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。     

Visible light active Cu-doped iron oxide for photocatalytic treatment of methylene blue

In recent work, pure α-Fe₂O₃ (F-1) and series of 5% Cu doped Fe₂O₃ (CF-5) , 10% Cu doped Fe₂O₃ (CF-10) and 15% Cu doped Fe₂O₃ (CF-15) nanoparticles by facile chemical coprecipitation method were synthesized to study the effect of concentration of doping for photocatalytic activity. As prepared F-1, CF-5, CF-10, CF-15 nanoparticles were subjected to X-ray diffraction (XRD) and Fourier transform infra-red (FTIR) techniques to analyse the structural and functional groups features. These characterization techniques confirmed the successful doping of Cu ²⁺ ions in α-Fe₂O₃. The crystallite size of synthesized samples was calculated by Scherrer formula. Gradually decline in crystallite size from 18 to 15 nm was observed for undoped to doped samples. Scanning electron microscopic (SEM) analysis expressed that doping of Cu reduced the aggregation of particles and enhanced the surface area of nanoparticles. UV–Visible spectroscopic analysis of synthesized samples was used to calculate the bandgap energy of F-1, CF-5, CF-10, CF-15 nanoparticles i.e., 2.0, 1.7, 1.5, 1.4eV respectively. Narrowing bandgap energy of doped hematite supported to perform excellent photocatalytic activity. Maximum degradation of methylene blue was recorded via CF-10 within 140 min. Higher degradation rate of methylene blue by optimal concentration of CF-10 is due to effective electron trapping ability of photocatalyst.     

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.     

Comparative analysis on temperature characteristics of hydrogen-powered and traditional fossil-fueled vehicle fires in the tunnel under longitudinal ventilations

Vehicle fires in the tunnel are a great threat to the safe operation of the tunnel. Due to the rapid development of the hydrogen economy, the fire due to the hydrogen leakage could not be avoided and may bring great damage to the passengers and infrastructure. Due to the large difference between pool fires of traditional fossil-fueled and jet fires of hydrogen-powered vehicles, it is in doubt whether the existing longitudinal ventilation design could still be effective for the safety issue of hydrogen powered vehicles. To solve this problem, it is necessary to compare temperature characteristics of hydrogen-powered and traditional vehicle fires with and without longitudinal ventilations. In present work, we conducted a numerical investigation to discuss the different temperature distributions of traditional and hydrogen-fueled vehicle fires. Results indicate that the high temperature zone of the pool fire only exists above the ceiling of the vehicle. For hydrogen-powered vehicle fire, the high-speed hydrogen jet with the strong inertial force could push the hot smoke flows back to the ground. The ceiling temperature of hydrogen-powered vehicle fire is larger since hydrogen-powered vehicle has a larger heat release rate and the fire hazard of jet fires bring more danger compared with the pool fire. Although the temperature stratification is also obvious for the hydrogen-powered vehicle fire, the air temperature in the lower region could be heated and still high enough to bring a great damage to the passengers’ lives. This is quite different with the traditional pool fire. In addition, the critical ventilation velocity is also discussed. The theoretical equation could well predicted the critical ventilation velocity of traditional vehicle fires. For hydrogen-powered vehicle fires, the critical ventilation velocity could reach up to 6 m/s. The theoretical equation could not well predict the critical ventilation velocity of hydrogen-powered vehicle fires due to exist of hydrogen jet fires.     

汉江上游干支流沉积物细菌群落多样性和影响因素

为了解汉江上游干支流沉积物细菌多样性以及确定性过程和随机性过程在沉积物细菌群落构建过程中的相对重要性,基于Illumina高通量测序技术,分析了环境因子对细菌群落组成的影响,采用非度量多维尺度(NMDS)排序探究了季节之间沉积物细菌群落的差异,并结合中性群落模型和标准化随机率量化了确定性过程和随机过程对群落构建的影响。结果表明:汉江上游及其支流细菌群落主要由变形菌门(Proteobacteria)、拟杆菌门(Bacteroidetes)、蓝藻门(Cyanophyta)、浮霉菌门(Planctomycetes)和酸杆菌门(Acidobacteria)等组成；细菌群落在不同季节有显著差异；地理距离和环境因子对细菌群落结构影响较小,确定性过程并未在细菌群落组成中起到主导作用；随机过程很大程度上影响了群落在秋季和春季的组成,是沉积物细菌群落构建的主导因素。     

Efficiency evaluation of healthcare services in China based on stochastic multicriteria acceptability analysis and directional distance function

Evaluating the efficiency of healthcare services accurately can help in analyzing the rationality of inputs and outputs in such services. Considering the consistency and equity of assessment criteria, this study conducts the stochastic multicriteria acceptability analysis (SMAA-2) with a directional distance function to evaluate the efficiency of healthcare services in 31 provincial administrative regions of mainland China, as observed in 2018. We use SMAA-DDF to explore all the projection directions to the efficient frontier instead of a certain projection direction. We measure the maximum and average efficiencies for each of the 31 provincial healthcare services. Our empirical findings show that only seven provinces achieve optimal healthcare service efficiency; the eastern area performed the best, followed by the central, western, and northeast areas. Furthermore, the path along the projection directions is provided to help inefficient provinces improve their efficiency and obtain the best possible positions.     

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.     

Synthesis and characterization of ZnO NRs with spray coated GO for enhanced photocatalytic activity

Zinc oxide nanorods, ZnO NRs, were synthesized on a clean glass and coated with graphene oxide (GO) using spray coating method to enhance the photocatalytic activity in wastewater treatment. The ZnO NRs were synthesized using the solution process synthesis that was optimized using Taguchi method. Several synthesis parameters have been optimized and studied to determine the best synthesis parameter to grow ZnO NRs for the photodegradation of organic contaminants. Field emission scanning electron microscopy (FESEM) with EDX, X-ray diffraction (XRD), Raman, ultraviolet visible near-infrared (UV-VIS-NIR), and photoluminescence (PL) spectroscopies were used to investigate the structural and optical properties of the produced nanorods. FESEM images revealed the vertical growth of ZnO NRs as well as layers of GO covering the ZnO NRs' top surface. The Raman study demonstrates the combination peak of GO and ZnO, hence proving the GO layer's successful coating. After the GO coating, decrease in the bandgap of the synthesized photocatalyst was detected by PL and UV–Vis absorption measurements. Under UVC exposure with treatment time of 6 h, the degradation of MB with ZnO NRs/GO photocatalyst reached a degradation percentage of 97.86%, which is greater than the degradation percentage achieved using pristine ZnO NRs, which is 93.28%. The results validated that the coating of GO enhances the photocatalytic activity of the host material, ZnO NRs.     

Fire safe,sustainable loose furnishing

The aim of this exploratory study has been to investigate the fire properties and environmental aspects of different upholstery material combinations, mainly for domestic applications. An analysis of the sustainability and circularity of selected textiles, along with lifecycle assessment, is used to qualitatively evaluate materials from an environmental perspective. The cone calorimeter was the primary tool used to screen 20 different material combinations from a fire performance perspective. It was found that textile covers of conventional fibres such as wool, cotton and polyester, can be improved by blending them with fire resistant speciality fibres. A new three‐dimensional web structure has been examined as an alternative padding material, showing preliminary promising fire properties with regard to ignition time, heat release rates and smoke production.