• Journal of KIISE:Databases
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• v.36 no.4
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• pp.292-305
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• 2009

Wireless sensor networks have a lot of application areas such as industrial process control, machine and resource management, environment and habitat monitoring. One of the main objects of using wireless sensor networks in these areas is the event detection. To detect events at a user's request, we need a join processing between sensor data and the predicates of the events. If there are too many predicates of events compared with a node's capacity, it is impossible to store them in a node and to do an in-network join with the generated sensor data This paper proposes a predicate-merge based in-network join approach to efficiently detect multiple events, considering the limited capacity of a sensor node and many predicates of events. It reduces the number of the original predicates of events by substituting some pairs of original predicates with some merged predicates. We create an estimation model of a message transmission cost and apply it to the selection algorithm of targets for merged predicates. The experiments validate the cost estimation model and show the superior performance of the proposed approach compared with the existing approaches.

• Journal of the Korean Wood Science and Technology
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• v.37 no.6
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• pp.556-565
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• 2009

Automated visual grading system of lumber needs correct input image. In order to create a correct image of domestic red pine lumber 3.6 m long feeding on a conveyer, part images were captured using area sensor and template matching algorithm was applied to merge part images. Two kinds of template matching algorithms and six kinds of template sizes were adopted in this operation. Feature extracted method appeared to have more excellent image merging performance than fixed template method. Error length was attributed to a decline of similarity related by difference of partial brightness on a part image, specific pattern and template size. The mismatch part was repetitively generated at the long grain. The best size of template for image merging was $100{\times}100$ pixels. In a further study, assignment of exact template size, preprocessing of image merging for reduction of brightness difference will be needed to improve image merging.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.2
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• pp.1-14
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• 2019

Since most documents used in web, XML, office applications are tree-structured, diff, merge, and version control for tree-structured documents in multi-user environments are crucial tasks. However research on edit scripts which is a basis for them is in primitive stage. In this paper, we present a document model for understanding the change of tree-structured documents as edit scripts are executed, and propose a method of switching adjacent edit operations on tree-structured documents based on the analysis of the effects of edit operations. Mostly, edit scripts which are produced as the results of diff on tree-structured documents only consist of basic operations such as update, insert, delete. However, when move and copy are included in edit scripts, because of the characteristics of their complex operation, it is often that edit scripts are generated to execute in two passes. In this paper, using the proposed method of switching edit operations, we present an algorithm of transforming the edit scripts of X-treeESgen, which are designed to execute in two passes, into the ones that can be executed in one pass.

• Nuclear Engineering and Technology
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• v.46 no.3
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• pp.439-446
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• 2014

An amphibious inspection robot system (hereafter AIROS) is being developed to visually inspect the in-containment refueling storage water tank (hereafter IRWST) strainer in APR1400 instead of a human diver. Four IRWST strainers are located in the IRWST, which is filled with boric acid water. Each strainer has 108 sub-assembly strainer fin modules that should be inspected with the VT-3 method according to Reg. guide 1.82 and the operation manual. AIROS has 6 thrusters for submarine voyage and 4 legs for walking on the top of the strainer. An inverse kinematic algorithm was implemented in the robot controller for exact walking on the top of the IRWST strainer. The IRWST strainer has several top cross braces that are extruded on the top of the strainer, which can be obstacles of walking on the strainer, to maintain the frame of the strainer. Therefore, a robot leg should arrive at the position beside the top cross brace. For this reason, we used an image processing technique to find the top cross brace in the sole camera image. The sole camera image is processed to find the existence of the top cross brace using the cross edge detection algorithm in real time. A 5-DOF robot arm that has multiple camera modules for simultaneous inspection of both sides can penetrate narrow gaps. For intuitive presentation of inspection results and for management of inspection data, inspection images are stored in the control PC with camera angles and positions to synthesize and merge the images. The synthesized images are then mapped in a 3D CAD model of the IRWST strainer with the location information. An IRWST strainer mock-up was fabricated to teach the robot arm scanning and gaiting. It is important to arrive at the designated position for inserting the robot arm into all of the gaps. Exact position control without anchor under the water is not easy. Therefore, we designed the multi leg robot for the role of anchoring and positioning. Quadruped robot design of installing sole cameras was a new approach for the exact and stable position control on the IRWST strainer, unlike a traditional robot for underwater facility inspection. The developed robot will be practically used to enhance the efficiency and reliability of the inspection of nuclear power plant components.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.131-140
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• 2009

This paper presents a new algorithm to the segmentation of the FISH images. First, for segmentation of the cell nuclei from background, a threshold is estimated by using the gaussian mixture model and maximizing the likelihood function of gray value of cell images. After nuclei segmentation, overlapped nuclei and isolated nuclei need to be classified for exact nuclei analysis. For nuclei classification, this paper extracted the morphological features of the nuclei such as compactness, smoothness and moments from training data. Three probability density functions are generated from these features and they are applied to the proposed Bayesian networks as evidences. After nuclei classification, segmenting of overlapped nuclei into isolated nuclei is necessary. This paper first performs intensity gradient transform and watershed algorithm to segment overlapped nuclei. Then proposed stepwise merging strategy is applied to merge several fragments in major nucleus. The experimental results using FISH images show that our system can indeed improve segmentation performance compared to previous researches, since we performed nuclei classification before separating overlapped nuclei.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2321-2326
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• 2011

Cervical vertebrae are a complex structure and an important part of human body connecting the head and the trunk. In this paper, we propose a method to extract sternocleidomastoid muscle from ultrasonography images of cervical vertabrae automatically. In our method, Region of Interests(ROI) is extracted first from an ultrasonography image after removing unnecessary auxiliary information such as metrics. Then we apply Ends-in search stretching algorithm in order to enhance the contrast of brightness. Average binarization is then applied to those pixels which its brightness is sufficiently large. The noise part is removed by image processing algorithms. After extracting fascia encloses sternocleidomastoid muscle, target muscle object is extracted using the location information of fascia according to the number of objects in the fascia. When only one object is to be extracted, we search downward first to extract the target muscle area and then search from right to left to extract the area and merge them. If there are two target objects, we extract first from the upper-bound of higher object to the lower-bound of lower object and then remove the fascia of the target object area. Smearing technique is used to restore possible loss of the fat area in the process. The thickness of sternocleidomastoid muscle is then calculated as the maximum thickness of those extracted objects. In this experiment with 30 real world ultrasonography images, the proposed method verified its efficacy and accuracy by health professionals.

• Journal of KIISE:Databases
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• v.34 no.2
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• pp.119-132
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• 2007

In molecular biology, approximate subsequence search is one of the most important operations. In this paper, we propose an accurate and efficient method for approximate subsequence search in large DNA databases. The proposed method basically adopts a binary trie as its primary structure and stores all the window subsequences extracted from a DNA sequence. For approximate subsequence search, it traverses the binary trie in a breadth-first fashion and retrieves all the matched subsequences from the traversed path within the trie by a dynamic programming technique. However, the proposed method stores only window subsequences of the pre-determined length, and thus suffers from large post-processing time in case of long query sequences. To overcome this problem, we divide a query sequence into shorter pieces, perform searching for those subsequences, and then merge their results. To verify the superiority of the proposed method, we conducted performance evaluation via a series of experiments. The results reveal that the proposed method, which requires smaller storage space, achieves 4 to 17 times improvement in performance over the suffix tree based method. Even when the length of a query sequence is large, our method is more than an order of magnitude faster than the suffix tree based method and the Smith-Waterman algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2749-2756
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• 2015

Recently, Depending on the quality of data increases, the problem of time-consuming to process the image is raised by being required to accelerate the image processing algorithms, in a traditional CPU and CUDA(Compute Unified Device Architecture) based recognition system for computing speed and performance gains compared to OpenMP When character recognition has been learned by the system to measure the input by the character data matching is implemented in an environment that recognizes the region of the well, so that the font of the characters image learning English alphabet are each constant and standardized in size and character an image matching method for calculating the matching has also been implemented. GPGPU (General Purpose GPU) programming platform technology when using the CUDA computing techniques to recognize and use the four cores of Intel i5 2500 with OpenMP to deal quickly and efficiently an algorithm, than the performance of existing CPU does not produce the rate of four times due to the delay of the data of the partition and merge operation proposed a method of improving the rate of speed of about 3.2 times, and the parallel processing of the video card that processes a result, the sequential operation of the process compared to CPU-based who performed the performance gain is about 21 tiems improvement in was confirmed.

• Korean Journal of Remote Sensing
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• v.22 no.2
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• pp.111-121
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• 2006

The classification using spectral angle is a new approach based on the fact that the spectra of the same type of surface objects in RS data are approximately linearly scaled variations of one another due to atmospheric and topographic effects. There are many researches on the unsupervised classification using spectral angle recently. Nevertheless, there are only a few which consider the characteristics of Hyperspectral data. On this study, we propose the ISOMUSAC(Iterative Self-Organizing Modified Unsupervised Spectral Angle Classification) which can supplement the defects of previous unsupervised spectral angle classification. ISOMUSAC uses the Angle Division for the selection of seed points and calculates the center of clusters using spectral angle. In addition, ISOMUSAC perform the iterative merging and splitting clusters. As a result, the proposed algorithm can reduce the time of processing and generate better classification result than previous unsupervised classification algorithms by visual and quantitative analysis. For the comparison with previous unsupervised spectral angle classification by quantitative analysis, we propose Validity Index using spectral angle.

• Journal of Korea Water Resources Association
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• v.56 no.spc1
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• pp.1027-1036
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• 2023

Coastal topographic information is crucial in coastal management, but point measurment based approeaches, which are labor intensive, are generally applied to land and underwater, separately. This study introduces an efficient method enabling land and undetwater surveys using an unmanned aerial vehicle (UAV). This method involves applying two different algorithms to measure the topography on land and water depth, respectively, using UAV imagery and merge them to reconstruct whole coastal digital elevation model. Acquisition of the landside terrain is achieved using the Structure-from-Motion Multi-View Stereo technique with spatial scan imagery. Independently, underwater bathymetry is retrieved by employing a depth inversion technique with a drone-acquired wave field video. After merging the two digital elevation models into a local coordinate, interpolation is performed for areas where terrain measurement is not feasible, ultimately obtaining a continuous nearshore terrain. We applied the proposed survey technique to Jangsa Beach, South Korea, and verified that detailed terrain characteristics, such as berm, can be measured. The proposed UAV-based survey method has significant efficiency in terms of time, cost, and safety compared to existing methods.