Jan Dirk Schmöcker, Jun Ji, Fajar Prawira Belgiawan, Nobuhiro Uno
We analyse evacuation decisions with data from a survey among 10,384 survivers of the 2011 Great East Japan earthquake. The decisions of individuals and families to evacuate or stay are influenced by the Tsunami warning system as well as the behaviour of the surrounding population which is modelled as the percentage of persons evacuating from a city. We formulate binary choice models with “field effects” where we try to control for the endogeneity with a 2-stage model approach. Our results quantify the field effect and suggest that with each minute the Tsunami warning arrives later, on average 3% less of the population are evacuating and surviving. We also show the importance of other variables, in particular the preparedness measures such as signage and evacuation drills.
{"title":"Evacuation Decisions during the Great East Japan Earthquake","authors":"Jan Dirk Schmöcker, Jun Ji, Fajar Prawira Belgiawan, Nobuhiro Uno","doi":"10.32866/001c.77365","DOIUrl":"https://doi.org/10.32866/001c.77365","url":null,"abstract":"We analyse evacuation decisions with data from a survey among 10,384 survivers of the 2011 Great East Japan earthquake. The decisions of individuals and families to evacuate or stay are influenced by the Tsunami warning system as well as the behaviour of the surrounding population which is modelled as the percentage of persons evacuating from a city. We formulate binary choice models with “field effects” where we try to control for the endogeneity with a 2-stage model approach. Our results quantify the field effect and suggest that with each minute the Tsunami warning arrives later, on average 3% less of the population are evacuating and surviving. We also show the importance of other variables, in particular the preparedness measures such as signage and evacuation drills.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":"177 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135643604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Paul Tautorat, Taha Ramazanoğlu, T. Schmidt, B. Steffen
Swiss dairy products are globally sought after but their production requires relatively large amounts of process heat, often generated from oil and gas. Low-carbon electricity- and biomass-based solutions exist but were often regarded as economically not viable in the past. Therefore, we evaluate the economic viability of low-carbon technologies for the Swiss dairy industry for scenarios of low and high fossil fuel prices in Europe, and its sensitivity to emission cost pathways. Results show a clear cost advantage of heat pumps and biomass boilers going forward, driven particularly by expected future gas prices.
{"title":"Energy Transitions in the Food Sector: The Economic Viability of Low-carbon Technologies in the Swiss Dairy Industry","authors":"Paul Tautorat, Taha Ramazanoğlu, T. Schmidt, B. Steffen","doi":"10.32866/001c.75416","DOIUrl":"https://doi.org/10.32866/001c.75416","url":null,"abstract":"Swiss dairy products are globally sought after but their production requires relatively large amounts of process heat, often generated from oil and gas. Low-carbon electricity- and biomass-based solutions exist but were often regarded as economically not viable in the past. Therefore, we evaluate the economic viability of low-carbon technologies for the Swiss dairy industry for scenarios of low and high fossil fuel prices in Europe, and its sensitivity to emission cost pathways. Results show a clear cost advantage of heat pumps and biomass boilers going forward, driven particularly by expected future gas prices.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43648356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The COVID-19 pandemic resulted in a sudden shift to working at home. People stopped commuting to their jobs. We fielded two surveys in New Jersey during the pandemic and included questions on what respondents did with time saved from not commuting as well as which activities they wished to see continue after the pandemic subsides. Key results include that a majority of respondents reported spending more time with their family, almost half spent time watching TV or were on the internet, a large share slept later, and many walked more for exercise. We also queried respondents on activities they would like to continue after the pandemic is over, with nearly half desiring to work at home at least some of the time and about a third desiring to commute less. We also present results by gender, finding some differences in time use and preferences.
{"title":"What do People want to do instead of Commuting to Work?","authors":"R. Noland, H. Younes, Wenwen Zhang","doi":"10.32866/001c.75441","DOIUrl":"https://doi.org/10.32866/001c.75441","url":null,"abstract":"The COVID-19 pandemic resulted in a sudden shift to working at home. People stopped commuting to their jobs. We fielded two surveys in New Jersey during the pandemic and included questions on what respondents did with time saved from not commuting as well as which activities they wished to see continue after the pandemic subsides. Key results include that a majority of respondents reported spending more time with their family, almost half spent time watching TV or were on the internet, a large share slept later, and many walked more for exercise. We also queried respondents on activities they would like to continue after the pandemic is over, with nearly half desiring to work at home at least some of the time and about a third desiring to commute less. We also present results by gender, finding some differences in time use and preferences.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43001294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Shuman, Awad Abdelhalim, Anson F. Stewart, Kayleigh B Campbell, Mira Patel, Inés Sánchez de Madariaga, Jinhua Zhao
Studies in the literature have found significant differences in travel behavior by gender on public transit that are largely attributable to household and care responsibilities falling disproportionately on women. While the majority of studies have relied on survey and qualitative data to assess “mobility of care”, we propose a novel data-driven workflow utilizing transit fare card transactions, name-based gender inference, and geospatial analysis to identify mobility of care trip making. We find that the share of women travelers trip-chaining in the direct vicinity of mobility of care places of interest is 10% - 15% higher than men.
{"title":"Can Mobility of Care Be Identified From Transit Fare Card Data? A Case Study In Washington D.C.","authors":"D. Shuman, Awad Abdelhalim, Anson F. Stewart, Kayleigh B Campbell, Mira Patel, Inés Sánchez de Madariaga, Jinhua Zhao","doi":"10.32866/001c.75352","DOIUrl":"https://doi.org/10.32866/001c.75352","url":null,"abstract":"Studies in the literature have found significant differences in travel behavior by gender on public transit that are largely attributable to household and care responsibilities falling disproportionately on women. While the majority of studies have relied on survey and qualitative data to assess “mobility of care”, we propose a novel data-driven workflow utilizing transit fare card transactions, name-based gender inference, and geospatial analysis to identify mobility of care trip making. We find that the share of women travelers trip-chaining in the direct vicinity of mobility of care places of interest is 10% - 15% higher than men.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45528384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Census data is crucial to understand energy and environmental justice outcomes such as poor air quality which disproportionately impact people of color in the U.S. Wwith the advent of sophisticated personal datasets and analysis, Census Bureau is considering adding top-down noise (differential privacy) and post-processing 2020 census data to reduce the risk of identification of individual respondents. Using 2010 demonstration census and pollution data, I find that compared to the original census, differentially private (DP) census significantly changes ambient pollution exposure in areas with sparse populations. White Americans have lowest variability, followed by Latinos, Asian, and Black Americans. DP underestimates pollution disparities for SO2 and PM2.5 while overestimates the pollution disparities for PM10.
{"title":"How Differential Privacy Will Affect Estimates of Air Pollution Exposure and Disparities in the United States","authors":"Madalsa Singh","doi":"10.32866/001c.74975","DOIUrl":"https://doi.org/10.32866/001c.74975","url":null,"abstract":"Census data is crucial to understand energy and environmental justice outcomes such as poor air quality which disproportionately impact people of color in the U.S. Wwith the advent of sophisticated personal datasets and analysis, Census Bureau is considering adding top-down noise (differential privacy) and post-processing 2020 census data to reduce the risk of identification of individual respondents. Using 2010 demonstration census and pollution data, I find that compared to the original census, differentially private (DP) census significantly changes ambient pollution exposure in areas with sparse populations. White Americans have lowest variability, followed by Latinos, Asian, and Black Americans. DP underestimates pollution disparities for SO2 and PM2.5 while overestimates the pollution disparities for PM10.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44087525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, intraday correlations between station centralities and ridership at stations of the Athens metro system in Greece are explored. An unweighted L-space representation of the physical metro network is developed, and degree, closeness and betweenness are selected as station centrality measures. Hourly smart-card data are used for representing passenger flows. For station classification, principal component analysis and k-means clustering are utilized. The findings suggest that centrality and ridership usually move in opposite directions, morning peak-hour boardings are completely uncorrelated with station centrality, and metro stations can be classified as ‘central destinations’, ‘averagely central origins’, and ‘underutilized peripheral stations’.
{"title":"How is Intraday Metro Ridership related to Station Centrality in Athens, Greece?","authors":"Athanasios Kopsidas, K. Kepaptsoglou","doi":"10.32866/001c.75171","DOIUrl":"https://doi.org/10.32866/001c.75171","url":null,"abstract":"In this study, intraday correlations between station centralities and ridership at stations of the Athens metro system in Greece are explored. An unweighted L-space representation of the physical metro network is developed, and degree, closeness and betweenness are selected as station centrality measures. Hourly smart-card data are used for representing passenger flows. For station classification, principal component analysis and k-means clustering are utilized. The findings suggest that centrality and ridership usually move in opposite directions, morning peak-hour boardings are completely uncorrelated with station centrality, and metro stations can be classified as ‘central destinations’, ‘averagely central origins’, and ‘underutilized peripheral stations’.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70181640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-11DOI: 10.48550/arXiv.2305.06993
J. Opitz
The Smatch metric is a popular method for evaluating graph distances, as is necessary, for instance, to assess the performance of semantic graph parsing systems. However, we observe some issues in the metric that jeopardize meaningful evaluation. E.g., opaque pre-processing choices can affect results, and current graph-alignment solvers do not provide us with upper-bounds. Without upper-bounds, however, fair evaluation is not guaranteed. Furthermore, adaptions of Smatch for extended tasks (e.g., fine-grained semantic similarity) are spread out, and lack a unifying framework. For better inspection, we divide the metric into three modules: pre-processing, alignment, and scoring. Examining each module, we specify its goals and diagnose potential issues, for which we discuss and test mitigation strategies. For pre-processing, we show how to fully conform to annotation guidelines that allow structurally deviating but valid graphs. For safer and enhanced alignment, we show the feasibility of optimal alignment in a standard evaluation setup, and develop a lossless graph compression method that shrinks the search space and significantly increases efficiency. For improved scoring, we propose standardized and extended metric calculation of fine-grained sub-graph meaning aspects. Our code is available at https://github.com/flipz357/smatchpp
{"title":"SMATCH++: Standardized and Extended Evaluation of Semantic Graphs","authors":"J. Opitz","doi":"10.48550/arXiv.2305.06993","DOIUrl":"https://doi.org/10.48550/arXiv.2305.06993","url":null,"abstract":"The Smatch metric is a popular method for evaluating graph distances, as is necessary, for instance, to assess the performance of semantic graph parsing systems. However, we observe some issues in the metric that jeopardize meaningful evaluation. E.g., opaque pre-processing choices can affect results, and current graph-alignment solvers do not provide us with upper-bounds. Without upper-bounds, however, fair evaluation is not guaranteed. Furthermore, adaptions of Smatch for extended tasks (e.g., fine-grained semantic similarity) are spread out, and lack a unifying framework. For better inspection, we divide the metric into three modules: pre-processing, alignment, and scoring. Examining each module, we specify its goals and diagnose potential issues, for which we discuss and test mitigation strategies. For pre-processing, we show how to fully conform to annotation guidelines that allow structurally deviating but valid graphs. For safer and enhanced alignment, we show the feasibility of optimal alignment in a standard evaluation setup, and develop a lossless graph compression method that shrinks the search space and significantly increases efficiency. For improved scoring, we propose standardized and extended metric calculation of fine-grained sub-graph meaning aspects. Our code is available at https://github.com/flipz357/smatchpp","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":"1 1","pages":"1550-1562"},"PeriodicalIF":0.0,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46859672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper evaluates a strategy that would target sales of internal combustion vehicles driven at high annual mileage for displacement by electric vehicles at the time of initial sale. Using the 2017 National Household Travel Survey data, we observe that the top 20% of light duty vehicles by kilometers traveled generate 46% of the annual greenhouse gas emissions. Displacing the sale of a combustion engine vehicle in the top mileage quintile with an electric vehicle would reduce annual greenhouse gas emissions and certain criteria pollutants by more than 15 times as much as displacing a vehicle in the bottom mileage quintile.
{"title":"Emissions Reductions from Electrifying High-Mileage Vehicles","authors":"Zack Aemmer, Daniel Malarkey, D. MacKenzie","doi":"10.32866/001c.75133","DOIUrl":"https://doi.org/10.32866/001c.75133","url":null,"abstract":"This paper evaluates a strategy that would target sales of internal combustion vehicles driven at high annual mileage for displacement by electric vehicles at the time of initial sale. Using the 2017 National Household Travel Survey data, we observe that the top 20% of light duty vehicles by kilometers traveled generate 46% of the annual greenhouse gas emissions. Displacing the sale of a combustion engine vehicle in the top mileage quintile with an electric vehicle would reduce annual greenhouse gas emissions and certain criteria pollutants by more than 15 times as much as displacing a vehicle in the bottom mileage quintile.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41486509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-09DOI: 10.48550/arXiv.2305.05474
Aleksandra Chrabrowa, Tsimur Hadeliya, D. Kajtoch, Robert Mroczkowski, Piotr Rybak
Novel intent discovery automates the process of grouping similar messages (questions) to identify previously unknown intents. However, current research focuses on publicly available datasets which have only the question field and significantly differ from real-life datasets. This paper proposes methods to improve the intent discovery pipeline deployed in a large e-commerce platform. We show the benefit of pre-training language models on in-domain data: both self-supervised and with weak supervision. We also devise the best method to utilize the conversational structure (i.e., question and answer) of real-life datasets during fine-tuning for clustering tasks, which we call Conv. All our methods combined to fully utilize real-life datasets give up to 33pp performance boost over state-of-the-art Constrained Deep Adaptive Clustering (CDAC) model for question only. By comparison CDAC model for the question data only gives only up to 13pp performance boost over the naive baseline.
{"title":"Going beyond research datasets: Novel intent discovery in the industry setting","authors":"Aleksandra Chrabrowa, Tsimur Hadeliya, D. Kajtoch, Robert Mroczkowski, Piotr Rybak","doi":"10.48550/arXiv.2305.05474","DOIUrl":"https://doi.org/10.48550/arXiv.2305.05474","url":null,"abstract":"Novel intent discovery automates the process of grouping similar messages (questions) to identify previously unknown intents. However, current research focuses on publicly available datasets which have only the question field and significantly differ from real-life datasets. This paper proposes methods to improve the intent discovery pipeline deployed in a large e-commerce platform. We show the benefit of pre-training language models on in-domain data: both self-supervised and with weak supervision. We also devise the best method to utilize the conversational structure (i.e., question and answer) of real-life datasets during fine-tuning for clustering tasks, which we call Conv. All our methods combined to fully utilize real-life datasets give up to 33pp performance boost over state-of-the-art Constrained Deep Adaptive Clustering (CDAC) model for question only. By comparison CDAC model for the question data only gives only up to 13pp performance boost over the naive baseline.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":"1 1","pages":"895-911"},"PeriodicalIF":0.0,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45021328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We propose a solution method for online vehicle routing, which integrates a machine learning routine to improve tours’ quality. Our optimization model is based on the Bertsimas et al. (2019) re-optimization approach. Two separate routines are developed. The first one uses a neural network to produce realistic pick-up times for the customers to serve. The second one relies on Q-learning in addition to random walks for the construction of the backbone graph corresponding to the instance problem of each time step. The second routine gives improved results compared to the original approach.
{"title":"Online Large-Scale Taxi Assignment: Optimization and Learning","authors":"Omar Rifki, Thierry Garaix","doi":"10.32866/001c.74765","DOIUrl":"https://doi.org/10.32866/001c.74765","url":null,"abstract":"We propose a solution method for online vehicle routing, which integrates a machine learning routine to improve tours’ quality. Our optimization model is based on the Bertsimas et al. (2019) re-optimization approach. Two separate routines are developed. The first one uses a neural network to produce realistic pick-up times for the customers to serve. The second one relies on Q-learning in addition to random walks for the construction of the backbone graph corresponding to the instance problem of each time step. The second routine gives improved results compared to the original approach.","PeriodicalId":73025,"journal":{"name":"Findings (Sydney (N.S.W.)","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48844192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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