• Journal of the Korean Solar Energy Society
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• v.28 no.3
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• pp.1-6
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• 2008

It is necessary to estimate empirical constants in order to predict the monthly mean daily global radiation on a horizontal surface in the developing areas for alternative energy. Therefore many different equations have proposed to evaluate them for certain areas. In this work a new correlation has been made to predict the solar radiation for any areas over Korea by calculating the regression models taking into account latitude, percentage of possible sunshine, and cloud cover. Results clearly demonstrates the reliability of the single linear equation for the estimation of global radiation, which is proposed by using percentage of possible sunshine method. When compared with the measured values, the average annual deviation falls between -3.1 to +0.6%.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.6
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• pp.403-406
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• 2015

In this paper, we propose a supervoxel clustering-based staircase extraction algorithm to obtain poses and dimensions of staircases from a point cloud. In order to effectively reduce the candidate points and accelerate supervoxel clustering, large planes in the scene, such as walls, floors, and ceilings, are eliminated while scanning the environment. Next, staircase candidates with small planes are initially estimated using supervoxel clustering. Then, parameter values for the staircases are refined, and higher staircases that remain undetected due to occlusion are predicted and generated virtually. Experimental results show that staircases are detected accurately and predicted successfully.

• Journal of Industrial Technology
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• v.18
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• pp.277-287
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• 1998

In this work continuous thermodynamics was adopted for describing the influence of copolymer polydispersity on phase separations in random copolymer solutions. Continuous themodynamic frameworks were formulated using the Flory-Huggin's excess Gibbs free energy model in which the concentration- and temperature-depentent terms of interaction parameter x were modified. Cloud-point curves and coexistence curves of poly(ethylene-vinylactate)/methylacetate solutions and poly(ehtylene-vinylacetate)/ethylacetate solutions were measured, and experimental data were fitted with theoretical relations formulated in this work. Calculated could-point curves were more good ageeable with experimental data than the modified Flory-Huggins's relations. Coexistence curves which were evaluated by using parameters of x estimated from experimental cloud-point curves, were found to coincide with experimental data.

• Journal of Broadcast Engineering
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• v.25 no.1
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• pp.25-35
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• 2020

Recently, the development of image processing technology, as well as hardware performance, has been continuing the research on 3D point processing technology that provides users with free viewing angle and stereoscopic effect in various fields. Point cloud technology, which is a type of representation of 3D point, has attracted attention in various fields because it can acquired/expressed point precisely. However, since Hundreds of thousands, millions of point are required to represent one 3D point cloud content, there is a disadvantage that a larger amount of storage space is required than a conventional 2D content. For this reason, the MPEG (Moving Picture Experts Group), an international standardization organization, is continuing to research how to efficiently compress, store, and transmit 3D point cloud content to users. In this paper, a V-PCC bitstream generated by a V-PCC (Video-based Point Cloud Compression) encoder proposed by the MPEG-I (Immersive) group is composed of an MPU (Media Processing Unit) defined by the MMT. In addition, by extending the signaling message defined in the MMT standard, a parameter for a segmented transmission method of the 3D point cloud content by area and quality parameters considering the characteristic of the 3D point cloud content, so that the quality parameters can be selectively determined according to the user's request. Finally, in this paper, we verify the result through design/implementation of the verification platform based on the proposed technology.

• Asia pacific journal of information systems
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• v.22 no.3
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• pp.99-124
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• 2012

Our society has long been talking about necessity for innovation. Since companies in particular need to carry out business innovation in their overall processes, they have attempted to apply many innovation factors on sites and become to pay more attention to their innovation. In order to achieve this goal, companies has applied various information technologies (IT) on sites as a means of innovation, and consequently IT have been greatly developed. It is natural for the field of IT to have faced another revolution which is called cloud computing, which is expected to result in innovative changes in software application via the Internet, data storing, the use of devices, and their operations. As a vehicle of innovation, cloud computing is expected to lead the changes and advancement of our society and the business world. Although many scholars have researched on a variety of topics regarding the innovation via IT, few studies have dealt with the issue of could computing as IT. Thus, the purpose of this paper is to set the variables of innovation attributes based on the previous articles as the characteristic variables and clarify how these variables affect "Performance Expectancy" of companies and the intention of using cloud computing. The result from the analysis of data collected in this study is as follows. The study utilized a research model developed on the innovation diffusion theory to identify influences on the adaptation and spreading IT for cloud computing services. Second, this study summarized the characteristics of cloud computing services as a new concept that introduces innovation at its early stage of adaptation for companies. Third, a theoretical model is provided that relates to the future innovation by suggesting variables for innovation characteristics to adopt cloud computing services. Finally, this study identified the factors affecting expectation and the intention to use the cloud computing service for the companies that consider adopting the cloud computing service. As the parameter and dependent variable respectively, the study deploys the independent variables that are aligned with the characteristics of the cloud computing services based on the innovation diffusion model, and utilizes the expectation for performance and Intention to Use based on the UTAUT theory. Independent variables for the research model include Relative Advantage, Complexity, Compatibility, Cost Saving, Trialability, and Observability. In addition, 'Acceptance for Adaptation' is applied as an adjustment variable to verify the influences on the expected performances from the cloud computing service. The validity of the research model was secured by performing factor analysis and reliability analysis. After confirmatory factor analysis is conducted using AMOS 7.0, the 20 hypotheses are verified through the analysis of the structural equation model, accepting 12 hypotheses among 20. For example, Relative Advantage turned out to have the positive effect both on Individual Performance and on Strategic Performance from the verification of hypothesis, while it showed meaningful correlation to affect Intention to Use directly. This indicates that many articles on the diffusion related Relative Advantage as the most important factor to predict the rate to accept innovation. From the viewpoint of the influence on Performance Expectancy among Compatibility and Cost Saving, Compatibility has the positive effect on both Individual Performance and on Strategic Performance, while it showed meaningful correlation with Intention to Use. However, the topic of the cloud computing service has become a strategic issue for adoption in companies, Cost Saving turns out to affect Individual Performance without a significant influence on Intention to Use. This indicates that companies expect practical performances such as time and cost saving and financial improvements through the adoption of the cloud computing service in the environment of the budget squeezing from the global economic crisis from 2008. Likewise, this positively affects the strategic performance in companies. In terms of effects, Trialability is proved to give no effects on Performance Expectancy. This indicates that the participants of the survey are willing to afford the risk from the high uncertainty caused by innovation, because they positively pursue information about new ideas as innovators and early adopter. In addition, they believe it is unnecessary to test the cloud computing service before the adoption, because there are various types of the cloud computing service. However, Observability positively affected both Individual Performance and Strategic Performance. It also showed meaningful correlation with Intention to Use. From the analysis of the direct effects on Intention to Use by innovative characteristics for the cloud computing service except the parameters, the innovative characteristics for the cloud computing service showed the positive influence on Relative Advantage, Compatibility and Observability while Complexity, Cost saving and the likelihood for the attempt did not affect Intention to Use. While the practical verification that was believed to be the most important factor on Performance Expectancy by characteristics for cloud computing service, Relative Advantage, Compatibility and Observability showed significant correlation with the various causes and effect analysis. Cost Saving showed a significant relation with Strategic Performance in companies, which indicates that the cost to build and operate IT is the burden of the management. Thus, the cloud computing service reflected the expectation as an alternative to reduce the investment and operational cost for IT infrastructure due to the recent economic crisis. The cloud computing service is not pervasive in the business world, but it is rapidly spreading all over the world, because of its inherited merits and benefits. Moreover, results of this research regarding the diffusion innovation are more or less different from those of the existing articles. This seems to be caused by the fact that the cloud computing service has a strong innovative factor that results in a new paradigm shift while most IT that are based on the theory of innovation diffusion are limited to companies and organizations. In addition, the participants in this study are believed to play an important role as innovators and early adapters to introduce the cloud computing service and to have competency to afford higher uncertainty for innovation. In conclusion, the introduction of the cloud computing service is a critical issue in the business world.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.660-669
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• 2019

Recently, with the development of three-dimensional scanning devices and multi-dimensional array cameras, research is continuously conducted on techniques for handling three-dimensional data in application fields such as AR (Augmented Reality) / VR (Virtual Reality) and autonomous traveling. In particular, in the AR / VR field, content that expresses 3D video as point data has appeared, but this requires a larger amount of data than conventional 2D images. Therefore, in order to serve 3D point cloud content to users, various technological developments such as highly efficient encoding / decoding and storage, transfer, etc. are required. In this paper, V-PCC bit stream created using V-PCC encoder proposed in MPEG-I (MPEG-Immersive) V-PCC (Video based Point Cloud Compression) group, It is defined by the MPEG-DASH (Dynamic Adaptive Streaming over HTTP) standard, and provides to be composed of segments. Also, in order to provide the user with the information of the 3D coordinate system, the depth information parameter of the signaling message is additionally defined. Then, we design a verification platform to verify the technology proposed in this paper, and confirm it in terms of the algorithm of the proposed technology.

• Journal of Internet Computing and Services
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• v.17 no.5
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• pp.51-58
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• 2016

The unprecedented power of cloud computing (CC) that enables free sharing of confidential data records for further analysis and mining has prompted various security threats. Thus, supreme cyberspace security and mitigation against adversaries attack during data mining became inevitable. So, privacy preserving data mining is emerged as a precise and efficient solution, where various algorithms are developed to anonymize the data to be mined. Despite the wide use of generalized K-anonymizing approach its protection and truthfulness potency remains limited to tiny output space with unacceptable utility loss. By combining L-diversity and (${\alpha}$,k)-anonymity, we proposed a hybrid K-anonymity data relocation algorithm to surmount such limitation. The data relocation being a tradeoff between trustfulness and utility acted as a control input parameter. The performance of each K-anonymity's iteration is measured for data relocation. Data rows are changed into small groups of indistinguishable tuples to create anonymizations of finer granularity with assured privacy standard. Experimental results demonstrated considerable utility enhancement for relatively small number of group relocations.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.725-734
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• 2016

For multi-mode radar signals in complex electromagnetic environment, different modes of one emitter tend to be deinterleaved into several emitters, called as "extension", when processing received signals by use of existing sorting methods. The "extension" problem inevitably deteriorates the sorting performance of multi-mode radar signals. In this paper, a novel method based on spatial data mining is presented to address above challenge. Based on theories of data field, we describe the distribution information of feature parameters using potential field, and makes partition clustering of parameter samples according to revealed distribution features. Additionally, an evaluation criterion based on cloud model membership is established to measure the relevance between different cluster-classes, which provides important spatial knowledge for the solution of the "extension" problem. It is shown through numerical simulations that the proposed method is effective on solving the "extension" problem in multi-mode radar signal sorting, and can achieve higher correct sorting rate.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.2
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• pp.123-130
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• 1992

We check up on whether the one-dimensional station precipitation model of Geogakakos and Bras is suitable to the storm model for Chonju station or not. The fundamental variables of the physically based model consists of the pressure at the cloud top, the hight-averaged updraft velocity(HAUV), and the inverse of the average diameter of the hydrometeors(ADH) at cloud base. And they are parameterized by input variables. The parameters are eastimated by the direct search algorithm of Hooke and Jeeves in this paper. The results show that HAUV and ADH are dominant factors to minimize root mean square error between the calculated and the observed rainfall. In this numerical analysis, the deviation between the calculated and the total observed rainfall is small, otherwise the gap for the time distribution is quite big.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.282-285
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• 2007

Satellite observed brightness temperature simulation using a radiative transfer model (here after, RTM) is useful for various fields, for example sensor design and channel selection by using theoretically calculated radiance data, development of satellite data processing algorithm and algorithm parameter determination before launch. This study is focused on elaborating the simulation procedure, and analyzing of difference between observed and modelled clear sky brightness temperatures. For the CMDPS (COMS Meteorological Data Processing System) development, the simulated clear sky brightness temperatures are used to determine whether the corresponding pixels are cloud-contaminated in cloud mask algorithm as a reference data. Also it provides important information for calibrating satellite observed radiances. Meanwhile, simulated brightness temperatures of COMS channels plan to be used for assessing the CMDPS performance test. For these applications, the RTM requires fast calculation and high accuracy. The simulated clear sky brightness temperatures are compared with those of MTSAT-1R observation to assess the model performance and the quality of the observation. The results show that there is good agreement in the ocean mostly, while in the land disagreement is partially found due to surface characteristics such as land surface temperature, surface vegetation, terrain effect, and so on.