• Journal of Information Processing Systems
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• v.9 no.4
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• pp.592-601
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• 2013

Object segmentation is a challenging task in image processing and computer vision. In this paper, we present a visual attention based segmentation method to segment small sized interesting objects in natural images. Different from the traditional methods, we first search the region of interest by using our novel saliency-based method, which is mainly based on band-pass filtering, to obtain the appropriate frequency. Secondly, we applied the Gaussian Mixture Model (GMM) to locate the object region. By incorporating the visual attention analysis into object segmentation, our proposed approach is able to narrow the search region for object segmentation, so that the accuracy is increased and the computational complexity is reduced. The experimental results indicate that our proposed approach is efficient for object segmentation in natural images, especially for small objects. Our proposed method significantly outperforms traditional GMM based segmentation.

• Journal of Magnetics
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• v.15 no.4
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• pp.190-193
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• 2010

The design of joints in a transformer core significantly affects the transformer's efficiency. Air gaps cause variations in the flux distribution at the joints of the laminations, which depend on the geometry. Two similar samples consisting of electrical steel strips and amorphous ribbons were made. The spatial flux distributions were determined using an array of search coils for each sample. 2D models of these samples were created and examined by finite element analysis. The magnetic flux distribution for each lamination in the samples was computed. The results show that the flux density in amorphous ribbons above and below the air gap starts to approach saturation at lower flux density levels than for electrical steel. The flux density measured using the search coil under the air gap is increased in amorphous ribbons and decreased in the electrical steel with increasing frequency.

• Proceedings of the ESK Conference
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• 1994.04a
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• pp.75-84
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• 1994

A control panel layout method based on the constraint satisfaction problem(CSP) technique was developed to generate an ergonomically sound panel design. This control panel layout method attempts to incorporate a variety of relevant ergonomic principles and design constrains, and generate an optimal or, at least, a "satisfactory" solution through the efficient search algorithm. The problem of seeking an ergonomically sound panel design should be viewed as a multiple criteria problem, and most of the design objectives should be understood as constraints. Hence, a CSP technique was employed in this study for dealing with the multi-constraiants layout problem. The efficient search algorithm using "preprocess" and "look ahead" procedures was developed to handle the vast amount of computational effort. In order to apply the CSP technique to the panel layout procedure, the ergonomic principles such as spatial compatibility, frequency-of- use, importance, functional grouping, and sequence-of-use were formalized as CSP terms. The effectiveness of the developed panel layout method was evaluated by example problems, and the results clearly showed that the generated layouts took various ergonomic design principles into account.esign principles into account.

• 한국정보통신설비학회:학술대회논문집
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• 2005.08a
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• pp.285-289
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• 2005

In recent years, RFID is widely used in industrial applications including factory, material flow, logistics and defense areas. In this paper, we developed a RFID baseband system with ASK modulation and convolutional channel code. A commercial ASK RF module is used its frequency range in $350{\sim}351$MHz and power is 10mW and the convolution code is constraint length k=3 and rate R=1/2 The performance is measured implemented the binary search algorithm as anti-collision method and we show the wave shapes whit collision occurrence.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.429-430
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• 2013

유비쿼터스 기술의 발전과 더불어 스마트 교육과 관련된 연구가 활발히 진행되고 있다. 교육 분야에서의 최신 IT 기술의 도입의 첫 단추는 도서관 시스템 이였다. 이용자와 도서관의 자료를 효율적으로 관리하기 위하여 많은 기관에서 RFID(Radio Frequency Identification) 소자를 기반으로 관련 RFID 리더 장비와 데이터 관리 장비를 구축하였다. 이러한 기술을 기반으로 유비쿼터스 기술을 학생들이 가장 많은 시간을 보내는 교실의 환경에 적용하여 스마트 교육 시스템으로 구축하는 것은 교육의 첨단화와 연계되어 연구되고 있다. 본 연구에서는 기존의 자원을 활용하여 네트워크 환경에서의 자원 배분을 원활히 이뤄내는 P2P 기술과 스마트 교육 시스템의 연계점을 연구하고자 한다. 기존 기술의 적용은 안정성과 신뢰성 측면에서 유용하며 새로운 구조의 제안에 있어서 빠른 적용이 가능한 모델로 전개될 수 있다.

• Publications of The Korean Astronomical Society
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• v.38 no.2
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• pp.59-73
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• 2023

Since the farside of the moon is a place to avoid artificial radio frequency interference (RFI) created by human civilization, it is a most suitable place for searching technosignature, which are signs of technological civilization in the universe, in the radio band. The RFI is a factor that makes the study of searching technosignature quite complicated because it is difficult to distinguish between technological signals produced by human and extraterrestrial civilizations. In this paper, we review why the farside of the moon is the best place to detect technosignature and also introduce radio observatories on the farside of the moon that have been proposed in radio astronomy. The SETI (Search for Extraterrestrial Intelligence) project on the farside of the moon is expected to be one of the main candidates for international collaboration research topics on lunar surface observatory.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.44-48
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• 2015

Housing price is a key indicator of housing demand. Actual Transaction Price Index of Apartment (ATPIA) released by Korea Appraisal Board is useful to understand the current level of housing price, but it does not forecast future prices. Big data such as the frequency of internet search queries is more accessible and faster than ever. Forecasting future housing demand through big data will be very helpful in housing market. The objective of this study is to develop a forecasting model of ATPIA as a part of forecasting housing demand. For forecasting, a concept of time shift was applied in the model. As a result, the forecasting model with the time shift of 5 months shows the highest coefficient of determination, thus selected as the optimal model. The mean error rate is 2.95% which is a quite promising result.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.378-384
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• 2023

In this study, we explore social awareness, interest, and acceptance of generative AI, including chatGPT, which has revolutionized web search, 30 years after web search was released. For this purpose, we performed a machine learning-based topic modeling analysis based on Korean news big data collected from November 30, 2022, when chatGPT was released, to August 31, 2023. As a result of our research, we have identified seven topics related to chatGPT and generative AI; (1)growth of the high-performance hardware market, (2)service contents using generative AI, (3)technology development competition, (4)human resource development, (5)instructions for use, (6)revitalizing the domestic ecosystem, (7)expectations and concerns. We also explored monthly frequency changes in topics to explore social interest related to chatGPT and Generative AI. Based on our exploration results, we discussed the high social interest and issues regarding generative AI. We expect that the results of this study can be used as a precursor to research that analyzes and predicts the diffusion of innovation in generative AI.

• Journal of the Korea Convergence Society
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• v.9 no.5
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• pp.15-20
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• 2018

In modern society, crime is one of the major social problems. Crime has a great impact not only on victims but also on those around them. It is important to predict crimes before they occur and to prevent crime. Various studies have been conducted to predict crime. One of the most important factors in predicting crime is frequency of crime occurrence. The frequency of crime is widely used as basic data for predicting crime. However, the frequency of crime occurrence is announced about 2 years after the statistical processing period. In this paper, we propose a frequency analysis of crime - related key words retrieved from the web as a way to indirectly grasp the frequency of crime occurrence. The relationship between the number of frequency of crime occurrence and frequency of actual crime occurrence was analyzed by correlation coefficient.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.383-391
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• 2010

A Lifelog management system provides users with services to store, manage, and search their life logs. This paper proposes a fully-automatic collecting method of real world social contacts and lifelog search engine using collected social contact information as keyword. Wireless short-distance network devices in mobile phones are used to detect social contacts of their users. Human-Bluetooth relationship matrix is built based on the frequency of a human-being and a Bluetooth device being observed at the same time. Results show that with 20% of social contact information out of full social contact information of the observation times used for calculation, 90% of human-Bluetooth relationship can be correctly acquired. A lifelog search-engine that takes human names as keyword is suggested which compares two vectors, a row of Human-Bluetooth matrix and a vector of Bluetooth list scanned while a lifelog was created, using vector information retrieval model. This search engine returns more lifelog than existing text-matching search engine and ranks the result unlike existing search-engine.