Jian Dai

Constructing and Validating a Geometric–Organic Index for Road Networks in Qing Dynasty County Cities

Longyin Teng, Li Li, Jian Dai

The position of urban road networks along the spectrum from geometric order to organic growth reflects the long-term tension between institutional planning and adaptive accommodation to local conditions, yet systematic quantification of this continuum in large historical urban datasets remains absent. This …

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S2ONN: A structured sparse optical neural network with reduced hardware complexity

Dewei Wang, Qing Chen, Zhiwei Yang, Tian Zhang et autres

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A Photonic-Electronic binary polynomial multiplier for efficient computing

Quan Chen, Zhiwei Yang, Tian Yao Zhang, Jian Dai et autres

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Modeling Ontology-Based Decay Analysis and HBIM for the Conservation of Architectural Heritage: The Big Gate and Adjacent Curtain Walls in Ibb, Yemen

Basema Qasim Derhem Dammag, Jian Dai, Abdulkarem Qasem Dammag, Yahya Alshawabkeh et autres

The conservation of architectural heritage (AH) in regions threatened by natural and human-induced factors requires interdisciplinary approaches that integrate physical documentation with semantic modeling. This study introduces a comprehensive framework combining Historic Building Information Modeling (HBIM) with ontology-based modeling aligned with the …

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Publisher Correction: Efficient off-chip configuration method for scalable programmable photonic integrated circuits

Zeyang Fan, JunMin Lin, Tian Yao Zhang, Jian Dai et autres

In the version of the article initially published, the authors’ names were presented with the family name first and have now been amended in the HTML and PDF versions of the article.

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Mechanisms and Resilience Governance of Built Heritage Spatial Differentiation in China: A Sustainability Perspective

Yuanwei Lu, Teng Li, Jian Dai, Qingwen Han et autres

Built heritage serves as a vital repository of human history and culture, and an examination of its spatial distribution and influencing factors holds significant value for the preservation and advancement of our historical and cultural narratives. This thesis brings together various forms …

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An MZI-Based Block Optical Neural Network Based on LDU Structure

Qi Chen, Dewei Wang, Tian Yao Zhang, Jian Dai et autres

We propose an LDU-based block optical neural network, significantly reducing hardware complexity and improving matrix mapping fidelity. It achieves 90.47% accuracy on SVHN dataset and maintains 80.84% under hardware errors, demonstrating effectiveness and exceptional robustness.

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On-Chip Reconfigurable Activation Functions based on Coherent Nonlinear Synthesis

Quan Chen, Yihang Lai, Zhiwei Yang, Tian Yao Zhang et autres

We propose a compact novel device with inverse design structure and phase shifter and achieved reconfigurable coherent nonlinear responses. In classical MNIST task, we prove our generated nonlinear responses to be efficient.

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Integrated Photonic Reservoir Computing with Tunable Memory Capacity

Yihang Lai, Zhiwei Yang, Quan Chen, Tian Zhang et autres

We propose a novel integrated reservoir computing scheme with dynamically adjustable short-term memory capacity, ranging from 0-20. Our scheme can efficiently complete NARMA time series prediction tasks while meeting different memory capacity requirements.

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Efficient off-chip configuration method for scalable programmable photonic integrated circuits

Zeyang Fan, JunMin Lin, Tian Yao Zhang, Jian Dai et autres

Programmable photonic integrated circuits can realize analog matrix multiplication to accelerate computing disruptively in various fields. However, a major challenge is the precise voltage configuration of the circuit to deal with the universal static error derived from manufacturing. Here, we propose a …

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Efficient training for large-scale optical neural network using an evolutionary strategy and attention pruning

Zhiwei Yang, Yihang Lai, Qi Chen, Tian Zhang et autres

MZI-based block optical neural networks (BONNs), which can achieve large-scale network models, have increasingly drawn attentions. However, the robustness of the current training algorithm is not high enough. Moreover, large-scale BONNs usually contain numerous trainable parameters, resulting in expensive computation and power …

RoNo: A novel way in generating reconfigurable on-chip nonlinear activation functions

Tian Yao Zhang, Jian Dai, Zheng Wang, Kun Xu

Due to the limitations of Moore's Law and the increasing demand of computing, optical neural network (ONNs) are gradually coming to the stage as an alternative to electrical neural networks. The control of nonlinear activation functions in optical environments, as an important …