• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_2
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• pp.645-651
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• 2007

In general, contours in digital vector maps, which represent terrain characteristics and shape, are created by 3D digitizing the same height points using aerial photographs on the analytical or digital plotters with stereoscopic viewing. Hence, it requires lots of task, and subjective decision and experience of the operators. DTMs are generated indirectly by using contours since the national digital maps do not include digital terrain model (DTM) data. In this study, model key points which depict the important information about terrain characteristics were extracted from the contours. Further, determination of the efficient and flexible grid sizes were proposed to generate optimal DTM in terms of both quantitative and qualitative aspects. For this purpose, a progressive sampling technique was implemented, i.e., the smaller grid sizes are assigned for the mountainous areas where have large relief while the larger grid sizes are assigned for the relatively flat areas. In consequence, DTMs with multi-grid for difference areas could be generated instead of DTMs with a fixed grid size. The multi-grid DTMs reduce computations for data processing and provide fast display.

• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.331-340
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• 2008

Feature Selection is one of methods to improve the classification accuracy of data in the field of machine learning. Many feature selection algorithms have been proposed and discussed for years. However, the problem of finding the optimal feature subset from full data still remains to be a difficult problem. Bio-inspired algorithms are well-known evolutionary algorithms based on the principles of behavior of organisms, and very useful methods to find the optimal solution in optimization problems. Bio-inspired algorithms are also used in the field of feature selection problems. So in this paper we proposed new improved bio-inspired algorithms for feature selection. We used well-known bio-inspired algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), to find the optimal subset of features that shows the best performance in classification accuracy. In addition, we modified the bio-inspired algorithms considering the prior importance (prior relevance) of each feature. We chose the mRMR method, which can measure the goodness of single feature, to set the prior importance of each feature. We modified the evolution operators of GA and PSO by using the prior importance of each feature. We verified the performance of the proposed methods by experiment with datasets. Feature selection methods using GA and PSO produced better performances in terms of the classification accuracy. The modified method with the prior importance demonstrated improved performances in terms of the evolution speed and the classification accuracy.

• Journal of Korea Spatial Information System Society
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• v.6 no.1 s.11
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• pp.31-50
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• 2004

With the growth of wireless communication networks and mobile devices taking in GPS, Location-Based Service(LBS) is becoming an integral part of mobile applications. LBS can deal with location-aware features such as persons holding mobile phones or vehicles equipped with GPS, and provide the users with the location information of the features. Thus it is necessary to develop moving object database systems to store, manage, and query moving objects which change their locations continuously as time passes. In this paper, we design and implement a query processing component which deals with moving objects as a key data type. For this component, we define a new SQL-like query language(called MOQL) and as a consequence, design and implement modules that analyze and execute queries. It supports various types of operators that process range queries, infer topological relations, compute trajectories, and find k-nearest neighbors. It can be used as a subsystem if other application systems which deal moving objects and also supports ADO.NET interface that can be used to interact end-users.

• Journal of KIISE:Databases
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• v.34 no.1
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• pp.1-17
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• 2007

As XML is becoming a de facto standard for distribution and sharing of information, the need for an efficient yet secure access of XML data has become very important. To enforce the fine-level granularity requirement, authorization models for regulating access to XML documents use XPath which is a standard for specifying parts of XML data and a suitable language for both query processing. An access control environment for XML documents and some techniques to deal with authorization priorities and conflict resolution issues are proposed. Despite this, relatively little work has been done to enforce access controls particularly for XML databases in the case of query access. Developing an efficient mechanism for XML databases to control query-based access is therefore the central theme of this paper. This work is a proposal for an efficient yet secure XML access control system. The basic idea utilized is that a user query interaction with only necessary access control rules is modified to an alternative form which is guaranteed to have no access violations using tree-aware metadata of XML schemes and set operators supported by XPath 2.0. The scheme can be applied to any XML database management system and has several advantages over other suggested schemes. These include implementation easiness, small execution time overhead, fine-grained controls, and safe and correct query modification. The experimental results clearly demonstrate the efficiency of the approach.

• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.67-82
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• 2006

We propose the HBEM(Hybrid Behavior Evolution Model) composed of rule classification and evolutionary neural network using rule descriptor and link descriptor for evolutionary behavior of virtual robots. In our model, two levels of the knowledge of behaviors were represented. In the upper level, the representation was improved using rule and link descriptors together. And then in the lower level, behavior knowledge was represented in form of bit string and learned adapting their chromosomes by the genetic operators. A virtual robot was composed by the learned chromosome which had the best fitness. The composed virtual robot perceives the surrounding situations and they were classifying the pattern through rules and processing the result in neural network and behaving. To evaluate our proposed model, we developed HBES(Hybrid Behavior Evolution System) and adapted the problem of gathering food of the virtual robots. In the results of testing our system, the learning time was fewer than the evolution neural network of the condition which was same. And then, to evaluate the effect improving the fitness by the rules we respectively measured the fitness adapted or not about the chromosomes where the learning was completed. In the results of evaluating, if the rules were not adapted the fitness was lowered. It showed that our proposed model was better in the learning performance and more regular than the evolutionary neural network in the behavior evolution of the virtual robots.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.159-166
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• 2008

Recently, according to the rapid development of location positioning technology and wireless communications technology and increasement of usage of moving object data, many researches and developments on the real-time locating systems which provides real time service of moving object data stream are under proceeding. However, MO (Moving Object) DBMS used based system in the in these systems is the inefficient management of moving object data streams, and the existing DSMS (Data Stream Management System) has problems that spatio-temporal data are not handled efficiently. Therefore, in this thesis, we designed and implemented spatio-temporal DSMS for efficient real-time management of moving object data stream. This thesis implemented spatio-temporal DSMS based STREAM (STanford stREam dAta Manager) of Stanford University is supporting real-time management of moving object data stream and spatio-temproal query processing and filtering for reduce the input loading. Specifically, spatio-temporal operators of the spatio-temporal DSMS support standard interface of SQL form which extended "Simple Feature Specification for SQL" standard specifications presented by OGC for compatibility. Finally, implemented spatio-temporal DSMS in this thesis, proved the effectiveness of the system that as applied real-time monitoring areas that require real-time locating of object data stream DSMS.

• The KIPS Transactions:PartD
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• v.10D no.7
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• pp.1171-1176
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• 2003

In this paper, we propose an effective bar code detection algorithm using the feature analysis and the labeling. After computing the direction of pixels using four line operators, we obtain the histogram about the direction of pixels by a block unit. We calculate the difference between the maximum value and the minimum value of the histogram and consider the block that have the largest difference value as the block of the bar code region. We get the line passing by the bar code region with the selected block but detect blocks of interest to get the more accurate line. The largest difference value is used to decide the threshold value to obtain the binary image. After obtaining a binary image, we do the labeling about the binary image. Therefore, we find blocks of interest in the bar code region. We calculate the gradient and the center of the bar code with blocks of interest, and then get the line passing by the bar code and detect the bar code. As we obtain the gray level of the line passing by the bar code, we grasp the information of the bar code.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.567-584
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• 2004

As XML becomes popular as the way of presenting information on the web, how to secure XML data becomes an important issue. So far study on XML security has focused on security of data communications by using digital sign or encryption technology. But, it now requires not just to communicate secure XML data on communication but also to manage query process to access XML data since XML data becomes more complicated and bigger. We can manage XML data queries by access control technique. Right now current XML data access control only deals with read operation. This approach has no option to process update XML queries. In this paper, we present XML access control model and technique that can support both read and update operations. In this paper, we will propose the operation for XML document update. Also, We will define action type as a new concept to manage authorization information and process update queries. It results in both minimizing access control steps and reducing memory cost. In addition, we can filter queries that have no access rights at the XML data, which it can reduce unnecessary tasks for processing unauthorized query. As a result of the performance evaluation, we show our access control model is proved to be better than other access control model in update query. But it has a little overhead to decide action type in select query.

• Proceedings of the Optical Society of Korea Conference
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• 2003.07a
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• pp.60-61
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• 2003

A new approach to reduce the computation time of genetic algorithm (GA) for making binary phase holograms is described. Synthesized holograms having diffraction efficiency of 75.8% and uniformity of 5.8% are proven in computer simulation and experimentally demonstrated. Recently, computer-generated holograms (CGHs) having high diffraction efficiency and flexibility of design have been widely developed in many applications such as optical information processing, optical computing, optical interconnection, etc. Among proposed optimization methods, GA has become popular due to its capability of reaching nearly global. However, there exits a drawback to consider when we use the genetic algorithm. It is the large amount of computation time to construct desired holograms. One of the major reasons that the GA' s operation may be time intensive results from the expense of computing the cost function that must Fourier transform the parameters encoded on the hologram into the fitness value. In trying to remedy this drawback, Artificial Neural Network (ANN) has been put forward, allowing CGHs to be created easily and quickly (1), but the quality of reconstructed images is not high enough to use in applications of high preciseness. For that, we are in attempt to find a new approach of combiningthe good properties and performance of both the GA and ANN to make CGHs of high diffraction efficiency in a short time. The optimization of CGH using the genetic algorithm is merely a process of iteration, including selection, crossover, and mutation operators [2]. It is worth noting that the evaluation of the cost function with the aim of selecting better holograms plays an important role in the implementation of the GA. However, this evaluation process wastes much time for Fourier transforming the encoded parameters on the hologram into the value to be solved. Depending on the speed of computer, this process can even last up to ten minutes. It will be more effective if instead of merely generating random holograms in the initial process, a set of approximately desired holograms is employed. By doing so, the initial population will contain less trial holograms equivalent to the reduction of the computation time of GA's. Accordingly, a hybrid algorithm that utilizes a trained neural network to initiate the GA's procedure is proposed. Consequently, the initial population contains less random holograms and is compensated by approximately desired holograms. Figure 1 is the flowchart of the hybrid algorithm in comparison with the classical GA. The procedure of synthesizing a hologram on computer is divided into two steps. First the simulation of holograms based on ANN method [1] to acquire approximately desired holograms is carried. With a teaching data set of 9 characters obtained from the classical GA, the number of layer is 3, the number of hidden node is 100, learning rate is 0.3, and momentum is 0.5, the artificial neural network trained enables us to attain the approximately desired holograms, which are fairly good agreement with what we suggested in the theory. The second step, effect of several parameters on the operation of the hybrid algorithm is investigated. In principle, the operation of the hybrid algorithm and GA are the same except the modification of the initial step. Hence, the verified results in Ref [2] of the parameters such as the probability of crossover and mutation, the tournament size, and the crossover block size are remained unchanged, beside of the reduced population size. The reconstructed image of 76.4% diffraction efficiency and 5.4% uniformity is achieved when the population size is 30, the iteration number is 2000, the probability of crossover is 0.75, and the probability of mutation is 0.001. A comparison between the hybrid algorithm and GA in term of diffraction efficiency and computation time is also evaluated as shown in Fig. 2. With a 66.7% reduction in computation time and a 2% increase in diffraction efficiency compared to the GA method, the hybrid algorithm demonstrates its efficient performance. In the optical experiment, the phase holograms were displayed on a programmable phase modulator (model XGA). Figures 3 are pictures of diffracted patterns of the letter "0" from the holograms generated using the hybrid algorithm. Diffraction efficiency of 75.8% and uniformity of 5.8% are measured. We see that the simulation and experiment results are fairly good agreement with each other. In this paper, Genetic Algorithm and Neural Network have been successfully combined in designing CGHs. This method gives a significant reduction in computation time compared to the GA method while still allowing holograms of high diffraction efficiency and uniformity to be achieved. This work was supported by No.mOl-2001-000-00324-0 (2002)) from the Korea Science & Engineering Foundation.