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Sarcasm Detection and Classification Using Deep Learning Model 7th

Sarcasm Detection and Classification Using Deep Learning Mod...

引用

7th International Conference on Soft Computing: Theories and Applications, SoCTA 2023

作者： Rajani, B. Saxena, Sameer Suresh Kumar, B. Narang, Geetika AMITY Institute of Information Technology Amity University Rajasthan Jaipur India School of Computer Science and Engineering Sanjay Ghodawat University Kolhapur India Trinity College of Engineering and Research Maharashtra Puna India

ISBN: (纸本)9789819720880

The Twitter and Facebook kind of web platforms have gained significant traction as prominent mediums for individuals to document and articulate their emotions, viewpoints, and evaluations. The use of appropriate extraction methodologies, such as sentiment analysis, renders this data valuable across several domains. Sarcasm detection is a methodology used to examine individuals’ cognitive and affective states, with the aim of classifying. There are several methods by which individuals might articulate their sentiments. These attitudes are occasionally attended with sarcasm, particularly when expressing strong emotions. Sarcasm has often understood as a kind of communication in which a good statement is made with an underlying negative purpose. The majority of existing research endeavors see these responsibilities as separate entities. Until far, the majority of methods for sentiment and sarcasm classification have been focused on treating them as separate and independent text categorization tasks. Nowadays, there has been notable growth in the field of study using deep learning methods, resulting in substantial improvements in the performance of standalone classifiers. One of the primary challenges encountered by these methodologies is their inability to accurately categorize sarcastic statements as negative. Given this consideration, we assert that possessing the ability to identify sarcasm will contribute to the enhancement of sentiment classification, and conversely, proficiency in sentiment classification will aid in the recognition of sarcasm. Our research has shown a positive correlation between these two activities. This study presents a system that employs a deep neural network and multi-task learning to effectively predict the connection between different tasks, with the goal of attracting the overall concert of sentiment analysis. The approach presented in this study demonstrates superior performance compared to the previous methods, with a notable margin o

关键词： Contrastive Learning

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A Deep Learning Based Approach to Recognize Real Time Emotions 5

A Deep Learning Based Approach to Recognize Real Time Emotio...

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5th International Conference on Contemporary Computing and Informatics, IC3I 2022

作者： Vatsa, Abhimanyu Gupta, Sumita Amity University Amity School of Engineering & Technology Department of Computer Science & Engineering Noida India

ISBN: (纸本)9798350398267

Facial expressions is the most primary way by which a human recognizes another person's emotion. With a rapid development in the field of Artificial Intelligence and Machine learning, research have started to develop and improve a sophisticated technology by which a machine or a computer can recognize emotions and mimic a human's thought process for the same. The proposed methodology for the same is to make use of deep learning. Deep learning is very closely related to machine learning. It allows multiple layers of neural networks to be stacked upon one another enabling our algorithm to 'think' like a human. Many mathematical models are also used to provide the best results and improve on the currently known technology. This paper discusses most of the known approaches for emotion recognition and tests out geometry based using machine learning and deep learning-based implementation providing a deep insight into both methodologies © 2022 IEEE.

关键词： Emotion Recognition

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A Deep Learning based Image Processing Technique for Early Lung Cancer Detection 1

A Deep Learning based Image Processing Technique for Early L...

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1st International Conference on Innovations in Communications, Electrical and computer engineering, ICICEC 2024

作者： Bhatt, Aman Joshi, Kireet Jain, Paras Gupta, Vishan Kumar Vidisha, Vidisha Graphic Era Deemed to be University School of Computer Science & Engineering Dehradun India Graphic Era Deemed to be University Department of Cse Dehradun India Vit Bhopal University School of Computing Engineering and Artificial Intelligence Kothri Kalan MP Bhopal India Amity University Punjab Amity School of Engineering and Technology Punjab Mohali India Amity University Punjab Amity School of Engineering and Technology Mohali India

ISBN: (纸本)9798350376517

The world's most common cause of cancer-related death is still lung cancer, which is mostly caused by rising tobacco use and industrialization in developing countries. Early detection combined with state-of-the-art medical facilities is essential since early diagnosis can drastically lower the death rate. In this study, we used 1,190 CT scan images from the Kaggle IQ-OTH/NCCD lung cancer dataset to test deep learning (DL) techniques. In order to identify high-risk patients, diagnose lung cancer, and predict malignancy, we developed enhanced images representing normal, malignant, and benign instances after completing thorough image preprocessing methods. This allowed for early intervention to avert long-term repercussions. We performed a thorough performance comparison within the framework of conventional Convolutional Neural Networks (CNN). Rigorous image preprocessing techniques such as affine transformation and Gaussian noise were utilized. Our approach achieved a validation accuracy of 99%, demonstrating the efficacy of our preprocessing methodology in reducing model complexity. The comparison highlighted that our suggested preprocessing method resulted in a higher F1-score of 99%, validating the robustness and accuracy of our approach. © 2024 IEEE.

关键词： Lung cancer

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Quant-Meta: Quantum Key Distribution Framework for Telesurgery in Metaverse Environment

Quant-Meta: Quantum Key Distribution Framework for Telesurge...

引用

2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Bhattacharya, Pronaya Ralegankar, Vishaka K Gupta, Rajesh Tanwar, Sudeep Rodrigues, Joel J. P. C. Amity School of Engineering and Technology Amity University Department of Computer Science and Engineering Kolkata700135 India Institute of Technology Nirma University Department of Computer Science and Engineering Ahmedabad382481 India Lusófona University Copelabs Lisbon Portugal

ISBN: (纸本)9798350370218

Advanced robotics, high-speed networking, and real-time haptics have opened a myriad of opportunities to extend telesurgery in Metaverse environments. The telesurgery metaverse (TMs) offers high-quality, immersive, and interactive surgical scenarios. Despite the remarkable progress, TMs suffer from operational threats against quantum-adversarial attacks, which can jeopardize the integrity, reliability, and safety of operated patients. The paper presents a novel framework Quant-Meta, that integrates quantum key distribution (QKD) in TM through the BB84 protocol. A framework is presented for TM, where the surgeon communicates via gestures that are communicated securely to the robotic arm present in a metaverse environment. A quantum channel sets up the BB84 key distribution, and the sender and receiver agree to the shared key. Once it is set up, the communication is supported by a 6G-envisioned tactile internet (TI) channel. which assures high reliability. To ensure high precision, explainable artificial intelligence (XAI) is integrated with the trained model to predict doctor gestures. The framework is analyzed in terms of BB84 protocol design, and quantum channel parameters. The result signifies a high probability of intruder detection and a 19.87 % improvement in channel transmission rate. The quantum bit error rate also likes below 4 %, with a high sifted key rate. The results indicate the potential viability of the framework in practical telesurgical deployments. © 2023 IEEE.

关键词： 6G BB84 protocol Healthcare 5.0 Metaverse Quantum Key Distribution Telesurgery

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An Approach to Generate Music with LSTMN

An Approach to Generate Music with LSTMN

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2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COM-IT-CON 2022

作者： Bhutani, Sparsh Gupta, Sumita Gupta, Dhruv Sehgal, Harshit Singh Amity University Amity School of Engineering & Technology Department of Computer Science &engineering Noida India

ISBN: (数字)9781665496025

ISBN: (纸本)9781665496025

Music was generally considered as a simple sign that was physically produced. Music has become progressively apparent to innovation lately, which can now make a suite out of music with no necessity for human interest. It should beat different specialized obstacles to finish this work, which are portrayed exhaustively in this paper. The paper incorporates a short prologue to music and its parts, as well as references and investigations of significant work by different researchers in the field. The fundamental objective of this examination is to bid a technique for producing melodic notes with Reccurent Neural Networks (RNN's), explicitly Long Short-Term Memory Network (LSTMN) organizations. This procedure is executed involving a model where information is addressed utilizing the ABC representation text record design for more straightforward access and understanding. Preprocessing information before it is likewise depicted to take care of it into the model. Over a solitary layered LSTMN organization, the model utilized in this study is utilized to grasp chorus melodic note successions. For more noteworthy learning, the algo should have the option to hold past subtleties of a melodic grouping and its construction. This paper presents a portrayal of the layered engineering utilized in the LSTMN model, in addition to its intertwining associations for fostering a brain organization. This study gives a slip look into weight and predisposition dispersions in each slab of the model, in addition to a point-by-point portrayal of misfortunes and exactness at each progression and group. After a careful assessment, the model delivered magnificent outcomes in the formation of new songs © 2022 IEEE.

关键词： Music

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Advancing Intrusion Detection Systems Innovative Approaches for Prevention and Response

Advancing Intrusion Detection Systems Innovative Approaches ...

引用

2024 International Conference on Communication, computer sciences and engineering, IC3SE 2024

作者： Reddy, M. Siva Swetha Krishna, B.S.S. Murali Asha, V. Nijhawan, Ginni Rana, Ajay Jabbar, Ahmed Sabah Abed Al-Zahra Institute Of Aeronautical Engineering Department Of Computer Science And Engineering Telangana Hyderabad India Mlr Institute Of Technology Department Of Computer Science And Engineering Telangana Hyderabad India Computer Application New Horizon College Of Engineering Bangalore India Lovely Professional University Phagwara India Amity School Of Engineering And Technology Amity University Greater Noida India The Islamic University Medical Laboratory Technology Department Najaf Iraq

ISBN: (纸本)9798350366846

A group intruder detection system built on K-Nearest Neighbors, Decision Trees, Neural Networks, Support Vector Machines, and Random Forests is shown in this study. A thorough study on ablation shows how the algorithms work together to make breach detection better. We compare how well the suggested method works in terms of memory, F1 score, false negative rate, accuracy, and detection time. Bar charts, line graphs, pie charts, stacked bar graphs, area plots, and scatter plots all show that the new way is better than the old ones. Tables are also used to organize data. An ensemble takes the best features of Random Forests, Support Vector Machines, Neural Networks, Decision Trees, and K-Nearest Neighbors and puts them all together in a single package. Broad powers make the suggested method better at solving cybersecurity problems across a range of review factors. The ablation study shows why each method is important and how they work together to make an adaptive intruder detection system. In a world where safety is always changing, the proposed answer is scalable, flexible, easy to set up, and cheap. © 2024 IEEE.

关键词： Nearest neighbor search

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Employment of Distinct Machine Learning Algorithms for Predicting Fake Tweets 1

Employment of Distinct Machine Learning Algorithms for Predi...

引用

1st International Conference on Computational Intelligence for Information, Security and Communication Applications, CIISCA 2023

作者： Rizwan Khan, Mohd Umair Shahid, Mohd Salman Swami, Shubhanshu Chauhan, Kalpesh Ranjan, Nalin Yadav, Ashok Kumar Aligarh Muslim University Department of Computer Science Aligarh India Amity School of Engineering and Technology Amity University Noida India

ISBN: (纸本)9798350339727

Both positive and negative aspects come with consuming information on social media. On the one hand, although social media is free and user-friendly, and information is circulated quickly, people capitalise it to locate and consume news. As a result, the research issue of spotting fake news on social networking sites is now receiving a lot of attention. First, fake news is deliberately produced to mislead readers, making it difficult and time-consuming to spot based purely on news substance. Second, because of the vast, erroneous, noisy, and unstructured data that individuals' social relationships with disinformation produce, exploiting this additional data is challenging in and of itself. Since it can be difficult and crucial to recognise bogus news on social media, we undertook the survey to support ongoing research. We provide an in-depth review of the identification of false news on social media in this paper, including fake news characterizations based on behavioral and sociological hypotheses, modern techniques for data mining, criteria for assessment, and examples of datasets. We also explore related academic fields, unanswered issues, and potential avenues for further investigation into how to identify bogus news on social networks. © 2023 IEEE.

关键词： Decision trees

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Optimizing Wind Turbine Placement for Enhanced Energy Production Using Modified Genetic Algorithm 7

Optimizing Wind Turbine Placement for Enhanced Energy Produc...

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7th International Conference on Contemporary Computing and Informatics, IC3I 2024

作者： Sudarshan, T.A. Srinivasulu, Ch. Thethi, H. Pal Bhutani, Vijay Subhashini, P. Ramesh, G. New Horizon College of Engineering Department of Mechanical Engineering Bangalore India Institute of Aeronautical Engineering Department of Computer Science and Engineering Telangana Hyderabad50043 India Lovely Professional University Phagwara India Amity University Amity School of Engineering and Technology Uttar Pradesh Greater Noida India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Griet Department of Computer Science and Engineering Bachupally Hyderabad India

ISBN: (纸本)9798350350067

The optimal site of wind farms is determined using an updated genetic algorithm approach, which maximizes output capacity while reducing the amount of turbines built and the area used by each farm. In particular, two examples are examined: One kind of wind is a homogeneous wind that blows in just one direction, while the other two are also possible. In the first scenario (a), 599 individuals were first split into 25 subpopulations and then evolved three thousand times. The evolution of case (b) takes place over three thousand generations, beginning with 600 individuals distributed over 19 subpopulations. Every design's fitness, overall power generation, power output efficiency, and ideal configurations are all part of the findings. The results show that the modified genetic algorithm provides much better results compared to the conventional Genetic Algorithm method. © 2024 IEEE.

关键词： Windmill

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A Novel Technique to Secure Telemedicine Using Blockchain and Visual Cryptography 1

引用

International Conference on. Cryptology and Network Security with Machine Learning, ICCNSML 2023

作者： Mittal, Poonam Vashista, Hariom Srivastava, Atul Department of Computer engineering J.C. Bose University of Science and Technology YMCA Faridabad India Amity School of Engineering and Technology AUUP Uttar Pradesh Lucknow India

ISBN: (数字)9789819706419

ISBN: (纸本)9789819706402

Medical facilities in the different regions of the world are not available as per requirement. More significantly, remote and rural areas have lots of scarcity of quality doctors and diagnosis facilities. Today, the whole world is connected via the Internet which can be used to facilitate medical prescription and diagnosis at distant places. Everything about these facilities is defined by a hypernym that is telemedicine. Medical data of the patients is very confidential and can be misused if someone is able to access the network and retrieve the data. Security mechanisms, such as digital watermarking and other primitive cryptographic technologies, are in use, but these technologies have their limitations. Therefore, there is a need to propose a security mechanism that can provide confidentiality, integrity, and authentication. The research proposes a security mechanism based on blockchain. The security features provided by blockchain, along with cryptographic primitives, can be used to safeguard the information. Most of the medical data is in an image format. The pixels of the data are arranged along with the patient's personal information, and a corresponding hash value is generated. Every terminal in the blockchain network is updated with the basic agreement and a hash value. It is protected with a proof-of-work mechanism which is very complex even to brute force. Along with this, elliptic curve digital signature algorithm and partial homomorphic encryption algorithm are also implemented to further ensure confidentiality, integrity, and authenticity of the data. The paper also presents a use case where we have used visual cryptography as a means to secure the medical images. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Telemedicine

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A Novel Approach to Detect Indian High Security Registration Plates 13

A Novel Approach to Detect Indian High Security Registration...

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13th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2022

作者： Bhardwaj, Arnav Gupta, Sumita Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University Noida India

ISBN: (纸本)9781713857938

In recent times, with the growing number of vehicles, road safety has become a paramount issue. To ensure safe and easy passage of vehicles on the road, it is important that we take help of certain techniques that ensure the road safety regulations are properly followed. The Government of India has mandated the usage of High Security Registration Plate (HSRP) to ensure safety of vehicles, since these plates are tamper proof and cannot be counterfeited easily. In this paper, we have proposed a novel approach to detect the HSRP on a car. The most prominent feature detectable through images of an HSRP is the "IND" text inscribed on it. We have used three License Plate (LP) detection models: Warped Planar Object Detection Network (WPOD-Net), You Only Look Once (YOLO) version 3 (YOLOv3) and version 5 (YOLOv5) to detect the license plate on a car. Once a plate is detected, we apply EasyOCR to determine whether the plate has "IND" inscribed on it or not. A comparative analysis is done on these three models and our experimental results show that WPOD-Net with EasyOCR gives and accuracy of 93.01%, making the proposed approach viable for HSRP detection. © Grenze Scientific Society, 2022.

关键词： Object detection

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