High quality 3D reconstruction based on fusion of polarization imaging and binocular stereo vision

Polarization imaging can retrieve inaccurate objects’ 3D shapes with fine textures, whereas coarse but accurate depths can be provided by binocular stereo vision. To take full advantage of these two complementary techniques, we investigate a novel 3D reconstruction method based on the fusion of polarization imaging and binocular stereo vision for high quality 3D reconstruction. We first generate the polarization surface by correcting the azimuth angle errors on the basis of registered binocular depth, to solve the azimuthal ambiguity in the polarization imaging. Then we propose a joint 3D reconstruction model for depth fusion, including a data fitting term and a robust low-rank matrix factorization constraint. The former is to transfer textures from the polarization surface to the fused depth by assuming their relationship linear, whereas the latter is to utilize the low-frequency part of binocular depth to improve the accuracy of the fused depth considering the influences of missing-entries and outliers. To solve the optimization problem in the proposed model, we adopt an efficient solution based on the alternating direction method of multipliers. Extensive experiments have been conducted to demonstrate the efficiency of the proposed method in comparison with state-of-the-art methods and to exhibit its wide application prospects in 3D reconstruction.     

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.     

Nonstoichiometric effect of A-site complex ions on structural,dielectric, ferroelectric,and electrostrain properties of bismuth sodium titanate ceramics

To investigate the nonstoichiometric effect of (Bi_0.5Na_0.5)TiO₃ (BNT) ceramics on their properties, we propose a novel chemical expression, (Bi_0.5+xNa_0.5−3x)TiO₃. The nonstoichiometric effect of BNT can be explored in compounds with this composition without being hampered by the charge imbalance problem. With x ranging from −0.02 to 0.02, we find that the morphological, dielectric, ferroelectric, and electrostrain properties differ considerably between Na-rich and Bi-rich ceramic samples. The average grain size (AGS) increased significantly in Na-rich samples compared to that in stoichiometric BNT, while it decreased slightly in Bi-rich samples. The dielectric characteristics measured from 30 °C to 500 °C indicate that conductivity is activated in Na-rich nonstoichiometric samples but is effectively suppressed in Bi-rich nonstoichiometric samples. The ferroelectric properties also show the same trend. In Na-rich samples, elliptical polarization against electric field (P-E) hysteresis loops were detected, indicating a conductive character induced by high electric field loading. However, saturated P-E loops are observed in Bi-rich samples with well-inhibited conductivity. Furthermore, compared to stoichiometric BNT and nonstoichiometric x = 0.02 Bi-rich samples, (Bi_0.5+xNa_0.5−3x)TiO₃ samples with x = 0.01 exhibit higher electrostrain from 30 °C to 150 °C. Based on the assumption of charge balance, our findings indicated that the presence of 1 mol% excess Bi would facilitate significant improvement in the dielectric, ferroelectric, and electrostrain properties of BNT and BNT-based systems.     

基于材料力学性能的最低设计金属温度曲线分析

铁素体钢在低温条件下存在明显的韧脆转变现象。为防止脆断事故的发生,需要确定铁素体钢制压力容器的最低使用温度。针对ASME中的A^D四条冲击豁免曲线,对应地选取了4种材料,基于材料实际的屈服强度和参考温度,按照ASME中豁免曲线的计算方法,计算得到4种材料的最低设计金属温度曲线,并与对应的A^D曲线对比,定量地分析ASME中豁免曲线的保守性。结果表明,ASME中的豁免曲线相对于材料自身的最低设计金属温度曲线保守性较大;韧性相近的材料被划分到不同的豁免曲线,使得韧性富裕量差异较大,对于某些材料,其断裂韧性被低估。     

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.     

Large piezoelectricity and potentially activated polarization reorientation around relaxor MPB in complex perovskite

Improving piezoelectric performance is always favorable to further enhance the sensitivity and accuracy of piezoelectric devices. Here, a complex piezoelectric system of Pb(Ni_1/3Nb_2/3)O₃-Pb(Yb_1/2Nb_1/2)O₃-Pb(Hf_0.1Ti_0.9)O₃ is designed and investigated in detail. Optimized piezoelectric response of ～ 880 pC/N is achieved at the composition of 0.51PNN-0.09PYN-0.40PHT. The characterization of TEM and In-situ high-energy synchrotron diffraction indicate that nanodomain growth and microdomain switching occurs in succession at around coercive electric field. Most interestingly, the coexisted tetragonal and rhombohedral-like phase transforms into multiple monoclinic-like phases with polarization vectors aligned as close to the electric field direction as possible under the strong electric field. The enhanced polarization instability in this complex morphotropic phase boundary sample should be ascribed to the strong local heterogeneity. The novel polarization rotation behavior found in this work would be important guidance for designing high-performance piezoceramics.     

Improved Corrosion Resistance of Selective Laser Melted Ti–5Cu Alloy Using Atomized Ti–5Cu Powder

The different types of metal powder used for selective laser melting(SLM) process would cause distinct corrosion behavior due to the uniformity of the obtained microstructure.The SLM-produced Ti–5Cu alloy using atomized Ti–5Cu metal powder(SLMed Ti–5Cu) in this work reveals a relatively uniform microstructure with overwhelming acicular α/α′ phase and shows great advantages on corrosion resistance compared with the SLM-produced Ti–5Cu alloy using the mixture powder(SLMedM Ti–5Cu).The effect of the micro-galvanic cells decreases due to the undetectable Ti_2Cu phase in the microstructure of the SLMed Ti–5Cu.An apparent passivation behavior was observed for SLMed Ti–5Cu instead of severe pitting phenomenon for the SLMed-M Ti–5Cu.The charge transfer resistance of SLMed Ti–5Cu in this work is 10.09 ± 2.63 MΩ cm~2, which is significantly higher than that of SLMed-M Ti–5Cu(4.76 MΩ cm~2).The above result indicates the atomized Ti–5Cu powder plays an important role in the formation of the uniform microstructure of SLMed product, thereby enhancing its corrosion resistance in Hank's solution at 37 ℃.     

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。     

03Cr18NiMoN节镍双相不锈钢的热变形行为及热加工图

关键词：双相不锈钢； 流变曲线； 本构方程； 热加工图     

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.