Background: As the lightest metal structural material in engineering, magnesium alloy has excellent mechanical properties, such as high specific strength, high specific stiffness, good damping performance, and good ma...
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Diagnosing multi-stage diseases typically requires doctors to consider multiple data sources,including clinical symptoms,physical signs,biochemical test results,imaging findings,pathological examination data,and even ...
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Diagnosing multi-stage diseases typically requires doctors to consider multiple data sources,including clinical symptoms,physical signs,biochemical test results,imaging findings,pathological examination data,and even genetic *** applying machine learning modeling to predict and diagnose multi-stage diseases,several challenges need to be ***,the model needs to handle multimodal data,as the data used by doctors for diagnosis includes image data,natural language data,and structured ***,privacy of patients’data needs to be protected,as these data contain the most sensitive and private ***,considering the practicality of the model,the computational requirements should not be too *** address these challenges,this paper proposes a privacy-preserving federated deep learning diagnostic method for multi-stage *** method improves the forward and backward propagation processes of deep neural network modeling algorithms and introduces a homomorphic encryption step to design a federated modeling algorithm without the need for an *** also utilizes dedicated integrated circuits to implement the hardware Paillier algorithm,providing accelerated support for homomorphic encryption in ***,this paper designs and conducts experiments to evaluate the proposed *** experimental results show that in privacy-preserving federated deep learning diagnostic modeling,the method in this paper achieves the same modeling performance as ordinary modeling without privacy protection,and has higher modeling speed compared to similar algorithms.
The article addresses the output-feedback control issue for a class of multi-input multi-output(MIMO)uncertain nonlinear systems with multiple event-triggered mechanisms(ETM).Compared to previous event-triggering stud...
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The article addresses the output-feedback control issue for a class of multi-input multi-output(MIMO)uncertain nonlinear systems with multiple event-triggered mechanisms(ETM).Compared to previous event-triggering studies,this paper aims to trigger both the output and filtered *** nonlinear dynamics are approximated using fuzzy logic systems(FLSs).Then,a novel kind of state observer has been designed to deal with unmeasurable state problems using the triggered output *** sampled estimated state,the triggered output signal,and the filtered signal are utilized to propose an event-triggering mechanism that consists of sensor-to-observer(SO)and observer-to-controller(OC).An event-triggered output feedback control approach is given inside backstepping control,whereby the filter may be employed to circumvent the issue of the virtual control function not being differentiable at the trigger *** is testified that,according to the Lyapunov stability analysis scheme,all closed-loop signals and the system output are ultimately uniformly constrained by our control ***,the simulation examples are performed to confirm the theoretical findings.
Learning weariness is a common psychological problem, which will affect students' learning effect and life quality. Currently, most ways to relieve the learning weariness require the intervention of a professional...
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To enhance the capability of classifying and localizing defects on the surface of hot-rolled strips, this paper proposed an algorithm based on YOLOv7 to improve defect detection. The BI-SPPFCSPC structure was incorpor...
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The Grey Wolf optimizer (GWO) is an efficient meta-heuristic algorithm based on swarm intelligence, inspired by the hierarchical structure and hunting behavior of natural wolf packs. Due to straightforward algorithm f...
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Transition metal carbide/nitride cores within MXenes make them considerably useful for ultra-high-temperature ***,extensive research on Ti_(3)C_(2)T_(x) MXene has revealed its tendency to undergo a phase transition to...
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Transition metal carbide/nitride cores within MXenes make them considerably useful for ultra-high-temperature ***,extensive research on Ti_(3)C_(2)T_(x) MXene has revealed its tendency to undergo a phase transition to TiCy at temperatures above 800℃due to high activity of a superficial Ti atomic ***,spark plasma sintering of Ti_(3)C_(2)T_(x) and TiC is performed to prevent the Ti_(3)C_(2)T_(x) phase transition at temperatures up to 1900℃through the fabrication of composites at a pressure of 50 *** a focused ion beam scanning electron microscope to separate layered substances in the composites and examining selected area diffraction spots in a transmission electron microscope enabled identification of non-phase-transitioned ***-principles calculations based on density functional theory indicated the formation of strong chemical bonding interfaces between Ti_(3)C_(2)T_(x) and TiC,which imposed a stability constraint on the Ti atomic layer at the Ti_(3)C_(2)T_(x) *** performance tests,such as three-point bending and fracture toughness analysis,demonstrated that the addition of Ti_(3)C_(2)T_(x) can effectively improve the cross-scale strengthening and toughening of the TiC matrix,providing a new path for designing and developing two-dimensional(2D)carbides cross-scale-enhanced three-dimensional(3D)carbides with the same elements relying on a wide variety of MXenes.
computer-aided pathology diagnosis based on whole slide images, which is often formulated as a weakly supervised multiple instance learning (MIL) paradigm. Current approaches generally employ attention mechanisms to a...
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The integration of artificial intelligence(AI)technology,particularly large language models(LLMs),has become essential across various sectors due to their advanced language comprehension and generation *** their trans...
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The integration of artificial intelligence(AI)technology,particularly large language models(LLMs),has become essential across various sectors due to their advanced language comprehension and generation *** their transformative impact in fields such as machine translation and intelligent dialogue systems,LLMs face significant *** challenges include safety,security,and privacy concerns that undermine their trustworthiness and effectiveness,such as hallucinations,backdoor attacks,and privacy *** works often conflated safety issues with security *** contrast,our study provides clearer and more reasonable definitions for safety,security,and privacy within the context of *** on these definitions,we provide a comprehensive overview of the vulnerabilities and defense mechanisms related to safety,security,and privacy in ***,we explore the unique research challenges posed by LLMs and suggest potential avenues for future research,aiming to enhance the robustness and reliability of LLMs in the face of emerging threats.
Modern machining machines are becoming more sophisticated and automated, but the problems of thermal deformation caused by machining have also come to the fore. CNC machine tools are used in high-speed, high-feed rate...
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