Cloud environments often exhibit varying levels of heterogeneity arising from the diverse characteristics of cloudlets and virtual machines. This research paper focuses on addressing this heterogeneity and proposes tw...
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In this paper, we propose hardware acceleration to improve a performance of scripting programming languages for embedded developments. Scripting programming languages enable more efficient software developments and sc...
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Self-supervised learning is attracting significant attention from researchers in the point cloud processing field. However, due to the natural sparsity and irregularity of point clouds, effectively extracting discrimi...
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Self-supervised learning is attracting significant attention from researchers in the point cloud processing field. However, due to the natural sparsity and irregularity of point clouds, effectively extracting discriminative and transferable features for efficient training on downstream tasks remains an unsolved challenge. Consequently, we propose PointSmile, a reconstruction-free self-supervised learning paradigm by maximizing curriculum mutual information(CMI) across the replicas of point cloud objects. From the perspective of how-and-what-to-learn, PointSmile is designed to imitate human curriculum learning, i.e.,starting with easier topics in a curriculum and gradually progressing to learning more complex topics in the curriculum. To solve “how-to-learn”, we introduce curriculum data augmentation(CDA) of point *** encourages PointSmile to follow a learning path that starts from learning easy data samples and progresses to learning hard data samples, such that the latent space can be dynamically affected to create better embeddings. To solve “what-to-learn”, we propose maximizing both feature-and class-wise CMI to better extract discriminative features of point clouds. Unlike most existing methods, PointSmile does not require a pretext task or cross-modal data to yield rich latent representations; additionally, it can be easily transferred to various backbones. We demonstrate the effectiveness and robustness of PointSmile in downstream tasks such as object classification and segmentation. The study results show that PointSmile outperforms existing self-supervised methods and compares favorably with popular fully supervised methods on various standard architectures. The code is available at https://***/theaalee/PointSmile.
Gesture recognition holds paramount significance in facilitating communication for individuals utilizing sign language to convey phrases and expressions. We present an innovative approach to gesture recognition in thi...
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Background Most existing chemical experiment teaching systems lack solid immersive experiences,making it difficult to engage *** address these challenges,we propose a chemical simulation teaching system based on virtu...
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Background Most existing chemical experiment teaching systems lack solid immersive experiences,making it difficult to engage *** address these challenges,we propose a chemical simulation teaching system based on virtual reality and gesture *** The parameters of the models were obtained through actual investigation,whereby Blender and 3DS MAX were used to model and import these parameters into a physics *** establishing an interface for the physics engine,gesture interaction hardware,and virtual reality(VR)helmet,a highly realistic chemical experiment environment was *** code script logic,particle systems,as well as other systems,chemical phenomena were ***,we created an online teaching platform using streaming media and databases to address the problems of distance *** The proposed system was evaluated against two mainstream products in the *** the experiments,the proposed system outperformed the other products in terms of fidelity and *** The proposed system which offers realistic simulations and practicability,can help improve the high school chemistry experimental education.
In this study,the separation and coalescence of oil-in-water emulsions are explored in an ultrasonic field using the lattice Boltzmann *** simulating the propagation of ultrasonic waves,this study focuses on examining...
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In this study,the separation and coalescence of oil-in-water emulsions are explored in an ultrasonic field using the lattice Boltzmann *** simulating the propagation of ultrasonic waves,this study focuses on examining the effects of acoustic wave frequency,the ratio of oil to water components,and the aspect ratio of the boundary on the emulsification and separation processes of oil-water *** following conclusions are drawn.①Frequency affects the speed of oil droplet separation,leading to an increase in droplet size over *** droplets are found near the source,while smaller droplets are distributed throughout the wave web.②As the boundary aspect ratio increases,the emulsification efficiency of the droplets weakens,and the system takes longer to stabilize.③Emulsions with a higher component of oil can better resist acoustic waves.④At the same acoustic frequency,longer wavelength ultrasonic fields promote the formation of uniformly distributed,smaller oil droplets,which is beneficial to the storage of *** numerical simulation results offer insights for optimizing conditions for oil-in-water separation and serve as a numerical reference for the study of oil-in-water emulsion separation in ultrasonic environments.
Automatic analysis of actions in sports training can provide useful feedback for athletes. Fencing is one of the sports disciplines in which the correct technique for performing actions is very important. For any prac...
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While tokenized graph Transformers have demonstrated strong performance in node classification tasks, their reliance on a limited subset of nodes with high similarity scores for constructing token sequences overlooks ...
Modern strides in autonomous vehicles and embedded advanced driver assistant part systems(ADAS) have forced the need of an efficient in addition to accurate system intended for clear road lane as in addition to vehicl...
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This paper focuses on an embedded system for air quality control and hazardous gas detection using multiple sensors to trigger real-time danger alerts. The system employs and integrates gas sensors MQ-2, MQ-3, and MQ-...
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ISBN:
(纸本)9798331522667
This paper focuses on an embedded system for air quality control and hazardous gas detection using multiple sensors to trigger real-time danger alerts. The system employs and integrates gas sensors MQ-2, MQ-3, and MQ-9, temperature, and humidity sensors for assessing many combustible gases including methane, carbon monoxide alcohol smoke and even fire. These sensors send signals to an embedded microcontroller which controls air and environmental quality for the circumferential range. Apart from the gas sensors, a fire sensor has been integrated within the system, improving its efficiency in ascertaining cases of fire outbreak in the presence of gas leakages. In addition to this, Power BI works with the system for sensor monitoring and data visualization through the sensors being connected online. The dashboard shows the most important parameters such as the level of gas leakage and the type of gas involved, the temperature of the surroundings, and the humidity. Power BI supports how to visualize what is going on at that time to monitor environmental conditions, how bad is the gas leakage, and make quick decisions. The dashboard also helps in looking out for risks by showing past trends of data and carrying out market predictions. The integration of multi-sensor systems with a drone is intensified to outstretch the boundaries even further where remote monitoring of industrial sites, areas that have been hit by disasters, and even of cities, is possible. The drone equipped with the embedded system provides the real time gas leak detection temperature, humidity monitoring and fire threat assessment in environments where the human presence is quite dangerous. This system is also easy, cheap and provides an admirable solution for environmental monitoring on a day to day basis for the sake of public safety, reduction in the response rates to dangerous situations and the encouragement of smart city designs. The research in this study focused on both stationary and mobile w
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