Search results for: Sujay Bisht
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10

Search results for: Sujay Bisht

10 Effect of Hill Interval Training on VO₂ Max among Filed Hockey Players

Authors: Sujay Bisht

Abstract:

The purpose of the study was to evaluate and find out the effect of Hill interval training on VO₂ MAX among field Hockey players. Thirty male field hockey players were selected from LNIPE, Guwahati who were studied in B.P.Ed course. The selected subjects were aged between 18 to 23 years. The VO₂ MAX was calculated and they were divided into two group. One group (N=15) considered as control group that did not participated in any special training apart from regular scheduled/curriculum and another group (N=15) considered as an experimental group which underwent four week Hill Training program. The selected criterion variable such VO₂ Max was measured by the cooper 12min/run/walk test and scores was recorded in ml/kg/min. The subjects were tested on selected criterion variable such as VO₂ Max prior and immediately after the training program. The pretest and posttest data were evaluate by the Analysis of Covariance (ANCOVA) to find out the significance difference if any between the experimental and control group on selected criterion variable. The level of significance was set at 0.05 level of confidence. After applied ANCOVA it was revealed that there was a significant different among the experimental and control group on VO₂ Max. Finally it was concluded that 4 week of Hill interval training effect the VO₂ max performance of field hockey players.

Keywords: VO₂ max, hill interval training, ANCOVA, experimental group

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9 Injury Pattern of Field Hockey Players at Different Field Position during Game and Practice

Authors: Sujay Bisht

Abstract:

The purpose of the study was to assess and examines the pattern of injury among the field hockey players at different field position during practice & game. It was hypothesized that the backfield might have the height rate of injury, followed by midfield. Methods: university level and national level male field hockey (N=60) are selected as a subject and requested to respond an anon questionnaire. Personal characteristics of each and individual players were also collected like (age, height, weight); field hockey professional information (level of play, year of experience, playing surface); players injury history (site, types, cause etc). The rates of injury per athlete per year were also calculated. Result: Around half of the injury occurred were to the lower limbs (49%) followed by head and face (30%), upper limbs (19%) and torso region (2%). Injuries included concussion, wounds, broken nose, ligament sprain, dislocation, fracture, and muscles strain and knee injury. The ligament sprain is the highest rate (40%) among the other types of injuries. After investigation and evaluation backfield players had the highest rate of risk of injury (1.10 injury/athletes-year) followed by midfield players (0.70 injury/athlete-year), forward players (0.45 injury/athlete-year) & goalkeeper was (0.37 injury/athlete-year). Conclusion: Due to the different field position the pattern & rate of injury were different. After evaluation, lower limbs had the highest rate of injury followed by head and face, upper limbs and torso respectively. It also revealed that not only there is a difference in the rate of injury between playing the position, but also in the types of injury sustain at a different position.

Keywords: trauma, sprain, strain, astroturf, acute injury

Procedia PDF Downloads 193
8 Detection of Cardiac Arrhythmia Using Principal Component Analysis and Xgboost Model

Authors: Sujay Kotwale, Ramasubba Reddy M.

Abstract:

Electrocardiogram (ECG) is a non-invasive technique used to study and analyze various heart diseases. Cardiac arrhythmia is a serious heart disease which leads to death of the patients, when left untreated. An early-time detection of cardiac arrhythmia would help the doctors to do proper treatment of the heart. In the past, various algorithms and machine learning (ML) models were used to early-time detection of cardiac arrhythmia, but few of them have achieved better results. In order to improve the performance, this paper implements principal component analysis (PCA) along with XGBoost model. The PCA was implemented to the raw ECG signals which suppress redundancy information and extracted significant features. The obtained significant ECG features were fed into XGBoost model and the performance of the model was evaluated. In order to valid the proposed technique, raw ECG signals obtained from standard MIT-BIH database were employed for the analysis. The result shows that the performance of proposed method is superior to the several state-of-the-arts techniques.

Keywords: cardiac arrhythmia, electrocardiogram, principal component analysis, XGBoost

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7 Cooling Profile Analysis of Hot Strip Coil Using Finite Volume Method

Authors: Subhamita Chakraborty, Shubhabrata Datta, Sujay Kumar Mukherjea, Partha Protim Chattopadhyay

Abstract:

Manufacturing of multiphase high strength steel in hot strip mill have drawn significant attention due to the possibility of forming low temperature transformation product of austenite under continuous cooling condition. In such endeavor, reliable prediction of temperature profile of hot strip coil is essential in order to accesses the evolution of microstructure at different location of hot strip coil, on the basis of corresponding Continuous Cooling Transformation (CCT) diagram. Temperature distribution profile of the hot strip coil has been determined by using finite volume method (FVM) vis-à-vis finite difference method (FDM). It has been demonstrated that FVM offer greater computational reliability in estimation of contact pressure distribution and hence the temperature distribution for curved and irregular profiles, owing to the flexibility in selection of grid geometry and discrete point position, Moreover, use of finite volume concept allows enforcing the conservation of mass, momentum and energy, leading to enhanced accuracy of prediction.

Keywords: simulation, modeling, thermal analysis, coil cooling, contact pressure, finite volume method

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6 Parameter Estimation for the Oral Minimal Model and Parameter Distinctions Between Obese and Non-obese Type 2 Diabetes

Authors: Manoja Rajalakshmi Aravindakshana, Devleena Ghosha, Chittaranjan Mandala, K. V. Venkateshb, Jit Sarkarc, Partha Chakrabartic, Sujay K. Maity

Abstract:

Oral Glucose Tolerance Test (OGTT) is the primary test used to diagnose type 2 diabetes mellitus (T2DM) in a clinical setting. Analysis of OGTT data using the Oral Minimal Model (OMM) along with the rate of appearance of ingested glucose (Ra) is performed to study differences in model parameters for control and T2DM groups. The differentiation of parameters of the model gives insight into the behaviour and physiology of T2DM. The model is also studied to find parameter differences among obese and non-obese T2DM subjects and the sensitive parameters were co-related to the known physiological findings. Sensitivity analysis is performed to understand changes in parameter values with model output and to support the findings, appropriate statistical tests are done. This seems to be the first preliminary application of the OMM with obesity as a distinguishing factor in understanding T2DM from estimated parameters of insulin-glucose model and relating the statistical differences in parameters to diabetes pathophysiology.

Keywords: oral minimal model, OGTT, obese and non-obese T2DM, mathematical modeling, parameter estimation

Procedia PDF Downloads 64
5 Work-Home Interference and Emotional Exhaustion: The Role of Psychological Detachment, Relaxation and Technology-Assisted Supplemental Work

Authors: Nidhi S. Bisht

Abstract:

The study examines the role of work-home interference, on enhancing emotional exhaustion in the branch officers of private MFIs in India. Additionally, the moderating role of recovery experiences and technology-assisted supplemental work (TASW) were studied. With the increasing expectations to perform job related tasks at home, technology-assisted supplemental work (TASW) was hypothesized to positively moderate the relationship between work-home interference and emotional exhaustion. Further, it was expected that recovery experiences-psychological detachment, relaxation will help to recover and unwind from work and negatively moderate the relationship between work-home interference and emotional exhaustion. Results of SEM-analyses largely offered support for the hypotheses. These findings increase our insight in the processes leading to increased emotional exhaustion and suggest that employees can protect themselves from emotional exhaustion by keeping a tab on technology-assisted supplemental work and facilitating recovery experiences.

Keywords: emotional exhaustion, India, microfinance institutions (MFIs), work-home interference

Procedia PDF Downloads 188
4 Improved Super-Resolution Using Deep Denoising Convolutional Neural Network

Authors: Pawan Kumar Mishra, Ganesh Singh Bisht

Abstract:

Super-resolution is the technique that is being used in computer vision to construct high-resolution images from a single low-resolution image. It is used to increase the frequency component, recover the lost details and removing the down sampling and noises that caused by camera during image acquisition process. High-resolution images or videos are desired part of all image processing tasks and its analysis in most of digital imaging application. The target behind super-resolution is to combine non-repetition information inside single or multiple low-resolution frames to generate a high-resolution image. Many methods have been proposed where multiple images are used as low-resolution images of same scene with different variation in transformation. This is called multi-image super resolution. And another family of methods is single image super-resolution that tries to learn redundancy that presents in image and reconstruction the lost information from a single low-resolution image. Use of deep learning is one of state of art method at present for solving reconstruction high-resolution image. In this research, we proposed Deep Denoising Super Resolution (DDSR) that is a deep neural network for effectively reconstruct the high-resolution image from low-resolution image.

Keywords: resolution, deep-learning, neural network, de-blurring

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3 A Finite Element Based Predictive Stone Lofting Simulation Methodology for Automotive Vehicles

Authors: Gaurav Bisht, Rahul Rathnakumar, Ravikumar Duggirala

Abstract:

Predictive simulations are one of the key focus areas in safety-critical industries such as aerospace and high-performance automotive engineering. The stone-chipping study is one such effort taken up by the industry to predict and evaluate the damage caused due to gravel impact on vehicles. This paper describes a finite elements based method that can simulate the ejection of gravel chips from a vehicle tire. The FE simulations were used to obtain the initial ejection velocity of the stones for various driving conditions using a computational contact mechanics approach. To verify the accuracy of the tire model, several parametric studies were conducted. The FE simulations resulted in stone loft velocities ranging from 0–8 m/s, regardless of tire speed. The stress on the tire at the instant of initial contact with the stone increased linearly with vehicle speed. Mesh convergence studies indicated that a highly resolved tire mesh tends to result in better momentum transfer between the tire and the stone. A fine tire mesh also showed a linearly increasing relationship between the tire forward speed and stone lofting speed, which was not observed in coarser meshes. However, it also highlighted a potential challenge, in that the ejection velocity vector of the stone seemed to be sensitive to the mesh, owing to the FE-based contact mechanical formulation of the problem.

Keywords: abaqus, contact mechanics, foreign object debris, stone chipping

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2 Development of Expanded Perlite-Caprylicacid Composite for Temperature Maintainance in Buildings

Authors: Akhila Konala, Jagadeeswara Reddy Vennapusa, Sujay Chattopadhyay

Abstract:

The energy consumption of humankind is growing day by day due to an increase in the population, industrialization and their needs for living. Fossil fuels are the major source of energy to satisfy energy needs, which are non-renewable energy resources. So, there is a need to develop green resources for energy production and storage. Phase change materials (PCMs) derived from plants (green resources) are well known for their capacity to store the thermal energy as latent heat during their phase change from solid to liquid. This property of PCM could be used for storage of thermal energy. In this study, a composite with fatty acid (caprylic acid; M.P 15°C, Enthalpy 179kJ/kg) as a phase change material and expanded perlite as support porous matrix was prepared through direct impregnation method for thermal energy storage applications. The prepared composite was characterized using Differential scanning calorimetry (DSC), Field Emission Scanning Electron Microscope (FESEM), Thermal Gravimetric Analysis (TGA), and Fourier Transform Infrared (FTIR) spectrometer. The melting point of the prepared composite was 15.65°C, and the melting enthalpy was 82kJ/kg. The surface nature of the perlite was observed through FESEM. It was observed that there are micro size pores in the perlite surface, which were responsible for the absorption of PCM into perlite. In TGA thermogram, the PCM loss from composite was started at ~90°C. FTIR curves proved there was no chemical interaction between the perlite and caprylic acid. So, the PCM composite prepared in this work could be effective to use in temperature maintenance of buildings.

Keywords: caprylic acid, composite, phase change materials, PCM, perlite, thermal energy

Procedia PDF Downloads 92
1 Recession Rate of Gangotri and Its Tributary Glacier, Garhwal Himalaya, India through Kinematic GPS Survey and Satellite Data

Authors: Harish Bisht, Bahadur Singh Kotlia, Kireet Kumar

Abstract:

In order to reconstruct past retreating rates, total area loss, volume change and shift in snout position were measured through multi-temporal satellite data from 1989 to 2016 and kinematic GPS survey from 2015 to 2016. The results obtained from satellite data indicate that in the last 27 years, Chaturangi glacier snout has retreated 1172.57 ± 38.3 m (average 45.07 ± 4.31 m/year) with a total area and volume loss of 0.626 ± 0.001 sq. Km and 0.139 Km³, respectively. The field measurements through differential global positioning system survey revealed that the annual retreating rate was 22.84 ± 0.05 m/year. The large variations in results derived from both the methods are probably because of higher difference in their accuracy. Snout monitoring of the Gangotri glacier during the ablation season (May to September) in the years 2005 and 2015 reveals that the retreating rate has been comparatively more declined than that shown by the earlier studies. The GPS dataset shows that the average recession rate is 10.26 ± 0.05 m/year. In order to determine the possible causes of decreased retreating rate, a relationship between debris thickness and melt rate was also established by using ablation stakes. The present study concludes that remote sensing method is suitable for large area and long term study, while kinematic GPS is more appropriate for the annual monitoring of retreating rate of glacier snout. The present study also emphasizes on mapping of all the tributary glaciers in order to assess the overall changes in the main glacier system and its health.

Keywords: Chaturangi glacier, Gangotri glacier, glacier snout, kinematic global positioning system, retreat rate

Procedia PDF Downloads 113