In this correspondence, we propose a movable antenna (MA)-aided multi-user hybrid beamforming scheme with a sub-connected structure, where multiple movable sub-arrays can independently change their positions within di...
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The overflow of water from a lake or river usually causes flooding. Sometimes, a dam breach might result in the unexpected release of vast quantities of water. Some of the water seeps into the ground, flooding the reg...
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Mobile networks are flexible enough to support a range of resource allocation models and service-based choices in computing domains, which affects both virtual reality and the Industrial Internet of Things (IIOT). Vir...
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This study introduces a system designed to identify pests in crops and classify them as either beneficial or harmful. The project begins by providing a comprehensive overview of various pest identification methods, an...
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Water quality assessment is a complex endeavour that involves identifying pollutants in water resources. The importance of this process lies in its objective to evaluate water quality for human use. Machines and deep ...
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Water quality assessment is a complex endeavour that involves identifying pollutants in water resources. The importance of this process lies in its objective to evaluate water quality for human use. Machines and deep learning algorithms play a vital role in this evaluation. In this context, feature selection methods were employed to identify critical factors that ensure optimal accuracy. Subsequently, these selected features were used as input for various classifiers for classification purposes. The Cauvery River dataset, obtained from the Tamil Nadu Pollution Control Board, was utilized to assess the performance of the proposed approach. This research was implemented using Python as the programming language. The performance of the PCA-RF model was evaluated using various metrics, including an accuracy of 0.96, precision of 0.97, recall of 0.94, and an F1-score of 0.95. The results demonstrate that the PCA-RF model outperforms conventional machine learning approaches, achieving a high R-squared score of 0.95.
The air quality index (AQI) is a metric used to report air quality levels. There has been a substantial rise in the level of air pollution in Indian cities. Multiple methodologies exist for formulating a mathematical ...
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Integrated sensing and communication (ISAC) emerged as a key feature of next-generation 6G wireless systems, allowing them to achieve high data rates and sensing accuracy. While prior research has primarily focused on...
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Artificial intelligence(AI) systems surpass certain human intelligence abilities in a statistical sense as a whole, but are not yet the true realization of these human intelligence abilities and behaviors. There are d...
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Artificial intelligence(AI) systems surpass certain human intelligence abilities in a statistical sense as a whole, but are not yet the true realization of these human intelligence abilities and behaviors. There are differences, and even contradictions, between the cognition and behavior of AI systems and humans. With the goal of achieving general AI, this study contains a review of the role of cognitive science in inspiring the development of the three mainstream academic branches of AI based on the three-layer framework proposed by David Marr, and the limitations of the current development of AI are explored and analyzed. The differences and inconsistencies between the cognition mechanisms of the human brain and the computation mechanisms of AI systems are analyzed. They are found to be the cause of the differences and contradictions between the cognition and behavior of AI systems and humans. Additionally, eight important research directions and their scientific issues that need to focus on braininspired AI research are proposed: highly imitated bionic information processing, a large-scale deep learning model that balances structure and function, multi-granularity joint problem solving bidirectionally driven by data and knowledge, AI models that simulate specific brain structures, a collaborative processing mechanism with the physical separation of perceptual processing and interpretive analysis, embodied intelligence that integrates the brain cognitive mechanism and AI computation mechanisms,intelligence simulation from individual intelligence to group intelligence(social intelligence), and AI-assisted brain cognitive intelligence.
Sim-to-real transfer, which trains RL agents in the simulated environments and then deploys them in the real world, has been widely used to overcome the limitations of gathering samples in the real world. Despite the ...
A supervised machine learning framework is implemented to predict the propagation loss of randomly structured nested hollow-core anti-resonant fiber for the first time. The random forest classifier outperforms other m...
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