A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is
Specifically, Kamath et al. ... From this viewpoint, Kamath et al.  proved that a version of the CCFM loses stability via a Hopf bifurcation. ...arXiv:1805.09743v1 fatcat:lkodljeyyfb7xkz24n7ihcakz4
Aim: The aim of this cross-sectional study is to estimate the prevalence of genital prolapse among married women of Udupi taluk, Karnataka, India. Materials and Methods: A cross-sectional study was conducted on 1256 married women using a structured questionnaire. Women were interviewed in their residence using the Manipal Pelvic Floor Dysfunction screening questionnaire. Result: The mean age of the women participated in this study was 42.3±12.2. The overall prevalence of genital prolapse founddoaj:7d31c7bf4f994a96b7f029ee848d80e8 fatcat:lqnmkvw5tzbirbdvx6mlu2mt2i
more »... n this study was 2% (n=25). Thirty-two percent (n=8) of the women with prolapse had symptoms of urinary incontinence. An association was reported between the age and the genital prolapse. Conclusion: This study shows a 2% (n=25) prevalence of genital prolapse in married women of Udupi Taluk.
Mathematical models for physiological processes aid qualitative understanding of the impact of various parameters on the underlying process. We analyse two such models for human physiological processes: the Mackey-Glass and the Lasota equations, which model the change in the concentration of blood cells in the human body. We first study the local stability of these models, and derive bounds on various model parameters and the feedback delay for the concentration to equilibrate. We then deducearXiv:1810.04783v1 fatcat:tdu5r6haaffsvcf3w2j56kqjsa
more »... nditions for non-oscillatory convergence of the solutions, which could ensure that the blood cell concentration does not oscillate. Further, we define the convergence characteristics of the solutions which govern the rate at which the concentration equilibrates when the system is stable. Owing to the possibility that physiological parameters can seldom be estimated precisely, we also derive bounds for robust stability\textemdash which enable one to ensure that the blood cell concentration equilibrates despite parametric uncertainty. We also highlight that when the necessary and sufficient condition for local stability is violated, the system transits into instability via a Hopf bifurcation, leading to limit cycles in the blood cell concentration. We then outline a framework to characterise the type of the Hopf bifurcation and determine the asymptotic orbital stability of limit cycles. The analysis is complemented with numerical examples, stability charts and bifurcation diagrams. The insights into the dynamical properties of the mathematical models may serve to guide the study of dynamical diseases.
Additionally, Kamath et al.  proved that the RCCFM loses stability via a Hopf bifurcation. ...doi:10.1109/cca.2016.7587992 dblp:conf/IEEEcca/KamathJR16 fatcat:soopsfvsyrew7fwqjlmb4sjye4
This paper describes a first investigation of potential domain expertise in Pinterest. We introduce measures for characterizing the volume and coherence of Pinterest users' pinning activity in a given category, their perceived and declared category-specific expertise and the response from the social network. We use such signals in the context of a supervised ML framework and report encouraging preliminary results on the task of mining potential experts for 4 popular content categories.dblp:conf/um/PopescuKC13 fatcat:leca6cuwufhvbgey6cngevktqu
Pinterest is a fast-growing interest network with significant user engagement and monetization potential. This paper explores quality signals for Pinterest boards, in particular the notion of board coherence. We find that coherence can be assessed with promising results and we explore its relation to quality signals based on social interaction.doi:10.1145/2487788.2487806 dblp:conf/www/KamathPC13 fatcat:fmqqimw4brgprawlgqcqdbtmqy
The presence of multiple comorbidities makes prescription of multiple drugs essential in the elderly. This is attended with an increased risk of potential drug-drug interactions (DDIs). Aim and objectives: To determine the number of DDIs, their severity, and the common DDIs detected in the prescriptions written for elderly patients of a tertiary care teaching hospital and identify any difference in terms of gender. Material and Methods: This was a cross-sectional study. Every prescription wasdoaj:06bb82132d7c4614b4acacc999ff38cf fatcat:uvhx267a7jajhob54xhuwaksxq
more »... reened for potential DDIs using the Lexicomp® software. The detected DDIs were classified as X, avoid combination; D, consider therapy modification; and C, monitor therapy as per the Lexicomp® criteria. Results: The data from 124 patients discharged from the General Medicine department of a tertiary care hospital were evaluated. Of these, 67.7% (82/124) were females. A total of 39 category X-DDIs, 71 category D-DDIs, and 349 category C-DDIs were seen. There was a significant positive correlation between the number of drugs prescribed and the number of DDIs detected (p < 0.001). Conclusion: Our study showed that DDIs were common among elderly patients. A large number of DDIs belong to category C, which requires only monitoring of therapy. Careful planning of the treatment regimen at the time of hospital discharge can decrease the number of drugs prescribed and, thereby, the number of potential DDIs can be decreased.
In this paper, we tackle the problem of predicting what online memes will be popular in what locations. Specifically, we develop data-driven approaches building on the global footprint of 755 million geo-tagged hashtags spread via Twitter. Our proposed methods model the geo-spatial propagation of online information spread to identify which hashtags will become popular in specific locations. Concretely, we develop a novel reinforcement learning approach that incrementally updates the bestdoi:10.1145/2505515.2505579 dblp:conf/cikm/KamathC13 fatcat:jhjfdwko7bfjbes62nkxdlry7i
more »... tial model. In experiments, we find that the proposed method outperforms alternative linear regression based methods.
Aerial Robotic Systems [Working Title]
This chapter deals with the development of vision-based sliding mode control strategies for a quadrotor system that would enable it to perform autonomous tasks such as take-off, landing and visual inspection of structures. The aim of this work is to provide a basic understanding of the quadrotor dynamical model, key concepts in image processing and a detailed description of the sliding mode control, a widely used robust non-linear control scheme. Extensive MATLAB simulations are presented todoi:10.5772/intechopen.86057 fatcat:qmdk7dqwbvcvrnuvnzudauii2e
more »... ance the understanding of the controller on the quadrotor system subjected to bounded disturbances and uncertainties. The vision algorithms developed in this chapter would provide the necessary reference trajectory to the controller enabling it to exercise control over the system. This work also describes, in brief, the implementation of the developed control and vision algorithms on the DJI Matrice 100 to present real-time experimental data to the readers of this chapter.
KRISHNA PALEMS Theorem 1 ( 1 Binomial Bound) Let Y1, Y2 ~ . . . Y, be i.i.d. Bernoulli trials, each with probability of success p . ... . * Department of Computer Science, Stanford University, Stanford, CA 94305(kamath@cs. s t a n f o r d . e d u ) . Supportedby US Army Office Research Grant DAAL-03091-G-0102. ! ...doi:10.1002/rsa.3240070105 fatcat:norvetkdnzfnxppgptdmofglpm
BMJ Case Reports
Contributors YK and AS are responsible for substantial contributions to the conception, design of the work, the acquisition, analysis and interpretation of data. YK, AS and SBS are responsible for drafting the work, revising it critically for important intellectual content. YK and KRA are responsible for final approval of the version published. Competing interests None declared. Patient consent Obtained. Provenance and peer review Not commissioned; externally peer reviewed.doi:10.1136/bcr-2016-217274 pmid:27733420 pmcid:PMC5073709 fatcat:jl5zu7p5hrgdjfjdxju6mhpdvm
*Krishna KamathTwitter, Inc.Aneesh SharmaGoogle, Inc. † In order to use similarity scores that reflect the current state of the graph at the time that the user is signing up, we use the nearreal time ...arXiv:1909.03543v2 fatcat:5jl5ehoy2nfevlgkaoyjnimoiy
We conduct a study of the spatio-temporal dynamics of Twitter hashtags through a sample of 2 billion geo-tagged tweets. In our analysis, we (i) examine the impact of location, time, and distance on the adoption of hashtags, which is important for understanding meme diffusion and information propagation; (ii) examine the spatial propagation of hashtags through their focus, entropy, and spread; and (iii) present two methods that leverage the spatio-temporal propagation of hashtags to characterizedoi:10.1145/2488388.2488447 dblp:conf/www/KamathCLC13 fatcat:zomiow3v6re3xdnx7xnv7bspcu
more »... locations. Based on this study, we find that although hashtags are a global phenomenon, the physical distance between locations is a strong constraint on the adoption of hashtags, both in terms of the hashtags shared between locations and in the timing of when these hashtags are adopted. We find both spatial and temporal locality as most hashtags spread over small geographical areas but at high speeds. We also find that hashtags are mostly a local phenomenon with long-tailed life spans. These (and other) findings have important implications for a variety of systems and applications, including targeted advertising, location-based services, social media search, and content delivery networks.
We study the problem of efficient discovery of trending phrases from high-volume text streams -be they sequences of Twitter messages, email messages, news articles, or other timestamped text documents. Most exisiting approaches return top-k trending phrases. But, this approach neither guarantees that the top-k phrases returned are all trending, nor that all trending phrases are returned. In addition, the value of k is difficult to set and is indifferent to stream dynamics. Hence, we propose andoi:10.1145/2063576.2063937 dblp:conf/cikm/KamathC11 fatcat:opaazarlrje3rbqjuxhr2dsj3e
more »... pproach that identifies all the trending phrases in a stream and is flexible to the changing stream properties.
The rise of social interactions on the Web requires developing new methods of information organization and discovery. To that end, we propose a generative community-based probabilistic tagging model that can automatically uncover communities of users and their associated tags. We experimentally validate the quality of the discovered communities over the social bookmarking system Delicious. In comparison to an alternative generative model (Latent Dirichlet Allocation (LDA), we find that thedoi:10.1145/1810617.1810642 dblp:conf/ht/KashoobCK10 fatcat:nh6g23es6rgghg4th6xfqyybzi
more »... sed communitybased model improves the empirical likelihood of held-out test data and discovers more coherent interest-based communities. Based on the community-based probabilistic tagging model, we develop a novel community-based ranking model for effective communitybased exploration of socially-tagged Web resources. We compare community-based ranking to three state-of-the-art retrieval models: (i) BM25; (ii) Cluster-based retrieval using K-means clustering; and (iii) LDA-based retrieval. We find that the proposed ranking model results in a significant improvement over these alternatives (from 7% to 22%) in the quality of retrieved pages.
« Previous Showing results 1 — 15 out of 390 results