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Performance of pradhan mantri fasal bima yojana: Perception of farmers in rural bangalore
Crop insurance is an agricultural development program supporting the sustainability of farmers. PradhanMantriFasalBimaYojana crop insurance scheme was introduced to provide insurance cover, financial stability, innovative and modern methods of agricultural practice. The study primarily focuses on the reasons for enrollment, benefits, challenges and suggestions regarding the PradhanMantriFasalBimaYojana with respect to farmers of Rural Bengaluru. A qualitative thematic analysis using a primary study reveals PMFBY as a source of financial security and financial stability with reduced premium that increases the confidence level among the farmers. 2019 SERSC. -
My Motherhood, My Way: A Sociological Study of Contemporary Employed Mothers in Kolkata
Motherhood in India has been understood primarily by placing mothers in the domestic space. A mother is constructed as a protector and the complete caregiver of her children. But there have been significant changes in the status of Indian women recently. In the 21st century, with suitable qualifications and employment opportunities, women have the choice to be economically independent and career-driven, which has a profound impact on their roles and responsibilities as protectors and caregivers in the home. It is essential to study and document how women in this generation have started to redefine their roles and negotiate what a mothers duties are at home. This study aims to make a systematic inquiry to understand the issues and challenges faced by employed mothers in everyday life and how they balance their career and childcare activities. Researchers investigate this through a qualitative study on mothers employed in different types of professions in the city of Kolkata. Data was collected by conducting in-depth interviews of around twenty-nine urban, upper-middle class employed mothers from different professional backgrounds to have a set of diverse narratives about their experiences and struggles. The key findings of this study provide an insight into the challenges that mothers face and their balancing mechanisms. Such studies have the scope to motivate many employed mothers by presenting some cases of women who have succeeded in breaking the stereotypical ideas of motherhood and are redefining their stories in more humane terms. 2021. Journal of International Womens Studies. -
A happy mother raises a happy child: insights from employed mothers in Bengali families in Kolkata
The present study explores the complexities of motherhood in Bengali middle-class families, where mothers are traditionally viewed as primary caregivers. Despite societal shifts and increased female workforce participation, mothers still face pressure to prioritize intensive mothering. Through qualitative analysis, the research explores how employed mothers balance work and childcare responsibilities, shedding light on their agency and empowerment within patriarchal structures. Findings reveal a nuanced landscape where mothers navigate societal expectations while striving for autonomy. Support systems, changing socio-economic dynamics, and technological advancements contribute to reshaping maternal roles. Mothers, though not uniformly identifying as feminists, challenge traditional norms, embracing an egalitarian approach to mothering. The study underscores the resilience of mothers in negotiating patriarchal constraints, highlighting their capacity to foster empowerment for themselves and their children within familial and societal contexts. This qualitative study conducted in-depth interviews with 37 employed mothers representing diverse professions and roles. 2025 Informa UK Limited, trading as Taylor & Francis Group. -
Real-time video segmentation using a vague adaptive threshold
For the last two decades, video shot segmentation has been a widely researched topic in the field of content-based video analysis (CBVA). However, over the course of time, researchers have aimed to improve upon the existing methods of shot segmentation in order to gain accuracy. Video shot segmentation or shot boundary analysis is a basic and vital step in CBVA, since any error incurred in this step reduces the precision of the other steps. The shot segmentation problem assumes greater proportions when detection is preferred in real time. A spatiotemporal fuzzy hostility index (STFHI) is proposed in this work which is used for edge detection of objects occurring in the frames of a video. The edges present in the frames are treated as features. Correlation between these edge-detected frames is used as a similarity measure. In a real-time scenario, the incoming images are processed and the similarities are computed for successive frames of the video. These values are assumed to be normally distributed. The gradients of these correlation values are taken to be members of a vague set. In order to obtain a threshold after defuzzification, the true and false memberships of the elements are computed using a novel approach. The threshold is updated as new frames are buffered in and is referred to as the vague adaptive threshold (VAT). The shot boundaries are then detected based on the VAT. The VAT for detecting the shot boundaries is determined by using the three-sigma rule on the defuzzified membership values. The effectiveness of the real-time video segmentation method is established by an experimental evaluation on a heterogeneous test set, comprising videos with diverse characteristics. The test set consists of videos from sports, movie songs, music albums, and documentaries. The proposed method is seen to achieve an average F1 score of 0.992 over the test set consisting of 15 videos. Videos from the benchmark TRECVID 2001 are selected for comparison with other state-of-the-art-methods. The proposed method achieves very high precision and recall, with an average F1 score of 0.939 on the videos chosen from the TRECVID 2001 dataset. This is a substantial improvement over the other existing methods. 2020 Elsevier Inc. -
Automated hyperspectral image clustering using multilevel quantum differential evolution on quantum /
Patent Number: 202141013977, Applicant: Tulika Dutta.
Hyperspectral images are data cubes composed of huge spectral information. The spectral bands contain abundant information but are also full of redundant data. The huge information content also increases the space and time complexity to deal with hyperspectral images and due to Hughes phenomena, the accuracy also decreases with increase in information content. The constraint of research data and ground truth images of hyperspectral images is a real limitation of efficiently developing algorithms, especially supervised ones which require priori knowledge about the dataset. -
Automatic detection of violence activity-A tool for women's safety /
Patent Number: 202041006858, Applicant: Debanjan Konar.
Human activity detection has gained popularity owing to wide range of applications from game development to surveillance. Recent development of Deep Pose (Human pose detection using deep neural network. -
A microcontroller based low cost electronic locking system using 2-way authentication /
Patent Number: 202041036194, Applicant: Siddhartha Bhattacharyya.
Multi-factor authentication aims in prevention of unauthorized access to any secured system, and the 2-way or 2-factor verification is one of the most effective and indispensable solution for this purpose. In this work, a low cost electronic locking system using 2-way authentication has been conceived to provide secured access to any assets or resources. -
Hybrid Computational Intelligence: Challenges and Applications
Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of hybrid computation as well as the history of their development. Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems. 2020 Elsevier Inc. -
Deep learning: Research and applications
This book focuses on the fundamentals of deep learning along with reporting on the current state-of-art research on deep learning. In addition, it provides an insight of deep neural networks in action with illustrative coding examples. Deep learning is a new area of machine learning research which has been introduced with the objective of moving ML closer to one of its original goals, i.e. artificial intelligence. Deep learning was developed as an ML approach to deal with complex input-output mappings. While traditional methods successfully solve problems where final value is a simple function of input data, deep learning techniques are able to capture composite relations between non-immediately related fields, for example between air pressure recordings and English words, millions of pixels and textual description, brand-related news and future stock prices and almost all real world problems. Deep learning is a class of nature inspired machine learning algorithms that uses a cascade of multiple layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The learning may be supervised (e.g. classification) and/or unsupervised (e.g. pattern analysis) manners. These algorithms learn multiple levels of representations that correspond to different levels of abstraction by resorting to some form of gradient descent for training via backpropagation. Layers that have been used in deep learning include hidden layers of an artificial neural network and sets of propositional formulas. They may also include latent variables organized layer-wise in deep generative models such as the nodes in deep belief networks and deep boltzmann machines. Deep learning is part of state-of-the-art systems in various disciplines, particularly computer vision, automatic speech recognition (ASR) and human action recognition. Tutorials on deep learning framework with focus on tensor flow, keras etc. Numerous worked out examples on real life applications Illustrative diagrams and coding examples. 2020 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved. -
Quantum machine learning
Quantum-enhanced machine learning refers to quantum algorithms that solve tasks in machine learning, thereby improving a classical machine learning method. Such algorithms typically require one to encode the given classical dataset into a quantum computer, so as to make it accessible for quantum information processing. After this, quantum information processing routines can be applied and the result of the quantum computation is read out by measuring the quantum system. While many proposals of quantum machine learning algorithms are still purely theoretical and require a full-scale universal quantum computer to be tested, others have been implemented on small-scale or special purpose quantum devices. New trends in Machine Learning based on Quantum Computing and Quantum Algorithms Examples on real life applications Illustrative diagrams and coding examples. 2020 Walter de Gruyter GmbH, Berlin/Boston. All rights reserved. -
Intelligent Environmental Data Monitoring for Pollution Management: A volume in Intelligent Data-Centric Systems
Intelligent Environmental Data Monitoring for Pollution Management discusses evolving novel intelligent algorithms and their applications in the area of environmental data-centric systems guided by batch process-oriented data. Thus, the book ushers in a new era as far as environmental pollution management is concerned. It reviews the fundamental concepts of gathering, processing and analyzing data from batch processes, followed by a review of intelligent tools and techniques which can be used in this direction. In addition, it discusses novel intelligent algorithms for effective environmental pollution data management that are on par with standards laid down by the World Health Organization. To learn more about Elseviers Series, Intelligent Data-Centric Systems, please visit this link: https://www.elsevier.com/books-and-journals/book-series/intelligent-data-centric-systems-sensor-collected-intelligence. 2021 Elsevier Inc. All rights reserved. -
Decoding the X-Ray Flare from MAXI J0709-159 Using Optical Spectroscopy and Multiepoch Photometry
We present a follow-up study on the recent detection of two X-ray flaring events by MAXI/Gas Slit Camera observations in soft and hard X-rays from MAXI J0709-159 in the direction of HD 54786 (LY CMa), on 2022 January 25. The X-ray luminosity during the flare was around 1037 erg s-1 (MAXI), which got reduced to 1032 erg s-1 (NuSTAR) after the flare. We took low-resolution spectra of HD 54786 from the 2.01 m Himalayan Chandra Telescope and the 2.34 m Vainu Bappu Telescope (VBT) facilities in India, on 2022 February 1 and 2. In addition to H? emission, we found emission lines of He i in the optical spectrum of this star. By comparing our spectrum of the object with those from the literature we found that He i lines show variability. Using photometric studies we estimate that the star has an effective temperature of 20,000 K. Although HD 54786 is reported as a supergiant in previous studies, our analysis favors it to be evolving off the main sequence in the color-magnitude diagram. We could not detect any infrared excess, ruling out the possibility of IR emission from a dusty circumstellar disk. Our present study suggests that HD 54786 is a Be/X-ray binary system with a compact object companion, possibly a neutron star. 2022. The Author(s). Published by the American Astronomical Society. -
Insights on the Optical and Infrared Nature of MAXI J0709-159: Implications for High-Mass X-ray Binaries
In our previous study (Bhattacharyya et al., 2022), HD 54786, the optical counterpart of the MAXI J0709-159 system, was identified to be an evolved star, departing from the main sequence, based on comparisons with non-X-ray binary systems. In this paper, using color-magnitude diagram (CMD) analysis for High-Mass X-ray Binaries (HMXBs) and statistical t-tests, we found evidence supporting HD 54786s potential membership in both Be/X-ray binaries (BeXRBs) and supergiant X-ray binaries (SgXBs) populations of HMXBs. Hence, our study points towards dual optical characteristics of HD 54786, as an X-ray binary star and also belonging to a distinct evolutionary phase from BeXRB towards SgXB. Our further analysis suggests that MAXI J0709-159, associated with HD 54786, exhibits low-level activity during the current epoch and possesses a limited amount of circumstellar material. Although similarities with the previously studied BeXRB system LSI +61? 235 (Coe et al., 1994) are noted, continued monitoring and data collection are essential to fully comprehend the complexities of MAXI J0709-159 and its evolutionary trajectory within the realm of HMXBs. 2024 Societe Royale des Sciences de Liege. All rights reserved. -
Identification of emission-line stars in transition phase from pre-main sequence to main sequence
Pre-main-sequence (PMS) stars evolve into main-sequence (MS) phase over a period of time. Interestingly, we found a scarcity of studies in existing literature that examine and attempt to better understand the stars in PMS to MS transition phase. The purpose of this study is to detect such rare stars, which we named as 'transition phase' (TP) candidates-stars evolving from the PMS to the MS phase. We identified 98 TP candidates using photometric analysis of a sample of 2167 classical Be (CBe) and 225 Herbig Ae/Be (HAeBe) stars. This identification is done by analysing the near-and mid-infrared excess and their location in the optical colour-magnitude diagram. The age and mass of 58 of these TP candidates are determined to be between 0.1-5 Myr and 2-10.5 M?, respectively. The TP candidates are found to possess rotational velocity and colour excess values in between CBe and HAeBe stars, which is reconfirmed by generating a set of synthetic samples using the machine learning approach. 2021 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
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