Evaluation of driving behavior based on massive vehicle trajectory data

Based on the driver surveillance video data and controller area network(CAN)data,the methods of studying commercial vehicles’driving behavior is relatively advanced.However,these methods have difficulty in covering private vehicles.Naturalistic driving studies have disadvantages of small sample size and high cost,one new driving behavior evaluation method using massive vehicle trajectory data is put forward.An automatic encoding machine is used to reduce the noise of raw data,and then driving dynamics and self-organizing mapping(SOM)classification are used to give thresholds or the judgement method of overspeed,rapid speed change,rapid turning and rapid lane changing.The proportion of different driving behaviors and typical dangerous driving behaviors is calculated,then the temporal and spatial distribution of drivers’driving behavior and the driving behavior characteristics on typical roads are analyzed.Driving behaviors on accident-prone road sections and normal road sections are compared.Results show that in Shenzhen,frequent lane changing and overspeed are the most common unsafe driving behaviors;16.1%drivers have relatively aggressive driving behavior;the proportion of dangerous driving behavior is higher outside the original economic special zone;dangerous driving behavior is highly correlated with traffic accident frequency.

Dynamics of 3-DOF Hybrid Robot Manipulator

This paper introduces a 3-dof hybrid robotic manipulator which is constructed by combining a parallel mechanism and a pantograph to increase stiffness as well as workspace. And by analyzing its kinematics and dynamics with Lagrange’s method, the dynamic model is obtained which is essential for feed-forward control of the manipulator. An explicit solution is given out. Finally, a simulation test is carried out on computers.

Study on How to Design Knitted Fabric Pattern with Mathematical Theory

To improve design capabilities for the knitted fabric pattern,a preliminary study is carried out for the design method.Based on mathematical theory,pattern could be created automatically by computer with inputting different parameters for mathematical functions.The knitted fabric simulation is realized by M1 CAD pattern preparation system of STOLL Company.In the pattern,different color unit is replaced by obverse stitch with different color,or by obverse stitch and reverse stitch with the same color separately,after that the effects of knitted fabrics could be simulated.Designing with this method,it would not only help to acquire a great of diversity patterns,but also improve design efficiency and save cost.

PAPR reduction in mobile WiMAX:A new ZCMT precoded random interleaved OFDMA system

Mobile WiMAX(worldwide interoperability for microwave access) air interface adopts orthogonal frequency division multiple access(OFDMA) as multiple access technique for its uplink(UL) and downlink(DL) to improve the multipath performance.All OFDMA based networks,like mobile WiMAX,experience the problem of high peak-to-average power ratio(PAPR).The high PAPR increases the complexity of analog-to-digital(A/D) and digital-to-analog(D/A) convertors,and also reduces the efficiency of RF high-power-amplifier(HPA).In this work,a new zadoff-chu matrix transform(ZCMT) precoding based random interleaved orthogonal frequency division multiple access(OFDMA) system was proposed for PAPR reduction in mobile WiMAX system.The system is based on precoding the constellation symbols with the ZCMT precoder before subcarrier mapping.The PAPR of proposed system is analyzed with the root-raised-cosine(RRC) pulse shaping to keep out of band radiation low and meet the transmission spectrum mask requirement.Simulation results show that the proposed system has better PAPR gain than the hadamard transform(WHT) precoded random interleaved OFDMA systems and the conventional random interleaved OFDMA systems.Symbol-error-rate(SER) performance of the system is also better than the conventional random interleaved OFDMA systems and the random interleaved OFDMA systems with WHT.The good improvement in PAPR significantly reduces the cost and the complexity of the transmitter.

我国农村学校教师编制测算模型研究

教师数量的学校分布与实际需要不匹配,是制约我国农村教育质量提升的重要因素。问题的关键在于,基于生师比单维指标的教师编制核算方式不切合学校教学的班级组织形式对教师的需求,导致教师数量未能满足正常的教育教学、教师的学习提升以及保证教师身心健康的需要。为此,应推行农村教师数量保障的综合改革,在学校层面采用"基本编+机动编"的方式配置教师;建立兼顾教育公平及教师资源利用效率,以课程设置、学生数量的年级和班级分布为基本参数的教师编制标准测算模型,科学核定基本编;依据轮训周期和轮训时间设置机动编的比例,保证每位农村教师能有充足的培训时间。

Microcontroller-Based Variable Speed Drive for Three-Phase Induction Motor in Cooling Applications

This paper presents an electronic VSD （variable speed drive） for three-phase IM （induction motor） using a microcontroller. The VSD is designed for cooling applications where the 1M is coupled to a cooling fan. The drive receives temperature feedback from objects to be cooled and output a corresponding frequency to the IM. A prototype of the VSD is constructed to control a 175 W, four pole, squirrel cage three-phase IM. The heart of the control circuit is a low-cost microchip＇s PICI6F777 microcontroller which is programmed using C language to generate variable frequency SPWM （sinusoidal pulse width modulation） switching signals. These switching signals are fed to an 1GBT inverter. The VSD constructed can be switched between two modes of speed control＂ automatic temperature-controlled mode and manual user-controlled mode. Cost savings using the prototype are demonstrated.

Battle damage assessment based on an improved Kullback-Leibler divergence sparse autoencoder

The nodes number of the hidden layer in a deep learning network is quite difficult to determine with traditional methods. To solve this problem, an improved Kullback-Leibler divergence sparse autoencoder （KL-SAE） is proposed in this paper, which can be applied to battle damage assessment （BDA）. This method can select automatically the hidden layer feature which contributes most to data reconstruction, and abandon the hidden layer feature which contributes least. Therefore, the structure of the network can be modified. In addition, the method can select automatically hidden layer feature without loss of the network prediction accuracy and increase the computation speed. Experiments on University ofCalifomia-Irvine （UCI） data sets and BDA for battle damage data demonstrate that the method outperforms other reference data-driven methods. The following results can be found from this paper. First, the improved KL-SAE regression network can guarantee the prediction accuracy and increase the speed of training networks and prediction. Second, the proposed network can select automatically hidden layer effective feature and modify the structure of the network by optimizing the nodes number of the hidden layer.

Design and performance test of a two-axis fast steering mirror driven by piezoelectric actuators

A novel design of a two-axis fast steering mirror(FSM) with piezoelectric actuators is proposed for incoherent laser beam combination. The mechanical performance of the FSM is tested. The results show that the tilting range of the mirror is about 4 mrad, and the 1st-order resonance frequency is about 250 Hz. A self-designed grating encoder is taken as the sensor, which ensures the optimal precision of 10 μrad. The novel mechanical design can meet the requirement of engineering in incoherent laser beam combination.