医疗损害风险的相关分析和因子分析

近年来,医疗纠纷的数量呈现逐年上升的趋势,已经明显干扰了医院的正常秩序。如何分析和把握医疗纠纷形成的原因及其相互作用,对能否有效干预医疗纠纷至关重要。着重讨论由于医院方面的失误导致纠纷发生的原因,试图通过较大样本量的调查分析,总结符合客观情况的一般规律,为避免或减少纠纷提供参考。

水库工程PM项目管理风险及应对方法研究

项目管理(PM)是水库工程建设重点模式,将其用于水库风险管理及防范控制,有助于实现水库管理与改造一体化建设。结合工程案例,水库PM项目管理分析及控制方法进行研究。

Quantitative risk assessment & leak detection criteria for a subsea oil export pipeline

A quantitative risk assessment （QRA） based on leak detection criteria （LDC） for the design of a proposed subsea oil export pipeline is presented in this paper. The objective of this QRA/LDC study was to determine if current leak detection methodologies were sufficient, based on QRA results, while excluding the use of statistical leak detection; if not, an appropriate LDC for the leak detection system would need to be established. The famous UK PARLOC database was used for the calculation of pipeline failure rates, and the software POSVCM from MMS was used for oil spill simulations. QRA results revealed that the installation of a statistically based leak detection system （LDS） can significantly reduce time to leak detection, thereby mitigating the consequences of leakage. A sound LDC has been defined based on QRA study results and comments from various LDS vendors to assist the emergency response team （ERT） to quickly identify and locate leakage and employ the most effective measures to contain damage.

Comprehensive Risk Analysis of Storm Surge Flood Based on WebGIS

The comprehensive risk analysis of storm surge flood is vital to the safety management of sea embank- ment, the scientific assessment of storm surge disaster and the improvement of emergent treatment in storm surge haz- ard. Based on the research of disaster-causing, disaster-pregnant and disaster-bearing factors, the influencing factors of storm surge risk are concluded to be flood natural risk, embankment position, embankment width and height. The membership degree of the factors of stoma surge risk is firstly determined by storm surge flood evolution based on WebGIS, and the comprehensive risk membership and risk grade of each influencing factor are obtained. Then the effects of a single factor on comprehensive risk and sensitivity analysis are discussed, and the storm surge flood risk map is obtained. Finally, the storm surge of Tianjin Binhai New Area is taken as a case. The results show that the in- fluencing degree of the factors on the comprehensive risk membership is in decreasing order of flood natural risk, em- bankment position, embankment width and height. The flood risk map of the case is drawn, which is useful to decrease losses caused by storm surge disaster.

Rough Outlier Detection Based Security Risk Analysis Methodology

Security is a nonfunctional information system attribute that plays a crucial role in wide sensor network application domains. Security risk can be quantified as the combination of the probability that a sensor network system may fail and the evaluation of the severity of the damage caused by the failure. In this paper, we devise a methodology of Rough Outlier Detection (ROD) for the detection of security-based risk factor, which originates from violations of attack requirements (namely, attack risks). The methodology elaborates dimension reduction method to analyze the attack risk probability from high dimensional and nonlinear data set, and combines it with rough redundancy reduction and the distance measurement of kernel function which is obtained using the ROD. In this way, it is possible to determine the risky scenarios, and the analysis feedback can be used to improve the sensor network system design. We illustrate the methodology in the DARPA case set study using step-by-step approach and then prove that the method is effective in lowering the rate of false alarm.

Prediction model of in-hospital mortality in elderly patients with acute heart failure based on retrospective study

Objectives The aim of this study was to develop a clinical risk model that is predictive of in-hospital mortality in elderly patients hos- pitalized with acute heart failure （AHF）. Methods 2486 patients who were 60 years and older from intensive care units of Cardiology De- partment in the hospital were analyzed. Independent risk factors for in-hospital mortality were obtained by binary logistic regression and then used to establish the risk prediction score system （RPSS）. The area under the curve （AUC） of receiver operator characteristic and C-statistic test were adopted to assess the performance of RPSS and to compare with previous get with the guidelines-heart failure （GWTG-HF）. Re- sults By binary logistic regression analysis, heart rate （OR： 1.043, 95% CI： 1.030-1.057, P 〈 0.001）, left ventricular ejection fraction （OR： 0.918, 95% CI： 0.833~）.966, P 〈 0.001）, pH value （OR： 0.001, 95% CI： 0.000-0.002, P 〈 0.001）, renal dysfunction （OR： 0.120, 95% CI： 0.066M）.220, P 〈 0.001） and NT-pro BNP （OR： 3.463, 95% CI： 1.870-6.413, P 〈 0.001） were independent risk factors of in-hospital mortal- ity for elderly AHF patients. Additionally, RPSS, which was composed of all the above-mentioned parameters, provided a better risk predic- tion than GWTG-THF （AUC： 0.873 vs. 0.818, P = 0.016）. Conclusions Our risk prediction model, RPSS, provided a good prediction for in-hospital mortality in elderly patients with A/IF.

Similar financial models： Are they free lunches？

In recent years, the academic and practical circles have paid so much attention to similar financial models because they generated a miracle in GOME （Gome Electrical Appliances Holding Limited） and SUNING （Suning Appliance Co., Ltd.） respectively. But what＇s the influence of such a model on corporate profitability and risk？ Are similar financial models free lunches？ To seek for the answers to the above questions, in this paper, we take Gree （GREE Electric Appliances, Inc. of Zhuhai）, Midea （Guangdong Midea Electric Appliances Co. Ltd. Stores） and GOME for examples to carry out a comprehensive and in depth financial analysis. The conclusions of this paper are： The company with similar financial characteristics has higher profitability and risk level; Only the companies which meet special requirements need or can implement such a model and the identification and control of hidden risk can guarantee its success.

Is the 2008 financial turmoil increasing the risk of a bank run？ An empirical research in Geneva

In this paper, the authors present the results of an empirical study that attempts to analyse the risk of bank run in Geneva, Switzerland. Two similar surveys have been conducted upon two independent samples of Geneva population （June 2008 and February 2009） to detect the existence of predictive signals leading to a bank run within the selected area. The authors discover that Geneva inhabitants are generally confident in Swiss banks; the risk of a bank run in the area is low. However, reliance to the national banking system is worsening： The number of people fearing about their savings and those thinking the default of a major Swiss bank as ＂possible＂ has significantly risen. Also, more and more people keep updated about the current financial crisis; overall trust in Swiss banks has slightly decreased.

Risk Factors of Commercial Banks in Malaysia

All kinds of risks exist in the banking industry. In order to cover these exposures, banks must manage these risk factors for better survival in any state of uncertainty. The objective is to examine the relevant risk factors that will affect the sensitivity of commercial banks in Malaysia. These factors are liquidity and interest rate risk, credit risk, market risk, operating and country risk, and exchange rate risk. A survey is conducted to solicit the appropriate factors that will influence the sensitivity of banks. Factor analysis is then used to identify the factors and a regression model is used to establish the associations. The results obtained through this research would be beneficial in constructing an effective solution or strategy to enable banks to minimize risk and possible failure in times of adversity.

Data Mining in Financial Application

Data mining enables us to form forecasts and models regarding future by making use of past data. Any method which helps to discover data can be used as a data mining method. Enterprises gain important competitive advantage by data mining methods. Data mining is used in different fields. In finance field, it is a specially used in portfolio management, fraud detection, payment prediction, loan risk analysis, mortgage scoring, determining transaction manipulation, determining financial risk management, determining customer profile and foreign exchange market. It can be costly, risky and time consuming for enterprises to gain knowledge. Thus today enterprises use data mining as an innovative competitive mean. The aim of the study is to determine the importance of data mining in financial applications.

An optimal incentive contract to venture capitalist

This paper aims to study the principal-agent relationship between investors and venture capitalists （VCs）, makes research on the moral hazard issues under this relationship, and how to design an effective incentive mechanism to avoid it. By constructing a new incentive model, this paper provides the reference for investors to establish a reasonable payment contract. The designed incentive contract is a kind of dominant consecutive payment mode, which plays a strong incentive role to the VCs, in addition, it also requires the VCs to invest certain capital to the project, which can effectively prevent the slapdash action of VCs, and reduce the agent cost of investors.

Cost Risk Appraisal： An Application of Project RiskManagement Process in Libyan Construction Projects

Projects delay and cost overrun have become general facts in the construction industry. Project cost risk analysis considers the different costs associated with a project and focuses on the uncertainties and risks that may affect these costs. An implementation of PRM （project risk management） process on regional construction project has been carried out to maximize the likelihood of project meeting its objectives within its constraints. Qualitative and quantitative risk analyses have been carried out. The qualitative analysis is presented in a table that shows top ranked risks in Libyan construction projects based on probability-impact grid technique. In quantitative risk analyses, Mont Carlo simulation technique has been conducted to quantify and evaluate the overall level of risk exposure associated with the project completion cost. A project simulation uses a model that translates cost uncertainties into their potential impact on project objectives. A frequency curve model that represents simulation results of project completion costs has been constructed. The frequency curve model shows all possible outcomes of expected project cost at different probabilities. Project manager or decision maker can select the appropriate project budget. If a probability of 0.95 confident project budget is selected that means cost overrun risk can be minimized to a probability of 0.05. It is very helpful for project manager to take decisions based on information that shows project completion cost and its associated probability rather than usin single information of estimated cost.

Safety of Dams： A Pathological Approach of Qualitative and Quantitative Risks

Dams are critical and essential elements in any infrastructure and, in front of accidents occurred in many countries, it is extremely important to know the risk of these structures. Inserted in this context, it was found in the technical literature, methods and tools capable of measuring the exposure value by means of indicators. In the study, the highlights were 12 methods of qualitative, semiquantitative and quantitative risk analysis, representing an overview of risk analysis methods available in the literature with potential use in dams, that it has been done into electronic spreadsheets. The case study is performed on a sample of concrete dam and earth/rockfill built and operated by Eletrobr^s Furnas Company, supported by documentary research, projects, field inspections and interviews with experts. After applying the methods and the analysis thereof, has been prepared the Eletrobras Fumas dam risk analysis method which is characterized by adapting the criteria analyzed to the reality of the company＇s dams and it was also performed the portfolio risk analysis of 18 dams. In spite of the variety and subjectivity of qualitative and semiquantitative methods, the results show that they tend to converge on the analysis of dam based on risk. The application methodology demonstrates the feasibility assessment stage, covering the preliminary analysis for portfolio dams, followed by formal and individual risk analyzes for the most critical structures. These results confirm the applicability of risk analysis techniques, contributing to the consolidation of this toot as fundamental in the dam safety.

The FAHP-based Risk Assessment in the Conclusion of Equipment Procurement Contract

The risk assessment of contract conclusion is the primary and key part of equipment purchase contract risk management. In this paper, based on the fuzzy characteristics of contract risks, and overcoming the traditional disadvantages of analytic hierarchy process （AHP）, the fuzzy analytic hierarchy process （FAHP） of contract conclusion is proposed for meeting the actual need of equipment procurement contract risk assessment, and implementing the risk factors qualitative and quantitative assessments of different working nodes in contract conclusion. Thus, a scientific and reliable important basis is provided for the risk management of equipment procurement contract.

Hazard Model Reliability Analysis Based on a Wind Generator Condition Monitoring System

This paper presents an application of the hazard model reliability analysis on wind generators, based on a condition monitoring system. The hazard model techniques are most widely used in the statistical analysis of the electric machine＇s lifetime data. The model can be utilized to perform appropriate maintenance decision-making based on the evaluation of the mean time to failures that occur on the wind generators due to high temperatures. The knowledge of the condition monitoring system is used to estimate the hazard failure, and survival rates, which allows the preventive maintenance approach to be performed accurately. A case study is presented to demonstrate the adequacy of the proposed method based on the condition monitoring data for two wind turbines. Such data are representative in the generator temperatures with respect to the expended operating hours of the selected wind turbines. In this context, the influence of the generator temperatures on the lifetime of the generators can be determined. The results of the study can be used to develop the predetermined maintenance program, which significantly reduces the maintenance and operation costs.

Risk analysis of dynamic control of reservoir limited water level by considering flood forecast error

Flood control forecast operation mode is one of the main ways for determining the upper bound of dynamic control of flood limited water level during flood season. The floodwater utilization rate can be effectively increased by using flood forecast information and flood control forecast operation mode. In this paper, Dahuofang Reservoir is selected as a case study. At first, the distribution pattern and the bound of forecast error which is a key source of risk are analyzed. Then, based on the definition of flood risk, the risk of dynamic control of reservoir flood limited water level within different flood forecast error bounds is studied. The results show that, the dynamic control of reservoir flood limited water level with flood forecast information can increase the floodwater utilization rate without increasing flood control risk effectively and it is feasible in practice.

Personal Credit Risk .Scoring Model Based on Rough Set and Neural Network

In order to improve the precision of personal credit risk assessment, applying rough set and neural network to the credit risk scoring prediction problem in an attempt to suggest a new model with better classification accuracy. To evaluate the prediction accuracy of the model, we compare its performance with those of SVM, linear discriminate analysis, logistic regression analysis, K-nearest neighbors, classification and regression tree, neural network and PCA-NN. The experimental results show the model have a very good prediction accuracy