心理统合感理论的回顾与争论

目的介绍国外健康领域研究中的一种新理论。方法利用文献综述法整合国内外的相关研究。结果概述了心理统合感理论的提出、含义、作用机制及存在的争论。结论国内研究应该给予这一理论更多的关注。

统合感理论在高中政治主观题中应用研究

根植绿色教育的沃土,教育信息的立体互动化,敦促学生的学习方式从‘以记零散知识为中心’的深度转向‘以思维分析为中心’,倾力于分析能力的锻造。对于集萃出‘理性精神’等核心素养的高中政治课堂而言,把主观题作为引领方式转变的一个主抓手,统揽宏观与微观、横向与纵向、整体与部分、现象与本质、直接与间接等综合多维多层的思维分析框架,是必然的选择。面对不同层次的学生,环境的不确定性增加,如何有针对性的破解这一问题,成为时代课题。我们立足学科系统思考,强调深度关注学生应对问题的倾向性,着力从统合的视角,践行学生的生活切入与学科语言、宏观的知识清晰逻辑与微观点的全覆盖深入、深度体验学习与全面主观题策略、学生反思之再反思与老师长期集中深入关注的共识、老师的服务思维转变与课代表精细对接统一理念。一线的长期耕耘与反思之再反思,为突破破主观题的瓶颈提供了有益尝试。

唐山某区学龄儿童感知觉统合能力现状

目的:调查学龄儿童感知觉统合能力的基本状况,提升对感知觉统合能力重要性的认识。方法:选取唐山市某区,4所小学学龄儿童为研究对象,共计576人,采用感知觉统合能力评定量表进行测查,分别统计比较学龄儿童总体阳性发生率;学龄儿童感知觉统合能力四大因子阳性发生率;学龄儿童感知觉统合能力四大因子不足程度分析;低年级学龄儿童与高年级学龄儿童阳性发生率差异分析;学龄儿童男生、生女阳性发生率对比;运用SPSS 24.0进行描述性统计、卡方检验,以P<0.05为有统计学意义,以标准分数低于60分认为存在阳性。结果:在503名学龄儿童中,总体阳性发生率为95.4%,四大因子阳性发生率:前庭平衡能力占43.3%,触觉分辨能力占93.1%,本体控制能力占76.5%,学习能力因子阳性发生率占80.3%;四大因子不足程度:前庭平衡能力轻度不足占比15.1%,中度不足占比28.0%,重度不足占比0.2%;触觉分辨能力轻度不足占比59.4%,中度不足占比33.2%,重度不足占比0.4%;本体控制能轻度力轻度不足占比53.1%,中度不足占比22.9%,重度不足占比0.6%;学习能力轻度不足占比32.6%,中度不足占比44.9%,重度不足占比2.8%;低年级总体阳性发生率为97.5%,高年级总体阳性率为93.5%,低年级总体阳性发生率与高年级总体阳性发生率差异显著;男生总体阳性发生率97.2%,女生总体阳性发生率93.7%,男生与女生之间阳性发生率差异不显著。结论:学龄儿童感知觉统合能力不足阳性发生率占比偏高,应该提高认识,引起重视,及早进行有效应对。

浅谈低年级智障学生感知觉统合注意力训练的活动设计要点

感知觉统合注意力训练作为低年级阶段智障学生教学重点内容,其开展情况直接影响着智障学生的今后生活能力,因此,教师要顺应低年级智障学生感知觉实际特点,把握感知觉统合注意力训练的活动设计要点,肩负起特殊教育使命任务,为智障学生未来的健康成长和独立生活贡献更多积极力量。本文从实际出发,结合教学案例分析,思考了低年级智障学生感知觉统合注意力训练的活动设计策略,以期促进我国智障学生特殊教育事业进步发展。

小游戏——让感知觉更统合

苏霍姆林斯基曾说:"在我们的创造性教育工作中,对差生的工作是最难啃的‘硬骨头’之一……"其实这些"差生"是源于他们的感知觉统合失调。教师家长需要了解孩子的感知觉水平,这样才能探寻他们这些问题背后的原因,进而通过改变根源,改善问题。

Sensor Registration in Asynchronous Data Fusion

To find an effective method to estimate and remove the registration error in asynchronous multisensor system, Kalman filtering technique and least squares approach have been proposed to estimate and remove sensor bias and sensor frame tilt errors in multisensor systems with asynchronous data. Simulation results is presented to demonstrate the performance of these approaches. The least squares approach can compress measurements to any time. The Kalman filter algorithm can detect registration errors and use the information to converge tracks from independent sensors. This is particularly important if the data from the sensors are to be fused.

Tightly-coupled model for INS/WSN integrated navigation based on Kalman filter

Aiming at the problem of poor observability of measurement information in the loosely-coupled integration of the inertial navigation system （INS） and the wireless sensor network （WSN）, this paper presents a tightly-coupled integration based on the Kalman filter （KF）. When the WSN is available, the difference between the distances from the blind node（BN） to the reference nodes （RNs） measured by the INS and those measured by the WSN are used as measurement information for the KF due to its better observability and independence, which can effectively improve the accuracy of the KF. Simulations show that the proposed approach reduces the mean error of the position by about 50% compared with loosely-coupled integration, while the mean error of the velocity is a little higher than that of loosely-coupled integration.

Temporal consistency maintenance on multiprocessor platforms with instance skipping

Maintaining temporal consistency of real-time data is important for cyber-physical systems.Most of the previous studies focus on uniprocessor systems.In this paper,the problem of temporal consistency maintenance on multiprocessor platforms with instance skipping was formulated based on the(m,k)-constrained model.A partitioned scheduling method SC-AD was proposed to solve the problem.SC-AD uses a derived sufficient schedulability condition to calculate the initial value of m for each sensor transaction.It then partitions the transactions among the processors in a balanced way.To further reduce the average relative invalid time of real-time data,SC-AD judiciously increases the values of m for transactions assigned to each processor.Experiment results show that SC-AD outperforms the baseline methods in terms of the average relative invalid time and the average valid ratio under different system workloads.

Coal mine gas monitoring system based on wireless sensor network

Based on the nowadays＇ condition, it is urgent that the gas detection cable communication system must be replaced by the wireless communication systems. The wireless sensors distributed in the environment can achieve the intelligent gas monitoring system. Apply with multilayer data fuse to design working tactics, and import the artificial neural networks to analyze detecting result. The wireless sensors system communicates with the control center through the optical fiber cable. All the gas sensor nodes distributed in coal mine are combined into an intelligent, flexible structure wireless network system, forming coal mine gas monitoring system based on wireless sensor network.

A Web-Based Integrated Intelligent System for Sensory Fabric Hand Evaluation

This paper presents a web-based integrated system for on-line sensory fabric hand evaluation. The methods of fuzzy techniques, neural networks, classical factorial analysis and other data analysis are used in the system to analyze the objective and subjective data, and to build the relationship between them. Given the objective data of a new fabric sample, the system can provide its sensory hand data and its total hand grade. In meantime, the total hand grade can be obtained directly from the sensory fabric hand data if provided. The sensory evaluation system is developed in Internet environment using Java language and SQL server database management system.

Multi-sensor Hybrid Fusion Algorithm Based on Adaptive Square-root Cubature Kalman Filter

In the normal operation condition, a conventional square-root cubature Kalman filter （SRCKF） gives sufficiently good estimation results. However, if the measurements are not reliable, the SRCKF may give inaccurate results and diverges by time. This study introduces an adaptive SRCKF algorithm with the filter gain correction for the case of measurement malfunctions. By proposing a switching criterion, an optimal filter is selected from the adaptive and conventional SRCKF according to the measurement quality. A subsystem soft fault detection algorithm is built with the filter residual. Utilizing a clear subsystem fault coefficient, the faulty subsystem is isolated as a result of the system reconstruction. In order to improve the performance of the multi-sensor system, a hybrid fusion algorithm is presented based on the adaptive SRCKF. The state and error covariance matrix are also predicted by the priori fusion estimates, and are updated by the predicted and estimated information of subsystems. The proposed algorithms were applied to the vessel dynamic positioning system simulation. They were compared with normal SRCKF and local estimation weighted fusion algorithm. The simulation results show that the presented adaptive SRCKF improves the robustness of subsystem filtering, and the hybrid fusion algorithm has the better performance. The simulation verifies the effectiveness of the proposed algorithms.

Data Fusion in Distributed Multi-sensor System

This paper presents a data fusion method in distributed multi-sensor system including GPS and INS sensors’ data processing. First, a residual χ 2 \|test strategy with the corresponding algorithm is designed. Then a coefficient matrices calculation method of the information sharing principle is derived. Finally, the federated Kalman filter is used to combine these independent, parallel, real\|time data. A pseudolite (PL) simulation example is given.

Impact of the Integrated Management Systems on the Achievement of Stable Quality and Safety of Biscuit Products

The implementation of Integrated Management System （IMS） of the quality management and safety is aiming to provide production of biscuit products corresponding to particular specification and client＇s requirements. This paper explores the possibilities of achieving stable sensory and microbiological parameters of the biscuits, through the implementation of IMS. An analysis was carried out of the factors affecting the achievement of stable quality. The achievement of the stability of the parameters of 150 different lots of biscuits has been measured before, during and after the implementation of IMS in the manufacturing company The performed water activity analysis and sensory analysis confirmed that despite the dynamic changes in the internal and external environments as well as the significant changes in the requirements of the standards and the legislation, the implemented IMS has allowed the maintenance of the stable quality and safety of the biscuit products.

Settlement monitoring system of pile-group foundation

In order to realize information construction on settlement of pile-group foundation of Sutong Bridge, the monitoring instruments of high-precision micro-pressure sensor and hydrostatic leveling and settlement profiler were integrated synthetically. A set of practical multi-scale monitoring system on settlement of super-large pile-group foundation in deep water was put forward. The reliable settlement results are obtained by means of multi-sensor data fusion. Finite element model of pile-group foundation is established. By analysis of finite element simulated calculation of pile-group foundation, rules of settlement and uneven settlement obtained by monitoring and calculation results are coincident and the absolute error of settlement between them is 4.7 mm. The research shows that it is reasonable and feasible to monitor settlement of pile-group foundation with the system, and it can provide a method for the same type pile-group foundation in deep water.

Application of Neuro-Fuzzy Estimation for Rotor Flux in Speed Vector Control of Bearingless Induction Motor

The main requirement of a vector controller is knowing the magnitude and position of the rotating flow in the rotor. This feature permits to use either flow sensors or flow estimators. The solution chosen was the estimation of rotor flux with the hybrid neuro-fuzzy system. The motor characteristics are： 3.75 kW （5 HP）, two pole-pair, operate at 60 Hz and air-gap length 0.2 mm. The ANFIS （adaptive neuro-fuzzy inference system） was used to tune the membership functions in fuzzy system. The hybrid estimator aims at compensating possible parametric variations of the machine caused by agents, such as temperature or nucleus saturation. The simulated results have shown good performance.

INFORMATION FUSION STEADY-STATE WHITE NOISE DECONVOLUTION ESTIMATORS WITH TIME-DELAYED MEASUREMENTS AND COLORED MEASUREMENT NOISES

White noise deconvolution or input white noise estimation problem has important appli-cation backgrounds in oil seismic exploration,communication and signal processing.By the modern time series analysis method,based on the Auto-Regressive Moving Average(ARMA) innovation model,under the linear minimum variance optimal fusion rules,three optimal weighted fusion white noise deconvolution estimators are presented for the multisensor systems with time-delayed measurements and colored measurement noises.They can handle the input white noise fused filtering,prediction and smoothing problems.The accuracy of the fusers is higher than that of each local white noise estimator.In order to compute the optimal weights,the formula of computing the local estimation error cross-covariances is given.A Monte Carlo simulation example for the system with 3 sensors and the Bernoulli-Gaussian input white noise shows their effectiveness and performances.

主题引领的双微机制:激发教师改革行为的师训模式探索

有效激发教师将所学和积累的理论、实践知识转化为真实的教改行为,既是学校教育教学面临的实践难题,也是教师专业发展中的理论难题。华南师范大学王红教授团队为教师更好地实践教育教学改革创设“价值-信念系统”“效能-激励系统”和“安全-保障系统”等支持条件,构建了有助于提升教师价值感、效能感、安全感的“三感统合”模型,以及专家陪伴“LOVE”行为模型,并提出能有效激发“三感”、推进理论向实践转化的教师专业发展新模式“主题引领的双微机制”,以形成助推教师“从心动到行动”践行教学改革的支持路径。

Achieving maximum power transfer of inductively coupled wireless power transfer system based on dynamic tuning control

As an emerging research field,inductively coupled wireless power transfer(ICWPT) technology has attracted wide spread attention recently.In this paper,the maximum power transfer performances of four basic topologies labeled as SS,SP,PS and PP are investigated.By modeling the equivalent circuits of these topologies in high frequency(HF),the primary resonance compensation capacitances for maximum power transfer capability are deduced.It is found that these capacitances fluctuate with load resistance change,which is disadvantageous to SP,PS and PP topologies and an obstacle to their practical applications as well.To solve this problem,a phase controlled inductor circuit is proposed.By adjusting the triggering angle,the real-time dynamic tuning control can be achieved to guarantee maximum power transfer.Finally,simulations and experiments show that the proposed method is of great effectiveness and reliability to solve the issue of resonance compensation capacitance fluctuation with load change and to guarantee the flexible applications of all topologies.

A Novel Readout System for Wireless Passive Pressure Sensors

This paper presents a novel readout system for wireless passive pressure sensors based on the inductively coupled inductor and cavity （LC） resonant circuits. The proposed system consists of a reader antenna inductively coupled to the sensor circuit, a readout circuit, and a personal computer （PC） post processing unit. The readout circuit generates a voltage signal representing the sensor＇s capacitance. The frequency of the reader antenna driving signal is a constant, which is equal to the sensor＇s resonant frequency at zero pressure. Based on mechanical and electrical modeling, the pressure sensor design based on the high temperature co-fired ceramic （HTCC） technology is conducted and discussed. The functionality and accuracy of the readout system are tested with a voltage-capacitance measurement system and demonstrated in a realistic pressure measurement environment, so that the overall performance and the feasibility of the readout system are proved.

Study of Optical Fibers Strain-Temperature Sensitivities Using Hybrid Brillouin-Rayleigh System

In this paper, the most recent progress as well as challenges of distributed optical fiber sensing （DOFS） in industrial applications is discussed. Compared to the vast market of sensors used to measure strain or temperature, the success of distributed optical fiber sensing （DOFS） at the industrial level is very limited, at best. One of the reasons for this lack of the wider acceptance is the mismatch between the commercially available systems and actual industrial requirements, especially for the spatial resolution and precision. These requirements are organized and clarified in the paper. It also describes the hybrid Brillouin-Rayleigh system, which exhibits capabilities surpassing those of strain gauges. The principles of the system are illustrated considering the fiber calibration methodology. Formulas required for determining strain, temperature, and hydro-pressure are derived and discussed. Finally, the examples of applications are presented.