• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제7권8호
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• pp.195-202
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• 2018

스마트폰, GPS 네비게이션과 같은 위치 응용프로그램이 발달함에 따라 위치 및 궤적 프라이버시를 보호하기 위한 연구가 활발히 진행되고 있다. 위치 관련 서비스를 제공받기 위해서는 자신의 정확한 위치를 서버에게 공개해야 한다. 그러나 사용자 위치의 공개는 서버에게 자신의 위치뿐만 아니라 궤적까지 노출하게 되어 사생활 침해의 우려가 있다. 또한 사용자가 서버에게 요청한 정보는 위치 정보뿐만 아니라 멀티미디어 정보(위치에 대한 사진, 리뷰 등)를 포함하고 있기 때문에 서버가 처리해야 하는 비용 및 사용자가 받아야하는 정보가 증가하게 된다. 따라서 이를 해결하기 위해 본 논문에서는 EGTC (Enhanced Grid-based Trajectory Cloaking) 기법을 제안한다. EGTC 기법은 기존 GTC (Grid-based Trajectory Cloaking) 기법과 마찬가지로 사용자 궤적을 사용자가 원하는 프라이버시 레벨(UPL: User's desired Privacy Level) 수준으로 그리드를 분할하여 클로킹 영역을 생성 한 후, 랜덤한 질의 순서를 정한다. 다음 단계로 사용자가 이동하고자 하는 경로에 해당하는 서브 그리드 셀을 c(x,y)로 간주해 필요한 정보를 색인으로 구성해 받는다. 제안 기법은 기존 GTC 기법과 같이 궤적 프라이버시를 보장하면서 사용자가 청취해야 하는 정보의 양을 줄였다. 실험 결과를 통하여 제안 기법의 우수성을 증명하였다.

• Geomechanics and Engineering
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• 제35권2호
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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.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2003년도 춘계학술대회 논문집
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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.

• 정보처리학회논문지A
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• 제14A권4호
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• pp.191-196
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• 2007

자연 현상에서 나타나는 연기나 난류의 움직임을 사실적으로 시뮬레이션하기 위해서는 Navier-Stokes 방정식을 사용할 수 있다. 이 방정식을 이용한 구현은 방대한 연산량과 계산의 복잡성으로 인하여 실시간 시뮬레이션이 어렵다. 실시간 처리를 위해서는 Navier-Stokes 방정식의 관사 형태를 사용하는 것이 일반적이다. 유체 시뮬레이션의 이류(advect) 과정을 근사화하기 위해, Semi-Lagrangian 방법을 이용하면, 연기 시뮬레이션의 경우는 시간이 지남에 따라 밀도가 현저히 줄어들고, 소규모의 소용돌이(small-scale vorticity) 현상 등을 표현하기가 어렵다. 본 논문에서는 이 문제를 해결하기 위해 이류항(advection term)을 계산하는 새로운 수치해석 방법을 제안한다. 이 방법에서는 이류항의 값을 구할 때, 격자(grid) 중심의 현재 속도에 비례하는 임계영역을 격자 주변에 선정하고, 임계영역 내에 있는 격자들 중에서 현재 격자의 위치로 이류하는 속도를 가진 격자를 추적하여, 그 격자에서의 속도를 현재 격자의 이류속도 벡터로 사용한다. 이는 밀도와 소용돌이 현상의 수치적 소실을 줄여서, 사실성을 높이면서도, 실시간 처리가 가능하다. 본 논문에서는 GPU 구현을 통해 벡터 연산 등의 효율성을 높임으로써, 제안하는 방법의 실시간이 가능함을 보인다.

• 대한원격탐사학회지
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• 제37권6_2호
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• pp.1891-1900
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• 2021

직경 2.5 ㎛ 이하인 초미세먼지는 급격한 도시화와 인구 증가로 인해 대도시에서 많이 발생하며, 유아 및 청소년기는 성인에 비해 초미세먼지에 취약하고 만성 질환으로 이어질 가능성이 높다. 특히 대부분의 청소년들은 학교에서 가장 많은 시간을 보내고 있으며, 다양한 이유에 의해 실외에서 발생한 초미세먼지가 실내로 유입된다. 본 연구는 외부 요인에 의해 발생하는 학교 초미세먼지를 예측하고 학교별 초미세먼지 범주화를 수행하였다. 10-fold cross validation과 grid-search method를 적용한 random forest (RF) 모델에 화학과 기상 인자, 위성 기반의 aerosol optical depth (AOD)를 입력 자료로 하여 학교 초미세먼지를 예측하고 정확도 평가를 위해 4가지 통계 지표를 이용하였다. 학교 미세먼지 범주화를 위해 6가지 유형을 가진 느슨한 기준과 엄격한 기준을 정의하였으며, 범주화 결과 느슨한 기준의 경우 유형 2와 3에, 엄격한 기준의 경우 유형 3과 4에 가장 많은 학교가 포함되었다.

• 한국전산유체공학회:학술대회논문집
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• 한국전산유체공학회 2005년도 추계 학술대회논문집
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• pp.135-139
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• 2005

An unstructured overset mesh method has been developed for the simulation of unsteady viscous flow fields around multiple bodies in relative motion. For this purpose, a robust and fast search technique is proposed for both triangle and high-aspect quadrilateral cell elements. The interpolation boundary is defined for data communication between grid systems and an interpolation method is suggested for viscous and inviscid cell elements. This method has been applied to calculate the flow fields around 2-D airfoil including relative motion. Validation were made by comparing the predicted results with those of experiments or other researcher's numerical results. It was demonstrated that the present method is efficient and robust for the prediction of unsteady time-accurate flow fields involving multiple bodies in relative motion.

• 한국전산유체공학회지
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• 제11권2호
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• pp.1-7
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• 2006

An unstructured overset mesh method has been developed for the simulation of unsteady viscous flow fields around multiple bodies in relative motion. For this purpose, a robust and fast search technique is proposed for both triangle and high-aspect ratio quadrilateral cell elements. The interpolation boundary is defined for data communication between grid systems and an interpolation method is suggested for viscous and inviscid cell elements. This method has been applied to calculate the flow fields around 2-D airfoils involving relative motion. Validations were made by comparing the predicted results with those of experiments or other numerical results. It was demonstrated that the present method is efficient and robust for the prediction of unsteady time-accurate flow fields involving multiple bodies in relative motion.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(3)
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• pp.13-16
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• 2001

In reinforcement teaming, Q-learning converges quite slowly to a good policy. Its because searching for the goal state takes very long time in a large stochastic domain. So I propose the speedup method using the Q-value initialization for model-free reinforcement learning. In the speedup method, it learns a naive model of a domain and makes boundaries around the goal state. By using these boundaries, it assigns the initial Q-values to the state-action pairs and does Q-learning with the initial Q-values. The initial Q-values guide the agent to the goal state in the early states of learning, so that Q-teaming updates Q-values efficiently. Therefore it saves exploration time to search for the goal state and has better performance than Q-learning. 1 present Speedup Q-learning algorithm to implement the speedup method. This algorithm is evaluated. in a grid-world domain and compared to Q-teaming.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2007년도 추계학술대회 논문집
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• pp.344-347
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• 2007

For modeling the non-periodic and randomly scattered powder particles, the quasi-random multi-particle array is introduced. The multi-scale process simulation, which enables to formulate a regression model with a response surface method, is performed by employing a homogenization method. The size of ${Al_2}{O_3}$ particle, amplitude of cyclic compaction pressure, and friction coefficient are considered as optimal process parameters. The optimal conditions of process parameters providing the highest relative density are finally found by using the grid search method.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 2005년도 추계학술대회 논문집
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• pp.476-479
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• 2005

In this study, the process parameters in powder compaction are optimized for getting high relative densities. To find optimized parameters, the analytic models of powder compaction are firstly prepared by 2-dimensional rod arrays with random green densities using a quasi-random multi-particle array. Then, using finite element method, the changes in relative densities are analyzed by varying the size of the particle, the amplitude of cyclic compaction, and the coefficient of friction, which influence the relative density in cyclic compactions. After the analytic function of relative density associated process parameters are formulated by aid of the response surface method, the optimal conditions in powder compaction process are found by the grid search method.