• 제목/요약/키워드: Data display

검색결과 2,241건 처리시간 0.023초

A Database System for High-Throughput Transposon Display Analyses of Rice

  • Inoue, Etsuko;Yoshihiro, Takuya;Kawaji, Hideya;Horibata, Akira;Nakagawa, Masaru
    • 한국생물정보학회:학술대회논문집
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    • 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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    • pp.15-20
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    • 2005
  • We developed a database system to enable efficient and high-throughput transposon analyses in rice. We grow large-scale mutant series of rice by taking advantage of an active MITE transposon mPing, and apply the transposon display method to them to study correlation between genotypes and phenotypes. But the analytical phase, in which we find mutation spots from waveform data called fragment profiles, involves several problems from a viewpoint of labor amount, data management, and reliability of the result. As a solution, our database system manages all the analytical data throughout the experiments, and provides several functions and well designed web interfaces to perform overall analyses reliably and efficiently.

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마이크로컴퓨터를 이용한 64채널 심장전기도시스템개발 (Development of 64 Channel Cardiac Mapping System Using Microcomputer)

  • 정성헌;김원기
    • 대한의용생체공학회:의공학회지
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    • 제12권4호
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    • pp.303-308
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    • 1991
  • Computer assisted cardiac mapping system has made it possible to display local activation times of the heart using a simultaneous multi-point data aquisition system, and opened an era in electrophyslology guided cardiac arrhythmia surgery especially in ventricular tachycardia. In this study, we have developed a 64 channel computerized cardiacmapping system us:ng a micro-computer for basic reasearch of electrophysiology and electrical propagation in cardiac arrhythmias. The significant tasks of this study were the simultaneous acquisition of large amount of data from 64 sites, accurate and rapid analysis, and the effective display of the analyzed data. To solve these problems, we made a 64 channel signal pre-processing board in order to amplify and fitter the raw signals. And we developed the soflu'are Yor cardiac isochronous mapping whictl is presented immediately ama computer-generated graphics. This system is expected 4o enable us to study pathophyslology of cardiac arrhythmia and to improve the results of diagnosis and surgical treatments for cardiac arrhythmia.

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Projection Pursuit K-Means Visual Clustering

  • Kim, Mi-Kyung;Huh, Myung-Hoe
    • Journal of the Korean Statistical Society
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    • 제31권4호
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    • pp.519-532
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    • 2002
  • K-means clustering is a well-known partitioning method of multivariate observations. Recently, the method is implemented broadly in data mining softwares due to its computational efficiency in handling large data sets. However, it does not yield a suitable visual display of multivariate observations that is important especially in exploratory stage of data analysis. The aim of this study is to develop a K-means clustering method that enables visual display of multivariate observations in a low-dimensional space, for which the projection pursuit method is adopted. We propose a computationally inexpensive and reliable algorithm and provide two numerical examples.

무선 근거리 통신망 환경을 위한 다단계 데이터베이스 시스템 (Multi-tier Database System for Wireless LAN Environment)

  • 박제호
    • 반도체디스플레이기술학회지
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    • 제3권4호
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    • pp.13-17
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    • 2004
  • As the usage of wireless LAN becomes common in working environment, the number of database systems that support both wired and wireless users increases rapidly. The characteristics of wireless LAN that its speed is slow relatively comparing to wired network and the users in its environment connects to different communication points as they moves creates another challenge to be resolved in database systems. In the environment of hybrid communication systems, wired and wireless for voluminous data amount and a number of users, the two layer architecture of the conventional client-server database systems has limitation in the system performance. This is due to that server is the only point of data service in client-server database systems. In this paper, we discuss a new extended database system architecture that data services are distributed among servers and clients based on user database access patterns in order to improve system performance. We analyze the expected system performance by using simulation technique and prove the practical utilization of the system by demonstrating experimental results.

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무선 센서 네트워크 환경에서 적응형 임계값 설정 방법 (An Adaptive Threshold Method in Wireless Sensor Network Environments)

  • 김인태;김두용
    • 반도체디스플레이기술학회지
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    • 제7권1호
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    • pp.23-27
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    • 2008
  • Wireless sensor networks are emerging as a solution for a wide range of data gathering applications. The most difficult challenge for the design of sensor nodes is the need for significant reductions in energy consumption. The threshold methods which filter redundant and similar data can be used to save energy. In this paper, we propose the adaptive threshold method to effectively manage the energy in wireless sensor nodes. In the adaptive threshold method, wireless sensor nodes can change the thresholds dynamically as the sensing environments vary. The simulation results show that the adaptive threshold method works very effectively even when we experience the significant volatility in the data. This scheme can be used in order to monitor the malfunction in the equipment of semiconductor manufacturing line.

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Deep-learning based In-situ Monitoring and Prediction System for the Organic Light Emitting Diode

  • Park, Il-Hoo;Cho, Hyeran;Kim, Gyu-Tae
    • 반도체디스플레이기술학회지
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    • 제19권4호
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    • pp.126-129
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    • 2020
  • We introduce a lifetime assessment technique using deep learning algorithm with complex electrical parameters such as resistivity, permittivity, impedance parameters as integrated indicators for predicting the degradation of the organic molecules. The evaluation system consists of fully automated in-situ measurement system and multiple layer perceptron learning system with five hidden layers and 1011 perceptra in each layer. Prediction accuracies are calculated and compared depending on the physical feature, learning hyperparameters. 62.5% of full time-series data are used for training and its prediction accuracy is estimated as r-square value of 0.99. Remaining 37.5% of the data are used for testing with prediction accuracy of 0.95. With k-fold cross-validation, the stability to the instantaneous changes in the measured data is also improved.

측정 자동화 구축을 위한 투영기의 치수오차 분석에 관한 연구 (A Study on Analysis of Dimensional Error of Projector for Formulations of Measurement Automation)

  • 최지선;김문기
    • 반도체디스플레이기술학회지
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    • 제20권4호
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    • pp.114-118
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    • 2021
  • In this research, the dimensional error of the measured specimen according to the measurement method was analyzed for the length, angle, radius of curvature and diameter using a projector which is used in industry. One-way analysis was performed on each data tested 30 times using a statistical technique. Through the experiment, it was found that an error occurred in each data when measuring the length and radius of curvature according to the measurement method, and the null hypothesis that no error occurred when measuring the angle and length was established. Based on this experimental data, the automatic measurement when measuring the projector causes less measurement error, so automatic measurement is recommended when measuring a small product. Also, an optimal measuring method is suggested for securing reliability on formulations of measurement automation.

실시간 모션 데이터를 활용한 메타버스 사용자-아바타 상호작용 구현 (Implementation of Metaverse User-Avatar Interaction using Real-time Motion Data)

  • 이강인;노은혜;조영재;이용환
    • 반도체디스플레이기술학회지
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    • 제22권4호
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    • pp.172-178
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    • 2023
  • With the expansion of metaverse content and hardware platforms, various interactions in the virtual world have been built, raising expectations for an increase in immersion which is a major element of the metaverse. However, among hardware platforms that increase virtual immersion elements, the typical HMD platform can be a barrier to new user inflows due to its high cost. Thus, this paper focused on improving virtual-to-real interactions by extracting motion data using relatively inexpensive webcam equipment in PC environments, utilizing Unity game engines, Photon unity network, multi-platform implementations, and Barracuda neural network inference libraries.

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Spatial database architecture for organizing a unified information space for manned and unmanned aviation

  • Maksim Kalyagin;Yuri Bukharev
    • Advances in aircraft and spacecraft science
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    • 제10권6호
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    • pp.545-554
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    • 2023
  • The widespread introduction of unmanned aircrafts has led to the understanding of the need to organize a common information space for manned and unmanned aircrafts, which is reflected in the Russian Unmanned aircraft system Traffic Management (RUTM) project. The present article deals with the issues of spatial information database (DB) organization, which is the core of RUTM and provides storage of various data types (spatial, aeronautical, topographical, meteorological, vector, etc.) required for flight safety management. Based on the analysis of functional capabilities and types of work which it needs to ensure, the architecture of spatial information DB, including the base of source information, base of display settings, base of vector objects, base of tile packages and also a number of special software packages was proposed. The issues of organization of these DB, types and formats of data and ways of their display are considered in detail. Based on the analysis it was concluded that the optimal construction of the spatial DB for RUTM system requires a combination of different model variants and ways of organizing data structures.

인공지능을 활용한 클라우드 컴퓨팅 서비스의 품질 관리를 위한 데이터 정형화 방법 (Data Standardization Method for Quality Management of Cloud Computing Services using Artificial Intelligence)

  • 정현철;서광규
    • 반도체디스플레이기술학회지
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    • 제21권2호
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    • pp.133-137
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    • 2022
  • In the smart industry where data plays an important role, cloud computing is being used in a complex and advanced way as a convergence technology because it has and fits well with its strengths. Accordingly, in order to utilize artificial intelligence rather than human beings for quality management of cloud computing services, a consistent standardization method of data collected from various nodes in various areas is required. Therefore, this study analyzed technologies and cases for incorporating artificial intelligence into specific services through previous studies, suggested a plan to use artificial intelligence to comprehensively standardize data in quality management of cloud computing services, and then verified it through case studies. It can also be applied to the artificial intelligence learning model that analyzes the risks arising from the data formalization method presented in this study and predicts the quality risks that are likely to occur. However, there is also a limitation that separate policy development for service quality management needs to be supplemented.