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Research on lightweight pavement disease detection model based on YOLOv7

Journal of Intelligent and Fuzzy Systems 2024年第4期46卷 10573-10589页

作者： Wang, Chishe Li, Jun Wang, Jie Zhao, Weikang School of Computer Science and Engineering Anhui University of Science and Technology Huainan China Jinling Institute of Technology Nanjing China

Rapid urbanization has made road construction and maintenance imperative, but detecting road diseases has been time-consuming with limited accuracy. To overcome these challenges, we propose an efficient YOLOv7 road disease detection model. Our approach involves integrating MobilieNetV3 as the backbone feature extraction network to reduce the network's parameters and computational requirements. Additionally, we introduce the BRA attention module into the spatial pyramid pooling module to eliminate redundant information and enhance the network's feature representation capability. Moreover, we utilize the F-ReLU activation function in the backbone network, expanding the convolutional layers' receptive field range. To optimize the model's boundary loss, we employ the Wise-IoU loss function, which places more emphasis on the quality of ordinary samples and enhances the overall performance and generalization ability of the network. Experimental results demonstrate that our improved detection algorithm achieves a higher recall rate and mean average precision (mAP) on the public dataset (RDD) and the NJdata dataset in Nanjing's urban area. Specifically, compared to YOLOv7, our model increases the recall rate and mAP on RDD by 3.3% and 2.6%, respectively. On the NJdata dataset, our model improves the recall rate and mAP by 1.9% and 1.3%, respectively. Furthermore, our model reduces parameter and computational requirements by 30% and 22.5%, respectively, striking a balance between detection accuracy and speed. In conclusion, our road disease detection model presents an effective solution to address the challenges associated with road disease detection in urban areas. It offers improved accuracy, efficiency, and generalization capabilities compared to existing models. © 2024 - IOS Press. All rights reserved.

关键词： Roads and streets

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Hybrid solar-wind farm site selection for reverse osmosis desalination: A case study in sistan and baluchestan using Geographic Information System

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Energy Reports 2025年 13卷 6059-6078页

作者： Jahangir, Mohammad Hossein Razeghi, Marziyeh Naseri, Amir Yousefi, Hossein Noorollahi, Younes School of Energy Engineering and Sustainable Resources College of Interdisciplinary Science and Technology University of Tehran Tehran Iran

iran, due to its location in arid and semi-arid climates, is one of the countries experiencing the most significant water stress. Given that the Sistan and Baluchestan province among other regions of the country, faces the highest water stress among other regions, there is an increasing need for a study that proposes solutions for utilizing brackish water in this province. This article, using Arc GIS 10.8 software, systematically identifies areas with surface and subsurface brackish water for the first time, for the construction of reverse osmosis desalination plants. These areas are technically and operationally suitable and simultaneously have the potential for wind and solar energy to power the plants. The research utilizes about 10 informational layers, including economic, environmental, technical, and geological potential. The amount of desalinated water is calculated based on the area of regions prone to having surface and subsurface brackish water resources, as well as areas with wind and solar energy potential, and the electricity generated by wind and photovoltaic power plants. Wind turbines with a capacity of 550 kilowatts and photovoltaic power plants with a capacity of 1 megawatt have been used in this study. If all the technically recoverable water is utilized, can, on average, produce 6643.56 and 9330.73 million cubic meters of freshwater using wind and solar energy, respectively, and on average, 20867.83 and 3047835.06 million cubic meters of freshwater from an operational perspective. This amount will fully meet the province's freshwater needs, and the surplus can be transferred to other provinces. Technically, the cities of Saravan and Chabahar in Sistan and Baluchestan province have the highest potential for simultaneous production of electricity and desalinated water using wind and solar energy, respectively, and the city of iranshahr also has the highest potential in terms of combined use of wind and solar energy. Operationally, the city of Zahed

关键词： Desalination

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A Novel CAPTCHA Recognition System Based on Refined Visual Attention

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computers, Materials & Continua 2025年第4期83卷 115-136页

作者： Zaid Derea Beiji Zou Xiaoyan Kui Monir Abdullah Alaa Thobhani Amr Abdussalam School of Computer Science and Engineering Central South UniversityChangsha410083China College of Computer Science and Information Technology Wasit UniversityWasit52001Iraq Department of Computer Science and Artificial Intelligence College of Computing and Information TechnologyUniversity of BishaBisha67714Saudi Arabia Electronic Engineering and Information Science Department University of Science and Technology of ChinaHefei230026China

Improving website security to prevent malicious online activities is crucial,and CAPTCHA(Completely Automated Public Turing test to tell computers and Humans Apart)has emerged as a key strategy for distinguishing human users from automated ***-based CAPTCHAs,designed to be easily decipherable by humans yet challenging for machines,are a common form of this ***,advancements in deep learning have facilitated the creation of models adept at recognizing these text-based CAPTCHAs with surprising *** our comprehensive investigation into CAPTCHA recognition,we have tailored the renowned UpDown image captioning model specifically for this *** approach innovatively combines an encoder to extract both global and local features,significantly boosting the model’s capability to identify complex details within CAPTCHA *** the decoding phase,we have adopted a refined attention mechanism,integrating enhanced visual attention with dual layers of Long Short-Term Memory(LSTM)networks to elevate CAPTCHA recognition *** rigorous testing across four varied datasets,including those from Weibo,BoC,Gregwar,and Captcha 0.3,demonstrates the versatility and effectiveness of our *** results not only highlight the efficiency of our approach but also offer profound insights into its applicability across different CAPTCHA types,contributing to a deeper understanding of CAPTCHA recognition technology.

关键词： Text-based CAPTCHA recognition refined visual attention web security computer vision

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Jamming-Resilient Consensus for Wireless Blockchain Networks

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Tsinghua science and technology 2025年第1期30卷 262-278页

作者： Yifei Zou Meng Hou Li Yang Minghui Xu Libing Wu Dongxiao Yu Xiuzhen Cheng School of Computer Science and Technology Shandong UniversityQingdao 266237China School of Cyber Science and Engineering Wuhan UniversityWuhan 430072China

As the device complexity keeps increasing,the blockchain networks have been celebrated as the cornerstone of numerous prominent platforms owing to their ability to provide distributed and immutable ledgers and data-driven autonomous *** distributed consensus algorithm is the core component that directly dictates the performance and properties of blockchain ***,the inherent characteristics of the shared wireless medium,such as fading,interference,and openness,pose significant challenges to achieving consensus within these networks,especially in the presence of malicious jamming *** cope with the severe consensus problem,in this paper,we present a distributed jamming-resilient consensus algorithm for blockchain networks in wireless environments,where the adversary can jam the communication channel by injecting jamming *** on a non-binary slight jamming model,we propose a distributed four-stage algorithm to achieve consensus in the wireless blockchain network,including leader election,leader broadcast,leader aggregation,and leader announcement *** high probability,we prove that our jamming-resilient algorithm can ensure the validity,agreement,termination,and total order properties of consensus with the time complexity of O(n).Both theoretical analyses and empirical simulations are conducted to verify the consistency and efficiency of our algorithm.

关键词： consensus in blockchain jamming attacks distributed algorithm

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A Review on Smart Healthcare employing Quantum Internet of Things

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IEEE engineering Management Review 2024年 1-9页

作者： Sutradhar, Kartick Venkatesh, Ranjitha Venkatesh, Priyanka Department of Computer Science and Engineering Indian Institute of Information Technology Sri City India Department of Computer Science and Engineering GITAM School of Technology Bengaluru India Department of Computer Science and Engineering Presidency University Bengaluru India

The Quantum Internet of Things (QIoT) in the healthcare industry holds the promise of transforming patient care, diagnostics, and medical research. Quantum-enhanced sensors, communication, and computation offer unprecedented capabilities that can revolutionize how healthcare services are delivered and experienced. This paper explores the potential of QIoT in the context of smart healthcare, where interconnected quantum-enabled devices and systems create an ecosystem that enhances data security, enables real-time monitoring, and advances medical knowledge. We delve into the applications of quantum sensors in precise health monitoring, the role of quantum communication in secure telemedicine, and the computational power of quantum computing in drug discovery and personalized medicine. We discuss challenges such as technical feasibility, scalability, and regulatory considerations, along with the emerging trends and opportunities in this transformative field. By examining the intersection of quantum technologies and smart healthcare, this paper aims to shed light on the novel approaches and breakthroughs that could redefine the future of healthcare delivery and patient outcomes. IEEE

关键词： Internet of things

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Character recognition competition for street view shop signs

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National science Review 2023年第6期10卷 27-31页

作者： Jingqun Tang Weidong Du Bin Wang Wenyang Zhou Shuqi Mei Tao Xue Xing Xu Hai Zhang Shanghai Byte Dance Technology Co. Ltd School of Control Science and Engineering Zhejiang University School of Computer Science and Technology University of Science and Technology of China School of Computer Science and Technology Tsinghua Univeristy Shenzhen Tencent Technology Co. Ltd School of Computer Science and Engineering University of Electronic Science and Technology of China Pazhou Laboratory (Huangpu) School of Mathematics Northwest University

INTRODUCTION Store signboards provide important information in street view images,andcharacter recognition in natural scenes is an important research direction in computer *** view store signboard character recognitio...

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Optimal Day-ahead Dynamic Pricing of Grid-connected Residential Renewable Energy Resources Under Different Metering Mechanisms

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Journal of Modern Power Systems and Clean Energy 2023年第1期11卷 168-178页

作者： Kimia Parandeh Abed Bagheri Shahram Jadid Center of Excellence for Power System Automation and Operation School of Electrical EngineeringIran University of Science and Technology(IUST)TehranIran

Nowadays,grid-connected renewable energy resources have widespread applications in the electricity ***,providing household consumers with photovoltaic(PV)systems requires bilateral interfaces to exchange energy and *** addition,residential consumers’contribution requires guaranteed privacy and secured data *** dynamic pricing is one of the incentive-based demand response methods that has substantial effects on the integration of renewable energy resources with smart grids and social *** metering mechanisms of renewable energy resources such as feed-in tariffs,net metering,and net purchase and sale are important issues in power grid operation *** this paper,optimal condition decomposition method is used for dayahead dynamic pricing of grid-connected residential renewable energy resources under different metering mechanisms:feed-intariffs,net metering,and net purchase and sale in conjunction with carbon emission *** to the stochastic nature of consumers’load and PV system products,uncertainties are considered in a two-stage decision-making *** results demonstrate that the net metering with the satisfaction average of 68%for consumers and 32%for the investigated electric company leads to 28%total load *** the case of net purchase and sale mechanism,a satisfaction average of 15%for consumers and 85%for the electric company results in 11%total load *** feed-in-tariff mechanism,in spite of increased social welfare,load reduction does not take place.

关键词： Dynamic pricing renewable energy resources feed-in-tariffs net metering net purchase and sale stochastic decision-making

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An Approach for Privacy-Aware Mobile App Package Recommendation

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6240-6252页

作者： Liu, Shanpeng Cao, Buqing Liu, Jianxun Kang, Guosheng Shi, Min Li, Xiong Fletcher, Kenneth K. Hunan University of Science and Technology School of Computer Science and Engineering Xiangtan411201 China Hunan University of Technology School of Computer Zhuzhou412007 China Harvard University Harvard Medical School BostonMA02138 United States School of Computer Science and Engineering Chengdu611731 China University of Massachusetts School of Computer Science BostonMA02125 United States

With the prosperity of the mobile Internet, the abundance of data makes it difficult for users to choose their favorite app. Thus, mobile app recommendation as an emerging topic attracts lots of attention. However, existing methods for app recommendation rarely consider recommendation accuracy under the privacy representation of user preferences. To address this problem, we propose a privacy-aware app package recommendation method named APP-Rec. Specifically, in this method: 1) treat an app and its associated heterogeneous entities (APP-Rec considers not only the apps themselves but also a variety of related factors-collectively referred to as heterogeneous entities, such as app category and app neighbors) as an app package and extract comprehensive features from the app package using an intrapackage attention network and an interpackage attention network to improve app recommendation;and 2) design a privacy module utilizing Laplace noise to achieve privacy preservation of user preferences. Experimental results show that APP-Rec outperforms the state-of-the-art methods in terms of area under the curve (AUC). Moreover, the privacy preservation of user preferences in APP-Rec is proved by theoretical analysis and experimental results. © 2024 IEEE.

关键词： Differential privacy

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Modifying Lyapunov exponent of chaotic map by self-cascading

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science China(Technological sciences) 2024年第7期67卷 2203-2214页

作者： YI ChenLong LI ChunBiao LI YongXin XIA Ming HUA ZhongYun School of Electronic and Information Engineering Nanjing University of Information Science&TechnologyNanjing 210044China School of Artificial Intelligence Nanjing University of Information Science&TechnologyNanjing 210044China School of Computer Science and Technology Harbin Institute of Technology Shenzhen Graduate SchoolShenzhen 518055China

The self-cascade(SC) method is an effective technique for chaos enhancement and complexity increasing in chaos ***, the controllable self-cascade(CSC) method allows for more accurate control of Lyapunov exponents of the discrete map. In this work, the SC and CSC systems of the original map are derived, which enhance the chaotic performance while preserving the fundamental dynamical characteristics of the original map. Higher Lyapunov exponent of chaotic sequences corresponding to higher frequency are obtained in SC and CSC systems. Meanwhile, the Lyapunov exponent could be linearly controlled with greater flexibility in the CSC system. The verification of the numerical simulation and theoretical analysis is carried out based on the platform of CH32.

关键词： self-cascade controllable self-cascade chaos enhancement chaos control

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Composite spectral spatial pixel CNN for land-use hyperspectral image classification with hybrid activation function

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Multimedia Tools and Applications 2025年第12期84卷 10527-10550页

作者： Banerjee, Anasua Swain, Satyajit Rout, Minakhi Bandyopadhyay, Mainak School of Computer Engineering Kalinga Institute of Industrial Technology-Deemed-to-be-University Bhubaneswar India Department of Computer Science and Engineering National Institute of Technology Silchar India

Deep learning methods have played a prominent role in the development of computer visualization in recent years. Hyperspectral imaging (HSI) is a popular analytical technique based on spectroscopy and visible imaging which examines the pattern of light in a target and recognizes objects based on varying spectral properties. However, in remote sensing, detecting surface material via HSI analysis is a critical and difficult task. The performance of spectral-spatial data exploitation is well established to outperform typical spectral pixel-wise techniques. Because of its great feature extraction ability, convolutional neural networks (CNN) have emerged as a potent deep learning approach. CNN translates the input features of an image into an equivalent CNN feature map, in addition to naturally combining spectral and spatial information. However, spectral-spatial properties when combined with pixel-wise extraction can learn more minute details of objects present on the earth’s terrain. In this paper, a noble Composite Spectral Spatial Pixel CNN model for the classification of hyperspectral data is presented which is an amalgamation of 3D-2D-1D CNN. While the 3D and 2D CNN exploit the spectral-spatial features effectively, 1D CNN works on pixel-wise feature extraction. Further, to optimize the classification performance of the proposed model, a new hybrid activation function Flatten-T Swish is also used which is the combination of ReLU and Swish function. The proposed model is compared with other state-of-the-art models based on three popular HSI datasets, and it is found that the proposed model performs better among others in terms of classification and computation time, giving 98.87% accuracy for Indian Pines, 99.92% accuracy for Pavia university, and 99.99% accuracy for Salinas Valley dataset. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Extraction

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