阅读教学目标系统化探析

阅读教学是语文教学中的重要任务。为了优化教学目标和教学环节,培养学生独立阅读的能力,提高语文教学的效益,我们在教学中进行了教学目标系统化尝试,取得了良好的效果。 一、认真而全面地研究教学大纲和教材,梳理出阅读教学的目标。

分析基于系统化的目标护理干预对慢性精神分裂症患者睡眠质量及社会功能康复的影响

目的:分析基于系统化的目标护理对慢性精神分裂症患者睡眠质量及社会功能康复的影响。方法:选取2020年3月至2022年3月福建省南安市康复院收治的慢性精神分裂症患者78例作为研究对象,按照随机数字表法分为观察组(n=40)和对照组(n=38)。观察组给予系统化的目标护理干预,对照组给予常规护理干预。采用精神分裂症PNASS量表比较2组患者的症状严重程度,采用精神患者社会功能评分(SSPI)比较2组患者的社会功能恢复情况,采用匹兹堡睡眠质量指数(PSQI)比较2组患者干预前后睡眠质量的变化。结果:护理干预后,2组PSQI评分、PANSS各项评分均有所降低,且观察组显著低于对照组,差异均有统计学意义(均P<0.05);护理干预后,2组SSPI各项评分均有所升高,且观察组显著高于对照组,差异均有统计学意义(均P<0.05)。结论:在慢性精神分裂症患者的护理中,基于系统化的目标护理能有效改善患者相关精神分裂症状,提高患者的睡眠质量,加快患者恢复社会功能,值得临床推广应用。

目标激励性系统化干预对淋巴瘤患者不良反应及生活质量的影响

分析对淋巴瘤患者提供目标激励性系统化干预的意义。方法 时间:2022年10月至2023年10月,样本:50例淋巴癌患者,电脑抽号法分组,常规组、研究组,各25例,对应常规护理、目标激励性系统化护理干预,对比两组差异。结果 研究组患者的睡眠质量、心理状况评分、不良反应更低,患者的生活质量更高(p均<0.05)。结论 对于淋巴瘤患者而言,给予其目标激励性系统化干预,对患者的睡眠质量有积极的纠正作用,对患者的心理状况有缓解作用,对患者的不良反应具有控制作用,对患者的生活质量起到改善作用。

关于构建我国粮食仓储网络原则的研究

文章在简要分析当前我国国家储备粮库建设存在问题的基础上,运用经济学、系统工程学、物流学理论提出了完善我国粮食仓储网络应遵循的基本原则,即粮库建设目标系统化原则、粮食物流要素集成化原则、粮库布局网络化原则、粮食流通走廊接口“无缝化”原则和粮库资源配置市场化原则。

目标激励性系统化干预在淋巴瘤患者护理中的应用

对目标激励性系统化干预在淋巴瘤患者护理中的应用效果进行观察。方法 收集2022年1月-2022年12月40例的淋巴瘤患者分为常规护理的对照组和目标激励性系统化干预的观察组,各20例,对比护理效果。结果 观察组患者负性情绪指标评分均低于对照组(P<0.05),观察组PSQI总分低于对照组(P<0.05),观察组患者在各个维度的生活质量评分上均显著高于对照组患者(P<0.05)。结论 淋巴瘤患者护理中应用目标激励性系统化干预具有显著的效果,可改善患者情绪和睡眠,增强生活的幸福感。

MULTIOBJECTIVE OPTIMIZATION OF EIGHT-DOF VEHICLE SUSPENSION BASED ON GAME THEORY

A systematic and effective optimization is proposed for the design of a three-dimensional （3-D） vehicle suspension model with eight degrees of freedom （DOF）, including vertical seat motion, vehicle suspension, pitching and rolling motions, and vertical wheel motions using the evolutionary game theory. A new design of the passive suspension is aided by game theory to attain the best compromise between ride quality and suspension deflections. Extensive simulations are performed on three type road surface models A, B, C pavement grades based on the guidelines provided by ISO-2631 with the Matlab/Simulink environment. The preliminary results show that, when the passive suspension is optimized via the proposed approach, a substantial improvement in the vertical ride quality is obtained while keeping the suspension deflections within their allowable clearance when the vehicle moves at a constant velocity v=20 m/s, and the comfort performance of a suspension seat can be enhanced by 20%-30%.

Multiobjective Optimization of Simulated Moving Bed by Tissue P System

The binaphthol enantiomers separation process using simulation moving bed technology is simulated with the true moving bed approach （TMB）. In order to systematically optimize the process with multiple productive objectives, this article develops a variant of tissue P system （TPS）. Inspired by general tissue P systems, the special TPS has a tissue-like structure with several membranes. The key rules of each membrane are the communication rule and mutation rule. These characteristics contribute to the diversity of the population, the conquest of the multimodal of objective function, and the convergence of algorithm. The results of comparison with a popular algorithm——the non-dominated sorting genetic algorithm 2（NSGA-2） illustrate that the new algorithm has satisfactory performance. Using the algorithm, this study maximizes synchronously several conflicting objectives, purities of different products, and productivity.

Hierarchical Algorithms of Large-Scale Systems with Nonseparable Multiobjective

A class of large-scale hierarchical control systems is considered, the overall objective function is a nonlinear and nonseparable function of multiple quadratic performance indices.The separation strategy of the multiobjective optimization technique and the three-level objective coordination method are applied to the large -sacle systems, and a four-level hierarchical algorithms of optimization control is obtained.

Multi-objective optimization scheduling for new energy power system considering energy storage participation

For the low utilization rate of photovoltaic power generation,taking a new energy power system constisting of concentrating solar power(CSP),photovoltaic power(PP)and battery energy storage system as an example,a multi-objective optimization scheduling strategy considering energy storage participation is proposed.Firstly,the new energy power system model is established,and the PP scenario generation and reduction frame based on the autoregressive moving average model and Kantorovich-distance is proposed.Then,based on the optimization goal of the system operation cost minimization and the PP output power consumption maximization,the multi-objective optimization scheduling model is established.Finally,the simulation results show that introducing energy storage into the system can effectively reduce the system operation cost and improve the utilization efficiency of PP.

Mixed Gl2／GH2 multi-channel multi-objective control synthesis for discrete time systems

This paper proposes a new approach for multi-objective robust control. The approach extends the standard generalized l2 (Gl2) and generalized H2 (GH2) conditions to a set of new linear matrix inequality (LMI) constraints based on a new stability condition. A technique for variable parameterization is introduced to the multi-objective control problem to preserve the linearity of the synthesis variables. Consequently, the multi-channel multi-objective mixed Gl2/GH2 control problem can be solved less conservatively using computationally tractable algorithms developed in the paper.

Multi-objective optimization of active steering system with force and displacement coupled control

A novel active steering system with force and displacement coupled control(the novel AFS system) was introduced,which has functions of both the active steering and electric power steering.Based on the model of the novel AFS system and the vehicle three-degree of freedom system,the concept and quantitative formulas of the novel AFS system steering performance were proposed.The steering road feel and steering portability were set as the optimizing targets with the steering stability and steering portability as the constraint conditions.According to the features of constrained optimization of multi-variable function,a multi-variable genetic algorithm for the system parameter optimization was designed.The simulation results show that based on parametric optimization of the multi-objective genetic algorithm,the novel AFS system can improve the steering road feel,steering portability and steering stability,thus the optimization method can provide a theoretical basis for the design and optimization of the novel AFS system.

A systematic strategy for multi-period heat exchanger network retrofit under multiple practical restrictions

A systematic strategy for retrofit of the multi-period heat exchanger network （HEN） on the basis of the multi- objective optimization is developed. In this three-stage procedure, a simplified multi-objective optimization model of the multi-period lIEN is first established and then solved to target the retrofit, aiming to minimizing the total annual cost and total annual CO2 emissions. The obtained Pareto front represents series of retrofit targets under different emission limitations, from which the most desirable one can be selected. The matching of the existing and the required heat exchangers is further implemented to finalize the retrofit, which will meet the practical retrofit requirements and matching restrictions. The application of the proposed procedure is illustrated through a case study of a HEN in a vacuum gas oil hydro-treating unit.

Gravitational search algorithm for coordinated design of PSS and TCSC as damping controller

A newly developed heuristic global optimization algorithm, called gravitational search algorithm （GSA）, was introduced and applied for simultaneously coordinated designing of power system stabilizer （PSS） and thyristor controlled series capacitor （TCSC） as a damping controller in the multi-machine power system. The coordinated design problem of PSS and TCSC controllers over a wide range of loading conditions is formulated as a multi-objective optimization problem which is the aggregation of two objectives related to damping ratio and damping factor. By minimizing the objective function with oscillation, the characteristics between areas are contained and hence the interactions among the PSS and TCSC controller under transient conditions are modified. For evaluation of effectiveness and robustness of proposed controllers, the performance was tested on a weakly connected power system subjected to different disturbances, loading conditions and system parameter variations. The cigenvalues analysis and nonlinear simulation results demonstrate the high performance of proposed controllers which is able to provide efficient damping of low frequency oscillations.

OPTIMIZATION ON ANTENNA PATTERN OF SPACEBORNE SAR WITH IMPROVED NSGA-Ⅱ

Optimization of antenna array pattern used in a spaceborne Synthetic Aperture Radar (SAR) system is considered in this study. A robust evolutionary algorithm, Non-dominated Sorting Genetic Algorithms (the improved NSGA-Ⅱ), is applied on a spaceborne SAR antenna pattern design. The system consists of two objective functions with two constraints. Pareto fronts are generated as a result of multi-objective optimization. After being validated by a test problem ZDT4, the algorithms are used to synthesize spaceborne SAR antenna radiation pattern. The good results with low Ambi- guity-to-Signal Ratio (ASR) and high directivity are obtained in the paper.

Energy Optimization of the Fin/Rudder Roll Stabilization System Based on the Multi-objective Genetic Algorithm （MOGA）

Energy optimization is one of the key problems for ship roll reduction systems in the last decade. According to the nonlinear characteristics of ship motion, the four degrees of freedom nonlinear model of Fin/Rudder roll stabilization can be established. This paper analyzes energy consumption caused by overcoming the resistance and the yaw, which is added to the fin/rudder roll stabilization system as new performance index. In order to achieve the purpose of the roll reduction, ship course keeping and energy optimization, the self-tuning PID controller based on the multi-objective genetic algorithm （MOGA） method is used to optimize performance index. In addition, random weight coefficient is adopted to build a multi-objective genetic algorithm optimization model. The objective function is improved so that the objective function can be normalized to a constant level. Simulation results showed that the control method based on MOGA, compared with the traditional control method, not only improves the efficiency of roll stabilization and yaw control precision, but also optimizes the energy of the system. The proposed methodology can get a better performance at different sea states.

Planning and Organizing the Projects in Team Co Cakovec, Croatia

The paper systemizes standard methods of planning, monitoring and controlling the realization of construction works in civil engineering projects and overviews the implementation of the methods in Team Co Cakovec from Croatia. The specificities of the methods are shown through the different construction works projects. Also, paper reviews the implementation, modification and improvement of existing methods for planning, monitoring and controlling the realization of projects in Team Co.

从活动设置谈物理学科核心素养的培养

物理学科活动是物理学科核心素养形成的主要途径之一,物理学科活动具有实践性、思维性、自主性和教育性四个基本特性。文章从“创设生活化的学科活动”“创设高阶思维学科活动”“创设认知冲突型学科活动”和“创设具有系统化目标的学科活动”四方面例谈物理学科核心素养的培养。

Multidisciplinary design optimization for air-condition production system based on multi-agent technique

In order to guarantee the overall production performance of the multiple departments in an air-condition production industry, multidisciplinary design optimization model for production system is established based on the multi-agent technology. Local operation models for departments of plan, marketing, sales, purchasing, as well as production and warehouse are formulated into individual agents, and their respective local objectives are collectively formulated into a multi-objective optimization problem. Considering the coupling effects among the correlated agents, the optimization process is carried out based on self-adaptive chaos immune optimization algorithm with mutative scale. The numerical results indicate that the proposed multi-agent optimization model truly reflects the actual situations of the air-condition production system. The proposed multi-agent based multidisciplinary design optimization method can help companies enhance their income ratio and profit by about 33% and 36%, respectively, and reduce the total cost by about 1.8%.

Research on Optimization Operation of Urban Gas Pipeline Network

The optimiz at ion operation of gas pipeline network is investigated in this paper. Based on th e theories of system optimization and the multi object decision, a mathematical model about the multi object optimization operation of gas pipeline network is established, in line with the demand of urban gas pipeline network operation. A t the same time, an effective solution of the mathematical model is presented. A calculating software about optimization operation is compiled, coupling the actual operation of gas pipeline network. It can be applied to the operation of the gas pipeline network. The software was examined by real examples. The resul ts indicated that 2.13% energy consumption and 3.12% gas supply cost can be reduced through optimization operation.

NSGA Ⅱ based multi-objective homing trajectory planning of parafoil system

Homing trajectory planning is a core task of autonomous homing of parafoil system.This work analyzes and establishes a simplified kinematic mathematical model,and regards the homing trajectory planning problem as a kind of multi-objective optimization problem.Being different from traditional ways of transforming the multi-objective optimization into a single objective optimization by weighting factors,this work applies an improved non-dominated sorting genetic algorithm Ⅱ(NSGA Ⅱ) to solve it directly by means of optimizing multi-objective functions simultaneously.In the improved NSGA Ⅱ,the chaos initialization and a crowding distance based population trimming method were introduced to overcome the prematurity of population,the penalty function was used in handling constraints,and the optimal solution was selected according to the method of fuzzy set theory.Simulation results of three different schemes designed according to various practical engineering requirements show that the improved NSGA Ⅱ can effectively obtain the Pareto optimal solution set under different weighting with outstanding convergence and stability,and provide a new train of thoughts to design homing trajectory of parafoil system.