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共 35836 条记录，以下是381-390 订阅

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Text-Based Sentimental Analysis to Understand User Experience Using Machine Learning Approaches 9

Text-Based Sentimental Analysis to Understand User Experienc...

引用

9th International Conference on Advanced Computing and Communication Systems, ICACCS 2023

作者： Gokulapriya, R. Sambandam, Rakoth Kandan Balamurugan, M. Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350397376

Data Analysis is turning into a driving force in every industry. It is a process in which data is analyzed in multiple ways to come to certain conclusions for the given situation. Sentiment analysis can be said to be a sub-section of data analysis where analysis is carried out on the emotions and opinions of the text. Social media has a plethora of sentiment data in various forms such as tweets, updates on the status, and so forth. Sentiment analysis on the huge volume of data can help in identifying the opinions of the general *** primary goal is to find the opinion of customers on the services of the Bangalore airport and to enhance the nature of these services according to the feedback provided. In this paper, we aim to measure customer opinion on services provided by Bangalore Airport through sentiment. Data is collected by a python-based scraper. The tweets are processed to determine whether they are of positive or negative opinion. These opinions are then analyzed to determine the factors which cause the negative opinions and the airport staff are alerted about the same. Various algorithms were used as part of the experimental analysis. LSTM produces more accuracy compared with existing approaches. © 2023 IEEE.

关键词： Python

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Enhanced Security Measures for Image Privacy: Encryption Perspectives 2

Enhanced Security Measures for Image Privacy: Encryption Per...

引用

2nd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2024

作者： Omshith, R. Balaji, Vemisetti Pavan Rahul, Rayapudi Venkata Kumaran, U. Amrita School of Computing Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350327533

A key technology in information security, picture encryption is intended to safeguard the integrity and confidentiality of digital photographs. Using a variety of cryptographic techniques and algorithms, the original image is transformed into an encrypted format throughout this process, making it more difficult for unauthorized users to view or understand the content. Secure communication, picture sharing, medical imaging, and many more fields requiring the protection of sensitive visual data find widespread use in image encryption. A key technology in information security, picture encryption is intended to safeguard the integrity and confidentiality of digital photographs. It also discusses the difficulties and potential paths for picture encryption, highlighting the rising demand for reliable, effective, and secure image encryption solutions in a world that is becoming more and more networked and data-driven. Advanced Encryption Standard (AES) is more secure than (Exclusive OR) XOR, Fernet. © 2024 IEEE.

关键词： Advanced Encryption Standard Confidentiality Encryption Exclusive OR (XOR) Fernet Integrity

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Intelligent Video Surveillance System 4

Intelligent Video Surveillance System

引用

4th International Conference on Expert Clouds and Applications, ICOECA 2024

作者： Aryan, Ansh Singh, Dharya Pratap Kumar, Nitish Amity University Dept. of Computer Science and Engineering Uttar Pradesh India

ISBN: (纸本)9798350385793

This research study provides the utilization of an intelligent video surveillance system, a sophisticated technology that integrates video cameras, sensors, and cutting-edge software to monitor and analyze activities within a designated area or locale. By seamlessly combining compute r vision and machine learning techniques, it goes beyond conventional video surveillance installations to provide real-time insights along with automated alerts. Intelligent video surveillance systems harness the power of machine learning and computer vision algorithms to analyze video feeds in real-time, empowering them to detect, track, and comprehend objects, individuals, and occurrences captured within the video frames. Furthermore, these systems can recognize a variety of objects, including cars, people, animals, and particular objects, even in complex and crowded settings. They also offer a variety of analytical tools and insights that are very helpful to organizations and security operations, such as traffic patterns, heatmaps, and other data. This research study provides a thorough explanation of the modern uses of machine learning in the field of surveillance systems. Two crucial issue statements are addressed by it in practice: the identification of human falls and the detection of auto accidents. This study's main goal is to demonstrate an end-to-end system that will act as a beacon for law enforcement and medical personnel, giving them the ability to quickly identify traffic accidents and serious injuries and guarantee that the necessary assistance is provided on time. © 2024 IEEE.

关键词： Deep learning

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Physical Layer Authentication via Underwater Acoustic Multipath Channel Crafting

Physical Layer Authentication via Underwater Acoustic Multip...

引用

OCEANS 2024 - Halifax, OCEANS 2024

作者： Eccher, Davide Casari, Paolo University of Trento Dept. of Information Engineering and Computer Science Trento Italy

ISBN: (纸本)9798331540081

With the increasing number of actors in the under-water environment and the development of new applications, such as large-scale monitoring and autonomous underwater vehicle control, securing underwater communications is becoming a primary necessity. Security was not prioritized in the past due to the constraints of underwater acoustic communications, which cannot sustain the overhead of typical cryptographic techniques. In this paper, we propose a method to authenticate a network device by exploiting the physical properties of the acoustic channel. In particular, our method hinges on the uniqueness and quasi-reciprocity of the channel, from which the authenticator (Alice) node can extract several parameters such as the number of multi path channel components, their delay and amplitude. These values are similar on both ends of a link between Alice and a legitimate transmitter (Bob), and can be used as a seed to craft a new artificial channel, that is then applied to transmissions from Bob to Alice. With this procedure, Alice can distinguish Bob from an impersonating attacker (Eve), given a previous message exchange history. Eve can try to bypass the protocol by estimating the channel parameters and by trying to replicate Bob's signal by crafting a similar channel. In our tests, we observe that the estimation error for Eve, caused by her wrong channel estimates, becomes significant even for short distances betwen Eve and Bob. This error results in a discrepancy between the signal generated by Eve and the one expected by Alice, and reveals Eve as an attacker. © 2024 IEEE.

关键词： Underwater acoustics

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Leukaemia: A Comparative Analysis of Deep Learning Models Using ALL Dataset 6

Leukaemia: A Comparative Analysis of Deep Learning Models Us...

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6th IEEE International Conference on Recent Advances in Intelligent Computational Systems, RAICS 2024

作者： Sudheer, Rhea Vivek, Rapaka Ramesh, Richa Sarvade, Apoorva Kakarla, Sada Preethi, P. Pes University Dept. of Computer Science and Engineering Karnataka Bangalore India

ISBN: (纸本)9798350381689

White blood cells, also known as leukocytes, or WBCs, spread abnormally in the bone marrow and blood, resulting in leukaemia (blood cancer). Leukaemia can be identified by pathologists by examining a patient's blood sample under a microscope. By counting different blood cells and physical characteristics, they can identify and classify leukaemia. This method takes a lot of time to forecast leukaemia. The pathologist's professional qualifications and experiences may also have an impact on this process. Traditional machine learning and deep learning techniques in computer vision are useful road maps that improve the precision and speed of identifying and categorizing medical images, such as minuscule blood cells. This paper offers a thorough analysis of the different Deep CNN models for identification and classification of WBCs and acute leukaemia in microscopic blood cells. © 2024 IEEE.

关键词： Contrastive Learning

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Utilizing Genetic-Neural System Fusion for Advanced Prediction and Classification of Damage Intensity in Road Traffic Accidents 2

Utilizing Genetic-Neural System Fusion for Advanced Predicti...

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2nd International Conference on Advancement in Computation and computer Technologies, InCACCT 2024

作者： Rahi, Parvez Kang, Sandeep Singh Singh, Ajay Pal Singh, Inderjeet Chandigarh University Dept. of Computer Science & Engineering Punjab Mohali India

ISBN: (纸本)9798350371314

This study proposes an analysis and prediction framework for road traffic accidents (RTAs) in the hilly terrain of Himachal Pradesh and several states in, India, integrating machine learning techniques such as neural networks (NNs) and genetic algorithms (GAs). Utilizing a comprehensive dataset comprising historical accident records, geographical features, weather conditions, and demographic information specific to Himachal Pradesh, the framework aims to identify patterns and correlations contributing to RTAs. Neural networks are employed to discern complex relationships within the data, while genetic algorithms optimize model parameters for enhanced predictive accuracy. By forecasting accident-prone areas and periods, this approach enables proactive interventions and targeted road safety measures. The outcomes of this research provide valuable insights for stakeholders and policymakers, facilitating the reduction of RTAs and mitigating their impact in the challenging terrain of Himachal Pradesh including all states of India. © 2024 IEEE.

关键词： Genetic algorithms

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Blockchain Based Credit System to Increase the Creditability through Carbon Offset Level 5

Blockchain Based Credit System to Increase the Creditability...

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5th IEEE International Conference on Computing, Power, and Communication Technologies, IC2PCT 2024

作者： Padmavathi, A. Reddy, G. Charan Santhosh, Gauri Amrita Vishwa Vidyapeetham Dept. of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350383522

Our country has relied significantly on agriculture as its main source of income for several decades. The demand for food and crops is growing due to the growing population, which offers the agriculture sector tremendous prospects for growth. However, despite the soaring demand and bright future, India's agriculture industry has failed to demonstrate appreciable profitability. In the paper that follows, we provide a novel strategy meant to revolutionize agricultural marketing networks. Blockchain technology is included in our approach to enable the virtualization of products and carbon offset certificates. This system encourages agricultural producers to reduce carbon emissions and address environmental concerns. By utilizing blockchain in a particular way, carbon offset credits can be used to securely track, trade, and for other fostering sustainability practices. This integration of technologies assures to change how agricultural products are marketed currently. It also helps in promoting sustainability and provides consumers with all the valuable information about the environmental impact of their purchases. © 2024 IEEE.

关键词： Blockchain carbon offset credits Product visualization virtualization

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Prompt-Based Domain Incremental Learning with Modular Classification Layer 27

Prompt-Based Domain Incremental Learning with Modular Classi...

引用

27th European Conference on Artificial Intelligence, ECAI 2024

作者： Wang, Boyu Ma, Yue Qiu, Qinru Dept. of Electrical Engineering and Computer Science Syracuse University United States

ISBN: (纸本)9781643685489

Continual learning is referred to as machine learning model's ability to learn a sequence of tasks or data over time without forgetting previously learned knowledge. In particular, we focus on domain incremental learning where the model trained on one domain, e.g., real-life photos, has to be augmented to accommodate data from new domains, e.g., cartoon images. Typical incremental learning relies on rehearsal-based methods, which store trained samples in a buffer and replay them during training alongside new data. This results in significant memory overhead and raise concerns about data privacy. Recently, prompt-based methods address these challenges and outperform them by utilizing the pre-trained Vision Transformer (ViT) and replacing the replay buffer with a prompt pool. However, existing prompt-based models fail to capture domain-specific knowledge and perform poorly in domain incremental learning. In this paper, we propose "domain prompt incremental learning via dynamic neural network", which combines the advantages of architecture-based and prompt-based methods. Specifically, our framework maintains two types of prompt: a instance-level prompt that improves the model's generalization ability is shared across all input samples;and a domain prompt that encodes domain-specific knowledge is assigned for each task. Furthermore, a separated classification head is trained for each domain so that the model has a pre-trained ViT and an ensemble of classification layers, one for each domain. The experimental results shows that our approach outperforms state-of-the-art methods by 2.3% in average on two domain incremental learning (DIL) benchmarks. © 2024 The Authors.

关键词： Contrastive Learning

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Twitter Scraping and Sentiment Analysis on Stock Price

Twitter Scraping and Sentiment Analysis on Stock Price

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2024 International Conference on Advances in Data engineering and Intelligent Computing Systems, ADICS 2024

作者： Iniyan, S. Thangakumar, J. Rajendran, P. Selvi Hindustan Institute Of Science And Technology Dept. Of Computer Science And Engineering Chennai603103 India

ISBN: (纸本)9798350364828

social media is useful in the community for sharing and discussing various events with others. The study's main objective is to predict the sign of the stock by sentimental analysis regarding the Hindenburg report on Adani group stocks by obtaining tweets from Twitter. The study's findings will aid in understanding the effect of the Hindenburg report on the stocks of the Adani group. Excel files are downloaded from Twitter containing tweets from social media users. Tweets are cleaned up by eliminating noise data after extraction. Machine learning algorithms, such as Logistic Regression (LR), Linear support classification (SVC), Random Forest (RF), and voting, were used to classify the data into positive, Neutral, and negative groups. © 2024 IEEE.

关键词： Logistic regression

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Performance Analysis of Load Balancing Mechanism in Cloud Computing 1

Performance Analysis of Load Balancing Mechanism in Cloud Co...

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

作者： Halappa, Annaiah Rajesh, A. Government Engineering College Dept. of Computer Science & Engineering Hassan India Jain Technological University Dept. of Computer Science & Engineering Bengaluru India

ISBN: (纸本)9798350323795

The advancement of Information Technology has made cloud computing technology an innovative model for offering its consumers services on a rental basis at any time or location. Numerous firms converted to cloud technology by establishing new data centers because of the flexibility of cloud services. However, it has become necessary to ensure successful job execution and effective resource usage. Load balancing (LB) in cloud computing remains a complex challenge, specifically in the Infrastructure as a Service (IaaS) cloud architecture. A server being overloaded or underloaded is a problem that mustn't happen in the process of cloud access because it would slow down processing or causes a system crash. Hence, to ignore these problems, a suitable resource schedule must be taken, so that system can load balance tasks over all accessible assists. This research suggests effective load-balancing approaches by analyzing the advantages, applications, and disadvantages of conventional LB techniques. The conclusions show that this research provides an exceptional path for researchers to overcome major drawbacks of existing LB techniques and achieves greater efficiency based on makespan, execution and response time, resource usage, efficiency, load balancing and throughput. © 2023 IEEE.

关键词： Infrastructure as a service (IaaS)

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