Through sentiment analysis technology, NPCs (Non-Player-controlled Character) in virtual reality roaming system are able to recognize the user's emotional state and react accordingly. In aspect-based sentiment ana...
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ISBN:
(数字)9798350353174
ISBN:
(纸本)9798350353181
Through sentiment analysis technology, NPCs (Non-Player-controlled Character) in virtual reality roaming system are able to recognize the user's emotional state and react accordingly. In aspect-based sentiment analysis, NLP techniques often use manually constructed features combined with machine learning models for classification. However, these methods are complex in feature engineering and lack generalisation capabilities. At the same time, traditional models often ignore the importance of local context for the correct classification of the sentiment polarity of aspect term, and process all input data indiscriminately. In order to solve the above problems and improve the processing efficiency of aspect-based sentiment analysis, an attention weight decay mechanism is proposed. On this basis, a multi-module model is constructed by fusing BERT, BiLSTM and TextCNN, and the performance of the model is verified experimentally. This model can be better applied to virtual reality roaming systems.
In recent years, a new design methodology is finding fertile ground in the building and plant engineering field: BIM (Building Information modeling). BIM is an innovative modeling method that proposes a substantial ch...
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ISBN:
(纸本)9781665409186
In recent years, a new design methodology is finding fertile ground in the building and plant engineering field: BIM (Building Information modeling). BIM is an innovative modeling method that proposes a substantial change in the entire workflow of a project aimed at the digitization of information processes and supported by the transition from 2D to 3D design. The Digital Twin, final product of the entire design process, represents a valuable tool to support the management of the building but, at present, its potential is not fully exploited. Today, the market offers many solutions for building and facility management, but in none of them the information is well contextualized within the space. SCADA (Supervisory control And data Acquisition) systems, in fact, applied to the building and plant field, do not offer a representation of the building that has a decisive impact on the final user experience. The objective of this discussion is, therefore, to propose an innovative system that exploits the unexpressed potential of BIM and extends the usefulness of the project beyond the construction of the building. The ability of BIM to produce a Digital Twin suggests the possibility of integrating this model within the SCADA system. The data, acquired and processed, are, in fact, linked to the "digital twin" that from static and parametric becomes dynamic and informative. The result is what can be defined as "Dynamic Digital Twin".
The ground-excited ice-roller has been able to effectively solve the problem of ice-snow on the roads, but its ice breaking mechanism, operating parameters and efficiency still need to be studied and improved. This pa...
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A flutter boundary prediction method based on HHT and machine learning is proposed to predict the flutter velocity before the wind speed reaches the subcritical state. Natural excitation technique is used to extract i...
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ISBN:
(纸本)9781510660816;9781510660823
A flutter boundary prediction method based on HHT and machine learning is proposed to predict the flutter velocity before the wind speed reaches the subcritical state. Natural excitation technique is used to extract impulse response signals. EMD ( empirical Mode decomposition method) is used to decompose the signal. Hilbert spectrum was obtained and analyzed by HHT to decompose the signal. The analysis methods included HHT spectrum and marginal spectrum analysis, so as to extract the characteristic quantity and establish the classification model according to different flight states. Then, regression models were established under different flutter modes for flutter degree analysis. During the prediction, according to the classification performance of the data to be measured, the flutter degree analysis result is weighted to obtain the flutter degree corresponding to the current wind speed, and then the flutter wind speed is calculated. In the selection of machine learning algorithm, naive Bayes algorithm, K-nearest neighbor algorithm and other machine learning algorithms are used to construct the classification model, linear regression,, Gaussian process regression and so on are used to construct the regression model. The results show that the K-nearest neighbor algorithm performs best in the classification algorithm, while the Gaussian process regression algorithm performs best in the regression algorithm. Through the cross-validation of the test data, the proposed method can accurately predict the critical flutter velocity when it is far away from the flutter boundary through flutter mode recognition and flutter degree analysis.
Ontology plays an essential role in biological research. It supports integrative analysis and interpretation by provisioning a standardized vocabulary, metadata, machine-readable axioms, and definitions. As a represen...
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The proceedings contain 150 papers. The special focus in this conference is on Computer-Aided Architectural Design Research in Asia. The topics include: COMMUNICATION WITH DETROIT: Machine Learning in Open Source Comm...
ISBN:
(纸本)9789887891796
The proceedings contain 150 papers. The special focus in this conference is on Computer-Aided Architectural Design Research in Asia. The topics include: COMMUNICATION WITH DETROIT: Machine Learning in Open Source Community Housing Design;PREDICTION AND OPTIMISATION OF THE TYPICAL AIRPORT TERMINAL CORRIDOR FAÇADE SHADING USING INTEGRATED MACHINE LEARNING AND EVOLUTIONARY ALGORITHMS;RESEARCH ON ARCHITECTURAL SKETCH TO SCHEME IMAGE BASED ON CONTEXT ENCODER;‘;TEXT-TO-GARDEN: Generating Traditional Chinese Garden Design From Text-Descriptions at Scale With Multimodal Machine Learning;INTEGRATION OF EEG AND DEEP LEARNING ON DESIGN DECISIONMAKING: A data-Driven Study of Perception in Immersive Virtual Architectural Environments;INCORPORATING PHYSICAL EXPERIMENTATION INTO CREATIVE DL-DRIVEN DESIGN SPACE EXPLORATION;AN IMAGE-BASED MACHINE LEARNING METHOD FOR URBAN FEATURES PREDICTION WITH THREE-DIMENSIONAL BUILDING INFORMATION;AN INTEGRATED APPLICATION OF BUILDING INFORMATION modeling, COMPUTER-AIDED MANUFACTURING, MACHINE LEARNING, AND THE INTERNET OF THINGS: A Hybrid Stadium as a Case Study;CROSS-DISCIPLINARY SEMANTIC BUILDING FINGERPRINTS: Knowledge Graphs To Store Topological Building Information Derived From Semantic Building Models (Bim) To Apply Methods Of Artificial Intelligence (Ai) Throughout The Life Cycle Of Buildings;SYNTHESIZING STYLE-SIMILAR RESIDENTIAL FACADE FROM SEMANTIC LABELING ACCORDING TO THE USER-PROVIDED EXAMPLE;VARIABILITY IN MACHINE LEARNING FOR MULTI-CRITERIA PERFORMANCE analysis;SKYWAYS VERSUS SIDEWALKS: Evaluating the Perceptual Qualities and Environmental Features of Elevated Pedestrian Systems in Hong Kong;BESPOKE 3D PRINTED CHAIR: Research On The Digital Design And Fabrication Method Of Multi-body Pose Fusion;TRADITIONAL CHINESE VILLAGE MORPHOLOGICAL FEATURE EXTRACTION AND CLUSTER analysis BASED ON MULTI-SOURCE data AND MACHINE LEARNING;GESTURE modeling: In Between Nature and control;PAINTERLY EXPANSION.
The proceedings contain 22 papers. The special focus in this conference is on Mobile Web and Intelligent Information Systems. The topics include: Simulation of SARSA-Based Reinforcement- Learning Dynamic SDN Migration...
ISBN:
(纸本)9783031680045
The proceedings contain 22 papers. The special focus in this conference is on Mobile Web and Intelligent Information Systems. The topics include: Simulation of SARSA-Based Reinforcement- Learning Dynamic SDN Migration process;Dynamic SDN Multiple Nodes Migration Using SARSA Reinforcement Learning;exploring Worst Arc Flow Minimization: A Comparative Study of a Provided Wireless Network and Its Derivation via Spanning Tree Topology;Decentralized Renewable Energy Trading: A Cross-Chain, NFT, and IPFS Framework;Advancing IAM in the Finance Sector by Integrating Zero Trust and Blockchain Technology;Enhanced Security for Animal Health Records Using RSA-Encrypted NFTs on the Blockchain;evaluating Third-Party Involvement in Android Apps: Norms and Anomalies in Usage Patterns;applying the Knowledge Behavior Gap Model to Study the Acceptance of Blockchain-Based Solutions;Transparent Threads: Enhancing Handicraft Supply Chain Ethics and Transparency with Blockchain, Smart Contracts and Encrypted-RSA NFTs;enhancing User control and Transparency in Personal data Trading: A Blockchain-Enabled Platform Approach;Quantum-Blockchain Healthcare System for Invasive and No-Invasive-IoMT data;exploring Human Artificial Intelligence Using the Knowledge Behavior Gap Model;review of Deep Learning Models for Remote Healthcare;Transformation Design Framework for AI-Driven Hyper-performance;a Statistical Approach for modeling the Expressiveness of Symbolic Musical Text;A Domain-Aware Federated Learning Study for CNC Tool Wear Estimation;information and Knowledge Management Methods for the Preparation of New Safety Standards and New Legislation for Use in Smart Cities;lessons Learned: A Usability Study of an Urban data Platform for Citizens;the Impact of Modern Information Technology on the Resistance to Disinformation in the Police;exploring Cognitive Enhancement Technologies in the Workplace: A Systematic Literature Review.
The proceedings contain 120 papers. The topics discussed include: deep reinforcement learning based demand response for domestic variable volume water heater;tomato disease degree recognition based on RGB and lab colo...
ISBN:
(纸本)9798350311259
The proceedings contain 120 papers. The topics discussed include: deep reinforcement learning based demand response for domestic variable volume water heater;tomato disease degree recognition based on RGB and lab color space conversion method;adaptive neural network asymptotic tracking control for autonomous surface vehicles;exergy-related operating performance assessment for hot rolling process based on multiple imputation and multi-class support vector data description;digital twin development: mathematical modeling;a survey of few-shot learning-based compound fault diagnosis methods for industrial processes;backstepping-based anti-disturbance flight control for attitude and altitude unmanned helicopters with state constraints;integrating worker assistance systems and enterprise resource planning in industry 4.0;an efficient condition monitoring and fault diagnosis method for bearings under multiple working conditions;and sliding window-based real-time remaining useful life prediction for milling tool.
The paper contains new knowledge about the expansion of technologies associated with Industry 4.0 and digitalization in selected companies including metallurgical companies in the Czech Republic and evaluates the inte...
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ISBN:
(纸本)9788088365068
The paper contains new knowledge about the expansion of technologies associated with Industry 4.0 and digitalization in selected companies including metallurgical companies in the Czech Republic and evaluates the intensity of business process innovation with a focus on internal processes implemented in companies. A probe was implemented which was purposefully focused on the analysis of statistical data on innovation activities in innovative companies including metallurgical companies in the Czech Republic in the period under study by. The processing of statistical data obtained by the CZSO by a survey made it possible to obtain more detailed overviews of the relative frequencies of enterprises that implemented individual types of process innovations in the period under study and that have introduced some of the elements or tools of Industry 4.0 and the digitalization. The importance of innovation for the continued existence and development of the company is recognized especially by large companies and companies under foreign control. Many of these companies are already applying technologies associated with Industry 4.0 and the digitalization and they are moving towards the creation of a digital enterprise. On the contrary, the implementation of innovation activities and the use of technologies associated with Industry 4.0 in small and medium-sized companies is low. The main obstacle is insufficient funding for new technologies and human resources.
High Temperature cameras allow ideal visual inspection and verification in extreme temperature environments. A unique fused glass seal provides an impenetrable safety barrier between the camera electronics and the har...
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ISBN:
(纸本)9780791887530
High Temperature cameras allow ideal visual inspection and verification in extreme temperature environments. A unique fused glass seal provides an impenetrable safety barrier between the camera electronics and the harsh process environments. The camera is protected from high temperatures, fumes and radiation. The dynamic imaging system provides a live view of the process, and analyzes the process by generating critical real time measurement data. In nuclear waste vitrification, radioactive material is heated with glass forming additives and poured into a containment vessel to cool into a uniform glass product. The use of high temperature camera systems allows verification that the melting and cooling processes are uniform and repeatable, by providing a live view and analysis of the process. This allows for maximum efficiency and safety, while maximizing the percentage of waste that can be immobilized in the glass product. The paper outlines the critical steps in the disposal of nuclear waste, including the vitrification processes. The strategies used to ensure process safety and efficiency are examined and the critical measurements in each step are determined. It is demonstrated that High Temperature cameras are a useful tool for monitoring those critical measurements to improve the processes of nuclear waste vitrification.
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