• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.7
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• pp.258-264
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• 2018

This paper presents application of a differential search (DS) meta-heuristic optimization algorithm for optimal operation of a micro grid system. The DS algorithm simulates the Brownian-like random-walk movement used by an organism to migrate. The micro grid system consists of a wind turbine, a diesel generator, a fuel cell, and a photovoltaic system. The wind turbine generator is modeled by considering the characteristics of variable output. Optimization is aimed at minimizing the cost function of the system, including fuel costs and maximizing fuel efficiency to generate electric power. The simulation was applied to a micro grid system only. This study applies the DS algorithm with excellence and efficiency in terms of coding simplicity, fast convergence speed, and accuracy in the optimal operation of micro grids based on renewable energy resources, and we compared its optimum value to other algorithms to prove its superiority.

• Geophysics and Geophysical Exploration
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• v.16 no.2
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• pp.97-105
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• 2013

Nuclear magnetic resonance (NMR) logging has become an important technique for formation evaluation, detecting interaction signals between H protons and applied magnetic fields. Measured decay signals called relaxation, contain important information about density of H protons and different decay rate due to its fluid type in the sensitive area. Thus, petrophysical information such as porosity, permeability and wettability can be estimated through the interpretation of the decay signals. Many researches on random walk simulation have been published, since a simulation method based on random walk for solving exponential decays was adapted in the early of 1950. This study first makes a review on NMR simulation researches, explains two most important methods: simulation with or without considering magnetic field gradient. Lastly, the study makes a comparison between NMR simulation responses with and without magnetic field gradient to show the importance to consider magnetic gradient to analyze the effects of magnetic gradients on NMR responses.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.167-181
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• 2024

Utilization of a driving simulator in the development of autonomous driving technology allows us to perform various tests effectively in criticial environments, thereby reducing the development cost and efforts. However, there exists a serious drawback that the driving simulator has a big difference from the real environment, so a problem occurs when the autonomous driving algorithm developed using the driving simulator is applied directly to the real vehicle system. This is defined as so-called Sim2Real problem and can be classified into scenarios, sensor modeling, and vehicle dynamics. This Paper presensts on a method to solve the Sim2Real problem in autonomous driving simulator focusing on IMU sensor. In order to reduce the difference between emulated virtual IMU sensor real IMU sensor, IMU sensor emulation techniques through precision error modeling of IMU sensor are introduced. The error model of IMU sensors takes into account bias, scale factor, misalignmnet, and random walk by IMU sensor grades.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.170-174
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• 2014

In this paper, an unknown input estimation method via the optimal FIR smoother is proposed for linear discrete-time systems. The unknown inputs are represented by random walk processes and treated as auxiliary states in augmented state space models. In order to estimate augmented states which include unknown inputs, the optimal FIR smoother is applied to the augmented state space model. Since the optimal FIR smoother is unbiased and independent of any a priori information of the augmented state, the estimates of each unknown input are independent of the initial state and of other unknown inputs. Moreover, the proposed method can be applied to stochastic singular systems, since the optimal FIR smoother is derived without the assumption that the system matrix is nonsingular. A numerical example is given to show the performance of the proposed estimation method.

• Journal of Environmental Science International
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• v.7 no.4
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• pp.511-522
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• 1998

The two-stage numerical model was used to study the relation between three-dimensional local wind seal area for Korean peninsula. The first stave is three dimensional time-dependent local wind model which elves the wind field and vertical diffusion coefncient. The second stage is advection/duusion model which uses the results of the first stage as input data. First, wand fields on Korean peninsula for none synoptic scale wand showed typical land and sea breeze circulation, and the emitted particles were transported by sea breeze for daytime, emissions return to sea by land breeze for nighttime.

• Journal of Korean Society for Atmospheric Environment
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• v.12 no.1
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• pp.29-41
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• 1996

The two-stage numerical model was used to study the relation between three-dimensional local wind model, advection/diffusion model of random walk method and second moment method on Pusan coastal area. The first stage is three dimensional time-dependent local wind model which gives the wind field and vertical dirrusion coefficient. The second stage is advection/diffusion model which uses the results of the first stage as input data. First, wind fields on Pusan coastal area for none synoptic scale wind showed typical land and sea breeze circulation, and convergence zone occured at 1200LST in northern of domain, in succession, moved northward of domain. Emissions from Sinpyeong industrial district were trasnported toward the inland by sea breeze during daytime, and reached the end part of domain about 1800LST. During nighttime, emissions return to sea by land breeze and vertical diffusion also contributes to upward transport. In order to use this model for forecast of air pollution concentration on the Pusan coastal area, it is necessary that computed value must be compared with measured value and wind fields model must also be dealt in detail.

• Journal of Korean Society for Quality Management
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• v.21 no.1
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• pp.181-189
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• 1993

Over the past two decades, forecasting has gained widespread acceptance as an integral part of business planning and decision making. Accurate forecasting is a prerequisite to successful planning. Accordingly, recent advances in forecasting techniques are of exceptional value to corporate planners. But most of forecasting mothods are reveal its limit and problem for precision and reliability duing to each relationship for raw data and possibility of explanation for each variable. Therefore, to construct the Integrated Forecasting Model(IFM) for Information Factor Analysis, it shoud be considered that whether law data has time lag and variables are explained. For this. following several method can be used : Least Square Method, Markov Process, Fibonacci series, Auto-Correlation, Cross-Correlation, Serial Correlation and Random Walk Theory. Thus, the unified property of these several functions scales the safety and growth of the system which may be varied time-to-time.

• Smart Media Journal
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• v.12 no.1
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• pp.9-16
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• 2023

Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.

• ETRI Journal
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• v.37 no.6
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• pp.1087-1095
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• 2015

Mobility management is important in mobile cellular networks. In this study, we considered an enhanced location-based registration (ELR) method. In the ELR method, even when a mobile phone enters a cell to find that the cell is already on its list (of visited cells) and then updates its main counter, it does not remove any cells from the list (memory space permitting), which gives better performance than the location-based registration (LR) method. However, the location registration cost of the ELR method is still high, and there is a lot of room for improvement with regards to this matter. We now propose an improved version of the ELR method; namely, the improved ELR (iELR). In the iELR method, when a mobile phone enters a cell to find that the cell counter value is less than the main counter value, or when a mobile phone enters a cell to register its location, it updates the main counter and the cell counter values as much as possible to reduce the future need for registrations. We show that our proposed iELR method provides better performance than the ELR method.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.5
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• pp.151-159
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• 2009

Network models for pedestrian flows have been studied in various ways. However, because of the simplicity and application, a number of researchers prefer the CA Model to analyze pedestrian's complicated behavior. These kinds of models based on Agent are being used as a microscopic analyzing method since it can easily adapt individuals' various characters and movement types. However, because pedestrians' movement can be (easily) effected by where they are and where they head, some models using the same rules have limit when considering pedestrians' every different movement. In this research, homogeneous section is defined as a similar movement type of individuals. With MDPM, we suggest simulation method explaining one-way walk and side-walk which could not be done in past.