This research looks into the differences in technological practices across Gen-X, Gen-Y, and Gen-Z employees in the workplace, with an emphasis on motivation, communication, collaboration, and productivity gaps. The study uses a systematic literature review to identify factors that contribute to these variations, taking into account each generation’s distinct experiences, communication methods, working attitudes, and cultural backgrounds. Bridging generational gaps, providing ongoing training, and incorporating cross-generational and technology-enhanced practices are all required in today’s workplace. This study compares the dominating workplace generations, Gen-X and Gen-Y, with the emerging Gen-Z. A review of the literature from 2010 to 2023, which was narrowed down from 1307 to 20 significant studies, emphasizes the importance of organizational management adapting to generational changes in order to increase productivity and maintain a healthy workplace. The study emphasizes the need of creating effective solutions for handling generational variations in workplace.

Software reverse engineering and reengineering are becoming common in the field of games and website development. Simulation and modeling play an important role in understanding the flow of the overall system. Business process modeling notation (BPMN) is used to show the overall architecture of the business process. Simulated business process re-engineering is essential for implementing change or creating new processes. The simulation model explains whether a change will be successful or not prior to adopting any new business processes or other changes. Some available tools help convert the BPMN to a simulating BPMN model but converting the discrete event simulation model build in commercial off the shelf simulation packages like Simul8 to the BPMN to help generate business process simulation to BPMN is also a key challenge. This framework is introduced to convert the simulation model to BPMN using the reverse engineering concept to understand how the converting tools convert the BPMN model to the simulation model. After understanding this process, the concept of reengineering will be used to build a BPMN from the simulation model. The framework is divided into three main parts model translation, model mapping, and model formation. For model building, two simulation tools Simul8 and BPSimulator are used. It is then tested on two case studies bank and product manufacturing. The output shows the BPMN model is generated from the simulation model within less time on a single click saving time and resources for developing BPMN model first and then making simulation model for testing purpose.

The difficulties of continuously monitoring cardiac patients in general hospital wards are still present because of the manual charting system and the slow clinical reaction to worsening physiological state. This paper outlines an edge- and fog-based Internet of Things (IoT) healthcare system to acquire, process, and prioritize the vital signs of patients in real time to minimize the alert latency and increase the time of clinical interventions. Wearable 12-lead ECG sensors transmit physiological measurements, such as heart rate, blood pressure, and oxygen saturation, to an intelligent edge service, where preprocessing, triage by threshold, and machine learning ECG classification are performed, and selective synchronization of physiological data with a cloud backend and data delivery to the clinician are made possible by a mobile application. The proposed architecture combines a ribbon-like streaming scheme, Flask-based gateway services, and Firebase Firestore to coordinate scalable mob/cloud with the help of multi-client data dissemination. To encompass borderline clinical deterioration, which is often unnoticed by conventional threshold systems, physiological parameters are classified into normal, alarming, emergency, and a new state, average. The Pan–Tompkins++ peak detector algorithm and multiple edge-resident classifiers, such as random forest, XGBoost, decision tree, naive Bayes, K-nearest neighbor, and support vector machine, are used to analyze the ECG waveforms. Experimental analysis of PhysioNet datasets and tests in real wards prove that the ensemble models can reach the highest possible ECG classification precision of 91.96 percent and snapshot-driven mobile alerts can decrease routine patient evaluation time by several minutes, to an average of 15.23 ± 2.71 s. These results suggest that edge-centric IoT systems can be appropriate in latency-critical hospital settings and that fog-based coordination is useful in next-generation smart healthcare systems.

Business process engineering is used to make business process more efficient, to increase the quality of product and reduce cost and time as well of current business process. The aim of this work is to find the problem associated with the administrative workflow in public sector university of Pakistan. The problem is when we do things manually, it consumes a great amount of time to complete work. In manual work the chances of human error are also more than any automated system used for administrative workflow. Students cover a lot of distance for administrative work and wait a lot in queues for their turn that also wastes a lot of time of students. University administrative staff have to spend too much time in dealing with current manual processes like paperwork, emails, and spread sheets. It takes a lot of time for one activity to be done in current process. In current business process there is a long queue in front of administrative officewhenever there is some important deadline. The use of an automated systems improves efficiency and effectiveness of an organization. An automated system is proposed by using business process engineering with modeling and simulation that will help the students as well as administrative staff in improving efficiency and will also reduce time and cost. The major outcome of this study is to propose a solution using modeling and simulation that will be accurate in performance, reduce human error, efficient work, save time as well. The results show that the automated system will reduce the burden of workload as well as the students waiting time outside the offices.