• Journal of the Korean Society of Marine Environment & Safety
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• v.13 no.2 s.29
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• pp.147-153
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• 2007

In this paper, the authors calculated maneuvering motions of a large container vessel approaching to the newly built container piers to get alongside to her berth in Busan harbour. The motion calculations were done by using fixed coordinate system and the object of the calculations is to check the maneuvering motions are safe or not for berthing the large vessel to her berth. The result of calculations manifested that a large container vessel can get alongside to the piers without any difficulty under normal weather conditions by using 2 Z. Peller tug boats of 4500 H.P. each and also these demonstrated it is difficult to conduct and get her alongside to the piers under rough weather conditions of wind force 16.9m/sec or more. Under rough weather conditions of 6 by Beaufort scale the average wind velocity is about 13.5m and if we add 25% increase of the normal velocity to it, the wind will becomes a gust of 16.9m/sec. So it is advisable to avoid conducting a large container vessel to the pier under the rough weather conditions of 6 or more by Beaufort scale. Also, it is better to use 3 Z. peller tug boats of 4500 H.P. each under the above mentioned rough weather in a case of unavoidable circumstances.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.223-233
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• 2018

In this study was classified the cadastral control points and parcel boundary points into 40m, 100m by flight altitude of UAV (Unmanned Aerial Vehicle) which compared the coordinates extracted from the orthophoto with the parcel boundary point coordinates by GNSS (Global Navigation Satellite System) ground survey. As a results of this study, first, in the spatial resolution analysis that the average error of the orthoimage by flight altitude were 0.024m at 40m, and 0.034m at 100m which were higher 40m than 100m for spatial resolution of orthophotos and position accuracy. Second, in order to analyze the accuracy of image recognition by airmark of flight altitude that was divided into three cases of nothing, green, and red of RMSE (Root Mean Square Error) were X=0.039m, Y=0.019m and Z=0.055m, the highest accuracy. Third, the result of the comparison between orthophotos and field survey results that showed the total RMSE error of the cadastral control points were X=0.029m, Y=0.028m, H=0.051m, and the parcel boundary points were X=0.041m, Y=0.030m. In conclusion, based on the results of this study, it is expected that if the average error of flight altitude is limited to less than 0.05m in the legal regulations related to orthophotos for cadastral surveying, it will be an economical and efficient method for cadastral survey as well as spatial information acquisition.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.1
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• pp.64-73
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• 2015

Recently, the integrated utilization of technology with IT is in demand for the effectiveness of field management together with the prevention and prompt action on safety accident at construction site. In addition, the establishment of construction site support system is necessary to implement the securing of worker's safety, smooth work instruction, efficiency in construction, and others. Data standardization and network architecture were designed regarding data and sound information for data transmission between systems and management. These were to construct USFSS based on integrated VI-GNSS technology in this research. In the stability test of data for each system constructed through it, around 98% stability was secured between workers and for transfer vehicle system within underground structure and field server system in regards to the data transmission stability, around 100% stability was secured between field server system and control system, respectively. Also, in the sound transmission stability test, around 99% reliability could be secured with 1km distance as its standard in case of sound transmission from underground structure construction site to field office near the field through wireless FRS system.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.207-215
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• 2022

This research has been focused on accessing precision and accuracy of UAV (Unmanned Aerial Vehicle)-derived 3-D surveying coordinates. To this end, a highly precise and accurate testing control network had been established by GNSS (Global Navigation Satellite Systems) campaign and its network adjustment. The coordinates of the ground control points and the check points were estimated within 1cm accuracy for 95% of the confidence level. FC330 camera mounted on DJI Phantom 4 repeatedly took aerial photos of an experimental area seven times, and then processed them by two widely used software packages. To evaluate the precision and accuracy of the aerial surveys, 3-D coordinates of the ten check points which automatically extracted by software were compared with GNSS solutions. For the 95% confidence level, the standard deviation of two software's result is within 1cm, 2cm, and 4cm for the north-south, east-west, and height direction, and RMSE (Root Mean Square Error) is within 9cm and 8cm for the horizontal, vertical component, respectively. The interest is that the standard deviation is much smaller than RMSE. The F-ratio test was performed to confirm the statistical difference between the two software processing results. For the standard deviation and RMSE of most positional components, exception of RMSE of the height, the null hypothesis of the one-tailed tests was rejected. It indicates that the result of UAV photogrammetry can be different statistically based on the processing software.

• Journal of Space Technology and Applications
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• v.2 no.3
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• pp.195-205
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• 2022

Space exploration is an area where international cooperation takes place more actively than any other space activities such as Earth observation, communication and navigation. This is because a country cannot afford a huge budget to have full infrastructure for deep space exploration, such as a heavy launch vehicle, communication and energy infrastructure, and human habitats, and has learned that it is not sustainable. Korea expressed its willingness to join humanity's epic exploration journey by signing the Artemis Accords in 2021 and launching Danuri lunar orbiter in 2022. The beginning of space exploration means that Korea's space activities have expanded beyond the stage of focusing only on technology development to set norms necessary to accompany other countries and cooperate diplomatically to solve exposed problems. This paper analyzed European space policy and space exploration, which are most actively participating in the Artemis Program and exerting diplomatic power in the space field, from the perspective of science and technology diplomacy. The suggestions for Korea's space exploration strategy from the perspective of science and technology diplomacy were drawn by examining the international cooperation strategies in Europe's space activities ranging from space policy, space strategy, and space exploration program to project units.

• Journal of Technology Innovation
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• v.26 no.3
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• pp.37-68
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• 2018

Since the 20th century, automobiles, which are the most common means of transportation, have been evolving as the use of electronic control devices and automotive semiconductors increases dramatically. Automotive semiconductors are a key component in automotive electronic control devices and are used to provide stability, efficiency of fuel use, and stability of operation to consumers. For example, automotive semiconductors include engines control, technologies for managing electric motors, transmission control units, hybrid vehicle control, start/stop systems, electronic motor control, automotive radar and LIDAR, smart head lamps, head-up displays, lane keeping systems. As such, semiconductors are being applied to almost all electronic control devices that make up an automobile, and they are creating more effects than simply combining mechanical devices. Since automotive semiconductors have a high data rate basically, a microprocessor unit is being used instead of a micro control unit. For example, semiconductors based on ARM processors are being used in telematics, audio/video multi-medias and navigation. Automotive semiconductors require characteristics such as high reliability, durability and long-term supply, considering the period of use of the automobile for more than 10 years. The reliability of automotive semiconductors is directly linked to the safety of automobiles. The semiconductor industry uses JEDEC and AEC standards to evaluate the reliability of automotive semiconductors. In addition, the life expectancy of the product is estimated at the early stage of development and at the early stage of mass production by using the reliability test method and results that are presented as standard in the automobile industry. However, there are limitations in predicting the failure rate caused by various parameters such as customer's various conditions of use and usage time. To overcome these limitations, much research has been done in academia and industry. Among them, researches using data mining techniques have been carried out in many semiconductor fields, but application and research on automotive semiconductors have not yet been studied. In this regard, this study investigates the relationship between data generated during semiconductor assembly and package test process by using data mining technique, and uses data mining technique suitable for predicting potential failure rate using customer bad data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.4
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• pp.63-68
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• 2018

The establishment of Ground Control Points (GCPs) in UAV-Photogrammetry is a working process that requires the most time and expenditure. Recently, the rapid developments of navigation sensors and communication technologies have enabled Unmanned Aerial Vehicles (UAVs) to conduct photogrammetric mapping without using GCP because of the availability of new methods such as RTK (Real Time Kinematic) and PPK (Post Processed Kinematic) technology. In this study, an experiment was conducted to evaluate the potential of RTK-UAV mapping with no GCPs compared to that of non RTK-UAV mapping. The positioning accuracy results produced by images obtained simultaneously from the two different types of UAVs were compared and analyzed. One was a RTK-UAV without GCPs and the other was a non RTK-UAV with different numbers of GCPs. The images were taken with a Canon IXUS 127 camera (focal length 4.3mm, pixel size $1.3{\mu}m$) at a flying height of approximately 160m, corresponding to a nominal GSD of approximately 4.7cm. As a result, the RMSE (planimetric/vertical) of positional accuracy according to the number of GCPs by the non-RTK method was 4.8cm/8.2cm with 5 GCPs, 5.4cm/10.3cm with 4 GCPs, and 6.2cm/12.0cm with 3 GCPs. In the case of non RTK-UAV photogrammetry with no GCP, the positioning accuracy was decreased greatly to approximately 112.9 cm and 204.6 cm in the horizontal and vertical coordinates, respectively. On the other hand, in the case of the RTK method with no ground control point, the errors in the planimetric and vertical position coordinates were reduced remarkably to 13.1cm and 15.7cm, respectively, compared to the non-RTK method. Overall, UAV photogrammetry supported by RTK-GPS technology, enabling precise positioning without a control point, is expected to be useful in the field of spatial information in the future.

• Korean Journal of Remote Sensing
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• v.37 no.5_1
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• pp.1135-1147
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• 2021

In order to geometrically correct high-resolution satellite imagery, the sensor modeling process that restores the geometric relationship between the satellite sensor and the ground surface at the image acquisition time is required. In general, high-resolution satellites provide RPC (Rational Polynomial Coefficient) information, but the vendor-provided RPC includes geometric distortion caused by the position and orientation of the satellite sensor. GCP (Ground Control Point) is generally used to correct the RPC errors. The representative method of acquiring GCP is field survey to obtain accurate ground coordinates. However, it is difficult to find the GCP in the satellite image due to the quality of the image, land cover change, relief displacement, etc. By using image maps acquired from various sensors as reference data, it is possible to automate the collection of GCP through the image matching algorithm. In this study, the RPC of KOMPSAT-3A satellite image was corrected through the extracted matching point using the UAV (Unmanned Aerial Vehichle) imagery. We propose a pre-porocessing method for the extraction of matching points between the UAV imagery and KOMPSAT-3A satellite image. To this end, the characteristics of matching points extracted by independently applying the SURF (Speeded-Up Robust Features) and the phase correlation, which are representative feature-based matching method and area-based matching method, respectively, were compared. The RPC adjustment parameters were calculated using the matching points extracted through each algorithm. In order to verify the performance and usability of the proposed method, it was compared with the GCP-based RPC correction result. The GCP-based method showed an improvement of correction accuracy by 2.14 pixels for the sample and 5.43 pixelsfor the line compared to the vendor-provided RPC. In the proposed method using SURF and phase correlation methods, the accuracy of sample was improved by 0.83 pixels and 1.49 pixels, and that of line wasimproved by 4.81 pixels and 5.19 pixels, respectively, compared to the vendor-provided RPC. Through the experimental results, the proposed method using the UAV imagery presented the possibility as an alternative to the GCP-based method for the RPC correction.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.

• Journal of Service Research and Studies
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• v.12 no.1
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• pp.25-35
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• 2022

Covid-19, of which the first patient in Korea occurred in January 2020, has affected various fields. Of these, the tourism sector might havebeen hit the hardest. In particular, since tourism-based industrial structure forms the basis of the region, Gangwon-province, and the tourism industry is the main source of income for small businesses and small enterprises, the damage is great. To check the situation and extent of such damage, targeting the Chuncheon region, where public access is the most convenient among the Gangwon regions, one-day tours are possible using public transportation from Seoul and the metropolitan area, with a general image that low expense tourism is recognized as possible, this study conducted empirical analysis through data analysis. For this, the general status of the region was checked based on the visitor data of Chuncheon city provided by the tourist information system, and to check the levels ofinterest in 2019, before Covid-19, and in 2020, after Covid-19, by comparing keywords collected from the web service sometrend of Vibe Company Inc., a company specializing in keyword collection, with SK Telecom's T-map search site data, which in parallel provides in-vehicle navigation service and communication service, this study analyzed the general regional image of Chuncheon-city. In addition, by comparing data from two years by developing a tourism popularity index applying keywords and T-map search site data, this study examined how much the Covid-19 situation affected the level of interest of visitors to the Chuncheon area leading to actual visits using a data analysis approach. According to the results of big data analysis applying the tourism popularity index after designing the data mart, this study confirmed that the effect of the Covid-19 situation on tourism popularity in Chuncheon-city, Gangwon-provincewas not significant, and confirmed the image of tourist destinations based on the regional characteristics of the region. It is hoped that the results of this research and analysis can be used as useful reference data for tourism economic policy making.