Physical Sciences and Mathematics Commons^™

Community Discussion: Catch The King Tide, Amy Matzke-Fawcett

News Items

No abstract provided.

Community Invited To Discuss King Tide Event, Amy Matzke-Fawcett

News Items

No abstract provided.

Introducing People With Asd To Crowd Work, Kotaro Hara, Jeffrey P. Bigham

Research Collection School Of Computing and Information Systems

Adults with Autism Spectrum Disorders (ASD) are unemployed at a high rate, in part because the constraints and expectations of traditional employment can be difficult for them. In this paper, we report on our work in introducing people with ASD to remote work on a crowdsourcing platform and a prototype tool we developed by working with participants. We conducted a six-week long user-centered design study with three participants with ASD. The early stage of the study focused on assessing the abilities of our participants to search and work on micro-tasks available on the crowdsourcing market. Based on our preliminary findings, …

Grading Complex Tasks Through Crowdsourcing, Lingyu Lyu

Commonwealth Computational Summit

Crowdsourcing provides huge opportunities and scalability solutions for grading large scale tasks, such as MOOCs.

Reliability and quality of graders and crowdsourced data are challenging issues.

Workers might give random grades, which are spam; or provide biased grades, which need to be corrected.

The budget for hiring graders is limited, in many cases.

Effect Of Label Noise On The Machine-Learned Classification Of Earthquake Damage, Jared Frank, Umaa Rebbapragada, James Bialas, Thomas Oommen, Timothy C. Havens

Michigan Tech Publications

Automated classification of earthquake damage in remotely-sensed imagery using machine learning techniques depends on training data, or data examples that are labeled correctly by a human expert as containing damage or not. Mislabeled training data are a major source of classifier error due to the use of imprecise digital labeling tools and crowdsourced volunteers who are not adequately trained on or invested in the task. The spatial nature of remote sensing classification leads to the consistent mislabeling of classes that occur in close proximity to rubble, which is a major byproduct of earthquake damage in urban areas. In this study, …

Measuring Fine-Grained Metro Interchange Time Via Smartphones, Weixi Gu, Kai Zhang, Zimu Zhou, Ming Jin, Yuxun Zhou, Xi Liu, Costas J. Spanos, Zuo-Jun (Max) Shen, Wei-Hua Lin, Lin Zhang

Research Collection School Of Computing and Information Systems

High variability interchange times often significantly affect the reliability of metro travels. Fine-grained measurements of interchange times during metro transfers can provide valuable insights on the crowdedness of stations, usage of station facilities and efficiency of metro lines. Measuring interchange times in metro systems is challenging since agentoperated systems like automatic fare collection systems only provide coarse-grained trip information and popular localization services like GPS are often inaccessible underground. In this paper, we propose a smartphone-based interchange time measuring method from the passengers’ perspective. It leverages low-power sensors embedded in modern smartphones to record ambient contextual features, and utilizes a …

Evaluating Relevance And Reliability Of Twitter Data For Risk Communication, Xiaohui Liu

Dissertations

While Twitter has been touted to provide up-to-date information about hazard events, the relevance and reliability of tweets is yet to be tested. This research examined the relevance and reliability of risk information extracted from Twitter during the 2013 Colorado floods using five different approaches. The first approach examined the relationship between tweet volume and precipitation amount. The second approach explored the relationship between geo-tagged tweets and degree of damage. In the third approach, the spatiotemporal distribution of tweets was compared with flood extent. In the fourth approach, risk information from tweets were compared with survey responses obtained in a …

Smartphone Sensing Meets Transport Data: A Collaborative Framework For Transportation Service Analytics, Yu Lu, Archan Misra, Wen Sun, Huayu Wu

Research Collection School Of Computing and Information Systems

We advocate for and introduce TRANSense, a framework for urban transportation service analytics that combines participatory smartphone sensing data with city-scale transportation-related transactional data (taxis, trains etc.). Our work is driven by the observed limitations of using each data type in isolation: (a) commonly-used anonymous city-scale datasets (such as taxi bookings and GPS trajectories) provide insights into the aggregate behavior of transport infrastructure, but fail to reveal individual-specific transport experiences (e.g., wait times in taxi queues); while (b) mobile sensing data can capture individual-specific commuting-related activities, but suffers from accuracy and energy overhead challenges due to usage artefacts and lack …

The Mobile Monitoring Of Particulate Matter Through Wearable Sensors And Their Influence On Students' Environmental Attitudes, Joseph M. Abbate

DePaul Discoveries

While we have a comprehensive understanding of air pollutants, and their spatiotemporal characteristics across global, and even regional, scales, we are quite limited in our capacity to monitor neighborhood-scale emissions. The mobile monitoring of air pollution is a growing field, prospectively filling in these gaps while personalizing air quality-based tools and risk assessment. In the present study, we developed wearable sensors for particulate matter (PM); and through a citizen science approach, students of partnering Chicago schools monitored PM concentrations throughout their commutes over a five-day period. While their recorded findings would be used to explore the relationship between PM concentrations …

Crowdsourced Delphis: Designing Solutions To Complex Environmental Problems With Broad Stakeholder Participation, Sarah Coleman, Stephanie Hurley, Christopher Koliba, Asim Zia

College of Agriculture and Life Sciences Faculty Publications

There is a well-established need for increased stakeholder participation in the generation of adaptive management approaches and specific solutions to complex environmental problems. However, integrating participant feedback into current science, research, and decision-making processes is challenging. This paper presents a novel approach that marries a rigorous Delphi method, borrowed from policy and organizational sciences, with contemporary “crowdsourcing” to address the complex problems of water pollution exacerbated by climate change in the Lake Champlain Basin. In an online Delphi forum that occurred over a six-week period during the Spring of 2014, fifty-three participants proposed and commented on adaptive solutions to address …

Crowdsourced Delphis: Designing Solutions To Complex Environmental Problems With Broad Stakeholder Participation, Sarah Coleman, Stephanie Hurley, Christopher Koliba, Asim Zia

College of Agriculture and Life Sciences Faculty Publications

There is a well-established need for increased stakeholder participation in the generation of adaptive management approaches and specific solutions to complex environmental problems. However, integrating participant feedback into current science, research, and decision-making processes is challenging. This paper presents a novel approach that marries a rigorous Delphi method, borrowed from policy and organizational sciences, with contemporary “crowdsourcing” to address the complex problems of water pollution exacerbated by climate change in the Lake Champlain Basin. In an online Delphi forum that occurred over a six-week period during the Spring of 2014, fifty-three participants proposed and commented on adaptive solutions to address …

Sustainability Standards And Stakeholder Engagement: Lessons From Carbon Markets, Hans Rawhouser, Michael E. Cummings, Alfred Marcus

Management, Entrepreneurship and Technology Faculty Publications

Stakeholders play an increasingly active role in private governance, including development of standards for measuring sustainability. Building on prior studies focused on standards and stakeholder engagement, we use an innovation management theoretical lens to compare stakeholder engagement and standards developed in two carbon markets: the Climate Action Reserve and the U.N.’s Clean Development Mechanism. We develop and test hypotheses regarding how different processes of stakeholder engagement in standard development affect the number, identity, and age of stakeholders involved, as well as the variation and quality of the resulting standards. In doing so, we contribute to the growing literature on stakeholder …

Crowd Data Analytics And Optimization, Habibur Rahman

Computer Science and Engineering Dissertations

Crowdsourcing can be defined as outsourcing with crowd, where crowd refers to the online workers who are willing to complete simple tasks for small monetary compensation. The overwhelming reach of internet has enabled us to exploit crowd in an unprecedented way. Crowdsourcing, nowadays, is considered as a tool to solve both simple tasks (such as labeling ground truth, image recognition etc.) and complex tasks (such as collaborative writing, citizen journalism etc.). Furthermore, it is also used to solve computational problems such as Entity Resolution, Top-k, Group-by etc. While crowdsourcing provides us with plenty of opportunities, it also presents us with …

A Probabilistic Approach To Crowdsourcing Pareto-Optimal Object Finding By Pairwise Comparisons, Nigesh Shakya

Computer Science and Engineering Theses

This is an extended study on crowdsourcing Pareto-Optimal Object Finding by Pairwise Comparisons. The prior study on the same topic demonstrate the framework and algorithms used to determine all the Pareto-Optimal objects with the goal of asking the fewest possible questions to the crowd. One of the drawbacks in that approach is it fails to incorporate every inputs given by the crowd and is biased towards the majority. We have developed an approach which represent the inputs provided by users as probabilistic values rather than a concrete one. The goal of this study is to find the ranks of the …

Crowdsourcing For Decision Making With Analytic Hierarchy Process, Ishwor Timilsina

Computer Science and Engineering Theses

Analytic Hierarchy Process (AHP) is a Multiple-Criteria Decision-Making MCDM) technique devised by Thomas L. Saaty. In AHP, all the pairwise comparisons between criteria and alternatives in terms of each criterion are used to calculate global rankings of the alternatives. In the classic AHP, the comparisons are provided collectively by a small group of decision makers. We have formulated a technique to incorporate crowd-sourced inputs into AHP. Instead of taking just one comparison for each pair of criteria or alternatives, multiple users are asked to provide inputs. As in AHP, our approach also supports consistency check of the comparison matrices. The …

Detecting Malicious Campaigns In Crowdsourcing Platforms, Hongkyu Choi

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Crowdsourcing sites such as Mechanical Turk and Crowdflower provide a marketplace where requesters create tasks and recruit workers, who may perform certain tasks in order to get financial compensation. Anyone in the world can be a requester and/or a worker as long as he/she has the Internet connection. Crowdsourcing creates a new way to solve various tasks by using “human computation power”. However, crowdsourcing has been misused by malicious requesters and unethical workers for account generation, search engine optimization, content and link generation, ad posting and spam mailing, and social network linking. It creates new threats to the Web system. …