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1974 articles for “ITS approach” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Polymer Chemistry-Driven Approaches for Improved Therapeutic Delivery
Abstract: Polymer chemistry has revolutionized pharmaceutical technology by enabling the development of advanced drug delivery systems with improved precision, stability, and therapeutic outcomes. This review explores the role of polymer design, synthesis, and functionalization in the development of responsive and targeted drug carriers. Emphasis is placed on various types of polymers—biodegradable, synthetic, natural, and stimuli-responsive—and their suitability for drug delivery platforms such as nanoparticles, micelles, hydrogels, dendrimers, and implants. The physicochemical …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 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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Formulation and Evaluation of Polyherbal Soap with Antibacterial and Dermatological Benefits: A Polymer Chemistry Approach
Abstract: This study investigates the formulation and evaluation of polyherbal soap composed of extracts from Vitex negundo, Azadirachta indica, and Curcuma longa. These plants possess significant antibacterial, dermatological, and skin-nourishing properties. The soap formulation follows a saponification process using coconut oil and sodium hydroxide as primary reactants, incorporating polymer chemistry principles in soap structuring and stability. Polymers such as polysaccharides and fatty acid chains contribute to the stability, viscosity, and foaming …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 158–164 Read article
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An Experimental Study on Multi-Criteria Parameters Optimization of Process for Al6351/SiC/Gr Metal Matrix Composites Using AHP-TOPSIS Approach
Abstract: This research focuses on optimizing the process parameters of Wire Electrical Discharge Machining (WEDM) for a hybrid Metal Matrix Composite (MMC) comprising Al6351 aluminum alloy reinforced with 4% SiC and 6% graphite (Gr), fabricated via squeeze casting. This technique enables the formation of dense, defect-free composites with uniform reinforcement distribution, enhancing both mechanical properties and structural integrity. Microstructural characterization using Scanning Electron Microscopy (SEM) confirmed the even dispersion and bonding …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 303–319 Read article
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Codal Validation and Optimization of Gantry Girders Under Variable Wheelbase and Impact Loads: A Review of Analytical, Numerical, and Codal Approaches
Abstract: Gantry girders serve as critical structural elements in industrial facilities such as steel plants, workshops, and heavy manufacturing units, where electric overhead traveling (EOT) cranes operate. The design of these girders is governed by stringent codal provisions to ensure safety under bending, shear, and deflection. However, discrepancies between codal predictions, analytical formulations, and finite element analysis (FEA) results, particularly under variable wheelbase and dynamic impact loads, have been widely reported. …
Published in Journal of Offshore Structure and Technology · Vol. 12, Issue 3, 2025 · pp. 23–29 Read article
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Catalytic Degradation of Polymers Using Metal Oxides (Zno, Cuo): A Sustainable Approach
Abstract: The growing accumulation of synthetic polymeric waste, especially plastics, has become one of the most pressing environmental challenges due to their non-biodegradable nature and long-lasting presence in ecosystems. This issue is compounded by the widespread use of plastic materials in various industries, resulting in vast amounts of plastic waste that contribute to environmental pollution, clog waterways, and pose threats to wildlife. As global plastic production continues to rise, the need …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 1052–1062 Read article
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Physico-Chemical Soil Analysis: A Scientific Approach to Life on Land and Terrestrial Ecosystem Conservation for Supporting SDG 15 Goals
Abstract: Soil health and fertility evaluation are foundational elements in the sustainable management of ecosystems and the enhancement of agricultural productivity. Accurate assessment of soil properties, especially Carbon (C), Nitrogen (N), and Phosphorus (P), is critical for informed decision-making in agriculture and environmental conservation. However, traditional laboratory methods for analyzing these essential nutrients often involve significant resource allocation and time commitments, making them less practical for large-scale or time-sensitive applications. To …
Published in Journal of Geotechnical Engineering · Vol. 12, Issue 1, 2025 · pp. 25–23 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Optical Image Sensing and Analysis of Iron Ore Pellets: A Machine Learning Approach
Abstract: The present work is aimed to improve quality control in steel production using SEM imaging and machine learning. High-resolution SEM images of iron ore pellets, primarily composed of hematite and magnetite, are analyzed to understand their microstructural features, which significantly impact pellet performance during reduction processes. Traditional microstructure analysis is manual, time- consuming, and prone to inconsistencies. This study proposes an automated approach using K-Means Clustering, Canny Edge Detection, DBSCAN, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 7–18 Read article
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Gradient Boosted Regression Tree Approach to Predicting Toxic Interactions on X and YouTube
Abstract: In the digital age, social media platforms play a vital role in facilitating user engagement, encompassing both positive interactions and avenues for negative, often harmful behaviors. Recognizing and addressing toxic exchanges is paramount to nurturing healthy online communities and preserving users’ well-being. This study introduces a novel method for identifying toxic interactions by utilizing Gradient Boosting Regression Trees (GBRT) algorithm, a machine learning approach renowned for its exceptional accuracy and …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 3, 2025 · pp. 7–14 Read article
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Stacked Generalization-Based Deep Learning Approach for Pneumonia Detection
Abstract: The proposed work focuses on a stacked generalization-based approach for diagnosing pneumonia from chest X-ray images. It utilizes regularization, early stopping, and data augmentation to deal with overfitting. It uses safe level SMOTE to deal with class imbalance and attention-based feature fusion to adaptively weigh features based on their importance. It uses two publicly available datasets (RSNA and Kermany) with ground truth provided by expert radiologists. The proposed work used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 20–31 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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Algebraic Foundations of Generalized Signal Processing: A Unified Approach Across Domains
Abstract: Using the techniques of algebra, notably polynomial algebras and modules, algebraic signal processing (ASP) is a contemporary, abstract framework that generalizes conventional signal processing— including Fourier analysis, filtering, and convolution. The notion is to use algebraic structures to explain signals, systems, and transformations such that ideas may be understood and generalized across many domains, including time, space, graph, or group. A unifying theoretical framework called ASP generalizes classical signal processing …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 33–44 Read article
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Comprehensive Analysis of Nutritional Constituents in Food: A Quantitative and Qualitative Approach
Abstract: The nutritional value of food is the quality & safety of food, and its effect on human health. The quest for food composition demands an integrated, quantitative and descriptive treatment. Nutritional Components Major nutritional components including carbohydrates, proteins, fats, vitamins, minerals and dietary fiber, were studied in selected food samples. We applied quantitative techniques such as proximate analysis, spectrophotometry, and chromatography to quantify levels of micronutrients and macronutrients. Qualitative analysis …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 14, Issue 3, 2025 · pp. 29–39 Read article
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Polymer–Gel Composite Phase Change Materials: A Functional Polymer Composite Approach for Solar-Thermal Energy Storage in Building Facades
Abstract: This study investigates polymer–composite phase change materials (PCMs) in the form of polymer–gel hybrids as multifunctional systems for solar–thermal energy storage in building façades. Paraffin- and PEG-based PCMs were embedded into polyurethane and acrylic gel matrices to create shape-stabilized polymer–composites with high PCM loading (70–80 wt%). Differential Scanning Calorimetry (DSC) confirmed distinct melting/freezing transitions at ~56°C (paraffin) and ~42°C (PEG), with enthalpy values of 120–150 J/g, closely matching theoretical predictions, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 36–51 Read article
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Dynamics of Prime Gap Sets: An Algorithmic and Set-Theoretic Approach
Abstract: In this paper, we present a theorem and an efficient algorithm for computing all prime numbers up to a given integer X. Our theorem establishes a relationship between the primes up to X and those up to (X+1)2, providing a theoretical foundation for the algorithm. The proposed method improves upon the traditional Sieve of Eratosthenes by dynamically eliminating multiples of primes using only the remaining numbers in the set, thereby …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 20–25 Read article
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Aspect-Based Sentiment Analysis Using a Hybrid Approach with Dependency Parsing
Abstract: The rapid expansion of digital communication has resulted in an unprecedented volume of consumer-generated textual data across online reviews, social media platforms, forums, and e-commerce websites. Extracting meaningful insights from this data is increasingly important for organizations seeking to understand customer opinions, preferences, and behavioral trends. Despite significant advances in sentiment analysis, many existing approaches primarily focus on surface-level features and often overlook deeper syntactic and semantic relationships within text. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 01–09 Read article
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Quick Service: A Scalable Multi-Service Web Platform—A Microservices Approach for Seamless Integration
Abstract: This study proposes a model designed to save both time and cost for individuals seeking convenient access to a variety of services. In today’s fast-paced lifestyle, people often require quick and reliable solutions that can be tailored to their immediate needs. Our approach focuses on delivering multiple on-demand services that can cater to both individuals and businesses, ensuring that essential tasks are completed efficiently and on time in many emerging …
Published in Journal of Open Source Developments · Vol. 12, Issue 3, 2025 · pp. 26–45 Read article
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Designing Self-Optimizing Operating Systems: Information-Theoretic Approaches to Thread Scheduler Implementation
Abstract: Thread Level Scheduling (TLS) in multi-core and many-core processor environments represents a critical frontier in next-generation operating system design. As computing systems grow increasingly heterogeneous and concurrent, traditional scheduling strategies often rely on heuristics or localized resource metrics, frequently overlooking the deeper, quantifiable relationships and uncertainties inherent in complex concurrent workloads. This study explores the application of information-theoretic approaches, specifically entropy-based task allocation, mutual information-driven dependency analysis, and channel capacity-inspired …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 3, 2025 · pp. 31–39 Read article