Parallel computing using the multiscale finite element method for sub-surface flow models

Subsurface flows, occurring in groundwater movement and production of hydrocarbons in the petroleum industry, are affected by the heterogeneity of the medium varying over large scales. In this thesis, we have used state of the art multiscale methods to solve one such flow model, influenced by high contrast permeability field. The focus is on the elliptic pressure equation which is solved on both fine and coarse scale for comparison purposes. Shared memory parallelism has been achieved for generating basis functions, which is computationally the most expensive portion of the multiscale implementation. Parallel systematic spectral enrichment using the GMsFEM (Generalized Multiscale Finite Element Method) is the key feature of the current work and has been compared with the MsFEM (Multiscale Finite Element Method). Efficiency of algorithmic implementation has been first tabulated for a two-dimensional finite element code using the MATLAB parallel computing toolbox and also has been given a more generalized form using a three-dimensional finite element code written in OpenMP (Open Multiprocessing) and C++. The timing comparison shows a significant decline in the execution time for the algorithms. It indicates that a higher level of enrichment and desired accuracy is achievable for large scale problems. Computational time gain and fewer memory requirements are two key features achieved in this work. Distributed parallel computing can further be implemented to achieve mass parallelism through which one can solve large problems accurately and efficiently when compared to benchmark fine scale solutions where global system solver, memory requirements and execution time become significant issues.Civil, Architectural, and Environmental Engineerin

Study of menstrual disorders and its correlation with BMI in adolescents

Background: Due to change in lifestyle, habits, diet, the prevalence of obesity has increased. Excess weight and obesity are associated with irregular menstrual cycles, which reduce fertility and increase hormone-sensitive cancers. Obesity is considered to cause abnormality of sex steroid hormone balance. Irregular menstruation is more frequently observed in women who became obese during puberty than in those who were obese during infancy. Obesity has a strong association with infertility and menstrual irregularities. Methods: This cross-sectional study was conducted at Durgapur (West Bengal), where total 600 adolescent girls aged 12-17 years from DAV Model School, Durgapur and GMPS High School, Durgapur were selected. Results: Out of total 600 girls, 119 girls (19.8%) had BMI<18.5 kg/m2, 357 girls (59.5%) had BMI between 18.5-24.99 kg/m2 and 124 girls (20.7%) had BMI>25 kg/m2. Only 68 girls (57.1%) with less BMI, 205 girls (57.4%) with normal BMI and 62 girls (50%) with BMI>25 kg/m2 had dysmenorrhoea. Only 19 girls (16%) with less BMI, 46 girls (12.9%) with normal BMI and only 15 girls (12.1%) with higher BMI had menorrhagia. Only 4 girls (3.4%) with less BMI, 14 girls (3.9%) with normal BMI and 12 girls (9.7%) with high BMI had hypomenorrhoea. Only 10 girls (8.4%) with less BMI, 37 girls (10.4%) with normal BMI and only 28 girls (22.5%) with high BMI had irregular cycles. Only 5 girls (4.2%) with less BMI, 12 girls (3.4%) with normal BMI and only 11 girls (8.9%) with high BMI had oligomenorrhoea. Only 2 girls (1.7%) with less BMI, 3 girls (0.8%) with normal BMI and only 4 girls (3.2%) with higher BMI had polymenorrhoea. Only 43 underweight girls (36.1%), 166 girls (46.5%) with normal BMI and 68 girls (54.8%) with higher BMI had premenstrual symptoms. Conclusions: Mean BMI was found 21.6±3.64 kg/m2. High BMI girls had more oligomenorrhoea, hypomenorrhoea, irregular menstrual cycles, polymenorrhoea, premenstrual symptoms and less dysmenorrhea and menorrhagia comparatively to normal BMI girls and underweight girls.

The role of forceps in current obstetrics: a retrospective study

Background: Forceps has been an integral part of the obstetrician’s armamentarium. Obstetric forceps was designed to assist extraction of the fetal head and thereby accomplish the delivery of the fetus. In this present day when there is universal concern regarding the alarming rise of cesarean section rates, a better understanding of this instrument will help the patient as well as the obstetrician. Methods: This was a retrospective observational study done over a two-year period. Cases were enrolled in the study after satisfying the inclusion and exclusion criteria. All data compared in terms of age, parity, gestational age, indications, maternal and neonatal outcome. Results: A total of 1150 antenatal cases were delivered out of which 42 cases were delivered by outlet forceps. Incidence of outlet forceps was 3.75%. Mean baby birth weight was 3.07 kg. No maternal mortality and morbidity recorded. Conclusions: Obstetric forceps have a significant place in modern obstetrics as it is a lifesaving procedure for mother and fetus in many situations

SanskritShala: A Neural Sanskrit NLP Toolkit with Web-Based Interface for Pedagogical and Annotation Purposes

We present a neural Sanskrit Natural Language Processing (NLP) toolkit named SanskritShala (a school of Sanskrit) to facilitate computational linguistic analyses for several tasks such as word segmentation, morphological tagging, dependency parsing, and compound type identification. Our systems currently report state-of-the-art performance on available benchmark datasets for all tasks. SanskritShala is deployed as a web-based application, which allows a user to get real-time analysis for the given input. It is built with easy-to-use interactive data annotation features that allow annotators to correct the system predictions when it makes mistakes. We publicly release the source codes of the 4 modules included in the toolkit, 7 word embedding models that have been trained on publicly available Sanskrit corpora and multiple annotated datasets such as word similarity, relatedness, categorization, analogy prediction to assess intrinsic properties of word embeddings. So far as we know, this is the first neural-based Sanskrit NLP toolkit that has a web-based interface and a number of NLP modules. We are sure that the people who are willing to work with Sanskrit will find it useful for pedagogical and annotative purposes. SanskritShala is available at: https://cnerg.iitkgp.ac.in/sanskritshala. The demo video of our platform can be accessed at: https://youtu.be/x0X31Y9k0mw4.Comment: 7 pages, Accepted at ACL23 (Demo track) to be held at Toronto, Canad

Functional evaluation of various modalities of management in floating knee injuries at a tertiary care centre in central India

Background: The injuries involving femur and tibia fractures due to high velocity are known as floating knee injuries. These fractures may involve the shaft, metaphysis or the articular surface. There are many complications associated with these injuries. This study evaluates the functional, clinical and radiological outcomes of floating knee injuries. Methods: A Prospective and interventional study was performed at MGMMC and MYH Hospital, Indore. We included 30 patients in our study. Femur fractures are managed by intramedullary nailing or distal femur plating. Tibia fractures are managed by Intramedullary nailing or tibia plating. Patient were called for regular follow up for a minimum of 6 months. Functional and clinical evaluation done by Karlstorm and olerud scoring system and radiological outcome by union on x rays were done. Results: Out of 30 patients 28 (93.33%) male and 2 (6.66%) female. According to Fraser classification, 17 (56.66%) type 1, 4 (13.33%) type 2A, 4 (13.33%) type2B, 5 (16.66%) type 2C injuries. A majority of the injuries occurred due to road traffic accidents involving right limb 21 (70%) more then left 9 (30%). Knee stiffness occurred in 8, infection in femur 3, infection in tibia 2, malunion of femur 2, limb length discrepancy in 2 patients. Outcome was excellent in 5 (16.66%), Good in 10 (33.33%), Acceptable in 9 (30%) and poor in 6 (20%). Conclusions: Fraser type 1 fracture has excellent results and Fraser type 2C has poor results. Closed fracture has better outcome compared to compound Fractures. A better functional outcome can be determined on the basis of implant choice based on Fraser Classification, level of injury, open or closed injury, simple or compound type of fracture

Emerging Electricity Markets: Including New Energy Storage Technologies & Integrating DERs via ISO-DSO Coordination

Most countries have set a vision of net-zero Greenhouse Gas (GHG) emissions by 2050; however, based on current trends, many of them are lagging in meeting the targets, even for 2025. Energy transition, shifting from fossil-fuel based to clean resources, is a critical step toward achieving Net-Zero Emission (NZE) targets, and is being explored worldwide. The ongoing effort to support the transition to a decarbonized system is to deploy large-scale Renewable Energy Sources (RES); but even after the remarkable increase in deployment of RES, it still seems impossible to achieve decarbonization targets. Various countries, including Canada, have pledged to achieve NZE grid by 2035 and system operators have developed their decarbonization pathways with target objectives and timelines to attain this goal. In this context, green hydrogen-based systems emerge as a potential zero-carbon solution to meet the CO2 emission reduction targets. The electricity sector is recognized as vital for energy sector transformation, in order to achieve NZE goals, as there are already low and emission free resources in this sector such as RES, hydro, etc., and it can easily integrate with other sectors (heat, transport, etc.) as part of the electrification drive. The continuously growing demand for electricity is a challenge to energy security, grid resiliency and results in exorbitant energy prices during peak demand periods. The intermittent nature of RES imposes limits on their use and their variability leads to imbalances between the grid demand and supply. To meet these challenges, the power system requires flexible resources, for which, various alternatives have been proposed including Distributed Energy Resources (DERs), Demand Response (DR) and Energy Storage Systems (ESSs), which seem to be the most promising ones. Also, there have been remarkable advancements in the arena of smart grid, which encourages consumers to deploy DERs and re-profile themselves as prosumers. Different regulating bodies and utilities worldwide are re-organizing their electricity markets to be future-ready with high-DER vision, and are developing coordination models between the Independent System Operator (ISO) and Distribution System Operators (DSOs) to integrate DERs and realize their true potential for the whole system (transmission and distribution). This thesis first presents a novel, Green Hydrogen Systems (GHSs) integrated, Uniform Marginal Price (UMP)-based Day-Ahead Market (DAM) framework and the mathematical model for electricity market auction. The wholesale electricity market participation of GHSs, comprising electrolyzers, storage tanks and fuel cells, is examined considering their bids and offers for charging and discharging modes, respectively. To support transition toward achieving an NZE grid, the effects of inclusion of GHS in the DAM with different emission control strategies, such as emission cap and carbon pricing are examined. Two real systems with distinct characteristics, Alberta and Ontario provinces of Canada, are considered. Subsequently, this thesis presents an extension of the GHS integrated UMP-based market model to Hydrogen-based Emission Free Resources (HEFRs) included Locational Marginal Price (LMP)-based DAM model by formulating appropriate mathematical model, complying with the existing market rules. Comprehensive case studies and sensitivity analysis are carried out to examine the impact of integration of HEFRs on market settlement, marginal prices and system emissions during normal, congestion and under RES uncertainties scenarios. Next, this thesis presents a novel framework with new mathematical models that integrate DR and Battery Energy Storage Systems (BESSs) simultaneously in an LMP-based Multi-Settlement Market (MSM), i.e. a coordinated DAM and Real-Time Market (RTM). A new set of generator ramping constraints, developed from the DAM settlement, and referred to as Day-Ahead Load-Following (DALF) Ramp, are included in the RTM auction model. The performance of the mathematical models are tested on the IEEE 24-bus Reliability Test System (RTS) by carrying out various case studies and scenarios, uncertainty and sensitivity analyses. Effect of DR and BESS characteristics such as level of participation, initial State-of-Charge (SOC), discharge rate, etc. on market settlement is examined. The results demonstrate the merits of the proposed framework, and the impact of the DALF Ramp, DR and BESS inclusion in the MSM auction models on marginal prices, market settlement and system operation. Finally, the thesis presents a new Cooperation Algorithm and a parallel-hierarchical framework for coupling the wholesale and retail electricity markets in order to facilitate the participation of DERs including small-capacity Behind-the-meter DERs (BTM-DERs), in a competitive and equitable manner. The detailed mathematical models of ISO-DSOs coordinated, wholesale and retail market settlements for day-ahead period are developed. The models are tested on the IEEE 24-bus RTS (wholesale market) and multiple 33-bus distribution systems (retail markets). Results demonstrate the effectiveness of the proposed framework over a centralized wholesale market in terms of computational time and over the sequential structure, in terms of DERs’ increased participation, reduced market prices, congestion management, emissions reduction and overall system operation

Enhancing Customer Buying Experience using MR

Abstract: This study provides a general overview of the MR technology that aids consumers in improving their shopping experiences. VR, AR, and MR technologies have revolutionised the online shopping experience of customers in the modern world. To keep clients, online e-commerce websites offer a seamless brand experience. Over 75% of buyers still leave their shopping carts full without placing the order, according to statistics. The use of mixed reality holds great promise for creating satisfying customer experiences that resemble those seen in physical establishments. In order to perceive the actual and digital worlds simultaneously on a single display, mixed reality mixes augmented reality with virtual reality. This technology raises the bar for the internet market and simplifies online buying for consumers. Retailers may now provide customers augmented reality (AR) and virtual reality (VR) perspective of their items through the usage of mixed reality. The user may overlay the products in both their real-world and virtual environments by combining this technology into a single application. Currently, a user dons a set of mixed reality glasses with cameras and sensors. It gathers as much data about the surroundings as it can using this tool and software, basically building a digital map of the actual world. The MR technology may enhance the world with holographic content and pictures using that map. Users of the MR glasses may view the objects they're viewing from different perspectives. In order to maximise their experience, they might then alter their own plans and deeds. The way individuals browse for things is anticipated to change as a result of this technology. eCommerce is undergoing a wave of transition as a result of mixed reality. We can anticipate seeing more of this kind of customer-enhancing technology in the future</jats:p

A neural network based approach for the vehicle classification

This paper presents a neural network based approach for vehicle classification. The proposed vehicle classification approach extracts various features from a vehicle image, normalises and classifies them into one of the known classes. It is based on structural features and a direct solution training method. The preliminary experiments on training and testing of 4 types of vehicles patterns were conducted. The experimental results are very promising and demonstrate the effectiveness and usefulness of the proposed approach