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261 articles for “Deep complex”
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Advanced Lithium-Ion Battery Prognostics: A Comprehensive Review of Machine Learning Approaches for Remaining Useful Life Prediction
Abstract: The lithium-ion battery (LIB), as one of the main sources for portable power systems, has been increasingly popular owing to its widespread applications in electric vehicles, consumer electronics, aerospace and renewable energy. Despite their advantages in high energy density and long cycle life, LIBs suffer from degradation over time of aging and cycling, resulting in loss of performance, safety issues, and economic bottlenecks. Predicting their Remaining Useful Life (RUL) is …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 3, Issue 2, 2025 · pp. 12–27 Read article
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Investigative Study of Relationship of Chemical Characteristics of Group V Elements and Electron Structure
Abstract: Understanding the chemical properties of Group V elements through their electron configurations deepens our comprehension of periodic trends. Transitioning from nitrogen to bismuth, we observe a shift from non-metals to metalloids and then to metals, a change driven by the progression of electron shell and orbital filling. This insight is crucial for forecasting and elucidating the varied chemical behaviors and uses of Group V elements, thereby aiding developments in chemistry …
Published in Journal of Materials & Metallurgical Engineering · Vol. 15, Issue 2, 2025 · pp. 39–45 Read article
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ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
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The Role of Adaptive Filters in Enhancing Acoustic Echo Cancellation Efficiency in Noisy Environments
Abstract: The novel approach that this work discusses is a DCD-based iterative learning filter approach improved with deep learning methodologies, designed to improve the efficiency of acoustic echo cancellation. The proposed system can really manage both linear and nonlinear echo scenarios, dynamically adapting to fluctuating acoustic environments. The above comparative evaluations with standard filter, the standard RLS filter, indicate that the mean square error, and the standard deviation of the correlation …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 2, 2024 · pp. 9–24 Read article
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Zero Trust Implementation Challenges in Legacy and Wireless Network Systems
Abstract: This article titled "Zero Trust Implementation Challenges in Legacy Systems and Wireless Network Systems" delves into the evolving landscape of cybersecurity, emphasizing the inadequacy of traditional perimeter-based security models in the face of modern cyber threats. The Zero Trust Security framework is highlighted as an essential advancement in this scenario, emphasizing the core idea of "never trust, always verify." This paradigm shift underscores the importance of continuous verification, least privilege …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 1, 2025 · pp. 39–50 Read article
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An Analysis of Graph Database in Data Modelling and Analysis for a Recommendation System
Abstract: This research work focuses on graph databases, mainly Neo4j databases, in recommendation systems for e-commerce websites. The importance of research is that it explains how graph databases efficiently handle the complex relationship between user-items, which is difficult for traditional databases. Sparsity, limited diversity, and high setup costs are the challenges traditional databases face. This research work overcomes these problems using Ne04j with Cypher query language and graph algorithms (PageRank, Shortest …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 33–39 Read article
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Deep Learning based Solution for Leaf disease Detection in Crops and Fertilizer Recommendation
Abstract: The field of agriculture faces significant threats, including diseases that attack plant leaves. To address this issue, our system assists farmers in promptly detecting plant diseases using advanced technology. The user, typically a farmer, only needs to capture an image of the affected leaf and input it into our system. Our system then analyzes the uploaded image to accurately identify the specific disease afflicting the leaf. This analytical process is …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 31–40 Read article
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Immunology and Immunotherapy of Pulmonary adenocarcinoma: A Systematic Review
Abstract: Lung cancer is the world's second leading cause of death, with an estimated 9.6 million deaths in 2018. Approximately 80% of all lung cancer is caused by non-small cell lung cancer (NSCLC). Due to lack of early detection and treatment, the incidence rate of lung cancer prognosis remains low. CD4+T-lymphocytes, macrophages, dendritic cells, and natural killer cells are among the immune cells involved in the pathogenesis of lung cancer. The …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 11, Issue 2, 2022 · pp. 15–25 Read article
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Study of Pros and Cons of Today’s Modern Operating System
Abstract: This research paper delves into the intricate realm of modern computer systems, which serve as the backbone of our daily digital interactions. These systems play a crucial role in powering the devices we rely on, from smartphones and tablets to laptops and desktop computers. By examining the positives and challenges inherent in these systems, this paper aims to shed light on their profound impact on our digital lives. One key …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 1, 2024 · pp. 17–23 Read article
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Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Evaluating Linezolid: A Comprehensive Analysis
Abstract: Treatments for infections caused by Gram-positive bacteria, such as methicillin-resistant staphylococci and VRE, including skin and soft tissue infections, community-acquired pneumonia, and other infections treated with linezolid, an oxazolidinone antimicrobial agent that functions by specifically inhibiting protein synthesis. Even while antibiotic resistance is becoming more frequent in many nations, linezolid resistance among these pathogens is still low, typically less than 1%. Thus, the emergence of resistance in clinical isolates should …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 11, Issue 2, 2024 · pp. 11–16 Read article
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Artificial Intelligence in Image Recognition: Context of Machine Vision
Abstract: The machine learning discipline is as old as decades, but some problems such as image recognition, location detection, image classification, image generation, speech recognition, and natural language processing cannot be solved. Image classification studies are another basic, most classic and essential line of research in deep learning. Computer intelligent recognition of the images technology has enabled a gradual reaction (updating) to foreign measurement trends, which promotes advancement of different areas …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 01–06 Read article
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Matriarchal Influence and Spiritual Identity: Exploring Women's Spirituality in Young Sheldon
Abstract: The study analyzes the TV series Young Sheldon (2017–2024) through maternal and spiritual feminism. It is a prequel to The Big Bang Theory, set in the 1980s. It is based on a ten-year-old Sheldon’s struggles to adjust to his environment. It aims to examine the study critically, emphasizing the role of his mother and her maternal and spiritual practices through episodes of seasons one to five. The study works on …
Published in Emerging Trends in Languages · Vol. 2, Issue 2, 2025 · pp. 33–43 Read article
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Role of Carbohydrates and Herbal Plants in the Management of Diabetes Mellitus
Abstract: This extensive review explores the intricate relationship between carbohydrates and diabetes mellitus, integrating historical perspectives, biochemical foundations, and modern therapeutic approaches. The article delves into the chemistry of carbohydrates, elucidating their structural diversity and metabolic significance in relation to diabetes pathophysiology. It traces the evolution of diabetes, understanding from ancient civilizations to contemporary molecular insights, highlighting pivotal discoveries such as insulin’s identification. They critically examined various forms of diabetes, including …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 1, 2025 · pp. 34–60 Read article
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Mathematical Approaches to Nonlinear Oscillatory Systems with Damping: Exact and Approximate Solutions
Abstract: The study of nonlinear oscillatory systems with damping is a key area of research in applied mathematics, particularly in the context of dynamical systems, stability analysis, and bifurcation theory. These systems, described by second-order nonlinear differential equations, exhibit a rich variety of behaviors, including periodic, quasi-periodic, and chaotic motions. The introduction of damping—representing energy dissipation—adds a layer of complexity, making the analytical and numerical solution of such systems a challenging …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 7–11 Read article
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AI and Machine Learning Approaches for Estimating Depression Severity: Techniques, Trends, and Applications
Abstract: Depression is a very common mental health disorder that results in a disorder of a person’s behavior, emotions, and cognitive abilities. Depression can be caused by environmental factors or hereditary factors. The person suffering from depression might have symptoms of suicidal thoughts, altering food patterns as well as sleeping issues. Depression is a global issue that has impacted millions of people globally having more effect on women worldwide. The complexity …
Published in Journal of Electronic Design Technology · Vol. 15, Issue 3, 2024 · pp. 29–38 Read article
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AI, Robotics, and the Future of Waste Management: A Systematic Review of Advanced Collection and Sorting Systems
Abstract: The rapid growth of cities and rise in population have made waste management a major concern that calls for innovative and efficient solutions. Conventional waste collecting techniques are dangerous, time-consuming, and frequently ineffective. The development of automated waste management systems powered by cutting-edge technology like robotics, deep learning, artificial intelligence (AI), and the Internet of Things (IoT) is examined in this study. Vision-based systems, convolutional neural networks (CNN) for garbage …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 1, 2025 · pp. 1–6 Read article
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A Survey On Leveraging Machine Learning for Phishing Attack Prediction and Detection
Abstract: Phishing is one of the biggest cybersecurity threats that exploits user trust by masquerading as a legitimate site or email to steal personal and sensitive information. A state- of-the-art-phishing detection systems survey, this review showcases the evolution from traditional list-based techniques, including blacklisting and whitelisting to machine learning and deep learning models. While list-based systems cannot evolve to detect new and zero-day attacks, the ML algorithms of Decision Tree, Random …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 3, 2025 · pp. 1–10 Read article
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Machine Learning Based Optimization of Polymer Structure Property Relationships in Composite Material Systems
Abstract: In modern engineering applications, polymer-based composite materials have garnered a lot of attention because of their lightweight nature, high strength-to-weight ratio, and changing physical features. In order to maximize the relationships between polymer structure and properties in composite materials, this study suggests a strategy based on reinforcement learning (RL). The research utilized the Polymer Composite Properties Dataset, which contains 12,700 records associated with polymer matrices, reinforcement fillers, interfacial bonding characteristics, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 242–255 Read article
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Harnessing NLP for Automation and Intelligence Across Sectors
Abstract: Natural Language Processing or NLP is a vital subset of Artificial Intelligence or AI which enables machines to interpret, understand, and communicate using human language in a remarkable way. From the traditional rule-based approaches to the modern advanced deep learning techniques such as transformers, neural networks, and hybrid models, NLP has been evolving year by year. This study reflects on various applications of NLP, including sentiment analysis, machine translation, analysis …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 23–32 Read article