A time-space network-based model for transportation service optimization of China Railway Express

This paper describes the development and optimization plans for the China Railway Express(CR Express).As a new type of international land transport organization,CR Express has emerged with the continuous expansion of China toward European investment and trade,and in particular,has expanded with the continuous progress of the One Belt and One Road(OBOR)initiative.In addition to improving the service quality of CR Express,the operating costs must be reduced for developing“smart railways”that serve“smart cities”.We propose a dualobjective-based function mathematical optimization model;the satisfaction of the cargo owner is considered,and the timeliness,transportation capacity,and goods category constraints of CR Express transportation are designed.Moreover,we present the normalized equivalent method of the two-objective function of the model.Finally,a case study is conducted against the background of certain trains in the western corridor of CR Express to validate the effectiveness of the model and research methods proposed in this study.

TIME-SPACE CONCEPT FOR PRECISION MEASUREMENT

The transformation between time and space is discussed. To improve real-time response speed of intelligent measuring system, the concept of exchanging program execution time with more circuitry is presented working in cycle mode. Displacement measuring by magnification is achieved with period measurement by magnification. To change the condition that traditional precision measurement depends on machining precision greatly, the concept of measuring space with time and theory of time-space coordinate transformation are proposed. Guided by the idea of measuring space with time, differential frequency measurement system and time grating displacement sensor are developed based on the proposed novel methods. And high-precision measurement is achieved without high-precision manufacture, which embeds the remarkable characteristics of low cost but high precision to the devices. Experiment and test results conform the validity of the proposed time-space concept.

Adaptive time-space resource and waveform control for collocated MIMO radar with simultaneous multi-beam

Collocated multiple input multiple output(MIMO)radar,which has agile multi-beam working mode,can offer enhanced multiple targets tracking(MTT)ability.In detail,it can illuminate different targets simultaneously with multi-beam or one wide beam among multi-beam,providing greater degree of freedom in system resource control.An adaptive time-space resource and waveform control optimization model for the collocated MIMO radar with simultaneous multi-beam is proposed in this paper.The aim of the proposed scheme is to improve the overall tracking accuracy and meanwhile minimize the resource consumption under the guarantee of effective targets detection.A resource and waveform control algorithm which integrates the genetic algorithm(GA)is proposed to solve the optimization problem.The optimal transmitting waveform parameters,system sampling period,sub-array number,binary radar tracking parameterχ_i(t_k),transmitting energy and multi-beam direction vector combination are chosen adaptively,where the first one realizes the waveform control and the latter five realize the timespace resource allocation.Simulation results demonstrate the effectiveness of the proposed control method.

Adaptive resource management for multi-target tracking in co-located MIMO radar based on time-space joint allocation

Compared with the traditional phased array radar, the co-located multiple-input multiple-output(MIMO) radar is able to transmit orthogonal waveforms to form different illuminating modes, providing a larger freedom degree in radar resource management. In order to implement the effective resource management for the co-located MIMO radar in multi-target tracking,this paper proposes a resource management optimization model,where the system resource consumption and the tracking accuracy requirements are considered comprehensively. An adaptive resource management algorithm for the co-located MIMO radar is obtained based on the proposed model, where the sub-array number, sampling period, transmitting energy, beam direction and working mode are adaptively controlled to realize the time-space resource joint allocation. Simulation results demonstrate the superiority of the proposed algorithm. Furthermore, the co-located MIMO radar using the proposed algorithm can satisfy the predetermined tracking accuracy requirements with less comprehensive cost compared with the phased array radar.

A Time-Space Optimal Parallel Sorting on a Hypercube

In this paper we discuss a parallel sorting algorithm on a hypercube. Its time complexity is O(n logn/p) +O(n). Here, P is the number of processors available and n, the amount of items to be sorted. Take the problem of time-space optimization into consideration, when P≤ O(log n), this algorithm is both timespace optimal and cost optimization. But this means only speedup is O(P) and it is not linear speedup. Therefore, we further discuss relevant parallel efficiency problems.

A "TIME-SPACE" RELATED DESIGN METHOD OF FREEZING WALL

Artificially ground freezing (AGF) is one of the main methods to establish temporary support for shaft sinking in unstable water bearing strata. Domde (1915) formula based on frozen soil strength has widely been used for designing freezing wall thickness. However, it can not ensure the stability of freezing wall, nor guarantee the safety of shaft construction as frozen depth increases in unstable water bearing strata. F A. Auld (1985, 1988)[1,2] presented a design method of freezing wall, which is on the basis of strength and stability, together with deformation of freezing wall. This paper, according to the practice in China, describes a "time -space" related design method for deep freezing wall. The method is based on "time-space" concept, which includes influence of excavation rate of advance, unsupported length of freezing wall and the sump state on inward deformation of freezing wall, and the allowable pipe deformation caused by inward deformation of freezing wall. Finally, successful application of this method to the large scale coal mine-Jining No. 2 Mine[3] in Shandong Province of China is presented. It saved much investment compared with F. A. Auld’s design for the same mine.

A traffic model of optical networks based on time-space complexity and traffic grooming

This paper researched the traffic of optical networks in time-space complexity,proposed a novel traf-fic model for complex optical networks based on traffic grooming,designed a traffic generator GTS(gener-ator based on time and space)with 'centralized+distributed' idea,and then made a simulation in Clanguage.Experiments results show that GTS can produce the virtual network topology which can changedynamically with the characteristic of scaling-free network.GTS can also groom the different traffic andtrigger them under real-time or scheduling mechanisms,generating different optical connections.Thistraffic model is convenient for the simulation of optical networks considering the traffic complexity.

Finite Difference Schemes for Time-Space Fractional Diffusion Equations in One-and Two-Dimensions

In this paper,finite difference schemes for solving time-space fractional diffusion equations in one dimension and two dimensions are proposed.The temporal derivative is in the Caputo-Hadamard sense for both cases.The spatial derivative for the one-dimensional equation is of Riesz definition and the two-dimensional spatial derivative is given by the fractional Laplacian.The schemes are proved to be unconditionally stable and convergent.The numerical results are in line with the theoretical analysis.

Modeling of Surface Waves in a Fluid Saturated Poro-Elastic Medium under Initial Stress Using Time-Space Domain Higher Order Finite Difference Method

In this present context, mathematical modeling of the propagation of surface waves in a fluid saturated poro-elastic medium under the influence of initial stress has been considered using time dependent higher order finite difference method (FDM). We have proved that the accuracy of this finite-difference scheme is 2M when we use 2nd order time domain finite-difference and 2M-th order space domain finite-difference. It also has been shown that the dispersion curves of Love waves are less dispersed for higher order FDM than of lower order FDM. The effect of initial stress, porosity and anisotropy of the layer in the propagation of Love waves has been studied here. The numerical results have been shown graphically. As a particular case, the phase velocity in a non porous elastic solid layer derived in this paper is in perfect agreement with that of Liu et al. (2009).

Earthquake-Affected Time-Space Domain, Recurrence Interval and Effective Preparation Time of Earthquakes

The study shows that earthquake-affected time-space domain (ETSD), i.e. a time-space range in which strong earthquakes are unable to occur owing to the influence of a prior earthquake occurring, shows a hyperbolic margin curve in the t(time)-r(distance) coordinate plane, which has a maximum affected radius r 0 at t=0 and a maximum influence time t 0 (i.e. the in-situ recurrence interval of earthquakes) at r=0. Based on the time-distance distributions of posterior earthquakes relative to prior ones in the regions of North China, Northwest China, Qinghai-Xizang (Tibet) plateau and Southwest China, the optimized and 90%-confidence margin curves are estimated using optimization and statistical analysis methods. This indicates that the concept and method of ETSD with 3-dimension (time-distance-magnitudes) instead of those of “recurrence interval" with 1-dimension (time) or 2-dimension (time-magnitude) provides a new approach to understanding the fluctuation of seismic activities, estimating the effective earthquake-preparation time of potential hypocenters, and therefore improving the medium- and long-term prediction of strong earthquakes.

文旅产业国际传播策略优化研究——基于YouTube#China travel视频用户评论语料分析

目的:了解外国游客对现有中国旅游业的评价与态度,是优化“媒体+文旅”形势下国际传播效果及文旅产业建设的重要佐证。方法:通过使用Gooseeker工具对YouTube #China travel和#144-hour标签下热门视频用户评价进行爬取和分析。结果:从受众视角揭示了我国现有文旅产业国际传播的现状及效果,为优化中国文旅产业国际传播策略提供数据支持。结论:面对外国社交媒体平台上“China travel”的爆火,我国的文旅产业建设及国际传播推广应从情感角度入手,把握受众的评价与态度,借助媒体融合的发展趋势建立细分化的国际传播矩阵。

SLC Method and Earthquakes' Clustering Features in Time-Space in the Top Area of the Kunlun-Altun-Arc

By using the SLC(Single-Link Cluster)method,this study worked in three respects:(a)set up three-dimensional(3-D)SLC software that can deal with a large catalogue of earthquakes and analyze the characteristics of earthquakes’ clustering and scattering in time-space:(b)defined several parameters to describe the distinguishing feature for the SLC frame and developed a technique to calculate the 3-D SLC frames and these parameters with gradual time-sliding,and inspected their variations with time,especially before large events; and(c)by using these means,treated the earthquake catalogue in the top area of the Kunlun-Altun-Arc as well as some valuable results that had been obtained.

ON MONOTONE TRAVELING WAVES FOR NICHOLSON'S BLOWFLIES EQUATION WITH DEGENERATE p-LAPLACIAN DIFFUSION

We study the existence and stability of monotone traveling wave solutions of Nicholson's blowflies equation with degenerate p-Laplacian diffusion.We prove the existence and nonexistence of non-decreasing smooth traveling wave solutions by phase plane analysis methods.Moreover,we show the existence and regularity of an original solution via a compactness analysis.Finally,we prove the stability and exponential convergence rate of traveling waves by an approximated weighted energy method.

Coexisting fast–slow dendritic traveling waves in a 3D-array electric field coupled neuronal network

Coexistence of fast and slow traveling waves without synaptic transmission has been found in hhhippocampal tissues,which is closely related to both normal brain activity and abnormal neural activity such as epileptic discharge. However, the propagation mechanism behind this coexistence phenomenon remains unclear. In this paper, a three-dimensional electric field coupled hippocampal neural network is established to investigate generation of coexisting spontaneous fast and slow traveling waves. This model captures two types of dendritic traveling waves propagating in both transverse and longitude directions: the N-methyl-D-aspartate(NMDA)-dependent wave with a speed of about 0.1 m/s and the Ca-dependent wave with a speed of about 0.009 m/s. These traveling waves are synaptic-independent and could be conducted only by the electric fields generated by neighboring neurons, which are basically consistent with the in vitro data measured experiments. It is also found that the slow Ca wave could trigger generation of fast NMDA waves in the propagation path of slow waves whereas fast NMDA waves cannot affect the propagation of slow Ca waves. These results suggest that dendritic Ca waves could acted as the source of the coexistence fast and slow waves. Furthermore, we also confirm the impact of cellular spacing heterogeneity on the onset of coexisting fast and slow waves. The local region with decreasing distances among neighbor neurons is more liable to promote the onset of spontaneous slow waves which, as sources, excite propagation of fast waves. These modeling studies provide possible biophysical mechanisms underlying the neural dynamics of spontaneous traveling waves in brain tissues.

Travel-Limiting Disabilities in the United States: Why Accessibility Matters?

This study evaluates the distribution of travel-limiting disabilities across genders and geographic locations in the United States. This study aims to describe and compare the socioeconomic and demographic variables of the people with and without travel-limiting disabilities across geographic locations and gender. The study further evaluates the trip purpose and impact of Covid-19 fourth wave pandemic on the use of public transit and travel to physical workplace for the people with and without travel-limiting disabilities across gender and geographic locations. The study uses the 2022 weighted National Household Travel Survey dataset and employs descriptive statistics. Results reaffirm the findings from previous literature that there are more people with travel-limiting disabilities in urban areas and among women. Over 50 percent of people aged 65 and above have a form of travel-limiting disabilities. The most trip for people with travel-limiting disabilities is made for shopping and medical purposes. Across all categories, rural areas, urban areas, male and female for the people without travel-limiting disabilities, COVID-19 fourth wave did not change the pattern of trips made to physical workplace as pre-COVID-19 era. This pattern is also observable for the people with travel-limiting disabilities in rural and urban areas. Females with travel-limiting disabilities reported making less trips to physical workplaces while male reported doing the same as before COVID-19 era. The study concludes that the quantification of travel-limiting disabilities across geographic location and gender is vital in disability study and could drive policy implementation for improved accessibility for the vulnerable population.

A Combination Prediction Model for Short Term Travel Demand of Urban Taxi

This study proposes a prediction model considering external weather and holiday factors to address the issue of accurately predicting urban taxi travel demand caused by complex data and numerous influencing factors.The model integrates the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise(CEEMDAN)and Convolutional Long Short Term Memory Neural Network(ConvLSTM)to predict short-term taxi travel demand.The CEEMDAN decomposition method effectively decomposes time series data into a set of modal components,capturing sequence characteristics at different time scales and frequencies.Based on the sample entropy value of components,secondary processing of more complex sequence components after decomposition is employed to reduce the cumulative prediction error of component sequences and improve prediction efficiency.On this basis,considering the correlation between the spatiotemporal trends of short-term taxi traffic,a ConvLSTM neural network model with Long Short Term Memory(LSTM)time series processing ability and Convolutional Neural Networks(CNN)spatial feature processing ability is constructed to predict the travel demand for urban taxis.The combined prediction model is tested on a taxi travel demand dataset in a certain area of Beijing.The results show that the CEEMDAN-ConvLSTM prediction model outperforms the LSTM,Autoregressive Integrated Moving Average model(ARIMA),CNN,and ConvLSTM benchmark models in terms of Symmetric Mean Absolute Percentage Error(SMAPE),Root Mean Square Error(RMSE),Mean Absolute Error(MAE),and R2 metrics.Notably,the SMAPE metric exhibits a remarkable decline of 21.03%with the utilization of our proposed model.These results confirm that our study provides a highly accurate and valid model for taxi travel demand forecasting.

“China Travel”打开中国国际传播新维度

随着中国免签“朋友圈”的不断扩容,越来越多的外国游客在72/144小时过境免签政策的鼓励下来到中国。外国游客沉浸体验实时现场展开的中国故事,“city不city”的“热梗”在网上病毒式传播,还在攀升中的“China Travel”正在打开中国国际传播的一个新维度。

Measurement of very low-molecular weight metabolites by traveling wave ion mobility and its use in human urine samples

The collision cross-sections(CCS)measurement using ion mobility spectrometry(IMS)in combination with mass spectrometry(MS)offers a great opportunity to increase confidence in metabolite identification.However,owing to the lack of sensitivity and resolution,IMS has an analytical challenge in studying the CCS values of very low-molecular-weight metabolites(VLMs250 Da).Here,we describe an analytical method using ultrahigh-performance liquid chromatography(UPLC)coupled to a traveling wave ion mobility-quadrupole-time-of-flight mass spectrometer optimized for the measurement of VLMs in human urine samples.The experimental CCS values,along with mass spectral properties,were reported for the 174 metabolites.The experimental data included the mass-to-charge ratio(m/z),retention time(RT),tandem MS(MS/MS)spectra,and CCS values.Among the studied metabolites,263 traveling wave ion mobility spectrometry(TWIMS)-derived CCS values(TWCCSN2)were reported for the first time,and more than 70%of these were CCS values of VLMs.The TWCCSN2 values were highly repeatable,with inter-day variations of<1%relative standard deviation(RSD).The developed method revealed excellent TWCCSN2 accuracy with a CCS difference(DCCS)within±2%of the reported drift tube IMS(DTIMS)and TWIMS CCS values.The complexity of the urine matrix did not affect the precision of the method,as evidenced by DCCS within±1.92%.According to the Metabolomics Standards Initiative,55 urinary metabolites were identified with a confidence level of 1.Among these 55 metabolites,53(96%)were VLMs.The larger number of confirmed compounds found in this study was a result of the addition of TWCCSN2 values,which clearly increased metabolite identification confidence.

Harmonic balance simulation of the influence of component uniformity and reliability on the performance of a Josephson traveling wave parametric amplifier

A Josephson traveling wave parametric amplifier(JTWPA),which is a quantum-limited amplifier with high gain and large bandwidth,is the core device of large-scale measurement and control systems for quantum computing.A typical JTWPA consists of thousands of Josephson junctions connected in series to form a transmission line and hundreds of shunt LC resonators periodically loaded along the line for phase matching.Because the variation of these capacitors and inductors can be detrimental to their high-frequency characteristics,the fabrication of a JTWPA typically necessitates precise processing equipment.To guide the fabrication process and further improve the design for manufacturability,it is necessary to understand how each electronic component affects the amplifier.In this paper,we use the harmonic balance method to conduct a comprehensive study on the impact of nonuniformity and fabrication yield of the electronic components on the performance of a JTWPA.The results provide insightful and scientific guidance for device design and fabrication processes.

Solving the Generalized Traveling Salesman Problem Using Sequential Constructive Crossover Operator in Genetic Algorithm

The generalized travelling salesman problem(GTSP),a generalization of the well-known travelling salesman problem(TSP),is considered for our study.Since the GTSP is NP-hard and very complex,finding exact solutions is highly expensive,we will develop genetic algorithms(GAs)to obtain heuristic solutions to the problem.In GAs,as the crossover is a very important process,the crossovermethods proposed for the traditional TSP could be adapted for the GTSP.The sequential constructive crossover(SCX)and three other operators are adapted to use in GAs to solve the GTSP.The effectiveness of GA using SCX is verified on some GTSP Library(GTSPLIB)instances first and then compared against GAs using the other crossover methods.The computational results show the success of the GA using SCX for this problem.Our proposed GA using SCX,and swap mutation could find average solutions whose average percentage of excesses fromthe best-known solutions is between 0.00 and 14.07 for our investigated instances.