• Korean Journal of Remote Sensing
• /
• v.36 no.5_4
• /
• pp.1153-1166
• /
• 2020

The purpose of this study was to analyze the spatial correlation between the heat distribution map of the satellite imaging base and the factors that deepen the heat wave, and to explore the heat concentration area and the space where the risk of future heat wave may increase. The global Moran's I of population, land use, and buildings, which are the causes of heat concentration and heat wave deepening, is found to be high and concentrated in specific spaces. According to the analysis results of local Moran's I, heat concentration areas appeared mainly in large cities such as metropolitan and metropolitan areas, and forests were dominant in areas with relatively low temperatures. Areas with high population growth rates were distributed in the surrounding areas of Gyeonggi-do, Daejeon, and Busan, and the use of land and buildings were concentrated in the metropolitan area and large cities. Analysis by Bivarate Local Moran's I has shown that population growth is high in heat-intensive areas, and that artificial and urban building environments and land use take place. The results of this research can lead to the ranking of heat concentration areas and explore areas with environments where heat concentration is concentrated nationwide and deepens it, so ultimately it is considered to contribute to the establishment of preemptive measures to deal with extreme heat.

• Journal of Korea Game Society
• /
• v.17 no.5
• /
• pp.113-122
• /
• 2017

The location of the objects that make up a game can be an element of immersion for players. repeatedly appearing at the same position, the fun may be reduced, and as the play time elapses, the players will feel the game's fun as they appear in a larger area than at the beginning of the game play. This paper is a study to find out the location of objects according to the passage of time and to see how players controlled these objects. First, foreground images are extracted and accumulated using OpenCV programming language. The accumulated result is displayed as a heat map image. Second, the mouse movement area is detected using the mouse tracking program and compared with the heat map image, so that the screen area in which the player is interested can be known.

• Smart Media Journal
• /
• v.9 no.3
• /
• pp.46-51
• /
• 2020

Pine wilt disease is one of the reasons that results in huge damage on pine trees in east Asia including Korea, Japan, and China, and early finding and removing the diseased trees is an efficient way to prevent the forest from wide spreading. This paper proposes a searching method of the damaged pine trees from wilt disease in ortho-images corrected from RGB images, which are captured by unmanned aviation vehicles. The proposed method constructs patch-based classifier using ResNet18 backbone network, classifies the RGB ortho-image patches, and make the results as a heat map. The heat map can be used to find the distribution of diseased pine trees, to show the trend of spreading disease, and to extract the RGB distribution of the diseased areas in the image. The classifier in the work shows 94.7% of accuracy.

• KIPS Transactions on Software and Data Engineering
• /
• v.10 no.9
• /
• pp.349-358
• /
• 2021

Recently, a method of finding the attention area or localization area for an object of an image using CAM (Class Activation Map)[1] has been variously carried out as a study of WSOL (Weakly Supervised Object Localization). The attention area extraction from the object heat map using CAM has a disadvantage in that it cannot find the entire area of the object by focusing mainly on the part where the features are most concentrated in the object. To improve this, using CAM and Selective Search[6] together, we first expand the attention area in the heat map, and a Gaussian smoothing is applied to the extended area to generate retraining data. Finally we train the data to expand the attention area of the objects. The proposed method requires retraining only once, and the search time to find an localization area is greatly reduced since the selective search is not needed in this stage. Through the experiment, the attention area was expanded from the existing CAM heat maps, and in the calculation of IOU (Intersection of Union) with the ground truth for the bounding box of the expanded attention area, about 58% was improved compared to the existing CAM.

• Journal of the Korean Society of Combustion
• /
• v.17 no.1
• /
• pp.48-57
• /
• 2012

Laminar lifted propane coflow-jet flames diluted with nitrogen were experimentally investigated to determine heat-loss-related self-excitation regimes in the flame stability map and elucidate the individual flame characteristics. There exists a critical lift-off height over which flame-stabilizing effect becomes minor, thereby causing a normal heat-loss-induced self-excitation with O(0.01 Hz). Air-coflowing can suppress the normal heat-loss-induced self-excitation through increase of a Peclet number; meanwhile it can enhance the normal heat-lossinduced self-excitation through reducing fuel concentration gradient and thereby decreasing the reaction rate of trailing diffusion flame. Below the critical lift-off height. the effect of flame stabilization is superior, leading to a coflow-modulated heat-loss-induced self-excitation with O(0.001 Hz). Over the critical lift-off height, the effect of reducing fuel concentration gradient is pronounced, so that the normal heat-loss-induced self-excitation is restored. A newly found prompt self-excitation, observed prior to a heat-loss-induced flame blowout, is discussed. Heat-loss-related self-excitations, obtained laminar lifted propane coflow-jet flames diluted with nitrogen, were characterized by the functional dependency of Strouhal number on related parameters. The critical lift-off height was also reasonably characterized by Peclet number and fuel mole fraction.

• International Journal of Contents
• /
• v.13 no.2
• /
• pp.21-28
• /
• 2017

Abnormal data in the manufacturing process makes it difficult to find useful information that can be applied in data management for the manufacturing industry. It causes various problems in the daily process of production. An issue from the abnormal data can be handled by our method that uses big data and visualization. Visualization is a new technology that transforms data representation into a two-dimensional representation. Nowadays, many newly developed technologies provide data analysis, algorithm, optimization, and high efficiency, and they meet user requirements. We propose combined production of the data visualization approach that uses integrative visualization of sources of abnormal pattern analysis results. The perceived idea of the proposed approach can solve the problem as it also works for big data. It can also improve the performance and understanding by using visualization and solving issues that occur in the manufacturing process with a calendar heat map.

• Journal of the Korean Society for Heat Treatment
• /
• v.30 no.5
• /
• pp.187-196
• /
• 2017

High temperature flow behaviors of AISI 4340 steel were investigated using isothermal compression tests under the temperature range from 850 to $1100^{\circ}C$ and a strain rate from 0.01 to $10s^{-1}$. The flow stress decreased with increasing compression temperature and decreasing strain rate. The dynamic softening related to the dynamic recrystallization was observed during hot deformation. The constitutive model based on Arrheniustyped equation with the Zener-Hollomon parameter was used to simulate the hot deformation behavior of AISI 4340 steel. The modification of the Zener-Hollomon parameter and lnA parameter resulted in the improvement of the calculation accuracy of the proposed constitutive model compared with the experimental flow curves. In addition, the process map of AISI 4340 steel was proposed. The instable process condition for hot deformation was predicted and its reliability was verified with the experimental observation.

• Journal of Broadcast Engineering
• /
• v.24 no.4
• /
• pp.564-572
• /
• 2019

With the development of deep learning, the performance of facial landmark detection methods has been greatly improved. The heat map regression method, which is a representative facial landmark detection method, is widely used as an efficient and robust method. However, the landmark coordinates cannot be directly obtained through a single network, and the accuracy is reduced in determining the landmark coordinates from the heat map. To solve these problems, we propose to combine integral regression with the existing heat map regression method. Through experiments using various datasets, we show that the proposed integral regression network significantly improves the performance of facial landmark detection.

• Nuclear Engineering and Technology
• /
• v.32 no.4
• /
• pp.395-409
• /
• 2000

Parametric studies were performed to assess the sensitivity in determining the maximum in-vessel heat removal capability from the core material relocated into the lower plenum of the reactor pressure vessel (RPV）during a core melt accident. A fraction of the sensible heat can be removed during the molten jet delivery from the core to the lower plenum, while the remaining sensible heat and the decay heat can be transported by rather complex mechanisms of the counter-current flow limitation (CCFL) and the critical heat flux (CHF）through the irregular, hemispherical gap that may be formed between the freezing oxidic debris and the overheated metallic RPV wall. It is shown that under the pressurized condition of 10MPa with the sensible heat loss being 50% for the reactors considered in this study, i.e. TMI-2, KORI-2 like, YGN-3&4 like and KNGR like reactors, the heat removal through the gap cooling mechanism was capable of ensuring the RPV integrity as much as 30% to 40% of the total core mass was relocated to the lower plenum. The sensitivity analysis indicated that the cooling rate of debris coupled with the sensible heat loss was a significant factor The newly proposed heat removal capability map (HRCM) clearly displays the critical factors in estimating the maximum heat removal from the debris in the lower plenum. This map can be used as a first-principle engineering tool to assess the RPV thermal integrity during a core melt accident. The predictive model also provided ith a reasonable explanation for the non-failure of the test vessel in the LAVA experiments performed at the Korea Atomic Energy Research Institute (KAERI), which apparently indicated a cooling effect of water ingression through the debris-to-vessel gap and the intra-debris pores and crevices.

• Journal of Climate Change Research
• /
• v.9 no.3
• /
• pp.209-221
• /
• 2018

The characteristics of heat wave events in Seoul are analyzed using weather station data from Korea Meteorological Administration (KMA) and European Centre for Medium-Range Weather Forecast (ECMWF) ERA-Interim reanalysis data from 1979 to 2016. Heat waves are defined as events in the upper 10th percentile of the daily maximum temperatures. The associated synoptic weather patterns are then classified into six clusters through Self-Organizing Map (SOM) analysis for sea-level pressure anomalies in East Asia. Cluster 1 shows an anti-cyclonic circulation and weak troughs in southeast and west of Korea, respectively. This synoptic pattern leads to southeasterly winds that advect warm and moist air to the Korean Peninsula. Both clusters 2 and 3 are associated with southerly winds formed by an anti-cyclonic circulation over the east of Korea and cyclonic circulation over the west of Korea. Cluster 4 shows a stagnant weather pattern with weak winds and strong insolation. Clusters 5 and 6 are associated with F?hn wind resulting from an anti-cyclonic circulation in the north of the Korean Peninsula. In terms of long-term variations, event frequencies of clusters 4 and 5 show increasing and decreasing trends, respectively. However, other clusters do not show any long-term trends, indicating that the mechanisms that drive heat wave events in Seoul have remained constant over the last four decades.