• Journal of KIISE:Computer Systems and Theory
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• v.32 no.6
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• pp.314-323
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• 2005

This paper proposes a real-time 3D visualization system for situational awareness of Air force operations. This 3D system of situational awareness supports a high-level commander of Air force during the war game operations. These situation aware supporting data such as the aircraft track data of radar, aircraft schedule database, map and satellite image data are integrated into one structured data and those are visualized as 3D structure. By using an Out-of-Core method, we can visualize a 3D huge data in real-time in mobile notebook environment. The experiment shows several examples of 3D visualization supporting situation awareness for Air force operation.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.4
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• pp.207-218
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• 2019

The purpose of this study is to develop a model that can systematically study the whole learning process of machine learning. Since the existing model describes the learning process with minimum coding, it can learn the progress of machine learning sequentially through the new model, and can visualize each process using the tensor flow. The new model used all of the existing model algorithms and confirmed the importance of the variables that affect the target variable, survival. The used to classification training data into training and verification, and to evaluate the performance of the model with test data. As a result of the final analysis, the ensemble techniques is the all tutorial model showed high performance, and the maximum performance of the model was improved by maximum 5.2% when compared with the existing model using. In future research, it is necessary to construct an environment in which machine learning can be learned regardless of the data preprocessing method and OS that can learn a model that is better than the existing performance.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.11-19
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• 2018

Recently, many companies offer various web-based map that is based on GIS(Geographic Information System) information. Google Map, Open street, Bing Map, Naver Map, Daum Map, Vwolrd Map, etc are the few examples of such system. In this paper, we propose a method to visualize ocean forecasting model data considering the flow diagram of tidal current, streamline expression algorithm, and user convenience by using vector field data information that is currently being served. It is confirmed that the proposed method of the flow diagram of tidal current, and stream line expression algorithm is faster than that of conventional ocean prediction model data by more than 2 times.

• International Journal of Contents
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• v.18 no.1
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• pp.17-26
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• 2022

With the acceleration of urbanization and industrialization, air pollution has become increasingly serious, and the pollution control situation is not optimistic. Climate change has become a major global challenge faced by mankind. To actively respond to climate change, China has proposed carbon peak and carbon neutral goals. However, atmospheric pollutants and meteorological factors that affect air quality are complex and changeable, and the complex relationship and correlation between them must be further clarified. This paper uses China's 2013-2018 high-resolution air pollution reanalysis open data set, as well as statistical methods of the Pearson Correlation Coefficient (PCC) to calculate and visualize the design and analysis of environmental monitoring big data, which is intuitive and it quickly demonstrated the correlation between pollutants and meteorological factors in the temporal and spatial sequence, and provided convenience for environmental management departments to use air quality routine monitoring data to enable dynamic decision-making, and promote global climate governance. The experimental results show that, apart from ozone, which is negatively correlated, the other pollutants are positively correlated; meteorological factors have a greater impact on pollutants, temperature and pollutants are negatively correlated, air pressure is positively correlated, and the correlation between humidity is insignificant. The wind speed has a significant negative correlation with the six pollutants, which has a greater impact on the diffusion of pollutants.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.722-729
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• 2010

Prediction problems are widely used in medical domains. For example, computer aided diagnosis or prognosis is a key component in a CDSS (Clinical Decision Support System). SVMs with nonlinear kernels like RBF kernels, have shown superior accuracy in prediction problems. However, they are not preferred by physicians for medical prediction problems because nonlinear SVMs are difficult to visualize, thus it is hard to provide intuitive interpretation of prediction results to physicians. Nomogram was proposed to visualize SVM classification models. However, it cannot visualize nonlinear SVM models. Localized Radial Basis Function (LRBF) was proposed which shows comparable accuracy as the RBF kernel while the LRBF kernel is easier to interpret since it can be linearly decomposed. This paper presents a new tool named VRIFA, which integrates the nomogram and LRBF kernel to provide users with an interactive visualization of nonlinear SVM models, VRIFA visualizes the internal structure of nonlinear SVM models showing the effect of each feature, the magnitude of the effect, and the change at the prediction output. VRIFA also performs nomogram-based feature selection while training a model in order to remove noise or redundant features and improve the prediction accuracy. The area under the ROC curve (AUC) can be used to evaluate the prediction result when the data set is highly imbalanced. The tool can be used by biomedical researchers for computer-aided diagnosis and risk factor analysis for diseases.

• Spatial Information Research
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• v.18 no.3
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• pp.41-52
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• 2010

This paper analyzed the interregional flow changes of software (SW) industries using a GIS Flow Map. Employment data for SW enterprise headquarters from 1999 until 2008 were constructed according to the Origin-Destination Matrix, and were mapped and analyzed using the Flow Mapper and ArcGIS Flow Data Model. From the result we can identify the decentralization of interregional flow in SW industries and recognize the possibilities of the larger SW enterprises' employment, the higher locational footlooseness. The GIS Flow Map was identified as useful tool for researching growth, decline and spatial movement of industrial clusters that experience business relocation. This method can be applied to understand and visualize urban spatial changes.

• Journal of Biosystems Engineering
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• v.27 no.3
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• pp.227-234
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• 2002

This study was conducted to nondestructively estimate the volumetric information of peach and pit and to visualize the 3D information of internal structure from magnetic resonance imaging(MRI) data. Bruker Biospec 7T spectrometer operating at a proton reosonant frequency of 300 MHz was used for acquisition of MRI data of peach. Image processing algorithms and visualization techniques were implemented by using MATLAB (Mathworks) and Visualization Toolkit(Kitware), respectively. Thresholding algorithm and Kohonen's self organizing map(SOM) were applied to MRI data fur region segmentation. Volumetric information were estimated from segemented images and compared to the actual measurements. The average prediction errors of peach and pit volumes were 4.5%, 26.1%, respectively for the thresholding algorithm. and were 2.1%, 19.9%. respectively for the SOM. Although we couldn't get the statistically meaningful results with the limited number of samples, the average prediction errors were lower when the region segmentation was done by SOM rather than thresholding. The 3D visualization techniques such as isosurface construction and volume rendering were successfully implemented, by which we could nondestructively obtain the useful information of internal structures of peach.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.176-182
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• 2020

In this paper, to analyze the meaning of middle-aged men's economic activities, TEXTOM was used to analyze them. The data collection period is set from 2017 to 2019. Among the collected data, 100 refined words were converted into a matrix in which the degree of social connection was calculated, and the keyword network analysis was performed again with the NetDraw program. According to the study, middle-aged men put more meaning on their current work and family than their future retirement. Also, the related word commonly included in the top five for all three years was 'work'. Related words commonly included in the top 10 were 'old age', 'family', and 'work', and in 2018 and 2019, 'health' was included in the top 10. As a result of this, the middle-aged men living in the modern age are the generation who keep their families through economic activities and are increasingly interested in health and prepare for retirement. Therefore, policy support for stable economic activities is needed to improve the quality of life for middle-aged men. It is necessary to extend the retirement age, expand jobs and provide effective vocational training so that it can handle its role as the head of a family. In addition, measures should be taken to reduce the wage gap between highly skilled and low-skilled workers.

• Proceedings of the Korean Geotechical Society Conference
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• 2001.03a
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• pp.501-508
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• 2001

A graph or topographic map can often convey larger amounts of information in a shorter time than ordinary text-based methods. To visualize information precisely it is necessary to collect all the geological information at design stage, but actually it is almost impossible to bore or explore the entire area to gather the required data. So, tunnel engineers have to rely on the judgement of expert from the limited number of the results of exploration and experiment. In this study, several programs are developed to handle the results of geological investigation with various data processing techniques. The results of the typical case study are also presented. For the electric survey, eleven points are chosen at the valley to measure the resistivity using Schlumberger array. The measured data are interpolated in 3-dimensional space by kriging and the distribution of resistivity are visualized to find weak or fractured zone. The correlation length appears to be around 5 to 20 meter in depth. Regression analyses were performed to find a correlation length. No nugget effect is assumed, and the topographic map, geologic formation, fault zone, joint geometry and the distribution of resistivity are successfully visualized by using the proposed technique.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.387-392
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• 1998

To establish a monthly data collection planning for the Ocean Scanning Multispectral Imager (OSMI), we have examined the global patterns of three impacting factors: pigment concentration, cloud cover, and sun glint. Other than satellite mission constraints (e.g., duty cycle), these three factors are considered critical for the OSMI data collection. The Nimbus-7 Coastal Zone Color Scanner (CZCS) monthly mean products and the International Satellite Cloud Climatology Project (ISCCP) monthly mean products (C2) were used for the analysis of pigment concentration and cloud cover distributions, respectively. And the monthly simulated patterns of sun glint were produced by performing the OSMI orbit prediction and the calculation of sun glint radiances at the top-of-atmosphere (TOA). Using monthly statistics (mean and/or standard deviation) of each factor in the above for a given 10$^{\circ}$ latitude by 10$^{\circ}$ longitude grid, we generated the priority map for each month. The priority maps of three factors for each month were subsequently superimposed to visualize the impact of three factors in all. The initial results illustrated that a large part of oceans in the summer hemisphere was classified into the low priority regions because of seasonal changes of clouds and sun illumination. Sensitivity tests were performed to see how cloud cover and sun glint affect the priority determined by pigment concentration distributions, and consequently to minimize their seasonal effects upon the data collection planning.