An Improved Trusted On-Demand Multicast Routing with QoS for Wireless Networks

Arivuselvan, K

doi:10.30534/ijatcse/2020/39912020

Cited by 12 publications

(9 citation statements)

References 6 publications

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“…Gopal et al [21] shows that due to advances in electronics and wireless communication, small-scale sensor nodes had developed that include data processing, sensing, and communication components. WSN was deployed which is regarded as a notable improvement compared to conventional wired sensor networks.…”

Section: Literature Reviewmentioning

confidence: 99%

Utilization of huffman coding for weather buoy system using long-range communication

Velasco¹,

Credo²,

Salazar³

et al. 2021

IJATEE

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Weather defines the short-term condition of the atmosphere in a certain region, while climate is the statistical weather condition at a given place during a specified period of time. Climate change describes the change of weather patterns over time within the range of decades to millions of years. According to studies, earth is experiencing climate change due to human activities. This past decade, predicting the weather condition has become a tough problem that humans encounter everywhere around the world. This sometimes results in an inaccurate weather prediction. But in order to predict and lessen the possibilities that risk and harm people's lives, developing marine weather information like buoys is done. Deploying weather buoys in the ocean helps predict weather conditions in a specific location in real-time. It is used to monitor the conditions of the ocean's surface and deep below it. *Author for correspondenceThe buoys also help to forecast natural phenomena such as earthquakes and storms by using sensors to gather different parameters such as air temperature, air density, relative humidity, wind speed, rainfall, solar radiation, water temperature and salinity profile [1].In predicting weather conditions, deploying weather buoy can now be deployed together with Wireless Sensor Networks (WSNs). WSNs are used in different areas of technology involving environment monitoring, medicine fields, logistics, etc. New Internet of Things (IoT) innovations, such as Long Range (LoRa), is evolving, allowing for very long wavelengths of power-efficient wireless connectivityLoRa is a technology is rapidly turning up and is used because of its technical advantages such as the lifetime of battery, long range, security and more [2]. LoRa has a good resistance to interference and provides

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Section: Literature Reviewmentioning

confidence: 99%

Utilization of huffman coding for weather buoy system using long-range communication

Velasco¹,

Credo²,

Salazar³

et al. 2021

IJATEE

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show abstract

“…Their method uses hybrid PCA called PCANet for segmentation and SVM for segmentation classification together called PCA-SVMNet. Their experiment shows high efficiency in recognizing unknown handwritten number classification without any segmentation method applied [15] Yue Yin; Wei Zhang [1] have concluded that out of all neural network implementations CNN method is valid for OCR based image classification systems. They claimed that OCR had become a preliminary technique in the field of computer vision; they state that if an image classification model performs well in OCR, then it can be used for any image classification systems.…”

Section: Related Workmentioning

confidence: 99%

Effective Handwritten Digit Recognition using Deep Convolution Neural Network

Bharadwaj¹

2020

IJATCSE

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This paper proposed a simple neural network approach towards handwritten digit recognition using convolution. With machine learning algorithms like KNN,SVM/SOM, recognizing digits is considered as one of the unsolvable tasks due to its distinctiveness in the style of writing. In this paper, Convolution Neural Networks are implemented with an MNIST dataset of 70000 digits with 250 distinct forms of writings. The proposed method achieved 98.51% accuracy for real-world handwritten digit prediction with less than 0.1 % loss on training with 60000 digits while 10000 under validation.

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“…The UTKFace dataset has different images with a life span from 0 to 100 and around 10000 images and more [13]. Each image has close and clear facial features along with expressions, different poses, and the images are at various resolutions.…”

Section: Datasetmentioning

confidence: 99%

Age and Gender prediction using Convolution, ResNet50 and Inception ResNetV2

Meghana¹

2020

IJATCSE

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Age and gender prediction are used extensively in the field of computer vision for surveillance. Advancement in computer vision makes this prediction even more practical and open to all, thus enables the world to come up with datasets, one of which, used in this paper, is UTKFace that has 1000 pictures of male and female actors ageing from 0 to 100. In this paper, we propose a Convolution Neural Network (CNN) with ResNet50 architecture to predict age and gender. CNN is a Neural Network (NN) algorithm that extracts the deep features from the image and specifies the desired output at the final layers. Age prediction is approximately near to the real values with a five difference in both ways. Gender prediction is accurate in all the test data presented to the model. Validating with arguments shows no change in training and validation. Our model successfully executed with approximately 80% in gender prediction and 60% in age prediction that can be furtherly advanced with pipelining with other classification models and much larger real-world datasets.

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An Improved Trusted On-Demand Multicast Routing with QoS for Wireless Networks

Cited by 12 publications

References 6 publications

Utilization of huffman coding for weather buoy system using long-range communication

Utilization of huffman coding for weather buoy system using long-range communication

Effective Handwritten Digit Recognition using Deep Convolution Neural Network

Age and Gender prediction using Convolution, ResNet50 and Inception ResNetV2

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