Denial of Sartre's Existentialism in The Time Traveler's Wife

By contrast with Sartre's existentialism,The Time Traveler's Wife depicts another humanistic world.Moreover,such things as meaning,reason,compensation and peace are indispensable in this world.

Jump Drive, Replicators, Transporters, and Time Travel

Jumping from place to place, replicating food, biological or mechanical parts or beaming up somebody, may not be fiction, rather an issue of practical implementation as shall be observed in this paper. Devices like transporter, food replicators or warp drive intrigue our imagination. This paper is intended to show that Jump drive is an issue of coordinate transformation. Changing location from planet X to planet Y does not necessarily require travelling a distance D connecting between the two planets. The theoretical knowledge of changing the location from coordinate X to coordinate Y exists;we do that in signal processing, but, we have not yet developed such a machine. The present paper shows the feasibility of jump drive;however, much work needs to be done on the implementation.

Love Is Intensified by Absence- Book Review on "The Time Traveler's Wife"

In this paper,a review was finished according to a novel-"The Time Traveler's Wife".It use time travel to explore miscommunication and distance in relationships.A lot of knowledge could be obtained from the passage.

Accessibility Comparison and Spatial Differentiation of Xi’an Scenic Spots with Different Modes Based on Baidu Real-time Travel

A study of the accessibility of a city’s scenic spots via different travel modes can contribute to optimization of tourism-related transportation while improving tourists’ travel-related satisfaction levels and advancing tourism. We systematically analyzed the accessibility of 56 scenic spots in Xi’an City, China, via car and public transport travel modes using the real-time travel function of the Baidu Maps API(Application Programming Interface) along with spatial analysis methods and the modal accessibility gap index of scenic spots. We obtained the following results. First, maximum and minimum travel times using public transport exceeded those using cars. Moreover, the accessibility of scenic spots via cars and public transport presented a circular spatial pattern of increasing travel time from the center to the periphery. Contrasting with travel by public transport, car travel showed a clear time-space compression effect. Second, accessibility of the scenic spots via cars and public transport showed some spatial heterogeneity, with no clear advantages of car accessibility in the central urban area. However, advantages of car accessibility were increasingly evident moving from the center to the periphery. Third, whereas the correlation of the modal accessibility gap index of scenic spots in Xi’an with global space was significantly positive, local spatial interdependence was only evident in some inner city areas and in marginal areas. Moreover, spatial heterogeneity was evident in two regions but was insignificant in other areas, indicating that the spatial interdependence of the modal accessibility gap index in most scenic spots was not apparent in terms of the overall effect of public transport routes, road networks, and the distribution of scenic spots. The improvement of public transport coverage in marginal areas and the optimization of public transport routes in central urban areas are essential tasks for improving travel using public transport in the future.

Bus transit travel time reliability evaluation based on automatic vehicle location data

In order to provide important parameters for schedule designing, decision-making bases for transit operation management and references for passengers traveling by bus, bus transit travel time reliability is analyzed and evaluated based on automatic vehicle location （AVL） data. Based on the statistical analysis of the bus transit travel time, six indices including the coefficient of variance, the width of travel time distribution, the mean commercial speed, the congestion frequency, the planning time index and the buffer time index are proposed. Moreover, a framework for evaluating bus transit travel time reliability is constructed. Finally, a case study on a certain bus route in Suzhou is conducted. Results show that the proposed evaluation index system is simple and intuitive, and it can effectively reflect the efficiency and stability of bus operations. And a distinguishing feature of bus transit travel time reliability is the temporal pattern. It varies across different time periods.

Shifted first arrival point travel time NMO inversion

Serious stretch appears in shallow long offsset signals after NMO correction. In this article we study the generation mechanism of NMO stretch, demonstrate that the conventional travel time equation cannot accurately describe the travel time of the samples within the same reflection wavelet. As a result, conventional NMO inversion based on the travel time of the wavelet＇s central point occurs with errors. In this article, a travel time equation for the samples within the same wavelet is reconstructed through our theoretical derivation （the shifted first arrival point travel time equation）, a new NMO inversion method based on the wavelet＇s first arrival point is proposed. While dealing with synthetic data, the semblance coefficient algorithm equation is modified so that wavelet first arrival points can be extracted. After that, NMO inversion based on the new velocity analysis is adopted on shot offset records. The precision of the results is significantly improved compared with the traditional method. Finally, the block move NMO correction based on the first arrival points travel times is adopted on long offset records and non-stretched results are achieved, which verify the proposed new equation.

Travel time function for basic link considering signal control in network traffic model

In order to describe the travel time of signalcontrolled roads, a travel time model for urban basic roads based on the cumulative curve is proposed. First, the traffic wave method is used to analyze the formation and dispersion of the vehicle queue. Cumulative curves for road entrances and exits are established. Based on the cumulative curves, the travel time of the one-lane road under stable flow input is derived. And then, the multi-lane road is decomposed into a series of single-lane links based on its topological characteristics. Hence, the travel time function for the basic road is obtained. The travel time is a function of road length, flow and control parameters. Numerical analyses show that the travel time depends on the supply-demand condition, and it has high sensitivity during peak hours.

Travel time and alternative configurations analysis for automated storage/retrieval systems based on geometrical method

In order to evaluate the efficiency of the automated storage/retrieval system(AS/RS)accurately,and compare different layouts of the AS/RS using mean travel time,under randomized storage conditions,an exact,geometry-based analytical model is presented.The model can be used to compute the expected single-command and dual-command travel time for a storage/retrieval(S/R)machine which can travel simultaneously horizontally and vertically as it moves along a storage aisle.The rack may be either square in time or non square in time.Additionally,the alternative layouts of the AS/RS and travel-time models are examined.Comparing with setting the I/O point at the left-lower corner of the rack,setting the I/O point at any point at the vertical edge can help enhance the efficiency of the AS/RS.

Beijing Time Travel

Daily travel within Beijing need not be anymore troublesome than going about any major metropolis.Simply,certain basic facts need to be kept in mind,and ordinary precautions taken.Essentially,it’s the same situation as midtown Manhattan or downtown Tokyo,except everyone’s speaking Chinese.

Time-varying confidence interval forecasting of travel time for urban arterials using ARIMA-GARCH model

To improve the forecasting reliability of travel time, the time-varying confidence interval of travel time on arterials is forecasted using an autoregressive integrated moving average and generalized autoregressive conditional heteroskedasticity （ARIMA-GARCH） model. In which, the ARIMA model is used as the mean equation of the GARCH model to model the travel time levels and the GARCH model is used to model the conditional variances of travel time. The proposed method is validated and evaluated using actual traffic flow data collected from the traffic monitoring system of Kunshan city. The evaluation results show that, compared with the conventional ARIMA model, the proposed model cannot significantly improve the forecasting performance of travel time levels but has advantage in travel time volatility forecasting. The proposed model can well capture the travel time heteroskedasticity and forecast the time-varying confidence intervals of travel time which can better reflect the volatility of observed travel times than the fixed confidence interval provided by the ARIMA model.

Time Travel in the Brain

当你什么都不做时你究竟在做什么?如果回答是“什么也没做”,从逻辑上看似乎是对的;但如果是一个涉及神经科学的题,那答案是错的。科学家经过大量的大脑扫描实验发现:当人在进行脑力活动时,大脑中主宰该活动的区域(相对较亮的区域)会变大。最新的研究表明,当大脑的一些区域变亮时其他的区域则变暗。当我们好像在做什么事的时候,这些变暗的区域处于休眠状态,而当我们好像什么也没做时,这些区域则相当活跃。那么,我们究竟在做什么呢?答案是“时间旅行”。

Alpha-reliable combined mean traffic equilibrium model with stochastic travel times

Based on the reliability budget and percentile travel time(PTT) concept, a new travel time index named combined mean travel time(CMTT) under stochastic traffic network was proposed. CMTT here was defined as the convex combination of the conditional expectations of PTT-below and PTT-excess travel times. The former was designed as a risk-optimistic travel time index, and the latter was a risk-pessimistic one. Hence, CMTT was able to describe various routing risk-attitudes. The central idea of CMTT was comprehensively illustrated and the difference among the existing travel time indices was analyzed. The Wardropian combined mean traffic equilibrium(CMTE) model was formulated as a variational inequality and solved via an alternating direction algorithm nesting extra-gradient projection process. Some mathematical properties of CMTT and CMTE model were rigorously proved. Finally, a numerical example was performed to characterize the CMTE network. It is founded that that risk-pessimism is of more benefit to a modest(or low) congestion and risk network, however, it changes to be risk-optimism for a high congestion and risk network.

Getting pre-stack time migration travel times from the single square root operator

Improving the focusing capability of pre-stack time migration allows the imaged section to reflect structural characteristics, depth, and interface shape and it is a key step for the preparation of the initial depth migration velocity model. The traditional symmetrical travel time equation is derived based on the assumption of a layered model. It is difficult to achieve the desired effect of focusing in media with strong lateral variation. The nonsymmetrical travel time equation based on Lie algebra and a pseudo-differential operator contains a lateral velocity derivative which can improve the focusing capability even in strongly lateral variable media and also the computation precision of the weight coefficients for relative amplitude preservation. Compared with the symmetrical methods, the nonsymmetrical method is more effective. In this paper, we describe several key steps of nonsymmetric pre-stack travel time calculation and present some test results using synthetic and real data.

Travel time prediction model of freeway based on gradient boosting decision tree

To investigate the travel time prediction method of the freeway, a model based on the gradient boosting decision tree (GBDT) is proposed. Eleven variables (namely, travel time in current period T i , traffic flow in current period Q i , speed in current period V i , density in current period K i , the number of vehicles in current period N i , occupancy in current period R i , traffic state parameter in current period X i , travel time in previous time period T i -1 , etc.) are selected to predict the travel time for 10 min ahead in the proposed model. Data obtained from VISSIM simulation is used to train and test the model. The results demonstrate that the prediction error of the GBDT model is smaller than those of the back propagation (BP) neural network model and the support vector machine (SVM) model. Travel time in current period T i is the most important variable among all variables in the GBDT model. The GBDT model can produce more accurate prediction results and mine the hidden nonlinear relationships deeply between variables and the predicted travel time.

Integrated reliability of travel time and capacity of urban road network under ice and snowfall conditions

In order to evaluate and integrate travel time reliability and capacity reliability of a road network subjected to ice and snowfall conditions,the conceptions of travel time reliability and capacity reliability were defined under special conditions.The link travel time model(ice and snowfall based-bureau public road,ISB-BPR) and the path choice decision model(elastic demand user equilibrium,EDUE) were proposed.The integrated reliability was defined and the model was set up.Monte Carlo simulation was used to calculate the model and a numerical example was provided to demonstrate the application of the model and efficiency of the solution algorithm.The results show that the intensity of ice and snowfall,the traffic demand and supply,and the requirements for level of service(LOS) have great influence on the reliability of a road network.For example,the reliability drops from 65% to 5% when the traffic demand increases by 30%.The comprehensive performance index may be used for network planning,design and maintenance.

Travel time prediction with viscoelastic traffic model

Travel time through a ring road with a total length of 80 km has been predicted by a viscoelastic traffic model(VEM), which is developed in analogous to the non-Newtonian fluid flow. The VEM expresses a traffic pressure for the unfree flow case by space headway, ensuring that the pressure can be determined by the assumption that the relevant second critical sound speed is exactly equal to the disturbance propagation speed determined by the free flow speed and the braking distance measured by the average vehicular length. The VEM assumes that the sound speed for the free flow case depends on the traffic density in some specific aspects, which ensures that it is exactly identical to the free flow speed on an empty road. To make a comparison, the open Navier-Stokes type model developed by Zhang(ZHANG, H. M. Driver memory, traffic viscosity and a viscous vehicular traffic flow model. Transp. Res. Part B, 37, 27–41(2003)) is adopted to predict the travel time through the ring road for providing the counterpart results.When the traffic free flow speed is 80 km/h, the braking distance is supposed to be 45 m,with the jam density uniquely determined by the average length of vehicles l ≈ 5.8 m. To avoid possible singular points in travel time prediction, a distinguishing period for time averaging is pre-assigned to be 7.5 minutes. It is found that the travel time increases monotonically with the initial traffic density on the ring road. Without ramp effects, for the ring road with the initial density less than the second critical density, the travel time can be simply predicted by using the equilibrium speed. However, this simpler approach is unavailable for scenarios over the second critical.

Robust user equilibrium model based on cumulative prospect theory under distribution-free travel time

The assumption widely used in the user equilibrium model for stochastic network was that the probability distributions of the travel time were known explicitly by travelers. However, this distribution may be unavailable in reality. By relaxing the restrictive assumption, a robust user equilibrium model based on cumulative prospect theory under distribution-free travel time was presented. In the absence of the cumulative distribution function of the travel time, the exact cumulative prospect value(CPV) for each route cannot be obtained. However, the upper and lower bounds on the CPV can be calculated by probability inequalities.Travelers were assumed to choose the routes with the best worst-case CPVs. The proposed model was formulated as a variational inequality problem and solved via a heuristic solution algorithm. A numerical example was also provided to illustrate the application of the proposed model and the efficiency of the solution algorithm.

A PSO-SVM Model for Short-Term Travel Time Prediction Based on Bluetooth Technology

The accurate prediction of travel time along roadway provides valuable traffic information for travelers and traffic managers. Aiming at short-term travel time forecasting on urban arterials,a prediction model( PSOSVM) combining support vector machine( SVM) and particle swarm optimization( PSO) is developed. Travel time data collected with Bluetooth devices are used to calibrate the proposed model. Field experiments show that the PSO-SVM model 's error indicators are lower than the single SVM model and the BP neural network( BPNN) model. Particularly,the mean-absolute percentage error( MAPE) of PSO-SVM is only 9. 453 4 %which is less than that of the single SVM model( 12. 230 2 %) and the BPNN model( 15. 314 7 %). The results indicate that the proposed PSO-SVM model is feasible and more effective than other models for shortterm travel time prediction on urban arterials.

Evaluation of Freeway Travel Time Variability and Reliability under Adverse Weather with TRANSMIT Data

Traffic congestion has caused many detrimental effects including higher fuel consumption, more vehicle emissions, increased accidents, as well as greater tension due to uncertain travel time. In addition to delay, the variability and reliability of travel time has been of concern to motorists on their daily travel, especially during peak periods. The objective of this study is to examine freeway travel time variability and reliability under different traffic and weather conditions with the use of TRANSMIT data collected by roadside readers deployed on a 40-mile segment of the Interstate Highway 1-287 in New Jersey. Travel time variability and reliability measures including mean travel time, the 95th percentile travel time, travel time index, buffer index, and planning time index under recurring and non-recurring congestion （adverse weather） are investigated. It was found that the standard deviation of travel time increased, due to the weather condition varying from dry to rain and to snow, while the buffer index increased from 29% to 45% and to 94%.

Stochastic network equilibrium model with reliable travel time confidence level

In order to ensure on-time arrival when travelersmake their trips, the stochastic network assignment modelunder uncertainty of travel time is investigated. First, basedon travelers＇ route choice behavior, the reliable travel timeconfidence level （RTTCL）, which is the probability that a triparrives within the shortest average travel time plus theacceptable travel time difference, is defined. Then, areliability-based user equilibrium （RUE） model, whichhypothesizes that for each OD pair no traveler can improvehis/her RTTCL by unilaterally changing routes, is built.Since the traditional traffic assignment algorithms are notfeasible to solve the RUE model, a quasi method of successiveaverage （QMSA） is developed. Using Nguyen-Dupuis andSioux Falls networks, the model and the algorithm are tested.The results show that the QMSA algorithm can rapidlyconverge to a high accuracy for solving the proposed RUEmodel, and the RUE model can provide a good response totravelers＇ behavior in the stochastic network.