Globally Optimal Crowdsourcing Quality Management

We study crowdsourcing quality management, that is, given worker responses to a set of tasks, our goal is to jointly estimate the true answers for the tasks, as well as the quality of the workers. Prior work on this problem relies primarily on applying Expectation-Maximization (EM) on the underlying maximum likelihood problem to estimate true answers as well as worker quality. Unfortunately, EM only provides a locally optimal solution rather than a globally optimal one. Other solutions to the problem (that do not leverage EM) fail to provide global optimality guarantees as well. In this paper, we focus on filtering, where tasks require the evaluation of a yes/no predicate, and rating, where tasks elicit integer scores from a finite domain. We design algorithms for finding the global optimal estimates of correct task answers and worker quality for the underlying maximum likelihood problem, and characterize the complexity of these algorithms. Our algorithms conceptually consider all mappings from tasks to true answers (typically a very large number), leveraging two key ideas to reduce, by several orders of magnitude, the number of mappings under consideration, while preserving optimality. We also demonstrate that these algorithms often find more accurate estimates than EM-based algorithms. This paper makes an important contribution towards understanding the inherent complexity of globally optimal crowdsourcing quality management

Truth Discovery in Crowdsourced Detection of Spatial Events

Postprin

Efficient crowdsourcing for multi-class labeling

Crowdsourcing systems like Amazon's Mechanical Turk have emerged as an effective large-scale human-powered platform for performing tasks in domains such as image classification, data entry, recommendation, and proofreading. Since workers are low-paid (a few cents per task) and tasks performed are monotonous, the answers obtained are noisy and hence unreliable. To obtain reliable estimates, it is essential to utilize appropriate inference algorithms (e.g. Majority voting) coupled with structured redundancy through task assignment. Our goal is to obtain the best possible trade-off between reliability and redundancy. In this paper, we consider a general probabilistic model for noisy observations for crowd-sourcing systems and pose the problem of minimizing the total price (i.e. redundancy) that must be paid to achieve a target overall reliability. Concretely, we show that it is possible to obtain an answer to each task correctly with probability 1-ε as long as the redundancy per task is O((K/q) log (K/ε)), where each task can have any of the $K$ distinct answers equally likely, q is the crowd-quality parameter that is defined through a probabilistic model. Further, effectively this is the best possible redundancy-accuracy trade-off any system design can achieve. Such a single-parameter crisp characterization of the (order-)optimal trade-off between redundancy and reliability has various useful operational consequences. Further, we analyze the robustness of our approach in the presence of adversarial workers and provide a bound on their influence on the redundancy-accuracy trade-off. Unlike recent prior work [GKM11, KOS11, KOS11], our result applies to non-binary (i.e. K>2) tasks. In effect, we utilize algorithms for binary tasks (with inhomogeneous error model unlike that in [GKM11, KOS11, KOS11]) as key subroutine to obtain answers for K-ary tasks. Technically, the algorithm is based on low-rank approximation of weighted adjacency matrix for a random regular bipartite graph, weighted according to the answers provided by the workers.National Science Foundation (U.S.

Developing Perfectly Matched Layer method to solve Heat Equation numerically

Perfectly Matched Layer (PML) techniques, although having been studied extensively to study systems with nonrestrictive boundaries in many physical fields, are not readily adaptable to the study of thermodynamic systems governed by the heat equation. Using the explicit finite difference method, we can easily describe systems with perfectly absorbing or reflecting boundaries. These, however, are highly idealized physical states, so we have begun extending our abilities to simulating more realistic physical situations by defining arbitrary spatial differential operators, which govern how heat at the boundaries of the system of interest propagates. As a first attempt, we transformed the linear spatial domain to a trigonometric domain to combat reflection from boundaries, but this is quite crude. We then approached the problem using Fourier Transforms in order to define the problem in a heat distribution\u27s frequency space, damp excessive heat past the boundaries, and transform back to position space. Initial results using the finite difference method verify the current computer simulation\u27s ability to solve problems with ideal circumstances, and the development of a PML method which accurately simulates nonrestrictive boundaries and can be easily translated into a computer algorithm is in progress

HarvardX and MITx: Two Years of Open Online Courses Fall 2012-Summer 2014

What happens when well-known universities offer online courses, assessments, and certificates of completion for free? Early descriptions of Massive Open Online Courses (MOOCs) have emphasized large enrollments, low certification rates, and highly educated registrants. We use data from two years and 68 open online courses offered by Harvard University (via HarvardX) and MIT (via MITx) to broaden the scope of answers to this question. We describe trends over this two-year span, depict participant intent using comprehensive survey instruments, and chart course participation pathways using network analysis. We find that overall participation in our MOOCs remains substantial and that the average growth has been steady. We explore how diverse audiences — including explorers, teachers-as-learners, and residential students — provide opportunities to advance the principles on which HarvardX and MITx were founded: access, research, and residential education

Effect of intonation on Cantonese lexical tones

In tonal languages, there are potential conflicts between the F0-based changes due to the coexistence of intonation and lexical tones. In the present study, the interaction of tone and intonation in Cantonese was examined using acoustic and perceptual analyses. The acoustic patterns of tones at the initial, medial, and final positions of questions and statements were measured. Results showed that intonation affects both the F0 level and contour, while the duration of the six tones varied as a function of positions within intonation contexts. All six tones at the final position of questions showed rising F0 contour, regardless of their canonical form. Listeners were overall more accurate in the identification of tones presented within the original carrier than of the same tones in isolation. However, a large proportion of tones 33, 21, 23, and 22 at the final position of questions were misperceived as tone 25 both within the original carrier and as isolated words. These results suggest that although the intonation context provided cues for correct tone identification, the intonation-induced changes in F0 contour cannot always be perceptually compensated for, resulting in some erroneous perception of the identity of Cantonese tone. © 2006 Acoustical Society of America.published_or_final_versio

Mapping the beach beneath the street:digital cartography for the playable city

Maps are an important component within many of the playful and gameful experiences designed to turn cities into a playable infrastructures. They take advantage of the fact that the technology used for obtaining accurate spatial information, such as GPS receivers and magnetometers (digital compasses), are now so wide-spread that they are considered as ‘standard’ sensors on mobile phones, which are themselves ubiquitous. Interactive digital maps, therefore, are are widely used by the general public for a variety of purposes. However, despite the rich design history of cartography digital maps typically exhibit a dominant aesthetic that has been de-signed to serve the usability and utility requirements of turn-by-turn urban navigation, which is itself driven by the proliferation of in-car and personal navigation services. The navigation aesthetic is now widespread across almost all spatial applications, even where a be-spoke cartographic product would be better suited. In this chapter we seek to challenge this by exploring novel neo-cartographic ap-proaches to making maps for use within playful and gameful experi-ences designed for the cities. We will examine the potential of de-sign approaches that can producte not only more aesthetically pleasing maps, but also offer the potential for influencing user be-haviour, which can be used to promote emotional engagement and exploration in playable city experiences

Affective Man-Machine Interface: Unveiling human emotions through biosignals

As is known for centuries, humans exhibit an electrical profile. This profile is altered through various psychological and physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such a MMI requires the correct classification of biosignals to emotion classes. This chapter starts with an introduction on biosignals for emotion detection. Next, a state-of-the-art review is presented on automatic emotion classification. Moreover, guidelines are presented for affective MMI. Subsequently, a research is presented that explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 21 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for parallel processing of multiple biosignals

Uncomplicated pharyngitis due to family transmission of hypervirulent Klebsiella pneumoniae

We describe two cases of uncomplicated pharyngitis caused by hypervirulent Klebsiella pneumoniae (hvKp) in a family, initially in an immunocompetent adolescent, followed by possible household spread resulting in similar presentations in the patient's parent. Genomic analysis confirmed hvKp from the two cases were genetically identical and typed as K2-ST3252. Nasopharyngeal carriage and respiratory secretion/droplet may play an important yet underrecognized role in the transmission of hvKp. Enhancing routine screening for hvKp in the upper respiratory culture, followed by genotyping provides an effective pathway for early diagnosis