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224 articles for “Inherent”
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Privacy Preservation Methods in Multimedia Applications: A Comprehensive Review
Abstract: This comprehensive review explores the current landscape of privacy preservation techniques in multimedia applications, offering a detailed examination of their effectiveness, limitations, and future directions. As the use of multimedia data continues to grow across diverse sectors such as healthcare, surveillance, social media, and entertainment, ensuring the confidentiality and integrity of this data has become a pressing concern. The study covers a broad spectrum of privacy-preserving approaches, from conventional cryptographic …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 33–41 Read article
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Strategies for Efficient Integration of Distributed Energy Resources into Microgrid Systems
Abstract: With the growing integration of Distributed Energy Resources into modern power systems, the global energy landscape is changing. Some of the DERs are solar photovoltaic (PV), wind turbines, battery storage systems, combined heat and power (CHP) units, and electric vehicles (EVs). Some of the advantages include lower transmission losses, better energy efficiency, and more resilience to grid failures. However, the far-reaching integration of DERs carries with it considerable technical, economic, …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 51–56 Read article
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Building Scalable Microservices with Micronaut, Kotlin, and AWS DynamoDB: A Comprehensive Architecture Study
Abstract: The evolution of enterprise software has trended steadily toward microservice architectures due to their inherent scalability and resilience advantages over monolithic systems. This research explores a comprehensive implementation approach using Micronaut, an innovative JVM-based framework specifically designed for resource-efficient microservices. The study combines Micronaut with Kotlin programming language and leverages AWS DynamoDB as a scalable NoSQL persistence layer, with Apache Kafka providing event-driven communication capabilities. We explore the critical role …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 40–57 Read article
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Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article
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Investigation of Mechanical Properties of Hollow Bricks Incorporating Aerated Aggregates: A Polymer-Cement Composite Approach
Abstract: The rapid advancement of construction technologies has necessitated the development of lightweight, thermally efficient, and sustainable building materials. Hollow bricks, due to their inherent voids, offer substantial reductions in dead load and enhanced insulation properties. However, their mechanical performance often falls short when compared to conventional solid bricks. To address this limitation, this study explores the synergistic integration of aerated aggregates and polymer-cement composites (PCCs) in hollow brick production. Aerated …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 92–105 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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Fuzzy Probability Distributions and Their Applications in Uncertain Data Analysis
Abstract: This study explores the use of fuzzy probability distributions in data analysis under uncertain conditions, with a specific focus on their implementation in evaluating call center customer satisfaction. Traditional probability models rely on precise parameters, often failing to account for the inherent variability and subjectivity present in real-world data. In contrast, fuzzy probability distributions, which integrate fuzzy logic principles, offer a more adaptable and realistic framework for addressing such complexities. …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
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Robust Access Control Mechanisms Using VHDL Programming for IoT Security
Abstract: The Internet of Things (IoT) devices are increasingly becoming targets for criminal actors. A compromised device can result in data breaches, denial-of-service attacks, and even physical damage. While software-based security solutions are important, they are susceptible to attacks and often impose significant overhead, negatively impacting both performance and battery life. A viable alternative is provided by hardware-based security, which takes advantage of the inherent security benefits that are associated with …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 2, 2025 · pp. 6–1`9 Read article
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Support Vector Machine Inspired Load Forecasting of a State University in Haryana
Abstract: Estimating the possible environmental impact and determining probable capital requirements are made easier with a solid grasp of electricity demand. Beginning in the middle of the 20th century, demand forecasting for electric power networks was studied theoretically. Prior to that, the study of demand forecasting had not developed because of the small scale of power networks. With the use of statistical prediction techniques, plans for the electric power industry have …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 33–40 Read article
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Comprehensive Review of Adenoid Cystic Carcinoma: Pathogenesis, Diagnosis, and Emerging Therapeutic Approaches
Abstract: Adenoid cystic carcinoma (ACC)is an infrequent neoplasm, highly malignant, that develops mainly in the salivary glands with the potential to exist in any secretory glandular sites, including the lacrimal glands, breast, and respiratory tract. ACC usually has a benign initial course, but conversely, it is notoriously aggressive in behavior with high incidence of perineural invasion, local recurrence, and distant metastasis, mostly to the lungs. The tumor’s molecular features are characterized …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–17 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Advancing Gene Therapy: Next-Generation Viral Vector Engineering for Precision, Safety, and Scalability
Abstract: Gene therapy has emerged as a paradigm-shifting modality for the treatment of genetic disorders, malignancies, and rare diseases through the delivery of therapeutic nucleic acids aimed at correcting or modulating dysfunctional gene expression. Among the various delivery systems, viral vectors including adeno-associated viruses (AAVs), lentiviruses, adenoviruses, retroviruses, and herpes simplex viruses have proven indispensable owing to their high transduction efficiencies and adaptability. This review offers a comprehensive assessment of viral …
Published in International Journal of Virus Studies · Vol. 2, Issue 2, 2025 · pp. 37–55 Read article
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Influence of Hybrid Fiber Reinforcement on the Interfacial Bonding and Fracture Toughness of Epoxy-Based Polymer Composites Under Cyclic Loading
Abstract: This study investigates the influence of hybrid fiber reinforcement on the interfacial bonding and fracture toughness of epoxy-based polymer composites under cyclic loading. Carbon, glass, and aramid fibers, both individually and in hybrid combinations, were incorporated into the epoxy matrix to evaluate their thermal, mechanical, and fatigue-resistant properties. Thermal characterization revealed distinct material behaviors, with carbon fibers exhibiting superior thermal conductivity, while glass and aramid fibers provided enhanced thermal stability. …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 799–824 Read article
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Evaluating the Performance of Test Cricket Players Using Principal Component Analysis and the Weighted Average Method
Abstract: This study evaluates cricket player performance using Principal Component Analysis (PCA) and a weighted average approach. In order to achieve this, we analyzed detailed batting and bowling datasets from the International Cricket Council (ICC) to calculate player performance based on various performance indicators. The datasets included comprehensive statistics from multiple matches and tournaments, allowing for an in-depth evaluation of players’ skills and contributions. PCA ranked players according to their participation …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 20–30 Read article
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Blockchain Enabled Security Framework: Smart Healthcare
Abstract: To explores the transformative potential of blockchain technology in managing, securing, and ensuring the integrity of Electronic Health Records (EHRs). EHRs, which store vital patient information such as medical histories, diagnoses, prescriptions, and imaging results, are essential for enhancing healthcare delivery. Conventional centralized Electronic Health Record (EHR) systems encounter issues such as susceptibility to single points of failure, security risks, and constraints in maintaining data integrity. By leveraging blockchain’s inherent …
Published in Journal Of Network security · Vol. 13, Issue 3, 2025 · pp. 11–17 Read article
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Analysis of Friction Stir Welding Utilizing ANSYS: A Study Based on Simulation
Abstract: Friction Stir Welding (FSW) represents a sophisticated solid-state welding methodology that has attracted considerable scholarly attention due to its efficacy in amalgamating high-strength, lightweight substrates including aluminium, magnesium, and titanium alloys. FSW enables the fabrication of defect free products with a substantial amount of mechanical and wear properties. The process is highly sensitive to various parameters that significantly influence the quality and strength of the final product. Studies have shown …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 62–77 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
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A Study on Unmanned Air Vehicles (UAV)
Abstract: Unmanned Air Vehicles (UAVs), commonly known as drones, represent one of the most transformative technologies of the 21st century, rapidly evolving from their initial military applications into a diverse array of civilian and commercial uses. This study explores the rapid proliferation of UAV technology, highlighting its profound impact across sectors such as logistics, agriculture, infrastructure inspection, communication, and public safety. We discuss the inherent advantages UAVs offer, including enhanced efficiency, …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 24–36 Read article
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Challenges of Upgrading Local Cattle with Exotic Breeds: Genetic, Environmental, Economic, and Sustainability Trade-offs
Abstract: The practice of upgrading local cattle with exotic breeds has gained popularity as a strategy to enhance milk and meat production. While this approach holds potential for improving productivity, it also presents a range of challenges that need careful consideration. This study examines the genetic, environmental, economic, and sustainability trade-offs associated with upgrading local cattle with exotic breeds. From a genetic perspective, upgrading can result in the dilution of traits …
Published in International Journal of Molecular Biotechnological Research · Vol. 3, Issue 2, 2025 Read article
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Homeopathy and Miasms: Exploring Their Vital Importance
Abstract: An individual’s susceptibility to disease is not solely an internal matter but is also profoundly shaped by a variety of external influences. These influences can be broadly categorized into meteoric factors – such as climate, weather changes, seasonal variations, and atmospheric conditions – and telluric factors, which include environmental and terrestrial elements like soil, water, living conditions, and geographical surroundings. When such external influences act upon the human organism, they …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 12, Issue 3, 2025 · pp. 16–21 Read article