Search results for: Shubham Dixit

Authors: Shubham Kumar, Chaitanya Goswami, Sudipto Sarkar

Abstract:

Pseudoplastic (n < 1, n being the power index) fluid flow can be found in food, pharmaceutical and process industries and has very complex flow nature. To our knowledge, inadequate research work has been done in this kind of flow even at very low Reynolds numbers. Here, in the present computation, we have considered unsteady laminar flow over a square cylinder in pseudoplastic flow environment. For Newtonian fluid flow, this laminar vortex shedding range lies between Re = 47-180. In this problem, we consider Re = 100 (Re = U∞ a/ ν, U∞ is the free stream velocity of the flow, a is the side of the cylinder and ν is the kinematic viscosity of the fluid). The pseudoplastic fluid range has been chosen from close to the Newtonian fluid (n = 0.8) to very high pseudoplasticity (n = 0.1). The flow domain is constituted using Gambit 2.2.30 and this software is also used to generate mesh and to impose the boundary conditions. For all places, the domain size is considered as 36a × 16a with 280 ×192 grid point in the streamwise and flow normal directions respectively. The domain and the grid points are selected after a thorough grid independent study at n = 1.0. Fine and equal grid spacing is used close to the square cylinder to capture the upper and lower shear layers shed from the cylinder. Away from the cylinder the grid is unequal in size and stretched out in all direction. Velocity inlet (u = U∞), pressure outlet (Neumann condition), symmetry (free-slip boundary condition du/dy = 0, v = 0) at upper and lower domain boundary conditions are used for this simulation. Wall boundary (u = v = 0) is considered on the square cylinder surface. Fully conservative 2-D unsteady Navier-Stokes equations are discretized and then solved by Ansys Fluent 14.5 to understand the flow nature. SIMPLE algorithm written in finite volume method is selected for this purpose which is the default solver in scripted in Fluent. The result obtained for Newtonian fluid flow agrees well with previous work supporting Fluent’s usefulness in academic research. A minute analysis of instantaneous and time averaged flow field is obtained both for Newtonian and pseudoplastic fluid flow. It has been observed that drag coefficient increases continuously with the reduced value of n. Also, the vortex shedding phenomenon changes at n = 0.4 due to flow instability. These are some of the remarkable findings for laminar periodic vortex shedding regime in pseudoplastic flow environment.

Keywords: Ansys Fluent, CFD, periodic vortex shedding, pseudoplastic fluid flow

Procedia PDF Downloads 185

Authors: Sarah Atalla, Shubham Gupta, Kim Alipio, Tanya Maric

Abstract:

Background: Chelsea and Westminster Hospital have introduced the Birmingham Symptom Specific Obstetric Triage System (BSOTS) for patients who present acutely to the Maternity Assessment Suite (MAS) to prioritise care by urgency. The primary objective was to evaluate whether BSOTS was used appropriately to assess patients (defined as a 90% threshold). The secondary objective was to assess whether patients were seen within their designated triaged timeframe (defined as a 90% threshold). Methodology: MAS records were retrospectively reviewed for a randomly selected one-week period of data from 2020 (21/09/2020 - 27/09/2020). 189 patients presented to MAS during this time. Data were collected on the presenting complaint, time of attendance (divided into four time categories), and triage colour code for the urgency of a review by a doctor (red: immediately, orange: within 15 minutes, yellow: within 1 hour, green: within 4 hours). The number of triage waiting times that were breached and the outcome of the attendance was noted. Results: 49% of patients presenting to MAS during this time period were triaged, which therefore did not meet the 90% target. 67% of patients who were triaged were seen within their allocated timeframe as designated by their triage colour code, which therefore did not meet the 90% target. The most frequent reason for patient attendance was reduced fetal movements (30.5% of attendances). The busiest time of day (when most patients presented) was between 06:01-12:00, and this was also when the highest number of patients were not triaged (26 patients or 54% of patients presenting in this time category). The most used triage category (59%) was the green colour code (to be seen by a doctor within 4 hours), followed by orange (24%), yellow (14%), and red (3%). 45% of triaged patients were admitted, whilst 55% were discharged. 62% of patients allocated to the green triage category were discharged, as compared to 56% of yellow category patients, 27% of orange category patients, and 50% of red category patients. The time of patient presentation to the hospital was also associated with the level of urgency and outcome. Patients presenting from 12:01 to 18:00 were more likely to be discharged (72% discharged) compared to 00:01-06:00 where only 12.5% of patients were discharged. Conclusion: The triage system for assessing the urgency of acutely presenting obstetric patients is only being effectively utilised for 49% of patients. There is potential for enhancing the employment of the triage system to enable further efficiency and boost the promotion of patient safety. It is noted that MAS was busiest at 06:01 - 12:00 when there was also the highest number of non-triaged patients – this highlights some areas where we can improve, including higher levels of staffing, better use of BSOTS to triage patients, and patient education.

Keywords: birmingham, BSOTS, maternal, obstetric, pregnancy, specific, symptom, triage

Procedia PDF Downloads 94

Authors: Sunita Boro, Saurabh Kumar Dixit

Abstract:

Terroir, an intricate fusion of geography, climate, soil, and human expertise, has long been acknowledged as a defining factor in the character of wines and foods. This research embarks on an exploration of terroir's profound influence on gastronomic tourism, shedding light on the intricate interplay between the physical environment and culinary artistry. Delving into the intricate science of terroir, we scrutinize its role in shaping the sensory profiles of wines and foods, emphasizing the profound impact of specific regions on flavor, aroma, and texture. We deploy a multifaceted methodology, amalgamating sensory analysis, chemical profiling, geographical information systems, and qualitative interviews to unearth the nuanced nuances of terroir expression. Through an exhaustive review of the literature, we elucidate the historical roots of terroir, unveil the intricate cultural dimensions shaping it, and provide a comprehensive examination of prior studies in the field. Our findings underscore the pivotal role of terroir in promoting regional identities, enhancing the economic viability of locales, and attracting gastronomic tourists. The paper also dissects the marketing strategies employed to promote terroir-driven food and wine experiences. We elucidate the utilization of storytelling, branding, and collaborative endeavors in fostering a robust terroir-based tourism industry. This elucidates both the potential for innovation and the challenges posed by oversimplification or misrepresentation of terroir. Our research spotlights the intersection of terroir and sustainability, emphasizing the significance of environmentally conscious practices in terroir-driven productions. We discern the harmonious relationship between sustainable agriculture, terroir preservation, and responsible tourism, encapsulating the essence of ecological integrity in gastronomic tourism. Incorporating compelling case studies of regions and businesses excelling in the terroir-based tourism realm, we offer in-depth insights into successful models and strategies, with an emphasis on their replicability and adaptability to various contexts. Ultimately, this paper not only contributes to the scholarly understanding of terroir's role in the world of food and wine tourism but also provides actionable recommendations for stakeholders to leverage terroir's allure, preserve its authenticity, and foster sustainable and enriching culinary tourism experiences.

Keywords: terroir, food tourism, wine tourism, sustainability

Procedia PDF Downloads 48

Authors: Satyen Mondal, Frederickson Entila, Shalabh Dixit, Pompe C. Sta. Cruz, Abdelbagi M. Ismail

Abstract:

Anaerobic condition caused by flooding during germination in direct seeded rice systems, known as anaerobic germination (AG), severely reduces crop establishment in both rainfed and irrigated areas. Seeds germinating in flooded soils could encounter hypoxia or even anoxia in severe cases, and this hinders germination and seedling growth. This study was conducted to quantify the effects of incorporating two major QTLs, AG1 and AG2, associated with tolerance of flooding during germination and to assess their interactive effects on enhancing crop establishment. A greenhouse experiment was conducted at the International Rice Research Institute (IRRI), Los Baňos, Philippines, using elite lines incorporating AG1, AG2 and AG1+AG2 in the background of the popular varieties PSBRc82 (PSBRc82-AG1, PSBRc82-AG2, PSBRc82-AG1+AG2) and Ciherang-Sub1 (Ciherang-Sub1-AG1, Ciherang-Sub1-AG2, Ciherang-Sub1-AG1+AG2), along with the donors Kho Hlan On (for AG1) and Ma-Zhan Red (AG2) and the recipients PSBRc82 and Ciherang-Sub1. The experiment was conducted using concrete tanks in an RCBD with three replications. Dry seeds were sown in seedling trays then flooded with 10 cm water depth. Seedling survival, root and shoot growth and relative growth rate were measured. The germinating seedlings were used for assaying nonstructural carbohydrate (NSC) and ascorbate concentrations, lipid peroxidation, total phenolic concentration, reactive oxygen species and total amylase enzyme activity. Flooding reduced overall survival, though survival of AG1+AG2 introgression lines was greater than other genotypes. Soluble sugars increased, while starch concentration decreased gradually under flooding especially in the tolerant checks and AG1+AG2 introgression lines. Less lipid peroxidation and higher amylase activity, reduced-ascorbate (RAsA) and total phenolic contents (TPC) were observed in the tolerant checks and in AG1+AG2 introgression lines. Lipid peroxidation correlated negatively with ascorbate and total phenolic concentrations and with reactive oxygen species (ROS). Introgression of AG1+AG2 QTLs upregulated total amylase activity causing rapid starch degradation and increase in ascorbate and total phenolic concentrations resulting in higher germination and seedling growth in flooded soils.

Keywords: amylase, anaerobic germination, ascorbate, direct-seeded rice, flooding, lipid peroxidation

Procedia PDF Downloads 269

Authors: Shubham Gogri, Lucia Florescu

Abstract:

Medical diagnosis and radiotherapy treatment planning using Computed Tomography (CT) rely on the quantitative accuracy and quality of the CT images. At the same time, requirements for CT imaging include reducing the radiation dose exposure to patients and minimizing scanning time. A solution to this is the sparse-view CT technique, based on a reduced number of projection views. This, however, introduces a new problem— the incomplete projection data results in lower quality of the reconstructed images. To tackle this issue, deep learning methods have been applied to enhance the quality of the sparse-view CT images. A first approach involved employing Mir-Net, a dedicated deep neural network designed for image enhancement. This showed promise, utilizing an intricate architecture comprising encoder and decoder networks, along with the incorporation of the Charbonnier Loss. However, this approach was computationally demanding. Subsequently, a specialized Generative Adversarial Network (GAN) architecture, rooted in the Pix2Pix framework, was implemented. This GAN framework involves a U-Net-based Generator and a Discriminator based on Convolutional Neural Networks. To bolster the GAN's performance, both Charbonnier and Wasserstein loss functions were introduced, collectively focusing on capturing minute details while ensuring training stability. The integration of the perceptual loss, calculated based on feature vectors extracted from the VGG16 network pretrained on the ImageNet dataset, further enhanced the network's ability to synthesize relevant images. A series of comprehensive experiments with clinical CT data were conducted, exploring various GAN loss functions, including Wasserstein, Charbonnier, and perceptual loss. The outcomes demonstrated significant image quality improvements, confirmed through pertinent metrics such as Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) between the corrected images and the ground truth. Furthermore, learning curves and qualitative comparisons added evidence of the enhanced image quality and the network's increased stability, while preserving pixel value intensity. The experiments underscored the potential of deep learning frameworks in enhancing the visual interpretation of CT scans, achieving outcomes with SSIM values close to one and PSNR values reaching up to 76.

Keywords: generative adversarial networks, sparse view computed tomography, CT image correction, Mir-Net

Procedia PDF Downloads 145

Authors: Apurva Patil, Ashay Aswale, Akshay Kulkarni, Shubham Bharadiya

Abstract:

The potential benefit of gravity compensation of linkages in mechanisms using springs to reduce actuator requirements is well recognized, but practical applications have been elusive. Although existing methods provide exact spring balance, they require additional masses or auxiliary links, or all the springs used originate from the ground, which makes the resulting device bulky and space-inefficient. This paper uses a method of static balancing of mechanisms with conservative loads such as gravity and spring loads using non-zero-free-length springs with child–parent connections and no auxiliary links. Application of this method to the developed arm of a humanoid robot is presented here. Spring balancing is particularly important in this case because the serial chain of linkages has to work against gravity.This work involves approximate spring balancing of the open-loop chain of linkages using minimization of potential energy variance. It uses the approach of flattening the potential energy distribution over the workspace and fuses it with numerical optimization. The results show the considerable reduction in actuator torque requirement with practical spring design and arrangement. Reduced actuator torque facilitates the use of lower end actuators which are generally smaller in weight and volume thereby lowering the space requirements and the total weight of the arm. This is particularly important for humanoid robots where the parent actuator has to handle the weight of the subsequent actuators as well. Actuators with lower actuation requirements are more energy efficient, thereby reduce the energy consumption of the mechanism. Lower end actuators are lower in cost and facilitate the development of low-cost devices. Although the method provides only an approximate balancing, it is versatile, flexible in choosing appropriate control variables that are relevant to the design problem and easy to implement. The true potential of this technique lies in the fact that it uses a very simple optimization to find the spring constant, free-length of the spring and the optimal attachment points subject to the optimization constraints. Also, it uses physically realizable non-zero-free-length springs directly, thereby reducing the complexity involved in simulating zero-free-length springs from non-zero-free-length springs. This method allows springs to be attached to the preceding parent link, which makes the implementation of spring balancing practical. Because auxiliary linkages can be avoided, the resultant arm of the humanoid robot is compact. The cost benefits and reduced complexity can be significant advantages in the development of this arm of the humanoid robot.

Keywords: actuator torque, child-parent connections, spring balancing, the arm of a humanoid robot

Procedia PDF Downloads 237

Authors: Priyanka Verma, Vijaya Dixit, Rishabh Bajpai

Abstract:

This research paper is aimed at selecting appropriate material handling equipment among the given choices so that the automation level in material handling can be enhanced. This work is a practical case scenario of material handling systems in consumer electronic appliances manufacturing organization. The choices of material handling equipment among which the decision has to be made are Automated Guided Vehicle’s (AGV), Autonomous Mobile Robots (AMR), Overhead Conveyer’s (OC) and Battery Operated Trucks/Vehicle’s (BOT). There is a need of attaining a certain level of automation in order to reduce human interventions in the organization. This requirement of achieving certain degree of automation can be attained by material handling equipment’s mentioned above. The main motive for selecting above equipment’s for study was solely based on corporate financial strategy of investment and return obtained through that investment made in stipulated time framework. Since the low cost automation with respect to material handling devices has to be achieved hence these equipment’s were selected. Investment to be done on each unit of this equipment is less than 20 lakh rupees (INR) and the recovery period is less than that of five years. Fuzzy analytic hierarchic process (FAHP) is applied here for selecting equipment where the four choices are evaluated on basis of four major criteria’s and 13 sub criteria’s, and are prioritized on the basis of weight obtained. The FAHP used here make use of triangular fuzzy numbers (TFN). The inability of the traditional AHP in order to deal with the subjectiveness and impreciseness in the pair-wise comparison process has been improved in the FAHP. The range of values for general rating purposes for all decision making parameters is kept between 0 and 1 on the basis of expert opinions captured on shop floor. These experts were familiar with operating environment and shop floor activity control. Instead of generating exact value the FAHP generates the ranges of values to accommodate the uncertainty in decision-making process. The four major criteria’s selected for the evaluation of choices of material handling equipment’s available are materials, technical capabilities, cost and other features. The thirteen sub criteria’s listed under these following four major criteria’s are weighing capacity, load per hour, material compatibility, capital cost, operating cost and maintenance cost, speed, distance moved, space required, frequency of trips, control required, safety and reliability issues. The key finding shows that among the four major criteria selected, cost is emerged as the most important criteria and is one of the key decision making aspect on the basis of which material equipment selection is based on. While further evaluating the choices of equipment available for each sub criteria it is found that AGV scores the highest weight in most of the sub-criteria’s. On carrying out complete analysis the research shows that AGV is the best material handling equipment suiting all decision criteria’s selected in FAHP and therefore it is beneficial for the organization to carry out automated material handling in the facility using AGV’s.

Keywords: fuzzy analytic hierarchy process (FAHP), material handling equipment, subjectiveness, triangular fuzzy number (TFN)

Procedia PDF Downloads 428

Authors: Mayoorika Shukla, Pramila Jakhar, Tejendra Dixit, I. A. Palani, Vipul Singh

Abstract:

Biosensors are analytical devices with wide range of applications in biological, chemical, environmental and clinical analysis. It comprises of bio-recognition layer which has biomolecules (enzymes, antibodies, DNA, etc.) immobilized over it for detection of analyte and transducer which converts the biological signal into the electrical signal. The performance of biosensor primarily the depends on the bio-recognition layer and therefore it has to be chosen wisely. In this regard, nanostructures of metal oxides such as ZnO, SnO2, V2O5, and TiO2, etc. have been explored extensively as bio-recognition layer. Recently, ZnO has the attracted attention of researchers due to its unique properties like high iso-electric point, biocompatibility, stability, high electron mobility and high electron binding energy, etc. Although there have been many reports on usage of ZnO as bio-recognition layer but to the authors’ knowledge, none has ever observed correlation between optical properties like defect suppression and biosensing capability of the sensor. Here, ZnO nanorods (ZNR) have been synthesized by a low cost, simple and low-temperature hydrothermal growth process, over Platinum (Pt) coated glass substrate. The ZNR have been synthesized in two steps viz. initially a seed layer was coated over substrate (Pt coated glass) followed by immersion of it into nutrient solution of Zinc nitrate and Hexamethylenetetramine (HMTA) with in situ addition of KMnO4. The addition of KMnO4 was observed to have a profound effect over the growth rate anisotropy of ZnO nanostructures. Clustered and powdery growth of ZnO was observed without addition of KMnO4, although by addition of it during the growth, uniform and crystalline ZNR were found to be grown over the substrate. Moreover, the same has resulted in suppression of defects as observed by Normalized Photoluminescence (PL) spectra since KMnO4 is a strong oxidizing agent which provides an oxygen rich growth environment. Further, to explore the correlation between defect suppression and biosensing capability of the ZNR Glucose oxidase (Gox) was immobilized over it, using physical adsorption technique followed by drop casting of nafion. Here the main objective of the work was to analyze effect of defect suppression over biosensing capability, and therefore Gox has been chosen as model enzyme, and electrochemical amperometric glucose detection was performed. The incorporation of KMnO4 during growth has resulted in variation of optical and charge transfer properties of ZNR which in turn were observed to have deep impact on biosensor figure of merits. The sensitivity of biosensor was found to increase by 12-18 times, due to variations introduced by addition of KMnO4 during growth. The amperometric detection of glucose in continuously stirred buffer solution was performed. Interestingly, defect suppression has been observed to contribute towards the improvement of biosensor performance. The detailed mechanism of growth of ZNR along with the overall influence of defect suppression on the sensing capabilities of the resulting enzymatic electrochemical biosensor and different figure of merits of the biosensor (Glass/Pt/ZNR/Gox/Nafion) will be discussed during the conference.

Keywords: biosensors, defects, KMnO4, ZnO nanorods

Procedia PDF Downloads 276

Authors: Saiyed M Ishtiaque, Priyal Dixit

Abstract:

Objectives: An approach is being suggested to design the filter media to maximize the filtration efficiency with minimum possible pressure drop of composite nonwoven by incorporating the layers of different packing densities induced by fibre of different deniers and punching parameters by using the concept of sequential punching technique in specific order in layered composite nonwoven structure. X-ray computed tomography technique is used to measure the packing density along the thickness of layered nonwoven structure composed by placing the layer of differently oriented fibres influenced by fibres of different deniers and punching parameters in various combinations to minimize the pressure drop at maximum possible filtration efficiency. Methodology Used: This work involves preparation of needle punched layered structure with batts 100g/m2 basis weight having fibre denier, punch density and needle penetration depth as variables to produce 300 g/m2 basis weight nonwoven composite. X-ray computed tomography technique is used to measure the packing density along the thickness of layered nonwoven structure composed by placing the layers of differently oriented fibres influenced by considered variables in various combinations. to minimize the pressure drop at maximum possible filtration efficiencyFor developing layered nonwoven fabrics, batts made of fibre of different deniers having 100g/m2 each basis weight were placed in various combinations. For second set of experiment, the composite nonwoven fabrics were prepared by using 3 denier circular cross section polyester fibre having 64 mm length on needle punched nonwoven machine by using the sequential punching technique to prepare the composite nonwoven fabrics. In this technique, three semi punched fabrics of 100 g/m2 each having either different punch densities or needle penetration depths were prepared for first phase of fabric preparation. These fabrics were later punched altogether to obtain the overall basis weight of 300 g/m2. The total punch density of the composite nonwoven fabric was kept at 200 punches/ cm2 with a needle penetration depth of 10 mm. The layered structures so formed were subcategorised into two groups- homogeneous layered structure in which all the three batts comprising the nonwoven fabric were made from same denier of fibre, punch density and needle penetration depth and were placed in different positions in respective fabric and heterogeneous layered structure in which batts were made from fibres of different deniers, punch densities and needle penetration depths and were placed in different positions. Contributions: The results concluded that reduction in pressure drop is not derived by the overall packing density of the layered nonwoven fabric rather sequencing of layers of specific packing density in layered structure decides the pressure drop. Accordingly, creation of inverse gradient of packing density in layered structure provided maximum filtration efficiency with least pressure drop. This study paves the way for the possibility of customising the composite nonwoven fabrics by the incorporation of differently oriented fibres in constituent layers induced by considered variablres for desired filtration properties.

Keywords: filtration efficiency, layered nonwoven structure, packing density, pressure drop

Procedia PDF Downloads 62

Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

Abstract:

Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

Procedia PDF Downloads 118