Performance Evaluation of Multiple Transform Watermarking System for Privacy Protection of Medical Data Using PSNR and Nc

Adegboye, Mutiu Adesina; Ajao, Lukman Adewale; Badmus, Taofeeq Alabi

doi:10.15546/aeei-2018-0032

Cited by 1 publication

(1 citation statement)

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“…The fish feeding regime system was implemented using a Multilayer perceptron neural network. The MLPNN was chosen because it has been the most common network employed in pattern classification studies [26], [37]- [40]. Moreover, MLPNN is applicable in both simple and complex input-output relationships with high accuracy.…”

Section: Machine Learning Experimentsmentioning

confidence: 99%

Incorporating Intelligence in Fish Feeding System for Dispensing Feed Based on Fish Feeding Intensity

et al. 2020

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The amount of feed dispense to match fish appetite plays a significant role in increasing fish cultivation. However, measuring the quantity of fish feed intake remains a critical challenge. To addressed this problem, this paper proposed an intelligent fish feeding regime system using fish behavioral vibration analysis and artificial neural networks. The model was developed using acceleration and angular velocity data obtained through a data logger that incorporated a triaxial accelerometer, magnetometer, and gyroscope for predicting fish behavioral activities. To improve the system accuracy, we developed a novel 8-directional Chain Code generator algorithm that extracts the vectors representing escape, swimming, and feeding activities. The set of sequence vectors extracted was further processed using Discrete Fourier Transform, and then the Fourier Descriptors of the individual activity representations were computed. These Fourier Descriptors are fed into an artificial neural network, the results of which are evaluated and compared with the Fourier Descriptors obtained directly from the acceleration and angular velocity data. The results show that the developed model using Fourier Descriptors obtained from Chain Code has an accuracy of 100%. In comparison, the developed classifier using Fourier Descriptors obtained directly from the fish movements acceleration, and angular velocity has an accuracy of 35.60%. These results showed that the proposed system could be used in dispensing feeds successfully without human intervention based on the fish requirements. INDEX TERMS Accelerometer, artificial neural network, aquaculture, chain code, fish, fish activities, fish feeding system, Fourier descriptor, IoT devices.

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Section: Machine Learning Experimentsmentioning

confidence: 99%