• Geomechanics and Engineering
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• 제18권5호
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• pp.493-502
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• 2019

Internal stability is an important safety issue for levees, embankments, and other earthen structures. Since a large part of the world's population lives near oceans, lakes and rivers, floods resulting from breaching of dams can lead to devastating disasters with tremendous loss of life and property, especially in densely populated areas. There are some main factors that affect the internal stability of dams, levees and other earthen structures, such as the erodibility of the soil, the water velocity inside the soil mass and the geometry of the earthen structure, etc. Thus, the mechanism of internal erosion and stability of soils is very complicated and it is vital to investigate the assessment methods of internal stability of soils in embankment dams and their foundations. This paper presents an improved support vector machine (SVM) model to predict the internal stability of soils. The grid search algorithm (GSA) is employed to find the optimal parameters of SVM firstly, and then the cross - validation (CV) method is employed to estimate the classification accuracy of the GSA-SVM model. Two examples of internal stability of soils are presented to validate the predictive capability of the proposed GSA-SVM model. In addition to verify the effectiveness of the proposed GSA-SVM model, the predictions from the proposed GSA-SVM model were compared with those from the traditional back propagation neural network (BPNN) model. The results showed that the proposed GSA-SVM model is a feasible and efficient tool for assessing the internal stability of soils with high accuracy.

• The Journal of Korea Robotics Society
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• 제8권4호
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• pp.256-265
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• 2013

A local map-based exploration algorithm for mobile robots is presented. Segmented frontiers and their relative transformations constitute a tree structure. By the proposed efficient frontier segmentation and a local map management method, a robot can reduce the unknown area and update the local grid map which is assigned to each frontier node. Although this local map-based exploration method uses only local maps and their adjacent node information, mapping completion and efficiency can be greatly improved by merging and updating the frontier nodes. Also, we suggest appropriate graph search exploration methods for corridor and hall environments. The simulation demonstrates that the entire environment can be represented by well-distributed frontier nodes.

• The Journal of the Korea Contents Association
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• 제17권3호
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• pp.329-336
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• 2017

In video compression, Motion Estimation(ME) limits the performance of image quality and generated bit rates. However, it requires much complexity in the encoder part. Multi-view video uses many cameras at different positions. Multi-view video coding needs huge computational complexity in proportion to the number of the cameras. To reduce computational complexity and maintain the image quality, an effective motion estimation method is proposed in this paper. The proposed method exploiting the characteristics of motion vector distribution and the motion of video. The proposed is a kind of a hierarchical search strategy. This strategy consists of multi-grid rhombus pattern, diagonal pattern, rectangle pattern, and refinement pattern. Experiment results show that the complexity reduction of the proposed method over TZ search method and PBS (Pel Block Search) on JMVC (Joint Multiview Video Coding) can be up to 40~75% and 98% respectively while maintaining similar video image quality and generated bit rates.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.37-44
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• 2001

This paper describes the modeling of work environment for the extraction of abstract operation rules for cooperative work with multiple agent. We propose the modeling method using a potential field. In the method, it is applied to a box pushing problem, which is to move a box from a start to a goal b multiple agent. The agents follow the potential value when they move and work in the work environment. The work environment is represented as the grid space. The potential field is generated by Genetic Algorithm(GA) for each agent. GA explores the positions of a potential peak value in the grid space, and then the potential value stretching in the grid space is spread by a potential diffusion function in each grid. However it is difficult to explore suitable setting using hand coding of the position of peak potential value. Thus, we use an evlolutionary computation way because it is possible to explore the large search space. So we make experiments the environment modeling using the proposed method and verify the performance of the exploration by GA. And we classify some types from acquired the environment model and extract the abstract operation rule, As results, we find out some types of the environment models and operation rules by the observation, and the performance of GA exploration is almost same as the hand coding set because these are nearly same performance on the evaluation of the consumption of agent's energy and the work step from point to the goal point.

• Journal of the Korea Society of Computer and Information
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• 제24권9호
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• pp.83-95
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• 2019

Recently, a variety of IoT data is collected by attaching geosensors to many vehicles that are on the road. IoT data basically has time and space information and is composed of various data such as temperature, humidity, fine dust, Co2, etc. Although a certain sensor data can be retrieved using time, latitude and longitude, which are keys to the IoT data, advanced search engines for IoT data to handle high-level user queries are still limited. There is also a problem with searching large amounts of IoT data without generating indexes, which wastes a great deal of time through sequential scans. In this paper, we propose a unified spatial index model that handles both grid and trajectory queries using a cell-based space-filling curve method. also it presents a visualization method that helps user grasp intuitively. The Trajectory query is to aggregate the traffic of the trajectory cells passed by taxi on the road searched by the user. The grid query is to find the cells on the road searched by the user and to aggregate the fine dust. Based on the generated spatial index, the user interface quickly summarizes the trajectory and grid queries for specific road and all roads, and proposes a Web-based prototype system that can be analyzed intuitively through road and heat map visualization.

• Transactions of the Korean Society of Mechanical Engineers A
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• 제20권10호
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• pp.3160-3172
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• 1996

A search algorithm for the collision free, time optimal transport path of overhead cranes has been proposed in this paper. The map for the working environment of overhead cranes was constructed in the form of three dimensional grid. The obstacle occupied region and unoccupied region of the map has been represented using the octree model. The best-first search method with a suitable estimation function was applied to select the knot points on the collision free transport path to the octree model. The optimization technique, minimizing the travel time required for transporting objects to the goal while subjected to the dynamic constraints of the crane system, was developed to find the smooth time optimal path in the form of cubic spline functions which interpolate the selected knot points. Several simulation results showed that the selected estimation function worked effectively insearching the knot points on the collision free transport path and that the resulting transport path was time optimal path while satisfying the dynamic constraints of the crane system.

• The KIPS Transactions:PartA
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• 제18A권2호
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• pp.75-80
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• 2011

Recently, many cleaning robots have been made with various algorithms for efficient cleaning. One of them is a DmaxCoverage algorithm which efficiently clean for the situation when the robot has a time limit. This algorithm uses Rectangle Tiling method for finding the biggest rectangle that doesn't have any obstacle. When the robot uses grid map, Rectangle Tiling method can find the optimal value. Rectangle Tiling method is to find all of the rectangles in the grid map. But when the grid map is big, it has a problem that spends a lot of times because of the large numbers of rectangles. In this paper, we propose Four Direction Rectangle Scanning(FDRS) method that has similar accuracy but faster than Rectangle Tiling method. FDRS method is not to find all of the rectangle, but to search the obstacle's all directions. We will show the FDRS method's performance by comparing of FDRS and Rectangle Tiling methods.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제19권7호
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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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 Institute of Information and Commucation Sciences Conference
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• 한국해양정보통신학회 2008년도 추계종합학술대회 B
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• pp.147-150
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• 2008

The real road network is regarded as a grid, and the grid is divided by fixed-sized cells. The path-finding is composed of two step searching. First searching travels on the abstract graph which is composed of a set of psuedo vertexes and a set of psuedo edges that are created by real road network and fixed-sized cells. The result of the first searching is a psuedo path which is composed of a set of selected psuedo edges. The cells intersected with the psuedo path are called as valid cells. The second searching travels with $A^*$ algorithm on valid cells. As pruning search space by removing the invalid cells, it would be possible to reduce the cost of exploring on real road network. In this paper, we present the method of creating the abstract graph and propose a path-finding algorithm on the abstract graph for extracting search space before traveling on real road network.