scholarly journals Railway Track Monitoring Using Train Measurements: An Experimental Case Study

2019 ◽  
Vol 9 (22) ◽  
pp. 4859 ◽  
Author(s):  
Abdollah Malekjafarian ◽  
Eugene OBrien ◽  
Paraic Quirke ◽  
Cathal Bowe
Keyword(s):  
Energy Level ◽  
Energy Levels ◽  
Railway Track ◽  
Forward Speed ◽  
Data Set ◽  
Global Positioning ◽  
The Hilbert Transform ◽  
Track Monitoring ◽  
Acceleration Signals

This paper investigates the use of drive-by train measurements for railway track monitoring. An in-service Irish Rail train was instrumented while using accelerometers and a global positioning system. The measurements were taken over two months and the train bogie accelerations from 60 passes on the Dublin-Belfast line were used for this study. A 6 km section of the line is the particular focus, where the maintenance measurements from a Track Recording Vehicle (TRV) were available. The Hilbert transform is used to obtain the instantaneous amplitudes of the acceleration signals. A new representation of the signal is proposed to show the signal energy level as a function of train location. It is shown that the forward speed of the train has a significant influence on the energy level of the signals. Therefore, a two-step speed correction is applied to the data. First, data from passes with forward speed below a certain limit are removed from the data set. Subsequently, a scaling factor is defined for the remaining signals and the energy levels of those signals are scaled while using online speed measurements. The scaled amplitudes are compared with the TRV data. It is shown that the energy levels of the signals match the TRV measurements very well.

EXPRESS: High-Energy Ad Content: A Large-scale Investigation of TV Commercials

2021 ◽  
pp. 002224372110678
Author(s):  
Joonhyuk Yang ◽  
Yingkang Xie ◽  
Lakshman Krishnamurthi ◽  
Purushottam Papatla
Keyword(s):  
Energy Level ◽  
Large Scale ◽  
Energy Levels ◽  
Positive Association ◽  
High Energy ◽  
Data Set ◽  
Product Categories ◽  
Tv Commercials

A trend reported by both academics and practitioners is that advertising on TV has become increasingly energetic. This study investigates the association between the energy level in ad content and consumers’ tendency of ad-tuning. Using a data set of over 27,000 TV commercials delivered to U.S. homes during the period between 2015 and 2018, the authors first present a framework to algorithmically measure the energy level in ad content from the video of ads. This algorithm-based measure is then compared to human-perceived energy levels, which shows that the measure is related to the level of arousal stimulated by ad content. By relating the energy levels in ad content with the tendency of ad-tuning using two empirical procedures, the authors document the following. Overall, more energetic commercials are likely to be tuned in more or avoided less by viewers. The positive association between energy levels in ad content and ad-tuning is statistically significant after controlling for placement and other aspects of commercials. However, the association varies across product categories and program genres. The main implication of this study is that advertisers should pay attention to components of ad content other than loudness, which has been regulated by law.

Road Closures and Freight Diversion

2012 ◽  
Vol 2269 (1) ◽  
pp. 51-57 ◽  
Author(s):  
David Pierce ◽  
Jeffrey Short
Keyword(s):  
Performance Measures ◽  
The United States ◽  
Valuable Insight ◽  
Data Set ◽  
Sensing Technology ◽  
Global Positioning ◽  
Data Points ◽  
System Data ◽  
The Impact

The FHWA-sponsored Freight Performance Measures (FPM) program generates and monitors a series of performance measures related to the freight transportation system of the United States. The primary information analyzed by the FPM program is a data set consisting of billions of Global Positioning System data points from trucks. These data can be used to demonstrate empirically changes in truck travel patterns and freight performance independent of the availability of roadside sensing technology. A case study that was based on the flooding closure of Arkansas Interstate 40 in May 2011 was presented to show how FPM data can be used to analyze diversion behavior around road closures. This type of empirical analysis is in contrast to the majority of current diversion analyses, which rely on modeling to generate results. Not only do FPM data provide a viable alternative to modeling for studying past events, but the data may provide valuable insight into the underlying assumptions of future models designed to predict the impact of disaster scenarios. By understanding more fully how previous events unfolded, planners can prepare better for the next disaster.

Optimized Railway Track Condition Monitoring and Derailment Prevention System Supported by Cloud Technology

2021 ◽  
pp. 036119812098043
Author(s):  
C. Chellaswamy ◽  
T. S. Geetha ◽  
M. Surya Bhupal Rao ◽  
A. Vanathi
Keyword(s):  
Global Positioning System ◽  
Railway Track ◽  
Measured Signal ◽  
Micro Electro Mechanical Systems ◽  
Flower Pollination ◽  
Track Condition ◽  
Global Positioning ◽  
Prevention System ◽  
Pass Through ◽  
Track Monitoring

This paper describes an easy way to monitor railway track abnormalities and update information on the track’s status to the cloud. Abnormalities present in railway tracks should be identified promptly and rectified to ensure safe and smooth travel. In this paper, a cloud-based track monitoring system (CTMS) is proposed for the monitoring of track conditions. The micro-electro mechanical systems (MEMS) accelerometers which are mounted in the axle are used to measure the railway track abnormality. The measured signal is optimized using the flower pollination optimization algorithm (FPOA). Because of signaling problems in the global positioning system (GPS), it is difficult to estimate the exact location of the abnormality in real time. A new method is introduced to overcome this problem. It provides the location of an abnormality even when the GPS signal is absent. The performance of the CTMS is compared with three different speed scenarios of the vehicle. The information about the abnormality on the track can be shared with other trains that pass through the same location so that the driver can reduce speed in that location to avoid derailment. Finally, an experimental setup was developed and the performance of CTMS is studied under four different irregularity cases.

scholarly journals An IOT based rail track condition monitoring and derailment prevention system

2020 ◽  
pp. 1-27
Author(s):  
C. Chellaswamy ◽  
T.S. Geetha ◽  
A. Vanathi ◽  
K. Venkatachalam
Keyword(s):  
Global Positioning System ◽  
Early Stage ◽  
Micro Electro Mechanical System ◽  
Railway Track ◽  
Positioning System ◽  
Track Condition ◽  
Global Positioning ◽  
Prevention System ◽  
The Status ◽  
Track Monitoring

This paper proposes a new method for monitoring the irregularities in railway tracks by updating the status of the tracks in the cloud. The IoT based Railway Track Monitoring System (IoT-RMS) is proposed for monitoring the health of the railway track. The system identifies any abnormality in the tracks at an early stage. These abnormalities are rectified before they develop for smoother transportation. The micro electro mechanical system (MEMS) accelerometers are placed in the axle box for measuring the signal. It becomes hard to identify the exact location of abnormalities when the global positioning system (GPS) falters due to signalling issues. In this paper, a new hybrid method is proposed for locating irregularities on a track; even in the absence of a GPS signal. Pre-processing of the GPS signal is carried out effectively because the sensors used in IoT-RMS are capable of functioning in a high noise environment. The IoT-RMS updates the location of the abnormality in the cloud and shares it with other trains that will be passing through that location. As a result, the drivers of trains respond accordingly and avoid derailment. An experimental setup has been developed for a study of the performances for four different abnormal cases, and the result shows the effectiveness of the proposed system.

Parent and Grandparent Relationships in Emerging Adulthood

2018 ◽  
Author(s):  
Michael W. Pratt ◽  
M. Kyle Matsuba
Keyword(s):  
Emerging Adulthood ◽  
Attachment Theory ◽  
Emerging Adults ◽  
Family Relationships ◽  
Longitudinal Research ◽  
Study Data ◽  
Family Development ◽  
Data Set ◽  
Theory Framework

Chapter 7 begins with an overview of Erikson’s ideas about intimacy and its place in the life cycle, followed by a summary of Bowlby and Ainsworth’s attachment theory framework and its relation to family development. The authors review existing longitudinal research on the development of family relationships in adolescence and emerging adulthood, focusing on evidence with regard to links to McAdams and Pals’ personality model. They discuss the evidence, both questionnaire and narrative, from the Futures Study data set on family relationships, including emerging adults’ relations with parents and, separately, with grandparents, as well as their anticipations of their own parenthood. As a way of illustrating the key personality concepts from this family chapter, the authors end with a case study of Jane Fonda in youth and her father, Henry Fonda, to illustrate these issues through the lives of a 20th-century Hollywood dynasty of actors.

Vocational Development in Emerging Adulthood

2018 ◽  
Author(s):  
Michael W. Pratt ◽  
M. Kyle Matsuba
Keyword(s):  
Turning Point ◽  
Life Stories ◽  
Life Story ◽  
Emerging Adult ◽  
Vocational Development ◽  
Data Set ◽  
The World ◽  
Key Concepts

Chapter 6 reviews research on the topic of vocational/occupational development in relation to the McAdams and Pals tripartite personality framework of traits, goals, and life stories. Distinctions between types of motivations for the work role (as a job, career, or calling) are particularly highlighted. The authors then turn to research from the Futures Study on work motivations and their links to personality traits, identity, generativity, and the life story, drawing on analyses and quotes from the data set. To illustrate the key concepts from this vocation chapter, the authors end with a case study on Charles Darwin’s pivotal turning point, his round-the-world voyage as naturalist for the HMS Beagle. Darwin was an emerging adult in his 20s at the time, and we highlight the role of this journey as a turning point in his adult vocational development.

How to Assess Prognostic Models for Survival Data: A Case Study in Oncology

2003 ◽  
Vol 42 (05) ◽  
pp. 564-571 ◽  
Author(s):  
M. Schumacher ◽  
E. Graf ◽  
T. Gerds
Keyword(s):  
Test Data ◽  
Survival Data ◽  
Prediction Error ◽  
Classification Scheme ◽  
Neural Nets ◽  
Brier Score ◽  
Data Set ◽  
Independent Test ◽  
Artificial Neural

Summary Objectives: A lack of generally applicable tools for the assessment of predictions for survival data has to be recognized. Prediction error curves based on the Brier score that have been suggested as a sensible approach are illustrated by means of a case study. Methods: The concept of predictions made in terms of conditional survival probabilities given the patient’s covariates is introduced. Such predictions are derived from various statistical models for survival data including artificial neural networks. The idea of how the prediction error of a prognostic classification scheme can be followed over time is illustrated with the data of two studies on the prognosis of node positive breast cancer patients, one of them serving as an independent test data set. Results and Conclusions: The Brier score as a function of time is shown to be a valuable tool for assessing the predictive performance of prognostic classification schemes for survival data incorporating censored observations. Comparison with the prediction based on the pooled Kaplan Meier estimator yields a benchmark value for any classification scheme incorporating patient’s covariate measurements. The problem of an overoptimistic assessment of prediction error caused by data-driven modelling as it is, for example, done with artificial neural nets can be circumvented by an assessment in an independent test data set.

scholarly journals Parking Places to Moped-Style Scooter Sharing Services Using GIS Location-Allocation Models and GPS Data

2021 ◽  
Vol 10 (4) ◽  
pp. 230
Author(s):  
Onel Pérez-Fernández ◽  
Juan Carlos García-Palomares
Keyword(s):  
Global Positioning System ◽  
Catchment Area ◽  
Public Spaces ◽  
Gps Data ◽  
Positioning System ◽  
Urban Centers ◽  
Location Allocation ◽  
Global Positioning ◽  
The City

Moped-style scooters are one of the most popular systems of micro-mobility. They are undoubtedly good for the city, as they promote forms of environmentally-friendly mobility, in which flexibility helps prevent traffic build-up in the urban centers where they operate. However, their increasing numbers are also generating conflicts as a result of the bad behavior of users, their unwarranted use in public spaces, and above all their parking. This paper proposes a methodology for finding parking spaces for shared motorcycle services using Geographic information system (GIS) location-allocation models and Global Positioning System (GPS) data. We used the center of Madrid and data from the company Muving (one of the city’s main operators) for our case study. As well as finding the location of parking spaces for motorbikes, our analysis examines how the varying distribution of demand over the course of the day affects the demand allocated to parking spaces. The results demonstrate how reserving a relatively small number of parking spaces for scooters makes it possible to capture over 70% of journeys in the catchment area. The daily variations in the distribution of demand slightly reduce the efficiency of the network of parking spaces in the morning and increase it at night, when demand is strongly focused on the most central areas.

Magnetotelluric static shift: Estimation and removal using the cokriging method

Geophysics ◽  
2007 ◽  
Vol 72 (1) ◽  
pp. F25-F34 ◽  
Author(s):  
Benoit Tournerie ◽  
Michel Chouteau ◽  
Denis Marcotte
Keyword(s):  
Apparent Resistivity ◽  
A Priori ◽  
Shift Factor ◽  
Static Shift ◽  
Geostatistical Model ◽  
Data Set ◽  
Resistivity Sounding ◽  
The Difference ◽  
Cross Variogram

We present and test a new method to correct for the static shift affecting magnetotelluric (MT) apparent resistivity sounding curves. We use geostatistical analysis of apparent resistivity and phase data for selected periods. For each period, we first estimate and model the experimental variograms and cross variogram between phase and apparent resistivity. We then use the geostatistical model to estimate, by cokriging, the corrected apparent resistivities using the measured phases and apparent resistivities. The static shift factor is obtained as the difference between the logarithm of the corrected and measured apparent resistivities. We retain as final static shift estimates the ones for the period displaying the best correlation with the estimates at all periods. We present a 3D synthetic case study showing that the static shift is retrieved quite precisely when the static shift factors are uniformly distributed around zero. If the static shift distribution has a nonzero mean, we obtained best results when an apparent resistivity data subset can be identified a priori as unaffected by static shift and cokriging is done using only this subset. The method has been successfully tested on the synthetic COPROD-2S2 2D MT data set and on a 3D-survey data set from Las Cañadas Caldera (Tenerife, Canary Islands) severely affected by static shift.

Radical induced intermolecular linkage and energy level modifications of a porphyrin monolayer

2017 ◽  
Vol 53 (6) ◽  
pp. 1104-1107 ◽  
Author(s):  
Abdolreza Jahanbekam ◽  
Colin Harthcock ◽  
David Y. Lee
Keyword(s):  
Energy Level ◽  
Scanning Tunneling Microscopy ◽  
Surface Structure ◽  
Energy Levels ◽  
New Method ◽  
Scanning Tunneling ◽  
Tunneling Microscopy ◽  
Molecular Scale

A new method to directly modify the surface structure and energy levels of a porphyrin monolayer was examined with molecular-scale resolution using scanning tunneling microscopy and spectroscopy (STM and STS) and presented in this communication.

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