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A Study on Work Engagement among the School Teachers
Work engagement is a measurable degree of an persons positive or negative emotional attachment to their job, colleagues and organization which profoundly influences their willingness to learn and perform at work. Now a days it is observed that the commitment and dedication of the teachers in their profession as decreasing. It is also seen that teacher turnover is also becoming high. Even though the teachers in the schools were paid good, the turn over seems to be increasing. The study here tries to investigate the relationship with the work engagement and the socio demographic characteristics of teachers where the demographic variables could explain the relationship between the dimensions of work engagement. Descriptive research design is being used in the study . This design is helpful to identify the socio demographic characteristics and its relationship between the Work engagement among School teachers . The sample consisted of 100 school teachers who having more than one years of experience and the sample was selected by using the convenient sampling method. The study was done using the UWES Scale developed by Wilmar Schaufeli and Arnold Bakker in 2003 and nineteen other questionnaires were developed to know the other factors contributing to work engagement. The resourceful work environment can foster teachers work engagement. Consequently, the study shows that the older experienced married teachers shows the high level of work engagement where the educational qualification has no much role in it. This means that the young generation is not much interested in the profession with a a passion rather than they themselves consider it as a job. The work engagement can be increased among them through making interventions like improving and enhancing effective job and personal resources. -
A Study on work engagement of secondary school teachers in relation to their psychological well-being, leadership behaviour of principals and organizational health
Organizational success is determined by work engagement and psychological well-being of the workforce. Efficient leadership and a healthy teaching environment determine the professional conduct of school teachers. Work engagement not only reflects teachers performance but also implies the performance of pupils and the school. Work engagement depends on the congeniality of the working conditions. The present study explores work engagement of 516 secondary school teachers working in Bengaluru, India. The Work and Well-being survey (UWES) was used to measure teachers work engagement by assessing their vigour, dedication, and absorption. The scale of psychological well-being scale (developed by Ryff) was employed to evaluate in terms of self-acceptance, positive relation with others,autonomy,environmental mastery, purpose in life and personal growth.The leadership behaviour of principals questionnaire was used to measure in terms of consideration and initiating structure. The Organizational health Inventory was employed to quantify the Organizational health at the institutional, managerial, and technical levels. Results from the regression analysis suggest that work engagement of teachers was positively correlated and significantly influenced by psychological well-being, leadership behaviour of principals and organizational health. -
A study on work engagement of secondary school teachers in relation to their psychological well-being, leadership behaviour of principals and organizational health /
Organizational success is determined by work engagement and psychological well-being of the workforce. Efficient leadership and a healthy teaching environment determine the professional conduct of school teachers. Work engagement not only reflects teachers’ performance but also implies the performance of pupils and the school. Work engagement depends on the congeniality of the working conditions. The present study explores work engagement of 516 secondary school teachers working in Bengaluru, India. -
A study to identify Critical Factors affecting Performance of Low Cost Airlines in India
The main objective of the study is to identify the critical factors affecting performance of low cost airlines in India For this purpose, the research focused on the low cost airline industry with regards to their macro environment, its strategic aspects and an analysis of the industry The study incorporated the Porters Five Forces Model to study the five forces having an impact on the industry and thus directing a firms strategic actions The study also conducted an industry analysis from the point of view of travel agents through questionnaire A customer satisfaction survey was also done to know their satisfaction levels and loyalty to a particular airline. This is achieved by the adoption of primary research techniques including surveys and interviews of the industry specialist and customers and secondary research including reading the existing literature on the subject, industry reports and articles published in journals A critical analysis of the industry highlighted the factors having an impact on the industry as a whole The porters five forces analysis revealed the current and future trends for the industry and provided an understanding for future survival strategies for the airlines. Industry professionals state that the Airline industry is in infancy stage They have a long way to go The factors such as airport infrastructure, massive expansion plans, aggressive growth strategies, demand and supply patterns and the exchange rate mechanism affects their performance But the highest factor restricting the growth of any airline is the high price of ATF All the three- industry professionals, travel agents and consumers believe that LCCs have benefited the industry providing low fares and making air travel affordable They are quite positive about the times ahead and hope that the industry will bounce back Consumers are quite satisfied and content with the offerings As suggested by a consumer that they should be named as ??value for money airlines and not LCCs The Porters Five Forces analysis revealed that there are high entry barriers as this is a highly capital intensive industry and that buyers and suppliers both have high bargaining power There is moderate threat of substitute like railways looking at the future potential of the aviation sector The analysis further revealed that the market is highly competitive with very few players and to reach the customers expectations the players have to cut their prices most often thus creating an imbalance in the cost and revenue Also, unhealthy competitive practices prevail in the industry which hamper the overall growth process and thus affect the performance The research provided insight on the future opportunities and the several future industry success and survival factors The research also gives further scope of the study and thereby concludes that there needs to be a consensus so that both the regulatory bodies and the airlines are benefited thus promoting growth and prosperity of the country. Dissertation Layout: The first chapter of the dissertation titled ??Introduction primarily covered a range of aspects from history to the LCC situation globally and then following it traces to India thus leading to the statement of the problem and the objectives of the study The second chapter ??Review of Literature covered the previous research on the factors impacting the performance of low cost airlines The third chapter ??Research Methodology covered the data collection process, sampling description and the methodology for data analysis The fourth chapter titled ??Data Analysis and Interpretation covered the customer satisfaction and industry analysis The fifth chapter ??Summary and Conclusion listed the major findings, implications and limitations, scope for further research and conclusion drawn from the research. Keywords: LCCs, critical factors, performance, airlines, low cost, ATF, aviation. -
A study towards constructing a reproductive health account as sub-account of health at sub-district level of India
Reproductive health is a state where everyone of the reproductive age cohort can make informed choices based on their reproductive health needs and reach a state of bliss and well-being. Informed choices are a possibility only if there is awareness regarding options of healthcare available. Awareness further indicates capacity to measure the worth of the options available in hand. One major aspect of measuring this worth is dominated by the financial aspect of awareness. -
A Study towards constructing a reproductive health account as sub-account of health at sub-district level of india
Reproductive health is a state where everyone of the reproductive age cohort can make newlineinformed choices based on their reproductive health needs and reach a state of bliss and newlinewell-being. Informed choices are a possibility only if there is awareness regarding options of healthcare available. Awareness further indicates capacity to measure the worth of the options available in hand. One major aspect of measuring this worth is dominated by the financial aspect of awareness. In other words, expenditures incurred on reproductive health should be an information for all stakeholders to understand, analyse and arrive at informed newlinechoices. It has been unanimously felt that this domain of health needs more sustained efforts in terms of research into the specific components of expenditures. One such instrument which has been suggested is to construct a system of reproductive health accounts which TOVCI can track the fund movements among the different actors operating in the sector of reproductive health. Reproductive health accounts at local and contextual levels, has to conform to the existing national framework of health accounting so as to lend itself to inter and intra-regional comparisons. It consists of a group of matrices which capture origin of funds from financial sources to the destination where funds will ultimately be used on health functions, based on accounting boundaries of space, activity and time. This study attempted to construct a reproductive health account at sub-district levels in the district of Ramanagara in the state of Karnataka, India. Two sub-districts, Ramanagara and Channapatna were chosen for this purpose based on their health and reproductive health indicators. Primary data was collected from a household survey based on probability proportional to size sampling method. Questionnaires for data collection were borrowed from World Health Organization Guide to producing Reproductive Health Account. -
A succinct analysis for deep learning in deep vision and its applications
Introduction: Deep learning methodologies can achieve forefront results on testing deep vision issues, for instance, picture portrayal, an object area, face affirmation, Natural Language Processing, Visual Data Processing and online life examination. ConvNet, Stochastic Hopfield network with hidden units, generative graphical model and sort of artificial neural network castoff to absorb competent information coding in an unproven way are deep learning plans used in deep vision issues. Objection: This paper gives a succinct survey of without a doubt the most critical Deep learning structures. Deep vision assignments, for instance, object revelation, face affirmation, Natural Language Processing, Visual Data Processing, web-based life examination and their utilization of this task are discussed with a short record of the historic structure, central focuses and impairments. Future headings in arranging Deep learning structures for Deep vision issues and the troubles included are analysed. Method: This paper consists of surveys. In Section two, Deep Learning Approaches and Changes are audited. In section three, we tend to portray the uses of Applications of deep learning in deep vision. In Section four, Deep learning challenges and directions are mentioned. At long last, Section five completes the paper with an outline of the results. Results and Conclusion: Though deep learning can recall a huge proportion of data and info, its feeble cognitive and perception of the data makes it a disclosure answer for certain applications. Deep learning despite everything encounters issues in showing various erratic facts modalities at the equal period. Multimodal profound learning is an extra notable heading in progressing deep learning research. IJCRR. -
A Survey Instrument for Ranking of the Critical Success Factors for the Successful ERP Implementation at Indian SMEs
Bioinfo Business Economics, Vol-1 (1), pp. 06-12. ISSN-2249-1775 -
A survey of blockchain: concepts, applications and challenges
With the development of Bitcoin, organisations, be it businesses or institutions, are centring on leveraging Bitcoins blockchain technology to non-monetary based applications to improve efficiency of the activities. Having various benefits like anonymity, decentralised, audibility etc. Blockchain technology can be vastly implemented in various sectors other than financial too. This paper gives an overview the blockchain technology. It briefs about various technical concepts used in the blockchain, its types and where it can be used. It also discusses some proposed applications of the technology and tools or frameworks that can be used to develop such. It also presents the limitations of the technology. Copyright 2023 Inderscience Enterprises Ltd. -
A Survey of Sentiment Analysis from Social Media Data
In the current era of automation, machines are constantly being channelized to provide accurate interpretations of what people express on social media. The human race nowadays is submerged in the idea of what and how people think and the decisions taken thereafter are mostly based on the drift of the masses on social platforms. This article provides a multifaceted insight into the evolution of sentiment analysis into the limelight through the sudden explosion of plethora of data on the internet. This article also addresses the process of capturing data from social media over the years along with the similarity detection based on similar choices of the users in social networks. The techniques of communalizing user data have also been surveyed in this article. Data, in its different forms, have also been analyzed and presented as a part of survey in this article. Other than this, the methods of evaluating sentiments have been studied, categorized, and compared, and the limitations exposed in the hope that this shall provide scope for better research in the future. 2014 IEEE. -
A survey of the studies on Gallai and anti-Gallai graphs
The Gallai graph and the anti-Gallai graph of a graph G are edge disjoint spanning subgraphs of the line graph L(G). The vertices in the Gallai graph are adjacent if two of the end vertices of the corresponding edges in G coincide and the other two end vertices are nonadjacent in G. The anti-Gallai graph of G is the complement of its Gallai graph in L(G). Attributed to Gallai (1967), the study of these graphs got prominence with the work of Sun (1991) and Le (1996). This is a survey of the studies conducted so far on Gallai and anti-Gallai of graphs and their associated properties. 2021 Azarbaijan Shahid Madani University. -
A Survey of Traditional and Cloud Specific Security Issues
The emerging technology popularly referred to as Cloud computing offers dynamically scalable computing resources on a pay per use basis over the Internet. Companies avail hardware and software resources as service from the cloud service provider as opposed to obtaining physical assets. Cloud computing has the potential for significant cost reduction and increased operating efficiency in computing. To achieve these benefits, however, there are still some challenges to be solved. Security is one of the prime concerns in adopting Cloud computing, since the user's data has to be released from the protection sphere of the data owner to the premises of cloud service provider. As more Cloud based applications keep evolving, the associated security threats are also growing. In this paper an attempt has been made to identify and categorize the security threats applicable to Cloud environment. Threats are classified into Cloud specific security issues and traditional security attacks on various service delivery models of Cloud. The work also briefly discusses the virtualization and authentication related issues in Cloud and tries to consolidate the various security threats in a classified manner. Springer-Verlag Berlin Heidelberg 2013. -
A Survey on 5G Standards, Specifications and Massive MIMO Testbed Including Transceiver Design Models Using QAM Modulation Schemes
Massive MIMO (Multiple Input Multiple Output)is the advanced technology in 5G architecture which improves mobile and data wireless system parameters in multiple folds. The basic idea of this technology is to include huge number of antennas in the base stations serving limited user equipment. This will enhance the parameters like spectral efficiency, data rate, wireless devices connectivity, energy or power efficiency and also, significant reduction in interference and error rates. The Third Generation Partnership Project (3GPP)consortium, International Mobile Telecommunication (IMT)and various partner telecom companies are on the way to develop unified architecture to meet the proposed 5G standards by the year 2020. Initial test beds and field-trials are already in process at various universities and telecom companies considering Long Term Evolution (LTE)releases features in the 5G architecture framework. However, the research is still an open issue on improving the parameters. This research paper provides a detailed overview on 5G standards, specifications and Field trials and test beds implemented by various universities and telecom industry utilizing Massive MIMO technology. This literature survey paper aims to enlighten the researchers working in the area of Massive MIMO to understand the test bed and field trials designs existing till date. This paper also motivates to complete experiments on Bit error rate (BER)estimation in various modulation schemes for single transmitter-receiver as well as in MIMO configuration. The reduction in BER is observed when MIMO models are used for transceiver design. The hardware utilization and simulation work of the field trials and testbed provide different existing techniques to develop a transceiver system which meets 5G standard. 2019 IEEE. -
A Survey on Adaptive Authentication Using Machine Learning Techniques
Adaptive authentication is a reliable technique to dynamically select the best mechanisms among multiple modalities to authenticate a user based on the users risk profile generated using behavior and context-based information. Websites or enterprise applications enabled with adaptive authentication will have a more robust security system as analyzing the large volume of the user, device, and browser data in real time generates a risk score that decides the appropriate level of security. Though a significant amount of research is being carried out on adaptive authentication, no single model is suitable for a global attack. This paper provides a structured (extensive) survey of current adaptive authentication techniques available in the literature to identify the challenges which demand future research. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Survey on Arrhythmia Disease Detection Using Deep Learning Methods
The Cardiovascular conditions are now one of the foremost common impacts on human health. Report from WHO, says that in India 45% of deaths are caused due to heart diseases. So, heart disease detection has more importance. Manual auscultation was used to diagnose cardiovascular problems just a few years ago. Nowadays computer-assisted technologies are used to identify diseases. Accurate detection of the disease can make recovery simpler, more effective, and less expensive. In this proposed work, 11years of research works on arrhythmia detection using deep learning are integrated. Moreover, here presents a comprehensive evaluation of recent deep learning-based approaches for detecting heart disease. There are a number of review papers accessible that focus on traditional methods for detecting cardiac disease. This article addresses some essential approaches for categorizing ECG signal images into desired classes, such as pre-processing, feature extraction, feature selection, and classification. However, the reviewed literatures consolidated details have been summarized. 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG. -
A survey on artificial intelligence for reducing the climate footprint in healthcare
The primary mission of the healthcare sector is to protect from various ailments with improved healthcare services and to use advanced diagnostic solutions to promote reliable treatments for complex diseases. However, healthcare is among the significant contributors to the current climate crisis. Therefore, research is underway to identify various measures to reduce the emissions from advanced healthcare systems. Modern healthcare facilities invest significantly in renewable energy, efficient energy solutions, and intelligent climate cooling and control technologies. Furthermore, innovative technologies like artificial intelligence (AI) are proposed to enable automation for patient health monitoring. With the advances in AI, there are green AI goals for potentially reducing emissions through data-driven and well-optimized models for healthcare. Furthermore, novel machine learning and deep learning techniques are continually proposed for improved efficiency to reduce emissions. Therefore, the scope of the research is to review the potential of AI in healthcare for lowering emission rates and its methodologies, current approaches, metrics, challenges, and future trends to attain a straightforward pathway. 2022 -
A Survey on Domain-Specific Summarization Techniques
Automatic text summarization using different natural language processing techniques (NLP) has gained much momentum in recent years. Text summarization is an intensive process of extracting representative gist of the contents present in a document. Manual summarization of structured and unstructured text is a tedious task that involves immense human effort and time. There are quite a number of successful text summarization algorithms for generic documents. But when it comes specialized for a particular domain, the generic training of algorithms does not suffice the purpose. Hence, context-aware summarization of unstructured and structured text using various algorithms needs specific scoring techniques to supplement the base algorithms. This paper is an attempt to give an overview of methods and algorithms that are used for context-aware summarization of generic texts. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
A Survey on Enhancing System Performance of Wireless Sensor Network by Secure Assemblage Based Data Delivery
To provide secure data transmission in Cluster Wireless Sensor Networks (CWSNs), the challenging task is to provide an efficient key management technique. To enhance the performance of sensor networks, clustering approach is used. Wireless Sensor Network (WSN) comprises of large collection of sensors having different hardware configurations and functionalities. Due to limited storage space and battery life, complex security algorithms cannot be used in sensor networks. To solve the orphan node problem and to enhance the performance of the WSN, authors introduced many secure protocols such as LEACH, Sec-LEACH, GS-LEACH and R-LEACH, which were not secure for data transmission. The energy consumption in existing approach is more due to overhead incurred in computation and communication in order to achieve security. This paper studies about different schemes used for secure data transmission. We are proposing new methodology called IBDS and EIBDS that will increase the performance of WSN by reducing computational overhead and also increases resilience against the adversaries. 2017 IEEE. -
A Survey on Feature Selection, Classification, and Optimization Techniques for EEG-Based BrainComputer Interface
In braincomputer interface (BCI) systems, the electroencephalography (EEG) signal is extensively utilized, as the recording of EEG brain signals is having relatively low cost, the potentiality for user mobility, high time resolution, and non-invasive nature. The EEG features are extracted by the BCI to execute commands. In the feature set obtained, the computational complexity increases, and poor classifier generalization can be caused by the utilization of a lot of overlapping features. The irrelevant features accumulation could be avoided with the feature selection procedures application. The feature selection algorithms are utilized to select diverse features for each classifier. Classifiers are the algorithms that are run to attain the classification. The researchers have examined diverse classifier implementation techniques to identify the feature vectors class. A review of EEG-BCI techniques available in the literature for feature selection, classifiers, and optimization algorithms is presented in this work. The research challenges, gaps, and limitations are identified in this paper. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
A survey on next-generation mixed line rate (MLR) and energy-driven wavelength-division multiplexed (WDM) optical networks
With the ever-increasing traffic demands, infrastructure of the current 10 Gbps optical network needs to be enhanced. Further, since the energy crisis is gaining increasing concerns, new research topics need to be devised and technological solutions for energy conservation need to be investigated. In all-optical mixed line rate (MLR) network, feasibility of a lightpath is determined by the physical layer impairment (PLI) accumulation. Contrary to PLI-aware routing and wavelength assignment (PLIA-RWA) algorithm applicable for a 10 Gbps wavelength-division multiplexed (WDM) network, a new Routing, Wavelength, Modulation format assignment (RWMFA) algorithm is required for the MLR optical network. With the rapid growth of energy consumption in Information and Communication Technologies (ICT), recently, lot of attention is being devoted toward "green" ICT solutions. This article presents a review of different RWMFA (PLIA-RWA) algorithms for MLR networks, and surveys the most relevant research activities aimed at minimizing energy consumption in optical networks. In essence, this article presents a comprehensive and timely survey on a growing field of research, as it covers most aspects of MLR and energy-driven optical networks. Hence, the author aims at providing a comprehensive reference for the growing base of researchers who will work on MLR and energy-driven optical networks in the upcoming years. Finally, the article also identifies several open problems for future research. 2015 by De Gruyter.