• Journal of KIISE:Information Networking
• /
• v.37 no.3
• /
• pp.167-174
• /
• 2010

Recently the distributed topology control algorithm for constructing the Recrystallization Topology in the unstructured peer-to-peer network was proposed. In this paper, we prove that such a hierarchical topology is a scale-free power-law network. We present a model of a construction process of the distributed protocol, and analyze it based on a mean-field approximation and the continuum theory, so that we show that the constructed Recrystallization Topology is a scale-free network. In the proposed model, all nodes are born with some initial attractiveness and the system incorporates the rewiring of some links at every time step. Some old links are removed with the anti-preferential probability, and some new links are added with preferential probability. In other words, according to the distributed algorithm, each node makes connections to the more-preferential nodes having higher hit-ratio than other nodes, while it disconnects the anti-preferential nodes having lesser hit-ratio. This gives a realistic description of the local processes forming the recrystallization topology in unstructured peer-to-peer network. We calculate analytically the degree distribution. The analytic result indicates that the constructed network is a scale-free network, of which the scaling exponent is 3.

• Journal of Korean Society of Rural Planning
• /
• v.21 no.3
• /
• pp.171-179
• /
• 2015

The objectives of this research have been focussed on 1) developing prediction techniques for the flash flood and landslide based on rainfall prediction data in agricultural area and 2) developing an integrated forecasting system for the abrupt disasters using USN based real-time disaster sensing techniques. This study contains following steps to achieve the objective; 1) selecting rainfall prediction data, 2) constructing prediction techniques for flash flood and landslide, 3) developing USN and communication network protocol for detecting the abrupt disaster suitable for rural area, & 4) developing mobile application and SMS based early warning service system for local resident and tourist. Local prediction model (LDAPS, UM1.5km) supported by Korean meteorological administration was used for the rainfall prediction by considering spatial and temporal resolution. NRCS TR-20 and infinite slope stability analysis model were used to predict flash flood and landslide. There are limitations in terms of communication distance and cost using Zigbee and CDMA which have been used for existing disaster sensors. Rural suitable sensor-network module for water level and tilting gauge and gateway based on proprietary RF network were developed by consideration of low-cost, low-power, and long-distance for communication suitable for rural condition. SMS & mobile application forecasting & alarming system for local resident and tourist was set up for minimizing damage on the critical regions for abrupt disaster. The developed H/W & S/W for integrated abrupt disaster forecasting & alarming system was verified by field application.

• Geophysics and Geophysical Exploration
• /
• v.10 no.1
• /
• pp.37-43
• /
• 2007

The MH21 Research Consortium has conducted a high-resolution 3D seismic survey and a seafloor geochemical survey, to explore methane hydrate reservoirs in the eastern Nankai Trough, offshore Japan. Excellent geological information about shallow formations was obtained from the high-resolution 3D seismic survey, which was designed to image the shallow formations where methane hydrates exist. The information is useful in constructing a geological and geochemical model, and especially to understand the complex geology of seafloor, including geochemical manifestations and the structure of migration conduits for methane gas or methane-bearing fluid. By comparing methane seep sites observed by submersibles with seismic sections, some significant relationships between methane hydrate reservoirs, free gas accumulations below the seafloor, and seafloor manifestations are recognised. Bathymetric charts and seafloor reflection amplitude maps, constructed from seismic reflections from the seafloor, are also useful in understanding the relationships over a vast area. A new geochemical seafloor survey targeted by these maps is required. The relationships between methane hydrate reservoirs and seafloor manifestations are becoming clearer from interpretation of high-resolution 3D seismic data. The MH21 Research Consortium will continue to conduct seafloor geochemical surveys based on the geological and geochemical model constructed from high-resolution 3D seismic data analysis. In this paper, we introduce a basis for exploration of methane hydrate reservoirs in Japan by fusion of 3D seismic exploration and seafloor geochemical surveys.

• Korean Chemical Engineering Research
• /
• v.46 no.3
• /
• pp.585-597
• /
• 2008

The aim of this study was to find an analytic solution to the problem of determining the optimal capacity (lot-size) of a batch-storage network to meet demand for a finished product in a system undergoing random failures of operating time and/or batch material. The superstructure of the plant considered here consists of a network of serially and/or parallel interlinked batch processes and storage units. The production processes transform a set of feedstock materials into another set of products with constant conversion factors. The final product demand flow is susceptible to short-term random variations in the cycle time and batch size as well as long-term variations in the average trend. Some of the production processes have random variations in product quantity. The spoiled materials are treated through regeneration or waste disposal processes. All other processes have random variations only in the cycle time. The objective function of the optimization is minimizing the total cost, which is composed of setup and inventory holding costs as well as the capital costs of constructing processes and storage units. A novel production and inventory analysis, the PSW (Periodic Square Wave) model, provides a judicious graphical method to find the upper and lower bounds of random flows. The advantage of this model is that it provides a set of simple analytic solutions while also maintaining a realistic description of the random material flows between processes and storage units; as a consequence of these analytic solutions, the computation burden is significantly reduced.

• Journal of The Korean Association For Science Education
• /
• v.38 no.2
• /
• pp.219-234
• /
• 2018

In this study, we explored the possibility of automating the process of analyzing elements of scientific argument in the context of a Korean classroom. To gather training data, we collected 990 sentences from science education journals that illustrate the results of coding elements of argumentation according to Toulmin's argumentation structure framework. We extracted 483 sentences as a test data set from the transcription of students' discourse in scientific argumentation activities. The words and morphemes of each argument were analyzed using the Python 'KoNLPy' package and the 'Kkma' module for Korean Natural Language Processing. After constructing the 'argument-morpheme:class' matrix for 1,473 sentences, five machine learning techniques were applied to generate predictive models relating each sentences to the element of argument with which it corresponded. The accuracy of the predictive models was investigated by comparing them with the results of pre-coding by researchers and confirming the degree of agreement. The predictive model generated by the k-nearest neighbor algorithm (KNN) demonstrated the highest degree of agreement [54.04% (${\kappa}=0.22$)] when machine learning was performed with the consideration of morpheme of each sentence. The predictive model generated by the KNN exhibited higher agreement [55.07% (${\kappa}=0.24$)] when the coding results of the previous sentence were added to the prediction process. In addition, the results indicated importance of considering context of discourse by reflecting the codes of previous sentences to the analysis. The results have significance in that, it showed the possibility of automating the analysis of students' argumentation activities in Korean language by applying machine learning.

• Spatial Information Research
• /
• v.22 no.1
• /
• pp.65-73
• /
• 2014

Recently indoor navigation with indoor map such as Indoor Google Maps is served. For the services, constructing indoor data are required. CityGML and IFC are widely used as standards for representing indoor data. The data models contains spatial information for the indoor visualization and analysis, but indoor navigation requires semantic and topological information like graph as well as geometry. For this reason, IndoorGML, which is a GML3 application schema and data model for representation, storage and exchange of indoor geoinformation, is under standardization of OGC. IndoorGML can directly describe geometric property and refer elements in external documents. Because a lot of data in CityGML or IFC have been constructed, a huge amount of construction time and cost for IndoorGML data will be reduced if CityGML can help generate data in IndoorGML. Thus, this paper suggest practical use of CityGML including deriving from and link to CityGML. We analyze relationships between IndoorGML and CityGML. In this paper, issues and solutions for linkage of IndoorGML and CityGML are addressed.

• Journal of Environmental Impact Assessment
• /
• v.22 no.6
• /
• pp.547-556
• /
• 2013

Recently, golf courses have increased over the years because golf became popular leisure sport. Various environmental problems have been then issued by a golf course during constructing and running them. A problem of pesticide, which is serious among various environmental problems, from golf course has harmful effect on surrounding area and makes human suffer from acute and chronic diseases. Pesticides are used for the cost-effective managing of golf course and the amount of pesticides also increases as the number of golf course increase. Since the assessment of pesticides on near-by surrounding has been focused on water and soil media, studies related to atmospheric dispersion have been hardly attempted. The method to assess an impact of pesticide nearby agricultural production by the atmospheric dispersion using AGDISP(AGricultural DISPersal) model was developed and applied to the actual planned golf course located in Hongcheon, Gangwon. For implementing AGDISP, parameters were investigated from the golf course's land use planning map, pesticide spray device, Hong-Cheon weather station and etc. First of all, a kind of pesticide, a form of spraying pesticide, geographical features, weather data, and distance(golf course to plantation) were investigated to understand how to work these parameters in AGDISP. Restricted data(slope angle, droplet size distribution and solar insolation) sensitivity analysis of these parameters to estimate effect of pesticide nearby a plantation and a high relative contribution data of analyzed data was selected for input data. Ethoprophos was chosen as the pesticide used in the golf course and the amounts of pesticide deposition per annual agricultural productions were predicted. The results show that maximum amount of pesticide deposition through atmospheric dispersion was predicted $2.32{\mu}/m^2$ at 96 m where the nearest organic plantation exists. The residues of pesticide were also estimated based on the annul production of the organic and the deposition amount of the pesticide. Consequently, buckwheat, wheat and millet were likely to exceed maximum residue limits for pesticides in foods(MRL) and sorghum, corn and peanut were likely to exceed MRL by organic farming as well.

• Journal of Korean Society for Geospatial Information Science
• /
• v.21 no.2
• /
• pp.99-105
• /
• 2013

In rapidly developing urban areas that include high-rise, large, and complex buildings, indoor and outdoor maps in GIS become a basis for utilizing and sharing information pertaining to various aspects of the real world. Although an indoor mapping has gained much attentions, research efforts are mostly in 2D and 3D modeling of terrain and buildings. Therefore, to facilitate fast and accurate construction of indoor GIS, this paper proposes a semi-automatic method consisting of preprocessing, 2D mapping, and 3D mapping stages. The preprocessing is designed to estimate heights of building interiors and to identify noise data from point clouds. In the 2D mapping, a floor map is extracted with a tracing grid and a refinement method. In the 3D mapping, a 3D wireframe model is created with heights from the preprocessing stage. 3D mesh data converted from noise data is combined with the 3D wireframe model for detail modeling. The proposed method was applied to point clouds depicting a hallway in a building. Experiment results indicate that the proposed method can be utilized to construct 2D and 3D maps for indoor GIS.

• Journal of Distribution Science
• /
• v.14 no.6
• /
• pp.107-118
• /
• 2016

Purpose - Over 90% of Domestic logistics industry is small enterprise and they are experiencing growth stagnation due to price-based competition structure rather than constructing logistics service of high added value. In order to get over this situation and pursue the development of logistics industry, strengthening its competitiveness, through inter-enterprise cooperative network build-up, would be a key alternative. Therefore, in this study, an index for measuring inter-enterprise cooperation level of Joint logistics business will be developed as a typical collaborative business model in logistics industry. Moreover, a strengthening competitiveness method suggests a developmental step and a key management index to mature in logistics industry. Research Design, Data, Methodology - This study is an index development research for measuring inter-enterprise cooperation level of logistics industry. Such a level was measured by performing a survey by targeting enterprises that participated in Joint logistics business. The targeting enterprises are typical cooperative models in logistics industry. Measurement items were developed which were based on the presented items in existing research. Question items were composed of selection type questions as answering Yes/No. They measures implementation status of corporate activity and detailed activity items measuring qualitative level. Total samples were based on 116 enterprise samples including 90 logistics enterprises and 26 shippers. In addition, by evaluating the importance for Joint logistics business recognition with personnel working level, the weight of measuring variable was extracted. This study has built an assessment tools (LPCI) on Joint logistics business cooperation level in a situation where there are no previous studies on joint logistics business, this study is meaningful for other studies. Results - As a result of analyzing LPCI presented in this study, the score of logistics enterprise was represented as 59.9 points based on full score of 100 points and that of shippers as 47.2 points and cooperation level among enterprises participated in Joint logistics business was revealed to be very low. In particular, as a result of measuring the importance between logistics enterprise and shippers, the difference by each measurement standard was represented among those enterprises. This difference is considered to be a key factor that cooperative operational conformity between logistics enterprises and shippers is represented to be low. Conclusions - As most joint logistics business, being promoted at present, is sharing facility and information with joint logistics business, it is hard to find such a joint logistics business in reality based on cooperative business model in main cooperation agents. Therefore, competitiveness of logistics industry could be strengthened by promoting joint logistics business based on their mutual cooperation among enterprises. In other words, it is to secure sustainable competitiveness of joint logistics business together with creation of new market by inter-enterprise cooperation based on integration of basic logistics business.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.38 no.1
• /
• pp.35-41
• /
• 2020

3D laser scanners are an effective way to quickly acquire a large amount of data about an object. Recently, it is used in various fields such as surveying, displacement measurement, 3D data generation of objects, construction of indoor spatial information, and BIM(Building Information Model). In order to utilize the point cloud data acquired through the 3D laser scanner, it is necessary to make the data acquired from many stations through a matching process into one data with a unified coordinate system. However, analytical researches on the accuracy of point cloud data according to the registration method are insufficient. In this study, we tried to analyze the accuracy of registration method of point cloud data acquired through 3D laser scanner. The point cloud data of the study area was acquired by 3D laser scanner, the point cloud data was registered by the ICP(Iterative Closest Point) method and the shape registration method through the data processing, and the accuracy was analyzed by comparing with the total station survey results. As a result of the accuracy evaluation, the ICP and the shape registration method showed 0.002m~0.005m and 0.002m~0.009m difference with the total station performance, respectively, and each registration method showed a deviation of less than 0.01m. Each registration method showed less than 0.01m of variation in the experimental results, which satisfies the 1: 1,000 digital accuracy and it is suggested that the registration of point cloud data using ICP and shape matching can be utilized for constructing spatial information. In the future, matching of point cloud data by shape registration method will contribute to productivity improvement by reducing target installation in the process of building spatial information using 3D laser scanner.