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320 articles for “scalability challenges”
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Advanced Water Purification Techniques for Sustainable Clean Water Management: A Comprehensive Review
Abstract: The growing global demand for safe drinking water, coupled with increasing pollution from industrialization, urbanization, and agricultural activities, has intensified the need for efficient and sustainable water purification technologies. Conventional water treatment processes often fail to remove emerging contaminants such as pharmaceuticals, microplastics, endocrine-disrupting compounds, and heavy metals. Advanced water purification technologies—including membrane filtration, advanced oxidation processes (AOPs), nanotechnology-based adsorbents, photocatalysis, electrochemical treatment, and bio-inspired purification systems—have emerged as promising …
Published in Journal of Water Pollution & Purification Research · Vol. 13, Issue 1, 2026 · pp. 47–52 Read article
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Smart Energy Systems as a Solution for Sustainability
Abstract: This study examines the critical function of smart energy networks (SENs) in addressing the urgent global challenge of climate change. The study begins by elucidating the significant contributors to climate change, emphasizing the role of traditional energy sources, and underscores the need for a paradigm shift towards sustainable and cleaner alternatives. It explores the many facets of smart energy networks (SENs), including demand-side management, energy storage, smart grids, and the …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 1, Issue 2, 2023 · pp. 18–31 Read article
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CLA0D1T—Auditing AWS Services S3 and IAM
Abstract: The swift embrace of cloud computing has revolutionized how organizations handle and provide their services, delivering unmatched scalability, flexibility, and cost-effectiveness. However, this shift has also introduced a range of new security challenges and vulnerabilities, particularly concerning data access and identity management. This project specifically aims to address these issues within the context of Amazon Web Services (AWS), focusing on auditing the Simple Storage Service (S3) and Identity and Access …
Published in Journal Of Network security · Vol. 12, Issue 3, 2024 · pp. 1–12 Read article
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The Integration of AI Technologies in Automating Cyber Defense Mechanisms for Cloud Services
Abstract: The swift growth of cloud computing has transformed how organizations handle and store data, providing greater scalability and adaptability. However, the transition to cloud-based environments has heightened the complexity of cybersecurity challenges, especially in detecting and responding to security incidents. Conventional methods of incident response, which heavily depend on manual efforts, are no longer adequate to address the rapidly evolving and complex nature of modern cyber threats. This study explores …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 1–14 Read article
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AI and IoT in Sustainable Agriculture: A Review
Abstract: Artificial Intelligence (AI) and Internet of Things (IoT) integration have transformed the world of sustainable agriculture, presenting new ways of resource optimization, increasing crop yields, and making environmental sustainability more accessible. The current literature review analyzes the applications of AI and IoT in three significant agricultural systems: aquaponics, hydroponics, and poultry farming. By critically analyzing recent studies, this paper emphasizes how deep learning- enabled computer vision techniques allow for the …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 2, 2025 · pp. 32–45 Read article
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VERONICA: AI-Driven Edge System for Comprehensive Bike Safety and Assistance Through Multi-Source Data Fusion
Abstract: Road safety for bike riders remains a significant concern, with accident rates highlighting the need for advanced solutions to ensure rider protection and awareness. This paper presents “VERONICA: AI-Driven Edge System for Comprehensive Bike Safety and Assistance Through Multi-Source Data Fusion”, a voice-activated, continuously operating assistance system designed to provide real-time, intelligent solutions for various riding scenarios. VERONICA integrates accident detection, low-traffic route navigation, traction control advisories, and weather updates …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 09–17 Read article
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Polymer-Mediated Electron Transfer in Eco-Friendly P3HT–rGO Nanocomposites for Optoelectronic Applications
Abstract: Conducting polymer–graphene hybrid nanocomposites have emerged as promising materials for next-generation optoelectronic applications owing to their solution processability, tunable interfacial properties, and mechanical flexibility. Recent studies have highlighted the importance of graphene–polymer hybrid systems in enhancing charge transport pathways, exciton dissociation efficiency, and interfacial stability in organic optoelectronic devices. Despite these advantages, a key challenge remains the efficient production of individual graphene sheets through the reduction of graphene oxide using …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 413–423 Read article
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A Systematic Literature Review on Security Challenges in Cloud–Edge Hybrid Systems
Abstract: Cloud–edge hybrid systems have become a key framework in today’s distributed computing landscape, combining fast, near-source data processing at the edge with the flexible scalability and resource richness of centralized cloud infrastructures. However, this in- tegration introduces a complex security landscape where tradi- tional perimeter- based cloud security measures are insufficient for resource- constrained and physically exposed edge nodes. This literature review synthesizes findings from established research publications (2020–2025), focusing …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 Read article
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From Theory to Practice: The Mathematical Foundations of Secure Blockchain Transactions
Abstract: The rise of blockchain technology has transformed the method of conducting secure and decentralized transactions across multiple industries. At its core, blockchain relies on a robust mathematical foundation to ensure data integrity, transparency, and immutability. This paper delves into the theoretical underpinnings that make secure blockchain transactions possible, including cryptographic algorithms, distributed consensus protocols, and mathematical proofs of security. We begin by exploring the role of cryptography, particularly public-key encryption, …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 1, 2025 · pp. 13–20 Read article
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A Decentralized Approach to Online Voting: Leveraging Blockchain Technology
Abstract: The increasing need for secure and transparent voting systems has led to the exploration of blockchain technology as a solution for online voting. This paper presents an innovative approach to online voting using blockchain, aiming to enhance the integrity, security, and transparency of the electoral process. Because of the decentralized, tamper-proof ledger that blockchain technology offers, every vote is reliably recorded and unchangeable. This study outlines the design and implementation …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 · pp. 1–6 Read article
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Securing the Internet of Things: Challenges and Solutions in the Era of IIoT
Abstract: The manufacturing, healthcare, and transportation sectors have undergone revolutionary changes due to the swift growth of the Internet of Things (IoT) and its industrial cousin, the Industrial Internet of Things (IoT). However, this technological advancement comes with significant security challenges. The heterogeneity of devices, ranging from simple sensors to complex machinery, creates a diverse attack surface. Additionally, many IoT devices lack robust security features, often due to cost constraints or …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 2, 2024 · pp. 34–44 Read article
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Real-Time Cab Fare and ETA Prediction Using API Integration
Abstract: The exponential proliferation of ride-hailing platforms has necessitated the formulation of sophisticated and highly responsive predictive models for cab fare estimation and estimated time of arrival (ETA) computation. This work elucidates a robust framework leveraging real-time application programming interface (API) integration from Uber and Ola within a Flutter-based ecosystem to enhance predictive analytics. By assimilating real-time geospatial data, dynamic pricing algorithms, and latency-optimized API responses, this study investigates the empirical …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 08–15 Read article
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Decoding Big Data: A Practical Comparison Between Hadoop and Spark
Abstract: This paper conducts a comprehensive comparison of Apache Hadoop and Apache Spark, two essential frameworks in the big data era. The rapid expansion of data possesses challenges in terms of volume, variety, and velocity, which necessitate advanced processing solutions. Hadoop, utilizing its MapReduce paradigm, provides scalable and fault-tolerant storage, whereas Spark, built upon Hadoop, introduces in-memory processing to increase speed and flexibility. This study includes a detailed examination of their …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 3, 2024 · pp. 15–23 Read article
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Isolated Bidirectional Flyback Converter in EV Charging and V2G Systems: A State-of-the-Art-Review
Abstract: The growing adoption of electric vehicles (EVs) and the potential of Vehicle-to-Grid (V2G) technology underscore the importance of efficient and reliable isolated bidirectional DC-DC converters in EV charging systems. The market for electric vehicles (EVs) is expanding at an exponential rate due to the worldwide trend towards sustainable transportation, with electric mobility emerging as a crucial way to lower carbon emissions and rely less on fossil fuels. This review examines …
Published in International Journal of Electrical Power and Machine Systems · Vol. 2, Issue 2, 2024 · pp. 23–32 Read article
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Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article
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The Role and Functions of Computer Engineers
Abstract: Computer engineers play a crucial role in shaping the ever-evolving technological landscape by designing, developing, and optimizing computer systems and software. Their expertise spans various domains, including hardware design, embedded systems, software development, cybersecurity, and network architecture. These professionals contribute significantly to advancements across multiple industries, from healthcare and finance to telecommunications and artificial intelligence. This article delves into the diverse responsibilities of computer engineers, highlighting their involvement in problem-solving, …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 37–51 Read article
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Dynamic Modeling and Simulation of Multi-Body Mechanical Systems: A Comprehensive Review of Methods, Tools, and Applications
Abstract: The dynamic modeling and simulation of multi-body mechanical systems (MBS) form a cornerstone in modern mechanical engineering, enabling in-depth analysis of the kinematic and kinetic behaviors of interconnected rigid and flexible components. MBS are foundational to a range of critical applications, from automotive suspensions and aerospace mechanisms to robotics and biomechanical structures. As system complexity and performance requirements increase, accurate and scalable modeling techniques are essential for both design validation …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 1, 2025 · pp. 35–42 Read article
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Melanoma Skin Cancer Detection Using Deep Learning
Abstract: Cancer as one of the major diseases rank in the World is still very challenging to diagnose and treat hence need for the technological advancements. Chemotherapy, radiation, as well as surgery therapies have several drawbacks including non-selective action, damage to healthy tissues, and multi-drug resistance. Smart nano-theranostics, an advanced integration of nanotechnology with diagnostic and therapeutic modalities, offers a next-generation approach for precision oncology. Thus, the development of multifunctional nanoparticles …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
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Data Compression for Backbone Network
Abstract: This article involves the application of data compression techniques to improve the efficiency and performance of the core infrastructure of modern digital networks. This approach focuses on reducing the size of transmitted data without compromising its quality, aiming to enhance network throughput, reduce latency, and minimize energy consumption. The study also considers practical implementation challenges and trade-offs to optimize resource utilization in backbone networks. We delve into various compression methods, …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 1, 2024 · pp. 30–40 Read article
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Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article