• Nuclear Engineering and Technology
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• v.47 no.5
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• pp.624-632
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• 2015

A self-diagnostic monitoring system is a system that has the ability to measure various physical quantities such as temperature, pressure, or acceleration from sensors scattered over a mechanical system such as a power plant, in order to monitor its various states, and to make a decision about its health status. We have developed a self-diagnostic monitoring system for an air-operated valve system to be used in a nuclear power plant. In this study, we have tried to improve the self-diagnostic monitoring system to increase its reliability. We have implemented three different machine learning algorithms, i.e., logistic regression, an artificial neural network, and a support vector machine. After each algorithm performs the decision process independently, the decision-making module collects these individual decisions and makes a final decision using a majority vote scheme. With this, we performed some simulations and presented some of its results. The contribution of this study is that, by employing more robust and stable algorithms, each of the algorithms performs the recognition task more accurately. Moreover, by integrating these results and employing the majority vote scheme, we can make a definite decision, which makes the self-diagnostic monitoring system more reliable.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3716-3724
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• 2023

Loose parts monitoring and detecting alarm type in real Nuclear Power Plant have challenges such as background noise, insufficient alarm data, and difficulty of distinction between alarm data that occur during start and stop. Although many signal processing methods and alarm determination algorithms have been developed, it is not easy to determine valid alarm and extract the meaning data from alarm signal including background noise. To address these issues, this paper proposes a denoising autoencoder-based majority vote classification. Training and test data are prepared by acquiring alarm data from real NPP and simulation facility for data augmentation, and noisy data is reproduced by adding Gaussian noise. Using DAEs with 3, 5, 7, and 9 layers, features are extracted for each model and classified into neural networks. Finally, the results obtained from each DAE are classified by majority voting. Also, through comparison with other methods, the accuracy and the false alarm rate are compared, and the excellence of the proposed method is confirmed.

• Journal of Broadcast Engineering
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• v.14 no.3
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• pp.342-356
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• 2009

This paper presents a vote decision-based deinterlacing scheme for false directional error correction(VDD) to convert interlaced signal into non-interlaced signal using only one fields. The VDD using the vote decision goes through four steps process. The first step extracts regions having doubt of false edge using MM-ELA method. In these regions, the edge direction is decided by the majority vote using upper adjacent pixels's information through the second step. But, we still have undecided directions, which will be decided by the majority vote and the directional average decision at the third step. This step preserves the edge directions and minimizes visual degradation. Finally, the last step interpolates undecided pixels using DOI method which can consider the fine edge direction. Although the VDD with hierarchical structure has a high complexity, it can extract delicate edge compared to other pixel-by-pixel or window-by-window deinterlacing algorithms. Simulation results show that it has significantly improved both the subjective and objective qualities of the reconstructed images.

• Korean journal of communication and information
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• v.17
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• pp.37-60
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• 2001

This study attempted to demonstrate the interaction effects between attitudinal frames of nine daily newspapers and community structure in the 1994s Michigan gubernatorial election. It was theoretically guided by framing research and the self-presentation theory of social-cognition perspective and empirically tested with archival data. For the purpose of this study, content analysis of nine statewide daily newspapers was employed in order to provide data on news framing. Data on voting rates for John Engler, winner of the 1994 Michigan Gubernatorial election, in each county of Michigan were used for vote choice while Michigan census data were used for constructing an Index of community structural differentiation. The results indicated that majority compliance frames were slightly more related with vote choice in homogeneous com-unities rather than were majority compliance frames in heterogeneous communities while social identification frames tended to have an influence on vote choice in heterogeneous communities more than did social identification frames in homogeneous communities.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.3
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• pp.247-259
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• 1992

In this paper, the types of the data exchange between a cell site and a cobile phonefor the call processing on the AMPS(Advanced Mobile Phone Service) are investigated, and the circuit for processing the wideband data stream according to the data types is designed and implemented. The circuit for detecting the Busy / Idle bit which is needed for determining the channel access, the circuit for detecting the word sync and the circuit for transmitting and receiving the wideband data is designed. The 3-out-of-5 majority vote of the 5received data is performed to reduce error and an algorithm requiring a small buffer size for real time processing of voting process is proposed. The method to overcome the computational complexity and the real time constraint of the conventional BCH decoding is proposed.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.4
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• pp.405-414
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• 2016

IC-implementations provide high performance for solving the high computational cost of pattern matching but have relative low flexibility for satisfying different applications. In this paper, we report an associative memory architecture for k nearest neighbor (KNN) search, which is one of the most basic algorithms in pattern matching. The designed architecture features reconfigurable vector-component parallelism enabled by programmable switching circuits between vector components, and a dedicated majority vote circuit. In addition, the main time-consuming part of KNN is solved by a clock mapping concept based weighted frequency dividers that drastically reduce the in principle exponential increase of the worst-case search-clock number with the bit width of vector components to only a linear increase. A test chip in 180 nm CMOS technology, which has 32 rows, 8 parallel 8-bit vector-components in each row, consumes altogether in peak 61.4 mW and only 11.9 mW for nearest squared Euclidean distance search (at 45.58 MHz and 1.8 V).

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.1
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• pp.37-45
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• 2015

As of June 2014, the rate of mobile internet users aged 6 and over is estimated at 98.3% (up by 2.8%p from the previous year). The vast majority of the teens (99.7%), the 20s (99.8%), the 30s (99.8%), and the 40s (98.1%) answer they use the smart phone. The existing notice methods have utilized noticeboard in the apartment. It is difficult to support real-time notice. The App has a merit to be accessed in anywhere, so that it is quite suitable for services requiring real-time support. This paper describes a development of apartmenrt notice and decision-making service using smart phone. We study previous researches about apartmenrt notice Apps. Then, we described the notice flow diagram and decision-making flow diagram. Apt admin sends the important notice message to residents using apt notice app in real-time. Apt admin writes the decision item in the admin web site. It pushes decision item to residents using apt notice app in real-time. The residents vote and send it to Apt admin. Apt admin counts the votes and send the collect the vote result to to residents.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.3
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• pp.230-235
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• 2004

This paper describes FPGA implementation of a pointer interpreter which can support a synchronization of SDH(or SONET)-based transmission network. The pointer interpreter consists of a pointer-word extractor and a pointer-word interpreter The pointer-word extractor which is composed of mod-6480 counter, shift register and pointer synchronizing block, finds out the H1 and H2 pointer word from a 51.84 Mb/s AU-3/STS-1 data frame and then performs the synchronizing with a 6.48 Mb/s by dividing them in 8. Based on the extracted pointer word, pointer-word interpreter analyzes pointer states such LOP, AIS and NORM according to pointer state-transition algorithm. It consists of a majority vote, a pointer word valid/invalid check, a pointer justification, and a pointer state check. The simulation results of Xilinx Virtex XCV200PQ240 FPGA chip shows the exact pointer word extraction and correct decision of pointer status based on extracted pointer word. The proposed pointer interpreter is suitable for pointer interpretation of 155 Mb/s STM-1/STS-3 frame.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.883-885
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• 2005

지지 벡터 기계(Support Vector Machine: SVM)를 이용한 다중부류 분류기법이 최근 활발히 연구되고 있다. SVM은 이진분류기이기 때문에 다중부류 분류를 위해서 다수의 분류기를 구성하고 이들을 효과적으로 결합하는 방법이 필요하다. 본 논문에서는 기존의 정적인 다중분류기 결합 방법과는 달리 포섭구조의 분류모델을 확률에 따라 동적으로 구성하는 방법을 제안한다. 확률적 분류기인 나이브 베이즈 분류기(NB)를 이용하여 입력된 샘플의 각 클래스에 대한 확률을 계산하고, OVA (One-Vs-All) 전략으로 구축된 다중의 SVM을 획득된 확률에 따라 포섭구조로 구성한다. 제안하는 방법은 OVA SVM에서 발생하는 중의적인 상황을 효과적으로 처리하여 고성능의 분류를 수행한다. 본 논문에서는 지문분류 문제에서 대표적인 NIST-4 지문 데이터베이스를 대상으로 제안하는 방법을 적용하여 $1.8\%$의 거부율에서 $90.8\%$의 분류율을 획득하였으며, 기존의 결합 방법인 다수결 투표(Majority vote), 승자독식(Winner-takes-all), 행동지식공간 (Behavior knowledge space), 결정템플릿(Decision template) 등보다 높은 성능을 확인하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.622-624
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• 2005

대규모 지문인식 시스템에서 비교해야할 지문의 수를 줄이기 위해서 지문분류는 필수적인 과정이다. 최근 이진분류기인 지지 벡터 기계(Support Vector Machine: SVM)를 이용한 지문분류 기법이 많이 연구되고 있다. 본 논문에서는 다중부류 지문분류에 적합하도록 자기 구성 지도(Self-Organizing Map:SOM)를 이용하여 OVA(One-Vs-All) SVM들을 결합하는 지문분류 기법을 제안한다. SOM을 이용하여 OVA SVM들을 동적으로 결합하기 위한 결합 지도를 생성하여 지문분류 성능을 높인다. 지문분류에 있어 대표적인 NIST-4 지문 데이터베이스를 대상으로 Jain이 구축한 FingerCode 데이터베이스에 제안하는 방법을 적용하여 $1.8\%$의 거부율에서 $90.5\%$의 분류율을 획득하였으며, 기존의 결합 방법인 승자독식(Winner-takes-all)과 다수결 투표(Majority vote)보다 높은 성능을 확인하였다.