Search results

The purpose of this paper is to enhance the accuracy of classification of streaming big data sets with lesser processing time. This kind of social analytics would contribute to society with inferred decisions at a correct time. The work is intended for streaming nature of Twitter data sets.

It is a demanding task to analyse the increasing Twitter data by the conventional methods. The MapReduce (MR) is used for quickest analytics. The online feature selection (OFS) accelerated bat algorithm (ABA) and ensemble incremental deep multiple layer perceptron (EIDMLP) classifier is proposed for Feature Selection and classification. Three Twitter data sets under varied categories are investigated (product, service and emotions). The proposed model is compared with Particle Swarm Optimization, Accelerated Particle Swarm Optimization, accelerated simulated annealing and mutation operator (ASAMO). Feature Selection algorithms and classifiers such as Naïve Bayes, support vector machine, Hoeffding tree and fuzzy minimal consistent class subset coverage with the k-nearest neighbour (FMCCSC-KNN).

The proposed model is compared with PSO, APSO, ASAMO. Feature Selection algorithms, and classifiers such as Naïve Bayes (NB), support vector machine (SVM), Hoeffding Tree (HT), and Fuzzy Minimal Consistent Class Subset Coverage with the K-Nearest Neighbour (FMCCSC-KNN). The outcome of the work has achieved an accuracy of 99%, 99.48%, 98.9% for the given data sets with the processing time of 0.0034, 0.0024, 0.0053, seconds respectively.

A novel framework is proposed for Feature Selection and classification. The work is compared with the authors’ previously developed classifiers with other state-of-the-art Feature Selection and classification algorithms.

The purpose of this paper is to present a methodology to assess material damage parameters for ductile crack initiation and growth ahead of a crack/notch tip in high hardening steel like AISI type 316L(N) stainless steel.

Ductile damage parameter and far field J-integral have been obtained from standard FEM analysis for a crack/notch tip undergoing large plastic deformation and resulting in crack initiation/growth. In conjunction with experimental results, the damage variable for low strength and high hardening material has been derived in terms of continuum parameters: equivalent plastic strain (ε_eq) and stress triaxiality (φ). The material parameters for damage initiation and growth in 316LN SS have been evaluated from tensile and fracture tests. With these material tensile/fracture parameters as input, elastic-plastic eXtended Finite Element Method (X-FEM) simulations were carried out on compact tension (CT) specimen geometry under varying initial stress triaxiality conditions.

The material parameters for damage initiation and growth have been assessed and calibrated by comparing the X-FEM predicted load-displacement responses with the experimental results. It is observed that the deviations in the predicted load values from the experimental data are within 6 percent for specimens with a/W=0.39, 0.55, 0.64, while for a/W=0.72, it is 17 percent.

The present study is a part of developing methods to obtain calibrated material damage parameters for crack growth simulation of components made of AISI 316L(N) stainless steel. This steel is used for fast breeder reactor-based power plant being built at Kalpakkam, India.

The purpose of this paper is to present a methodology to predict initial crack growth behavior of crack or notch like stress raisers in AISI 316L(N) stainless steel material subjected to monotonic loading condition.

The methodology for critical crack blunting corresponding to crack initiation in crack or notch like stress raisers is based on critical plastic strain (Epc) at a characteristic distance (lc), where uniform strain (Eu) is considered as Epc and two grain diameter is considered as lc. Further crack growth is based on parabolic crack tip opening displacement (CTOD) scheme established based on coupled experimental and FEM analysis of compact tension (CT) specimen subjected to mode-I loading condition. The FEM predicted load-displacement plots is compared with experimental result of CT specimens with different a/W ratios. It has shown that the proposed methodology could account initial crack blunting appropriately and predict the fracture load and load-displacement plots for initial crack growth regime.

The results show that for crack growth with near straight crack front, experimental data from a CT specimen of particular a/W ratio coupled with plane strain 2D FEM analysis could predict load vs displacement plots for different a/W ratios when initial crack blunting is accounted appropriately with a local damage model.

The present study is a part of developing methods to analyse fracture behavior of AISI 316L(N) SS material components used for fast breeder reactor-based power plant being built at Kalpakkam, India.

The study aims to analyse the challenges faced by the Indian Handloom Sector with a special focus on the state of Uttar Pradesh before and during the COVID-19 pandemic. This study further explores the benefits of AatmaNirbhar Bharat Abhiyan for the betterment of the livelihood of the COVID-19–hit handloom weavers and allied workers.

A total of 400 handloom weavers and allied workers from ten cities of Uttar Pradesh were contacted through telephone. Descriptive statistics were applied to measure the awareness about the government welfare schemes and the benefits of these schemes. Furthermore, satisfaction and opinion of the handloom weavers and allied workers regarding the benefits and sufficiency of the funds received under these schemes have also been measured.

Based on the results, the least awareness has been noted about government welfare schemes. However, a small number of weavers and allied workers were found beneficiaries of the schemes. Additionally, the majority of the respondents were found dissatisfied with the benefits. The COVID-19 pandemic is an addendum to the plight of handloom weavers and allied workers. The measures of AatmaNirbhar Bharat Abhiyan could be used to aid weavers and allied workers to restore their lost revenue.

This study has limitations. Firstly, the research is limited to the handloom industry of Uttar Pradesh. Future researchers could consider the handloom sector of other states like Maharashtra and Andhra Pradesh, known for hand-woven clothes. Secondly, this study aims to analyse the role of AatmaNirbhar Bharat Abhiyan in improving the living conditions of handloom weavers and allied workers and not to measure the impact of the Abhiyan on handloom weavers or the handloom sector. Researchers could measure the impact in future studies. Thirdly, the authors have not applied any behavioural theory or marketing models such as the Theory of Reasoned Action or the Blackwell model, which may be applied to study the attitude of handloom weavers towards welfare schemes. This may prove to be a potential direction for future research. Additionally, master weavers and handloom cooperatives societies were excluded while collecting the data. Future researchers could consider them to examine the role of the government’s welfare schemes for uplifting the socio-economic condition of the handloom weavers, allied workers, master weavers and the business of cooperative societies. Finally, due to lockdown and travel ban, the authors were forced to limit their survey to telephone only because of which they could not get the qualitative information in full. Researchers for future studies could visit the handloom concentrated areas personally or take the help of an enumerator for data collection.

The research holds significance for the young and competent designers, handloom weavers and allied workers. Designers could work with and hire handloom weavers of Uttar Pradesh. If designers and weavers work together, it will help them restore their business and generate revenue that they have lost due to the COVID-19 pandemic. Furthermore, policymakers can collaborate with designers, which will help enhance the socio-economic condition of handloom weavers and allied workers, which has deteriorated due to the COVID-19 crisis.

The research holds significance from the point of view of exploring the challenges faced by handloom weavers and allied workers of the state of UP before and during the COVID-19 period while examining the role of AatmaNirbhar Bharat Abhiyan in setting off these challenges.

This article aims to provide the current state of the art of the literature on the contribution of information and communication technologies (ICTs) on the measurement and management of performance in the healthcare sector. In particular, the work aims to identify current and emerging ICTs and how these relate to the performance measurement and management (PMM) cycle of healthcare organizations.

To address the research objective, we adopted a systematic literature review. In particular, we used the preferred reporting items for systematic reviews and meta-analysis (PRISMA) methodology to select articles related to the investigated topic. Based on an initial screening of 560 items retrieved from Scopus and ISI Web of Knowledge, we identified and analyzed 58 articles dealing with ICTs and PMM in the healthcare sector. The last update of the dataset refers to February 2024.

Although we attempted to address a relevant topic for both research and practice, we noticed that a relatively small sample of articles directly addressed it. Through this literature review, in addition to providing descriptive statistics of research on ICTs and PMM in healthcare, we identified six theoretical clusters of scientific streams focusing on the topic and eleven categories of ICTs effectively tackled by the literature. We then provided a holistic framework to link technologies to the different PMM phases and functions.

Nowadays, the availability of ICTs to support healthcare organizations’ processes and services is extensive. In this context, managers at various organizational levels need to understand and evaluate how each ICT can support different activities to benefit most from their adoption. The findings of this study can offer valuable insights to top and line managers of healthcare organizations for planning their investments in both existing and emerging ICTs to support the various stages of development and functions of PMM.

Most of the current literature focusing on ICTs in the healthcare sector refers to the contribution that technology provides to clinical processes and services, devoting limited attention to the impact of ICTs on administrative processes, such as PMM. To the best of the authors’ knowledge, this represents the first literature review on the contribution of ICTs to PMM in the healthcare sector. The review, differently from other research focused on specific ICTs and/or specific PMM functions, provides a holistic perspective to understand how these technologies may support healthcare organizations and systems in measuring and managing their performance.

Digital information seeking behavior incorporates the effective information seeking, retrieving and using in maritime studies. Moreover, digital information literacy skills support the employment of digital tools and information databases for decision making and for performing specific tasks online. The main aim of this paper is to explore the relevant research for the information needs and information seeking behaviour of maritime students.

A systematic literature review over scholarly publications in English language over the last decade was performed through PRISMA method.

The systematic literature review resulted to 22 related publications that are consistent with the criteria of the systematic literature review. These publications are analysed and discussed. The need for further research in the area of information seeking behaviour of students of maritime studies as well as of digital information literacy is exposed.

This work explores the behavioural patterns surrounding the central role of information for maritime students as well as for decision-making in the maritime sector. Digital information literacy competencies are discussed in order to be included in the curricula of maritime studies.

This study aims to explore the application scenarios of metaverse offices in organizations, including immersive work experiences, weak social networks and virtual meetings. Based on the exploration of this application scenario, this study discusses four levels of organizational change that will be brought about by the future metaverse office, such as the inter-enterprise ecological collaboration model, distributed autonomous organization, flexible leadership and individual belongingness. The metaverse office has some special advantages over traditional office models, but the metaverse office still raises some issues, such as privacy, security, addiction, equity and usability. These issues brake the widespread adoption of metaverse technologies. The study recommends that researchers take these issues into account in future metaverse research and development.

This study surveys the relevant literature by means of a literature review in order to analyze how metaverse technology can be applied to teleworking. Two databases including Web of Science (https://www.webofscience.com/) and Google Scholar (http://scholar.google.com) were selected for this study. Keywords such as “teleworking and metaverse” were used, and 18 publications were found to be relevant to the study. After excluding duplicates, less relevant and older literature, only 14 articles could be used as references for this study. Based on the exploration of this application scenario, this study discusses four levels of organizational change and issues that will be brought about by the metaverse office of the future.

It presents the application scenarios of the metaverse office in organizations, including immersive work experience, weak social networking and virtual meetings.

The pandemic triggers a desire for contactless working. The three main applications of the metaverse office also have a practical value which has been proven in some high-tech companies. It is foreseeable that an efficient, electronic and personalized office model will be enthusiastically adopted by society. Metaverse office will gradually step into people's view in the future.

The concept of the metaverse office has rarely been touched upon by theoretical research, although the technology is gradually becoming known. Even its application to teleworking has only recently been reached by some organizations.

Total quality management (TQM) and knowledge management (KM) are two similar and complementary management philosophies synergistic combinations that can form a cycle of improvement and development. This paper aims to investigate the impact of TQM factors on knowledge creation in the organizations of Bangladesh.

A list of TQM factors was identified through reviewing the relevant literature. Knowledge creation was analyzed through the framework proposed by Nonaka and Takeuchi (1995). Data were collected through a self-administered questionnaire survey among 450 top and mid-level managers of the organizations. A quantitative research approach, namely, structural equation modeling (SEM) was used in the study. The data were analyzed in SmartPLS 3.

From the study, it is found that a positive and significant relationship exists between leadership, employee empowerment, benchmarking, customer focus and information technology with the knowledge creation process and four knowledge conversion modes. In contrast, a negative and significant relationship has been found between employee training and continuous improvement with the knowledge creation process and three knowledge conversion modes.

Previous researches in Bangladesh empirically validated the effect of TQM on organizational performance, competitive advantage, financial performance, market performance and productivity. But, no such study was undertaken to empirically validate the effect of TQM on knowledge creation process for organizations of Bangladesh. Here, the study has a unique contribution. The empirical support for the hypotheses to explain and predict the contribution of the TQM in promoting knowledge creation.

The findings highlight the role of leadership practices. Organizational leadership needs to focus more on following issues: gathering required knowledge from the superior sources; transforming prevailing knowledge into a meaningful format to perform activities in better and innovative ways; employing opinions from experiences; facilitating mechanism for employees to update their knowledge; creating a virtual network; implementing customer relationship management system and providing tools and technologies to employees for performing KM activities more efficiently. On the other hand, negative effect of employee training and continuous improvement on knowledge creation sheds light on understanding the reasons for this kind of relationship and formulating effective strategies to resolve problems inside the organizations. In this regard, employees need to be well equipped through regular and appropriate training. Also, employees need to use problem-solving approach to identify problems inside the organizational system thereby availing opportunities for continuous improvement.

This study was conducted to identify factors that enable knowledge creation in organizations from developing countries like Bangladesh. TQM has been adopted in many organizations. But, its effect was mostly measured to determine its impact on improving organizational performance or competitiveness or identifying its critical success factors of implementation. Hence, this study sheds light on identifying the effect of TQM from a new perspective.

The purpose of this paper is to identify the key influencing factors of aviation accidents and to predict the aviation accidents caused by the factors.

This paper proposes an improved gray correlation analysis (IGCA) theory to make the relational analysis of aviation accidents and influencing factors and find out the critical causes of aviation accidents. The optimal varying weight combination model (OVW-CM) is constructed based on gradient boosted regression tree (GBRT), extreme gradient boosting (XGBoost) and support vector regression (SVR) to predict aviation accidents due to critical factors.

The global aviation accident data from 1919 to 2020 is selected as the experimental data. The airplane, takeoff/landing and unexpected results are the leading causes of the aviation accidents based on IGCA. Then GBRT, XGBoost, SVR, equal-weight combination model (EQ-CM), variance-covariance combination model (VCW-CM) and OVW-CM are used to predict aviation accidents caused by airplane, takeoff/landing and unexpected results, respectively. The experimental results show that OVW-CM has a better prediction effect, and the prediction accuracy and stability are higher than other models.

Unlike the traditional gray correlation analysis (GCA), IGCA weights the sample by distance analysis to more objectively reflect the degree of influence of different factors on aviation accidents. OVW-CM is built by minimizing the combined prediction error at sample points and assigns different weights to different individual models at different moments, which can make full use of the advantages of each model and has higher prediction accuracy. And the model parameters of GBRT, XGBoost and SVR are optimized by the particle swarm algorithm. The study can guide the analysis and prediction of aviation accidents and provide a scientific basis for aviation safety management.