by Sujeet Kumar Tiwari
Journal of Engineering Research and Sciences, Volume 5, Issue 2, Page # 9-23, 2026; DOI: 10.55708/js0502002
Abstract: Flakiness in automation is one of the most intractable barriers to dependable enterprise CI/CD, in which organizations can run more than 50M tests daily, and a 5-10% flaky rate may spoil thousands of builds. The paper brings together empirical research and industrial case studies on UI, API, mobile, and data pipelines to describe the prevalent… Read More

(This article belongs to the Section Hardware and Architecture – Computer Science (HAC))

by Vasile Grosu
Journal of Engineering Research and Sciences, Volume 5, Issue 9, Page # 15-34, 2026; DOI: 10.55708/js0509002
Abstract: Analog electronic design automation has historically lagged behind its digital counterpart due to the complex, multi-dimensional design space and strict sensitivity to parasitic effects, process variations, and geometric constraints. A comprehensive review of the evolution, current state-of-the-art, and future trajectories of electronic design automation tools specifically tailored for analog integrated circuit design could serve as… Read More

(This article belongs to the Section Electronic Engineering (EEE))

by Vasile Grosu, Nicolae Patache and Emilian David
Journal of Engineering Research and Sciences, Volume 5, Issue 7, Page # 1-15, 2026; DOI: 10.55708/js0507001
Abstract: In recent times, machine learning applications have become an important component of the analog integrated circuit development cycle. Several phases such as circuit sizing, optimization or pre-silicon verification have benefited from machine learning automation. For developing such machine learning models, a certain amount of training and testing samples needs to be acquired through circuit simulations.… Read More

(This article belongs to the Special Issue on SP8 (Special Issue on Digital and Engineering Transformations in Science and Technology (SI-DETST-26)) and the Section Electronic Engineering (EEE))

by Vaibhavi Tiwari, Ola Suaifan, Ramy Othman and Anand Gupta
Journal of Engineering Research and Sciences, Volume 5, Issue 6, Page # 67-96, 2026; DOI: 10.55708/js0506006
Abstract: Graph Neural Networks (GNNs) have emerged as a promising approach for fault diagnosis in complex cyber-physical systems because they can model intercomponent relationships, fault propagation, and system-level anomalies across domains such as industrial automation, smart grids, transportation, and healthcare. This survey presents a multidimensional review of GNN-based fault diagnostics, organizing existing methods according to graph… Read More

(This article belongs to the Section Interdisciplinary Applications – Computer Science (IAC))

by Hanan Hassan Ali Adlan, Reham Al Zamanan, Leen Almufleh, Tala Almuqrin and Jory Alhassoun
Journal of Engineering Research and Sciences, Volume 5, Issue 2, Page # 1-8, 2026; DOI: 10.55708/js0502001
Abstract: The Traditional date harvesting is labor-intensive and inefficient, leading to losses and quality issues. This paper introduces an AI-powered robotic system that automates date harvesting using computer vision, LiDAR sensors, and a robotic arm with a suction mechanism. The robot is capable of perception, it detects, classifies, and harvests ripe dates autonomously, ensuring minimal damage… Read More

(This article belongs to the Section Automation and Control Systems (ACS))

by Sravan Reddy Kathi
Journal of Engineering Research and Sciences, Volume 4, Issue 9, Page # 12-21, 2025; DOI: 10.55708/js0409002
Abstract: Enterprises with large Java codebases are increasingly facing challenges in maintaining different versions of Java, mainly during upgrade of legacy Java 8 to modern long-term support (LTS) versions like Java 17. These concerns are majorly identified in environments where several Java versions co-exist, such as during incremental migration or version restrictions based on dependencies. This… Read More

(This article belongs to the Section Software Engineering – Computer Science (SEC))

by Vinil Apelagunta and Vishnuvardhan Reddy Tatavandla
Journal of Engineering Research and Sciences, Volume 4, Issue 8, Page # 41-49, 2025; DOI: 10.55708/js0408005
Abstract: Resilient and compliant supply chains, while essential to the Life Sciences, depend heavily upon SAP systems to manage the complexities involved. The standard Purchase Order (PO) approval process in SAP is an important upstream control point in the supply chain, but seldom has the required intelligence needed to manage endorsed compliance (e.g., GxP) or to… Read More

(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))

by Vaibhavi Tiwari
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 21-36, 2024; DOI: 10.55708/js0310003
Abstract: The incorporation of cutting-edge technologies like sensor networks, artificial intelligence (AI), and vehicle-to everything (V2X) communication has hastened the rollout of autonomous vehicles (AVs), offering significant possibilities for the future of transportation. This document offers an extensive overview of AV technology, covering essential elements such as technological infrastructure, degrees of automation, cybersecurity threats, societal impacts,… Read More

(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 and the Section Transportation Science & Technology (TST))

by Muhammad Numan, Usama Saadat and Muhammad Usman Farooq
Journal of Engineering Research and Sciences, Volume 3, Issue 2, Page # 1-7, 2024; DOI: 10.55708/js0302001
Abstract: Building Information Modeling (BIM) provides a robust foundation for driving sustainability across architecture, engineering and construction (AEC) practices. This paper presents a systematic review of literature elucidating the confluence of BIM tools and processes with accelerated performance simulations and green building certification systems needed to guide environmentally sensitive design. Integrated Revit-Insight 360 is shown to… Read More

(This article belongs to the Section Civil Engineering (CVE))