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检索条件"任意字段=2023 International Conference on Algorithms, Computing and Data Processing, ACDP 2023"

共 6977 条记录，以下是841-850 订阅

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Proceedings of the 2nd international conference on Edge computing and Applications, ICECAA 2023

Proceedings of the 2nd International Conference on Edge Comp...

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2nd international conference on Edge computing and Applications, ICECAA 2023

ISBN: (纸本)9798350347579

The proceedings contain 278 papers. The topics discussed include: SDN-assisted routing scheme in cloud data center using queueing vacation policy;a multi-stage partial homomorphic encryption scheme for secure data processing in cloud computing;an efficient pre-clusters assessment technique for efficient data partitions;optimizing integrated features in mobile devices using kotlin framework;the role of artificial intelligence in biometrics;detection and evaluation of cervical cancer by multiple instance learning;a platform for anonymous tip-off and evidence validation;identification of plants with anti-inflammatory properties from their leaves using machine learning;forecasting future sea level rise: a data-driven approach using climate analysis;artificial neural network using image processing for digital forensics crime scene object detection;speech-to-text and text-to-speech recognition using deep learning;and deep water culture using automated hydroponic systems.

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Techniques to Estimate the Status of Legal Proceedings Considering Sequential Text data 5

Techniques to Estimate the Status of Legal Proceedings Consi...

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5th international conference on Emerging Smart computing and Informatics, ESCI 2023

作者： Mustari, Nafisa Sen, Sanjib Kumar Banik, Ananna Mehedi, Md Humaion Kabir Rasel, Annajiat Alim Brac University Department of Computer Science and Engineering Bangladesh

ISBN: (纸本)9781665475242

The relationship between law and natural language processing is impressively expanding, and it has the potential to fundamentally alter how prosecutors go about their regular tasks. The volume of text produced by legal practitioners is enormous and has not yet been fully inves-tigated by data science. Recent developments in NLP and machine learning allow us the capability to develop forecasting analytics that can be used to identify trends influencing judicial judgments. This study's objective is to generate a classifier that can anticipate judicial decisions in Bangladeshi Supreme Court law. According to our exploratory research, the fundamental facts of a case are the most significant predictor. Then, some of their traits were ascertained from a small sample of judicial subjects. Then, taking these language qualities into consideration, a variety of classifiers were used to forecast the legal results. © 2023 IEEE.

关键词： Natural language processing systems

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E-Commerce Product Review Classification based on Supervised Machine Learning Techniques 9

E-Commerce Product Review Classification based on Supervised...

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9th international conference on Advanced computing and Communication Systems, ICACCS 2023

作者： Dharrao, Deepak Deokate, Sarika Bongale, Anupkumar M Urolagin, Siddhaling Symbiosis Institute of Technology Department of Computer Science and Engineering Pune India Pimpari Chinchwad College of Engineering Department of Computer Science and Engineering Pune India Symbiosis Institute of Technology Department of Artificial Intelligence and Machine Learning Pune India Department of Computer Science and Engineering Birla Institute of Technology & Science Dubai International Academic City P. O. Box No 345055 Dubai United Arab Emirates

ISBN: (纸本)9798350397376

To become a successful organization it is the most important aspect to consider is the customer satisfaction. A business can grow only when the customers enjoy their product/service and how much they recommend it. For the same, companies collect reviews and ratings from its customers to understand their perspective better. Amazon is also such a giant, which values its customers' opinions. It is very difficult or nearly impossible to have a detailed manual scan of each and every review for each and every product available on the website. This is where NLP (Natural language processing) comes into picture. It processes human language from text to arrays of numbers in order to find sense in the text so that the machine learning algorithms can process them further and classify the texts. This project focuses on processing the amazon reviews of various categories and products and then classify them into 5 ratings, from 1 to 5, worst to best respectively. The supervised machine learning algorithms used to process these reviews are Support Vector machines (SVM), Naïve Bayes classifier and Decision Tree classifier. The analysis of comparison of these algorithms has also been discussed using accuracy score bar charts. © 2023 IEEE.

关键词： Sentiment analysis

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data Engineering Techniques for Efficient and Accurate Human Physical Activities data Collection: a Summary of the State-of-the-art 2

Data Engineering Techniques for Efficient and Accurate Human...

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2nd Edition IEEE international conference on Metrology for eXtended Reality, Artificial Intelligence and Neural Engineering, MetroXRAINE 2023

作者： Abdullayev, Javidan Zingoni, Andrea Western Caspian University Department of Information Computing and Technology Baku Azerbaijan University of Tuscia Department of Economics Engineering Business and Society Viterbo Italy

ISBN: (纸本)9798350300802

This contribution presents an overview of engineering techniques to collect human behavior data, highlighting the main research trends and challenges. From our research it emerged that wearable and smartphone sensors are popular for monitoring movement and vital signs, although accuracy can be influenced by environmental factors. Combining multiple sensors improves data accuracy, while machine learning algorithms enable pattern detection and behavior analysis. Non-invasive techniques, such as video monitoring and speech analysis, offer a comprehensive view of behavior. Despite all the positive advancements, there are still remaining challenges that require further research, including the need to enhance sensor accuracy, develop sensor fusion methods, and refine machine learning algorithms for improved data analysis in human activity monitoring. © 2023 IEEE.

关键词： Artificial intelligence data engineering Human behavior Human monitoring Physical activity Sensors

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The data and Images of Natural Disaster News Report Based on Artificial Intelligence Technology processing 15

The Data and Images of Natural Disaster News Report Based on...

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15th international conference on Computer Research and Development, ICCRD 2023

作者： Wang, Chunxiao Peng, Ruiqi Computer Science City University of Hong Kong Beijing China Data Journalism Communication University of China Beijing China

ISBN: (纸本)9781665487504

In recent years, the technology of writing data news report by using artificial intelligence has been rapidly developed. The news that is generated automatically has strong timeliness. However, due to lack of humanistic care, it can't be widely used in long reports. Based on the collection and analysis ability on data of artificial intelligence, the data news can be completed by program algorithms and machine learning. By taking use of natural disaster data extracted by crawler, and achieving recognition and classification of disaster weather warning images by convoluted networks, this paper comes up with the model of data and images in the natural disaster news report based on artificial intelligence technology processing. © 2023 IEEE.

关键词： Disasters

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FedDHr: Improved Adaptive Learning Strategy Using Federated Learning for Image processing

FedDHr: Improved Adaptive Learning Strategy Using Federated ...

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2023 international conference on Self Sustainable Artificial Intelligence Systems, ICSSAS 2023

作者： Velagapudi, Anuhya Jhansi, B. Hemalikha, M. Vijayalakshmi, P. Koneru Lakshmaiah Education Foundation Department of Artificial Intelligence and Data Science Andhra Pradesh Vaddeswaram India

ISBN: (纸本)9798350300857

FL (Federated learning) has grown in popularity as a field of research that allows for the training of an algorithm over many decentralised servers that are having local data samples without requiring data exchange. Numerous application domains (like medical image analysis diagnosis made by doctors) lack a significant amount of properly labeled and full data that can be found in one place. Due to the prevalence of artificial intelligence in new application sectors, there are few rising issues on privacy of data and user. New algorithms of various research works are analysed in this study and it introduces a new technique that address the data heterogeneity and adaptive learning rate of the model to perform Image processing, Deep Learning. © 2023 IEEE.

关键词： Electronic data interchange

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Quantum computing's Double-Edged Sword Unravelling the Vulnerabilities in Quantum Key Distribution for Enhanced Network Security

Quantum Computing's Double-Edged Sword Unravelling the Vulne...

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2023 IEEE international conference on Next Generation Electronics, NEleX 2023

作者： Anantraj, I. Umarani, B. Karpagavalli, C. Usharani, C. Lakshmi, S. Jothi Sri Krishna College of Engineering and Technology Department of Computer Science and Business Systems Coimbatore India Kongunadu College of Engineering and Technology Department of Electronics and Communication Engineering Namakkal India Ramco Institute of Technology Department of Artificial Intelligence and Data Science Rajapalayam India

ISBN: (纸本)9798350319088

Quantum computing has emerged as both a boon and a bane in the realm of network security. This paper delves into the intriguing interplay between quantum computing and the vulnerabilities of Quantum Key Distribution (QKD) protocols, a cornerstone of secure quantum communication. While QKD offers unmatched security through the principles of quantum mechanics, it is not impervious to attacks in the age of rapidly advancing quantum computing. We examine these vulnerabilities, highlighting the challenges of ensuring the long-term security of quantum networks in a post-quantum world. Through a comprehensive exploration of threat models and the practicality of QKD, we uncover potential weaknesses in quantum network security. In particular, we investigate QKD's susceptibility to evolving quantum algorithms, hardware vulnerabilities, and post-processing security concerns. This work aims to provide a roadmap for understanding and addressing these vulnerabilities, ensuring the continued robustness of quantum communication networks, and fostering the development of post-quantum cryptographic solutions. As quantum computing advances, its implications for quantum network security are far-reaching. This study underlines the critical need for research and innovation in securing quantum communication. By unravelling the vulnerabilities within Quantum Key Distribution and exploring post-quantum cryptographic alternatives, this research contributes to the development of more resilient and secure quantum networks, safeguarding sensitive information and communications in an increasingly quantum-enabled world. © 2023 IEEE.

关键词： Quantum cryptography

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A Method for Analyzing data in Measuring Devices Using a Specialized computing System for Synthesizing and Evaluating Statistical Hypotheses 5

A Method for Analyzing Data in Measuring Devices Using a Spe...

引用

5th international conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2023

作者： Tarasov, Ilya RTU MIREA Laboratory of Specialized Computer Systems Moscow Russia

ISBN: (纸本)9798350309126

The article examines the application of a method for processing experimental data in measurement systems by generating hypotheses about the presence of a given set of parameters and estimating their probability. The difference between the method is the use of the error probability distribution function with an independent parameter "distribution scale"and the search for a combination of process model parameters at which the posterior probability function takes the maximum value. The method is characterized by high resistance to impulse noise, as a result of which it can be used in measuring systems. A special feature of the method is the large number of calculations required to generate hypotheses and test their probability. To solve this problem, a parallel computing system architecture has been proposed that generates hypotheses and evaluates them using independent processing elements. © 2023 IEEE.

关键词： Impulse noise

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Prefetching-based Adaptive Video Streaming Strategy on Edge computing 29

Prefetching-based Adaptive Video Streaming Strategy on Edge ...

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29th IEEE international conference on Parallel and Distributed Systems, ICPADS 2023

作者： Yi, Xuanyu Zhou, Jipeng Jinan University Department of Computer Science Guangzhou China Jinan University School of Data Science of Guangzhou Huashang College Department of Computer Science Guangzhou China

ISBN: (纸本)9798350330717

Dynamic Adaptive Streaming over HTTP (DASH) is a widely adopted video streaming protocol. Adaptive Bitrate Streaming (ABR) algorithm is utilized to dynamically switch between different bitrates. However, traditional ABR algorithms have gradually failed to meet users' demands for high-quality video transmission, especially in complex network environments. Thus, the current research focus has shifted towards enhancing the accuracy of algorithm. The advent of edge computing has brought new possibilities for DASH transmission. Edge computing-based algorithms can make decisions from a more macroscopic perspective, which can enhance algorithm efficiency. In this paper, we propose an edge computing-based strategy that enables the edge server to obtain the actual file size of the next segment at every bitrate. As a result, edge servers can obtain more informations. We further propose an edge-based system model that assists the ABR algorithm in achieving better operational efficiency. With additional information, the algorithm located at the edge node possesses the capability to make more precise decisions, which is advantageous for enhancing the quality of experience (QoE) for users. Our experiments demonstrate that the proposed strategy can significantly enhance QoE and network resource utilization. © 2023 IEEE.

关键词： DASH Edge computing Video Streaming

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Ranking on Heterogeneous Manifold for Multimodal Information Retrieval 21

Ranking on Heterogeneous Manifold for Multimodal Information...

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21st IEEE international Symposium on Parallel and Distributed processing with Applications, 13th IEEE international conference on Big data and Cloud computing, 16th IEEE international conference on Social computing and Networking and 13th international conference on Sustainable computing and Communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Jin, Zhenkun Wan, Xingshi Nie, Xin Zhou, Xinlei Yi, Yuanyuan Zhou, Gefei Wuhan Business University Wuhan Research Institute of Posts and Telecommunications Wuhan China Wuhan Research Institute of Posts and Telecommunications Wuhan China Huazhong University of Science and Technology Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security Wuhan China Huazhong University of Science and Technology School of Journalism and Information Communication Wuhan China Huazhong University of Science and Technology School of Computer Science & Technology Wuhan China

ISBN: (纸本)9798350329223

In light of recent advancements in Internet of Multimedia Things (IoMT) and 5G technology, both the variety and quantity of data have been rapidly increasing. Consequently, handling zero-shot cross-modal retrieval (ZSCMR) of unlabeled multi-modal data has emerged as a prominent research topic. Early models utilized generative adversarial networks and class embeddings to assist in building a common feature space. However, this approach resulted in a loss of reliability in the feature distributions of individual modalities. In this paper, we propose a method called Ranking on Heterogeneous Manifold (RHM) to address the aforementioned issue. Our model comprises three feature extractors, each dedicated to extracting features from text, images and multimodal data. Subsequently, the relationship structures derived from these feature extractors are employed to construct a heterogeneous manifold. A diffusion process is then conducted on this heterogeneous manifold, ultimately yielding the final ranking scores. Comprehensive experiments demonstrate that the proposed modal has the capability to acquire more effective knowledge representation, thus enhancing the effectiveness of ZSCMR. © 2023 IEEE.

关键词： Knowledge representation

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