Generative AI (GenAI) chatbots have taken the world by storm with their ability to summarize information and produce complex natural language *** the same time, the demand for computerscience education has grown *** ...
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To accommodate the wide range of input voltages supplied by redundant batteries and ensure an adequate hold-up time for communication systems during utility power failures, power supplies used in 5 G base stations typ...
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In this work, initially a rectangular microstrip patch antenna measuring (94.8 × 110 × 10) μm3 with a polyamide substrate has been analyzed and developed. The antenna has a bandwidth of 170 GHz (1.98 - 2.15...
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Capacitive sensors are common ubiquitous sensing devices that permeate through many industries. The overwhelming majority of touchscreens use capacitive sensor arrays for the precise detection of touch. Many MEMS sens...
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Axial flux permanent magnet (AFPM) machines have technological competitiveness for electric propulsion systems that require compact structures and high-power density. However, challenging design and manufacturing prob...
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Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutio...
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Within the electronic design automation(EDA) domain, artificial intelligence(AI)-driven solutions have emerged as formidable tools, yet they typically augment rather than redefine existing methodologies. These solutions often repurpose deep learning models from other domains, such as vision, text, and graph analytics, applying them to circuit design without tailoring to the unique complexities of electronic circuits. Such an “AI4EDA” approach falls short of achieving a holistic design synthesis and understanding,overlooking the intricate interplay of electrical, logical, and physical facets of circuit data. This study argues for a paradigm shift from AI4EDA towards AI-rooted EDA from the ground up, integrating AI at the core of the design process. Pivotal to this vision is the development of a multimodal circuit representation learning technique, poised to provide a comprehensive understanding by harmonizing and extracting insights from varied data sources, such as functional specifications, register-transfer level(RTL) designs, circuit netlists,and physical layouts. We champion the creation of large circuit models(LCMs) that are inherently multimodal, crafted to decode and express the rich semantics and structures of circuit data, thus fostering more resilient, efficient, and inventive design methodologies. Embracing this AI-rooted philosophy, we foresee a trajectory that transcends the current innovation plateau in EDA, igniting a profound “shift-left” in electronic design methodology. The envisioned advancements herald not just an evolution of existing EDA tools but a revolution, giving rise to novel instruments of design-tools that promise to radically enhance design productivity and inaugurate a new epoch where the optimization of circuit performance, power, and area(PPA) is achieved not incrementally, but through leaps that redefine the benchmarks of electronic systems' capabilities.
Permanent magnets (PM) demagnetization occurs when applying external fields opposite the PM's polarity. To a certain degree, this effect is reversible and useful in high-speed permanent magnet synchronous motors (...
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Recent advancements in Visual Question Answering (VQA) have been driven by the integration of complex attention mechanisms. This work introduces a novel approach aimed at enhancing multi-modal representations through ...
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A designed Mg_(88.7)Ni_(6.3)Y_(5)hydrogen storage alloy containing 14H type LPSO(long-period stacking ordered)and ternary eutectic structure was prepared by regulating the alloy composition and *** hydrogen storage pe...
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A designed Mg_(88.7)Ni_(6.3)Y_(5)hydrogen storage alloy containing 14H type LPSO(long-period stacking ordered)and ternary eutectic structure was prepared by regulating the alloy composition and *** hydrogen storage performance of the alloy was improved by adding nano-flower-like TiO_(2)@C *** decomposition of the LPSO structure during hydrogenation led to the formation of plenty of nanocrystals which provided abundant interphase boundaries and activation *** nanoscale TiO_(2)@C catalyst was uniformly dispersed on the surface of alloy particles,and the"hydrogen overflow''effect of TiO_(2)@C accelerated the dissociation and diffusion of hydrogen on the surface of the alloy *** a result,the in-situ endogenous nanocrystals of the LPSO structure decomposition and the externally added flower-like TiO_(2)@C catalyst uniformly dispersed on the surface of the nanoparticles played a synergistic catalytic role in improving the hydrogen storage performance of the Mg-based *** the addition of the TiO_(2)@C catalyst,the beginning hydrogen desorption temperature was reduced to 200℃.Furthermore,the saturated hydrogen absorption capacity of the sample was 5.32 wt.%,and it reached 4.25 wt.%H_(2) in 1 min at 200℃and 30 bar.
Various methods have been proposed to secure access to sensitive information over time, such as many cryptographic methods in use to facilitate secure communications on the internet. But other methods like steganograp...
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