Mining urban recurrent congestion evolution patterns from GPS-equipped vehicle mobility data

2016 ◽  
Vol 373 ◽  
pp. 515-526 ◽  
Author(s):  
Shi An ◽  
Haiqiang Yang ◽  
Jian Wang ◽  
Na Cui ◽  
Jianxun Cui
Keyword(s):  
Mobility Data ◽  
Vehicle Mobility

Understanding urban structures and crowd dynamics leveraging large-scale vehicle mobility data

2020 ◽  
Vol 14 (5) ◽  
Author(s):  
Zhihan Jiang ◽  
Yan Liu ◽  
Xiaoliang Fan ◽  
Cheng Wang ◽  
Jonathan Li ◽  
...  
Keyword(s):  
Large Scale ◽  
Crowd Dynamics ◽  
Urban Structures ◽  
Mobility Data ◽  
Vehicle Mobility

Drive2friends: Inferring Social Relationships From Individual Vehicle Mobility Data

2020 ◽  
Vol 7 (6) ◽  
pp. 5116-5127 ◽  
Author(s):  
Jie Li ◽  
Fanzi Zeng ◽  
Zhu Xiao ◽  
Hongbo Jiang ◽  
Zhirun Zheng ◽  
...  
Keyword(s):  
Social Relationships ◽  
Mobility Data ◽  
Vehicle Mobility

Mission Mobility Reliability Analysis of Off-Road Ground Vehicles

2020 ◽  
Author(s):  
Yixuan Liu ◽  
Chen Jiang ◽  
Zhen Hu ◽  
Zissimos P. Mourelatos ◽  
Yan Fu ◽  
...  
Keyword(s):  
Reliability Analysis ◽  
Mobility Model ◽  
Dynamic Decision Making ◽  
Ground Vehicles ◽  
Mobility Data ◽  
Uncertainty Sources ◽  
Vehicle Mobility ◽  
On Line ◽  
Dynamic Updating ◽  
Kriging Surrogate Modeling

Abstract The NATO Reference Mobility Model (NRMM) has been developed to predict the mobility of off-road ground vehicles based on modeling and simulation (M&S). Due to various uncertainty sources in the M&S, uncertainty is inherent in the vehicle mobility. Aims to account for the uncertainty in the mobility prediction in mission planning, this paper develops a simulation-based mission mobility reliability analysis framework for off-road ground vehicles. A concept of mission mobility reliability (MMR) is first proposed to quantify the reliability of a mission path which passes through different types of soils. A single-loop Kriging surrogate modeling method is then employed to overcome the challenge in the mission mobility reliability assessment caused by the computationally expensive mobility simulation. Built upon the surrogate model-based mission mobility reliability analysis, a dynamic updating scheme is proposed to update the MMR estimation based on the on-line mobility data, during the course of a specific mission and for a particular vehicle. The online dynamic updating of MMR allows for effective and dynamic decision making during the mission phase. A case study is used to demonstrate the effectiveness of the proposed MMR analysis and updating framework.

Social Relationship Inference over Private Vehicle Mobility Data

2021 ◽  
pp. 1-1
Author(s):  
Jie Li ◽  
Fanzi Zeng ◽  
Zhu Xiao ◽  
Zhirun Zheng ◽  
Hongbo Jiang ◽  
...  
Keyword(s):  
Social Relationship ◽  
Private Vehicle ◽  
Mobility Data ◽  
Vehicle Mobility

scholarly journals DeepVM: RNN-based Vehicle Mobility Prediction to Support Intelligent Vehicle Applications

2020 ◽  
Author(s):  
Wei Liu
Keyword(s):  
Theoretical Analysis ◽  
Prediction Algorithm ◽  
Intelligent Vehicle ◽  
Mobility Prediction ◽  
Mobility Data ◽  
Potential Market ◽  
Deep Recurrent Neural Network ◽  
Vehicle Mobility ◽  
Comprehensive Evaluations

The recent advances in vehicle industry and vehicle-to-everything communications are creating a huge potential market of intelligent vehicle applications, and exploiting vehicle mobility is of great importance in this field. Hence, this paper proposes a novel vehicle mobility prediction algorithm to support intelligent vehicle applications. First, a theoretical analysis is given to quantitatively reveal the predictability of vehicle mobility. Based on the knowledge earned from theoretical analysis, a deep recurrent neural network (RNN)-based algorithm called DeepVM is proposed to predict vehicle mobility in a future period of several or tens of minutes. Comprehensive evaluations have been carried out based on the real taxi mobility data in Tokyo, Japan. The results have not only proved the correctness of our theoretical analysis, but also validated that DeepVM can significantly improve the quality of vehicle mobility prediction compared with other state-of-art algorithms.

scholarly journals DeepVM: RNN-based Vehicle Mobility Prediction to Support Intelligent Vehicle Applications

2020 ◽  
Author(s):  
Wei Liu
Keyword(s):  
Theoretical Analysis ◽  
Prediction Algorithm ◽  
Intelligent Vehicle ◽  
Mobility Prediction ◽  
Mobility Data ◽  
Potential Market ◽  
Deep Recurrent Neural Network ◽  
Vehicle Mobility ◽  
Comprehensive Evaluations

The recent advances in vehicle industry and vehicle-to-everything communications are creating a huge potential market of intelligent vehicle applications, and exploiting vehicle mobility is of great importance in this field. Hence, this paper proposes a novel vehicle mobility prediction algorithm to support intelligent vehicle applications. First, a theoretical analysis is given to quantitatively reveal the predictability of vehicle mobility. Based on the knowledge earned from theoretical analysis, a deep recurrent neural network (RNN)-based algorithm called DeepVM is proposed to predict vehicle mobility in a future period of several or tens of minutes. Comprehensive evaluations have been carried out based on the real taxi mobility data in Tokyo, Japan. The results have not only proved the correctness of our theoretical analysis, but also validated that DeepVM can significantly improve the quality of vehicle mobility prediction compared with other state-of-art algorithms.

An Evaluation of a Plasma Fractionation System

1960 ◽  
Vol 4 (01) ◽  
pp. 031-044
Author(s):  
George Y. Shinowara ◽  
E. Mary Ruth
Keyword(s):  
Biological Activity ◽  
Ionic Strength ◽  
Plasma Proteins ◽  
High Concentration ◽  
Significant Evidence ◽  
Native Proteins ◽  
Mobility Data ◽  
Fractionation Procedure ◽  
The Individual ◽  
Low Ionic Strength

SummaryFour primary fractions comprising at least 97 per cent of the plasma proteins have been critically appraised for evidence of denaturation arising from a low temperature—low ionic strength fractionation system. The results in addition to those referable to the recovery of mass and biological activity include the following: The high solubilities of these fractions at pH 7.3 and low ionic strengths; the compatibility of the electrophoretic and ultracentrifugal data of the individual fractions with those of the original plasma; and the recovery of hemoglobin, not hematin, in fraction III obtained from specimens contaminated with this pigment. However, the most significant evidence for minimum alterations of native proteins was that the S20, w and the electrophoretic mobility data on the physically recombined fractions were identical to those found on whole plasma.The fractionation procedure examined here quantitatively isolates fibrinogen, prothrombin and antithrombin in primary fractions. Results have been obtained demonstrating its significance in other biological systems. These include the following: The finding of 5 S20, w classes in the 4 primary fractions; the occurrence of more than 90 per cent of the plasma gamma globulins in fraction III; the 98 per cent pure albumin in fraction IV; and, finally, the high concentration of beta lipoproteins in fraction II.

DETERMINATION OF PERFORMANCE INDICATORS OF THE TRUCK KrAZ-6510TE

2020 ◽  
pp. 19-26
Author(s):  
Olexandr Pavlenko ◽  
Serhii Dun ◽  
Maksym Skliar
Keyword(s):  
Mathematical Model ◽  
Surface Friction ◽  
Building Structures ◽  
Maximum Torque ◽  
Military Equipment ◽  
Military Vehicles ◽  
Force Magnitude ◽  
Vehicle Mobility ◽  
The Mathematical Model

In any economy there is a need for the bulky goods transportation which cannot be divided into smaller parts. Such cargoes include building structures, elements of industrial equipment, tracked or wheeled construction and agricultural machinery, heavy armored military vehicles. In any case, tractor-semitrailer should provide fast delivery of goods with minimal fuel consumption. In order to guarantee the goods delivery, tractor-semitrailers must be able to overcome the existing roads broken grade and be capable to tow a semi-trailer in off-road conditions. These properties are especially important for military equipment transportation. The important factor that determines a tractor-semitrailer mobility is its gradeability. The purpose of this work is to improve a tractor-semitrailer mobility with tractor units manufactured at PJSC “AutoKrAZ” by increasing the tractor-semitrailer gradeability. The customer requirements for a new tractor are determined by the maximizing the grade to 18°. The analysis of the characteristics of modern tractor-semitrailers for heavy haulage has shown that the highest rate of this grade is 16.7°. The factors determining the limiting gradeability value were analyzed, based on the tractor-semitrailer with a KrAZ-6510TE tractor and a semi-trailer with a full weight of 80 t. It has been developed a mathematical model to investigate the tractor and semi-trailer axles vertical reactions distribution on the tractor-semitrailer friction performances. The mathematical model has allowed to calculate the gradeability value that the tractor-semitrailer can overcome in case of wheels and road surface friction value and the tractive force magnitude from the engine. The mathematical model adequacy was confirmed by comparing the calculations results with the data of factory tests. The analysis showed that on a dry road the KrAZ-6510TE tractor with a 80 t gross weight semitrailer is capable to climb a gradient of 14,35 ° with its coupling mass full use condition. The engine's maximum torque allows the tractor-semitrailer to overcome a gradient of 10.45° It has been determined the ways to improve the design of the KrAZ-6510TE tractor to increase its gradeability. Keywords: tractor, tractor-semitrailer vehicle mobility, tractor-semitrailer vehicle gradeability.

Spatial Metabolomics of the Human Kidney Using MALDI Trapped Ion Mobility Imaging Mass Spectrometry

2020 ◽  
Author(s):  
Elizabeth Neumann ◽  
Lukasz Migas ◽  
Jamie L. Allen ◽  
Richard Caprioli ◽  
Raf Van de Plas ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility ◽  
Imaging Mass Spectrometry ◽  
Structural Complexity ◽  
Human Kidney ◽  
Resolving Power ◽  
Mobility Separation ◽  
Trapped Ion ◽  
Mobility Data ◽  
Ion Mobility Separation

<div> <div> <p>Small metabolites are essential for normal and diseased biological function but are difficult to study because of their inherent structural complexity. MALDI imaging mass spectrometry (IMS) of small metabolites is particularly challenging as MALDI matrix clusters are often isobaric with metabolite ions, requiring high resolving power instrumentation or derivatization to circumvent this issue. An alternative to this is to perform ion mobility separation before ion detection, enabling the visualization of metabolites without the interference of matrix ions. Here, we use MALDI timsTOF IMS to image small metabolites at high spatial resolution within the human kidney. Through this, we have found metabolites, such as arginic acid, acetylcarnitine, and choline that localize to the cortex, medulla, and renal pelvis, respectively. We have also demonstrated that trapped ion mobility spectrometry (TIMS) can resolve matrix peaks from metabolite signal and separate both isobaric and isomeric metabolites with different localizations within the kidney. The added ion mobility data dimension dramatically increased the peak capacity for molecular imaging experiments. Future work will involve further exploring the small metabolite profiles of human kidneys as a function of age, gender, and ethnicity.</p></div></div>

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