• Title/Summary/Keyword: 입력 프레임워크

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Design and Implementation of a Reusable and Extensible HL7 Encoding/Decoding Framework (재사용성과 확장성 있는 HL7 인코딩/디코딩 프레임워크의 설계 및 구현)

  • Kim, Jung-Sun;Park, Seung-Hun;Nah, Yun-Mook
    • Journal of KIISE:Computing Practices and Letters
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    • v.8 no.1
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    • pp.96-106
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    • 2002
  • this paper, we propose a flexible, reusable, and extensible HL7 encoding and decoding framework using a Message Object Model (MOM) and Message Definition Repository (MDR). The MOM provides an abstract HL7 message form represented by a group of objects and their relationships. It reflects logical relationships among the standard HL7 message elements such as segments, fields, and components, while enforcing the key structural constraints imposed by the standard. Since the MOM completely eliminates the dependency of the HL7 encoder and decoder on platform-specific data formats, it makes it possible to build the encoder and decoder as reusable standalone software components, enabling the interconnection of arbitrary heterogeneous hospital information systems(HISs) with little effort. Moreover, the MDR, an external database of key definitions for HL7 messages, helps make the encoder and decoder as resilient as possible to future modifications of the standard HL7 message formats. It is also used by the encoder and decoder to perform a well formedness check for their respective inputs (i. e., HL7 message objects expressed in the MOM and encoded HL7 message strings). Although we implemented a prototype version of the encoder and decoder using JAVA, they can be easily packaged and delivered as standalone components using the standard component frameworks like ActiveX, JAVABEAN, or CORBA component.

Design and Implementation of Media Manager in Multimedia Streaming Framework (스트리밍 프레임워크에서 미디어 관리자의 설계 및 구현)

  • Lee, Jae-Wook;Lee, Sung-Young;Hong, Een-Kee
    • Journal of KIISE:Computing Practices and Letters
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    • v.7 no.4
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    • pp.273-287
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    • 2001
  • In this paper, we introduce our experience for designing and implementing a media manager in the Integrated Streaming Service Architecture (ISSA) developed by the authors. The media manager is regarded as a necessary module in the ISSA framework for the following reasons. It realizes that from which locations of the media source devices, the media streams are coming. Once it knows where the origin is, the media manager should recognizes what types of stream are. After that, it performs how to chose an appropriate CODEC to handle the recognized input streams efficiently, and what type of media playback device should be selected. In order to do such a job efficiently, the proposed media manager consists of two modules source module and sink module. The major role of a media source module is to make an abstraction for the media streams that are coming from various types of media device. This, in consequence, enables a media manager to consistently handle tlle media streams without considering wherever they come from. On the other hand, the media sink module distributes the input streams to an appropriate media device to playback. One of the remarkable virtues of the proposed media manager is an ability to supporting high value-added database services since it provides an interface between the ISSA and real-time multimedia database. Also, it provides the RTP!RTSP source filter and Winamp gateway modules which allow the flexibility to the system. Moreover, the media manager can adopt any types of new media which in fact will provide scalability to the ISSA.

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Efficient Computation of Grouping Sets Queries Using MapReduce (맵리듀스에서 Grouping Sets 질의의 효율적인 계산 기법)

  • Park, So-Jeong;Park, Eun-Ju;Lee, Ki Yong
    • Annual Conference of KIPS
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    • 2014.11a
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    • pp.783-786
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    • 2014
  • 맵리듀스(MapReduce)는 대용량의 데이터를 여러 컴퓨터에서 분산, 병렬 처리하는 프레임워크이다. Grouping sets 질의는 사용자가 지정한 여러 개의 group-by들을 모두 구하는 질의로서, 롤업(rollup)과 큐브(cube)가 너무 많은 결과를 반환하는 단점을 보완하여 원하는 group-by들에 대한 결과만 얻을 수 있도록 한다. 본 논문은 맵리듀스 환경에서 grouping sets 질의를 효율적으로 계산하는 방법을 제안한다. 제안 방법은 grouping sets 질의를 2개의 맵리듀스 잡(job)을 통해 단계적으로 계산한다. 첫 번째 맵리듀스 잡은 grouping sets 질의에 포함된 group-by들이 모두 계산될 수 있는 '부모' group-by를 먼저 계산한다. 두 번째 맵리듀스 잡은 부모 group-by를 입력으로 하여 grouping sets 질의에 포함된 group-by들을 각각 계산한다. 부모 group-by의 크기가 입력 데이터의 크기에 비해 매우 작은 경우, 제안 방법은 입력 데이터로부터 각 group-by를 독립적으로 구하는 단순 방법보다 좋은 성능을 보인다. 실험을 통해 제안 방법이 각 group-by를 독립적으로 구하는 단순 방법보다 좋은 성능을 가짐을 보인다.

A Mobile Agent Programming System for Efficient Distributed Applications (효율적 분산 응용을 위한 이동 에이전트 프로그래밍 시스템)

  • Jeong, Won-Ho;Kang, Mi-Yeon;Kim, Yun-Su
    • The KIPS Transactions:PartA
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    • v.10A no.5
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    • pp.439-452
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    • 2003
  • Mobile agent is one of the good technologies for overcoming network load and latency in distributed applications, and it may be a promising way of base technology of distributed applications because of its high adaptability for various network environments. In this paper, a mobile agent programming system, called HUMAN, is designed and implemented efficient use in various distributed applications based on mobile agents. HUMAN supports such high level utilities as file searhing, addressing by groups of nodes, storing path information, storing search information, and thus it gives us high easiness in agent-based programming. And it provides various itinerary modes and flexible reply modes for easy adaptation to given network environment. It also provides a management server for registering and active agents. Thus it can be efficiently applied for such varous distributed applications as searching distributed information, remote control, and file sharing in networks. A simple electronic commerce system is designed is designed and implemented as a HUMAN based illustrative application.

Recognition of Korean Isolated Digits Using Classification and Prediction Neural Networks (예측형과 분류형 신경망을 이용한 한국어 숫자음 인식)

  • 한학용;김주성;고시영;허강인;안점영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.12B
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    • pp.2447-2454
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    • 1999
  • This paper proposes a N-APPEM(Nonlinear A Posteriori Probability Estimation Method) with a frame normalization method to conventional classification network to increase speech recognition ability. It also tests the recognition ability of the classification and prediction neural networks for the Korean isolated digits. From the experimental results, the prediction network with MLP(Multi-Layer Perceptron) achieves the highest recognition ability of 98.0%. The prediction requires very complicated networks increased linearly with the number of incoming speech categories. However, the classification network with the N-APPEM and the normalization improves the recognition ability up to 85.5% with a sin81e network, which is almost 12.0% improvement.

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A Study on Tools for Event Report Request Generation on MPEG-21 (MPEG-21 이벤트리포트 요구 생성도구 구현)

  • Lee Chang-Min;Ji Kyung-Hee;Moon Nam-Mee;Kang Jung-Won
    • Annual Conference of KIPS
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    • 2006.05a
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    • pp.1085-1088
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    • 2006
  • MPEG-21 멀티미디어 프레임워크의 주요 기술 중 하나인 이벤트 리포팅은 MPEG-21 내에서 사용자, 피어, 디지털아이템 사이에서 발생하는 모든 보고 가능한 이벤트에 대한 정보를 공유하기 위한 표준적인 측정 방법과 인터페이스를 제공한다는 점에서 그 중요성을 가진다. 현재 MPEG을 중심으로 MPEG-21 이벤트 리포팅에 대한 연구가 진행되고 있으나 이를 구현한 예가 극히 드물다. 본 논문은 MPEG-21의 이벤트 리포팅 표준 기술을 바탕으로 이벤트 리포트 요구 생성 도구의 설계 및 구현 그리고 구현 결과에 대해 논하였다. 이벤트 리포트 요구 생성 도구는 메인 프레임, 입력 다이얼로그, 그리고 생성 프로세스로 구성되어 있다. 이벤트 리포트 요구의 표현언어는 XML이며 XML 표준 문법과 이벤트 리포트 요구 디지털 아이템 구조에 맞게 생성되도록 설계되었다.

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Performance Evaluation of Price-based Input Features in Stock Price Prediction using Tensorflow (텐서플로우를 이용한 주가 예측에서 가격-기반 입력 피쳐의 예측 성능 평가)

  • Song, Yoojeong;Lee, Jae Won;Lee, Jongwoo
    • KIISE Transactions on Computing Practices
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    • v.23 no.11
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    • pp.625-631
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    • 2017
  • The stock price prediction for stock markets remains an unsolved problem. Although there have been various overtures and studies to predict the price of stocks scientifically, it is impossible to predict the future precisely. However, stock price predictions have been a subject of interest in a variety of related fields such as economics, mathematics, physics, and computer science. In this paper, we will study fluctuation patterns of stock prices and predict future trends using the Deep learning. Therefore, this study presents the three deep learning models using Tensorflow, an open source framework in which each learning model accepts different input features. We expand the previous study that used simple price data. We measured the performance of three predictive models increasing the number of priced-based input features. Through this experiment, we measured the performance change of the predictive model depending on the price-based input features. Finally, we compared and analyzed the experiment result to evaluate the impact of the price-based input features in stock price prediction.

Efficient Mobile Writing System with Korean Input Interface Based on Face Recognition

  • Kim, Jong-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.25 no.6
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    • pp.49-56
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    • 2020
  • The virtual Korean keyboard system is a method of inputting characters by touching a fixed position. This system is very inconvenient for people who have difficulty moving their fingers. To alleviate this problem, this paper proposes an efficient framework that enables keyboard input and handwriting through video and user motion obtained through the RGB camera of the mobile device. To develop this system, we use face recognition to calculate control coordinates from the input video, and develop an interface that can input and combine Hangul using this coordinate value. The control position calculated based on face recognition acts as a pointer to select and transfer the letters on the keyboard, and finally combines the transmitted letters to integrate them to perform the Hangul keyboard function. The result of this paper is an efficient writing system that utilizes face recognition technology, and using this system is expected to improve the communication and special education environment for people with physical disabilities as well as the general public.

A study of how to input data validation from the central viewpoint using eGov framework (전자정부 표준프레임워크를 이용한 중앙집중적인 관점에서의 입력 데이터 검증 방법 연구)

  • Lee, Sang-Gu;Choi, Jin-Young
    • Annual Conference of KIPS
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    • 2013.11a
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    • pp.666-669
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    • 2013
  • 2012년 고시된 '정보시스템 구축 운영 지침'에 따라 행정안전부에서는 '전자정부 SW 개발 운영자를 위한 시큐어 코딩 가이드'를 배포하고 있다. 시큐어 코딩 기법을 예제 위주로 제시함으로써, 개발 실무에 활용도를 높이기 위하여 배포된 시큐어 코딩 가이드는 유용한 지침서임에는 틀림이 없으나, 개발자 개개인이 그 내용을 모두 숙지하기 위해서는 많은 시간과 노력을 필요로 한다. 특히 입력 데이터 검증 및 표현에 관한 시큐어 코딩은 시스템 아키텍쳐 차원의 중앙집중적인 관점이 아닌 개발자 개개인이 구현한 기능 단위 수준에서 수행되고 있는 필드의 현실상, 이를 중앙집중적인 관점에서의 입력 데이터 검증을 통하여, 보다 안전한 소프트웨어를 제작하기 위한 방법을 코드 중심의 사례로 설명하고자 한다.

RGB-VO: Visual Odometry using mono RGB (단일 RGB 영상을 이용한 비주얼 오도메트리)

  • Lee, Joosung;Hwang, Sangwon;Kim, Woo Jin;Lee, Sangyoun
    • Annual Conference of KIPS
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    • 2018.05a
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    • pp.454-456
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    • 2018
  • 주율 주행과 로봇 시스템의 기술이 발전하면서 이와 관련된 영상 알고리즘들의 연구가 활발히 진행되고 있다. 제안 네트워크는 단일 영상을 이용하여 비주얼 오도메트리를 예측하는 시스템이다. 딥러닝 네트워크로 KITTI 데이터 세트를 이용하여 학습과 평가를 하며 네트워크의 입력으로는 연속된 두 개의 프레임이 들어가고 출력으로는 두 프레임간 카메라의 회전과 이동 정보가 된다. 이를 통하여 대표적으로 자동차의 주행 경로를 알 수 있으며 여러 로봇 시스템 등에서 활용할 수 있다.