谈淤泥质复杂基坑地基处理及支护技术

淤泥质地形在施工过程中可能因地基强度不够而发生事故,施工难度高,对此类地基处理及支护技术的研究较为重要。     

Alcoholism detection based on Hu moment invariants of event-related potentials

Diagnostic efforts to identify alcoholism are frequently subjective; however, recent technological advances have allowed the automated assessment of objective signals. To improve the performance of the automated classification of patients with alcohol dependence (AD) and controls, we analyzed features of event-related potentials (ERPs) in 72 subjects with AD and 42 controls while the subjects underwent three different visual oddball tasks. In addition to such commonly used morphological features (MFs) as time-domain amplitude and latency components as well as discrete wavelet transform coefficient entropies (WEs), we analyzed Hu moment invariants (HMIs) in this study. Smaller P3 and P2 amplitudes, longer latencies, lower WE values, and lower HMI values were observed for AD subjects relative to those observed for controls. We used a Naïve Bayes algorithm to compare classification accuracies among MFs, WEs, HMIs, combinations of MFs/WEs, and combinations of all three characteristics. We found that HMIs improved the classification accuracy by 17%. Our findings demonstrated that a combined feature analysis of ERPs obtained during a visual oddball task can be a useful and discriminative tool for diagnostic purposes in alcoholism and that HMIs show promise for improving the objective diagnosis of alcoholism and similar diseases.     

结合深度学习与支持向量机的金属零件识别

目的 在视觉引导的工业机器人自动拾取研究中，关键技术难点之一是机器人抓取目标区域的识别问题。特别是金属零件，其表面的反光、随意摆放时相互遮挡等非结构化因素都给抓取区域的识别带来巨大的挑战。因此，本文提出一种结合深度学习和支持向量机的抓取区域识别方法。方法 分别提取抓取区域的方向梯度直方图（HOG）和局部二进制模式（LBP）特征，利用主成分分析法（PCA）对融合后的特征进行降维，以此来训练支持向量机（SVM）分类器。通过训练Mask R-CNN（regions with convolutional neural network）神经网络完成抓取区域的初步分割。然后利用SVM对Mask R-CNN识别的抓取区域进行二次分类，完成对干扰区域的剔除。最后计算掩码完成实例分割，以此达到对抓取区域的精确识别。结果 对于随机摆放的铜质金属零件，本文算法与单一的Mask R-CNN及多特征融合的SVM算法就识别准确率、错检率、漏检率3个指标进行了比较，结果表明本文算法在识别准确率上较Mask R-CNN和SVM算法分别提高了7%和25%，同时有效降低了错检率与漏检率。结论 本文算法结合了Mask R-CNN与SVM两种方法，对于反光和遮挡情况具有一定的鲁棒性，同时有效地提升了目标识别的准确率。     

Looking into the TESSERACT: Time-drifts in event streams using series of evolving rolling averages of completion times

Business processes are dynamic and change due to diverse factors. While existing approaches aim to detect drifts in the process structure, Tesseract looks for temporal drifts in activity interim times. This orthogonal view on the process extends the traditional data cube of events – case id, activities and timestamps – by a fourth dimension and improves the operational support by a visualization of temporal drifts in real-time.Insights about temporal deviations lead to an augmented awareness of imminent failures or improved service times. The detection of related structural concept drifts can be improved by early warning, as operation times of critical parts often increase before they catastrophically fail.     

The application of decision support tools and the influence of local data in prioritizing barrier removal in lower Michigan,USA

Web-based decision support tools (DSTs) can be useful to facilitate decision-making processes for managing complex natural resource systems. However, the alignment of DSTs with the objectives in governmental policies or management plans and the influence of limited local data on the outputs of these tools may reduce the use of DSTs by decision makers. In this study, we examined the outcomes of web-based DSTs when different types of local data were incorporated and demonstrated a way to incorporate outputs from multiple DSTs or local inventories to benefit barrier removal decisions. Restoring habitat connectivity in rivers in northwest lower Michigan, USA, was used as a case study due to the abundance of local inventory data and web-based DSTs. We found that, when compared to prioritizations made using local data, some DSTs could produce similar outcomes (in barriers selected, cost, and the benefit for migratory fish) with limited data, but the trade-offs among users' objectives might influence the cost and effectiveness of DSTs' outputs. Improving the ability of DSTs to incorporate objectives consistent with policy and stakeholders' values (e.g., restore certain species or sedimentation control) across management scales can help close the gap between tool recommendations and management decisions while making the barrier removal prioritization process transparent and efficient.     

Revamping SiO2 Spheres by Core–Shell Porosity Endowment to Construct a Mazelike Nanoreactor for Enhanced Catalysis in CO2 Hydrogenation to Methanol

Beyond the catalytic activity of nanocatalysts, the support with architectural design and explicit boundary could also promote the overall performance through improving the diffusion process, highlighting additional support for the morphology-dependent activity. To delineate this, herein, a novel mazelike-reactor framework, namely multi-voids mesoporous silica sphere (MVmSiO₂), is carved through a top-down approach by endowing core-shell porosity premade Stöber SiO₂ spheres. The precisely-engineered MVmSiO₂ with peripheral one-dimensional pores in the shell and interconnecting compartmented voids in the core region is simulated to prove combined hierarchical and structural superiority over its analogous counterparts. Supported with CuZn-based alloys, mazelike MVmSiO₂ nanoreactor experimentally demonstrated its expected workability in model gas-phase CO₂ hydrogenation reaction where enhanced CO₂ activity, good methanol yield, and more importantly, a prolonged stable performance are realized. While tuning the nanoreactor composition besides morphology optimization could further increase the catalytic performance, it is accentuated that the morphological architecture of support further boosts the reaction performance apart from comprehensive compositional optimization. In addition to the found morphological restraints and size-confinement effects imposed by MVmSiO₂, active sites of catalysts are also investigated by exploring the size difference of the confined CuZn alloy nanoparticles in CO₂ hydrogenation employing both in-situ experimental characterizations and density functional theory calculations.     

8603工作面回采巷道支护方案优化及数值模拟

针对深部软岩巷道围岩变形量大,传统支护结构失效的问题,以煤峪口矿回采巷道为研究背景,综合应用数值模拟和工程实践对原支护方案下巷道破坏特征进行分析,提出采用中空注浆锚索进行补强支护,并采用FLAC3D分析了两种支护方案下巷道围岩的收敛量以及应力分布情况,得出了优化支护方案能够有效控制巷道围岩破碎程度,并通过工程实践得到验证。     

Qualitative analysis of fluid dynamics and heat transfer characteristics in porous structures towards aqueous phase reforming hydrogen production

Porous structure is commonly used as a catalytic support in the field of fixed-bed reactor for hydrogen production from methanol aqueous phase reforming. The fluid dynamics and heat transfer characteristics of the fluid in a specific porous structure are considered profound influences for catalytic reactions. This study presented a qualitative investigation on the flow and heat transfer characteristics of fluids in variable porous structures. Specifically, the discrete average interpolation method was employed to obtain the value of a continuous structure. From the results, using the area-average temperature equation was 11% (±1.5%) larger and precise than that from the previous work using traditional hydrodynamic equation. The proposed variable porous structure could not only increase the turbulence intensity of the fluid which could further enhance reaction mass transfer but also enhance the convective heat transfer of the fluidic reactants. Some of these findings could inspire the reactor design for improving catalytic efficiency of hydrogen production.     

高压压气机转子结构设计及改进方法

为提高设计效率并快速得到适于工程应用的高压压气机转子结构，以改型设计方法为基础对某高压压气机转子结构进行了详细设计，同时对结构改进方法进行了一定的探索。采用叶—盘耦合系统循环对称结构算法及整体转子系统二维轴对称结构算法进行强度设计及改进，前轴颈最大应力下降最多达26%；其次进行支承结构设计，计算校核母型机轴承承载能力。结果表明：轴向力安全裕度最小为28%，轴承寿命大于100 000 h；给出2种调整鼠笼厚度的估算方法用以指导三维有限元计算，同时计算得到前支承刚度；通过二维有限元分析模型计算转子的临界转速，仅将后轴承支承位置沿压气机轴线向后移动7.5 mm，全运行工况转速与第2阶临界转速的安全裕度由18.5%提高到21.2%。