Nash equilibrium bidding strategies in a bilateral electricitymarket

This paper examines bidding strategies in a bilateral market in which generating companies submit bids to loads. A load accepts electricity delivery from the generator with the lowest bid at its bid price as long as this price is not higher than the load's willingness to pay. Necessary and sufficient conditions of Nash equilibrium (NE) bidding strategy are derived based on a generic generating cost matrix and the loads' willingness to pay vector. The study shows that in any NE, efficient allocation is achieved. Furthermore, all Nash equilibria are revenue equivalent for the generators. Based on the necessary and sufficient conditions, this problem is formulated as an optimal assignment problem. Network optimization techniques are applied to calculate NE bid prices for the generators     

HHD型核子秤电离室物理性能检测

HHD型核子秤电离室已成功地使用于HCS型核子秤.对它的各种物理性能指标进行了检测,各项性能指标都达到了设计要求。     

有扰对称信道平均信息量的计算

照相手机让诺基亚抢了风头，这真是亚洲人的失策。在日本和韩国，内置摄像头的手机早就不是什么值得炫耀的东西了。不过日本人的动作还是很快的，GD88和N8一副后来居上的架势，让人不敢小瞧。     

Exploratory analysis of brain connectivity with ICA.

Covariance-based methods of exploration of functional connectivity of the brain from functional magnetic resonance imaging (fMRI) experiments, such as principal component analysis (PCA) and structural equation modeling (SEM), require a priori knowledge such as an anatomical model to infer functional connectivity. In this research, a hybrid method, combining independent component analysis (ICA) and SEM, which is capable of deriving functional connectivity in an exploratory manner without the need of a prior model is introduced. The spatial ICA (SICA) derives independent neural systems or sources involved in task-related brain activation, while an automated method based on the SEM finds the structure of the connectivity among the elements in independent neural systems. Unlike second-order approaches used in earlier studies, the task-related neural systems derived from the ICA provide brain connectivity in the complete statistical sense. The use and efficacy of this approach is illustrated on two fMRI datasets obtained from a visual task and a language reading task.     

高质量的一级光栅1．55μmDFB激光器

本文详细叙述了ＤＦＢ激光器的设计要点和新的工艺。采用一级全息光栅和二步液相外延法批量研制出高稳定单纵模工作的１．５５μｍ分布反馈激光器（ＤＦＢ—ＬＤ）。外延片成品率＞４０％。器件特性：２５℃时阈值电流２０ｍＡ，单面光功率＞１０ｍｗ，主边模抑制比ＳＭＳＲ达４３ｄＢ（λ／４相移光栅），谱线宽度△ν－２０ｄＢ＝０．３ｎｍ，调制速率＞１．８ＧＨｚ。可靠性测试显示：高温监测光谱稳定，２５°Ｃ时阈值退化率△Ｉｔｈ／ｔ＜０．３ｍＡ／ｋｈ，对应器件预估寿命将超过１０万ｈ。     

An error and sensitivity analysis of the atmospheric- andsoil-correcting variants of the NDVI for the MODIS-EOS

Several soil- and atmospheric-correcting variants of the normalized difference vegetation index (NDVI) have been proposed to improve the accuracy in estimating biophysical plant parameters. In this study, a sensitivity analysis, utilizing simulated model data, was conducted on the NDVI and variants by analyzing the atmospheric- and soil-perturbed responses as a continuous function of leaf area index. Percent relative error and vegetation equivalent “noise” (VEN) were calculated for soil and atmospheric influences, separately and combined. The NDVI variants included the soil-adjusted vegetation index (SAVI), the atmospherically resistant vegetation index (ARVI), the soil-adjusted and atmospherically resistant vegetation index (SARVI), the modified SAVI (MSAVI), and modified SARVI (MSARVI). Soil and atmospheric error were of similar magnitudes, but varied with the vegetation index. All new variants outperformed the NDVI. The atmospherically resistant versions minimized atmospheric noise, but enhanced soil noise, while the soil adjusted variants minimized soil noise, but remained sensitive to the atmosphere. The SARVI, which had both a soil and atmosphere calibration term, performed the best with a relative error of 10 percent and VEN of ±0.33 LAI. By contrast, the NDM had a relative error of 20 percent and VEN of ±0.97 LAI