• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.343-348
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• 2019

In this paper, a dual-band antenna is proposed for the autonomous vehicle as well as omni-directional. The proposed antenna operates in the 4G/LTE band (1,710~2,170MHz) and 5G/NR band (3,400~3,700MHz). In order to obtain the dual-band operation, the planar monopole antenna is proposed as the novel structure with single port of the 50ohm. To give the properties of dual-band, an additional antenna element with slit was added to the planar monopole antenna, and then a structural adjustment parameter was optimized for achieving the target performance in bands. The planar monopole antenna in the LTE band acts as the coupled feed for the added parasitic radiator in the 5G NR band. The proposed antenna has $38.5{\times}36.0{\times}1.0[mm^3]$ on a ground with diameter of 96mm. From the fabrication and measurement results, the impedance bandwidth (VSWR<2) of the proposed antenna covers 1,480~2,260MHz (LTE band: 1,710~2,170MHz) and 3,310~3,930MHz (5G NR band: 3,400~3,700MHz). The proposed planar monopole antenna also obtained the measured gain and radiation pattern of omni-directional radiation pattern in the anechoic chamber.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.35-51
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• 2019

The two main goals of this study are to derive independent factors affecting the success rate of crowdfunding and to empirically analyze the variation of independent factors' effects on the success of crowdfunding by industry (Internet, culture/art, manufacturing/distribution), and funding type (stock type, bond type). To identify the success factors of crowdfunding for invigoration and strategic utilization, first, several variables were refined after interviews with experts and platform operators with investment experiences in numerous crowdfunding projects. Then, independent factors affecting project involvement were categorized as follows: a characteristic of project, participant activity, and enterprise. Also, the results derived from the influence of independent variables on crowdfunding after moderating effects were driven. Selected independent factors in this study are as follows: crowdfunding period, target amount, visual contents, minimum account money, number of comments, number of SNS followers, level of interest, financial Statement disclosure, investment attraction, venture company, intellectual property rights disclosure, and business operation period. Selected moderating factors in this study are as follows: industry (Internet, culture/art, manufacturing/distribution), and funding type (stock type, bond type). In conclusion, a discussion of the academical and practical implications and a suggestion of directions for further research are explained.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.191-199
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• 2021

A distillation column, which is a main facility of the chemical process, separates the desired product from a mixture by using the difference of boiling points. The distillation process requires the optimization and the prediction of operation because it consumes much energy. The target process of this study is difficult to operate efficiently because the composition of feed flow is not steady according to the supplier. To deal with this problem, we could develop a data-driven model to predict operating conditions. However, data preprocessing is essential to improve the predictive performance of the model because the raw data contains outlier and noise. In this study, after optimizing the predictive model based long-short term memory (LSTM) and Random forest (RF), we used a low-pass filter and one-class support vector machine for data preprocessing and compared predictive performance according to the method and range of the preprocessing. The performance of the predictive model and the effect of the preprocessing is compared by using R2 and RMSE. In the case of LSTM, R2 increased from 0.791 to 0.977 by 23.5%, and RMSE decreased from 0.132 to 0.029 by 78.0%. In the case of RF, R2 increased from 0.767 to 0.938 by 22.3%, and RMSE decreased from 0.140 to 0.050 by 64.3%.

• Journal of the Korean Society of Radiology
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• v.15 no.1
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• pp.37-43
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• 2021

Republic of Korea has many nuclear facilities in the country, and Democratic People's Republic of Korea(North Korea) locates in the surrounding country. Therefore, it is necessary to construct the target facility's nuclear forensic data in a preemptive response to the changing international situation. For this reason, this study suggests "signature" materials used to understand the origins and sources of nuclear and other radioactive materials, taking into account domestic nuclear facilities and the nuclear fuel cycle. In domestic, pressurized light water reactors and pressurized heavy water reactors are in operation, and enriched and natural uranium are used as fuels. In the front-end fuel cycle, the signature materials can be nature uranium and UF6 in the uranium enrichment process. The domestic back-end fuel cycle adopts a non-circulating cycle excluding the reprocessing process, and the primary signature material is spent nuclear fuel. According to IAEA recommendation, the importance of these materials as the signature and characteristic contents are suggested in this study. To prove the integrity of nuclear material and build a national nuclear forensics library, it is necessary to grasp the signature material and acquire the characteristic data considering the domestic nuclear facilities and the nuclear fuel cycle.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.

• Ecology and Resilient Infrastructure
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• v.7 no.4
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• pp.327-335
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• 2020

The method of selecting an existing flood hazard area via a numerical model requires considerable time and effort. In this regard, this study proposes a method for selecting flood vulnerable areas through topographic analysis based on a surface runoff mechanism to reduce the time and effort required. Flood vulnerable areas based on runoff mechanisms refer to those areas that are advantageous in terms of the flow accumulation characteristics of rainfall-runoff water at the surface, and they generally include lowlands, mild slopes, and rivers. For the analysis, a digital topographic map of the target area (Seoul) was employed. In addition, in the topographic analysis, eight topographic factors were considered, namely, the elevation, slope, profile and plan curvature, topographic wetness index (TWI), stream power index, and the distances from rivers and manholes. Moreover, receiver operating characteristic analysis was conducted between the topographic factors and actual inundation trace data. The results revealed that four topographic factors, namely, elevation, slope, TWI, and distance from manholes, explained the flooded area well. Thus, when a flood vulnerable area is selected, the prioritization method for various factors as proposed in this study can simplify the topographical analytical factors that contribute to flooding.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.627-636
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• 2021

Although many studies on ship detection using synthetic aperture radar (SAR) satellite images are being conducted around the world, there are still very few employing SAR microsatellites, as most of the microsatellites are optical satellites. Recently, the ICEYE and Capella Space have embarked on the development of microsatellites with SAR sensor, and similar projects are being initiated globally in line with the flow of the new space era [e.g., for the ICEYE: 18 satellites (~2021); Capella Space: 36 satellites (~2023); and the Coast Guard SAR: 32 satellites in the early development stage]. In preparation for these new systems, it is important to review the SAR microsatellite system and the recent advances in this technology. Accordingly, in this paper, the current status and characteristics of optical and SAR microsatellite constellation operation are described, and studies using them are investigated. In addition, based on the status and characteristics of the representative SAR microsatellites, specifically the ICEYE and Capella systems, methods for using SAR microsatellite data for ship detection applications are described. Our results confirm that the SAR microsatellites operate as a constellation and have the advantages of short revisit cycles and quick provision of high-resolution images. With this technology, we expect SAR microsatellites to contribute greatly to the monitoring a wide-area target vessel, in which the spatiotemporal resolution of the imagery is especially important.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.591-598
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• 2021

One of the requirements of metro trains is to stop with precision to ensure that the train can stop precisely at the designated location on the platform. If this is not satisfied, interference with the screen door occurs, causing inconvenience to passengers and delays in operation. In the case of an automatic operated train, the current position is determined by the current speed information of the train, and control is performed by issuing an acceleration/deceleration command. Therefore, accurate control becomes impossible if the error of the speed information is large. In metro railroads, a Precision Stop Marker (PSM) is used to correct the position error, so that the error of stop control can be reduced by correcting the position error at a specific point. On the other hand, because the PSM itself has only position information, it does not compensate for the speed error. This paper proposes a method for performing in-place stop control by estimating the speed with the PSM progress information. The speed can be estimated when the train is operated at a constant deceleration speed, and the target deceleration can be obtained to perform stop control. The feasibility and excellence of the proposed method are shown through a numerical simulation.

• The Journal of the Korean Institute of Forest Recreation
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• v.22 no.4
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• pp.1-9
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• 2018

This study aimed to improve the quality of forest healing program through analyses of the program activities given at National Healing Forest and surveys conducted by Korea Forest Service. 99 DB data of the healing forest that were surveyed by KFS (August 2015~April 2016) were collected in order to affirm the activities. We analysed DB based on the format of the survey by target, 6 healing factors, location, season, time periods, operation hours and multifaceted evaluation. The results showed that the activities in the forest healing program targeted general public and the factor that was considered the most was psychotherapy factor. Healing forest trails were used as a location, spring, summer and fall as season, morning and afternoon as time period for the majority of the activities. The running time was 60 minutes. The multifaceted evaluation revealed that dynamic activities were preferred the most in development of programs. According to the results of the forest healing programs, it seems to be critical to enhance forest healing instructors' diversified professionalism. However, this will only be achievable once further investigations regarding forest healing effects by types of illnesses are conducted and provide solid foundation for such professionalism.

• The Journal of Bigdata
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• v.5 no.2
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• pp.17-27
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• 2020

District heating system supplies heat from low-cost high-efficiency heat production facilities to heat demand areas through a heat pipe network. For efficient heat supply system operation, it is important to accurately predict the heat demand within the region and optimize the heat production plan accordingly. In this study, a heat demand forecasting model is proposed considering real-time calorimeter information from local heat demands. Previous models considered ambient temperature and heat demand history data to predict future heat demands. To improve forecast accuracy, the proposed heat demand forecast model added big data from real-time calorimeters installed in the heat demands within the target region. By employing calorimeter information directly in the model, it is expected that the proposed forecast model is to reflect heat use pattern of each demand. Computational experiemtns based on the actual heat demand data shows that the forecast accuracy of the proposed model improved when the calorimeter big data is reflected.