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Articles 1051 - 1080 of 25763
Full-Text Articles in Computer Engineering
Penggunaan Microsoft Excel Di Kehidupan Sehari-Hari, Dimas Hafidz Alfarisi, Bilal Al Kindi, Aisya Mardatila, Reni Anggraeni, Desi Wulandari
Penggunaan Microsoft Excel Di Kehidupan Sehari-Hari, Dimas Hafidz Alfarisi, Bilal Al Kindi, Aisya Mardatila, Reni Anggraeni, Desi Wulandari
Bhakti: Jurnal Pengabdian Masyarakat
Community Service Program (KKN) is one of the main parts of the tridharma of higher education, which requires students to play an active role in community empowerment through education, research, and service. This article discusses one of program from the KKN team from Universitas Negeri Semarang (UNNES), which took place in Tlogopucang Village, Kandangan District, Temanggung. In today's digital era, mastery of information technology has become a crucial requirement, including the ability to operate data processing applications such as Microsoft Excel. Unfortunately, many people, especially in rural areas, are still unfamiliar with the benefits of Excel. However, this application has …
Chplx: The Hpx Solution For Bridging Chapel And C++, Shreyas Swanand Atre
Chplx: The Hpx Solution For Bridging Chapel And C++, Shreyas Swanand Atre
LSU Master's Theses
Historically, domain scientists faced steep learning curves due to low-level programming models and fragmented tooling. Between 2003 and 2008, Cray, now part of HPE, introduced the Chapel language as part of DARPA’s High Productivity Computing Systems (HPCS) program. Today, Chapel remains under active development and is used across research and production projects. In parallel, the STE||AR Group has advanced C++-based parallel programming through HPX, a standards-conforming runtime that provides lightweight tasking, futures, and distributed execution while abstracting much of the algorithmic “heavy lifting.” Yet for many domain scientists, C++ presents a steeper learning curve than Chapel. To close this complexity …
Sensing The Pulse Of A Data Stream In Real Time, Vishnu S. Pendyala
Sensing The Pulse Of A Data Stream In Real Time, Vishnu S. Pendyala
Open Educational Resources
In an era where data never sleeps, streaming algorithms offer a powerful toolkit for extracting meaningful insights from high-velocity data flows. This talk explores some foundational techniques that enable efficient, real-time analytics with minimal memory requirements. The algorithms covered include a clever bit-based strategy for approximating the count of 1s in a sliding window, ideal for binary streams where space efficiency is paramount. Another algorithm helps estimate statistical moments (mean, variance, skewness) using compact sketches, enabling a deeper understanding of stream distributions without storing the entire dataset. One other algorithm identifies trending items with exponential decay, giving more weight to …
Synthetically Expressive: Evaluating Gesture And Voice For Emotion And Empathy In Vr And 2d Scenarios, Haoyang Du, Kiran Chhatre, Christopher Peters, Brian Keegan, Rachel Mcdonnell, Cathy Ennis
Synthetically Expressive: Evaluating Gesture And Voice For Emotion And Empathy In Vr And 2d Scenarios, Haoyang Du, Kiran Chhatre, Christopher Peters, Brian Keegan, Rachel Mcdonnell, Cathy Ennis
Conference papers
The creation of virtual humans increasingly leverages automated synthesis of speech and gestures, enabling expressive, adaptable agents that effectively engage users. However, the independent development of voice and gesture generation technologies, alongside the growing popularity of virtual reality (VR), presents significant questions about the integration of these signals and their ability to convey emotional detail in immersive environments. In this paper, we evaluate the influence of real and synthetic gestures and speech, alongside varying levels of immersion (VR vs. 2D displays) and emotional contexts (positive, neutral, negative) on user perceptions. We investigate how immersion affects the perceived match between gestures …
Enhancing 6g Network Security With Quantum Key Distribution: A Comprehensive Review, Bassma M. Kamil
Enhancing 6g Network Security With Quantum Key Distribution: A Comprehensive Review, Bassma M. Kamil
Al-Esraa University College Journal for Engineering Sciences
With the considerable progress of sixth-generation (6G) networks further on the horizon, security has attracted much attention in the face of increasingly sophisticated threats, especially from quantum computing. Classical cryptographic schemes based on computational hardness are becoming more and more brittle, as they can easily be attacked with a quantum computer. Quantum Key Distribution (QKD) arises as a promising tool for information-theoretic security through quantum mechanics to obtain an unbreakable key by exchanging unknown bit sequences. In this paper, we provide an extensive survey on the integration of QKD both in the envisioned 6G architecture, including current implementations, technical feasibility, …
Protection The Nfv Net-Work Using The Random Forest Classification, Mustafa H. Taha, Ibtesam Jomaa Hawi, Wafaa Waheeb Abdullah Ali
Protection The Nfv Net-Work Using The Random Forest Classification, Mustafa H. Taha, Ibtesam Jomaa Hawi, Wafaa Waheeb Abdullah Ali
Al-Esraa University College Journal for Engineering Sciences
A misuse attack is the most common and dangerous type of attack that could target NFV (Network Function Virtualization). In a misuse attack, the attacker attempts to consume the NVF environment’s resources by sending a large amount of traffic. To protect the NFV environment, an early and accurate misuse attack detection system has been proposed based on NFV and Random Forest Classifier. The proposed model starts with importing the dataset and analyzing it then pre-processing and feature selection using a PSO (particle swarm optimization) Test algorithm, classification is based on the most common and efficient machine learning technique, which is …
Design Of A Hybrid System For Powering Wireless Communication Units, Samer Rabih, Ahed Alboody
Design Of A Hybrid System For Powering Wireless Communication Units, Samer Rabih, Ahed Alboody
Al-Esraa University College Journal for Engineering Sciences
Wireless and optical communication units are becoming more widespread nowadays, especially in rural areas. Therefore, feeding electricity has become essential for the continuity of services. As a result of economic and social development, there has been an urgent need to supply electrical power for the basic requirements of wired and wireless telecommunications equipment. This is linked to public safety, long life, and connection to uninterruptible power systems to ensure continuous power supply, whether from renewable energy sources or traditional diesel systems. This research studies and designs a renewable energy (solar) power system to power telecommunications equipment. The proposed power system …
Dynamic Ris-Enabled Massive Mimo Noma Systems Power Allocation Optimization For 6g Using Machin Learning Approach, Mohamed Hassan, Khalid Hamid, Salah Hagahmoodi, Elmuntaser Hassan
Dynamic Ris-Enabled Massive Mimo Noma Systems Power Allocation Optimization For 6g Using Machin Learning Approach, Mohamed Hassan, Khalid Hamid, Salah Hagahmoodi, Elmuntaser Hassan
Al-Esraa University College Journal for Engineering Sciences
This study examines spectral efficiency (SE) and throughput throughout a spectrum of user densities (from 50 to 1000 users), user mobility speeds (0 to 350 km/h), latency, packet loss, and fairness index, within a wide range of signal-to-noise ratios (SNRs). The analysis includes a number of different situations, such as (i) cooperative non-orthogonal multiple access (NOMA) with massive multiple-input multiple-output (mMIMO), (ii) mMIMO cooperative NOMA integrated with cognitive radio (CR), and (iii) CR-assisted mMIMO cooperative NOMA enhanced with reconfigurable intelligent surfaces (RIS). All of these are part of 6G millimeter-wave (mmWave) networks. The study investigates the enhancement of latency, packet …
Harnessing Waste Heat From Solar Cells Using Advanced Energy Storage Systems, Hayder Ibrahim Ismael
Harnessing Waste Heat From Solar Cells Using Advanced Energy Storage Systems, Hayder Ibrahim Ismael
Al-Esraa University College Journal for Engineering Sciences
Renewable energy is largely produced by photovoltaic (PV) solar cells, but such a process is greatly impacted with thermal buildup as the solar cells work. Redundant heat not only lowers the level of electrical production, but also hastens deterioration and decreases the life-time of PV modules. In this study, we suggest a hybrid system which combines high-performance energy storage devices, namely, super-capacitors, and PV modules coupled with the use of waste heat as a source of useful energy and which increases efficiency of the system in conjunction. In order to estimate the potential amount of thermal energy recovery, as well …
Empirical Research Of A Greenhouse Monitoring And Controlling System Using Zigbee Protocol, Mohammed Hijazeh, Salah Hagahmoodi
Empirical Research Of A Greenhouse Monitoring And Controlling System Using Zigbee Protocol, Mohammed Hijazeh, Salah Hagahmoodi
Al-Esraa University College Journal for Engineering Sciences
Greenhouses are of great importance in the agricultural field as they provide the appropriate and important environment for the growth and production of various plants regardless of the surrounding environmental conditions. Monitoring and controlling these houses are considered necessary and important in order to provide the required environment and obtain the best production. Therefore, the aim of this project is to study the monitoring and control of these houses using wireless sensor networks, which are considered modern and simple methods due to the accuracy of work and little effort they provide, and thus better production. The study will be for …
Designing An Efficient Deduplication Algorithm For Audio Files In Cloud Storage, Ammar Zakzouk, Alaa Al Sebae, Hasan Hasan
Designing An Efficient Deduplication Algorithm For Audio Files In Cloud Storage, Ammar Zakzouk, Alaa Al Sebae, Hasan Hasan
Al-Esraa University College Journal for Engineering Sciences
Data duplication is a significant challenge in large-scale data storage systems, as it consumes storage space and impacts data organization, management, and processing. An optimal storage system effectively utilizes available storage space. To solve this problem, hash algorithms are employed to generate hash keys for files. Matching files have the same hash key. However, the hash key for two different files in the data may match, and this is what we refer to as a collision. The collision issue is related to the length of the hash key. As the length of the hash key increases, the probability of a …
The Future Of Al-Driven Cybersecurity For Advanced Iot, Estqlal Hammad Dhahi, Sanaa Hammad Dhahi, Ohood Fadil Alwan
The Future Of Al-Driven Cybersecurity For Advanced Iot, Estqlal Hammad Dhahi, Sanaa Hammad Dhahi, Ohood Fadil Alwan
Al-Esraa University College Journal for Engineering Sciences
Internet of Things technologies experience rapid advancement because of 5G networks and upcoming 6G technologies, which resulted in transformational changes to security dynamics. This study examines the functionality of artificial intelligence through platforms developed to secure Internet of Things systems. The demand for improved security capabilities has become essential because IoT devices generate new assault channels, and their market penetration speed is escalating. Machine learning algorithms, together with deep learning and natural language processing methods, are investigated in this paper for enhancing the security protocols of IoT systems through studies found in academic literature. The paper explores upcoming developments and …
Foundations Of Artificial Intelligence In Healthcare Diagnostics: A Systematic Survey, Raghad Tariq Al-Hassani
Foundations Of Artificial Intelligence In Healthcare Diagnostics: A Systematic Survey, Raghad Tariq Al-Hassani
Al-Esraa University College Journal for Engineering Sciences
Artificial Intelligence (AI) is becoming the cornerstone of the future of healthcare diagnostics, that has to ability to change the healthcare diagnostic landscape in terms of diagnostic accuracy, speed, and availability. This systematic review investigates the basic methods, tools, applications, and challenges involved in the integration of AI in diagnostic medicine. It emphasizes the using of machine learning models, deep learning networks (e.g., CNNs), NLP for clinical documentation, and smart computing infrastructures, such as edge device and IoMT. They are making possible real-time, data-driven decision making that is already at human-expert-level performance or, in some cases, even better (in the …
Secure Gif Files Based On Zuc Stream Cipher And Present Algorithm, Suhad Fakhri Hussein
Secure Gif Files Based On Zuc Stream Cipher And Present Algorithm, Suhad Fakhri Hussein
Al-Esraa University College Journal for Engineering Sciences
Some important security needs include authentication, confidentiality, integrity, non-repudiation, and user privacy. Many security systems include these required protections for information transmission. The encryption process is one of the most important security measures. Many secure encryption algorithms are based on different keys and key lengths to ensure a high degree of security. GIF file format is common file format that is used in several application, securing these files through transmission is imperative. In this paper, an efficient method for encryption GIF file is proposed based on using modified present algorithm, modified ZUC stream cipher, and an efficient method for key …
Advanced Strategies And Solutions Towards More Secure And Effective Two-Factor Authentication In Networking, Zahraa Sameer Jawad
Advanced Strategies And Solutions Towards More Secure And Effective Two-Factor Authentication In Networking, Zahraa Sameer Jawad
Al-Esraa University College Journal for Engineering Sciences
With the rapid increase in cybersecurity threats targeting network systems, traditional two-factor authentication (2FA) methods are insufficient to address advanced attacks. Vulnerabilities such as phishing, SIM-swapping, and social engineering exploit the limitations of SMS-based and email-based 2FA. This paper examines advanced strategies and solutions for securing networked environments through robust 2FA mechanisms, focusing on approaches like elliptic curve cryptography (ECC), digital certificates, and biometric verification. This article offers a comparative review of various strategies about their effectiveness in enhancing security, while also highlighting their capacity to optimize user-friendliness and adaptability to emerging threats. Research findings promote an effective countermeasure strategy …
Advancements In Ultrasound Technology And Iot Security: A Physics-Based Approach To Enhanced Imaging With Lightweight Encryption Algorithms, Noor Fawzi Shafiq
Advancements In Ultrasound Technology And Iot Security: A Physics-Based Approach To Enhanced Imaging With Lightweight Encryption Algorithms, Noor Fawzi Shafiq
Al-Esraa University College Journal for Engineering Sciences
The rapid advancements in ultrasound technology, coupled with the growing significance of IoT security, present a unique opportunity to enhance imaging systems while ensuring data integrity. This study explores the integration of physics-based principles in ultrasound imaging, focusing on how lightweight encryption algorithms can secure data transmitted from IoT devices.Ultrasound technology has evolved significantly, benefiting from improved imaging techniques and the incorporation of IoT devices. As these devices proliferate across various applications, including healthcare and industrial monitoring, the need for secure data transmission becomes paramount. This paper proposes a framework that combines advanced ultrasound imaging with robust lightweight encryption methods …
Artificial Intelligence Approaches To Mitigating Network Congestion In Iot Systems, Aysar Hadi Oleiwi
Artificial Intelligence Approaches To Mitigating Network Congestion In Iot Systems, Aysar Hadi Oleiwi
Al-Esraa University College Journal for Engineering Sciences
The unprecedented explosion of Internet of Things (IOT) devices has elevated the requirements of the network infrastructures to unprecedented levels, causing severe congestion problems, especially in applications which demand low latency, high throughput, and real-time feedback. Static routing protocols, AQM, and TCP variants are some of the traditional mechanisms for congestion control that are unable to perform efficiently in dynamic and diverse IoT environments as they are reactive-based and inflexible. To this end, in this paper, we explore the promising ability of Artificial Intelligence (AI) methods such as Machine Learning (ML), Deep Learning (DL), Reinforcement Learning (RL), and their combination …
Groundwater Quality Analyses For Irrigation Purposes In Salah Al-Din, Iraq: A Review, Noor A. Radhi, Dawood E. Sachit, Abdul-Sahib T. Al-Madhhachi
Groundwater Quality Analyses For Irrigation Purposes In Salah Al-Din, Iraq: A Review, Noor A. Radhi, Dawood E. Sachit, Abdul-Sahib T. Al-Madhhachi
Al-Esraa University College Journal for Engineering Sciences
The focus of this study is the effect of the physical and chemical characteristics of groundwaters on plants and agricultural crops, following the last studies on this matter. The results underscore the necessity for groundwater treatment before its utilization in irrigation for sustainable agricultural farming. It is also possible to identify which crop type can be grown in well-watered land, according to the characteristics of irrigation water and the yield of each crop. The study also introduces some ideas about irrigation water quality parameters such as Electrical conductivity (EC), Total Dissolved Solids (TDS), pH, Chloride (Cl–), Sodium (Na …
Examining Iot-Enhanced For Current Developments In Face Image Authentication (Fia) Methods And Their Drawbacks, Marwa Jamal Hadi, Emaan Ouudha Oraby
Examining Iot-Enhanced For Current Developments In Face Image Authentication (Fia) Methods And Their Drawbacks, Marwa Jamal Hadi, Emaan Ouudha Oraby
Al-Esraa University College Journal for Engineering Sciences
The quick development of IoT and facial image manipulation (FIM) algorithms, as well as the growth of their user-friendly applications, highlight the pressing need for manipulation detection methods. These techniques need to demonstrate how face photos have been altered and validate their legitimacy. The scientific community has recently taken notice of the phrase “DeepFakes” and methods for detecting them. Take note of the latest methods for identifying watermark-based face image modification as well. The important thing to remember is that every one of these methods has its own set of drawbacks. This study provides a brief introduction to face image …
Advancing Mobileclip Through Hybrid Quantization: A Cpu-Focused Approach, Atiqur Rahman
Advancing Mobileclip Through Hybrid Quantization: A Cpu-Focused Approach, Atiqur Rahman
2025 Fall Honors Capstones Projects - Archive
MobileCLIP is a compact model that connects images and text, enabling it to perform tasks like image identification and question answering without needing to be retrained for each new task. Although it’s designed to be lightweight, it still runs slowly on regular computers without a powerful graphics card (GPU). This research focuses on making MobileCLIP run faster and smaller by using post-training quantization, which reduces the model’s precision after training without hurting performance. We combined several strategies: analyzing which parts of the model are more sensitive to changes, applying targeted adjustments to its structure, and running everything using CPU-only tools. …
Improved Context For Llm Queries On Knowledge Graphs Using The Model Context Protocol, Talha Tahmid
Improved Context For Llm Queries On Knowledge Graphs Using The Model Context Protocol, Talha Tahmid
2025 Fall Honors Capstones Projects - Archive
Large Language Models (LLMs) struggle on factual, relation-heavy questions without structured external knowledge. This thesis implements a standards-based pipeline that connects LLMs to Resource Description Framework (RDF) knowledge graphs through the Model Context Protocol (MCP). The system comprises an MCP tool that executes SPARQL against approved endpoints, an Natural Language (NL) to SPARQL step in which the LLM (ChatGPT) generates the SPARQL query using prompt-based templates, followed by a generation stage conditioned on the retrieved graph facts. Final experiments focus on the Rhea knowledge graph. We evaluated the same base model with and without MCP on a 50-question benchmark spanning …
Deep-Learning Based Microstructure Reconstruction And Generation, Cameron J. Maloney, Lucas Taliaferro, Nina St. John
Deep-Learning Based Microstructure Reconstruction And Generation, Cameron J. Maloney, Lucas Taliaferro, Nina St. John
College of Engineering Summer Undergraduate Research Program
Microscopic imaging is essential to characterize multi-scale material behavior and understanding structure-property relationships. Recently our group developed a deep learning approach based on a Generative Adversarial Network (GAN) to reconstruct and artificially generate microstructures of strain-sensing nanomaterial networks based on microscope imagery. In this SURP project we would like to evaluate an alternative approach called diffusion to see if we can improve the quality of our results. Furthermore, we aim to test our approaches on a wider variety of materials, which will have different microstructures, to evaluate how versatile our models are.
Constructing A High-Performance Iot Pipeline For Smart Manufacturing Environments, Seth Langel
Constructing A High-Performance Iot Pipeline For Smart Manufacturing Environments, Seth Langel
College of Engineering Summer Undergraduate Research Program
The Fourth Industrial Revolution, or Industry 4.0, integrates a range of advanced technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Cloud Computing, and Data Analytics to improve the efficiency, productivity, scalability, and security of modern manufacturing systems. Smart manufacturing leverages these technologies across various domains to enhance data-driven decision-making and quality control in production processes. In a smart manufacturing environment, heterogeneous IoT sensors interact with each other and control systems to automate real-time monitoring, analysis, and decision-making. This integration enables manufacturers to optimize production, quickly detect and address anomalies, reduce environmental impact, and adapt rapidly to changing …
Ai-Powered Accessibility Tracker For Inclusive Public Spaces, Yenny Ma, Kevin Beltran
Ai-Powered Accessibility Tracker For Inclusive Public Spaces, Yenny Ma, Kevin Beltran
College of Engineering Summer Undergraduate Research Program
This research project will develop and evaluate a smartphone-based, AI-powered system to crowdsource and analyze accessibility features and barriers in public spaces. Using computer vision and geospatial mapping, the system will identify and categorize issues such as uneven sidewalks, missing or inadequate curb ramps, damaged tactile paving, obstructive overhangs, and the absence of visual or auditory wayfinding cues. The overarching goal is to generate a dynamic, real-time accessibility map that empowers individuals with diverse mobility, sensory, and cognitive needs to navigate public spaces more safely and confidently. The project will integrate technologies and methods from applied machine learning, mobile computer …
How Does User Control Reduce Irritation Of Mid-Roll Ads, Elijah Villanueva
How Does User Control Reduce Irritation Of Mid-Roll Ads, Elijah Villanueva
College of Engineering Summer Undergraduate Research Program
Large video platforms like YouTube and Twitch rely extensively on advertising for revenue. Often, they deploy mid-roll advertising: ads that play in the middle of video content, interrupting it. Such interruptions can irritate consumers significantly. This project primarily involves conducting user testing of an already-developed YouTube browser extension that that gives users some control over when mid-roll ads play. We hope to ascertain how effectively the design mitigates user irritation from mid-roll ads. Tasks will involve recruiting people into a laboratory setting where they will use the browser extension, interviewing them about their experience, and manually extracting themes from the …
Mastering Undergraduate Algorithms: Improving Problem-Solving Skills And Fluency Through Scaffolding Learning Modules, Anissa Soungpanya
Mastering Undergraduate Algorithms: Improving Problem-Solving Skills And Fluency Through Scaffolding Learning Modules, Anissa Soungpanya
College of Engineering Summer Undergraduate Research Program
The primary objective of the undergraduate algorithms course is to equip students with the ability to design and analyze algorithms, prove theorems about computation, and effectively communicate these algorithms and proofs to a human audience. In addition, the course aims to help students foster their fluency in the process of formulating and solving computational problems. Scaffolding exercises and activities that focus on these aspects could serve as useful learning tools in providing targeted feedback and helping students develop their confidence and fluency. To address the challenges that students encounter when solving algorithmic problems -- particularly in regard to problem decomposition …
Deep Learning In Eye-Tracking Biomarkers For Anomaly Detection, Jay Rajesh
Deep Learning In Eye-Tracking Biomarkers For Anomaly Detection, Jay Rajesh
College of Engineering Summer Undergraduate Research Program
This research project proposes the development of a novel, data-driven framework for detecting concussions using machine learning (ML) and deep learning (DL) models applied to high-resolution eye-tracking data. Unlike traditional concussion assessments that rely on subjective evaluations, this work seeks to identify objective, quantifiable biomarkers derived from ocular dynamics—such as saccadic velocity, smooth pursuit accuracy, and pupillary response—captured through advanced eye-tracking technology. The project will explore state-of-the-art feature extraction techniques and predictive modeling approaches to uncover subtle neuro-ocular signatures associated with mild traumatic brain injury. By combining principles from biomedical signal processing, artificial intelligence, and neurophysiology, this work advances current …
Reinforcement Learning For Autonomous Parking, Ravi Panchal
Reinforcement Learning For Autonomous Parking, Ravi Panchal
College of Engineering Summer Undergraduate Research Program
This research project proposes the development of an adaptive reinforcement learning (RL)-based parking system designed to handle complex parking maneuvers that are often unaddressed in existing research. Unlike previous works that focus on isolated maneuvers such as reverse parking or parallel parking, this work presents a flexible framework where multiple parking types (reverse, parallel, diagonal) are addressed through independent agents and then integrated into a cohesive system. The primary gap addressed by this work is the integration of diverse parking maneuvers into a unified RL framework with adaptability to dynamic and varied parking environments. Additionally, this project introduces curriculum learning …
Relational Algebra Interpreter, Sydney Lynch
Relational Algebra Interpreter, Sydney Lynch
College of Engineering Summer Undergraduate Research Program
We would like to build a compiler for relational algebra that converts it to SQL. This compiler will be used in database labs to give the students hands-on experience to write relational algebra code. Current relational algebra compilers that are open source are not very good and are hard for the students to use.
Hand-Tracking And Extended Reality Interfa, Alexander Bloomer, Alberto Cornejo
Hand-Tracking And Extended Reality Interfa, Alexander Bloomer, Alberto Cornejo
College of Engineering Summer Undergraduate Research Program
This project explores the use of Extended Reality (XR) technologies to enhance human- robot interaction in industrial contexts. Building upon prior research in affective and cognitive state recognition during human-cobot collaboration, this study investigates how natural hand and head gestures, captured through Meta Quest passthrough mode, can be used to communicate human intent to a Universal Robotics e-Series collaborative robot. The XR system provides users with an immersive, real-world visual interface while tracking motion and position in real time. The captured gestures are interpreted through a custom software pipeline that integrates machine learning models and rule-based logic to trigger adaptive …