Journal of Engineering and Applied Sciences Technology
Journal of Engineering and Applied Sciences Technology is an open access peer-reviewed journal from the publishers of Scientific Research and Community (SRC) which publishes articles in the form of written, video and power-point presentations from the arena of Engineering and Applied Sciences Technology. The journal focuses to build up accessing the complete content of articles freely from online for reader’s perusal. Article acceptance will be in the form of Research, Review, Case Reports, Analysis, Magazines, Editorials, Opinion, Communications, Mini-Review, Short Communications, Picturized, Book Review, Video Type and Power Point Presentations (PPTS). Articles can be submitted through online from https://www.onlinescientificresearch.com/submit-online or can send through an e-mail with attachment for Email: appliedengineering@onlinescientificresearch.info or jeast@onlinescientificresearch.net
A Comprehensive Analysis of Gradient Boosting Algorithms for Automated Risk Assessment and Underwriting Decision Systems in Financial Industries Incorporating Behavioral and Historical Data Modeling
Modern financial services depend on automated underwriting and risk assessment to price premiums, extend credit, and catch fraud. However, traditional statistical models often struggle with today’s data which is increasingly high-dimensional, non-linear, and time-sensitive. Gradient Boosting Algorithms (GBAs), such as XGBoost, LightGBM, and CatBoost, have stepped in to fill this gap, offering the flexibility needed to process complex, diverse data sources. This study dives into how these frameworks can be optimized for financial risk. We move beyond basic algorithmic theory to address the "missing pieces" of implementation: feature representation, model interpretability, and the merging of historical records with real-time behavioral data. This reseacrh also introduce a hybrid modeling approach that syncs behavioral scoring with transactional patterns to sharpen predictive accuracy. Our testing on benchmark datasets shows that these optimized models don't just perform better they provide the stability and discrimination power necessary for high-stakes financial decisions. This study addresses the trade-offs between raw performance and the ethical necessity of fairness and transparency in automated systems.
Gradient Boosting (XGBoost, LightGBM, CatBoost)
Copyright (c) 2019 Journal of Engineering and Applied Sciences Technology
AI on Wheels: How Self-Driving Cars Perceive, Decide, and Navigate in Smart Cities
Self-driving cars are becoming an important part of smart cities. They are designed to move safely without human control by using artificial intelligence, cameras, and sensors to understand the world around them. This talk explains how these cars “see” their surroundings using computer vision, how they “think” using AI models and sensor data, and how they “act” by making real-time driving decisions. It also covers how different technologies such as deep learning, LiDAR, radar, and GPS work together to help the car find its way, follow traffic rules, and avoid obstacles. The session will also highlight how these systems are connected with city infrastructure—like smart traffic lights and road sensors—to make transportation safer and more efficient. By the end, attendees will have a clear picture of how artificial intelligence powers self-driving cars and how this technology is shaping the future of smart city mobility.
Copyright (c) 2026 Journal of Engineering and Applied Sciences Technology
Artificial Intelligence for Human Safety
Team of human Experts write computer program or programs in machine language to operate or to do work by a machine or a robot. Human intelligence is converted into workable machine language so that machines or robots which act as sophisticated slaves to do a particular job. Machines obey human commands and work in the atmosphere where humans find it difficult or impossible to endure. Such convenience, Robots and automatic machines can give and replace humans say from hazardous ambience and dangerous to work with by any human. Repeated and monotonous work or jobs given to human workers can also be replaced by Robots and intelligent machines to work instead of human beings. Several part programs combined together can be fed into a computer and intelligent jobs can be carried out using sophisticated machines.
Wi-Fi Sensing for Post-Crash Occupant Assessment: Promise, Scope, and Pitfalls
Vehicles increasingly ship with multi-antenna Wi-Fi for connectivity and diagnostics. With the arrival of IEEE 802.11bf (WLAN Sensing), the same radios can be used to sense people by interpreting channel state information (CSI), opening a path to low-cost, privacy-preserving in-cabin perception that works in darkness, smoke, or when cameras are occluded by airbags. This talk surveys the state of Wi-Fi sensing and its relevance to post-crash telematics: we outline how CSI can recover coarse-to-fine human pose and micro-motion (breathing), and how those signals could augment Advanced Automatic Crash Notification (AACN) datasets to communicate occupant state (e.g., motionlessness, posture consistent with injury) to PSAPs and EMS. We position Wi-Fi against today’s in-cabin modalities, especially 60 GHz radar used for occupancy/child-presence detection, and discuss semiconductor and integration implications for TCUs. We then map the limits: RF variability across cabins, antenna placement and MIMO geometry, interference, domain shift and generalization, structural pose fidelity issues, calibration/aging, standards compliance, Euro NCAP expectations for in-cabin monitoring, and privacy/regulatory considerations when deriving biometrics from RF. Finally, we sketch a practical roadmap: data collection via Wi-Fi/vision pairs, cross-domain training and evaluation protocols, bench and sled testing tied to AACN fields, and deployment options leveraging 802.11bf primitives.
5G Mobile Edge Computing – Integrated, Secured Platform for Industrial Metaverse Use Cases
The purpose of the presentation is to describe how 5G edge computing can be utilized in automated industrial processes that require real-time, immersive digital capabilities. It builds on recent experiences in planning and implementing use cases in the selected industry sectors that are seeking new business opportunities from the applications of industrial metaverse. The use cases are characterized with an ambition to strive for sustainable and digital operations without compromising security. The presentation starts with a short analysis of the emerging industry digitalization (Industry 4.0) from real-time data and metaverse perspective. It contains the introduction of key concepts, terms, and definitions under the umbrella of industrial metaverse. The presentation focuses on the real-life use cases of selected industrial enterprises to improve customer satisfaction, efficiency, and sustainability with industrial metaverse applications. The use cases are studied from the lens of five different industry sectors that have both similarities and differences in applying new digital capabilities. They provide new insight on the use of digital twins, video analytics, and AR/VR supported operations. In principle, all use cases require full mobility and are therefore to be implemented based on 5G standalone technology which allows high throughput and low latency with edge computing. As the interoperability between IT and OT systems play a significant role, meeting the requirements of cybersecurity become vital. The 5G mobile edge provides industrial enterprises with a trusted, scalable connectivity and computing platform that enables the development of real-time metaverse applications in a sustainable and secure manner.
World First: Browse the 3D Web without Limits, Protected and Invisible by Patented Design. Access Knowledge, Consume Securely, Whatever the Sector or State of Your Data
In five years’, time, the web will be a 3D universe where we’ll navigate like drones, exploring digital territories, manipulating objects and ideas with immersive tactile interfaces. 3D tutorials and 3D printers will enable us to fix almost anything, while collaborative work will replace Taylorization. This freedom of discovery will become addictive and viral. Over 80% of the world will have access to ultra-fast Internet, browsing digital twins of cities, objects, molecules or organs, exploring everything from hardware to health, leisure to safety, right up to the limits of intellectual property. Everything will be accessible, fun and educational, with no apparent risk. But danger lurks: a simple incident (data theft, substitution of a virtual component) could lead to the production of defective, weakened or even dangerous objects, unknowingly integrated into the consumer chain. Traceability will become blurred, and these “modified” objects will represent a real threat. The whole world will become accustomed to “touching” virtually everything, comparing details and testing before buying. Companies that don’t respect 3D web standards will disappear, wiped off the map in a matter of months. This reality is no longer fiction: the era of the three-dimensional web is about to take hold, mixing the real and the fake, security and pitfalls. We need to anticipate the risks if we are to take full advantage of this revolution, where innovation rubs shoulders with counterfeiting, and where the invisible becomes an asset. Anticipating the worst to experience the best: that’s the challenge of this fascinating new era.
Can Robots Have Consciousness – What Does Mathematical Science Say About This?
Although AI has currently triggered global hype, its applications are subject to narrow limits, which are often ignored today. AI is ideal for mathematical and big data environments, but it has massive difficulties in practical applications in natural environments, as can be clearly seen in the obstacles facing mobile robotics and autonomous driving in the natural environment. In particular, inductive AI has serious difficulties with all applications in the extrapolation space and in the area of small data. Humans, on the other hand, can make the right decisions with just a few data sets (sometimes a single hot stove is enough for a child). Human brains and current AI systems are fundamentally different. Particularly serious is the complexity limit that cannot be overcome by any current AI, which is represented by second-order predicate logic. No AI system in the world today can systematically exceed this limit, while even children have no problems with it. AI should therefore evolve from algorithmic AI to dedicated neuromorphic AI. The lecture will show how. Ultimately, the lecture presents mathematical possibilities for describing qualia and consciousness and outlines hypotheses on how consciousness could be generated on technical systems (machine consciousness). The theory presented thus bridges the gap between natural science and Japanese Shintoism, as Shintoism not only appears to have evidence, but can also be strictly mathematically justified.
“Diámesos”: The Art of Interfacing Robotics to Things in Space
The domain of robotics today translates to any type of system that manipulates, moves, affects or modifies either its environment or other things. For decades elements in space are monolithic, built on the ground and then transported to space for one purpose and life. Applying the construct of “robotics” to the space domain enables a rethinking of how single use elements are designed and can be utilized, post launch. The singular challenge to changing this entrenched culture is the lowly “interface”; the entity that connects two or more things together. This talk with discuss the unique challenges and morphology of space system design, and where potential connection points between elements may lie for efficiency and optimization, all under the rubric of applying elements of robotics to affect, post launch.
Automating HR Processes with Robotic Process Automation (RPA)
The integration of Robotic Process Automation (RPA) into Human Resources (HR) functions represents a significant advancement in organizational efficiency and effectiveness. RPA technology automates repetitive and rule-based tasks, allowing HR professionals to focus on strategic initiatives that add value to the organization. This paper provides a comprehensive introduction to RPA within HR, detailing its applications, benefits, implementation strategies, and how its principles can be transferred to other domains such as finance. By examining the transformative potential of RPA, organizations can better prepare for the future of work, where automation and human ingenuity coexist to drive success.
Copyright (c) 2023 Journal of Engineering and Applied Sciences Technology
Stability Augmentation in Lateral Directional Dynamics: A Multivariable Approach
This paper delves into the concept of stability augmentation in lateral-directional dynamics, focusing on a multivariable approach. In aircraft control systems, ensuring lateral-directional stability is crucial for safe and efficient flight. The primary objective is to examine the feedback control system's role in enhancing stability and how it interacts with the aircraft's inherent dynamics. We begin by exploring the basic augmentation system for lateraldirectional dynamics, which includes the feedback of body-axis roll rate to ailerons and yaw rate to the rudder, commonly referred to as the yaw damper. One of the key challenges addressed in this paper is the need to overcome the interference caused by the yaw damper when coordinating turns. This interference results from the constant nonzero yaw rate present during coordinated turns. To address this issue, the concept of "transient rate feedback" is introduced, which uses a washout filter to differentiate the feedback signal and minimize its effect during steady-state conditions. The paper presents mathematical models and transfer functions that describe the behavior of the lateral-directional augmentation system. It discusses the impact of different parameters, such as the time constants of actuators and washout filters, on the system's performance. The design of the feedback loops for roll and yaw control is elaborated upon, emphasizing the trade-offs between roll response, dutch roll damping, and roll-yaw coupling. Simulation results are used to evaluate the effectiveness of the stability augmentation system in improving the aircraft's roll response and dutch roll damping under varying flight conditions. The paper concludes with insights into the challenges and benefits of multivariable control system design for lateral-directional stability augmentation in aircraft.
WFM is an essential component of healthcare systems that have transformed organizational functioning, increased the quality of patient services, and improved comparability with legislation. This paper examines how WFM systems find application in the health sector to improve staff rostering, cut costs, and increase employee morale. At one point, it examines most facets of WFM, such as staffing, time, and workfoce reporting, and how these aspects yield the best patient results. The authors also found WFM helpful in reducing legal issues such as compliance with labor laws and health care regulations. In addition, the paper concludes by highlighting potential developments in WFM within the healthcare profession, including AI and machine learning, which provide forecasts for staff requirements. They proceed to the issues that make WFM crucial, including the increasing size and age of the population and the global shortage of healthcare workers. Thus, the paper offers suggested guidelines for healthcare leaders to adopt and leverage WFM systems to improve organizational efficiency and patient care quality. Employing the availability of current WFM technologies, healthcare establishments can address the changing needs of such a field, delivering operational efficiency and caring for patients.
Text-To-Speech in Voice Assistants: Challenges and Mitigation Strategies
Voice Assistants (VAs) have grown rapidly from technological novelties to integral parts of our daily lives to perform tasks like streaming music or news, setting alarms or responding to questions. These virtual conversational agents rely on an intricate combination of technologies, and one of the pivotal components is Text-to-Speech (TTS) synthesis. In this paper, we delve into the technical intricacies of TTS in voice assistants, addressing challenges, solutions, and future directions. VAs like Alexa, Siri and Google Assistant have transformed human-computer interactions. The underpinning TTS technology is crucial for converting text-based information into spoken language, making the interaction more natural and accessible. The synthesis of human-like speech from textual data is a complex and interdisciplinary domain, encompassing fields such as speech signal processing, natural language processing, deep learning, and linguistics. This paper aims to contribute a detailed analysis of TTS in voice assistants, emphasizing not only the theoretical aspects but also the practical implementation and real-world implications. The paper will examine the challenges associated with TTS, considering its technical, linguistic, and user-centric dimensions. The paper will also present mitigation strategies for these challenges. In a world where voice-driven interactions are becoming commonplace, a deep understanding of TTS is vital. By delving into the depths of this technology, we can unlock its full potential and ensure that voice assistants continue to enrich our lives and technical domains.
Cyber Resilience in Cloud-Based Critical Infrastructure
Cyber resilience within the cloud-based critical infrastructure refers to the capability of protecting electronic data and the systems from cyberattacks within the business operations within fintech sectors. The proposed research tries to investigate the cruciality of cyber resilience within cloud-based infrastructures. In the current era, the intense emergence of cyber threats necessitates the protection of critical infrastructure. The key findings of this research underline the dynamic approach to the maintenance of resilience against cyberattacks. Through providing actionable recommendations for the organizations, this research reinforces the baseline for the cloud security positions.
Review and Analysis of Autonomous Vehicles - Current State and Challenges
Vehicles that can function independently of human control are known as autonomous vehicles. They detect their surroundings, make judgments, and steer clear of danger using a network of sensors and cameras fed data by complex computer algorithms. The findings of this study summarise the present status of autonomous car technology and its ramifications on society. The paper begins by discussing the different types of autonomous vehicles and the sensors and technologies used to enable their operation. It then examines the challenges that must be overcome to achieve widespread adoption of autonomous vehicles, including safety, regulation, and public acceptance. Finally, the paper also explores the potential benefits of autonomous vehicles, such as improved transportation efficiency, reduced traffic congestion, and improved accessibility for people with disabilities.
Inter-Plan Blue Cross Blue Shield Programs - A Case Study in Payor Claims
The Blue Cross Blue Shield (BCBS) Inter-Plan Programs that comprise BlueCard, National Accounts, and the Federal Employee Program (FEP) are significant to broaden the healthcare benefits for all members by offering consistent and supreme features. With the help of these programs, it is possible to access a wide range of services in the healthcare industry both on a country level and across the world. Though these benefits are available for all members, people who travel frequently find these pros appealing. In addition, members who are shifting from burn to another place gain more benefits from these offerings. Furthermore, EDI 837 transactions enhance smooth submissions by offering an effective exchange of information across all related elements of BCBS. This rapid exchange of information among coordinators enhances the functionality of the system by real-time collaboration which increases the level of satisfaction among all members. This further reduces the possible delays as well as the probability of mistakes. Unlike their competitors including CVS Health as well as Aetna, BCBS features offer a wide range of appealing prospects making it an ideal choice for those looking for inclusive healthcare insurance. BCBS Inter-Plan Programs' requisite assortment of effective and robust care plus inclusive accessibility tend to bring diversity in healthcare outcomes throughout the BCBS system.
Authentication and Authorization in Web Applications
This article navigates through the landscape of OAuth 2.0, a pivotal authentication and authorization protocol widely adopted in web applications. By demystifying the core components – namely the Resource Owner, Client, Resource Server, Authorization Server, Access Token, and Refresh Token – the article sheds light on their distinct roles and interplay in safeguarding user credentials while permitting authorized access to protected resources. Furthermore, it delves into the various authorization flows, elucidating mechanisms that guide secure interactions between users, applications, and resource servers. With an adjunct focus on security considerations and challenges, the article provides a holistic view of implementing OAuth 2.0. It aims to give developers and IT professionals comprehensive insights into effectively leveraging this protocol while mitigating potential vulnerabilities. A balanced perspective juxtaposes the protocol's robustness and complexity, striving to offer a thorough understanding of employing OAuth 2.0 in diverse web application scenarios.
Threat Detection Using Real-Time Data Engineering Pipelines
Due to rising cyber threats and data quantities, existing systems need better threat detection. Real-time data engineering pipelines boost threat detection in this research. This study uses 2016–2020 literature data to examine threat detection methodologies, tools, and models. Results suggest that data security, integration, and standardisation must be addressed before broad use of these pipelines, despite their obvious advantages. Machine learning, blockchain, and IoT are promising.
Peeling Reveals Problems of Strength Standards for Brittle Materials
Peeling creates a ubiquitous crack used regularly to open plastic packaging. Such peel cracks have been utilised for centuries, especially in separating cellulose fibres, yet these peeling cracks are not usually mentioned in fracture texts [1,2]. In this paper, theories and experiments show that peel cracks have unique properties quite different from the tensile-test cracks generally used to define and standardize strength of materials. Peeling is the easiest fracture test at the lowest force with the simplest theory describing constant speed cracks that are readily observed. It differs markedly from the catastrophic tensile cracks seen in many brittle materials such as concrete and glass, that accelerate rapidly at high force. The problem is that strength in peeling is not consistent with strength in tension. There is a large size effect in peeling where strength drops for larger sample size. Therefore, standards need to be modified. This paper describes peeling observations in several crack test geometries, fitting the energy theory of thermodynamic crack equilibrium, contrary to the stress/strength criteria that dominate existing brittle-material standards, which need correction.
Containerization vs. Serverless Architectures for Data Pipelines
The pace of big data and cloud computing ages has accelerated and made new architectural alternatives designed for deploying and executing data pipelines a reality. A couple of the ways are clustered into containerization, like Docker and Kubernetes on one side, and the other on the other hand is serverless computing with platforms like AWS Lambda, Google Cloud Functions, and Azure Functions.
The question “How to calculate the dimensions of the universe?” has intrigued astronomers for centuries. The discovery of light remnants from the big bang not only provided supportive evidence for the big bang theory, but also allowed scientists to calculate the age of the universe. The big bang is the currently accepted theory of how the universe began and the beginning of time as we know it.
Quantifying the Impact: Evaluating Success Metrics and KPIs for Data Science Initiatives and ROI Optimization
In the dynamic intersection of business and technology, data science emerges as a linchpin for innovation and competitive advantage. This paper delves into the nuanced realm of success metrics and key performance indicators (KPIs) crucial for evaluating the impact and success of data science initiatives. Unveiling metrics such as accuracy, model performance, and business impact, it outlines the strategic importance of Return on Investment (ROI) and data quality in the data science landscape. This paper also provides a comprehensive guide for data scientists to implement and monitor these metrics, emphasizing the iterative nature of improvement. Illustrated through a case study on customer lifetime value (CLV), the piece underscores the role of success metrics in optimizing outcomes, showcasing the significance of continuous monitoring and improvement for organizations venturing into data-centric endeavors.
Limiting Heating & Cooling Peak Loads for Net Zero Carbon Buildings
Limiting peak heating and cooling loads is an important factor in net zero carbon building in relation to renewable energy implementation, load shifting, etc. Passive and active measures are necessary to limit or shift peak loads in net zero carbon buildings. With the increasing demand for more sustainable and energy-efficient buildings and services to combat climate change, weather data has now become an essential component of virtually every new building design and major refurbishment. In this study, dynamic simulation is used to predict the peak heating and cooling loads for an office building to understand the impact of different load estimate parameters on heating and cooling loads. This paper will discuss the impact of using different weather files, heat gains and shading on the peak loads. It also provided guidance to minimise heat peak loads spikes.
Creating a High-Performing ELD Application: Ensuring Compliance and Efficiency in Fleet Management
Electronic Logging Devices (ELDs) are critical in modern fleet management, ensuring compliance with the Hours of Service (HOS) regulations mandated by the Federal Motor Carrier Safety Administration (FMCSA). This paper outlines the development of a high-performing ELD application, focusing on strict data requirements, event creation, data processing, and the architecture of an ELD system.
Structural Analysis of “La Giralda”, Bell Tower of the Seville Cathedral
La Giralda is a tall bell tower, an icon of Seville, the city where it stands. It was built in the 12th century using brick and then modified and increased in the 16th century to reach its current height: more than 90 meters. This height and its other geometric characteristics, together with its resistance to all external agents suffered for more than four centuries (especially earthquakes) make La Giralda an interesting monument on a structural level. For this reason, this article studies and analyzes the structural capacity of this monument from the current engineering vision: a geometric analysis is carried out, an analysis of the foundation is highlighted, a gravitational structural analysis (own weight) is carried out, a third-party analysis is carried out, and fourth are structural analyzes against wind and earthquake. This fourfold analysis will allow a better understanding of the structural functioning of the monument as a whole and its survival after so many years.
The paper "Three Mindsets of Product Development" presents an analysis of three pivotal approaches in product development: Design Thinking, Lean, and Agile. It explores how Design Thinking focuses on understanding user needs for innovative solutions, Lean emphasizes value creation with minimal resources and continuous improvement, and Agile advocates for adaptability and prioritization in response to change. The narrative is enriched with a story about Erik, a restaurant customer, to illustrate the practical application of these mindsets in enhancing customer value, process efficiency, and problem prioritization.
Challenges and Advances in Distributed Estimation for Networked Stochastic Systems
Distributed estimation in networked stochastic systems has become a cornerstone of modern signal processing, control, and monitoring applications. Under the assumption of perfect communication links, centralized estimation approaches —in which all sensor measurements are transmitted to a fusion center where a global estimator processes the complete dataset— can achieve optimal performance. However, in real-world networked systems, communication channels are often imperfect, and transmitting all data to a central node can be impractical or even infeasible, especially in large-scale or geographically distributed networks. By enabling individual sensor nodes to estimate global system parameters through localized computations and limited communication with neighbouring nodes, distributed strategies overcome these limitations, offering scalable, robust, and energy-efficient alternatives to centralized methods. These advantages are particularly vital in resource-constrained environments such as wireless sensor networks, industrial automation systems, and autonomous multi-agent platforms. This keynote presents a global overview of recent advances in distributed estimation, with an emphasis on addressing key practical challenges encountered in real-world deployments. After introducing the fundamental principles of distributed estimation and its advantages over centralized schemes, we focus on four critical issues: 1. Random variations in system parameters, 2. Quantization effects due to limited measurement resolution, 3. Temporal correlations in observation noise, and 4. The presence of mixed random attacks. Recent theoretical developments addressing these challenges will be presented. The talk concludes with a discussion of promising future directions, including the analysis of communication delays and packet dropouts on estimator performance, the design of distributed estimation mechanisms under complex and dynamic attack scenarios, and the integration of random-access communication protocols as an active defense mechanism against potential attacks. Key references will be provided for researchers interested in further exploring the mathematical foundations and engineering applications of distributed estimation.
SLAM for Autonomy: From Concept to Deployment
In this session, I’ll be talking about the challenges of using SLAM in robotics—from sensor limitations and computational constraints to maintaining accuracy in fast-changing 3D environments. I’ll also discuss how SLAM can be effectively applied to robotics for indoor and outdoor navigation, highlighting key strategies and practical insights from real-world implementations.
Responsible AI In the Age of Autonomous Agents
Responsible AI in the Age of Autonomous Agents. As conversational AI systems evolve to become more autonomous and integrated into business operations, the need for trustworthy AI practices — including safety, privacy, security, fairness, and transparency — is more urgent than ever. These systems must be unbiased, explainable, secure, respectful of user privacy, and include human oversight to ensure they effectively address user needs. Yet today, privacy is often violated. Testing and evaluation frameworks for conversational AI remain insufficient or underdeveloped. Many companies still lack practical tools to validate their systems beyond surface-level performance metrics and safeguard filters. Meanwhile, academic research — although valuable — is often difficult to apply in real-world product environments. This presentation explores: • The risks of deploying AI agents without responsible AI foundations • The gap between academic theory and practical implementation • The need for more applicable, business-friendly frameworks for testing AI systems • Why measuring ROI and user impact should be part of every responsible AI strategy The idea is to give participants a clearer view of what effective testing for conversational AI systems should look like.
Introduction to Industrial Cutting Fluid – A Review
Cutting fluids play a crucial role in metalworking and machining processes by extending tool life, enhancing surface finish, and dissipating the heat generated during cutting operations. Their primary function is to manage heat dissipation and prevent overheating during machining, which in turn improves tool longevity and machining efficiency. Choosing the right cutting fluid is essential in these processes, as various types provide unique benefits and properties. Cutting fluids are widely utilized in machining and metalworking to lubricate, cool, and remove metal chips. These fluids enhance tool longevity, workpiece quality, and overall machining efficiency. Different types, such as oils, emulsions, and synthetics, are selected based on the specific requirements of the application. Effective selection and management of cutting fluids are vital for optimizing processes.
Impact of O-RAN on Small Cell Deployments
The Open Radio Access Network (O-RAN) architecture has emerged as a transformative approach in wireless networks, enabling greater flexibility, reduced costs, and vendor diversity. Small cells play a critical role in improving coverage and capacity, especially in urban and rural areas. This paper examines the suitability of O-RAN for small cell deployments, highlighting its advantages, technical adaptations, use cases, and challenges. Simulation results and existing implementations are analyzed to underscore O-RAN’s potential in this domain.