Modeling uncertainties in performance of object recognition

Efficient probability modeling is indispensable for uncertainty quantification of the recognition data. If the model assumptions do not reflect the intrinsic nature of data and associated random variables, then a strong performance measure will most likely fail to come up with a correct match for recognition. In this paper we propose the probability models for two kinds of data obtained with two distinct goals of recognition: identification and discovery. We consider both frequentisi and Bayesian approaches for drawing inferences from the data

Journal of Documentation: A Bibliometrics Analysis (2005-2018)

The purpose of this article was to explore the pattern of publications, using bibliometric analysis, of Journal of Documentation for the period of 2005 to 2018. The results of the study shows that a total of 687 articles were published in the 14 years period from 2005 to 2018, with 71 (10.3%) articles being published the highest total in the year 2018. The study confirmed that the maximum number of articles i.e. 304 (43.9%), were published by single authors, out of which, a large number were on research articles. Out of total number of articles published 228 (33.1%) were 16-20 pages in length. Volume number 74 in 2018 had the highest number of citations with a total of 91 (13.6%). In addition, the study confirmed that the highest number of articles were research articles with a total of 493 (71.7), while others were case studies, conceptual studies, literature reviews, viewpoints and technical papers and short communications, etc

Knowledge Sharing Idiosyncrasies of Research Scholars at CCS Haryana Agricultural University, Hisar, India

The main aim of the present study is to investigate the knowledge sharing behaviour of research scholars at Chaudhary Charan Singh Haryana Agricultural University (CCS HAU), Hisar, India. To understand and reveal the knowledge sharing idiosyncrasies of research scholars, various factors have been covered such as knowledge sharing definition, knowledge sharing attitude, communication channels preferred for knowledge sharing, barriers of knowledge sharing, knowledge sharing motivators, and other factors related to knowledge sharing in an academic institution. For the present study, survey method was adopted with the aid of online structured questionnaire for the purpose of data collection. Total 125 research scholars were approached electronically and shared questionnaires through WhatsApp groups and personal e-mails. Out of total 125, 114 valid questionnaires were collected and considered for final analysis, which representing the response rate of about 91.2 per cent. The findings reveals that about 66% of the respondents were in the opinion that sharing knowledge with peers shall benefit all and majority of the respondents possessed a positive attitude towards knowledge sharing and were aware of its importance in their learning process. The face-to-face interaction for sharing knowledge among the respondents is the most preferred communication channel for majority of the respondents (81.58%); however, some major barriers of knowledge sharing among the research scholars have also been noticed. In order to overcome these barriers, the researchers suggest that academic institutions may foster cordial relationship among the research scholars by providing sufficient interaction opportunities. In the end, practical implication of this study has also been discussed

Ensemble Boosted Tree based Mammogram image classification using Texture features and extracted smart features of Deep Neural Network

/n This work proposes a technique of breast cancer detection from mammogram images. It is a multistage process which classifies the mammogram images into benign or malignant category. During preprocessing, images of Mammographic Image Analysis Society (MIAS) database are passed through a couple of filters for noise removal, thresholding and cropping techniques to extract the region of interest, followed by augmentation process on database to enhance its size. Features from Deep Convolution Neural Network (DCNN) are merged with texture features to form final feature vector. Using transfer learning, deep features are extracted from a modified DCNN, whose training is performed on 69% of randomly selected images of database from both categories. Features of Grey Level Co-Occurrence Matrix (GLCM) and Local Binary Pattern (LBP) are merged to form texture features. Mean and variance of four parameters (contrast, correlation, homogeneity and entropy) of GLCM are computed in four angular directions, at ten distances. Ensemble Boosted Tree classifier using five-fold cross-validation mode, achieved an accuracy, sensitivity, specificity of 98.8%, 100% and 92.55% respectively on this feature vector

New Numerical And Computational Methods Leveraging Dynamical Systems Theory For Multi-Body Astrodynamics

Many proposed interplanetary space missions, including Europa Lander and Dragonfly, involve trajectory design in environments where multiple large bodies exert gravitational influence on the spacecraft, such as the Jovian and Saturnian systems as well as cislunar space. In these contexts, an analysis based on the mathematical theory of dynamical systems provides both better insight as well as new tools to use for the mission design compared to classic two-body Keplerian methods. Indeed, a rich variety of dynamical phenomena manifest themselves in such systems, including libration point dynamics, stable and unstable mean-motion resonances, and chaos. To understand the previously mentioned dynamical behaviors, invariant manifolds such as periodic orbits, quasi-periodic invariant tori, and stable/unstable manifolds are the major objects whose interactions govern the local and global dynamics of relevant celestial systems. This work is focused on the development of numerical methodologies for computing such invariant manifolds and investigating their interactions. In Chapter 2, after a study of persistence of mean-motion resonances in the planar circular restricted 3-body problem (PCRTBP), techniques for computing the stable/unstable manifolds attached to resonant periodic orbits and heteroclinics corresponding to resonance transitions are presented. Chapter 3 focuses on the development of accurate and efficient parameterization methods for numerical calculation of whiskered quasi-periodic tori and their attached stable/unstable manifolds, for periodically-forced PCRTBP models. As part of this, a method for Levi- Civita regularization of such periodically-forced systems is introduced. Finally, Chapter 4 presents methods for combining the previously mentioned parameterizations with knowledge of the objects’ internal dynamics, collision detection algorithms, and GPU computing to very rapidly compute propellant-free heteroclinic connecting trajectories between them, even in higher dimensional models. Such heteroclinics are key to the generation of chaos and large scale transport in astrodynamical systems.Ph.D

Thyroid ophthalmopathy in an adolescent girl: a case report

A 14 year old girl presented with protrusion of both the eyes for duration of 3 months and pain, redness and watering of right eye for 20 days. On examination, she was thin built, poorly nourished and the thyroid gland was found to be enlarged. Both eyes were proptosed and there was incapability of complete closure of the eyelids on both sides. On right eye, conjunctiva was congested and there was a corneal lesion seen inferomedially with an epithelial defect. CT scan of the orbit revealed picture of thyroid ophthalmopathy. Thyroid profile revealed picture suggestive of hyperthyroidism and anti-thyroid peroxidase antibody was found to be very high. She was diagnosed as a case of thyroid ophthalmopathy both eyes with exposure keratitis right eye. She was treated with anti-thyroid medication along with conservative treatment for ocular symptoms and lateral tarsorrhaphy of right eye for exposure keratopathy. Pulse steroid therapy was started and subsequent follow up showed resolution of the signs

Modeling and Sentiment Analysis of Online Reviews in Hospitality Industry

With the great extent of use of smartphones and the internet, the online hotel booking service providers have excessively increased thus producing more user-generated content in the form of reviews and comments about the customer experience. These reviews of visited customer’s aids hotel management personnel not only to forecast the future demand but also to implement effective strategies for better service. It is becoming a tuff job in this scenario for the hotel management to get exact information from the wide range of reviews. In this analysis, it is to identify the classification of the sentiment from the customer reviews. The classification can be done with text mining approach with the source of information. Two dictionaries are developed for the usage of data classification around 431 reviews taken from Tripadvisor.com and Booking.com. Finally Latent Dirichent Allocation (LDA) modeling algorithm is applied to identify related topics and it was used to sort out the issues in consumer sentiment analysis.     Study findings revealed that majority of the reviews were with positive sentiments and the topics found best with hospitality domain and sentiment term were such as “food”, “hospitality”, “room”, “people”, “friendly” , “Relax”, “feelings”, and “holiday” as hospitality terms and “Strong Positive” and “Ordinary Positive” as sentiment terms

Mode of delivery and outcome of breech presentation: a prospective observational study in a tertiary centre

Background: Breech presentation is the commonest malpresentation with the incidence of 3-4% at term. This study was done with the objective of studying the mode of delivery in breech presentation and to compare the maternal and fetal outcome in patients delivered vaginally to those delivered by cesarean section.Methods: This prospective observational study was conducted in Vanivilas Hospital, affiliated to Bangalore Medical College and Research Institute, from June 2014 to May 2015. The study group included 509 patients with breech presentation who were studied with respect to their gestational age, birth weight, type of breech, mode of delivery, maternal and perinatal outcome.Results: The incidence of breech presentation was 2.92% (509) among 17454 total deliveries with the incidence of 3.17% in primi and 2.73% in multies. 193 (38%) patients had vaginal breech delivery and 316 (62%) delivered by LSCS. Apgar score of less than 7 at 1 minute was seen with 21.42% of vaginally delivered fetuses and 9.09% of fetuses delivered by cesarean section. The perinatal mortality was 1.6% (8 cases) in vaginal group 0.8% (4 cases) in LSCS group. The short term maternal complications in LSCS group was 7.62% and in vaginal delivery group was 3.09%.Conclusions: The short term maternal morbidity is higher in patients with cesarean section compared to those with vaginal breech delivery. Perinatal outcome is better in babies delivered by cesarean section. Still vaginal breech delivery can be an option for breech babies with proper selection and when conducted by a skilled obstetrician