• 지식경영연구
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• 제19권1호
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• pp.133-146
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• 2018

This study develops an Education framework for users who need public open data for workplace etiquette education in a timely manner by mobile application. It facilitates utilizing efficiently Workplace etiquette contents that scattered in various platforms such as blogs, Youtube and web-sites run by private education agencies. Furthermore, it makes Public open data for workplace etiquette through gathering 'metadata', which is a comprehensive source of workplace etiquette. Accordingly, framework changes recognition about necessity of workplace etiquette education positively and suggests method that can promote effective workplace etiquette education. If the system in the study can provide public open data of workplace etiquette education, many young job applicants and workers will have a proper perception on it and sound workplace etiquette culture will be settled in the companies. Public data has been rising as a vital national strategic asset these days. Hopefully the public data will pave a way to discover the blue ocean in the market and open up a new type of businesses.

• 한국멀티미디어학회논문지
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• 제24권10호
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• pp.1403-1413
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• 2021

In this paper, we investigate automated data validation techniques for artificial intelligence training, and also disclose open-source frameworks, such as Google's TensorFlow Data Validation (TFDV), that support automated data validation in the AI model development process. We also introduce an experimental study using public data sets to demonstrate the effectiveness of the open-source data validation framework. In particular, we presents experimental results of the data validation functions for schema testing and discuss the limitations of the current open-source frameworks for semantic data. Last, we introduce the latest studies for the semantic data validation using machine learning techniques.

• 전기학회논문지
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• 제67권2호
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• pp.270-276
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• 2018

Apache Spark is one of the high performance in-memory computing frameworks for big-data processing. Recently, to improve the performance, general-purpose computing on graphics processing unit(GPGPU) is adapted to Apache Spark framework. Previous Spark-GPGPU frameworks focus on overcoming the difficulty of an implementation resulting from the difference between the computation environment of GPGPU and Spark framework. In this paper, we propose a Spark framework based on a heterogenous pipeline computing with OpenCL to further improve the performance. The proposed framework overlaps the Java-to-Native memory copies of CPU with CPU-GPU communications(DMA) and GPU kernel computations to hide the CPU idle time. Also, CPU-GPU communication buffers are implemented with switching dual buffers, which reduce the mapped memory region resulting in decreasing memory mapping overhead. Experimental results showed that the proposed Spark framework based on a heterogenous pipeline computing with OpenCL had up to 2.13 times faster than the previous Spark framework using OpenCL.

• 지능정보연구
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• 제26권4호
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• pp.27-65
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• 2020

많은 정보통신기술 기업들은 자체적으로 개발한 인공지능 기술을 오픈소스로 공개하였다. 예를 들어, 구글의 TensorFlow, 페이스북의 PyTorch, 마이크로소프트의 CNTK 등 여러 기업들은 자신들의 인공지능 기술들을 공개하고 있다. 이처럼 대중에게 딥러닝 오픈소스 소프트웨어를 공개함으로써 개발자 커뮤니티와의 관계와 인공지능 생태계를 강화하고, 사용자들의 실험, 적용, 개선을 얻을 수 있다. 이에 따라 머신러닝 분야는 급속히 성장하고 있고, 개발자들 또한 여러가지 학습 알고리즘을 재생산하여 각 영역에 활용하고 있다. 하지만 오픈소스 소프트웨어에 대한 다양한 분석들이 이루어진 데 반해, 실제 산업현장에서 딥러닝 오픈소스 소프트웨어를 개발하거나 활용하는데 유용한 연구 결과는 미흡한 실정이다. 따라서 본 연구에서는 딥러닝 프레임워크 사례연구를 통해 해당 프레임워크의 도입 전략을 도출하고자 한다. 기술-조직-환경 프레임워크를 기반으로 기존의 오픈 소스 소프트웨어 도입과 관련된 연구들을 리뷰하고, 이를 바탕으로 두 기업의 성공 사례와 한 기업의 실패 사례를 포함한 총 3 가지 기업의 도입 사례 분석을 통해 딥러닝 프레임워크 도입을 위한 중요한 5가지 성공 요인을 도출하였다: 팀 내 개발자의 지식과 전문성, 하드웨어(GPU) 환경, 데이터 전사 협력 체계, 딥러닝 프레임워크 플랫폼, 딥러닝 프레임워크 도구 서비스. 그리고 도출한 성공 요인을 실현하기 위한 딥러닝 프레임워크의 단계적 도입 전략을 제안하였다: 프로젝트 문제 정의, 딥러닝 방법론이 적합한 기법인지 확인, 딥러닝 프레임워크가 적합한 도구인지 확인, 기업의 딥러닝 프레임워크 사용, 기업의 딥러닝 프레임워크 확산. 본 연구를 통해 각 산업과 사업의 니즈에 따라, 딥러닝 프레임워크를 개발하거나 활용하고자 하는 기업에게 전략적인 시사점을 제공할 수 있을 것이라 기대된다.

• 한국문헌정보학회지
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• 제53권3호
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• pp.101-120
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• 2019

클라우드 형태의 학술연구데이터 인프라에서는 데이터 분석과 융합의 작업환경에 연구자가 직접 개입할 수 있게 된다. 때문에 연구기록 등의 학술연구데이터에 대한 명확한 연구자 인식은 보다 중요하다. 본 연구는 기록관리 분야 연구자들의 인식에 초점을 두고 학술연구데이터의 하나인 연구기록이 갖는 구조적 논리성을 차세대 연구정보 인프라 요건으로 강조한다. 최근 발행된 논문들의 연구프레임 분석을 통하여 연구의 구조적 요건에 대한 저자들의 인식을 진단하고 인식교정이 필요한 취약 부분들을 지적하고 개선 방안을 제시했다.

• Asia pacific journal of information systems
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• 제26권3호
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• pp.339-366
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• 2016

National and local governments around the world have been allowing access to administrative data to increase transparency, motivate civic engagement of citizens, and improve collaboration between the public and the government. This study reviews and classifies existing literature on open government data (OGD). To create a structure to organize the existing studies, the researchers devised a framework based on socio-technical theory and summarized the significance of studies along four major points: (1) readiness, (2) implementation, (3) emerging effects, and (4) actors of open data. Studies in OGD have been growing steadily in the recent years because of the rapid development of adoptable technologies that have enabled easier access to government data. Nonetheless, an examination of existing research not only shows a disparity in research and development of OGD across countries in the Open Government partnership program but also reveals pertinent issues that have arisen in different stages of the OGD initiative. The growing number of studies and expanding body of knowledge show the importance of organizing existing literature. This step is timely and significant to map out the current breadth and depth of OGD research. According to existing research, current open governments fall short in encouraging citizen participation and collaborations among citizens and the government. This study pointed out how studies on OGD actors might be the reason as well as the solution to existing findings. This paper aims to provide a framework for organizing OGD studies, present the status of OGD research, and provide recommendations on current gaps that must be addressed.

• 한국컴퓨터정보학회논문지
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• 제22권6호
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• pp.57-68
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• 2017

The Linked Open Data(LOD) cloud is quickly becoming one of the largest collections of interlinked datasets and the de facto standard for publishing, sharing and connecting pieces of data on the Web. Data publishers from diverse domains publish their data using Resource Description Framework(RDF) data model and provide SPARQL endpoints to enable querying their data, which enables creating a global, distributed and interconnected dataspace on the LOD cloud. Although it is possible to extract structured data as query results by using SPARQL, users have very poor in analysis and visualization of RDF data from SPARQL query results. Therefore, to tackle this issue, based on Formal Concept Analysis, we propose a novel approach for analyzing and visualizing useful information from the LOD cloud. The RDF data analysis and visualization technique proposed in this paper can be utilized in the field of semantic web data mining by extracting and analyzing the information and knowledge inherent in LOD and supporting classification and visualization.

• 대한임베디드공학회논문지
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• 제11권6호
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• pp.325-334
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• 2016

Recently, Open Computing Language (OpenCL) has been proposed to provide a framework that supports heterogeneous computing platforms. By using an OpenCL framework, digital communication systems can support various protocols in a unified computing environment to achieve both high portability and high performance. This article introduces a parallel software decoder of Low Density Parity Check (LDPC) codes for China Multimedia Mobile Broadcasting (CMMB) on a heterogeneous platform. Each step of LDPC decoding has different parallelization characteristics. In this paper, steps suitable for task-level parallelization are executed on the CPU, and steps suitable for data-level parallelization are processed by the GPU. To improve the performance of the proposed OpenCL kernels for LDPC decoding operations, explicit thread scheduling, loop-unrolling, and effective data transfer techniques are applied. The proposed LDPC decoder achieves high performance by using heterogeneous multi-core processors on a unified computing framework.

• 한국정보통신학회논문지
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• 제23권10호
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• pp.1179-1187
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• 2019

오늘날의 기술 환경에서 대다수의 빅 데이터 기반 애플리케이션 및 솔루션은 스트리밍 데이터의 실시간 처리를 기반으로 한다. 빅 데이터 스트림의 실시간 처리 및 분석은 빅 데이터 기반 애플리케이션 및 솔루션 개발에서 중요한 역할을 한다. 특히 해사 분야 데이터 처리 환경에서도 데이터의 폭발적 증대에 따른 대용량 실시간 데이터를 빠르게 처리 및 분석할 수 있는 기술 개발의 필요성이 가속화되고 있다. 따라서 본 논문에서는 다양한 빅 데이터 처리를 위한 오픈소스 기술 중에 적합한 오픈소스로 NiFi, Kafka, Druid의 특징을 분석하여 한국형 e-Navigation 서비스에서 해사 분야 서비스 분석에 필요한 외부 연계 필요 정보들을 상시 최신 정보로 제공할 수 있도록 실시간 데이터 처리를 위한 개방형 데이터 프레임워크 기술 적용의 기초를 마련하고자 한다.

• 대한원격탐사학회지
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• 제6권2호
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• pp.89-113
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• 1990

The purpose of this study is to develop means to apply GIS and remote sensing technology to the analysis of Korean urban open spaces. To achieve this objective, a framework of analysis of urban open spaces was developed, and then the framework was applied for the evaluation of the potential and suitability of open spaces of Ansan City, which is a new town developed to accomodate industries relocation from Seoul, Korea, mainly due to their pollution problems. The software used in this study are IDRISI, a grid-based GIS, and KMIPS, a remote sensing analysis system. Both packages are based on IBM PC/AT computers with Microsoft DOS. Landsat MSS and TM data were used for the land use classification, land use change detection, and analysis of transformed vegetation indices. The size of the geographic data base is 110 rows and 150 columns with the spatial resolution of 100m$\times$100m. The framework of analysis includes both quanititative and qualitative analysis of open spaces. The quantitative analysis includes size and distribution of open spaces, urban develpment of open spaces, and the degree of vegree of vegetation removal of the study area. The qualitative analysis includes evaluative criteria for primary productivity of land, park use potential, major visual resources, and urban environmental control. The findings of this study can be summarized as follows. First, the size of builtup areas increased 18.73km$^2$, while the size of forest land decreased 10.86km$^2$ during last ten years. Agricultural lands maintained its size, but shifted toward outside of the city into forest. Second, the potential of open spaces for park use is limited mainly due to their lack of accessibility and connectivity among open spaces, in spite of ample acreage and good site conditions. Third, major landscape elements and historic sites should be connected to the open space system of the city by new accesses and buffers.