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Simulation and fabrication of tungsten oxide thin films for electrochromic applications
Electrochromics is the emerging technology that is used in sunlight control window glazing for buildings, automobiles and it can also control indoor climate through smart windows. Electrochromism is the mutable change in optical properties of an electrochromic material caused by redox reactions due to the application of voltage. Easy intercalating the H + ions on a dense electrochromic material (WO3) is the most important parameter as far as the reaction kinetics is concerned. The goal of our work is to improve the electrochemical response of electrochromic material by constructing nano-pillars rather than using dense electrochromic materials. Electrochemical performance of both the dense (planar) and porus (nano pillars) structures were simulated and experimentally proved with a systematic discussion in the present work. It is proven and shown here the increase in the electrochemical kinetics through easy diffusion of ions into the nanostructured electrochromic material. 2022 Elsevier B.V. -
On ion transport during the electrochemical reaction on plane and GLAD deposited WO3 thin films
Tungsten oxide thin films were deposited on FTO and Corning glass substrates on Plane and GLAD (75) using DC magnetron sputtering and characterized using SEM, XRD, UVVis spectrophotometer, and Electrochemical analyzer systematically. Further, a comparative analysis was carried out in which it was observed that the result of surface morphology for plane showed the denser and GLAD showed nanopillars deposition. The amorphous nature of the sample was evident from XRD analysis. Optical transmittance was between 87% and 81% for both plane and GLAD. The Electrochemical studies showed the diffusion coefficient of H+ ions are more compared to Li+ ions for both plane and GLAD and Coloration efficiency was calculated at the scan rates of 10, 30, and 50 mV/s at the wavelength of 500 to 600 nm. 2021 -
Sputter deposited tungsten oxide thin films and nanopillars: Electrochromic perspective
Tungsten oxide (WO3) thin films and nano pillars were grown on FTO and corning substrates by using DC magnetron sputtering. Structural properties, surface morphology, optical properties, and electrochromic properties were systematically characterized by using SEM, XRD, UVVis Spectrometer, and Electrochemical Analyser respectively. Increased oxygen partial pressure resulted a rise in the optical transmittance from 72% to 89% at a wavelength of 600 nm. Moreover, coloration efficiency was also found to vary with partial pressures for both planar and glad from 30.48 cm2C-1 to 78.36 cm2C-1. We observe that glad deposited nano pillars showing higher coloration efficiency as compared to the planar thin film. The coloration efficiency found for the planar thin film and nano pillars at optimized partial pressure are 37.04 cm2C-1 and 78.36 cm2C-1 respectively. A strong influence of oxygen partial pressure and surface to volume ratio has been observed on the coloration efficiency, which can play a major role in the electrochromic application. 2022 Elsevier B.V. -
Glancing angle sputter deposited tungsten trioxide (WO3) thin films for electrochromic applications
The columnar growth angle-dependent tungsten oxide (WO3) thin films were grown by using the Glancing angle sputter deposition (GLAD) technique with varying different substrate angles (00, 700, 750, and 800) on Fluorine-doped tin oxide (FTO) and Corning glass (CG) corning glass substrates at room temperature. The surface morphology, crystallographic structure, optical, and electrochemical properties were determined using X-ray diffraction (XRD), Field emission scanning electron microscopy (FE-SEM), UltravioletVisible(UVVis) spectrometer, and electrochemical analyzer, respectively. The structural properties reveal that the films are amorphous in nature. FE-SEM studies observed the columnar growth of the nano-rods and surface porosity. The optical transmittance of the deposited films was decreased from 83 to 78%, and the optical bandgap decreased from 3.08 to 2.88eV with increasing GLAD angle. The electrochemical studies reveal that the GLAD angle influenced the coloration efficiency (CE). The highest CE of 32cm2/C at 600nm and highest Diffusion coefficient (DC) of 6.529 109 cm2s?1 of the films was observed for the films deposited at an angle of 750. 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature. -
Effect of annealing and oxygen partial pressure on the RF sputtered WO3 thin films for electrochromic applications
the electrochromic thin layer of Tungsten trioxide (WO3) was RF sputtered on FTO (fluorine-doped tin oxide) slide. In a reactive Ar + O2 gas environment with varying oxygen partial pressures, the deposition continued. The samples were air annealed at 400 C for 2 h after being deposited at room temperature. SEM, XRD, UVVisible spectrometer, and electrochemical analyzer characterization methods were employed to analyze the surface, structural morphology, optical, and electrochromic behaviour of the deposited material after annealing. The Optical Bandgap and Transmittance were found to be of a higher value for air annealed samples than RT deposited samples because RT deposited samples are amorphous whereas air annealed samples exhibit crystalline nature with Oxidation, reduction peak currents variation with respect to the temperature. 2021 -
Factor Analysis for Portfolio Returns: Investigating How Macroeconomic Factors Impact the Performance of the equity Portfolio
This paper investigates the complex relationship between macroeconomic factors and equity portfolio performance using regression analysis. In today's volatile financial environment, it emphasizes the importance of understanding how variables such as interest rates, inflation, money supply and GDP influence investment outcomes. Exact statistical techniques and historical data from a specific time period are used to uncover hidden factors affecting portfolio returns, with a particular focus on interest rates, inflation, money supply, and GDP. The goal of the research is to provide a comprehensive understanding of how these macroeconomic factors influence the equity investments. 2024 IEEE. -
Envisaging an Intelligent Blockchain Network by Intelligence Sharing
Blockchain Technology is gaining popularity throughout various industry verticals due to its data decentralization and tamper-evident nature. Machine Learning (ML) is all about embedding a learning capability to computing machines so that the machine can learn based on historical data in a way how human beings learn things. An important part of ML is the process of learning which needs humongous processing capability and hence it is time-consuming. Significant benefits have been predicted from the integration of these two technologies. Making a complete blockchain network intelligent in a simple and efficient way is a major challenge. In this work, a Multi Layer Perceptron (MLP) model is implanted in every node of the blockchain network. An efficient technique is proposed to make an intelligent blockchain network in minimum possible time and using minimum processing power. During the network formation, every node of the network has knowledge of the model architecture. At some point in time, the model of the randomly selected node gets trained. After completion of the training of that node, the intelligence is replicated to the entire network. 2022 IEEE. -
A Low Voltage and Low Power Analog Multiplier
In this research work, a low voltage analog multiplier has been realized through the utilization of a flipped voltage follower (FVF). The multiplier is characterized by its capacity to function at low power while exhibiting high gain. The exclusive use of transistors in its implementation renders it highly appropriate for fully integrated circuit applications. The multiplier has been developed using a supply voltage of 500 mV and an operating frequency of 25 KHz. The design consumes power of 8.23 uW. Moreover, a comparative study between the proposed multiplier and the conventional gilbert multiplier is presented in the paper. All simulations and layout designs have been conducted through the virtuoso analog design environment (ADE) of Cadence at 45 nm CMOS technology. 2023 IEEE. -
Topic Modelling of ongoing conflict between Russia and Ukraine
Online news sites provide hotspots to extract popular ratings and opinions on a wide range of topics. Realizing what individuals are referring to and understanding their concerns and suppositions is exceptionally significant to organizations and political missions. Furthermore, it is incredibly difficult to physically peruse such enormous volumes of data and gather the themes. Keeping in mind the prevailing plight of war-Torn nations such as the recent conflict between Russia and Ukraine. This study performs aims to perform topic modelling using LDA (Latent Dirichlet Allocation) and text analysis on datasets collected from various online news websites. To increase the accuracy and efficacy of the topic modelling, a comparative analysis is proposed that elevates the performance of machine learning models. This study also develops an algorithm where the entire process can be automated from the point of data collection to finding optimum array of topics in the given dataset. Searching for insights from the collected information can therefore become very tedious and time-consuming. Topic modelling was designed as a tool to organize, search, and understand vast quantities of textual information. The topic model using LDA was utilized to do a text analysis for this research. In the beginning, researchers have scraped a total of 1178 articles that covered the war conflict between Russia and Ukraine from December 1, 2021, to May 16, 2022. After that, researcher built the LDA model and modified hyper parameters based on the coherence score Cv that was used for the model evaluation technique. When using the most effective model, prominent topics, and representative documents pertaining to each topic, topic allocation among the documents, and potential enhancements are covered in the last section. 2022 IEEE. -
Identifying the population of T-Tauri stars in Taurus: UVoptical synergy
With the third data release of the Gaia mission, Gaia DR3 with its precise photometry and astrometry, it is now possible to study the behavior of stars at a scale never seen before. In this paper, we developed new criteria to identify T-Tauri stars (TTS) candidates using UV and optical color-magnitude diagrams (CMDs) by combining the GALEX and Gaia surveys. We found 19 TTS candidates and five of them are newly identified TTS in the Taurus molecular cloud (TMC), not cataloged before as TMC members. For some of the TTS candidates, we also obtained optical spectra from several Indian telescopes. We also present the analysis of distance and proper motion of young stars in the Taurus using data from Gaia DR3. We found that the stars in Taurus show a bimodal distribution with distance, having peaks at 130.17-1.241.31 pc and 156.25-5.001.86 pc. The reason for this bimodality, we think, is due to the fact that different clouds in the TMC region are at different distances. We further showed that the two populations have similar ages and proper motion distribution. Using the Gaia DR3 CMD, we showed that the age of Taurus is consistent with 1Myr. 2023, Indian Academy of Sciences. -
Routing TQM through HR strategies to achieve organizational effectiveness: themediating role of HR outcomes in India
Purpose: The present research focuses on improving the awareness related to soft total quality management (TQM) practices by looking from the viewpoint of strategic human resources (HR). In addition, it is intended to reflect on the resulting soft TQM-HR outcomes and determine the mediating effect between soft TQM-HR strategies and organizational effectiveness (OE). Design/methodology/approach: An exploratory research methodology with an online survey technique was adopted for the study. Three hundred and three managerial-level personnel from nine large Indian manufacturing organizations participated in the research. A theoretical model is projected and verified using correlation and mediation analysis. Findings: The results show that commitment, reduced turnover intentions and satisfaction levels of employees mediate the relationship between resources, development and retention strategies and OE. However, the retention strategy has the strongest association with the OE of the three strategies. Also, of the three HR outcomes, satisfaction was strongly associated with OE. The analysis proved that the proposed model is an acceptable fit. Practical implications: Implementing HR-related TQM strategies will likely impact OE since it elicits positive HR outcomes such as commitment, reduced turnover intention and satisfaction. Recognizing human resources as a unique strategic asset will help HR managers devise adequate resourcing, development and retention strategies instrumental in executing TQM. Originality/value: The present micro study is unique in scrutinizing the influence of soft TQM-HR practices on organizational effectiveness by analysing the mediating effects of commitment, reduced turnover intention and satisfaction in Indian large-scale manufacturing organizations. The study is unique since no literature deciphers the linkages between HR strategies and organizational effectiveness in the Indian manufacturing sector. 2023, Emerald Publishing Limited. -
Joycean novels: A broad secularizing project
This paper discusses how the Irish novelist James Joyce used the Novel form as an interface of religion and secularism in fiction. The secularism of his novels is a nuanced, complex project, as he was deeply haunted by the fabric of religious upbringing which he had only partially disowned. Joyce's works as well as life reflect an ambiguous relationship to religious texts, themes, and institutions. A non-teleological concept of modernity is what is present in the works of Joyce especially in his novels, A Portrait of the Artist as a Young Man and Ulysses. Here, the secular and the religious exist in an intimately antinomian, mutually defining opposition in many aspects of cultural life, including literature. 2015 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore), ISSN: 0253-7222. -
Becoming knowledge societies: A happiness framework for institutions of higher education in India
The transformation of Indian Higher Education Institutions (IHEIs) to knowledge societies require multiple coordinated interventions and actions on both the local and the global levels of institution administration, management, supply and demands of the economy and society. A vibrant knowledge society will not only require institutions support to plan and amend practices but also require the engagement of all stakeholders and the ability of individuals and society to imbibe new ways of thinking, working, and acting. It is vital to chart a direction and an approach that is in alignment with the local context and culture. At the supply front, IHEIs should initiate intervention programmes to enhance human capital through investment in a Happiness Framework and a shift in the workplace culture that requires conscious measures of intervention, which will drive institutional effectiveness and improve student experiences. This happiness framework should be integral and reinforced, first as an induction-training programme, and practised as institutional culture. Individuals, who are thus, trained at the local level of institutions, while participating in the global labour market with their increased skills and competencies will drive the IHEIs towards a fully functioning knowledge-based society. A knowledge-based society thus built to generate, disseminate, and use knowledge to improve the standard of living and the quality of life of citizens in an ethical and sustainable way will certainly make happiness as its ultimate goal and will focus on happiness as a process to improve efficiency and efficacy of the work force. 2019 Journal of Dharma: Dharmaram Journal of Religions and Philosophies (DVK, Bangalore),. -
The future of urban life: The technological and humanistic dimensions of cognitive cities
A smart city implies realising sustainable city growth enabled by technology-based intelligent solutions to give its citizens a good quality of life. Information and communication technologies play a crucial role as the nerve centre of the smart city for collecting and analysing data from various sources, like mobile, social media, and sensors. The Internet of things (IoT) and big data (BD) also play a critical role in smart city infrastructures, changing how we analyse patterns and trends in human behaviour. Smart cities generate massive amounts of data and therefore need many flexible ways to process data and implement solutions. Recently, cognitive analytics have attracted the attention of researchers and practitioners worldwide as a technology-based innovative solution. It is a novel approach to information discovery and decision-making which uses multiple intelligent technologies such as statistical machine learning, deep learning, distributed artificial intelligence, natural language processing and visual pattern recognition to understand data and generate insights. A cognitive smart city refers to the convergence of emerging IoT and smart city technologies to realise cyber-physical social systems, their generated big data from sensing to communication and computing, and artificial intelligence techniques for all aspects of collaborative computing in sensors, actuators and human-machine interfaces. The field of humanities typically approaches the concept of cognitive cities from a cultural, philosophical, and humanistic perspective. Humanities scholars examine how cities shape our thoughts, beliefs, values, and experiences and how they impact our collective memory and identity. They consider the role of cities as sites of cultural production and consumption and explore the social and political implications of urbanisation and technological advancement. This paper aims to highlight the connection between technology and the humanities in the context of cognitive cities. The paper will explore the technological aspects of cognitive cities and their cultural, humanistic, and philosophical implications. 2023 Author(s). -
Effectiveness of performance appraisal systems in relation to teacher dedication in public and private secondary schools in zimbabwe
Performance appraisal systems need to be effective in improving or sustaining employee performance; otherwise, they are a sheer waste of time and money spent on their development and implementation. This study was an evaluation of the effectiveness of the current teacher performance appraisal system, in relation to teacher dedication to work, newlineas practised in Zimbabwean Secondary Schools. Since the introduction of the current teacher appraisal scheme in Zimbabwe in 2011, no research was carried out to determine whether it serves the purposes for which it was designed. Evaluating the effectiveness of the system encompasses a wide scope, including the perceptions of those appraised. The question that comes to the fore is,and#8214; What are teachers perceptions of the effectiveness of the current system of teacher appraisal as practised in public and private secondary schools in Zimbabwe?and#8214; Both quantitative newlineand qualitative methods of research were used to address the question. The study sought to establish the strength of the relationship that exist between the current teacher performance appraisal system and day to day newlineduties of the teacher, the extent to which it leads to improvements in the teaching and students learning process. It also seeks to establish how it addresses teacher development needs and whether the mechanisms and procedures for the management and implementation of the appraisal system in the schools are adequate. The current Performance Appraisal System, Result-Based Management and is output oriented. The main objective of this study was to assess the effectiveness of the current performance appraisal system on the performance of teachers in public and private secondary schools in Zimbabwe, by studying its implementation in five of the ten provinces. The overall purpose of the newlinestudy is to contribute to current policy and practice debate on how to improve and strengthen teacher performance appraisal and management system in Zimbabwe. -
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IoT-based traffic prediction and traffic signal control system for smart city
Because of the population increasing so high, and traffic density remaining the same, traffic prediction has become a great challenge today. Creating a higher degree of communication in automobiles results in the time wastage, fuel wastage, environmental damage, and even death caused by citizens being trapped in the middle of traffic. Only a few researchers work in traffic congestion prediction and control systems, but it may provide less accuracy. So, this paper proposed an efficient IoT-based traffic prediction using OWENN algorithm and traffic signal control system using Intel 80,286 microprocessor for a smart city. The proposed system consists of 5 phases, namely IoT data collection, feature extraction, classification, optimized traffic IoT values, and traffic signal control system. Initially, the IoT traffic data are collected from the dataset. After that, traffic, weather, and direction information are extracted, and these extracted features are given as input to the OWENN classifier, which classifies which place has more traffic. Suppose one direction of the place has more traffic, it optimizes the IoT values by using IBSO, and finally, the traffic is controlled by using Intel 80,286 microprocessor. An efficient OWENN algorithm for traffic prediction and traffic signal control using a Intel 80,286 microprocessor for a smart city. After extracting the features, the classification is performed in this step. Hereabout, the classification is done by using the optimized weight Elman neural network (OWENN) algorithm that classifies which places have more traffic. OWENN attains 98.23% accuracy than existing model also its achieved 96.69% F-score than existing model. The experimental results show that the proposed system outperforms state-of-the-art methods. 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. -
Optimal Stacked Sparse Autoencoder Based Traffic Flow Prediction in Intelligent Transportation Systems
Recently, intelligent transportations system (ITS) has gained significant internet due to the higher needs for road safety and competence in interconnected road network. As a vital portion of the ITS, traffic flow prediction (TFP) is offer support in several dimensions like routing, traffic congestion, and so on. To accomplish effective TFP outcomes, several predictive approaches have been devised namely statistics, machine learning (ML), and deep learning (DL). This study designs an optimal stacked sparse autoencoder based traffic flow prediction (OSSAE-TFP) model for ITS. The goal of the OSSAE-TFP technique is to determine the level of traffic flow in ITS. In addition, the presented OSSAE-TFP technique involves the traffic and weather data for TFP. Moreover, the SSAE based prediction model is designed for forecasting the traffic flow and the optimal hyperparameters of the SSAE model can be adjusted by the use of water wave optimization (WWO) technique. To showcase the enhanced predictive outcome of the OSSAE-TFP technique, a wide range of simulations was carried out on benchmark datasets and the results portrayed the supremacy of the OSSAE-TFP technique over the recent state of art methods. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
Blockchain with deep learning-enabled secure healthcare data transmission and diagnostic model
At these times, internet of things (IoT) technologies have become ubiquitous in the healthcare sector. Because of the increasing needs of IoT, massive quantity of patient data is being gathered and is utilized for diagnostic purposes. The recent developments of artificial intelligence (AI) and deep learning (DL) models are commonly employed to accurately identify the diseases in real-time scenarios. Despite the benefits, security, energy constraining, insufficient training data are the major issues which need to be resolved in the IoT enabled medical field. To accomplish the security, blockchain technology is recently developed which is a decentralized architecture that is widely utilized. With this motivation, this paper introduces a new blockchain with DL enabled secure medical data transmission and diagnosis (BDL-SMDTD) model. The goal of the BDL-SMDTD model is to securely transmit the medical images and diagnose the disease with maximum detection rate. The BDL-SMDTD model incorporates different stages of operations such as image acquisition, encryption, blockchain, and diagnostic process. Primarily, moth flame optimization (MFO) with elliptic curve cryptography (ECC), called MFO-ECC technique is used for the image encryption process where the optimal keys of ECC are generated using MFO algorithm. Besides, blockchain technology is utilized to store the encrypted images. Then, the diagnostic process involves histogram-based segmentation, Inception with ResNet-v2-based feature extraction, and support vector machine (SVM)-based classification. The experimental performance of the presented BDL-SMDTD technique has been validated using benchmark medical images and the resultant values highlighted the improved performance of the BDL-SMDTD technique. The proposed BDL-SMDTD model accomplished maximum classification performance with sensitivity of 96.94%, specificity of 98.36%, and accuracy of 95.29%, whereas the feature extraction is performed based on ResNet-v2 World Scientific Publishing Company. -
Steering through the pandemic: narrative analysis of school leader experiences in India
The COVID ?19 pandemic has disrupted the regular functioning of schools. Transitioning to online learning posed significant challenges to all stakeholders in the educational system. The continued changes and challenges due to the pandemic require school leaders to make intuitive decisions. School leaders vision and leadership styles can considerably impact successfully managing crises and challenges. The current study looks at the lived experiences of eight school leaders working in India. The data collected using an interview guide was subjected to narrative thematic analysis. The interviews were designed primarily in an open-ended manner to captivate the story of their experiences. The results yielded an understanding of how school leaders navigated through multiple challenges such as transitioning online, attending to student needs, financial challenges adopting crisis and collaborative leadership. The results highlight various personal feelings and experiences that helped the school leaders to hold up during the crisis. School leaders lack training in crisis management, and their mental health needs are neglected. The paper calls for professional support for school leaders in managing professional and personal challenges. The article gives direction for school professionals on focus areas and requirements in Indian schools. 2022 Informa UK Limited, trading as Taylor & Francis Group.