• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1518-1524
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• 2014

In this paper, a new method of spatial query, which is called Surround Search (SuSe) is suggested. This method makes it possible to search for the closest spatial object of interest to the user from a query point. SuSe is differentiated from the existing spatial object query schemes, because it locates the closest spatial object of interest around the query point. While SuSe searches the surroundings, the spatial object is saved on an R-tree, and MINDIST, the distance between the query location and objects, is measured by considering an angle that the existing spatial object query methods have not previously considered. The angle between targeted-search objects is found from a query point that is hidden behind another object in order to distinguish hidden objects from them. The distinct feature of this proposed scheme is that it can search the faraway or hidden objects, in contrast to the existing method. SuSe is able to search for spatial objects more precisely, and users can be confident that this scheme will have superior performance to its predecessor.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.1
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• pp.5-25
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• 2009

In recent years the popularity of multi-hop wireless networks has been growing. Its flexible topology and abundant routing path enables many types of applications. However, the lack of a centralized controller often makes it difficult to design a reliable service in multi-hop wireless networks. While packet routing has been the center of attention for decades, recent research focuses on data discovery such as file sharing in multi-hop wireless networks. Although there are many peer-to-peer lookup (P2P-lookup) schemes for wired networks, they have inherent limitations for multi-hop wireless networks. First, a wired P2P-lookup builds a search structure on the overlay network and disregards the underlying topology. Second, the performance guarantee often relies on specific topology models such as random graphs, which do not apply to multi-hop wireless networks. Past studies on wireless P2P-lookup either combined existing solutions with known routing algorithms or proposed tree-based routing, which is prone to traffic congestion. In this paper, we present two wireless P2P-lookup schemes that strictly build a topology-dependent structure. We first propose the Ring Interval Graph Search (RIGS) that constructs a DHT only through direct connections between the nodes. We then propose the ValleyWalk, a loosely-structured scheme that requires simple local hints for query routing. Packet-level simulations showed that RIGS can find the target with near-shortest search length and ValleyWalk can find the target with near-shortest search length when there is at least 5% object replication. We also provide an analytic bound on the search length of ValleyWalk.

• School Mathematics
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• v.8 no.3
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• pp.265-290
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• 2006

The purpose of this study is to search an effective teaching & learning program by examining how much does Excel affect on problem solving of linear function. This study was based on qualitative case study. Teaching experiment was performed for seven periods with five students in 8th graders. Pre and posts tests were attempted to analyze the changes of student's ability on problem solving of linear function. The analysis of tests were performed in category with correct process-object perspective, near process-object perspective, incorrect process-object perspective. According to this study, the subjects showed an improvement on problem solving perspective of linear function. This meant that lessons using Excel had influenced on the problem solving of linear function. We noticed that exploring the learning environment with Excel could supplement paper-and-pencil environment. We believed that Excel with an intuitive dynamic and explorative skills can play a role in scaffolding to support problem solving of linear function.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.4
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• pp.102-110
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• 2009

In this paper, we propose an object detection method for real-time in infrared (IR) images and PowerPC (PPC) and H/W design based on field programmable gate array (FPGA). An open H/W architecture has the advantages, such as easy transplantation of HW and S/W, support of compatibility and scalability for specification of current and previous versions, common module design using standardized design, and convenience of management and maintenance. Proposed background modeling for an open H/W architecture design decreases size of search area to construct a sparse block template of search area in IR images. We also apply to compensate for motion compensation when image moves in previous and current frames of IR sensor. Separation method of background and objects apply to adaptive values through time analysis of pixel intensity. Method of clutter reduction to appear near separated objects applies to median filter. Methods of background modeling, object detection, median filter, labeling, merge in the design embedded system execute in PFC processor. Based on experimental results, proposed method showed real-time object detection through global motion compensation and background modeling in the proposed embedded system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.6 s.177
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• pp.1529-1539
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• 2000

A newly developed optimization method which uses the genetic algorithm combined with the sensitivity analysis is presented in this paper. The genetic algorithm is a probabilistic method, searching the optimum at several points simultaneously, requiring only the values of the object and constraint functions. It has therefore more chances to find global solution and can be applied various problems. Nevertheless, it has such shortcomings that even it approaches the optimum rapidly in the early stage, it slows down afterward and it can't consider the constraints explicitly. It is only because it can't search the local area near the current points. The traditional method, on the other hand, using sensitivity analysis is of great advantage in searching the near optimum. Thus the combination of the two techniques makes use of the individual advantages, that is, the superiority both in global searching by the genetic algorithm and in local searching by the sensitivity analysis. Application of the method to the several test functions verifies that the method suggested is very efficient and powerful to find the global solutions, and that the constraints can be considered properly.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.172-176
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• 2015

In this research, a tool was developed to automate one-dimensional finite element analysis (1D FEA) for design of a machine tool spindle. Based on object-oriented programing, this tool employs the objects of a CAD system to construct a geometric model and then to convert it into the FE model of 1D beams at the workbenches of the CAD system with minimum data to define the spindle such as bearing positions and cross-sections of the shaft. Graphic user interfaces were developed for users to interact with the tool. This tool is helpful in identifying a near optimal design of the spindle with the automation of the FEA process with numerous design changes in minimum time and efforts. It is also expected to allow even design engineers to perform the FEA in search of an optimal design of the machine tool spindle.

• Journal of Digital Convergence
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• v.10 no.3
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• pp.167-172
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• 2012

This paper presents the technique separating objects on the single frame image from the background using region segmentation technique based on active contour. Active contour is to extract contours of objects from the image, which is set to have multi-search starting point to extract each objects contours for multi-object segmentation. Initial rough object segments are generated from binary-coded image using object specific contour information, and then the hole filling is performed to compensate internal segmentation caused by the change of inner object hole area and pixels. This procedure complements the problems caused by the noise from the region segmentation and the errors of segmentation near by the contour. The proposed method and conventional method is compared to verify the superiority of the proposed method.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.503-505
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• 2015

The galaxy cluster is an important object for investigating the large scale structure and evolution of galaxies. Recent wide and deep near-IR surveys provide an opportunity to search for galaxy clusters in the high redshift universe. We have identified candidate clusters of 0.8< z <1.2 from the $25deg^2$ SA22 field using an optical-near-IR dataset from merged UKIDSS DXS, IMS and CFHTLS catalogs. Using these candidates, we investigate the star forming activity of member galaxies. Consequently, at z ~1, the star forming activity of cluster galaxies is not distinguishable from those of field galaxies, which is different from members in local clusters. This means the environmental effect becomes more important for $M_{\ast}>10^{10}M_{\odot}$ galaxies at z <1.

• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.549-556
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• 2001

The general problems of recovering 3D for 2D imagery require the depth information for each picture element form focus. The manual creation of those 3D models is consuming time and cost expensive. The goal in this paper is to simplify the depth estimation algorithm that extracts the depth information of every region from monocular image sequence with camera translation to implement 3D video in realtime. The paper is based on the property that the motion of every point within image which taken from camera translation depends on the depth information. Full-search motion estimation based on block matching algorithm is exploited at first step and ten, motion vectors are compensated for the effect by camera rotation and zooming. We have introduced the algorithm that estimates motion of object by analysis of monocular motion picture and also calculates the averages of frame depth and relative depth of region to the average depth. Simulation results show that the depth of region belongs to a near object or a distant object is in accord with relative depth that human visual system recognizes.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.2
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• pp.305-313
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• 2002

The genetic algorithm(GA), an optimization technique based on the theory of natural selection, has proven to be relatively robust means to search for global optimum. It is converged near to the global optimum point without auxiliary information such as differentiation of function. When studying some optimization problems with continuous variables, it was found that premature saturation was reached that is no further improvement in the object function could be found over a set of iterations. Also, the general GA oscillates in the region of the new global optimum point so that the speed of convergence is decreased. This paper is to propose the concept of restarting and elitist preserving strategy as a measure to overcome this difficulty. Some benchmark examples are studied involving 3-bar truss and cantilever beam with plane stress elements. The modifications to GA improve the speed of convergence.