131 research outputs found
Neural geolocation prediction in Twitter
No full textInferring the location of a user has been a valuable step for many applications that leverage social media, such as marketing, security monitoring and recommendation systems. Motivated by the recent success of Deep Learning techniques for many tasks such as computer vision, speech recognition, and natural language processing, we study the application of neural models to the problem of geolocation prediction and experiment with multiple techniques to analyze neural networks for geolocation inference based solely on text. Experimental results on the dataset suggest that choosing appropriate network architecture can all increase performance on this task and demonstrate a promising extension of neural network based models for geolocation prediction. Our systematic extensive study of four supervised and three unsupervised tweet representations reveal that Convolutional Neural Networks (CNNs) and fastText best encode the the textual and geoloca- tional properties of tweets respectively. fastText emerges as the best model for low resource settings, providing very little degradation with reduction in embedding size.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2019-05-01The student, Pramod Srinivasan, accepted the attached license on 2017-04-25 at 12:15.The student, Pramod Srinivasan, submitted this Thesis for approval on 2017-04-25 at 12:51.This Thesis was approved for publication on 2017-04-25 at 18:42.DSpace SAF Submission Ingestion Package generated from Vireo submission #11043 on 2017-08-10 at 14:32:36Made available in DSpace on 2017-08-10T19:52:23Z (GMT). No. of bitstreams: 2
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Excited-state intramolecular proton transfer of 2-acetylindan-1,3-dione studied by ultrafast absorption and fluorescence spectroscopy
No full textWe employ transient absorption from the deep-UV to the visible region and fluorescence upconversion to investigate the photoinduced excited-state intramolecular proton-transfer dynamics in a biologically relevant drug molecule, 2-acetylindan- 1,3-dione. The molecule is a ß-diketone which in the electronic ground state exists as exocyclic enol with an intramolecular H-bond. Upon electronic excitation at 300 nm, the first excited state of the exocyclic enol is initially populated, followed by ultrafast proton transfer (±160 fs) to form the vibrationally hot endocyclic enol. Subsequently, solvent-induced vibrational relaxation takes place (±10 ps) followed by decay (±390 ps) to the corresponding ground state. © 2015 Author(s)1561sciescopu
Supersymmetric many-body systems from partial symmetries — integrability, localization and scrambling
No full textPartial symmetries are described by generalized group structures known as symmetric inverse semigroups. We use the algebras arising from these structures to realize supersymmetry in (0+1) dimensions and to build many-body quantum systems on a chain. This construction consists in associating appropriate supercharges to chain sites, in analogy to what is done in spin chains. For simple enough choices of supercharges, we show that the resulting states have a finite non-zero Witten index, which is invariant under perturbations, therefore defining supersymmetric phases of matter protected by the index. The Hamiltonians we obtain are integrable and display a spectrum containing both product and entangled states. By introducing disorder and studying the out-of-time-ordered correlators (OTOC), we find that these systems are in the many-body localized phase and do not thermalize. Finally., we reformulate a theorem relating the growth of the second Rényi entropy to the OTOC on a thermal state in terms of partial symmetries. © 2017, The Author(s)2211Nsciescopu
Anomaly-Based DNN Model for Intrusion Detection in IoT and Model Explanation: Explainable Artificial Intelligence
No full textIoT has gained immense popularity recently with advancements in technologies and big data. IoT network is dynamically increasing with the addition of devices, and the big data is generated within the network, making the network vulnerable to attacks. Thus, network security is essential, and an intrusion detection system is needed. In this paper, we proposed a deep learning-based model for detecting intrusions or attacks in IoT networks. We constructed a DNN model, applied a filter method for feature reduction, and tuned the model with different parameters. We also compared the performance of DNN with other machine learning techniques in terms of accuracy, and the proposed DNN model with weight decay of 0.0001 and dropout rate of 0.01 achieved an accuracy of 0.993, and the reduced loss on the NSL-KDD dataset having five classes. DL models are a black box and hard to understand, so we explained the model predictions using LIME.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Cyber Securit
Myśleć fantastyką. Przez science fiction do posthumanizmu
No full textThe author presents the thesis that fantastic literature and film, especially in the science fiction variant, is a privileged form of expression in posthumanist discourse. The themes, motifs and protagonists of science fiction are invoked in various contexts by Donna J. Haraway, Rosi Braidotti, Luciana Parisi, and Pramod K. Nayar. The author analyzes various areas of the involvement and usage of science fiction in posthumanist discourse: on the ontological, axiological and epistemological levels.The author presents the thesis that fantastic literature and film, especially in the science fiction variant, is a privileged form of expression in posthumanist discourse. The themes, motifs and protagonists of science fiction are invoked in various contexts by Donna J. Haraway, Rosi Braidotti, Luciana Parisi, and Pramod K. Nayar. The author analyzes various areas of the involvement and usage of science fiction in posthumanist discourse: on the ontological, axiological and epistemological levels
Phytochemicals identification, anti-microbial, anti-oxidant and anti-diabetic activities of Polygala sphenoptera Fresen
No full text246-257Polygala sphenoptera Fresen, belonging to the family Polygalaceae, is a plant traditionally used in folk medicine for various
health benefits. However, its chemical composition and pharmacological properties have not been explored. This study was to
prepare and optimise the ethanolic extract of P. sphenoptera, investigate its phytochemical composition, and evaluate its antimicrobial,
in-vitro anti-oxidant and anti-diabetic activities. The ethanolic extract of the authenticated whole plant of
P. sphenoptera was investigated for the presence of phytochemicals and evaluated for anti-microbial properties by determining
the minimum inhibitory concentration and zone of inhibition. The anti-oxidant capacity was evaluated using the 2,2-diphenyl-1-
picrylhydrazyl radical (DPPH) scavenging assay. The anti-diabetic potential was assessed by measuring α-amylase and
α-glucosidase inhibitory activities. Phytochemical investigations indicate the presence of carbohydrates, flavonoids, tannins,
alkaloids, and phenolic compounds. The phenolic content of the extract was found to be 8.733 mg GAE/g. The extract
demonstrated significant anti-microbial activity against both bacterial and fungal strains. In-vitro studies indicated that the plant
extract possesses strong anti-oxidant and anti-diabetic properties. Further detailed research will help to understand its
mechanisms and validate its therapeutic potential
Security for proof of work blockchains via checkpointing
No full textFinality gadgets are comprised of a Byzantine Fault Tolerant (BFT) protocol finalizing blocks produced by a Proof-of-Work (PoW) or Proof-of-Stake (PoS) chain protocol. They have become very popular methods for combining the best features of the BFT and PoW protocols and are proposed for deployment in many major blockchains. While the finality gadget architecture has been explored through many distinct dimensions, their performance under an adversarial majority in the PoW chain protocol has received scant attention. The raison d’etre for a finality gadget is to provide safety even under an adversarial majority in the PoW chain (hence the term “finality” gadget). While safety guarantee is easily provided by the finality gadget, significant liveness vulnerabilities exist. The proposed remedy achieves asymptotic liveness but the achieved chain quality (the fraction of honest blocks in the ledger) and latency deteriorate exponentially as the adversary power increases beyond 50%. Furthermore, the proposed gadget does not guarantee liveness in protocols beyond the Nakamoto longest chain.
In this thesis, we propose Advocate, a new finality gadget architecture, which achieves two main results: (a) optimal chain quality and low latency under a super-majority adversary for the Nakamoto longest chain protocol and (b) generalization to a variety of parallel-chain based scaling architectures, including OHIE, Prism and ledger combiner. We demonstrate via a full-stack implementation the robustness of Advocate under a 90% adversarial majority.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2023-08-01The student, Siheng Pan, accepted the attached license on 2021-07-20 at 16:05.The student, Siheng Pan, submitted this Thesis for approval on 2021-07-20 at 16:29.This Thesis was approved for publication on 2021-07-21 at 09:38.DSpace SAF Submission Ingestion Package generated from Vireo submission #16599 on 2022-01-12 at 13:02:53Made available in DSpace on 2022-01-12T22:51:33Z (GMT). No. of bitstreams: 2
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Development of a body force model for centrifugal compressors
No full textThesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2013.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 167-169).This project is focused on modeling the internal ow in centrifugal compressors for the purpose of assessing the onset of rotating stall and surge. The current methods to determine centrifugal compressor stability limits are based on empirical data and often, experiments. Unsteady full wheel simulations have become feasible due to the increase in computation power but the prediction of the stability limit still remains a challenge. The presented methodology is based on the idea of body forces and a blade passage model suitable for centrifugal compressors is derived. Previous work has shown that blade passage models are capable of capturing the response to inlet ow distortions and the onset of instability in axial compressors. In this thesis, a blade passage model is developed for centrifugal compressors with the goal of capturing the three-dimensional through-ow computed by steady RANS simulations. The model consists of three main elements, a normal force model, a viscous parallel force model, and a blade metal blockage model. The work demonstrates the model's capabilities on a radial impeller with prismatic blades where the total-to-static pressure rise coefficient and stage loading coefficient are in agreement with RANS calculations within 6.75% and 5%, respectively. While the model denition is shown to be consistent with other blade passage models for axial compressors, its application to a transonic axial compressor rotor and a high-speed centrifugal compressor stage revealed numerical convergence problems. It is thought that the model derivation and denition are sound and that these issues are due to implementation errors. The methodology and related modeling process are investigated step by step for three-dimensional blade geometries and, where applicable, verified with direct numerical calculation. The model limitations and potential implementation error are discussed at length so as to guide future work required to complete the demonstration of this blade passage model for axial and centrifugal compressors with three-dimensional blade shapes.by Anjaney Pramod Kottapalli.S.M
Mobility and Insurgent Celebrityhood: The Case of Arundhati Roy
No full textPramod K. Nayar Published online: 2017-04-24 | DOI: https://doi.org/10.1515/culture-2017-0005. Abstract Indian novelist and Booker winner Arundhati Roy is a celebrity author, but her celebrityhood is a cross-genre and cross-domain one. This essay argues that a certain insurgent celebrityhood emerges in the case of Roy through her mobility into and across many public domains. In this process of mobility, Roy also mobilises in her rhetoric and her polemics, the precariat public sphere by her..
State Estimation of Linear Systems With Sparse Inputs and Markov-Modulated Missing Outputs
No full textIn this paper, we consider the problem of estimating the states of a linear dynamical system whose inputs are jointly sparse and outputs at a few unknown time instants are missing. We model the missing data mechanism using a Markov chain with two states representing the missing and non-missing data. This mechanism with memory governed by the Markov chain models intermittent outages due to communication channels and occlusions corresponding to moving objects. We rely on the sparse Bayesian learning framework to derive an estimation algorithm that uses Kalman smoothing to handle temporal correlation and the Viterbi algorithm to handle missing data. Further, we demonstrate the utility of our algorithm by applying it to the frequency division duplexed multiple input multiple output downlink channel estimation problem.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Signal Processing System
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