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This study presents exploratory work and seeks to identify and evaluate the success and failure factors that could form a guideline for further study and to some extent help professionals to understand some critical aspects that impact project performance concerning construction in India. A total of 55 attributes affecting the performance of construction projects are analysed in terms of their level of influence on four key performance criteria ? schedule, cost, quality, and no disputes ? using a two-stage questionnaire survey. These attributes ?are then further analysed, interpreted and evalu

This study presents exploratory work and seeks to identify and evaluate the success and failure factors that could form a guideline for further study and to some extent help professionals to understand some critical aspects that impact project performance concerning construction in India. A total of 55 attributes affecting the performance of construction projects are analysed in terms of their level of influence on four key performance criteria - schedule, cost, quality, and no disputes - using a two-stage questionnaire survey. These attributes are then further analysed, interpreted and evaluated. Based on the critical success factors obtained from the study, a neural network model-based predictive model for project performance has been developed. The performance prediction models have been derived for all four project performance criteria. Further, a hypothesis that 'project success' is influenced by 'success traits' has also been formulated. The hypothesized positive inter-relationships between success traits and project success have been tested using the structural equation modelling technique. Besides supporting the intuition of past researchers in recognizing 'coordination' as a key success factor, this study has revealed that coordination is not an isolated and independent activity, but is a typical management function with an inherent role in all major management activities. Key elements affecting coordination have also been identified and their influence on coordination effort has been studied. Furthermore, the present study has also identified three broad skill groups required of effective project coordinators. The results are validated through case studies of live projects and structured interviews with experts in the field of construction management.

Journalists are professionals and their primary obligations are owed to business managers in their respective media firms, members of the public and society in general. These primary obligations lead to certain considerations and other associated obligations. One of the most important associated obligations for journalists is considered to be objectivity. That is to say, journalists have an obligation to report the news objectively and the media coverage ought not to be slanted in favor of government or any public or private agency. Alongside, journalists themselves are expected to be objective to report the news in a neutral manner. In view of this, I examine a few virtue-theoretic implications of objectivity in news media to argue for the need for journalists to cultivate the virtues of objectivity and care to overcome conflicting views and opinions in news media to report the news impartially even while sharing a bond of attachment with the people in the world.

This research paper indicates that it is not the case that social movement's fall neatly into identity- or interest- based categories. Instead, some movements are encouraged to foreground identity claims as a result of the broader political context in which they operate. Instead, the questioning of borders took place in the course of the processing of social movement demands in local politics. As the world's largest multi-ethnic democracy, India has a federal Constitution that is well-equipped with administrative devices that offer apparent recognition and measures of self-governance to territorially concentrated ethnic groups. This article analyzes how demands for political autonomy—or statehood—within the federal system have been used as a frame for social movement mobilization. It focuses on the most recent states to have been created in India: Chhattisgarh, Jharkhand and Uttarakhand, which came into being in 2000.

In the current scenario, the economic status of countries is dependent on stock markets. However, predicting the future prices of any stock is a multifaceted task, as the nature of data is complex and unstructured in nature, which is difficult understand. The focus of the study relies on applying deep neural techniques with regression-based application to discover knowledge from financial databases. The authors have applied LSTM, an advanced version of RNN, and regression-based methods such as ARIMA for predicting future prices of stocks. The study was supported by implementing the techniques on real-world data that was captured from SBI for 6 years. The data has significant opening and closing prices of stock markets. To implement the current study approach, the authors have utilized Python language, where result predicts various performance parameters such as MAE, MSE, RMSE, and bias for both LSTM as well as ARIMA. The performance matrix of LSTM and ARIMA were compared for MAE (mean absolute error) for LSTM, which is 4.32, whereas for ARIMA is 3.83. Also, MSE (mean squared error) value for LSTM is 29.52, for ARIMA was 24.53, and RMSE (root mean squared error) for LSTM and ARIMA are 5.43 and 4.95. The overall accuracy of both of the algorithm were widely applied for real-world prediction among the stock market analysis.

Intro -- Preface -- Contents -- Editors and Contributors -- Machine Learning-Based Ensemble Approach for Predicting the Mortality Risk of COVID-19 Patients: A Case Study -- 1 Introduction -- 2 Literature Review -- 3 Dataset and Methodology Used -- 3.1 Dataset Description and Preparation -- 3.2 Data Preprocessing -- 3.3 Classification and Ensembling Approaches -- 4 Ensembling Approaches -- 4.1 Boosting -- 4.2 Bagging -- 5 Experiments and Results -- 5.1 Feature Selection of Patient Attributes -- 5.2 Performance of Individual Classifiers -- 6 Conclusion -- References -- Role of Internet of Health Things (IoHTs) and Innovative Internet of 5G Medical Robotic Things (IIo-5GMRTs) in COVID-19 Global Health Risk Management and Logistics Planning -- 1 Introduction -- 1.1 Background of the Study -- 1.2 Aims and Objective of the Study -- 2 Literature Review -- 3 Research Design and Implementation -- 3.1 Research Analysis -- 3.2 Research Discussion -- 4 Future Research Focus -- 5 Recommendation -- 6 Conclusion -- References -- Battling COVID-19 with Process Model of Integrated Digital Technology: An Analysis of Qualitative Data -- 1 Introduction -- 2 Research Design and Structure -- 3 Digital Technology to Combat COVID-19 -- 3.1 Mobile Applications and COVID-19 -- 3.2 Artificial Intelligence, Internet of Things (IoT), Big Data Analytics, and COVID 19 -- 3.3 Social Media and COVID -- 4 Summarization of Digital Technology Applications and COVID-19 -- 5 Process Model of Integrated Digital Technology -- 6 Conclusion -- References -- High-Fidelity Intelligence Ventilator to Help Infect with COVID-19 Based on Artificial Intelligence -- 1 Introduction -- 2 Operating and Revision Modes -- 3 Design and Condition of the Instrument -- 4 Materials and Technology -- 4.1 Typical Parts Needed -- 4.2 Arduino Nano Compatible V3.0 ATmega328.

According to the information efficiency view, stock price synchronicity reflects the degree of integration of firm-specific information with market-level information. Stock price synchronicity is higher (lower) when there is a higher (lower) level of integration between the firm and the overall market information. As the disclosure of environmental, social and governance data provides more firm-specific, non-financial, value-relevant information to the market, stock prices reflect such information efficiently. It leads to more information efficiency and lower synchronicity of stock prices. Against this backdrop, the present study examines the relationship between ESG and its component scores and stock price synchronicity using a sample of 163 Indian companies reporting their ESG scores through the Thomson Reuters database from 2011 to 2021. The findings of the study confirmed that the ESG score and the scores of its components (except the governance score) have a significant negative impact on stock price synchronicity and a significant positive impact on idiosyncratic volatility. This is consistent with the information efficiency viewpoint, implying that ESG disclosure has value relevance in the capital market and that investors in the Indian market consider ESG information when making investment decisions.