• 한방재활의학과학회지
• /
• 제28권1호
• /
• pp.61-72
• /
• 2018

Objectives The authors propose a new checklist model adapted for safety miniscalpel acupuncture procedure of cervical and lumbar spine. Methods On the basis of available literature and expert opinion, a prototype checklist was developed. The checklist was adapted on the basis of observation of daily practice. Results The checklist has three parts: 1. prevention and management of healthcare associated infections, 2. verification list before and after miniscalpel acupuncture treatment, 3. adverse event monitoring after procedure. We presented a summary checklist based on the above contents. Conclusions We propose the first patient safety checklist for minicalpel acupuncture treatment of cervical and lumbar spine. The checklist will be complemented using further research methodologies.

• 대한전기학회논문지:전력기술부문A
• /
• 제55권9호
• /
• pp.351-358
• /
• 2006

In this paper, DSPOCS(Digital Switchgear-Panel Operation and Control Solution) is designed, which is the intelligent inference based operation and control solution to obtain the safety and reliability of electric power supply in substation based on IED. DSPOCS is designed as a scheduled monitoring and control task and a real-time alarm inference task, and is interlinked with BRES(Bus Reconfiguration Expert System) in the required case. The intelligent alarm inference task consists of the alarm knowledge generation part and the real-time pattern matching part. The alarm knowledge generation part generates automatically alarm knowledge from DB saves it in alarm knowledge base. On the other hand, the pattern matching part inferences the real-time event by comparing the real-time event information furnished from IEDs of substation with the patterns of the saved alarm knowledge base.; Especially, alarm knowledge base includes the knowledge patterns related with fault alarm, the overload alarm and the diagnosis alarm. In order to design the database independently in substation structure, busbar is represented as a connectivity node which makes the more generalized graph theory possible. Finally, DSPOCS is implemented in MS Visual $C^{++}$, MFC, the effectiveness and accuracy of the design is verified by simulation study to the typical distribution substation.

• 한국지열·수열에너지학회논문집
• /
• 제8권2호
• /
• pp.55-60
• /
• 2012

In many cases, geothemal wells will not be opened up a geothermal reservoir under such conditions that an extraction of geothermal energy is economically viable without any further measures. Geothermal wells often have to be stimulated, in order to increase productivity. For the non-volcanic area, such as Korea, the hydraulic stimulation is necessary to complete geothermal power plant. The analysis of induced seismic event showed that the thermal resource might have a much wider extent and a much higher generation potential than previously assumed. In order to record compressional and shear waves emitted during fracture stimulation, three-component geophones are placed in a seismometer. The recorded data from one seismometer is the convolution of the source magnitude, the transmission media, and the sensitivity of the instrument.

• Smart Structures and Systems
• /
• 제15권3호
• /
• pp.881-896
• /
• 2015

The authors' research group has developed a noncontact type of sensors which directly measure the inter-story drift displacements of a building during a seismic event. Soon after that event, such seismically-induced drift displacement data would provide structural engineers with useful information to judge how the stories have been damaged. This paper presents a scheme of estimating the story cumulative plastic deformation ratios based on such measured drift displacement information toward the building safety monitoring. The presented scheme requires the data of story drift displacements and the ground motion acceleration. The involved calculations are rather simple without any detailed information on structural elements required: the story hysteresis loops are first estimated and then the cumulative plastic deformation ratio of each story is evaluated from the estimated hysteresis. The effectiveness of the scheme is demonstrated by utilizing the data of full-scale building model experiment performed at E-defense and conducting numerical simulations.

• Food Science and Biotechnology
• /
• 제18권3호
• /
• pp.694-699
• /
• 2009

A multiplex polymerase chain reaction (PCR) method was developed for the detection of 4 events of genetically modified (GM) soybean. The event-specific primers were designed from 4 events of GM soybean (RRS, A2704-12, DP356043-5, and MON89788). The lectin was used as an endogenous reference gene of soybean in the PCR detection. The primer pair YjLec-4-F/R producing 100 bp amplicon was used to amplify the lectin gene and no amplified product was observed in any of the 9 different plants used as templates. This multiplex PCR method allowed for the detection of event-specific targets in a genomic DNA mixture of up to 1% GM soybean mixture containing RRS, A2704-12, DP356043-5, and MON89788. In this study, 20 soybean products obtained from commercial food markets were analyzed by the multiplex PCR. As a result, 6 samples contained RRS. These results indicate that this multiplex PCR method could be a useful tool for monitoring GM soybean.

• 대한산업공학회지
• /
• 제39권6호
• /
• pp.577-586
• /
• 2013

In a shipyard, it is hard to predict block movement due to the uncertainty caused during the long period of shipbuilding operations. For this reason, block movement is rarely scheduled, while main operations such as assembly, outfitting and painting are scheduled properly. Nonetheless, the high operating costs of block movement compel task managers to attempt its management. To resolve this dilemma, this paper proposes a new block movement analysis framework consisting of the following operations: understanding the entire process, log clustering to obtain manageable processes, discovering the process model and detecting exceptional processes. The proposed framework applies fuzzy mining and trace clustering among the process mining technologies to find main process and define process models easily. We also propose additional methodologies including adjustment of the semantic expression level for process instances to obtain an interpretable process model, definition of each cluster's process model, detection of exceptional processes, and others. The effectiveness of the proposed framework was verified in a case study using real-world event logs generated from the Block Process Monitoring System (BPMS).

• 한국정보통신학회:학술대회논문집
• /
• 한국해양정보통신학회 2010년도 춘계학술대회
• /
• pp.547-549
• /
• 2010

본 논문에서는 실내 환경에서 반도체 장비 주변에 배치된 다수의 센서로부터 정보를 취득하고 취득된 정보를 바탕으로 반도체 장비의 상황을 인지하는 시스템을 제안한다. 제안하는 반도체 장비 상황인지 시스템은 가속도, 압력, 온도, 가스 센서로부터 정보를 취득하고 서버로 전송한다. 그리고 서버로 전송된 데이터는 단일이벤트와 다중이벤트의 상황인지 알고리즘을 통해 알람을 발생시킨다. 그 결과 불필요한 알람이 줄어 수준 높은 실시간 감시가 가능하고 주위의 정보를 한 번에 알 수 있어 효율적인 관리가 가능하다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제6권1호
• /
• pp.229-240
• /
• 2012

Advances in MEMS and CMOS technologies have motivated the development of low cost/power sensors and wireless multimedia sensor networks (WMSN). The WMSNs were created to ubiquitously harvest multimedia content. Such networks have allowed researchers and engineers to glimpse at new Machine-to-Machine (M2M) Systems, such as remote monitoring of biosignals for telemedicine networks. These systems require the acquisition of a large number of data streams that are simultaneously generated by multiple distributed devices. This paradigm of data generation and transmission is known as event-streaming. In order to be useful to the application, the collected data requires a preprocessing called data fusion, which entails the temporal alignment task of multimedia data. A practical way to perform this task is in a centralized manner, assuming that the network nodes only function as collector entities. However, by following this scheme, a considerable amount of redundant information is transmitted to the central entity. To decrease such redundancy, data fusion must be performed in a collaborative way. In this paper, we propose a collaborative data alignment approach for event-streaming. Our approach identifies temporal relationships by translating temporal dependencies based on a timeline to causal dependencies of the media involved.

• Nuclear Engineering and Technology
• /
• 제54권1호
• /
• pp.193-206
• /
• 2022

Several algorithms for nuclear power plant (NPP) break event detection, isolation, localization, and size estimation are proposed. A break event can be promptly detected and isolated after its occurrence by simultaneously monitoring changes in the sensing readings and by employing an interquartile range-based isolation scheme. By considering the multi-sensor data block of a break to be rank-one, it can be located as the position whose lead field vector is most orthogonal to the noise subspace of that data block using the Multiple Signal Classification (MUSIC) algorithm. Owing to the flexibility of deep neural networks in selecting the best regression model for the available data, we can estimate the break size using multiple-sensor recordings of the break regardless of the sensor types. The efficacy of the proposed algorithms was evaluated using the data generated by Maanshan NPP simulator. The experimental results demonstrated that the MUSIC method could distinguish two near breaks. However, if the two breaks were close and of small sizes, the MUSIC method might wrongly locate them. The break sizes estimated by the proposed deep learning model were close to their actual values, but relative errors of more than 8% were seen while estimating small breaks' sizes.

• 지질공학
• /
• 제34권2호
• /
• pp.173-191
• /
• 2024

Landslides pose significant threats to many countries globally, yet the development and implementation of effective landslide early warning systems (LEWS) remain challenging due to multifaceted complexities spanning scientific, technological, and political domains. Addressing these challenges demands a holistic approach. Technologically, integrating thresholds, such as rainfall thresholds, with real-time data within accessible, open-source software stands as a promising solution for LEWS. This article introduces LandScient_EWS, a PHP-based program tailored to address this need. The software facilitates the comparison of real-time measured data, such as rainfall, with predefined landslide thresholds, enabling precise calculations and graphical representation of real-time landslide advisory levels across diverse spatial scales, including regional, basin, and hillslope levels. To illustrate its efficacy, the program was applied to a case study in Medellin, Colombia, where a rainfall event on August 26, 2008, triggered a shallow landslide. Through pre-defined rainfall intensity and duration thresholds, the software simulated advisory levels during the recorded rainfall event, utilizing data from a rain gauge positioned within a small watershed and a single grid cell (representing a hillslope) within that watershed. By identifying critical conditions that may lead to landslides in real-time scenarios, LandScient_EWS offers a new paradigm for assessing and responding to landslide hazards, thereby improving the efficiency and effectiveness of LEWS. The findings underscore the software's potential to streamline the integration of rainfall thresholds into both existing and future landslide early warning systems.