• Title/Summary/Keyword: Product Risk Management

Search Result 323, Processing Time 0.022 seconds

The Effect of External PEEP on Work of Breathing in Patients with Auto-PEEP (Auto-PEEP이 존재하는 환자에서 호흡 일에 대한 External PEEP의 효과)

  • Chin, Jae-Yong;Lim, Chae-Man;Koh, Youn-Suck;Park, Pyung-Whan;Choi, Jong-Moo;Lee, Sang-Do;Kim, Woo-Sung;Kim, Dong-Soon;Kim, Won-Dong
    • Tuberculosis and Respiratory Diseases
    • /
    • v.43 no.2
    • /
    • pp.201-209
    • /
    • 1996
  • Background : Auto-PEEP which develops when expiratory lung emptying is not finished until the beginning of next inspiration is frequently found in patients on mechanical ventilation. Its presence imposes increased risk of barotrauma and hypotension, as well as increased work of breathing (WOB) by adding inspiratory threshold load and/or adversely affecting to inspiratory trigger sensitivity. The aim of this study is to evaluate the relationship of auto-PEEP with WOB and to evaluate the effect of PEEP applied by ventilator (external PEEP) on WOB in patients with auto-PEEP. Method : 15 patients, who required mechanical ventilation for management of acute respiratory failure, were studied. First, the differences in WOB and other indices of respiratory mechanics were examined between 7 patients with auto-PEEP and 8 patients without auto-PEEP. Then, we applied the 3 cm $H_2O$ of external PEEP to patients with auto-PEEP and evaluated its effects on lung mechanics as well as WOB. Indices of respiratory mechanics including tidal volume ($V_T$), repiratory rate, minute ventilation ($V_E$), peak inspiratory flow rate (PIFR), peak expiratory flow rate (PEFR), peak inspiratory pressure (PIP), $T_I/T_{TOT}$, auto-PEEP, dynamic compliance of lung (Cdyn), expiratory airway resistance (RAWe), mean airway resistance (RAWm), $p_{0.1}$, work of breathing performed by patient (WOB), and pressure-time product (PTP) were obtained by CP-100 Pulmonary Monitor (Bicore, USA). The values were expressed as mean $\pm$ SEM (standard error of mean). Results : 1) Comparison of WOB and other indices of respiratory mechanics in patients with and without auto-PEEP : There was significant increase in WOB ($l.71{\pm}0.24$ vs $0.50{\pm}0.19\;J/L$, p=0.007), PTP ($317{\pm}70$ vs $98{\pm}36\;cm$ $H_2O{\cdot}sec/min$, p=0.023), RAWe ($35.6{\pm}5.7$ vs $18.2{\pm}2.3\;cm$ H2O/L/sec, p=0.023), RAWm ($28.8{\pm}2.5$ vs $11.9{\pm}2.0cm$ H2O/L/sec, p=0.001) and $P_{0.1}$ ($6.2{\pm}1.0$ vs 2.9+0.6 cm H2O, p=0.021) in patients with auto-PEEP compared to patients without auto-PEEP. The differences of other indices including $V_T$, PEFR, $V_E$ and $T_I/T_{TOT}$ showed no significance. 2) Effect of 3 cm $H_2O$ external PEEP on respiratory mechanics in patients with auto-PEEP : When 3 cm $H_2O$ of external PEEP was applied, there were significant decrease in WOB ($1.71{\pm}0.24$ vs $1.20{\pm}0.21\;J/L$, p=0.021) and PTP ($317{\pm}70$ vs $231{\pm}55\;cm$ $H_2O{\cdot}sec/min$, p=0.038). RAWm showed a tendency to decrease ($28.8{\pm}2.5$ vs $23.9{\pm}2.1\;cm$ $H_2O$, p=0.051). But PIP was increased with application of 3 cm $H_2O$ of external PEEP ($16{\pm}2$ vs $22{\pm}3\;cm$ $H_2O$, p=0.008). $V_T$, $V_E$, PEFR, $T_I/T_{TOT}$ and Cdyn did not change significantly. Conclusion : The presence of auto-PEEP in mechanically ventilated patients was accompanied with increased WOB performed by patient, and this WOB was decreased by 3 cm $H_2O$ of externally applied PEEP. But, with 3 cm $H_2O$ of external PEEP, increased PIP was noted, implying the importance of close monitoring of the airway pressure during application of external PEEP.

  • PDF

International Monetary System Reform and the G20 (국제통화제도의 개혁과 G20)

  • Cho, Yoon Je
    • KDI Journal of Economic Policy
    • /
    • v.32 no.4
    • /
    • pp.153-195
    • /
    • 2010
  • The recent global financial crisis has been the outcome of, among other things, the mismatch between institutions and the reality of the market in the current global financial system. The International financial institutions (IFIs) that were designed more than 60 years ago can no longer effectively meet the challenges posed by the current global economy. While the global financial market has become integrated like a single market, there is no international lender of last resort or global regulatory body. There also has been a rapid shift in the weight of economic power. The share of the Group of 7 (G7) countries in global gross domestic product (GDP) fell and the share of emerging market economies increased rapidly. Therefore, the tasks facing us today are: (i) to reform the IFIs -mandate, resources, management, and governance structure; (ii) to reform the system such as the international monetary system (IMS), and regulatory framework of the global financial system; and (iii) to reform global economic governance. The main focus of this paper will be the IMS reform and the role of the Group of Twenty (G20) summit meetings. The current IMS problems can be summarized as follows. First, the demand for foreign reserve accumulation has been increasing despite the movement from fixed exchange rate regimes to floating rate regimes some 40 years ago. Second, this increasing demand for foreign reserves has been concentrated in US dollar assets, especially public securities. Third, as the IMS relies too heavily on the supply of currency issued by a center country (the US), it gives an exorbitant privilege to this country, which can issue Treasury bills at the lowest possible interest rate in the international capital market. Fourth, as a related problem, the global financial system depends too heavily on the center country's ability to maintain the stability of the value of its currency and strength of its own financial system. Fifth, international capital flows have been distorted in the current IMS, from EMEs and developing countries where the productivity of capital investment is higher, to advanced economies, especially the US, where the return to capital investment is lower. Given these problems, there have been various proposals to reform the current IMS. They can be grouped into two: demand-side and supply-side reform. The key in the former is how to reduce the widespread strong demand for foreign reserve holdings among EMEs. There have been several proposals to reduce the self-insurance motivation. They include third-party insurance and the expansion of the opportunity to borrow from a global and regional reserve pool, or access to global lender of last resort (or something similar). However, the first option would be too costly. That leads us to the second option - building a stronger globalfinancial safety net. Discussions on supply-side reform of the IMS focus on how to diversify the supply of international reserve currency. The proposals include moving to a multiple currency system; increased allocation and wider use of special drawing rights (SDR); and creating a new global reserve currency. A key question is whether diversification should be encouraged among suitable existing currencies, or if it should be sought more with global reserve assets, acting as a complement or even substitute to existing ones. Each proposal has its pros and cons; they also face trade-offs between desirability and political feasibility. The transition would require close collaboration among the major players. This should include efforts at the least to strengthen policy coordination and collaboration among the major economies, and to reform the IMF to make it a more effective institution for bilateral and multilateral surveillance and as an international lender of last resort. The success on both fronts depends heavily on global economic governance reform and the role of the G20. The challenge is how to make the G20 effective. Without institutional innovations within the G20, there is a high risk that its summits will follow the path of previous summit meetings, such as G7/G8.

  • PDF

The Prediction of DEA based Efficiency Rating for Venture Business Using Multi-class SVM (다분류 SVM을 이용한 DEA기반 벤처기업 효율성등급 예측모형)

  • Park, Ji-Young;Hong, Tae-Ho
    • Asia pacific journal of information systems
    • /
    • v.19 no.2
    • /
    • pp.139-155
    • /
    • 2009
  • For the last few decades, many studies have tried to explore and unveil venture companies' success factors and unique features in order to identify the sources of such companies' competitive advantages over their rivals. Such venture companies have shown tendency to give high returns for investors generally making the best use of information technology. For this reason, many venture companies are keen on attracting avid investors' attention. Investors generally make their investment decisions by carefully examining the evaluation criteria of the alternatives. To them, credit rating information provided by international rating agencies, such as Standard and Poor's, Moody's and Fitch is crucial source as to such pivotal concerns as companies stability, growth, and risk status. But these types of information are generated only for the companies issuing corporate bonds, not venture companies. Therefore, this study proposes a method for evaluating venture businesses by presenting our recent empirical results using financial data of Korean venture companies listed on KOSDAQ in Korea exchange. In addition, this paper used multi-class SVM for the prediction of DEA-based efficiency rating for venture businesses, which was derived from our proposed method. Our approach sheds light on ways to locate efficient companies generating high level of profits. Above all, in determining effective ways to evaluate a venture firm's efficiency, it is important to understand the major contributing factors of such efficiency. Therefore, this paper is constructed on the basis of following two ideas to classify which companies are more efficient venture companies: i) making DEA based multi-class rating for sample companies and ii) developing multi-class SVM-based efficiency prediction model for classifying all companies. First, the Data Envelopment Analysis(DEA) is a non-parametric multiple input-output efficiency technique that measures the relative efficiency of decision making units(DMUs) using a linear programming based model. It is non-parametric because it requires no assumption on the shape or parameters of the underlying production function. DEA has been already widely applied for evaluating the relative efficiency of DMUs. Recently, a number of DEA based studies have evaluated the efficiency of various types of companies, such as internet companies and venture companies. It has been also applied to corporate credit ratings. In this study we utilized DEA for sorting venture companies by efficiency based ratings. The Support Vector Machine(SVM), on the other hand, is a popular technique for solving data classification problems. In this paper, we employed SVM to classify the efficiency ratings in IT venture companies according to the results of DEA. The SVM method was first developed by Vapnik (1995). As one of many machine learning techniques, SVM is based on a statistical theory. Thus far, the method has shown good performances especially in generalizing capacity in classification tasks, resulting in numerous applications in many areas of business, SVM is basically the algorithm that finds the maximum margin hyperplane, which is the maximum separation between classes. According to this method, support vectors are the closest to the maximum margin hyperplane. If it is impossible to classify, we can use the kernel function. In the case of nonlinear class boundaries, we can transform the inputs into a high-dimensional feature space, This is the original input space and is mapped into a high-dimensional dot-product space. Many studies applied SVM to the prediction of bankruptcy, the forecast a financial time series, and the problem of estimating credit rating, In this study we employed SVM for developing data mining-based efficiency prediction model. We used the Gaussian radial function as a kernel function of SVM. In multi-class SVM, we adopted one-against-one approach between binary classification method and two all-together methods, proposed by Weston and Watkins(1999) and Crammer and Singer(2000), respectively. In this research, we used corporate information of 154 companies listed on KOSDAQ market in Korea exchange. We obtained companies' financial information of 2005 from the KIS(Korea Information Service, Inc.). Using this data, we made multi-class rating with DEA efficiency and built multi-class prediction model based data mining. Among three manners of multi-classification, the hit ratio of the Weston and Watkins method is the best in the test data set. In multi classification problems as efficiency ratings of venture business, it is very useful for investors to know the class with errors, one class difference, when it is difficult to find out the accurate class in the actual market. So we presented accuracy results within 1-class errors, and the Weston and Watkins method showed 85.7% accuracy in our test samples. We conclude that the DEA based multi-class approach in venture business generates more information than the binary classification problem, notwithstanding its efficiency level. We believe this model can help investors in decision making as it provides a reliably tool to evaluate venture companies in the financial domain. For the future research, we perceive the need to enhance such areas as the variable selection process, the parameter selection of kernel function, the generalization, and the sample size of multi-class.