• Korean Journal of Construction Engineering and Management
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• v.9 no.2
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• pp.125-135
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• 2008

A controller who is responsible for visiter's safety makes a decision about measures for visiter safety in human-based decision making process. Many potential accidents that are caused by human error lurk in results of the process. The accidents can be decreased by changing the decision making process from human-based into technology-based. Technology-based decision making process can catch a controller's attention through data filtering, alarm filtering, and so on. So, the controller can get information on occurrence of an unforeseen accident pro-actively. The objective of this study is to suggest a concept of 3D spatial information control system for visitor flow control in multi complex building using technology-based decision making process. This study shows utilization of the system and contribution.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.59-60
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• 2016

사물통신 기기의 발달로 다양한 응용에서 대용량의 스트림 데이터의 실시간 복합 이벤트 처리 기법에 대한 중요성이 증가되고 있다. 본 논문에서는 유사 연산 처리 비용을 감소시키기 위한 다수의 복합 이벤트 처리 기법을 제안한다. 제안하는 기법은 다수의 복합 이벤트를 처리하기 위한 연산자를 그래프로 표현하고 중복적인 연산을 감소시킨다.

• The KIPS Transactions:PartD
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• v.17D no.3
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• pp.193-202
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• 2010

Recently, there have been several researches on automatic object identification and distributed computing technology to realize a ubiquitous computing environment. Radio Frequency IDentification (RFID) technology has been applied to many business areas to simplify complex processes and gain important benefits. To derive real benefits from RFID, the system must rapidly implement functions to process a large quantity of event data generated by the RFID operations and should be configured dynamically for changing businesses. Consequently, developers are forced to implement systems to derive meaningful high-level events from simple RFID events and bind them to various business processes. Although applications could directly consume and act on RFID events, extracting the business rules from the business logic leads to better decoupling of the system, which consequentially increases maintainability. In this paper, we describe an RFID business aware framework for business processes in the Electronic Product Code (EPC) Network. This framework is proposed for developing business applications using business services. The term "business services" refers to generated events that can be used in business applications without additional data collection and processing. The framework provides business rules related to data collection, processing, and management, and supports the rapid development and easy maintenance of business applications based on business services.

• The Transactions of the Korea Information Processing Society
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• v.13 no.9
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• pp.404-412
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• 2024

The adoption of cloud environments has revolutionized application deployment and management, with microservices architecture and container technology serving as key enablers of this transformation. However, these advancements have introduced new challenges, particularly the necessity to precisely understand service interactions and conduct detailed analyses of internal processes within complex service environments such as microservices. Traditional monitoring techniques have proven inadequate in effectively analyzing these complex environments, leading to increased interest in eBPF (extended Berkeley Packet Filter) technology as a solution. eBPF is a powerful tool capable of real-time event collection and analysis within the Linux kernel, enabling the monitoring of various events, including file system activities within the kernel space. This paper proposes a container activity analysis system based on eBPF, which monitors events occurring in the kernel space of both containers and host systems in real-time and analyzes the collected data. Furthermore, this paper conducts a comparative analysis of prominent eBPF-based container monitoring systems (Tetragon, Falco, and Tracee), focusing on aspects such as event detection methods, default policy application, event type identification, and system call blocking and alert generation. Through this evaluation, the paper identifies the strengths and weaknesses of each system and determines the necessary features for effective container process monitoring and restriction. In addition, the proposed system is evaluated in terms of container metadata collection, internal activity monitoring, and system metadata integration, and the effectiveness and future potential of eBPF-based monitoring systems.

• The KIPS Transactions:PartD
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• v.12D no.7 s.103
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• pp.957-964
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• 2005

According to rapid growth of web environment, user interface design needs to support the complex interactions between human and computer. In the paper we suggest the object modeling method for Qualify Improvement of User Interface. We propose the 4 business event's object modeling phases such as business event object modeling, task object modeling, transaction object modeling, and form object modeling to enhance visual cohesion of UI. As a result, this 4 phases in this paper allows us to enhance visual cohesion of User Interface prototype. We have found that the visual cohesion of business events become strong and unskilled designer can develope the qualified user interface prototype. And it also improves understanding of business task and reduces prototype system development iteration.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.43-50
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• 2018

Biometric information computing is greatly influencing both a computing system and Big-data system based on the bio-information system that combines bio-signal sensors and bio-information processing. Unlike conventional data formats such as text, images, and videos, biometric information is represented by text-based values that give meaning to a bio-signal, important event moments are stored in an image format, a complex data format such as a video format is constructed for data prediction and analysis through time series analysis. Such a complex data structure may be separately requested by text, image, video format depending on characteristics of data required by individual biometric information application services, or may request complex data formats simultaneously depending on the situation. Since previous bio-information processing computing systems depend on conventional computing component, computing structure, and data processing method, they have many inefficiencies in terms of data processing performance, transmission capability, storage efficiency, and system safety. In this study, we propose an improved biosensing converged big data computing architecture to build a platform that supports biometric information processing computing effectively. The proposed architecture effectively supports data storage and transmission efficiency, computing performance, and system stability. And, it can lay the foundation for system implementation and biometric information service optimization optimized for future biometric information computing.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.5
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• pp.330-339
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• 2015

Power quality (PQ) problems are becoming a big issue, since delicate complex electronic devices are widely used. We present a new denoising technique using discrete wavelet transform (DWT), where a modified correlation thresholding is used in order to reliably detect the PQ disturbances. We consider various PQ disturbances on the basis of IEEE-1159 standard over noisy environments, including voltage swell, voltage sag, transient, harmonics, interrupt, and their combinations. These event signals are decomposed using DWT for the detection of disturbances. We then evaluate the PQ disturbance detection ratio of the proposed denoising scheme over Gaussian noise channels. Simulation results also show that the proposed scheme has an improved signal-to-noise ratio (SNR) over existing scheme.

• 한국방재학회:학술대회논문집
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• 2010.02a
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• pp.51.1-51.1
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• 2010

본 논문은 중소 도시하천을 위한 수해관리시스템 개발에 관한 것이다. 일반적으로 도시하천은 집중호우 발생 시 수위가 급격히 상승하는 특성이 있으므로 하천 재난관리 측면에 있어서 특별한 주의가 필요하다. 따라서 이와 같은 하천의 경우에는 강우와 유출 관계식으로부터 수립된 수문학적 모형을 사용하여 홍수 발생 여부를 예측하는 것 보다는 하천 수위의 실시간 변동 상황을 즉시 감지하고 위험상황 발생 시 이를 신속히 전파하는 것이 재난관리 측면에 있어 더욱 유리할 수 있다. 본 연구에서는 이를 위하여 실시간 센서 데이터를 보다 효율적으로 처리할 수 있는 복합 이벤트 처리기법을 사용하여 수해관리시스템을 개발하였다. 또한, 외부의 재난관리시스템과 정보를 공유하며 연동을 원활히 수행할 수 있으며 경보를 다수의 사용자에게 효과적으로 전파할 수 있는 이벤트 주도적 아키텍처를 적용하였다. 본 연구를 통해서 최근 실시간 데이터 처리기법으로 주목을 받고 있는 복합 이벤트 처리기법이 수해관리에 효과적임을 알 수 있었으며 타 분야의 재난관리에도 널리 적용될 수 있는 것으로 파악되었다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.4
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• pp.49-58
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• 2008

This paper proposes a methodology to measure the risk level in real-time for Business Activity Monitoring (BAM). A decision-tree methodology was employed to analyze the effect of process attributes on the result of the process execution. In the course of process execution, the level of risk is monitored in real-time, and an early warning can be issued depending on the change of the risk level. An algorithm for estimating the risk of ongoing processes in real-time was formulated. Comparison experiments were conducted to demonstrate the effectiveness of our method. The proposed method detects the risks of business processes more precisely and even earlier than existing approaches.

• Genomics & Informatics
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• v.17 no.2
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• pp.15.1-15.7
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• 2019

Automatically detecting mentions of pharmaceutical drugs and chemical substances is key for the subsequent extraction of relations of chemicals with other biomedical entities such as genes, proteins, diseases, adverse reactions or symptoms. The identification of drug mentions is also a prior step for complex event types such as drug dosage recognition, duration of medical treatments or drug repurposing. Formally, this task is known as named entity recognition (NER), meaning automatically identifying mentions of predefined entities of interest in running text. In the domain of medical texts, for chemical entity recognition (CER), techniques based on hand-crafted rules and graph-based models can provide adequate performance. In the recent years, the field of natural language processing has mainly pivoted to deep learning and state-of-the-art results for most tasks involving natural language are usually obtained with artificial neural networks. Competitive resources for drug name recognition in English medical texts are already available and heavily used, while for other languages such as Spanish these tools, although clearly needed were missing. In this work, we adapt an existing neural NER system, NeuroNER, to the particular domain of Spanish clinical case texts, and extend the neural network to be able to take into account additional features apart from the plain text. NeuroNER can be considered a competitive baseline system for Spanish drug and CER promoted by the Spanish national plan for the advancement of language technologies (Plan TL).