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( Myoungjin Kim ),( Seungho Han ),( Yun Cui ),( Hanku Lee ),( Changsung Jeong ) 한국인터넷정보학회 2012 KSII Transactions on Internet and Information Syst Vol.6 No.11
Previously, we described a social media cloud computing service environment (SMCCSE). This SMCCSE supports the development of social networking services (SNSs) that include audio, image, and video formats. A social media cloud computing PaaS platform, a core component in a SMCCSE, processes large amounts of social media in a parallel and distributed manner for supporting a reliable SNS. Here, we propose a Hadoop-based multimedia system for image and video transcoding processing, necessary functions of our PaaS platform. Our system consists of two modules, including an image transcoding module and a video transcoding module. We also design and implement the system by using a MapReduce framework running on a Hadoop Distributed File System (HDFS) and the media processing libraries Xuggler and JAI. In this way, our system exponentially reduces the encoding time for transcoding large amounts of image and video files into specific formats depending on user-requested options (such as resolution, bit rate, and frame rate). In order to evaluate system performance, we measure the total image and video transcoding time for image and video data sets, respectively, under various experimental conditions. In addition, we compare the video transcoding performance of our cloud-based approach with that of the traditional frame-level parallel processing-based approach. Based on experiments performed on a 28-node cluster, the proposed Hadoop-based multimedia transcoding system delivers excellent speed and quality.
An Efficient Design and Implementation of an MdbULPS in a Cloud-Computing Environment
( Myoungjin Kim ),( Yun Cui ),( Hanku Lee ) 한국인터넷정보학회 2015 KSII Transactions on Internet and Information Syst Vol.9 No.8
Flexibly expanding the storage capacity required to process a large amount of rapidly increasing unstructured log data is difficult in a conventional computing environment. In addition, implementing a log processing system providing features that categorize and analyze unstructured log data is extremely difficult. To overcome such limitations, we propose and design a MongoDB-based unstructured log processing system (MdbULPS) for collecting, categorizing, and analyzing log data generated from banks. The proposed system includes a Hadoop-based analysis module for reliable parallel-distributed processing of massive log data. Furthermore, because the Hadoop distributed file system (HDFS) stores data by generating replicas of collected log data in block units, the proposed system offers automatic system recovery against system failures and data loss. Finally, by establishing a distributed database using the NoSQL-based MongoDB, the proposed system provides methods of effectively processing unstructured log data. To evaluate the proposed system, we conducted three different performance tests on a local test bed including twelve nodes: comparing our system with a MySQL-based approach, comparing it with an Hbase-based approach, and changing the chunk size option. From the experiments, we found that our system showed better performance in processing unstructured log data.
Myoungjin Kim 서울대학교 언어교육원 2019 語學硏究 Vol.55 No.1
The present research intends to compare the orthographic and phonological vocabulary sizes of Korean EFL students in middle school and to address the relationship between the two different types of vocabulary size tests and L2 reading and listening comprehension. The participants were found to have greater orthographic vocabulary knowledge than phonological knowledge. Specifically, their vocabulary knowledge, regardless of its modality, drastically decreased in frequency level from 1,000 to 2,000 and from 3,000 to 4,000. Although both types of vocabulary knowledge exhibit a correlation with each other, as well as with reading and listening comprehension, orthographic vocabulary size was shown to be the most predictive in terms of the variance found in both reading and listening. The findings of the study contribute to existing research on L2 vocabulary acquisition by providing further evidence of the non-parallel development of phonological and orthographic vocabulary knowledge by EFL students, and by suggesting the significant predictive value that orthographic vocabulary knowledge has on the performance of students in reading and listening comprehension tests employed in Korea.
MyoungJin Kim,Sung-Bae Roger Park 한국코칭능력개발원 2017 International Journal of Coaching Science Vol.11 No.2
Analysis of the commonly used statistical techniques and statistical software packages can improve statistics education. The purpose of this study was to examine the use of statistical techniques in recent sport management research studies published in the Journal of Sport Management (JSM). To do so, the authors reviewed the 222 published articles in JSM between 2006 and 2015. The results indicated that descriptive statistics were the most frequently used in sport management research articles accounting for 57.61% of all statistical techniques used and that SPSS was the most frequently used statistical software. Our findings offer important considerations for statistics education in both academia and practice.
AspectHPJ: 자바기반의 관심 지향적 병렬 프로그래밍 모델
김명진(Myoungjin Kim),이한구(Hanku Lee),이동근(Dongkeun Lee),이원사(Wonsa Lee) 한국정보과학회 2008 한국정보과학회 학술발표논문집 Vol.35 No.1
최근의 융합학문의 발전으로 생물, 물리, 화학, 천문, 우주학, 지구과학 분야에서도 병렬 프로그램을 이용한 대용량 데이터를 처리하는 빈도가 높아졌다. 그러나 병렬 프로그래밍은 병렬환경의 전문성을 가지고 있지 않는 다른 학문의 전문가가 사용하기는 어려운 것이 현실이다. 이에 본 논문에서는 병렬환경의 비전문가도 사용하기 용이한 관심 지향적 병렬 프로그래밍 모델과 자바 기반으로 구현된 AspectHPJ 시스템을 제안한다. 본 시스템의 첫 번째 특징은 일반 사용자가 Sequential 코드로 프로그램을 작성하고 병렬화 하고자 하는 코드영역에 병렬마크를 사용하여 병렬코드로 전환하는 특징을 가지고 있다. 두 번째는 병렬환경 요소(프로세서 개수, 분산배열 속성)를 AOP 개념의 관심(aspect)으로 추출하여 사용자가 보다 용이하게 병렬환경 요소를 설정할 수 있게 해주는데 있다.