基于改进MobileFaceNet的人脸识别方法北大核心

针对目前大多数人脸识别算法参数多、计算量大,难以部署到移动端和嵌入式设备中的问题,提出了一种基于改进MobileFaceNet的人脸识别方法。通过对MobileFaceNet模型结构的调整,将bottleneck模块优化为sandglass模块,改良深度卷积和逐点卷积的相对位置,适当增大sandglass模块的输出通道数,从而减少特征压缩时的信息丢失,增强人脸空间特征的提取。实验结果表明:改进后的方法在LFW测试数据集上准确率达99.15%,模型大小和计算量分别仅为原算法的61%和45%,验证了所提方法的有效性。     

爆破位置对深凹露天矿山炮烟扩散的影响研究

深凹露天矿山由于其特殊的结构,爆破产生的炮烟扩散稀释较为困难,严重危害生产作业人员的生命安全与健康。基于实际矿山构建了深凹露天矿山的二维物理及数学模型,采用非稳态数值分析方法研究了不同爆破位置下,深凹露天矿山采坑内爆破炮烟的扩散规律。研究结果表明：不同爆破位置下,露天采坑内均出现复环流,爆破点位置是影响露天采坑内风流结构特征的重要因素；露天采坑内的炮烟最高浓度均随着时间变化而逐渐下降,但下降的速率逐步减小,呈现三个阶段的下降趋势；爆破位置位于背风侧时露天采坑内的炮烟最高浓度和降至安全浓度所需时间远高于迎风侧三个爆破位置；随着背风侧爆破点距采坑底部距离的减小,炮烟最高浓度及降至安全浓度所需时间先降低后增加,炮烟最高浓度及降至安全浓度所需时间随着迎风侧爆破位置距采坑底部距离的减小而增加。研究结果对于指导深凹露天矿山企业合理组织爆破后的生产作业和保障作业人员安全具有重要意义。     

An analytical model for gas leakage through contact interface in proton exchange membrane fuel cells

Sealing performance between two contacting surfaces is of significant importance to stable operation of proton exchange membrane (PEM) fuel cells. In this work, an analytical micro-scale approach is first established to predict the gas leakage in fuel cells. Gas pressure and uneven pressure distribution at the interface are also included in the model. At first, the micro tortuous leakage path at the interface is constructed by introducing contact modelling and fractal porous structure theory. In order to obtain the leakage at the entire surface, contact pressure distribution is predicted based on bonded elastic layer model. The gas leakage through the discontinuous interface can be obtained with consideration of convection and diffusion. Then, experiments are conducted to validate the numerical model, and good agreement is obtained between them. Finally, influences of surface topology, gasket compression and gasket width on leakage are studied based on the model. The results show that gas leakage would be greatly amplified when the asperity standard deviation of surface roughness exceeds 1.0 μm. Gaskets with larger width and smaller thickness are beneficial to sealing performance. The model is helpful to understand the gas leakage behavior at the interface and guide the gasket design of fuel cells.     

Dynamic simulation of hydrogen-based off-grid zero energy buildings with hydrogen storage considering Fanger model thermal comfort

In this study, some locations with different climates, off-grid zero energy buildings with hydrogen energy storage systems are designed, and transient analysis is conducted. These considered buildings supply their electricity consumption without using the electrical grid and PV panels or wind turbines. Also, they supply thermal comfort to occupants by using a vapor compression chiller and humidifier. Domestic hot water of occupants is supplied using solar collectors. For analyzing building's performance and objectives achievement, TRNSYS software is used. Also, for evaluating occupant thermal comfort, the Fanger model is used. The considered building is a one-story building with a 150 m² area. Four occupants are considered. Both of them are seated at rest, and another is seated with light working such as typing. Using the Fanger model equation and MATLAB software, the thermal comfort of occupants is determined. For domestic hot water consumption, verified profiles that vary during 24 h of the day are considered. Achieved results show that for humid and cold cities, PV panels with an area of 73 and 76 m² can be supplied the required electricity of considered building with four occupants and battery state of charge is higher than 50% and 10%, respectively. Moreover, with a suitable air conditioner system, the predicted percentage of dissatisfied (PPD) can be lower than 12% and 8% for humid and cold cities. Therefore, the building can be converted to a zero-energy building using its rooftop area.     

A numerical study on nonlinear DPL model for analyzing heat transfer in tissue during thermal therapy

In the present paper, therapeutic treatment of infected tumorous cells has been studied through mathematical modeling and simulation of heat transfer in tissues by using a nonlinear dual-phase lag bioheat transfer model with Dirichlet boundary condition. The components of volumetric heat source in this model such as blood perfusion and metabolism are assumed experimentally validated temperature-dependent function, which gives more accurate temperature distribution in tissues through this model. We have used the finite difference and RK (4, 5) techniques of numerical methods to solve the proposed problem and obtained the exact solution in a particular case. After comparison, we got a good agreement between them. We have used dimensionless quantities throughout this paper. The effect of relaxation and thermalization time with respect to dimensionless temperature distribution has been analyzed in the treatment process.     

Farmers' preferences for adopting on-farm concentration of raw milk: Results from a discrete choice experiment in Germany

Milk concentrates are used in the manufacturing of dairy products such as yogurt and cheese or are processed into milk powder. Processes for the nonthermal separation of water and valuable milk ingredients are becoming increasingly widespread at farm level. The technical barriers to using farm-manufactured milk concentrate in dairies are minimal, hence the suspicion that the practice of on-farm raw milk concentration is still fairly uncommon for economic reasons. This study, therefore, set out to investigate farmers' potential willingness to adopt a raw milk concentration plant. The empirical analysis was based on discrete choice experiments with 75 German dairy farmers to identify preferences and the possible adoption of on-farm raw milk concentration. The results showed that, in particular, farmers who deemed the current milk price to be insufficient viewed on-farm concentration using membrane technology as an option for diversifying their milk sales. We found no indication that adoption would be impeded by a lack of trustworthy information on milk processing technologies or capital.     

Constitutive model for gas hydrate-bearing soils considering different types of hydrate morphology and prediction of strength-band

The present study proposes a new elasto-plastic constitutive model that considers different types of hydrates in pore spaces. Many triaxial compression tests on both methane hydrate-bearing soils and carbon dioxide hydrate-bearing soils have been carried out over the last few decades. It has been revealed that methane hydrate-bearing soils and carbon dioxide hydrate-bearing soils have different strength and dilatancy properties even though they have the same hydrate contents. The reason for this might be due to the different types of hydrate morphology. In this study, therefore, the effect of the hydrate morphology on the mechanical response of gas-hydrate-bearing sediments is investigated through a model analysis by taking into account the different hardening rules corresponding to each type of hydrate morphology. In order to evaluate the capability of the proposed model, it is applied to the results of past triaxial compression tests on both methane hydrate-containing and carbon dioxide hydrate-containing sand specimens. The model is found to successfully reproduce the different stress–strain relations and dilatancy behaviors, by only giving consideration to the different morphology distributions and not changing the fitting parameters. The model is then used to predict a possible range in which the maximum deviator stress can move for various hydrate morphology ratios; the range is defined as the strength-band. The predicted curve of the maximum deviator stress obtained by the constitutive model matches the empirical equations obtained from past experiments. It supports the fact that the hydrate morphology ratio changes with the total hydrate saturation. These findings will contribute to a better understanding of the relation between the microscopic structures and macro-mechanical behaviors of gas-hydrate-bearing sediments.     

一种直升机避障电力线检测方法

电力线是一类形状细长、特征稀疏、随着视角的变化容易混淆在大量背景信息中的特殊障碍物，常规电力线检测识别算法得到的目标框对电力线所在位置的估计不够准确。为此，提出了一种相对角度估计方法，基于常规电力线目标检测与识别算法，并结合电力线相对角度估计，从而提高电力线的检测识别过程中所在位置的精度。相比电力线绝对角度回归的方法，提出的相对角度估计方法容易训练易收敛，计算量小，适用于实时性要求较高的应用场合。     

5G核心网业务模型的智能化预测研究

摘 要：核心网业务模型的建立是5G网络容量规划和网络建设的基础，通过现有方法得到的理论业务模型是静态不可变的且与实际网络存在偏离。为了克服现有5G核心网业务模型与现网模型适配性较差以及规划设备无法满足用户实际业务需求的问题，提出了一种长短期记忆（long short-term memory，LSTM）网络与卷积LSTM （convolution LSTM，ConvLSTM）网络双通道融合的 5G 核心网业务模型预测方法。该方法基于人工智能（artificial intelligence，AI）技术以实现高质量的核心网业务模型的智能预测，形成数据反馈闭环，实现网络自优化调整，助力网络智能化建设。