Life quality index for the estimation of societal willingness-to-pay for safety

The engineering and management of human safety is an important societal objective that includes extensive efforts by governments, both legislative and administrative, to enhance the health and safety of the public. Although the achievement of safety goals depend primarily on individuals and organizations responsible for safety, much support is drawn from expertise in diverse scientific and engineering disciplines. The activities range from structural safety (dams, tunnels, bridges to tall buildings) to safe operation of hazardous industrial installations (energy generation facilities, LNG terminals, petrochemical plants) to transportation systems (airline, rail, car safety) to technologies designed to minimize adverse impacts on the environment. All these activities are crucially concerned with risk: with the likelihood and the probable effects of various measures on life and health. We have developed a unified rationale and a clear basis for effective strategic management of risk across diverse sectors. Safety is an important objective in society but it is not the only one. The allocation of society's resources devoted to safety must be continually appraised in light of competing needs, because there is a limit on the resources that can be expended to extend life. The paper presents the Life Quality Index (LQI) as a tool for the assessment of risk reduction initiatives that would support the public interest and enhance safety and quality of life. The paper provides an intuitive reformulation of the LQI as equivalent to a valid utility function that is consistent with the principles of rational decision analysis. The LQI is further refined to consider the issues of discounting of life years, competing background risks, and population age and mortality distribution. The LQI is applied to quantify the societal willingness-to-pay, which is an acceptable level of public expenditure in exchange for a reduction in the risk of death that results in improved life-quality.     

准噶尔盆地边缘山区的初步静校正

本文讨论了准噶尔盆地边缘山区替代速度对初步静校正精度的影响。通过用相遇法[1]从多次覆盖反射地震采集记录中的初至折射波计算基岩面的t0时和选用合适的替代速度进行初步静校正，在很大程度上消除了表层不均匀和基岩面起伏引起的大静校量，使静校误差控制在自动静校的要求范围之内、从而提高了速度谱和水平叠加剖面的质量。     

北京地区膳食摄入^232Th吸收入体液份额f1值的探讨

从北京地区公众成年人~(232)Th 的膳食日食入量,空气日吸入量,以及骨中~(232)Th 的沉积量出发,利用 ICRP 30号报告中参考人的代谢参数和内照射的库室模型,估算了北京地区公众成年人膳食摄入~(232)Th 后经胃肠道向体液转移份额 f_1值。结果表明,对于公众中成年人0.005是 f_1值的合适代表值,是 ICRP 30号报告推荐值 f_1=0.0002的25倍。虽然 ICRP 推荐值并不用于公众,但可以对群体有所了解;而北京地区从实测数据资料出发导出的 f_1值可能是更适于公众的。     

对供电损失率变动规律的分析与预测

通过对历史统计资料的研究,揭示出了供电损失率变动的基本趋势,得出预测的数学模型,同时也获得一种简捷计算供电损失率理论值的方法,便于从宏观角度掌握供电损失率,也可为供电损失管理部门决策提供参考。     

The philosophical technologies

The thesis of this paper is that ethics and action theory are the two philosophical branches of technology. The reason is that they, just like mechanical engineering and management science, are concerned with human action. But of course there are differences between the philosophical technologies and the others, among them their degree of generality. An example from ethics and another from praxiology are discussed, to show that these disciplines can be just as exact and relevant to real contemporary life as electrical engineering and law. Finally, some consequences for the classification of technologies and for the design of academic curricula are drawn.     

无线传感器网络簇内实时数据融合研究

现有的无线传感器网络数据融合技术存在数据延迟和数据正确性两方面的问题。针对该问题设计一种基于簇内实时数据融合的方法．该方法首先通过量化计算将数据划分为紧急数据和非紧急数据并作标记,将紧急数据迅速融合传给用户以提高实时性。在融合过程中引入传感器测量修正并结合关系矩阵法对数据进行相应的融合处理．然后对融合结果进行分析并进行反馈调整。仿真实验结果表明．该方法能够提高簇内实时数据融合正确性并且降低数据延迟．     

一个高性能Key/Value数据库XDB的设计与实现

传统SQL数据库在管理大数据、性能和扩展性等方面的不足使得其不能胜任如大规模数据挖掘、商务智能及社交网络等应用场景,而NoSQL数据库由于其在上述应用领域优良的特性近年来得到很快发展。本文在分析现有开源NoSQL数据库产品Kyoto Cabinet和Tair的不足基础上,设计并实现了一个高性能的Key/Value数据库XDB。XDB分段流水并发处理Key/Value请求,并采用一致性算法保证在并发环境中对Key/Value记录读写的相关性,在随机写入和顺序写入实验中,相比于Kyoto Cabinet,XDB的性能分别提高6倍和15倍。     

Exploring the dynamic model of the returns from value stocks and growth stocks using time series mining

This study considered that value stocks and growth stocks are 2-dimensional concepts. We defined the book-to-market ratio as the value factor and the return on equity as the growth factor. We used these 2 factors to divide stocks into 4 types: high-value, low-value, high-growth, and low-growth stocks. Furthermore, we explored the change in stock prices and stock returns for these 4 categories before and after the formation of investment portfolios. We also established a dynamic model showing the returns from value stocks and growth stocks, called the exponential decay model. Finally, we used Taiwan Stock Exchange data to examine effectiveness of the model during the period from 1995 to 2009. The results are as follows: first, high-value stocks and low-value stocks exhibit a significantly over-reacting phenomenon. Second, high-growth stocks and low-growth stocks exhibit an obviously under-reacting phenomenon. Third, in each current quarter, high-value stocks exhibit the lowest returns; however, in the subsequent quarter, they have the highest returns, and then demonstrate a slow declining trend in the following quarters. These results showed that the stock market can exhibit a dramatic response to extraordinary information and proved that the stock market requires considerable time to correct themselves from an excessive reaction, thus high-value stocks exhibited a higher return. Fourth, in each current quarter, high-growth stocks had the highest return, followed by a rapidly decreasing trend in the following quarters. The t + 3 quarter returns were lower than those of low-growth stocks. This result demonstrated that the stock market does not exhibit an adequate reaction, but still remains rather efficient for routine financial information. Finally, regardless of value stocks or growth stocks, exponential decay models could accurately match with the data.