The rapid advancement of artificial intelligence(AI) has significantly impacted photonics, creating a symbiotic relationship that accelerates the development and applications of both fields. From the perspective of AI...
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The rapid advancement of artificial intelligence(AI) has significantly impacted photonics, creating a symbiotic relationship that accelerates the development and applications of both fields. From the perspective of AI aiding photonics, deep-learning methods and various intelligent algorithms have been developed for designing complex photonic structures, where traditional design approaches fall short. AI's capability to process and analyze large data sets has enabled the discovery of novel materials, such as for photovoltaics,leading to enhanced light absorption and efficiency. AI is also significantly transforming the field of optical imaging with improved performance. In addition, AI-driven techniques have revolutionized optical communication systems by optimizing signal processing and enhancing the bandwidth and reliability of data transmission. Conversely, the contribution of photonics to AI is equally profound. Photonic technologies offer unparalleled advantages in the development of AI hardware, providing solutions to overcome the bottlenecks of electronic systems. The implementation of photonic neural networks, leveraging the high speed and parallelism of optical computing, demonstrates significant improvements in the processing speed and energy efficiency of AI computations. Furthermore, advancements in optical sensors and imaging technologies not only enrich AI applications with high-quality data but also expand the capabilities of AI in fields such as autonomous vehicles and medical imaging. We provide comprehensive knowledge and a detailed analysis of the current state of the art, addressing both challenges and opportunities at the intersection of AI and photonics. The multifaceted interactions between AI and photonics will be explored, illustrating how AI has become an indispensable tool in the development of photonics and how photonics, in turn,facilitates advancements in AI. Through a collection of case studies and examples, we underscore the potential
In order to investigate the characteristics of drivers’ eye movements during distracted driving caused by mobile phone conversation and establish a driving distraction discriminant model, a driving simulation experim...
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As the world continues to experience significant and dynamic changes, the concept of graduate employability remains a well-discussed subject in the body of knowledge. Consequently, the concept has attracted the intere...
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COVID-19 is a contagious infection that has severe effects on the global economy and our daily *** diagnosis of COVID-19 is of importance for consultants,patients,and *** this study,we use the deep learning network Al...
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COVID-19 is a contagious infection that has severe effects on the global economy and our daily *** diagnosis of COVID-19 is of importance for consultants,patients,and *** this study,we use the deep learning network AlexNet as the backbone,and enhance it with the following two aspects:1)adding batch normalization to help accelerate the training,reducing the internal covariance shift;2)replacing the fully connected layer in AlexNet with three classifiers:SNN,ELM,and ***,we have three novel models from the deep COVID network(DC-Net)framework,which are named DC-Net-S,DC-Net-E,and DC-Net-R,*** comparison,we find the proposed DC-Net-R achieves an average accuracy of 90.91%on a private dataset(available upon email request)comprising of 296 images while the specificity reaches 96.13%,and has the best performance among all three proposed *** addition,we show that our DC-Net-R also performs much better than other existing algorithms in the literature.
The growing amount of data and advances in data science have created a need for a new kind of cloud platform that provides users with flexibility, strong security, and the ability to couple with supercomputers and edg...
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Innovative technology and local content cannot be achieved without appropriate techniques and testing methods to realize sustainable civil infrastructure in a challenging economy. This paper examines the utilization o...
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ISBN:
(数字)9798331542559
ISBN:
(纸本)9798331542566
Innovative technology and local content cannot be achieved without appropriate techniques and testing methods to realize sustainable civil infrastructure in a challenging economy. This paper examines the utilization of operation research techniques and innovative testing methods for sustainable construction materials. Pertinent literature and empirical studies were combined to explore the theoretical foundations and real-world applications of operation research methodologies and novel testing methods for sustainable construction. Findings revealed that operation research techniques play a significant role in maximizing the consumption of sustainable construction materials. In the construction sector, ultrasonic testing (UT) is a popular non-destructive testing (NDT) method for evaluating the characteristics and structural integrity of materials like composites, steel, and concrete. Radiographic testing (RT), Computed tomography (CT), digital image correlation (DIC), and laser scanning are Ekiti State, Nigeria beneficial. A non-invasive geophysical technique called ground-penetrating radar (GPR) is used to find and map subsurface features, utilities, and irregularities in soil and building materials. Despite the advancements in operation research techniques and innovative testing methods for sustainable construction materials, several challenges persist, and future directions warrant attention to further enhance their effectiveness and applicability in construction projects. In conclusion, integrating operation research techniques and innovative testing methods represents a transformative opportunity to build a more sustainable future for the construction industry and society. Supportive policies and regulations can drive the adoption of sustainable practices and innovative technologies in the construction industry.
As the size of datasets and neural network models increases, automatic parallelization methods for models have become a research hotspot in recent years. The existing auto-parallel methods based on machine learning or...
As the size of datasets and neural network models increases, automatic parallelization methods for models have become a research hotspot in recent years. The existing auto-parallel methods based on machine learning or graph algorithms still have issues with search efficiency and applicability. This paper proposes an automatic parallel method based on a dual-population genetic algorithm, TGA, which transforms model partitioning and placement into an integer linear programming problem and constructs a cost model to evaluate the solution. The solution space is built using the neural network’s dataflow graph and device cluster’s topology, and the dual-population genetic algorithm is used to search for the optimal model parallel strategy. Experiments with various models show that the proposed method can improve single-step execution time by up to 42% compared to the Baechi method and up to 37.7% compared to the Hierarchical method.
With the development of social media, various rumors can be easily spread on the Internet and such rumors can have serious negative effects on society. Thus, it has become a critical task for social media platforms to...
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This one-day hybrid workshop builds on previous feminist CSCW workshops to explore feminist theoretical and methodological approaches that have provided us with useful tools to see things differently and make space fo...
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Topological physics of phonon spectra has been attracting great interest. Using the first-principle calculations and symmetry analysis, we show the realistic ternary nitride Li6WN4 features ideal (nearly flat) nodal-s...
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Topological physics of phonon spectra has been attracting great interest. Using the first-principle calculations and symmetry analysis, we show the realistic ternary nitride Li6WN4 features ideal (nearly flat) nodal-surface and nodal-line structures in its phonon spectra. These nodal degeneracies are shaped like lanterns, and their existence is guaranteed by nonsymmorphic symmetry. The corresponding topological phonon surface state covers exactly half the surface Brillouin zone and can thereby be distinguished from those of conventional nodal-line and nodal-surface semimetals. Our study enriches the classification of topological quantum phases, predicts ideal material candidates, and provides a good platform for investigating the interaction between nodal-line and nodal-surface phonons.
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