• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.471-480
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• 2002

In this paper, we implemented a real-time system improving the performance of the paper currency discrimination by integrating a weighted region of interest matching algorithm with a weighted shape feature matching algorithm of the blocked image. The system classifies the paper currency by comparing a query image with compared images based on the database that contain images of paper currency. Especially, the system has good efficiency at the contaminated, rotated, and translated paper currency. The system hardware consists of three parts as follows : the paper currency image acquired by CIS(contact image sensor) is applied to the pre-processing part with A/D converter and PLD. Finally the pre-processed image data are classified by the main image processing part with a high-speed DSP based on the proposed algorithm.

• The KIPS Transactions:PartD
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• v.9D no.1
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• pp.21-30
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• 2002

The active database system introduces the active rules detecting specified state. As the condition evaluation of the active rules is performed every time an event occurs, the performance of the system has a great influence, depending on the conditions processing method. In this paper, we propose the conditions processing system with the preprocessor which determines the delta tree structure, constructs the classification tree, and generates the aggregate function table. Due to the characteristics of the active database through which the active rules can be comprehended beforehand, the preprocessor can be introduced. In this paper, the delta tree which can effectively process the join, selection operations, and the aggregate function is suggested, and it can enhance the condition evaluation performance. And we propose the classification tree which effectively processes the join operation and the aggregate function table processing the aggregate function which demands high cost. In this paper, the conditions processing system can be expected to enhance the performance of conditions processing in the active rules as the number of conditions comparison decreases because of the structure which is made in the preprocessor.

• Journal of the Microelectronics and Packaging Society
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• v.28 no.4
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• pp.109-114
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• 2021

We investigated the effects of atmospheric hydrogen plasma treatment on Cu-Cu direct bonding. Hydrogen plasma was effective in reducing the surface oxide layer of Cu thin film, which was confirmed by GIXRD analysis. It was observed that larger plasma input power and longer treatment time were effective in terms of reduction and surface roughness. The interfacial adhesion energy was measured by DCB test and it was observed to decrease as the bonding temperature decreased, resulting in bonding failure at bonding temperature of 200℃. In case of wet treatment, strong Cu-Cu bonding was observed above bonding temperature of 250℃.

• Smart Media Journal
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• v.12 no.11
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• pp.36-47
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• 2023

Industrial Control System(ICS), which controls facilities at major industrial sites, is increasingly connected to other systems through networks. With this integration and the development of intelligent attacks that can lead to a single external intrusion as a whole system paralysis, the risk and impact of security on industrial control systems are increasing. As a result, research on how to protect and detect cyber attacks is actively underway, and deep learning models in the form of unsupervised learning have achieved a lot, and many abnormal detection technologies based on deep learning are being introduced. In this study, we emphasize the application of preprocessing methodologies to enhance the anomaly detection performance of deep learning models on time series data. The results demonstrate the effectiveness of a Wavelet Transform (WT)-based noise reduction methodology as a preprocessing technique for deep learning-based anomaly detection. Particularly, by incorporating sensor characteristics through clustering, the differential application of the Dual-Tree Complex Wavelet Transform proves to be the most effective approach in improving the detection performance of cyber attacks.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.2008-2012
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• 2007

통계청 등의 기관에 구축되어있는 기본적인 비점오염원 자료들은 행정구역별로 나뉘어져 있지만 실제수계에 도달하는 부하량 산정을 위해서는 유역별로 구분을 다시 해야만 하는 번거로움이 있다. 따라서 본 연구에서는 반복되는 비점오염원 자료의 전처리 과정의 번거로움을 피하기 위하여 지리정보체계(Geographical Infomation System; GIS)와 VBA(Visual Basic for Application)를 이용하여 통계자료의 전처리 과정을 한 번에 처리할 수 있는 시스템을 구축하였다. 본 시스템은 선택한 유역도와 행정구역도를 중첩하여 유역 내 최소행정구역의 점유율을 반영한 통계자료를 사용자 친화적으로 재분류하는 시스템이다. 본 시스템의 적용성 확인을 위하여 새만금유역 내 주상천유역을 대상으로 연구를 실시하였으며, 새만금유역에 포함되는 전라북도 최소행정구역의 토지이용 통계자료만을 기본 데이터로 활용하였다. 본 연구에서 구축된 시스템은 오염부하량 산정에 있어 요구되는 기본적인 데이터를 얻는 것에 있어서 기존의 장시간에 걸친 단순 반복작업을 대신하는 효율적인 시스템이며, ArcGIS에 대한 이해가 부족한 사용자의 경우에도 간단한 시스템조작만으로도 필요한 데이터를 구축할 수 있어 사용자에게 편리함을 제공한다. 향후 본 시스템을 이용하여 비점오염부하량 산정시스템을 개발할 수 있고, 기상자료 등과 같은 수문모형으로의 적용도 가능할 것으로 기대된다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.2
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• pp.219-224
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• 2011

Recently increasing importance of information security, personal security is researched. Among them, biometrics research is very good at recognition and security particularly in terms of iris recognition. Recent hospital physicians and employees for access control is emphasized. But most of them, easy-employee card access control systems are used. It has difficulties of iris recognition on the issue of accurate iris recognition algorithm to eliminate noise and inaccuracy of pretreatment methods for recognition from existing research. Therefore, this paper complements existing encryption methods to the disadvantages of biometric iris recognition using high-access records in the hospital management system is applied. In addition to conventional pretreatment process to increase recognition eyebrows when mask line component added to the extraction mask, the correct preparation method, and accordingly proposed to improve the recognition of records management systems offer access to the hospital.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.7
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• pp.225-232
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• 2022

Recent development in information and communication technology has been beneficial to many, but at the same time, malicious attack attempts are also increasing through vulnerabilities in new programs. Among malicious attacks, malware operate in various ways and is distributed to people in new ways every time, and to solve this malware, it is necessary to quickly analyze and provide defense techniques. If new malware can be classified into the same type of malware, malware has similar behavioral characteristics, so they can provide defense techniques for new malware using analyzed malware. Therefore, there is a need for a solution to this because the method of accurately and quickly classifying malware and the number of data may not be uniform for each family of analyzed malware. This paper proposes a system that combines image preprocessing and ensemble techniques to increase accuracy in imbalanced data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1890-1897
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• 2021

People counting is an important technology to provide application services such as smart home, smart building, smart car, etc. Due to the social distancing of COVID-19, the people counting technology attracted public attention. People counting system can be implemented in various ways such as camera, sensor, wireless, etc. according to service requirements. People counting system using WiFi AP uses WiFi CSI data that reflects multipath information. This technology is an effective solution implementing indoor with low cost. The conventional WiFi CSI-based people counting technologies have low accuracy that obstructs the high quality service. This paper proposes a deep learning people counting system based on WiFi CSI data. Data preprocessing using auto-encoder, data augmentation that transform WiFi CSI data, and a proposed deep learning model improve the accuracy of people counting. In the experimental result, the proposed approach shows 89.29% accuracy in 6 subjects.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.3
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• pp.59-70
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• 2021

With the recent advancements in the Internet of Things, context-aware system that provides customized services become important to consider. The existing context-aware systems analyze data generated around the user and abstract the context information that expresses the state of situations. However, these datasets is mostly unstructured and have difficulty in processing with simple approaches. Therefore, providing context-aware services using the datasets should be managed in simplified method. One of examples that should be considered as the unstructured datasets is a deep learning application. Processes in deep learning applications have a strong coupling in a way of abstracting dataset from the acquisition to analysis phases, it has less flexible when the target analysis model or applications are modified in functional scalability. Therefore, an abstraction model that separates the phases and process the unstructured dataset for analysis is proposed. The proposed abstraction utilizes a description name Analysis Model Description Language(AMDL) to deploy the analysis phases by each fat client is a specifically designed instance for resource-oriented tasks in edge computing environments how to handle different analysis applications and its factors using the AMDL and Fat client profiles. The experiment shows functional scalability through examples of AMDL and Fat client profiles targeting a vehicle image recognition model for vehicle access control notification service, and conducts process-by-process monitoring for collection-preprocessing-analysis of unstructured data.

• Proceedings of the Korea Water Resources Association Conference
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• 2002.05a
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• pp.317-322
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• 2002

본 연구는 유역 수질의 효과적인 관리와 수질 모델의 효율적인 활용을 위하여 GIS를 기반으로 수질 모델과 지형 및 문자 데이터베이스를 통합한 모델링 시스템(Water Quality Management System)을 개발하고 전라북도 내 동진강에 대해 적용하였다. WQMS는 DOS 기반의 수질모델이 가지는 복잡성과 결과해석의 불편을 최소화하기 위하여 윈도우 기반의 하천모델을 운용하기 위한 시스템을 구축하고, 나아가 GIS 기반의 사용자에게 보다 편리한 모델링 환경을 제공하도록 설계되었다. 개발된 시스템의 구현 단계는 전처리와 모델링 실행, 후처리의 세단계로 구분될 수 있다. 전처리단계는 DB에 의해 모델실행을 지원하며 후처리 단계에서는 GIS를 이용하여 모델실행 결과를 그래프와 속성 자료로 확인할 수 있도록 하였다. 또한 실측자료를 활용하여 WQMS의 적용성을 평가한 결과 신뢰성이 높게 평가되었다. WQMS는 기존 DOS 기반의 모델링의 복잡성을 제거하고 정도 높은 수질분석을 수행하므로서 효율적인 유역 수질관리에 필요한 기본자료를 제공할 것으로 기대된다.