• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.716-718
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• 2004

The false alarm data in intrusion detection systems are divided into false positive and false negative. The false positive makes bad effects on the performance of intrusion detection system. And the false negative makes bad effects on the efficiency of intrusion detection system. Recently, the most of works have been studied the data mining technique for analysis of alert data. However, the false alarm data not only increase data volume but also change patterns of alert data along the time line. Therefore, we need a tool that can analyze patterns that change characteristics when we look for new patterns. In this paper, we focus on the false positives and present a framework for analysis of false alarm pattern from the alert data. In this work, we also apply incremental data mining techniques to analyze patterns of false alarms among alert data that are incremental over the time. Finally, we achieved flexibility by using dynamic support threshold, because the volume of alert data as well as included false alarms increases irregular.

• Archives of Plastic Surgery
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• v.48 no.3
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• pp.295-304
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• 2021

Clinical photography is an essential component of patient care in plastic surgery. The use of unsecured smartphone cameras, digital cameras, social media, instant messaging, and commercially available cloud-based storage devices threatens patients' data safety. This paper Identifies potential risks of clinical photography and heightens awareness of safe clinical photography. Specifically, we evaluated existing risk-mitigation strategies globally, comparing them to industry standards in similar settings, and formulated a framework for developing a risk-mitigation plan for avoiding data breaches by identifying the safest methods of picture taking, transfer to storage, retrieval, and use, both within and outside the organization. Since threats evolve constantly, the framework must evolve too. Based on a literature search of both PubMed and the web (via Google) with key phrases and child terms (for PubMed), the risks and consequences of data breaches in individual processes in clinical photography are identified. Current clinical-photography practices are described. Lastly, we evaluate current risk mitigation strategies for clinical photography by examining guidelines from professional organizations, governmental agencies, and non-healthcare industries. Combining lessons learned from the steps above into a comprehensive framework that could contribute to national/international guidelines on safe clinical photography, we provide recommendations for best practice guidelines. It is imperative that best practice guidelines for the simple, safe, and secure capture, transfer, storage, and retrieval of clinical photographs be co-developed through cooperative efforts between providers, hospital administrators, clinical informaticians, IT governance structures, and national professional organizations. This would significantly safeguard patient data security and provide the privacy that patients deserve and expect.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.1
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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.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.590-591
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• 2007

Legacy utilities can not adapt to changing business conditions without having complete control of operational systems and a flexible infrastructure that supports change. What is needed is a framework that enables data to be coalesced and transformed in to usable knowledge. This framework should be robust enough to that as new situations arise, information can be shared in ways not previously anticipated. Utility Integration Bus (UIB) provides an integration framework which solves many of these issues while controlling complexity. This paper provides UIB's overview and course.

• Journal of the Korea Society of Computer and Information
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• v.23 no.11
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• pp.103-109
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• 2018

This paper presents an idea and framework to automate a full cycle business process management and re-engineering by integrating traditional business process management systems, process mining, data mining, machine learning, and simulation. We build our framework on the cloud-based platform such that various data sources can be incorporated. We design our systems to be extensible so that not only beneficial for practitioners of BPM, but also for researchers. Our framework can be used as a test bed for researchers without the complication of system integration. The automation of redesigning phase and selecting a baseline process model for deployment are the two main contributions of this study. In the redesigning phase, we deal with both the analysis of the existing process model and what-if analysis on how to improve the process at the same time, Additionally, improving a business process can be applied in a case by case basis that needs a lot of trial and error and huge data. In selecting the baseline process model, we need to compare many probable routes of business execution and calculate the most efficient one in respect to production cost and execution time. We also discuss the challenges and limitation of the framework, including the systems adoptability, technical difficulties and human factors.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.259-265
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• 2020

The study aims to define the career competency of HRD practitioners based on an intelligent career framework. This intelligent career framework has been described as having been achieved by the accumulation of career capital through the three ways of knowing, including knowing why, knowing how, and knowing with whom. The data were collected from the interviews with 15 HRD practitioners. Semi-structured interviews were used to collect data from the HRD practitioners. For the orientation about the interview, the researcher explained the importance of gathering data about the personal experiences of the respondents on their work and career. After that explanation, the researcher asked several questions based on the pre-structured interview guide. The data collected were qualitatively analyzed on the basis of the intelligent career framework. Based on the analysis of the interviews, the subcategories of each way of knowing competency were identified. For the knowing why, identity, credibility, and career clarity were identified. The subcategories of knowing how are remaining updates, hard skills, and soft skills, while the subcategories of knowing with whom are personal networking and professional networking. The interdependency among the three career competencies was found. The findings provide theoretical implications of applying an intelligent career framework.

• Journal of Soil and Groundwater Environment
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• v.20 no.7
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• pp.112-120
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• 2015

Statistical trend analysis using the data from the National Groundwater Quality Monitoring Network (NGQMN) of Korea was conducted to establish a new groundwater quality management framework. Sen’s test, a non-parametric statistical method for trend analysis, was used to determine the linear trend of the groundwater quality data. The analysis was conducted at different confidence levels (i.e., at 70, 80, 90, 95, and 99% confidence levels) for three of groundwater quality parameters, i.e., nitrate-nitrogen, chloride, and pH, which have sufficient time series of the NGQMN data between 2007 and 2013. The results showed that different trends can be determined for different depths even for the same monitoring site and the numbers of wells having significant trends vary with different confidence levels. The wells with increasing or decreasing trends were far less than the wells with no trend. Chloride had more wells with increasing trend than other parameters. On the other hand, nitrate-nitrogen had the most wells with increasing trend and concentration exceeding 75% of the threshold values (TVs). Based on the methodology used for this study, we suggest including groundwater TVs and trend analysis to evaluate groundwater quality and to establish an advanced groundwater quality management framework.

• International Journal of Advanced Culture Technology
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• v.4 no.1
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• pp.28-30
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• 2016

Due to the high increment in usage and built-in advanced technology of smartphones, human activity recognition relying on smartphone sensor data has become a focused research area. In order to reduce noise of collected data, most of previous studies assume that smartphones are fixed at certain positions. This strategy is impractical for real life applications. To overcome this issue, we here investigate a framework that allows detecting the status of a traveller as idle or moving regardless the position and the direction of smartphones. The application of our work is to estimate the total energy consumption of a traveller during a trip. A number of experiments have been carried out to show the effectiveness of our framework when travellers are not only walking but also using primitive vehicles like motorbikes.

• The Journal of Korea Robotics Society
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• v.14 no.4
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• pp.340-347
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• 2019

Due to advances in machine intelligence and increased demands for autonomous machines, the complexity of the underlying software platform is increasing at a rapid pace, overwhelming the developers with implementation details. We attempt to ease the burden that falls onto the developers by creating a graphical programming framework we named Splash. Splash is designed to provide an effective programming abstraction for autonomous machines that require stream processing. It also enables programmers to specify genuine, end-to-end timing constraints, which the Splash framework automatically monitors for violation. By utilizing the timing constraints, Splash provides three key language semantics: timing semantics, in-order delivery semantics, and rate-controlled data-driven stream processing semantics. These three semantics together collectively serve as a conceptual tool that can hide low-level details from programmers, allowing developers to focus on the main logic of their applications. In this paper, we introduce the three-language semantics in detail and explain their function in association with Splash's language constructs. Furthermore, we present the internal workings of the Splash programming framework and validate its effectiveness via a lane keeping assist system.

• Journal of Engineering Education Research
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• v.21 no.6
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• pp.90-98
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• 2018

This paper proposes a framework of engineering education for product development processes based on product data management (PDM) software and 3D printing. The PDM software supports the product development process-oriented educational coursework, collaborative team projects and project-based learning environment. The 3D printing supports the prototyping step in the product development process and helps participants consider physical realization of their designs during the product design and development phases. The framework was implemented in an introductory course for engineering students to product design and development, and author found that it is important to support rich communication among participants including lecturers, teaching assistants and students to enhance the quality of education and to overcome the burden of learning various computer-aided tools and 3D printing techniques needed for the framework.