Content-Based Image Retrieval using Deep Learning

A content-based image retrieval (CBIR) system works on the low-level visual features of a user input query image, which makes it difficult for the users to formulate the query and also does not give satisfactory retrieval results. In the past image annotation was proposed as the best possible system for CBIR which works on the principle of automatically assigning keywords to images that help image retrieval users to query images based on these keywords. Image annotation is often regarded as the problem of image classification where the images are represented by some low-level features and the mapping between low-level features and high-level concepts (class labels) is done by some supervised learning algorithms. In a CBIR system learning of effective feature representations and similarity measures is very important for the retrieval performance. Semantic gap has been the key challenge in the past for this problem. A semantic gap exists between low-level image pixels captured by machines and the high-level semantics perceived by humans. Machine learning has been exploited to bridge this gap in the long term. The recent successes of deep learning techniques especially Convolutional Neural Networks (CNN) in solving computer vision applications has inspired me to work on this thesis so as to solve the problem of CBIR using a dataset of annotated images

Multiscale materials modelling using DFT-based localization relationships

With the tremendous amount of research done in the field of numerical methods for engineering the number of possible applications as well as users have drastically increased. However, mostly these tools have been developed independently for solving problems of a particular kind, by particular methods on a particular scale, which leads to some limitations. One of these limitations, interoperability, will be dealt with in this thesis and a methodology to resolve it for a small use-case of finite element problems at a continuum scale will be proposed.Multiscale modelling is the need of the hour, and this can be con rmed from the fact that several initiatives have been taken to bring together researchers from di erent domains by formation of projects like Integrated Computational Materials Engineering (ICME), Materials Genome Initiative etc. This increasing interest can be pertained to the fact that there is a need for creating new materials with desired e ective properties for new applications like Additive Manufacturing (AM). Until recently the discovery of new materials was based on empirical methods of trial and error, which takes roughly twenty years to bring in a new material into manufacturing. Therefore, it is important to address these two difficult problems. First is Multiscale modelling, which enables communication between constitutive models at di erent length scales, thus improving accuracy of failure predictions and second, is Accelerated Material Discovery, which can reduce the development time of new materials with desired properties. As it turns out, both these problems are closely related and can be addressed simultaneously. The key to success in both these areas is making problem solving data driven, i.e., convertint these non-trivial problems Big Data friendly so that the techniques from Data Science can be used for building scalable, robust and computationally efficient solutions. Another good reason to use data science for these problems is that it makes data reusable i.e., data that was produced during solution of one problem can be used in solving another problem by establishing syntactic material databases, where not only e ective properties but also the internal structure of the materials is readily available. In this thesis, one such mathematical framework called Material Knowledge Systems (MKS) is used to solve both the above mentioned problems. MKS is derived from the Statistical Continuum theories, and has been successfully implemented in real world problems. MKS is based on the rigorous mathematical framework called Material Sensitive Design (MSD), which is further derived from generalized homogenization theories. MSD provides a rigorous methodology for quanti cation of the internal structure of the material, which spans multiple length and time scales with a microstructure function . But the biggest achievement of MSD is that it allows us to incorporate the n-point spatial correlations in the homogenization theories. Also it addresses the problem of localization, which has been under addressed as compared to the homogenization problems. The use of n-point spatial correlations to represent the internal structure of the material is very rigorous, thus, the amount of structural information is substantially large. To deal with this increased amount of information, dimensional reduction techniques like Principal Component Analysis, Naive Bayes etc., from the eld of Data Science. Using these techniques, the material designer can not only visualize the structure-property linkages, but can also begin to solve the inverse problem of creating microstructures using hybrid processes which exhibit the desired effective properties. These linkages are also called Property-Structure-Process (PSP) relations. Establishment of such PSP linkages will change the way how materials are created in the future

Fair CRISP-DM: Embedding Fairness in Machine Learning (ML) Development Life Cycle

With rapid adoption of machine learning (ML) technologies, the organizations are constantly exploring for efficient processes to develop such technologies. Cross-industry standard process for data mining (CRISP-DM) provides an industry and technology independent model for organizing ML projects’ development. However, the model lacks fairness concerns related to ML technologies. To address this important theoretical and practical gap in the literature, we propose a new model – Fair CRISP-DM which categorizes and presents the relevant fairness challenges in each phase of project development. We contribute to the literature on ML development and fairness. Specifically, ML researchers and practitioners can adopt our model to check and mitigate fairness concerns in each phase of ML project development

Computational study of non-isothermal slag eye formation and its effects on ladle refining

Ladle refining is one of the most important aspects of high-quality steel production. Ladle argon purging which facilitates the refining process also leads to the unwarranted opening of the slag cover known as Slag Eye-opening and has a deleterious effect on the quality of steel. Slag eye-opening has been analysed in past under isothermal conditions whereas ladle refining is a transient and non-isothermal operation. The current study deals with the modelling of slag-eye opening and its effects on ladle refining under non-isothermal conditions. The bubble plume is modelled with the help of Discrete Phase modelling (DPM) coupled with a discrete random walk model for including the particle level turbulence. Temperature-dependent thermophysical properties of slag are obtained from FactSage. Opening of slag-metal interface cools the slag-eye region, which causes changes in the thermophysical properties of the slag phase. These changes are then reflected in the flow characteristics of this complex fluid. The slags flow profile and eye formation are compared and explained between cold modelling techniques and actual ladle metallurgy. The consequences of changing thermophysical prop during ladle refining manifest in their influence on the overall mass transfer coefficient and the kinetics of desulfurization. This can be achieved without the requirement to solve computationally demanding species transport equations, thereby enhancing the practical efficiency of this approach.Comment: 21 pages, 17 figures, 8 table

Starving Millions and Right to Food

Right to food is a basic human right. In India, with increase in population the demand for food is on the rise. Providing adequate food to the teeming millions has been a challenge for the government. This paper explores the origin of right to food while placing the emphasis on the realisation of the right in its true sense. It argues that the state has failed to secure adequate food to its citizenry because of its misplaced priorities and lack of political will. It calls for strengthening of public distribution system and buffer stock to guarantee adequate food security to people

Optical nanoantennas as cavities : nanoscale control of couplings strength and single photon emission

Optical nanoantennas confine light on the nanoscale, enabling strong light-matter interactions with potential for ultra-compact optical devices. Apart from the direct applications in optical nanoscopy and sensing, nanoantennas can strongly enhance the spontaneous emission rate of single photon emitters. A nanoantenna, acting as a nanocavity, enables high photon output due to its high radiative losses associated with plasmonic resonances and thus pave the way for compact, bright, and pure single photon sources with applications in quantum technologies. The sub-wavelength field localization at the nanoantenna causes a vectorial field distribution with non-zero field components in all dimensions. The efficiency of coupling between an emitter such as single molecule and nanoantenna will thus strongly depend on the spatial overlap of the emitter's dipole with the nanoantenna field. In order to achieve such coupling, careful nanopositioning of the emitter, in its location as well as the orientation, within the nanocavity field is required. Therefore, the full vectorial characterization of the emitter-nanoantenna is crucial to maximize the coupling strength. This thesis addresses the aforementioned issues and studies the controlled nanoscale interaction of a single molecule with a resonant nanoantenna. To this end we first fabricate nanoantennas on the vertex of a fiber tip using focused-ion-beam milling and use a near-field technique for the nanopositioning control. In the first experiment, we investigate the excitation properties of a resonant dipole nanoantenna by mapping its vectorial near-field distribution with molecular resolution. The nanoantenna tip is scanned over specifically selected single molecules to map x-, y-, and z-field components. In addition to characterization of the vectorial field, we show the apparent position of the molecule shifts up to 20 nm depending on their orientation with important implications for localization microscopy. Next, our unprecedented experimental approach allows us to examine an often overlooked, but important near-field concept of nanoantennas, local interference. The highly structured vectorial amplitude and phase distribution of the nanoantenna overlaps with the exciting far-field to create this local interference. We perform a detailed study through direct observation and show an example of exploiting this local interference to shape and control the near-field of the nanoantenna. Lastly, we quantify the vectorial interaction of a molecule-nanoantenna cavity system by mapping the coupling strength g with 5 nm spatial resolution. We show that for a molecule's optimal position at the nanoantenna, the coupling rate reaches up to g_max= 206 GHz, much higher than for any conventional cavities. Such a large coupling provides ideal conditions for fast and pure non-classical photon emission, enabling a single photon source with an emission rate above 1 GHz at room-temperatureNanoantenas ópticas confinan la luz a una escala nanométrica, permitiendo interacciones fuertes entre la luz y la materia con potencial en dispositivos ópticos ultra-compactos. Aparte de las aplicaciones directas en nanoscopía y detección, nanoantenas pueden aumentar fuertemente la tasa de emisión espontánea de un emisor de fotón único. Una nanoantena, actuando como una nanocavidad, permite un rendimiento elevado de fotones debido a sus pérdidas radiativas asociadas con las resonancias plasmónicas y por tanto allana el camino para fuentes de fotón único compactas y brillantes con aplicaciones en tecnologías cuánticas. La localización sublongitud de onda de campos en la nanoantena crea una distribución vectorial de campos con componentes no nulas en todas las dimensiones. La eficiencia del acoplamiento entre un emisor como una molécula única y una nanoantena dependerá en gran medida de la superposición espacial del momento dipolar del emisor y el campo de la nanoantena. Con el fin de lograr este acoplamiento, el posicionamiento preciso del emisor, tanto su ubicación como su orientación, dentro de la nanocavidad es necesario. Por tanto, la caracterización vectorial del sistema emisor-nanoantena es crucial para maximizar la fuerza de su acoplamiento. Esta tesis aborda los temas antes mencionados y estudia la interacción controlada de una molécula única junto con una nanoantena. Con este fin primero fabricamos las nanoantenas en el vértice de una fibra óptica utilizando un haz de iones enfocado fresado y usamos una técnica de campo cercano para controlar el nanoposicionamiento. En el primer experimento, investigamos las propiedades de excitación de una nanoantena dipolar resonante al mapear su distribución de campo cercano con una resolución molecular. La punta de la nanoantena se escanea sobre moléculas únicas seleccionadas específicamente para mapear las componentes x-, y-, y z-del campo. Además de la caracterización del campo vectorial, se demuestra que la posición aparente de la molécula se desplaza hasta arriba 20 nm, dependiendo de su orientación, con importantes implicaciones para la microscopía de localización. A continuación, nuestro enfoque experimental sin precedentes nos permite examinar un concepto de campo cercano menudo pasado por alto, pero uno importante para las nanoantenas, la interferencia local. La distribución vectorial altamente estructurada de la amplitud y fase de la nanoantena se solapa con el campo lejano excitante para crear esta interferencia local. Realizamos un estudio detallado a través de la observación directa y damos un ejemplo de cómo aprovechar de esta interferencia local para dar forma y controlar el campo cercano de la nanoantena. Por último, se cuantifica la interacción vectorial de un sistema molécula-nanoantena mapeando la fuerza de acoplamiento g con una resolución espacial de 5 nm. Demostramos que para la posición óptima de una molécula en la nanoantena, la tasa de acoplamiento llega hasta g_max = 206 GHz, muy superior a todas las cavidades convencionales. Tal acoplamiento grande proporciona las condiciones ideales para la emisión de fotones no clásicas de forma rápida y puro, haciendo posible una fuente de fotones únicas con una tasa de emisión por encima de 1 GHz a temperatura ambientePostprint (published version

Isolation, characterization and morphological study of Azotobacter isolates

Among the diazotrops, great attention has been paid to the genus Azotobacter and its role in increasing the growth and health of plants. In the present study, forty two strains of Azotobacter were isolated from soil. These strains were purified and characterized through microscopical and biochemical test for cell shape, pigmentation, colony size, Gram reaction and catalase activity were identified as Azotobacter sp These strains showed wide variability to these characters. Among 42 isolates, 7 were single cocci, 7 coccidal chain and 4 were cocci in clumps. Majority of isolates i.e. 24, were small, medium and large rod shaped. Thirty two isolates were Gram –ve, catalase positive and 10 were Gram +ve, catalase negative. Finally from these isolates, twenty two were confirmed as Azotobacter strains on cyst formation. The carbon-source utilization pattern revealed that out of 22 strains that 16 strains resembled the characters of A. chroococcum, 3 matched with A. vinelandii and 3 with A. beijerinckii. All 22 isolates were analyzed for its nitrogen fixing ability by using Microkjeldhal method. The highest amount of N2 (18.88 mg g-1 sucrose) was fixed by Azo-SBT 72 while lowest (6.04 mg g-1 sucrose) by Azo-SUR 25 strain. However, injudicious and hazardous use of chemical fertilizers have degraded the soil health and there is need of ecofriendly management of soil by screening and hunting of potential nitrogen fixing strains to protect the soil environment and health. In this context, biofertilizers hunting natural environment is the need of soil to ensure better health of future generations

Faith, heresy and economic theory

John Rapley’s recent book Twilight of the Money Gods: Economics as a Religion and How It All Went Wrong is a riveting tale of the development of economic thought. “This fundamental critique of economics,” writes Avinash Persaud in his review (“The Corruption of Economics,” EPW, 24 February 2018), “is a must-read for all.” I argue here that although this is indeed a very important book for our times, one cannot agree with the fi rst part of Persaud’s assessment

Systemic Variety of Anaplastic Large - Cell Lymphoma

We present a case report of a patient with very aggressive course of anaplastic large-cell lymphoma. The patient had nonspecific complaints of easy fatigability and progressive breathlessness and had generalized lymphadenopathy. Initial investigations revealed pancytopenia. Bone marrow examination revealed presence of atypical cells. Liver biopsy showed portal tracts infiltrated by atypical lymphoid cells. Fine-needle aspiration of the lymph node finally confirmed anaplastic large-cell lymphoma. Patient succumbed to the illness

Nanoscale mapping and control of antenna-coupling strength for bright single photon sources

Cavity QED is the art of enhancing light-matter interaction of photon emitters in cavities, with opportunities for sensing, quantum information and energy capture technologies. To boost emitter-cavity interaction, i.e. coupling strength , ultrahigh quality cavities have been concocted yielding photon trapping times of µs to ms. However, such high-Q cavities give poor photon output, hindering applications. To preserve high photon output it is advantageous to strive for highly localised electric fields in radiatively lossy cavities. Nanophotonic antennas are ideal candidates combining low-Q factors with deeply localised mode volumes, allowing large , provided the emitter is positioned exactly right inside the nanoscale mode volume. Here, with nanometre resolution, we map and tune the coupling strength between a dipole nanoantenna-cavity and a single molecule, obtaining a coupling rate of max ~ 200 GHz. Together with accelerated single photon output, this provides ideal conditions for fast and pure non-classical single photon emission with brightness exceeding 10E9 photons/sec. Clearly, nanoantennas acting as “bad” cavities offer an optimal regime for strong coupling , to deliver bright on-demand and ultrafast single photon nanosources for quantum technologies.Peer ReviewedPostprint (author's final draft