Organisational management is one of the contemporary delinquents, most of the organisations have to address. Issues like job satisfaction, employee commitment and employee performance are crucial factors which may affect organisational climate. Religiosity and spirituality are prominent and actual factors that can speed up satisfaction, commitment and performance. A substantial research gap connecting religiosity and spirituality with job satisfaction, employee commitment and employee performance exists. This study reconnoitres the link between religiosity, spirituality, job satisfaction, employee commitment and performance by using quantile regression. The study adopted a survey method to collect data from teachers from six different streams. Findings of the current study suggest that spirituality has no influence on employee performance but endorse the linkages between job satisfaction, employee commitment and performance.

Digital archive management solutions have become increasingly popular in archive management as information technology and wireless technology have advanced. Unlike traditional paper archives, which have inherent distinctiveness and strong tamper-proof modification, electronic files and data are mainly stated based on the available data base. Today's Internet enables marketers to reach deeper into their present customers, establish new online marketplaces, and drive new demand. This dynamic market involvement employs modern technology to more effectively target customers. In this research article, we analyze how block chain technology may influence a company's marketing efforts. This research blends block chain technology alongside distributed ledgers, consensus processes, encryption techniques, and so forth. There are several incentives available to businesses who want to participate in green products. To beginning with, a company's perceived dedication to environmental concerns is a growing element affecting many consumers' buying patterns?As a result, electronic information management is required for its capacity to properly store and retrieve huge amounts of data while ensuring computer system performance integrity.

Heart attack and anxiety disorder are proving to be two major medical complexities in the present scenario. This study illustrates the role of machine learning and artificial neural networks in making successful predictions of these two medical abnormalities. This research paper presents the significance of incorporating artificial intelligence-based mechanisms in minimising the errors of the diagnosis process. In this context, a brief description of the evolution of the usage of AI technology in medical diagnosis has been portrayed here. The different branches of AI like machine learning, artificial neural networks and their contribution to the analysis and interpretation of heart diseases are elaborated in this research paper. Besides primary research has been conducted for the purpose of gaining knowledge about what is the human perception of this technology and its relevance in the modern healthcare system. Analysis and interpretation have also been provided in this research paper to present a clear description of experimental result. Findings suggested that “Random Forest” and Vector Machine are the most used algorithms in heart attack risk prediction and ANN is the least used algorithm. However, developing ANN by integrating autoencoder and feature classifier can perform better in anxiety disorder heart attack prediction.

Implementation of AI technology plays a great role in developing effective healthcare applications. It can help to specify various effective software applications in order to develop the process of healthcare prediction. Machine-learning and cloud-computing play significant role in developing intelligent healthcare applications. It can help to collect and analyse various health care data in order to provide quick responses. AI also plays a great role in disease detection and prediction processes. This effective intelligent process can help to provide accurate detection of disease. Wireless networking sensors can help to detect the behaviour of every individual. Body sensors can help to detect body movements and facial expressions by the usage of neural networks. It also consists of various technological implementations to develop the process of data mining, computing. This research primarily focuses on the effectiveness of implementing various effective technologies in order to build healthcare prediction system. AI provides various sensor techniques in application to make it more efficient for healthcare purposes. Another question from the research has a great impact on the health care system. Machine learning can help to provide modelling methods to determine the errors of biomedicines. Wireless sensors provide the facility of behaviour detection through collecting current environmental data.

Towards processing efficient technology management in healthcare sectors, the contribution of cloud computing is at once essential. In order to reduce human efforts, cloud computing and its benefits are used immensely for the growth and development of the entire health care sector. Regarding analyzing various advantages, bringing technological changes and improvements in healthcare aspects become easier than before. Today, systemic and smart healthcare approaches promote both the cooperation and exchanges of essential medical records and services. Designing proper sensor-based smart healthcare systems is an essential concern for physicians with the use of cloud computing technology. The process includes cost-effective sharing and storing of essential medical records for a safer and more successful generation of sensor-based smart systems. However, with this innovative use of cloud technology, physicians can easily track any relevant patient's information from a large database. In contrast to that, cloud computing techniques also help doctors to detect and diagnose any type of medical complications in today's clinical sectors for a sustainable future. A quantitative method has been adopted in the research study through conducting survey analysis among 60 participants. In order to analyze the importance of applying cloud computing as one of the innovative technologies along with smart designing of health care systems, these survey results can be highly effective. Moreover, a detailed interpretation, analysis, and discussion have been also conducted successfully after evaluating all the survey results regarding the particular research topic.

A neural network defines an artificial circuit consisting of artificial nodes that can be effectively utilized for adaptive control, predictive modeling purposes and many others. Hidden patterns and the interrelation among particular datasets can be effectively analyzed through this unique model. The introduction part comprises the definition of inventory management and its components of it. The application and advantages of neural networks over designing inventory management have also been analyzed thoroughly. The literature review part analyzed the detailed structure of neural networks and also comprises a flow diagram through which a detailed mechanism of the neural network model can be reflected. The discussion part critically analyzes the effective utilization of machine learning-based neural network models in diverse industries. Authentic examples have also been cited in this context for a better understanding of its effectiveness among different enterprises. A clear conclusion has also been given that comprises concise findings from the whole research paper. In this research study, a detailed analysis has occurred where 61 individuals have been selected for asking questions. Two crucial questions depending on this innovative model has been asked and they have given the instruction to clearly express their concerns against these questions. According to their opinion, a graphical representation has been mentioned in this paper through which an individual can generate a clear idea about the importance of this research study.