scholarly journals Probabilistic Traffic Flow Breakdown in Stochastic Car-Following Models

2003 ◽  
Vol 1852 (1) ◽  
pp. 152-158 ◽  
Author(s):  
Dominic Jost ◽  
Kai Nagel

Whether traffic displays multiple phases (e.g., laminar, jammed, synchronized) has been much discussed. Computational evidence is presented that a stochastic car-following model can be moved from two phases (laminar and jammed) to one phase by changing one of its parameters. Models with two phases show three states. Two of them are homogeneous and correspond to the two phases. The third state consists of a mix of the two phases (phase coexistence). Although the gas–liquid analogy to traffic models has been widely discussed, no traffic-related model ever displayed a completely understood stochastic version of that transition. A stochastic model is important to the understanding of the potentially probabilistic nature of the transition. If indeed two-phase models describe certain aspects correctly, predictions for breakdown probabilities can be made. Alternatively, if one-phase models describe these aspects better, there is no breakdown. Interestingly, such one-phase models can still allow for jam formation on a small scale, which may give the impression of two-phase dynamics.

2020 ◽  
Vol 3 (4) ◽  
pp. 142-152
Author(s):  
Mohammad Waliul Hasanat ◽  
Kamna Anum ◽  
Ashikul Hoque ◽  
Mahmud Hamid ◽  
Sandy Francis Peris ◽  
...  

In developing countries, the role of women in the business sector is continuously improving. As a result, female enterprises have also been encouraged in Pakistan. This study is based on life cycle development phases from which women-owned enterprises have to go through in order to become successful. As a primary data source, face-to-face interviews with owners of successful women-owned enterprises were preferred. The data collection process was divided into two phases i.e. Phase-I and Phase-II. After data collection, qualitative analysis has been performed using NVIVO. Findings provide both generic and specific factors involved in life cycle development of women-owned enterprises. This study provides a detailed view of life cycle development model followed by successful women enterprises. The outcome of this research work is a theoretical finding which can be utilized by entrepreneurs owning small scale enterprises to improve their level of performance. Findings can also be helpful for potentially talented women interested in setting up their own business.


2021 ◽  
Vol 43 (1) ◽  
pp. 1-73
Author(s):  
David J. Pearce

Rust is a relatively new programming language that has gained significant traction since its v1.0 release in 2015. Rust aims to be a systems language that competes with C/C++. A claimed advantage of Rust is a strong focus on memory safety without garbage collection. This is primarily achieved through two concepts, namely, reference lifetimes and borrowing . Both of these are well-known ideas stemming from the literature on region-based memory management and linearity / uniqueness . Rust brings both of these ideas together to form a coherent programming model. Furthermore, Rust has a strong focus on stack-allocated data and, like C/C++ but unlike Java, permits references to local variables. Type checking in Rust can be viewed as a two-phase process: First, a traditional type checker operates in a flow-insensitive fashion; second, a borrow checker enforces an ownership invariant using a flow-sensitive analysis. In this article, we present a lightweight formalism that captures these two phases using a flow-sensitive type system that enforces “ type and borrow safety .” In particular, programs that are type and borrow safe will not attempt to dereference dangling pointers. Our calculus core captures many aspects of Rust, including copy- and move-semantics, mutable borrowing, reborrowing, partial moves, and lifetimes. In particular, it remains sufficiently lightweight to be easily digested and understood and, we argue, still captures the salient aspects of reference lifetimes and borrowing. Furthermore, extensions to the core can easily add more complex features (e.g., control-flow, tuples, method invocation). We provide a soundness proof to verify our key claims of the calculus. We also provide a reference implementation in Java with which we have model checked our calculus using over 500B input programs. We have also fuzz tested the Rust compiler using our calculus against 2B programs and, to date, found one confirmed compiler bug and several other possible issues.


Author(s):  
Vishu Madaan ◽  
Aditya Roy ◽  
Charu Gupta ◽  
Prateek Agrawal ◽  
Anand Sharma ◽  
...  

AbstractCOVID-19 (also known as SARS-COV-2) pandemic has spread in the entire world. It is a contagious disease that easily spreads from one person in direct contact to another, classified by experts in five categories: asymptomatic, mild, moderate, severe, and critical. Already more than 66 million people got infected worldwide with more than 22 million active patients as of 5 December 2020 and the rate is accelerating. More than 1.5 million patients (approximately 2.5% of total reported cases) across the world lost their life. In many places, the COVID-19 detection takes place through reverse transcription polymerase chain reaction (RT-PCR) tests which may take longer than 48 h. This is one major reason of its severity and rapid spread. We propose in this paper a two-phase X-ray image classification called XCOVNet for early COVID-19 detection using convolutional neural Networks model. XCOVNet detects COVID-19 infections in chest X-ray patient images in two phases. The first phase pre-processes a dataset of 392 chest X-ray images of which half are COVID-19 positive and half are negative. The second phase trains and tunes the neural network model to achieve a 98.44% accuracy in patient classification.


IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Mingfei Mu ◽  
Junjie Zhang ◽  
Changmiao Wang ◽  
Jun Zhang ◽  
Can Yang

Author(s):  
Marzia S Vaccaro ◽  
Francesco P Pinnola ◽  
Francesco Marotti de Sciarra ◽  
Marko Canadija ◽  
Raffaele Barretta

In this research, the size-dependent static behaviour of elastic curved stubby beams is investigated by Timoshenko kinematics. Stress-driven two-phase integral elasticity is adopted to model size effects which soften or stiffen classical local responses. The corresponding governing equations of nonlocal elasticity are established and discussed, non-classical boundary conditions are detected and an effective coordinate-free solution procedure is proposed. The presented mixture approach is elucidated by solving simple curved small-scale beams of current interest in Nanotechnology. The contributed results could be useful for design and optimization of modern sensors and actuators.


2007 ◽  
Vol 129 (11) ◽  
pp. 1415-1421 ◽  
Author(s):  
Joseph Borowsky ◽  
Timothy Wei

An experimental investigation of a two-phase pipe flow was undertaken to study kinematic and dynamic parameters of the fluid and solid phases. To accomplish this, a two-color digital particle image velocimetry and accelerometry (DPIV∕DPIA) methodology was used to measure velocity and acceleration fields of the fluid phase and solid phase simultaneously. The simultaneous, two-color DPIV∕DPIA measurements provided information on the changing characteristics of two-phase flow kinematic and dynamic quantities. Analysis of kinematic terms indicated that turbulence was suppressed due to the presence of the solid phase. Dynamic considerations focused on the second and third central moments of temporal acceleration for both phases. For the condition studied, the distribution across the tube of the second central moment of acceleration indicated a higher value for the solid phase than the fluid phase; both phases had increased values near the wall. The third central moment statistic of acceleration showed a variation between the two phases with the fluid phase having an oscillatory-type profile across the tube and the solid phase having a fairly flat profile. The differences in second and third central moment profiles between the two phases are attributed to the inertia of each particle type and its response to turbulence structures. Analysis of acceleration statistics provides another approach to characterize flow fields and gives some insight into the flow structures, even for steady flows.


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