Evaluation of Grade Crossing Hazard Ranking Models

2017 ◽  
Author(s):  
Benjamin R. Sperry ◽  
Bhaven Naik ◽  
Jeffery E. Warner
Keyword(s):  
Literature Review ◽  
Prediction Model ◽  
Selection Process ◽  
Project Selection ◽  
Accident Prediction ◽  
Ranking Models ◽  
Ranking Model ◽  
Hazard Ranking ◽  
Grade Crossing ◽  
The U.S

Public agencies involved with highway-railroad grade crossing safety must allocate available funding to projects which are considered the most in need for improvements. Mathematical models provide a ranking of hazard risk at crossings and support the project selection process. This paper reports the results of a research study sponsored by the Ohio Rail Development Commission (ORDC) and the Ohio Department of Transportation (ODOT) examining hazard ranking models for grade crossing project selection. The goal of the research was to provide ORDC, ODOT, and other stakeholders with a better understanding of the grade crossing hazard ranking formulas and other methods used by States to evaluate grade crossing hazards and select locations for hazard elimination projects. A comprehensive literature review along with personal interviews of state DOT personnel from eight states yielded best practices for hazard ranking and project selection. The literature review found that more than three-quarters of states utilize some type of hazard ranking formula or other systematic method for project prioritization. The most commonly-used hazard ranking model in use is the U.S. DOT Accident Prediction Model; however, at least eleven states utilize state-specific hazard ranking models. Detailed evaluation of several different hazard ranking models determined that the existing hazard ranking model used in Ohio, the U.S. DOT Accident Prediction Model, should continue to be used. The research also recommends greater use of sight distance information at crossings and expanding the preliminary list of crossings to be considered in the annual program as enhancements to the existing project selection process used by the ORDC and ODOT.

Current Issues in Highway–Rail Grade Crossing Hazard-Ranking and Project Development

2017 ◽  
Vol 2608 (1) ◽  
pp. 19-26 ◽  
Author(s):  
Benjamin R. Sperry ◽  
Bhaven Naik ◽  
Jeffery E. Warner
Keyword(s):  
Department Of Transportation ◽  
Accident Prediction ◽  
Ranking Models ◽  
Starting Point ◽  
Hazard Ranking ◽  
Emerging Issues ◽  
Grade Crossing ◽  
Key Variables ◽  
The U.S ◽  
Selection Of

This paper reports on a comprehensive research study of hazard-ranking models for prioritization and selection of highway–rail grade crossing improvement projects. The U.S. Department of Transportation (DOT) accident prediction model is the most commonly used hazard-ranking model, although 11 states use state-specific models. Key variables not included in the U.S. DOT model but included in state-specific models may provide useful insight for identifying hazardous crossing locations. Emerging issues, such as the crash modeling approach used by the U.S. DOT model and the application of economic analysis principles in project prioritization, are also discussed. The findings reported in this paper provide a starting point for a broader discussion among all stakeholders in the grade crossing safety community about ways to improve hazard-ranking and project selection for highway–rail grade crossing investments.

scholarly journals Adapting the definition of multimorbidity – development of a locality-based consensus for selecting included Long Term Conditions

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Nasrin Hafezparast ◽  
Ellie Bragan Turner ◽  
Rupert Dunbar-Rees ◽  
Alice Vodden ◽  
Hiten Dodhia ◽  
...  
Keyword(s):  
Literature Review ◽  
Selection Process ◽  
Final Decision ◽  
Local Health ◽  
Urban Context ◽  
Long Term Conditions ◽  
Large Cities ◽  
Second Stage ◽  
Local Health Service

Abstract Background Defining multimorbidity has proved elusive in spite of attempts to standardise definitions. For national studies, a broad definition is required to capture national diversity. For locally based studies, the definition may need to reflect demographic and morbidity patterns. We aimed to define multimorbidity for an inner city, multi-ethnic, deprived, young age community typical of many large cities. Methods We used a scoping literature review to identify the international literature, standards and guidelines on Long Term Condition (LTC) definitions for inclusion in our multimorbidity definition. Consensus was categorised into high, medium or low consensus, depending on the number of literature sources citing each LTC. Findings were presented to a workshop consisting of local health service stakeholders who were asked to select LTCs for inclusion in a second stage review. In the second stage, each LTC was tested against seven evaluation domains: prevalence, impact, preventability, treatment burden, progression to multiple LTCs, impact on younger people, data quality. These domains were used to create 12 target criteria. LTC rankings according to consensus group and target criteria scores were presented to a second workshop for a final decision about LTC inclusion. Results The literature review identified 18 literature sources citing 86 LTCs: 11 were excluded because they were LTC clusters. The remainder were allocated into consensus groupings: 13 LTCs were ‘high consensus’ (cited by ≥ 11 sources); 15 were ‘medium consensus’ (cited by 5–10 sources); 47 were ‘low consensus’ (cited by < 5 sources). The first workshop excluded 31 LTCs. The remaining 44 LTCs consisted of: 13 high consensus LTCs, all with high target score (score 6–12); 15 medium consensus LTCs, 11 with high target scores; 16 low consensus LTCs, 6 with high target scores. The final workshop selected the 12 high consensus conditions, 12 medium consensus LTCs (10 with high target scores) and 8 low consensus LTCs (3 with high target scores), producing a final selection of 32 LTCs. Conclusions Redefining multimorbidity for an urban context ensures local relevance but may diminish national generalisability. We describe a detailed LTC selection process which should be generalisable to other contexts, both local and national.

scholarly journals Validation of UAV-based alfalfa biomass predictability using photogrammetry with fully automatic plot segmentation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Zhou Tang ◽  
Atit Parajuli ◽  
Chunpeng James Chen ◽  
Yang Hu ◽  
Samuel Revolinski ◽  
...  
Keyword(s):  
Prediction Model ◽  
High Throughput ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Selection Process ◽  
Forage Legume ◽  
Breeding Programs ◽  
High Throughput Phenotyping ◽  
Fully Automatic ◽  
Uav Images

AbstractAlfalfa is the most widely cultivated forage legume, with approximately 30 million hectares planted worldwide. Genetic improvements in alfalfa have been highly successful in developing cultivars with exceptional winter hardiness and disease resistance traits. However, genetic improvements have been limited for complex economically important traits such as biomass. One of the major bottlenecks is the labor-intensive phenotyping burden for biomass selection. In this study, we employed two alfalfa fields to pave a path to overcome the challenge by using UAV images with fully automatic field plot segmentation for high-throughput phenotyping. The first field was used to develop the prediction model and the second field to validate the predictions. The first and second fields had 808 and 1025 plots, respectively. The first field had three harvests with biomass measured in May, July, and September of 2019. The second had one harvest with biomass measured in September of 2019. These two fields were imaged one day before harvesting with a DJI Phantom 4 pro UAV carrying an additional Sentera multispectral camera. Alfalfa plot images were extracted by GRID software to quantify vegetative area based on the Normalized Difference Vegetation Index. The prediction model developed from the first field explained 50–70% (R Square) of biomass variation in the second field by incorporating four features from UAV images: vegetative area, plant height, Normalized Green–Red Difference Index, and Normalized Difference Red Edge Index. This result suggests that UAV-based, high-throughput phenotyping could be used to improve the efficiency of the biomass selection process in alfalfa breeding programs.

Three essays on the commercialization of university discoveries

2020 ◽  
Author(s):  
◽  
Hao Cheng
Keyword(s):  
Selection Process ◽  
Empirical Studies ◽  
Project Selection ◽  
University Of Missouri ◽  
Type 1 Error ◽  
Ex Post ◽  
The University ◽  
Type 2 Error

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT REQUEST OF AUTHOR.] Universities commercialize their discoveries at an increasing pace in order to maximize their economic impact and generate additional funding for research. They form technology transfer offices (TTOs) to evaluate the commercial value of university inventions and choose the most promising ones to patent and commercialize. Uncertainties and asymmetric information in project selection make the TTO choices difficult and can cause both type 1 error (forgo valuable discoveries) and type 2 error (select low-value discoveries). In this dissertation, I examine the TTO's project selection process and the factors that influence the choice of academic inventions for patenting and commercialization, the type 1 error committed, and the final licensing outcome. The dissertation contains three essays. In the first essay, I analyze project selection under uncertainty when both the quality of the proposed project and the motives of the applicant are uncertain. Some inventors may have an incentive to disguise the true quality and commercial value of their discoveries in order to conform to organizational expectations of disclosure while retaining rights to potentially pursue commercialization of their discoveries outside the organization's boundaries for their own benefit. Inventors may equally, ex post, lose interest to the commercialization of their invention due to competing job demands. I develop a model to examine the decision process of a university TTO responsible for the commercialization of academic inventions under such circumstances. The model describes the conditions that prompt Type 1 and Type 2 errors and allows for inferences for minimizing each. Little is known about the factors that make project selection effective or the opposite and there has been limited empirical analysis in this area. The few empirical studies that are available, examine the sources of type 2 error but there is no empirical work that analyzes type 1 error and the contributing factors. Research on type 1 error encounters two main difficulties. First, it is difficult to ascertain the decision process and second, it is challenging to approximate the counterfactual. Using data from the TTO of the University of Missouri, in the second essay I study the factors that influence the project selection process of the TTO in and the ex post type 1 error realized. In most cases, universities pursue commercialization of their inventions through licensing. There have been a few empirical studies that have researched the factors that affect licensing and their relative importance. In the third essay, I examine the characteristics of university inventions that are licensed using almost 10 years of data on several hundred of inventions, their characteristics, and the licensing status.

scholarly journals A Multi-criteria Approach in the Project Selection Process in Multi-Project Context

2021 ◽  
Vol 14 (6) ◽  
pp. 125
Author(s):  
Charles Éric Manyombé ◽  
Sébastien H. Azondékon
Keyword(s):  
Selection Process ◽  
Selection Procedure ◽  
Project Selection ◽  
Project Portfolio ◽  
Organizational Complexity ◽  
Scarce Resources ◽  
Project Environment ◽  
Effective Decision ◽  
Effective Decision Making

In a multi-project environment, organizational complexity refers to the difficulties that organizations often face in choosing projects to build their portfolios, since they do not aim to achieve the same strategic business objectives. It is for this reason that the project selection process requires the implementation of an effective decision-making tool when composing a project portfolio. The objective of this paper is to propose an adapted framework for a better project selection procedure inspired by the approaches of strategic relevance, profitability criteria, uncertainty, and risk analysis, the ability to dispose of scarce resources, and the determination of interdependencies between different projects.&nbsp;

scholarly journals Accident Prediction Model at Unsignalized Intersection Using Multiple Linear Regression Method

2017 ◽  
Vol 1 (2) ◽  
pp. 379-389
Author(s):  
N. K. Oghoyafedo ◽  
J. O. Ehiorobo ◽  
Ebuka Nwankwo
Keyword(s):  
Linear Regression ◽  
Prediction Model ◽  
Multiple Linear Regression ◽  
Regression Method ◽  
Linear Regression Method ◽  
Design Standards ◽  
Accident Prediction ◽  
Geometric Characteristics ◽  
Unsignalized Intersections ◽  
Multiple Linear Regression Method

The issue of road accidents is an increasing problem in developing countries. This could be due to increasing road traffic/vehicle occupancy, geometric characteristics and road way condition. The factors influencing accidents occurrence are to be analysed for remedies. The purpose of this research is to develop an accident prediction model as a measure for future study, aid planning phase preceding the designed intervention, enhance the production of updated design standards to enable practitioners design unsignalized intersection for optimal safety, reduce the number of accidents at unsignalized intersections. Five intersections were selected randomly within Benin City and traffic count carried out at these intersections as well as geometric characteristics and roadway conditions. The prediction model was developed using multiple linear regression method and the standard error of estimate was computed to show how close the observed value is to the regression line. The model was validated using coefficient of multiple determination. The establishment of the relationship between accidents and traffic flow site characteristics on the other hand would enable improvement to be more realistically accessed. This study will also enhance the production of updated design standards to enable practitioners design unsignalized intersection for optimal safety, reduce the number of accidents at unsignalized intersections.

scholarly journals Informed Consent in the U.S. Indigenous Peoples Context: A Systematic Literature Review 

2021 ◽  
Author(s):  
Tasha Gross ◽  
Clarita Lefthand-Begay
Keyword(s):  
Informed Consent ◽  
Literature Review ◽  
Cultural Values ◽  
Systematic Literature Review ◽  
Human Subjects ◽  
The United States ◽  
Inclusion Criteria ◽  
Research Practices ◽  
The Individual ◽  
The U.S

Abstract BACKGROUND: Tribal communities in the United States (U.S.) have a long history of subjection to unethical and exploitive medical and research practices. Today, many Tribal nations are establishing procedures in order to protect themselves from further harm and to advance culturally informed research practices. These procedures are also meant to ensure that their communities benefit from research conducted within their communities. Informed consent is a key element in protecting human subjects, but it may not be sufficient in the tribal context, as its conception is rooted in Western understandings of protection. Specifically, the informed consent emphasizes the individual, rather than the community as a whole, which is just as important in the context of conducting research with Native communities.METHODS: We conduct a systematic literature review to answer two related questions: How is informed consent being conceived of by U.S. tribes? And how is informed consent being required by U.S. tribes? Our inclusion criteria include articles focusing on informed consent within the U.S. tribal context, written in English in 2010-2020. Articles that did not fit our inclusion criteria were excluded. Two reviewers independently reviewed and coded 30 peer-reviewed articles by using content analysis and, in an iterative process, agreed on emerging codes and themes. RESULTS: A number of themes arise in the selected literature, including the conception of informed consent as a process, its operation at various levels (individual, collective, and government-to-government), possible alternatives to informed consent, and the need for specificity about ownership of samples and data, benefits and/or risks, and the methods and procedures that researchers use in the course of study.CONCLUSIONS: Our key results point to a need for clear and transparent information for prospective research participants and for consent forms and processes to include the collective, as well as the individual. This will better align with the cultural values and political standing of sovereign tribes in the U.S.

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