• Journal of Korea Multimedia Society
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• v.11 no.4
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• pp.554-565
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• 2008

The French neo-impressionist painter, George Seurat, introduced pointillism under the theory that the individual pigments of colors on the canvas are reconstructed on the human retina. Pointillism is a painting technique in which many small brush strokes are combined to form a picture in the canvas. When such a painting is seen from a far, the individual stroke color are unnoticeable and they are seen as intermixed colors. This is called juxtaposed color mixture. In this paper, we present a painterly rendering method for generating the pointillism images. For expressing countless separate dots which shown in the pointillism works, we propose a hierarchical points structure using Wang The method. Also a user defined palette is constructed based on the usage that Neo-Impressionist painter works on his palette. Lastly, based on this, a probability algorithm will be introduced, which divides the colors in the image(sampled by hierarchical point structure) into juxtaposed colors. A hierarchical points set which undergone juxtaposed color division algorithm is converted into brush strokes.

• Journal of the Korean Society for Computer Game
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• v.31 no.4
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• pp.167-174
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• 2018

The homogeneous key arrangement is a method of consistently arranging notes in a tile-shaped keyboard musical instrument, and arranging them in the same direction in the same direction on the neighboring keys in the same direction to enable a consistent musical arrangement. It has been used for a long time, but recently it has attracted attention by applying it to various modern musical instrument design and software instrument interface. There have been many different methods of deployment, but there are few studies on the existence of some or none of them. In this paper, we propose a classification method for such a key arrangement and analyze the relationship between them. This shows that there are far fewer types of homologous key arrangement than the known ones, and provided the basis of the study on the homogeneous key arrangement by providing a classification framework. Based on this, it is expected that more systematic analysis and research will be done and it will be used to develop various music interfaces. These studies will play a very important role in training students to understand the basic elements of pitch, harmony, harmony, and scales in music education games.

• Korean Journal of Construction Engineering and Management
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• v.13 no.3
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• pp.99-108
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• 2012

The rough design information is only available from BIM(Building Information Model) based schematic design. So, it is difficult to obtain sufficient information for generating BOQ. Like 2D design, there are some problems that the results are depend on what the choice of cost estimator. However, the most research of BIM based cost estimation are focus on quantity takeoff, the consideration of work item for generating BOQ is insufficient. Therefore, this paper present automatic inference process of work items in a BOQ using ontology. The proposed process and ontology is validated through applying tiling construction. If the proposed process is utilized, it is expected the basis of developing generation method for consistent BOQ by resolving intervention of cost estimator's arbitrary decision.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.801-814
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• 2004

In this paper, we propose a block adaptive binarization (BAB) using a modified quadratic filter (MQF) to binarize business card images acquired by personal digital assistant (PDA) cameras effectively. In the proposed method, a business card image is first partitioned into blocks of 8${\times}$8 and the blocks are then classified into character Hocks (CBs) and background blocks (BBs). Each classified CB is windowed with a 24${\times}$24 rectangular window centering around the CB and the windowed blocks are improved by the pre-processing filter MQF, in which the scheme of threshold selection in QF is modified. The 8${\times}$8 center block of the improved block is barbarized with the threshold selected in the MQF. A binary image is obtained tiling each binarized block in its original position. Experimental results show that the MQF and the BAB have much better effects on the performance of binarization compared to the QF and the global binarization (GB), respectively, for the test business card images acquired in a PDA. Also the proposed BAB using MQF gives binary images of much better quality, in which the characters appear much better clearly, over the conventional GB using QF. In addition, the binary images by the proposed BAB using MQF yields about 87.7% of character recognition rate so that about 32.0% performance improvement over those by the GB using QF yielding about 55.7% of character recognition rate using a commercial character recognition software.

• Journal of KIISE:Software and Applications
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• v.36 no.6
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• pp.451-461
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• 2009

The Adaptive Random Testing(ART) aims to improve the performance of traditional Random Testing(RT) by reducing the number of test cases to find the failure region which is located in the input domain. Such enhancement can be obtained by efficient selection algorithms of test cases. The ART through Iterative Partitioning(IP-ART) is one of ART techniques and it uses an iterative input domain partitioning method to improve the performance of early-versions of ART which have significant drawbacks in computation time. And the IP-ART with Enlarged Input Domain(EIP-ART), an improved version of IP-ART, is known to make additional performance improvement with scalability by expanding to virtual test space beyond real input domain of IP-ART. The EIP-ART algorithm, however, have the drawback of heavy cost of computation time to generate test cases mainly due to the virtual input domain enlargement. For this reason, two algorithms are proposed in this paper to mitigate the computation overhead of the EIP-ART. In the experiments by simulations, the tiling technique of input domain, one of two proposed algorithms, showed significant improvements in terms of computation time and testing performance.

• Journal of The Korean Society of Integrative Medicine
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• v.8 no.3
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• pp.181-188
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• 2020

Purpose : The purpose of this study is to compare the effects on abdominal muscle thickness and breathing by applying trunk strength exercise and deep stabilization exercise along with breathing exercise, which is the main respiratory muscle during breathing, to present an efficient exercise method with diaphragm breathing. Methods : This study was performed on normal 6 females and 14 males subjects. They were divided into 2 groups which trunk strength exercise and deep stabilization exercise group. The trunk strength exercise group (TSE) attended prone press-up, crunch and pelvic tiling. The deep stabilization exercise group (DSE) attended abdominal drawing, horizontal side-support and bridging exercise. Breathing exercise was performed for each set break time for 1 minute. Results : First, in the comparison of the change in the thickness of the abdominal muscle between the trunk strength training group and the deep stabilization group before and after exercise, there was a statistically significant difference in the comparison of transverse abdominis (TrA), rectus femoris (RF), external oblique (EO), internal oblique (IO) (p<.05). However, there was no significant difference in any comparison between groups (p>.05). Second, in the comparison of changes in respiratory function between the trunk strength exercise group and the deep stabilization exercise group before and after exercise, there were statistically significant differences in the exerted forced vital capacity (FVC), forced expiratory volume at one second (FEV₁), peak expiratory flow (PEF) in the comparison before and after the experiment (p<.05). However, there was no significant difference in any comparison between groups (p>.05). Conclusion : As a result of this study, it can be said that both trunk strength exercises and deep stabilization exercises along with diaphragm breathing are exercises that strengthen deep and superficial muscles, and have a positive effect on breathing function as well as muscle strength. However, it is not known which exercise was more effective, and because it was combined with breathing exercise, the interference effect appeared.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.561-570
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• 2010

The purpose of this study is to develop an Android smartphone app providing analysis capabilities of remote sensing images, by using mobile browsing open sources of gvSIG, open source remote sensing software of OTB and open source DBMS of PostgreSQL. In this app, five kinds of remote sensing algorithms for filtering, segmentation, or classification are implemented, and the processed results are also stored and managed in image database to retrieve. Smartphone users can easily use their functions through graphical user interfaces of app which are internally linked to application server for image analysis processing and external DBMS. As well, a practical tiling method for smartphone environments is implemented to reduce delay time between user's requests and its processing server responses. Till now, most apps for remotely sensed image data sets are mainly concerned to image visualization, distinguished from this approach providing analysis capabilities. As the smartphone apps with remote sensing analysis functions for general users and experts are widely utilizing, remote sensing images are regarded as information resources being capable of producing actual mobile contents, not potential resources. It is expected that this study could trigger off the technological progresses and other unique attempts to develop the variety of smartphone apps for remote sensing images.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.9
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• pp.359-366
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• 2021

A number of construction companies in Korea invest considerable human and financial resources to construct a system for managing apartment defect data and for categorizing repair tasks. Thus, this study proposes machine learning models to automatically classify defect complaint text-data into one of the sub categories of 'finishing work' (i.e., one of the defect repair tasks). In the proposed models, we employed two word representation methods (Bag-of-words, Term Frequency-Inverse Document Frequency (TF-IDF)) and two machine learning classifiers (Support Vector Machine, Random Forest). In particular, we conducted both binary- and multi- classification tasks to classify 9 sub categories of finishing work: home appliance installation work, paperwork, painting work, plastering work, interior masonry work, plaster finishing work, indoor furniture installation work, kitchen facility installation work, and tiling work. The machine learning classifiers using the TF-IDF representation method and Random Forest classification achieved more than 90% accuracy, precision, recall, and F1 score. We shed light on the possibility of constructing automated defect classification systems based on the proposed machine learning models.