Optimization of Energy and Security in Mobile Sensor Network Using Classification Based Signal Processing in Heterogeneous Network

Ramesh, S.; Nirmalraj, S.; Murugan, S. Sakthivel; Manikandan, R.; Al‐Turjman, Fadi

doi:10.1007/s11265-021-01690-y

Cited by 25 publications

(6 citation statements)

References 22 publications

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“…Nolte et.al. [ 12 ] presented that Cartesian representation is better for examining brain connections because the typical magnitude and step of coherency involve the exact details as the actual and imagined sections. Mormann et.al.…”

Section: Literature Surveymentioning

confidence: 99%

A Real-Time Medical Ventilation on Heart Failure Analysis Based on Sleep Apnea Snore and Meta-Analysis

Liu

Zhao

2022

Journal of Healthcare Engineering

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An issue with cardiac ventilation can result in death at any moment throughout a person’s life. The apnea-hypopnea index (AHI) has historically been influenced by medical ventilation on heart failure; nevertheless, the sleep snore analysis is the best model to diagnose. The problems with ventilation are caused by problems with air pressure and blood circulation in the heart valves, where the pathological measures are continually detecting ventilation issues. Understanding the pathophysiology of OSA will have a direct impact on clinical treatment choices as well as the design of clinical studies. Treatments could be tailored to each patient's unique needs based on the fundamental reason to their OSA. Through the OSA treatment, patients could feel better, and understanding OSA symptoms and also outcomes will improve patient’s health; as a result, the study reveals that most of the population are likely to benefit from specific OSA treatment approaches. For achieving the benefits of OSA treatment the classification accuracy is needed to be improved. So, in this research work, an LeNet-100 CNN-based deep learning technology is used to get information and apply the classification approaches. We obtained the heart failure dataset from the Kaggle website for conducting a meta-analysis. An accuracy of 93.25%, sensitivity of 97.29%, recall of 96.34%, and F measure of 95.34% had been attained. This approach outperforms the technology and is comparable to the present heart failure meta-analysis..

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Section: Literature Surveymentioning

confidence: 99%

A Real-Time Medical Ventilation on Heart Failure Analysis Based on Sleep Apnea Snore and Meta-Analysis

Liu

Zhao

2022

Journal of Healthcare Engineering

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“…Big data is mostly about volume. However, this paper exposes all the V family of big data [3]. Vs Big Data gets the lion's share of revenue there is a lot of controversy and confusion about Big Data.…”

Section: Big Datamentioning

confidence: 99%

Exploring the recent trends in Big Data Analysis

Suresh¹,

Ramachandran²,

Sivaji³

2022

Data Analytics and Artificial Intelligence

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Big Data is a collection of technologies developed to store, analyze and manage this data. It is a macro tool. Today it is used in fields as diverse as medicine, agriculture, gambling and environmental protection. Machine learning, forecasting Companies use big data to streamline their marketing campaigns and techniques. Modeling and other advanced analytics applications enable big data organizations to generate valuable insights. Companies use it in machine learning. Programs cannot balance large data in any particular database. When datasets are large in size, velocity, and volume, the following three distinct dimensions constitute "big data." Examples of big data analytics include stock markets, social media platforms, and jet engines. But it is growing exponentially with time. Traditional data management tools cannot store or process it efficiently. It is a large scale technology developed by Story, Analysis and Manoj, Macro-Tool. Find patterns of exploding confusion in information about smart design, however, implying that various big data structures are structured, whether this includes the amount of information, the speed with which it is generated and collected, or the variety or scope of related data points. In the past, data was collected only from spreadsheets and databases of large, disparate information that grew at an ever-increasing rate. Very large, complex data refers to large amounts of data for sets that are impossible to analyze with traditional data processing applications. Is software configuration used to handle the problem? Apache is an advanced application for storing and processing large, complex data sets and analyzing big data. Analytical techniques against very large, heterogeneous databases containing varying amounts of data, big data analytics help businesses gain insights from today's massive data sources. Defined as software tools for processing and extraction. People, companies and more and more machines are now developing technologies to analyze more complex and large databases that cannot be handled by traditional management tools. It is designed to discover patterns of chaos that explode in information in order to design smart solutions.

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“…Gaussian smoothing, window fitting, bilateral filtration, Cane margin detection, calibration, such as arithmetic code and bandwidth change this includes various image processing techniques. Subjective image bandwidth is the basic paradigm for converting an image with a visual model, using an encoding algorithm, then decoding the image from the perceptual domain and then transferring it back to the active domain [19]. In our previous perspective on human visual modeling, it was similar to encoding an image in a form that is at the level of the optic nerve.…”

Section: Image Compressionmentioning

confidence: 99%

Recent Advances in Selection Techniques for Image Processing

Sathiyaraj¹,

Ramachandran²,

Vidhya³

2022

EAE

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The parameters and modifying the code, the library allows students in image processing to learn practical methods. In addition, in addition to teaching programming in the "turtle graphics" paradigm, such as color and dimension and to introduce users to image ideas A new module is provided. Online gallery of examples, in addition to providing an overview of the available activity, commonly used in image processing Introduces several algorithms. These usually include an introduction to the package and an insight, for image processing ideas Provides introductions. Well documented application programming interface (API) contributes to the learning experience with tools that facilitate visualization, It also makes it easier to explore the effect of various algorithms and parameters. So, it is not surprising that there are so many Image processing algorithms for margin extraction, upgrade, rearrangement; data compression, etc. are unambiguous. Artifacts can also be introduced through digital image processing such as margin enhancement. Since artifacts can prevent diagnosis or provide incorrect measurements, it is important to avoid them or at least understand their appearance. It is clear that a pattern independent of the spatial size or scale of image features is required and only emphasizes the range of less-contrasting features. Diversified image processing has been extensively studied not only by computer scientists but also by neurophysiologists, and the approach to improving this image is currently being used in a clinical way. It is well known that the human visual system uses a multifaceted approach.

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Optimization of Energy and Security in Mobile Sensor Network Using Classification Based Signal Processing in Heterogeneous Network

Cited by 25 publications

References 22 publications

A Real-Time Medical Ventilation on Heart Failure Analysis Based on Sleep Apnea Snore and Meta-Analysis

A Real-Time Medical Ventilation on Heart Failure Analysis Based on Sleep Apnea Snore and Meta-Analysis

Exploring the recent trends in Big Data Analysis

Recent Advances in Selection Techniques for Image Processing

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