Distributed learning consensus control based on neural networks for heterogeneous nonlinear multiagent systems

This paper considers a novel distributed iterative learning consensus control algorithm based on neural networks for the control of heterogeneous nonlinear multiagent systems. The system's unknown nonlinear function is approximated by suitable neural networks; the approximation error is countered by a robust term in the control. Two types of control algorithms, both of which utilize distributed learning laws, are provided to achieve consensus. In the provided control algorithms, the desired reference is considered to be an unknown factor and then estimated using the associated learning laws. The consensus convergence is proven by the composite energy function method. A numerical simulation is ultimately presented to demonstrate the efficacy of the proposed control schemes.     

安家岭露天矿过采空区危险源辨识及安全措施研究

危险源辨识对提高煤矿安全生产具有重要的现实意义。研究建立了基于层次分析法的安家岭露天矿危险源辨识模型,确定了危险源指标的权重。依据危险源辨识的权重研究了安家岭露天矿过采空区安全开采存在的主要危险源,并把采空区分为高温明火采空区、积水采空区、存在有毒气体的采空区、未冒实采空区,针对不同的类别的采空区提出了相应的安全开采措施。     

Influence of Si-Doping on the Performance of InGaN/GaN Multiple Quantum Well Solar Cells

Semiconductors - The performance of InGaN/GaN multiple quantum well (MQW) solar cells with five different Si-doping concentrations, namely 0, 4 × 1017 cm–3, 1 × 1018 cm–3, 3...     

Automatic breast tumor detection in ABVS images based on convolutional neural network and superpixel patterns

Breast cancer is one of the most common female malignancies, as well as the second leading cause of mortality for women. Early detection and treatment can dramatically decrease the mortality rate. Recently, automated breast volume scanner (ABVS) has become one of the most frequently used diagnose methods for breast tumor screening because of its operator-independent and reproducible advantages. However, it is a challenging job to obtain the tumors’ accurate locations and shapes by reviewing hundreds of ABVS slices. In this paper, a novel computer-aided detection (CADe) system is developed to reduce clinicians’ reading time and improve the efficiency. The CADe system mainly contains three parts: tumor candidate acquisition, false-positive reduction and tumor segmentation. Firstly, a local phase-based approach is built to obtain breast tumor candidates for further recognition. Subsequently, a convolutional neural network (CNN) is applied to reduce false positives (FPs). The introduction of CNN can help to avoid complicated feature extraction as well as elevate the accuracy and efficiency. Finally, superpixel-based segmentation is used to outline the breast tumor. Here, superpixel-based local binary pattern (SLBP) is proposed to assist the segmentation, which improves the performance. The methods were evaluated on a clinical ABVS dataset whose abnormal cases were manually labeled by an experienced radiologist. The experiment results were mainly composed of two parts. At the FP reduction stage, the proposed CNN achieved 100% and 78.12% sensitivity with FPs/case of 2.16 and 0. At the segmentation stage, our SLBP obtained 82.34% true positive, 15.79% false positive and 83.59% Dice similarity. In summary, the proposed CADe system demonstrated promising potential to detect and outline breast tumors in ABVS images.

     

In-situ crystal growth and photoluminescence properties of YBO3: Tb3+ microstructures

Three-dimensional (3D) YBO₃:Tb³⁺ flower-like and dense flower-like hierarchitecture constituted of nanoflakes are solvothermally synthesized in the presence of polyborate precursors in the mixture of ethanol and water. The growth process of the YBO₃:Tb³⁺ flowers and dense flowers was explored based on the time-dependent experiment and the results showed that the growth mechanism follows an in situ growth rather than self-assembly process as reported previously. YBO₃:Tb³⁺ morphologies composed of nanoflakes are achieved by controlling the concentration of ethanol and dependence of photoluminescence on morphology was studied. Remarkable photoluminescence enhancement was observed for YBO₃:Tb³⁺ with flower-like morphology demonstrating the potential of the microstructure in future applications as a green phosphor. Such a synthetic method and growth mechanism may be applied to fabricate complex 3D architectures of other materials.     

马钢张庄矿高压辊磨机装配工艺研究

针对马钢张庄矿高压辊磨机辊套疲劳断裂严重、对辊精度不能满足生产要求等问题，马钢重机公司根据张庄矿实际生产要求对对辊进行国产化，国产化内容包括辊轴、辊套等零部件的新制以及装配工艺攻关，通过技术研发同时结合实际生产经验，成功对高压辊磨机辊套与辊轴以及辊轴与轴承进行装配，完成了张庄矿高压辊磨机整对对辊的国产化，为该型设备后续生产及优化提供了理论和实践参考依据。     

土壤中石油污染物的脱附过程

文章中主要采用有机溶剂萃取法（OSE）对高浓度石油污染土壤进行修复，经过精馏操作，有效回收原油，建立脱附等温曲线，研究了石油污染物在土壤-有机溶剂两相间的迁移规律。     

变频器调速装置节能浅析

1概述 近十多年来,随着电力电子技术、微电子技术及现代控制理论的发展,变频调速技术已经广泛地用于交流电动机的速度控制,其最主要的特点是具有高效率的驱动性能及良好的控制特性.它是一种高新技术电力节能装置,它通过改变（降低）电源工作频率,来降低动力设备（电机）的转速,减少设备的输出功率,达到输出功率与工作负荷的最佳匹配,实现节能目的,有效地提高了经济效益和产品质量.几乎可以说,有电动机的地方就有变频器,在一切需要进行速度控制的场合,变频器以其操作方便、体积小、控制性能高而获得广泛应用.