Tree traversal is a technique which involves visiting, verifying, and updating each node in a tree just once. This paper gives insight on the various approaches for the same. The tree can be visited in two ways recurs...
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The review article, 'Speech Emotion Recognition: A Comprehensive Study,' starts off by summarizing the significance of speech emotion recognition and highlighting all of the different ways it may be used in fi...
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Most data structures use hash tables. A key method in computerscience for effectively storing, accessing, and searching for data is hashing. It involves converting a key into a hash value and using this value to acce...
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The Disaster Management Web Application is a comprehensive solution designed to facilitate efficient communication and coordination during disaster situations. This application aims to provide a platform for seamless ...
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The Internet of Things (IoT) represents a network of interconnected digital devices that communicate wirelessly, enabling data collection, transmission, and storage without the need for human interaction. This paper i...
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The ability to identify emotions in text is essential for a range of applications, including sentiment analysis, customer feedback analysis, and monitoring mental health. In recent years, machine learning algorithms h...
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From AlphaGo to ChatGPT,the field of AI has launched a series of remarkable achievements in recent ***,comparing,and summarizing these achievements at the paradigm level is important for future AI innovation,but has n...
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From AlphaGo to ChatGPT,the field of AI has launched a series of remarkable achievements in recent ***,comparing,and summarizing these achievements at the paradigm level is important for future AI innovation,but has not received sufficient *** this paper,we give an overview and perspective on machine learning ***,we propose a paradigm taxonomy with three levels and seven dimensions from a knowledge ***,we give an overview on three basic and twelve extended learning paradigms,such as Ensemble Learning,Transfer Learning,etc.,with figures in unified *** further analyze three advanced paradigms,i.e.,AlphaGo,AlphaFold and ***,to enable more efficient and effective scientific discovery,we propose to build a new ecosystem that drives AI paradigm shifts through the decentralized science(DeSci)movement based on decentralized autonomous organization(DAO).To this end,we design the Hanoi framework,which integrates human factors,parallel intelligence based on a combination of artificial systems and the natural world,and the DAO to inspire AI innovations.
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...
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With the ongoing advancements in sensor networks and data acquisition technologies across various systems like manufacturing,aviation,and healthcare,the data driven vibration control(DDVC)has attracted broad interests...
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With the ongoing advancements in sensor networks and data acquisition technologies across various systems like manufacturing,aviation,and healthcare,the data driven vibration control(DDVC)has attracted broad interests from both the industrial and academic *** shaping(IS),as a simple and effective feedforward method,is greatly demanded in DDVC *** convolves the desired input command with impulse sequence without requiring parametric dynamics and the closed-loop system structure,thereby suppressing the residual vibration *** on a thorough investigation into the state-of-the-art DDVC methods,this survey has made the following efforts:1)Introducing the IS theory and typical input shapers;2)Categorizing recent progress of DDVC methods;3)Summarizing commonly adopted metrics for DDVC;and 4)Discussing the engineering applications and future trends of *** doing so,this study provides a systematic and comprehensive overview of existing DDVC methods from designing to optimizing perspectives,aiming at promoting future research regarding this emerging and vital issue.
Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power *** deep-learning-based methods can perform well if there are sufficient t...
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Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power *** deep-learning-based methods can perform well if there are sufficient training data and enough computational ***,there are challenges in building models through centralized shared data due to data privacy concerns and industry *** learning is a new distributed machine learning approach which enables training models across edge devices while data reside *** this paper,we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM *** design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting *** evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy,and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.
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