探索新体系 形成新特色──编写《电力系统分析》教材的体会和作法

本文介绍了作者在总结教学改革和课程建设成果的基础上编写《电力系统分析》教材的体会和作法。指导思想是‘探索新体系,形成新特色”。针对课程本身的任务和学科的系统性,将全书分为三篇：电力系统的基础知识;电力系统的基本计算和电力系统的运行分析。特色为：注重学生能力的培养;少而精;适时反映学科的发展与进步。配套：思考题、习题及计算机辅助教学软件包（ＣＡＩ）。     

Safety assessment of the NET Predesign

Work carried out by European Associations on Safety and Environment inside the EC Fusion Technology Programme and by NET has been concentrated on safety-related guidance and on safety assessment of the NET Predesign. Emphasis has been put on analysis of accident sequences of regulatory concern up to worst case accidents, including quantification of consequences to components, systems, and plant, and of doses to the public. Probabilistic safety studies for the most important systems and broadly for the entire plant have been performed to supplement the calculated accidental doses by expectation values for their occurrence rate, and to check the relevance of the reference accident sequences selected initially by judgment. Waste masses per year of operation and for decommissioning have been quantified. For two countries and according to the practices and regulations of these countries, volumes of radioactive waste packaged for final disposal have been determined.Presented at the IAEA Technical Committee Meeting on Developments in Fusion Safety, Toronto, June 7–11, 1993.     

Analogy and duality of texture analysis by harmonics or indicators

According to the classic harmonic approach, an orientation density function (odf)f is expanded into its corresponding Fourier orthogonal series with respect to generalized spherical harmonics, and a pole density function (pdf) into its corresponding Fourier orthogonal series with respect to spherical harmonics. While pdfs are even (antipodally symmetric) functions, odfs are generally not. Therefore, the part of the odf which cannot be determined from normal diffraction pdfs can be mathematically represented as the odd portion of its series expansion. If the odff is given, the even part can be mathematically represented explicitly in terms off itself. Thus, it is possible to render maps ofharmonic orientation ghosts, and to evaluatevariants of mathematical standard odfs resulting in identical pdfs independent of pdf data. However, if only normal diffraction pdfs are known, the data-dependentvariation width of feasible odfs remained unaccessible, and within the harmonic approach a measure of confidence in a solution of the pdf-to-odf inversion problem does not exist.According to any discrete approach, an odff defined on some setG of orientations is expanded into its corresponding Fourier orthogonal series with respect to indicator functions of the elements of a partition ofG, and a pdf defined on the upper (lower) unit hemisphereS ₊ ^{3 3} into its corresponding Fourier orthogonal series with respect to indicator functions of the elements of a partition ofS ₊ ³ . The ambiguity of the pdf-to-odf inversion problem is discussed in terms of column-rank deficiency of the augmented projection matrix. The implication of the harmonic approach to split an odf into auniquely determined and anundetermined part does no longer seem to be reasonable. However, it is possible to numerically determine data-dependent confidence intervals for the Fourier coefficients with respect to the indicator functions which can be immediately interpreted as mean orientation densities within the elements of the partition ofG. Doing so for all Fourier coefficients in the finite series expansion, i.e. for all elements of the partition of the setG, eventually results in the data-dependent variation width of odfs feasible with respect to given pdf data, and to the partitions ofG andS ₊ ³ .Thus it is confirmed that the appearance of orientation ghosts, in particular correlations oftrue andghost orientation components, depends on the representation of an odf. It may be questioned whether in practical applications the implicit assumption of the harmonic method that the even part can be determined uniquely and free of error is generally a reasonable initial condition to develop ghost correction procedures.     

Horizontal Voting Ensemble Based Predictive Modeling System for ColonCancer

Colon cancer is the third most commonly diagnosed cancer in the world. Most colon AdenoCArcinoma (ACA) arises from pre-existing benign polyps in the mucosa of the bowel. Thus, detecting benign at the earliest helps reduce the mortality rate. In this work, a Predictive Modeling System (PMS) is developed for the classification of colon cancer using the Horizontal Voting Ensemble (HVE) method. Identifying different patterns in microscopic images is essential to an effective classification system. A twelve-layer deep learning architecture has been developed to extract these patterns. The developed HVE algorithm can increase the system’s performance according to the combined models from the last epochs of the proposed architecture. Ten thousand (10000) microscopic images are taken to test the classification performance of the proposed PMS with the HVE method. The microscopic images obtained from the colon tissues are classified into ACA or benign by the proposed PMS. Results prove that the proposed PMS has ~8% performance improvement over the architecture without using the HVE method. The proposed PMS for colon cancer reduces the misclassification rate and attains 99.2% of sensitivity and 99.4% of specificity. The overall accuracy of the proposed PMS is 99.3%, and without using the HVE method, it is only 91.3%.     

Disaggregating growth in future retail electricity rates

The retail rate impacts of a number of emerging trends (e.g., rapid deployment of electric vehicles and storage, transmission build-out for large-scale renewables deployment, and grid modernization) are unknown. Importantly, decision-makers are concerned about the potential future rate impacts on energy affordability and equity. We disaggregate the key drivers of retail electricity rates and assess their impacts on future rate growth considering their interactions and uncertainty. Specifically, we develop ranges of future cost growth for a generic investor-owned and vertically-integrated electric utility representing typical cost and operating characteristics. The rate driver growth rate ranges are applied in isolation and jointly to quantify the uncertainty and variability in future retail electricity rates. The results identify what rate drivers and factors may minimize and/or decrease uncertainty in retail rate growth and their linkages to industry trends.     

An Automated Brain Image Analysis System for Brain Cancer using Shearlets

In this paper, an Automated Brain Image Analysis (ABIA) system that classifies the Magnetic Resonance Imaging (MRI) of human brain is presented. The classification of MRI images into normal or low grade or high grade plays a vital role for the early diagnosis. The Non-Subsampled Shearlet Transform (NSST) that captures more visual information than conventional wavelet transforms is employed for feature extraction. As the feature space of NSST is very high, a statistical t-test is applied to select the dominant directional sub-bands at each level of NSST decomposition based on sub-band energies. A combination of features that includes Gray Level Co-occurrence Matrix (GLCM) based features, Histograms of Positive Shearlet Coefficients (HPSC), and Histograms of Negative Shearlet Coefficients (HNSC) are estimated. The combined feature set is utilized in the classification phase where a hybrid approach is designed with three classifiers; k-Nearest Neighbor (kNN), Naive Bayes (NB) and Support Vector Machine (SVM) classifiers. The output of individual trained classifiers for a testing input is hybridized to take a final decision. The quantitative results of ABIA system on Repository of Molecular Brain Neoplasia Data (REMBRANDT) database show the overall improved performance in comparison with a single classifier model with accuracy of 99% for normal/abnormal classification and 98% for low and high risk classification.     

SBS改性沥青超热老化模式下氧化与挥发的贡献机理

利用宏观和微观分析相结合的方法,定量分析了SBS改性沥青超热老化模式下氧化与挥发的贡献机理。通过研究不同老化温度下常规三大指标,DSR流变车辙因子分别在空气氛和高纯氮气氛下老化的衰变规律,并结合傅里叶变换红外光谱微观表征手段,定量计算出SBS改性沥青超热老化过程中氧化与挥发的贡献率,得出SBS改性沥青在超热老化模式下,其老化机理是以SBS分子中的双键被氧化为主要因素,但随着超热老化温度升高,小分子挥发等非氧化因素逐渐成为超热老化的又一主要因素。宏观分析中,从普通老化的163℃到超热老化的198℃,氧化与挥发对SBS改性沥青针入度衰减的贡献率比由6∶4变为1∶1;对延度衰减的贡献率比由7∶3变为1∶1;对车辙因子的贡献率比由24∶1变为2∶1;而红外光谱微观分析中,氧化与挥发对SBS改性沥青超热老化后不饱和双键的衰减贡献率比由7∶3变为1∶1。     

液氦温区大型低温制冷系统的可靠性评估

针对改进Claude循环的大型氦低温制冷系统,以制冷量不足为顶事件建立了故障树模型。利用结构法对故障树模型进行定性分析,分析得到系统的最小割集为18个。利用来自不同数据库的部件失效率对故障树模型进行定量计算,得到了不同的结果,并分析其原因。对各部件的关键重要度进行了计算,以衡量各个部件对系统发生故障的贡献程度。并通过增加系统冗余部件和提高关键部件可靠度等措施,为提高系统可靠性找到了有效的解决途径。     

从竞争情报视角研究超级电容器产业的技术竞争态势

利用德温特创新索引(DII)数据库的专利文献数据,通过产业竞争环境分析和主要竞争对手分析,从竞争情报的视角研究了超级电容器产业的技术竞争态势。通过计算专利技术生命周期、技术研发重点、主要专利优先权国家分布、主要研发机构等指标,明确了我国在该技术领域的位置,提出了发展我国超级电容器产业对策和建议。     

Reconstructing design parameters of a rectangular resonator via peak signal-to-noise ratio and global optimization algorithms

This article proposes an approach for reconstructing physical parameters of a sample in a rectangular resonator during microwave radiation, knowing a priori, its electric field distribution. The inverse problem was solved using two global optimization algorithms and the peak signal-to-noise ratio (PSNR) criterion. First, the Self-regulated Fretwidth Harmony Search algorithm (SFHS) identified suitable resonant frequencies for a given configuration. Next, the unified Particle Swarm Optimization (UPSO) optimized said configuration. Together, they became a maximization strategy of the PSNR through a dual optimization process. Results showed the ability of the approach for estimating the height of each sample block and the resonating frequency of the cavity. This process takes longer to finish as a higher PSNR is demanded (mainly due to the aforementioned dual optimization). Even so, it allows for more similar electric field distributions between both, the direct and inverse problems.