• 한국멀티미디어학회논문지
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• 제25권3호
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• pp.510-518
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• 2022

This paper confirmed the technical reliability of mobile-based sarcopenia prediction and monitoring system. In implementing the developed system, we designed using only sensors built into a smartphone without a separate external device. The prediction system predicts the possibility of sarcopenia without visiting a hospital by performing the SARC-F survey, the 5-time chair stand test, and the rapid tapping test. The Monitoring system tracks and analyzes the average walking speed in daily life to quickly detect the risk of sarcopenia. Through this, it is possible to rapid detection of undiagnosed risk of undiagnosed sarcopenia and initiate appropriate medical treatment. Through prediction and monitoring system, the user may predict and manage sarcopenia, and the developed system can have a positive effect on reducing medical demand and reducing medical costs. In addition, collected data is useful for the patient-doctor communication. Furthermore, the collected data can be used for learning data of artificial intelligence, contributing to medical artificial intelligence and e-health industry.

• 한국인터넷방송통신학회논문지
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• 제15권6호
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• pp.311-319
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• 2015

본 논문에서는 산업공장 내의 생산 효율을 높이기 위하여 제조공정 자원을 예측하고 위험 관리를 효율적으로 이행하는 자원예측 및 위험관리를 위한 의사결정 시스템을 제안하였다. 각 공정에서 발생되는 다양한 정보들을 효율적으로 관리하는 세부 공정별 시나리오 생성이 어렵고, 동일한 공정 내에서도 다양한 제품의 생산하기 위해 제조 설비의 조건 변경이 빈번하다. 제품의 생산 주기 또한 일정하지 않아 연속되지 않은 데이터가 발생하여 소량의 데이터로 변동을 확인해야 하는 문제점이 있다. 이러한 문제점을 해결하기 위해서는 제조공정의 데이터 일원화, 공정 자원 예측, 위험 예측, 공정 현황 모니터링을 통하여 문제 발생시 즉각 조치가 가능하여야 한다. 본 논문에서는 설계도면 변경 범위, 자원 예측, 공정 완료 예정일을 회귀알고리즘을 이용하여 수식을 도출하였으며, 분류 트리 기법, 경계값 분석을 통하여 3단계로 의사결정 시스템을 제안하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.3039-3056
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• 2020

Beaches have many risk factors that cause various accidents, such as drifting and drowning, these accidents have many risk factors. To analyze them, in this paper, we identify beach risk factors, and define the criteria and correlation for each risk factor. Then, we generate new risk factors based on Fuzzy theory, and define Situation Awareness for each time. Finally, we propose a beach risk assessment and prediction model based on linear regression using the calculated risk result and pre-defined risk factors. We use national public data of the Korea Meteorological Administration (KMA), and the Korea Hydrographic and Oceanographic Agency (KHOA). The results of the experiment showed the prediction accuracy of beach risk to be 0.90%, and the prediction accuracy of drifting and drowning accidents to be 0.89% and 0.86%, respectively. Also, through factor correlation analysis and risk factor assessment, the influence of each of the factors on beach risk can be confirmed. In conclusion, we confirmed that our proposed model can assess and predict beach risks.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2007년도 춘계학술발표회 논문집
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• pp.371-374
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• 2007

For development of landslide risk assessment techniques using GIS(Geographic Information System), this study classifies the category of socioeconomic factors. The landslide quantitative risk assessment performs first prediction of flow trajectory and runout distance of debris flow over natural terrain. Based on those results, it can be analyzed the factors of socioeconomic which are directly related to the magnitude of risk due to landslide hazards. Those risk assessment results can deliver factual damage situation prediction to policy making for the landslide damage mitigation. Therefore, this study is based on feature classification of the digital map ver. 2.0 provided by the National Geographic Information Institute. The category of factors can be used as useful data in preventing landslide.

• Journal of Multimedia Information System
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• 제8권3호
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• pp.183-190
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• 2021

In this paper, we implement a system for a fund recommendation based on the investment propensity and for a future fund price prediction. The investment propensity is classified by scoring user responses to series of questions. The proposed system recommends the funds with a suitable risk rating to the investment propensity of the user. The future fund prices are predicted by Prophet model which is one of the machine learning methods for time series data prediction. Prophet model predicts future fund prices by learning the parameters related to trend changes. The prediction by Prophet model is simple and fast because the temporal dependency for predicting the time-series data can be removed. We implement web pages for the fund recommendation and for the future fund price prediction.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2007년도 정기 학술대회 논문집
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• pp.295-300
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• 2007

Probabilistic Risk Assessment considering statistically random variables is performed for the preliminary design of a Arch Bridge. Component reliabilities of girders have been evaluated using the response surfaces of the design variables at the selected critical sections based on the maximum shear and negative moment locations. Response Surface Method (RSM) is successfully applied for reliability analyses for this relatively small probability of failure of the complex structure, which is hard to be obtained by Monte-Carlo Simulations or by First Order Second Moment Method that can not easily calculate the derivative terms of implicit limit state functions. For the analysis of system reliability, parallel resistance system composed of girders is changed into parallel series connection system. The upper and lower probabilities of failure for the structural system have been evaluated and compared with the suggested prediction method for the combination of failure modes. The suggested prediction method for the combination of failure modes reveals the unexpected combinations of element failures in significant]y reduced time and efforts compared with the previous permutation method or system reliability analysis method.

• Asian Pacific Journal of Cancer Prevention
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• 제14권1호
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• pp.595-598
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• 2013

Background: Lung cancer is the leading cause of cancer death worldwide Therefore, identification of genetic as well as environmental factors is very important in developing novel methods of lung cancer prevention. However, this is a multi-layered problem. Therefore a lung cancer risk prediction system is here proposed which is easy, cost effective and time saving. Materials and Methods: Initially 400 cancer and non-cancer patients' data were collected from different diagnostic centres, pre-processed and clustered using a K-means clustering algorithm for identifying relevant and non-relevant data. Next significant frequent patterns are discovered using AprioriTid and a decision tree algorithm. Results: Finally using the significant pattern prediction tools for a lung cancer prediction system were developed. This lung cancer risk prediction system should prove helpful in detection of a person's predisposition for lung cancer. Conclusions: Most of people of Bangladesh do not even know they have lung cancer and the majority of cases are diagnosed at late stages when cure is impossible. Therefore early prediction of lung cancer should play a pivotal role in the diagnosis process and for an effective preventive strategy.

• 한국안전학회지
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• 제21권6호
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• pp.74-81
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• 2006

Probabilistic Risk Assessment considering statistically random variables is performed for the preliminary design of a Arch Bridge. Component reliabilities of girders have been evaluated using the response surfaces of the design variables at the selected critical sections based on the maximum shear and negative moment locations. Response Surface Method(RSM) is successfully applied for reliability analyses for this relatively small probability of failure of the complex structure, which is hard to be obtained by Monte-Carlo Simulations or by First Order Second Moment Method that can not easily calculate the derivative terms of implicit limit state functions. For the analysis of system reliability, parallel resistance system composed of girders is changed into parallel series connection system. The upper and lower probabilities of failure for the structural system have been evaluated and compared with the suggested prediction method for the combination of failure modes. The suggested prediction method for the combination of failure modes reveals the unexpected combinations of element failures in significantly reduced time and efforts compared with the previous permutation method or system reliability analysis method.

• Journal of Ship and Ocean Technology
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• 제4권4호
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• pp.19-33
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• 2000

For the prevention of marine accidents based on human factor, the risk assessment analysis procedure is proposed which consists of (1) the structural analysis of marine accident, (2) the estimation of incidence probability based on the Fault Tree analysis, (3) the prediction of ef-fectiveness to reduced the accident risk by suitable countermeasures in the specified functional system, and (4) the risk assessment by means of minimizing of the total cost expectation and the background risk. As a practical example, the risk assessment analysis for preventing is investigated using the proposed method.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2001년도 봄 학술발표회 논문집
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• pp.493-500
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• 2001

The construction of bored tunnels in soft ground inevitably causes ground movements. In the urban environment these may be of particular significance, because of their influence on buildings, other tunnels and services. The prediction of ground movements and the assessment of the potential effects on the structures is therefore an essential aspect of planning, design and construction of a tunnelling project in the urban environment. In this study, to minimize the effect of tunnelling-Induced ground movements on the adjacent structures, a system for tile settlement risk management was developed. The GIS based risk assessment system for adjacent structures developed in this study consists of several modules such as building information module, settlement evaluation module, potential risk assessment module for adjacent structures, and analysis module for monitoring data. This system focuses on controlling and managing construction processes that may lead to settlement In the surrounding buildings and can contribute to producing the optimum technical and economic design.