• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.527-530
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• 2000

현재까지 제안된 대부분의 워터마킹 방법들은 전체 프레임 기반이기 때문에 전체영상은 보호할 수 있지만, 공격자가 영상을 구성하는 특정한 객체만을 잘라내어 사용할 경우 객체 그 자체는 보호하기가 어려워 멀티미디어 데이터를 보호하는데 있어서 그 한계가 있다. 따라서 본 논문에서는 영상을 구성하는 특정한 임의의 객체를 추출한 후, 영상의 왜곡을 최소화하기 위해 객체보다 큰 배경영상을 사용, 인간시각 특성을 이용한 웨이브릿 영역에서의 객체기반 워터마킹 방법을 제안한다 제안한 방법은 영상을 구성하는 각각의 객체를 선별하여 워터마크를 삽입함으로서 전체 영상뿐 아니라 각각의 객체를 보호할 수 있어 기존의 방법이 객체공격에 취약한 단점을 보완하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06d
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• pp.132-134
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• 2012

본 논문에서는 오디오 데이터를 분석하여 촉각 피드백을 출력할 수 있는 햅틱 라이브러리를 소개한다. 개발한 라이브러리는 안드로이드 플랫폼에서 동작하며, 어플리케이션에서 발생하는 오디오 신호를 이용하여 촉각 효과를 생성하므로, 기존 어플리케이션의 수정 없이 촉각 효과를 제공할 수 있다. 또한 복합적인 오디오 음원으로부터 사용자가 원하는 특정 주파수 대역을 선별하여 촉각 효과를 적용할 수 있다. 마지막으로 개발한 라이브러리를 레이싱 게임 및 음악감상 어플리케이션에 적용한 사례를 소개한다.

• Proceedings of the KAIS Fall Conference
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• 2008.05a
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• pp.215-217
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• 2008

RFID 시스템은 향후 바코드를 대체하고 우리 생활 전반에 걸쳐 사용될 획기적인 시스템 이지만 태그의 정보가 외부에 노출될 경우 심각한 문제가 발생 할 수 있다. 본 논문에서는 여러 보안 문제중 프라이버시 보호를 위해 RBAC 기반으로 리더의 권한을 배분하여 태그가 데이터를 선별적으로 전송하고 태그가 리더로부터 수신한 난수로부터 매 세션마다 비밀키 및 실시간으로 새로운 해쉬 함수를 생성하는 인증 프로토콜을 제안한다. 제안된 RBAC를 이용한 해쉬 기반 인증 프로토콜은 각종 공격에 대해 안전하며 연산을 최소화하여 다양한 적용성을 제공한다.

• Proceedings of the KIPE Conference
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• 2019.07a
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• pp.439-440
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• 2019

리튬 이온 배터리가 전기 자동차 및 다양한 어플리케이션에 적용됨에 따라 폐배터리의 수요 또한 증가하고 있다. 내부 화학적 상태가 상이한 배터리의 전기적 특성실험을 통해 파라미터를 선정하였으며, 데이터의 분포에 적합한 Fuzzy Logic을 설계하였다. 설계된 Fuzzy Logic을 통한 Cell Grading으로 내부 화학적 특성이 유사한 셀을 선별하였다.

• Journal of the Korea Society of Computer and Information
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• v.18 no.4
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• pp.97-112
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• 2013

The quality of the data is the most basic prerequisite for effective use of data. Problems and the resulting loss due to error data has emerged using case studies and a number of, to a national, quality certification system of the data has been enforced, you must manage to generate data study on the method for selecting the point of view of an organization's data CTQ is a very unsatisfactory state of affairs. Selected CTQ main data is subject to quality control in the organization, to develop criteria for CTQ data side of the business and IT so that it can be managed in a systematic manner, the proposed model, to filter the data accordingly presented in detail how to manage enterprise-wide CTQ data that can be quantified Te. By utilizing SPSS, factor analyzes, for which I used the AHP method for quantification. In particular, we present a framework of management measures along the maturity of the data in the organization due to the enforcement of authentic quality certification system of DB, utilizing the CTQ-DSMM model readily applicable to practice.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.12 no.4
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• pp.345-361
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• 2014

The systematic quality assurance activities on documents of the safety assessment are required for the safety case of the low- and intermediate-level radioactive waste disposal facility. In this paper, quality assurance system focused on the input data including the site characterization, groundwater flow, system design and monitoring are prepared and discussed. Rule for the input data selection is suggested and applied for the safety assessment which is based on the in-situ/experiment observations, final facility design and waste pileup plan, engineered barrier, field monitoring, recent biosphere, and radionuclide inventory. The reduction of data uncertainty will be expected to contribute to the safety of disposal facility further.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.241-248
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• 2014

It has been expanded the bandwidth of data usages due to the rapid developments of information technology and infra hardware and then it was proposed to new paradigm of Big Data era. It has a trend to increase a Big Data technology and its performance gradually, thus enterprises have realized the importance of Data and the movement to take advantage of Big Data becomes active. This study has been performed to verify the importance through select the factors in order to active adoption of Big Data technology and utilization when enterprises use Big Data. It was selected that Big Data characteristic factors are the natures of predictability, manageability, affordability, competitiveness, creativity, responsiveness and supportability on the study. It is verified and showed that manageability were influenced to introduce Big Data in order, at the result of survey and statistics for enterprise practitioners who have big data experience.

• Journal of Korean Elementary Science Education
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• v.43 no.1
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• pp.81-94
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• 2024

This study explores and conducts an in-depth comparison of the epistemic characteristics in different data types utilized in the science inquiries of preservice teachers regarding noise as a risk in everyday life. Focusing on primary and secondary data in the context of science inquiries about noise, we examined how these data types differ in science inquires in terms of inquiry design, data collection, and analyses. The findings reveal that sensor-based primary data enable direct measurement and observation of key phenomena. Conversely, secondary data rely on predetermined measurement methods within a public data system. These differences require different epistemic considerations during the inquiry process. Based on these findings, we discuss the educational implications concerning teaching approaches for science inquiries, teacher education for inquiry teaching, and the development of risk response competencies in preparation for the VUCA (Volatility, Uncertainty, Complexity, and Ambiguity) era.

• Journal of the Korea Society of Computer and Information
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• v.24 no.12
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• pp.17-24
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• 2019

The biggest problem in the AI field, which has become a hot topic in recent years, is how to deal with the lack of training data. Since manual data construction takes a lot of time and efforts, it is non-trivial for an individual to easily build the necessary data. On the other hand, automatic data construction needs to handle data quality issue. In this paper, we introduce a method to automatically extract the data required to develop Korean speech command recognizer from the web and to automatically select the data that can be used for training data. In particular, we propose a modified ResNet model that shows modest performance for the automatically constructed Korean speech command data. We conducted an experiment to show the applicability of the command set of the health and daily life domain. In a series of experiments using only automatically constructed data, the accuracy of the health domain was 89.5% in ResNet15 and 82% in ResNet8 in the daily lives domain, respectively.

• The KIPS Transactions:PartD
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• v.13D no.6 s.109
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• pp.755-764
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• 2006

In recent, data streams are generated in various application fields such as a ubiquitous computing and a sensor network, and various algorithms are actively proposed for processing data streams efficiently. They mainly focus on the restriction of their memory usage and minimization of their processing time per data element. However, in the algorithms, if data elements of a data stream are generated in a rapid rate for a time unit, some of the data elements cannot be processed in real time. Therefore, an efficient load shedding technique is required to process data streams effcientlv. For this purpose, a load shedding technique over a data stream is proposed in this paper, which is based on the predicting technique of the frequency of data element considering its current frequency. In the proposed technique, considering the change of the data stream, its threshold for tuple alive is controlled adaptively. It can help to prevent unnecessary load shedding.