Modeling Power Supply Noise in Delay Testing

Excessive power supply noise during test can cause overkill. This article discusses two models for supply noise in delay testing and their application to test compaction. The proposed noise models avoid complicated power network analysis, making them much faster than existing power noise analysis tools. can cause performance degradation and     

Seya-Nanioka系统真空紫外单色仪的分辨能力及波长读数精度

本文分析了Seya-Namioka系统光学参数与离焦量的关系,为选取最佳光学参数提供了依据。同时,简要说明了影响谱线质量及波长读数精度的因素,并讨论了补偿波长读数误差的方法。     

Guest Editors' Introduction: Attacking Functional Verification through Hybrid Techniques

Hybrid techniques are effective for exploring interesting corner cases, coverage holes, invariant variations, and so forth, in the general area of directed functional validation. However, despite the emergence of several effective hybrid validation techniques, several questions still remain. The five articles in this special issue help explain some of the different facets of this area.     

High-temperature sensible-heat storage options

Alkali-metal carbonate salts meet the requirements for high-temperature solar central receiver systems, but because of their corrosiveness they present special problems in the design of storage tanks. In order to reduce corrosion and temperature sufficiently to retain strength in the storage containing wall, internal and thermal insulation is required. We present design options and operation criteria for sensible-heat, molten-salt storage with internal insulation.     

Data mining of resilience indicators

In recent years, the Asia-Pacific region has experienced several financial setbacks, including speculative attacks in 1998 and the SARS outbreak in 2003. Financial stresses of this nature are unanticipated, and not all of the dangers can be predicted by the examination of market information and macroeconomic indicators. The Early Warning System (EWS) that has been adopted by the International Monetary Fund may not be able to predict future financial crises for all possible scenarios, because shocks come in many different forms. To supplement the EWS, this paper proposes a data mining framework to measure the resilience of an economy. The resilience framework does not predict a crisis, but rather assesses the current state of health of an economy and its ability to withstand a financial shock should one occur. The framework is based on a feedback system consisting of two stages. The first stage assigns a resilience score to each economy based on a fuzzy logic scoring scheme that is built on the ambiguous reasoning of experts. The second stage uses the classification tree approach to estimate thresholds for each economic indicator, and examines the quality of the fuzzy score. The result from the second stage is then passed back to the first stage as feedback. The final result is obtained when the feedback system reaches its equilibrium state. The proposed resilience framework is applied to the external-sector and the public-sector economies of several countries to illustrate its applicability.