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Damaged apple detection with a hybrid YOLOv3 algorithm

Information Processing in Agriculture 2024年第2期11卷 163-171页

作者： Meng Zhang Huazhao Liang Zhongju Wang Long Wang Chao Huang Xiong Luo Schoolof Computer and Communication Engineering University of Science and Technoogy BejingBejing 1083China lShunde Innovation SchoolUniversity of Science and Technology BeijingFoshan 528399China

This paper proposes an improved You Only Look Once(YOLOv3)algorithm for automatically detecting damaged apples to promote the automation of the fruit processing *** the proposed method,a clustering method based on Rao-1 algorithm is introduced to optimize anchor box *** clustering method uses the intersection over the union to form the objective function and the most representative anchor boxes are generated for normal and damaged apple *** verify the feasibility and effectiveness of the proposed method,real apple images collected from the Internet are *** with the generic YOLOv3 and Fast Region-based Convolutional Neural Network(Fast R-CNN)algorithms,the proposed method yields the highest mean average precision value for the test ***,it is practical to apply the proposed method for intelligent apple detection and classification tasks.

关键词： Rao algorithm Apple detection Clustering Smart agriculture

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Analysis on unit maximum capacity of orthogonal multiple watermarking for multimedia signals in B5G wireless communications

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Digital Communications and Networks 2024年第1期10卷 38-44页

作者： Mianjie Li Senfeng Lai Jiao Wang Zhihong Tian Nadra Guizani Xiaojiang Du Chun Shan School of Electronics and Information Guangdong Polytechnic Normal UniversityGuangzhou510665China Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510006China Schoolof Electrical Engineering and Computer Science Washington State UniversityPullmanWA99164USA Department of Computer and Information Science Temple UniversityPhiladelphiaPA19122USA

Beyond-5G(B5G)aims to meet the growing demands of mobile traffic and expand the communication *** that intelligent applications to B5G wireless communications will involve security issues regarding user data and operational data,this paper analyzes the maximum capacity of the multi-watermarking method for multimedia signal hiding as a means of alleviating the information security problem of *** multiwatermarking process employs spread transform dither *** the watermarking procedure,Gram-Schmidt orthogonalization is used to obtain the multiple spreading ***,multiple watermarks can be simultaneously embedded into the same position of a multimedia ***,the multiple watermarks can be extracted without affecting one another during the extraction *** analyze the effect of the size of the spreading vector on the unit maximum capacity,and consequently derive the theoretical relationship between the size of the spreading vector and the unit maximum capacity.A number of experiments are conducted to determine the optimal parameter values for maximum robustness on the premise of high capacity and good imperceptibility.

关键词： B5G Multimedia information security Spread transform dither modulation Spreading vector measurement Unit maximum capacity

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Feature selection strategy optimization for lithium-ion battery state of health estimation under impedance uncertainties

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Journal of Energy Chemistry 2025年第2期101卷 87-98,I0003页

作者： Xinghao Du Jinhao Meng Yassine Amirat Fei Gao Mohamed Benbouzid UMR CNRS 6027 IRDL University of BrestBrest 29238France School of Electrical Engineering xi'an Jiaotong UniversityXi'an 710049ShaanxiChina L@bISEN ISEN Yncrea OuestBrest 29200France Schoolof Energy and Computer Science University of Technology of Belfort-MontbeliardBelfort 90000France

Battery health evaluation and management are vital for the long-term reliability and optimal performance of lithium-ion batteries in electric *** impedance spectroscopy(EIS)offers valuable insights into battery degradation analysis and ***,previous studies have not adequately addressed the impedance uncertainties,particularly during battery operating conditions,which can substantially impact the robustness and accuracy of state of health(SOH)*** by this,this paper proposes a comprehensive feature optimization scheme that integrates impedance validity assessment with correlation *** utilizing metrics such as impedance residuals and correlation coefficients,the proposed method effectively filters out invalid and insignificant impedance data,thereby enhancing the reliability of the input ***,the extreme gradient boosting(XGBoost)modeling framework is constructed for estimating the battery degradation *** XGBoost model incorporates a diverse range of hyperparameters,optimized by a genetic algorithm to improve its adaptability and generalization *** validation confirms the effectiveness of the proposed feature optimization scheme,demonstrating the superior estimation performance of the proposed method in comparison with four baseline techniques.

关键词： Lithium-ion battery Stateof health Electrochemical impedance spectroscopy Extreme gradient boosting

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Tunable Multicolor Fluorescence of Perovskite-Based Composites for Optical Steganography and Light-Emitting Devices

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Research 2023年第1期2022卷 185-195页

作者： Kewei Ma Qingfeng Gui Cihui Liu Yunyi Yang Fangjian Xing Yunsong Di Xiaoming Wen Baohua Jia Zhixing Gan Center for Future Optoelectronic Functional Materials School of Computer and Electronic Information/School of Artificial IntelligenceNanjing Normal UniversityNanjing 210023China College of Naval Architecture and Ocean Engineering Jiangsu Maritime InstituteNanjing 211170China Centrefor Translational Atomaterials Schoolof ScienceSwinburne University of TechnologyJohn Street Hawthon VIC3122Australia School of Science RMIT UniversityMelbourne3000 VICAustralia College of Materials Science and Engineering Qingdao University of Science and TechnologyQingdao 266042China

Multicolor fluorescence of mixed halide perovskites enormously enables their applications in photonics and ***,it remains an arduous task to obtain multicolor emissions from perovskites containing single halogen to avoid phase ***,a fluorescent composite containing Eu-based metal-organic frameworks(MOFs),OD Cs PbBre,and 3D CsPbBrs is *** excitations at 365 nm and 254nm,the pristine composite emits blue(B)and red(R)fluorescence,which are ascribed to radiative defects within CsPbBr and 5Do→7F,transitions of Eu^(3+),***,after light soaking in the ambient environment,the blue fluorescence gradually converts into green(G)emission due to the defect repairing and 0D-3D phase *** permanent and unique photochromic effect enables anticounterfeiting and microsteganography with increased security through a micropatterning ***,the RGB luminescence is highly stable after encapsulation by a transparent polymer ***,trichromatic light-emitting modules are fabricated by using the fluorescent composites as color-converting layers,which almost fully cover the standard color ***,this work innovates a strategy for construction of tunable multicolor luminescence by manipulating the radiative defects and structural dimensionality.

关键词： composite composites perovskite

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Capturing the hierarchically assorted modules of protein–protein interactions in the organized nucleome

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Molecular Plant 2023年第5期16卷 930-961页

作者： Shuaijian Dai Shichang Liu Chen Zhou Fengchao Yu Guang Zhu Wenhao Zhang Haiteng Deng Al Burlingame Weichuan Yu Tingliang Wang Ning Li Division of Life Science The Hong Kong University of Science and TechnologyHong Kong SARChina Department of Chemical and Biological Engineering The Hong Kong University of Science and TechnologyHong KongChina Tsinghua-Peking Joint Centre for Life Sciences Centre for Structural BiologySchoolof Life Sciences and Schoolof MedicineTsinghua UniversityBejing 100084China The Hk.UST Shenzhen-Hong Kong Collaborative Innovation Research Institute FutianShenzhenGuangdong 518057China Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyHong Kong SARChina Department of Pharmaceutical Chemistry University of CaliforniaSan FranciscoSan FranciscoCAUSA

Nuclear proteins are major constituents and key regulators of nucleome topological organization and manipulators of nuclear *** decipher the global connectivity of nuclear proteins and the hierarchically organized modules of their interactions,we conducted two rounds of cross-linking mass spectrometry(XL-MS)analysis,one of which followed a quantitative double chemical cross-linking mass spectrometry(in vivo qXL-MS)workflow,and identified 24,140 unique crosslinks in total from the nuclei of soybean *** in vivo quantitative interactomics enabled the identification of 5340 crosslinks that can be converted into 1297 nuclear protein–protein interactions(PPIs),1220(94%)of which were non-confirmative(or novel)nuclear PPIs compared with those in *** were 250 and 26 novel interactors of histones and the nucleolar box C/D small nucleolar ribonucleoprotein complex,*** analysis of orthologous Arabidopsis PPIs produced 27 and 24 master nuclear PPI modules(NPIMs)that contain the condensate-forming protein(s)and the intrinsically disordered region–containing proteins,*** NPIMs successfully captured previously reported nuclear protein complexes and nuclear bodies in the ***,these NPIMs were hierarchically assorted into four higher-order communities in a nucleomic graph,including genome and nucleolus *** combinatorial pipeline of 4C quantitative interactomics and PPI network modularization revealed 17 ethylene-specific module variants that participate in a broad range of nuclear *** pipeline was able to capture both nuclear protein complexes and nuclear bodies,construct the topological architectures of PPI modules and module variants in the nucleome,and probably map the protein compositions of biomolecular condensates.

关键词： nucleome 4C interactomics in vivo qXL-MS biomolecular modulomics CHAMPION 4D biomolecular modulomes

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FedVC: Virtual Clients for Federated Learning with Imbalanced Label Distribution 24

FedVC: Virtual Clients for Federated Learning with Imbalance...

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3rd International Conference on Algorithms, Data Mining, and Information technology, ADMIT 2024

作者： Chen, Zhouguo Chen, Hongda Liu, Shuai Liu, Yongdong Schoolof Computer Science and Engineering Southeast University Jiangsu Nanjing China The 30th Research Institute of China Electronics Technology Group Corporation Sichuan Chengdu China School of Software Engineering Xian Jiaotong University Shaanxi Xian China China Industrial Control Systems Cyber Emergency Response Team Beijing China

ISBN: (纸本)9798400718120

Federated Learning (FL) has gained considerable attention for collaborative training in big data analysis, particularly in terms of privacy and communication constraints. Despite its promising advantages, FL faces the challenge of dealing with imbalanced label distribution on edge devices, which complicates the learning task. In literature, numerous studies have attempted to tackle this issue by introducing additional hyperparameters, which can complicate and prolong the process of model training and tuning. This complexity may potentially lead to overfitting and limited performance on new datasets. In this paper, we present a new Federated Learning framework called FedVC, which introduces virtual clients to minimize hyperparameter reliance. FedVC aims to bridge the gap between balanced and imbalanced label distribution. Compared with traditional federated learning frameworks, the proposed FedVC model designs a dynamically balanced dataset by utilizing virtual clients, which is proposed for the first time in this work. These virtual clients determine which part of the data should be used in one single training round and manage backpropagation timing for local real clients. The balanced dataset promotes greater stability in local models, thereby enhancing the overall stability of the training process. The experimental results show that FedVC outperforms classical FedAvg and the compared baseline methods for the data with imbalanced label distribution. Especially, FedVC exhibits more stable and accurate results than alternative approaches in highly heterogeneous settings. The source code is available at https://***/aikedaerC/FedVC. © 2024 Copyright held by the owner/author(s).

关键词： Federated learning

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Visual object detection using audio data 5

Visual object detection using audio data

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5th International Conference on Computing and Data science, CONF-CDS 2023

作者： Chaturvedi, Rajnish Kumar Sahu, Dinesh Prasad Tyagi, Manoj Kumar Diwakar, Manoj Singh, Prabhishek Shankar, Achyut Sathishkumar, V.E. Schoolof Computer Science Engineering and Technology Bennett University Greater Noida India Galgotias University India CSE Dept. Graphic Era Deemed to Be University Dehradun India University of Warwick United Kingdom Department of Software Engineering Jeonbuk National University Jeonju-si Jeollabuk-do Korea Republic of

Nowadays Internet of Things (IoT) and Machine Learning (ML) are growing fields. One application of these two fields is object detection, which detects semantic objects using digital images and videos of classes like humans, vehicles, buildings, etc. Visual object detection systems are very effective and accurate due to the appearance information obtained from the cameras. But they face the problem of a limited Field of View. This paper aims to tackle this issue by using audio data to localize the object. A microphone is used to estimate the angular position of the object emitting the sound. Objects currently in the Field of View of a camera are detected and tracked using optical flow, but when they go out of the Field of View, the sound emitted by the object is used by the microphone to calculate the object's angular position. Once the angle is calculated, the camera is rotated in that direction. This thus ensures that the object can be located even if it goes out of frame. Once the object is located through IoT devices, we use ML to identify the person's face. © Published under licence by IOP Publishing Ltd.

关键词： Object detection

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Two-Beam Ultrafast Laser Scribing of Graphene Patterns with 90-nm Subdiffraction Feature Size

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Ultrafast science 2023年第1期3卷 1-9页

作者： Xi Chen Min Gu Institute of Photonic Chips University of Shanghaifor Science and Technology Shanghai 200093China Centre for Artificial-lntelligence Nanophotonics Schoolof Optical-Electrical and Computer Engineering University of Shanghai for Science and TechnologyShanghai 200093China

The fabrication of high-resolution laser-scribed graphene devices is crucial to achieving large surface areas and thus performance ***,since the investigation mainly focuses on the laser-induced reduction of graphene oxide,the single-beam scribing provides a tremendous challenge to realizing subdiffraction features of graphene ***,we present an innovative 2-beam laser scribing pathway for the fabrication of subdiffraction graphene ***,an oxidation reaction of highly reduced graphene oxide can be controllably driven by irradiation of a 532-nm femtosecond laser *** on the oxidation mechanism,a 2-beam laser scribing was performed on graphene oxide thin films,in which a doughnut-shaped 375-nm beam reduces graphene oxide and a spherical 532-nm ultrafast beam induces the oxidation of laser-reduced graphene *** spherical beam turns the highly reduced graphene oxide(reduced by the doughnut-shaped beam)to an oxidized state,splitting the laser-scribed graphene oxide line into 2 subdiffraction featured segments and thus forming a laserscribed graphene/oxidized laser-scribed graphene/laser-scribed graphene *** the adjustment of the oxidation beam power,the minimum linewidth of laser-scribed graphene was measured to be 90 ***,we fabricated patterned supercapacitor electrodes containing parallel laser-scribed graphene lines with subdiffraction widths and *** outstanding gravimetric capacitance of 308 F/g,which is substantially higher than those of reported graphene-based supercapacitors,has been *** results offer a broadly accessible strategy for the fabrication of high-performance graphene-based devices including high-capacity energy storage,high-resolution holograms,high-sensitivity sensors,triboelectric nanogenerators with high power densities,and artificial intelligence devices with high neuron densities.

关键词： diffraction oxidized shaped

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Colour based Object Classification using KNN Algorithm for Industrial Applications 1

Colour based Object Classification using KNN Algorithm for I...

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1st IEEE International Conference on Automation, Computing and Renewable Systems, ICACRS 2022

作者： Santosh Kumar, N.C. Uma Maheswari, S. Vigneshwari, M. Pramila, P.V. Khilar, Rashmita Kumar, Ashok Department of Computer Science Engineering Kakatiya Institute of Technology and Science Telangana Warangal India Department of Electronics and Communication Engineering Panimalar Engineering College India Department of Information Technology Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College Tamil Nadu Chennai India Department of Computer Science and Engineering Saveetha Schoolof Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India Department of Information Technology Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai India Department of Computer Science Banasthali Vidyapith Rajasthan India

ISBN: (纸本)9781665460842

Object classification and detection involve numerous applications like image processing, picture retrieval, security and surveillance, video communication, robot vision and observation. They are often classified based on their properties like colour, shape, quality and texture. However, their accuracy is mostly predicted by colour recognition. Colour based detection of objects has a discriminating quality to detect an object of any primary colour. The extraction of two or three-dimensional objects based on colour plays a vital role in real-time image processing technology. This review paper proposes the method for colour-based object classification applied in the lays industry using the 'K-nearest neighbour algorithm' which is the simplest form of machine learning classification method. The ML model is designed in such a way that once the colour of the lays pack is detected it also specifies its particular flavour. Hence for efficient machine-based colour identification in industries, this method would be an appropriate one and can be used for many other applications. © 2022 IEEE

关键词： Classification (of information)

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High-performance γ-MnO_(2) Dual-Core,Pair-Hole Fiber for Ultrafast Photonics

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Ultrafast science 2023年第1期3卷 19-25页

作者： Xiaohui Li Xiangzhen Huang Yueheng Han Enci Chen Penglai Guo Wenmin Zhang Mingqi An Zhiwen Pan Qian Xu Xiaoxiao Guo Xiwei Huang Yishan Wang Wei Zhao School of Physics and Information Technology Shaanxi Normal UniversityXian 710000ShaanxiChina School of Electronic Engineering Guangxi University of Science and TechnologyLiuzhou 545006GuangxiChina Schoolof Computer Science and Engineering Macao University of Science and TechnologyTaipa 999078MacaoChina State Key Laboratory of Transient Optics and Photonics Xi'an Institute of Optics and Precision MechanicsChinese Academy of SciencesXi'an 710119ShaanxiChina

Manganese dioxide(MnO2)is a widely used and well-studied 3-dimensional(3D)transition metal oxide,which has advantages in ultrafast optics due to large specific surface area,narrow bandgap,multiple pores,superior electron transfer capability,and a wide range of light ***,few studies have considered its excellent performance in ultrafast photonics.y-MnO2 photonics devices were fabricated based on a special dual-core,pair-hole fiber(DCPHF)carrier and applied in ultrafast optics fields for the first *** results show that the soliton molecule with tunable temporal separation(1.84 to 2.7 ps)and 600-MHz harmonic solitons are achieved in the *** result proves that this kind of photonics device has goodapplications in ultrafast lasers,high-performance sensors,fiber optical communications,etc.,which can help expand the prospect of combining 3D materials with novel fiber for ultrafast optics device technology.

关键词： fiber optics performance

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