• The Bulletin of The Korean Astronomical Society
• /
• v.46 no.1
• /
• pp.39.1-39.1
• /
• 2021

The Local Volume Mapper(LVM) project in the fifth iteration of the Sloan Digital Sky Survey (SDSS-V) will produce large integral-field spectroscopic survey data to understand the physical conditions of the interstellar medium in the Milky Way, the Magellanic Clouds, and other local-volume galaxies. We are developing the LVM Instrument control software. The architecture design of the software follows a hierarchical structure in which the high-level software packages interact with the low-level and mid-level software and hardware components. We adopt the spiral software development model in which the software evolves by iteration of sequential processes, i.e., software requirement analysis, design, code generation, and testing. This spiral model ensures that even after being commissioned, the software can be revised according to new operational requirements. We designed the software by using the Unified Modeling Language, which can visualize functional interactions in structure diagrams. We plan to use the SDSS software framework CLU for the interaction between components, based on the RabbitMQ that implemented the Advanced Message Queuing Protocol (AMQP).

• The Bulletin of The Korean Astronomical Society
• /
• v.46 no.2
• /
• pp.38.1-38.1
• /
• 2021

Dust polarization depends on the physical and mechanical properties of dust, as well as the properties of local environments. To understand how dust polarization varies with grain mechanical properties and the local environment, in this paper, we model the wavelength-dependence polarization of starlight and polarized dust emission by aligned grains by simultaneously taking into account grain alignment and rotational disruption by radiative torques (RATs). We explore a wide range of the local radiation field and grain mechanical properties characterized by tensile strength. We find that the maximum polarization and the peak wavelength shift to shorter wavelengths as the radiation strength U increases due to the enhanced alignment of small grains. Grain rotational disruption by RATs tends to decrease the optical-near infrared polarization but increases the ultraviolet polarization of starlight due to the conversion of large grains into smaller ones. In particular, we find that the submillimeter (submm) polarization degree at 850㎛(P850) does not increase monotonically with the radiation strength or grain temperature (Td), but it depends on the tensile strength of grain materials. Our physical model of dust polarization can be tested with observations toward star-forming regions or molecular clouds irradiated by a nearby star, which have higher radiation intensity than the average interstellar radiation field. Finally, we compare our predictions of the P850-Td relationship with Planck data and find that the observed decrease of P850 with Td can be explained when grain disruption by RATs is accounted for, suggesting that interstellar grains unlikely to have a compact structure but perhaps a composite one. The variation of the submm polarization with U (or Td)can provide a valuable constraint on the internal structures of cosmic dust

• The Journal of Korean Institute of Next Generation Computing
• /
• v.13 no.5
• /
• pp.80-92
• /
• 2017

The popularity of cloud computing has led to the emergence of various types of cloud services, and the hybrid cloud, a deployment model that integrates public cloud and private cloud and offset their shortcomings, is in the spotlight recently. However, the complexity of different clouds integration and the lack of related integration solutions have delayed the adoption of hybrid cloud and cloud strategy by companies and organizations. Therefore, in this paper, we propose a cloud integration mechanism to solve the integration complexity problem. The cloud integration mechanism proposed in this paper consists of integration script that solves the cloud integration by the script based on the hybrid cloud function, a process of creating and executing it, and a script creation model applying the software design pattern. By integrating the various cloud services, we can quickly generate scripts that meet the user's needs. It is expected that the introduction of hybrid cloud and the acquisition of cloud strategy can be accelerated through this proposed integration mechanism.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.28 no.3D
• /
• pp.417-422
• /
• 2008

With standard orthorectification algorithms, one can produce unacceptable structure duplication in the orthophoto due to the double projection. Because of the abrupt height differences, such structure duplication is a frequently occurred phenomenon in the dense urban area which includes multi-history buildings. Therefore, occlusion area detection especially for the urban area is a critical issue in generation of true orthophoto. This paper deals with occlusion area detection with visible height based approach from aerial imagery and LiDAR. In order to accomplish this, a grid format DSM is produced from the point clouds of LiDAR. Next, visible height based algorithm is proposed to detect the occlusion area for each camera exposure station with DSM. Finally, generation of true orthophoto is presented with DSM and previously produced occlusion maps. The proposed algorithms are applied in the Purdue campus, Indiana, USA.

• Journal of Hydrogen and New Energy
• /
• v.34 no.5
• /
• pp.526-534
• /
• 2023

To evaluate the risk of leakage when using liquid hydrogen, a leakage test was conducted using liquid nitrogen in an outdoor environment rather than a laboratory environment. To assume a real-scale continuous leak, liquid nitrogen was allowed to leak for 5 minutes through a pipe with a diameter of 25.4 mm at a design spill rate of 60 L/min. The measurement system consisted of devices for climate conditions, LN2 spread and vapor clouds. The main experimental results are the liquid pool radius and the concentration of vapor cloud, and the radius of the liquid pool was compared with the numerical analysis results.

• Journal of Environmental Science International
• /
• v.32 no.12
• /
• pp.883-898
• /
• 2023

To investigate the occurrence characteristics and types of fog on the Korean Peninsula over the past three years (2020 to 2022), data from 96 synoptic meteorological observatories and 21 ocean buoys were collected and analyzed. We included precipitation fog, which occurs after precipitation events, and cloud-base lowering fog, which is caused by the development of lower-level clouds, with a total six subtypes of fog. In the case of cloud-base lowering fog, the occurrence frequency at 2.6% was not high at 2.6%, but the duration of low visibility below 200 m was very long at 6.9 hours. The seasonal frequency of fog is low in spring and winter, high in summer over islands and coastal areas, and high in autumn over inland areas. The frequency of inland fog, which is characterized by high radiation fog and dense fog, requires attention in terms of transportation safety, with an occurrence time of 0500 LST to 1000 LST. Therefore, systematic analysis of precipitation fog and cloud-base lowering, as well as radiation and advection fog, is required in the analysis of recognizing fog as a disaster and causing transportation disorders.

• Korean Journal of Remote Sensing
• /
• v.39 no.5_1
• /
• pp.507-519
• /
• 2023

Multi-temporal optical images have been utilized for time-series monitoring of croplands. However, the presence of clouds imposes limitations on image availability, often requiring a cloud removal procedure. This study assesses the applicability of various machine learning algorithms for effective cloud removal in optical imagery. We conducted comparative experiments by focusing on two key variables that significantly influence the predictive performance of machine learning algorithms: (1) land-cover types of training data and (2) temporal variability of land-cover types. Three machine learning algorithms, including Gaussian process regression (GPR), support vector machine (SVM), and random forest (RF), were employed for the experiments using simulated cloudy images in paddy fields of Gunsan. GPR and SVM exhibited superior prediction accuracy when the training data had the same land-cover types as the cloud region, and GPR showed the best stability with respect to sampling fluctuations. In addition, RF was the least affected by the land-cover types and temporal variations of training data. These results indicate that GPR is recommended when the land-cover type and spectral characteristics of the training data are the same as those of the cloud region. On the other hand, RF should be applied when it is difficult to obtain training data with the same land-cover types as the cloud region. Therefore, the land-cover types in cloud areas should be taken into account for extracting informative training data along with selecting the optimal machine learning algorithm.

• Journal of The Korean Astronomical Society
• /
• v.56 no.1
• /
• pp.75-89
• /
• 2023

We investigate the astronomical phenomenon records of Sukjong's Chunbang-Ilgi made by Sigangwon (Royal Educational Office of the Crown Prince) at which King Sukjong was the crown prince (i.e., 1667 January 24-1674 September 22). From the daily records of 2,799 days, we extract the astronomical records of 1,443 days and classify them into 14 categories. Then, we group the records of each category into five phenomena (Atmosphere, Eclipse, Daylight Appearance, Apparition, and Appulse) and compare them with the results of modern astronomical computations wherever possible. Except for Atmosphere group comprising records of meteorological events, such as solar halo, lunar halo, and unusual clouds, the significant findings in every other group are as follows: In Eclipse group, the solar eclipse that occurred on 1673 August 12 was unobservable in Korea, which is in contrast to the record of Joseonwangjo-Sillok (Annals of the Joseon Dynasty), which states that the sun was in eclipse around sunset time, as observed at Nam mountain. From the lunar eclipse records, we verify that the Joseon court did not change the date of the events observed after midnight. In Daylight Appearance group, we confirm that this phenomenon was observed during the daytime and not during twilight. We further suggest that if observation conditions are met, a celestial body brighter than -2.3 mag could be seen during the daytime with the naked-eye. In Apparition group, we find the possibilities that the Orionid meteor shower had influence on the meteor records and the seasonality on the aurora records. We also find that the Korean records in which the coma of comet C/1668 E1 was located below the horizon were overlooked in previous studies. Finally, we find that the records of Appulse group generally agree with the results of modern calculations. The records of Beom (trespass in literal) and Sik (eating in literal) events show average angular separations of 1.2° and 1.0°, respectively. In conclusion, we believe this work helps study the astronomical records of other logs of Sigangwon, such as Sukjong's Chunbang-Ilgi.

• Journal of KIBIM
• /
• v.13 no.4
• /
• pp.96-105
• /
• 2023

This study focuses on developing a building object recognition technology for efficient use in the remodeling of buildings constructed without drawings. In the era of the 4th industrial revolution, smart technologies are being developed. This research contributes to the architectural field by introducing a deep learning-based method for automatic object classification and recognition, utilizing point cloud data. We use a TD3D network with voxels, optimizing its performance through adjustments in voxel size and number of blocks. This technology enables the classification of building objects such as walls, floors, and roofs from 3D scanning data, labeling them in polygonal forms to minimize boundary ambiguities. However, challenges in object boundary classifications were observed. The model facilitates the automatic classification of non-building objects, thereby reducing manual effort in data matching processes. It also distinguishes between elements to be demolished or retained during remodeling. The study minimized data set loss space by labeling using the extremities of the x, y, and z coordinates. The research aims to enhance the efficiency of building object classification and improve the quality of architectural plans by reducing manpower and time during remodeling. The study aligns with its goal of developing an efficient classification technology. Future work can extend to creating classified objects using parametric tools with polygon-labeled datasets, offering meaningful numerical analysis for remodeling processes. Continued research in this direction is anticipated to significantly advance the efficiency of building remodeling techniques.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.44 no.1
• /
• pp.125-132
• /
• 2024

Optical satellite images are being used for national security and collection of information, and their utilization is increasing. However, it acquires low-quality images that are not suitable for the user's requirement due to weather conditions and time constraints. In this paper, a deep learning-based conversion of image and colorization model referring to high-resolution SAR images was created to simulate the occluded area with clouds of optical satellite images. The model was experimented according to the type of algorithm applied and input data, and each simulated images was compared and analyzed. In particular, the amount of pixel value information between the input black-and-white image and the SAR image was similarly constructed to overcome the problem caused by the relatively lack of color information. As a result of the experiment, the histogram distribution of the simulated image learned with the Gray-scale image and the high-resolution SAR image was relatively similar to the original image. In addition, the RMSE value was about 6.9827 and the PSNR value was about 31.3960 calculated for quantitative analysis.