• Journal of the Korean Institute of Navigation
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• v.23 no.1
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• pp.29-43
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• 1999

The production process of the compound-curved hull plates includes hull design, definition, fairing, modeling, lofting, cutting, and forming in sequence. Traditional fabrication methods and shop environment caused low level to productivity in medium and small sized shipyards. The most effective solution to solve those problems is to rationalize the layout of facilities. For the well-balanced development of domestic shipbuilding industry, it is urgently required to reduce the gap between modernized large sized shipyards and traditional small and medium sized shipyards in production technologies and efficiencies. For the efficient and accurate hull piece forming, all information from design to forming should be clarified and organized in a systematic manner. Thus, management of the information plays an important role in the computerized and automated of hull piece forming. The object of this paper is to survey the status of the field, to find out the feasibility and to introduce a draft of hull piece fabrication line for small and medium sized shipyards. The development of required system follows the object oriented technology to extend to simulation based system for carrying out physical product flow and facilities layout analysis. It is feasible to operate such a modernized facility for a group of small and medium shipyards who are unable to have each of their own facility because of its large amount of initial investment and insufficient work load.

• Journal of Forest and Environmental Science
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• v.32 no.4
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• pp.384-391
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• 2016

In this study, regions infected by pine wilt disease were extracted by using object-based classification method (OB-infected region), and the characteristics of special distribution about OB-infected region were figured out. Scale 24, Shape 0.1, Color 0.9, Compactness 0.5, and Smoothness 0.5 was selected as the objected-based, optimal weighted value of OB-infected region classification. The total accuracy of classification was high with 99% and Kappa coefficient was also high with 0.97. The area of OB-infected region was approximately 90 ha, 16% of the total area. The OB-infected region in Age class V and VI was intensively distributed with 97% of the total. Also, The OB-infected region in Middle and Large DBH class was intensively distributed with 99% of the total. In terms of the topographic characteristics of OB-infected region, the damages occurred approximately 86% below the altitude of 200 m, and occurred 91% with a slope less than 10 degree. The damage occurred a lot in low hilly mountain and undulating slope. In addition, the accessibility to road and residential area from OB-infected region was less than 300 m in large part. Overall, it was figured out that artificial effect is stronger than natural effect with regard to the spread of pine wilt disease.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.4 s.181
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• pp.183-190
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• 2006

Digital 3D Real Object Duplication System (RODS) consists of 3D Scanner and Solid Freeform Fabrication System (SFFS). It is a device to make three-dimensional objects directly from the drawing or the scanning data. In this research, we developed an office type SFFS based on Three Dimensional Printing Process and an industrial SFFS using Dual Laser. An office type SFFS applied sliding mode control with sliding perturbation observer (SMCSPO) algorithm for control of this system. And we measured process variables about droplet diameter measurement and powder bed formation etc. through experiments. In case of industrial type SFFS, in order to develop more elaborate and speedy system for large objects than existing SLS process, this study applies a new Selective Dual-Laser Sintering (SDLS) process and 3-axis Dynamic Focusing Scanner for scanning large area instead of the existing f lens. In this process, the temperature has a great influence on sintering of the polymer. Also the laser parameters are considered like that laser beam power, scan speed, and scan spacing. Now, this study is in progress to evaluate the effect of experimental parameters on the sintering process.

• ETRI Journal
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• v.42 no.2
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• pp.230-238
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• 2020

Human-object interaction (HOI) detection is a popular computer vision task that detects interactions between humans and objects. This task can be useful in many applications that require a deeper understanding of semantic scenes. Current HOI detection networks typically consist of a feature extractor followed by detection layers comprising small filters (eg, 1 × 1 or 3 × 3). Although small filters can capture local spatial features with a few parameters, they fail to capture larger context information relevant for recognizing interactions between humans and distant objects owing to their small receptive regions. Hence, we herein propose a three-stream HOI detection network that employs a context convolution module (CCM) in each stream branch. The CCM can capture larger contexts from input feature maps by adopting combinations of large separable convolution layers and residual-based convolution layers without increasing the number of parameters by using fewer large separable filters. We evaluate our HOI detection method using two benchmark datasets, V-COCO and HICO-DET, and demonstrate its state-of-the-art performance.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.416-422
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• 2021

Due to the large differences in human activity within classes, the large similarity between classes, and the problems of visual angle and occlusion, it is difficult to extract features manually, and the detection rate of human behavior is low. In order to better solve these problems, an improved Faster R-CNN-based detection algorithm is proposed in this paper. It achieves multi-object recognition and localization through a second-order detection network, and replaces the original feature extraction module with Dense-Net, which can fuse multi-level feature information, increase network depth and avoid disappearance of network gradients. Meanwhile, the proposal merging strategy is improved with Soft-NMS, where an attenuation function is designed to replace the conventional NMS algorithm, thereby avoiding missed detection of adjacent or overlapping objects, and enhancing the network detection accuracy under multiple objects. During the experiment, the improved Faster R-CNN method in this article has 84.7% target detection result, which is improved compared to other methods, which proves that the target recognition method has significant advantages and potential.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.969-979
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• 2004

Recently, large-scale enterprise information systems are commonly based on the multi-tiered middleware or frameworks to support such requirements as functional reuse, heterogeneous system resources, and multiple platforms. However, these multi-tiered or distributed multi-platform architecture incurs the interoperability issue of the components and metadata among the middleware. This paper introduces the Simple Object Application Framework (SOAF) which supports heterogeneous resources and platform-independent component-based development, with the abstract programming style of the object-oriented frameworks and the XML-SOAP based component persistence mechanism.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.5
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• pp.2141-2155
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• 2020

In order to meet the requirements of background change, illumination variation, moving shadow interference and high accuracy in object detection of moving camera, and strive for real-time and high efficiency, this paper presents an object detection algorithm based on sparse approximation recursion and sparse coding migration in subspace. First, low-rank sparse decomposition is used to reduce the dimension of the data. Combining with dictionary sparse representation, the computational model is established by the recursive formula of sparse approximation with the video sequences taken as subspace sets. And the moving object is calculated by the background difference method, which effectively reduces the computational complexity and running time. According to the idea of sparse coding migration, the above operations are carried out in the down-sampling space to further reduce the requirements of computational complexity and memory storage, and this will be adapt to multi-scale target objects and overcome the impact of large anomaly areas. Finally, experiments are carried out on VDAO datasets containing 59 sets of videos. The experimental results show that the algorithm can detect moving object effectively in the moving camera with uniform speed, not only in terms of low computational complexity but also in terms of low storage requirements, so that our proposed algorithm is suitable for detection systems with high real-time requirements.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5888-5903
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• 2019

The Relational ranking method applies authority-based ranking in relational dataset that can be modeled as graphs considering also their tuples' values. Authority directions from tuples that contain the given keywords and transfer to their corresponding neighboring nodes in accordance with their values and semantic connections. From our previous work, ObjectRank extends to ValueRank that also takes into account the value of tuples in authority transfer flows. In a maked difference from ObjectRank, which only considers authority flows through relationships, it is only valid in the bibliographic databases e.g. DBLP dataset, ValueRank facilitates the estimation of importance for any databases, e.g. trading databases, etc. A relational keyword search paradigm Object Summary (denote as OS) is proposed recently, given a set of keywords, a group of Object Summaries as its query result. An OS is a multilevel-tree data structure, in which node (namely the tuple with keywords) is OS's root node, and the surrounding nodes are the summary of all data on the graph. But, some of these trees have a very large in total number of tuples, size-l OSs are the OS snippets, have also been investigated using ValueRank.We evaluated the real bibliographical dataset and Microsoft business databases to verify of our proposed approach.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.83-88
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• 2006

Digital image processing algorithm was proposed to measure the area inside of an object image using angle-distance graph used to analyze the pattern of an object in the digital image processing techniques. The first angle-distance graph is generated from a point inside of an object area. The second angle-distance graphs are generated for the areas missed in the first graph by extracting the positions with large gradient in the first angle-distance graph. The order of the graph increases according to the complexity of an object pattern. Size of the area inside of an object boundary is measured by integrating square of distance multiplied by angle for each area from the hierarchical angie-distance graphs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.4
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• pp.289-297
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• 2007

Normaly, the map generlization methode has been used for the making of small scale map using a large scale map. The object join methode is consumed of a lots of processing time and the manual process. The object Join technique used in the NGI based on the digital map ver. 1.0 have problems of poor Joining rate and a lots of processing time. This study has improved the object Join technique considering of the geometry and attribute information for the digital map ver. 2.0. Using improved technique increased joining rate of object and reduced the processing time.