• 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.

• 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.

• 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).

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.1-12
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• 2023

A public address (PA) system installed in a building is a system that delivers alerts, announcements, instructions, etc. in an emergency or disaster situation. As for the products used in PA systems, with the development of information and communication technology, PA products with various functions have been introduced to the market. PA systems recently launched in the market may be connected through a single network to enable efficient management and operation, or use voice recognition technology to deliver quick information in case of an emergency. In addition, a system capable of locating a user inside a building using a location-based service and guiding or responding to a safe area in the event of an emergency is being launched on the market. However, the new PA systems currently on the market add some functions to the existing PA system configuration to make system operation more convenient, but they do not change the complex PA system configuration to reduce facility costs, maintenance, and management costs. In this paper, we propose a novel PA system configuration for buildings using audio networks and control hierarchy over peer-to-peer (Anchor) technology based on audio over IP (AoIP), which simplifies the complex PA system configuration and enables convenient operation and management. As a result of the study, through the emergency signal processing algorithm, fire broadcasting was made possible according to the detection of the existence of a fire signal in the Anchor system. In addition, the control device of the PA system was replaced with software to reduce the equipment installation cost, and the PA system configuration was simplified. In the future, it is expected that the PA system using Anchor technology will become the standard for PA facilities.

• 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 the Korea Academia-Industrial cooperation Society
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• v.13 no.12
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• pp.6060-6070
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• 2012

Real-Time Enterprise (RTE)'s key requirement is that it should respond and adapt fast to the change of the firms' internal and external situations including the change of market and customers' needs. Recently, the big data processing technology to support the speedy change of the firms is spotlighted. Under the circumstances that wire and wireless communication networks are evolving with an accelerated rate, it is especially critical to provide a strong security monitoring function and stable services through a real-time processing of massive communication data traffic. By applying the big data processing technology based on a cloud computing architecture, this paper solves the managerial problems of telecommunication service providers and discusses how to operate the network management system effectively.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.1
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• pp.31-46
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• 2012

The most critical technology to implement ubiquitous health care is Ubiquitous Sensor Network (USN) technology which makes use of various sensor technologies, processor integration technology, and wireless network technology-Radio Frequency Identification (RFID) and Wireless Sensor Network (WSN)-to easily gather and monitor actual physical environment information from a remote site. With the feature, the USN technology can make the information technology of the existing virtual space expanded to actual environments. However, although the RFID and the WSN have technical similarities and mutual effects, they have been recognized to be studied separately, and sufficient studies have not been conducted on the technical integration of the RFID and the WSN. Therefore, EPCglobal which realized the issue proposed the EPC Sensor Network to efficiently integrate and interoperate the RFID and WSN technologies based on the international standard EPCglobal network. The proposed EPC Sensor Network technology uses the Complex Event Processing method in the middleware to integrate data occurring through the RFID and the WSN in a single environment and to interoperate the events based on the EPCglobal network. However, as the EPC Sensor Network technology continuously performs its operation even in the case that the minimum conditions are not to be met to find complex events in the middleware, its operation cost rises. Moreover, since the technology is based on the EPCglobal network, it can neither perform its operation only for the sake of sensor data, nor connect or interoperate with each information system in which the most important information in the ubiquitous computing environment is saved. Therefore, to address the problems of the existing system, we proposed the design and implementation of USN integration management system. For this, we first proposed an integration system that manages RFID and WSN data based on Session Initiation Protocol (SIP). Secondly, we defined the minimum conditions of the complex events to detect unnecessary complex events in the middleware, and proposed an algorithm that can extract complex events only when the minimum conditions are to be met. To evaluate the performance of the proposed methods we implemented SIP-based integration management system.

• Journal of KIISE
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• v.42 no.7
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• pp.840-845
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• 2015

In recent years, Big Data has been a topic of great interest for the production and operation work of offshore plants as well as for enterprise resource planning. The ability to predict future equipment performance based on historical results can be useful to shuttling assets to more productive areas. Specifically, a centrifugal compressor is one of the major piece of equipment in offshore plants. This machinery is very dangerous because it can explode due to failure, so it is necessary to monitor its performance in real time. In this paper, we present stream data processing architecture that can be used to compute the performance of the centrifugal compressor. Our system consists of two major components: a virtual tag stream generator and a real-time data stream manager. In order to provide scalability for our system, we exploit a parallel programming approach to use multi-core CPUs to process the massive amount of stream data. In addition, we provide experimental evidence that demonstrates improvements in the stream data processing for the centrifugal compressor.

• The Journal of the Acoustical Society of Korea
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• v.15 no.1E
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• pp.5-19
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• 1996

This paper proposes a loose part monitoring system (LPMS) design with a signal processing method based on fuzzy logic. Considering fuzzy characteristics of metallic impact waveform due to not only interferences from various types of noises in an operating nuclear power plant but also complex wave propagation paths within a monitored mechanical structure, the proposed LPMS design incorporates the comprehensive relation among impact signal features in the fuzzy rule bases for the purposes of alarm discrimination and impact diagnosis improvement. The impact signal features for the fuzzy rule bases include the rising time, the falling time, and the peak voltage values of the impact signal envelopes. Fuzzy inference results based on the fuzzy membership values of these impact signal features determine the confidence level data for each signal feature. The total integrated confidence level data is used for alarm discrimination and impact diagnosis purposes. Through the perpormance test of the proposed LPMS with mock-up structures and instrumentation facility, test results show that the system is effective in diagnosis of the loose part impact event(i.e., the evaluation of possible impacted area and degree of impact magnitude) as well as in suppressing false alarm generation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.290-293
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• 2015

개개인의 데이터가 비즈니스적으로 중요하지 않을 수 있지만, 대량으로 모으면 그 안에 숨겨진 새로운 정보를 발견할 가능성이 있는 데이터의 집합체로 빅데이터 분석 활용 사례는 점차 늘어나는 추세이다. 빅데이터 분석 기술 중 전통적인 데이터 분석방법인 하둡(Hadoop)은 예전부터 현재에 이르기까지 정형 비정형 빅데이터 분석에 널리 사용되고 있는 기술이다. 하지만 하둡은 배치성 처리 시스템으로 데이터가 많아질수록 응답 지연이 발생할 가능성이 높아, 현재 기업 경영환경과 시장환경에 대한 엄청난 양의 고속 이벤트 데이터에 대한 실시간 분석이 어려운 상황이다. 본 논문에서는 급변하는 비즈니스 환경에 대한 대안으로 오픈소스 CEP(Complex Event Processing)기반 기술을 사용하여 초당 수백에서 수십만건 이상의 이벤트 스트림을 실시간으로 지연 없이 분석가능하게 하는 실시간 분석 시스템을 개발하여 병원 ERP시스템에 적용하였다.