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共 18747 条记录，以下是531-540 订阅

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Optimized Fog Colony Framework for Efficient Service Placement using Hybrid Genetic Algorithm

Optimized Fog Colony Framework for Efficient Service Placeme...

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2023 International Conference on Decision Aid Sciences and Applications, DASA 2023

作者： Verma, Nilesh Kumar Naik, K. Jairam National Institute of Technology Dept. of Computer Science & Engineering Raipur India

ISBN: (纸本)9798350342055

The transition from Cloud Computing to Fog Computing is being investigated as the preferred method for rapid data processing in Internet of Things (IoT) applications. Fog computing is a decentralized computing paradigm, harnesses the computational capabilities of IoT devices at the network edge to perform data processing and provide real-time services. However, effective service placement in fog environments remains a challenge. This research paper focuses on the lack of efficient techniques for organizing fog devices into optimal fog colonies that possess self-rule capabilities and require minimal energy for administration. We propose a hierarchical clustering-based fog colony architecture to fill this void, which will allow for in-dept. investigation and analysis of various colony configurations. The resulting dendrogram includes all feasible colony configurations, and a genetic algorithm is used for precise colony selection based on fitness and accuracy. The multi-objective hybrid genetic algorithm NSGA-II is used to assess how efficiently the suggested framework performs under a variety of conditions. The goal is to reduce the delay between an app's initial interaction with a user and the initial practice of the app. The results show improvements in reaching predefined goals when the proposed strategy is applied to different contexts. © 2023 IEEE.

关键词： Genetic algorithms

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Generating Textual Video Summaries using Modified Bi-Modal Transformer and Whisper Model 3

Generating Textual Video Summaries using Modified Bi-Modal T...

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3rd International Conference on Advanced Computing Technologies and Applications, ICACTA 2023

作者： Madkaikar, Siddhesh Belhekar, Vipul Dharmadhikari, Yash Tripathy, Amiya Kumar Don Bosco Institute of Technology Dept. of Computer Engineering Mumbai India

ISBN: (纸本)9798350348347

Online video material availability has grown significantly over the past few years, making it challenging for viewers to consume and process information effectively. Video summaries written in text form have shown to be a helpful technique for solving this problem. The key aspects of a video can be accurately and briefly summarised by utilizing methods like video summarising and natural language processing. The purpose of the model is to display a short textual summary of the video to the user before the user watches the complete video. It is frequently difficult and time-consuming for students to locate a suitable educational video. It is occasionally seen on video streaming platforms such as YouTube that the title and the content of the video are not precisely the same. So the model will generate a textual summary of the video and the user can read the summary and get to know about the content of the video. Also, this approach to summarizing videos is helpful in other tasks like video content moderation and could also enable visually-impaired people to consume video material and improve their quality of life. © 2023 IEEE.

关键词： Video recording

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Tourist Place Classification Using Topic Modeling Algorithms 56

Tourist Place Classification Using Topic Modeling Algorithms

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56th International Carnahan Conference on Security technology, ICCST 2023

作者： Wadhe, Apeksha Arun Suratkar, Shraddha S. Vjti Mumbai Dept. of Computer Engineering & Information Technology 400019 India

ISBN: (纸本)9798350315875

Today social media is one of the most powerful and popular tool which is expanding rapidly in the world. Many tourism websites publish tourist places data for describing places in the form of Description. Over this data, Analysis can be performed and meaningful insights can be drawn. By analyzing this data we can find the subject or topic discussed in Description. By performing topic modeling over these data we can predict the category of tourist place. Also topic Modeling can help to cluster textual content into groups as per the subject of the text. In research study, Comparative analysis of topic modeling algorithms has been performed which will find a category of tourist places. Tourist place description blog data was gathered from tourism websites. Using tourist place Description dataset, comparative study of Topic modeling algorithms i.e. LDA Variational Inference(VI) algorithm and LDA Gibbs Sampling(GS) algorithm has been performed. Results of experiments has been analyzed with performance evaluation using various factors such as coherence score, perplexity, training execution time and accuracy percentage. LDA Gibbs Sampling(GS) algorithm outperforms LDA Variational Inference (VI) algorithm in terms of coherence score, perplexity, accuracy percentage. Whereas, LDA Variational Inference(VI) algorithm requires less execution time as compared to the LDA Gibbs Sampling(GS) algorithm © 2023 IEEE.

关键词： Websites

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Cross-Database Facial Expression Recognition using CNN with Attention Mechanism 14

Cross-Database Facial Expression Recognition using CNN with ...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Chandra, Jatin Annappa, B. Rashmi Adyapady, R. National Institute of Technology Dept. of Computer Science and Engineering Karnataka India

ISBN: (纸本)9798350335095

Facial expression is one of the most effective and universal ways to express emotions and intentions. It reflects what a person is thinking or experiencing. Thus, the expression recognition is one of the key aspects of understanding non-verbal communication and interpreting emotions in social interactions. Some emotions are very confusing, and separating the features between them becomes difficult because they share the same feature space. For example, the distinction between fear, anger, and disgust is confusing. This work tried to improve the model's class-wise performance to detect each class correctly. A distinct combination of deep-learning models is used to calculate the performance of the model, such as ResNet, XceptionNet, DenseNet, etc. The datasets like Real-world Affective Faces Database (RAF-DB), Japanese Female Facial Expression (JAFFE) & Facial Expression Recognition 2013 Plus (FER+) are used to evaluate the model's performance. The proposed model achieved better results and overcame the previous work's limitations. CDE's performance on RAF-DB and FER+ evaluations was significantly better than the current SOTA methods, with an increase in accuracy of 5.18% and 3.98%, respectively. © 2023 IEEE.

关键词： Face recognition

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Distress Detection Using a Hybrid SVM - CNN Classifier 1

Distress Detection Using a Hybrid SVM - CNN Classifier

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

作者： Varsha, Modha Aithal, Yukthi R Fathima, Sufia Sen, Snigdha Global Academy of Technology Dept. of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798350339727

Due to the escalating frequency of reported crimes, there has been a surge in research endeavors focused on various approaches to enhance monitoring and surveillance techniques. As opposed to vision-based applications, which are currently the most used framework for monitoring purposes, audio-based systems can be more flexible and relatively less intrusive. While current research studies predominantly utilize images as the primary input for Deep Learning (DL) algorithms, it is worth noting that sound can also serve as a valuable source of input for these models. In this paper, we propose and develop a novel hybrid deep learning model for identifying and detecting people in distress by their screams. The working of our proposed system is built by integrating sound detection module and DL model which will help us to detect if a person is in distress or not. The system uses hybridization concept consisting of Support Vector Machine (SVM) and Convolutional Neural Network (CNN) models, with the audio snippet undergoing 3 levels of classification, with the accuracy of each level found to be 93%, 100% and 92% respectively. The audio data is finally classified as an instance of distress or no-distress. © 2023 IEEE.

关键词： Support vector machines

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Blockchain-Based Music Streaming Services: A Novel Approach to Transparent Artist Control 3

Blockchain-Based Music Streaming Services: A Novel Approach ...

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3rd IEEE International Conference on Blockchain and Distributed Systems Security, ICBDS 2024

作者： Ashtagi, Rashmi Deshmukh, Tanmay Jadhav, Swati Bidwe, Ranjeet Akkalkot, Afsha Buchade, Amar Uke, Nilesh Banerjee, Sudipta Vishwakarma Institute of Technology Dept. of Computer Engineering Pune India Symbiosis Institute of Technology Dept. of Cse Pune India Coep Technological University Dept. Name of Computer Engineering Pune India Data Science Vishwakarma Institute Technology Dept. of Artificial Intelligence Pune India Indira College of Engineering and Management Pune India Symbiosis Institute of Technology Pune India

ISBN: (纸本)9798350354348

Artists have historically used music as a form of personal expression. However, due to the centralized nature of music streaming services, artists receive only a small percentage of the revenue generated and have no control over their content produced. To address these issues, a revolutionary technique is needed that provides artists with greater control and transparency over their output. This paper focuses on a decentralized strategy that utilizes blockchain technology to facilitate direct interaction between artists and users, enabling artists to upload their music, sell songs, and receive royalties. The implementation of blockchain technology could potentially revolutionize the music industry by ensuring that rightful owners receive payment for their music while reducing the waste of paying intermediaries. Without intermediaries involved in the distribution process, the music industry could pay out more royalties to rights holders automatically and instantaneously. The proposed solution also addresses piracy concerns through the use of encryption and watermarking techniques. Blockchains provide security, confidentiality, tamper-proofing, traceability, control, and oversight over information. By developing a secure, self-installing, cross-platform reader positioned on the header of the digital content file, The research empowers data owners to manage the flow of information even after it has been made available. The suggested approach enables content owners to control their digital content and monitor its most popular components after distribution. The blockchain-based system also benefits from token distribution among the content's owner, distributor, and consumer. The simulation results demonstrate that our approach is capable of overcoming the flaws of the existing system. © 2024 IEEE.

关键词： Blockchain

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Quote Detection: A New Task and Dataset for NLP 7

Quote Detection: A New Task and Dataset for NLP

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7th Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, LaTeCH-CLfL 2023

作者： Tekir, Selma Güzel, Aybüke Tenekeci, Samet Haman, Bekir Ufuk Izmir Institute of Technology Dept. of Computer Engineering Izmir35430 Turkey

ISBN: (纸本)9781959429548

Quotes are universally appealing. Humans recognize good quotes and save them for later reference. However, it may pose a challenge for machines. In this work, we build a new corpus of quotes and propose a new task, quote detection, as a type of span detection. We retrieve the quote set from Goodreads and collect the spans through a custom search on the Gutenberg Book Corpus. We run two types of baselines for quote detection: Conditional random field (CRF) and summarization with pointer-generator networks and Bidirectional and Auto-Regressive Transformers (BART). The results show that the neural sequence-to-sequence models perform substantially better than CRF. From the viewpoint of neural extractive summarization, quote detection seems easier than news summarization. Moreover, model fine-tuning on our corpus and the Cornell Movie-Quotes Corpus introduces incremental performance boosts. Finally, we provide a qualitative analysis to gain insight into the performance. © 2023 Association for Computational Linguistics.

关键词： Random processes

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Text Filtering Insignificant Word (TFIW) Readability Framework Model to Explain NLP in Sentiment Analysis Using Reinforcement Machine Learning 2

Text Filtering Insignificant Word (TFIW) Readability Framewo...

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2nd International Conference on Recent Trends in Microelectronics, Automation, Computing, and Communications Systems, ICMACC 2024

作者： Kandakatla, Rajesh Kumar, V Dhilip Vel Tech Rangarajan Dr. Sagunthala R & D Institute of Science and Technology Dept. Computer Science and Engineering Chennai India BVRIT HYDERABAD College of Engineering for Women Dept. Computer Science and Engineering Hyderabad India

ISBN: (纸本)9798350366570

Reading of a text in a given sentence have lot of parameters to consider for expressing an opinion on a given text to conclude nature of the text. The data which need to be formed in the form of data sets based on specific constrains. The Natural Language Processing (NLP) will always presume that Text readability made as the considerable measure for better round spread of any newspaper. The data related to these documents must be collected and store them in data sets. During this process of measuring text readability at the granular level of the text reading is a cumbersome task. This will always implicate a problem of machine readability of the text and explainability of the text taken from the documents mentioned above. In this context human readability will act an important role in predicting the text reading at granular level where the text-based sentiment analysis have been predicted through a machine learning model. The text reading has been evaluated in order to improve the readability through explainable system. The explainable systems will capture and explain the predictions of text reading. In this technical work an explainable system Text Filtering Insignificant Word (TFIW) is introduced where it improves the textual reading at the granule level based on sentiments by prediction the words which need to be filtered. This will improve the explainability of text and text reading and improve the fast text and explainability of the document. © 2024 IEEE.

关键词： Reinforcement learning

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Alumni Management and Networking System 2

Alumni Management and Networking System

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2nd International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation, ICAECA 2023

作者： Rajini, S. Hari, Prasad B Upendrasingh, A. Dept. of Computer Science and Engineering Kumaraguru College of Technology Coimbatore India

ISBN: (纸本)9798350306811

The Alumni Management and Networking System aims to address the challenges of alumni disconnection and facilitate effective communication and engagement between educational institutions and their alumni. The system provides a platform for institutes to create profiles, connect with fellow alumni and offers opportunities for alumni to contribute to the institution's success through mentorship, volunteering, and other forms of support. This paper reviews existing research on alumni management systems, highlighting their strengths, limitations, and gaps. It evaluates different approaches such as centralized systems, data collection methods, interactive questionnaires, secure messaging, and tag recommendation systems. The proposed Alumni Network Management System incorporates content-based tagging, utilizing a fine-tuned BERT model trained on a dataset of 10,000 Twitter posts. This approach generates relevant tags for new social media posts, enhancing content visibility and discoverability. Additionally, it employs end-to-end encryption for secure messaging, ensuring privacy and confidentiality. The system's implementation has been tested successfully, showcasing its user-friendliness and effectiveness in managing alumni databases. The results indicate that the system provides a convenient platform for alumni to update their information, stay connected, and engage with their alma mater. © 2023 IEEE.

关键词： Cryptography

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Quantum Inspired Zeroshot Classification For Adverse Drug Reactions Detection From Social Media Reviews

Quantum Inspired Zeroshot Classification For Adverse Drug Re...

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2024 International Conference on Artificial Intelligence and Emerging technology, Global AI Summit 2024

作者： Dey, Arijit Shrivastava, Jitendra Nath B. P. Poddar Institute of Management and Technology Dept. of Computer Applications WB Kolkata India Invertis University Dept. of Computer Science and Engineering UP Bareilly India

ISBN: (纸本)9798350379716

A deep learning model enhanced with quantum transformer has been introduced in detection of adverse reactions of drugs within the reviews collected from social media written in English language. This proposed model enhanced the human language understanding for detecting adverse reactions of drug. Quantum transformers are used for position embedding and attention purpose. Variational quantum circuit encoded the human language and identify the relevant components of the input reviews as class feature vectors to develop a relationship network for each drug correspond to the condition and review comments on which probability distribution functions applied to detect ADRs found in a medicinal product or not. The correctness of advanced model architecture built on quantum transformer is quite encouraging, and it performs better than other cutting-edge learning models. Achieved an accuracy of 93% with a loss of 0.0393 with this proposed model. Though it is too early to declare that quantum computing has completely replaced. This proposed quantum enhanced transformer helps to show the direction towards quantum enhanced hybrid model design in research. © 2024 IEEE.

关键词： Distribution functions

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