Evaluating Passenger Railway Ride Quality Over Long Distances Using Smartphones

2020 ◽  
Author(s):  
Ngoan Tien Do ◽  
Parisa Haji Abdulrazagh ◽  
Mustafa Gül ◽  
Michael T. Hendry ◽  
Alireza Roghani ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Low Cost ◽  
Ride Quality ◽  
Level Crossing ◽  
Future Plan ◽  
Vibration Data ◽  
The Future ◽  
Smartphone Sensors ◽  
Iso 2631

Abstract This paper presents a smartphone-based ride quality assessment conducted on a VIA Rail route in the province of Ontario Canada. The vibration data were collected by different smartphones placed in different locations on the train. The levels of ride quality were subsequently quantified by the two commonly used indices recommended in the ISO 2631:1-1997, and BS EN 12299:2009 standards. The results show that using smartphones for ride quality yields reasonable assessment in a low-cost and convenient manner and identify that the major poor ride quality values are recorded at stiffness transitions such as bridges, level crossing and switches. Limitations of smartphone sensors, and the future plan for improvement of the use of smartphones for evaluation of ride quality has also been discussed.

Applications of Operations Research in Human Resource Management

2021 ◽  
Vol 9 (9) ◽  
pp. 1611-1614
Author(s):  
Vanya Aggarwal
Keyword(s):  
Human Resource Management ◽  
Human Resource ◽  
Real World ◽  
Operations Research ◽  
Operational Research ◽  
Low Cost ◽  
External World ◽  
Future Plan ◽  
The Future ◽  
Future Path

Abstract: Operational HR encompasses the highly visible, day-to-day tactical operations required to keep a workforce running. This made us look for strategic approaches essential for most organisations. Be it defining the future path, determining the future plan, mission, vision, planning, objectives and goals of a particular organization. In a nutshell, we wanted to bring out the intricate relationship between HR and operational research especially considering the current dynamics of the external world. The unprecedented changes in HRM made us dig deeper on the importance of the role and applications of operations research to cope with these changes. Finally, we believed our research was complete when we presented real-world examples, and it was demonstrated to us that Operations Research approaches may assist firms in making good HR policy decisions at a low cost

Estimation of Gravel Roads Ride Quality Through an Android-Based Smartphone

2018 ◽  
Vol 2672 (40) ◽  
pp. 14-21 ◽  
Author(s):  
Waleed Aleadelat ◽  
Cameron H. G. Wright ◽  
Khaled Ksaibati
Keyword(s):  
Low Cost ◽  
Ride Quality ◽  
Initial Validation ◽  
Road Condition ◽  
Gravel Roads ◽  
Signal Demodulation ◽  
Smartphone Sensors ◽  
Quality Rating ◽  
Local Agencies ◽  
Gravel Road

This study demonstrated the ability of smartphone sensors in evaluating gravel roads conditions. Seventy gravel roads with various conditions, surface materials, and geometric features were included in this study. The analysis was based on signal demodulation and wavelet transformation to reduce the effect of many external factors (i.e., speed dependency, engine vibrations, and suspension system) that may affect the obtained measurements. It was found that the acquired signals from a smartphone accelerometer can reflect the actual conditions of a gravel road. In addition, the location and the severity of surface deteriorations such as potholes could be identified. A regression model ( R2 = 0.78) based on the acquired signals from smartphones was developed to predict the overall rating of the gravel road condition according to the Riding Quality Rating Guide (RQRG) system. An initial validation analysis, conducted on 35 new gravel roads, showed that this model was able to return reasonable ratings. Also, the statistical analysis showed that any difference between the predicted and the actual ratings of <1.3 was not significant. The proposed methodology can be considered as a baseline for building a low cost crowdsourcing platform that helps local agencies in managing their inventory of gravel roads.

On Using the ISO Standard To Evaluate the Ride Quality of Broad-Band Vibration Spectra in Transportation Vehicles

1976 ◽  
Vol 98 (4) ◽  
pp. 440-443 ◽  
Author(s):  
Craig C. Smith
Keyword(s):  
Broad Band ◽  
International Standards ◽  
Whole Body ◽  
Ride Quality ◽  
Iso Standard ◽  
Vibration Data ◽  
Power Spectral ◽  
Country Road ◽  
International Standards Organization ◽  
Iso 2631

The International Standards Organization “Guide for the Evaluation of Human Exposure to Whole-Body Vibrations”, ISO 2631, is converted to a form usable for direct comparison with vibration data represented in power spectral density form. Comparisons are made between the ISO standard, the Urban Tracked Air Cushion Vehicle (UTACV) specification, and measured vibrations at the floorboard and seat of an automobile over smooth and rough roads. The data indicate that the ISO standard is less restrictive than the UTACV specification, and generally not restrictive enough to indicate the roughness of an automobile ride on a rough country road.

INFORMAL DISCUSSION. LOW COST OPTIONS FOR RAILWAYS OF THE FUTURE.

1983 ◽  
Vol 74 (3) ◽  
pp. 607-610
Author(s):  
JJ ROUND ◽  
J ROBSON ◽  
DN BRADLEY ◽  
REB BARNARD ◽  
RA WILLIAMS ◽  
...  
Keyword(s):  
Low Cost ◽  
The Future ◽  
Informal Discussion

scholarly journals Aptamers for Detection and Diagnostics (ADD) is a proposed mobile app acquiring optical data from conjugated quantum nanodots to identify molecules indicating presence of SARS-CoV-2 virus: Why public health and healthcare need smartphone sensors as a platform for early detection and prevention

2020 ◽  
Author(s):  
Shoumen Datta
Keyword(s):  
Low Cost ◽  
Mobile App ◽  
Optical Data ◽  
Invasive Monitoring ◽  
Non Invasive ◽  
Secure Information ◽  
Biomedical Device ◽  
Smartphone Sensors ◽  
Healthcare Need ◽  
Early Detection And Prevention

Proposed SARS-CoV-2 surveillance tool using a mobile app for non-invasive monitoring of humans and animals. <p>Engineering a biomedical device as a low-cost, non-invasive, detection, and diagnostic platform for surveillance of infections in humans, and animals. The system embraces the IoT <i>“digital by design”</i> metaphor by incorporating elements of connectivity, data sharing and (secure) information arbitrage. Using an array of aptamers to bind viral targets may help in detection, diagnostics, and potentially prevention in case of SARS-CoV-2. The ADD tool may become part of a broader platform approach.</p>

scholarly journals Fault Diagnosis of Industrial Gear Hobbing Machine

2020 ◽  
Vol 9 (3) ◽  
pp. 2039-2043
Keyword(s):  
Fault Diagnosis ◽  
Low Cost ◽  
Market Competition ◽  
Vibrational Analysis ◽  
High Quality ◽  
Mems Accelerometer ◽  
Spectral Kurtosis ◽  
Vibration Data ◽  
Gear Hobbing ◽  
Dynamic Time

The aim of this paper is to develop a fault diagnosis algorithm by vibrational analysis for an industrial gear hobbing machine. Gear Hobbing is the most dominant and profitable process for manufacturing high quality gears. In order to sustain the market competition gear manufacturers, need to produce high quality gears with minimum possible cost. However, catastrophic failures do occur in gear hobbing process which causes unexpected machine down time and revenue loss. These failures can be avoided by using condition monitoring approaches. In the proposed approach vibration data during different faults such as lubrication error, excessive feed rate, loose bearing error is collected from an industrial gear hobbing machine using three axis MEMS accelerometer. The collected data is analyzed and classified with spectral kurtosis and Dynamic Time Warping algorithm. The efficiency of the proposed approach is 90 percent as determined by experimental results. The proposed approach can provide a low-cost solution for predictive maintenance for gear hobbing industries..

scholarly journals Supermarket Sales Prediction Using Regression

2021 ◽  
Vol 10 (2) ◽  
pp. 1153-1157
Keyword(s):  
Machine Learning ◽  
Performance Metrics ◽  
Low Cost ◽  
Machine Learning Algorithms ◽  
Machine Learning Techniques ◽  
Customer Data ◽  
Sales Data ◽  
Online Marketplace ◽  
Sales Prediction ◽  
The Future

Sales forecasting is an important when it comes to companies who are engaged in retailing, logistics, manufacturing, marketing and wholesaling. It allows companies to allocate resources efficiently, to estimate revenue of the sales and to plan strategies which are better for company’s future. In this paper, predicting product sales from a particular store is done in a way that produces better performance compared to any machine learning algorithms. The dataset used for this project is Big Mart Sales data of the 2013.Nowadays shopping malls and Supermarkets keep track of the sales data of the each and every individual item for predicting the future demand of the customer. It contains large amount of customer data and the item attributes. Further, the frequent patterns are detected by mining the data from the data warehouse. Then the data can be used for predicting the sales of the future with the help of several machine learning techniques (algorithms) for the companies like Big Mart. In this project, we propose a model using the Xgboost algorithm for predicting sales of companies like Big Mart and founded that it produces better performance compared to other existing models. An analysis of this model with other models in terms of their performance metrics is made in this project. Big Mart is an online marketplace where people can buy or sell or advertise your merchandise at low cost. The goal of the paper is to make Big Mart the shopping paradise for the buyers and a marketing solutions for the sellers as well. The ultimate aim is the complete satisfaction of the customers. The project “SUPERMARKET SALES PREDICTION” builds a predictive model and finds out the sales of each of the product at a particular store. The Big Mart use this model to under the properties of the products which plays a major role in increasing the sales. This can also be done on the basis hypothesis that should be done before looking at the data

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