Railway Operations Models

2018 ◽  
pp. 745-767
Author(s):  
Sundaravalli Narayanaswami
Keyword(s):  
Prior Knowledge ◽  
Conceptual Understanding ◽  
Real World ◽  
Analytical Approach ◽  
Model Development ◽  
Transportation Industry ◽  
Railway Transportation ◽  
Academic Context ◽  
Railway Operations ◽  
Transportation Scheduling

This chapter is intended as an exposure to OR based methods, particularly the analytical approach to modelling railway operations. An overview of several planned operations in railway transportation is provided in an academic context. Some of the applications and the associated models are applied in realistic settings in the transportation industry, and also have demonstrated evidence of acceptance over a long number of years. Primary coverage is on transportation scheduling and the concise discussions are on planning phases, various operations that can be deterministically modeled and analysed, model development, few exercises and real-world stories, wherever appropriate. All sections are adequately provided with the list of references and an interested reader can benefit from a conceptual understanding to model development and to implement and deploy, under some prior knowledge on the basics and programming experience.

Railway Operations Models

2016 ◽  
pp. 313-334
Author(s):  
Sundaravalli Narayanaswami
Keyword(s):  
Prior Knowledge ◽  
Conceptual Understanding ◽  
Real World ◽  
Analytical Approach ◽  
Model Development ◽  
Transportation Industry ◽  
Railway Transportation ◽  
Academic Context ◽  
Railway Operations ◽  
Transportation Scheduling

This chapter is intended as an exposure to OR based methods, particularly the analytical approach to modelling railway operations. An overview of several planned operations in railway transportation is provided in an academic context. Some of the applications and the associated models are applied in realistic settings in the transportation industry, and also have demonstrated evidence of acceptance over a long number of years. Primary coverage is on transportation scheduling and the concise discussions are on planning phases, various operations that can be deterministically modeled and analysed, model development, few exercises and real-world stories, wherever appropriate. All sections are adequately provided with the list of references and an interested reader can benefit from a conceptual understanding to model development and to implement and deploy, under some prior knowledge on the basics and programming experience.

scholarly journals Modelling instruction effect with different reasoning ability on physics conceptual understanding by controlling the prior knowledge

2020 ◽  
pp. 73-84
Author(s):  
Ike Lusi Meilina ◽  
Supriyono Koes Handayanto ◽  
Muhardjito Muhardjito
Keyword(s):  
Prior Knowledge ◽  
Conceptual Understanding ◽  
Scientific Reasoning ◽  
Model Development ◽  
Learning Model ◽  
Reasoning Ability ◽  
Knowledge Test ◽  
Ability Test ◽  
Reasoning Abilities ◽  
Significant Difference

Modelling instruction is systematic instructional activity for constructing and applying scientific knowledge in Physics lesson. The purpose of this research is to determine the effect of Modelling instruction with different reasoning abilities on understanding physical concepts by controlling students’ prior knowledge. This research used experimental method with 2x2 factorial design with two Modelling instruction classes and two conventional classes with a total of 176 students. The instrument used was reasoning ability test, prior knowledge test, and physics concept test. It used LCTSR (Lawson’s Classroom Test of Scientific Reasoning) instrument. Prior knowledge test instruments consisted of 25 problems to identify how deep the students understand the topic before they undergo the learning process and physics concept test consisted of 25 problems. Based on the statistical test using two factor Ancova, it proved that there was a significant difference in students’ ability to master the physics concept between using Modelling instruction learning model and using conventional learning model. The result showed that the Modelling instruction increasing conceptual understanding better than conventional learning. There are two important parts in the Modelling instruction that are model development and model deployment. This study also confirms that there are significant differences in understanding the concepts between students of high reasoning ability and low reasoning ability. Students with high reasoning abilities have a better understanding of concepts than students with low reasoning abilities.

scholarly journals Conceptualising changes to tobacco and alcohol policy as affecting a single interlinked system

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Duncan Gillespie ◽  
Jenny Hatchard ◽  
Hazel Squires ◽  
Anna Gilmore ◽  
Alan Brennan
Keyword(s):  
Health Economic ◽  
Policy Change ◽  
Conceptual Understanding ◽  
Communicable Disease ◽  
Model Development ◽  
Economic Models ◽  
Alcohol Policy ◽  
Policy System ◽  
The People ◽  
Main Components

Abstract Background To support a move towards a coordinated non-communicable disease approach in public health policy, it is important to conceptualise changes to policy on tobacco and alcohol as affecting a single interlinked system. For health economic models to effectively inform policy, the first step in their development should be to develop a conceptual understanding of the system complexity that is likely to affect the outcomes of policy change. Our aim in this study was to support the development and interpretation of health economic models of the effects of changes to tobacco and alcohol policies by developing a conceptual understanding of the main components and mechanisms in the system that links policy change to outcomes. Methods Our study was based on a workshop from which we captured data on participant discussions on the joint tobacco–alcohol policy system. To inform these discussions, we prepared with a literature review and a survey of participants. Participants were academics and policy professionals who work in the United Kingdom. Data were analysed thematically to produce a description of the main components and mechanisms within the system. Results Of the people invited, 24 completed the survey (18 academic, 6 policy); 21 attended the workshop (16 academic, 5 policy). Our analysis identified eleven mechanisms through which individuals might modify the effects of a policy change, which include mechanisms that might lead to linked effects of policy change on tobacco and alcohol consumption. We identified ten mechanisms by which the tobacco and alcohol industries might modify the effects of policy changes, grouped into two categories: Reducing policy effectiveness; Enacting counter-measures. Finally, we identified eighteen research questions that indicate potential avenues for further work to understand the potential outcomes of policy change. Conclusions Model development should carefully consider the ways in which individuals and the tobacco and alcohol industries might modify the effects of policy change, and the extent to which this results in an unequal societal distribution of outcomes. Modelled evidence should then be interpreted in the light of the conceptual understanding of the system that the modelling necessarily simplifies in order to predict the outcomes of policy change.

scholarly journals Improving speed of models for improved real-world decision-making

2021 ◽  
Author(s):  
Jason Thompson ◽  
Haifeng Zhao ◽  
Sachith Seneviratne ◽  
Rohan Byrne ◽  
Rajith Vidanaarachichi ◽  
...  
Keyword(s):  
High Performance Computing ◽  
Real World ◽  
High Performance ◽  
Time Pressure ◽  
Practical Importance ◽  
Model Development ◽  
Sudden Onset ◽  
Health Crisis ◽  
Performance Improvements ◽  
Performance Computing

The sudden onset of the COVID-19 global health crisis and as-sociated economic and social fall-out has highlighted the im-portance of speed in modeling emergency scenarios so that ro-bust, reliable evidence can be placed in policy and decision-makers’ hands as swiftly as possible. For computational social scientists who are building complex policy models but who lack ready access to high-performance computing facilities, such time-pressure can hinder effective engagement. Popular and ac-cessible agent-based modeling platforms such as NetLogo can be fast to develop, but slow to run when exploring broad param-eter spaces on individual workstations. However, while deploy-ment on high-performance computing (HPC) clusters can achieve marked performance improvements, transferring models from workstations to HPC clusters can also be a technically challenging and time-consuming task. In this paper we present a set of generic templates that can be used and adapted by NetLogo users who have access to HPC clusters but require ad-ditional support for deploying their models on such infrastruc-ture. We show that model run-time speed improvements of be-tween 200x and 400x over desktop machines are possible using 1) a benchmark ‘wolf-sheep predation’ model in addition to 2) an example drawn from our own work modeling the spread of COVID-19 in Victoria, Australia. We describe how a focus on improving model speed is non-trivial for model development and discuss its practical importance for improved policy and de-cision-making in the real world. We provide all associated doc-umentation in a linked git repository.

scholarly journals Skateboarding as a tool for reading the city

2019 ◽  
Author(s):  
Polina Yu. Krutskikh
Keyword(s):  
Urban Youth ◽  
Analytical Approach ◽  
Youth Sports ◽  
Urban Infrastructure ◽  
Complex Nature ◽  
Academic Context ◽  
The Common ◽  
The City

Modern urban youth sports cultures are notable for their diverse and complex nature. The question arises as to what analytical approach should be used to study their multifaceted character. Using the St Petersburg skateboard scene as an example, the article shows the advantages in applying the concept of the post-sport cultures to understand how the common functions of urban infrastructure are redefined, what trends exist on the scene, how they shape the meanings attributed to them by the scene participants, and how those signs are read.  The study also employs the solidarity approach to describe the interactions between the scene participants through the ideas and ideological controversies shared by them. The focus of the paper is how to apply solidarity approach to study the nature of urban post-sport cultures based on St Petersburg skateboard scene case study. Given the lack of Russian publications on the topic, the study is also aimed at inscribing the Russian skateboarding experience into the Western academic context.

On the Identification of Modeler Communities

2014 ◽  
Vol 5 (2) ◽  
pp. 22-40 ◽  
Author(s):  
Dirk van der Linden ◽  
Stijn J.B.A. Hoppenbrouwers ◽  
Henderik A. Proper
Keyword(s):  
Conceptual Understanding ◽  
Real World ◽  
Empirical Support ◽  
Enterprise Modeling ◽  
Modeling Language ◽  
Science Students ◽  
Modeling Process ◽  
Psychometric Data ◽  
Computing Science ◽  
Insight Into

The authors discuss the use and challenges of identifying communities with shared semantics in Enterprise Modeling (EM). People tend to understand modeling meta-concepts (i.e., a modeling language's constructs or types) in a certain way and can be grouped by this conceptual understanding. Having an insight into the typical communities and their composition (e.g., what kind of people constitute such a semantic community) can make it easier to predict how a conceptual modeler with a certain background will generally understand the meta-concepts s/he uses, which is useful for e.g., validating model semantics and improving the efficiency of the modeling process itself. The authors have observed that in practice decisions to group people based on certain shared properties are often made, but are rarely backed up by empirical data demonstrating their supposed efficacy. The authors demonstrate the use of psychometric data from two studies involving experienced (enterprise) modeling practitioners and computing science students to find such communities. The authors also discuss the challenge that arises in finding common real-world factors shared between their members to identify them by and conclude that there is no empirical support for commonly used (and often implicit) grouping properties such as similar background, focus and modeling language.

scholarly journals Development of a composite friction modifier with carbon nanotubes for applications at the wheel–rail interface

2020 ◽  
Vol 29 ◽  
pp. 2633366X2093001
Author(s):  
Juan Camilo Vélez ◽  
Jesús Antonio Carlos Cornelio ◽  
Robinson Buitrago Sierra ◽  
Juan Felipe Santa ◽  
Lina Marcela Hoyos-Palacio ◽  
...  
Keyword(s):  
Carbon Nanotubes ◽  
Traction Force ◽  
Solid Lubricants ◽  
Total Solid ◽  
Transportation Industry ◽  
Railway Transportation ◽  
Friction Modifier ◽  
Total Mass Loss ◽  
Efficient Alternative ◽  
Cost Efficient

Wear of wheels and rails is a major problem in railway transportation industry. Solid lubricants constitute a cost-efficient alternative to control wear and friction at the wheel–rail interface, especially when a fine-tuned balance between traction force and energy consumption is sought. In this work, composite friction modifiers (CFMs) composed of a vinyl ester matrix reinforced with molybdenum disulfide and carbon nanotubes were developed. The total solid additive content was less than a half in comparison with a commercial product available on the market, which was used as a reference. A benchmarking study of the CFM was carried out by means of tribological tests in a twin-disc machine at a contact pressure of 1.1 GPa and different slip values. The results indicated that the developed CFM reduce coefficient of traction by 10% compared to unlubricated conditions that is similar to the reference. However, the total mass loss of steel components due to wear under CFM lubrication was lower than in the reference test.

Model My Watershed: Connecting Students' Conceptual Understanding of Watersheds to Real-World Decision Making

2014 ◽  
Vol 62 (1) ◽  
pp. 61-73 ◽  
Author(s):  
Susan E. Gill ◽  
Nanette Marcum-Dietrich ◽  
Rachel Becker-Klein
Keyword(s):  
Decision Making ◽  
Conceptual Understanding ◽  
Real World

scholarly journals Linear Bandits with Feature Feedback

2020 ◽  
Vol 34 (04) ◽  
pp. 5331-5338
Author(s):  
Urvashi Oswal ◽  
Aniruddha Bhargava ◽  
Robert Nowak
Keyword(s):  
Computational Complexity ◽  
Prior Knowledge ◽  
Real World ◽  
Time Horizon ◽  
The Novel ◽  
Bandit Problem ◽  
Real World Applications ◽  
New Form ◽  
Feature Feedback ◽  
Over Time

This paper explores a new form of the linear bandit problem in which the algorithm receives the usual stochastic rewards as well as stochastic feedback about which features are relevant to the rewards, the latter feedback being the novel aspect. The focus of this paper is the development of new theory and algorithms for linear bandits with feature feedback which can achieve regret over time horizon T that scales like k√T, without prior knowledge of which features are relevant nor the number k of relevant features. In comparison, the regret of traditional linear bandits is d√T, where d is the total number of (relevant and irrelevant) features, so the improvement can be dramatic if k ≪ d. The computational complexity of the algorithm is proportional to k rather than d, making it much more suitable for real-world applications compared to traditional linear bandits. We demonstrate the performance of the algorithm with synthetic and real human-labeled data.

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