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Chaotic Map-Based Authentication and Key Agreement Protocol with Low-Latency for Metasystem

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Computers, Materials & Continua 2024年第3期78卷 4471-4488页

作者： Guojun Wang Qi Liu School of Electronics&Information Engineering Nanjing University of Information Science&TechnologyNanjing210044China yancheng polytechnic college Yancheng224000China Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services School of SoftwareNanjing University of Information Science and TechnologyNanjingChina

With the rapid advancement in exploring perceptual interactions and digital twins,metaverse technology has emerged to transcend the constraints of space-time and reality,facilitating remote AI-based *** this dynamic metasystem environment,frequent information exchanges necessitate robust security measures,with Authentication and Key Agreement(AKA)serving as the primary line of defense to ensure communication ***,traditional AKA protocols fall short in meeting the low-latency requirements essential for synchronous interactions within the *** address this challenge and enable nearly latency-free interactions,a novel low-latency AKA protocol based on chaotic maps is *** protocol not only ensures mutual authentication of entities within the metasystem but also generates secure session *** security of these session keys is rigorously validated through formal proofs,formal verification,and informal *** confronted with the Dolev-Yao(DY)threat model,the session keys are formally demonstrated to be secure under the Real-or-Random(ROR)*** proposed protocol is further validated through simulations conducted using VMware workstation compiled in HLPSL language and C *** simulation results affirm the protocol’s effectiveness in resisting well-known attacks while achieving the desired low latency for optimal metaverse interactions.

关键词： Metasystem authentication and key agreement chaotic map secure communication

Manipulating Nb-doped SrFeO_(3−δ)with excellent performance for proton-conducting solid oxide fuel cells

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Journal of Advanced Ceramics 2024年第5期13卷 579-589页

作者： Hailu Dai Hongzhe Du Samir Boulfrad Shoufu Yu Lei Bi Qinfang Zhang School of Materials Science and Engineering Yancheng Institute of TechnologyYancheng 224051China college of Science&Engineering Hamad Bin Khalifa UniversityDoha 34110Qatar School of Resource Environment and Safety Engineering University of South ChinaHengyang 421001China

Nb-doped SrFeO_(3−δ)(SFO)is used as a cathode in proton-conducting solid oxide fuel cells(H-SOFCs).First-principles calculations show that the SrFe0.9Nb0.1O_(3−δ)(SFNO)cathode has a lower energy barrier in the cathode reaction for H-SOFCs than the Nb-free SrFeO_(3−δ)*** experimental studies show that Nb doping substantially enhances the performance of the SrFeO_(3−δ)***,oxygen vacancies(VO)were introduced into SFNO using the microwave sintering method,further improving the performance of the SFNO *** mechanism behind the performance improvement owing to VO was revealed using first-principles calculations,with further optimization of the SFNO cathode achieved by developing a suitable wet chemical synthesis route to prepare nanosized SFNO *** method significantly reduces the grain size of SFNO compared with the conventional solid-state reaction method,although the solid-state reaction method is generally used for preparing Nb-containing *** a result of defect engineering and synthesis approaches,the SFNO cathode achieved an attractive fuel cell performance,attaining an output of 1764 mW·cm−2 at 700℃ and operating for more than 200 *** manipulation of Nb-doped SrFeO_(3−δ)can be seen as a“one stone,two birds”strategy,enhancing cathode performance while retaining good stability,thus providing an interesting approach for constructing high-performance cathodes for H-SOFCs.

关键词： SrFeO_(3−δ)-(SFO) cathode proton conductor solid oxide fuel cells(SOFCs)

Nanostructured ZnO/ZnS with Type-II Hetero-junction for Efficient CO_(2) Photoreduction

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Chemical Research in Chinese Universities 2024年第3期40卷 484-489页

作者： XIAO Qi LIU Ting ZHOU Qianhe LI Liangyu CHANG Chuntao GAO Dawei LI Danyang YOU Feifei School of Textile Garment and Design Changshu Institute of TechnologyChangshu 215500P.R.China School of Civil and Environmental Engineering The University of New South WalesAustralia college of Textile and Clothing Yancheng Institute of Technology.Yancheng 224051P.R.China Jiangsu Yueda Cotton Spinning Co. Ltd.Yancheng 224051P.R.China

Photocatalytic CO_(2) reduction driven by solar light is a green approach that can decrease the greenhouse effect induced by high CO_(2) concentration in the atmosphere and generate carbon-based chemicals/fuels as *** this paper,non-metal co-catalysts ZnO/ZnS type-II hetero-junction nanoparticles with a rough surface were prepared through a hydrothermal *** used as a photocatalyst for CO_(2) reduction,the optimal one showed good cycle stability and a higher yield rate of 27.8µmol·g^(−1)·h^(−1) for CO_(2) conversion into *** outstanding catalytic activity originated from i)the rich interfaces between ZnO and ZnS in the nanoscale could significantly reduce the delivery path of carriers and improve the utilization efficiency of photo-excited electron/hole pairs and ii)enriched surface oxygen defects could supply much more reaction active sites for CO_(2) adsorption.

关键词： ZnO/ZnS Photocatalytic CO_(2)reduction Oxygen defect

Prediction of Wordle Scores Based on ARIMA and LSTM Models

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Journal of Applied Mathematics and Physics 2024年第2期12卷 543-553页

作者： Biyun Chen Wenqiang Li college of Information Engineering Yancheng Teachers University Yancheng China

This paper examines the effectiveness of the Differential autoregressive integrated moving average (ARIMA) model in comparison to the Long Short Term Memory (LSTM) neural network model for predicting Wordle user-reported scores. The ARIMA and LSTM models were trained using Wordle data from Twitter between 7th January 2022 and 31st December 2022. User-reported scores were predicted using evaluation metrics such as MSE, RMSE, R2, and MAE. Various regression models, including XG-Boost and Random Forest, were used to conduct comparison experiments. The MSE, RMSE, R2, and MAE values for the ARIMA(0,1,1) and LSTM models are 0.000, 0.010, 0.998, and 0.006, and 0.000, 0.024, 0.987, and 0.013, respectively. The results indicate that the ARIMA model is more suitable for predicting Wordle user scores than the LSTM model.

关键词： Time Series ARIMA LSTM Wordle Prediction

Graphitic carbon nitride nanosheets mitigate cadmium toxicity in Glycine max *** promoting cadmium retention in root and improving photosynthetic performance

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Journal of Environmental Sciences 2024年第5期139卷 543-555页

作者： Kai Xu Yunyu Guo Chenghua Xing Ronglong Fu Bin Zou Rongchuan Liu Luyi Cai Jianfang Yan Xi-Lin Wu Miaozhen Cai college of Geography and Environmental Sciences Zhejiang Normal UniversityJinhua 321004China college of Agriculture Jinhua PolytechnicJinhua 321007China

Cadmium(Cd)pollution poses a serious threat to plant growth and *** have shown great application potential for alleviation of Cd toxicity to *** this study,we applied graphitic carbon nitride nanosheets(g-C_(3)N_(4)NSs)for alleviation of Cd-toxicity to soybean(Glycine max L.).The g-C_(3)N_(4)NSs supplementation significantly improved plant growth and reduced oxidative damage in the Cd-toxicated soybean seedlings through hydroponic ***,the g-C_(3)N_(4)NSs dynamically regulated the root cell wall(RCW)components by increasing pectin content and modifying its demethylation via enhancing pectin methylesterase(PME)activity,therefore greatly enhanced stronger RCW-Cd retention(up to 82.8%)and reduced Cd migration to the ***,the g-C_(3)N_(4)NSs reversed the Cd-induced chlorosis,increased photosynthetic efficiency because of enhancement in F_v/F_mration,Y(Ⅱ)and sugars *** results provide new insights into the alleviation of Cd toxicity to plants by g-C_(3)N_(4)NSs,and shed light on the application of low-cost and environmental-friendly carbon-based NMs for alleviating heavy metal toxicity to plants.

关键词： Cadmium Carbon nitride nanosheets Cell wall Pectin Pectin methylesterase Soybean

An Underwater Target Detection Algorithm Based on Attention Mechanism and Improved YOLOv7

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Computers, Materials & Continua 2024年第2期78卷 2829-2845页

作者： Liqiu Ren Zhanying Li Xueyu He Lingyan Kong Yinghao Zhang college of Information Science and Engineering Dalian Polytechnic UniversityDalian116034China

For underwater robots in the process of performing target detection tasks,the color distortion and the uneven quality of underwater images lead to great difficulties in the feature extraction process of the model,which is prone to issues like error detection,omission detection,and poor ***,this paper proposed the CER-YOLOv7(CBAM-EIOU-RepVGG-YOLOv7)underwater target detection *** improve the algorithm’s capability to retain valid features from both spatial and channel perspectives during the feature extraction phase,we have added a Convolutional Block Attention Module(CBAM)to the backbone *** Reparameterization Visual Geometry Group(RepVGG)module is inserted into the backbone to improve the training and inference *** Efficient Intersection over Union(EIoU)loss is also used as the localization loss function,which reduces the error detection rate and missed detection rate of the *** experimental results of the CER-YOLOv7 algorithm on the UPRC(Underwater Robot Prototype Competition)dataset show that the mAP(mean Average Precision)score of the algorithm is 86.1%,which is a 2.2%improvement compared to the *** feasibility and validity of the CER-YOLOv7 are proved through ablation and comparison experiments,and it is more suitable for underwater target detection.

关键词： Deep learning underwater object detection improved YOLOv7 attention mechanism

Examining the Use of Scott’s Formula and Link Expiration Time Metric for Vehicular Clustering

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2421-2444页

作者： Fady Samann Shavan Askar Department of Energy Engineering Technical College of EngineeringDuhok Polytechnic UniversityDuhok42001Iraq Department of Information System Engineering Technical College of EngineeringErbil Polytechnic UniversityErbil44001Iraq

Implementing machine learning algorithms in the non-conducive environment of the vehicular network requires some adaptations due to the high computational complexity of these algorithms.K-clustering algorithms are simplistic,with fast performance and relative ***,their implementation depends on the initial selection of clusters number(K),the initial clusters’centers,and the clustering *** paper investigated using Scott’s histogram formula to estimate the K number and the Link Expiration Time(LET)as a clustering *** traffic flows were considered for three maps,namely Highway,Traffic Light junction,and Roundabout junction,to study the effect of road layout on estimating the K number.A fast version of the PAM algorithm was used for clustering with a modification to reduce time *** Affinity propagation algorithm sets the baseline for the estimated K number,and the Medoid Silhouette method is used to quantify the ***++,Veins,and SUMO were used to simulate the traffic,while the related algorithms were implemented in *** Scott’s formula estimation of the K number only matched the baseline when the road layout was ***,the clustering algorithm required one iteration on average to converge when used with LET.

关键词： Clustering vehicular network Scott’s formula FastPAM

Intelligent In-Vehicle Safety System Based on Yolov5

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Journal of Computer and Communications 2024年第3期12卷 207-218页

作者： Biyun Chen Wei Cai Jinwen Zhu college of Computer Information and Engineering Yancheng Teachers University Yancheng China

In order to reduce the occurrence of traffic accidents and assist drivers to avoid dangerous driving. This paper presents a smart in-vehicle safety system that utilises the Yolov5 algorithm. Yolov5 algorithm is used to anticipate driver fatigue and distraction behaviours, and remind drivers to pay attention to safe driving in time. The system continuously splits the frames and analyses the frame content through the video feedback from the front camera, compared to the traditional machine learning, Yolov5’s mosaic data is enhanced, resulting in a batch size enhancement of 92.3%, and it also uses the Drop Block mechanism to prevent overfitting. The hardware of this system uses STM32 microcontroller and uses system DMA interrupt control and buzzer alarm device to warn about dangerous driving behaviour.

关键词： Behaviour Detection STM32 Pyside2 Yolov5 Dlib Open Source Library Perclos Model

Repair of Second-Generation Recycled Fine Aggregate of Waste Concrete from Freeze-Thaw Environment by Carbonation Treatment

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Journal of Renewable Materials 2024年第1期12卷 187-201页

作者： Jie Huang Rongbin Jiang Xiaobo Sun Yingyong Shuai School of Building Engineering Taizhou Polytechnic CollegeTaizhou225300China

The reuse of waste recycled concrete from harsh environments has become a research hotspot in the field of *** study investigated the repair effect of carbonation treatment on second-generation recycled fine aggregate(SRFA)obtained from recycled fine aggregate concrete(RFAC)subjected to freeze-thaw(FT)*** and after carbonation,the properties of SRFA were *** second-generation recycled fine aggregate(CSRFA)at five substitution rates(0%,25%,50%,75%,100%)to replace SRFA was used to prepare carbonated second-generation recycled fine aggregate concrete(CSRFAC).The water absorption,porosity and mechanical properties of CSRFAC were tested,and its frost-resisting durability was *** results showed after carbonation treatment,the physical properties of SRFA was improved and met the requirements of II *** micro-hardness of the interfacial transition zone and attached mortar in CSRFA was 50.5%and 31.2%higher than that in SRFA,*** the increase of CSRFA replacement rate,the water absorption and porosity of CSRFAC gradually decreased,and the mechanical properties and frost resistance of CSRFAC were gradually *** treatment effectively repairs the damage of SRFA caused by FT cycles and improves its application potential.

关键词： Carbonation treatment repair freeze-thaw cycles second-generation recycled fine aggregate