattern model based on the composition of features as our ongoing work.

• The KIPS Transactions:PartD
• /
• v.14D no.1 s.111
• /
• pp.83-88
• /
• 2007

In this paper, we introduce MDA based Development Method for Embedded Software Component. This method applies MDA approach to solve problems about reusability of the heterogeneous embedded software system. With our proposed method, we produce 'Target Independent Meta Model'(TIM) which is transformed into 'Target Specific Model'(TSM) and generate 'Target Dependent Code' (TDC) via TSM. We would like to reuse a meta-model to develop heterogeneous embedded software systems. To achieve this mechanism, we extend xUML to solve unrepresented elements (such as real things about concurrency, and real time, etc) on dynamic modeling of the particular system. We introduce 'MDA based Embedded S/W Modeling Tool' with extended XUML. With this tool, we would like to do more easily modeling embedded or concurrent/real time s/w systems. It contains two examples of heterogeneous imbedded systems which illustrate the proposed approach.

• Journal of Broadcast Engineering
• /
• v.17 no.2
• /
• pp.223-236
• /
• 2012

We develop a video processing method that allows the more advanced human perception oriented video coding. The proposed method necessarily reflects all influences by the rate-distortion based optimization and the human visual perception that is affected by the visual saliency, the limited space-time resolution and the regional moving history. For reflecting the human perceptual effects, we devise an online moving pattern classifier using the Hedge algorithm. Then, we embed the existing visual saliency into the proposed moving patterns so as to establish a human visual perception model. In order to realize the proposed human visual perception model, we extend the conventional foveation filtering method. Compared to the conventional foveation filter only smoothing less stimulus video signals, the developed foveation filter can locally smooth and enhance signals according to the human visual perception without causing any artifacts. Due to signal enhancement, the developed foveation filter more efficiently transfers the bandwidth saved at smoothed signals to the enhanced signals. Performance evaluation verifies that the proposed video processing method satisfies the overall video quality, while improving the perceptual quality by 12%~44%.

• Journal of KIISE:Computing Practices and Letters
• /
• v.13 no.2
• /
• pp.100-109
• /
• 2007

Object recognition of service robots is very important for most of services such as delivery, and errand. Conventional methods are based on the geometric models in static industrial environments, but they have limitations in indoor environments where the condition is changable and the movement of service robots occur because the interesting object can be occluded or small in the image according to their location. For solving these uncertain situations, in this paper, we propose the method that exploits observed objects as context information for predicting interesting one. For this, we propose the method for modeling domain knowledge in probabilistic frame by adopting Bayesian networks and ontology together, and creating knowledge model dynamically to extend reasoning models. We verify the performance of our method through the experiments and show the merit of inductive reasoning in the probabilistic model

• Journal of Korea Multimedia Society
• /
• v.12 no.2
• /
• pp.231-243
• /
• 2009

Currently interests of embedded software in various areas such as automotive field, ship field, robot field is increasing according to expand market of embedded systems. Various researches such as embedded operating systems, embedded software modeling technique, embedded software testing, and so on are going in progress. However systematic engineering approach in embedded system development is poor because embedded areas focus on hardware parts until now. Furthermore, framework-based de sign technique considering reusability is not reflected in embedded system development. Those development results in many of dead codes scattered in system, and results in poor reusability of system. This paper suggests a framework of embedded system for reusability and a static meta-model for reuse framework. Proposed meta-model expresses not only the structure of reuse framework, but also allows a designer to extend and design easily models of embedded system based on reuse framework according to various embedded system types.

• Journal of Industrial Convergence
• /
• v.22 no.2
• /
• pp.13-22
• /
• 2024

In the current epoch of educational technology (EdTech), the realization of a personalized learning system has become increasingly important. This is due to the growing diversity of today's learners in terms of backgrounds, learning styles, and abilities. Traditional educational methods that deliver the same content to all learners often fail to take this diversity into account. This paper identifies models that comprehensively analyze learners' characteristics, interests, and learning histories to meet the growing demand for learner-centered education. Based on these models, we have designed a personalized learning system. This system is structured to support autonomous learning tailored to the learner's current level and goals by identifying strengths and weaknesses based on the learner's learning history. In addition, the system is designed to extend necessary learning elements without changing its architecture. Through this research, we can identify the essential foundations for constructing a user-tailored learning system and effectively develop a system architecture to support personalized learning.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.7
• /
• pp.3194-3200
• /
• 2012

The aim of the paper is systematically to organize the historical facts of financial IT development process through various tracking and proved knowledge, it is to propose the direction and the advanced frame of core-banking model in next generation for the year 2020s. To achieve it, this study variously analyzed the meaningful pattern of development process of financial IT by backtracking life-cycle of Core-Banking model and it presented new model of Core-Banking for the past 40 years. In research findings, the life cycle of financial IT system and core-banking model have been analyzed about 10 years and the longest model of life cycle is about 33 years. As a result, It proved to be desirable that the advanced frame of the Core-Banking model adds the functions of business hub and product life cycle management to basic frame of its existing model in the future. In addition, big bang development method of new next generation system must be sublated. Also, They need to be initiated more business-oriented than IT-oriented. Along with this, the financial IT should be developed into the convergence industry, and it needs to extend the systematization of Core-Banking model studies and more professionals. Finally, this study has arranged the financial IT development process in domestic and presents new frame through analyzing intensively the Core-Banking model for the first time Therefore, it can be contributed to serve the guideline regarding the direction in new next generation system.

• The Journal of the Korea Contents Association
• /
• v.22 no.3
• /
• pp.354-360
• /
• 2022

Metabolic disease is a disease with a prevalence of 26% in Korean, and has three of the five states of abdominal obesity, hypertension, hunger glycemic disorder, high neutral fat, and low HDL cholesterol at the same time. This paper links the consumer panel data of the Rural Development Agency(RDA) and the medical care data of the National Health Insurance Service(NHIS) to generate a classification model that can be divided into a metabolic disease group and a control group through food consumption characteristics, and attempts to compare the differences. Many existing domestic and foreign studies related to metabolic diseases and food consumption characteristics are disease correlation studies of specific food groups and specific ingredients, and this paper is logistic considering all food groups included in the general diet. We created a classification model using regression, a decision tree-based classification model, and a classification model using XGBoost. Of the three models, the high-precision model is the XGBoost classification model, but the accuracy was not high at less than 0.7. As a future study, it is necessary to extend the observation period for food consumption in the patient group to more than 5 years and to study the metabolic disease classification model after converting the food consumed into nutritional characteristics.

• Phonetics and Speech Sciences
• /
• v.10 no.1
• /
• pp.33-38
• /
• 2018

Although deep neural network-based acoustic models have greatly improved the performance of automatic speech recognition (ASR), reverberation still degrades the performance of distant speech recognition in indoor environments. In this paper, we adopt the DenseNet, which has shown great performance results in image classification tasks, to improve the performance of reverberant speech recognition. The DenseNet enables the deep convolutional neural network (CNN) to be effectively trained by concatenating feature maps in each convolutional layer. In addition, we extend the concept of multi-resolution CNN to multi-resolution DenseNet for robust speech recognition in reverberant environments. We evaluate the performance of reverberant speech recognition on the single-channel ASR task in reverberant voice enhancement and recognition benchmark (REVERB) challenge 2014. According to the experimental results, the DenseNet-based acoustic models show better performance than do the conventional CNN-based ones, and the multi-resolution DenseNet provides additional performance improvement.