334 research outputs found
"More Societal than Generational": Examining the Construction and Resistance of Generational Messages in the Workplace
No full textAuthor email: [email protected] Millennial generation, those born between 1980-2000, have drawn vast, sometimes fanatical, criticism in popular media. Slated as narcissistic praise hounds, they are cast as demanding graduate divas who are about to attack the workplace and everything ‘you hold sacred’ (Clark, 2008; Safer, 2007). The abundance of such messages about this generation in formats ‘tailored, targeted, and consumed’ by the public is problematic given that generational constructs are by many perceived as sacrosanct (Myers et al, 2010).
The proliferation of such criticism is by no means innocuous given the very likely impact that they will have on Millennial work opportunities. For many scholars the field of Millennial research suffers from a lack of empirical and cross sectional data to establish more calculated and careful generational constructs, – instead relying on or reacting to popular negative stereotypes. While some Millennial scholarship has begun to move beyond criticisms of popular media, Millennial research is by many considered contradictory at best and confusing at worst (Kowske et al, 2010). Additional difficulties arise when the scramble to publish more research-based work has led to methodologies which are inherently flawed because they reinforce the very same monolithic generational categories they are supposed to assess.
This study, undertaken in New Zealand, explores critical approaches as a means of examining the construction of generational messages and the establishment of generational difference. As a starting point, this small-scale examination analyses the very way in which generational messages are constructed and resisted within the workplace through an analysis of interviews undertaken with 26 employees of a Small to Medium Enterprise (SME) in the information technology sector.
Unlike many generational studies, this project did not seek to draw conclusions by framing differences and measuring responses across generational lines, but rather took a bottom-up approach to understand how participants themselves constructed and resisted messages about generational difference. The project asked two research questions: First, how are generational messages constructed in the context of the workplace? And second, how are generational messages resisted in the workplace? Through axial coding this research categorized five themes under which participants constructed generational difference. These five themes are Technology, Voice, Fairness, Informality, and Stimulus. Broadly speaking, these themes were underpinned by a belief that Millennials have a great demand for respect, democratic process, and the reduction of power distances.
Given the critical approach, the study also observed resistance as a component of the discursive process. As such this research outlines the partiality of resistance and outlines strategies of resistance employed by employees. In line with the idea that construction and resistance are mutually implicated as negotiation, participants were frequently observed simultaneously constructing and resisting generational difference, both synchronically and diachronically. Through axial coding this study also categorized three strategies of resistance. These three strategies are established as Dismissal, the Third Person Effect, and the Decline Metaphor.
This research highlights the usefulness of adopting critical approaches by illustrating the way in which generational meaning is perpetually produced, reproduced, negotiated, and resisted by participants (Murphy, 1998). While there are several factors which are indicative of the Millennial generation, this thesis establishes the hegemonic character of most constructions of generational difference. Given the fragmented and complex state of society, this thesis posits that the usefulness of the monolithic birth-cohort generation has long since passed and we should instead look to understanding generations in terms of their consumption of similar cultural capital
Journal Of The Nepal Medical Association
No full textNEW DIRECTOR
NEPAL MEDICAL COUNCIL
CONFERENCE AND SEMINARS
SYMPOSIUM
MEDICLA NEWS
BIRTHDAY AWARDS
CENTRAL BODY
KATHMANDU BRANCH
BIRATNAGAR BRANCH
AN ACKNOWLEDGEMENT
JORE GANESH PRESS Pvt. Ltd
Influence of geometric parameters on 3D periodic lattice effective properties
No full textLattice materials are generated by tessellating a unit cell, composed of a specific truss configurations, in an infinite periodicity to combine the effect of bulk material properties and geometric periodicity. They offer enhanced mechanical and dynamic properties per unit mass, and the ability to engineer the material response by optimizing the unit cell. Characterizing lattice properties through experiments can be a time consuming and costly process, so analytical and numerical methods are crucial. Specifically, the Bloch-wave homogenization approach allows one to characterize the effective static properties of the lattice unit cell while simultaneously analyzing wave propagation properties. While this analysis has been used for some time, a thorough study of this approach on 3D lattice materials with different symmetries and geometries is presented here. Using Bloch-wave homogenization, multiple periodic lattices with cubic, transversely isotropic, and tetragonal symmetry, including an auxetic geometry, over a wide range of relative densities are analyzed within a finite element framework. The effect of geometric parameters on lattice properties is discussed and a comparison between lattices based on their anisotropy index is presented. Method studied in this thesis can be extended for designing multifunctional metamaterials with optimized static and dynamic properties simultaneously. This work can also serve as the basis for nondestructive evaluation of metamaterials properties using ultrasonic velocity measurements.Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2021-05-01The student, Ganesh Patil, accepted the attached license on 2019-04-24 at 19:00.The student, Ganesh Patil, submitted this Thesis for approval on 2019-04-24 at 19:11.This Thesis was approved for publication on 2019-04-25 at 12:03.DSpace SAF Submission Ingestion Package generated from Vireo submission #13897 on 2019-08-22 at 15:08:33Made available in DSpace on 2019-08-23T20:36:11Z (GMT). No. of bitstreams: 2
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Previous issue date: 2019-04-25Embargo set by: Seth Robbins for item 112211
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A learning hierarchy for classification and regression
No full textThesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 51-53).This thesis explores the problems of learning analysis of variance (ANOVA) decompositions over GF(2) and R, as well as a general regression setup. For the problem of learning ANOVA decompositions, we obtain fundamental limits in the case of GF(2) under both sparsity and degree structures. We show how the degree or sparsity level is a useful measure of the complexity of such models, and in particular how the statistical complexity ranges from linear to exponential in the dimension, thus forming a "learning hierarchy". Furthermore, we discuss the problem in both an "adaptive" as well as a "one-shot" setting, where in the adaptive case query choice can depend on the entire past history. Somewhat surprisingly, we show that the "adaptive" setting does not yield significant statistical gains. In the case of R, under query access, we demonstrate an approach that achieves a similar hierarchy of complexity with respect to the dimension. For the general regression setting, we outline a viewpoint that captures a variety of popular methods based on locality and partitioning of some kind. We demonstrate how "data independent" partitioning may still yield statistically consistent estimators, and illustrate this by a lattice based partitioning approach.by Ganesh Ajjanagadde.M. Eng
V.S. Naipaul’s ?The Mystic Masseur?: A Study of Post- Colonial Myth and Reality
No full text<h3 data-fontsize="17" data-lineheight="23">Abstract</h3>
<p>The Mystic Masseur is one of the V.S. Naipaul’s finest comic creations in which we see immense sensibility, humour, success, politics and endless inventive imagination that have become the hallmarks of the author’s genius. It is Naipaul’s first novel that depicts the story of the rise of Ganesh Ramsumair, from failed primary teacher and struggling masseur to author, revered mystic and M.B.E. It is a journey memorable for its hilarious and bewildering success through politics. V.S. Naipaul has made the claim that the story of Ganesh Ramsumair is the history of their time. In each step of the career of Ganesh Ramsumair the author has satirized the rise of power of a representative of the country, called Trinidad which was about to achieve it’s independence from the British colonial rule in 1962.Beneath the muchness and manyness the author traces the romance and realism, imagination and fact of the ?rise? and ?decline? of Ganesh Ramsumair. The story of the novel is not only the life history of Ganesh Ramsumair; rather it is a story of social and economic life of the Indian islanders. The author shows his alienation and rootlessness of the people migrated from India to Trinidad. Here he puts stress on the importance of imagination for survivalThe question is whether the novel The Mystic Masseur depicts the real Trinidad, the question is answered in King’s observations in his book. ?Those familiar with Trinidadian history should recognize how Naipaul has used local events, characters and such politicians characters and such politicians as Uriah Butler, Albert Gomes, Arthur Cipriani and Naipaul’s two uncles, Rudranath and SimbhoonathCapildeo in his novel. Naipaul’s early fiction is based on memories of Trinidadian cultural and political life before he left for England in 1950.? (King 29) My paper proposes to examine how V.S. Naipaul usesthe post-colonial myth and reality in his novel The Mystic Masseu</p>
Transforming images into words: optical character recognition solutions for image text extraction
No full textOptical character recognition (OCR) tool is a boon and greatest advancement in today’s emerging technology which has proven its remarkability in recent years by making it easier for humans to convert the textual information in images or physical documents into text data making it useful for analysis, automation processes and improvised productivity for different purposes. This paper presents the designing, development and implementation of a novel OCR tool aiming at text extraction and recognition tasks. The tool incorporates advanced techniques such as computer vision and natural language processing (NLP) which offer powerful performance for various document types. The performance of the tool is subject to metrics like analysis, accuracy, speed, and document format compatibility. The developed OCR tool provides an accuracy of 98.8% upon execution providing a character error rate of 2.4% and word error rate (WER) of 2.8%. OCR tool finds its applications in document digitization, personal identification, archival of valuable documents, processing of invoices, and other documents. OCR tool holds an immense amount of value for researchers, practitioners and many organizations which seek effective techniques for relevant and accurate text extraction and recognition tasks
Enhancing accessibility with long short-term memory-based sign language detection systems
No full textIndividuals who are deaf or experience difficulties with hearing and speech predominantly rely on sign language as their medium to communicate, which is not universally comprehended leading to obstacles in achieving effective communication. Advances in deep learning technologies in recent years have enabled the development of systems intended to autonomously interpret gestures in sign language and translate them into spoken language. This paper introduces a system built on deep learning methodologies for recognizing sign language. It uses long short-term memory (LSTM) architecture to distinguish and classify hand gestures which are static and dynamic. The system is divided into three primary components, including dataset collection, neural network assessment, and sign detection component that encompasses hand gesture extraction and sign language classification. The module to extract hand gestures makes use of recurrent neural networks (RNNs) for the detection and tracking of hand movements in video sequences. Another RNN that is incorporated by classification module categorizes these gestures into established sign language classes. Upon evaluation on a custom dataset, the proposed system attains an accuracy rate of 99.42%, thus making it visualize its promise as an assistive technology for handicapped hearing individuals. This system can further be enhanced by including further classes on sign language and real-time gesture interpretation
Transparent precision: Explainable AI empowered breast cancer recommendations for personalized treatment
No full textBreast cancer stands as a prevalent global concern, prompting extensive research into its origins and personalized treatment through Artificial Intelligence (AI)-driven precision medicine. However, AI's black box nature hinders result acceptance. This study delves into Explainable AI (XAI) integration for breast cancer precision medicine recommendations. Transparent AI models, fuelled by patient data, enable personalized treatment recommendations. Techniques like feature analysis and decision trees enhance transparency, fostering trust between medical practitioners and patients. This harmonizes AI's potential with the imperative for clear medical decisions, propelling breast cancer care within the precision medicine era. This research work is dedicated to leveraging clinical and genomic data from samples of metastatic breast cancer. The primary aim is to develop a machine learning (ML) model capable of predicting optimal treatment approaches, including but not limited to hormonal therapy, chemotherapy, and anti-HER2 therapy. The objective is to enhance treatment selection by harnessing advanced computational techniques and comprehensive data analysis. A decision tree model developed here for the prediction of suitable personalized treatment for breast cancer patients achieves 99.87% overall prediction accuracy. Thus, the use of XAI in healthcare will build trust in doctors as well as patients
CD16a with oligomannose-type N-glycans is the only “low-affinity” Fc γ receptor that binds the IgG crystallizable fragment with high affinity in vitro
No full textFc γ receptors (FcγRs) bind circulating IgG (IgG1) at the surface of leukocytes. Antibodies clustered at the surface of a targeted particle trigger a protective immune response through activating FcγRs. Three recent reports indicate that the composition of the asparagine-linked carbohydrate chains (N-glycans) of FcγRIIIa/CD16a impacted IgG1-binding affinity. Here we determined how N-glycan composition affected the affinity of the “low-affinity” FcγRs for six homogeneous IgG1 Fc N-glycoforms (G0, G0F, G2, G2F, A2G2, and A2G2F). Surprisingly, CD16a with oligomannose N-glycans bound to IgG1 Fc (A2G2) with a KD = 1.0 ± 0.1 nM. This affinity represents a 51-fold increase over the affinity measured for CD16a with complex-type N-glycans (51 ± 8 nM) and is comparable with the affinity of FcγRI/CD64, the sole “high-affinity” FcγR. CD16a N-glycan composition accounted for increases in binding affinity for the other IgG1 Fc glycoforms tested (10–50-fold). This remarkable sensitivity could only be eliminated by preventing glycosylation at Asn162 with an Asn-to-Gln mutation; mutations at the four other N-glycosylation sites preserved tighter binding in the Man5 glycoform. None of the other low-affinity FcγRs showed more than a 3.1-fold increase upon modifying the receptor N-glycan composition, including CD16b, which differs from CD16a by only four amino acid residues. This result indicates that CD16a is unique among the low-affinity FcγRs, and modifying only the glycan composition of both the IgG1 Fc ligand and receptor provides a 400-fold range in affinities.This research was originally published in the Journal of Biological Chemistry. Subedi, Ganesh P., and Adam W. Barb. "CD16a with oligomannose-type N-glycans is the only “low-affinity” Fc γ receptor that binds the IgG crystallizable fragment with high affinity in vitro." Journal of Biological Chemistry 293, no. 43 (2018): 16842-16850. © the Author(s). doi: 10.1074/jbc.RA118.004998.</p
Revealing antiferromagnetic transition of van der Waals MnPS3 via vertical tunneling electrical resistance measurement
No full textUnderstanding the correlation between the electronic and magnetic properties of materials is a crucial step to functionalize or modulate their properties. However, it is not straightforward to electrically characterize magnetic insulators, especially large-bandgap materials, due to their high resistivity. Here, we successfully performed electrical measurements of a two-dimensional (2D) antiferromagnetic insulator, van der Waals-layered MnPS3, by accounting for the vertical graphene/MnPS3/graphene heterostructure. Antiferromagnetic transition is observed by the variance in electrical resistance from the paramagnetic to antiferromagnetic transition near similar to 78 K in the vertically stacked heterostructure devices, which is consistent with the magnetic moment measurement. This opens an opportunity for modulating the magnetic transition of 2D van der Waals materials via an electrical gate or surface functionalization. (c) 2019 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)11sciescopu
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