• The KIPS Transactions:PartA
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• v.19A no.4
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• pp.187-194
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• 2012

This paper proposes a string analysis based system for classifying Android Apps that may access so called harmful sites, and shows an experiment result for real Android apps on the market. The system first transforms Android App binary codes into Java byte codes, it performs string analysis to compute a set of strings at all program points, and it classifies the Android App as bad ones if the computed set contains URLs that are classified because the sites provide inappropriate contents. In the proposed approach, the system performs such a classification in the stage of distribution before installing and executing the Apps. Furthermore, the system is suitable for the automatic management of Android Apps in the market. The proposed system can be combined with the existing methods using DNS servers or monitoring modules to identify harmful Android apps better in different stages.

• Proceedings of the Korea Information Processing Society Conference
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• 2001.04a
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• pp.39-42
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• 2001

XML 데이터 검색 질의처리를 위해서 개개의 데이터베이스 시스템은 여러 형태로 대안을 제시하고 있다.. 그런데 데이터베이스관리 시스템별로 XML 질의처리방식과 함수처리 방식이 달라서 다형 구조의 데이터를 통합하여 검색하는데 어려움이 있으며 여기에 관계형 데이터베이스시스템과 XML 스키마 결합의 불일치 문제점도 해결 과제로 남아 있다. 본 논문에서는 이런 문제점을 해결하는 방안으로 XML 데이터 검색 질의처리 시스템을 제안한다. 또한 다형적 구조의 환경에서 XML 데이터 시스템와 구조적인 데이터 시스템의 연계방안과 검색질의 시스템에 관해서도 논의한다.

• Journal of Bio-Environment Control
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• v.22 no.4
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• pp.328-334
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• 2013

A greenhouse heating system to improve heat pump performance using inside and outside air of greenhouse as a heat source selectively and cut $CO_2$ enrichment costs by delay of greenhouse ventilation was developed. In this system, thermal storage modes divided into inside circulation mode using surplus solar energy and outside circulation mode using outside air heat. The thermal storage modes were designed to be switched mutually according to inside greenhouse temperature and six temperature values were input to control the heat pump operating, thermal storage mode switching and greenhouse heating automatically. Operating characteristics of this system were tested in a plastic greenhouse of non-ventilation condition. The results of test showed that the inside circulation mode began at about 11:00 and lasted for about 210 minutes and inside greenhouse temperature was maintained between $20{\sim}28^{\circ}C$ in spite of non-ventilation. System heating COP of the inside circulation mode in the daytime was 3.35, which was 36% and 25% higher than that of the outside circulation modes in the nighttime and daytime respectively.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.453-458
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• 2024

Due to global issues such as climate crisis and rising energy costs, there is an increasing focus on energy conservation and management. In the case of South Korea, approximately 53.5% of the total energy consumption comes from industrial complexes. In order to address this, we aimed to improve issues through the 'Shared Network Utility Plant' among companies using similar energy utilities to find energy-saving points. For effective energy conservation, various techniques are utilized, and stable data supply is crucial for the reliable operation of factories. Many anomaly detection and alert systems for checking the stability of data supply were dependent on Energy Management Systems (EMS), which had limitations. The construction of an EMS involves large-scale systems, making it difficult to implement in small factories with spatial and energy constraints. In this paper, we aim to overcome these challenges by constructing a data collection system and anomaly detection alert system on embedded devices that consume minimal space and power. We explore the possibilities of utilizing anomaly detection alert systems in typical institutions for data collection and study the construction process.

• Korean Journal of Construction Engineering and Management
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• v.16 no.4
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• pp.70-79
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• 2015

With the rise of the interest in a renewable system, the importance of the Life Cycle Cost Analysis(LCCA), an economic evaluation tool, has been increasing. However, there is an inevitable gap between a real cost and an estimation from LCCA because of the uncertainty of the external environment in real world. As the input variables in an analysis, such as a real discount rate and an energy cost, ares subject to change as time goes by, strategic decision on the current operating system is made depending on the real cost. Current economic evaluation approaches have treated only the fluctuation of input variables without consideration of the flexibility in operation, which has consequently led to the impairment on the reliability of LCCA. Therefore, new approach needs to be proposed to consider both the uncertainty of input variables and operational flexibility. To address this issue, the application of the Real Option to LCCA is presented in this study. Through a case analysis of LCCA of a solar heating system, the limits and current status of LCCA are identified. As a result, quantitative presentation of strategic decisions has been added in the new approach to implement the traditional approach.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.19-27
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• 2022

In this study, we propose a language and platform to describe and manage the MLOps(Machine Learning Operations) workflow for time series data anomaly detection. Time series data is collected in many fields, such as IoT sensors, system performance indicators, and user access. In addition, it is used in many applications such as system monitoring and anomaly detection. In order to perform prediction and anomaly detection of time series data, the MLOps platform that can quickly and flexibly apply the analyzed model to the production environment is required. Thus, we developed Python-based AI/ML Modeling Language (AMML) to easily configure and execute MLOps workflows. Python is widely used in data analysis. The proposed MLOps platform can extract and preprocess time series data from various data sources (R-DB, NoSql DB, Log File, etc.) using AMML and predict it through a deep learning model. To verify the applicability of AMML, the workflow for generating a transformer oil temperature prediction deep learning model was configured with AMML and it was confirmed that the training was performed normally.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05b
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• pp.891-894
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• 2003

이동 객체의 현재 위치를 갱신하고, 이를 탐색하는 기법은 이동 객체의 수가 많아 이동이 자주 발생할 때 많은 시간과 비용이 소요된다. 본 논문은 노드의 계층적인 위치 관리 구조상에서 갱신 시간은 다소 증가 하나 탐색 시간은 감소되어 효율적으로 위치 정보를 관리할 수 있는 기법을 제시한다. 본 논문에서 제시하는 위치 관리 기법은 고정 호스트에 이동 객체의 위치를 기록하는 사용자 프로파일을 호출 대 이동 비율에 따라 복제하여 유지함으로써 위치 갱신과 위치 탐색을 효율적으로 수행하는 노드의 계층적 위치 정보를 이용한 복제본 위치 탐색(RLS : Replication Location Search) 기법이다. 이 기법은 자주 이동하는 객체의 위치 정보를 복제함으로써 위치 탐색시에 기존 기법보다 적은 비용으로 보다 빠른 시간 안에 원하는 이동 객체의 현재 위치를 탐색할 수 있는 새로운 위치 관리 기법에 대한 연구이다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.6
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• pp.115-122
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• 2010

The main purpose of centralized monitoring system is to manage factory electrical installation efficiently by on-line data acquisition and supervisory control. The existing centralized system is only able to be managed by operator whenever electrical installation's faults are detected. Therefore, it may be possible for propagating the installation's faults when operator make the unexpected mistakes. To overcome the unexpected mistakes, in this paper, the author presents a centralized monitoring system for factory electrical installation using active database. by using active database production rule, stated system can minimize unexpected mistake and can operate centralized monitoring system efficiently. Test results on the five factory electrical installations show that performance is efficient and robust.

• Journal of Broadcast Engineering
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• v.14 no.1
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• pp.15-27
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• 2009

As various portable digital devices are developed, the space of the TV audience is expanding. We propose a structure of broadcasting control in VOD service in which viewers can resume the viewing of digital broadcasting contents in different devices after they have stopped the viewing to move to another place. Then we design a session and resource management system of VOD for this control. In particular, we design the session management of each consumer and simulate the seamless VOD connection model.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.1038-1040
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• 2022

지속적인 지구 평균 기온 상승으로 인해 우리나라를 포함한 전 세계적으로 탄소중립을 위한 혁신이 이루어지고 있다. 본 연구는 해양수산부 '해양수산분야 2050 탄소중립 로드맵'의 기준에 따라 에너지 자립률을 극대화하고 효율을 최적화시킨 제로에너지 탄소중립 건축물을 제시한다. 태양광 발전 시스템에서, 패널의 태양 일주추적 기능을 통해 에너지 발전률을 극대화하고, 패널 하향정렬 및 딥러닝 모델을 통해 유지 보수를 용이하게 하여 성능 저하를 예방한다. 폐열을 이용한 열 회수/바이패스 환기 시스템을 통해 에너지 효율을 최적화하고, 온/습도에 가중치를 부여하여 모호했던 환기 시스템 결정 기준을 에너지 효율화에 맞게 최적화해 제시한다. 탄소중립 BEMS 기능이 내재된 앱 개발로 위의 건축물 시스템을 제어·관리한다. 본 연구를 통해 제로 에너지 건축물으로서 항만 건물의 가능성을 제고하고, 탄소중립 항만의 구현을 기대한다.