Miracle-dz/UniFAR-FTUs huggingface dataset:
A woman's place: negative binomial analysis of sex-based discrimination complaints by gender composition of state workforce

Recommended Citation Oehmen, Nicole Marie. "A woman's place: negative binomial analysis of sex-based discrimination complaints by gender composition of state workforce. has been approved by the Examining Committee for the thesis requirement for the Master of Arts degree in Sociology at the May 2015 graduation. i ii ACKNOWLEDGEMENTS I would like to express my most sincere gratitude to my thesis supervisor, Dr. Sarah Harkness, for her incredibly useful remarks, assistance, encouragement, and unwavering support during the entire process. Furthermore, I would like to thank Dr. Marina Zaloznaya for her helpful comments and guidance along the way. I am also very grateful to Dr. Mary Noonan for her insightful feedback and help with clarification. I would also like to thank my friends, family, and loved ones for their constant reassurance, especially my loving, understanding, and supportive partner, Stephen Shaun Bouxsein, and my wonderful friends in the Department of Sociology. I am forever grateful for your time, caring, and patience. ABSTRACT Continued research on sex-based discrimination is necessary given the pervasiveness of the problem and well-documented adverse outcomes for those who experience it. One widely studied contributor to sex-based discrimination in the workplace is gender composition. While a litany of studies have predicted a linear relationship between the proportion of men in a workforce and the incidence of sex discrimination, newer research has indicated a curvilinear relationship. As the state workforce represents both an aggregation of its institutions and the broader environment in which these institutions exist, state-level analysis is needed to resolve this discrepancy. However, past studies have largely been conducted at the institutional or work-group level and no research to date has explored the effect the gender composition of a state's workforce may have on sex-based discrimination filings. Using a unique dataset compiled from the Equal Employment Opportunity Commission, Bureau of Labor Statistics, and United States Census Bureau for the years 2009-2012, I find that the state is indeed an important locus of inquiry with regard to sex discrimination outcomes. Negative binomial analysis of state sex-based discrimination filings on gender composition of state workforce reveals a curvilinear relationship, with the least filings in the most balanced and the most male-dominated state workforces, net of all controls. iv PUBLIC ABSTRACT Sex-based discrimination remains a major problem in workplaces today, with severe outcomes for those who experience it. It is therefore important to understand the conditions under which sex-based discrimination occurs and …
Measuring Situation Awareness through Automated Communication Analysis

Acknowledgements Work on this paper was partially supported by a Phase II Small Business Innovative Research Contract (N00014-05-C-0438) awarded to Cheryl Bolstad and Peter Foltz from the Office of Naval Research (ONR). The views and conclusions contained herein, however, are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the ONR, U. S. Navy, Department of Defense, U. S. Government, or the organizations with which the authors are affiliated. We thank an anonymous reviewer for helpful suggestions on improving this chapter.
Feature allocations, probability functions, and paintboxes

The problem of inferring a clustering of a data set has been the subject of much research in Bayesian analysis, and there currently exists a solid mathematical foundation for Bayesian approaches to clustering. In particular, the class of probability distributions over partitions of a data set has been characterized in a number of ways, including via exchangeable partition probability functions (EPPFs) and the Kingman paintbox. Here, we develop a generalization of the clustering problem, called feature allocation, where we allow each data point to belong to an arbitrary, non-negative integer number of groups, now called features or topics. We define and study an “exchangeable feature probability function” (EFPF)—analogous to the EPPF in the clustering setting—for certain types of feature models. Moreover, we introduce a “feature paintbox” characterization—analogous to the Kingman paintbox for clustering—of the class of exchangeable feature models. We provide a further characterization of the subclass of feature allocations that have EFPF representations.
User Modeling as a goal in itself: an Artificial Companion for the Elderly

User modeling tends to be seen as a “means to an end”: something that is needed to adapt systems to users, and that we want to make as painless and effortless for the users as possible. This paper describes how user modeling can be a goal in itself, a pleasurable activity that provides users with somebody to have meaningful conversations with. The example of interactive Television as an artificial companion for the elderly is explored. In addition, it is shown how techniques for knowledge editing as put forward by the Natural Language Generation community can help to make user modeling easy and pleasant.
Chianti: A Prototype Change Impact Analysis Tool for Java

This paper reports on the design and implementation of Chianti, a change impact analysis tool for Java that is implemented in the context of the Eclipse environment. Chianti analyzes two versions of an application and decomposes their difference into a set of atomic changes. Change impact is reported in terms of affected tests whose execution behavior may have been modified by the applied changes. For each affected test, Chianti also determines a set of affecting changes that were responsible for the test’s modified behavior. We evaluated Chianti on 6 months of data fromM. Ernst’s Daikon system, and found that, on average, 62.4% of the tests is affected. Furthermore, each affected test, on average, is affected by only 5.6% of the atomic changes. These findings suggest that change impact analysis is a promising technique for assisting developerswith programunderstanding and debugging.
Balanced Input Allows Optimal Encoding in a Stochastic Binary Neural Network Model: An Analytical Study

Recent neurophysiological experiments have demonstrated a remarkable effect of attention on the underlying neural activity that suggests for the first time that information encoding is indeed actively influenced by attention. Single cell recordings show that attention reduces both the neural variability and correlations in the attended condition with respect to the non-attended one. This reduction of variability and redundancy enhances the information associated with the detection and further processing of the attended stimulus. Beyond the attentional paradigm, the local activity in a neural circuit can be modulated in a number of ways, leading to the general question of understanding how the activity of such circuits is sensitive to these relatively small modulations. Here, using an analytically tractable neural network model, we demonstrate how this enhancement of information emerges when excitatory and inhibitory synaptic currents are balanced. In particular, we show that the network encoding sensitivity -as measured by the Fisher information- is maximized at the exact balance. Furthermore, we find a similar result for a more realistic spiking neural network model. As the regime of balanced inputs has been experimentally observed, these results suggest that this regime is functionally important from an information encoding standpoint.
Services Sectors' Concentration: The European Union, Greece, and the New Economic Geography

The aim of this article is to investigate services sectors’ concentration based on employment data in the European Union and to disentangle the sector-specific developments and influential factors over time. We find that only the financial intermediation, retail trade and water transport sectors are subject to an increasing level of concentration over time. Implementing a two-way fixed effects model, we find that knowledge spillovers as well as externalities arising from technological similarities appear to be highly significant in explaining services’ concentration patterns for the European Union. Technological differences as a reason for services’ concentration only appear to have been important in the period prior to the Single European Market Enactment. Further evidence is found for the relevance of factor intensity in explaining concentration of non-market services.
Predictions tasks with words and sequences: Comparing a novel recurrent architecture with the Elman network

The classical connectionist models are not well suited to working with data varying over time. According to this, temporal connectionist models have emerged and constitute a continuously growing research field. In this paper we present a novel supervised recurrent neural network architecture (SARASOM) based on the Associative Self-Organizing Map (A-SOM). The A-SOM is a variant of the Self-Organizing Map (SOM) that develops a representation of its input space as well as learns to associate its activity with an arbitrary number of additional inputs. In this context the A-SOM learns to associate its previous activity with a delay of one iteration. The performance of the SARASOM was evaluated and compared with the Elman network in a number of prediction tasks using sequences of letters (including some experiments with a reduced lexicon of 10 words). The results are very encouraging with SARASOM learning slightly better than the Elman network.
Improved edit detection in speech via ENF patterns

In a recent paper published in the IEEE TIFS, we proposed an edit detection method based on the instantaneous variations of the Electrical Network Frequency (ENF). In this work we modify the detection criteria of that method by taking advantage of the typical pattern of ENF variations elicited by audio edits. We describe the implemented modifications and directly confront the performance of both methods using two distinct signal databases that contain real-life speech recordings. The experimental results demonstrate that the new proposition has an improved performance in terms of lower equal error rates when compared to its former version.
Secondary Project Proposal Post-seismic deformation of Chi-chi earthquake

Li 2 Secondary project proposal MOTIVATION Personal prospective My interests for earthquake deformation were initially motivated by the 2008 Wenchuan, China earthquake. Casualties during this magnitude 8.0 earthquake were shown by the government as follows: dead 69,142; missing 17,921; injured 374, 065. This earthquake was felt strongly by the whole nation, both physically and mentally. While people all over the country and the world were offering their help to Wenchuan, I questioned myself: as a geophysicist, what you can do to render help? In addition to claiming that earthquake is not predictable, can I provide at least some understanding of the earthquake? Research prospective Postseismic deformation is widely observed following large earthquakes. Study of postseismic deformation is essential to the understanding of the physics of the earthquake nucleation as a time-dependent process. Also, postseismic deformation redistributes the stress in the crust and thus influences the occurrence of future earthquakes. Segall (2010) points out that postseismic deformation could be explained by many mechanical processes, including viscous relaxation of rock below the seismogenic zone; transient fault slip (afterslip), either within the rupture zone or below the rupture zone; and flow of pore fluids induced by the earthquake. While the poroelastic effects on the observable crustal deformation have only been recently recognized, differentiating the effects of viscoelastic relaxation and afterslip have been an active area of research for a long time Thatcher (1983) studied afterslip and viscoelastic relaxation effects using thick lithosphere and thin lithosphere model, respectively. He concluded in that paper that contributions of afterslip and viscoelastic relaxation couldn't be differentiated based on the fitting on the data from California. Segall (2010) also showed the mathematical equivalence between these two models for the infinitely long strike-slip faults. However, for finite, dip-slip faults, there is still a chance to differentiate the effects of these two different mechanisms. conclude that afterslip is the dominant mechanism of post-seismic deformation in the 15-month period following the Chi-Chi earthquake. However, Sheu and Shieh (2004) claim a concurrence of afterslip and viscoelastic relaxation , with afterslip dominated the near field post-seismic deformation, and vis-coelastic relaxation dominated the far field. After 10 years of Chi-Chi earthquake, a large amount of continuous and Campaign GPS data are obtained. Therefore, another analysis is necessary to determine the contribution of different mechanisms in Li 3 Secondary project proposal a relatively longer period.
Broad Hα Wings in Nebulae around Evolved Stars and in Young Planetary Nebulae

Eleven objects that have been reported as proto-planetary nebula or as young planetary nebulae that show very extended Hα wings are presented. The extension of these wings is larger than 800 km s-1. Data for two symbiotic stars that show this same characteristic are also presented. Raman scattering is the mechanism that best explains the wings in 10 of the PNe and in the two symbiotic stars. In the PN IRAS 20462+3416 the wing profile can be explained by very intense stellar wind.
Coordinated Genome-Wide Modifications within Proximal Promoter Cis-regulatory Elements during Vertebrate Evolution

There often exists a “one-to-many” relationship between a transcription factor and a multitude of binding sites throughout the genome. It is commonly assumed that transcription factor binding motifs remain largely static over the course of evolution because changes in binding specificity can alter the interactions with potentially hundreds of sites across the genome. Focusing on regulatory motifs overrepresented at specific locations within or near the promoter, we find that a surprisingly large number of cis-regulatory elements have been subject to coordinated genome-wide modifications during vertebrate evolution, such that the motif frequency changes on a single branch of vertebrate phylogeny. This was found to be the case even between closely related mammal species, with nearly a third of all location-specific consensus motifs exhibiting significant modifications within the human or mouse lineage since their divergence. Many of these modifications are likely to be compensatory changes throughout the genome following changes in protein factor binding affinities, whereas others may be due to changes in mutation rates or effective population size. The likelihood that this happened many times during vertebrate evolution highlights the need to examine additional taxa and to understand the evolutionary and molecular mechanisms underlying the evolution of protein–DNA interactions.
Pengembangan Pembelajaran Sistem Blended Berbasis Universal Design for Learning untuk Kelas Inklusif

Abstract: This research intends to develop blended learning system based on Universal Design for Learning (UDL) for inclusive classrooms. Development of blended learning system to generate valid media and instructional design in accordance with the principle of Universal Design for Learning (UDL) and effectively used by diverse students in inclusive classrooms. For students who do not have special needs, as well as students with special needs. The media can be used to facilitate learning in traditional classrooms and online learning. Abstrak: Penelitian ini bermaksud untuk mengembangkan pembelajaran sistem blended berebasis Universal Design for Learning (UDL) untuk kelas inklusif. Pengembangan pembelajaran sistem blended untuk menghasilkan media dan desain pembelajaran yang valid sesuai dengan prinsip-prinsip Universal Design for Learning (UDL) serta efektif digunakan oleh beragam mahasiswa di kelas inklusif. Baik mahasiswa reguler yang tidak berkebutuhan khusus, maupun mahasiswa yang berkebutuhan khusus. Media tersebut nantinya bisa digunakan untuk memfasilitasi pembelajaran di kelas tradisional dan pembelajaran online.
Human Identification via Gait Recognition Using Accelerometer Gyro Forces

Many applications, both cooperative and hostile, require the ability to identify humans. This paper proposes a method that exploits the biometric property of human gait to identify people. A single sensor composed of an accelerometer and gyroscope is used to record gait characteristics. Using a Direct Form II Transpose, gait cycles are extracted and compressed to their characteristic features. Using simple classifiers on these feature vectors, this approach achieves 95% accuracy in classifying gait cycles to individuals. This model-driven approach uniquely exploits the physics of human gait through the use of gyroscope forces and proves its viability for smart environment applications.
Research on Typical Algorithms in Negative Sequential Pattern Mining

Negative sequential pattern (NSP), which contains both non-occurring and occurring items, can discover much more interest roles than positive sequential pattern (PSP) in many applications. NSP mining, however, has been just caught attention and very limited methods are available to mine NSP. Furthermore, there is not a unified definition about negative containment, i.e., how a data sequence contains a negative sequence. The researchers who begin to study nega- tive sequential pattern are often confused by these different definitions and are eager to know the differences of the exist- ing methods. So in this paper, we select four typical existing methods, PNSP, Neg-GSP, e-NSP and NSPM, implement their algorithms by JAVA, and compare their definition, method, runtime and the number of NSPs. Examples and experi- ments on four dataset clearly show their differences.
Improving recommendation diversity using tensor decomposition and clustering approaches

Diversity and novelty of items in recommendation, and coverage of overall recommended items are emerging recommendation quality measures for user and system respectively. These measures tend to alleviate the problem of user satisfaction in terms of redundancy in recommendations caused by accuracy-oriented approaches. This work proposes solution to provide diversity in different modes when we are dealing with multi-mode data. To provide diverse suggestion list of communities to join, the proposed framework uses Tensor Decomposition to reveal latent topics among multi-mode data including communities, users and social tags. It exploits co-clustering approaches on decomposed components to extract clusters of communities based on user similarity and tag similarity. Afterwards, clusters' information is used to develop and apply re-ranking algorithms, which leads to improvement in diversity and coverage of recommended lists.
The GMRT 150 MHz all-sky radio survey - First alternative data release TGSS ADR1

We present the first full release of a survey of the 150 MHz radio sky, observed with the Giant Metrewave Radio Telescope (GMRT) between April 2010 and March 2012 as part of the TIFR GMRT Sky Survey (TGSS) project. Aimed at producing a reliable compact source survey, our automated data reduction pipeline efficiently processed more than 2000 h of observations with minimal human interaction. Through application of innovative techniques such as image-based flagging, direction-dependent calibration of ionospheric phase errors, correcting for systematic offsets in antenna pointing, and improving the primary beam model, we created good quality images for over 95 percent of the 5336 pointings. Our data release covers 36 900 deg 2 (or 3.6 π steradians) of the sky between −53° and +90° declination (Dec), which is 90 percent of the total sky. The majority of pointing images have a noise level below 5 mJy beam -1 with an approximate resolution of 25′′×25′′ (or 25′′×25′′/ cos(Dec−19°) for pointings south of 19° declination). We have produced a catalog of 0.62 Million radio sources derived from an initial, high reliability source extraction at the seven sigma level. For the bulk of the survey, the measured overall astrometric accuracy is better than two arcseconds in right ascension and declination, while the flux density accuracy is estimated at approximately ten percent. Within the scope of the TGSS alternative data release (TGSS ADR) project, the source catalog, as well as 5336 mosaic images (5°×5°) and an image cutout service, are made publicly available at the CDS as a service to the astronomical community. Next to enabling a wide range of different scientific investigations, we anticipate that these survey products will provide a solid reference for various new low-frequency radio aperture array telescopes (LOFAR, LWA, MWA, SKA-low), and can play an important role in characterizing the epoch-of-reionisation (EoR) foreground. The TGSS ADR project aims at continuously improving the quality of the survey data products. Near-future improvements include replacement of bright source snapshot images with archival targeted observations, using new observations to fill the holes in sky coverage and replace very poor quality observational data, and an improved flux calibration strategy for less severely affected observational data.
Hierarchy-aware distributed overlays in data centers using DC2

Popular online services such as social networks, e-commerce and bidding are routinely hosted in large-scale data centers. Group communication systems (e.g., multicast) and distributed key-value stores are among some of the most essential building blocks for these services. Due to their scaling requirements, overlay networks such as distributed hash tables (DHTs) have been traditionally used in such systems. Modern hierarchical datacenter networks and global services running across datacenters pose unique challenges that traditional systems are ill-equipped to handle. For instance, the inherent multi-rooted tree topology design with oversubscription at the core translates into lesser bandwidth at the upper levels of the trees; traditional systems do not take this into consideration leading to a wastage of precious network resources. To solve this problem, we introduce a hierarchy-aware distributed overlay framework called DC2, for large scale and highly dynamic services. We build two applications-DC2-Multicast and DC2-Store-on top of DC2. In our experiments using a real prototype deployed over 700 nodes running over a Modelnet topology with 2 datacenters, we found that DC2-Multicast minimizes message latencies by several orders of magnitude, and reduces node and link stress by a factor of 2 to 3. We also find a reduction in object lookup latency by a factor of 8.