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160 articles for “trees”
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A Review on Lung Cancer Prediction Using Machine Learning
Abstract: Lung cancer continues to be a major contributor to cancer-related mortality across the globe. Timely diagnosis and reliable prediction models play a crucial role in enhancing treatment outcomes and survival rates for patients. The present study focuses on the utilization of machine learning (ML) methods for the prediction of lung cancer. Using datasets that incorporate clinical records, imaging modalities, and genetic profiles, the research assesses the predictive capabilities of multiple …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–11 Read article
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Progress in Renal Tumor Surgery: The Role of 3D Surgical Planning in Partial Nephrectomy
Abstract: Renal cell carcinoma is the most common form of kidney cancer, representing 2–3% of global cases, with the highest incidence in Western Europe. For small renal tumors, partial nephrectomy is the preferred treatment, where the tumor is surgically removed. This procedure does not affect oncological outcomes, allowing part of the kidney to remain functional. During tumor removal, the surgeon minimizes excessive bleeding and improves visibility by cutting off the arterial …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 3, 2025 · pp. 35–40 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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Electromagnetic and Dielectric Performance of Polymer–Ceramic Composite Substrates for Fractal-Based IoT-Antenna Fabrication
Abstract: Polymer–ceramic composite substrates play a crucial role in determining the electromagnetic performance, mechanical stability, and thermal reliability of radio-frequency devices. In this work, a polymer-based composite substrate is systematically investigated for its suitability in compact IoT and RFID antenna applications. A fractal-structured antenna is employed as a functional test platform to evaluate the dielectric behavior, impedance characteristics, and radiation efficiency of the composite substrate. Novelty of the proposed reader antenna …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1518–1534 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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An Automated Smart Contract Repair Framework for Reentrancy, Integer Overflow, and Denial- of-Service Vulnerabilities
Abstract: This paper introduces a novel static analysis framework designed to bridge a long-standing gap in Ethereum smart contract security: the disconnect between vulnerability detection and automated remediation. Although widely adopted tools such as Slither and Oyente are highly effective at identifying security weaknesses, they stop short of providing actionable fixes. As a result, developers manually patch vulnerabilities, a process that is not only time-consuming but also susceptible to human error …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 31–41 Read article
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Data-Driven Energy Forecasting for Smart Homes: Ensemble Learning from IoT Meters and Relevance for Polymer-Composite Based Smart Infrastructure
Abstract: Reliable estimation of household electricity demand is relevant in creating efficiency in energy usage, optimization of the loads, and intelligent demand-side management in intelligent grid systems. This paper introduces a varied machine learning model that approaches residential electric consumption prediction using an assortment of ensemble regression boosts, including Linear Regression, Lasso Regression, Decision Tree Regressor, Random Forest, and Gradient Boosting, to predict residential electricity consumption environments on a time-series arrested …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 29–64 Read article
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Demodex spp. (Acari: Demodicidae) Infestation in Humans: Diagnostic Clues and Therapeutic Approaches to Primary and Secondary Demodicosis.
Abstract: Demodicosis represents an inflammatory dermatosis and adnexal disorder arising from pathologic overgrowth of Demodex mites, primarily Demodex folliculorum and Demodex brevis, which are ubiquitous human ectoparasites residing in pilosebaceous units and eyelid margins. Once regarded as benign commensals, these mites are now recognized as primary drivers or key cofactors in diverse clinical phenotypes, including papulopustular eruptions, pityriasis folliculorum, rosacea-like disorders, blepharitis, meibomian gland dysfunction, and exacerbations of comorbid dermatoses such …
Published in International Journal of Insects · Vol. 3, Issue 1, 2026 · pp. 12–20 Read article
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Design and Development of Onion Storage Shade for Better Ventilation and Longer Life
Abstract: Onions are one of the most important cash crops for farmers in India and many other countries. However, most harvested onions are lost every year due to improper storage. Traditional storage methods, such as keeping onions in heaps under trees, in closed rooms, or in poorly ventilated sheds, do not provide sufficient airflow. As a result, moisture accumulates, leading to sprouting, fungal growth, rotting, and physical damage. These losses reduce …
Published in International Journal of Trends in Horticulture · Vol. 3, Issue 1, 2026 · pp. 31–41 Read article
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Comprehensive Evaluation of Quercetin from Bauhinia purpurea for Its Anti-Acne and Anti-Inflammatory Potential, Including Advances in Quercetin-Loaded Nanogel Formulation
Abstract: Acne vulgaris is among the most prevalent chronic inflammatory dermatoses in clinical dermatology, afflicting a substantial proportion of the global adolescent and adult population. Conventional pharmacotherapies — including topical retinoids, benzoyl peroxide, and systemic antibiotics — remain the therapeutic mainstay; however, their long-term utility is progressively undermined by adverse cutaneous reactions, systemic toxicity, and the rising prevalence of antibiotic-resistant Cutibacterium acnes strains. These limitations have intensified scientific interest in plant-derived …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 13, Issue 2, 2026 Read article
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Formulation Challenges in Long-acting Injectable Small Molecules: Emerging Strategies and Perspectives
Abstract: Long-acting injectable (LAI) formulations represent a transformative approach in pharmacotherapy, particularly for conditions demanding sustained drug exposure over weeks to months. Although biologics have dominated this space historically, the adaptation of LAI technology to small molecules presents a distinct and complex set of challenges rooted in physicochemical properties, manufacturing scalability, and regulatory expectations. This review systematically addresses the principal formulation barriers encountered in developing LAI small-molecule products, including aqueous solubility …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 13, Issue 2, 2026 Read article
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An Overview on AI-Driven IoT Based Decision Making in Climate change Study: KSK approach in Climate Change Study
Abstract: As the Earth’s climate enters a state of unprecedented volatility, the traditional methods of ecological observation—characterized by delayed reporting and fragmented data—are no longer sufficient. This study investigates the paradigm shift toward AI-driven IoT (KSK Approach)-based decision-making frameworks as the primary frontier in climate science. By deploying a "planetary nervous system" of interconnected sensors—measuring everything from soil moisture in the Sahel to glacial melt rates in the Arctic—we generate a …
Published in International Journal of Climate Conditions · Vol. 3, Issue 1, 2026 · pp. 1–10 Read article
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ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
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Analyzing and Predicting Academic Behavior from Peer Pressure Indicators Using Machine Learning
Abstract: The academic achievement of a student is determined by their capability, but also by the companions with whom they associate. Friends can have a positive impact on students' motivation for school, and at times friends are distractions leading to a lack of attention on their school assignments. This particular study focuses on the number and quality of companions students associate with and to what extent that could be used as …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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Systematic Analysis of the Pharmacological Properties of Different Plant Parts of Madhuca sp.
Abstract: Madhuca sp., a perennial tree belonging to the Sapotaceae family, are widely distributed across South and Southeast Asia. It holds considerable value across the food, beverage, and pharmaceutical sectors. The growing interest among cultivators, agronomists, and industry stakeholders stems from the diverse bioactive potential documented across different parts of the plant, including the bark, leaves, seeds, and flowers. Traditional and emerging evidence points to a wide spectrum of pharmacological actions, …
Published in Research & Reviews : Journal of Botany · Vol. 15, Issue 2, 2026 Read article
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Assessment of Agricultural Potentials and Constraints of Natural Resources Management for Research Implementation in Gedeo Zone South Ethiopia Region
Abstract: This study aimed at assessing agricultural potentials and constraints of natural resources management for research implementation in Gedeo zone south Ethiopia Region. The result indicates that the use of organic and inorganic fertilizers was not efficient and the crop yield was decreasing from year to year. Use of organic fertilizer is for only high value crops of enset and coffee without determined rate. Farmers were not practiced organic fertilizers like …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 2, 2026 · pp. 82–93 Read article
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Reduction of Air Pollutants of Urban Canyons through Management of Particulate Matters 2.5 in the Streets
Abstract: Urban canyons are long and high sky-scrappers closely to narrow streets result in very different microclimate challenges. These spaces often trap pollutants and restrict air circulation and intensify more retention of heat making them very uncomfortable for pedestrians. In order to resolve this issue a strong set of design guidelines and frameworks were needed which can balance out the human comfort and environmental aspects. This research studies strategies to improve …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 11–23 Read article
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Smart Education through Machine Learning: A Review of Trends, Benefits, and Risks
Abstract: Machine learning (ML) is transforming the contemporary education by transforming it into smarter, data-driven and personalised learning. This review examines the key tendencies, advantages, and possible threats of applying ML in intelligent education. ML promotes adaptive learning, automatization of assessments, and student engagement, which is highly beneficial both to learners and educators. Nonetheless, issues like data privacy, algorithmic bias or unequal access are also a significant concern. The article emphasises …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 24–28 Read article
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Analyzing and Predicting Academic Behavior from Peer Pressure Indicators Using Machine Learning
Abstract: The academic achievement of a student is determined by their capability, but also by the companions with whom they associate. Friends can have a positive impact on students' motivation for school, and at times friends are distractions leading to a lack of attention on their school assignments. This particular study focuses on the number and quality of companions students associate with and to what extent that could be used as …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 1–7 Read article
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A Comprehensive Investigation of Bagging-Based Ensemble Methods for Improving Machine Learning Model Robustness
Abstract: Machine learning models such as Decision Trees, Logistic Regression, and K-Nearest Neighbors are widely used for classification tasks due to their simplicity and interpretability. However, these models often suffer from high variance, overfitting, and poor generalization when applied to real-world datasets, particularly those that are small, noisy, or imbalanced, as commonly encountered in healthcare, finance, and cybersecurity applications. To address these limitations, this research proposes a Bagging (Bootstrap Aggregating)-based ensemble …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 24–34 Read article