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GeoCamp Online Reviewing Application Using NodeJS and MongoDB 6

GeoCamp Online Reviewing Application Using NodeJS and MongoD...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Lohani, Bhanu Prakash Singh, Devang Pratap Kumar, Navneet Akhil Singh, Pankaj Ansari, Salim Amity School of Engineering and Technology Department of Computer Science and Engineering Greater Noida India Amity School of Engineering and Technology Department of Computer Science and Engineering Uttar Pradesh Greater Noida India Lloyd Law College Uttar Pradesh Greater Noida India Lloyed Institute of Engineering and Technology Uttar Ptadesh Greater Noida India

ISBN: (纸本)9798350304480

Today's consumers frequently use online search to reduce the perceived risk involved with relying on unfamiliar businesses and services. Consumers may turn to online reviews in particular (i.e., reviews written by other customers of a product), and many are likely to believe online reviews more than suggestions from friends and family. © 2023 IEEE.

关键词： Campgrounds Full Stack Online Reviewing

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Twitter Sentiment Analysis using Machine Learning 12

Twitter Sentiment Analysis using Machine Learning

引用

12th International Conference on Cloud Computing, Data science and engineering, Confluence 2022

作者： Ikram, Abdullah Kumar, Mohit Munjal, Geetika Computer Science And Engineering Amity School Of Engineering Uttar Pradesh Noida India Computer Science And Engineering Amity School Of Engineering And Technology Uttar Pradesh Noida India

ISBN: (纸本)9781665437011

In this exponentially evolving age of technology, the emergence of social media has enveloped all life forms on our planet. Twitter is that social media platform on which millions of users post their opinions or sentiments as tweets daily on a plethora of topics. Sentiment analysis is a technique for analyzing source material, determining its sentiment, and categorizing it as favorable, negative, or unbiased. Twitter Sentiment Analysis is the utilization of several libraries in order to collect data from the Twitter API on a topic, assess it, and derive public and private views on it. It is of immense importance for a corporation to employ opinion mining to examine its online reputation for maximizing its profits. This study aims to acquire and transform the dataset named Sentiment140 from an unstructured to a structured format through data preprocessing, perform feature selection on the dataset, train, evaluate, and compare various machine learning models using it, and utilize the classifier that achieves the highest accuracy along with vectorization through a pipeline to identify the sentiment of a new tweet given as an input. © 2022 IEEE.

关键词： Sentiment analysis

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FaceWave: SVM and Wavelet Transformation-Based Face Recognition Framework for Women Cricketers 4th

FaceWave: SVM and Wavelet Transformation-Based Face Recogni...

引用

4th International Conference on Frontiers of Electronics, Information and Computation Technologies, ICFEICT 2024

作者： Kumar, Sachin Prasad, Vivek Kumar Bhattacharya, Pronaya Dutta, Pushan Kumar Tikadar, Subrata Bhushan, Bharat Department of Computer Science and Engineering Institute of Technology Nirma University Gujarat Ahmedabad309081 India Amity School of Engineering and Technology Amity University West Bengal Kolkata700135 India Department of Computer Science and Engineering School of Engineering and Technology Sharda University Greater Noida201310 India

ISBN: (纸本)9789819653171

Advancements in machine learning (ML) have significantly enhanced image processing algorithms, leading to notable improvements in face recognition technology. The paper introduces a framework, FaceWave, which uses a support vector machine (SVM) model combined with wavelet transformation to extract vital facial features from female cricketers. The integration addresses the existing challenges of identifying facial features in context of lighting, posture, and angles. In the framework, raw images are first collected using the Google Chrome Fatkun addon. These images undergo a thorough preprocessing stage to enhance their quality and remove any noise or artifacts. Subsequently, wavelet transformation is applied to derive significant features from the facial images. The processed feature vectors are then utilized to train our SVM model. Our model demonstrates impressive accuracy, achieving 76% during training and 84% during testing. These results highlight the robustness of FaceWave in accurately identifying female cricketers, showcasing the potential of our customized approach in this specialized application. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Wavelet decomposition

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Short Range Visible Light Communication: LED Based Applications 5th

Short Range Visible Light Communication: LED Based Applicati...

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5th EAI International Conference on Cognitive Computing and Cyber Physical Systems, IC4S 2024

作者： Mishra, Sumita Grover, Jyoti Gupta, Nishu Electronics and Communication Engineering Department Amity School of Engineering and Technology Amity University Uttar Pradesh Lucknow Campus India Computer Science and Engineering Department Malaviya National Institute of Technology Jaipur India VTT Technical Research Centre of Finland Ltd. Oulu Finland

ISBN: (纸本)9783031770746

Visible Light Communication (VLC) systems are capable of providing significantly higher data rates compared to traditional wireless technologies. Apart from high data rate, other advantages offered by VLC are license free spectrum, improved security, and no environmental radiation hazards. Light Emmiting Diode (LED) based VLC systems allow visible light to be used for indoor communications and high-precision positioning. But widespread deployment of VLC is limited due to several challenges such as layout modification to the current infrastructure, limited bandwidth of optical source, and the need to combat problems caused by ambient light and shadowing in VLC applications. This paper explores the current state of VLC and its various short range applications and presents an inclusive review on design challenges and their potential solutions. © ICST Institute for computer sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Radiation hazards

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Stock Price Prediction for Market Forecasting Using Machine Learning Analysis 4th

Stock Price Prediction for Market Forecasting Using Machine ...

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4th International Conference on Computing, Communications, and Cyber-Security, IC4S 2022

作者： Prasad, Vivek Kumar Savaliya, Darshan Sanghavi, Sakshi Sakariya, Vatsal Bhattacharya, Pronaya Verma, Jai Prakash Shah, Rushabh Tanwar, Sudeep Institute of Technology Nirma University Gujarat Ahmedabad India Department of Computer Science and Engineering Amity School of Engineering and Technology Amity University West Bengal Kolkata700135 India

ISBN: (纸本)9789819914784

A common opinion of stock market in society is that the stock market is either insecure to invest in or troublesome to trade, so many people are disinterested. The stock market is a marketplace that facilitates the acquisition and sale of business stock. The stock index has its unique value on each stock exchange. The index is the average value calculated by aggregating the prices of several stocks. The forecast of the entire stock market is time-varying and depends on the stock price movement. The seasonal variance and steady flow of any index helps both professional as well as amateur investors understand and decide whether to invest in shares and the stock market. Individuals and businesses alike can be affected significantly by the stock market. As a consequence, accurately anticipating stock movements can lower the risk of losing money while increasing profits. To address these issues, time series analysis will be the most effective tool for predicting the trend or even the future. This article represents the comparison of LSTM, ARIMA and SARIMAX models for stock price prediction. It is observed that error for ARIMA model is less as compared to SARIMAX model. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Deep neural networks

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Transfer Learning Approach for Detection of Autism Spectrum Disorder using Facial Images 10

Transfer Learning Approach for Detection of Autism Spectrum ...

引用

10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and computer engineering, UPCON 2023

作者： Patel, Krisha Ramanuj, Ashwini Sakhiya, Sohan Kumar, Yogesh Rana, Ajay Pandit Deendayal Energy University Department of Computer Science and Engineering Gandhinagar India Amity School of Engineering and Technology Amity University UP Greater Noida India

ISBN: (纸本)9798350382471

Autism Spectrum Disorder (ASD) is characterized by deficits in social interaction, communication issues, and repetitive behavioral patterns. Effective ASD intervention and assistance depend on early detection and diagnosis. Children with autism differ noticeably from normally developing (TD) children in their patterns of facial features. Autism may be indicated by a child's eyes, nose, and lip distances as well as their placement. Using common evaluation measures like accuracy, sensitivity, and specificity, the built ASD detection system is assessed. The outcomes of this study show the utility of facial image analysis in the identification of ASDs. The proposed strategy shows potential in aiding physicians and researchers in early diagnosis by utilizing face clues and machine learning techniques. This study aims to investigate how well machine learning and feature extraction algorithms based on deep learning can identify ASD in young children. Deep convolutional neural networks known for their capacity to extract significant characteristics from images, VGG16 and VGG19, are used. Several machine learning algorithms, such as logistic regression, support vector machines (SVM), naive Bayes,, and artificial neural networks (ANN), are then applied with the retrieved characteristics as input. © 2023 IEEE.

关键词： Autism Deep Learning Facial Images Machine Learning medical feature extractions VGG16

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Evaluation of Trust Establishment Mechanisms in Wireless Networks: A Statistical Perspective 1

引用

3rd International Conference on Machine Learning, Advances in Computing, Renewable Energy and Communication, MARC 2021

作者： Choudhary, Ashutosh Kumar Rahamatkar, Surendra Department of Computer Science & Engineering Amity School of Engineering & Technology Amity University Chhattisgarh Raipur India Amity School of Engineering & Technology Amity University Chhattisgarh Raipur India

ISBN: (数字)9789811928284

ISBN: (纸本)9789811928277

Establishing trust in wireless networks requires the network designer to incorporate different levels of security protocols in the network. These security protocols enable certain checks in the network which if found to be followed properly increase the trust level of nodes. A very simplistic trust establishment example is a network where in all nodes have IP (internet protocol) addresses starting with prime numbers. In such a network, if a node with a non-prime IP join in, then the other network nodes can identify this new (or discovered) node as an attacker and block communications with it. But for large-scale networks, complex trust establishment algorithms are needed, which can provide multi-level checks and thereby enhance the overall security of the network. In order to design a trust-based network, it is necessary for the network designers to evaluate and select the best protocol(s) suited for their network. To perform this task, a large amount of design time is dedicated to protocol evaluation, which delays network deployments. Thus, this text provides a statistical comparison of different trust establishment protocols applied to wireless networks and assists network designers to select the best suited protocol for their application. Moreover, this text also recommends certain upgradations to the existing protocols in order to further improve their security levels. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Wireless networks

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Balancing Usability and Security Innovative Approaches to Privacy in Digital Environments

Balancing Usability and Security Innovative Approaches to Pr...

引用

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

作者： Baswaraju, Swathi Yadav, M. Geeta Nijhawan, Ginni Rana, Ajay Rani, T. K. Pushpa Al-Rubaye, Taqi Mohammed Khattab New Horizon College Of Engineering Department Of Computer Science - Data Science Bangalore India Institute Of Aeronautical Engineering Department Of Computer Science And Engineering Telangana Hyderabad India Lovely Professional University Phagwara India Amity School Of Engineering And Technology Amity University Greater Noida India Mlr Institute Of Technology Department Of Computer Science And Engineering Telangana Hyderabad India College Of Medical Technologies The Islamic University Department Of Medical Laboratory Technology Najaf Iraq

ISBN: (纸本)9798350366846

Data analysis, private protection, detecting unusual things, identifying people, and transferring data are part of the study's unique security design. The major system method is AUA. Your authentication level depends on your activity, device, and location. Context-aware Privacy uses AUA to tailor user privacy options. Encrypting AES data transfers with Secure Data Transfer (SDT) is offered. Machine learning anomaly detection (ADML) analyzes user behavior and implements security measures to uncover vulnerabilities rapidly. DPDA employs controlled noise to make it statistically tougher to identify a person while processing data to safeguard privacy. Ablation study indicates adaptive security design strategies function better together. The recommended design may be safer and easier to employ with visual models and performance testing. With this knowledge, managers may be able to create business-friendly security solutions. Finally, the framework's extensive and adaptable security models boost digital safety. It offers new privacy protection in the internet age. © 2024 IEEE.

关键词： Data Analytics

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Honeypot Comparison of Attack Detection and Mitigation of SSH Attack 3

Honeypot Comparison of Attack Detection and Mitigation of SS...

引用

3rd IEEE Delhi Section Flagship Conference, DELCON 2024

作者： Ali, Wasif Sajid, Ahthasham Ghodke, Tanvi Ajit Malik, Rida Malik, Neeru Kaushik, Keshav Riphah Institute of System Engineering Riphah International University Department of Cyber Security Islamabad Pakistan Pimpri Chinchwad University Department of Computer Science and Engineering Maharashtra India School of Engineering & Technology Pimpri Chinchwad University Maharashtra Pune India Amity School of Engineering and Technology Amity University Mohali India

ISBN: (纸本)9798331518592

This research study addresses the importance of honeypots at multiple levels, which includes but not limited to placement in network or group of networks working alongside in an organization. This paper talks about the usage of multiple honeypots working alongside to log useful data for the mitigation of ongoing bot or actual attack this approach helps the organization better understand the threat they are dealing and the techniques which they can use to overcome the gap of the unseen security risks. The comparison will shed better light to the working and attack patterns of the ongoing attacks, gaining more confidence on using the honeypot for better protection. This allows strategic, optimized and critical insight to the evolving attack patterns. © 2024 IEEE.

关键词： Network intrusion

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Improving Trust Levels In Wireless Networks Using Blockchain Powered Dempster Shaffer Route Optimization 1

Improving Trust Levels In Wireless Networks Using Blockchain...

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1st International Conference on Technologies for Smart Green Connected Society 2021, ICTSGS 2021

ISBN: (纸本)9781607685395

Improved node and network trust levels in wireless networks assist the network to have better security and quality of service (QoS) performance, Security performance is measured in terms of number of attacks detected and mitigated by the network, while QoS performance is measured in terms of end-to-end delay, communication throughput, energy requirement, and packet delivery ratio metrics. In order have good trust levels in the network, a wide variety of methods including reputation evaluation, historical analysis, temporal network & node analysis, etc. are proposed by network researchers. Implementation of these algorithms increases computational complexity of the network, thereby increasing end-to-end delay during communication. During routing, repeated calculations of trust in the network further increases number of computational steps required for route selection. These added calculations improve network security but reduce overall QoS at node and network level. Moreover, if these calculations are simplified for reducing computational complexity;then QoS improves but network security is compromised. In order to maintain a high network QoS with sufficient level of security;this paper proposes a novel blockchain powered routing model that uses Dempster Shaffer (DS) route optimization. The model utilizes node-to-node distance, energy efficacy, and temporal packet forwarding capabilities in order to select the most efficient routing strategy. This strategy is combined with a proof-of-work (PoW) based blockchain solution, that allows the network to have high trust levels. Due to decentralized processing, the network is able to have good QoS levels along with high security. Results of the proposed model were compared with existing models;and it is observed that the underlying architecture is 10% efficient in terms of end-to-end delay, consumes 12% lower energy, and can detect & mitigate Masquerading, Sybil, and Flooding attacks with high efficiency. © The Electrochemic

关键词： blockchain Dempster Shaffer QoS security Trust

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