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80 articles for “Forest”
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Forestation and Forest Regeneration: The Micro-Stream Technique.
Abstract: Forests are important for The Earth Ecosystem and proper Homo sapiens evolvement at high standards of living. Forest coverage modulate local and global climate, in general where there is a forest there should be considered life at high standards because of proper oxygenation, weather, agriculture, farming and food supply and scenary in the case of close-to-forest urban areas. Micro-streams are at the plateau of river basins and exits because of …
Published in International Journal of Agrochemistry · Vol. 6, Issue 1, 2020 · pp. 58–61 Read article
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Underground Microbe-Root Networks Directed Forestation and Forest Regeneration: Towards a High Planetary Standard of Life
Abstract: Educated predictions for the 21st Century regarding Earth and Homo sapiens status evolvement on it have foreseen new and better advances in Science and Technology: Magnetism as the primer energy source, Robotics and Artificial Intelligence for automation, The Universal Basic Income, Cryptocurrencies and the Internet of Things as the suitable and improved replacement for central banking system, and the development of a Global Culture, with it the establishment of global …
Published in International Journal of Agrochemistry · Vol. 5, Issue 2, 2019 · pp. 30–37 Read article
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IOT-enabled Anti-poaching System for Protecting Wildlife and Forests Through Advanced Monitoring and Alert Mechanisms
Abstract: Forests are essential for preserving the intricate ecological harmony of our planet, serving as critical habitats for numerous animal species. Unfortunately, this equilibrium is increasingly jeopardized not only by illegal logging but also by the scourge of animal poaching the global demand for exotic animal parts and products fuels poaching, which presents a major menace to wildlife populations across the globe. The repercussions of poaching extend far beyond individual animals. …
Published in International Journal of Animal Biotechnology and Applications · Vol. 10, Issue 1, 2024 · pp. 36–44 Read article
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Bio-Fertilizer in Forest Nursery-A Review
Abstract: Many micro-organisms like bacteria, fungi, algae possess plant growth promoting mechanisms. These micro-organisms may be implemented as biofertilizers in agriculture and forestry, improving crop yields. These Biofertilizers can enhance plant increase through numerous different mechanisms. The synthesis of plant nutrients or phytohormones, which may be absorbed with the aid of using plants, mobilization of soil compounds, making them to be available for the plant for use as nutrients, the safety …
Published in International Journal of Industrial Biotechnology and Biomaterials · Vol. 6, Issue 2, 2020 · pp. 1–14 Read article
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Forest and Landscape Restoration: A Review
Abstract: On the word of a global assessment of restoration potential, it is estimated that there are more than two billion hectares of deforested and degraded land around the world. In these degraded land, there is vast opportunities for the restoration. Restoring forests and forest landscapes is an important step in regaining the health and functionality of these ecosystems. Forest landscape restoration (FLR) system is an underway step of restoring ecological …
Published in International Journal of Landscape Planning and Architecture · Vol. 4, Issue 1, 2018 · pp. 49–56 Read article
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Bacterial Diversity of Decomposing Leaf Litters of Polyalthia longifolia (Sonner.) Thw. and Rhododendron arboreum Sm. Under Natural Condition
Abstract: The role of microorganisms in the decomposition of plant material is of immense importance. A large amount of plant litter is added annually to the soil through leaf fall and death of plants. As the plant materials fall on the ground, they are immediately attacked by various groups of soil microorganisms and soon after, the process of decomposition is initiated. Microorganisms being heterotrophic in their mode of nutrition are responsible …
Published in International Journal of Plant Biotechnology · Vol. 1, Issue 1-2, 2015 · pp. 34–41 Read article
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Strengthening Forest Conservation with an IoT-Based Anti-Poaching Alarm System for Trees
Abstract: There are frequent incidents of theft of valuable trees, such as sandalwood, sagwan, and timber, worldwide. These trees are used in medicine, cosmetics, furniture, and more. To prevent such theft and protect the forests, preventive measures must be taken. Additionally, forest fires can cause significant damage to wildlife and trees, so it is crucial to control them quickly. To address these issues, a framework has been developed that utilizes three …
Published in International Journal of Green Chemistry · Vol. 9, Issue 1, 2023 · pp. 49–58 Read article
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Speech Emotion Recognition using Multi- Kernel CNN for Features extraction and Random Forest Classifier
Abstract: Identifying human emotional states from speech signals is the main goal of Speech Emotion Recognition (SER), which has grown to be a significant area of study in affective computing. However, class imbalance and efficient feature extraction from speech data pose problems for many of the current methods. This study suggests a hybrid framework that combines a Random Forest (RF) classifier with a multi-kernel Convolutional Neural Network (CNN) to address these …
Published in International Journal of Digital Communication and Analog Signals · Vol. 12, Issue 2, 2026 Read article
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COVID-19 Detection Using Decision Tree Support Vector Machine Random Forest.
Abstract: The rapidly spreading novel coronavirus (SARS-CoV-2) presents a substantial global health risk, necessitating swift detection through efficient diagnostic methods. Reports highlight lung-related issues in many COVID-19 patients, and both chest CT scans and X-rays are effective in identification. Chest X-ray (CXR) imaging, due to its convenience, faster imaging, simplicity, and lower cost, stands out. In our study, we applied Decision Tree, Random Forest, and Support Vector Machine to identify COVID-19 …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 9, Issue 2, 2023 · pp. 7–21 Read article
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Ethereum Price Prediction Using Extra Trees and Random Forest Regressors
Abstract: The Ethereum market is famous for its unpredictability and the possibility of significant profits, presenting both opportunities and obstacles for investors and stakeholders. Given the dynamic nature of this ecosystem, accurate prediction of Ethereum’s price movements is essential for informed decision-making. In this project, we propose an innovative approach that leverages ensemble learning techniques, specifically extra trees and random forest regressors, for Ethereum price prediction. By harnessing a diverse dataset …
Published in International Journal of Distributed Computing and Technology · Vol. 10, Issue 2, 2024 · pp. 9–25 Read article
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Unveiling Employee Attrition: Harnessing Predictive Modeling for Proactive Workforce Management
Abstract: This study aims to predict employee turnover and identify organizational factors contributing to attrition by employing predictive analytics techniques. Employee attrition, which refers to the loss of employees without immediate replacements, leads to reduced overall workforce productivity. The study evaluates different machine learning techniques, such as gradient boosting, random forest, and logistic regression, to identify employees who are most likely to leave, and uses SPSS software to ensure the reliability …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 2, 2024 · pp. 1–10 Read article
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Deforestation: Causes and Consequences of the Global Crisis
Abstract: Climate change is unavoidable due to the dynamic character of global ecosystems. The reasons of these environmental changes are both man-made and natural. Human activities have always had an impact on the environment. As economic activity and population expansion have risen to the point that they can no longer be disregarded or seen in isolation, the consequences of mankind just on environment could no longer be ignored or examined in …
Published in International Journal of Environmental Chemistry · Vol. 8, Issue 1, 2022 · pp. 29–34 Read article
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Securing Smart Electrical Systems through Comparative Analysis of Machine Learning Models for Classification
Abstract: In the realm of cybersecurity, the intersection of technology and security measures has spurred significant advancements, particularly in safeguarding electrical systems against cyber threats. This research delves into the evolving landscape of cybersecurity within electrical systems, leveraging machine learning techniques to mitigate challenges. By incorporating cybersecurity protocols with machine learning algorithms, this study demonstrates enhanced security measures tailored for electrical infrastructures, pivotal in ensuring efficiency and resilience. Through meticulous examination, …
Published in International Journal of Electrical Power System and Technology · Vol. 12, Issue 2, 2026 Read article
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CyberSentinel: A Proposed Hybrid AI Framework for Real-Time Cyber Threat Intelligence
Abstract: Modern cyberattacks have grown far more sophisticated, frequent, and fast-moving than the signature-based intrusion detection systems many organizations still rely on. This paper proposes CyberSentinel, a hybrid artificial intelligence framework for real-time cyber threat intelligence (CTI) that combines three complementary techniques into a single detection pipeline: a Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) module for network traffic anomaly detection, a Random Forest ensemble for structured log classification, and a transformer-based …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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Assessment of LULC changes on Soil Erosion & River Channel Shifting: A case study of Gin Ganga River Basin
Abstract: Abstract- Soil erosion and river channel shifting are critical environmental problems with major socio-economic implications. These issues are exacerbated in areas experiencing rapid land use and land cover (LULC) changes. The study investigates the soil erosion due to LULC Changes and river channel displacement areas of the Gin Ganga River Basin over the period of 2014-2024. Using RUSLE model and GIS-based analyses, mean annual soil erosion were estimated as 0.36 …
Published in International Journal of Water Resources Engineering · Vol. 12, Issue 1, 2026 · pp. 21–32 Read article
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Use of Natural Language Processing for Hate Speech Detection on SocialMedia:
Abstract: The exponential growth of social media platforms has led to an increase in user- generated content, enhancing global connectivity but also facilitating the spread of harmful language, including hate speech. Addressing this issue requires robust, Naïve Bayes, Decision Tree, K-Nearest Neighbours (KNN), Linear Regression, and Random Forest—were tested, with Linear Regression achieving the highest accuracy automated systems for detecting and mitigating offensive content. This paper presents a comprehensive analysis of …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 2, 2025 · pp. 9–16 Read article
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Isolation and Characterization of Alkaloidsfrom Ancistrocladus Heyneanus Leaves: A Phytochemical Study
Abstract: Leaves of Ancistrocladus heyneanus were collected from the forest of the Matheran hills of Maharashtra. From these leaves, alkaloids were extracted using dichloromethane, and two new monomeric Naphthyl-iso-quinoline alkaloids, Youndamine A and Ancistrocline were isolated using TLC and HPLC. HPLC/MS and NMR further identified the patient. The present study involves the collection and chemical investigation of the leaves of Ancistrocladus heyneanus, a plant species found in the forested regions of …
Published in International Journal of Analytical and Applied Chemistry · Vol. 10, Issue 2, 2024 · pp. 7–20 Read article
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Advancements in Predictive Maintenance: A Review of Data-Driven Approaches, Machine Learning, and AI in Diverse Industrial Landscapes
Abstract: The Internet of Things (IoT), the use of machine learning (ML), and artificial intelligence (AI)-driven advances in predictive maintenance are the key topics of this study. With the goal of offering a thorough grasp of existing approaches and potential future developments, it analyzes applications in predictive maintenance in many sectors. Predictive maintenance approaches are the major topic of discussion, with an emphasis on their advantages, disadvantages, difficulties, and prospects. Additionally, …
Published in International Journal of Computer Aided Manufacturing · Vol. 10, Issue 2, 2024 · pp. 19–32 Read article
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Network Intrusion Detection Using Wireshark and Machine Learning
Abstract: The growth of networked devices has highlighted the desire for advanced intrusion detection (IDS) tools to protect digital systems from evolving cyber threats. Traditional IDS systems are often difficult to adapt to the threat environment because they rely on predefined signature lists. This study presents a new approach that combines Wireshark, a widely used network packet analysis tool, with advanced machine learning for intrusion detection. Our system leverages Wireshark's data …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 1, 2024 · pp. 23–31 Read article
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How Interdependency of Living Being Impacts the Development of a Biodiversity: In Context to Urban Ecology
Abstract: In many respects, organisms depend on the interactions they have with their surroundings and other living things. Biodiversity is the variability of many organisms with their ecological complexes in which they fall. The diversity of living organisms can be within them or possibly between them. Either directly or indirectly, both plants and animals depend on each other. The way they depend on, forms compatibility with their surroundings. Originally, plants were …
Published in International Journal of Landscape Planning and Architecture · Vol. 9, Issue 1, 2023 · pp. 14–21 Read article