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Service quality matters of private hospitals in prevention of orthopedic issues during the covid-19 outbreak in india
This chapter explores patient satisfaction with healthcare service quality particularly medical and nonmedical service quality as a significant component in the appraisal of service quality attention of the COVID-19 outbreak. In this way, this investigation discovers how the patients evaluated service nature of facilities at private medical clinics in India. This examination in private emergency clinics with 300 patients arbitrarily chose from five private medical clinics. Information was gathered utilizing a survey,the legitimacy and dependability of which was affirmed in past examination. The outcomes demonstrated that among eight hypotheses of service quality, the patients were progressively happy with doctor meeting, services expenses, and confirmation process. There was a noteworthy connection between the positive impression of service quality and socio-economic factors in this research process. Most of the patients had positive involvement in visiting facilities and non-medical service quality arrangement. Copyright 2023, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. 2023 by IGI Global. All rights reserved. -
Experimental study of solar dryer used for drying chilly and ginger
Open air solar drying is one of the most popular methods for drying food products holds many drawbacks resulting in contamination of food products. This project is to transform the traditional method to an innovative, clean and cost-effective method to dry chilly and ginger, two being the top export commodity of India. Here a solar dryer is made which comprised of flat plate air heater, a chamber for drying and an air blower which induces forced convection. This system enhances the drying process even at low-intensity sunlight by assimilating heat storage materials. The equipment was tested in the meteorologicalcondition of the faculty of engineering, Christ (Deemed to be University) (latitude of 12.86N, a longitude of 77.43E) Bangalore, Karnataka. The process has reduced the moisture content from around 72.69% to 28.24% in the case of chilly and from 68.88% to 14.31% in the case of ginger within a period of 10 hours for a mass flow rate of 0.051kg/s. Average drier efficiency was estimated to be about 22%. The specific moisture extraction rate was estimated to be about 0.76 kg/kWh. This process resulted in a better moisture extraction rate, eliminating the defects caused by open sun drying. This process resulted in a better moisture extraction rate, eliminating the defects caused by open sun drying. 2019 Author(s). -
Numerical Modelling and Experimental Validation of Novel Para Winglet Tape for Heat Transfer Enhancement
Heat exchangers are predominantly used in the industries of production, manufacturing, power, oil and gas, petroleum, and cooling solutions. The competence of the heat exchanger is optimized through active and passive augmented techniques. The current study revolves around the performance evaluation of Novel Para winglet tape for flow and friction characteristics. Turbulence flow properties from Re of 30,000-to-6000 were explored for three different inclinations and pitches, respectively. Experimental and numerical solutions are derived to showcase the flow behavior over Para winglet tape inserts in the double pipe heat exchanger. Appreciable results were obtained in enhancing the Nusselt number (Nup) for a better heat transfer enforcement through the DEX. All case studies also increased when compared to the smooth pipe. Experimentally, the maximum Nu and Nusselt number ratio was observed to be 398.23 and 5.05 times over the plain tube. Similarly, the maximum friction factor and its ratio were observed to be near 0.33 and 8.89 times over the plain tube. Finally, the maximum POI of 2.68 to 2.37 was achieved with 20 inclinations. The experimental and numerical outcomes of Para winglet tape with the higher inclination and shorter pitch were found to be best out of the others. 2022 by the authors. -
Optimizing the efficiency of solar flat plate collector with trapezoidal reflector
Solar flat plate collectors are the most vital parts of a solar heating system. The collector plate absorbs the energy from the sun and transforms this radiation into heat and then transmit this heat into a fluid, it can either water or air. This research paper proposes a new technology to enhance the performance of the solar flat plate collector. A trapezoidal solar reflector is connected with the flat plate collector to enhance the amount of sunlight which hits the collector plate surface. The trapezoidal reflector concentrates both the direct and diffused radiation of the sun towards the flat plate collector. To maximize the concentration of incident radiation the trapezoidal reflector was permitted to change its inclination with the direction of sunlight. A prototype of a solar water heating system with trapezoidal reflector was constructed and achieved the improvement of collector plate efficiency by around 12%-13%. Thus the current solar heating system has the best thermal performance compared to the existing systems. 2019 Author(s). -
Novel algorithm for control of a shunt active power filter based on a three-level voltage source inverter
A three-level voltage source inverter is utilized to implement a shunt active power filter. SVPWM technique is used in the control circuit to generate the required gate pulses for the voltage source inverter. Principle of operation and analysis of the control circuit is presented. The proposed control algorithm ensures balance of dc bus voltages. Hence this active power filter is ideally suited for high power drives and transmission systems. The simulation results are presented and analyzed. The THD of load current is reduced to 6.47 % from 28.795 % in steady operation. 2010 Institute of Thermomechanics AS CR. -
Dissecting the Dichotomy of Skill and Social Justice Theory of Law School Legal Aid Clinics in the USA and India: A Re-look of the Past and the Present
With the mushrooming of legal aid clinics across institutions imparting legal education, there exists a conundrum as to their actual objectives. With passage of time, social justice theory is losing ground and skill development theory has gained greater predominance. In order to understand the objectives behind establishing legal aid clinics, the article traces its inter-linkages with the theory of social justice. In doing so, an analysis of the context under which legal aid clinics were established and their relevance to the present day is explored through the article. With the passage of 22 years of establishment of law school legal aid clinics in India, there still exists a dichotomy as to their real purpose and objective. These models of legal aid clinics of the past not only offer insights to develop present models of legal aid clinics, but there is also a need to emulate these models as they are relevant and apt even to this day. The article adapts a comparative approach between India and the USA, chronicling the past and present sojourns of the journey of law school legal aid clinics and the suitability of the social justice theory to the current Indian context. 2021 The West Bengal National University of Juridical Sciences. -
An Efficient Wireless Sensor Network based Intrusion Detection System
Wireless Sensor Networks (WSNs) are widely used in diverse applications due to their cost-effectiveness and versatility. However, they face substantial difficulties because of their innate resource constraints and susceptibility to security attacks. A possible method to improve the security of WSNs is clustering-based intrusion detection and responding mechanisms. An in-depth analysis of the clustering-based intrusion detection and response method for WSNs is presented in this study. The suggested method efficiently uses data mining and machine learning techniques to identify unusual behaviour and probable intrusions. The system effectively analyses data inside clusters by grouping Sensor Nodes (SN) into clusters, allowing it to differentiate between legitimate patterns and insecure activity. The network may respond promptly to identified breaches and react to the responsive mechanism, which reduces their impact and protects network integrity. The proposed Mathematically Modified Gene Populated Spectral Clustering Based Intrusion Detection System and Responsive Mechanism (MMMMGPSC-IDS-RM) is compared with existing state-of-art techniques, and MMMMGPSC-IDS-RM outperforms with the highest detection rate of 96%. 2023 IEEE. -
Probiotics and its applications: A systematic review
The digestive system of human beings contains a large group of microbes which help in controlling the host's internal environment and thereby assist in maintaining the health of the host. These microorganisms exist in a mutual relationship with the human host which has led to extensive research in this particular field. Most of these microorganisms have become resistant to day-today drugs and antibiotics. These organisms control various functions like defense, eupepsia, catabolism, anabolism and also help in brain-gut responses. Probiotics assist in improving gut bacteria and are found to be effective in controlling various diseases. Prescribing probiotics to children with malnutrition in underdeveloped countries can reduce the death of many children. This review outlines the importance of probiotics in human health and in the treatment of several metabolic disorders. 2021 World Research Association. All rights reserved. -
Cognitive Fuzzy-based Behavioral Learning System for Augmenting the Automated Multi-issue Negotiation in the E-commerce Applications
Evolution of agent-based technology presents behavioral learning and sustainable negotiation challenges in e-commerce applications. In particular, the challenge of designing the negotiation strategy to incorporate sustainability in e-commerce business that can leverage the agent to reach its objectives by increasing the negotiation coordination and cooperation with the opponent agents. Therefore, the proposed research introduces the negotiation strategy sustainable solution using a cognitive fuzzy-based behavioral learning system which can change the preferences of negotiating agents according to human psychological characteristics. It will mimic the attitudes of human risk, patience and regret during the course of bilateral negotiation and also change the preference structures according to the fuzzy logic rules. As a result, the proposed negotiation strategy makes significant improvements on various parameters such as utility value, success rate, total negotiation time, and communication overhead while changing the negotiation rounds from 50 to 500. Since this system leverages the negotiation strategy of the agent by taking appropriate decisions to reach better agreement based on the interest, belief and psychological characteristics of negotiating opponents. Moreover, the usage of negotiation in the cloud-based platform can leverage the e-commerce applications to handle as many requests as possible due to its dynamic elasticity. 2022 Taiwan Academic Network Management Committee. All rights reserved. -
Cloud-Based Diabetic Retinopathy Severity Recognition System Using Ensemble Deep Convolutional Neural Network Classifier Model
One of the key reasons for visual impairments is due to the ignorance of diabetic retinopathy disease. This research study focuses on the early recognition of diabetic retinopathy disease from the fundus images and identifies its severity stages to make successful treatments against blindness risk. Some traditional approaches explored the decision tree, kernel-based support vector machine, and Nae Bayes classifier models to extract the features from fundus images. Most of the researchers applied the modern approach of convolutional neural network model through transfer learning mechanism to extract relevant features from the fundus images. It helps in the diagnosis of diabetic retinopathy that may delay the prediction process and create inconsistency among the doctors. So, a deep learning-based approach is proposed in this research study to provide stage-wise prediction of diabetic retinopathy disease with a multi-task learning mechanism. As a result, the proposed deep convolutional neural network classifier with an ensemble model outperforms the existing classifier with EfficientNet-B4, EfficientNet-B5, SE-ResNeXt50 (380?380), and SE-ResNeXt50 (512?512) networking methods in the context of prediction correctness, sensitivity, specificity, macro F1, and quadratic weighted kappa (QWK) score metrics. Exploiting hyperparameter optimizations on the deep learning classifier model and multi-task regression learning approaches make significant improvements over the performance evaluation metrics. Finally, the proposed approaches make the effective recognition of diabetic retinopathy disease stages based on the human fundus image. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Cloud-Based Cataract Recognition System Using Hybrid Classifier Model
One of the key challenges of ophthalmologists is to diagnose the various ranges of ophthalmological illnesses such as diabetic retinopathy, cataract, and glaucoma. Here, cataract disease is identified as the one of the leading and most common ophthalmological problems that occurs due to aging. A computer-assisted cataract detection and diagnosis support system is required by the ophthalmologists to overcome the error that occurs during manual screening process. So, a cloud-based cataract recognition system is proposed using the convolutional neural network with support vector machine classifier model to improve the prediction accuracy, sensitivity, specificity, precision, recall, F1-score, and Mathews correlation coefficient. Moreover, the four-layer convolutional neural network is finetuned with a rich set of features and trained with various network models such as Inception V3, MobileNet, VGG-16, VGG-19, and ResNet-101. Therefore, the proposed hybrid combination of ResNet-101 with support vector machine classifier makes better cataract detection and outperforms the existing classifier models in terms of above-mentioned performance evaluation metrics. Moreover, the proposed hybrid approach provides the better telemedical solution to remote people by providing accurate disease prediction and severity grading such as normal, mild, premature, and severe cataract. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
IoT-based smart healthcare video surveillance system using edge computing
Managing distributed smart surveillance system is identified as a major challenging issue due to its comprehensive aggregation and analysis of video information on the cloud. In smart healthcare applications, remote patient and elderly people monitoring require a robust response and alarm alerts from surveillance systems within the available bandwidth. In order to make a robust video surveillance system, there is a need for fast response and fast data analytics among connected devices deployed in a real-time cloud environment. Therefore, the proposed research work introduces the Cloud-based Object Tracking and Behavior Identification System (COTBIS) that can incorporate the edge computing capability framework in the gateway level. It is an emerging research area of the Internet of Things (IoT) that can bring robustness and intelligence in distributed video surveillance systems by minimizing network bandwidth and response time between wireless cameras and cloud servers. Further improvements are made by incorporating background subtraction and deep convolution neural network algorithms on moving objects to detect and classify abnormal falling activity monitoring using rank polling. Therefore, the proposed IoT-based smart healthcare video surveillance system using edge computing reduces the network bandwidth and response time and maximizes the fall behavior prediction accuracy significantly comparing to existing cloud-based video surveillance systems. 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Cloud service negotiation framework for real-time E-commerce application using game theory decision system
A major demanding issue is developing a Service Level Agreement (SLA) based negotiation framework in the cloud. To provide personalized service access to consumers, a novel Automated Dynamic SLA Negotiation Framework (ADSLANF) is proposed using a dynamic SLA concept to negotiate on service terms and conditions. The existing frameworks exploit a direct negotiation mechanism where the provider and consumer can directly talk to each other, which may not be applicable in the future due to increasing demand on broker-based models. The proposed ADSLANF will take very less total negotiation time due to complicated negotiation mechanisms using a third-party broker agent. Also, a novel game theory decision system will suggest an optimal solution to the negotiating agent at the time of generating a proposal or counter proposal. This optimal suggestion will make the negotiating party aware of the optimal acceptance range of the proposal and avoid the negotiation break off by quickly reaching an agreement. 2021 - IOS Press. All rights reserved. -
Cost-enabled QoS aware task scheduling in the cloud management system
Maintaining the quality of service (QoS) related parameters is an important issue in cloud management systems. The lack of such QoS parameters discourages cloud users from using the services of cloud service providers. The proposed task scheduling algorithms consider QoS parameters such as the latency, make-span, and load balancing to satisfy the user requirements. These parameters cannot sufficiently guarantee the desired user experience or that a task will be completed within a predetermined time. Therefore, this study considered the cost-enabled QoS-aware task (job) scheduling algorithm to enhance user satisfaction and maximize the profit of commercial cloud providers. The proposed scheduling algorithm estimates the cost-enabled QoS metrics of the virtual resources available from the unified resource layer in real-time. Moreover, the virtual machine (VM) manager frequently updates the current state-of-the art information about resources in the proposed scheduler to make appropriate decisions. Hence, the proposed approach guarantees profit for cloud providers in addition to providing QoS parameters such as make-span, cloud utilization, and cloud utility, as demonstrated through a comparison with existing time-and cost-based task scheduling algorithms. 2021 - IOS Press. All rights reserved. -
Cloud-enabled Diabetic Retinopathy Prediction System using optimized deep Belief Network Classifier
Diabetic retinopathy disease is one of the notorious metabolic disorders happens due to increase of blood sugar level in human body. In computer vision, images are recognized as the indispensable tool for precise prediction and diagnosis of diabetic retinopathy. Therefore, the proposed research study considers the fundus images of various patients containing the diabetic disease. Basic idea behind this research is to introduce a stochastic neighbor embedding (SNE) feature extraction approach for the sake of dimensional reduction and unnecessary noise removal from the fundus images. After feature extraction, the proposed optimized deep belief network (O-DBN) classifier model is capable of measuring the image features into various classes that gives the severity levels of diabetic retinopathy disease. Moreover, the proposed cloud-enabled diabetic retinopathy prediction system using the SNE feature extraction and O-DBN classification model could outperform the existing online prediction systems in terms of sensitivity, specificity, F1-score, prediction time and accuracy. 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Utilization of IoT-Based Healthcare System and Vital Data Monitoring of patients
The next generation of technology, known as the Internet of Things (IoT), will provide a comprehensive system that connects different domains, functions, and innovations. With the increasing demand for elderly care due to the growing ageing population, health monitoring systems have become increasingly important. Continuous monitoring is required in ICU to monitor the health conditions of patients. In cases where patients are released from the hospital, they are advised to rest and observed for a certain period, and the IoT system is very helpful in such cases. This article primarily discusses the implementation of a precise autonomous medical facility management system using IoT. In the past, only current data was displayed, and the patients history could not be accessed. In this study, we propose an IoT-based healthcare system for continuous monitoring of a patients health conditions. The healthcare system focuses on measuring and monitoring various biological parameters of the patients body, such as heart rate, blood oxygen saturation level, and temperature, using a web server and an Android application. Doctors can continuously monitor the patients condition on their smart phones using the Android application. Moreover, the patients history will be stored on the web server, and doctors can access the information from anywhere without being physically present. RJPT All right reserved. -
Multilayer flow and heat transport of nanoliquids with nonlinear Boussinesq approximation and viscous heating using differential transform method
Multilayer fluid flow models are significant in various applications, namely, cooling electronic systems, solar thermal systems, and nuclear reactors. The density of a fluid fluctuates nonlinearly due to large temperature difference circumstances in thermal systems. Thus, the linear Boussinesq approximation is no longer relevant. Therefore, this article describes a multilayer flow of nanoliquids in the presence of nonlinear Boussinesq approximation. The hybrid nanoliquid layer is sandwiched between two nanoliquid layers. The single-phase khanafer-vafai-lightstone model is implemented to simulate the nanoliquids. The quadratic density temperature fluctuation and viscous heating are taken into account. The temperature and velocity across the interface are assumed to be continuous. The equations that govern the problem are solved analytically by using the differential transformation method. The results show that the presence of a hybrid nanoliquid layer affects the velocity and heat transfer properties of the nanofluid flow. Hybrid nanofluid can be used to achieve the desired multilayer flow properties of a nanofluid and its heat transfer properties. Further, the quadratic convection aspect increases the velocity distributions. 2021 Wiley Periodicals LLC -
Electro-osmotic effect on the three-layer flow of Binary nanoliquid between two concentric cylinders
The three-layer flow of an immiscible nanoliquid in composite annulus with an electro-kinetic effect is analyzed using Buongiornos model. This model helps in analyzing the impact of two major phenomena, namely thermophoresis and Brownian motion. In this model, an interfacial layer is formed between the liquids due to the immiscibility of the base liquids. The use of a multilayer model especially in cooling systems brings more applications in many industries such as nuclear, biomedical, and solar. Different from the earlier studies on multilayer channel flow, this paper explains the three-layer flow between two concentric cylinders in the presence of cross-diffusion which makes the work unique. Further, the middle region is assumed to be porous and heat source or sink is applied to the entire system. Also, the flux conservation condition for nanoparticle volume fraction is considered. The equations governing the problem are simplified and are solved using the differential transform method. The results indicate that the electroosmotic parameter enhances the velocity but reduces the electrostatic potential. Further, the diffusion ratio improves the temperature and decreases the solute concentration of the fluid. 2022, Akadiai Kiad Budapest, Hungary. -
Magnetohydrodynamic flow of two immiscible hybrid nanofluids between two rotating disks
The two-layer model of the magnetohydrodynamic flow of hybrid nanofluid (HNF) between two disks of the same radii is analyzed in this study. The base fluids of both the hybrid nanofluids are immiscible so that these two fluids form an interfacial layer making the study more unique and innovative. The heat source/sink with viscous dissipation effect on energy equation is discussed. The governing equation is in the form of PDEs that are later reduced to ODEs with the help of the Von Karman transformation. The resulting ODEs are solved using the RK method and the results are interpreted graphically. In addition to temperature and concentration gradient, the radial, tangential and axial velocities for different parameters are studied. The results indicate that the physical ratios such as viscosity and thermal conductivity ratios can improve the fluid motion and temperature even in the presence of magnetic field. Also, the ratio of stretching rate produced by the rotation of disk can effectively control the fluid motion. The two fluid flow between two rotating disk forms an interfacial layer between the fluids results in the increment of heat transfer rate which finds application in the field such as heat ex-changer equipment, Cryogenic systems, electronic appliances, and solar collectors. 2024 Taylor & Francis Group, LLC. -
Subaltern languages : The question of vernaculars in 21st century India /
Jopurnal of Educational Planning And Administration, Vol.33, Issue 1, pp.51-65