The development of real time data driving multi-axis linkage and synergic movement control system of 3D variable cross-section roll forming machine

The three dimensional variable cross-section roll forming is a kind of new metal forming technol- ogy which combines large forming force, multi-axis linkage movement and space synergic movement, and the sequential synergic movement of the ganged roller group is used to complete the metal sheet forming according to the shape of the complicated and variable forming part data. The control system should meet the demands of quick response to the test requirements of the product part. A new kind of real time data driving multi-axis linkage and synergic movement control strategy of 3D roll forming is put forward in the paper. In the new control strategy, the forming data are automatically generated according to the shape of the parts, and the multi-axis linkage movement together with cooperative motion among the six stands of the 3D roll forming machine is driven by the real-time information, and the control nodes are also driven by the forming data. The new control strategy is applied to a 48 axis 3D roll forming machine developed by our research center, and the control servo period is less than 10ms. A forming experiment of variable cross section part is carried out, and the forming preci- sion is better than ＋ 0.5mm by the control strategy. The result of the experiment proves that the control strategy has significant potentiality for the development of 3D roll forming production line with large scale, multi-axis ganged and svner^ic movement

Discrete-time movement model of a group of trains on a rail line with stochastic disturbance

This paper presents a discrete-time model to describe the movements of a group of trains, in which some operational strategies, including traction operation, braking operation and impact of stochastic disturbance, are defined. To show the dynamic characteristics of train traffic flow with stochastic disturbance, some numerical experiments on a railway line are simulated. The computational results show that the discrete-time movement model can well describe the movements of trains on a rail line with the moving-block signalling system. Comparing with the results of no disturbance, it finds that the traffic capacity of the rail line will decrease with the influence of stochastic disturbance. Additionally, the delays incurred by stochastic disturbance can be propagated to the subsequent trains, and then prolong their traversing time on the rail line. It can provide auxiliary information for rescheduling trains When the stochastic disturbance occurs on the railway.

Time of the Tengchong-Lianghe Movement in Southwest Yunnan

The Tengchong-Lianghe movement, proposed and named by Chen et al （ 1991 ）, is an important tectonic event occurred from the late stage of middle Pleistocene to the early stage of the late Pleistocene in the Tenchong Block of southwest Yunnan. It reactivated the old faults in the region, and tilted, folded and fractured the Q1 and Q2 strata, resulting in the common angular unconformity between them. In addition, this region entered into an erosion-cutting stage, with its cutting depth reaching up to tens of meters, and formed very striking high lake terraces.

DISPLACEMENT TIME SERIS AT FIDUCIAL STATIONS OBTAINED FROM GPS OBSERVATIONS IN CRUSTAL MOVEMENT OBSEREVATION NETWORK OF CHINA

A preliminary analysis of the time series of displacements at fiducial stations obtained from continuous GPS observations during the period of Sept. 1998 to Oct. 2001 in the Crustal Movement Observation Network of China (CMONOC) is made. The selection of datum for producing displacement time series suitable for earthquake prediction is discussed. Time series of horizontal crustal displacements are obtained by using a datum of a stable group of 9 stations with very small relative horizontal displacements in eastern China as reference. Time series of vertical crustal displacements are obtained by using a stable group of 7 stations scattered in different regions with relatively small relative vertical displacements as reference. During the period of 2000 to 2001, anomalous horizontal and vertical displacements occurred twice at the fiducial stations in western China. These anomalies may be related to seismic activities of magnitudes about 6 in the Yunnan region on the North South seismic belt.

“Eternal Motion” as a “Form of Movement of a Special Nature” and the Main Condition for the Creation of the Universe

The article hypothesizes that DE and DM (UCM) are a “Form of Motion of a Special Nature”, where “Form of Motion” means “Eternal Motion” as the power of dynamics of different levels and varying degrees of self-sufficiency, and by “Special Nature”, gravitational and two other properties of matter, “tied” to the “Eternal Movement” and completely dependent on it. Carriers of key properties of a “Special Nature” have been established: “0”-DE particles and “3”-DM particles (UDM). The unity of their inherent “motionally-gravitational” properties and the peculiarity of the relationship between “motion” and “gravity” are revealed: the higher the intensity of “Eternal Motion”, the stronger the gravitational properties of matter are manifested (and vice versa). The relationship of “time” with the “vibration frequency” and the “mass” of photons with the “degree of bonding and deformation properties of the field” is shown. The maximum level of gravity has been determined, which allows Nature to successfully create the Universe: such a landmark is the proximity to the property of the Primary Source—the “pure graviton” of the OSP space, the most powerful “motionally-gravitational” particle of the Universe. The reasons for the emergence of such an identity of the gravitational properties of particles with the indicators of a “pure graviton” are established: for “0”-DE particles, this is the acquisition of the function of “freedom of movement”;for “3”-DM particles (UDM), the creation of a special structure—a “double field” (“Main” and “Small”). The presence in the “double field” of specific “tools” for the creation of the worlds of the Universe—gravitational “waves” gives rise to impulses (shocks) of varying intensity and shape. A list of functions performed by “waves” in the “Main” and “Small” fields has been compiled. The specific conditions for the formation of “UDM Streams”, their transformation into a “Vortex” and, under the influence of a powerful Initial Impulse (push), sending them to the “place” of the creation of galaxies, are shown. It is suggested that there is a “Cycle of Matter in Nature” in the closed structure of our Universe due to the “work” of “waves” and the functioning of special “factories” in the form of exotic space objects—Black holes.

Prediction of Departure Aircraft Taxi Time Based on Deep Learning

With the continuous increase in the number of flights,the use of airport collaborative decision-making(ACDM)systems has been more and more widely spread.The accuracy of the taxi time prediction has an important effect on the A-CDM calculation of the departure aircraft’s take-off queue and the accurate time for the aircraft blockout.The spatial-temporal-environment deep learning(STEDL)model is presented to improve the prediction accuracy of departure aircraft taxi-out time.The model is composed of time-flow sub-model(airport capacity,number of taxiing aircraft,and different time periods),spatial sub-model(taxiing distance)and environmental sub-model(weather,air traffic control,runway configuration,and aircraft category).The STEDL model is used to predict the taxi time of departure aircraft at Hong Kong Airport and the results show that the STEDL method has a prediction accuracy of 95.4%.The proposed model also greatly reduces the prediction error rate compared with the other machine learning methods.

Slacklining:An explanatory multi-dimensional model considering classical mechanics,biopsychosocial health and time

This paper aims to overcome slacklining’s limited formulated explanatory models.Slacklining is an activity with increasing recreational use,but also has progressive adoption into prehabilitation and rehabilitation.Slacklining is achieved through self-learned strategies that optimize energy expenditure without conceding dynamic stability,during the neuromechanical action of balance retention on a tightened band.Evolved from rope-walking or‘Funambulus’,slacklining has an extensive history,yet limited and only recent published research,particularly for clinical interventions and in-depth hypothesized multi-dimensional models describing the neuromechanical control strategies.These‘knowledge-gaps’can be overcome by providing an,explanatory model,that evolves and progresses existing standards,and explains the broader circumstances of slacklining’s use.This model details the individual’s capacity to employ control strategies that achieve stability,functional movement and progressive technical ability.The model considers contributing entities derived from:Self-learned control of movement patterns;subjected to classical mechanical forces governed by Newton’s physical laws;influenced by biopsychosocial health factors;and within time’s multi-faceted perspectives,including as a quantified unit and as a spatial and cortical experience.Consequently,specific patient and situational uses may be initiated within the framework of evidence based medicine that ensures a multi-tiered context of slacklining applications in movement,balance and stability.Further research is required to investigate and mathematically define this proposed model and potentially enable an improved understanding of human functional movement.This will include its application in other diverse constructed and mechanical applications in varied environments,automation levels,robotics,mechatronics and artificial-intelligence factors,including machine learning related to movement phenotypes and applications.

Forecasting directional movement of Forex data using LSTM with technical and macroeconomic indicators

Forex(foreign exchange)is a special financial market that entails both high risks and high profit opportunities for traders.It is also a very simple market since traders can profit by just predicting the direction of the exchange rate between two currencies.However,incorrect predictions in Forex may cause much higher losses than in other typical financial markets.The direction prediction requirement makes the problem quite different from other typical time-series forecasting problems.In this work,we used a popular deep learning tool called“long short-term memory”(LSTM),which has been shown to be very effective in many time-series forecasting problems,to make direction predictions in Forex.We utilized two different data sets—namely,macroeconomic data and technical indicator data—since in the financial world,fundamental and technical analysis are two main techniques,and they use those two data sets,respectively.Our proposed hybrid model,which combines two separate LSTMs corresponding to these two data sets,was found to be quite successful in experiments using real data.

A Water Movement Study in Lianzhou Bay, Guangxi Province, China

This study investigates the physical conditions(water depth, current speed, salinity, temperature) in Lianzhou Bay, a shallow coastal bay in southern China, during two expeditions in the dry and wet seasons of 2011. Based on these expedition data, basic hydrodynamic parameters like Brunt-V?is?l? Frequency, Richardson Number, Rossby radius, and Resonance Period are calculated. The results show that Lianzhou Bay is characterized by comparatively small quantity of freshwater input and weak stratification. Strong tides, which are spatially uniform within the bay, cause turbulent mixing. Residence time of the water is shorter in winter due to a stronger coastal current in that season. Consideration of the water movement may help to reduce the harmful ecological impact of aquaculture waste water discharge.

Horizontal crustal movement in Chinese mainland before and after the great Kunlun Mountain M=8.1 earthquake in 2001

The continuous GPS observation at the fiducial stations in the Crustal Movement Observation Network of China (CMONOC) recorded the crustal movement of Chinese mainland before and after the great Kunlun Mountain earthquake of M=8.1 on November 14, 2001, especially the horizontal crustal movement in the western part of China. Based on the datum defined by a group of stable stations with small mutual horizontal displacements for a few years, the time series of horizontal displacements at fiducial stations were obtained. Significant anomalous horizontal displacements had appeared at the fiducial stations in the western part of China since early November 2000 and several earthquakes with the magnitudes about 6.0 had occurred in Yunnan and Sichuan Provinces. The northward components of the horizontal displacement at the fiducial stations in west China had decreased signifi-cantly and even changed in the opposite sense since mid April 2001. After the earthquake, the northward dis-placements still decreased and there were significant westward displacements. The process of the crustal move-ment in the western part of Chinese mainland (in reference to east China) suggests that the main force source for this earthquake came from the northward pushing of the Indian plate. The great earthquake released a large amount of energy, as a result, the action applied by the Indian plate to Chinese mainland diminished significantly and after the great earthquake, the seismic activity in Chinese mainland decreased considerably until the end of 2002.

Early constraint-induced movement therapy affects behavior and neuronal plasticity in ischemia-injured rat brains

Constraint-induced movement therapy is an effective rehabilitative training technique used to improve the restoration of impaired upper extremity movement after stroke. However, whether constraint-induced movement therapy is more effective than conventional rehabilitation in acute or sub-acute stroke remains controversial. The aim of the present study was to identify the optimal time to start constraint-induced movement therapy after ischemic stroke and to explore the mechanisms by which constraint-induced movement therapy leads to post-stroke recovery. Sixty-four adult male Sprague-Dawley rats were randomly divided into four groups: sham-surgery group, cerebral ischemia/reperfusion group, early constraint-induced movement therapy group, and late constraint-induced movement therapy group. Rat models of left middle cerebral artery occlusion were established according to the Zea Longa line embolism method. Constraint-induced movement therapy was conducted starting on day 1 or day 14 in the early constraint-induced movement therapy and late constraint-induced movement therapy groups, respectively. To explore the effect of each intervention time on neuromotor function, behavioral function was assessed using a balance beam walking test before surgery and at 8 and 21 days after surgery. The expression levels of brain-derived neurotrophic factor, nerve growth factor and Nogo receptor were evaluated using real time-polymerase chain reaction and western blot assay to assess the effect of each intervention time. The results showed that the behavioral score was significantly lower in the early constraint-induced movement therapy group than in the cerebral ischemia/reperfusion and late constraint-induced movement therapy groups at 8 days. At 21 days, the scores had significantly decreased in the early constraint-induced movement therapy and late constraint-induced movement therapy groups. At 8 days, only mild pyknosis appeared in neurons of the ischemic penumbra in the early constraint-induced movement therapy group, which was distinctly better than in the cerebral ischemia/reperfusion group. At 21 days, only a few vacuolated cells were observed and no obvious inflammatory cells were visible in late constraint-induced movement therapy group, which was much better than at 8 days. The mRNA and protein expression levels of brain-derived neurotrophic factor and nerve growth factor were significantly higher, but expression levels of Nogo receptor were significantly lower in the early constraint-induced movement therapy group compared with the cerebral ischemia/reperfusion and late constraint-induced movement therapy groups at 8 days. The changes in expression levels at 21 days were larger but similar in both the early constraint-induced movement therapy and late constraint-induced movement therapy groups. Besides, the protein nerve growth factor level was higher in the late constraint-induced movement therapy group than in the early constraint-induced movement therapy group at 21 days. These results suggest that both early(1 day) and late(14 days) constraint-induced movement therapy induces molecular plasticity and facilitates functional recovery after ischemic stroke, as illustrated by the histology. The mechanism may be associated with downregulation of Nogo receptor expression and upregulation of brain-derived neurotrophic factor and nerve growth factor expression.

Neural and Spinal Modules in Implementation of a Simple Ballistic Movement

A simple ballistic movement and two of its attributes (namely, reversal in time and synchronization with external events) are formulated. A three-dimensional, three-link musculoskeletal arm is subjected to a fast ballistic type movement. The central components of the movement from hippocampal, cerebellar, basal ganglia and reticular formation structures that may be involved in timing are identified. The role of agonist muscles and spinal reflexes in the execution of ballistic movements (namely, in fast starts and fast stops) is discussed. The needed three time intervals are constructed in real time and can be coordinated with external events. Delaying or advancing in time, synchronization, time scaling and inverting events in time relative to the movement is formulated. Digital computer simulations are presented to test the behavior of the formulated neural and spinal processing and demonstrate the behavior of the arm under such control.

Restoration of Time-Spatial Scales in Global Temperature Data

The objective of this paper is to utilize images of spatial and temporal fluctuations of temperature over the Earth to study the global climate variation. We illustrated that monthly temperature observations from weather stations could be decomposed as components with different time scales based on their spectral distribution. Kolmogorov-Zurbenko (KZ) filters were applied to smooth and interpolate gridded temperature data to construct global maps for long-term (≥ 6 years) trends and El Nino-like (2 to 5 years) movements over the time period of 1893 to 2008. Annual temperature seasonality, latitude and altitude effects have been carefully accounted for to capture meaningful spatiotemporal patterns of climate variability. The result revealed striking facts about global temperature anomalies for specific regions. Correlation analysis and the movie of thermal maps for El Nino-like component clearly supported the existence of such climate fluctuations in time and space.

进港航班滑入时间预测

准确预测进港航班滑入时间对合理调配航班保障资源和提高机场场面运行效率具有重要意义,可有效克服各大机场粗放式预测航班进港时刻的不足,为此提出一种基于机器学习模型的滑入时间预测方法。以首都机场为具体研究对象,分析进港航班滑入时间的影响因素并构建特征集;将线性回归、K-最近邻、支持向量机、决策树、随机森林和梯度提升回归树6种在滑出时间预测方面得到广泛应用的机器学习模型用于进港航班滑入时间预测。研究结果表明:在误差范围±3 min内6种机器学习模型的预测精度均超过90%,表明特征集的构建和模型的选择是有效的;综合预测性能与模型拟合评估结果,梯度提升回归树模型的预测效果最好;在梯度提升回归树模型上场面流量特征的贡献度最大,新引入的跨区特征对预测模型的贡献度超过了大部分传统特征。

不同风格驾驶员眼动特性分析——夜间快速路分流区

为提高驾驶员在夜间快速路分流区换道的安全性,以不同风格的驾驶员为研究对象,分析不同风格驾驶员换道时眼动参数的变化规律。首先在前人研究基础上自编夜间快速路驾驶风格量表,对量表进行信度和Pearson相关系数法的效度检验;然后通过主成分分析法对问卷调查法得出的结果进行分析,得出驾驶风格综合得分量化模型,并使用K均值聚类分析法划分驾驶风格;最后基于眼动仪进行实车试验,获取三种风格驾驶员换道的眼动数据。试验结果表明:谨慎型、一般型、激进型驾驶员对于后视镜平均注视次数占比为48%、27%、25%;对左右两侧的平均累计注视时间占比是31%、25%、19%;平均瞳孔面积占比为56.3%、27.6%、16.1%。试验结果可以为提高驾驶员换道的行车安全性研究提供一定的数据支持。

基于射频识别技术的笼养雏鸡运动监测研究

为了解笼养雏鸡的运动行为和健康状况,研究设计了一种基于射频识别技术(RFID)的笼养鸡个体实时运动监测系统。研究首先搭建了一个模拟的试验环境,其包括一个超高频的射频识别读写器,三个天线和若干标签,一台计算机以及射频识别读写软件;随后使用机器学习的方法拟合出当前环境下不同天线接收信号强度与距离之间的关系,并进行性能比较;通过对数据进行预处理,使用获得的距离模型计算出标签与不同天线之间的距离,使用多点定位计算出所建立坐标系下标签的位置信息,实现对不同标签的运动轨迹可视化。结果显示,选定的6个电子标签测试时间为30 min,标签的计算位置与真实位置的最小欧式误差距离为4.52 cm,所有测试点的平均误差距离为9.56 cm;对比标签的真实运动轨迹和计算运动轨迹,RFID监测系统能够动态地识别活动量减少或不活动的病鸡。研究表明,基于RFID建立的笼养鸡个体实时运动检测系统能够实时监测笼养鸡个体活动情况,为家禽健康监测和疾病预防提供技术支持。

扫秒式与跳秒式机芯声发射信号时间序列研究

声发射技术是评价机芯内部结构及传动所产生的振动和噪声的有效方法,试验研究了扫秒式机芯和跳秒式机芯的声发射信号特征参数及其时域信号,并对其建立时间序列AR模型进行分析.研究表明,相比扫秒式机芯,跳秒式机芯声发射信号能量与振幅更大,具有较强的信号强度和频度,且其时域信号更为对称,波形振幅更大.机芯声发射信号时间序列AR模型可以较好表征出不同类型机芯的振动及噪声特征,可用于机芯结构性能的评价表征.

活动行为时间使用流行病学及其国内研究展望

活动行为时间使用流行病学已成为当前国际公共卫生领域的重要发展前沿之一。本文对时间使用流行病学的学科形成进行概述,并从关键研究问题、数据性质和统计学分析方法3个方面总结活动行为时间使用流行病学的特点。通过梳理国内活动行为时间使用流行病学的研究现状,提出未来应重点开展活动行为时间分配的健康影响效应、活动行为最佳使用时间分配、活动行为使用时间分配模式的分布及其影响因素等领域的研究,同时指出在方法学方面的改进之处。

“元亨利贞”与《周易》春夏秋冬的四时结构模式

《周易》以“元亨利贞”一句开篇,而“元亨利贞”是与春夏秋冬四时相呼应的,是四时观念的总结升华。农耕文明的生产方式决定了中国文化对时间的敏感,“食哉,惟时”是早期中国的重要思想理论,《周易》特别强调“时义大矣哉”的思想。先秦经典文本存在以四时为基础的文本结构形式,《周易》与《尚书》《诗经》《周礼》《吕氏春秋》等经典文献一样,都存在一个以春夏秋冬为中心线索的文本结构形态。《周易》以元亨利贞的四时观念为文本总纲,以“雷以动之”的意象为中心而结构文本,《屯》《豫》《革》《复》四卦是春夏秋冬四时运转的具体象征形式,《周易》的四时结构体现着时之动、物之象、礼之成、义之合的基本原则。

改进DTW算法的游泳训练视频手臂动作识别方法

针对复杂场景下游泳训练视频不同手臂动作识别准确性不足的问题,研究一种基于改进动态时间规整(DTW)算法的游泳训练视频手臂动作识别方法.将图像划分为若干个超像素区域,并通过计算显著值将像素合并成显著区域;借助人体骨骼结构,从显著区域中提取游泳手臂动作特征参数;将特征组成时间序列数据,利用改进DTW算法通过相似度匹配的特性来完成动作类型识别.结果表明:该方法的杰卡德系数较高,可以识别和分析不同场景下不同泳姿动作,具有更高的准确性和一致性.