• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.77-84
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• 2022

A submarine power cable is a transmission cable for carrying electric power below the surface of the water. Recently, submarine cables transfer power from offshore renewable energy schemes to shore, e.g. wind, wave and tidal systems, and these cables are either buried in the seabed or lie on the ocean floor, depending on their location. Since these power cables are used in the extreme environments, they are made to withstand in harsh conditions and temperatures, and strong currents. However, undersea conditions are severe enough to cause all sorts of damage to offshore cables, these conditions result in cable faults that disrupt power transmission. In this paper, we explore the design criteria for such cables and the procedures and challenges of installation, and cable transfer splicing system. The specification of submarine cable designed with 3 circuits of 154kV which is composed of the existing single circuit and new double circuits, and power capacity of 100MVA per cable line. The determination of new submarine cable burial depth and cable arrangement method with both existing and new cables are studied. We have calculated the permission values of cable power capacity for underground route, the values show the over 100MW per cable line.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.2
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• pp.178-188
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• 2022

The introduction of virtual power plants is actively being discussed to solve the problem of grid acceptability caused by the spread of distributed renewable energy, which is the key to achieving carbon neutrality. However, a new business such as virtual power plants is difficult to secure economic feasibility at the initial stage of introduction because it is common that there is no compensation mechanism. Therefore, appropriate support including subsidy is required at the early stage. But, it is generally difficult to obtain the cost model to determine the subsidy level because of the lack of enough data for the new business model. In this study, a survey of domestic experts on the requirements, appropriate scale, and cost required for the introduction of virtual power plants is conducted. First, resource composition scenarios are designed from the survey results to consider the impact of the resource composition on the cost. Then, the cost estimation model is obtained using the individual cost estimation data for their resource compositions using logistic regression analysis. In the case study, appropriate initial subsidy levels are analyzed and compared for the virtual power plants on the scale of 20-500MW. The results show that mid-to-large resource composition cases show 29-51% lower cost than small-to-large resource composition cases.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.367-374
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• 2022

The purpose of this study was to propose a deep learning algorithm that applies to the fault diagnosis of fuel pumps and purifiers of autonomous ships. A deep learning algorithm reflecting the time dependence of the measured signal was configured, and the failure pattern was trained using the vibration signal, measured in the equipment's regular operation and failure state. Considering the sequential time-dependence of deterioration implied in the vibration signal, this study adopts Conv1D with sliding window computation for fault detection. The time dependence was also reflected, by transferring the measured signal from two-dimensional to three-dimensional. Additionally, the optimal values of the hyper-parameters of the Conv1D model were determined, using the grid search technique. Finally, the results show that the proposed data preprocessing method as well as the Conv1D model, can reflect the sequential dependency between the fault and its effect on the measured signal, and appropriately perform anomaly as well as failure detection, of the equipment chosen for application.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.190-196
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• 2023

Recently, following the development of LIDAR technology which can detect distance from the object, the interest for LIDAR based 3D object detection network is getting higher. Previous networks generate inaccurate localization results due to spatial information loss during voxelization and downsampling. In this study, we propose an attention-based convergence method and a camera-LIDAR convergence system to acquire high-level features and high positional accuracy. First, by introducing the attention method into the Voxel-RCNN structure, which is a grid-based 3D object detection network, the multi-scale sparse 3D convolution feature is effectively fused to improve the performance of 3D object detection. Additionally, we propose the late-fusion mechanism for fusing outcomes in 3D object detection network and 2D object detection network to delete false positive. Comparative experiments with existing algorithms are performed using the KITTI data set, which is widely used in the field of autonomous driving. The proposed method showed performance improvement in both 2D object detection on BEV and 3D object detection. In particular, the precision was improved by about 0.54% for the car moderate class compared to Voxel-RCNN.

• Journal of Korean Society of Transportation
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• v.19 no.4
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• pp.35-47
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• 2001

Traffic represents one of the largest sources of primary air pollutants in urban area. As a consequence. numerous abatement strategies are being pursued to decrease the ambient concentration of pollutants. A characteristic of most of the these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emission inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for vehicle types. The majority of inventories are compiled using passive data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. The study of current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this study, a methodology of motor vehicle emission calculation by using real-time traffic data was studied. A methodology for estimating emissions of CO at a test area in Seoul. Traffic data, which are required on a street-by-street basis, is obtained from induction loops of traffic control system. It was calculated speed-related mass of CO emission from traffic tail pipe of data from traffic system, and parameters are considered, volume, composition, average velocity, link length. And, the result was compared with that of a method of emission calculation by VKT(Vehicle Kilometer Travelled) of vehicles of category.

• Progress in Medical Physics
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• v.27 no.1
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• pp.31-36
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• 2016

The paper discusses radiation dose of dual energy CT on which copper modulation layer, is mounted in order to improve diagnostic performance of the dual energy CT. The radiation dose is estimated using MCNPX and its results are compared with that of the conventional dual energy CT system. CT X-ray spectra of 80 and 120 kVp, which are usually used for thorax, abdominal, head, and neck CT scans, were generated by the SPEC78 code and were used for the source specification 'SDEF' card for MCNPX dose modeling. The copper modulation layer was located 20 cm away from a source covering half of the X-ray window. The radiation dose was measured as changing its thickness from 0.5 to 2.0 mm at intervals of 0.5 mm. Since the MCNPX tally provides only normalized values to a single particle, the dose conversion coefficients of F6 tally for the modulation layer-based dual energy CBCT should be calculated for matching the modeling results into the actual dose. The dose conversion coefficient is $7.2*10^4cGy/output$ that is obtained from dose calibration curve between F6 tally and experimental results in which GAFCHORMIC EBT3 films were exposed by an already known source. Consequently, the dose of the modulation layer-based dual energy cone beam CT is 33~40% less than that of the single energy CT system. On the basis of the results, it is considered that scattered dose produced by the copper modulation layer is very small. It shows that the modulation layer-based dual energy CBCT system can effectively reduce radiation dose, which is the major disadvantage of established dual energy CT.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.109-119
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• 2016

The height datum of Korea is currently separated into land and sea, which makes it difficult to acquire homogeneous and accurate height information throughout the whole nation. In this study, we therefore tried to suggest the more effective way to transform the height information were constructed separately according to each height datum on land and sea to those on the unique height datum using precise geoid models and tidal observations in Korea. For this, Anmyeon island was selected as a study area to develop the precise geoid models based on the height datums land (IMSL) and sea (LMSL), respectively. In order to develop two hybrid geoid models based on each height datum of land an sea, we firstly develop a precise gravimetric geoid model using the remove and restore (R-R) technique with all available gravity observations. The gravimetric geoid model were then fitted to the geometric geoidal heights, each of which is represented as height datum of land or sea respectively, obtained from GPS/Leveling results on 15 TBMs in the study area. Finally, we determined the differences between the two hybrid geoid models to apply the height transformation between IMSL and LMSL. The co-tidal chart model of TideBed system developed by Korea Hydrographic and Oceanographic Agency (KHOA) which was re-gridded to have the same grid size and coverage as the geoid model, in order that this can be used for the height datum transformation from LMSL to local AHHW and/or from LMSL to local DL. The accuracy of height datum transformation based on the strategy suggested in this study was approximately ${\pm}3cm$. It is expected that the results of this study can help minimize not only the confusions on the use of geo-spatial information due to the disagreement caused by different height datum, land and sea, in Korea, but also the economic and time losses in the execution of coastal development and disaster prevention projects in the future.

• Environmental and Resource Economics Review
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• v.31 no.2
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• pp.165-204
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• 2022

This study organized data from 2000 to 2014 for 20 grid-connected countries in Europe and analyzed the determinants of carbon emissions through the panel GLS method considering the problem of heteroscedasticity and autocorrelation. At the same time, the effect of introducing ETS was considered by dividing the sample period as of 2005 when the European emission trading system was introduced. Carbon emissions from individual countries were used as dependent variables, and proportion of generation by each source, power self-sufficiency ratio of neighboring countries, power production from resource-holding countries, concentration of power sources, total energy consumption per capita in the industrial sector, tax of electricity, net electricity export per capita, and size of national territory per capita. According to the estimation results, the proportion of nuclear power and renewable energy generation, concentration of power sources, and size of the national territory area per capita had a negative (-) effect on carbon emissions both before and after 2005. On the other hand, the proportion of coal power generation, the power supply and demand rate of neighboring countries, the power production of resource-holding countries, and the total energy consumption per capita in the industrial sector were found to have a positive (+) effect on carbon emissions. In addition, the proportion of gas generation had a negative (-) effect on carbon emissions, and tax of electricity were found to have a positive (+) effect. However, all of these were only significant before 2005. It was found that net electricity export per capita had a negative (-) effect on carbon emissions only after 2005. The results of this study suggest macroscopic strategies to reduce carbon emissions to green growth, suggesting mid- to long-term power mix optimization measures considering the electricity trade market and their role.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.1-21
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• 2012

In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.153-163
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• 2017

The objective of this study is to enhance the model's speed of estimating weather variables (e.g., minimum/maximum temperature, sunshine hour, PRISM (Parameter-elevation Regression on Independent Slopes Model) based precipitation), which are applied to the Agrometeorological Early Warning System (http://www.agmet.kr). The current process of weather estimation is operated on high-performance multi-core CPUs that have 8 physical cores and 16 logical threads. Nonetheless, the server is not even dedicated to the handling of a single county, indicating that very high overhead is involved in calculating the 10 counties of the Seomjin River Basin. In order to reduce such overhead, several cache and parallelization techniques were used to measure the performance and to check the applicability. Results are as follows: (1) for simple calculations such as Growing Degree Days accumulation, the time required for Input and Output (I/O) is significantly greater than that for calculation, suggesting the need of a technique which reduces disk I/O bottlenecks; (2) when there are many I/O, it is advantageous to distribute them on several servers. However, each server must have a cache for input data so that it does not compete for the same resource; and (3) GPU-based parallel processing method is most suitable for models such as PRISM with large computation loads.