본 연구에서는 한국정보올림피아드 경시부문 초등부 지역예선을 준비하고 컴퓨터 원리를 학습할 수 있는 교재를 Polya의 문제해결 단계의 원리를 적용하여 개발하였다. 교재의 내용은 학생들이 컴퓨터 원리를 학습할 수 있도록 프로그래밍의 기본이 되는 이산수학과 자료구조로 선정하였다. 개발된 교재는 J대학교의 정보영재교육원에 재학 중인 초등학생을 대상으로 투입한 뒤 기출문제를 재구성한 검사도구를 활용하여 정보올림피아드 문제해결 능력 신장에 도움이 되었음을 밝혔다. 앞으로 정보올림피아드 지도교사를 위한 지도서의 개발 및 연수 등 컴퓨터 교육을 정상화 할 수 있는 현실적인 여건이 구비되어야 할 것이다. In this study, the teaching material has been developed based on Polya's Problem Solving Techniques for preparing Korea Information Olympiad qualification and studying principle of computer. the basis of discrete mathematics and data structures were selected as the content of textbooks for students to learn computer programming principles. After the developed textbooks were applied to elementary school students of Science Gifted Education Center of J University, the result of study proves that textbook helps improve problem-solving ability using the testing tool restructured sample questions from previous test. We need guidebook and training course for teachers and realistic conditions for teaching the principles of computer.
XML has been known as a document standard in representation and exchange of data on the Internet, and is also used as a standard language for the search and reuse of scattered documents on the Internet. The issues related to XML are how to model data on effective and efficient management of semi-structured data and how to actually store the modeled data when implementing a XML contents management system. Previous researches on XML have limitations in (1) reproduction of XML documents from the stored data, (2) retrieval of XML sub-graph from search, (3) supporting only top-down search, not full-search, and (4) dependency of data structure on XML documents. The purpose of this paper is to present a hybrid XML data model architecture for the storage and search of XML document data. By representing both data and structure views of XML documents, this new XML data model technique overcomes the limitations of previous researches on data model for XML documents as well as the existing database systems such as relational and object-oriented data model. Kim,Choi,Hong, Kim,Chun Hybrid XML Data Model Architecture for Efficient Document Management
【The purpose of this paper is to explore the strategy of future Korean medicine(KM) clinical research through the study on the current situation and issues for KM clinical research worldwide. In this study, the papers published in English through Pubmed were investigated mainly. And we analyzed the methodological issues from the clinical research reports in the KM fields. As a result of examining the current situation of the RCTs(Randomized Controlled Trials) studies in KM, the sample size for most studies was small and the overall methodological quality appeared to be low. And there was a discussion about whether or not to apply RCTs method to the KM clinical research. The majority of studies have argued the use of RCTs method for KM clinical research. In addition, we could find some problems through the analysis of KM clinical studies. First, the majority of RCTs in KM were of low quality. Second, RCTs method was applied to the KM clinical studies according to the Western medicine methods only. Third, the actual KM diagnosis was not used in the KM studies and inadequate outcomes measurement methods were utilized without considering the characteristics of KM practice. The methodological issues in the KM clinical research were caused by the conflict between the characteristics of KM practice and clinical research method based on the western medicine.】
Due to end of Dennard Scaling, the latest chip architectures are multi-core, with each core customized for specific domains e.g. computer vision, deep learning, graphics, signal processing, image processing etc. However, software has not evolved to utilize such heterogeneous (or asymmetrical) multi-core architectures to improve performance and latency. The key challenge of multi-core programming is efficient implementation within the context of an easy to use open software framework with high utilization. This paper presents an efficient software architecture to parallelize the execution of multiple processing cores using standard Khronos OpenVX framework. The paper proposes multiple novelties, namely, extension to the standard Khronos OpenVX, multi-CPU buffer exchange, non-blocking processing stall, early buffer release and late buffer submit. The proposed implementation is done on TI Jacinto 7 platform enabling multi-core utilization of 99% (less than 1% overhead) maintaining real time performance for surround view analytics application for automotive market.
To protect customers' sensitive information, many mobile financial applications include steps to probe the runtime environment and abort their execution if the environment is deemed to have been tampered with. This paper investigates the security of such self-defense mechanisms used in 76 popular financial Android apps in the Republic of Korea. Our investigation found that existing tools fail to analyze these Android apps effectively because of their highly obfuscated code and complex, non-traditional control flows. We overcome this challenge by extracting a call graph with a self-defense mechanism, from a detailed runtime trace record of a target app's execution. To generate the call graph, we identify the causality between the system APIs (Android APIs and system calls) used to check device rooting and app integrity, and those used to stop an app's execution. Our analysis of 76 apps shows that we can pinpoint methods to bypass a self-defense mechanism using a causality graph in most cases. We successfully bypassed self-defense mechanisms in 67 out of 73 apps that check device rooting and 39 out of 44 apps that check app integrity. While analyzing the self-defense mechanisms, we found that many apps rely on third-party security libraries for their self-defense mechanisms. Thus we present in-depth studies of the top five security libraries. Our results demonstrate the necessity of a platform-level solution for integrity checks.
Malicious activities in mobile applications may affect the mobile usages and even leave security concerns in the mobile applications. For example, they may drain the batteries, use up CPU or memories, increase bandwidth utilization, and even steal our information. In this paper, we analyze the Sherlock data to explore the patterns in mobile usage by different types of the mobile apps and their benign or malicious status. These initial findings potentially are helpful to assist malware detections and usage warning.
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