Assessment of Seismic Hazards in Underground Mine Operations using Machine Learning

The most common causes of coal mining accidents are seismic hazard, fires, explosions, and landslips. These accidents are usually caused by various factors such as mechanical and technical failures, as well as social and economic factors. An analysis of these accidents can help identify the exact causes of these accidents and prevent them from happening in the future. There are also various seismic events that can occur in underground mines. These include rock bumps and tremors. These have been reported in different countries such as Australia, China, France, Germany, India, Russia, and Poland. Through the use of advanced seismological and seismic monitoring systems, we can now better understand the rock mass processes that can cause a seismic hazard. Unfortunately, despite the advancements, the accuracy of these methods is still not perfect. One of the main factors that prevent the development of effective seismic hazard prediction techniques is the complexity of the seismic processes. In order to carry out effective seismic risk assessment in mines, it is important that the discrimination of seismicity in different regions is carried out. The widespread use of machine learning in analyzing seismic data, it provides reliability and feasibility for preventing major mishaps. This paper provides uses various machine learning classifiers to predict seismic hazards

Globalization and Public Health: An Examination of Cross-Border Health Issues

The rapid interconnection facilitated by globalization intensifies the dissemination of infectious diseases, posing substantial obstacles for public health systems globally. This paper utilizes a comparative methodology to analyze the impact of globalization on the dynamics of health issues that transcend national borders. It does so by closely examining two distinct pandemics: COVID-19 and the Nipah virus. Utilizing epidemiological data, public health policies, and scholarly literature, we examine the transmission patterns, susceptibilities, and strategies for addressing both viruses. By contrasting the easily transmissible and airborne characteristics of COVID-19 with the localized outbreaks and zoonotic source of the Nipah virus, we expose the varied difficulties presented by distinct cross-border health hazards. The main discovery we made emphasizes the contradictory connection between globalization and the readiness of public health. Interconnectedness not only speeds up the spread of viruses, but also promotes international collaboration in areas such as research, surveillance, and sharing of resources. We contend that effectively addressing cross-border health threats necessitates a nuanced comprehension of the dual nature of globalization, highlighting the importance of strong national health systems in conjunction with intensified global cooperation. This paper seeks to offer valuable insights to policymakers and public health professionals by analyzing the divergent cases of COVID-19 and Nipah virus. It aims to assist them in effectively managing the intricate relationship between globalization and health concerns that transcend national borders. We promote a proactive strategy that utilizes the advantages of international collaboration while enhancing local capacity to guarantee efficient readiness and reaction to forthcoming pandemics

Securing the Digital Frontier: The Role of Technology in Social Medical Public Healthcare Security

The rapid expansion of digital connectivity within social medical public healthcare systems (SMPH) has fundamentally transformed the way patient care is delivered. However, it has also made sensitive data vulnerable to a wide range of cybersecurity threats. This study introduces and assesses a new hybrid deep learning model, GANA-AO, with the aim of improving real-time anomaly detection and threat prevention in SMPH. GANA-AO leverages the capabilities of Generative Adversarial Networks (GAN) and Autoencoders, enhanced by Adam optimization, to achieve outstanding accuracy and generalizability. Generative Adversarial Networks (GAN) produce authentic artificial data to supplement the training dataset and tackle the problem of imbalanced classes. On the other hand, Autoencoders acquire compact representations of normal data, aiding in the detection of anomalies by identifying deviations. Adam optimization effectively adjusts model hyperparameters, thereby improving performance. The efficacy of GANA-AO is demonstrated through our experiments conducted on the publicly accessible IoT-23 dataset. The model demonstrates an exceptional accuracy of 98.33% and a True Positive Rate (TPR) of 98.67%, surpassing the performance of baseline models by a significant margin. The results emphasize the capability of GANA-AO to enhance SMPH cybersecurity by promptly detecting and addressing malicious activities, protecting sensitive healthcare data, and ensuring patient safety. This paper not only introduces a robust technical solution but also highlights the vital significance of technology in safeguarding the digital boundaries of SMPH. By adopting cutting-edge approaches such as GANA-AO, we can establish a stronger and more adaptable system, promoting confidence and enabling patients in the digital era of healthcare. DOI: https://doi.org/10.52710/seejph.48

Nexus of circular economy and sustainable performance in the era of digitalization

This study aims to conduct a comprehensive review and network-based analysis by exploring future research directions in the nexus of circular economy (CE) and sustainable business performance (SBP) in the context of digitalization. A systematic literature review methodology was adopted to present the review in the field of CE and SBP in the era of digitalization. WOS and SCOPUS databases were considered in the study to identify and select the articles. The bibliometric study was carried out to analyze the significant contributions made by authors, various journal sources, countries and different universities in the field of CE and SBP in the era of digitalization. Further, network analysis is carried out to analyze the collaboration among authors from different countries. The study revealed that digitalization could be a great help in developing sustainable circular products. Moreover, the customers' involvement is necessary for creating innovative sustainable circular products using digitalization. A move toward the product-service system was suggested to accelerate the transformation toward CE and digitalization. The paper discusses digitalization and CE practices' adoption to enhance the SP of the firms. This work's unique contribution is the systematic literature analysis and bibliometric study to explore future research directions in the nexus of CE and SP in the context of digitalization. The present study has been one of the first efforts to examine the literature of CE and SBP integration from a digitalization perspective along with bibliometric analysis.N/