• Journal of the Korean Institute of Gas
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• v.17 no.2
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• pp.28-35
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• 2013

The number of large and complex buildings is growing and they are usually concentrated in metropolitan cities. There is a possibility in such buildings that a small accident can expand to a massive disaster since their scale and complexity. To deal with this issue, a research on gas sensors which can detect multiple gases and early-warning systems has been conducted. Proper criteria or standards are necessary for effective application and operation of such sensor-based disaster monitoring system. In this study, we have proposed the alarm criteria of concentration of hazardous gases for the detection and the alarm release. For each alarm level, systematic disaster response plans consist of responsive actions and information delivery have been prepared. These disaster monitoring criteria can help the detection of hazardous gas-related disaster in the early stage of accident and the provision of appropriate emergency responses.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1979-1986
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• 2010

Biological early warning system detects toxicity by looking at behavior of organisms in water. The system uses classifier for judgement about existence and amount of toxicity in water. Boosting algorithm is one of possible application method for improving performance in a classifier. Boosting repetitively change training example set by focusing on difficult examples in basic classifier. As a result, prediction performance is improved for the events which are difficult to classify, but the information contained in the events which can be easily classified are discarded. In this paper, an incremental learning method to overcome this shortcoming is proposed by using the extended data expression. In this algorithm, decision tree classifier define class distribution information using the weight parameter in the extended data expression by exploiting the necessary information not only from the well classified, but also from the weakly classified events. Experimental results show that the new algorithm outperforms the former Learn++ method without using the weight parameter.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.33-40
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• 2012

This paper proposes a method to implement biological early warning systems(BEWS). This system generates periodically data event using a monitoring daemon and it extracts the feature parameters from this data sets. The feature parameters are derived with 6 variables, x/y coordinates, distance, absolute distance, angle, and fractal dimension. Specially by using the fractal dimension theory, the proposed algorithm define the input features represent the organism characteristics in non-toxic or toxic environment. And to find a moderate algorithm for learning the extracted feature data, the system uses an extended learning algorithm(UChoo) popularly used in machine learning. And this algorithm includes a learning method with the extended data expression to overcome the BEWS environment which the feature sets added periodically by a monitoring daemon. In this algorithm, decision tree classifier define class distribution information using the weight parameter in the extended data expression. Experimental results show that the proposed BEWS is available for environmental toxicity detection.

• Environmental Analysis Health and Toxicology
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• v.25 no.1
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• pp.19-26
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• 2010

Discharged materials from the point or non-point source are released into the sea, and as the results, marine environment is directly affected. We must estimate the impacts of contaminants to marine pollution rapidly and accurately. Therefore, it is needed on early warning system for appreciating marine environmental impacts, and required a bioassay to evaluate abnormal changes. A bioassay test was developed to examine the effects of heavy metal contaminants on the early life stages of the marine annimals. We have studied the effects of metals on early development of a sea urchin species, Strongylocentrotus intermedius. S. intermedius embryos were tested with six metals (Cu, Ag, Zn, Cd, Cr, Ni) and showed the highest sensitivity to Cu as well as the lowest sensitivity to Cd. The order of biological impact for metals was Cu>Ag>Ni>Zn>Cr>Cd. In accordance with the results, sea urchins embryos can provide biological criteria for seawater quality assessment. The sensitivity of developmental bioassay whith S. intermedius is at intermediate level among marine organisms commonly used in aquatic bioassays. And this sea urchin can be routinely employed as a test organism for ecotoxicity assays.

• Molecular & Cellular Toxicology
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• v.4 no.3
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• pp.199-204
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• 2008

The bio-molecules involved in defense mechanisms can be used as efficient biomarkers for physiological changes in organisms caused by both of internal and external stress. Thus, the expression level of genes which encoding such molecules serve as critical 'early warning system' for environmental assessment as well as health diagnosis of biological organisms. In this study, Cytochrome P450, Heat shock protein 90, Ubiquitin and ${\beta}$-actin gene were isolated for the first time from a red alga Gracilaria textorii. The quantitative differential gene expression analyses of three genes, GteCYP1A, GteHsp90 and Gte-UB, were carried out in G. textorii sporophytes collected from two different localities, polluted Sujeong (Masan, Korea) and potentially unpolluted Danggeum (Daemaemuldo Is., Korea). The transcripts of all three tested genes were highly expressed in the Sujeong population. The results suggest: 1) the Sujeong site was more polluted than the Danggeum site; 2) G. textorii could be applicable to marine environment monitoring in coastal regions.

• Korean Journal of Ecology and Environment
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• v.49 no.4
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• pp.343-353
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• 2016

Oligochaetes distribute widely in freshwater ecosystem, and some species are used as bioindicators for water quality assessment because they are tolerant to organic enrichment. They are acknowledged for potential for environmental health recovery of organic polluted environment. There are a lot of studies on ecology and toxicity assessment using oligochaetes in aquatic environment. In this study, we reviewed literature on ecotoxicology of aquatic oligochaetes. We searched literature from a database 'google scholar' by using keywords such as aquatic, oligochaete, and toxicity. The literature were summarized according to publication years, species, test methods, and chemicals. We obtained 133 articles published from 1953 to 2015 from the database. Among them, 58 papers(43.6% of total) have been published in 1990s. Three species(Lumnbriculus variegatus, Tubifex tubifex, and Limnodrilus hoffmeisteri) have been used most frequently in the study. Different species displayed different toxicological responses to different toxic chemicals. The results on the ecotoxicological study with aquatic oligochaetes revealed the possibility of the development for early warning system using aquatic oligochaetes to monitor aquatic ecosystem disturbance.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.175-185
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• 2021

Purpose: Vital sign are used to help assess the general physical health of a person, give clues to possible diseases, and show progress toward recovery. Researchers are using vital sign data and AI(artificial intelligence) to manage a variety of diseases and predict mortality. In order to analyze vital sign data using AI, it is important to select and extract vital sign data suitable for research purposes. Methods: We developed a method to visualize vital sign and early warning scores by processing retrospective vital sign data collected from EMR(electronic medical records) and patient monitoring devices. The vital sign data used for development were obtained using the open EMR big data MIMIC-III and the wearable patient monitoring device(CareTaker). Data processing and visualization were developed using Python. We used the development results with machine learning to process the prediction of mortality in ICU patients. Results: We calculated NEWS(National Early Warning Score) to understand the patient's condition. Vital sign data with different measurement times and frequencies were sampled at equal time intervals, and missing data were interpolated to reconstruct data. The normal and abnormal states of vital sign were visualized as color-coded graphs. Mortality prediction result with processed data and machine learning was AUC of 0.892. Conclusion: This visualization method will help researchers to easily understand a patient's vital sign status over time and extract the necessary data.

• Journal of Korean Society of Environmental Engineers
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• v.34 no.12
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• pp.828-834
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• 2012

The ecotoxicity detection device for preliminary test (Test jig) was manufactured to develop the biological early warning system using Vibrio fischeri. In this study, the ecotoxicity detection charateristics of the Test jig was investigated for 6 heavy metals (Cr, Zn, Pb, Cd, Cu and Hg). It was observed that relative luminescence unit (RLU) of Vibrio fischeri constantly decreased by the concentrations of the tested heavy metals. In contrast with other heavy metals, RLUs of Pb and Hg constantly decreased even at low concentrations. RLU of Hg drastically decreased when its concentration increased from 0.13 mg/L to 0.25 mg/L. $EC_{50}$ values of Cr, Zn, Pb and Cd gradually decreased with exposure time, whereas there was no significant change in $EC_{50}$ values of Cu and Hg with time. On the other hand, $EC_{50}$ values between the Test jig and Reference device were compared to evaluate the ecotoxicity detection performance of the Test jig. No big difference was found in $EC_{50}$ vlaues between the two devices, indicating that the Test jig could be applied as the ecotoxicity detection device for heavy metals.

• Environmental Analysis Health and Toxicology
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• v.20 no.1
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• pp.1-11
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• 2005

환경오염의 조기 경보 시스템으로 생체지표를 이용한 생태독성 모니터링이 최근 널리 연구되고 있다. 환경내의 생물종에서 측정한 생체지표를 이용한 환경 모니터링은 생태계 수준의 영향에 대한 예측 정보를 제공해 줄 수도 있다. 이를 위해서는 생체지표와 개체군 수준에서의 반응과의 인과관계가 밝혀져야 한다. 오염물질에 대한 생체의 반응은 분자, 세포, 생화학, 생리적, 개체, 개체군, 군집 수준에서 나타나게 되며, 이러한 각 단계별 반응은 반응 시간의 규모와 독성학적, 생태적 관련성에 따라 구분 지어 볼 수 있다. 각 개별 수준에서의 반응을 종합하면 오염물질에 노출된 생체의 전제적인 영향을 이해할 수 있으며, 이러한 이해를 바탕으로 개체군에서 나타나는 영향에 대한 인과관계를 추론할 수 있다. 생체지표와 개체군 수준의 반응과의 인과관계 정립은 효율적인 환경오염 예방기능 수행에 필수적인 과정이며, 다단계 생체 지표는 각 단계별 반응의 인과관계를 밝히기 위해 가장 적절한 접근 방법이다. 수서 무척추 생물인 Chironomus의 유충은 이러한 다단계 바이오마커 연구에 매우 적절한 생물학적 모델이다. 이 논문의 첫 번째 부분은 생체지표를 이용한 환경 모니터링을, 두 번째 부분은 Chironomus의 유충에서 생체지표의 적용에 대해서 다룬다.

• Korean Journal of Environmental Biology
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• v.34 no.2
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• pp.124-131
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• 2016

The toxic responses of flagellate Euglena agilis Carter to 8 heavy metals (Ag, Cd, Cr (VI), Cu, Hg, Ni, Pb, Zn) were measured using E. agilis system (E-Tox), an automated biomonitoring system. The E-Tox measures cell movement parameters, such as velocity, motility, and forms of the cells, as biological endpoints. $EC_{50}$ values from the E. agilis biomonitoring test were compared with the literature data from the tests with Daphnia magna, Vibrio fischeri and Euglena gracilis. Measurement of the E. agilis movement behavior and D. magna acute toxicity test were also conducted for the wastewater samples. E. agilis is less sensitive than D. magna but is comparable to or more sensitive than V. fischeri and E. gracilis for the heavy metals tested in this study. E. agilis shows prompt changes of these parameters for the toxic metal plating wastewater. Major advantages of the E-tox are automatic, easy to handle and fast ecotoxicity monitoring system compared to other biological test systems. These results imply that E. agilis biomonitoring test using E-Tox can be a putative ecotoxicity test as a good early warning tool for the monitoring of toxic wastewater.