• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.415-424
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• 1999

Systematic telecommunication network management is essential for operating large-scale integrated networks which consist of various network components manufactured by different vendors. ISO and ITU-T recommend the CMIP-based TMN architecture for this purpose. TMN uses GDMO for the definition of managed objects, and various GDMO compilers have been developed. However, the development of management objects by using these compilers is still a difficult task. In this paper, we present a GUI-based managed objects development environment, MODE. MODE divides managed object codes by system independent code(SIC) and system dependent cede(SDC). By providing development environments for SIC and SDC, MODE can ease the development of managed objects. To show the efficiency of MODE, we develop the managed objects of an ATM switch in MODE.

• Korean Journal of Child Studies
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• v.6 no.2
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• pp.21-33
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• 1985

This study was conducted to ascertain whether a didactic mode of instruction, favored students who indicated a preference for left hemispheric information processing. The subjects were 50 fifth grade students whose California Achievement Test score percentile ranks were between 50 - 80. They were randomly selected from one elementary school in Chapel Hill, NC, USA. All Ss completed the Form CC of "Your Style of Learning and Thinking" (Torrance and McCarthy, 1980) which is a paper/pencil inventory designed to categorize the subjects according to their hemispheric preference for processing information; right hemisphere, left hemisphere, and integrated. Then all Ss received a didactic mode of instruction, a verbal question/answer followed by teacher's reading of a fictional animal story, "The Chinese Bee-eater". After completion of instruction, the Ss were asked to respond to eighteen open-ended questions about the animal. Eight of the 50 subjects were found to fall into the right hemisphere style of information processing group; fourteen into left; and fourteen into integrated. The remaining fourteen could not be assigned to either of these three categories and were not included in the analysis of the results. the mean scores of the comprehensive test among hemispheric groups and among sex groups. A two way analysis of variance also presented no significant differences among the hemispheric preference combined by sex groups. These results failed to prove the research hypothesis that students who indicate a preference for left hemispheric information processing will have higher scores on a comprehensive test after receiving a didactic mode of instruction, the so-called left style of instruction. Some limits in research process and conceptual confusion about hemisphericity were discussed. Finally, it was suggested that educators need to be more careful in drawing educational implications from neurological hemispheric research.

• The Korean Journal of Applied Statistics
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• v.27 no.7
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• pp.1171-1185
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• 2014

Rhipe that integrates R and Hadoop environment, made it possible to process and analyze massive amounts of data using a distributed processing environment. In this paper, we implemented multiple regression analysis using Rhipe with various data sizes of actual data and simulated data. Experimental results for comparing the computing speeds of pseudo-distributed and fully-distributed modes for configuring Hadoop cluster, showed fully-distributed mode was more fast than pseudo-distributed mode and computing speeds of fully-distributed mode were faster as the number of data nodes increases. We also compared the performance of our Rhipe with stats and biglm packages available on bigmemory. The results showed that our Rhipe was more fast than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3642-3651
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• 1999

In this paper, we propose a new caching scheme for continuous media data where the buffer allocation unit is divided into two modes : interval and object. All of objects' access patterns are monitored and based on the results of monitoring, a request for an object is decided to cache its data with either interval mode or object mode. The results of our simulation show that our proposed caching scheme is better than the existing caching algorithms such as interval caching where the access patterns of the objects are changed with time.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.11a
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• pp.1688-1690
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• 2010

컴퓨터에서 안정성은 가장 중요시된다. 파일 시스템의 안정성이 문제가 되어 시스템이 다운되거나 여러 가지 문제가 발생할 경우, 데이터가 손상 되거나 데이터 복구가 불가능하게 될 수 있다. EXT3 파일 시스템은 이러한 문제점을 보안하기 위해 기존의 EXT2 파일 시스템에 저널링 기능이 추가된 파일 시스템이다. EXT3 파일 시스템은 매우 안정적이고, 기존의 EXT2 파일 시스템에서의 변경 과정이 쉽고 간단하여 일반적으로 많이 사용 되고 있는 저널링 파일 시스템이다. EXT3 파일 시스템은 기본적으로 ordered mode 를 사용하는데 메타데이터가 저널에 기록되는 추가적인 과정이 이루어져야 하기 때문에 성능의 저하가 발생한다. 본 논문에서는 ordered mode 에 압축 저장 기법을 적용하여 효율적인 공간 관리와 쓰기 속도가 향상된 ordered mode 저널링 기능을 제안하여 파일 시스템 기능을 개선하고자 한다.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.556-570
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• 2021

The existing video expression recognition methods mainly focus on the spatial feature extraction of video expression images, but tend to ignore the dynamic features of video sequences. To solve this problem, a multi-mode convolution neural network method is proposed to effectively improve the performance of facial expression recognition in video. Firstly, OpenFace 2.0 is used to detect face images in video, and two deep convolution neural networks are used to extract spatiotemporal expression features. Furthermore, spatial convolution neural network is used to extract the spatial information features of each static expression image, and the dynamic information feature is extracted from the optical flow information of multiple expression images based on temporal convolution neural network. Then, the spatiotemporal features learned by the two deep convolution neural networks are fused by multiplication. Finally, the fused features are input into support vector machine to realize the facial expression classification. Experimental results show that the recognition accuracy of the proposed method can reach 64.57% and 60.89%, respectively on RML and Baum-ls datasets. It is better than that of other contrast methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10A
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• pp.776-783
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• 2009

Current-cut circuit is an effective method to obtain low power consumption in wireless communication systems as high speed OFDM. For the operation of current-mode FFT LSI with analog signal processing essentially requires current-mode serial-to-parallel/parallel-to-serial converter with multi input and output structure. However, the Hold-mode operation of current-mode serial-to-parallel/parallel-to-serial converter has unnecessary power consumption. We propose a novel current-mode serial-to-parallel/parallel-to-serial converter with current-cut circuit and full chip simulation results agree with experimental data of low power consumption. The proposed current-mode serial-to-parallel/parallel-to-serial converter promise the wide application of the current-mode analog signal processing in the field of low power wireless communication LSI.

• Journal of the Korean Society of Industry Convergence
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• v.10 no.4
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• pp.241-248
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• 2007

It is recently trend that local government which introduce the BIS is increasing steadily. Communication is inevitably necessary to offer a data of a collected bus position to transportation center and supply construed information. Until now, most BIS connection research is actively in data of collecting, processing, offer but Research is Relatively insufficient on communication mode to connect it. Therefore, this study is achieving applicable communication mode on BIS of present common use inning that communication mode. Study resulting, characteristic of BIS communication mode is analyzed that send-receive of short packet data happens frequently and It is inevitably necessary to synthetically analyze economical side, authoritativeness side of communication, introducing communication mode.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.42-48
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• 1994

In this paper, a low power and high speed flash Analog-to-Digital Converter using current-mode concept is proposed. Current-mode approach offers a number of advantages over conventional voltage-mode approach, such as lower power consumption small chip area improved accuracy etc. Rescently this concept was applied to algorithmic A/D Converter. But, its conversion speed is limited to medium speed. Consequently this converter is not applicable to the high speed signal processing system. This ADC is fabricated in 1.2um double metal CMOS standard process. This ADC's conversion time is measured to be 7MHz, and power consumption is 2.0mW, and differential nonlinearity is less than 1.14LSB and total harmonic distortion is -50dB. The active area of analog chip is about 350 x 550u$m^2$. The proposed ADC seems suitable for a single chip design of digital signal processing system required high conversion speed, high resolution small chip area and low power consumption.

• Proceedings of the Korean Society for Information Management Conference
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• 2006.08a
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• pp.163-168
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• 2006

Nursing diagnosis process is described as nurses assessing the patients' conditions by applying reasoning and looking for patterns, which fit the defining characteristics of one or more diagnoses. This process is similar to using a typical document retrieval system if we consider the patients' conditions as queries, nursing diagnoses as documents, and the defining characteristics as index terms of the documents. However, there is a small fixed number of nursing diagnoses and infinite number of patients' conditions in a typical hospital setting. This state is more suitable to applying document routing mode of information access, which is defined as a number of archived profiles, compared to individual documents. In this paper, we describe a ROUting-based Nursing Diagnosis (ROUND) system and its Natural Language Processing-based query processing component, which converts the defining characteristics of nursing diagnoses into query representations.