The work prioritizes the development of a modular pipeline that efficiently utilizes existing models for image restoration instead of creating new ones from scratch. Restoration is conducted at an object-specific leve...
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ISBN:
(数字)9798350360882
ISBN:
(纸本)9798350360899
The work prioritizes the development of a modular pipeline that efficiently utilizes existing models for image restoration instead of creating new ones from scratch. Restoration is conducted at an object-specific level, with each object being regenerated based on its corresponding class label information. What sets this approach apart is its provision of comprehensive user control throughout the restoration process. Users have the flexibility to choose models for specific restoration tasks, customize the sequence of steps according to their requirements, and enhance the resulting regenerated image with depth awareness. The study offers two distinct pathways for implementing image regeneration, allowing for a comparative analysis of their strengths and limitations. One of the main advantages of this adaptable system is its flexibility. Users can tailor the restoration process to target specific object categories, such as medical images, by leveraging models trained on those specific object classes. The entire code to replicate the pipeline is publicly accessible on [1].
The proceedings contain 198 papers. The topics discussed include: using iterative learning control to improve the accuracy of desktop fused deposition modeling printers: an experimental case study;non-planar slicing m...
ISBN:
(纸本)9780791885819
The proceedings contain 198 papers. The topics discussed include: using iterative learning control to improve the accuracy of desktop fused deposition modeling printers: an experimental case study;non-planar slicing method for maximizing the anisotropic behavior of continuous fiber-reinforced fused filament fabricated parts;deep learning-based super-resolution for the finite element analysis of additive manufacturing process;a functionally gradient NiTi shape-memory alloy fabricated by selective laser melting;one-step 3D printed layers along with xy-in plane directions for enhanced multifunctional nanocomposites;a crystal plasticity finite element method modeling of zircaloy with hydride phases based on scanning electron micrographs;coupled diffusion-deformation-damage model for polymers used in hydrogen infrastructure;effects of process parameters on thin-wall substrate WAAM deposition;analysis of conduction cooling strategies for wire arc additive manufacturing;and the development and validation of a novel thread forming fastener for high strength steel applications.
We discuss the problem of generating synthetic processcontrol Monitoring (PCM) data and evaluating how accurately it reflects the distribution of actual measurements from manufactured wafers. PCMs are small test stru...
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ISBN:
(数字)9798331520137
ISBN:
(纸本)9798331520144
We discuss the problem of generating synthetic processcontrol Monitoring (PCM) data and evaluating how accurately it reflects the distribution of actual measurements from manufactured wafers. PCMs are small test structures placed in the scribe lines of the wafer, on which electrical tests (E-tests) are conducted to monitor the impact of process variation on a manufactured wafer. Besides its immediate use in assessing and controlling wafer health, collective PCM data holds invaluable information for process engineers who seek to maximize yield and performance across process corners. Yet availability of such data is limited during the ramp-up phase of a process, when it is needed the most. To address this limitation, we introduce a methodology that leverages correlations across E-test measurements and across wafer locations to generate a large synthetic population from a small data sample. Furthermore, we discuss statistical metrics that can be used to evaluate the accuracy of the synthetically generated vis-à-vis the actual population. Effectiveness of our solution is experimentally validated using E-test data from ~8K wafers fabricated in an advanced GlobalFoundries FinFET node.
With the development of information technology, teaching reforms have been innovated, and the quality of university programs has become higher and higher. However, the emergence and widespread application of deep gene...
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ISBN:
(数字)9798350363609
ISBN:
(纸本)9798350363616
With the development of information technology, teaching reforms have been innovated, and the quality of university programs has become higher and higher. However, the emergence and widespread application of deep generative models have brought more challenges and opportunities to classroom teaching. With the continuous development of educational technology and the updating of teaching concepts, the depth generation model, as an emerging teaching mode, is gradually receiving attention from the educational community. In order to verify the effectiveness of the depth generation model, this study selected a certain number of college English classes as experimental subjects, and conducted in-depth dataanalysis and discussion by comparing the differences between the experimental group and the control group in terms of the frequency of interactions, the quality of interactions, the degree of student participation and learning effects. By comparing the classroom effects of using a deep generative modelling classroom with a traditional classroom, the study found that students’ overall grades in English classrooms using deep generative modelling improved by approximately 31 points, and that the average completion rate of assignments in deep generative modelling classrooms was 94.8%, which was much higher than that of traditional classrooms.
Automatic prediction of team performance and workload plays a crucial role in team selection, training, evaluation, and re-training processes. This study investigated the potential of using voice analysis of team-base...
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Automatic prediction of team performance and workload plays a crucial role in team selection, training, evaluation, and re-training processes. This study investigated the potential of using voice analysis of team-based communication for predicting team workload (TW) and team performance (TP). Both the TW and TP categories were labeled objectively. Ten teams of three participants were tasked with completing a computer-based command-and-control simulation that required communication of task-specific information to each team member. Recordings of each participant's voice communications were used to train Convolution Neural Network (CNN) models for each team separately. It was hypothesized that integrating TW and TP information into the prediction process would support the prediction of both TW and TP categories. Two experiments were conducted. In the first experiment, the TP prediction networks were fine-tuned to predict TW, and conversely, the TW prediction networks were fine-tuned to predict TP. In the second experiment, the TP or TW prediction based on the assembly of interconnected TP and TW classifiers was tested. Both experiments confirmed the hypothesis. It was shown that task-related pre-requisite knowledge embedded into the neural network reduced neural network model training time and improved performance without increasing the training data size. Predictions based on combined TW and TP classification outcomes (using either separate or interconnected TW or TP classifiers) outperformed the baseline method using a single CNN model trained to predict either TW or TP alone. The classification accuracy was consistent with previously reported cognitive load prediction based on objective measures.
Postural monitoring in wheelchair users is a topic of growing interest. The detection of changes in the sitting patterns of these patients may serve to detect changes in their functional status and be able to adapt re...
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The air purifier is of great significance for purifying air. In this paper, aiming at the use of air purifiers, the data preprocessing of ten representative air purifiers is first carried out. After the consistency te...
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ISBN:
(纸本)9798400711831
The air purifier is of great significance for purifying air. In this paper, aiming at the use of air purifiers, the data preprocessing of ten representative air purifiers is first carried out. After the consistency test of the selected eight indicators, the entropy weight method is used to weight them, and the TOPSIS method is used to process the data set. A comprehensive multi-index evaluation model for evaluating the advantages and disadvantages of air purifiers is established. Based on this model, the selected ten air purifiers are ranked in terms of comprehensive cost performance. Then, the air purifier model and the living room simulation model were established by using SolidWorks software. Based on the dispersion of fluid mechanics, control equations and equations, the control equation model of gas fluid is constructed. The CFD finite element simulation is used to establish a suitable three-dimensional model of the analysis scene. In this paper, the air purifier and the model and the living room simulation model are meshed and the calculation area is adjusted. The control equation model of the air fluid in the scene is solved by the pressure base solver. The equation and the established material balance model are imported into Fluent software for calculation. Finally, the cloud map of the influence of an air purifier placed at different positions in the room on the concentration of air pollutants at different heights in the room is obtained by fluent-post.
In this paper, the take-up judder phenomenon caused by the accumulated geometric deviation of clutch plates is simulated and verified by experiments. Firstly, the vibration test and dataanalysis are carried out for t...
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The proceedings contain 198 papers. The topics discussed include: using iterative learning control to improve the accuracy of desktop fused deposition modeling printers: an experimental case study;non-planar slicing m...
ISBN:
(纸本)9780791885802
The proceedings contain 198 papers. The topics discussed include: using iterative learning control to improve the accuracy of desktop fused deposition modeling printers: an experimental case study;non-planar slicing method for maximizing the anisotropic behavior of continuous fiber-reinforced fused filament fabricated parts;deep learning-based super-resolution for the finite element analysis of additive manufacturing process;a functionally gradient NiTi shape-memory alloy fabricated by selective laser melting;one-step 3D printed layers along with xy-in plane directions for enhanced multifunctional nanocomposites;a crystal plasticity finite element method modeling of zircaloy with hydride phases based on scanning electron micrographs;coupled diffusion-deformation-damage model for polymers used in hydrogen infrastructure;effects of process parameters on thin-wall substrate WAAM deposition;analysis of conduction cooling strategies for wire arc additive manufacturing;and the development and validation of a novel thread forming fastener for high strength steel applications.
Safe and efficient deep-sea drilling is inseparable from accurate and timely recognition of the ocean and geological *** refers to ocean dynamics,meteorology,hydrology,ecology,chemistry,ocean sound,light physical char...
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ISBN:
(数字)9789887581536
ISBN:
(纸本)9781665482561
Safe and efficient deep-sea drilling is inseparable from accurate and timely recognition of the ocean and geological *** refers to ocean dynamics,meteorology,hydrology,ecology,chemistry,ocean sound,light physical characteristics,ocean geology and geography.A complex ocean environment is one of the challenges facing ocean engineering at *** is difficult to establish an independent ocean or geological model for controller of the deep-sea drilling *** the face of complex and changeable ocean environment,modeling and analysis of wave environmental factors alone is not suitable for the control of deep-sea drilling *** paper analyzes the influence of various marine environmental factors on the offshore drilling platform and studies the internal relationship between each ***,the models of ocean breeze,wave and ocean current were designed to realize the simulation of ocean environment and parameterized description of ocean environment for deep-sea drilling *** has laid the foundation for the design of a deep-sea drilling control system.
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