基于QBD法和PAT法的经典名方制剂示例研究教学改革探讨

目的探究质量源于设计(QBD)法与过程分析技术(PAT)法在经典名方制剂示例研究课程教学中的应用及其推进教学改革中的作用。方法选择2023年1~12月两个学期选课成功的学生作为研究对象,采用传统教学模式与经QBD法设计的教学模式对比教学,通过学生的分段成绩和调查问卷的形式考察两种教学模式的教学效果。结果教学结束后,传统教学模式与经QBD法设计的教学模式学生得分情况:预实验设计平均成绩分别为54分和76分,实验操作技能平均成绩分别为75分和90分,实验报告平均成绩为69分和87分,期末实验方案设计平均成绩分别为65分和89分;学生的满意度调查结果:不满意为23%和5%,较为满意为38%和24%,满意为39%和71%。结论经QBD法设计的教学模式教学效果优于传统教学模式,能明显提升学生的课程学习和科研能力。同时,基于PAT理念,提出了对该课程教学的一些改革设想和具体实施方法。

基于PAT 模型的下肢骨折康复心流要素研究

研究基于PAT(个体-产品-任务模型,Person-Artifact-Task的简称)心流模型,对下肢骨折康复中的心流体验要素进行研究,以期提升下肢骨折康复人群训练体验。采用半结构化访谈提取心流关键词,再结合成熟的心流前因要素研究结果和PAT模型构建个体动机-康复产品-训练任务模型并设计量表,获取目标人群原始数据。以此为基础,建立下肢骨折康复心流体验结构方程模型,得到影响心流产生各项要素的权重分布,最后根据权重分布提出下肢骨折康复产品设计策略。研究深度解析心流体验要素的量化方法,提升康复产品的用户体验,为下肢骨折康复产品设计提供有益参考。

板栗PAT基因家族成员鉴定及不同胁迫响应分析

【目的】鉴定和分析板栗PAT基因家族及其对不同胁迫的响应,探究板栗PAT基因家族的抗逆功能。【方法】在板栗全基因组水平上进行搜索和鉴定板栗PAT基因家族成员,利用生物信息学方法研究其系统发育进化树、基因结构和motif、蛋白理化性质、染色体定位、共线性和启动子顺式元件等。以燕山红栗为试验材料,分析盐胁迫、抗病胁迫和干旱胁迫处理对板栗PAT基因家族表达模式的影响。【结果】在板栗基因组中共鉴定出包含DHHC结构域的21个PAT基因家族成员,他们与24个AtPAT基因家族成员共聚集为6个亚组;大多数CmPAT家族成员为具有亲水性的碱性稳定蛋白;21个PAT基因家族成员不均匀地分布在板栗的9条染色体上;在CmPAT基因启动子区域鉴定到多种非生物胁迫及激素响应元件;表达模式分析表明,多个CmPAT基因不同程度地参与抗病、干旱、盐胁迫响应。【结论】共鉴定了21个板栗PAT基因家族成员,同时筛选到CmPAT24、CmPAT7、CmPAT14可能共同参与了盐胁迫和干旱胁迫的调控,CmPAT7可能共同参与盐胁迫、干旱胁迫、抗病胁迫的调控。

Aircraft Engine Gas Path Fault Diagnosis Based on Hybrid PSO-TWSVM

Twin support vector machine(TWSVM)is a new development of support vector machine(SVM)algorithm.It has the smaller computation scale and the stronger ability to cope with unbalanced problems.In this paper,TWSVM is introduced into aircraft engine gas path fault diagnosis.The generalization capacity of Gauss kernel function usually used in TWSVM is relatively weak.So a mixed kernel function is used to improve performance to ensure that the TWSVM algorithm can better balance a strong generalization ability and a good learning ability.Experimental results prove that the cross validation training accuracy of TWSVM using the mixed kernel function averagely increases 2%.Grid search is usually applied in parameter optimization of TWSVM,but it heavily depends on experience.Therefore,the hybrid particle swarm algorithm is introduced.It can intelligently and rapidly find the global optimum.Experiments prove that its training accuracy is better than that of the classical particle swarm algorithm by 5%.

Effective path planning method for low detectable aircraft

To utilizing the characteristic of radar cross section （RCS） of the low detectable aircraft, a special path planning algorithm to eluding radars by the variable RCS is presented. The algorithm first gives the RCS changing model of low detectable aircraft, then establishes a threat model of a ground-based air defense system according to the relations between RCS and the radar range coverage. By the new cost functions of the flight path, which consider both factors of the survival probability and the distance of total route, this path planning method is simulated based on the Dijkstra algorithm, and the planned route meets the flight capacity constraints. Simulation results show that using the effective path planning algorithm, the low detectable aircraft can give full play to its own advantage of stealth to achieve the purpose of silent penetration.

Path-tracking Control of a Tractor-aircraft System

An aircraft tractor plays a significant role as a kind of important marine transport and support equipment. It＇s necessary to study its controlling and manoeuvring stability to improve operation efficiency. A virtual prototyping model of the tractor-aircraft system based on Lagrange＇s equation of the first kind with Lagrange mutipliers was established in this paper, According to the towing characteristics, a path-tracking controller using fuzzy logic theory was designed. Direction control herein was carried out through a compensatory tracking approach. Interactive co-simulation was performed to validate the path-tracking behavior in closed-loop, Simulation results indicated that the tractor followed the reference courses precisely on a flat ground.

Optimal control based coordinated taxiing path planning and tracking for multiple carrier aircraft on flight deck

Coordinated taxiing planning for multiple aircraft on flight deck is of vital importance which can dramatically improve the dispatching efficiency.In this paper,first,the coordinated taxiing path planning problem is transformed into a centralized optimal control problem where collision-free conditions and mechanical limits are considered.Since the formulated optimal control problem is of large state space and highly nonlinear,an efficient hierarchical initialization technique based on the Dubins-curve method is proposed.Then,a model predictive controller is designed to track the obtained reference trajectory in the presence of initial state error and external disturbances.Numerical experiments demonstrate that the proposed“offline planningþonline tracking”framework can achieve efficient and robust coordinated taxiing planning and tracking even in the presence of initial state error and continuous external disturbances.

Mechanical Dispatch Reliability Prediction for Civil Aircraft Considering Operational Parameters

To effectively predict the mechanical dispatch reliability(MDR),the artificial neural networks method combined with aircraft operation health status parameters is proposed,which introduces the real civil aircraft operation data for verification,to improve the modeling precision and computing efficiency.Grey relational analysis can identify the degree of correlation between aircraft system health status(such as the unscheduled maintenance event,unit report event,and services number)and dispatch release and screen out themost closely related systems to determine the set of input parameters required for the prediction model.The artificial neural network using radial basis function(RBF)as a kernel function,has the best applicability in the prediction of multidimensional,small sample problems.Health status parameters of related systems are used as the input to predict the changing trend ofMDR,under the artificial neural network modeling framework.The case study collects real operation data for a certain civil aircraft over the past five years to validate the performance of the model which meets the requirements of the application.The results show that the prediction quadratic error Ep of the model reaches 6.9×10−8.That is to say,in the existing operating environment,the prediction of the number of delay&cancel events per month can be less than once.The accuracy of RBF ANN,BP ANN and GA-BP ANN are compared further,and the results show that RBF ANN has better adaptability to such multidimensional small sample problems.The efforts of this paper provide a highly efficientmethod for theMDR prediction through aircraft system health state parameters,which is a promising model to enhance the prediction and controllability of the dispatch release,providing support for the construction of the civil aircraft operation system.

Optimization of press bend forming path of aircraft integral panel

In order to design the press bend forming path of aircraft integral panels,a novel optimization method was proposed, which integrates FEM equivalent model based on previous study,the artificial neural network response surface,and the genetic algorithm.First,a multi-step press bend forming FEM equivalent model was established,with which the FEM experiments designed with Taguchi method were performed.Then,the BP neural network response surface was developed with the sample data from the FEM experiments.Furthermore,genetic algorithm was applied with the neural network response surface as the objective function. Finally,verification was carried out on a simple curvature grid-type stiffened panel.The forming error of the panel formed with the optimal path is only 0.098 39 and the calculating efficiency has been improved by 77%.Therefore,this novel optimization method is quite efficient and indispensable for the press bend forming path designing.

Engine-Out Takeoff Path Optimization for Large Civil Aircraft

Maximum regulated takeoff weights and hence payloads of large commercial jets are limited by government regulations which take into account local airport conditions as well as a variety of safety factors. One of the challenging conditions that must be met is linked to a minimum obstacle clearance in the unlikely event of an engine failure on the runway at the worst possible time. This requirement becomes an overriding factor for airports surrounded by challenging terrain, and therefore a well defined takeoff path out of these airports has the potential to transform a financially unsustainable operation into a commercially viable one. The research described in this paper represents an ongoing attempt to resolve this important problem and makes use of recent advances in robot path planning techniques.

循证家庭教育指导服务:美国PAT项目的实践启示

家庭教育指导服务是一种重要的家庭教育培训、引导活动。伴随着循证教育理念的逐步深入,家庭教育指导也逐渐向基于证据的循证式服务转型。美国循证家庭教育指导服务的杰出代表PAT项目以发现家庭教育指导问题、获取家庭教育指导证据、评估并选择证据、改进家庭教育指导服务质量为实施路径。遵循以能力建设为基础、以精准服务为目标、以标准规范为保障、以多维评估为推力的行动逻辑,实现家庭教育指导服务效能提升。客观认识循证家庭教育指导服务的实践特征与难点,可为我国家庭教育指导服务提供经验参考。

CABIN NOISE SOURCE-PATH IDENTIFICATIONFOR AD-200 ULTRALIGHT AIRCRAFT

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黏性条件下基于导叶和叶轮匹配关系的多级导叶式离心泵PAT性能预测

在实际流程工业中,用单级蜗壳式离心泵反转作透平无法有效地从高压液体系统中回收能量,需采用多级导叶式离心泵反转作透平来回收这部分能量,而现阶段理论不能预测多级导叶式离心泵在透平工况下最优工况点性能参数。此外,离心泵作透平回收液体余压能量时,实际流道内液体往往具有一定的黏度,介质黏度的变化会导致其在透平工况下最优工况点的性能参数较介质为清水时会有差异。为研究实际工业流程中多级导叶式离心泵的选型问题,借鉴离心泵叶轮和压水室的匹配原理和ISO国际标准《输送黏性介质离心泵的性能修正》的修正方法,理论推导了黏性条件下基于导叶与叶轮匹配关系的性能预测公式,得到介质为黏性液体时泵工况与透平工况之间的流量之比与扬程之比,通过数值模拟的方法验证理论推导的准确性。结果表明,性能预测公式得到的流量之比与数值模拟方法得到的流量之比的误差在4%~6%,而扬程之比与数值模拟结果之间的误差在2%~7%。证明研究可为多级导叶式离心泵作透平用于回收黏性液体中余压能量时的选型提供依据。

A Modified Four Path Method for Calculating Coupling Field of Super-Low Altitude Aircraft Target

A novel modified four path method (FPM) is presented for calculating coupling field of super-low altitude aircraft target. Based on the hybrid method PO + MEC (Physical Optics and Method of Equivalent Currents), the antenna radiation pattern is introduced to consider the multipath interference from side lobe of seeker. The modified FPM is used to calculate the coupling field from super-low altitude aircraft target above different terrestrial environments. The curves of scattering coefficient are analyzed. The influences of height of target, root mean square (RMS), and incident angle on coupling field characteristics are discussed. The simulation results can be used for reference in detection for super-low altitude target and optimization for radar system.

Spatial Organization Mechanism of Aircraft Manufacturing

Unquestionably,aircraft industry plays an important part in both economy and security of a nation.However,few of articles have dealt with the spatial development of this industry sector.The purpose of this article is to analyze the dynamics of agglomeration and diffusion of aircraft industry.In a historical view,with some spatial analysis methods,this research discusses the characteristics and patterns of aircraft industry's spatial organization and evolution,globally,nationally and regionally respectively.We find out there is a ‘Matthew effect' in aircraft industry of the world,and the spatial evolution of the industry is consistent with the nation's industrialization process.Then,it concludes that the main agglomeration forces consist of capital,talents,technology and cluster's advantages,and the main diffusion forces include comparative advantages,cost and risk sharing,emerging markets,development policy for backward regions and military requirements.All the factors can be divided into market forces making the spatial development of aircraft industry normal and non-market forces making that irregular.In particular,lessons from the USA and France are expected to be conducive to the rise of China's aircraft industry in the future.

Fuzzy Q learning algorithm for dual-aircraft path planning to cooperatively detect targets by passive radars

The problem of passive detection discussed in this paper involves searching and locating an aerial emitter by dualaircraft using passive radars. In order to improve the detection probability and accuracy, a fuzzy Q learning algorithrn for dual-aircraft flight path planning is proposed. The passive detection task model of the dual-aircraft is set up based on the partition of the target active radar＇s radiation area. The problem is formulated as a Markov decision process （MDP） by using the fuzzy theory to make a generalization of the state space and defining the transition functions, action space and reward function properly. Details of the path planning algorithm are presented. Simulation results indicate that the algorithm can provide adaptive strategies for dual-aircraft to control their flight paths to detect a non-maneuvering or maneu- vering target.

The Aircraft Industry in Japan： Niche Construction and Patent Portfolio Strategy

The Japanese aircraft industry changed its course in approximately 2007. Mitsubishi Heavy Industry （MHI） Co. launched a project in which regional jets （Mitsubishi Regional Jet （MILl）） reentered the airliner manufacturing market. Honda announced plans to develop, manufacture, and sell small passenger jets, or Honda Jets, in the United States （US） market. This paper summarizes the historical development of the industry using aircraft production statistics and analyzes the patent portfolio strategy from 1995 to 2006, a period in which MHI and Honda accumulated patents for the upcoming market entry. The author uses the following two measurements to evaluate niche widths among aircraft manufacturing companies： the Morishita＇s index and the principal component analysis. The former index is used in population ecology to measure overlapping species. The latter measurement is presented to clarify the validity of the Morishita＇s index. The author identifies MHI as a market leader, Kawasaki Heavy Industry （KHI） Co. as a challenger, Fuji Heavy Industry （FHI） Co. as a follower, and Honda as a nicher in the aircraft patent portfolio strategy in Japan.

A cloud Bayesian network approach to situation assessment of scouting underwater targets with fixed-wing patrol aircraft

The battlefield situation changes rapidly because underwater targets'are concealment and the sea environment is uncertain.So,a great number of situation information greatly increase,which need to be dealt with in the course of scouting underwater targets.Situation assessment in sea battlefield with a lot of uncertain information is studied,and a new situation assessment method of scouting underwater targets with fixed-wing patrol aircraft is proposed based on the cloud Bayesian network,which overcomes the deficiency of the single cloud model in reasoning ability and the defect of Bayesian network in knowledge representation.Moreover,in the method,the cloud model knowledge deal with the input data of Bayesian network reasoning,and the advantages in knowledge representation of cloud theory and reasoning of Bayesian network are applied;also,the fuzziness and stochasticity of cloud theory in knowledge expression,the reasoning ability of Bayesian network,are combined.Then,the situation assessment model of scouting underwater targets with fixed-wing patrol aircraft is established.Hence,the directed acyclic graph of Bayesian network structure is constructed and the assessment index is determined.Next,the cloud model is used to deal with Bayesian network,and the discrete Bayesian network is obtained.Moreover,after CPT of each node and the transformation between certainty degree and probability are accomplished;the final situation level is obtained through a probability synthesis formula.Therefore,the target type and the operational intention of the other side are deduced to form the battlefield situation.Finally,simulations are carried out,and the rationality and validity of the proposed method are testified by simulation results.By this method,the battlefield situation can be gained.And this method has a wider application range,especially for large sample data processing,and it has better practicability.

The Contribution of United States Aircraft Reconnaissance Data to the China Meteorological Administration Tropical Cyclone Intensity Data:An Evaluation of Homogeneity

This paper investigates the homogeneity of United States aircraft reconnaissance data and the impact of these data on the homogeneity of the tropical cyclone(TC)best track data for the seasons 1949-1987 generated by the China Meteorological Administration(CMA).The evaluation of the reconnaissance data shows that the minimum central sea level pressure(MCP)data are relatively homogeneous,whereas the maximum sustained wind(MSW)data show both overestimations and spurious abrupt changes.Statistical comparisons suggest that both the reconnaissance MCP and MSW were well incorporated into the CMA TC best track dataset.Although no spurious abrupt changes were evident in the reconnaissance-related best track MCP data,two spurious changepoints were identified in the remainder of the best-track MCP data.Furthermore,the influence of the reconnaissance MSWs seems to extend to the best track MSWs unrelated to reconnaissance,which might reflect the optimistic confidence in making higher estimates due to the overestimated extreme wind“observations”.In addition,the overestimation of either the reconnaissance MSWs or the best track MSWs was greater during the early decades compared to later decades,which reflects the important influence of reconnaissance data on the CMA TC best track dataset.The wind-pressure relationship(WPR)used in the CMA TC best track dataset is also evaluated and is found to overestimate the MSW,which may lead to inhomogeneity within the dataset between the aircraft reconnaissance era and the satellite era.

Review on uncertainty analysis and information fusion diagnosis of aircraft control system

In the aircraft control system,sensor networks are used to sample the attitude and environmental data.As a result of the external and internal factors(e.g.,environmental and task complexity,inaccurate sensing and complex structure),the aircraft control system contains several uncertainties,such as imprecision,incompleteness,redundancy and randomness.The information fusion technology is usually used to solve the uncertainty issue,thus improving the sampled data reliability,which can further effectively increase the performance of the fault diagnosis decision-making in the aircraft control system.In this work,we first analyze the uncertainties in the aircraft control system,and also compare different uncertainty quantitative methods.Since the information fusion can eliminate the effects of the uncertainties,it is widely used in the fault diagnosis.Thus,this paper summarizes the recent work in this aera.Furthermore,we analyze the application of information fusion methods in the fault diagnosis of the aircraft control system.Finally,this work identifies existing problems in the use of information fusion for diagnosis and outlines future trends.