基于改进Double-Head RCNN的无人机航拍图像小目标检测算法

为解决无人机航拍图像中小目标特征信息少且容易被噪声干扰导致现有算法漏检率和误检率高的问题,提出一种改进Double-Head Region-卷积神经网络(RCNN)的无人机航拍图像小目标检测算法。在骨干网络ResNet-50上引入Transformer和可变形卷积(DCN)模块,更有效提取小目标特征信息和语义信息;提出一种基于内容感知特征重组(CARAFE)的特征金字塔网络(FPN)结构模块,解决特征融合过程中小目标被背景噪声干扰而丢失特征信息的问题;在区域建议网络中针对小目标尺度分布特点重新设置Anchor生成尺度,进一步提升小目标检测性能。在VisDrone-DET2021数据集上的实验结果表明:所提算法能提取更具有表征能力的小目标特征信息和语义信息,对比Double-Head RCNN算法,所提算法的参数量增加了9.73×10^(6),FPS损失了0.6,但是AP、AP50和AP75分别提升了2.6%、6.2%和2.1%,APs提升了3.1%。

Observer-based robust high-order fully actuated attitude autopilot design for spinning glide-guided projectiles

This paper investigates the design of an attitude autopilot for a dual-channel controlled spinning glideguided projectile(SGGP),addressing model uncertainties and external disturbances.Based on fixed-time stable theory,a disturbance observer with integral sliding mode and adaptive techniques is proposed to mitigate total disturbance effects,irrespective of initial conditions.By introducing an error integral signal,the dynamics of the SGGP are transformed into two separate second-order fully actuated systems.Subsequently,employing the high-order fully actuated approach and a parametric approach,the nonlinear dynamics of the SGGP are recast into a constant linear closed-loop system,ensuring that the projectile's attitude asymptotically tracks the given goal with the desired eigenstructure.Under the proposed composite control framework,the ultimately uniformly bounded stability of the closed-loop system is rigorously demonstrated via the Lyapunov method.Validation of the effectiveness of the proposed attitude autopilot design is provided through extensive numerical simulations.

Not in Control,but Liable?Attributing Human Responsibility for Fully Automated Vehicle Accidents

Human agency has become increasingly limited in complex systems with increasingly automated decision-making capabilities.For instance,human occupants are passengers and do not have direct vehicle control in fully automated cars(i.e.,driverless cars).An interesting question is whether users are responsible for the accidents of these cars.Normative ethical and legal analyses frequently argue that individuals should not bear responsibility for harm beyond their control.Here,we consider human judgment of responsibility for accidents involving fully automated cars through three studies with seven experiments(N=2668).We compared the responsibility attributed to the occupants in three conditions:an owner in his private fully automated car,a passenger in a driverless robotaxi,and a passenger in a conventional taxi,where none of these three occupants have direct vehicle control over the involved vehicles that cause identical pedestrian injury.In contrast to normative analyses,we show that the occupants of driverless cars(private cars and robotaxis)are attributed more responsibility than conventional taxi passengers.This dilemma is robust across different contexts(e.g.,participants from China vs the Republic of Korea,participants with first-vs third-person perspectives,and occupant presence vs absence).Furthermore,we observe that this is not due to the perception that these occupants have greater control over driving but because they are more expected to foresee the potential consequences of using driverless cars.Our findings suggest that when driverless vehicles(private cars and taxis)cause harm,their users may face more social pressure,which public discourse and legal regulations should manage appropriately.

Enhancing efficiency and stability of organic solar cells through a simplified four-step synthesis of fully non-fused ring electron acceptor

Design and synthesis of superior cost-effective non-fullerene acceptors(NFAs)are still big challenges for facilitating the commercialization of organic solar cells(OSCs),yet to be realized.Herein,two medium bandgap fully non-fused ring electron acceptors(NFREAs,medium bandgap,i,e.,1,3-1,8 eV),namely PTR-2Cl and PTR-4Cl are synthesized with only four steps by using intramolecular noncovalent interaction central core,structured alkyl side chain orientation linking units and flanking with different electron-withdrawing end group.Among them,PTR-4C1 exhibits increased average electrostatic potential(ESP)difference with polymer donor,enhanced crystallinity and compactπ-πstacking compared with the control molecule PTR-2CI.As a result,the PTR-4Cl-based OSC achieved an impressive power conversion efficiency(PCE)of 14.72%,with a much higher open-circuit voltage(V_(OC))of 0.953 V and significantly improved fill factor(FF)of 0.758,demonstrating one of the best acceptor material in the top-performing fully NFREA-based OSCs with both high PCE and V_(OC).Notably,PTR-4Cl-based cells maintain a good T_80lifetime of its initial PCE after over 936 h under a continuous thermal annealing treatment and over1300 h T_(80)lifetime without encapsulation.This work provides a cost-effective design strategy for NFREAs on obtaining high V_(OC),efficient exciton dissociation,and ordered molecular packing and thus high-efficiency and stable OSCs.

Design of Fully Automatic Specification Selection System for Resistance Welding Equipment

A system for fully automatic selection of welding specifications in resistance welding equipment has been developed to address the problem of workers frequently choosing the wrong specifications during manual welding of multiple parts on a single machine in automobile factories. The system incorporates an automatic recognition system for different workpiece materials using the added machine fixture,visual detection system for nuts and bolts,and secondary graphical confirmation to ensure the correctness of specification calling. This system achieves reliable,fully automatic selection of welding specifications in resistance welding equipment and has shown significant effects in improving welding quality for massproduced workpieces,while solving the problem of specification calling errors that can occur with traditional methods involving process charts and code adjustments. This system is particularly suitable for promoting applications in manual welding of multiple parts on a single machine in automobile factories,ensuring correct specification calling and welding quality.

Optimal Cooperative Secondary Control for Islanded DC Microgrids via a Fully Actuated Approach

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

GRU-integrated constrained soft actor-critic learning enabled fully distributed scheduling strategy for residential virtual power plant

In this study,a novel residential virtual power plant(RVPP)scheduling method that leverages a gate recurrent unit(GRU)-integrated deep reinforcement learning(DRL)algorithm is proposed.In the proposed scheme,the GRU-integrated DRL algorithm guides the RVPP to participate effectively in both the day-ahead and real-time markets,lowering the electricity purchase costs and consumption risks for end-users.The Lagrangian relaxation technique is introduced to transform the constrained Markov decision process(CMDP)into an unconstrained optimization problem,which guarantees that the constraints are strictly satisfied without determining the penalty coefficients.Furthermore,to enhance the scalability of the constrained soft actor-critic(CSAC)-based RVPP scheduling approach,a fully distributed scheduling architecture was designed to enable plug-and-play in the residential distributed energy resources(RDER).Case studies performed on the constructed RVPP scenario validated the performance of the proposed methodology in enhancing the responsiveness of the RDER to power tariffs,balancing the supply and demand of the power grid,and ensuring customer comfort.

Fuzzy Inventory Model under Selling Price Dependent Demand and Variable Deterioration with Fully Backlogged Shortages

The objective is to develop a model considering demand dependent on selling price and deterioration occurs after a certain period of time, which follows two-parameter Weibull distribution. Shortages are allowed and fully backlogged. Fuzzy optimal solution is obtained by considering hexagonal fuzzy numbers and for defuzzification Graded Mean Integration Representation Method. A numerical example is provided for the illustration of crisp and fuzzy, both models. To observe the effect of changes in parameters, sensitivity analysis is carried out.

温度对不同饱和状态全风化泥岩抗剪强度的影响

为研究温度对不同饱和状态全风化泥岩抗剪强度的影响,以典型季冻区全风化泥岩试样为研究对象,利用GDS非饱和试验系统,对饱和状态及天然非饱和状态下的全风化泥岩分别进行室内三轴试验,研究不同温度对其抗剪强度参数的影响,并对比分析饱和状态及天然非饱和状态下全风化泥岩抗剪强度参数之间的区别。结果表明:全风化泥岩强度受饱和度与温度影响较大。随温度降低两种土样的黏聚力均增加,内摩擦角均先增加再减小。温度与试验系统条件一致时,非饱和全风化泥岩试样黏聚力始终大于饱和全风化泥岩试样。饱和度对试样的内摩擦角影响较小,两种土样的内摩擦角分别在-5℃与0℃时达到峰值。研究成果可为季冻区不同饱和状态全风化泥岩地层中,工程的设计施工及方案优化过程中力学参数的选取等方面提供理论参考和指导。

WADdiana Compact全自动血型分析仪偶见故障及排除

介绍了WADdiana Compact全自动血型分析仪在使用中出现的5例偶见故障,详细分析了故障原因,提出了具体的排除方法,为同行维修类似故障提供了参考。

综放工作面动态注氮参数研究及数值模拟

针对目前防灭火注氮工程中存在的资源浪费、效率低等问题,本文提出了一种动态注氮的防灭火方法。围绕朱仙庄矿884工作面,开展采空区自燃“三带”测定,通过连续监测束管数据获得氧气浓度。依据氧气浓度含量,利用Fluent模拟软件构建计算模型,模拟不同注氮位置和注氮流量对自燃“三带”分布的影响,确定动态注氮工艺参数。结果表明:注氮位置在进风侧距离工作面30~60 m,注氮量为440~500 m^(3)/h时,动态注氮防灭火效果最佳,效益最好。

全自动运行列车制动电阻液压风机自动控制方法研究

全自动运行列车制动电阻液压风机是一种利用液压技术驱动的设备,在列车运行过程中,其性能受到多个因素影响,容易导致输出气流或气压不稳定问题,因此研究全自动运行列车制动电阻液压风机的自动控制技术具有重要意义。在列车与轨道间作用力的基础上,构建列车制动模型,获取制动力矩,将相对扭转角作为基础,计算自旋蠕滑力矩,根据瞬时蠕滑速度,计算出列车车轮与轨道间的粘着力矩;构建列车驱动模型,建立制动力矩主动分配目标函数,利用Park变换和Clarke变换,获取电阻液压风机电磁转矩,通过转子磁链与控制频率实现电阻液压风机的自动控制。实验结果表明:该控制方法在列车制动控制过程中,其风机效率及恒速占比均值分别为5.26 s和99.77%,控制电阻后的风机电压与理想电压基本一致,能够高效恒定的实现制动电阻液压风机控制,提高列车的安全性。

Orlicz空间的Fully k凸

赋Orlicz范数的Orlicz空间当且仅当自反严格凸时具有Fully k凸(k≥z)

Realization of Fully Differential Fourth-Order Bessel Filter with Accurate Group Delay

A fully differential R-MOSFET-C fourth-order Bessel active lowpass filter employing fully differential operational amplifier,passive resistors,and current-steering MOS transistors as a variable resistor is proposed.This proposed implementation relies on the tunability of current-steering MOS transistors operating in the triode region counteracting the concert deviation of resistor in the integrated circuit manufacturing technology in orde r that the group delay of Bessel active filter could be designed accurately.The amplifier is not only with voltage common-mode negative feedback,but also with current common-mode negative feedback,which will benefit for the stability of its D C operating point.0.75μs group delay fourth-order Bessel lowpass filter,whic h is synthesized according to passive doubly terminated RLC prototype lowpass filter,demonstrates better than -65dB THD using 100kHz,2.5V pp signal in Taiwan UMC 2P2M(2-poly,2-metal)5.0V,0.5μm CMOS technology.

程度副词TOTALLY和FULLY的语义韵对比分析——一项基于BNC和CLEC语料库的研究

本研究以CLEC和BNC语料库为基础,通过检索软件AntConc对程度副词totally和fully进行语义韵对比分析,揭示了中国英语学习者和英语本族语使用者在使用这两个词时产生的不同语义韵特征,分析了产生差异的原因并对英语教学尤其是词汇教学提出了积极的建议。本研究的结果将有助于促进学习者对词语搭配和语义韵的习得,加深学习者对语言现象的理解并将在一定程度上拓展词汇教学的内容和词汇教学的方法。

基于强化学习的完全分布式事件驱动二分一致性算法

使用强化学习(Reinforcement Learning,RL)方法和基于事件驱动的完全分布式控制策略来研究系统模型信息未知的多智能体系统(MASs)的二分一致性问题。首先,基于状态阈值和时间阈值提出了一种混合事件触发机制,用于减少智能体间的通信频率。其次,利用局部采样的状态信息设计了一个自适应事件触发一致性控制协议,使所有追随智能体的二分一致性误差最终趋于零。通过排除有限时间内的芝诺(Zeno)行为,证实了上述事件触发机制的有效性。然后,基于RL方法提出了一种无模型算法来获得反馈增益矩阵,并在模型信息未知的情况下实现了自适应事件触发控制策略的构建。与现有的相关工作不同,这种基于RL的事件触发自适应控制算法只依赖于局部采样的状态信息,与任何模型信息或全局网络信息无关。此外,将上述结果扩展到切换拓扑情形,这更具挑战性,因为状态估计在以下两种情况下更新:1)交互图切换时;2)事件触发机制满足时。最后,通过实例验证了上述自适应事件触发控制算法的有效性。

Threshold Voltage Model for a Fully Depleted SOI-MOSFET with a Non-Uniform Profile

A novel approximation of the two-dimensional （2D） potential function perpendicular to the channel is proposed,and then an analytical threshold voltage model for a fully depleted SOI-MOSFET with a non-uniform Gaussian distribution doping profile is given based on this approximation. The model agrees well with numerical simulation by MEDICI. The result represents a new way and some reference points in analyzing and controlling the threshold voltage of non-uniform fully depleted （FD） SOI devices in practice.

高精度可扩展的密态隐私保护语音分类

为解决现有全同态加密技术在语音分类任务中计算效率和分类准确率均较低的挑战,提出一种高精度可扩展的密态隐私保护语音分类PPSC方案。设计基于CKKS全同态加密技术两方服务器协同的安全乘法协议,因避免使用昂贵的自举操作,可有效提升深层次密文乘法的计算效率,从而使得方案可扩展到更深层次的神经网络;基于上述架构设计安全指数、安全倒数以及安全比较等安全非多项式协议,相较于多项式近似拟合非多项式运算的方法,在提高计算精度的同时,降低了计算开销。安全实现卷积层、ReLU层、平均池化层、全连接层、Softmax层等PPSC方案的基本模块,确保语音数据、语音模型和中间计算结果的隐私性。从有效性和安全性等维度对PPSC方案进行了详尽的理论分析,证明安全乘法协议在更深层次的乘法运算中具有更高的运算效率。在Speech Command Database语音数据集上的实验结果表明,PPSC方案可以在保护数据和模型参数隐私的情况下实现有效的语音分类,其准确率相比于HEKWS方案提高3.57个百分点。

Two Second-Order Ecient Numerical Schemes for the Boussinesq Equations

In this paper,we construct two fully decoupled,second-order semi-discrete numerical schemes for the Boussinesq equations based on the scalar auxiliary variable(SAV)approach.By introducing a scalar auxiliary variable,the original Boussinesq system is transformed into an equivalent one.Then we discretize it using the second-order backward di erentiation formula(BDF2)and Crank-Nicolson(CN)to obtain two second-order time-advanced schemes.In both numerical schemes,a pressure-correction method is employed to decouple the velocity and pressure.These two schemes possess the desired property that they can be fully decoupled with satisfying unconditional stability.We rigorously prove both the unconditional stability and unique solvability of the discrete schemes.Furthermore,we provide detailed implementations of the decoupling procedures.Finally,various 2D numerical simulations are performed to verify the accuracy and energy stability of the proposed schemes.

An Analytical Threshold Voltage Model for Fully Depleted SOI MOSFETs

A new two-dimensional （2D） analytical model for the threshold-voltage of fully depleted SOI MOSFETs is derived. The 2D potential distribution functions in the active layer of the devices are obtained through solving the 2D Poisson＇s equation. The minimum of the potential at the oxide-Si layer interface is used to monitor the threshold voltage of the SOI MOSFETs. This model is verified by its excellent agreement with MEDICI simulation using SOI MOSFETs with different gate lengths,gate oxide thicknesses,silicon film thicknesses,and channel doping concentrations.