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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Jagadeesan, M. Saravanan, T.M. Selvaraj, P.A. Nithya, S. Snegha, K. Sowmiya, P. Kongu Engineering College Perundurai Department of Computer Applications Erode TamilNadu Perundurai638060 India

ISBN: (纸本)9798350348217

Every day, a great amount of data is generated online in the age of technology. However, an unprecedented amount of material is being disseminated online, most of it false news. Fake news is created to draw in viewers, influence people's opinions and actions, raise click through rates, and have a significant impact on important events like elections. Fake News incorporates material that steers readers in the wrong directions. It may have unfavorable repercussions in the actual world that seek to deceive people, sway public opinion, or attract attention or damage reputation. It is necessary to detect fake news mainly for media outlets to have the capability to attract viewers to their website to generate online advertising revenue. This project develops a SVM approach and uses this model to detect whether the news are fake or not. It uses a fake news dataset, which contains News text and corresponding labels (REAL or FAKE). The pervasive increase in fake news, whether it is produced by humans or algorithms, has a severe social and political impact on society and individuals. The rapid turnover of news in the age of social networks makes it difficult to assess its veracity in a timely manner. Tools for automatically detecting bogus news become essential. K- Nearest Neighbor and a classification based on a support vector machine are utilized in this case to overcome the aforementioned issue. In contrast to other research that merely took particular sentences or phrases into account, The purpose of this study is to investigate a false news posture detection mechanism based on the title and text of the news. Python 3.7 is used in the project's development. © 2023 IEEE.

关键词： Support vector machines

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Prediction and Processing of Environment Geography Images Using Deep Learning Techniques

Prediction and Processing of Environment Geography Images Us...

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2023 International Conference on Sustainable Communication Networks and Application, ICSCNA 2023

作者： Rahunathan, L. Vijayakumar, P. Sivabalaselvamani, D. Nekhaa, T. Nekitha, M. Yaswanth, Paruchuri Kongu Engineering College Department of Master of Computer Applications Tamil Nadu Perundurai638060 India

ISBN: (纸本)9798350313987

Image processing and prediction have grown in popularity in recent years. The term 'image processing' refers to the modification and analysis of digital images using various techniques and approaches. This research study contains four types of images: land, water, cloud, and green area. In addition, models such as CNN and ImageNet are compared. Further, the images are used as input, and deep learning techniques are used to analyze various images and predict the results for both dataset and real-time images. © 2023 IEEE.

关键词： Convolution Neural Networks Deep Learning Image processing and prediction ImageNet

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Digital Evidence Management: Modern Techniques in Digital Forensics 3

Digital Evidence Management: Modern Techniques in Digital Fo...

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3rd International Conference on Electronics and Renewable Systems, ICEARS 2025

作者： Venkataramanan, N. Jayalakshmi, V. Anitha, S. Ganesan, R. Jenifer, V. Drbccc Hindu College Department of Computer Applications Pattabiram Chennai600072 India Department of Computer Science and Applications Ramapuram600089 India Anna University St. Joseph's College of Engineering Department of Artificial Intelligence and Machine Learning Chennai600119 India Vel Tech Rangarajan Dr.Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai600062 India Department of Computer Science and Applications Ramapuram Campus 600089 India

ISBN: (纸本)9798331509675

This research study reviews the significance of digital forensic analysis in modern criminal investigations, highlighting the way it complements conventional methods of inquiry and the difficulties it encounters in the information era. To solve crimes effectively, investigators must combine digital knowledge with traditional forensic techniques. This will enable them to use evidence from many different types of digital and physical sources. The specific intricacies of digital crime scenes need specialized methods for the proper storage and analysis of digital evidence to identify criminal intent and patterns of conduct. To propose Modern Techniques for Digital Evidence Management [MT-DEM] based Digital Forensics Service. Multidisciplinary teams and cutting-edge technology are becoming necessities in digital forensic investigation as the field adjusts to new threats like data encryption and massive amounts of data. The admissibility of evidence in the legal world depends on digital forensic procedures being transparent and adhering to set criteria. Digital forensic analysis has become an indispensable tool for contemporary investigators with the rise of digital evidence. © 2025 IEEE.

关键词： Forensic science

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A Review of Segmentation and Recognition Techniques for Indian Sign Language using Machine Learning and computer Vision 10

A Review of Segmentation and Recognition Techniques for Indi...

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17th INDIACom;2023 10th International Conference on Computing for Sustainable Global Development, INDIACom 2023

作者： Kumari, Subhangi Tarlue, Ernest Diallo, Aissatou Chhabra, Megha Mishra, Gouri Shankar Goyal, Mayank Kumar School of Engineering and Technology Sharda University Department of Computer Science and Applications Greater Noida India

ISBN: (纸本)9789380544472

Indian Sign Language (ISL) is a complex and diverse language used by the deaf and hard-of-hearing community in India. ISL recognition and segmentation have been active areas of research in recent years due to the growing demand for assistive technologies for this population. In this review paper, we provide an overview of the various techniques used for ISL recognition and segmentation using machine learning and computer vision. We begin by discussing the challenges involved in ISL recognition and segmentation, such as the variations in sign language gestures, lighting conditions, and background noise. We then review the literature on various techniques used for ISL recognition. We analyze the strengths and limitations of each technique, comparing their accuracy, speed, and robustness against various factors. Finally, we present the recent advancements and future directions for ISL recognition and segmentation © 2023 Bharati Vidyapeeth, New Delhi.

关键词： Machine learning

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Prediction of Mango Leaf Diseases using Convolutional Neural Network

Prediction of Mango Leaf Diseases using Convolutional Neural...

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2023 International Conference on computer Communication and Informatics, ICCCI 2023

作者： Saravanan, T.M. Jagadeesan, M. Selvaraj, P.A. Aravind, M. Raj, G.Dharun Lokesh, P. Kongu Engineering College Department of Computer Applications Tamil Nadu Perundurai638 060 India

ISBN: (纸本)9798350348217

The Convolutional Neural Network CNN works by obtaining a picture and designating it with some weightage supported by the various objects of the image, to distinguish them from one another. CNN needs little or no pre-processing information as compared to different deep learning algorithms. Early diagnosis and correct identification of mango plant disease prediction will manage the unfolding of the diseases Mango leaf diseases damage mango quality and *** research uses deep learning to automatically identify leaf diseases in different mango plant kinds. The planned work is Associated with the Nursing correct identification approach for the mango plant disease prediction exploitation of the Convolutional Neural Network. It includes generating comfortable method pathological pictures Associate in nursing coming up with a model and a design of the Convolutional Neural Network to discover mango leaf diseases. The image augmentation method is employed to extend the number of images. completely different information augmentation techniques square measure applied to stop overfitting and improve generalization. © 2023 IEEE.

关键词： Forecasting

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A Data Privacy-Preserving Model driven on Differential Approach in Cloud Environment

A Data Privacy-Preserving Model driven on Differential Appro...

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2023 International Conference on Green Energy, Computing and Intelligent Technology, GEn-CITy 2023

作者： Gupta, Rishabh Saxena, Deepika Singh, Ashutosh Kumar Department of Computer Science and Engineering The University of Aizu Aizuwakamatsu Japan Department of Computer Applications National Institute of Technology Kurukshetra India

ISBN: (纸本)9781839539596

With the wide range of cloud services, including flexibility, high scalability, and the least upfront capital investment, it also offers machine learning services that are utilized in various applications, such as medical diagnosis, risk analysis, and product recommendation. Since it has many advantages, many organizations move their data to the cloud platform for storage, processing, and distribution intentions. The classification service is offered by the cloud service provider so that owners can assess their data. It gathers the data from the owners' side for training the machine learning model and accomplishing the classification task. The cloud servers handled by a third party might not be totally trusted by the data owners. However, data privacy is a significant challenge among the critical barriers to preserving data while distributing it. A novel data protection model is proposed, driven on machine learning and differential approaches that carry out classification tasks while protecting the owners' data through noise addition. The model enables the different owners to store, share, and utilize data on the cloud platform. The experiments are carried out on Cleveland, New-Thyroid, and SA-Heart datasets to determine the effectiveness of the model in terms of accuracy, precision, recall, and F1-score. The results show that it achieves high accuracy, precision, recall, and F1-score up to 88.37%, 83.28%, 98.41%, and 82.91%, respectively. © The Institution of engineering & Technology 2023.

关键词： Risk analysis

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Role of ELMo Embedding in Detecting Fake News on Social Media 11

Role of ELMo Embedding in Detecting Fake News on Social Medi...

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11th International Conference on System Modeling and Advancement in Research Trends, SMART 2022

作者： Garg, Sonal Sharma, Dilip Kumar GLA University Department of Computer Engineering and Applications India

ISBN: (纸本)9781665487320

The advancement of technology makes it difficult to distinguish between genuine and false information. Social media allow fake news to spread faster in comparison to conventional media. The propagation of such fake news creates a harmful effect on the public and society. It can also generate biased opinions and disturb the stability of the news ecosystem. To combat the rapid proliferation of fake news on online media, a holistic approach is required. In this paper, we used Elmo word embedding for counterfeit detection. For implementation, the Reuter dataset is used. In particular, This paper used different machine-learning models to evaluate their effectiveness. © 2022 IEEE.

关键词： Embeddings

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Analysis of Network on Chip Topologies 1

Analysis of Network on Chip Topologies

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1st IEEE International Conference on Applied Intelligence and Sustainable Computing, ICAISC 2023

作者： Ramakrishnan, Nithin Sanju, V. Farhanaaz REVA University School of Computer Science and Engineering Bengaluru India REVA University School of Computer Science and Applications Bengaluru India

ISBN: (纸本)9798350323795

The incorporation of multi-core processors using current technologies is a challenging task as establishing effective communication among distant cores consumes significant time, ultimately diminishing the benefits of multi-core functionality. A new technology called Network on Chip (NoC) has been introduced to address this issue and is considered the future of the semiconductor industry. To develop new multi-core processors that outperform existing processors, it is crucial to compare traditional technologies with NoC. The traditional method faces difficulties implementing multi-core systems effectively and establishing efficient communication among different logic units, making NoC a helpful tool for developing multi-core processors. A detailed study of the NoC architecture is necessary, including the understanding of each component of its basic building blocks, such as topology, flow control mechanisms, routing logic, and router micro-architecture, and their performance comparison. This understanding is critical to select the most appropriate NoC architecture for implementing multi-core processors. © 2023 IEEE.

关键词： Network-on-chip

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An implementation of personalized therapy in Clinical Decision Support System using adaptive transformer and hybrid deep learning network

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Australian Journal of Electrical and Electronics engineering 2025年第1期22卷 105-120页

作者： Praveena Rachel Kamala, S. T, Saraswathi. Kaliraj, V. Nithya, A. Hema, R. Ramyadevi, R. Department of Information Technology Easwari Engineering college Tamil Nadu Chennai India Department of CSE S.A Engineering College Tamil Nadu Chennai India Department of Computer Science and Engineering St.Joseph’s College of Engineering Tamil Nadu Chennai India Department of Electronics and Communication Engineering Easwari Engineering College Tamil Nadu Chennai India Department of Computer Science and Applications SRM Institute of Science and Technology Tamil Nadu Chennai India

This paper suggests a new mechanism from deep learning concept for personalised therapy in Clinical Decision Support Systems (CDSS). Basically, the texts used for the observation are acquired from the standard data sources and then forwarded to the text preprocessing task. In the pre-processing phase, the punctuation and special character removal, stop word removal, and stemming process are applied to remove noise and help to eliminate the redundant information in order to improve the data quality. Further, the pre-processed text is applied to the Adaptive Transformer Net (ATN) for the feature extraction purpose, where the attributes in this task are optimally determined with the aid of the Adaptive Walrus Optimization Algorithm (AWOA). Finally, the resultant text is subjected to the Hybrid Deep Learning Network (HDLNet). The HDLNet model is implemented by integrating the ‘Residual Long Short-Term Memory (Residual LSTM) with Dilated Recurrent Neural Network (Dilated RNN)’. From the results, the sensitivity analysis performed in the implemented technique secured 3.7% more efficient than LSTM, 7.76% improved than MobileNet, 6.7% superior to residual LSTM, and 0.90% effective than dilated RNN in dataset 1. Throughout the validation, the conventional techniques are evaluated with the suggested personalised therapy in CDSS to prove its efficacy. ©, Engineers Australia.

关键词： Long short-term memory

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Quantum Cryptography: Mathematical Modelling and Security Analysis 3

Quantum Cryptography: Mathematical Modelling and Security An...

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3rd IEEE Asian Conference on Innovation in Technology, ASIANCON 2023

作者： Takalkar, Atharva Shiragapur, Bahubali School of Computer Science Engineering and Applications D y Patil International University Pune India

ISBN: (纸本)9798350302288

This paper offers a thorough investigation into quantum cryptography, a security paradigm based on the principles of quantum mechanics that provides exceptional guarantees for communication and information protection. The study covers the fundamental principles of quantum cryptography, mathematical modelling, practical applications, and future prospects. It discusses the representation of quantum states, quantum operations, and quantum measurements, emphasising their significance in mathematical modelling. The paper showcases the real-world applications of quantum cryptography in secure communication networks, financial systems, government and defence sectors, and data centres. Furthermore, it identifies emerging domains such as IoT, 5G networks, blockchain technology, and cloud computing as promising areas for implementing quantum cryptographic solutions. The paper also presents avenues for further research, including post-quantum cryptography, quantum cryptanalysis, multi-party quantum communication, and device-independent quantum cryptography. Lastly, it underscores the importance of developing robust infrastructure, establishing standards, and ensuring interoperability to facilitate widespread adoption of quantum cryptography. This comprehensive exploration of quantum cryptography contributes to the advancement of secure communication, information protection, and the future of information security in the era of quantum technology. © 2023 IEEE.

关键词： Secure communication

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