172 research outputs found
Review of Violent Intimacies: The Trans Everyday and the Making of an Urban World by Aslı Zengin (Duke University Press)
No full textAslı Zengin’s Violent Intimacies theorizes the fraught encounter between the Turkish state and its trans subjects. Introducing the analytic framework of “violent intimacies,” Zengin advances two main claims: structural violence unfolds through intimate contact with gendered bodies, and trans women, in turn, confront this violence with intimate practices of resistance. Zengin’s work marks a significant intervention within trans studies. She pays close attention to the materiality of the body as the location where violence is both enacted and contested—a welcome departure from the tendency towards abstraction in trans theoretical production. She also pushes the field in transnational directions to address experiences of gender transgression beyond North America and Western Europe. A rich ethnography of trans life in Turkey, the text depicts everyday scenes of violent intimacies across several interpersonal and institutional settings: the street, police, medicine, law, and family. Violent Intimacies offers a vibrant account of Turkish trans women who—faced with state neglect and social exclusion—envision alternative ways of building worlds and sustaining life
Technology, Policy, and Inclusion
No full textTechnology, Policy, and Inclusion looks at the intersections between public policy and technology in India. It explores the barriers in instituting effective governance and development and examines how these can be mitigated through technological interventions in developing countries.
Increased digitisation of the economy has added to the development challenges in India and issues such as exclusion and social inequality. This volume stresses the need for governments to leverage technology to bring more vulnerable and marginalised groups into the fold of financial and social inclusion. It also focuses on the importance of regulation for a responsible integration of technologies and minimising risks. The book includes examples and case studies from different areas including management of the COVID-19 pandemic through digital means, real estate digital infrastructure, digital census, e-markets for farmers, and government interventions that use technology to deliver financial services in remote areas of the country. It also outlines various solutions for fostering equity and socio-economic development.
Part of the Innovations, Practice and the Future of Public Policy in India series, this volume will be of interest to students and researchers of public policy, political science, development studies, and sociology as well as policy professionals and technocrats.
This book is freely available as a downloadable Open Access PDF at http://www.taylorfrancis.com under a Creative Commons (CC-BY-NC-ND) 4.0 license
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Term burstiness: evidence, model and applications
No full textThe present thesis looks at the phenomenon of term burstiness in text. Term burstiness is defined as the multiple re-occurrences in short succession of a particular term after it has occurred once in a certain text. Term burstiness is important as it aids in providing structure and meaning to a document. Various kinds of term burstiness in text are studied and their effect on a dataset explored in a series of homogeneity experiments. A novel model of term burstiness is proposed and evaluations based on the proposed model are performed on three different applications. The “bag-of-words” assumption is often used in statistical Natural Language Processing and Information Retrieval applications. Under this assumption all structure and positional information of terms is lost and only frequency counts of the document are retained. As a result of counting frequencies only, the “bag-of-words” representation of text assumes that the probability of a word occurring remains constant throughout the text. This assumption is often used because of its simplicity and the ease it provides for the application of mathematical and statistical techniques on text. Though this assumption is known to be untrue [CG95b, CG95a, ChuOO], but applications [SB97, Lew98, MN98, Seb02] based on this assumption appear not to be much hampered. A series of homogeneity based experiments are carried out to study the presence and extent of term burstiness against the term independence based homogeneity assumption on the dataset. A null hypothesis stating the homogeneity of a dataset is formulated and defeated in a series of experiments based on the y2 test, which tests the equality between two partitions of a certain dataset. Various schemes of partitioning a dataset are adopted to illustrate the effect of term burstiness and structure in text. This provided evidence of term burstiness in the dataset, and fine-grained information about the distribution of terms that might be used for characterizing or profiling a dataset. A model for term burstiness in a dataset is proposed based on the gaps between successive occurrences of a particular term. This model is not merely based on frequency counts like other existing models, but takes into account the structural and positional information about the term’s occurrence in the document. The proposed term burstiness model looks at gaps between successive occurrences of the term. These gaps are modeled using a mixture of exponential distributions. The first exponential distribution provides the overall rate of occurrence of a term in a dataset and the second exponential distribution determines the term’s rate of re-occurrence in a burst or when it has already occurred once previously. Since most terms occur in only a few documents, there are a large number of documents with no occurrences of a particular term. In the proposed model, non-occurrence of a term in a document is accounted for by the method of data censoring. It is not straightforward to obtain parameter estimates for such a complex model. So, Bayesian statistics is used for flexibility and ease of fitting this model, and for obtaining parameter estimates. The model can be used for all kinds of terms, be they rare content words, medium frequency terms or frequent function words. The term re-occurrence model is instantiated and verified against the background of different collections, in the context of three different applications. The applications include studying various terms within a dataset to identify behavioral differences between the terms, studying similar terms across different datasets to detect stylistic features based on the term’s distribution and studying the characteristics of very frequent terms across different datasets. The model aids in the identification of term characteristics in a dataset. It helps distinguish between highly bursty content terms and less bursty function words. The model can differentiate between a frequent function word and a scattered one. It can be used to identify stylistic features in a term’s distribution across text of varying genres. The model also aids in understanding the behaviour of very frequent (usually function) words in a dataset
Modeling a continuous granular mixer using periodic discrete element method sub-models
No full textContinuous granular mixing provides an alternative to traditional batch blending operations employed by pharmaceutical, food, mining, and construction industries. For large throughput operations, continuous mixing is more economical as labor costs associated with loading, unloading, and cleaning can be reduced. Moreover, issues pertaining to process scale-up can be avoided as continuous mixers can be operated for longer durations to obtain a larger quantity of blended material. Characterization of the influence of operating conditions and material properties is necessary if the performance of a continuous mixer is to be optimized. Such parametric and optimization studies can be performed in a computational framework using modeling tools such as the discrete element method (DEM). Since DEM is a computationally expensive method, large scale parametric studies using the full continuous blender geometry is not feasible. A more efficient modeling approach is to use periodic slice sub-models representing sections of the full blender. Even though inlet and outlet effects are not captured accurately using periodic slice sub-models, comparisons of flow microdynamics show that the periodic slice approach reproduces the flow inside a full blender reasonably well. Using periodic slice sub-models, parametric studies investigating the influence of impeller speed, fill level, particle cohesion, and particle size in a continuous mixer are performed. The optimal mixing strategy for blending non-cohesive and cohesive particles is found to be similar, even though mixing rates for cohesive materials are generally smaller. A large impeller speed at a small fill level (small inlet feed rate) leads to fluidization of granular bed, which results in best mixing performance. Varying the size of particles has a weak influence on advective flow but strongly affects mixing rates. Mixing rates measured from periodic slice simulations are also used in the advection-diffusion equation in an attempt to develop an hybridized DEM-continuum mixing model. The periodic slice approach significantly reduces simulation time when used instead of a full continuous blender DEM model. Useful information regarding flow patterns and mixing mechanisms inside a continuous mixer is obtained from periodic slice simulations at a fraction of the computation cost. Periodic slice sub-models of the continuous blender can be used to further study other parameters of interest not discussed in this work, such as mixer design and material properties of particles. The periodic slice approach described in this work may also be applicable for modeling other continuous granular operations such as continuous granulation and continuous coating
The Capacity Region of the Gaussian Z-Interference Channel with Gaussian Input and Weak Interference
No full textWe consider a wireless communication scenario with two transmit-receive pairs
where each of the transmitters has a message for its corresponding receiver and only
one of the receivers face interference from the undesired transmitter. In our research,
we focused on devising optimal ways to manage this undesired interference and
characterize the best communication rates for both transmit-receive pairs. Currently,
this problem of interference is dealt with by restricting the two communications in
di erent frequency or time bands. We explore the possibility of achieving better rates
by allowing them to operate in the same band. Such channels were identi ed about
4 decades ago, but the maximum rate of communication when the transmitters have
a power constraint is still unknown. In this work, we characterize the best rates for
this channel under a reasonable practical constraint of using Gaussian signals at both
the transmitters
Echographic Optic Nerve Evaluation: A Novel Diagnostic Modality in Glaucoma
No full textIntroduction: Primary Open-Angle Glaucoma (POAG) is considered a leading cause of blindness among all others. Different technologies such as Scanning Laser Polarimetry (SLP) and Optical Coherence Tomography (OCT) closely correlate in measuring structural parameters of the Retinal Nerve Fiber Layer (RNFL) and Optic Nerve Head (ONH). Visual impairment related to glaucomatous damage is attributed to the RNFL. Earlier studies have shown that retro-bulbar optic nerve thickness is reduced in glaucoma and have suggested that this is also the result of RNFL destruction.
Aim: To investigate the correlation between the orbital and intraocular portions of the optic nerve among POAG patients.
Materials and Methods: This was a hospital-based cross-sectional study done in a tertiary care ophthalmic institute from October 2019 to February 2021. One eye of 32 volunteers with newly diagnosed POAG underwent optic disc analysis using OCT and echographic measurements of the retrobulbar optic nerve. For statistical calculations, Statistical Package for Social Sciences (SPSS) Statistics version 20.0 software (IBM Corp., Armonk, NY, USA) was used. Spearman’s rho (rs) was used as the index of correlation between retrobulbar optic nerve dimensions and ONH topographical data. A correlation between OCT-based RNFL and optic disc parameters was compared with retrobulbar optic nerve dimensions measured with the help of Ultrasonography- Brightness (USG B) Scan.
Results: Orbital Optic Nerve Diameter (OND) and Optic Nerve Cross-sectional Area (ONCSA) significantly and positively correlated with Neuro-retinal Rim (NR) area (OND: p-value=0.00001; ONCSA: p-value=0.00001) and average nerve fiber layer thickness (OND: p-value=0.0001; ONCSA: p-value=0.00002). The Retrobulbar ONCSA-to-disc area ratio (ONCSA/D) was found to have a statistically demonstrable positive correlation with Neuro-retinal Rim Area/Disc area ratio (NR/D) (p=0.00003).
Conclusion: This study showed that retrobulbar optic nerve dimensions correlate well with SD-OCT-based ONH parameters. Echographic measurements of the retrobulbar optic nerve add a new biomarker in the diagnosis of glaucoma
Self-learning Emulators and Eigenvector Continuation
No full textEmulators that can bypass computationally expensive scientific calculations
with high accuracy and speed can enable new studies of fundamental science as
well as more potential applications. In this work we discuss solving a system
of constraint equations efficiently using a self-learning emulator. A
self-learning emulator is an active learning protocol that can be used with any
emulator that faithfully reproduces the exact solution at selected training
points. The key ingredient is a fast estimate of the emulator error that
becomes progressively more accurate as the emulator is improved, and the
accuracy of the error estimate can be corrected using machine learning. We
illustrate with three examples. The first uses cubic spline interpolation to
find the solution of a transcendental equation with variable coefficients. The
second example compares a spline emulator and a reduced basis method emulator
to find solutions of a parameterized differential equation. The third example
uses eigenvector continuation to find the eigenvectors and eigenvalues of a
large Hamiltonian matrix that depends on several control parameters.Comment: 6 + 5 pages (main + supplemental), 5 + 7 figures (main +
supplemental), additional discussion, references, and examples adde
Convergence of Eigenvector Continuation
No full textEigenvector continuation is a computational method that finds the extremal eigenvalues and eigenvectors of a Hamiltonian matrix with one or more control parameters. It does this by projection onto a subspace of eigenvectors corresponding to selected training values of the control parameters. The method has proven to be very efficient and accurate for interpolating and extrapolating eigenvectors. However, almost nothing is known about how the method converges, and its rapid convergence properties have remained mysterious. In this Letter, we present the first study of the convergence of eigenvector continuation. In order to perform the mathematical analysis, we introduce a new variant of eigenvector continuation that we call vector continuation. We first prove that eigenvector continuation and vector continuation have identical convergence properties and then analyze the convergence of vector continuation. Our analysis shows that, in general, eigenvector continuation converges more rapidly than perturbation theory. The faster convergence is achieved by eliminating a phenomenon that we call differential folding, the interference between nonorthogonal vectors appearing at different orders in perturbation theory. From our analysis we can predict how eigenvector continuation converges both inside and outside the radius of convergence of perturbation theory. While eigenvector continuation is a nonperturbative method, we show that its rate of convergence can be deduced from power series expansions of the eigenvectors. Our results also yield new insights into the nature of divergences in perturbation theory
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