Browse Items (11858 total)
Sort by:
-
Bi Functional Manganese-Pyridine 2,6 Dicarboxylic Acid Metal Organic Frameworks with Reduced Graphene Oxide as an Electroactive Material for Energy Storage and Water Splitting Applications
In recent years, metal organic frameworks (MOFs) with porous carbon materials have significantly improved the design and engineering of high performance electrode materials and have found applications in energy storage devices. This study explores the supercapacitor and electrocatalytic water splitting applications of Mn-MOF/reduced graphene oxide (rGO) composite synthesized via a hydrothermal technique using pyridine 2,6 dicarboxylic acid as a linker. Mn-MOF/rGO exhibits a specific capacitance of 428.28 F g?1 with a rate capability of 83.7% and high cyclic stability. The oxygen evolution reaction of the composite is evaluated using linear sweep voltammetry, and the overpotential is calculated to be 400 mV. Our primary goal is to investigate the effect of rGO on the electrochemical response of MOF. The dielectrode (Mn-MOF/rGO) electrolysis system exhibits long-run stability with a low cell potential of 1.8 V, indicating its prospective application as an excellent water electrolyzer. The combination of Mn-MOF with rGO helps in increasing the number of active sites, thereby improving its electronic conductivity by enhancing the electron transfer rate. The outstanding electrochemical behaviour of Mn-MOF/rGO paves the way for the use of rGO-incorporated Mn-MOF in bifunctional applications as energy-generating and storage devices. 2023 The Electrochemical Society (ECS). Published on behalf of ECS by IOP Publishing Limited. -
Facile synthesis of Mn-Ni bimetal organic framework decorated with amine as an electrode for a high-performance supercapacitor
In the recent years, the whole world is looking for better energy storage devices. Supercapacitors are among the mostpromising high-capacity energy storage devices. Manganese-based material has gained more importance among transition metals due to its cost, easy fabrication, and wide potential applications. Here, we report the synthesis of a novel MOF using metal centers, dicarboxylate ligand, and aminoterephthalic acid as a co-ligand {Mn-Ni-NH2(h2fipbb)}MOF. The synthesized material has a unique hierarchical morphology consisting of manganese and nickel connected with NH2 through h2fipbb ligand linkage, which is highly efficient for the permeation of the electrolyte and electron transfer. The {Mn-Ni-NH2(h2fipbb)}MOF shows an excellent specific capacitance of 711.60 F g?1 using 2M KOH at a current density of 1 A g?1. The two electrode system material exhibitsa high-power and energy density of 743.99Wkg?1 and 20.49 Wh kg?1, respectively. From the above results, the synthesized {Mn-Ni-NH2(h2fipbb)}MOF can be considered a promising material for electrochemical energy storageapplications. 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Designing coordinatively unsaturated metal sites in bimetallic organic frameworks for oxygen evolution reaction
Metal organic frameworks (MOFs) are developing as promising catalysts for oxygen evolution reactions. A bimetallic electrocatalyst MOF using Ni and Cu as metal sources and 1,4-benzene dicarboxylic acid as a linker has been synthesized and evaluated for oxygen evolution reaction. Compared to monometallic MOFs, bimetallic MOFs participate more actively in electrocatalysis due to the higher abundance of active sites, local crystallinity, and lower long-range disorder. When utilized as oxygen evolution catalysts, NiCu MOFs have a low overpotential of 340 mV at 10 mA/cm2 and a low Tafel slope of 65 mV/dec. The study paves the way for the development of highly efficient catalysts for water splitting applications. 2023 Elsevier Ltd -
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. -
Modified Metal Organic Frameworks for Electrocatalytic Water Splitting and Energy Storage Applications
Metal-organic frameworks (MOFs) are a class of crystalline material formed by the newlinecombination of metal ions/clusters along with organic linkers. This work is mainly based on newlinesynthesizing MOFs and their application in electrocatalytic water splitting and newlinesupercapacitors. The MOFs synthesized in the present work are Ni-Cu, {Mn-NiNH2(h2fipbb)}, Mn-MOF/rGO, and Sm-MOF/rGO/PANI using different ditopic and tritopic linkers. Using various characterization techniques, the formation of the synthesized MOFs is confirmed. The increasing use of fossil fuels now contributes to a number of environmental problems, including climate change and global warming. High-performance electrochemical energy storage devices are essential for portable electronics, electric cars, newlineand renewable energy storage medium, driving demand. MOFs are emerged as a promising newlinecontender for energy storage applications owing to their novel microstructures, atomically dispersed metal centers, and earth-abundant metal components. Electrochemical water splitting is a crucial approach in the pursuit of producing environmentally friendly fuels such newlineas H2 and O2, reducing our dependence on traditional fossil fuels while promoting newlinesustainable and clean energy sources. In order to produce hydrogen with the best efficiency and lowest cost, these MOFs are used. Electrochemical studies like cyclic voltammetry, galvanostatic charge discharge, and electrochemical impedance spectroscopy reveal that the prepared MOFs can be used as supercapacitors. Linear sweep voltammetry and Tafel plot determine the performance of these MOFs towards water splitting studies. Supercapacitors, which are electrochemical capacitors, are popular energy storage devices with quick charge rate, high power density, excellent rate capability, and outstanding life expectancy. -
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.