A deep neural network-based method for solving obstacle problems

In this paper, we propose a method based on deep neural networks to solve obstacle problems. By introducing penalty terms, we reformulate the obstacle problem as a minimization optimization problem and utilize a deep neural network to approximate its solution. The convergence analysis is established by decomposing the error into three parts: approximation error, statistical error and optimization error. The approximate error is bounded by the depth and width of the network, the statistical error is estimated by the number of samples, and the optimization error is reflected in the empirical loss term. Due to its unsupervised and meshless advantages, the proposed method has wide applicability. Numerical experiments illustrate the effectiveness and robustness of the proposed method and verify the theoretical proof.     

小功率高转速蒸汽透平试验研究和优化

小功率高转速蒸汽透平试验研究和优化邵振麒（同济大学汽车工程系上海２０００９２）关键词：小蒸汽透平，效率，优化１前言回收能量和工业装置的余热及利用太阳能等新能源是节能和环保的重要措施，由此产生的机械能可供发电，气体增压等多种用途。在一些废热量不大且不宜...     

计及污垢影响的换热器热优化

本文利用熵产生数方法研究了气体和液体传热介质的顺流、逆流换热器的热力学完善性，结果表明，如给定冷、热流体的入口温度，在综合考虑传热、流动阻力和污垢的情况下，可用优化方法确定其它参数。     

S-wave baryons in an equally mixed scalar-vector square root potential model of independent quarks

A relativistic model of independent quarks based on Dirac equation with an equally mixed scalar-vector square root confining potential is used to compute the quark core contributions to the static properties like magnetic moments, charge radii and axial vector coupling constant ratios of the baryon octet. The results obtained with appropriate corrections due to centre-of-mass motion agree fairly well with experimental values. The model is also extended to the study of magnetic moments of the quark core of baryons in the charmed andb-flavoured sectors and the overall predictions so obtained compare well with other model predictions.     

对象散全息元件产生的正交象散特性的研究

本文从理论上分析了用全息方法制作具有象散特征的一种光学元件——象散全息元件——的可能性,并得到实验上的证明.对由象散全息元件在空间正交方向上产生的象散特性作了较为仔细的研究,给出了实验结果.若用此元件代替普通象散系统,将具有使用方便,经济等优点.     

一种金属腔体中微波断层成像的最优分层非均一背景

针对基于金属腔体的微波断层成像系统,提出了一种最优分层非均一背景的设计方法.该方法使用一种新的微波断层成像积分算子评价方法和模拟退火法等最优化方法.首先,介绍了一种基于有限元法的微波断层成像积分算子计算方法.然后,提出一种新的微波断层成像积分算子度量,该度量可以综合评价整个积分算子奇异值谱,并通过一组仿真研究证明该度量与反演结果的误差具有相关性;该度量用一个数值综合评价一个积分算子,可以方便地应用于最优化算法中;利用模拟退火法选择圆形金属腔体中分层非均一背景的每一层介质的相对介电常数,从而获得一个最优分层非均一背景.最后,对尺寸小于半波长的圆柱目标和"凹"字形复杂目标进行仿真研究,仿真结果证明该最优分层非均一背景可以提高微波断层成像算法的收敛速度,提高反演结果的准确性.     

A framework for classification with single feature kernel matrix

In this paper, we propose a novel classification framework using single feature kernel matrix. Different from the traditional kernel matrices which make use of the whole features of samples to build the kernel matrix, this research uses features of the same dimension of any two samples to build a sub-kernel matrix and sums up all the sub-kernel matrices to get the single feature kernel matrix. We also use single feature kernel matrix to build a new SVM classifier, and adapt SMO (Sequential Minimal Optimization) algorithm to solve the problem of SVM classifier. The results of the experiments on several artificial datasets and some challenging public cancer datasets display the classification performance of the algorithm. The comparisons between our algorithm and L₂-norm SVM on the cancer datasets demonstrate that the accuracy of our algorithm is higher, and the number of support vectors selected is fewer, indicating that our proposed framework is a more practical approach.     

Intelligent reversible watermarking technique in medical images using GA and PSO

The advances in recording, editing, and broadcasting multimedia contents in digital form motivate to protect these digital contents from illegal use, such as duplication, manipulation, and redistribution. However, watermarking algorithms are designed to satisfy requirements of applications, as different applications have different concerns. We intend to design a watermarking algorithm for applications which require high embedding capacity and imperceptibility, to maintain the integrity of the host signal as well as embedded information. Reversible watermarking is a promising technique which satisfies our requirements. In this paper, we concentrate on improving the watermark capacity and reducing the perceptual degradation of an image. We investigated the Luo's [1] additive interpolation-error expansion algorithm and enhanced it by incorporating with two intelligent techniques: genetic algorithm (GA), and particle swarm optimization (PSO). Genetic algorithm is applied to exploit the correlation of image pixel values to obtain better estimation of neighboring pixel values, which results in optimal balance between information storage capacity and imperceptibility. Particle swarm optimization (intelligent technique) is also applied for the same purpose. Experimental results show that PSO and GA nearly give the same results, but GA outperforms the PSO. Experimental results also reveal that the proposed strategy outperforms the state of art works in terms of perceptual quality and watermarking payload.     

再谈静电能的损失

本文从暂态过程的角度和能流的观点分析和讨论电容器并联过程中能量的损失问题.     

A High-Efficiency Second-Harmonic Gyrotron with a Depressed Collector

The gyrotron with an electrically insulated collector has been manufactured and tested. The 60% output efficiency is obtained for the Collector Potential Depression (CPD) operation regime. The results of the numerical simulation of the electron energy spectrum in the collector region of the second-harmonic technological 24 GHz gyrotron are presented. It is shown, that the minimal electron beam energy is about 20% of the initial value and that the gyrotron cavity should be expanded to achieve the highest output efficiency of the gyrotron with energy recovery. The highest experimental decelerating voltage is in good agreement with the calculation of the electron energy spectrum.