• Progress in Medical Physics
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• v.10 no.3
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• pp.133-140
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• 1999

In this paper, as a preliminary study for developing a full 3D electron dose calculation algorithm, We developed 2.5D electron dose calculation algorithm by extending 2D pencil-beam model to consider three dimensional geometry such as air-gap and obliquity appropriately. The dose calculation algorithm was implemented using the IDL5.2(Research Systems Inc., USA), For calculation of the Hogstrom's pencil-beam algorithm, the measured data of the central-axis depth-dose for 12 MeV(Siemens M6740) and the linear stopping power and the linear scattering power of water and air from ICRU report 35 was used. To evaluate the accuracy of the implemented program, we compared the calculated dose distribution with the film measurements in the three situations; the normal incident beam, the 45$^{\circ}$ oblique incident beam, and the beam incident on the pit-shaped phantom. As results, about 120 seconds had been required on the PC (Pentium III 450MHz) to calculate dose distribution of a single beam. It needs some optimizing methods to speed up the dose calculation. For the accuracy of dose calculation, in the case of the normal incident beam of the regular and irregular shaped field, at the rapid dose gradient region of penumbra, the errors were within $\pm$3 mm and the dose profiles were agreed within 5%. However, the discrepancy between the calculation and the measurement were about 10% for the oblique incident beam and the beam incident on the pit-shaped phantom. In conclusions, we expended 2D pencil-beam algorithm to take into account the three dimensional geometry of the patient. And also, as well as the dose calculation of irregular field, the irregular shaped body contour and the air-gap could be considered appropriately in the implemented program. In the near future, the more accurate algorithm will be implemented considering inhomogeneity correction using CT, and at that time, the program can be used as a tool for educational and research purpose. This study was supported by a grant (＃HMP-98-G-1-016) of the HAN(Highly Advanced National) Project, Ministry of Health & Welfare, R.O.K.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.4
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• pp.171-181
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• 2013

Recently, ground penetrating radar(GPR) has been widely used in detecting metallic and nonmetallic buried landmines and a number of related researches have been reported. A novel preprocessing method is proposed in this paper to flag potential locations of buried mine-like objects from GPR array measurements. GPR operates by measuring the reflection of an electromagnetic pulse from discontinuities in subsurface dielectric properties. As the GPR pulse propagates in the geologic medium, it suffers nonlinear attenuation as the result of absorption and dispersion, besides spherical divergence. In the proposed algorithm, a logarithmic transformed regression model which successfully represents the time-varying signal amplitude of the GPR data is estimated at first. Then, background signals may be densely distributed near the regression model and candidate signals of targets may be far away from the regression model in the time-amplitude space. Based on the observation, GPR signals are decomposed into candidate signals of targets and background signals using residuals computed from the estimated value by regression and the measurement of GPR. Candidate signals which may contain target signals and noise signals need to be refined. Finally, targets are detected through the refinement of candidate signals based on geometric signatures of mine-like objects. Our algorithm is evaluated using real GPR data obtained from indoor controlled environment and the experimental results demonstrate remarkable performance of our mine-like object detection method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.38-45
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• 2020

A magnetically levitating capsule train, which runs inside the sub-vacuum tube, can reach ultra-fast speeds by dramatically reducing the aerodynamic drag and friction. The capsule train uses the superconductor electrodynamic suspension (SC-EDS) method for levitation. The SC-EDS method has advantages, such as a large levitation gap and free of gap control, which could reduce the infra-construction cost. On the other hand, disadvantages, such as the large variation of the levitation-guidance gap and small damping characteristics in levitation-guidance force, could degrade the running stability and ride comfort of the capsule train. In this study, a dynamic analytical model of a capsule train based on the SC-EDS was developed to analyze the running dynamic characteristics. First, as important factors in the capsule train dynamics, the levitation and guidance stiffness in the SC-EDS system were derived, which depend non-linearly on the velocity and gap variation. A 3D dynamic analysis model for capsule trains was developed based on the derived stiffness. Through the developed model, the effects of the different running speeds on the ride comfort were analyzed. The effects of a disturbance from infrastructure, such as the curve radius, tube sag, and connection joint difference, on the running stability of the capsule train, were also analyzed.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.171-178
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• 2014

This paper presents dynamic modelling of a virtual object in augmented reality environments when external forces are applied to the object in real-time fashion. In order to simulate a natural behavior of the object we employ the theory of Newtonian physics to construct motion equation of the object according to the varying external forces applied to the AR object. In dynamic modelling process, the physical interaction is taken placed between the augmented object and the physical object such as a haptic input device and the external forces are transferred to the object. The intrinsic properties of the augmented object are either rigid or elastically deformable (non-rigid) model. In case of the rigid object, the dynamic motion of the object is simulated when the augmented object is collided with by the haptic stick by considering linear momentum or angular momentum. In the case of the non-rigid object, the physics-based simulation approach is adopted since the elastically deformable models respond in a natural way to the external or internal forces and constraints. Depending on the characteristics of force caused by a user through a haptic interface and model's intrinsic properties, the virtual elastic object in AR is deformed naturally. In the simulation, we exploit standard mass-spring damper differential equation so called Newton's second law of motion to model deformable objects. From the experiments, we can successfully visualize the behavior of a virtual objects in AR based on the theorem of physics when the haptic device interact with the rigid or non-rigid virtual object.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.527-536
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• 2017

With the recent development of smart grid industry, the necessity for efficient EMS(Energy Management System) has been increased. In particular, in order to reduce electric load and energy cost, sophisticated electric load forecasting and efficient smart grid operation strategy are required. In this paper, for more accurate electric load forecasting, we extend the data collected at demand time into high time resolution and construct an artificial neural network-based forecasting model appropriate for the high time resolution data. Furthermore, to improve the accuracy of electric load forecasting, time series data of sequence form are transformed into continuous data of two-dimensional space to solve that problem that machine learning methods cannot reflect the periodicity of time series data. In addition, to consider external factors such as temperature and humidity in accordance with the time resolution, we estimate their value at the time resolution using linear interpolation method. Finally, we apply the PCA(Principal Component Analysis) algorithm to the feature vector composed of external factors to remove data which have little correlation with the power data. Finally, we perform the evaluation of our model through 5-fold cross-validation. The results show that forecasting based on higher time resolution improve the accuracy and the best error rate of 3.71% was achieved at the 3-min resolution.

• Journal of Korean Society of Steel Construction
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• v.23 no.6
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• pp.669-677
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• 2011

The multi-span suspension bridge generally has more than three towers and two main spans. To economically and effectively design a multi-span suspension bridge, the proper stiffness ratio of the center tower to the side tower must be determined. This study was conducted to propose a method of figuring out briefly the structural behavior of the towers in a multi-span suspension bridge. In the equivalent suspension bridge model, the main cable of the multi-span suspension bridge is idealized as an equivalent cable spring, and the external loads of horizontal and vertical forces that were calculated using the tensile forces of the main cable were applied on top of the towers. The equilibrium equations of the equivalent multi-span suspension bridge model were derived and the equations were solved via nonlinear analysis. To verify the proposed method, a sample four-span suspension bridge with a main span length of 3,000 m was analyzed using thefinite element method. The displacements and moment reactions of each tower in the proposed method were compared with the FEM analysis results. Consequently, the results of the analysis of the equivalent suspension bridge model tended to be consistent with the results of the FEM analysis.

• Korean Journal of Weed Science
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• v.30 no.2
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• pp.103-110
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• 2010

This experiment was conducted to investigate seedling emergence and early growth of Monochoria vaginalis and Scirpus juncoides in the controlled-environment chamber maintained at different temperatures. Non-linear regression analyses of observed data against effective accumulated temperature (EAT) with the Gompertz and logistic models showed that the Gompertz and logistic models worked well in describing seedling emergence and early growth of both weed species, respectively, regardless of temperature. EATs required for 50% of the maximum seedling emergence and the maximum leaf number of M. vaginalis were estimated to be 69.3 and $131^{\circ}C$, respectively, while those of S. juncoides were 94.8 and $137^{\circ}C$, respectively. Models developed in this study thus were used to predict seedling emergence and early growth under elevated temperature condition. If rotary tillage with water is made on 27 May under $+3^{\circ}C$ elevated temperature condition, dates for 50% of the maximum seedling emergence and 4 leaf stage were predicted to be 1 June and 15 June for M. vaginalis and 3 June and 14 June for S. juncoides, respectively. As compared with current temperature, these dates are 1-2 days earlier for the seedling emergence and 3 days earlier for the early growth, suggesting that earlier application of herbicides is required for effective control of M. vaginalis and S. juncoides under elevated temperature condition in the future.

• Journal of the Korea Society for Simulation
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• v.22 no.3
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• pp.1-6
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• 2013

The ecosystem is the complex system consisting of various biotic and abiotic factors and the factors interact with each other in the hierarchical predator-prey relationship. Since the competitive relation spatiotemporally occurs, the initial state of population density and species distribution are likely to play an important role in the stability of the ecosystem. In the present study, we constructed a lattice model to simulate the three-trophic ecosystem (predatorprey- plant) and using the model, explored how the ecosystem stability is affected by the initial density. The size of lattice space was $L{\times}L$, (L=100) with periodic boundary condition. The initial density of the plant was arbitrarily set as the value of 0.2. The simulation result showed that predator and prey coexist when the density of predator is less than or equal to 0.4 and the density of prey is less than or equal to 0.5. On the other hand, when the predator density is more than or equal to 0.5 and the density of prey is more than or equal to 0.6, both of predator and prey were extinct. In addition, we found that the strong nonlinearity in the interaction between species was observed in the border area between the coexistence and extinction in the species density space.

• The KIPS Transactions:PartA
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• v.11A no.6
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• pp.459-468
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• 2004

Sharing XML trees on mobile devices has become more and more popular. Optimistic replication of XML trees for mobile devices raises the need for reconciliation of concurrently modified data. Especially for reconciling the modified tree structures, we have to compare trees by node mapping which takes O($n^2$) time. Also, using semantic based conflict resolving policy is often discussed in the literature. In this research, we focused on an efficient reconciliation method for mobile environments, using edit scripts of XML data sent from each device. To get a simple model for mobile devices, we use the XML list data sharing model, which allows inserting/deleting subtrees only for the repetitive parts of the tree, based on the document type. Also, we use keys for repetitive part subtrees, keys are unique between nodes with a same parent. This model not only guarantees that the edit action always results a valid tree but also allows a linear time reconciliation algorithm due to key based list reconciliation. The algorithm proposed in this paper takes linear time to the length of edit scripts, if we can assume that there is no insertion key conflict. Since the previous methods take a linear time to the size of the tree, the proposed method is expected to provide a more efficient reconciliation model in the mobile environment.

• Korean Journal of Construction Engineering and Management
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• v.14 no.3
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• pp.42-52
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• 2013

The aim of this study is to present a prediction model of construction cost for a bridge that has a high reliability using historical data from the planning phase based on a CBR (Case-Based Reasoning) method in order to overcome limitations of existing construction cost prediction methods, which is linearly estimated. To do this, a reasoning model of bridge construction cost by a spreadsheet template was suggested using complexly both CBR and GA (Genetic Algorithm). Besides, this study performed a case study to verify the suggested cost reasoning model for bridge construction projects. Measuring efficiency for a result of the case study was 8.69% on average. Since accuracy of the suggested prediction cost is relatively high compared to the other analysis methods for a prediction of construction cost, reliability of the suggested model was secured. In the case that information for detailed specifications of each bridge type in an initial design phase is difficult to be collected, the suggested model is able to predict the bridge construction cost within the minimized measuring efficiency with only the representative specifications for bridges as an improved correction method. Therefore, it is expected that the model will be used to estimate a reasonable construction cost for a bridge project.