• Ocean Science Journal
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• v.43 no.4
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• pp.165-173
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• 2008

In this article, we describe a simple yet effective method for insertion of observational datasets in a mesoscale atmospheric model used in one-dimensional configuration through Nudging. To demonstrate the effectiveness of this technique, vertical profiles of meteorological parameters obtained from GLASS Sonde launches from a tiny island of Kaashidhoo in the Republic of Maldives are injected in a mesoscale atmospheric model - Advanced Regional Prediction System (ARPS), and model simulated parameters are compared with the available observational datasets. Analysis of one-time nudging in the model simulations over Kaashidhoo show that incorporation of this technique reasonably improves the model simulations within a time domain of +6 to +12 Hrs, while its impact on +18 Hrs simulations and beyond becomes literally null.

• The Journal of Society for e-Business Studies
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• v.19 no.3
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• pp.107-123
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• 2014

Current text mining techniques suffer from the problem that the conventional text representation models cannot express the semantic or conceptual information for the textual documents written with natural languages. The conventional text models represent the textual documents as bag of words, which include vector space model, Boolean model, statistical model, and tensor space model. These models express documents only with the term literals for indexing and the frequency-based weights for their corresponding terms; that is, they ignore semantical information, sequential order information, and structural information of terms. Most of the text mining techniques have been developed assuming that the given documents are represented as 'bag-of-words' based text models. However, currently, confronting the big data era, a new paradigm of text representation model is required which can analyse huge amounts of textual documents more precisely. Our text model regards the 'concept' as an independent space equated with the 'term' and 'document' spaces used in the vector space model, and it expresses the relatedness among the three spaces. To develop the concept space, we use Wikipedia data, each of which defines a single concept. Consequently, a document collection is represented as a 3-order tensor with semantic information, and then the proposed model is called text cuboid model in our paper. Through experiments using the popular 20NewsGroup document corpus, we prove the superiority of the proposed text model in terms of document clustering and concept clustering.

• Journal of Astronomy and Space Sciences
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• v.14 no.2
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• pp.202-206
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• 1997

We have modeled the infrared spectral energy distributions of proto stars with close attention to the dust envelopes around the stars. The observed spectral energy distributions are closely compared with our models. The model results and observations are compared on IRAS color-color diagrams. Typical model results can explain the observations fairly well.

• Journal of the Korean Society of Industry Convergence
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• v.22 no.1
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• pp.39-45
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• 2019

We propose an active color model based method for tracking motions of multiple human using a networked multiple-camera system in IoT space as a human-robot coexistent system. An IoT space is a space where many intelligent devices, such as computers and sensors(color CCD cameras for example), are distributed. Human beings can be a part of IoT space as well. One of the main goals of IoT space is to assist humans and to do different services for them. In order to be capable of doing that, IoT space must be able to do different human related tasks. One of them is to identify and track multiple objects seamlessly. In the environment where many camera modules are distributed on network, it is important to identify object in order to track it, because different cameras may be needed as object moves throughout the space and IoT space should determine the appropriate one. This paper describes appearance based unknown object tracking with the distributed vision system in IoT space. First, we discuss how object color information is obtained and how the color appearance based model is constructed from this data. Then, we discuss the global color model based on the local color information. The process of learning within global model and the experimental results are also presented.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.116-121
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• 2020

With the recent development of the 4th Industrial Revolution, efforts have been made to carry out communication in a smart factory, farm, etc. at low cost and reliably. Methods for utilizing empty frequencies using TVWS(TV White Space) have been studied which can be used locally within 30 km. However, there have not been many studies on Path-Loss model considering Korean environment. In this paper, the Path-Loss model is divided into LOS (Line Of Sight) and NLOS (None LOS). In case of LOS model, we checked the difference between Free space model, Friis model, 2-ray model and Hata model with measured data. In the case of NLOS model, we checked the difference between Lee Model, ITU-R526-3 Model with measured data. In order to overcome the difference in Korean environment, we derived a model that can be applied in LOS and NLOS and prove its usefulness through performance evaluation through simulation.

• Korean Institute of Interior Design Journal
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• v.24 no.3
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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 Society of Environmental Restoration Technology
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• v.23 no.4
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• pp.13-30
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• 2020

This study aims to analyze the qualitative and quantitative effects of environmental policies in terms of green space management using logistic regression model(LRM). Landsat satellite imageries in 1985, 1992, 2000, 2008, and 2015 are classified using a hybrid-classification method. Based on these classified maps, logistic regression model having a deforestation tendency of the past is built. Binary green space change map is used for the dependent variable and four explanatory variables are used: distance from green space, distance from settlements, elevation, and slope. The green space map of 2008 and 2015 is predicted using the constructed model. The conservation effect of Ulsan's environmental policies is quantified through the numerical comparison of green area between the predicted and real data. Time-series analysis of green space showed that restoration and destruction of green space are highly related to human activities rather than natural land transition. The effect of green space management policy was spatially-explicit and brought a significant increase in green space. Furthermore, as a result of quantitative analysis, Ulsan's environmental policy had effects of conserving and restoring 111.75㎢ and 175.45㎢ respectively for the periods of eight and fifteen years. Among four variables, slope was the most determinant factor that accounts for the destruction of green space in the city. This study presents logistic regression model as a way of evaluating the effect of environmental policies that have been practiced in the city. It has its significance in that it allows us a comprehensive understanding of the effect by considering every direct and indirect effect from other domains, such as air and water, on green space. We conclude discussing practicability of implementing environmental policy in terms of green space management with the focus on a non-statutory plan.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.381-385
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• 1992

In this paper, dynamic modeling and adaptive control problems for a space robot system are discussed. The space robot consist of a robot manipulator mounted on a free-floating base where no attitude control is applied. Using an extended robot model, the entire space robot can be viewed as an under-actuated robot system. Based on nonlinear control theory, the extended space robot model can then be decomposed into two subsystems: one is input-output exactly linearizable, and the other is unlinearizable and represents an internal dynamics. With this decomposition, a normal form-augmentation approach and an augmented state-feedback control are proposed to facilitate the design of adaptive control for the space robot system against parameter uncertainty, unknown dynamics and unmodeled payload in space applications. We demonstrate that under certain conditions, the entire space robot can be represented as a full-actuated robot system to avoid the inclusion of internal dynamics. Based on the dynamic model, we propose an adaptive control scheme using Cartesian space representation and demonstrate its validity and design procedure by a simulation study.

• Bulletin of the Korean Space Science Society
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• 2011.04a
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• pp.30.1-30.1
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• 2011

We present construction of 3D Earth optical Model for in-orbit performance prediction of L1 halo orbiting earth remote sensing instrument; the Albedo Monitor and Radiometer (Amon-Ra) using Integrated Ray Tracing (IRT) computational technique. The 3 components are defined in IRT; 1) Sun model, 2) Earth system model (Atmosphere, Land and Ocean), 3)Amon-Ra Instrument model. In this report, constructed sun model has Lambertian scattering hemisphere structure. The atmosphere is composed of 16 distributed structures and each optical model includes scatter model with both reflecting and transmitting direction respond to 5 deg. intervals of azimuth and zenith angles. Land structure model uses coastline and 5 kinds of vegetation distribution data structure, and its non-Lambertian scattering is defined with the semi-empirical "parametric kernel method" used for MODIS (NASA) missions. The ocean model includes sea ice cap with the sea ice area data from NOAA, and sea water optical model which is considering non-Lambertian sun-glint scattering. The IRT computation demonstrate that the designed Amon-Ra optical system satisfies the imaging and radiometric performance requirement. The technical details of the 3D Earth Model, IRT model construction and its computation results are presented together with future-works.

• Journal of environmental and Sanitary engineering
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• v.15 no.2
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• pp.65-74
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• 2000

The purpose of this study is to develop the stochastic stream water quality model for the intake station of Chung-Ju city waterworks in the Han river system. This model was based on the theory of Box-Jenkins Multiplicative ARIMA(SARIMA) and the state space model to simulate changes of water qualities. Variable of water qualities included in the model are temperature and dissolved oxygen(DO). The models development were based on the data obtained from Jan. 1990 to Dec. 1997 and followed the typical procedures of the Box-Jenkins method including identification and estimation. The seasonality of DO and temperature data to formulate for the SARIMA model are conspicuous and the period of revolution was twelve months. Both models had seasonality of twelve months and were formulates as SARIMA {TEX}$(2,1,1)(1,1,1)_{12}${/TEX} for DO and temperature. The models were validated by testing normality and independency of the residuals. The prediction ability of SARIMA model and state space model were tested using the data collected from Jan. 1998 to Oct. 1999. There were good agreements between the model predictions and the field measurements. The performance of the SARIMA model and state space model were examined through comparisons between the historical and generated monthly dissolved oxygen series. The result reveal that the state space model lead to the improved accuracy.