Simulation And Analysis Of Indian Air Traffic

Air Traffic Density In India And The World At Large Is Growing Fast . The Airspace And Air Traffic Management Therefore Need Augmentation Of System Capability Without Compromising Safety . This Report Addresses The Judicious Use Of Simulation Facilities To Predict Present And Futuristic Problems. It Is Intended To Help Service Providers Plan And Come Out With Strategies For Air Traffic Management. "State Of The Art Simulation Facilities Are Also Useful In Training A Team Of Reliable, Safe And Efficient Air Traffic Controllers . The Report Presents Results Of Simulation Of Three International Airports : One Existing In Bangalore, The One Planned At Devanahalli And The One In Cochin . The Problems Addressed Are Those Of Delay Encountered At The Three Airports, Controller Workload And Noise Contours Around The Bangalore Aerodrome

Modelling,simulation, and analysis of HAL Bangalore13; international airport

Air traffic density in India and the world at large is growing fast and posing challenging13; problems. The problems encountered can be parameterized as flight delay, workload of air traffic13; controllers and noise levels in and around aerodromes. Prediction and quantification of these13; parameters aid in developing strategies for efficient air traffic management. In this study, the13; method used for quantifying is by simulation and analysis of the selected aerodrome and air13; space. This paper presents the results of simulation of HAL Bangalore International Airport,13; which is used by civil as well as military aircraft. With the test flying of unscheduled military13; aircraft and the increase in the civil air traffic, this airport is hitting the limit of acceptable delay.13; The workload on air traffic controllers is pushed to high during peak times. The noise contour13; prediction, especially for the test flying military aircraft is sounding a wake up call to the13; communities living in the vicinity of the Airport.13

Influence of tuck stitch in course direction on thermal comfort characteristics of layered knitted fabrics

The thermal comfort characteristics of bi-layer knitted fabrics have been studied for shuttle badminton sportswear. Bilayerknitted fabrics are developed by changing tuck position in course direction such as 6, 10, 14 and 18 course repeat,keeping the tuck on 12th wale the same. It is observed that the greater the distance between successive tuck points, the betterwill be the air, heat and moisture transfer properties. Bi-layer knitted fabric with slack structure facilitates lower thicknessand mass per unit area, and exhibits better thermal comfort characteristics. By wear trial method, bi-layer knitted fabric withtuck on 18th course and 12th wale shows good rating compared to other bi-layer knitted fabrics. The results are discussed at95% significant level with ANOVA analysis and Friedman one-way analysis of variance

Comfort properties of double face knitted fabrics for tennis sportswear

The comfort properties of different bi-layer knitted structures made from tencel yarn as an outer layer and acrylic/micro-fibre polyester yarn as an inner layer have been studied. Six union fabrics have been produced and then analyzed objectively and subjectively for their comfort properties. The air permeability, water vapour permeability, wicking ability and drying rate are found to be higher and thermal resistance is found to be lower for bi-layer knitted fabric made out of micro-fibre polyester (inner layer) with less tuck points as compared to all other fabrics. The same structure shows good ranking on subjective rating of thermal environment scale. The results are discussed with 95% significant level with ANOVA analysis and Friedman one-way analysis of variance

Influence of tuck stitch in wale direction on thermal comfort characteristics of layered knitted fabrics

Thermo-physiological comfort of the clothing has been studied considering the ability to manage heat and to transfersensible and insensible perspiration to the environment. Four bi-layer knitted fabrics are developed by changing the tuckstitch placement in four different points on wale, such as tuck on 4th, 8th, 12th and 16th wale with same course. It isobserved that the bi-layer knitted fabric with tuck on 12th wale exhibits better air, heat and moisture transfer as comparedto those with tuck on 4th, 8th, and 16th wales. The lower thickness and low mass per unit area exhibit better thermalconductivity, air permeability, water vapour permeability, wicking, moisture absorbency, drying rate and moisturemanagement properties. The less number of tuck stitch shows better thermal comfort characteristics considering bothobjective and wear trial method. The results are discussed with 95% significant level with ANOVA analysis andFriedman one-way analysis of variance

Red Deer Optimization with Deep Learning based Robust White Blood Cell Detection and Classification Model

The use of deep learning techniques for White Blood Cell (WBC) classification has garnered significant attention on medical image analysis due to its potential to automate and enhance the accuracy of WBC classification, which is critical for disease diagnosis and infection detection. Convolutional neural networks (CNNs) have revolutionized image analysis tasks, including WBC classification effectively capturing intricate spatial patterns and distinguishing between different cell types. A key advantage of deep learning-based WBC classification is its capability to handle large datasets, enabling models to learn the diverse variations and characteristics of different cell types. This facilitates robust generalization and accurate classification of previously unseen samples. In this paper, a novel approach called Red Deer Optimization with Deep Learning for Robust White Blood Cell Detection and Classification was presented. The proposed model incorporates various components to improve performance and robustness. Image pre-processing involves the utilization of median filtering, while U-Net++ is employed for segmentation, facilitating accurate delineation of WBCs. Feature extraction is performed using the Xception model, which effectively captures informative representations of the WBCs. For classification, BiGRU model is employed, leveraging its ability to model temporal dependencies in the WBC sequences. To optimize the performance of the BiGRU model, the RDO is utilized for parameter tuning, resulting in enhanced accuracy and faster convergence of the deep learning models. The integration of RDO contributes to more reliable detection and classification of WBCs, further improving the overall performance and robustness of the approach. Experimental results demonstrate the superiority of our Red Deer Optimization with deep learning-based approach over traditional methods and standalone deep learning models in achieving robust WBC detection and classification. This research highlights the possibility of combining deep learning techniques with optimization algorithms for improving WBC analysis, offering valuable insights for medical professionals and medical image analysis

Development of breathable and liquid/microbes barrier woven surgical gowns for hospital usage

An attempt has been made to develop a breathable woven surgical gown with antimicrobial and liquid repellent properties by finishing with nanoparticles of silver and fluorocarbon using pad-dry-cure method. Box-Behnken design has been used to optimize the coating parameters, i.e. concentrations of nanosilver (NS), nanofluorocarbon (NFC) and binder. The selected coating parameters has decisive influence on the fabric properties, such as air permeability, moisture vapour permeability, antimicrobial and tensile behaviour. The optimum coating parameters such as concentrations of NS, NFC and binder result in improved air permeability and moisture vapour permeability of the fabric for 3 g/L of NS and 40 g/L of NFC. The antibacterial activity of fabric is found to be higher for increased NS concentration and lower for increased NFC. In case of tensile properties of coated fabrics, the increase in NS concentration increases the tensile strength and decreases the bending modulus of fabrics

Modelling, Simulation, and Analysis of HAL BangaloreInternational Airport

Air traffic density in India and the world at large is growing fast and posing challengingproblems. The problems encountered can be parameterized as flight delay, workload of air trafficcontrollers and noise levels in and around aerodromes. Prediction and quantification of theseparameters aid in developing strategies for efficient air traffic management. In this study, themethod used for quantifying is by simulation and analysis of the selected aerodrome and airspace. This paper presents the results of simulation of HAL Bangalore International Airport,which is used by civil as well as military aircraft. With the test flying of unscheduled militaryaircraft and the increase in the civil air traffic, this airport is hitting the limit of acceptable delay.The workload on air traffic controllers is pushed to high during peak times. The noise contourprediction, especially for the test flying military aircraft is sounding a wake up call to thecommunities living in the vicinity of the Airport

Does the Digital Environment Improve Modern Users\u27 Internet Awareness?

This paper traces users\u27 Internet literacy level by measuring their Library visit and attitude towards the library as a means of access to electronic resources. Modern users\u27 dependence on the Internet increases day by day. The value of any product that exists in the market can be measured in terms of use. The present study revolves around users\u27 frequency of library visits and their Internet awareness levels. The research questions are; do modern users\u27 library visits differ? ; do the users\u27 Internet awareness levels differ? ; do the users\u27 library visits influence them to upgrade their awareness of the Internet