• Journal of the Korean Data and Information Science Society
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• 제18권3호
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• pp.809-815
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• 2007

Since Bollerslev(1986), the GARCH model has been popular in analysing the volatility of the financial time series. In real data analysis, practitioners conventionally put the normal assumption on the innovation random variables of the GARCH model, which is often violated. In this paper, we analyse the domestic financial data based on the GARCH(1,1) model and among existing normality tests, perform the Jarque-Bera test based on the residuals. It is shown that the innovation based on the GARCH(1,1) model dose not follow the normality assumption.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권1호
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• pp.228-246
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• 2011

A 3D model based approach for a face representation and recognition algorithm has been investigated as a robust solution for pose and illumination variation. Since a generative 3D face model consists of a large number of vertices, a 3D model based face recognition system is generally inefficient in computation time and complexity. In this paper, we propose a novel 3D face representation algorithm based on a pixel to vertex map (PVM) to optimize the number of vertices. We explore shape and texture coefficient vectors of the 3D model by fitting it to an input face using inverse compositional image alignment (ICIA) to evaluate face recognition performance. Experimental results show that the proposed face representation and recognition algorithm is efficient in computation time while maintaining reasonable accuracy.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2011년도 춘계 학술논문 발표대회 1부
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• pp.145-148
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• 2011

As a futuristic construction model, building information model(BIM) based project management system(PMIS) and mobile PMIS have been showing visible sign. However, researches on the 3D BIM based PMIS using mobile device are hard to find, result from limitation of mobile device application(slow speed at huge BIM file, display size, and etc.) and undefined standard of business processes. Therefore, this research aims at studying feasibility of mobile BIM PMIS based on cloud computing as a business model. In case of applying mobile BIM PMIS, 3D drawings and integrated building informations are possible on mobile devices in real time. it would support increasing the productivity of project participants as designer, engineer, supervisor, and etc. Globally, BIM based PMIS and Mobile BIM system, cloud computing based mobile BIM simulator are in the concept or experimental phase, therefore it is possible to secure global leading technology of IT and construction merger in the mobile BIM.

• 한국실내디자인학회논문집
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• 제24권3호
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• pp.146-155
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• 2015

It is an undeniable fact that the modern people's interest in knowledge and information and their roles are some of the core factors used to define the modern society. Besides, as phenomena indicating and leading the modern society, we have fusion, hybrid and convergence, etc. that combine several different elements into a new one. Such changes in social, cultural and technological circumstances require a paradigm shift for the composition of knowledge and information facilities and space. However, more diversified and advanced recently, interfaces for the delivery of knowledge and information cause users to show new behaviors and even change the spatial concept with space composition elements hybridized. Especially for the space of libraries, it is necessary to access and utilize any forms of knowledge and information data (digital + analog) regardless of time and space limitations and approach with an integrated spatial concept likely to change flexibly depending on social demands. In this light, this study aims to make a basic proposal for sustainable integrated-type hybrid space for the space of a public library in this era of knowledge and information. Particularly, this study intends to seek a way to establish a hybrid space model that can effectively converge the most important factors of the space of libraries (human-space(network)-information). With 18 different cases, this study analyzed knowledge and information composition systems, knowledge and information delivery systems and users' space systems. As a result, this study extracted 3 kinds of models, an information-based model, a culture-based model and an education-based model, with the integrated hybrid space model of knowledge and information facilities

• Journal of the Korean Data and Information Science Society
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• 제13권2호
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• pp.271-284
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• 2002

In this paper we consider the robust inference for the parameter of linear regression model based on weighted least squares. First we consider the sequential test of multiple outliers. Next we suggest the way to assign a weight to each observation $(x_i,\;y_i)$ and recommend the robust inference for linear model. Finally, to check the performance of confidence interval for the slope using proposed method, we conducted a Monte Carlo simulation and presented some numerical results and examples.

• Architectural research
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• 제12권2호
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• pp.15-22
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• 2010

Our prediction model is based on the development of "Semantic Location Model." It embodies geometrical and topological information which can increase the efficiency in prediction and make it easy to manipulate the prediction model. Data mining is being implemented to extract the inhabitant's location patterns generated day by day. As a result, the self-learning system will be able to semantically predict the inhabitant's location in advance. This context-aware system brings about the key component of the ubiquitous computing environment. First, we explain the semantic location model and data mining methods. Then the location prediction model for the ubiquitous computing system is described in details. Finally, the prototype system is introduced to demonstrate and evaluate our prediction model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3791-3805
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• 2016

The visual attention mechanism includes 2 attention models, the bottom-up (B-U) and the top-down (T-D), the physiology of which have not yet been accurately described. In this paper, the visual attention mechanism is regarded as a Bayesian fusion process, and a visual attention model based on particle filter is proposed. Under certain particular assumed conditions, a calculation formula of Bayesian posterior probability is deduced. The visual attention fusion process based on the particle filter is realized through importance sampling, particle weight updating, and resampling, and visual attention is finally determined by the particle distribution state. The test results of multigroup images show that the calculation result of this model has better subjective and objective effects than that of other models.

• 한국음향학회지
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• 제43권2호
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• pp.207-213
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• 2024

본 논문은 기계학습 기반 자동악보전사 모델의 입력에 음악적인 정보를 추가하는 방법을 통해 원하는 성능 향상을 얻는 방법을 다루었다. 여기서, 추가한 음악적인 정보는 각 시간 단위마다 발생하는 음고 개수 정보이며, 이는 정답지에서 활성화되는 음고 개수를 세는 방법으로 획득한다. 획득한 음고 개수 정보는 기존 모델의 입력인 로그 멜-스펙트로그램 아래에 연결하여 사용했다. 본 연구에서는 네 가지 음악 정보를 예측하는 네 종류의 블록이 포함된 자동악보전사 모델을 사용하였으며, 각 블록이 예측해야하는 음악 정보에 해당하는 음고 개수 정보를 기존의 입력에 추가해주는 간단한 방법이 모델의 학습에 도움이 됨을 확인했다. 성능 개선을 검증하기 위하여 MIDI Aligned Piano Sounds(MAPS) 데이터를 활용하여 실험을 진행하였으며, 그 결과 모든 음고 개수 정보를 활용할 경우 프레임 기준 F1 점수에서 9.7 %, 끝점을 포함한 노트 기준 F1 점수에서 21.8 %의 성능 향상을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.907-923
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• 2020

For the severe haze situation in the Beijing-Tianjin-Hebei region, conventional fine particulate matter (PM2.5) concentration prediction methods based on pollutant data face problems such as incomplete data, which may lead to poor prediction performance. Therefore, this paper proposes a method of predicting the PM2.5 concentration based on image analysis technology that combines image data, which can reflect the original weather conditions, with currently popular machine learning methods. First, based on local parameter estimation, autoregressive (AR) model analysis and local estimation of the increase in image blur, we extract features from the weather images using an approach inspired by free energy and a no-reference robust metric model. Next, we compare the coefficient energy and contrast difference of each pixel in the AR model and then use the percentages to calculate the image sharpness to derive the overall mass fraction. Furthermore, the results are compared. The relationship between residual value and PM2.5 concentration is fitted by generalized Gauss distribution (GGD) model. Finally, nonlinear mapping is performed via the wavelet neural network (WNN) method to obtain the PM2.5 concentration. Experimental results obtained on real data show that the proposed method offers an improved prediction accuracy and lower root mean square error (RMSE).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제6권9호
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• pp.2370-2387
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• 2012

A new security management model based on Rough set and Bayesian learner is proposed in the paper. The model focuses on finding out malicious nodes and getting them under control. The degree of dissatisfaction (DoD) is defined as the probability that a node belongs to the malicious node set. Based on transaction history records local DoD (LDoD) is calculated. And recommended DoD (RDoD) is calculated based on feedbacks on recommendations (FBRs). According to the DoD, nodes are classified and controlled. In order to improve computation accuracy and efficiency of the probability, we employ Rough set combined with Bayesian learner. For the reason that in some cases, the corresponding probability result can be determined according to only one or two attribute values, the Rough set module is used; And in other cases, the probability is computed by Bayesian learner. Compared with the existing trust model, the simulation results demonstrate that the model can obtain higher examination rate of malicious nodes and achieve the higher transaction success rate.