Efficient Flexible M-Tree Bulk Loading Using FastMap and Space-Filling Curves

Many database applications currently deal with objects in a metric space. Examples of such objects include unstructured multimedia objects and points of interest (POIs) in a road network. The M-tree is a dynamic index structure that facilitates an efficient search for objects in a metric space. Studies have been conducted on the bulk loading of large datasets in an M-tree. However, because previous algorithms involve excessive distance computations and disk accesses, they perform poorly in terms of their index construction and search capability. This study proposes two efficient M-tree bulk loading algorithms. Our algorithms minimize the number of distance computations and disk accesses using FastMap and a space-filling curve, thereby significantly improving the index construction and search performance. Our second algorithm is an extension of the first, and it incorporates a partitioning clustering technique and flexible node architecture to further improve the search performance. Through the use of various synthetic and real-world datasets, the experimental results demonstrated that our algorithms improved the index construction performance by up to three orders of magnitude and the search performance by up to 20.3 times over the previous algorithm.     

印刷电路板缺陷检测的实际应用

电路板在我们的日常生活中非常常见,这就使得印刷电路板的缺陷检测显得尤为重要。AOI作为新兴的检测PCB板缺陷的系统,在生产实际中正在被大家熟知并且应用。相较于传统的检测方式,AOI系统比较灵活,无论是在检测时间还是系统运算上,或者是对相关技术人员的要求相较于传统方式都比较有优势,本文就AOI系统在实际中的应用展开讨论,分析并且介绍了在实际应用中的具体细则。     

裸眼井中扩张式封隔器力学行为研究

封隔器在石油天然气开采中起着非常重要的作用,而扩张式封隔器在裸眼井中广泛应用。本文采用有限元软件建立了裸眼封隔器与地层的模型,对胶筒在坐封过程中与井壁接触应力的变化进行了研究,并研究了在不同摩擦系数下接触压力的变化,结果表明,建立粗糙井壁面能够更加符合实际情况,胶筒肩部为应力集中的区域,地层与胶筒的接触应力会随着摩擦系数的增加而减小。研究结果为裸眼扩张式封隔器的设计和改进提供了理论依据。     

Elitist clonal selection algorithm for optimal choice of free knots in B-spline data fitting

Data fitting with B-splines is a challenging problem in reverse engineering for CAD/CAM, virtual reality, data visualization, and many other fields. It is well-known that the fitting improves greatly if knots are considered as free variables. This leads, however, to a very difficult multimodal and multivariate continuous nonlinear optimization problem, the so-called knot adjustment problem. In this context, the present paper introduces an adapted elitist clonal selection algorithm for automatic knot adjustment of B-spline curves. Given a set of noisy data points, our method determines the number and location of knots automatically in order to obtain an extremely accurate fitting of data. In addition, our method minimizes the number of parameters required for this task. Our approach performs very well and in a fully automatic way even for the cases of underlying functions requiring identical multiple knots, such as functions with discontinuities and cusps. To evaluate its performance, it has been applied to three challenging test functions, and results have been compared with those from other alternative methods based on AIS and genetic algorithms. Our experimental results show that our proposal outperforms previous approaches in terms of accuracy and flexibility. Some other issues such as the parameter tuning, the complexity of the algorithm, and the CPU runtime are also discussed.     

Evaluation of bismuth doped La2-xBixNiO4+δ (x = 0, 0.02 and 0.04) as cathode materials for solid oxide fuel cells

Bismuth doped La_2-xBi_xNiO_4+δ (x = 0, 0.02 and 0.04) oxides are investigated as SOFC cathodes. The effects of Bi doping on the phase structure, thermal expansion, electrical conduction behavior as well as electrochemical performance are studied. All the samples exist as a tetragonal Ruddlesden-Popper structure. Bi-doped LBNO-0.02 and LBNO-0.04 have good chemical and thermal compatibility with LSGM electrolyte. The average TEC over 20–900°С was 13.4 × 10^?6 and 14.2 × 10^?6 K^?1 for LBNO-0.02 and LBNO-0.04, respectively. The electrical conductivity was decreasing with the rise of Bi doping content. EIS measurement indicates Bi doping can decrease the ASR values. At 750 °C, the obtained ASR for LBNO-0.04 is 0.18 Ωcm², which is 56% lower than that of the sample without Bi doping, suggesting Bi doping is beneficial to the electrochemical catalytic activity of LBNO cathodes.     

减少手术创伤始终是妇科肿瘤手术快速康复的决定性因素

减少手术创伤始终是快速康复的决定性因素,这一点在目前的加速康复外科研究尤其是复杂手术,如妇科肿瘤手术中尚未得到充分重视。尊重学习曲线、全面规划手术方案、总结失利经验、开展前瞻性研究是解决此问题的主要方案。本文着重讨论妇科肿瘤手术创伤对术后加速康复的影响及可能的改进措施。     

Novel electrospun polymer electrolytes incorporated with Keggin‐type hetero polyoxometalate fillers as solvent‐free electrolytes for lithium ion batteries

In this study, solvent‐free nanofibrous electrolytes were fabricated through an electrospinning method. Polyethylene oxide (PEO), lithium perchlorate and ethylene carbonate were used as polymer matrix, salt and plasticizer respectively in the electrolyte structures. Keggin‐type hetero polyoxometalate (Cu‐POM@Ru‐rGO, Ni‐POM@Ru‐rGO and Co‐POM@Ru‐rGO (POM, polyoxometalate; rGO, reduced graphene oxide)) nanoparticles were synthesized and inserted into the PEO‐based nanofibrous electrolytes. TEM and SEM analyses were carried out for further evaluation of the synthesized filler structures and the electrospun nanofibre morphologies. The fractions of free ions and crystalline phases of the as‐spun electrolytes were estimated by obtaining Fourier transform infrared and XRD spectra, respectively. The results showed a significant improvement in the ionic conductivity of the nanofibrous electrolytes by increasing filler concentrations. The highest ionic conductivity of 0.28 mS cm^?1 was obtained by the introduction of 0.49 wt% Co‐POM@Ru‐rGO into the electrospun electrolyte at ambient temperature. Compared with solution‐cast polymeric electrolytes, the electrospun electrolytes present superior ionic conductivity. Moreover, the cycle stability of the as‐spun electrolytes was clearly improved by the addition of fillers. Furthermore, the mechanical strength was enhanced with the insertion of 0.07 wt% fillers to the electrospun electrolytes. The results implied that the prepared nanofibres are good candidates as solvent‐free electrolytes for lithium ion batteries. © 2020 Society of Chemical Industry     

Residual learning rates in lead-acid batteries: Effects on emerging technologies

The low price of lead-acid, the most popular battery, is often used in setting cost targets for emerging energy storage technologies. Future cost reductions in lead acid batteries could increase investment and time scales needed for emerging storage technologies to reach cost-parity. In this paper the first documented model of cost reductions for lead-acid batteries is developed. Regression to a standard experience curve using 1989–2012 data yield a poor fit, with R² values of 0.17 for small batteries and 0.05 for larger systems. To address this problem, battery costs are separated into material and residual costs, and experience curves developed for residual costs. Depending on the year, residual costs account for 41–86% of total battery cost. Using running-time averages to address volatility in material costs, a 4-year time average experience curve for residual costs yield much higher R², 0.78 for small and 0.74 for large lead-acid batteries. The learning rate for residual costs in lead-acid batteries is 20%, a discovery with policy implications. Neglecting to consider cost reductions in lead-acid batteries could result in failure of energy storage start-ups and public policy programs. Generalizing this result, learning in incumbent technologies must be understood to assess the potential of emerging ones.