• Journal of Computing Science and Engineering
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• 제8권4호
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• pp.181-186
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• 2014

Web data mining aims at discovering useful knowledge from various Web resources. There is a growing trend among companies, organizations, and individuals alike of gathering information through Web data mining to utilize that information in their best interest. In science, cloud computing is a synonym for distributed computing over a network; cloud computing relies on the sharing of resources to achieve coherence and economies of scale, similar to a utility over a network, and means the ability to run a program or application on many connected computers at the same time. In this paper, we propose a new system framework based on the Hadoop platform to realize the collection of useful information of Web resources. The system framework is based on the Map/Reduce programming model of cloud computing. We propose a new data mining algorithm to be used in this system framework. Finally, we prove the feasibility of this approach by simulation experiment.

• 한국지구과학회지
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• 제39권4호
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• pp.388-400
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• 2018

The purpose of this study was to explore the nine components of computational thinking (CT) practices and their operational definitions from the view of science education and to develop a CT practice framework that is going to be used as a planning and assessing tool for CT practice, as it is required for students to equip with in order to become creative problem solvers in $21^{st}$ century. We employed this framework into the earlier developed STEAM programs to see how it was valid and reliable. We first reviewed theoretical articles about CT from computer science and technology education field. We then proposed 9 components of CT as defined in technology education but modified operational definitions in each component from the perspective of science education. This preliminary CTPF (computational thinking practice framework) from the viewpoint of science education consisting of 9 components including data collection, data analysis, data representation, decomposing, abstraction, algorithm and procedures, automation, simulation, and parallelization. We discussed each component with operational definition to check if those components were useful in and applicable for science programs. We employed this CTPF into two different topics of STEAM programs to see if those components were observable with operational definitions. The profile of CT components within the selected STEAM programs for this study showed one sequential spectrum covering from data collection to simulation as the grade level went higher. The first three data related CT components were dominating at elementary level, all components of CT except parallelization were found at middle school level, and finally more frequencies in every component of CT except parallelization were also found at high school level than middle school level. On the basis of the result of CT usage in STEAM programs, we included 'generalization' in CTPF of science education instead of 'parallelization' which was not found. The implication about teacher education was made based on the CTPF in terms of science education.

• 간호행정학회지
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• 제18권2호
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• pp.222-233
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• 2012

Purpose: This study was conducted to develop an evaluation framework for QI activity in medical institutions and to analyze QI activity cases by applying the developed evaluation framework. Method: A four-phase process was employed to develop the evaluation framework, and a descriptive survey was used for the QI case study. Data were collected in April, 2010 by examining 157 QI activity cases presented at conferences and published in Journal of Korean Society of Quality Assurance in Health Care over the past three years. Developed QI activity evaluation instruments were used for data collection. Data were analyzed using the SPSS 18.0 for Windows program. Result: A QI Activity Evaluation Framework was developed. This framework consisted of 45 items. The department with the highest level of QI participation was the nursing department. The most frequent QI activity theme was patient safety. QI activity levels in Korean medical institutions are relatively equalized without significant differences according to institution characteristics. Conclusions: From the quality aspect of QI activity, more systematic and scientific approaches are required to upgrade QI activity. This study could provide methodological guidelines for QI activity and be useful in setting goals and directions for QI activity in medical institutions in Korea.

• 정보처리학회논문지D
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• 제17D권3호
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• pp.193-202
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• 2010

유비쿼터스 컴퓨팅 환경을 실현하기 위한 핵심 기술로 자동화된 개체 식별, 분산 컴퓨팅 기술 등의 연구가 다양한 분야에서 이루어 지고 있다. 라디오 주파수를 이용해서 개체를 식별하는 RFID 기술은 EPCglobal에서 표준을 제시하고 있고 EPC Network를 기반으로 구축된 인프라를 바탕으로 응용 시스템을 개발하고자 하는 경우, RFID 미들웨어로부터 대규모의 EPC정보를 처리해야 하고, EPC를 기반으로 EPC와 관련된 고유 정보와 이력 정보를 수집해야 한다. 또한 정보획득 및 가공에 관한 인과관계 처리가 분명히 이루어져야 하고, 비즈니스 룰에 따른 이벤트의 발생 조건에 관한 처리를 고려하여야 한다. 본 논문에서는 EPC Network 기반에서 응용 시스템 개발을 지원하기 위해 비즈니스 서비스를 제공하는 미들웨어 플랫폼을 제시하고 이에 관한 효용성을 검증한다. 비즈니스 서비스란 추가적인 정보 획득이나 가공 과정 없이 응용 시스템에서 바로 이용이 가능한 이벤트를 전달하는 서비스를 의미한다. 미들웨어 플랫폼에서는 정보 획득, 정보 가공 과정을 지원하며, 또한 비즈니스 룰 처리를 지원한다. 미들웨어 플랫폼은 비즈니스 서비스를 기반으로 응용 시스템의 빠른 개발을 가능하게 하고, 유지보수를 용이하게 한다.

• Journal of Information Technology Applications and Management
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• 제26권5호
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• pp.13-25
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• 2019

Recently, as evaluation of information security (IS) management become more diverse and complicated, the contents and procedure of the evidence to prepare for actual assessment are rapidly increasing. As a result, the actual assessment is a burden for both evaluation agencies and institutions receiving assessments. However, most of them reflect the evaluation system used by foreign government agencies, standard organizations, and commercial companies. It is necessary to consider the evaluation system suitable for the domestic environment instead of reflecting the overseas evaluation system as it is. The purpose of this study is as follows. First, we will present the problems of the existing information security assessment system and the improvement direction of the information security assessment system through analysis of existing information security assessment system. Second, it analyzes the technical guidance for information security testing and assessment and the evaluation of information security management in the Special Publication 800-115 'Technical Guide to Information Security Testing and Assessment' of the National Institute of Standards and Technology (NIST). Third, we will build a framework to implement the evidence collection system and present a system implementation method for the '6. Information System Security' of 'information security management actual condition evaluation index'. The implications of the framework development through this study are as follows. It can be expected that the security status of the enterprises will be improved by constructing the evidence collection system that can collect the collected evidence from the existing situation assessment. In addition, it is possible to systematically assess the actual status of information security through the establishment of the evidence collection system and to improve the efficiency of the evaluation. Therefore, the management system for evaluating the actual situation can reduce the work burden and improve the efficiency of evaluation.

• International Journal of Internet, Broadcasting and Communication
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• 제8권1호
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• pp.73-82
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• 2016

The computational thinking refers to the ability to solve the complex and a variety of problems by utilizing a computer in core of the software education. It create a model through data collection and analysis and realize that the computer can understand to solve problems. Recently, the educational application of 3D printer appears in importance, which is one method to improve the computing thinking. In this paper, we propose the data analysis framework to stretch the computing thinking of learner that can incorporate 3D printing technology to the current elementary school curriculum and apply in a case study.

• Journal of Animal Science and Technology
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• 제66권1호
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• pp.167-177
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• 2024

Iris segmentation is an initial step for identifying the biometrics of animals when establishing a traceability system for livestock. In this study, we propose a deep learning framework for pixel-wise segmentation of bovine iris with a minimized use of annotation labels utilizing the BovineAAEyes80 public dataset. The proposed image segmentation framework encompasses data collection, data preparation, data augmentation selection, training of 15 deep neural network (DNN) models with varying encoder backbones and segmentation decoder DNNs, and evaluation of the models using multiple metrics and graphical segmentation results. This framework aims to provide comprehensive and in-depth information on each model's training and testing outcomes to optimize bovine iris segmentation performance. In the experiment, U-Net with a VGG16 backbone was identified as the optimal combination of encoder and decoder models for the dataset, achieving an accuracy and dice coefficient score of 99.50% and 98.35%, respectively. Notably, the selected model accurately segmented even corrupted images without proper annotation data. This study contributes to the advancement of iris segmentation and the establishment of a reliable DNN training framework.

• 한국멀티미디어학회논문지
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• 제21권11호
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• pp.1353-1361
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• 2018

With the availability of real-time educational data collection and analysis techniques, the education paradigm is shifting from educator-centric to data-driven lectures. However, most offline and online education frameworks collect students' feedback from question-answering data that can summarize their understanding but requires instructor's attention when students need additional help during lectures. This paper proposes a content restructure recommendation framework based on collected student feedback. We list the types of student feedback and implement a web-based framework that collects both implicit and explicit feedback for content restructuring. With a case study of four-week lectures with 50 students, we analyze the pattern of student feedback and quantitatively validate the effect of the proposed content restructuring measured by the level of student engagement.

• 반도체디스플레이기술학회지
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• 제20권2호
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• pp.121-125
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• 2021

Cloud service has the characteristic that it must be always available and that it must be able to respond immediately to user requests. This study suggests a method for constructing a proactive and autonomous quality and performance management system to meet these characteristics of cloud services. To this end, we identify quantitative measurement factors for cloud service quality and performance management, define a structure for applying a time series framework to cloud service application quality and performance management for proactive management, and then use big data and artificial intelligence for autonomous management. The flow of data processing and the configuration and flow of big data and artificial intelligence platforms were defined to combine intelligent technologies. In addition, the effectiveness was confirmed by applying it to the cloud service quality and performance management system through a case study. Using the methodology presented in this study, it is possible to improve the service management system that has been managed artificially and retrospectively through various convergence. However, since it requires the collection, processing, and processing of various types of data, it also has limitations in that data standardization must be prioritized in each technology and industry.

• 한국공간정보시스템학회 논문지
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• 제11권2호
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• pp.45-53
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• 2009

The fast progress on multimedia data acquisition technologies has enabled collecting vast amount of videos in real time. Although the amount of information gathered from these videos could be high in terms of quantity and quality, the use of the collected data is very limited typically by human-centric monitoring systems. In this paper, we propose a framework for analyzing long traffic video using series of content-based analyses tools. Our framework suggests a method to integrate theses analyses tools to extract highly informative features specific to a traffic video analysis. Our analytical framework provides (1) re-sampling tools for efficient and precise analysis, (2) foreground extraction methods for unbiased traffic flow analysis, (3) frame property analyses tools using variety of frame characteristics including brightness, entropy, Harris corners, and variance of traffic flow, and (4) a visualization tool that summarizes the entire video sequence and automatically highlight a collection of frames based on some metrics defined by semi-automated or fully automated techniques. Based on the proposed framework, we developed an automated traffic flow analysis system, and in our experiments, we show results from two example traffic videos taken from different monitoring angles.