ScooterLab - Griffin.pptx
•Download as PPTX, PDF•
0 likes•253 views
Greg Griffin's presentation on UTSA's ScooterLab, part of the TPR Think Science series held on 9/12/23.
Report
Share
Report
Share
Recommended
(Geo-) Daten für ein besseres Verständnis der Fahrradmobilität
This document summarizes key points from a presentation about using data to better understand bicycle mobility.
The presentation discusses how (1) historically, transportation planning focused on motorized modes and marginalized walking and cycling due to a lack of data, (2) new technologies now enable widespread collection of mobility data at fine-grained spatial and temporal scales, and (3) combining these diverse data sources could provide insights but also challenges relating to data integration and ensuring data quality and representation. The presentation calls for more work developing methods and models to fuse different data types and involve stakeholders to create an evidence base that increases visibility and support for sustainable transport.
Presentation at EnviroInfo 2014, Oldenburg
This document discusses how GIS (geographic information systems) can help promote safe cycling. GIS allows for spatial modeling and analysis of cycling infrastructure and accidents, providing an evidence-based approach. The document outlines accident analysis of over 3,000 bicycle accidents in Salzburg, Austria over 10 years. It also describes an indicator-based assessment model for evaluating bicycle safety and infrastructure across an entire network. Finally, it concludes that GIS can directly address road infrastructure and information to help plan cycling routes and identify weaknesses in the network.
Big data: uncovering new mobility patterns and redefining planning practices
Using representations and data that are digital, we can create images about what happens where and when in cities, including mobility patterns that remained unaccounted until now. If properly analysed, big data for mobility can radically improve the socioeconomic and environmental analysis of public and sustainable transport. This session will discuss how big data is affecting mobility in terms of new travel behaviour and transport planning. At the user level, the relations between social networks, social media usage and travel behaviour in EU countries will be discussed. Scientific insight on the social media usage of millennial students in EU countries to understand their impact on social activities and mobility in urban areas will be presented. At the planer level, responses to changes in mobility patterns or unaccounted needs given by the analysis of public transport smart data will be presented. Advances on an integrated accessibility index will be discussed as a way for policy makers to improve current transport planning practices. Yet, big data in transport is not immune from some problems, especially those relating to statistical validity, bias and incorrectly imputed causality. This point will be discussed alongside liability, since Big data is gathered and manipulated by many different stakeholders. The proposed panel discussion therefore aims to provide to the audience a clear understanding on ways in which big data affects travel behaviour and transport planning, while accounting for data quality and pan European standardisation aspects.
Active modes and urban mobility: outcomes from the ALLEGRO project
In this presentation, we present some examples of the main outcomes of the ALLEGRO project so far. The talks starts with showing how active mode traffic can play a major role given that cities are getting denser.
Yinhai Wang - Smart Transportation: Research under Smart Cities Context - GCS16
This document discusses challenges and opportunities in smart transportation research under smart cities. It outlines how transportation is a major issue impacting environment, safety, and public health. Smart cities and transportation big data can help address key issues of efficiency, sustainability and safety through data analytics. The document presents examples of extracting transportation data from mobile networks and DRIVE Net, a system for data sharing, visualization, and analysis to support e-science investigations in transportation. Research needs include developing methods to utilize spatial and temporal big data to support analysis and decision making in transportation.
Mina Lee - E-scooter demand model for NYC
1) The document discusses forecasting rental demand for electric scooter sharing systems in New York City. It reviews previous research on bike sharing demand and models.
2) The methodology includes summarizing Portland's electric scooter pilot program data, estimating linear regression and multinomial logit choice models using Portland and NYC data to predict scooter ridership.
3) The models suggest electric scooters will constitute 1% of NYC trips, targeting short trips in Manhattan neighborhoods like Tribeca and Soho. The models can advise optimal scooter placement and numbers.
April 2020 top read artilce in Computer Science and Information Technology
April 2020 top read artilce in Computer Science and Information TechnologyAIRCC Publishing Corporation
Big Data is used in decision making process to gain useful insights hidden in the data for business and engineering. At the same time it presents challenges in processing, cloud computing has helped in advancement of big data by providing computational, networking and storage capacity. This paper presents the review, opportunities and challenges of transforming big data using cloud computing resources.Crowdsourcing and citizen engagement for people-centric smart cities
This document discusses how crowdsourcing and citizen science can be used to improve smart cities through collective intelligence. It describes how crowdsourcing involves solving problems through open crowds, using both paid microtasks and unpaid volunteering. Citizen science involves scientific research conducted by amateur scientists. The document outlines examples like using crowdsourcing to audit urban areas through a virtual street view tool. It emphasizes that citizen engagement projects must consider people's diverse motivations for participating and align incentives appropriately to encourage sustained involvement. Assessments of data quality and understanding participant behaviors are also important.
Recommended
(Geo-) Daten für ein besseres Verständnis der Fahrradmobilität
This document summarizes key points from a presentation about using data to better understand bicycle mobility.
The presentation discusses how (1) historically, transportation planning focused on motorized modes and marginalized walking and cycling due to a lack of data, (2) new technologies now enable widespread collection of mobility data at fine-grained spatial and temporal scales, and (3) combining these diverse data sources could provide insights but also challenges relating to data integration and ensuring data quality and representation. The presentation calls for more work developing methods and models to fuse different data types and involve stakeholders to create an evidence base that increases visibility and support for sustainable transport.
Presentation at EnviroInfo 2014, Oldenburg
This document discusses how GIS (geographic information systems) can help promote safe cycling. GIS allows for spatial modeling and analysis of cycling infrastructure and accidents, providing an evidence-based approach. The document outlines accident analysis of over 3,000 bicycle accidents in Salzburg, Austria over 10 years. It also describes an indicator-based assessment model for evaluating bicycle safety and infrastructure across an entire network. Finally, it concludes that GIS can directly address road infrastructure and information to help plan cycling routes and identify weaknesses in the network.
Big data: uncovering new mobility patterns and redefining planning practices
Using representations and data that are digital, we can create images about what happens where and when in cities, including mobility patterns that remained unaccounted until now. If properly analysed, big data for mobility can radically improve the socioeconomic and environmental analysis of public and sustainable transport. This session will discuss how big data is affecting mobility in terms of new travel behaviour and transport planning. At the user level, the relations between social networks, social media usage and travel behaviour in EU countries will be discussed. Scientific insight on the social media usage of millennial students in EU countries to understand their impact on social activities and mobility in urban areas will be presented. At the planer level, responses to changes in mobility patterns or unaccounted needs given by the analysis of public transport smart data will be presented. Advances on an integrated accessibility index will be discussed as a way for policy makers to improve current transport planning practices. Yet, big data in transport is not immune from some problems, especially those relating to statistical validity, bias and incorrectly imputed causality. This point will be discussed alongside liability, since Big data is gathered and manipulated by many different stakeholders. The proposed panel discussion therefore aims to provide to the audience a clear understanding on ways in which big data affects travel behaviour and transport planning, while accounting for data quality and pan European standardisation aspects.
Active modes and urban mobility: outcomes from the ALLEGRO project
In this presentation, we present some examples of the main outcomes of the ALLEGRO project so far. The talks starts with showing how active mode traffic can play a major role given that cities are getting denser.
Yinhai Wang - Smart Transportation: Research under Smart Cities Context - GCS16
This document discusses challenges and opportunities in smart transportation research under smart cities. It outlines how transportation is a major issue impacting environment, safety, and public health. Smart cities and transportation big data can help address key issues of efficiency, sustainability and safety through data analytics. The document presents examples of extracting transportation data from mobile networks and DRIVE Net, a system for data sharing, visualization, and analysis to support e-science investigations in transportation. Research needs include developing methods to utilize spatial and temporal big data to support analysis and decision making in transportation.
Mina Lee - E-scooter demand model for NYC
1) The document discusses forecasting rental demand for electric scooter sharing systems in New York City. It reviews previous research on bike sharing demand and models.
2) The methodology includes summarizing Portland's electric scooter pilot program data, estimating linear regression and multinomial logit choice models using Portland and NYC data to predict scooter ridership.
3) The models suggest electric scooters will constitute 1% of NYC trips, targeting short trips in Manhattan neighborhoods like Tribeca and Soho. The models can advise optimal scooter placement and numbers.
April 2020 top read artilce in Computer Science and Information Technology
April 2020 top read artilce in Computer Science and Information TechnologyAIRCC Publishing Corporation
Big Data is used in decision making process to gain useful insights hidden in the data for business and engineering. At the same time it presents challenges in processing, cloud computing has helped in advancement of big data by providing computational, networking and storage capacity. This paper presents the review, opportunities and challenges of transforming big data using cloud computing resources.Crowdsourcing and citizen engagement for people-centric smart cities
This document discusses how crowdsourcing and citizen science can be used to improve smart cities through collective intelligence. It describes how crowdsourcing involves solving problems through open crowds, using both paid microtasks and unpaid volunteering. Citizen science involves scientific research conducted by amateur scientists. The document outlines examples like using crowdsourcing to audit urban areas through a virtual street view tool. It emphasizes that citizen engagement projects must consider people's diverse motivations for participating and align incentives appropriately to encourage sustained involvement. Assessments of data quality and understanding participant behaviors are also important.
New Research Articles 2020 November Issue International Journal of Software E...
The International Journal of Software Engineering & Applications (IJSEA) is a bi-monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Software Engineering & Applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts & establishing new collaborations in these areas.
Bicycle Infrastructure Improvement Study and Implementation Plan
The Urban Information Lab at the University of Texas at Austin will conduct a 3-phase study to evaluate the university's bicycle infrastructure and policies. Phase 1 will inventory existing bike lanes, racks, and other infrastructure. Phase 2 will collect data from smartphone apps on biking routes, issues, and preferences. Phase 3 will analyze the findings to identify specific improvements like expanding bike lanes and facilities to increase biking and support sustainability goals. The goal is to provide a detailed plan to convert car drivers to bike commuters and better support biking on campus.
Tutorial on AI-based Analytics in Traffic Management
This is the tutorial on AI analytical techniques for traffic management presented at the IJCAI 2013 conference, Beijing, China presented by Biplav Srivastava and Akshat Kumar.
Katja leyendecker - presentation to APPCG 29 Dec 2016
On behalf of the Cycling Embassy of Great Britain, I spoke at All-party Parliamentary Cycling Group at Westminster, London
Intro to Big Data in Urban GIS Research
Urban big data are increasingly being used in urban GIS research. This presentation, developed for an introductory GIS course, introduces the seven V's of big data: volume, variety, velocity, veracity, value, visualization, and variability. Major sources of urban big data include sensor systems, user-generated content, administrative systems, private sector data, humanities data, and hybrid data. These categories and the seven V's are illustrated with six examples of cutting-edge urban big data research: the Array of Things sensing network, Austin bike data, analysis of London's transport network, scraping Craigslist to analyze rental housing, the Mapping Inequality Project, and the EPA Smart Locations Database. The presentation concludes with a discussion of critiques surrounding the use of big data.
City of Chicago Tech Plan 18 Month Progress Update
The document outlines Chicago's 18-month progress report on its technology plan to establish the city as a center of innovation. Key accomplishments include expanding broadband access, especially affordable gigabit internet; increasing public access to technology through initiatives like free WiFi in parks and libraries; growing the tech sector through job growth and training programs; and improving digital education for youth. The plan aims to ensure all residents and communities can participate in and benefit from Chicago's growing digital economy.
What makes smart cities “Smart”?
Smart cities use digital technologies and information communication technologies to enhance quality and performance of urban services. This makes cities "smart" by providing smarter citizens, governance, environment, equality, context-aware and cost effective services. Technology like sensors, real-time data collection and analytics, and integrated services across a city help power smart cities. However, challenges remain around data quality, privacy, bias, and over-complexity that must be addressed for smart city technologies and data analytics to achieve their full potential.
Urban Big Data Centre
Sarah Currier from the University of Glasgow presenting about the Urban Big Data Centre. Presented at Women in Tech Scotland Meetup on 22nd March 2016.
Smart city- services and technologies
Services, applications, infrastructures that makes a city smart.
Technologies that enables these concepts.
Using gamification to generate citizen input for public transport planning
Presentation at the 2016 ePart conference in Guimaraes, Portugal. Research in progress presenting a case study of a smart cities app, and discussing how the data can be used for increased citizen participation.
Austin Vision Zero
A presentation given at the 2016 Traffic Safety Conference during Breakout Session 7: Vision Zero: One Year Update. By Laura Dierenfield, Manager, Active Transportation, Austin Transportation Department, City of Austin
The role of open data in driving sustainable mobility in nine smart cities
The work was presented in European Conference on Information Systems (ECIS 2017) , at Guimaraes Portugal. The work presents a comprehensive survey results on open data focused in mobility domain in nine smart cities like Barcelona, Dublin, NewYork etc.
Role of Big Data for Smart City Applications
Talk given to the Smart City course students at CEPT University. Oct 19, 2014.
* Overview on Physical (IoT/Sensor), Cyber (OpenGov) and Social (citizen Sensing) data
* Relevance to City Departments
* Three smart city applications (from India, Europe and US)
More on the course: http://indianexpress.com/article/india/india-others/cept-launches-first-ever-course-on-smart-cities/
Taking Pedestrian and Bicycle Counting Programs to the Next Level
Taking Pedestrian and Bicycle Counting Programs to the Next Level Project for Public Spaces & National Center for Biking and Walking
Title: Taking Pedestrian and Bicycle Counting Programs to the Next Level
Track: Connect
Format: 90 minute panel
Abstract: Panelists will provide practical guidance for pedestrian and bicycle counting programs based on findings from NCHRP Project 07-19, "Methods and Technologies for Collecting Pedestrian and Bicycle Volume Data."
Presenters:
Presenter: Robert Schneider University of Wisconsin-Milwaukee
Co-Presenter: RJ Eldridge Toole Design Group, LLC
Co-Presenter: Conor Semler Kittelson & Associates, Inc.Katja Leyendecker @ Cycling & Society Symposium Manchester Sep2015
This document presents a summary of Katja Leyendecker's PhD research which compares public perceptions of cycling in Newcastle and Gateshead, UK to Bremen, Germany. The research involves three phases: 1) quantifying cycling rates in both cities, 2) conducting interviews and surveys to understand perceptions of cycling safety and infrastructure, and 3) developing recommendations to improve cycling rates based on differences observed between the two locations. Background information is provided on factors influencing women's cycling rates and the importance of socio-cultural context in comparing transportation modes between cities.
A review of current online bicycle routing portals and their potential role i...
This document evaluates how online bicycle routing portals address safety when providing route recommendations. It reviews 30 pre-trip route planning websites and finds that while most allow users to select routing criteria like distance and time, very few explicitly include safety as a criteria. When safety is included, it is rarely defined or explained. The document concludes that since safety is an important factor in bicyclists' route choices but is largely ignored by current routing tools, more needs to be done to better reflect the complexity of safety considerations and individual preferences in route recommendations.
Women activists’ critique of cycle politics
Prepared for RGS-IGB Annual Conference
31 August 2018
Katja Leyendecker EurIng CEng
Researcher at Northumbria University, UK
Big Data & Smart City Applications
A talk that was given to share experience in building Smart City applications to the city administrators of Dunedin, NZ.
Invest Bavaria Maifest Keynote
Keynote address for the Invest Bavaria #MaifestMobility Conference highting innovative startups demoing their product ! Averon, DSP Concepts, Inc., BCG Digital Ventures, HAAS Alert, EVELOZCITY, LimeBike, Mindtronic AI, TrueFace.ai, Toposens GmbH & Xapix
Qing TRB Poster 16
This paper presents a new Hierarchical Clustering and Grid Mapping (H-G) approach to estimate hourly traffic emissions for an entire city using cellular activity data. The proposed method involves five steps: 1) preprocessing cellular data to generate GPS-labeled records, 2) generating a grid map of the city, 3) using hierarchical clustering to group cell towers and generate centroids, 4) matching movements to grids using shortest path algorithms, and 5) estimating emissions using an output of vehicle miles traveled in each grid. The method was tested using data from a midsize city in China and was able to reveal city-scale traffic dynamics and estimate hourly vehicle emissions across the entire city.
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Ozturkcan, S., Berndt, A., & Angelakis, A. (2024). Mending clothing to support sustainable fashion. Presented at the 31st Annual Conference by the Consortium for International Marketing Research (CIMaR), 10-13 Jun 2024, University of Gävle, Sweden.
The binding of cosmological structures by massless topological defects
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
More Related Content
Similar to ScooterLab - Griffin.pptx
New Research Articles 2020 November Issue International Journal of Software E...
The International Journal of Software Engineering & Applications (IJSEA) is a bi-monthly open access peer-reviewed journal that publishes articles which contribute new results in all areas of the Software Engineering & Applications. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on understanding Modern software engineering concepts & establishing new collaborations in these areas.
Bicycle Infrastructure Improvement Study and Implementation Plan
The Urban Information Lab at the University of Texas at Austin will conduct a 3-phase study to evaluate the university's bicycle infrastructure and policies. Phase 1 will inventory existing bike lanes, racks, and other infrastructure. Phase 2 will collect data from smartphone apps on biking routes, issues, and preferences. Phase 3 will analyze the findings to identify specific improvements like expanding bike lanes and facilities to increase biking and support sustainability goals. The goal is to provide a detailed plan to convert car drivers to bike commuters and better support biking on campus.
Tutorial on AI-based Analytics in Traffic Management
This is the tutorial on AI analytical techniques for traffic management presented at the IJCAI 2013 conference, Beijing, China presented by Biplav Srivastava and Akshat Kumar.
Katja leyendecker - presentation to APPCG 29 Dec 2016
On behalf of the Cycling Embassy of Great Britain, I spoke at All-party Parliamentary Cycling Group at Westminster, London
Intro to Big Data in Urban GIS Research
Urban big data are increasingly being used in urban GIS research. This presentation, developed for an introductory GIS course, introduces the seven V's of big data: volume, variety, velocity, veracity, value, visualization, and variability. Major sources of urban big data include sensor systems, user-generated content, administrative systems, private sector data, humanities data, and hybrid data. These categories and the seven V's are illustrated with six examples of cutting-edge urban big data research: the Array of Things sensing network, Austin bike data, analysis of London's transport network, scraping Craigslist to analyze rental housing, the Mapping Inequality Project, and the EPA Smart Locations Database. The presentation concludes with a discussion of critiques surrounding the use of big data.
City of Chicago Tech Plan 18 Month Progress Update
The document outlines Chicago's 18-month progress report on its technology plan to establish the city as a center of innovation. Key accomplishments include expanding broadband access, especially affordable gigabit internet; increasing public access to technology through initiatives like free WiFi in parks and libraries; growing the tech sector through job growth and training programs; and improving digital education for youth. The plan aims to ensure all residents and communities can participate in and benefit from Chicago's growing digital economy.
What makes smart cities “Smart”?
Smart cities use digital technologies and information communication technologies to enhance quality and performance of urban services. This makes cities "smart" by providing smarter citizens, governance, environment, equality, context-aware and cost effective services. Technology like sensors, real-time data collection and analytics, and integrated services across a city help power smart cities. However, challenges remain around data quality, privacy, bias, and over-complexity that must be addressed for smart city technologies and data analytics to achieve their full potential.
Urban Big Data Centre
Sarah Currier from the University of Glasgow presenting about the Urban Big Data Centre. Presented at Women in Tech Scotland Meetup on 22nd March 2016.
Smart city- services and technologies
Services, applications, infrastructures that makes a city smart.
Technologies that enables these concepts.
Using gamification to generate citizen input for public transport planning
Presentation at the 2016 ePart conference in Guimaraes, Portugal. Research in progress presenting a case study of a smart cities app, and discussing how the data can be used for increased citizen participation.
Austin Vision Zero
A presentation given at the 2016 Traffic Safety Conference during Breakout Session 7: Vision Zero: One Year Update. By Laura Dierenfield, Manager, Active Transportation, Austin Transportation Department, City of Austin
The role of open data in driving sustainable mobility in nine smart cities
The work was presented in European Conference on Information Systems (ECIS 2017) , at Guimaraes Portugal. The work presents a comprehensive survey results on open data focused in mobility domain in nine smart cities like Barcelona, Dublin, NewYork etc.
Role of Big Data for Smart City Applications
Talk given to the Smart City course students at CEPT University. Oct 19, 2014.
* Overview on Physical (IoT/Sensor), Cyber (OpenGov) and Social (citizen Sensing) data
* Relevance to City Departments
* Three smart city applications (from India, Europe and US)
More on the course: http://indianexpress.com/article/india/india-others/cept-launches-first-ever-course-on-smart-cities/
Taking Pedestrian and Bicycle Counting Programs to the Next Level
Taking Pedestrian and Bicycle Counting Programs to the Next Level Project for Public Spaces & National Center for Biking and Walking
Title: Taking Pedestrian and Bicycle Counting Programs to the Next Level
Track: Connect
Format: 90 minute panel
Abstract: Panelists will provide practical guidance for pedestrian and bicycle counting programs based on findings from NCHRP Project 07-19, "Methods and Technologies for Collecting Pedestrian and Bicycle Volume Data."
Presenters:
Presenter: Robert Schneider University of Wisconsin-Milwaukee
Co-Presenter: RJ Eldridge Toole Design Group, LLC
Co-Presenter: Conor Semler Kittelson & Associates, Inc.Katja Leyendecker @ Cycling & Society Symposium Manchester Sep2015
This document presents a summary of Katja Leyendecker's PhD research which compares public perceptions of cycling in Newcastle and Gateshead, UK to Bremen, Germany. The research involves three phases: 1) quantifying cycling rates in both cities, 2) conducting interviews and surveys to understand perceptions of cycling safety and infrastructure, and 3) developing recommendations to improve cycling rates based on differences observed between the two locations. Background information is provided on factors influencing women's cycling rates and the importance of socio-cultural context in comparing transportation modes between cities.
A review of current online bicycle routing portals and their potential role i...
This document evaluates how online bicycle routing portals address safety when providing route recommendations. It reviews 30 pre-trip route planning websites and finds that while most allow users to select routing criteria like distance and time, very few explicitly include safety as a criteria. When safety is included, it is rarely defined or explained. The document concludes that since safety is an important factor in bicyclists' route choices but is largely ignored by current routing tools, more needs to be done to better reflect the complexity of safety considerations and individual preferences in route recommendations.
Women activists’ critique of cycle politics
Prepared for RGS-IGB Annual Conference
31 August 2018
Katja Leyendecker EurIng CEng
Researcher at Northumbria University, UK
Big Data & Smart City Applications
A talk that was given to share experience in building Smart City applications to the city administrators of Dunedin, NZ.
Invest Bavaria Maifest Keynote
Keynote address for the Invest Bavaria #MaifestMobility Conference highting innovative startups demoing their product ! Averon, DSP Concepts, Inc., BCG Digital Ventures, HAAS Alert, EVELOZCITY, LimeBike, Mindtronic AI, TrueFace.ai, Toposens GmbH & Xapix
Qing TRB Poster 16
This paper presents a new Hierarchical Clustering and Grid Mapping (H-G) approach to estimate hourly traffic emissions for an entire city using cellular activity data. The proposed method involves five steps: 1) preprocessing cellular data to generate GPS-labeled records, 2) generating a grid map of the city, 3) using hierarchical clustering to group cell towers and generate centroids, 4) matching movements to grids using shortest path algorithms, and 5) estimating emissions using an output of vehicle miles traveled in each grid. The method was tested using data from a midsize city in China and was able to reveal city-scale traffic dynamics and estimate hourly vehicle emissions across the entire city.
Similar to ScooterLab - Griffin.pptx (20)
New Research Articles 2020 November Issue International Journal of Software E...
New Research Articles 2020 November Issue International Journal of Software E...
Bicycle Infrastructure Improvement Study and Implementation Plan
Bicycle Infrastructure Improvement Study and Implementation Plan
Tutorial on AI-based Analytics in Traffic Management
Tutorial on AI-based Analytics in Traffic Management
Katja leyendecker - presentation to APPCG 29 Dec 2016
Katja leyendecker - presentation to APPCG 29 Dec 2016
City of Chicago Tech Plan 18 Month Progress Update
City of Chicago Tech Plan 18 Month Progress Update
Using gamification to generate citizen input for public transport planning
Using gamification to generate citizen input for public transport planning
The role of open data in driving sustainable mobility in nine smart cities
The role of open data in driving sustainable mobility in nine smart cities
Taking Pedestrian and Bicycle Counting Programs to the Next Level
Taking Pedestrian and Bicycle Counting Programs to the Next Level
Katja Leyendecker @ Cycling & Society Symposium Manchester Sep2015
Katja Leyendecker @ Cycling & Society Symposium Manchester Sep2015
A review of current online bicycle routing portals and their potential role i...
A review of current online bicycle routing portals and their potential role i...
Recently uploaded
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Ozturkcan, S., Berndt, A., & Angelakis, A. (2024). Mending clothing to support sustainable fashion. Presented at the 31st Annual Conference by the Consortium for International Marketing Research (CIMaR), 10-13 Jun 2024, University of Gävle, Sweden.
The binding of cosmological structures by massless topological defects
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
The cost of acquiring information by natural selection
This is a short talk that I gave at the Banff International Research Station workshop on Modeling and Theory in Population Biology. The idea is to try to understand how the burden of natural selection relates to the amount of information that selection puts into the genome.
It's based on the first part of this research paper:
The cost of information acquisition by natural selection
Ryan Seamus McGee, Olivia Kosterlitz, Artem Kaznatcheev, Benjamin Kerr, Carl T. Bergstrom
bioRxiv 2022.07.02.498577; doi: https://doi.org/10.1101/2022.07.02.498577
Equivariant neural networks and representation theory
Or: Beyond linear.
Abstract: Equivariant neural networks are neural networks that incorporate symmetries. The nonlinear activation functions in these networks result in interesting nonlinear equivariant maps between simple representations, and motivate the key player of this talk: piecewise linear representation theory.
Disclaimer: No one is perfect, so please mind that there might be mistakes and typos.
dtubbenhauer@gmail.com
Corrected slides: dtubbenhauer.com/talks.html
Randomised Optimisation Algorithms in DAPHNE
Slides from talk:
Aleš Zamuda: Randomised Optimisation Algorithms in DAPHNE .
Austrian-Slovenian HPC Meeting 2024 – ASHPC24, Seeblickhotel Grundlsee in Austria, 10–13 June 2024
https://ashpc.eu/
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
Pests of Storage_Identification_Dr.UPR.pdf
InIndia-post-harvestlosses-unscientificstorage,insects,rodents,micro-organismsetc.,accountforabout10percentoftotalfoodgrains
Graininfestation
Directdamage
Indirectly
•theexuviae,skin,deadinsects
•theirexcretawhichmakefoodunfitforhumanconsumption
About600speciesofinsectshavebeenassociatedwithstoredgrainproducts
100speciesofinsectpestsofstoredproductscauseeconomiclosses
快速办理(UAM毕业证书)马德里自治大学毕业证学位证一模一样
学校原件一模一样【微信：741003700 】《(UAM毕业证书)马德里自治大学毕业证学位证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。
本公司拥有海外各大学样板无数，能完美还原。
1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700
【主营项目】
一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！
二.真实使馆公证(即留学回国人员证明,不成功不收费)
三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）
四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度)
如果您处于以下几种情况：
◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】
◇面对父母的压力，希望尽快拿到；
◇不清楚认证流程以及材料该如何准备；
◇回国时间很长，忘记办理；
◇回国马上就要找工作，办给用人单位看；
◇企事业单位必须要求办理的
◇需要报考公务员、购买免税车、落转户口
◇申请留学生创业基金
留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
Authoring a personal GPT for your research and practice: How we created the Q...
Thematic analysis in qualitative research is a time-consuming and systematic task, typically done using teams. Team members must ground their activities on common understandings of the major concepts underlying the thematic analysis, and define criteria for its development. However, conceptual misunderstandings, equivocations, and lack of adherence to criteria are challenges to the quality and speed of this process. Given the distributed and uncertain nature of this process, we wondered if the tasks in thematic analysis could be supported by readily available artificial intelligence chatbots. Our early efforts point to potential benefits: not just saving time in the coding process but better adherence to criteria and grounding, by increasing triangulation between humans and artificial intelligence. This tutorial will provide a description and demonstration of the process we followed, as two academic researchers, to develop a custom ChatGPT to assist with qualitative coding in the thematic data analysis process of immersive learning accounts in a survey of the academic literature: QUAL-E Immersive Learning Thematic Analysis Helper. In the hands-on time, participants will try out QUAL-E and develop their ideas for their own qualitative coding ChatGPT. Participants that have the paid ChatGPT Plus subscription can create a draft of their assistants. The organizers will provide course materials and slide deck that participants will be able to utilize to continue development of their custom GPT. The paid subscription to ChatGPT Plus is not required to participate in this workshop, just for trying out personal GPTs during it.
Immersive Learning That Works: Research Grounding and Paths Forward
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
Bob Reedy - Nitrate in Texas Groundwater.pdf
Presented at June 6-7 Texas Alliance of Groundwater Districts Business Meeting
The debris of the ‘last major merger’ is dynamically young
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
ESR spectroscopy in liquid food and beverages.pptx
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
8.Isolation of pure cultures and preservation of cultures.pdf
Isolation of pure culture, its various method.
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
Sharlene Leurig - Enabling Onsite Water Use with Net Zero WaterTexas Alliance of Groundwater Districts
Presented at June 6-7 Texas Alliance of Groundwater Districts Business Meeting11.1 Role of physical biological in deterioration of grains.pdf
Storagedeteriorationisanyformoflossinquantityandqualityofbio-materials.
Themajorcausesofdeteriorationinstorage
•Physical
•Biological
•Mechanical
•Chemical
Storageonlypreservesquality.Itneverimprovesquality.
Itisadvisabletostartstoragewithqualityfoodproduct.Productwithinitialpoorqualityquicklydepreciates
Applied Science: Thermodynamics, Laws & Methodology.pdf
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
Recently uploaded (20)
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
The binding of cosmological structures by massless topological defects
The binding of cosmological structures by massless topological defects
The cost of acquiring information by natural selection
The cost of acquiring information by natural selection
Equivariant neural networks and representation theory
Equivariant neural networks and representation theory
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...
Authoring a personal GPT for your research and practice: How we created the Q...
Authoring a personal GPT for your research and practice: How we created the Q...
Immersive Learning That Works: Research Grounding and Paths Forward
Immersive Learning That Works: Research Grounding and Paths Forward
The debris of the ‘last major merger’ is dynamically young
The debris of the ‘last major merger’ is dynamically young
ESR spectroscopy in liquid food and beverages.pptx
ESR spectroscopy in liquid food and beverages.pptx
8.Isolation of pure cultures and preservation of cultures.pdf
8.Isolation of pure cultures and preservation of cultures.pdf
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
11.1 Role of physical biological in deterioration of grains.pdf
11.1 Role of physical biological in deterioration of grains.pdf
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
GBSN - Biochemistry (Unit 6) Chemistry of Proteins
Applied Science: Thermodynamics, Laws & Methodology.pdf
Applied Science: Thermodynamics, Laws & Methodology.pdf
ScooterLab - Griffin.pptx
- 1. ScooterLab: Let’s think about our future Dr. Greg Griffin, AICP https://scooterlab.utsa.edu/ Think Science, 12Sept2023
- 2. Murtuza Jadliwala (overall lead) Sushil Prasad Raveen Wijewickrama Buddhi Ashan Mallika Kankanamalage Greg Griffin Nico Molina Anindya Maiti Khoi Trinh Acknowledgements Investigators & Students Research Collaborators
- 3. Origin—Street Noise & Bicycling Safety Correlated in Washington, D.C., but not in Austin Griffin, G. P., Hankey, S., Buehler, R., Dai, B., Le, H. T., & Simek, C. (2019). Exploring Street Noise and Bicycle Safety: Initial Evidence from Austin, TX and the Washington, DC Capital Area (No. 19-03944).
- 4. Origin—Crowdsensing Pedestrian Safety and E-scooters Maiti, A., Vinayaga-Sureshkanth, N., Jadliwala, M., Wijewickrama, R., & Griffin, G. (2022, March). Impact of e-scooters on pedestrian safety: A field study using pedestrian crowd-sensing. In PerCom Workshops (pp. 799-805). IEEE.
- 5. Origin—Shared Micromobility Can Reduce Vehicle Traffic, but not only e-scooters Choi, K., Park, H. J., & Griffin, G. P. (2023). Can shared micromobility replace auto travel? Evidence from the US urbanized areas between 2012 and 2019. International Journal of Sustainable Transportation, 1-9.
- 6. What Now? Do e-scooter rental term lengths change travel patterns? Can machine learning support urban policy making? What type of street-level features may increase e-scooter crash risks?
- 7. How is ScooterLab different? The ScooterLab testbed is envisioned as an instrument for the entire research community—not just local teams. Downtown + suburban contexts No private company data agreements Community data privacy and sharing platform
- 9. The ScooterLab Architecture The ScooterLab testbed will comprise of: • Vehicles • Fleet Controller • Research Activities Management Portal (RAMP)
- 10. Demo 10
- 13. Raw Data • Orientation (via Accelerometer) 13 *No scooters or riders wereharmed in obtaining this data.
- 15. Raw Data • GPS – Speed 15
- 16. Raw Data • GPS – Route 16
- 20. ScooterLab is building a new urban sensing platform for improving cities. Multi-disciplinary challenges require collaboration and sharing. C O N T R I B U T I O N
- 21. Data science cannot solve all urban challenges Urban planning addresses wicked problems with inclusiveness, policy, design, and financing. H O W E V E R
- 22. ScooterLab: Let’s think about our future Dr. Greg Griffin, AICP https://scooterlab.utsa.edu/ Think Science, 12Sept2023
Editor's Notes
- What type of data e.g.: time series. Don’t go too much in to details of examples
- Angular Velocity