• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2008.11a
• /
• pp.616-618
• /
• 2008

The objective of this study is to prepare the plan for managing construction noise effectively and solving the popular enmity from construction noise reasonably. In order to carry out this purpose, it covers the efficient improvement plan for installing and managing the automatically noise-measuring system which shows the advantage for construction noise management and popular enmity solution due to construction noise.

• Knowledge Management Research
• /
• v.13 no.1
• /
• pp.1-12
• /
• 2012

A knowledge map is a network-typed diagram visualizing all kinds of knowledge that influences each other to solve a problem. A knowledge map determines the structure of knowledge categorizing and archiving by defining the relationship of referential navigation among knowledge. Since tremendous and increasing number of knowledge needs to be included in a knowledge map, a knowledge map must be organized automatically by considering the contents and relationships of knowledge. This paper suggests the concept and prototype of a semi-automated knowledge map which automatically maps new piece of knowledge onto a manually provided draft map. The prototype knowledge map is based on the recursive programming to make a knowledge map automatically determine the location of the newly-entered knowledge by considering the referential relationship between knowledge. The proposed knowledge enables the knowledge network to expand autonomously by automatically including and storing knowledge. Also, it can improve the accuracy and applicability of knowledge for problem-solving, because the relationship of referential navigation among knowledge can be efficiently and effectively expressed.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.932-935
• /
• 2004

In this paper, we present a framework that is easy to develop, modify, maintain and extend a control and monitoring software for any kinds of instruments. The presented framework is composed of three XML documents (IID, MAP, and CMIML) and two tools (Virtual Instrument Wizard, Generator). Interface information about behaviors and states of instruments is written on IID. Mapping information between the interface information in IID and API of a real instrument driver is written on MAP. Finally information about control and monitoring software is written on CMIML. IID, MAP and CMIML are written with XML format to provide common usage and platform independence of the suggested framework. VI Wizard generates CMIML (platform independent intermediate document) using IID and existing CMIML, and Generator generates source code of a control and monitoring software (platform dependent code) automatically using CMIML and MAP. The suggested framework that automatically generates control and monitoring software based on GUI provides easy development and maintenance. Also, reusability can be increased by reusing platform independent software description documents.

• Journal of Information Science Theory and Practice
• /
• v.6 no.4
• /
• pp.28-38
• /
• 2018

Wikipedia is composed of millions of articles, each of which explains a particular entity with various languages in the real world. Since the articles are contributed and edited by a large population of diverse experts with no specific authority, Wikipedia can be seen as a naturally occurring body of human knowledge. In this paper, we propose a method to automatically identify key entities and relations in Wikipedia articles, which can be used for automatic ontology construction. Compared to previous approaches to entity and relation extraction and/or identification from text, our goal is to capture naturally occurring entities and relations from Wikipedia while minimizing artificiality often introduced at the stages of constructing training and testing data. The titles of the articles and anchored phrases in their text are regarded as entities, and their types are automatically classified with minimal training. We attempt to automatically detect and identify possible relations among the entities based on clustering without training data, as opposed to the relation extraction approach that focuses on improvement of accuracy in selecting one of the several target relations for a given pair of entities. While the relation extraction approach with supervised learning requires a significant amount of annotation efforts for a predefined set of relations, our approach attempts to discover relations as they occur naturally. Unlike other unsupervised relation identification work where evaluation of automatically identified relations is done with the correct relations determined a priori by human judges, we attempted to evaluate appropriateness of the naturally occurring clusters of relations involving person-artifact and person-organization entities and their relation names.

• ETRI Journal
• /
• v.35 no.5
• /
• pp.838-848
• /
• 2013

This paper presents a novel approach to automatically generate Korean multiword sentiment expressions by using a seed sentiment lexicon and a large-scale domain-specific corpus. A multiword sentiment expression consists of a seed sentiment word and its contextual words occurring adjacent to the seed word. The multiword sentiment expressions that are the focus of our study have a different polarity from that of the seed sentiment word. The automatically extracted multiword sentiment expressions show that 1) the contextual words should be defined as a part of a multiword sentiment expression in addition to their corresponding seed sentiment word, 2) the identified multiword sentiment expressions contain various indicators for polarity shift that have rarely been recognized before, and 3) the newly recognized shifters contribute to assigning a more accurate polarity value. The empirical result shows that the proposed approach achieves improved performance of the sentiment analysis system that uses an automatically generated lexicon.

• Proceedings of the KSRS Conference
• /
• 2005.10a
• /
• pp.709-712
• /
• 2005

Ground processing for geostationary weather satellite such as GOES, MTSAT includes the process called image navigation. Image navigation means the retrieval of satellite navigational parameters from images and requires landmark detection by matching satellite images against landmark chips. For an automated preprocessing, a matching must be performed automatically. However, if match results contain errors, the accuracy of image navigation deteriorates. To overcome this problem, we propose the use of a robust estimation technique, called Random Sample Consensus (RANSAC), to automatically detect mismatches. We tested GOES-9 satellite images with 30 landmark chips. Landmark chips were extracted from the world shoreline database. To them, matching was applied and mismatch results were detected automatically by RANSAC. Results showed that all mismatches were detected correctly by RANSAC with a threshold value of 2.5 pixels.

• Proceedings of the KOSOMBE Conference
• /
• v.1994 no.05
• /
• pp.27-31
• /
• 1994

Intravascular ultrasound images of coranary artery contain very important informations on heart disease. The intimal contours on the image show informations and data to examine intravascular problems of patients. A new computation algorithm to detect the intimal and adventitial contours from the intravascular images was developed. An Image processing on gray level image was used. It uses arrays of pixels in each radial lines on the images. A "Robert" filter was adopted at first step for one dimensional image processing. Some other calculation techniques were developed to inclose the accuracy of automatically detected contours. The standard contour data to compare with automatically detected contour data were obtained through manually tracing by experienced cardiological medical doctors. The result of the new algorithm shows high accuracy of 80 % matching with the standard contour data.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.51 no.3
• /
• pp.100-107
• /
• 2002

In this paper, we propose an expert system for electronic interlocking which enhances the safty, efficiency and expanability of the existing system by designing real-time interlocking control based on the interlocking table automatically generated using artificial intelligence approach. The expert system consists of two parts; an interlocking table generation part and a real-time interlocking control part. The former generates automatically the interlocking relationship of all possible routes by searching dynamically the station topology which is obtained from station database. On the other hand, the latter controls the status of station facilities in real-time by applying the generated interlocking relationship to the signal facilities such as signal devices, points, track circuits for a given route. The expert system is implemented in C language which is suitable to implement the interlocking table generation part using the dynamic memory allocation technique. Finally, the effectiveness of the expert system is proved by simulating for the typical station model.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.327-330
• /
• 2004

This research work is concerned with a location-based alert service in wireless communication network environment. The alert service automatically transfers alert message to subscriber in the disaster area. This research work deals with automatic alert services that automatically provide people in emergency area with the state of emergency. The alert service uses the mobile device to inform its urgency to the subscribers in its area. The location tracking service will give the list of people in emergency area. The all processes of this research work are followed as. First, when a disaster or a calamity comes in, an emergency management center receives the emergency to analyze its shape and size and to declare the place to 'the disaster area.' Secondly, then the center finds information of mobile device subscribers in the disaster area. Finally, the center automatically generates a shape of text or audio of alert message of the emergency to send the message to the subscribers in the disaster area. Our mobile automatic alert service proposed above is so efficient that the subscribers in disasters area may meet the emergency more efficiently and may save their own valuable lives and properties more safely.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.6 no.2
• /
• pp.95-99
• /
• 2006

A tape feeder of a SMD(Surface Mount Device) mounter is a device that sequentially feeds electronic components on a tape reel to the pick-up system of the mounter. As components are getting much smaller, feeding accuracy of a feeder becomes one of the most important factors for successful component pick-up. Therefore, it is critical to keep the feeding accuracy to a specified level in the assembly and production of tape feeders. This paper describes a tape feeder inspection system that was developed to automatically measure and to inspect feeding accuracy using machine vision. It consists of a feeder base, an image acquisition system, and a personal computer. The image acquisition system is composed of CCD cameras with lens, LED illumination systems, and a frame grabber inside the PC. This system loads up to six feeders at a time and inspects them automatically and sequentially. The inspection software was implemented using Visual C++ on Windows with easily usable GUI. Using this system, we can automatically measure and inspect the quality of ail feeders in production process by analyzing the measurement results statistically.