With the rapid growth of various images and video data on the network platform, multimodal emotional analysis and recognition have become an increasingly popular research field. Inspired by the human emotional judgmen...
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ISBN:
(纸本)9781665488679
With the rapid growth of various images and video data on the network platform, multimodal emotional analysis and recognition have become an increasingly popular research field. Inspired by the human emotional judgment and cross information between different characteristics, this paper proposed a multimodal video emotional analysis network of time features alignment and information auxiliary learning(METI). This network not only fully consider the time alignment between modals to obtain the preliminary information but also pay attention to the auxiliary information in the video and make emotional judgments. METI network is mainly composed of the following three parts: Time alignment network pays attention to time alignment information between different modes;Prepose feedback module uses the auxiliary information in the video to simulate the emotional judgment process;Multimodal gate control module pays attention to the emotional correlation of the context. The comparison of experimental results shows that the performance of the METI model on the dataset exceeds the current most advanced emotional analysis model. At the same time, it has been proved from ablation experiments that the modules and methods proposed in this paper can improve the accuracy of emotion recognition by nearly 4%, and has been respectively proved in the seven classification experiment of emotions and three classification experiment of sentiment.
This article presents research results on the impact of textual data augmentation on the classification model training process and its resulting quality. The importance of using text augmentation techniques for specif...
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ISBN:
(数字)9798331532178
ISBN:
(纸本)9798331532185
This article presents research results on the impact of textual data augmentation on the classification model training process and its resulting quality. The importance of using text augmentation techniques for specific tasks is justified. This study examines how the different text augmentation techniques affect model's tendency to overfit and their impact on resulting accuracy. For that purpose, a sentiment classifier based on recurrent neural network was developed and tested. Experiments focus on the impact of the augmentation factor on classifying data using a small-sized dataset.
Designing a sustainable tourism travel trip is based on evaluation and handling different types of information. Many times, available data can be characterized as imperfect. In many cases, decision criteria for sustai...
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ISBN:
(纸本)9783031671944;9783031671951
Designing a sustainable tourism travel trip is based on evaluation and handling different types of information. Many times, available data can be characterized as imperfect. In many cases, decision criteria for sustainable tourism travel trip designing are assessed using linguistic terms, which also have a certain degree of reliability. To operate with a high level of uncertainties, it is suggested to use an approach based on Z-information. Z-numbers allow the categorization of destinations, weighting the preferences, and selecting destinations that score high in sustainability and cultural richness. Using a Z-number-based approach for such multi-stage processes as sustainable tourism travel trip design that includes goal definitions, gathering data, itinerary design, continuous adjustment, and post-trip analysis allows one to rely on personal experiences and feedback from locals or fellow travelers. This feedback can be used to refine future travel plans, further applying Z-numbers to interpret and act on this inherently subjective information. Fuzzy data is integral at every stage, from understanding preferences and evaluating destinations to making decisions about activities and adjusting plans. The application of Z-information allows for a more nuanced and adaptable approach to travel planning, especially in the context of sustainability and cultural experiences where data is often subjective and variable. The modeling and handling of Z-information are implemented in Z-lab software.
dataanalysis involves the use of a wide variety of systems and libraries to support the exploration and development of models that can uncover valuable patterns and enable individuals and businesses to draw informed ...
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ISBN:
(纸本)9781665439022
dataanalysis involves the use of a wide variety of systems and libraries to support the exploration and development of models that can uncover valuable patterns and enable individuals and businesses to draw informed insights. However, efforts towards the automation of the ML-based dataanalysismodelingprocess faces numerous challenges. In this paper, we describe our ongoing work towards the automation of the dataanalysismodeling phase based on a variability-aware approach. This approach involves capturing the variabilities through feature models, designing an automated framework to support the analysis, and developing use cases. The work advances the state of the art in the development of methods and tools to support the automation of ML-based dataanalysis.
Aiming at cleaning requirements of stainless-steel wall surface for nuclear plant station (NPS) fuel pool, an underwater cleaning robot with two motion modes of swimming and crawling was proposed. According to the str...
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Finite element analysis (FEA) is an important tool for smart structure modelling, particularly in the context of piezoelectric beams. A key challenge in such modelling is the derivation of electro-elastic coupling, wh...
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In this contribution a new discrete event control scheme is proposed to ensure a defined and a reproducible process in reactive sputtering plants. The control scheme is based on a novel hybrid model that describes the...
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ISBN:
(数字)9798331518493
ISBN:
(纸本)9798331518509
In this contribution a new discrete event control scheme is proposed to ensure a defined and a reproducible process in reactive sputtering plants. The control scheme is based on a novel hybrid model that describes the pressure behaviour and the electrical behaviour of such processes. A new automation system is developed to allow the experimental validation of the control scheme, which consists of two parts. An interlock control prevents prohibited process states and a sequence control ensures a desired sequence of process states. Experimental data are shown to demonstrate the applicability of the discrete event control scheme and of the automation system.
In many industries, the focus of testing is currently shifting away from classical hardware tests to the virtual verification and validation of products. To this end, cosimulation has become a common tool for the simu...
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In many industries, the focus of testing is currently shifting away from classical hardware tests to the virtual verification and validation of products. To this end, cosimulation has become a common tool for the simulation and analysis of complex systems that span multiple engineering domains and usually involve multiple, heterogeneous and application-specific simulation environments. In particular, the so-called explicit cosimulation allows a widespread application since it has minimal requirements regarding the capabilities of the tool interfaces. However, explicit cosimulation also poses a numerical challenge, especially when the system includes stiff coupling loops. The model-based corrector approach presented in Haid et al. (The 5th Joint International conference on Multibody System Dynamics, 2018) provides a method for the efficient cosimulation of such systems. In this article, this model-based corrector approach is extended to additional extrapolation methods. By modeling the cosimulation process through a linear recurrence equation and applying it to the two-mass oscillator test model, the influence of model-based correction on the underlying extrapolation methods in terms of stability, accuracy, and error convergence is analyzed. It is shown that adding model-based correction can significantly improve the overall cosimulation, allowing > 10 times larger macrostep sizes or reducing the cosimulation error by a factor of 10 or more in some cases.
Individuals and brands with large fan bases face difficulty in understanding fan sentiment and its potential impact on fan engagement and performance. This is particularly pertinent within fast-paced sports such as Fo...
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The accurate station models and parameters are the foundation for modeling and equivalence studies of new energy stations. However, due to the black-box nature of actual control models, it is difficult to directly obt...
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