this paper represents the design of a portable and IoT based device for monitoring nitrogen, phosphorus, potassium, pH, and moisture of soil, along with surrounding temperature and humidity, for crops and fertilizer r...
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ISBN:
(数字)9798350305463
ISBN:
(纸本)9798350305470
this paper represents the design of a portable and IoT based device for monitoring nitrogen, phosphorus, potassium, pH, and moisture of soil, along with surrounding temperature and humidity, for crops and fertilizer recommendation. the idea and execution of a wireless, portable system for assessing soil quality, recommending the optimal amount of fertilizer, and suggesting appropriate crops depending on the soil conditions are the main goals of this research project. the system is designed to have a user-friendly interface. It uses a cloud-based platform for analyzing data and implementation of machine learning models. Multiple classification-based machine learning algorithms are compared to gain better accuracy of the system. the results of the system are validated using different samples of both indoor and outdoor environments. this cost-effective design, which includes monitoring of seven parameters necessary for crop cultivation along with crop recommendation feature and fertilizer suggestion, makes it desirable for agroindustry.
the present healthcare sector is experiencing a fundamental upheaval withthe emergence of the Healthcare Internet of things (HIoT). this article delves into the transformational potential of HIoT by examining its use...
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ISBN:
(数字)9798350305463
ISBN:
(纸本)9798350305470
the present healthcare sector is experiencing a fundamental upheaval withthe emergence of the Healthcare Internet of things (HIoT). this article delves into the transformational potential of HIoT by examining its use in bettering patient care and monitoring. the paper dives into the introduction of HIoT, the methodologies adopted for research and development, the compelling findings gained, and the farreaching consequences in conclusion the opening part sets the scene by describing the fundamental transformation in healthcare facilitated by HIoT. It emphasizes the catalyst for rethinking patient care and monitoring as the combination of internet-connected devices, smart sensors, and data analytics. HIoT equips doctors with up-to-the-minute information, allowing for more precise diagnoses and more individualized plans of care. Furthermore, deep learning and artificial intelligence were incorporated to exploit the richness of HIoTgenerated data, allowing sophisticated analytics and informed decision-making. the compelling findings of this study are clear, withthe suggested technique regularly beating existing methods across numerous criteria. A remarkable accuracy score of 0.94 was reached, demonstrating the reliability of the suggested strategy in supporting informed healthcare decisions. Furthermore, in terms of cost efficiency, the suggested approach scored 0.95, suggesting its costeffectiveness and potential for economic viability. the development of HIoT promises a healthcare system that is more patient-centered, data-driven, and efficient in the future. To ensure healthcare continues to grow into an age of unmatched patient care and monitoring, researchers, healthcare providers, and governments must work together to harness this transformational potential while tackling the issues that come with it.
Multimodal biometric recognition is a technology that combines multiple biometric features for identity verification and access control. It can be applied to system access control to improve security and convenience. ...
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ISBN:
(数字)9798350305463
ISBN:
(纸本)9798350305470
Multimodal biometric recognition is a technology that combines multiple biometric features for identity verification and access control. It can be applied to system access control to improve security and convenience. the basic principles and application fields of multimodal biometric recognition technology have been widely studied and applied. By integrating multiple biological features such as fingerprints, iris, voice, facial features, etc., higher security can be provided because these biological features have high uniqueness and unforgeability. Compared with traditional identity verification methods, multimodal biometric recognition technology does not require memorizing complex passwords or carrying identification documents, thus providing a more convenient user experience. However, multimodal biometric recognition technology also faces some challenges and privacy issues in its application process. For example, the storage and protection of biometric data require careful handling to prevent the risk of data leakage and abuse According to the data, the usage rate of multimodal biometric recognition in system access control increased sharply from 6.27% in 2015 to 67.92% in 2021. this shows the role and prospects of multimodal biometric recognition in system access controlsystems. While promoting and applying multimodal biometric recognition technology, it is also necessary to pay attention to solving privacy and security issues to ensure its effective application in system access control.
the flexibility of cloud computing has ushered in a new digital era, giving businesses more freedom, prospects for expansion, and lower costs. Cloud computing raises worries about cost, security, and performance. To a...
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ISBN:
(数字)9798350305463
ISBN:
(纸本)9798350305470
the flexibility of cloud computing has ushered in a new digital era, giving businesses more freedom, prospects for expansion, and lower costs. Cloud computing raises worries about cost, security, and performance. To address these issues and enhance cloud use, we need new cloud monitoring techniques. this study examines three ways to these difficulties. the first application, “Real-time Performance Monitoring,” analyzes key performance metrics to assist businesses in identifying problems. In Algorithm 2, “Predictive Analytics for Anomaly Detection,” machine learning increases the safety of cloud debugging. the third technique, “Cost Optimization and Resource Scaling,” modifies resource use to optimize resource usage. three complete photographs show the results. Diagram 1 depicts shifting metrics and indicates performance concerns. Diagram 2 emphasizes the problems by comparing plans to reality. Dependability and security improve. Diagram 3 depicts resource allocation alternatives. data-driven decisions have the potential to optimize cloud spending. For enterprises, these cutting-edge alternatives enhance cloud cost, speed, and growth. they help cloud-dependent businesses meet their growth objectives and match their cloud operations withtheir business goals in this digital age.
High-Performance Computing (HPC) and Artificial Intelligence (AI) have come together to usher in a new age of data mining in the field of bioinformatics. Using high-performance computing (HPC) and artificial intellige...
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ISBN:
(数字)9798350305463
ISBN:
(纸本)9798350305470
High-Performance Computing (HPC) and Artificial Intelligence (AI) have come together to usher in a new age of data mining in the field of bioinformatics. Using high-performance computing (HPC) and artificial intelligence (AI), this research presents a suggested strategy for improving data mining techniques and then evaluates it alongside six more conventional approaches. Discovering latent patterns in high-dimensional biological data is the goal of the proposed technique, which combines Principal Component Analysis (PCA), Convolutional Neural Networks (CNN), and Random Forest (RF). the suggested technique consistently outperforms the state-of-the-art methods in our comparisons, including in terms of accuracy, precision, recall, and F1 score. these performance criteria are essential for effective data mining in bioinformatics, and the system's shown equilibrium between them is rather impressive. the suggested strategy also drastically decreases execution time, which is a crucial aspect in effectively managing large-scale biological information. Our findings highlight the need for AI-drivendata mining methods in the field of bioinformatics. the application of PCA offers dimensionality reduction, assisting in feature selection and boosting model performance. When it comes to classifying and ranking the value of features, RF provides ensemble learning capabilities, whereas CNNs excel at extracting complicated patterns from pictures and sequences. the suggested technique is holistic in nature, drawing on the advantages of several algorithms to improve data mining and provide a complete service to the field of biological research. Our results show that the suggested approach has considerable potential to further bioinformatics studies and applications. It helps scientists speed up drug development, improve the accuracy of diagnostics, and unearth new biological insights. In addition, the faster execution time suggests better use of computer resources, which is useful for
Medical imaging has changed a lot since “Synergistic Fusion of Multi-Contrast Imaging and Computational Image Synthesis for Quadruple ContrastEnhanced Images and Multi-Map Generation” came out. this innovative techn...
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ISBN:
(数字)9798350305463
ISBN:
(纸本)9798350305470
Medical imaging has changed a lot since “Synergistic Fusion of Multi-Contrast Imaging and Computational Image Synthesis for Quadruple ContrastEnhanced Images and Multi-Map Generation” came out. this innovative technology might revolutionize diagnostic imaging by providing a complete view of tissue features and enhancing accuracy. this study describes a system that utilizes ultrasound, PET, MRI, and CT data. Better detection is the goal of this technology. this first segment begins a new medical imaging age in which clinicians may view the full patient by combining data from diverse sources. the strategy might increase diagnosis accuracy, treatment focus, and healthcare quality. this research uses cutting-edge deep learning, feature extraction, and fusion techniques. DLESA synthesizes images using convolutional neural networks. Since no one does it by hand, errors are less likely. the Feature Extraction and Fusion Algorithm (FEFA) integrates significant features from several picture approaches to maximize their benefits. CERA and SAEA are essential for picture clarity and line accuracy. Reality reveals that the proposed way performs better than usual. PSNR (13.29%), SSIM (6.98%), CNR (11.61%), and Dice Coefficient (8.54%) have all increased. the technology may be utilized outside of healthcare since it employs science to mix data, learn deep, and extract characteristics. this strategy that integrates multiple disciplines of research might revolutionize how we obtain, analyze, and use information, leading to groundbreaking scientific, technological, and health advances. this novel technology advances diagnostic pictures and data-driven diagnostics, bringing accuracy and comprehension to medical and other disciplines.
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