• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.181-186
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• 2005

In collaborative environment, it is necessary that the participants in collaboration should share the same understanding about the semantics of terms. For example, they should know that 'Part' and 'Item' are different word-expressions for the same meaning. In this paper, we consider sharing between CAD and PDM data. In order to handle such problems in information sharing, an information system needs to automatically recognize that the terms have the same semantics. Serving this purpose, the semantic mapping logic and the ontology based mapper system is described in this paper. In the semantic mapping logic topic, we introduce our logic that consists of four modules: Character Matching, Instance Reasoning, definition comparing and Similarity Checking. In the ontology based mapper, we introduce the system architecture and the mapping procedure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1481-1489
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• 2016

A art from the typical data services based on 1:1 data communications, various new services based on 1:N communications have recently appeared. These services are becoming to require advanced 1:N communication schemes which can transfer the same data to many receivers efficiently and in high-performance. Especially, a Push-To-Talk (PTT) service, which is an important service in public safety communication system, requires a service server to disseminate the same voice media data to multiple receivers in a group in real-time and low latency. In this paper, we propose an efficient scheme to disseminate the same data to multiple receivers in low latency. In addition, we provide an analysis which gives a guide the performance of the 1:N communications in practical wired/wireless system environments in the perspective of the PTT service index.

• Journal of the Korea Safety Management & Science
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• v.12 no.1
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• pp.105-111
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• 2010

The air logistics process is complex and need many informations because various agencies participate in the logistics service and there are many stakeholders in air logistics. But it is hard to improve the infra of facilities because of an enormous expense, so it needs to simplify air logistics process for growing air freight. When documents are sent, it needs to change the form of documents in spite of same document due to different form by agencies. Also documents are changed even though different documents have same informations. Consequently, errors are increased because the names of the same data are different from each other and stakeholders reproduce the documents. In order to mitigate these problems, we selected documents and analyzed data of documents for the interface optimization in general air logistics process. Next, we unified the names of data and defined contents of data. Also we set the type of the defined data on DB type, and gave the code to the defined data. It made easy to exchange informations among the stakeholders to match documents corresponding with the defined data.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.507-519
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• 2023

Multi-temporal optical images have been utilized for time-series monitoring of croplands. However, the presence of clouds imposes limitations on image availability, often requiring a cloud removal procedure. This study assesses the applicability of various machine learning algorithms for effective cloud removal in optical imagery. We conducted comparative experiments by focusing on two key variables that significantly influence the predictive performance of machine learning algorithms: (1) land-cover types of training data and (2) temporal variability of land-cover types. Three machine learning algorithms, including Gaussian process regression (GPR), support vector machine (SVM), and random forest (RF), were employed for the experiments using simulated cloudy images in paddy fields of Gunsan. GPR and SVM exhibited superior prediction accuracy when the training data had the same land-cover types as the cloud region, and GPR showed the best stability with respect to sampling fluctuations. In addition, RF was the least affected by the land-cover types and temporal variations of training data. These results indicate that GPR is recommended when the land-cover type and spectral characteristics of the training data are the same as those of the cloud region. On the other hand, RF should be applied when it is difficult to obtain training data with the same land-cover types as the cloud region. Therefore, the land-cover types in cloud areas should be taken into account for extracting informative training data along with selecting the optimal machine learning algorithm.

• Journal of Korean Library and Information Science Society
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• v.30 no.3
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• pp.295-322
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• 1999

The purpose of this study is to identify and present the solution to the problems of KORMARC on Disc, which was produced by the National Library of Korea and is being distributed nationwide. Currently, KORMARC on Disc has reached the serious level of duplicates of input record, error on input data and noise of retrieval. Futhermore, input data is not in accordance with KORMARC Rules for Descriptive Cataloging, thus generating many problems. Of all thing, since current MARC system itself is based on manual system, it does not correspond effectively to the online environment. Accordingly, in order to elevate the quality of KORMARC database, current problems must be resolved, at the same time, korea Machine Readable Cataloging must be modified into a format, more suitable to Machine Readable environment. Consequently, the current study analyzes and identifies problems of data in KORMARC on Disc, at the same time, it examines currently used KORMARC Format and Korea machine Readable Cataloging Rules for descriptive Cataloging as to provide easier usage and guidelines for accurate data inputs.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2003.11a
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• pp.3-8
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• 2003

Census data are usually provided at an aggregated level. However, the aggregated data are essentially arbitrary geographical areas. The areal units used to report census data have no natural or meaningful geographical identity. Unfortunately, this means that analyses of these area aggregations may be conditional upon the set of zones, which are presented. This effect is known as the modifiable areal unit problem (MAUP) and has two related aspects. First, scale effect is the variation in numerical results that occurs due to the number of zones used in an analysis. Second, results may also differ between different ways of aggregating exactly the same data to the same scale; this may be called the aggregation effect (Openshaw, 1984). This study aims to provide a practical tool for the study of MAUP. I have created a set of 91 areal units based on 280 basic units in Nonhyun-2 dong to solve zoning problem and scale problem. We can easily recognize the importance of areal classification as statistics were different according to areal classification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2590-2606
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• 2017

Generally, research of classical image classification algorithms assume that training data and testing data are derived from the same domain with the same distribution. Unfortunately, in practical applications, this assumption is rarely met. Aiming at the problem, a domain adaption image classification approach based on multi-sparse representation is proposed in this paper. The existences of intermediate domains are hypothesized between the source and target domains. And each intermediate subspace is modeled through online dictionary learning with target data updating. On the one hand, the reconstruction error of the target data is guaranteed, on the other, the transition from the source domain to the target domain is as smooth as possible. An augmented feature representation produced by invariant sparse codes across the source, intermediate and target domain dictionaries is employed for across domain recognition. Experimental results verify the effectiveness of the proposed algorithm.

• Korean Journal of Computational Design and Engineering
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• v.11 no.6
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• pp.422-428
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• 2006

In this paper, an NC data optimization approach for enhancing 5-axis machining speed is presented. It is usual to use expensive commercial CAD/CAM programs for NC data of 5-axis machining, since it needs very large calculations for optimal tool positioning and orientation, tool path planning, and collision-free tool path generation. Since commercial CAD/CAM systems have similar functions and efficiency based on common algorithms of reliable theories, they do not have their own unique features for machining speed and efficiency. In other words, most commercial CAD/CAM systems consider only the characteristics of part geometry to be machined, which means that they generate almost the same NC data if the part to be machined is the same, even though different machines are used for the pin. A new approach is proposed for optimizing NC data of 5-axis machining, which is based on the characteristics of the machine to be operated. As a result, the speed of 5-axis machining can increase without losing machining accuracy and surface quality.

• Journal of Korean Society of Transportation
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• v.4 no.2
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• pp.37-58
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• 1986

Since 1960's there have been conducted quite numbers of origin and destination (0-D) surveys in Korea, Most of them, however, were to be said not so successful. In this paper, it was investigated that why the previous 0-D surveys were failed, and that how it could be improved. The findings of this study are: 1. The collection of sample data itself was performed relatively well, but the problem was in the improper expansion methods which were applied. 2. To improve the expansion methods, it should be performed not only the dwelling unit-based sample surveys but also commercial vehicle survey, cordon line survey, screen line counts and other auxiliary travel surveys like transit patronage survey, vehicle miles survey etc. at the same time. 3. To expand the sample surveyed data in a proper way, the adjustment factors should take a disaggregate form and also should be applied not to the specific trips, but to the specific trip makers to avoid the bias which could be caused by the application of adjustment factors in a way that has been used previously. 4. If there is no considerable change in travel patterns, we can synthesize the present 0-D data with past surveyed sample data, using present statistic data in the same way which was developed in this paper when expanding and adjusting sample data.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.75-81
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• 1997

A new DTPP (Desk-Top Program Production) system has been developed that enables multiple program producers (directors) working at different locations to collaborate over a computer network and prepare a single program for broadcasting. In this system, information is shared among users by exchanging data edited on non-linear editing terminals in program post-production work over a network in real time. In short, the new DTPP system provides a collaborative work space for producing TV programs. The system does not make use of a special server for collaborative work but rather multiple interconnected editing terminals having the same functions. In this configuration, data at a terminal which has just been edited by some operation is forwarded to all other connected terminals for updating. This form of information sharing, however, requires that some sort of data synchronizing method be established since multiple terminals are operating on the same data simultaneously. We therefore adopt a method whereby the system synchronizes the clocks on each terminal at the time of connection and sends an operation time stamp together with edited data. This enables most recently modified data to be identified and all information on all terminals to be updated appropriately. This paper provides an overview of this new collaborative DTPP system and describes the techniques for exchanging edited data and synchronizing data.