Evaluating Factors Affecting Safety at Highway–Railway Grade Crossings

2005 ◽  
Vol 1918 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Young-Jin Park ◽  
Frank F. Saccomanno
Keyword(s):  
Statistical Models ◽  
Statistical Significance ◽  
Cost Effective ◽  
Interactive Effects ◽  
Factors Affecting ◽  
Explanatory Variables ◽  
Grade Crossings ◽  
Complex Relationships ◽  
Four Quadrant ◽  
The Cost

Various countermeasures can be introduced to reduce collisions at highway–railway grade crossings. Existing improvements to crossings include the installation of flashing lights or gates, the addition of extra warning devices such as four-quadrant barriers or wayside horns, and the enforcement of speed limits on the approaching highway. Statistical models are needed to ensure that countermeasures introduced at a given crossing are both cost-effective and practicable. However, in large part because of issues of colinearity, poor statistical significance, and parametric bias, many existing statistical models are simple in structure and feature few statistically significant explanatory variables. Accordingly, they fail to reflect the full gamut of factor inputs that explain variation in collision frequency at individual crossings over a given period of time. Before statistical models can be used to investigate the cost-effectiveness of specific countermeasures, models must be developed that more fully reflect the complex relationships that link a specific countermeasure to collision occurrence. This study presents a sequential modeling approach based on data mining and statistical methods to estimate the main and interactive effects of introducing countermeasures at individual grade crossings. This paper makes use of Canadian inventory and collision data to illustrate the potential merits of the model in decision support.

A Model for Evaluating Countermeasures at Highway–Railway Grade Crossings

2005 ◽  
Vol 1918 (1) ◽  
pp. 18-25 ◽  
Author(s):  
Frank F. Saccomanno ◽  
Xiaoming Lai
Keyword(s):  
Prediction Model ◽  
Prediction Models ◽  
Statistical Significance ◽  
Cost Effective ◽  
Model Parameters ◽  
Full Spectrum ◽  
Factors Affecting ◽  
Collision Prediction ◽  
Grade Crossings ◽  
Input Variables

Current collision prediction models fail to account for the full spectrum of relevant factors affecting the number of collisions at specific highway– railway grade crossings. A number of reasons contribute to this failure, including biases in model parameters resulting from collinearity in the model inputs, absence of important variables in the prediction model caused by lack of statistical significance, the inability of models to consider higher-order interactions, and the presence of unexplained variation in the prediction estimates. These problems have compromised the use of collision prediction models in decisions concerning the development and evaluation of cost-effective safety treatments or countermeasures for application at specific crossings. This paper introduces a stratified collision prediction model for highway–railway grade crossings. The development of this model involves three steps: ( a) crossing inventory variables are expressed in terms of a limited number of orthogonal (nonlinear) underlying attributes or factors; ( b) factor scores are estimated for each crossing and factor, and these scores are used as “seed points” in a subsequent clustering exercise to yield groups or clusters of crossings with similar underlying attributes; and ( c) for each cluster, separate collision prediction models are developed and include important treatment input variables of interest to decision makers and planners. The paper describes an application of a stratified collision prediction model to Canadian highway–railway grade crossing inventory and collision occurrence data for the period 1993 to 2001. The usefulness of the model in estimating collision reduction benefits of selected treatments is illustrated with reference to two countermeasure strategies: upgrades in the type of warning device and the removal of whistle prohibition.

A structured model for evaluating countermeasures at highway–railway grade crossings

2005 ◽  
Vol 32 (4) ◽  
pp. 627-635 ◽  
Author(s):  
Young-Jin Park ◽  
Frank F Saccomanno
Keyword(s):  
Data Mining ◽  
Statistical Models ◽  
Decision Support Tool ◽  
Cost Effective ◽  
Expected Number ◽  
Structured Model ◽  
Support Tool ◽  
Data Mining Techniques ◽  
Use Of Data ◽  
Grade Crossings

Various countermeasures can be introduced to reduce collisions at highway–railway grade crossings. These countermeasures may take different forms, such as passive and (or) active driver warning devices, supplementary traffic controls (four quadrant barriers, wayside horn, closed circuit television (CCTV) monitoring, etc.), illumination, signage and highway speed limit, etc. In this research, we present a structured model that makes use of data mining techniques to estimate the effect of changes in countermeasures on the expected number of collisions at a given crossing. This model serves as a decision-support tool for the evaluation and development of cost-effective and practicable safety program at highway–railway grade crossings. The use of data mining techniques helps to resolve many of the problems associated with conventional statistical models used to predict the expected number of collisions for a given type of crossing. Statistical models introduce biases that limit their ability to fully represent the relationship between selected countermeasures and resultant collisions for a mix of crossing attributes. This paper makes use of Canadian inventory and collision data to illustrate the potential merits of the proposed model to provide decision support.Key words: highway–railway grade crossing, collision prediction model, countermeasures, Poisson regression.

Marginal analysis and cost effectiveness in seed orchard management

1987 ◽  
Vol 17 (6) ◽  
pp. 510-515 ◽  
Author(s):  
Thomas A. Thomson ◽  
Donald T. Lester ◽  
Jeanne A. Martin
Keyword(s):  
Seed Production ◽  
Analytical Techniques ◽  
Cost Effective ◽  
Seed Orchard ◽  
Induction Treatment ◽  
Marginal Analysis ◽  
Orchard Management ◽  
Improvement Programs ◽  
Four Quadrant ◽  
The Cost

We use marginal analysis for three seed orchard management decisions. First we consider the roguing of a seed orchard established with many untested trees. We show that inferior parents should be rogued to the point where the number of orchard trees times the average expected volume gain of trees from seed produced by that orchard is maximized. Marginal analysis also is useful where one must choose the number of trees to establish in an orchard planted after progeny tests have identified superior parents. The cost of establishing many ramets to meet early seed production goals can be balanced with the projected value of seed. For the example presented, an additional orchard tree is cost effective if its seed is needed at an orchard age of 12 to 15 years. Finally, we use marginal analysis to determine whether to induce a seed orchard to increase its seed production when there is an excess demand for seed. This decision is guided by balancing the cost of the induction treatment with the combined effect of expected increase in seed harvest, the amount of genetic gain, and the discount rate. We present a four-quadrant decision diagram for estimating this balance. In designing tree improvement programs, these analytical techniques can be applied to proposed alternatives as one way to structure decision making and to provide comparable economic assessments from which cost-effective choices can be made.

scholarly journals Profitable Decarbonization through E-Mobility

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4042
Author(s):  
Gürkan Kumbaroğlu ◽  
Cansu Canaz ◽  
Jonathan Deason ◽  
Ekundayo Shittu
Keyword(s):  
Power Generation ◽  
Co2 Emissions ◽  
Emission Reduction ◽  
Large Scale ◽  
Cost Effective ◽  
Electricity Sector ◽  
Complex Relationships ◽  
The Cost ◽  
Relationship Of ◽  
The Impact

This paper focuses on the interdependent relationship of power generation, transportation and CO2 emissions to evaluate the impact of electric vehicle deployment on power generation and CO2 emissions. The value of this evaluation is in the employment of a large-scale, bottom-up, national energy modeling system that encompasses the complex relationships of producing, transforming, transmitting and supplying energy to meet the useful demand characteristics with great technological detail. One of such models employed in this analysis is the BUEMS model. The BUEMS model provides evidence of win-win policy options that lead to profitable decarbonization using Turkey’s data in BUEMS. Specifically, the result shows that a ban on diesel fueled vehicles reduces lifetime emissions as well as lifetime costs. Furthermore, model results highlight the cost-effective emission reduction potential of e-buses in urban transportation. More insights from the results indicate that the marginal cost of emission reduction through e-bus transportation is much lower than that through other policy measures such as carbon taxation in transport. This paper highlights the crucial role the electricity sector plays in the sustainability of e-mobility and the value of related policy prescriptions.

Paint-Line Retroreflectivity over Time

1997 ◽  
Vol 1585 (1) ◽  
pp. 53-63 ◽  
Author(s):  
Michael Scheuer ◽  
Thomas L. Maleck ◽  
Dale R. Lighthizer
Keyword(s):  
Cost Effective ◽  
Michigan State University ◽  
State University ◽  
Department Of Transportation ◽  
Factors Affecting ◽  
Lane Marking ◽  
Lane Line ◽  
Effective Use ◽  
The Cost ◽  
Pavement Marking

The Michigan Department of Transportation contracted with Michigan State University to evaluate the performance of highway paint-line material. Several types of pavement-marking materials were studied under a variety of conditions. The project’s goal is to help develop guidelines governing the cost-effective use of pavement-marking materials. Preliminary results indicate that retroreflectivity levels of paint lines did not vary as a function of material; pavement surface had little effect on lane-marking performance; and snowplowing and sanding appeared to be the main factors affecting the decay of lane line retroreflectivity.

scholarly journals Verification and Optimization of an Ultra-Low Volume (ULV) Sprayer Used for the Inactivation of Indoor Total Bacteria

2021 ◽  
Vol 11 (8) ◽  
pp. 3713
Author(s):  
Yun-Hee Choi ◽  
Da-An Huh ◽  
Ju-Yeon Lee ◽  
Ji Yoon Choi ◽  
Kyong Whan Moon
Keyword(s):  
Cost Effective ◽  
Interactive Effects ◽  
Surface Model ◽  
Chemical Cleaning ◽  
Factors Affecting ◽  
Room Size ◽  
Low Volume ◽  
The Individual ◽  
Physical And Chemical ◽  
Total Bacteria

Physical and chemical cleaning for the removal of indoor microorganisms, which can cause allergic reactions and respiratory diseases, is labor-intensive and time-consuming. An ultra-low volume (ULV) sprayer, a newly introduced device to inactivate pathogenic microorganisms, allows the disinfectant particles to reach hard-to-reach spaces indoors and is more cost-effective than the existing methods. However, few studies have been conducted to verify the efficiency of the ULV sprayer. Here, we verified the disinfection efficiency of the ULV sprayer for inactivating total bacteria present on indoor surfaces, considering the factors affecting bacteria inactivation, and presented the optimal ULV sprayer usage conditions to achieve the highest disinfection efficiency depending on room size. The total bacteria removal efficiency was high (range: 0.56–2.46 log10 reductions), including hard-to-reach spaces. A response surface model was developed to identify the individual and interactive effects of the disinfectant concentration, spray amount, and room size on total bacteria disinfection efficiency. These three variables had interactive effects on the total bacteria disinfection efficiency. The experimental data were fitted to a second-order polynomial model, with high coefficients of determination (R2) for all models (R2 > 0.82). The optimum conditions were a spray amount of 3.08–6.40 L in 160 m3, 3.78–7.22 L in 230 m3, and 5.68–8 L in 300 m3 surface area when using dilution rates of 100 times. These conditions predicted a bacterial disinfection efficiency of >1.10 log10 reductions (92%) on all surfaces. Our results clearly indicate that the ULV sprayer effectively inactivates total bacteria present on indoor surfaces.

scholarly journals The analysis of factors affecting price of selected commodities

2021 ◽  
Vol 129 ◽  
pp. 03001
Author(s):  
Vladimíra Adamkovičová ◽  
Michal Gimerský
Keyword(s):  
Exchange Rate ◽  
Negative Impact ◽  
Investment Decision ◽  
Statistical Significance ◽  
Precious Metals ◽  
Value Added ◽  
Dollar Exchange Rate ◽  
Factors Affecting ◽  
Price Development ◽  
Explanatory Variables

Research background: Commodities are attractive investment opportunities and are objects of many researches. Traditional and most stable seem to be precious metals gold and silver. In the global world where anyone can access information in seconds it is crucial to know the background of price development in order to make the right investment decision. Purpose of the article: This paper focuses on international commodity exchanges and analyzes factors affecting prices of selected commodities. It offers a summary of recent studies and continues with an analysis of most relevant factors affecting price of gold and silver. Methods: After collecting data and testing their consistency we construct two hypothesis models. Using linear regression model we test the appropriateness of models which are constructed for each commodity. Subsequently, we test statistical significance of individual explanatory variables, such as dollar exchange rate, VIX, CPI, DJIA, DAX or oil price. Additionally, we take into consideration not traditional factors e.g. Bitcoin. Findings & Value added: Finally an evaluation of results are carried out and the influence of variables are quantified. For instance, negative impact of VIX and dollar exchange rate in observed period of time was confirmed. Given the fact that there can be various other factors influencing price development of gold and silver this paper serves as basis for further analysis in this direction.

The IBM-PC in electron microscopy

1996 ◽  
Vol 54 ◽  
pp. 612-613
Author(s):  
James F. Mancuso
Keyword(s):  
Head Start ◽  
Image Acquisition ◽  
Cost Effective ◽  
Financial Applications ◽  
Number Of Factors ◽  
Instrument Control ◽  
The Cost ◽  
Training And Support ◽  
Control Image ◽  
Ibm Pc

IBM PC compatible computers are widely used in microscopy for applications ranging from control to image acquisition and analysis. The choice of IBM-PC based systems over competing computer platforms can be based on technical merit alone or on a number of factors relating to economics, availability of peripherals, management dictum, or simple personal preference.IBM-PC got a strong “head start” by first dominating clerical, document processing and financial applications. The use of these computers spilled into the laboratory where the DOS based IBM-PC replaced mini-computers. Compared to minicomputer, the PC provided a more for cost-effective platform for applications in numerical analysis, engineering and design, instrument control, image acquisition and image processing. In addition, the sitewide use of a common PC platform could reduce the cost of training and support services relative to cases where many different computer platforms were used. This could be especially true for the microscopists who must use computers in both the laboratory and the office.

Sonographically guided, transcatheter foam sclerotherapy of the great saphenous vein

Phlebologie ◽  
2007 ◽  
Vol 36 (06) ◽  
pp. 309-312 ◽  
Author(s):  
T. Schulz ◽  
M. Jünger ◽  
M. Hahn
Keyword(s):  
Saphenous Vein ◽  
Great Saphenous Vein ◽  
Clinical Stage ◽  
Clinical Signs ◽  
Cost Effective ◽  
Duplex Sonography ◽  
Foam Sclerotherapy ◽  
Average Loss ◽  
One Year ◽  
The Cost

Summary Objective: The goal of the study was to assess the effectiveness and patient tolerability of single-session, sonographically guided, transcatheter foam sclerotherapy and to evaluate its economic impact. Patients, methods: We treated 20 patients with a total of 22 varicoses of the great saphenous vein (GSV) in Hach stage III-IV, clinical stage C2-C5 and a mean GSV diameter of 9 mm (range: 7 to 13 mm). We used 10 ml 3% Aethoxysklerol®. Additional varicoses of the auxiliary veins of the GSV were sclerosed immediately afterwards. Results: The occlusion rate in the treated GSVs was 100% one week after therapy as demonstrated with duplex sonography. The cost of the procedure was 207.91 E including follow-up visit, with an average loss of working time of 0.6 days. After one year one patient showed clinical signs of recurrent varicosis in the GSV; duplex sonography showed reflux in the region of the saphenofemoral junction in a total of seven patients (32% of the treated GSVs). Conclusion: Transcatheter foam sclerotherapy of the GSV is a cost-effective, safe method of treating varicoses of GSV and broadens the spectrum of therapeutic options. Relapses can be re-treated inexpensively with sclerotherapy.

A Digital Economy Model for Talent Prediction Data Analytic

2019 ◽  
Vol 2 (4) ◽  
pp. 260-266
Author(s):  
Haru Purnomo Ipung ◽  
Amin Soetomo
Keyword(s):  
Business Model ◽  
Industrial Revolution ◽  
Technology Innovation ◽  
Cost Effective ◽  
Sharing Economy ◽  
Token Economy ◽  
Economy Model ◽  
New Business ◽  
The Cost ◽  
Data Analytic

This research proposed a model to assist the design of the associated data architecture and data analytic to support talent forecast in the current accelerating changes in economy, industry and business change due to the accelerating pace of technological change. The emerging and re-emerging economy model were available, such as Industrial revolution 4.0, platform economy, sharing economy and token economy. Those were driven by new business model and technology innovation. An increase capability of technology to automate more jobs will cause a shift in talent pool and workforce. New business model emerge as the availabilityand the cost effective emerging technology, and as a result of emerging or re-emerging economic models. Both, new business model and technology innovation, create new jobs and works that have not been existed decades ago. The future workers will be faced by jobs that may not exist today. A dynamics model of inter-correlation of economy, industry, business model and talent forecast were proposed. A collection of literature review were conducted to initially validate the model.

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