The process of designing progressive dies is highly complex and has always required the attention of very skilled designers. Various systems have been developed to automate much of the process with the objective of re...
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The process of designing progressive dies is highly complex and has always required the attention of very skilled designers. Various systems have been developed to automate much of the process with the objective of reducing the complexity and effort needed. This paper reviews these techniques employed and examines, in particular, the level of work done in the area of punch design automation. In general, most systems need the designer to specify the punch shapes either through interactive or graphical input. There have been attempts to automate this but only through restricting the punches to regular shapes. Another objective of this review is to create a system reference model which represents an ideal automated design system for progressive dies. Useful techniques such as knowledge-based tools and heuristic rules that could be used to implement this model will be discussed, using available case studies.
The boom in metal–organic frameworks (MOFs) for applications from chemical separations and gas storage to membranes for energy conversion and storage has stimulated interest in scalable MOF production methods. Combin...
To address the manufacturing complexity of multi-component host systems in red phosphorescent OLEDs, this study proposes a matched bipolar host premixing engineering strategy. Through molecular design, a composite sys...
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Renal cell carcinoma tumor images are utilized in various fields for critical functions. Application is constrained in unique scenarios requiring specific tumor imaging, which is often difficult to obtain due to rarit...
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ISBN:
(数字)9798331520526
ISBN:
(纸本)9798331520533
Renal cell carcinoma tumor images are utilized in various fields for critical functions. Application is constrained in unique scenarios requiring specific tumor imaging, which is often difficult to obtain due to rarity or privacy concerns. While general tumor synthesis has been successful as a data acquisition solution, specific domains demand precise control and accurate depiction of tumor characteristics. Our study addresses these limitations by integrating RENAL score guidelines into the synthesis process, enabling clinically instructed tumor synthesis tailored to specific medical demands. In this work, we introduce a generative framework that begins by decoding a segmentation mask from the textual outputs of a multimodal large language model, using clinical descriptions from RENAL score descriptors. The decoded mask is then integrated into a latent diffusion model, transforming a healthy volume into a tumor-bearing one. Our results demonstrate a high degree of alignment between the textual queries and the generated tumors, and the synthetic tumors closely replicate those found in other synthetic and real-world sources.
The analysis of an induction hardening device is a complex process because induction hardening is a combination of heat transfer and electromagnetic, and the temperature dependence of the material properties causes th...
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The classification of surface electromyography (sEMG) signals represents a key objective in the domain of rehabilitation and prosthetic control. This task is particularly challenging due to several factors, including ...
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ISBN:
(数字)9798331519667
ISBN:
(纸本)9798331519674
The classification of surface electromyography (sEMG) signals represents a key objective in the domain of rehabilitation and prosthetic control. This task is particularly challenging due to several factors, including the high dimensionality of the data and the high computational cost of the currently used deep learning models. In this context, quantum computing methods may prove advantageous due to their capacity to process a substantial amount of data facilitated by quantum phenomena such as superposition. In light of these considerations, the objective of this study is to demonstrate the feasibility of quantum computing by performing a comparison between evolutionarybased quantum classifiers for sEMG signals. In particular, the considered quantum classifiers are based on variational quantum circuits trained using evolutionary algorithms such as genetic algorithms, differential evolution and particle swarm optimization. As demonstrated in the experimental session utilizing a wellknown hand gesture dataset, quantum classifiers, and especially those based on genetic algorithms, are effective for sEMG signal classification.
Due to its high hydrogen storage capacity and established infrastructure, ammonia (NH3) decomposition has been extensively investigated as a clean hydrogen productionprocess. However, hydrogen production via ammonia ...
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To solve the clinical problem of constructing an aesthetic and appropriate orbital prosthesis model,two methods based on volume cutting and surface cutting respectively are proposed in this *** spline interpolation,re...
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ISBN:
(纸本)9781509001668
To solve the clinical problem of constructing an aesthetic and appropriate orbital prosthesis model,two methods based on volume cutting and surface cutting respectively are proposed in this *** spline interpolation,region growth,triangular patch calculation,cylinder cutting and other techniques,we obtain the 3D orbital prosthesis model with a proper size and smooth ***,a visual feedback mechanism is added in the process of prosthesis construction to make the prosthesis model fit the defect part *** results show that the CT image based 3D orbital prosthesis model construction method in this paper significantly improves the clinical acceptability and effectiveness.
Plants sequester carbon through photosynthesis and provide primary productivity for the ecosystem. However, they also simultaneously consume water through transpiration, leading to a carbon-water balance relationship....
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Plants sequester carbon through photosynthesis and provide primary productivity for the ecosystem. However, they also simultaneously consume water through transpiration, leading to a carbon-water balance relationship. Agricultural production can be regarded as a form of carbon sequestration *** the perspective of the natural-social-economic complex ecosystem, excessive water usage in food production will aggravate regional water pressure for both domestic and industrial purposes. Hence, achieving a harmonious equilibrium between carbon and water resources during the food productionprocess is a key scientific challenge for ensuring food security and sustainability. Digital intelligence(DI) and cyber-physical-social systems(CPSS) are emerging as the new research paradigms that are causing a substantial shift in the conventional thinking and methodologies across various scientific fields, including ecological science and sustainability studies. This paper outlines our recent efforts in using advanced technologies such as big data, artificial intelligence(AI), digital twins, metaverses, and parallel intelligence to model, analyze, and manage the intricate dynamics and equilibrium among plants, carbon, and water in arid and semiarid ecosystems. It introduces the concept of the carbon-water balance and explores its management at three levels: the individual plant level, the community level, and the natural-social-economic complex ecosystem level. Additionally, we elucidate the significance of agricultural foundation models as fundamental technologies within this context. A case analysis of water usage shows that, given the limited availability of water resources in the context of the carbon-water balance, regional collaboration and optimized allocation have the potential to enhance the utilization efficiency of water resources in the river basin. A suggested approach is to consider the river basin as a unified entity and coordinate the relationship between the
Metasurfaces, with their capability to control all possible dimensions of light, have become integral to quantum optical applications, including quantum state generation, operation, and tomography. We utilize a metasu...
Metasurfaces, with their capability to control all possible dimensions of light, have become integral to quantum optical applications, including quantum state generation, operation, and tomography. We utilize a metasurface to generate polarization–hologram hybrid entanglement between a signal–idler photon pair to construct a quantum hologram. The properties of the quantum hologram can be revealed by collapsing the polarization degree of freedom of the idler photon, inducing interference between two holographic states of the signal photon as a meaningful and selective erasure of the holographic content. On the contrary, interference disappears when the idler photon is detected without observing polarization. This process can be further interpreted as a quantum holographic eraser, where the erasing action is visualized with erased contents in holograms. Our construction of a polarization–hologram hybrid entangled state with metasurfaces will be useful for quantum communication with enhanced robustness, anticounterfeiting applications through the additional quantum degrees of freedom or phase difference between two holographic states, and as an emerging platform for exploring fundamental quantum concepts for entanglement and nonlocality.
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