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Fuzzy deep learning architecture for cucumber plant disease detection and classification

Journal of Big Data 2025年第1期12卷 1-21页

作者： Bilal, Anas Khan, Junaid Ali Alzahrani, Abdulkareem Almohammadi, Khalid Alamri, Maha Liu, Xiaowen College of Information Science and Technology Hainan Normal University Haikou571158 China Department of Computer Science HITEC University Taxila Taxila47080 Pakistan Computer Science Department Faculty of Computing and Information Al-Baha University Al-Baha65779 Saudi Arabia Computer Science Department Applied College University of Tabuk Tabuk Saudi Arabia Software Engineering Department Faculty of Computing and Information Al-Baha University Al-Baha65779 Saudi Arabia

This paper introduces a novel fuzzy deep convolutional neural network architecture for cucumber plant disease detection, contributing to precision farming in Industry 5.0. The proposed architecture incorporates 40 convolutional layers, 4 pooling layers, 4 inverted bottleneck blocks, 4 bottleneck blocks, 5 fuzzy layers, and a fully connected layer designed to enhance accuracy and stability when analyzing remotely sensed data. The fuzzy optimistic formula is used for activation in four blocks, enabling effective information fusion. At the same time, the ReLU transfer function ensures robustness, mainly when dealing with noisy or incomplete image segments. Feature vector optimization is performed using a chaotic particle swarm algorithm, enhancing the model’s overall accuracy, reliability, and ease of implementation. The architecture achieves 98% classification accuracy, outperforming leading models like VGG-19, DarkNet-19, and ResNet-50. Moreover, the computational time per run (40–90 s) is significantly lower than these models, which use higher learnable parameters (5.7 million). The proposed approach is efficient and feasible, offering a more stable and accurate disease detection system while utilizing fewer resources. This work demonstrates the potential of AI-driven solutions in agriculture, particularly in improving disease detection and crop yield through advanced machine learning techniques. © The Author(s) 2025.

关键词： Convolutional neural networks

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Fourier-domain mode-locked lasers on a hybrid-integrated silicon photonic chip

Fourier-domain mode-locked lasers on a hybrid-integrated sil...

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Smart Photonic and Optoelectronic Integrated Circuits 2025

作者： Kwan, Ching Chi Poon, Andrew W. Photonic Device Laboratory Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong

ISBN: (纸本)9781510684881

We are in the process of developing a hybrid-integrated compact frequency-comb Fourier-domain mode-locked (FDML) laser source for swept-source optical coherence tomography (SS-OCT) applications. Our approach incorporates silicon photonic components, including electro-optic (EO) and thermo-optic (TO)-tunable silicon microring-based Vernier filters as the tunable filter to achieve a high sweep rate in multi-MHz and a high-quality-factor silicon microring frequency comb to enhance the imaging depth. We aim to use an external semiconductor optical amplifier with these components to demonstrate the feasibility of high-performance hybrid-integrated chip-based laser source for SS-OCT. © 2025 SPIE.

关键词： Semiconductor optical amplifiers

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External-feedback-coupled microring lasers on a III-V-on-Si photonic chip for reservoir computing

External-feedback-coupled microring lasers on a III-V-on-Si ...

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Smart Photonic and Optoelectronic Integrated Circuits 2025

作者： Niu, Yue Poon, Andrew W. Photonic Device Laboratory Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong

ISBN: (纸本)9781510684881

Photonic reservoir computing using a single neuron node exploits transient states at different times of a nonlinear oscillator. A semiconductor laser diode (LD) with injection carriers and emission photons oscillating in a laser cavity can work as a photonic reservoir. An LD coupled with an external feedback cavity increases the memory capacity and the nonlinearity of a reservoir. A microring laser cavity is equipped with additional nonlinearities with two counterpropagating lasing modes in a compact size. In this paper, we present our progress in the design and fabrication of an external-feedbackcoupled microring laser on a heterogeneously integrated III-V-on-Si platform to construct a photonic reservoir computing system. © 2025 SPIE.

关键词： Photonic integrated circuits

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Enhancing WRSN Sustainability through On-demand Directional Wireless Charging with Multiple Green-powered Mobile Vehicles

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IEEE Internet of Things Journal 2025年第11期12卷 18019-18030页

作者： Ma, Xiongbo Liu, Xilong Ansari, Nirwan Ding, Jun The School of Information Science and Engineering Yunnan University Yunnan Kunming650500 China The Advanced Networking Laboratory Helen & John C. Hartmann Department of Electrical and Computer Engineering New Jersey Institute of Technology NewarkNJ07102 United States

Current research on scheduling mobile charging vehicles (MCVs) generally focuses on periodic and omnidirectional charging of sensor nodes (SNs). However, this approach leads to significant energy wastage, especially when relying on fossil energy sources. In this work, we propose to schedule multiple green energy-powered MCVs equipped with directional antennas to efficiently charge SNs. We first develop an on-demand and directional charging model based on far-field wireless charging. Then, we formulate the SN survival maximization problem to efficiently prolong the lifetime of wireless rechargeable sensor networks (WRSNs). Given the NP-hard nature of this optimization problem, we develop the three-Step directIonal wireless charGiNg (SIGN) algorithm to efficiently solve this problem. SIGN strategically determines the MCVs’ anchor points (APs), traveling paths and wireless energy emitting directions. Finally, we conduct extensive simulation experiments to validate the superiority of our proposed algorithm in optimizing energy usage and prolonging network lifetime. © 2014 IEEE.

关键词： Wireless charging

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A Systematic Flexible-Window based Scheduling Framework for Time-Sensitive Networking

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IEEE Internet of Things Journal 2025年第11期12卷 15636-15649页

作者： Sun, Wenjing Zou, Yuan Guan, Nan Zhang, Xudong Liu, Jiahui Farzaneh, Morteza Hashemi Beijing Institute of Technology National Engineering Laboratory for Electric Vehicles School of Mechanical Engineering and Collaborative Innovation Center of Electric Vehicles in Beijing Beijing100081 China City University of Hong Kong Department of Computer Science Hong Kong RealtimeIT Germany

Time-Sensitive Networking (TSN) is increasingly applied in automotive and industrial internet fields due to its low latency and deterministic communication. Gate control list (GCL) is foundational for deploying TSN. Currently, most scheduling research focuses on frame-to-window based scheduling. This scheduling approach typically generates a specific window for each frame, leading to a proliferation of GCL in large networks, which increases the complexity of implementing TSN. To simplify deployment and enhance scheduling reliability, this paper introduces a systematic flexible-window based scheduling framework. Utilizing a gapless GCL design approach, it optimizes flow's worst-case end-to-end (e2e) delays through window length design, with delays obtained through network calculus analysis. A generic solving framework based on metaheuristic algorithms is established to address this optimization problem. The scheduling framework also features a load-balanced turn prohibition routing strategy to balance link loads and avoid cyclic dependencies, alongside a K-means priority clustering method based on routing overlap to reduce the number of priorities. Simulation validation in a high-level autonomous driving vehicle's in-vehicle network shows that the proposed method can decrease GCL numbers by nearly 90% against frame-to-window scheduling. In common industrial internet scenario, it significantly reduces worst-case e2e delays and enhances scheduling success rates compared to the analogous scheduling method. Large-scale complex network scenario further demonstrates its scalability. © 2025 IEEE.

关键词： K-means clustering

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Integrated quantum photonics in 3C-SiCOI platforms

Integrated quantum photonics in 3C-SiCOI platforms

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Smart Photonic and Optoelectronic Integrated Circuits 2025

作者： Poon, Andrew W. Zhang, Qianni Wang, Jiantao Photonic Device Laboratory Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong

ISBN: (纸本)9781510684881

3C-silicon carbide-on-insulator (3C-SiCOI) is an emerging photonic platform for integrated quantum photonics due to its moderate second- and third-order optical nonlinearities, wide bandgap energy, and compatibility with silicon complementary metal-oxide-semiconductor technologies. In this work, we report our progress in photon-pair generation and quantum state manipulation on the 3C-SiCOI platform. We demonstrate the generation of photon pairs through the spontaneous parametric down-conversion process using modal phase-matching in an elliptical microring resonator on this platform. We will present the design principle and recent progress of our experimental work. © 2025 SPIE.

关键词： Photonic integrated circuits

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High-Q AlGaAs-on-insulator microresonators for spontaneous parametric down-conversion

High-Q AlGaAs-on-insulator microresonators for spontaneous p...

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Smart Photonic and Optoelectronic Integrated Circuits 2025

作者： Tan, Bo Xue Wang, Jiantao Poon, Andrew W. Photonic Device Laboratory Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Clear Water Bay Hong Kong

ISBN: (纸本)9781510684881

Aluminum gallium arsenide (AlGaAs) is a promising photonic platform for photon-pair generation through spontaneous parametric down-conversion (SPDC) or spontaneous four-wave mixing due to its high optical nonlinearities. In this paper, we report our progress in the design and fabrication of high-quality-factor waveguide-coupled microring resonators in an AlGaAs-on-insulator (AlGaAsOI) platform using i-line (365 nm) photolithography. We design the waveguide geometries for the modal-phase matching for SPDC. Our preliminary results suggest the potential for efficient photon-pair generation in an AlGaAsOI platform for quantum photonic applications. © 2025 SPIE.

关键词： Four wave mixing

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Metamorphic Relation Patterns for Metamorphic Testing, Exploration and Robustness

Metamorphic Relation Patterns for Metamorphic Testing, Explo...

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作者： Ying, Zhihao Towey, Dave Bellotti, Anthony Chua, Caslon Quan Zhou, Zhi School of Computer Science University of Nottingham Ningbo China Zhejiang Ningbo China Department of Computer Science and Software Engineering Swinburne University of Technology HawthornVIC Australia School of Computing and Information Technology University of Wollongong WollongongNSW Australia

Metamorphic testing (MT) is an effective software quality assurance method;it uses metamorphic relations (MRs) to examine the inputs and outputs of multiple test cases. Metamorphic exploration (ME) and metamorphic robustness testing (MRT) are advanced additions to the MT literature: ME can enable better understanding, and thus testing, of systems;MRT can test software robustness without an oracle. Metamorphic relation patterns (MRPs) are abstractions or templates for multiple concrete MRs. The performance of MT/ME/MRT relies on the quality of MRs, but the identification of MRs is often a manual task requiring some knowledge of MRPs, creative thinking and a good understanding of the system. In other words, the effective identification of MRs remains a challenge and requires further study. In this paper, we propose formal definitions to describe the relationship between multiple MRPs in order to classify them. We also identify a series of new MRPs and propose a new MT framework that can guide the identification and application of MRPs. Based on our definitions, we present the notion of MRP family trees and further propose two trees by classifying previously published MRPs and our proposed MRPs, in order to make it easier for users to find their target MRPs for reuse, reference or inference. Finally, we report on case studies using the MRPs and our framework to guide the identification of MRs for MT/ME/MRT and successfully detect multiple violations. © 2025 John Wiley & Sons Ltd.

关键词： software testing

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MR-COGraphs: Communication-Efficient Multi-Robot Open-Vocabulary Mapping System via 3D Scene Graphs

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IEEE Robotics and Automation Letters 2025年第6期10卷 5713-5720页

作者： Gu, Qiuyi Ye, Zhaocheng Yu, Jincheng Tang, Jiahao Yi, Tinghao Dong, Yuhan Wang, Jian Cui, Jinqiang Chen, Xinlei Wang, Yu Tsinghua University Shenzhen International Graduate School Shenzhen518055 China Pengcheng Laboratory Shenzhen518055 China Tsinghua University Department of Electronic Engineering Beijing100084 China University of Science and Technology of China Department of Computer Science Hefei230002 China Openmind Wuhu241000 China Pengcheng Laboratory Shenzhen Guangdong518055 China

Collaborative perception in unknown environments is crucial for multi-robot systems. With the emergence of foundation models, robots can now not only perceive geometric information but also achieve open-vocabulary scene understanding. However, existing map representations that support open-vocabulary queries often involve large data volumes, which becomes a bottleneck for multi-robot transmission in communication-limited environments. To address this challenge, we develop a method to construct a graph-structured 3D representation called COGraph, where nodes represent objects with semantic features and edges capture their spatial adjacency relationships. Before transmission, a data-driven feature encoder is applied to compress the feature dimensions of the COGraph. Upon receiving COGraphs from other robots, the semantic features of each node are recovered using a decoder. We also propose a feature-based approach for place recognition and translation estimation, enabling the merging of local COGraphs into a unified global map. We validate our framework on two realistic datasets and the real-world environment. The results demonstrate that, compared to existing baselines for open-vocabulary map construction, our framework reduces the data volume by over 80% while maintaining mapping and query performance without compromise. © 2016 IEEE.

关键词： Mapping

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A trajectory-level robot skill learning method based on fuzzy systems

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science China(Information sciences) 2025年第5期68卷 38-52页

作者： Chao ZENG Zhen DENG Boyang TI Yongsheng GAO Department of Computer Science University of Liverpool School of Mechanical Engineering and Automation Fuzhou University State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences State Key Laboratory of Robotics and System Harbin Institute of Technology

Learning from demonstration(LfD) allows for the effective transfer of human manipulation skills to a robot by building a model that represents these skills based on a limited number of demonstrated ***,a skilllearning model that can comprehensively satisfy multiple requirements,such as computational complexity,modeling accuracy,trajectory smoothness,and robustness,is still ***,this work aims to provide such a model by employing fuzzy ***,we introduce an LfD model named Takagi-Sugeno-Kang fuzzy system-based movement primitives(TSKFMPs),which exploits the advantages of the fuzzy theory for effective robotic imitation learning of human *** work formulates the TSK fuzzy system and gradient descent(GD) as imitation learning models,leveraging recent advancements in GD-based optimization for fuzzy *** study takes a two-step strategy.(ⅰ) The input-output relationships of the model are established using TSK fuzzy systems based on demonstration *** this way,the skill is encoded by the model parameter in the latent space.(ⅱ) GD is used to optimize the model parameter to increase the modeling accuracy and trajectory *** further explain how learned trajectories are adapted to new task scenarios through local *** conduct multiple tests using an open dataset to validate our method,and the results demonstrate performance comparable with those of other ***,we implement it in a real-world case study.

关键词： robot skill learning movement primitives TSK fuzzy systems gradient descent robotics

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