This research study explores the impact of cloud computing on engineering education in India, focusing onhow it enhances educational outcomes. This study examines the potentialof strategic cloud implementation in high...
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The proliferation of Wireless Sensor Networks (WSN) in various applications has necessitated the exploration of network architectures that can ensure efficient, scalable, and reliable communication. This study present...
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Agriculture is changing into a more sustainable and productive sector as a result of the fusion of modern technologies, especially the Internet of Things (Io'T), with traditional farming methods. This shift, dubbe...
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ISBN:
(纸本)9798350379945
Agriculture is changing into a more sustainable and productive sector as a result of the fusion of modern technologies, especially the Internet of Things (Io'T), with traditional farming methods. This shift, dubbed 'Smart Agriculture,' rethinks how farmers conduct cultivation, managing resources, and sustainability by using the power of online access, data analytics, and automation. A network of linked systems and gadgets that gather, transfer, and evaluate real-time data forms the basis of smart agriculture. With previously unheard-of precision and efficiency, farmers may now remotely track and supervise a variety of aspects of their farming activities thanks to this connectivity. The transformative influence of IoT on productivity, sustainability, or precision farming highlights the need for it in agriculture. A crucial element of smart agriculture is precision farming, which entails exact management of resources like pesticides, fertilizers, and water as well as real-time data processing. This study examines the ways in which integrated geospatial technologies, weather forecasting, and IoT -driven automation and actuation support productive and sustainable farming methods. The emphasis on aquaculture monitoring also draws attention to the wide range of uses for IoT in agriculture that go beyond conventional crop growing. The crucial part that IoT plays in meeting the growing need for food production on a worldwide scale while using scarce resources. Precision farming, management of water, and crop monitoring are made possible by Internet of Things technologies including sensors, drones, or automated machinery. These apps support environmental sustainability in agriculture, improve resource efficiency, and enable data-driven decision-making. This research work goes into more detail on the fundamental components of smart agriculture, such as sensor technologies, infrastructure connectivity, automation, data transfer, acquisition, and integration with geospatial tec
Artificial intelligence (AI) is an area of tremendous potential, especially in the software testing domain, where it has changed the dynamics of the process, storms in efficiency, accuracy, and flexibility in a given ...
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As the global population ages, sarcopenia - age-related muscle decline - demands innovative solutions. This paper introduces GRIPPY, a VR grip controller that transforms basic handgrip exercises into immersive, gamifi...
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Software testing is crucial for ensuring software quality, including security. This research presents a case study examining manual and open-source tool-based security testing of an e-commerce website. By applying var...
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The present work comprises the measurement of activity concentrations of three radionuclides, 22⁶Ra, 228Ra, and 4⁰K in 33 species of vegetables commonly used in Koya district, the Iraqi Kurdistan region. The analysis ...
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Breast cancer is a type of cancer responsible for higher mortality rates among *** cruelty of breast cancer always requires a promising approach for its earlier *** light of this,the proposed research leverages the re...
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Breast cancer is a type of cancer responsible for higher mortality rates among *** cruelty of breast cancer always requires a promising approach for its earlier *** light of this,the proposed research leverages the representation ability of pretrained EfficientNet-B0 model and the classification ability of the XGBoost model for the binary classification of breast *** addition,the above transfer learning model is modified in such a way that it will focus more on tumor cells in the input ***,the work proposed an EfficientNet-B0 having a Spatial Attention Layer with XGBoost(ESA-XGBNet)for binary classification of *** this,the work is trained,tested,and validated using original and augmented mammogram images of three public datasets namely CBIS-DDSM,INbreast,and MIAS *** accuracy of 97.585%(CBISDDSM),98.255%(INbreast),and 98.91%(MIAS)is obtained using the proposed ESA-XGBNet architecture as compared with the existing ***,the decision-making of the proposed ESA-XGBNet architecture is visualized and validated using the Attention Guided GradCAM-based Explainable AI technique.
Distributed energy resources (DER), renewable energy sources (RES) and electric vehicles (EV) pose considerable challenges with respect to their efficient integration within the power system. Operation and control str...
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The global prevalence of arm amputations, particularly transradial or below-elbow amputations, presents a pressing challenge due to the high costs of commercially available prosthetic hands. This issue is particularly...
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