• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.07a
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• pp.286-287
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• 2020

Depth map is the most common way of expressing 3D space in immersive media. In this paper, we propose a post-processing method to improve the quality of depth map. In proposed method, a depth map is divided into segments, and the plane of each segment estimated using RANSAC. In order to increase the accuracy of the RANSAC process, we apply matching reliability of each pixel in depth map as a weighting factor.

• The Transactions of the Korea Information Processing Society
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• v.2 no.1
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• pp.95-105
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• 1995

An appendix to the MAP 3.0 specification notes that there are primary advantages to use of fiber optics : noise immunity, ability to run in difficult electrical environments, safety and high data rates. All of these may be quite useful in various manufacturing environments. In this paper, we study on construction schmes for a fiber-based 802.4 MAP system including the use of both bus and star topologies. We suggest passive star network and FDDI network for manufacturing environment. And then, we propose the FDDI protocol including the use a dual ring topology running at 100 Mbps to physical and datalink layer of MAT specification and analysis it's protocol and topology for abilities in manufacturing environments, We evaluate about applications service, time-critical processing and topology of two models in manufacturing environment.

• Spatial Information Research
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• v.5 no.2
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• pp.147-160
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• 1997

"The "Map Algebra", beeing recognized as a viable theoretical framework for GIS (Geographica Infonnation System), models map layers as "operands" which are the basic unit of geo-processing, and a variety of GIS commands as "operators." In this paper, we attempt at lifting some limitations of map algebras proposed in GIS literature. First, we model map layer as "function" such that we may employ the notion of meta operator (or, higher-order funtion) available in the functional programming paradigm. This approach provides map algebraic language with "programmability" needed in GIS user language. Second, we extend the semantics of, and improve on the sytactic structure of map algebraic language. Mer the data model and language associated with map algebra are formalized, we proceed to design and implement a prototype of map algebraic processor. The parser of the language in our prototype plays the role of transforming the native and heterogeneous user language of current GISs into a canonical map algebraic language. The prototype, named "MapSee" is a proof-of-concept system for the ideas we propsed in this paper. We believe that the uniform interface based on the map algebraic language will make promising infrastructure to support "Internet GIS." This is because the uniform but powerful interface through the Web clients allow access to both geo-data and geo-processing resources distributed over the network.to both geo-data and geo-processing resources distributed over the network.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.61-72
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• 2020

Recently, researches that are using deep learning technology in various fields are being conducted. The fields include geographic map processing. In this paper, I propose a method to infer where the map area included in the image is. The proposed method generates and learns images including a map, detects map areas from input images, extracts character strings belonging to those map areas, and converts the extracted character strings into coordinates through geocoding to infer the coordinates of the input image. Faster R-CNN was used for learning and map detection. In the experiment, the difference between the center coordinate of the map on the test image and the center coordinate of the detected map is calculated. The median value of the results of the experiment is 0.00158 for longitude and 0.00090 for latitude. In terms of distance, the difference is 141m in the east-west direction and 100m in the north-south direction.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.241-243
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• 2010

Previous approaches to the 2D to 3D conversion problem require heavy computation or considerable amount of user input. In this paper, we propose a rather simple method in estimating the depth map from a single image using a monocular depth cue: haze. Using the haze imaging model, we obtain the distance information and estimate a reliable depth map from a single scenery image. Using the depth map, we also suggest an algorithm that converts the single image to 3D stereoscopic images. We determine a disparity value for each pixel from the original 'left' image and generate a corresponding 'right' image. Results show that the algorithm gives well refined depth maps despite the simplicity of the approach.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.05a
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• pp.417-420
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• 2009

The hot forming process of a CAM for vessel engine was designed by finite element (FE) simulation and experimental analysis. An aim of process design was to achieve the near-net shaped CAM forgings by hot forging process. Based on the compression test results of the low alloy steel, deformation processing map was generated using the superposition approach between the dynamic materials model (DMM) and flow stability and/or instability criteria. From the processing map, the initial heating temperature was determined as $1200^{\circ}C$. FE analysis was simulated to predict the formation of rolling defects and deformed shape with different forging designs. Optimum process design suggested in this work was made by comparing with the CAM for vessel engine manufactured by actual forging process.

• Annual Conference of KIPS
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• 2009.04a
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• pp.834-837
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• 2009

There is a growing need for ad-hoc analysis of extremely large data sets, especially at e-Commerce companies which depend on recommender application. Nowadays, as the number of e-Commerce web pages grow to a tremendous proportion; vertical recommender services can help customers to find what they need. Recommender application is one of the reasons for e-Commerce success in today's world. Compared with general e-Commerce recommender application, obviously, general e-Commerce recommender application's processing scope is greatly narrowed down. MapReduce is emerging as an important programming model for large-scale data-parallel applications such as web indexing, data mining, and scientific simulation. The objective of this paper is to explore MapReduce framework for the e-Commerce recommender application on major general and dedicated link analysis for e-Commerce recommender application, and thus the responding time has been decreased and the recommender application's accuracy has been improved.

• The Transactions of the Korea Information Processing Society
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• v.1 no.3
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• pp.391-397
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• 1994

In this paper, we have developed a PLD Designer which is a design tool for digital circuits design using PLD device. PLD designer consists of a state graphic editor to extract boolean equations from state table within 20 states of FSM and a pin map editor to assign pin map for PLD device(PAL16R4, PAL22V10, GAL16V8, etc), which is suitable for extracted boolean equations. Also pin map editor generates a necessary JEDEC file to implement PLD device by using fuse map and checksum algorithm. To verify extracted boolean equation, we have developed simulation test vector generation algorithm. The results of JEDEC files generated by PLD designer is same with the results of JEDEC files generated by PALASM.

• KIISE Transactions on Computing Practices
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• v.21 no.8
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• pp.561-566
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• 2015

Hadoop is becoming widely adopted in scientific and commercial areas as an open-source distributed data processing framework. Recently, for real-time processing and analysis of data, an attempt to apply high-performance computing technologies to Hadoop is being made. In this paper, we have expanded the Hadoop Filesystem library to support Lustre, which is a popular high-performance parallel distributed filesystem, and implemented the Hadoop MapReduce execution environment over the Lustre filesystem. We analysed Hadoop MapReduce over Lustre by using Hadoop standard benchmark tools. We found that Hadoop MapReduce over Lustre execution has a performance 2-13 times better than a typical Hadoop MapReduce execution.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.668-676
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• 2017

Recently, the importance of big data has been emphasized with the development of smartphone, web/SNS. As a result, MapReduce, which can efficiently process big data, is receiving worldwide attention because of its excellent scalability and stability. Since big data has a large amount, fast creation speed, and various properties, it is more efficient to process big data summary information than big data itself. Wavelet histogram, which is a typical data summary information generation technique, can generate optimal data summary information that does not cause loss of information of original data. Therefore, a system applying a wavelet histogram generation technique based on MapReduce has been actively studied. However, existing research has a disadvantage in that the generation speed is slow because the wavelet histogram is generated through one or more MapReduce Jobs. And there is a high possibility that the error of the data restored by the wavelet histogram becomes large. However, since the wavelet histogram generation system based on the MapReduce developed in this paper generates the wavelet histogram through one MapReduce Job, the generation speed can be greatly increased. In addition, since the wavelet histogram is generated by adjusting the error boundary specified by the user, the error of the restored data can be adjusted from the wavelet histogram. Finally, we verified the efficiency of the wavelet histogram generation system developed in this paper through performance evaluation.