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International Conference on Confluence The Next Generation Information technology Summit (Confluence)

作者： Swati Aggarwal Nupur Chugh Computer Engineering Netaji Subhas University of Technology (Formerly Netaji Subhas Institute of Technology) New Delhi India

ISBN: (数字)9781728127910

ISBN: (纸本)9781728127927

EEG signals have been investigated in medical and entertainment applications for many years. Recently, researchers have investigated EEG signals as a biometric trait for person identification and authentication. EEG biometric system has achieved reasonable accuracy, yet some of the challenges hinder the development of ready to deploy EEG based biometric systems. This paper highlights the emerging challenges of the EEG biometric system. The authors present the interrelationships among identified challenges and review the published articles quantitatively based on publication time and online library.

关键词： Conferences Cloud computing Data science Electroencephalography Biomedical engineering computer science Identification of persons

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Determining Attention Mechanism for Visual Sentiment Analysis of an Image using SVM Classifier in Deep learning based Architecture 8

Determining Attention Mechanism for Visual Sentiment Analysi...

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8th IEEE International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2020

作者： Das, Papiya Ghosh, Anupam Majumdar, Rana Meghnad Saha Institute of Technology Department of Computer Science India Netaji Subhash Engineering College Department of Computer Science India

ISBN: (纸本)9781728170169

Image (Visual) Sentiment Analysis (ISA) which exhibits the reaction of humans on visual elements for example images and videos, has been an animating and thought provoking problem. ISA demonstrates to apply the fields computer Vision and Natural Language Processing (NLP) for classifying, extracting, and computing the subjective information in analytical fashion. The accomplishment of existing models can be credited to the progress of solid methodology from Image processing and computer Vision. A large portion of present models were attempted to tackle the problem by highlighting visual features from the complete image or video. Whole image features are the foremost anticipated inputs. For increasing the accuracy of the overall ISA system we proposed a deep learning based model including attention mechanism for consideration instrument for centering local regions of an image determining the required sentiment and adding support vector machine (SVM) in place of soft-max classification layer on deep Convolution Neural Network (CNN). We additionally consider the relevant hash tags of an image to put attention weights on CNN layer indicating by the semantic mapping of image regions and hash tags. Our deep learning based proposed framework is accomplished of spontaneously determining sentimental of specified images and it out spaces existing state-of-the-art approaches to VSA. © 2020 IEEE.

关键词： Support vector machines

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Measurement of Variation of Ultraviolet Radiation Due to Different Greenhouse Gases Using Internet of Things 4

Measurement of Variation of Ultraviolet Radiation Due to Dif...

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4th Smart Cities Symposium, SCS 2021

作者： Biswas, Subhradip Biswas, Satyadip Nandi, Satrajit Basak, Raju Dutta, Pushan Kumar Department of Electrical Engineering Netaji Subhash Engineering College India Kalyani Government Engineering College Nadia Kalyani India Computer Science and Engineering Department Ideal Institute of Engineering Nadia India Electrical Engineering Department Techno India University Kolkata India Amity University Kolkata Amity School of Engineering and Technology India

ISBN: (纸本)9781839536588

Sun is the main source of all energy (along with light energy) on Earth. Among the wide range of light, rays come to the Earth from the Sun every moment, the ultraviolet ray is the electromagnetic wave which lies in the wavelength range of 10nm to 400nm, i.e., shorter than visible light but longer than X-rays. Several research works show that this UV ray radiation can cause severe damage to all living things, along with humans on Earth. But the ozone gas layer present in the stratosphere acts like the almighty protector from this harmful UV radiation. But in recent years due to the advancement of technologies, rapid Industrial growth has increased the release of several chemicals in the atmosphere which cause the ozone layer depletion, causing the UV ray to reach the ground. It is known that CFC is the main reason for ozone depletion, yet several greenhouse gases can do severer effects. This paper thoroughly proposes a procedure that could measure UV radiation by smart devices along with creating storage of data for further analysis on the effects of ozone layer depletion by the variation of greenhouse gases. © 2021 IET Conference Proceedings. All rights reserved.

关键词： Greenhouse gases

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Linearity investigation of ultra-low-power cylindrical SOI schottky barrier MOSFET for biomedical and 5G/LTE circuits application 4

Linearity investigation of ultra-low-power cylindrical SOI s...

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4th International Conference on Devices for Integrated Circuit, DevIC 2021

作者： Saxena, Amit Sharma, R.K. Kumar, Manoj Gupta, R.S. Guru Gobind Singh Indraprastha University USICT New Delhi110078 India Netaji Subhas University of Technology East Campus Department of Electronics and Communication Engineering New Delhi110031 India Shaheed Rajguru College of Applied Sciences for Women Department of Electronics Delhi110096 India Maharaja Agrasen Institute of Technology Department of Electronics and Communication Engineering New Delhi110086 India

ISBN: (纸本)9781728199559

Non-linearity is a major challenge for 5G/LTE communication circuit designers. Also, OFF state power consumption in circuits used for biomedical body implant circuits is also a major challenge. Linearity and OFF state power consumption analysis are performed for cylindrical SOI schottky barrier(SB) MOSFET, by extracting FOM's like gm2, gm3, VIP2, VIP3, IIP3, IMD3, 1-dBCP, and IOFF current. The results are compared with dielectric pocket (DP) SB MOSFET and schottky barrier MOSFET. © 2021 IEEE.

关键词： Low power electronics

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Next-Generation PON with Enhanced Spectral Efficiency: Analysis and Design 3rd

Next-Generation PON with Enhanced Spectral Efficiency: Analy...

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3rd International Conference on Optical and Wireless Technologies, OWT 2019

作者： Gupta, Mukesh Kumar Ambrish Singh, Ghanshyam Department of Electronics and Communication Engineering MBM Engineering College Jodhpur India Department of Electronics and Communication Engineering Netaji Subhas Institute of Technology New Delhi India Department of Electronics and Communication Engineering Malaviya National Institute of Technology JaipurRajasthan302017 India

ISBN: (纸本)9789811529252

This model depicts a detailed analysis of spectral efficiency and reach enhancement in next-generation passive optical network (NG-PON). The DPSK modulation format mitigates stimulated Raman scattering (SRS) effects in the fiber and boosts channel capacity with the multi-gigabit transmission rate. At 20 km fiber length, a power loss of 8 dB was observed that is compensated to 7 dB with a pump power of 180 mW. A system is analyzed at 10 Gbps data rate to 128, 32 users for 20 km and 55 km, respectively, in permissible BER. The DPSK modulation with interferometry detection technique provides 0.3 (bits/s)/Hz higher spectral efficiency in comparison with other modulation formats. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Spectrum efficiency

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DiaRet: A browser-based application for the grading of diabetic retinopathy with integrated gradients

arXiv

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arXiv 2021年

作者： Patel, Shaswat Lohakare, Maithili Prajapati, Samyak Singh, Shaanya Patel, Nancy Department of Computer Science & Engineering Netaji Subhas Institute of Technology New Delhi India Department of Computer Science & Engineering Pandit Deendayal Energy University Gandhinagar India Department of Computer Science & Engineering National Institute of Technology New Delhi India Bachelor of Medicine Bachelor of Surgery AMC MET Medical College Ahmedabad India

Patients with long-standing diabetes often fall prey to Diabetic Retinopathy (DR) resulting in changes in the retina of the human eye, which may lead to loss of vision in extreme cases. The aim of this study is two-fold: (a) create deep learning models that were trained to grade degraded retinal fundus images and (b) to create a browser-based application that will aid in diagnostic procedures by highlighting the key features of the fundus image. In this research work, we have emulated the images plagued by distortions by degrading the images based on multiple different combinations of Light Transmission Disturbance, Image Blurring and insertion of Retinal Artifacts. InceptionV3, ResNet-50 and InceptionResNetV2 were trained and used to classify retinal fundus images based on their severity level and then further used in the creation of a browser-based application, which implements the Integration Gradient (IG) Attribution Mask on the input image and demonstrates the predictions made by the model and the probability associated with each class. © 2021, CC BY-NC-ND.

关键词： Eye protection

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An Efficient Approach to Information Hiding through Image Steganography using Edge Detection 4

An Efficient Approach to Information Hiding through Image St...

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4th International Conference on Information Systems and computer Networks, ISCON 2019

作者： Bhardwaj, Mudit Singh, Lovedeep Saini, Khushil Kumar Netaji Subhas University of Technology Department of Computer Engineering Delhi India

ISBN: (纸本)9781728136516

Least Significant Bit (LSB) substitution is the most popular information hiding scheme in spatial steganography. Its popularity lies in the fact that it has very little effect on the cover image and secret message can remain largely unidentified by the human eye, hence, making information exchange more secure. LSB substitution can be further optimised by combining it with edge detection techniques. This is because different regions in cover image can store different number of bits. Complex regions or regions having an edge are less sensitive to change and can hide more data than smooth regions. In this research, a steganographic approach is proposed that combines edge detection based steganographic techniques with Optimal Pixel Adjustment Process (OPAP). Through experiments it is demonstrated that proposed method leads to better image quality at high payloads than even some of the state-of-the-art high capacity steganographic methods. It is also shown that proposed method can have embedding rates up to 3.407 bpp at PSNR value of 35dB, which can't be discerned by the Human Visual System (HVS). This is greater than any other method in literature. © 2019 IEEE.

关键词： Pixels

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Diversity and progress controlled gravitational search algorithm for balancing load in cloud 6th

Diversity and progress controlled gravitational search algor...

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6th International Symposium on Security in Computing and Communications, SSCC 2018

作者： Chaudhary, Divya Kumar, Bijendra Garg, Shaksham Department of Computer Engineering Netaji Subhas Institute of Technology DwarkaNew Delhi110078 India

ISBN: (纸本)9789811358258

Load scheduling is used to distribute load over the cloud. Various load scheduling techniques are used for efficient functioning of cloud. Recently many search based optimization techniques have been successfully used for the process of load scheduling. These optimization techniques considerably reduces the time which is required to solve the problem of load scheduling in cloud computing. This paper discusses about Diversity and Progress Controlled Gravitational Search Algorithm. The results of proposed approach are compared with Gravitational Search Algorithm and Particle Swarm Optimization. Experimental results confirm that the proposed approach is better than PSO and GSA. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Cloud computing

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Detection of Epileptic Seizures using EEG Signals

Detection of Epileptic Seizures using EEG Signals

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International Symposium on Artificial Intelligence and Signal Processing (AISP)

作者： Sarthak Gupta Siddhant Bagga Vikas Maheshkar M. P. S. Bhatia Division of Information Technology Netaji Subhas University of Technology New Delhi India Department of Computer Engineering Netaji Subhas University of Technology New Delhi India

ISBN: (数字)9781728144580

ISBN: (纸本)9781728144597

Epilepsy is a neurological disorder which causes abnormal brain activity such as seizures. Electroencephalogram (EEG) signals are recordings of the electrical activity of brain, which are used extensively in many medical applications, including detection of epileptic seizures. Traditionally, neurologists made inferences by visual inspection. However, this was usually very time consuming and the results are subject to the expertise of the reader. Hence, automatic epileptic seizure detection techniques are needed, which are able to provide high quality results in a short time. In this paper, an approach has been proposed that uses Discrete Wavelet Transform to convert the EEG signal into the time-frequency domain. Approximation and detail coefficients were obtained after the discrete wavelet transform of EEG signals. Then, various features are extracted and then classification is carried out on a number of classifiers including convolutional neural networks, random forests etc for the detection of epilepsy seizure. Results show that our processing technique and the combination of features extracted provide far superior results than those obtained by applying the classifiers on the EEG signals directly. In our work, an accuracy of 99.29 was achieved which outperformed the conventional epileptic seizure detection techniques. The proposed approach is tested on Bonn University's EEG signal dataset.

关键词： Electroencephalography Feature extraction Discrete wavelet transforms Time-frequency analysis Epilepsy Fourier transforms

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Comparative Study for Predicting the Severity of Cyberbullying Across Multiple Social Media Platforms

Comparative Study for Predicting the Severity of Cyberbullyi...

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International Conference on ent Computing and Control Systems (ICICCS)

作者： Akshita Aggarwal Kavita Maurya Anshima Chaudhary Department of Computer Engineering Netaji Subhas University of Technology New Delhi India

ISBN: (数字)9781728148762

ISBN: (纸本)9781728148779

Initially, cyberbullying detection was mostly done by explicit reporting of inappropriate content by users on the internet, but victims usually are not in the mental space to report such instances, which ultimately go unnoticed by the social media websites. A need for automated methods of cyberbullying detection was realized but the current detection methods require massive improvements to correctly determine the extent of cyberbullying. Our paper aims to identify instances of cyberbullying across various social media platforms and classify them based on the level of severity of cyberbullying. We wish to provide a comparative study of various traditional machine learning and deep learning models that can be used for the above *** also wish to release 3 datasets that are annotated in 4 labels based on the severity of cyberbullying (none, low, medium, and high) to be used for future work by the interested person(s). Since young adults are very vulnerable to such incidents, the paper aims to work on social media platforms trending amongst the youth, like Reddit, Twitter, and Formspring.

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