• The Journal of the Korea Contents Association
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• v.17 no.2
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• pp.327-336
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• 2017

People spend most of their time in the indoor environment. Among the various indoor environmental factors, air and thermal environment directly affect human's health and efficiency of work. Therefore, efficient monitoring of indoor environment is highly important. For assisting the residents to understand the state of the indoor environment much easier and more intuitive, this paper analyze the visualization cases of the conventional indoor environment. Then explore the direction of improvement for the visualization method to propose a more effective visualization method. The approach of web and BIM(Building Information Model)-based visualization of indoor environment proposed in this study is composed of four major parts: 1) the generation of the model data of the building; 2) the generation of indoor environmental data; 3) the creation of visualization elements; 4) data mapping. Then it realized through the generating process of visualization results.

• Journal of Korean Society of Environmental Engineers
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• v.22 no.10
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• pp.1833-1841
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• 2000

Microelectrode probe was made and applied to the biofilm in the biological treatment process as the state-of-art technology in order to actually measure the biofilm thickness, ionic concentration gradient, and material transport, etc. instead of classical theoretical approach. The working microelectrode, one of the main components of microelectrode probe, was easily contaminated and broken when determining the differences in the ionic concentrations through the measurement of biofilm's EMF (electromotive force). As a demonstration, two microelectrode probes were constructed in our lab for the measurement of the pH and $NO_3{^-}$ concentration in denitrifying biofilm. The microelectrode probe through the inner biofilm ($350{\mu}m$ from the surface of biofilm) showed that the pH was increased from pH 8 in the bulk solution to pH 8.3, on the other hand, the $NO_3{^-}$ concentration was decreased from 30 fig N/L in the bulk solution to 4 fig N/L.

• Journal of the Korea Society of Computer and Information
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• v.16 no.12
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• pp.1-10
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• 2011

As requirements of embedded system get complicated, the tool for analyzing the reliability of embedded software is being needed. A probabilistic modeling is used as the way of analyzing the reliability of a software and to apply it to embedded software controlling multiple devices. So, it is necessary to specialize that to embedded software. Also, existing reliability analyzers should measure the transition probability of each condition in different ways and doesn't consider reusing the model once used. In this paper, we suggest a reliability analyzer for embedded software using embedded software Markov chin model and a unit testing tool. Embedded software Markov chain model is model specializing Markov chain model which is used for analyzing reliability to an embedded software. And a unit testing tool has host-target structure which is appropriate to development environment of embedded software. This tool can analyze the reliability more easily than existing tool by automatically measuring the transition probability between units for analyzing reliability from the result of unit testing. It can also directly apply the test result updated by unit testing tool by representing software model as a XML oriented document and has the advantage that many developers can access easily using the web oriented interface and SVN store. In this paper, we show reliability analyzing of a example by so doing show usefulness of reliability analyzer.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.9
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• pp.733-742
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• 2016

In recent years, gas engines fueled with LNG or synthetic gas have been attracting considerable attention for marine use owing to their potential to facilitate better fuel economy and to reduce emissions. It has been confirmed that gas engines using the Otto cycle, which involves premixed combustion, can satisfy Tier III regulations without the EGR or SCR system. The objective of this study is to acquire simulation technologies for predicting gas engine performances in industrial fields. Using the commercial software BOOST, the simulation is conducted on a gasoline engine rather than a marine engine due to the gasoline engine's easier accessibility. This study consists of two stages. In the first stage published previously, the optimal modeling techniques for representing the behavior of the gas in the intake and exhaust systems were determined. In the current study, we formulated a method to evaluate the combustion and heat transfer processes in the cylinder and to ultimately determine the major performance parameters, given that the analytical model derived from the previous stage has been applied. Through this study, we were able to determine a combustion and heat transfer model and a valve discharge coefficient that are less reliant on empirical data: we were also able to formulate a methodology through which relevant constants are decided. We confirmed that the values of transient cylinder pressure variation, indicated mean effective pressure, and air supply can be successfully predicted using our modeling techniques.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.4
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• pp.397-405
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• 2019

Quantitative electroencephalography (QEEG) has been widely used in research and clinical fields. QEEG has been widely used to objectively document cerebral changes for the purpose of identifying the electrophysiological biomarkers across various clinical symptoms and for the stimulation of specific cortical regions associated with cognitive function. In electroencephalography (EEG), the difference in quantitative and qualitative analyses is discriminated not by its measurement methods and relevant clinical or research environments, but by its analysis methods. When performing a qualitative analysis, it is possible for a medical technologist or experienced researchers to read the EEG waveforms to exclude artifacts. However, the quantitative analysis is still based on mathematical modeling, and all EEG data are included for the analysis, leading the results to be affected by unexpected artifacts. In the hospital setting, the case that the medical technologists in charge of the EEG test perform academic research has been little reported, compared to other clinical physiological measurement-based research. This is because there are few laboratories specialized in clinical physiological research. In this respect, this study is expected to be utilized as a basic reference material for medical technologists, students, and academic researchers, all of whom would like to conduct a quantitative analysis.

• Information Systems Review
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• v.24 no.1
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• pp.59-87
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• 2022

Since over-the-top (OTT) service has emerged as a new way of consuming video contents, OTT markets grow exponentially and the competition among the OTT services becomes intense. Only limited systematic research effort has been paid to understand why users subscribe such OTT services among other services. Therefore, we used developmental sequential mixed methods approach to find out the quality factors and their effect on post-subscription experiences and continuance intention. In the qualitative study, we derived six factors which a user considers important to continue the subscription. Based on the explored factors, we hypothesized a research model with modified three qualities from ISSM. The proposed research model was validated through quantitative research, a survey of 226 OTT service users in South Korea, using structural equation modeling. The results indicated that content quality is the key factor affecting both perceived enjoyment and satisfaction whereas system quality affects satisfaction, and service quality only affects enjoyment. Enjoyment affects satisfaction which sequentially affects continuance usage intention. This study contributes to research by modifying ISSM through mixed methods. It also provides OTT service providers with insight to enhance users' post experience and continuance intention to use the service through qualities derived from the interview.

• Korean Journal of Optics and Photonics
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• v.16 no.3
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• pp.182-190
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• 2005

The fiber Raman amplifier(FRA) is a distinctly advantageous technology. Due to its wider, flexible gain bandwidth, and intrinsically lower noise characteristics, FRA has become an indispensable technology of today. Various FRA modeling methods, with different levels of convergence speed and accuracy, have been proposed in order to gain valuable insights for the FRA dynamics and optimum design before real implementation. Still, all these approaches share the common platform of coupled ordinary differential equations(ODE) for the Raman equation set that must be solved along the long length of fiber propagation axis. The ODE platform has classically set the bar for achievable convergence speed, resulting exhaustive calculation efforts. In this work, we propose an alternative, highly efficient framework for FRA analysis. In treating the Raman gain as the perturbation factor in an adiabatic process, we achieved implementation of the algorithm by deriving a recursive relation for the integrals of power inside fiber with the effective length and by constructing a matrix formalism for the solution of the given FRA problem. Finally, by adiabatically turning on the Raman process in the fiber as increasing the order of iterations, the FRA solution can be obtained along the iteration axis for the whole length of fiber rather than along the fiber propagation axis, enabling faster convergence speed, at the equivalent accuracy achievable with the methods based on coupled ODEs. Performance comparison in all co-, counter-, bi-directionally pumped multi-channel FRA shows more than 102 times faster with the convergence speed of the Average power method at the same level of accuracy(relative deviation < 0.03dB).

• Korean Journal of Cognitive Science
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• v.28 no.2
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• pp.111-131
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• 2017

The connectionist model is one approach to studying language processing from a computational perspective. And building a representation in the connectionist model study is just as important as making the structure of the model in that it determines the level of learning and performance of the model. The connectionist model has been constructed in two different ways: localist representation and distributed representation. However, the localist representation used in the previous studies had limitations in that the unit of the output layer having a rare target activation value is inactivated, and the past distributed representation has the limitation of difficulty in confirming the result by the opacity of the displayed information. This has been a limitation of the overall connection model study. In this paper, we present a new method to induce distributed representation with local representation using abstraction of information, which is a feature of restricted Boltzmann machine, with respect to the limitation of such representation of the past. As a result, our proposed method effectively solves the problem of conventional representation by using the method of information compression and inverse transformation of distributed representation into local representation.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.487-501
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• 2020

As a viable option for retrieval of LST (Land Surface Temperature), this paper presents a DNN (Deep Neural Network) based approach using 148 Landsat 8 images for South Korea. Because the brightness temperature and emissivity for the band 10 (approx. 11-㎛ wavelength) of Landsat 8 are derived by combining physics-based equations and empirical coefficients, they include uncertainties according to regional conditions such as meteorology, climate, topography, and vegetation. To overcome this, we used several land surface variables such as NDVI (Normalized Difference Vegetation Index), land cover types, topographic factors (elevation, slope, aspect, and ruggedness) as well as the T₀ calculated from the brightness temperature and emissivity. We optimized four seasonal DNN models using the input variables and in-situ observations from ASOS (Automated Synoptic Observing System) to retrieve the LST, which is an advanced approach when compared with the existing method of the bias correction using a linear equation. The validation statistics from the 1,728 matchups during 2013-2019 showed a good performance of the CC=0.910~0.917 and RMSE=3.245~3.365℃, especially for spring and fall. Also, our DNN models produced a stable LST for all types of land cover. A future work using big data from Landsat 5/7/8 with additional land surface variables will be necessary for a more reliable retrieval of LST for high-resolution satellite images.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.34-47
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• 2018

As interest in advanced countries regarding the convergence technology development increases, a methodology for identifying the core convergence technology that has a large spill-over effect on the technology and industry is required for the nation's competitiveness enhancement in the convergence technology field. Based on patent citation network analysis using 1,124 USPTO patents in the ICT convergence technology field of the smart factory, this study examined the proposed heterogeneous technology convergence index as a tool for measuring the convergence characteristics of the spillovers compared to other indexes (i.e. other sector ratio index and homogeneous technology convergence index). The proposed heterogeneous technology convergence index was used to investigate core technology sectors among ICT technology sectors of smart factory identified by government ministries. Results found 6 core ICT convergence technology sectors including the manufacturing execution analysis application sector. Also, this study conducted blockmodeling analysis using the IPC codes of patents in the manufacturing execution analysis application sector, and identified that the blocks representing the electronic communication and electric digital data processing technology sectors (Block 3 & 4) are related technology sectors which can be converged with core technology. Based on the findings, the implications for the convergence technology development planning of the smart factory field are discussed.