• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.55-66
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• 2007

There has been increasing concerns regarding marine mineral resources as the land energy resources has been depleting from worldwide energy crisis. Also, all the coastal countries around the world are getting into the high competition as EEZ implemented to widen each country's marine autonomy. Especially, the adoption of EEZ in UN's marine regulation agreement at the January of 1996 has aggravated conflicts among coastal countries and eventually resulted in critical agenda to determine the boundaries of EEZ among such countries. It is imperative for us to have negotiation with neighboring countries to determine the boundaries of EEZ. For the preparation of such negotiation, it is essential to have data such as mineral distribution, deep-sea geology, related agreement and marine laws, etc. Therefore, this study mainly concentrates on analyzing existing data of resources exploration and establishing standards for each type of data and manipulating data based on such standards, thereby building a database for more efficient management of EEZ data from marine resources survey. MRIS has also been developed to diversely analyze and visualize graphic and attribute data considering data usage and inter-relationship in the database. This system can provide various spatial analysis and spatial searching techniques to enable easier comparison of cost-benefit analysis and data provision of any area in EEZ thereby facilitating major policy making. In addition, the system can support sustainable management of marine resources of EEZ regions and data supply for systematic management of national marine resources. Furthermore, this will be very useful for negotiating with neighboring countries to determine EEZ boundaries to lead more favorable results.

• Journal of Korea Spatial Information System Society
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• v.8 no.3
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• pp.105-115
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• 2006

A sensor network which uses DCS(Data-Centric Storage) stores the same data into the same sensor node. Thus it has a hot spot problem when the sensor network grows and the same data arise frequently. In the past researches of the sensor network using DCS, the hot spot problem caused by growing the sensor network was ignored because they only concentrated on managing stored sensor data efficiently. In this paper, we proposed a non-equal region split method that supports efficient scalability on storing multi-dimensional sensor data. This method can reduce the storing cost, as the sensor network is growing, by dividing whole space into regions which have the same number of sensor nodes according to the distribution of sensor nodes, and storing and managing sensor data within each region. Moreover, this method can distribute the energy consumption of sensor nodes by increasing the number of regions according to the size of the sensor network, the number of sensor nodes within the sensor network, and the quantity of sensor data. Therefore it can help to increase the life time and the scalability of the sensor network.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.213-220
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• 2015

Wireless sensor network(WSN) is made up of a lot of battery operated inexpensive sensors that, once deployed, can not be replaced. Therefore, energy efficiency of WSN is essential. Among the methods for energy efficiency of the network, clustering algorithms, which divide a WSN into multiple smaller clusters and separate all sensors into cluster heads and their associated member nodes, are very energy efficient routing technique. The first cluster-based routing protocol, LEACH, randomly elects the cluster heads in accordance with the probability. However, if the distribution of selected cluster heads is not good, uniform energy consumption of cluster heads is not guaranteed and it is possible to decrease the number of active nodes. Here we propose a new routing scheme that, by comparing the remaining energy of all nodes in a cluster, selects the maximum remaining energy node as a cluster head. Because of decrease in energy gap of nodes, the node that was a cluster head operates as a member node much over. As a result, the network lifespan is increased and more data arrives at base station.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.237-242
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• 2014

Recently, wind energy is expanding to combination of computing to forecast of wind power generation as well as intelligent of wind powerturbine. Wind power is rise and fall depending on weather conditions and difficult to predict the output for efficient power production. Wind power is need to reliably linked technology in order to efficient power generation. In this paper, distributed power generation forecasts to enhance the predicted and actual power generation in order to minimize the difference between the power of distributed power short-term prediction model is designed. The proposed model for prediction of short-term combining the physical models and statistical models were produced in a physical model of the predicted value predicted by the lattice points within the branch prediction to extract the value of a physical model by applying the estimated value of a statistical model for estimating power generation final gas phase produces a predicted value. Also, the proposed model in real-time National Weather Service forecast for medium-term and real-time observations used as input data to perform the short-term prediction models.

• Journal of Digital Convergence
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• v.12 no.3
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• pp.211-218
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• 2014

Recently, wind energy is expanding to combination of computing to forecast of wind power generation as well as intelligent of wind powerturbine. Wind power is rise and fall depending on weather conditions and difficult to predict the output for efficient power production. Wind power is need to reliably linked technology in order to efficient power generation. In this paper, distributed power generation forecasts to enhance the predicted and actual power generation in order to minimize the difference between the power of distributed power short-term prediction model is designed. The proposed model for prediction of short-term combining the physical models and statistical models were produced in a physical model of the predicted value predicted by the lattice points within the branch prediction to extract the value of a physical model by applying the estimated value of a statistical model for estimating power generation final gas phase produces a predicted value. Also, the proposed model in real-time National Weather Service forecast for medium-term and real-time observations used as input data to perform the short-term prediction models.

• Atmosphere
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• v.33 no.5
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• pp.519-530
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• 2023

Deep convection can make adverse effects on safe and efficient aviation operations by causing various weather hazards such as convectively-induced turbulence, icing, lightning, and downburst. To prevent such damage, it is necessary to accurately predict spatiotemporal distribution of deep convective area near the airport and airspace. This study developed a new index, the Aviation Convective Index (ACI), for deep convection, using the operational global Unified Model of the Korea Meteorological Administration. The ACI was computed from combination of three different variables: 3-hour maximum of Convective Available Potential Energy, averaged Outgoing Longwave Radiation, and accumulative precipitation using the fuzzy logic algorithm. In this algorithm, the individual membership function was newly developed following the cumulative distribution function for each variable in Korean Peninsula. This index was validated and optimized by using the 1-yr period of radar mosaic data. According to the Receiver Operating Characteristics curve (AUC) and True Skill Score (TSS), the yearly optimized ACI (ACI_YrOpt) based on the optimal weighting coefficients for 1-yr period shows a better skill than the no optimized one (ACI_NoOpt) with the uniform weights. In all forecast time from 6-hour to 48-hour, the AUC and TSS value of ACI_YrOpt were higher than those of ACI_NoOpt, showing the improvement of averaged value of AUC and TSS by 1.67% and 4.20%, respectively.

• Journal of the Korean Society for Marine Environment & Energy
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• v.4 no.3
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• pp.74-80
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• 2001

Due to floating marine debris, seabed litters, dead shellfishes and polluted sediments, etc. , which are mainly caused by fishery activities in a large scale around the coastline, expansion of industrialized areas from economic development and drastic increase of free time by the improved standard of living, Korean coast is believed to be cast beyond the self purification of marine ecosystem. Seabed litters, if not remedied in a timely manner, will eventually lead to the overall disorder of benthic ecosystem. Thus, in order to prevent marine ecosystem from being thrown into confusion by seabed litters and to restore ocean environments, it is reasonable to investigate the current status of the seabed litters by carrying out an extensive examination on them and to equip ourselves for marine debris with an systemized tool that provides supports to the building process of an efficient methodology of litters disposal through managing related data appropriately. As an primary step to this goal, a systematic method of investigation is presented in this paper. With this methodology, the present state of the seabed titters is properly understood for the specified list of ports.

• Progress in Medical Physics
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• v.29 no.3
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• pp.92-100
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• 2018

The manufacturer of a linear accelerator (LINAC) has reported that the target melting phenomenon could be caused by a non-recommended output setting and the excessive use of monitor unit (MU) with intensity-modulated radiation therapy (IMRT). Due to these reasons, we observed an unexpected beam interruption during the treatment of a patient in our institution. The target status was inspected and a replacement of the target was determined. After the target replacement, the beam profile was adjusted to the machine commissioning beam data, and the absolute doses-to-water for 6 MV and 10 MV photon beams were calibrated according to American Association of Physicists in Medicine (AAPM) Task Group (TG)-51 protocol. To verify the beam data after target replacement, the beam flatness, symmetry, output factor, and percent depth dose (PDD) were measured and compared with the commissioning data. The difference between the referenced and measured data for flatness and symmetry exhibited a coincidence within 0.3% for both 6 MV and 10 MV, and the difference of the PDD at 10 cm depth ($PDD_{10}$) was also within 0.3% for both photon energies. Also, patient-specific quality assurances (QAs) were performed with gamma analysis using a 2-D diode and ion chamber array detector for eight patients. The average gamma passing rates for all patients for the relative dose distribution was $99.1%{\pm}1.0%$, and those for absolute dose distribution was $97.2%{\pm}2.7%$, which means the gamma analysis results were all clinically acceptable. In this study, we recommend that the beam characteristics, such as beam profile, depth dose, and output factors, should be examined. Further, patient-specific QAs should be performed to verify the changes in the overall beam delivery system when a target replacement is inevitable; although it is more important to check the beam output in a daily routine.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.2
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• pp.159-179
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• 2022

Often a network becomes complex, and multiple entities would get in charge of managing part of the whole network. An example is a utility grid. While the entire grid would go under a single utility company's responsibility, the network is often split into multiple subsections. Subsequently, each subsection would be given as the responsibility area to the corresponding sub-organization in the utility company. The issue of how to make subsystems of adequate size and minimum number of interconnections between subsystems becomes more critical, especially in real-time simulations. Because the computation capability limit of a single computation unit, regardless of whether it is a high-speed conventional CPU core or an FPGA computational engine, it comes with a maximum limit that can be completed within a given amount of execution time. The issue becomes worsened in real time simulation, in which the computation needs to be in precise synchronization with the real-world clock. When the subject of the computation allows for a longer execution time, i.e., a larger time step size, a larger portion of the network can be put on a computation unit. This translates into a larger margin of the difference between the worst and the best. In other words, even though the worst (or the largest) computational burden is orders of magnitude larger than the best (or the smallest) computational burden, all the necessary computation can still be completed within the given amount of time. However, the requirement of real-time makes the margin much smaller. In other words, the difference between the worst and the best should be as small as possible in order to ensure the even distribution of the computational load. Besides, data exchange/communication is essential in parallel computation, affecting the overall performance. However, the exchange of data takes time. Therefore, the corresponding consideration needs to be with the computational load distribution among multiple calculation units. If it turns out in a satisfactory way, such distribution will raise the possibility of completing the necessary computation in a given amount of time, which might come down in the level of microsecond order. This paper presents an effective way to split a given electrical network, according to multiple criteria, for the purpose of distributing the entire computational load into a set of even (or close to even) sized computational loads. Based on the proposed system splitting method, heavy computation burdens of large-scale electrical networks can be distributed to multiple calculation units, such as an RTDS real time simulator, achieving either more efficient usage of the calculation units, a reduction of the necessary size of the simulation time step, or both.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.202-211
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• 2015

Companies build the factory automation system to improve management effectiveness and productivity as prime strategies for sustainable growth. But most companies undergo various trials and errors while carrying out the project without elaborate preparation stage for factory automation. In this study, we tried to verify what factors are critical to effectively building distribution automation system, which is a branch of factory automation system. A consulting model for setting up a Material Handling Automation System by utilizing the Stage-Gate Process, which is product development process was studied. 29 material handling automation projects carried out between the year 1990 to 2013 at K-Company were selected. Interviews with the project managers, operators and maintenance personnels, various records and current status of the projects were used as data for structural equations based on the Milan consulting model and existing researches of factory automation, CIM for material handling automation. Creating effective basis of production, material handling system and energy saving system with expert review, when preparing a material handling automation project, help promote the project planning thus contributing to the performance of the resulting system, which appears though rather weakly in our data. Also the effect of material handling automation can be enhanced through sufficient and effective links to the relevant environments such as production logistics management and automated warehouses. More detailed planning characteristics of project promotion or some time-series data of effective Material Handling Automation System could enhace furthur studies. We propose a consulting model for setting up an efficient material handling automation system.