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24 articles for “real-world scenarios”
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Reinforcement Learning in Real World Application: A Study on Robotics; Autonomous Vehicles and Industrial Automation
Abstract: This research paper investigates the practical application of reinforcement learning (RL) in three critical domains: robotics, autonomous vehicles, and industrial automation. The study delves into the implementation of RL algorithms to enhance decision-making, adaptability, and autonomy in these real-world scenarios. Through a comprehensive review of existing literature, methodologies, and case studies, the paper addresses the challenges faced and the successes achieved in deploying RL in each domain. The findings offer …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 1, Issue 3, 2023 · pp. 1–15 Read article
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Primality Testing: A Comprehensive Analysis of Methods and Time Complexity
Abstract: This paper examines various primality testing algorithms and analyzes their time complexity. The algorithms we examine include the trial division, which is straightforward but becomes inefficient with large numbers; Fermat’s little theorem which is a probabilistic method included in Monte Carlo type of randomized algorithm; the Solovay–Strassen, based on properties from number theory, particularly those related to Euler’s criterion and Jacobi symbols; and the Miller–Rabin Probabilistic Test, which balances efficiency …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 25–31 Read article
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Advancements in Data Structures: Bridging the Gap Between Theory and Real-world Applications
Abstract: In the rapidly advancing landscape of computer science, this study unfolds a comprehensive exploration of Data Structures, spanning from foundational principles to cutting-edge innovations. Data structures form the backbone of computational processes, and this study aims to dissect and illuminate their pivotal role. Beginning with fundamental concepts such as Arrays, Linked Lists, Stacks, and Queues, the narrative progresses to intricate structures like Trees, Graphs, and Hash Tables. Practical applications in …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Real-time Mask Detector (Monitoring COVID-19)
Abstract: This study presents the development and implementation of a real-time mask detection system designed to monitor and enforce mask-wearing policies during the COVID-19 pandemic. Utilizing a convolutional neural network (CNN) and a dataset consisting of annotated images, our system can accurately detect the presence or absence of masks on individuals in various environments. The proposed system achieves high accuracy and can be deployed in public spaces to help mitigate the …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 2, 2024 · pp. 42–49 Read article
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Mathematical Modeling of Epidemics Using Stochastic Differential Equations: A Review
Abstract: The accurate modeling of infectious disease dynamics is crucial for predicting outbreaks and informing public health interventions. While deterministic models such as the SIR (Susceptible-Infected-Recovered) framework have traditionally been used to understand disease transmission, they often fail to account for the randomness inherent in real-world scenarios. Disease spread is influenced by numerous uncertain factors, including individual behavioral changes, environmental fluctuations, and imperfect data reporting. These uncertainties can significantly impact model …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 1–6 Read article
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Novel Perspectives in Quantum Safe Crypto algorithms for Enhanced Cyber Security
Abstract: This paper explores novel perspectives in quantum-safe cryptographic algorithms to bolster cybersecurity in the face of impending quantum computing advancements. Due to the efficient resolution of intricate mathematical problems by quantum computers, posing a substantial threat to existing cryptographic systems, there is a pressing requirement to create resilient alternatives. This study delves into innovative approaches, drawing from quantum-resistant cryptographic primitives, lattice-based cryptography, code-based cryptography, and hash-based cryptography. By examining the …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 18–22 Read article
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An Investigative Study of Quantum-safe Secure Multi-party Computation
Abstract: This article represents the comprehensive investigation in the emerging field of quantum-safe secure multi-party computation (QSSMPC) and presents novel perspectives to address the impending threat posed by quantum computers to classical cryptographic systems. As the era of quantum computing approaches, traditional encryption methods become vulnerable to quantum algorithms, necessitating the development of quantum-resistant cryptographic protocols. In this context, the paper introduces innovative approaches to secure multi-party computation in a quantum-safe …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 1, 2024 · pp. 39–44 Read article
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(𝛅,Ü ) Convex Structure on Partial B-Metric Space Concerning Quasi Contraction and Fixed-Point Results
Abstract: This work introduces the concept of (δ,Ü )– Convex Partial b-Metric Spaces using convex structure. Motivated by this approach, we demonstrated fixed point results and their uniqueness, as well as quasi contraction, and provided some supporting instances for the established results. Our findings expand prior fixed-point results to a novel concept (δ,Ü )– Convex Partial b-Metric Spaces. To support our theoretical findings, we provide several instances that exemplify the established …
Published in Recent Trends in Mathematics · Vol. 1, Issue 1, 2024 Read article
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Ensuring Data Traceability Across Multiple Cloud Environments
Abstract: This study investigates the challenges and solutions for ensuring data traceability across multiple cloud environments. With organizations' increasing reliance on cloud infrastructure, maintaining data traceability is crucial for compliance, data integrity, and secure data management. The diversity of cloud systems, spanning public, private, and hybrid models, introduces complexities in tracking data lineage, access, and movement. This study delves into multi-cloud strategies' technical and operational hurdles, such as varying data formats, …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 08–22 Read article
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Investigations of Mechanical Testing and its Effects on Lithium Ion Battery and Battery Pack for Electric Vehicle Application
Abstract: This research delves into the comprehensive study of mechanical testing methodologies and their consequential impact on the structural integrity, safety, and performance of Lithium-Ion batteries (Li-ion) and battery packs designed for electric vehicle (EV) applications. The investigation aims to enhance the understanding of mechanical stressors' influence on the reliability and safety of energy storage systems crucial for the sustainable advancement of electric mobility. The paper opens with mechanical testing protocols …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 2, 2024 · pp. 35–49 Read article
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Advancements in Humanoid Robot Locomotion: A Review of Control Strategies and Kinematic Models
Abstract: Humanoid robot locomotion has significantly improved over the past few decades, driven by improvements in control strategies and kinematic models. Researchers aim to develop robots that can walk, run, and navigate complex terrains with efficiency and stability. This review explores recent developments in humanoid locomotion, highlighting control strategies such as model predictive control, reinforcement learning, and central pattern generators. Additionally, it examines kinematic models, including inverted pendulum models and zero …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
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Phase – Field Modeling of Brittle and Ductile Fracture Under Complex Loading Conditions
Abstract: Phase-field modeling has emerged as a powerful computational framework for predicting fracture behavior in engineering materials, offering a unified description of crack initiation, propagation, branching, and coalescence without the need for explicit crack tracking. This study presents an in-depth examination of phase-field modeling applied to both brittle and ductile fracture under complex loading conditions, including multiaxial stress states, cyclic loading, thermal gradients, and dynamic impact. The phase-field approach regularizes the …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 3, Issue 2, 2025 · pp. 13–18 Read article
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Development and implementation of Solar-Thermoelectric Hybrid Energy Harvester
Abstract: In today’s consumer-oriented and technology-driven market, researchers are increasingly emphasizing the need to harvest energy from ambient and renewable sources to support sustainable power generation and to minimize dependence on conventional energy resources such as batteries and fossil-fuel-based electricity. The rising deployment of portable electronics, wireless sensor networks, and Internet of Things (IoT) devices has created an urgent demand for compact, low-power, long-life, and maintenance-free energy solutions. In many real-world …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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AI-Driven Robotics for Sustainable Solutions in Disaster Management
Abstract: Disasters, whether natural or man-made, present significant challenges to societies worldwide. Efficient response, recovery, and mitigation strategies are crucial to minimizing human suffering, loss of life, and economic damage. Traditional disaster management strategies, while effective to some degree, often face limitations related to human resources, response time, accessibility, and safety. The integration of artificial intelligence (AI) and robotics into disaster management offers transformative potential for overcoming these challenges. This paper …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 1, 2025 · pp. 24–30 Read article
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Comprehensive Comparative Analysis of Intrusion Detection Systems: Evaluating Signature Based, Anomaly Based, and Hybrid Approaches
Abstract: In the fast-changing world of cybersecurity, Intrusion Detection Systems (IDS) play a vital role in protecting digital resources. This study offers an in-depth comparative analysis to evaluate the efficiency and performance of different IDS solutions. It examines a variety of both commercial and opensource platforms, encompassing signature based, anomaly based, and hybrid models, to assess their effectiveness in identifying and responding to a wide range of cyber threats. Methodologies for …
Published in International Journal of Information Security Engineering · Vol. 3, Issue 2, 2025 · pp. 39–44 Read article
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Optimizing Cellular Manufacturing Systems: Minimizing Production Time with Collaborative Robots (Cobots) using PSO
Abstract: This study focuses on the implementation of cobots in a cellular manufacturing system to minimize production time. The use of cobots, collaborative robots capable of working alongside human operators, aims to increase efficiency and reduce manual labor in the manufacturing process. The mathematical model presented in this research evaluates the impact of cobots on production time by considering various factors, including task times, machine setup, inspection, waiting, and idle times. …
Published in International Journal of Industrial and Product Design Engineering · Vol. 1, Issue 1, 2023 · pp. 22–27 Read article
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AI-Powered Emotion Recognition in Dog
Abstract: Understanding animal emotions is important for improving veterinary care, human animal interaction, and overall pet well-being. Inspired by previous research that utilized a modified EfficientNetB5 model for emotion classification in cats and dogs, our study builds upon this foundation with a focus on real-time emotion recognition in dogs. While earlier approaches achieved high accuracy using Dense Residual and Squeeze-and-Excitation blocks, they often lacked real-time applicability and were not optimized for …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 20–32 Read article
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Reaching Conditions for Discrete-time Sliding Mode Control: Analysis and Design
Abstract: Sliding mode control (SMC) is a robust control method widely used in engineering due to its ability to handle uncertainties and disturbances effectively. In discrete-time sliding mode control (DSMC), system trajectories are constrained to sliding surfaces in the state space, leading to improved performance and stability. This paper provides an overview of DSMC, focusing on its applications, advantages, and limitations. It discusses the use of DSMC in various engineering fields …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 1, 2024 · pp. 7–14 Read article
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How small circuits power big technology in the world of VSIL
Abstract: Very Small Integration Level (VSIL) circuit technology represents an emerging class of ultra- compact, low-power electronic design methodologies that enable the creation of highly efficient and scalable systems. This article explores the fundamental principles behind VSIL circuits, including device miniaturization, optimized layout strategies, adaptive power management, and noise-resilient architectures. We also look into the methodical engineering of VSIL circuits to satisfy the ever-tougher performance, robustness, and long- term energy-efficiency demands …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 44–53 Read article
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Role of Generative AI in Redefining Data Analytics
Abstract: The rapid evolution of data-driven technologies has introduced both significant challenges and promising opportunities within the field of data analytics. Among the most impactful advancements is Generative Artificial Intelligence (Generative AI), a groundbreaking subset of AI that is reshaping how data is interpreted, generated, and utilized. Unlike traditional analytical tools that rely solely on existing data patterns, generative AI possesses the capability to create synthetic data, simulate complex scenarios, and …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 01–07 Read article