一种基于FCOS神经网络的小建筑物目标检测方法北大核心

提出了一种基于FCOS神经网络的小建筑物目标检测算法,针对FCOS模型在特征提取阶段提取到的小建筑物目标特征较少问题,引入多尺度检测和可变形卷积方式,加强网络对小建筑物目标的特征提取能力,并通过改进后的SGE注意力机制降低特征图中的干扰噪声权重。改进后的网络可以提取到更多的小建筑物目标特征,对环境干扰噪声的鲁棒性更强。在自己搭建的数据集上进行了实验测试,结果表明,在相同环境下网络改进后建筑物的整体检测准确率提升了1.7%,其中对小建筑物目标提升了3.6%,减少了小建筑物目标漏检、误检的问题。     

一种基于抽取LMS的距离旁瓣抑制方法

在噪声雷达中，传统相关处理方法的距离旁瓣受到时宽带宽积的限制，在有限相关处理时间内得到的距离旁瓣较高，会造成微弱目标被强目标、杂波旁瓣淹没的现象。提出一种基于抽取最小均方（Least Mean Square,LMS）滤波的噪声雷达旁瓣抑制方法，将LMS滤波器的系数作为距离压缩结果，从而获取较低的距离旁瓣。对该方法的性能进行了理论分析，并通过数字仿真验证了算法的有效性和理论分析的正确性。     

快速近似计算Shapley值的归因解释方法

Shapley值归因解释方法虽然能更准确量化解释结果, 但过高的计算复杂度严重影响了该方法的实用性. 本文引入KD树重新整理待解释模型的预测数据, 通过在KD树上插入虚节点, 使之满足TreeSHAP算法的使用条件, 在此基础上提出了KDSHAP方法. 该方法解除了TreeSHAP算法仅能解释树结构模型的限制, 将该算法计算Shapley值的高效性放宽到对所有的黑盒模型的解释中, 同时保证了计算准确度. 通过实验对比分析, KDSHAP方法的可靠性, 以及在解释高维输入模型时的适用性.     

Research and demonstration on hydrogen compatibility of pipelines: a review of current status and challenges

Hydrogen transportation by pipelines gradually becomes a critical engineering route in the worldwide adaptation of hydrogen as a form of clean energy. However, due to the hydrogen embrittlement effect, the compatibility of linepipe steels and associated welds with hydrogen is a major concern when designing hydrogen-carrying pipelines. When hydrogen enters the steels, their ductility, fracture resistance, and fatigue properties can be adversely altered. This paper reviews the status of several demonstration projects for natural gas-hydrogen blending and pure hydrogen transportation, the pipeline materials used and their operating parameters. This paper also compares the current standards of materials specifications for hydrogen pipeline systems from different parts of the world. The hydrogen compatibility and tolerance of varying grades of linepipe steels and the relevant testing methods for assessing the compatibility are then discussed, and the conservatism or the inadequacies of the test conditions of the current standards are pointed out for future improvement.     

Crystallization behavior and density functional theory study of solution combustion synthesized silicon doped calcium phosphates

The influence of heat-treatment temperatures (700 °C, 900°C, 1200 °C) on the phase, physical properties, crystallization rate, and in vitro properties of the solution combustion synthesized silicon-doped calcium phosphates (CaPs) were investigated. The thermodynamic aspects (enthalpy, entropy, and free energy) of the synthesis process and the crystallographic properties of the final samples were first predicted and then confirmed using density functional theory (DFT). Results demonstrated that the crystallization rate was controlled by the fuel(s) type (glycine, citric acid, and urea) and the amounts of Si⁴⁺ ions (0, 0.1, 0.4 mol). The highest calculated crystallization rate values of the un-doped, 0.1, and 0.4 mol Si-doped samples were 64%, 22%, 38%, respectively. The obtained results from the DFT simulation revealed that crystal growth in the direction of c-axis of hydroxyapatite (HAp) structure could change the stability of (001) surface of (HAp). Also, the computational data confirmed the adsorption of Si–OH groups on the (001) surface of HAp during the SCS process with an adsorption energy of 1.53 eV. AFM results in line with DFT simulation showed that the observed change in the surface roughness of Si-doped CaPs from 2 to 8 nm could be related to the doping of Si⁴⁺ ions onto the surface of CaPs. Besides, the theoretical and experimental investigation showed that crystal growth and doping of Si⁴⁺ ions could decrease the activation energy of oxygen reduction reaction (ORR). Furthermore, the results showed that the crystallized HAp structure could have great potential to efficiently reduce oxidative stress in human body.     

Coupling effects of water content,temperature, oxygen density,and polytetrafluoroethylene loading on oxygen transport through ionomer thin film on platinum surface in catalyst layer of proton exchange membrane fuel cell

In this work, coupling effects of water content, temperature, oxygen density, and polytetrafluoroethylene (PTFE) loading on oxygen transport through an ionomer thin film on a platinum surface in a catalyst layer of a proton exchange membrane (PEM) fuel cell are investigated using molecular dynamics approach. Taguchi orthogonal algorithm is employed to comprehensively analyze the coupling effects in a limited number of cases. It is found that the effect of operation temperature is the weakest among the four factors, which has the smallest effect index 14.4. Coupling effects including the PTFE loadings on the oxygen transfer through the ionomer thin film is uncovered. Less PTFE loadings should be beneficial for the oxygen transfer. The chemical potential gradient is considered as the major driven force for the oxygen transport through the ionomer thin film, and oxygen density is the dominating factor, significantly affecting the chemical potential in the thin film.     

Improved thermal stability of the near-infrared Al-modulated Zn3Ga2GeO8: Cr3+ phosphors for plant growth applications

The exploration of the high thermal stability near-infrared (NIR) phosphors is significantly crucial for the development of plant lighting. However, NIR phosphors suffer from the poor chemical and thermal stability, which severely limits their long-term operation. Here, the successful improvement of luminous intensity (149.5%) and thermal stability at 423 K of Zn₃Ga₂GeO₈ (ZGGO): Cr³⁺ phosphors is achieved for the introduction of Al³⁺ ions into the host. The release of carriers in deep traps inhibits the emission loss for the thermal disturbance. Furthermore, an NIR light emitting diodes (LEDs) lamp is explored by combining the optimized Zn₃Ga_1.1675Al_0.8GeO₈: 0.0325Cr³⁺ phosphors with a commercial 460 nm blue chip, and the emission band can match well with the absorption bands of photosynthetic pigments and the phytochrome (P_R and P_FR) of plants. The explored LEDs lamp further determines the growth and the pheromone content of the involved plants for the participation of the NIR emission originated from Cr³⁺ ions. Our work provides a promising NIR lamp as plant light with improved thermal stability for long-term operation.     

A Tradeoff Between Accuracy and Speed for K-Means Seed Determination

With a sharp increase in the information volume, analyzing and retrieving this vast data volume is much more essential than ever. One of the main techniques that would be beneficial in this regard is called the Clustering method. Clustering aims to classify objects so that all objects within a cluster have similar features while other objects in different clusters are as distinct as possible. One of the most widely used clustering algorithms with the well and approved performance in different applications is the k-means algorithm. The main problem of the k-means algorithm is its performance which can be directly affected by the selection in the primary clusters. Lack of attention to this crucial issue has consequences such as creating empty clusters and decreasing the convergence time. Besides, the selection of appropriate initial seeds can reduce the cluster’s inconsistency. In this paper, we present a new method to determine the initial seeds of the k-mean algorithm to improve the accuracy and decrease the number of iterations of the algorithm. For this purpose, a new method is proposed considering the average distance between objects to determine the initial seeds. Our method attempts to provide a proper tradeoff between the accuracy and speed of the clustering algorithm. The experimental results showed that our proposed approach outperforms the Chithra with 1.7% and 2.1% in terms of clustering accuracy for Wine and Abalone detection data, respectively. Furthermore, achieved results indicate that comparing with the Reverse Nearest Neighbor (RNN) search approach, the proposed method has a higher convergence speed.