• 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 radiological science and technology
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• v.46 no.2
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• pp.115-122
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• 2023

The purpose of this study was to examine the association between the shapes and colors of emergency exit symbols, magnetic field warning symbols, and radiation zone symbols used in hospitals for staff and patient safety and their effects on cognitive memory. The hippocampal region's signal intensity(SI) was analyzed using fMRI. The Symbol 2 (1.75±0.54) with a green background had the highest signal intensity (SI) for emergency exits, according to the findings. The black symbol 2 (1.60±0.51) with a yellow background had the highest signal intensity (SI) for the magnetic field warning symbol, followed by the black symbol 1 (1.59±0.65) with an orange background. The black symbol 2 (1.59±0.59) with a yellow background and the black symbol 3 (1.58±0.52) with an orange background had the low signal intensity with slight differences as for the radiation zone symbols. In conclusion, it was determined that the signal intensity of the black symbol with a yellow background was the highest in the magnetic field area and radiation area. This implies that symbols with a high signal intensity (SI) must be utilized intensively. To ensure that the correct meaning of the symbols is communicated in the future, they must also be utilized regularly and continually in disaster safety education.

• Journal of the Korea Institute of Construction Safety
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• v.5 no.1
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• pp.1-8
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• 2023

The purpose of this study is to suggest a way to solve the excessive paperwork of safety managers in domestic construction sites, and to suggest a work efficiency plan that can shorten the time required to prevent safety accidents. First, a function to automatically generate a safety document and find the necessary data is applied using the RPA program. The second is document creation using mobile devices. After safety training, use the Moleil app to keep the training log. Third, to prevent omission of essential safety and health documents, the automatic warning function is activated according to the RPA submission time and sent to the person in charge by e-mail or text. Fourth, the function to find the latest data with high accuracy and speed through 'Google Cloud Search', a search function, was applied.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.24
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• pp.10637-10642
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• 2015

Background: Section 5 of India's tobacco control legislation "Cigarettes and Other Tobacco Products Act (COTPA), 2003"comprehensively prohibits all kinds of tobacco advertisement, promotion and sponsorship (TAPS), but permits advertisments at the point-of-sale (POS) under certain conditions. This provision has been exploited by the tobacco companies to promote their products. Objective: To measure compliance with the provisions of Section 5 of Indian tobacco control legislation (COTPA, 2003) at point of sale. Materials and Methods: A cross-sectional survey using an observation checklist was conducted in 1860 POS across three jurisdictions (Chennai city, District Vadodara and District Mohali) in India. Results: The most common mode of advertisement of tobacco products was product showcasing (51.1%), followed by dangles (49.6%), stickers (33.8%) and boards (27.1%). More than one fourth of POS were found violating legal provisions for displaying advertisement boards in one or other forms (oversized, extended to full body lenth of POS, displayed brandname/packshot and promotional messages). Advertisement boards (16.3%) without health warnings were also found and wherever found, more than 90% health warning were not as per the specification in respect to size, font and background color. Conclusions: Point of sale advertising is aggressively used by the tobacco industry to promote their products. There is an urgent need of effective implementation of a comprehensive ban on tobacco product advertisement, promotion and sponsorship at point of sale.

• Atmosphere
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• v.16 no.4
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• pp.269-278
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• 2006

Extremely hot weathers may cause major weather-related deaths in the summertime. Influences of heat waves on daily mortalities in 6 major cities of South Korea were investigated. Daily deaths at Seoul were exponentially increased with the daily maximum temperature. However, there were regional differences of the temperature dependence on the mortality because of an acclimation effect of inhabitants. The threshold temperature (with respect to daily maximum temperature) at Seoul was found to be about $31^{\circ}C$ provided that it is determined by a two-phase regression model. The meteorological causes of recordable hot summer in late July of 1994 and their impacts on human health were also investigated. Strong surface heating caused by strong insolation under conditions with clear sky and dry surface due to prolonged drought was likely to be closely associated with the extreme hot weather in 1994 in South Korea.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.501-512
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• 2018

We propose Sequential Patient Recruitment Monitoring (SPRM), a new monitoring procedure for patient recruitment in a clinical trial. Based on the sequential probability ratio test using improved stopping boundaries by Woodroofe, the method allows for continuous monitoring of the rate of enrollment. It gives an early warning when the recruitment is unlikely to achieve the target enrollment. The packet data approach combined with the Central Limit Theorem makes the method robust to the distribution of the recruitment entry pattern. A straightforward application of the counting process framework can be used to estimate the probability to achieve the target enrollment under the assumption that the current trend continues. The required extension of the recruitment period can also be derived for a given confidence level. SPRM is a new, continuous patient recruitment monitoring tool that provides an opportunity for corrective action in a timely manner. It is suitable for the modern, centralized data management environment and requires minimal effort to maintain. We illustrate this method using real data from two well-known, multicenter, phase III clinical trials.

• Economic and Environmental Geology
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• v.56 no.1
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• pp.65-73
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• 2023

As one of the most vulnerable countries to floods, there should be an increased necessity for accurate and reliable flood forecasting in Indonesia. Therefore, a new prediction model using a machine learning algorithm is proposed to provide daily flood prediction in Indonesia. Data crawling was conducted to obtain daily rainfall, streamflow, land cover, and flood data from 2008 to 2021. The model was built using a Random Forest (RF) algorithm for classification to predict future floods by inputting three days of rainfall rate, forest ratio, and stream flow. The accuracy, specificity, precision, recall, and F1-score on the test dataset using the RF algorithm are approximately 94.93%, 68.24%, 94.34%, 99.97%, and 97.08%, respectively. Moreover, the AUC (Area Under the Curve) of the ROC (Receiver Operating Characteristics) curve results in 71%. The objective of this research is providing a model that predicts flood events accurately in Indonesian regions 3 months prior the day of flood. As a trial, we used the month of June 2022 and the model predicted the flood events accurately. The result of prediction is then published to the website as a warning system as a form of flood mitigation.

• Smart Structures and Systems
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• v.33 no.3
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• pp.227-241
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• 2024

Safety and structural integrity of civil structures, like bridges and buildings, can be substantially enhanced by employing appropriate structural health monitoring (SHM) techniques for timely diagnosis of incipient damages. The information gathered from health monitoring of important infrastructure helps in making informed decisions on their maintenance. This ensures smooth, uninterrupted operation of the civil infrastructure and also cuts down the overall maintenance cost. With an early warning system, SHM can protect human life during major structural failures. A real-time online damage localization technique is proposed using only the vibration measurements in this paper. The concept of the 'Degree of Scatter' (DoS) of the vibration measurements is used to generate a spatial profile, and fractal dimension theory is used for damage detection and localization in the proposed two-phase algorithm. Further, it ensures robustness against environmental and operational variability (EoV). The proposed method works only with output-only responses and does not require correlated finite element models. Investigations are carried out to test the presented algorithm, using the synthetic data generated from a simply supported beam, a 25-storey shear building model, and also experimental data obtained from the lab-level experiments on a steel I-beam and a ten-storey framed structure. The investigations suggest that the proposed damage localization algorithm is capable of isolating the influence of the confounding factors associated with EoV while detecting and localizing damage even with noisy measurements.

• East Asian Journal of Business Economics (EAJBE)
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• v.2 no.4
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• pp.48-55
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• 2014

Indian railways has been regularly in the news albeit for the wrong reasons. The frequency with which train accidents have been taking place has led to serious doubts in the public mind about the safety of rail travel and also the health of the network. Against this background, an attempt is made in this paper to assess the trends in railway accidents for the period from 2000-01 to 2009-10. The paper also highlighted the various measures taken by IR to prevent accidents to ensure safety to the public.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2003.10a
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• pp.319-322
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• 2003

Integrated coastal management (ICM) requires robust indicators that gauge the 'health' of the coast in relation to environmental, social and economic activities. Biological indicators(bio-indicators) offer a signal of the biological condition in an ecosystem. Using bio-indicators as an early warning of pollution or degradation in an ecosystem can help sustain critical resources. This review examines the rationale and value of selecting species as bio-indicators of human induced changes within estuaries, using examples from both the western and southern coast. It include a range of biological parameters relating to particular species, groups of species and biological processes. The use of these indicators is critically reviewed and the presence or absence of a relevant framework for their use in Korean ICM programs is discussed.