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From Laboratory to Field:Unsupervised Domain Adaptation for Plant Disease Recognition in the Wild

Plant Phenomics 2023年第2期5卷 195-208页

作者： Xinlu Wu Xijian Fan Peng Luo Sruti Das Choudhury Tardi Tjahjadi Chunhua Hu College of Information Science and Technology Nanjing Forestry UniversityNanjing 210037China Institute of Forest Resource Information Techniques Chinese Academy of ForestryBeijing 100091China Key Laboratory of Forestry Remote Sensing and Information System National Forestry and Grassland AdministrationBeijing 100091China Department of Computer Science and Engineering University of Nebraska-LincolnLincolnNE 68588USA School of Engineering University of WarwickCoventry CV47ALUK

Plant disease recognition is of vital importance to monitor plant development and predicting crop ***,due to data degradation caused by different conditions of image acquisition,e.g.,laboratory *** environment,machine learning-based recognition models generated within a specific dataset(source domain)tend to lose their validity when generalized to a novel dataset(target domain).To this end,domain adaptation methods can be leveraged for the recognition by learning invariant representations across *** this paper,we aim at addressing the issues of domain shift existing in plant disease recognition and propose a novel unsupervised domain adaptation method via uncertainty regularization,namely,Multi-Representation Subdomain Adaptation Network with Uncertainty Regularization for Cross-Species Plant Disease Classification(MSUN).Our simple but effective MSUN makes a breakthrough in plant disease recognition in the wild by using a large amount of unlabeled data and via nonadversarial ***,MSUN comprises multirepresentation,subdomain adaptation modules and auxiliary uncertainty *** multirepresentation module enables MSUN to learn the overall structure of features and also focus on capturing more details by using the multiple representations of the source *** effectively alleviates the problem of large interdomain *** adaptation is used to capture discriminative properties by addressing the issue of higher interclass similarity and lower intraclass ***,the auxiliary uncertainty regularization effectively suppresses the uncertainty problem due to domain *** was experimentally validated to achieve optimal results on the PlantDoc,Plant-Pathology,Corn-Leaf-Diseases,and Tomato-Leaf-Diseases datasets,with accuracies of 56.06%,72.31%,96.78%,and 50.58%,respectively,surpassing other state-of-the-art domain adaptation techniques considerably.

关键词： Plant breakthrough details

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A Novel BIBO Automated Ticketing system Based on Blockchain Mobile Sensors for Public Transport Modes

A Novel BIBO Automated Ticketing System Based on Blockchain ...

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IEEE Conference on Vehicular Technology (VTC)

作者： Tor-Morten Grønli Abdullah Lakhan Sajida Memon School of Economics Innovations and Technology Kristiania University College Oslo Norway Department of Computer System engineering Dawood University of Engineering and Technology Pakistan

ISBN: (数字)9798350387414

ISBN: (纸本)9798350387421

This paper proposes a novel Be-in and Be-Out (BIBO) automated ticketing system based on blockchain mobile sensors for public transport modes (e.g., metro, tram, train, and bus). The existing Bluetooth and GPS-integrated BIBO suffering from fraud may involve users deliberately turning off their Bluetooth connection during a trip to deceive the system into charging a reduced fare. Even if Bluetooth is turned off or there is a loss of mobile ticketing connection, the system can still gather sufficient location data to compute fares. However, this becomes impossible if a user's phone is powered off. This paper tackled these issues and suggested a blockchain-enabled BIBO mobile sensors-enabled automated system based on socket programming for public transport. We aim to generate BIBO automated ticketing based on mobile sensors without Bluetooth and GPS while boarding public transport. This paper presents the blockchain mobile ticketing system (BMTS-BIBO) algorithm, which consists of different steps to solve the problem. We trained the ticketing model based on a deep convolutional neural network (DCNN) and integrated it with socket programming based on the application. Simulation results show that the BMTS-BIBO algorithm outperformed and obtained 98% BIBO ticketing without GPS and Bluetooth.

关键词： Bluetooth Sockets Simulation Programming Sensor systems Sensors Blockchains

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Discovering Cohesive Temporal Subgraphs with Temporal Density Aware Exploration

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Journal of computer Science & Technology 2022年第5期37卷 1068-1085页

作者： Chun-Xue Zhu Long-Long Lin Ping-Peng Yuan Hai Jin National Engineering Research Center for Big Data Technology and System Huazhong University of Science and TechnologyWuhan 430074China Service Computing Technology and System Laboratory Huazhong University of Science and TechnologyWuhan 430074China Cluster and Grid Computing Laboratory Huazhong University of Science and TechnologyWuhan 430074China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China

Real-world networks,such as social networks,cryptocurrency networks,and e-commerce networks,always have occurrence time of interactions between *** networks are typically modeled as temporal *** cohesive subgraphs from temporal graphs is practical and essential in numerous data mining applications,since mining cohesive subgraphs gets insights into the time-varying nature of temporal ***,existing studies on mining cohesive subgraphs,such as Densest-Exact and k-truss,are mainly tailored for static graphs(whose edges have no temporal information).Therefore,those cohesive subgraph models cannot indicate both the temporal and the structural characteristics of *** this end,we explore the model of cohesive temporal subgraphs by incorporating both the evolving and the structural characteristics of temporal ***,the volume of time intervals in a temporal network is *** a result,the time complexity of mining temporal cohesive subgraphs is *** efficiently address the problem,we first mine the temporal density distribution of temporal *** by the distribution,we can safely prune many unqualified time intervals with the linear time ***,the remaining time intervals where cohesive temporal subgraphs fall in are examined using the greedy *** results of the experiments on nine real-world temporal graphs indicate that our model outperforms state-of-the-art solutions in efficiency and ***,our model only takes less than two minutes on a million-vertex DBLP and has the highest overall average ranking in EDB and TC metrics.

关键词： temporal network temporal feature distribution cohesive subgraph convex property

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APNet: Adaptive Patch-based Network for Microaneurysm Detection in Fundus Images

APNet: Adaptive Patch-based Network for Microaneurysm Detect...

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： Xinpeng Zhang Congcong Wang Yilin Han Shengyong Chen Engineering Research Center of Learning-Based Intelligent System Ministry of Education School of Computer Science and Engineering of Tianjin University of Technology Tianjin China

ISBN: (数字)9798350394085

ISBN: (纸本)9798350394092

Microaneurysms (MAs) in fundus images are a crucial indicator for the early detection of diabetes and the treatment of diabetic retinopathy. In this paper, we propose an efficient method for microaneurysms detection. We propose an Att-UCtransnet network to extract the MA candidate region, where only positive samples which contain at least one microaneurysm are chosen. Inspired by the concept of the effective receptive field (ERF), we design an algorithm to adaptively select the appropriate patch size, preserving crucial information around the microaneurysm while minimizing interference from irrelevant environments. Besides, we introduce a classification network for accurate mass detection in whole fundus images. Extensive experiments conducted on four publicly available datasets demonstrate that our method outperforms the state-of-the-art approaches in MA detection.

关键词： Training Industrial electronics Diabetic retinopathy Adaptive systems Accuracy Interference Manuals

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Efficient Modeling Attack on Multiplexer PUFs via Kronecker Matrix Multiplication

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IEEE Transactions on computer-Aided Design of Integrated Circuits and systems 2025年

作者： Wang, Hongfei Wan, Caixue Jin, Hai Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Wuhan430074 China Huazhong University of Science and Technology National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Wuhan430074 China

The Physical Unclonable Function (PUF) is valued for its lightweight nature and unique functionality, making it a common choice for securing hardware products requiring authentication and key generation mechanisms. In response to the susceptibility of individual PUFs to modeling attacks, advanced PUF variants have been developed to improve security measures. One notable type in this regard is the multiplexer-based composition of arbiter PUFs, known as MPUF, which aims to meet high reliability and security standards simultaneously. Current research on attacking MPUF encounters challenges such as substantial demands for training CRPs and low success rates. In this work, we propose a novel numerical modeling attack strategy for MPUFs. Using Kronecker products from mathematical perspective, this method precisely describe the MPUF model without using complex network architectures, boosting attack accuracy and overall efficiency. Experiment comparison with state-of-the-art works demonstrates that our method achieves better performance in terms of attack accuracy, robustness, and efficiency. Our method is able to successfully attack a (512, 8)-MPUF in 32.71 minutes with 97.14% accuracy, outperforming all existing attack methods on MPUFs. More, we validate our method through experiments with hardware implementations on FPGAs. The advantages of our method also include the adaptability to be employed to attack other MPUF variations like cMPUF and rMPUF, and the capability to be integrated with an existing attack method for launching efficient attack on MPUFs leveraging reliability information. © 2025 IEEE.

关键词： modeling attack multiplexer-based PUF Physical unclonable function

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X-Stream: A Flexible, Adaptive Video Transformer for Privacy-Preserving Video Stream Analytics

X-Stream: A Flexible, Adaptive Video Transformer for Privacy...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Dou Feng Lin Wang Shutong Chen Lingching Tung Fangming Liu National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Huazhong University of Science and Technology China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Paderborn University Germany National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Guangxi University China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Cluster and Grid Computing Lab School of Computer Science and Technology Peng Cheng Laboratory China

ISBN: (数字)9798350383508

ISBN: (纸本)9798350383515

Video stream analytics (VSA) systems fuel many exciting applications that facilitate people’s lives, but also raise critical concerns about exposing too much individuals’ privacy. To alleviate these concerns, various frameworks have been presented to enhance the privacy of VSA systems. Yet, existing solutions suffer two limitations: (1) being scenario-customized, thus limiting the generality of adapting to multifarious scenarios, (2) requiring complex, imperative programming, and tedious process, thus largely reducing the usability of such systems. In this paper, we present X-Stream, a privacy-preserving video transformer that achieves flexibility and efficiency for a large variety of VSA tasks. X-Stream features three major novel designs: (1) a declarative query interface that provides a simple yet expressive interface for users to describe both their privacy protection and content exposure requirements, (2) an adaptation mechanism that dynamically selects the most suitable privacy-preserving techniques and their parameters based on the current video context, and (3) an efficient execution engine that incorporates optimizations for multi-task deduplication and inter-frame inference. We implement X-Stream and evaluate it with representative VSA tasks and public video datasets. The results show that X-Stream achieves significantly improved privacy protection quality and performance over the state-of-the-art, while being simple to use.

关键词： Privacy Transforms Streaming media Transformers Multitasking Real-time systems Task analysis

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Integrated Comb-Driven Silicon Photonics

Integrated Comb-Driven Silicon Photonics

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2023 Optical Fiber Communications Conference and Exhibition, OFC 2023

作者： Wang, Xingjun Shen, Bitao Shu, Haowen Chang, Lin Tao, Yuansheng Xie, Weiqiang Bowers, John E. Peking University School of Electronics State Key Laboratory of Advanced Optical Communications System and Networks Beijing100871 China University of California Department of Electrical and Computer Engineering Santa BarbaraCA93106 United States

We realize the combination of integrated microcomb and silicon photonics, employing the advanced AlGaAsOI optical nonlinear platform and novel SiPh chips. Data link with 2-Tbps aggregate rate and highly reconfigurable... 详细信息

ISBN: (纸本)9781957171180

关键词： Silicon photonics

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Offensive Chinese Text Detection Based on Multi-Feature Fusion 4

Offensive Chinese Text Detection Based on Multi-Feature Fusi...

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4th International Symposium on computer engineering and Intelligent Communications, ISCEIC 2023

作者： Li, Na Li, Shaomei Hong, Jiahao Zhengzhou University Academy of Cyberspace Security Zhengzhou China Strategic Support Force Information Engineering University National Engineering Research Center for Digital Program-Controlled Switching System Zhengzhou China Zhengzhou University School of Computer and Artificial Intelligence Zhengzhou China

ISBN: (纸本)9798350306323

To purify the online environment, it is essential to identify objectionable content, including offensive texts. However, some offensive texts are expressed in a more subtle manner, making it difficult to detect their literal characteristics. To enhance the effectiveness of detecting offensive Chinese text, we propose a multi-feature fusion-based method. First, we combine the word vectors obtained from Wobert with the character vectors obtained from ALBERT. The attention mechanism assigns greater importance to key features within the word vectors. Next, we merge the fusion vector with the sentence vector generated by ALBERT, which encompasses contextual semantics and syntactic information. This results in a new fusion vector that captures information at the character, word, and sentence levels. Finally, we employ a fully connected layer to process the three-level fusion vector and obtain the detection outcome. Experimental results demonstrate that this approach provides a comprehensive characterization of offensive text by fusing information from multiple levels. It substantially enhances the detection performance for offensive Chinese text. © 2023 IEEE.

关键词： Vectors

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A robust multi-objective optimization algorithm for accurate parameter estimation for solar cell models

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Soft Computing 2024年第19期28卷 11265-11277页

作者： Singla, Manish Kumar Gupta, Jyoti Alsharif, Mohammed H. Kim, Mun-Kyeom Aljaidi, Mohammad Safaraliev, Murodbek Department of Interdisciplinary Courses in Engineering Chitkara University Institute of Engineering & ampTechnology Chitkara University Punjab India Applied Science Research Center Applied Science Private University Amman11931 Jordan School of Engineering and Technology K. R. Mangalam University Gurgaon Haryana122003 India Department of Electrical Engineering College of Electronics and Information Engineering Sejong University 209 Neungdong-Ro Gwangjin-Gu Seoul05006 Korea Republic of School of Energy System Engineering Chung-Ang University 84 Heukseok-Ro Dongjak-Gu Seoul06974 Korea Republic of Department of Computer Science Zarqa University Zarqa13110 Jordan Department of Automated Electrical Systems Ural Federal University Yekaterinburg620002 Russia

The accuracy of solar cell models is crucial for enhancing the performance of solar photovoltaic (PV) systems. However, existing solar cell models lack precise parameters, and the manufacturer's datasheet does not provide the required information for reliable modeling. Consequently, accurate parameter estimation becomes necessary. This paper presents a simple multi-objective optimization algorithm (Hybrid Particle Swarm Optimization and Rat Search Algorithm (PSORSA)) designed to estimate cell parameters based on this observation. Unlike other optimization algorithms addressing this issue, the proposed algorithm aims to overcome challenges related to local minima and premature convergence, which often lead to suboptimal results. The paper focuses on assessing the reliability of the proposed algorithm by comparing its performance with other well-known optimization algorithms. The proposed optimizing algorithm is tested on the CEC 2019 benchmark function. Experimental results (RMSE), including statistical analysis, validate the algorithm's effectiveness by comparing them with other algorithms. At the end, non-parametric test is performed to justify the outcomes, vouching for the better performance of the proposed algorithm. The findings demonstrate that the proposed algorithms are particularly well-suited for estimating solar PV models. With its simple structure and high accuracy, the proposed algorithm exhibits great potential for various applications in the field of solar energy. Moreover, its computational efficiency and ease of implementation further contribute to its practicality. © The Author(s) 2024.

关键词： Solar cells

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Leveraging Predictive Maintenance for Photovoltaic systems 9th

Leveraging Predictive Maintenance for Photovoltaic Systems

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9th International Conference on Smart City Applications, SCA 2024

作者： Ledmaoui, Younes Raif, Mourad El Aroussi, Mohamed Saadane, Rachid Jakimi, Abdeslam Chehri, Abdellah Laboratory Engineering System Hassania School of Public Works Casablanca Morocco Software Engineering and Information Systems Engineering Team FST of Errachidia Moulay Ismail University Meknes Morocco Department of Mathematics and Computer Science Royal Military College of Canada KingstonONK7K 7B4 Canada

ISBN: (纸本)9783031886522

This paper introduces a novel edge device architecture designed to optimize solar energy management systems. It integrates cutting-edge functionalities such as generation prediction, maintenance alerts, and anomaly detection into a unified framework. Through the utilization of edge computing, the system enables real-time analysis and decision-making at the network’s edge. Leveraging machine learning algorithms and predictive models, these edge devices provide highly accurate energy generation forecasts, facilitating efficient energy utilization and strategic planning. Additionally, the architecture incorporates anomaly detection techniques to proactively identify deviations from normal operation, minimizing downtime and enabling timely maintenance interventions. The seamless integration of these features within the edge devices significantly enhances the overall efficiency, reliability, and performance of energy monitoring systems. By adopting this advanced edge device architecture, energy stakeholders can reap benefits such as improved energy management, reduced operational costs, and enhanced system reliability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Battery management systems

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