Measuring the social value of nuclear energy using contingent valuation methodology

As one of the promising energy sources for the next few decades, nuclear energy receives more attention than before as environmental issues become more important and the supply of fossil fuels becomes unstable. One of the reasons for this attention is based on the rapid innovation of nuclear technology which solves many of its technological constraints and safety issues. However, regardless of these rapid innovations, social acceptance for nuclear energy has been relatively low and unchanged. Consequently, the social perception has often been an obstacle to the development and execution of nuclear policy requiring enormous subsidies which are not based on the social value of nuclear energy. Therefore, in this study, we estimate the social value of nuclear energy-consumers’ willingness-to-pay for nuclear energy—using the Contingent Valuation Method (CVM) and suggest that the social value of nuclear energy increases approximately 68.5% with the provision of adequate information about nuclear energy to the public. Consequently, we suggest that the social acceptance management in nuclear policy development is important along with nuclear technology innovation

Measuring the role of technology-push and demand-pull in the dynamic development of the semiconductor industry: The case of the global DRAM marke

This paper reexamines and resolves the long dispute over the source of technological innovation by suggesting an integrated technology-push and demand-pull model. We derive an equilibrium model within the framework of differentiated product analysis and explain the dynamic interaction between these two sources of innovation. Based on the empirical analysis of the global DRAM market, we show that the relative importance of technology-push and demandpull in technological innovation is described by an L-type curve which describes the phenomenon where technology-push is greater than demand-pull in the early stages and then decreases as demand-pull becomes greater. Our finding suggests that the role of supply and demand is different in inducing technological change and their relative importance changes with product development over the technological life cycle; the marginal prices of products are an important factor in determining the principal forces of technological innovation between these two source s.sources of technological innovation, technology-push, demand-pull, Nash equilibrium of technological innovation, DRAM

Copula-Based Approach to Synthetic Population Generation

<div><p>Generating synthetic baseline populations is a fundamental step of agent-based modeling and simulation, which is growing fast in a wide range of socio-economic areas including transportation planning research. Traditionally, in many commercial and non-commercial microsimulation systems, the iterative proportional fitting (IPF) procedure has been used for creating the joint distribution of individuals when combining a reference joint distribution with target marginal distributions. Although IPF is simple, computationally efficient, and rigorously founded, it is unclear whether IPF well preserves the dependence structure of the reference joint table sufficiently when fitting it to target margins. In this paper, a novel method is proposed based on the copula concept in order to provide an alternative approach to the problem that IPF resolves. The dependency characteristic measures were computed and the results from the proposed method and IPF were compared. In most test cases, the proposed method outperformed IPF in preserving the dependence structure of the reference joint distribution.</p></div

Lonicera vidalii Franch. et Savat.

原著和名: オニヘウタンボク科名: スイカズラ科 = Caprifoliaceae採集地: 長野県 北佐久郡 軽井沢町西部 (信濃 北佐久郡 軽井沢町西部)採集日: 1984/5/23採集者: 萩庭丈壽整理番号: JH022209国立科学博物館整理番号: TNS-VS-97220

Collection view of CBJF (Partition lines are for the example in Table 1).

<p>Collection view of CBJF (Partition lines are for the example in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0159496#pone.0159496.t001" target="_blank">Table 1</a>).</p

Dependency measures for synthetic ED patient populations.

<p>Dependency measures for synthetic ED patient populations.</p

Reference joint types in the test set.

<p>(a) Bivariate normal, (b) Bimodal, (c) Lower tail dependence, (d) U-shape, (e) Circle.</p

Mapping <i>x</i>^(<i>k</i>) to .

<p>Mapping <i>x</i>^(<i>k</i>) to .</p