Implementation of Reliability Antecedent Forwarding Technique Using Straddling Path Recovery in Manet

Basha, S. Rahamat; Sharma, C.B.; Sayeed, Farrukh; Arularasan, A. N.; Pramila, P. V.; Shinde, Santaji Krishna; Pant, Bhasker; Rajaram, Anand; Yeshitla, Alazar

doi:10.1155/2022/6489185

Cited by 34 publications

(7 citation statements)

References 20 publications

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“…In any case, the current calculations have a few disadvantages: the connections between pixels are not being viewed as the calculation is not reasonable for huge informational collections and does not genuinely do well when the informational index has further commotion that the target classes are lapping. It is difficult to track down the ideal angles [14][15][16][17][18]. Along these lines, the inner parts of the retina make the most common way of finding veins troublesome.…”

Section: Existing Systemmentioning

confidence: 99%

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[Retracted] Recognition of Diabetic Retinopathy with Ground Truth Segmentation Using Fundus Images and Neural Network Algorithm

Kshirsagar

Manoharan²,

Meshram³

et al. 2022

Computational Intelligence and Neuroscience

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Diabetes problems can lead to a condition called diabetic retinopathy (DR), which permanently damages the blood vessels in the retina. If not treated, DR is a significant cause of blindness. The only DR treatments currently accessible are those that block or delay vision loss, which emphasizes the value of routine scanning with high-efficiency computer-based technologies to identify patients early. The major goal of this study is to employ a deep learning neural network to identify diabetic retinopathy in the retina’s blood vessels. The NN classifier is put to the test using the input fundus image and DR database. It effectively contrasts retinal images and distinguishes between classes when there is a legitimate edge. For the resolution of the problems in the photographs, it is particularly useful. Here, it will be tested to see if the classification of diabetic retinopathy is normal or abnormal. Modifying the existing study’s conclusion strategy, existing diabetic retinopathy techniques have sensitivity, specificity, and accuracy levels that are much lower than what is required for this research.

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Section: Existing Systemmentioning

confidence: 99%

“…e network receives input. e parameters, or weights, translate the input into a set of final guesses made by the network [14][15][16][17][18][19][20][21][22].…”

Section: Nn Process and Detectionmentioning

confidence: 99%

[Retracted] Recognition of Diabetic Retinopathy with Ground Truth Segmentation Using Fundus Images and Neural Network Algorithm

Kshirsagar

Manoharan²,

Meshram³

et al. 2022

Computational Intelligence and Neuroscience

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“…Te use of these smart grid characteristics to grid-connected microgrids has considerable promise. If this system is implemented successfully, it can serve as an example of sustainable development for many regions of Asia, where almost 40% of the population lacks access to power [15][16][17][18][19][20]. In this study, PowerFlexHouse, a research center for investigating the technical possibilities of active load control in a distributed power system with a high penetration of renewable energy, is introduced.…”

Section: Literature Reviewmentioning

confidence: 99%

Intelligent Controller Design and Fault Prediction Using Machine Learning Model

Kumar

Pande

Kumar

et al. 2023

International Transactions on Electrical Energy Systems

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In a solar power plant, a solid phase transformer and an optimization coordinated controller are utilized to improve transient responsiveness. Transient stability issues in a contemporary electrical power system represent one of the difficult tasks for an electrical engineer due to the rise in uncertain renewable energy sources (RESs) as a result of the need for green energy. The potential for terminal voltage to be adversely impacted by this greater RES raises the possibility of electrical device damage. It is possible to use a solid state transformer (SST) or smart transformer to address a transient response issue. These devices are frequently employed to interact between RES and a power grid. SST features a variety of regulated converters to maintain the necessary voltage levels. This method can therefore simultaneously lessen power fluctuations and transient responsiveness. In order to improve the quality of RES power injections and the electrical system’s transient stability, this work provides a controller design for a solar photovoltaic (SPV) system that is connected to the grid by SST. The optimization of a controller model is proposed by modifying a PI controller taken from a commercial one. With the use of IEEE 39 standard buses, the proposed controller is tested. When evaluating the effectiveness of a suggested controller, it is important to take into account a variety of solar radiation patterns as well as a time delay uncertainty that can range from 425 ms to 525 ms. According to simulation results, the proposed controller can be employed to lessen power fluctuation brought on by unpredictable RES. Additionally, the proposed coordinated regulation of SPV and SST can prevent catastrophic damage in the event of substantial disturbances like a circuit breaker collapsing to expand a power line due to a fault by inhibiting significant voltage cycles within an electronic appliance’s rated voltage limit. The results indicate that a transitory stability issue in a modern power system caused by an unforeseen increase in RES may be addressed utilizing the suggested controllers as alternatives.

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“…here, the corrected error covariance matrix is denoted as 􏽢 P k and the value of R gives the noise measurement of the covariance matrix. us, the noise measurement of the magnetometer sensors and gyroscope is obtained [38][39][40][41][42][43][44][45].…”

Section: Extended Kalman Filter (Ekf) ¶mentioning

confidence: 99%

Onboard Pointing Error Detection and Estimation of Observation Satellite Data Using Extended Kalman Filter

Dhanalakshmi¹,

Bhavani

Raju

et al. 2022

Computational Intelligence and Neuroscience

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The satellite communication is embellished constantly by providing information, ensuring security, and enables the communication among huge at a particular time efficiently. The satellite navigation helps in determining the people’s location. Global development, natural disasters, change in climatic conditions, agriculture crop growth, etc., are monitored using satellite observation. Hence, the satellite includes detailed information data, and it must be protected confidentially. The field of the satellite is enhanced at an astonishing pace. Satellite data play an important role in this modern world; hence, the onboard-satellite data must secure through the proper selection of error detection and estimation schema. Lightweight deep learning algorithm based on Extended Kalman Filter (KFK) is proposed to detect and estimate onboard pointing error such as an error in attitude and orbit. The Extended Kalman Filter (EKF) is widely used in the satellite system. EKF is utilized in this proposed model to detect the onboard pointing error such as attitude and orbit determination. An autonomous estimation of orbit position is possible through space-borne gravity. The information obtained through the observation of satellite data is compared with the accurate gravity model in detecting the error. The utilization of EKF reduces the dependence of the ground tracking system in satellite determination. The orbital altitude and orbital position are the most important challenges faced in the satellite determination system. The satellite model using the Extended Kalman Filter is an optimum method in estimating the orbital parameters. The errors in the linearization process are detected, and this can be overcome through the proper selection of linear expansion point with the EKF algorithmic model with the Jacobian matrix calculation. The results show that the EKF implementation helps in attaining better accuracy than other methodologies. Its contribution is enormous to many space missions, autonomous rendezvous and docking for manned and unmanned missions (e.g., ISS operations and beyond, in-orbit servicing, and in-orbit refueling), routine satellite OD operations, orbital debris removal systems, Space Situational Awareness (SSA) operations, and others.

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Implementation of Reliability Antecedent Forwarding Technique Using Straddling Path Recovery in Manet

Cited by 34 publications

References 20 publications

[Retracted] Recognition of Diabetic Retinopathy with Ground Truth Segmentation Using Fundus Images and Neural Network Algorithm

[Retracted] Recognition of Diabetic Retinopathy with Ground Truth Segmentation Using Fundus Images and Neural Network Algorithm

Intelligent Controller Design and Fault Prediction Using Machine Learning Model

Onboard Pointing Error Detection and Estimation of Observation Satellite Data Using Extended Kalman Filter

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