Pakistan Journal of Scientific Research <p>Pakistan Journal of Scientific Research (PJOSR) is a peer-reviewed, scientific and technical journal owned and published by the <strong>Pakistan Association for the Advancement of Science</strong>, Lahore, Pakistan<em>. PJOSR</em> publishes high-quality original scientific articles dealing with the use of analytic and quantitative tools for modelling, analysis, design and engineering management in Engineering and Technology. </p> en-US (Prof. Dr. Muhammad Shoaib) (Ms. Saima Sheikh) Sat, 01 Jun 2024 00:00:00 +0000 OJS 60 INTER-PROCESS COMMUNICATION AMONGST MICROSERVICES <p><strong>The purpose of the study is to perform critical analysis on Inter-Process Communication (IPC) in the Microservice Architecture and to evaluate its impact on the basis of various non-business-related functionalities, such as effectiveness of performance, accessibility, adaptability, and complexity. There are various techniques for establishing IPC within Microservices, each with its own set of benefits and drawbacks. Throughout this research, IPC approaches are divided into two categories: synchronous and asynchronous. The Representational State Transfer Application Programming Interface (REST API) and google Remote Procedure Call (gRPC) are utilized in the synchronous kind, whereas Rabbit Message Queue (RabbitMQ) is utilized in the asynchronous type. A workload test was conducted across each model to get quantitative measurements on the Performance Efficiency and Accessibility of each technique, and a relatively similar functionality set was utilized to provide qualitative data on almost every other IPC method's adaptability and complexity. The research outcome shows if there is any standardized IPC solution that can be utilized in all scenarios.</strong></p> Maria Shehzadi, Nauman Riaz Chaudhry, Abobakar Aslam, Reema Choudhary Copyright (c) 2024 Tue, 04 Jun 2024 00:00:00 +0000 UNVEILING THE PATHOPHYSIOLOGICAL LANDSCAPE OF COVID-19: INSIGHTS FOR NOVEL THERAPEUTIC STRATEGIES <p><strong>The ongoing COVID-19 epidemic has emphasised the critical need for a thorough understanding of the disease’s pathophysiology environment. This article explores the complex relationship between SARS-CoV-2, the virus responsible for COVID-19, and the human body, offering light on the underlying mechanisms that determine illness susceptibility, development, and severity. The genetic, immunological, and physiological aspects that contribute to the different clinical presentations of COVID-19 using a multidisciplinary approach have been discussed. This article aims to provide significant insights that pave the way for potential therapeutic options addressing the core pathophysiological processes by deciphering these complex pathways. As the global community attempts to combat the epi- demic, a fuller knowledge of COVID-19’s molecular complexities holds the prospect of new interventions that can effectively lessen its effects. In addition, a case study featuring Quantitative Poly- merase Chain Reaction (QPCR) amplification curves and Cycle Threshold (CT) values is shown to demonstrate the significance of making an accurate diagnosis. This diagnostic approach lets physicians to distinguish between positive and negative cases, assess viral load, and offer informed treatment recommendations. By combining QPCR results with clinical data, we can acquire a greater understanding of COVID-19’s progression and influence the development of novel therapy methods. This research aims to aid the global effort to eradicate COVID-19 by elucidating its pathophysiological intricacies and employing sophisticated diagnostic techniques such as (QPCR).</strong></p> Laiba Iqbal, Dr. Naila Iqbal, M. Milhan Afzal Khan Copyright (c) 2024 Thu, 06 Jun 2024 00:00:00 +0000 ITSM APPLICATIONS WITHIN SELECTED LOGISTICS AND TRANSPORT <p>This article manages data ITSM, with its procedures well-defined by ITIL structure, which is the data of ITSM library collection. ITSM is a customer-first approach to providing IT services, focusing on delivering IT services to customers within the same business, rather than a static system. The consequences of research depend on the proposition of data ITSM model concentrated on the choose logistics and transport administration (tracking and tracing service). Article shows the foundation of the tracking and tracing service and its lifecycle (administration technique, administration configuration, administration change, administration activity and ceaseless help improvement). The article defines connections among capacities and procedures of the tracking and tracing support. The proposition of the model is predictable with standardized procedures. The accuracy of the model is checked by contrasting its consistency and standard ISO/IEC20000.</p> Tariq Niamat, Dr. Waqar Azeem, Saira Imtiaz, Sajida Nawaz, Kainat Ilyas, M. Nouman Copyright (c) 2024 Tue, 25 Jun 2024 00:00:00 +0000 ENHANCED AND OPTIMIZED INDUSTRIAL PROCESSES MANAGEMENT USING MACHINE LEARNING (ML) AND BLOCKCHAIN <p>The development of the fourth Industrial Revolution 4.0 and inventive smart manufacturing gave rise to a predictive maintenance system for monitoring or tracking industrial equipment. At present, Industry 5.0 has emerged, smudging a significant milestone. Smart factories are on the rise in business productivity, thereby showcasing the limitations of Industry 4.0. The latest industrial revolution is represented by Industry 5.0, amalgamating technologies such as IoT and artificial intelligence. It encompasses an extensive network of interconnected devices, that ensures prompt data transport, especially within a 5G-capable setting. However going forward, the protocols that are based on centralization and conventional access control techniques are unlikely to remain relevant. Hence, for device-to-device interaction and communication, a robust and efficient decentralized access control system is required. Privacy, confidence and reliability stand out as the most significant issues Privacy, security and reliability stand out as primary concerns in the context of industrial process management. The melding of Blockchain (BC), Industrial IOT, MQTT communications protocol, and ML techniques are emphasized in this research study. Through industrial machinery, real-time data from sensors measure characteristics like current, vibration and temperature. Machine learning(ML) models are utilized for examining this data in order to detect any abnormalities or deviations and failures forecast. With the help of the MQTT communication protocol the consistent interaction among the cloud server, gateway devices and sensors. The system underwent testing using an up-running machine data set, employing the ML model linear regression (LR) algorithms for the processing in the proposed framework and analysis of collected/gathered data to forecast machine failures and provide enhanced and secure maintenance level. This method minimizes costs and operational interruptions through optimized maintenance decisions and schedules, illustrating an Industry 5.0 approach for advanced and smart manufacturing.</p> Ghania Azhar, Muhammad Ashar, Dr. Waqar Azeem, Dr Umer Farooq Copyright (c) 2024 Tue, 25 Jun 2024 00:00:00 +0000