• Journal of Korea Spatial Information System Society
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• v.7 no.1 s.13
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• pp.77-89
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• 2005

Recently, application area on the Location Based System(LBS) is increasing because of development of mobile-communication and GPS technique. Previous studies on the index of moving objects are classified as either index for past trajectories or current/future positions. It is necessary to develop a unified index because many applications need to process queries about both past trajectories and current/future positions at the same time. In this paper, the past trajectories of moving objects are represented as line segments and the current and future positions are represented as the function of time. We propose a new index called PCR-tree(Past, Current R-tree) for unification of past, current and future positions. Nodes of the index have bounding boxes that enclose all position data and entries in the nodes are accessed with only one interface. We implement the proposed index and show a feasibility of processing the queries about temporal-spatial domain with the query tool which we develop.

• Journal of the Korea Convergence Society
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• v.7 no.5
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• pp.213-219
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• 2016

This paper presents a branch-and-bound algorithm for solving the concave minimization problem with upper bounded variables whose single constraint is linear. The algorithm uses simplex as partition element. Because the convex envelope which most tightly underestimates the concave function on the simplex is uniquely determined by solving the related linear equations. Every branching process generates two subsimplices one lower dimensional than the candidate simplex by adding 0 and upper bound constraints. Subsequently the feasible points are partitioned into two sets. During the bounding process, the linear programming problems defined over subsimplices are minimized to calculate the lower bound and to update the incumbent. Consequently the simplices which do certainly not contain the global minimum are excluded from consideration. The major advantage of the algorithm is that the subproblems are defined on the one less dimensinal space. It means that the amount of work required for the subproblem decreases whenever the branching occurs. Our approach can be applied to solving the concave minimization problems under knapsack type constraints.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.5
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• pp.939-955
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• 2010

With the progress of IT and mobile positioning technologies, various types of location-based services (LBS) have been proposed and implemented. Finding a shortest path between two nodes is one of the most fundamental tasks in many LBS related applications. So far, there have been many research efforts on the shortest path finding problem. For instance, $A^*$ algorithm estimates neighboring nodes using a heuristic function and selects minimum cost node as the closest one to the destination. Pruning method, which is known to outperform the A* algorithm, improves its routing performance by avoiding unnecessary exploration in the search space. For pruning, shortest paths for all node pairs in a map need to be pre-computed, from which a shortest path container is generated for each edge. The container for an edge consists of all the destination nodes whose shortest path passes through the edge and possibly some unnecessary nodes. These containers are used during routing to prune unnecessary node visits. However, this method shows poor performance as the number of unnecessary nodes included in the container increases. In this paper, we focus on this problem and propose a new border line-based pruning scheme for path routing which can reduce the number of unnecessary node visits significantly. Through extensive experiments on randomly-generated, various complexity of maps, we empirically find out optimal number of border lines for clipping containers and compare its performance with other methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.942-948
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• 2003

In this paper, we analyze the performance of multiple trellis coded modulation applied to continuous phase frequency shift keying (MTCM/CPFSK) for the noncoherent receiver without channel state information (CSI) on the interleaved Rician fading channel. In this system, the squared cross-correlation between the received signal and a candidate signal is used as the branch metric of the Viterbi decoder. To obtain the bit error performance of this system, we analyze the approximated pairwise error probability (PEP) and the exact PEP. We also derive the equivalent normalized squared distance (ENSD) and compare it with the ENSD of the noncoherent receiver with perfect CSI. Simulation results are also provided to verify the theoretical performance analysis.

• Journal of the Korea Convergence Society
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• v.10 no.11
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• pp.71-77
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• 2019

This paper defines a multi-selection knapsack problem and presents an algorithm for seeking its optimal solution. Multi-selection means that all members of the particular group be selected or excluded. Our branch-and-bound algorithm introduces a simplex containing the feasible region of the original problem to exploit the fact that the most tightly underestimating function on the simplex is linear. In bounding operation, the subproblem defined over the candidate simplex is minimized. During the branching process the candidate simplex is splitted into two one-less dimensional subsimplices by being projected onto two hyperplanes. The approach of this paper can be applied to solving the global minimization problems under various types of the knapsack constraints.

• Journal of Korea Multimedia Society
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• v.22 no.10
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• pp.1168-1177
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• 2019

In order to diagnose and prevent Alzheimer's Disease (AD), it is becoming increasingly important to develop a CAD(Computer-aided Diagnosis) system for AD diagnosis, which provides effective treatment for patients by analyzing 3D MRI images. It is essential to apply powerful deep learning algorithms in order to automatically classify stages of Alzheimer's Disease and to develop a Alzheimer's Disease support diagnosis system that has the function of detecting hippocampus and CSF(Cerebrospinal fluid) which are important biomarkers in diagnosis of Alzheimer's Disease. In this paper, for AD diagnosis, we classify a given MRI data into three categories of AD, mild cognitive impairment, and normal control according by applying 3D brain MRI image to the Faster R-CNN model and detect hippocampus and CSF in MRI image. To do this, we use the 2D MRI slice images extracted from the 3D MRI data of the Faster R-CNN, and perform the widely used majority voting algorithm on the resulting bounding box labels for classification. To verify the proposed method, we used the public ADNI data set, which is the standard brain MRI database. Experimental results show that the proposed method achieves impressive classification performance compared with other state-of-the-art methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1357-1363
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• 2019

In this paper, we compares the performance of the gredient descent optimizers of the Faster Region-based Convolutional Neural Network (R-CNN) model for the chromosome object detection in digital images composed of human metaphase chromosomes. In faster R-CNN, the gradient descent optimizer is used to minimize the objective function of the region proposal network (RPN) module and the classification score and bounding box regression blocks. The gradient descent optimizer. Through performance comparisons among these four gradient descent optimizers in our experiments, we found that the Adamax optimizer could achieve the mean average precision (mAP) of about 52% when considering faster R-CNN with a base network, VGG16. In case of faster R-CNN with a base network, ResNet50, the Adadelta optimizer could achieve the mAP of about 58%.

• Land and Housing Review
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• v.14 no.1
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• pp.123-134
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• 2023

The BIM (Building Information Modeling) model created in the design stage can be used for prior review and schedule management for the construction stage. However, in the case of actual BIM application cases, additional work is required, such as creating a new model suitable for the construction stage, rather than using the 3D model in the design stage, due to the difference in the purpose of use between the design stage and the construction stage. Therefore, in this study, a division function of BIM model is proposed as a method of recycling it in the construction stage without a remodeling process. In addition, the application to the actual BIM model and the 4D CAD system linkage of the divided object and the comparison with the existing division method are used to verify the usability.