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463 articles for “forests”
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A Study on Distribution of Acridoidea (Orthoptera) of Patna District, Bihar (India)
Abstract: A thorough study of species shows that 12 types of grasshoppers fall into 3 families: Acridoidae, Catantopidae, and Pyrgomorphidae. These families have 7, 3, and 2 species, respectively. The survey places with rich plants and different weather conditions – like rainfall, humidity, and temperature. Researchers did an extensive survey. They checked many crops and habitats to gather grasshoppers from various agricultural spots. These insects were observed in their natural habitat. …
Published in Research & Reviews : Journal of Ecology · Vol. 13, Issue 3, 2024 · pp. 1–5 Read article
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Biodiversity of Gentiana sikkimensis C.B. Clarke in Sikkim Himalaya
Abstract: The mountain ecology is a fragile ecology where the species are ecologically linked and grow maintaining particular ecological niche. Several species of alpine forest are unique in their diversity. This result might be resulted due to the microclimatic conditions of mountain ecology. Since, this writing covers Gentiana sikkimensis Clarke and according to the report, the Himalayan region is bestowed with the different species of Gentiana upto ca. 71 species. Out …
Published in Research & Reviews : Journal of Ecology · Vol. 13, Issue 3, 2024 · pp. 33–37 Read article
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Land Degradation Mapping Using Integration of Remote Sensing and Geographic Information Systems in Maricá, Rio de Janeiro, Brazil
Abstract: The purpose of this paper is to study the growing problem of soil erosion in the municipality of Maricá, Rio de Janeiro, Brazil. The study area has an excellent agricultural condition. However, due to human and natural factors, water erosion is becoming a major problem. Therefore, new approaches are needed to determine soil degradation not only for the identification of hotspots, but also to identify areas prone to degradation to …
Published in Journal of Remote Sensing & GIS · Vol. 15, Issue 3, 2024 · pp. 45–56 Read article
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Literature Review and Discussion of Machine Learning Algorithms for Predicting Chronic Kidney Disease
Abstract: Being one of the most serious and most occurring diseases in our era, chronic kidney disease requires a fast and correct diagnosis. The usage of machine learning in medicine has now grown to such a level that it could be a means of diagnosis. The doctor can be the first one to get the ailment by using machine learning classifier algorithms. This has been the data science sector’s new horizons, …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 34–39 Read article
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Strategy to Accelerate the Biopharmaceuticals Production Using Komogataella phaffii (Pichia pastoris)
Abstract: Revenue generation has been the primary goals for nations as well as the industries worldwide. Biopharmaceutical verticals have become potential revenue generators as they are the industrial workhorses and the economic engines that drive the upcoming biopharmaceutical industries with advances in DNA recombinant technology. A breakthrough in the indusrial biotechnology for the production of biopharmaceuticals using Pichia pastoris is awaited. Ablynx NV, Recombinant proteins (RP), HSA-pFSH beta, antibodies, borosin, N-glycoprotein, …
Published in International Journal of Advance in Molecular Engineering · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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Diabetes Prediction Using ML Techniques
Abstract: Diabetes mellitus, commonly referred to as diabetes, denotes a cluster of prevalent endocrine disorders characterized by persistent elevated levels of blood sugar. Diabetes is classified into two main types: type 1 and type 2. Type 1 diabetes arises when the body is unable to produce insulin, while type 2 diabetes involves either insulin resistance or insufficient insulin production. Early detection and intervention are essential to reduce its harmful impacts. The …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Detection of Phished URLs Using Machine Learning
Abstract: Phishing attacks remain a significant cybersecurity challenge, requiring innovative detection strategies. This study investigates the use of machine learning to detect phishing URLs, to improve the accuracy and reliability of detection systems. Utilizing a diverse dataset of legitimate and phishing URLs we extracted the features such as lexical properties, domain-specific details, and HTML content to train various machine learning models. Algorithms including Random Forest, support vector machine (SVM), and gradient …
Published in Journal of Web Engineering & Technology · Vol. 11, Issue 3, 2024 · pp. 1–7 Read article
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Unified Ensemble Techniques for Enhanced DDoS Attack Prevention and Detection
Abstract: Today’s world is entirely reliant on the internet. The internet is a worldwide information source that all users rely on, hence its accessibility is critical. There have been reports in recent years, particularly in the information and technology division of significant organizations worldwide, of data breaches where the terms denial-of-service (DoS) and DDoS are consistently present in the stolen material. Network security is seriously threatened by DoS attacks. They have …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 20–27 Read article
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Resilience Building through Disaster Risk Reduction
Abstract: A catastrophe is a serious disruption to a society's functioning that causes mortal, material, profitable, and environmental losses beyond a community's capability to manage. It results from the admixture of hazards, surroundings of exposure, and lack of volume or measures to lower the implicit negative results of threat. Hence, catastrophe control may be delineated as the arranging and administration of effects and the responsibility for handling all philanthropic angles of …
Published in International Journal of Environmental Planning and Development Architecture · Vol. 2, Issue 2, 2024 · pp. 32–45 Read article
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Preliminary Checklist of Acridoidea (Orthoptera) of Patna District, Bihar (India)
Abstract: The family Acrididae, which falls under the order Orthoptera includes locusts and grasshoppers. Insects are found all over the globe. In general, locusts refer to larger acridids, while smaller species are known as grasshoppers. The comprehensive study indicates that there are 19 species from various families, which include 12 species from Acrididae, 4 Catantopidae, and 3 from Pyrgomorphidae. A thorough investigation was carried out across different crops and habitats to …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 3, 2024 · pp. 67–71 Read article
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Water Quality Testing of Yamuna River at Poiya Ghat (Vaikunth Dham/Swarg Dham), Agra: A Systems Study
Abstract: Since pre-historic times, river water has been used as a source of drinking water. River water is now a source of hydropower generation, irrigation, aquaculture, navigation, transportation, socioeconomic activities, human settlements and home for aquatic living forms. Apart from this, river water has very vital role in maintaining soil fertility, wildlife conservation and development of forest resources. Due to increase in industrialization, urbanization, mining, sewage disposal and rampant use of …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 15, Issue 3, 2024 · pp. 01–03 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
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Integrative Machine Learning Approaches for Predicting the Rheological Behaviour of Soft Magnetorheological Elastomers
Abstract: Magnetorheological Elastomers (MREs) are advanced composite materials known for their ability to alter mechanical properties under external magnetic fields, making them highly valuable in adaptive damping systems, vibration control, and smart devices. The accurate prediction of rheological behavior in soft MREs remains a significant challenge due to the complex interplay between material composition and magnetic fields. To address this challenge, this study employs a multi-pronged approach that integrates traditional material …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1083–1096 Read article
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A Hybrid Machine Learning Approach for Cardiovascular Disease Prediction
Abstract: Heart disease ranks among the top causes of death globally. Accurately predicting cardiovascular conditions has become a key challenge in the realm of clinical data analysis. It has been shown that machine learning is an effective means of assisting with predicting and decision-making based on the large volume of data produced by the medical industry. In this study, we describe a unique approach that increases the prediction accuracy of heart-related …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 69–75 Read article
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A Survey of Several Machine Learning (ML) Algorithms for Security Solution in Internet of Things (IoT) Networks
Abstract: The Internet of Things (IoT) refers to the integration of physical objects with the Internet, allowing for connectivity and monitoring. This idea has garnered immense attention from researchers and users alike, driven by the widespread accessibility of the Internet. It spans a wide range of devices, including smart versions of conventional appliances, innovative tools tailored for Internet-enabled ecosystems, and sensors that leverage connectivity to revolutionize industries such as manufacturing, healthcare, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 1–11 Read article
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Identification and Prioritization of Critical Erosion Prone and Water Potential Areas of Manandragarh Watershed Using HEC-HMS for Management
Abstract: This study was carried out at Indira Gandhi Krishi Vishwavidyalaya, Raipur (CG) on hydrological modelling and development of soil and water conservation plan for critical erosion prone and water potential sub-watersheds of Manendragarh watershed of upper Hasdeo subbasin in Chhattisgarh using Hydrological Engineering Centre-Hydrological Modelling System (HEC-HMS). The Hydrological Engineering Centre-Geo Hydrological Modelling System (HEC-Geo HMS) was utilized for developing the model setup, while the HEC-HMS model was employed to …
Published in Research & Reviews : Journal of Ecology · Vol. 14, Issue 1, 2025 · pp. 26–44 Read article
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IoT-based Heart Attack Prediction System Using Machine Learning
Abstract: Heart disease, particularly heart attacks, is one of the leading causes of mortality worldwide. Timely detection and prompt intervention play a vital role in significantly improving the survival rates of individuals at risk of cardiac events. Unfortunately, most traditional healthcare systems are not equipped with mechanisms for continuous, real-time monitoring of patients' cardiovascular health. This limitation makes it extremely difficult for healthcare providers to identify warning signs early enough to …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 1–5 Read article
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Statistical Models for Predicting Genetic Variability and Disease Susceptibility
Abstract: Differences in genetics are key to understanding why some individuals are more prone to certain diseases than others. Recent advancements in genomic research, combined with statistical modeling techniques, have made significant strides in predicting disease risk based on genetic factors. This review explores the application of statistical models for predicting genetic variability and their role in disease susceptibility. We discuss traditional methods like linear regression and genome-wide association studies (GWAS), …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 30–34 Read article
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Atmospheric Boundary Layer Processes: Impacts on Weather Patterns and Climate Change
Abstract: The atmospheric boundary layer (ABL) is a vital component of the Earth's climate system, acting as the interface between the terrestrial surface and the overlying atmosphere. This layer, typically extending from the surface to a height of a few hundred meters, is characterized by strong gradients in meteorological variables such as temperature, humidity, wind speed, and atmospheric pressure. Understanding the dynamics of the ABL is essential for comprehending weather phenomena, …
Published in International Journal of Atmosphere · Vol. 1, Issue 2, 2024 · pp. 22–25 Read article
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Diversity and Sustainability: The Role of Traditional Fruit Trees in Uttarakhand Agricultural Landscape
Abstract: Uttarakhand state is characterized by a rich diversity of traditional fruit trees. Uttarakhand is largely a mountainous state, with only around 10% of its overall geographical area being plains, and more than three-quarters (78%) of its total people relying on agriculture for survival. The state's geographical features and climatic circumstances are suited for growing temperate and subtropical fruit crops. It provides a variety of agro-geoclimatic conditions that are ideal for …
Published in International Journal of Land · Vol. 1, Issue 2, 2024 · pp. 22–25 Read article