• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.163-169
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• 2016

To establish the equitable distribution of total energy load, a representative cluster based routing protocol LEACH selects cluster heads randomly in accordance with the pre-determined probability every round. But because the current energy level of sensor nodes is not considered, if a sensor node which has little residual energy is elected as a cluster head, it can not live to fulfil the role of cluster head which has big energy load. As a result, the first time of death of a node is quickened and the service quality of WSN gets worse. In this regard we propose a new routing method that, by considering the current energy of a cluster head and the distance between cluster heads and a base station, selects the sub cluster head for saving the energy of a cluster head. Simulation results show that the first time of death of a node prolongs, more data arrive at the base station and the service quality of WSN improves.

• Journal of Preventive Medicine and Public Health
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• v.55 no.1
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• pp.1-9
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• 2022

An index that evaluates the health level of a population group considering both death and loss of function due to disease is called a summary measure of population health (SMPH). SMPHs are broadly divided into life year indices and life expectancy indices, the latter of which comprise healthy life expectancy (HLE). HLE is included as a policy target in various national and regional level healthcare plans, and the term "HLE" is commonly used in academia and by the public. However, the overall level of understanding of HLE-such as the precise definition of HLE and methods of calculating HLE-still seems to be low. As discussed in this study, the types of HLE are classified into disability-free life expectancy, disease-free life expectancy, quality-adjusted life expectancy, self-rated HLE, and disability-adjusted life expectancy. Their characteristics are examined to facilitate a correct understanding and appropriate utilization of HLE. In addition, the Sullivan method, as a representative method for calculating HLE, is presented in detail, and major issues in the process of calculating HLE, such as selection of the population group and age group, estimation of death probability, calculation of life years, and incorporation of health weights, are reviewed. This study will help researchers to select an appropriate HLE type and evaluate the validity of HLE research results, and it is expected to contribute to the vitalization of HLE research.

• Journal of Korean Academy of Nursing
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• v.41 no.1
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• pp.92-100
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• 2011

Purpose: Mortality Provability Model (MPM) II is a model for predicting mortality probability of patients admitted to ICU. This study was done to test the validity of MPM II for critically ill neurological patients and to determine applicability of MPM II in predicting mortality of neurological ICU patients. Methods: Data were collected from medical records of 187 neurological patients over 18 yr of age who were admitted to the ICU of C University Hospital during the period from January 2008 to May 2009. Collected data were analyzed through $X^2$ test, t-test, Mann-Whiteny test, goodness of fit test, and ROC curve. Results: As to mortality according to patients' general and clinically related characteristics, mortality was statistically significantly different for ICU stay, hospital stay, APACHE III score, APACHE predicted death rate, GCS, endotracheal intubation, and central venous catheter. Results of Hosmer-Lemeshow goodness-of-fit test were MPM $II_0$ ($X^2$=0.02, p=.989), MPM $II_24$ ($X^2$=0.99 p=.805), MPM $II_48$ ($X^2$=0.91, p=.822), and MPM $II_72$ ($X^2$=1.57, p=.457), and results of the discrimination test using the ROC curve were MPM $II_0$, .726 (p<.001), MPM $II_24$, .764 (p<.001), MPM $II_48$, .762 (p<.001), and MPM $II_72$, .809 (p<.001). Conclusion: MPM II was found to be a valid mortality prediction model for neurological ICU patients.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.6
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• pp.3-12
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• 2019

Current risk assessment methods typically determine accident risks embedded in construction projects by combining severity and frequency; however, they do not reflect the characteristics of construction projects. To solve the problem, this study aims to develop a novel risk assessment method that combines severity, frequency, and disaster influence factors (i.e., weather conditions and worker's characteristics) for assessing risks of activities occurring on a construction site actually. In this study, a severity was estimated by death against victims, and a frequency was estimated by the victim rate. The frequency was then converted to probability taking disaster influence factors into account. Thus, instead of considering severity and frequency for assessing the original risks (RO), the proposed method uses severity and probability to yield adjusted risks (RA) for each activity. A case study was conducted to determine if the proposed method works as intended in a real setting. The results show that RA is more sensitive to disaster influence factors than RO and, therefore, is able to assess the actual risks reflecting the working environment and conditions of a construction site. This study contributes to risk management of construction projects by offering a risk assessment method that measures a possibility of potential disasters from the probabilistic perspective. This method would help project managers assess accident risks in a more systematic and quantitative manner.

• Genomics & Informatics
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• v.17 no.4
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• pp.41.1-41.12
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• 2019

Survival analysis mainly deals with the time to event, including death, onset of disease, and bankruptcy. The common characteristic of survival analysis is that it contains "censored" data, in which the time to event cannot be completely observed, but instead represents the lower bound of the time to event. Only the occurrence of either time to event or censoring time is observed. Many traditional statistical methods have been effectively used for analyzing survival data with censored observations. However, with the development of high-throughput technologies for producing "omics" data, more advanced statistical methods, such as regularization, should be required to construct the predictive survival model with high-dimensional genomic data. Furthermore, machine learning approaches have been adapted for survival analysis, to fit nonlinear and complex interaction effects between predictors, and achieve more accurate prediction of individual survival probability. Presently, since most clinicians and medical researchers can easily assess statistical programs for analyzing survival data, a review article is helpful for understanding statistical methods used in survival analysis. We review traditional survival methods and regularization methods, with various penalty functions, for the analysis of high-dimensional genomics, and describe machine learning techniques that have been adapted to survival analysis.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.1
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• pp.483-488
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• 2014

Aim: This study employed public use National Health and Nutrition Examination Survey (NHANES III) data to investigate the association between urinary cadmium (UDPSI) and all cause, all cancer and prostate cancer mortalities in men. Patients and Methods: NHANES III household adult, laboratory and mortality data were merged. The sampling weight used was WTPFEX6, with SDPPSU6 applied for the probability sampling unit and SDPSTRA6 to designate the strata for the survey analysis. Results: For prostate cancer death, the significant univariates were UDPSI, age, weight, and drinking. Under multivariate logistic regression, the significant covariates were age and weight. For all cause mortality in men, the significant covariates were UDPSI, age, and poverty income ratio. For all cancer mortality in men, the significant covariates were UDPSI, age, black and Mexican race. Conclusions: UDPSI was a predictor of all cause and all cancer mortalities in men as well as prostate cancer mortality.

• Asian Journal of Business Environment
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• v.4 no.1
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• pp.25-35
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• 2014

Purpose - Appropriate project management knowledge as well as its effective application in the construction industry increase construction quality and, therefore, reduce fatalities and destruction. Research design, data, and methodology - This study was conducted through a comparative analysis of earthquake fatalities in Iran, Turkey, Pakistan, Indonesia, China, Haiti, Japan, and the United States of America. The data was analyzed using a frequency study. The analysis contrasts the fatalities of some of the strongest earthquakes around the world between 1960 and 2010. Results - Poor quality construction practices and a lack of effective application of project management knowledge play a major role in the vast destruction, high death toll, and dismal tragedies that are associated with earthquakes, especially in Iran. Conclusions - Despite the history of tragic earthquakes and their continuing recurrence, this study attempts to make governments, companies, and disaster management personnel aware of the dangers of poor quality construction and the deficient application of project management knowledge and, further, accentuates effective ways to prevent the probability of serious damage in future. This study contains valuable information on the effects of project management application towards reducing earthquake fatalities and destruction.

• The Journal of Korean Physical Therapy
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• v.10 no.2
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• pp.161-171
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• 1998

Balance can be defined as the ability to maintain the body's center of gravity within the base of support with minimal sway. Falls occur frequently in the elderly persons by the physiological change and dysfunction with age. Injuries resulting from falls include soft tissue damage and fractures of the radius, humerus, and femoral neck other consequences of falls include decreased mobility, reduced confidence, long lies (which can give rise to hypothermia, dehydration and pneumonia), and death Risk factors for falls have beau classified as intrinsic (those related to the individual) and extrinsic(those associated with environmental features), Intrinsic factors include decreased strength, visual deficits, vestibular dysfunction, and decreased vibratory sensation in the feet. Improvement of the balance related to the increased probability for fells in the elderly persons and is important for fall preventions and improvement of the living quality ef the elderly persons

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.215-220
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• 2013

Recently, death number of heart attack in the world is increasing rapidly. Therefore, to solve these problem, it is trend that is making mandatory automatic defibrillator AED establishment to airport, school, at home. However, AED use in an emergency or equipment failure caused malfunctions if equipped with AED may even become obsolete. In this paper, in order to improve this problem, AED Simulator using the fuzzy simulation technique in comparison to existing methods Tilt ambient temperature conditions and in consideration of the conditions, self-diagnostics, error detection at the time to determine whether the development of intelligent simulation. Moreover, in this paper, it proved that fuzzy AED Simulation improved fault detection probability results 30% more than conventional method.

• Journal of Hospice and Palliative Care
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• v.24 no.3
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• pp.184-193
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• 2021

Purpose: This study attempted to develop clinical guidelines to help patients use hospice and palliative care (HPC) at an appropriate time after writing physician orders for life-sustaining treatment (POLST) by identifying the characteristics of HPC use of patients with terminal cancer. Methods: This retrospective study was conducted to understand the characteristics of HPC use of patients with terminal cancer through decision tree analysis. The participants were 394 terminal cancer patients who were hospitalized at a cancer-specialized hospital in Seoul, South Korea and wrote POLST from January 1, 2019 to March 31, 2021. Results: The predictive model for the characteristics of HPC use showed three main nodes (living together, pain control, and period to death after writing POLST). The decision tree analysis of HPC use by terminal cancer patients showed that the most likely group to use HPC use was terminal cancer patients who had a cohabitant, received pain control, and died 2 months or more after writing a POLST. The probability of HPC usage rate in this group was 87.5%. The next most likely group to use HPC had a cohabitant and received pain control; 64.8% of this group used HPC. Finally, 55.1% of participants who had a cohabitant used HPC, which was a significantly higher proportion than that of participants who did not have a cohabitant (1.7%). Conclusion: This study provides meaningful clinical evidence to help make decisions on HPC use more easily at an appropriate time.