scholarly journals New Analytic Solutions of Queueing System for Shared–Short Lanes at Unsignalized Intersections

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 55 ◽  
Author(s):  
Ilija Tanackov ◽  
Darko Dragić ◽  
Siniša Sremac ◽  
Vuk Bogdanović ◽  
Bojan Matić ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Queueing System ◽  
Analytic Solutions ◽  
Service Discipline ◽  
Second Phase ◽  
Single Server ◽  
Two Phase ◽  
Left Turn ◽  
Unsignalized Intersections ◽  
High Level

Designing the crossroads capacity is a prerequisite for achieving a high level of service with the same sustainability in stochastic traffic flow. Also, modeling of crossroad capacity can influence on balancing (symmetry) of traffic flow. Loss of priority in a left turn and optimal dimensioning of shared-short line is one of the permanent problems at intersections. A shared–short lane for taking a left turn from a priority direction at unsignalized intersections with a homogenous traffic flow and heterogeneous demands is a two-phase queueing system requiring a first in–first out (FIFO) service discipline and single-server service facility. The first phase (short lane) of the system is the queueing system M(pλ)/M(μ)/1/∞, whereas the second phase (shared lane) is a system with a binomial distribution service. In this research, we explicitly derive the probability of the state of a queueing system with a short lane of a finite capacity for taking a left turn and shared lane of infinite capacity. The presented formulas are under the presumption that the system is Markovian, i.e., the vehicle arrivals in both the minor and major streams are distributed according to the Poisson law, and that the service of the vehicles is exponentially distributed. Complex recursive operations in the two-phase queueing system are explained and solved in manuscript.

scholarly journals P PEMODELAN ARUS LALU LINTAS DAN WAKTU TUNGGU TOTAL OPTIMAL DI PERSIMPANGAN JL. JEMUR ANDAYANI – AHMAD YANI SEBAGAI UPAYA MENGURAI KEMACETAN

2020 ◽  
Vol 14 (3) ◽  
pp. 389-398
Author(s):  
Yuniar Farida ◽  
Aris Fanani ◽  
Ida Purwanti ◽  
Luluk Wulandari ◽  
Nanida Jenahara Zaen
Keyword(s):  
Traffic Flow ◽  
Waiting Time ◽  
Traffic Management ◽  
Traffic Flows ◽  
Left Turn ◽  
Traffic Performance ◽  
Time Calculation ◽  
High Level ◽  
Signal Time

One crossroad of ​​Surabaya whose high level of congestion is the crossing of Jemur Andayani – Ahmad Yani Street. It needs to Improve traffic management, geometric, and signal time to obtain optimal traffic performance. The purpose of this study is to make a model of traffic flow and determine the optimal total waiting time at the crossing of Jemur Andayani – Ahmad Yani using Compatible Graph. Compatible graphs are two sets where vertices indicate objects to be arranged and edges indicate compatible pairs of objects. Compatible traffic flow is two traffic flows which if both of them run simultaneously can run safely and not collide. The results of the optimal waiting time calculation using a compatible graph assuming the left turn following the lamp is 75 seconds. While the optimal total waiting time by assuming the left turn not following the lights is 60 seconds. The optimal total waiting time is smaller than the actual total waiting time currently applied at Frontage Ahmad Yani street, which is 170 seconds by assuming turn left following the lights.

scholarly journals Detection and Grading of Gliomas Using a Novel Two-Phase Machine Learning Method Based on MRI Images

2021 ◽  
Vol 15 ◽  
Author(s):  
Tao Chen ◽  
Feng Xiao ◽  
Zunpeng Yu ◽  
Mengxue Yuan ◽  
Haibo Xu ◽  
...  
Keyword(s):  
Treatment Decision ◽  
Local Feature ◽  
Second Phase ◽  
Low Grade ◽  
Imaging Data ◽  
Two Phase ◽  
Membership Probability ◽  
Classification Framework ◽  
Gradient Based ◽  
High Level

The early detection and grading of gliomas is important for treatment decision and assessment of prognosis. Over the last decade numerous automated computer analysis tools have been proposed, which can potentially lead to more reliable and reproducible brain tumor diagnostic procedures. In this paper, we used the gradient-based features extracted from structural magnetic resonance imaging (sMRI) images to depict the subtle changes within brains of patients with gliomas. Based on the gradient features, we proposed a novel two-phase classification framework for detection and grading of gliomas. In the first phase, the probability of each local feature being related to different types (e.g., diseased or healthy for detection, benign or malignant for grading) was calculated. Then the high-level feature representing the whole MRI image was generated by concatenating the membership probability of each local feature. In the second phase, the supervised classification algorithm was used to train a classifier based on the high-level features and patient labels of the training subjects. We applied this framework on the brain imaging data collected from Zhongnan Hospital of Wuhan University for glioma detection, and the public TCIA datasets including glioblastomas (WHO IV) and low-grade gliomas (WHO II and III) data for glioma grading. The experimental results showed that the gradient-based classification framework could be a promising tool for automatic diagnosis of brain tumors.

Two-Phase Bounded-Acceleration Traffic Flow Model: Analytical Solutions and Applications

2003 ◽  
Vol 1852 (1) ◽  
pp. 220-230 ◽  
Author(s):  
J. P. Lebacque
Keyword(s):  
Traffic Flow ◽  
Analytical Solutions ◽  
Flow Model ◽  
Second Phase ◽  
Traffic Equilibrium ◽  
Two Phase ◽  
Traffic Flow Model ◽  
Flow Models ◽  
First Order ◽  
Traffic Flow Models

A two-phase traffic flow model is described. One phase is traffic equilibrium: flow and speed are functions of density, and traffic acceleration is low. The second phase is characterized by constant acceleration. This model extends first-order traffic flow models and recaptures the fact that traffic acceleration is bounded. Calculation of analytical solutions of the two-phase model for dynamic traffic situations is shown, a set of calculation rules is provided, and some examples are analyzed.

A Comparison of Tem and Apfim to the Interpretation of Modulated Microstructures

1985 ◽  
Vol 43 ◽  
pp. 70-71
Author(s):  
M.G. Burke ◽  
M.K. Miller
Keyword(s):  
Low Temperature ◽  
Microstructural Characterization ◽  
Superlattice Reflection ◽  
High Volume ◽  
Atom Probe ◽  
Dark Field ◽  
Miscibility Gap ◽  
Second Phase ◽  
Two Phase ◽  
Probe Field

Interpretation of fine-scale microstructures containing high volume fractions of second phase is complex. In particular, microstructures developed through decomposition within low temperature miscibility gaps may be extremely fine. This paper compares the morphological interpretations of such complex microstructures by the high-resolution techniques of TEM and atom probe field-ion microscopy (APFIM).The Fe-25 at% Be alloy selected for this study was aged within the low temperature miscibility gap to form a <100> aligned two-phase microstructure. This triaxially modulated microstructure is composed of an Fe-rich ferrite phase and a B2-ordered Be-enriched phase. The microstructural characterization through conventional bright-field TEM is inadequate because of the many contributions to image contrast. The ordering reaction which accompanies spinodal decomposition in this alloy permits simplification of the image by the use of the centered dark field technique to image just one phase. A CDF image formed with a B2 superlattice reflection is shown in fig. 1. In this CDF micrograph, the the B2-ordered Be-enriched phase appears as bright regions in the darkly-imaging ferrite. By examining the specimen in a [001] orientation, the <100> nature of the modulations is evident.

THE DYNAMIC FRACTURE OF TWO PHASE ALLOYS WITH SECOND PHASE INCLUSIONS

1985 ◽  
Vol 46 (C5) ◽  
pp. C5-251-C5-255
Author(s):  
S. Pytel ◽  
L. Wojnar
Keyword(s):  
Dynamic Fracture ◽  
Second Phase ◽  
Two Phase

Behaviour of air injection nozzles in dissolved air flotation

1995 ◽  
Vol 31 (3-4) ◽  
pp. 25-35 ◽  
Author(s):  
E. M. Rykaart ◽  
J. Haarhoff
Keyword(s):  
Bubble Coalescence ◽  
Second Phase ◽  
Initial Growth ◽  
Two Phase ◽  
Dissolved Air Flotation ◽  
Nozzle Orifice ◽  
Pressure Release ◽  
Air Volume ◽  
Air Flotation ◽  
Dissolved Air

A simple two-phase conceptual model is postulated to explain the initial growth of microbubbles after pressure release in dissolved air flotation. During the first phase bubbles merely expand from existing nucleation centres as air precipitates from solution, without bubble coalescence. This phase ends when all excess air is transferred to the gas phase. During the second phase, the total air volume remains the same, but bubbles continue to grow due to bubble coalescence. This model is used to explain the results from experiments where three different nozzle variations were tested, namely a nozzle with an impinging surface immediately outside the nozzle orifice, a nozzle with a bend in the nozzle channel, and a nozzle with a tapering outlet immediately outside the nozzle orifice. From these experiments, it is inferred that the first phase of bubble growth is completed at approximately 1.7 ms after the start of pressure release.

scholarly journals A novel two-phase cycle algorithm for effective cyber intrusion detection in edge computing

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yiguang Gong ◽  
Yunping Liu ◽  
Chuanyang Yin
Keyword(s):  
Intrusion Detection ◽  
Optimal Parameter ◽  
Edge Computing ◽  
Cloud Services ◽  
Second Phase ◽  
Pareto Optimal ◽  
Two Phase ◽  
Multi Objective ◽  
Phase Cycle ◽  
Positive Rate

AbstractEdge computing extends traditional cloud services to the edge of the network, closer to users, and is suitable for network services with low latency requirements. With the rise of edge computing, its security issues have also received increasing attention. In this paper, a novel two-phase cycle algorithm is proposed for effective cyber intrusion detection in edge computing based on a multi-objective genetic algorithm (MOGA) and modified back-propagation neural network (MBPNN), namely TPC-MOGA-MBPNN. In the first phase, the MOGA is employed to build a multi-objective optimization model that tries to find the Pareto optimal parameter set for MBPNN. The Pareto optimal parameter set is applied for simultaneous minimization of the average false positive rate (Avg FPR), mean squared error (MSE) and negative average true positive rate (Avg TPR) in the dataset. In the second phase, some MBPNNs are created based on the parameter set obtained by MOGA and are trained to search for a more optimal parameter set locally. The parameter set obtained in the second phase is used as the input of the first phase, and the training process is repeated until the termination criteria are reached. A benchmark dataset, KDD cup 1999, is used to demonstrate and validate the performance of the proposed approach for intrusion detection. The proposed approach can discover a pool of MBPNN-based solutions. Combining these MBPNN solutions can significantly improve detection performance, and a GA is used to find the optimal MBPNN combination. The results show that the proposed approach achieves an accuracy of 98.81% and a detection rate of 98.23% and outperform most systems of previous works found in the literature. In addition, the proposed approach is a generalized classification approach that is applicable to the problem of any field having multiple conflicting objectives.

scholarly journals Three-Dimensional Analysis of the In Vivo Motion of Implantable Cardioverter Defibrillator Leads

2021 ◽  
Author(s):  
Tamas Szili-Torok ◽  
Jens Rump ◽  
Torsten Luther ◽  
Sing-Chien Yap
Keyword(s):  
Three Dimensional ◽  
Second Phase ◽  
Two Phase ◽  
Maximum Curvature ◽  
Phase Study ◽  
Absolute Curvature ◽  
Icd Leads ◽  
Lead Testing ◽  
Design And Testing

Abstract Better understanding of the lead curvature, movement and their spatial distribution may be beneficial in developing lead testing methods, guiding implantations and improving life expectancy of implanted leads. Objective The aim of this two-phase study was to develop and test a novel biplane cine-fluoroscopy-based method to evaluate input parameters for bending stress in leads based on their in vivo 3D motion using precisely determined spatial distributions of lead curvatures. Potential tensile, compressive or torque forces were not subjects of this study. Methods A method to measure lead curvature and curvature evolution was initially tested in a phantom study. In the second phase using this model 51 patients with implanted ICD leads were included. A biplane cine-fluoroscopy recording of the intracardiac region of the lead was performed. The lead centerline and its motion were reconstructed in 3D and used to define lead curvature and curvature changes. The maximum absolute curvature Cmax during a cardiac cycle, the maximum curvature amplitude Camp and the maximum curvature Cmax@amp at the location of Camp were calculated. These parameters can be used to characterize fatigue stress in a lead under cyclical bending. Results The medians of Camp and Cmax@amp were 0.18 cm−1 and 0.42 cm−1, respectively. The median location of Cmax was in the atrium whereas the median location of Camp occurred close to where the transit through the tricuspid valve can be assumed. Increased curvatures were found for higher slack grades. Conclusion Our results suggest that reconstruction of 3D ICD lead motion is feasible using biplane cine-fluoroscopy. Lead curvatures can be computed with high accuracy and the results can be implemented to improve lead design and testing.

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