• Journal of the Korea Society for Simulation
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• v.24 no.4
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• pp.137-151
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• 2015

This study undertakes a simulation analysis for evaluating the benefits and costs of smart grid hub project. The purpose of the study is to explore extensively the alternatives for infrastructure configurations and identify the best scenarios that can satisfy all the stakeholder needs. We consider 19 parameters for configurating a smart grid hub city, and take a strategy of exhaustive search to find configurations that meet the two criteria simultaneously: each stakeholder's B/C ratio should be equally distributed and the B/C ratio of the entire city should be maximized. The results offer some meaningful implications for building a successful deployment strategy that can facilitate the diffusion of smart grid technologies.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1283-1287
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• 2003

Reverse engineering technology refers to the process that creates a CAD model of an existing part using measuring devices. Recently, non-contact scanning devices have become more accurate and the speed of data acquisition has increased drastically. However, they generate thousands of points per second and various types of point data. Therefore. it becomes a important to handle the huge amount and various types of point data to generate a surface model efficiently. This paper proposes a new triangular mesh generation method using 3D grids. The geometric information of a part can be obtained from point cloud data by estimating normal values of the points. In our research, the non-uniform 3D grids are generated first for feature based data reduction based on the geometric information. Then, triangulation is performed with the reduced point data. The grid structure is efficiently used not only for neighbor point search that can speed up the mesh generation process but also for getting surface connectivity information to result in same topology surface with the point data. Through this integrated approach, it is possible to create surface models from scanned point data efficiently.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.6
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• pp.1593-1603
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• 2016

In the smart grid environment, there are various security threats. In particular, exposure of smart meter data can lead to serious privacy violation. In this paper, we propose a method for de-identification method of metering data. The proposed method is to de-identify the time data and the numeric data, respectively. Therefore, it can't analyze the pattern information from the metering data. In addition, there is an advantage that the query is available, such as the range of search in the database for statistical analysis.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1821-1830
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• 2018

With the wide application of intelligent household appliances, the optimization of electricity behavior has become an important component of home-based intelligent electricity. In this study, a multi-objective optimization model in an intelligent electricity environment is proposed based on economy and comfort. Firstly, the domestic consumer's load characteristics are analyzed, and the operating constraints of interruptible and transferable electrical appliances are defined. Then, constraints such as household electrical load, electricity habits, the correlation minimization electricity expenditure model of household appliances, and the comfort model of electricity use are integrated into multi-objective optimization. Finally, a continuous search multi-objective particle swarm algorithm is proposed to solve the optimization problem. The analysis of the corresponding example shows that the multi-objective optimization model can effectively reduce electricity costs and improve electricity use comfort.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11a
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• pp.985-987
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• 2005

자료의 크기가 방대한 응용 프로그램에서는 메인 메모리와 저장 장치간의 자료 입출력(I/O)이 전체 계산의 주요 병목 요인으로 작용한다. 본 논문은 [2004 한국정보처리학회 추계논문집 제11권 제2호 1139-1142]에서 제안된 그리드(grid) 그래프를 위한 입출력 효율적인 depth-first search (DFS) 알고리즘을 지원하기 위한 입출력 효율적인 영역 구분자를 구하는 알고리즘을 제안 한다. 그 입출력 복잡도 (I/O-Complexity)는 O(Soft(N))이다. 여기서 N=|V|+|E|이고 $sort(N)=\Theta((N/B)log_{M/B}(N/B))$이다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.666-669
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• 2000

Localization is the process of aligning the robot's local coordinates with the global coordinates of a map. A mobile robot's location is basically computed by a dead reckoning scheme, but this position information becomes increasingly inaccurate during navigation due to odometry errors. In this paper, the method of building a map of a robot's environment using ultrasonic sensor data and the occupancy grid map scheme is briefly presented. Then, the search and matching algorithms to compensate for the odometry error by comparing the local map with the reference map are proposed and verified by experiments. It is shown that the compensated error is not accumulated and exists within the limited range.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10a
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• pp.3-5
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• 1999

최근접 검색(nearest neighbor search)을 위해서 대부분의 기존 기법들은 데이터를 특정한 공간 인덱스 구조를 이용하여 인덱싱하고 이 인덱스를 이용하여 질의를 수행하는 방법을 사용하였다. 본 연구에서는 이러한 데이터 자체를 인덱싱하는 방법과는 달리 미리 최근접 질의의 결과가 되는 Vorononi 다이어그램을 생성해두고, 이를 통하여 최근접 검색을 수행하는 VGrid(Voronoi diagram-Grid) 기법을 제안한다. 이 방법은 미리 모든 데이터에 대한 Voronoi 다이어그램을 계산하고 그 결과를 격자(grid)를 이용하여 인덱싱한 다음 최근접 검색 질의가 주어지면 이 격자 인덱스를 이용하여 빠르게 결과를 찾아낸다. 이 방법을 이용하면 처음 인덱스를 생성할 때는 많은 계산 시간이 소모되지만, 일단 인덱스가 구성되고 나면 최근접 검색 질의 처리 시 디스크 접근 회수가 줄기 때문에 기존의 기법에 비해 빠르게 최근접 검색 질의를 수행할 수 있다.

• Geophysics and Geophysical Exploration
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• v.18 no.2
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• pp.54-63
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• 2015

Petrophysical parameters such as porosity and fluid saturation which provide useful information for reservoir characterization could be estimated by rock physics model (RPM) using seismic velocity and resistivity. Therefore, accurate P-wave velocity and resistivity information have to be obtained for successful estimation of the petrophysical parameters. Compared with the individual inversion of electromagnetic (EM) or seismic data, the joint inversion using both EM and seismic data together can reduce the uncertainty and gives the opportunity to use the advantages of each data. Thus, more reliable petrophysical properties could be estimated through the joint inversion. In this paper, for the successful estimation of petrophysical parameters, we proposed an effective method which applies a grid-search method to find the porosity and fluid saturation. The relations of porosity and fluid saturation with P-wave velocity and resistivity were expressed by using RPM and the improved resistivity distribution used to this study was obtained by joint inversion of seismic and EM data. When the proposed method was applied to the synthetic data which were simulated for subsea reservoir exploration, reliable petrophysical parameters were obtained. The results indicate that the proposed method can be applied for detecting a reservoir and calculating the accurate oil and gas reserves.

• Geomechanics and Engineering
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• v.35 no.2
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• pp.121-133
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• 2023

The demand for cement and limestone crushed materials has increased many folds due to the tremendous increase in construction activities in Pakistan during the past few decades. The number of cement production industries has increased correspondingly, and so the rock-blasting operations at the limestone quarry sites. However, the safety procedures warranted at these sites for the blast-induced ground vibrations (BIGV) have not been adequately developed and/or implemented. Proper prediction and monitoring of BIGV are necessary to ensure the safety of structures in the vicinity of these quarry sites. In this paper, an attempt has been made to predict BIGV using artificial neural network (ANN) at three selected limestone quarries of Pakistan. The ANN has been developed in Python using Keras with sequential model and dense layers. The hyper parameters and neurons in each of the activation layers has been optimized using randomized and grid search method. The input parameters for the model include distance, a maximum charge per delay (MCPD), depth of hole, burden, spacing, and number of blast holes, whereas, peak particle velocity (PPV) is taken as the only output parameter. A total of 110 blast vibrations datasets were recorded from three different limestone quarries. The dataset has been divided into 85% for neural network training, and 15% for testing of the network. A five-layer ANN is trained with Rectified Linear Unit (ReLU) activation function, Adam optimization algorithm with a learning rate of 0.001, and batch size of 32 with the topology of 6-32-32-256-1. The blast datasets were utilized to compare the performance of ANN, multivariate regression analysis (MVRA), and empirical predictors. The performance was evaluated using the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and root mean squared error (RMSE)for predicted and measured PPV. To determine the relative influence of each parameter on the PPV, sensitivity analyses were performed for all input parameters. The analyses reveal that ANN performs superior than MVRA and other empirical predictors, andthat83% PPV is affected by distance and MCPD while hole depth, number of blast holes, burden and spacing contribute for the remaining 17%. This research provides valuable insights into improving safety measures and ensuring the structural integrity of buildings near limestone quarry sites.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2002-2007
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• 2006

The path search method in the telematics system should consider traffic flow of the roads as well as the shortest time because the optimal path with minimized travel time could be continuously changed by the traffic flow. The existing path search methods are not able to cope efficiently with the change of the traffic flow. The search method to use traffic information also needs more computation time than the existing shortest path search. In this paper, a method for efficiency improvement of path search is implemented and its performance is evaluated. The method employs the fixed grid for adjustable heuristic to traffic flow. Moreover, in order to simplify the computation of estimation values, it only adds graded decimal values instead of multiplication operation of floating point numbers with due regard to the gradient between a departure and a destination. The results obtained from the experiments show that it achieves the high accuracy and short execution time as well.