• The KIPS Transactions:PartD
• /
• 제8D권3호
• /
• pp.285-294
• /
• 2001

Recently many efforts on the development of automatic processing system for delivery sequency sorting have been performed in ETRI, which requires the use of postal 4-state bar code system to encode delivery points. This paper addresses the issue on the extension of read range and the improvement of image processing method. For the improvement of image processing procedure, applied information acquisition method through basic two thresholds onto the horizontal axial line of gray image based on reference information of 4-state bar code symbology. Symbol values are computed after creating two threshold values based on the obtained information through search of horizontal axial values. The implementation result of 4-state bar code reader are obtained the symbol values within 30~60 msec (58,000~116,000 mail item/hour)without noise removal or image rotation in spite of the incline $\pm 45^{\circ}$.

• The Journal of the Korea Contents Association
• /
• 제19권6호
• /
• pp.565-574
• /
• 2019

In this study, we evaluated the usefulness of an automatic blood typing analyzer using QWALYS-2 up (Diagast, Loos Cedex, France). During a month( 01OCT2013 - 31OCT2013) we performed 1,636 tests for ABO & RhD blood typing, 1,374 tests for antibody screen & identification tests and compared the results by automatic blood type analyzer with previous manual methods and column agglutination tests. And we analyzed the economic performance by comparison the test unit price between automatic blood type analyzer and manual methods. In ABO & RhD blood typing tests, there were complete concordances between manual and automated blood typing analyzer for 200 clinical samples. In Antibody screen tests, the concordance rate between manual and automated blood typing analyzer was 98.5% and more strong reaction in automated blood typing analyzer than manual methods. Therefore, the introduction of an automated blood typing analyzer, reagents costs were increased but labor costs were decreased. Considering the importance of transfusion safety and economic advantages, the introduction of an automated blood typing analyzer was very useful.

• Journal of Industrial Convergence
• /
• 제20권8호
• /
• pp.77-84
• /
• 2022

This study aims to present a method for implementing a decision support system that can be used for selecting emerging technologies by applying a machine learning-based automatic classification technique. To conduct the research, the architecture of the entire system was built and detailed research steps were conducted. First, emerging technology candidate items were selected and trend data was automatically generated using a big data system. After defining the conceptual model and pattern classification structure of technological development, an efficient machine learning method was presented through an automatic classification experiment. Finally, the analysis results of the system were interpreted and methods for utilization were derived. In a DTW-kNN-based classification experiment that combines the Dynamic Time Warping(DTW) method and the k-Nearest Neighbors(kNN) classification model proposed in this study, the identification performance was up to 87.7%, and particularly in the 'eventual' section where the trend highly fluctuates, the maximum performance difference was 39.4% points compared to the Euclidean Distance(ED) algorithm. In addition, through the analysis results presented by the system, it was confirmed that this decision support system can be effectively utilized in the process of automatically classifying and filtering by type with a large amount of trend data.

• Journal of Navigation and Port Research
• /
• 제38권1호
• /
• pp.53-57
• /
• 2014

This thesis, concentrates on marine collision risks of the area divided by cells. Using a gas molecular collision calculation model, a collision risk model is proposed. Collision risk is estimated by relative angle, relative speed, and ship's density in the cell. For one week, Automatic Identification System (AIS) data was collected and analyzed on the Busan North Port area. The results indicate a high-risk area at the sea route connection point in Busan North Port. It also shows that twilight is the time of day when most collisions occur. This means that the area is high risk due to the number of collisions and other dangerous factors related to twilight. Although there is still need to consider other risks such as grounding risks, the results of this study are useful to for plotting a risk map for the port.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.635-639
• /
• 2004

In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the modeling of chaotic nonlinear systems. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting the fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet transform. The basic idea of our wavelet based FNN is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. And our network can automatically identify the fuzzy rules by modifying the connection weights of the networks via the gradient descent scheme. To verify the efficiency of our network structure, we evaluate the modeling performance for chaotic nonlinear systems and compare it with those of the FNN and the WFM.

• International Journal of Internet, Broadcasting and Communication
• /
• 제12권1호
• /
• pp.122-129
• /
• 2020

The circumference of the body is not only an indicator in order to buy clothes in our life but an important factor which can increase the effectiveness healing properly after figuring out the shape of body in a hospital. There are several measurement tools and methods so as to know this, however, it spends a lot of time because of the method measured by hand for accurate identification, compared to the modern advanced societies. Also, the current equipments for automatic body scanning are not easy to use due to their big volume or high price generally. In this papers, OpenPose model which is a deep learning-based Skeleton Tracking is used in order to solve the problems previous methods have and for ease of application. It was researched to find joints and an approximation by applying the data of the deep camera via reference data of the measurement parts provided by the hospitals and to develop a program which is able to measure the circumference of the body lighter and easier by utilizing the elliptical circumference formula.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제4권1호
• /
• pp.111-118
• /
• 2004

In this paper, we present a novel approach for the structure of Fuzzy Neural Network(FNN) based on wavelet function and apply this network structure to the solution of the tracking problem for mobile robots. Generally, the wavelet fuzzy model(WFM) has the advantage of the wavelet transform by constituting the fuzzy basis function(FBF) and the conclusion part to equalize the linear combination of FBF with the linear combination of wavelet functions. However, it is very difficult to identify the fuzzy rules and to tune the membership functions of the fuzzy reasoning mechanism. Neural networks, on the other hand, utilize their learning capability for automatic identification and tuning. Therefore, we design a wavelet based FNN structure(WFNN) that merges these advantages of neural network, fuzzy model and wavelet transform. The basic idea of our wavelet based FNN is to realize the process of fuzzy reasoning of wavelet fuzzy system by the structure of a neural network and to make the parameters of fuzzy reasoning be expressed by the connection weights of a neural network. And our network can automatically identify the fuzzy rules by modifying the connection weights of the networks via the gradient descent scheme. To verify the efficiency of our network structure, we evaluate the tracking performance for mobile robot and compare it with those of the FNN and the WFM.

• Journal of the Korean Institute of Intelligent Systems
• /
• 제23권3호
• /
• pp.191-195
• /
• 2013

This paper proposes an automatic method for discovering cross-lingual links from English Wikipedia documents to Korean ones in order to increase connectivity among vast web resources. Compared to the existing methods roughly estimating link probability of phrases, candidate anchors are selected from English documents by using various information such as title lists and linking probability extracted from Wikipedia dumps and the results of named-entity recognition, and the anchors are translated into Korean words, and then the most suitable Korean documents with the words are selected as cross-lingual links. The experimental results showed 0.375 of MAP.

• Proceedings of the KSRS Conference
• /
• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
• /
• pp.253-256
• /
• 2005

The use of satellite remote sensing in maritime safety and security can aid in the detection of illegal fishing activities and provide more efficient use of limited aircraft or patrol craft resources. In the area of vessel traffic monitoring for commercial vessels, Vessel Traffic Service (VTS) which use the ground-based radar system have some difficulties in detecting moving ships due to the limited detection range. A virtual vessel traffic control system is introduced to contribute to prevent a marine accident such as collision and stranding from happening. Existing VTS has its limit. The virtual vessel traffic control system consists of both data acquisition by satellite remote sensing and a simulation of traffic environment stress based on the satellite data, remotely sensed data. And it could be used to provide timely and detailed information about the marine safety, including the location, speed and direction of ships, and help us operate vessels safely and efficiently. If environmental stress values are simulated for the ship information derived from satellite data, proper actions can be taken to prevent accidents. Since optical sensor has a high spatial resolution, JERS satellite data are used to track ships and extract their information. We present an algorithm of automatic identification of ship size and velocity. This paper lastly introduce the field testing results of ship detection by RADARSAT SAR imagery, and propose a new approach for a Vessel Monitoring System(VMS), including VTS, and SAR combination service.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• 제15권12호
• /
• pp.2590-2598
• /
• 2011

AIS(Automatic Identification System) is a key of maritime information system to prevent maritime accident through communication among any adjacent ship and to establish information base by fusing information collected from ships with other information. The AIS information includes various potential information, but it is not easy to use due to insufficiency storing and management. Furthermore, we need AIS transponders to acquire the information. In this paper, we propose the vessel positional information service using AIS and XML. We decode the AIS information from the NMEA-0183 encoding data and store the AIS information to the database and provide the access service in the internet using XML.