• 제목/요약/키워드: Abnormal events

검색결과 201건 처리시간 0.023초

폐쇄성 수면 무호흡 증후군과 상기도 저항 증후군의 진단적 및 임상적 차이 (Diagnostic and Clinical Differences in Obstructive Sleep Apnea Syndrome and Upper Airway Resistance Syndrome)

  • 최영미
    • 수면정신생리
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    • 제18권2호
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    • pp.63-66
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    • 2011
  • It has been controversial whether upper airway resistance syndrome (UARS) is a distinct syndrome or not since it was reported in 1993. The International Classification of Sleep Disorders classified UARS under obstructive sleep apnea syndrome (OSAS) in 2005. UARS can be diagnosed when the apnea-hypopnea index (AHI) is fewer than 5 events per hour, the simultaneously calculated respiratory disturbance index (RDI) is more than 5 events per hour due to abnormal non-apneic non-hypopneic respiratory events accompanying respiratory effort related arousals (RERAs), and oxygen saturation is greater than 92% at termination of an abnormal breathing event. Although esophageal pressure measurement remains the gold standard for detecting subtle breathing abnormality other than hypopnea and apnea, nasal pressure transducer has been most commonly used. RERAs include phase A2 of cyclical alternating patterns (CAPs) associated with EEG changes. Symptoms of OSAS can overlap with UARS, but chronic insomnia tends to be more common in UARS than in OSAS and clinical symptoms similar with functional somatic syndrome are also more common in UARS. In this journal, diagnostic and clinical differences between UARS and OSAS are reviewed.

토픽의 조합으로 이벤트 흐름을 예측하기 위한 시각적 분석 시스템 (Visual Analytics using Topic Composition for Predicting Event Flow)

  • 연한별;김석연;장윤
    • 정보과학회 컴퓨팅의 실제 논문지
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    • 제21권12호
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    • pp.768-773
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    • 2015
  • 사회적 혼란을 야기하는 이벤트는 발생 직후 어떻게 대응하느냐에 따라 소요되는 비용의 편차가 크다. 이에 따라 비정상적인 이벤트를 탐지하고 의미를 파악하는 연구가 많이 진행되고 있다. 또한 예측 분석에 관한 연구도 많이 수행되고 있다. 그러나 대부분의 연구는 이벤트의 전체적인 미래 경향에 대한 수치 결과를 예측할 뿐, 이벤트가 내포하는 의미에 대한 예측 연구는 미비하다. 이에 따라 본 논문에서는 비정상적인 이벤트가 내포하는 토픽의 조합을 통해 미래에 어떠한 일이 발생할 수 있는지에 대한 시각적 예측 분석 방법을 제안한다. 제안하는 방법은 먼저 트윗에서 실시간으로 비정상 이벤트를 탐지한다. 그 다음 과거 유사한 사례를 탐색한 다음 이벤트와 관련된 토픽들을 추출한다. 마지막으로 사용자는 의미 있는 토픽의 조합을 통해 미래에 어떠한 일이 발생할 수 있을지 분석할 수 있다. 실험은 두 가지 상황에 대한 예측 분석을 수행하였으며, 실험 결과 본 논문에서 제안한 방법의 타당성을 입증하였다.

전자무역의 베이지안 네트워크 개선방안에 관한 연구 (A Study on the Improvement of Bayesian networks in e-Trade)

  • 정분도
    • 통상정보연구
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    • 제9권3호
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    • pp.305-320
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    • 2007
  • With expanded use of B2B(between enterprises), B2G(between enterprises and government) and EDI(Electronic Data Interchange), and increased amount of available network information and information protection threat, as it was judged that security can not be perfectly assured only with security technology such as electronic signature/authorization and access control, Bayesian networks have been developed for protection of information. Therefore, this study speculates Bayesian networks system, centering on ERP(Enterprise Resource Planning). The Bayesian networks system is one of the methods to resolve uncertainty in electronic data interchange and is applied to overcome uncertainty of abnormal invasion detection in ERP. Bayesian networks are applied to construct profiling for system call and network data, and simulate against abnormal invasion detection. The host-based abnormal invasion detection system in electronic trade analyses system call, applies Bayesian probability values, and constructs normal behavior profile to detect abnormal behaviors. This study assumes before and after of delivery behavior of the electronic document through Bayesian probability value and expresses before and after of the delivery behavior or events based on Bayesian networks. Therefore, profiling process using Bayesian networks can be applied for abnormal invasion detection based on host and network. In respect to transmission and reception of electronic documents, we need further studies on standards that classify abnormal invasion of various patterns in ERP and evaluate them by Bayesian probability values, and on classification of B2B invasion pattern genealogy to effectively detect deformed abnormal invasion patterns.

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권역외상센터 간호사의 외상사건 경험, 지각된 스트레스 및 스트레스 대처방식 (Traumatic Events Experience, Perceived Stress, and Stress Coping of Nurses in Regional Trauma Centers)

  • 박준영;서은지
    • 근관절건강학회지
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    • 제27권2호
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    • pp.122-131
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    • 2020
  • Purpose: This study aims to investigate major traumatic events experienced by nurses in regional trauma centers and explore the relationship among their traumatic events experience, perceived stress, and stress coping. Methods: Data were collected from 208 nurses in the trauma emergency room (trauma-bay) and trauma intensive care unit at four regional trauma centers. Results: The mean score of the traumatic events experience was 44.3 out of 76 points. The scores for physical injuries caused by traffic accidents or falls as well as patient care with abnormal behaviors were high. Significantly positive correlations among traumatic events experience, perceived stress, and stress coping were identified. Conclusion: Nurses working in the regional trauma centers experienced many various traumatic events, leading to high levels of stress. This study suggests that it is necessary to establish a regular surveillance system for nurses' traumatic events experience and perceived stress.

Abnormal state diagnosis model tolerant to noise in plant data

  • Shin, Ji Hyeon;Kim, Jae Min;Lee, Seung Jun
    • Nuclear Engineering and Technology
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    • 제53권4호
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    • pp.1181-1188
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    • 2021
  • When abnormal events occur in a nuclear power plant, operators must conduct appropriate abnormal operating procedures. It is burdensome though for operators to choose the appropriate procedure considering the numerous main plant parameters and hundreds of alarms that should be judged in a short time. Recently, various research has applied deep-learning algorithms to support this problem by classifying each abnormal condition with high accuracy. Most of these models are trained with simulator data because of a lack of plant data for abnormal states, and as such, developed models may not have tolerance for plant data in actual situations. In this study, two approaches are investigated for a deep-learning model trained with simulator data to overcome the performance degradation caused by noise in actual plant data. First, a preprocessing method using several filters was employed to smooth the test data noise, and second, a data augmentation method was applied to increase the acceptability of the untrained data. Results of this study confirm that the combination of these two approaches can enable high model performance even in the presence of noisy data as in real plants.

랜덤포레스트를 이용한 기상 환경에 따른 이상기온 분류 (Classification Abnormal temperatures based on Meteorological Environment using Random forests)

  • 김윤수;송광윤;장인홍
    • 통합자연과학논문집
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    • 제17권1호
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    • pp.1-12
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    • 2024
  • Many abnormal climate events are occurring around the world. The cause of abnormal climate is related to temperature. Factors that affect temperature include excessive emissions of carbon and greenhouse gases from a global perspective, and air circulation from a local perspective. Due to the air circulation, many abnormal climate phenomena such as abnormally high temperature and abnormally low temperature are occurring in certain areas, which can cause very serious human damage. Therefore, the problem of abnormal temperature should not be approached only as a case of climate change, but should be studied as a new category of climate crisis. In this study, we proposed a model for the classification of abnormal temperature using random forests based on various meteorological data such as longitudinal observations, yellow dust, ultraviolet radiation from 2018 to 2022 for each region in Korea. Here, the meteorological data had an imbalance problem, so the imbalance problem was solved by oversampling. As a result, we found that the variables affecting abnormal temperature are different in different regions. In particular, the central and southern regions are influenced by high pressure (Mainland China, Siberian high pressure, and North Pacific high pressure) due to their regional characteristics, so pressure-related variables had a significant impact on the classification of abnormal temperature. This suggests that a regional approach can be taken to predict abnormal temperatures from the surrounding meteorological environment. In addition, in the event of an abnormal temperature, it seems that it is possible to take preventive measures in advance according to regional characteristics.

중환자실 간호사의 외상성 사건 경험이 이직의도에 미치는 영향 : 감성지능의 조절효과 (The Influence of Traumatic Events on Turnover Intention among Nurses Working in Intensive Care Units: The Moderating Effect of Emotional Intelligence)

  • 김현미;박지영
    • 중환자간호학회지
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    • 제14권2호
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    • pp.70-81
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    • 2021
  • Purpose : The purpose of this study was to identify the moderating effects of emotional intelligence on the relationship between traumatic events and turnover intention among nurses working in intensive care units (ICUs). Method : In this predictive correlation study, the convenience sample included 133 ICU nurses. Data were collected using an online, structured self-report survey. The collected data were analyzed by descriptive statistics, an independent t-test, an analysis of variance, Pearson's correlation coefficient, and a hierarchical multiple regression analysis using SPSS/WIN 25.0. Results : The most frequently experienced traumatic events in ICUs were "nursing patients with abnormal behavior, including shouting and delirium," "end-of-life care," and "nursing patients with a risk of disease transmission, including AIDS and tuberculosis." The moderating effect of emotional intelligence was found to be statistically significant on the relationship between traumatic events and turnover intentions (𝛽=-0.15, p =.029). Conclusion : Intervention to improve the emotional intelligence of ICU nurses can be a salient strategy to reduce turnover intention resulting from traumatic events.

Aspergillus nidulans에 있어서 체세포 재조합의 유발에 화학물질이 미치는 영향 (Induction of Mitotic Recombination by Chemical Agents in Aspergillus nidulans)

  • 송재만;강현삼
    • 미생물학회지
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    • 제17권3호
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    • pp.137-151
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    • 1979
  • Germinating conidia of Aspergillus nidulans diploid heterozygous for color and other genetic markers were used to direct and distinguish genetic events such as mutation, mitotic crossingover and nondisjunction in a single test after treatment with N-methyl-N'-nitro-N-nitrosoguanidine (NG), mitomycin C(MC), and chloral hydrate(CH). The following results were obtained : 1. NG reduced the survival of conidia and increased the frequencies of miototic segregants about sevenfoli over the control ; among the mitotic segregants the predominant genetic event was mitotic crossingover. NG also produced many abnormal colonies, which appeared to be of the types caused by induced semidominant lethals or chromosomal aberrations, and the aneuploid types found spontaneously. 2. After treatment with MC the survival of conidia was reduced but few abnormal colonies were produced. The frequencies of miotic segregants were increased about threefold over the control ; in the mitotic segeregants the induced genetic event was mitotic crossingover. 3. CH gave no apparent effect on the survival of conidia and the frequencies of mitotic segregants. However, CH generated abnormal colonies, very greatly, which turned out to be of the aneuploid types. This result suggests that CH interferes with the normal distribution of chromosomes in mitosis.

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