期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到31篇文章
< 1 2 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
Evaluation and Optimization of the Mixed Redundancy Strategy in Cloud-Based Systems 认领 引用
1
作者 Pan He Xueliang Zhao +2 位作者 Chun Tan Zhihao Zheng Yue Yuan 《China Communications》 SCIE CSCD 2016年第9期237-248,共12页
Mixed redundancy strategies are generally used in cloud-based systems,with different node switch mechanisms from traditional fault-tolerant strategies.Existing studies often concentrate on optimizing a single strategy... Mixed redundancy strategies are generally used in cloud-based systems,with different node switch mechanisms from traditional fault-tolerant strategies.Existing studies often concentrate on optimizing a single strategy in cloud computing environment and ignore the impact of mixed redundancy strategies.Therefore,a model is proposed to evaluate and optimize the reliability and performance of cloud-based degraded systems subject to a mixed active and cold standby redundancy strategy.In this strategy,node switching is triggered by a continual monitoring and detection mechanism when active nodes fail.To evaluate the transient availability and the expected job completion rate of systems with such kind of strategy,a continuous-time Markov chain model is built on the state transition process and a numerical method is used to solve the model.To choose the optimal redundancy for the mixed strategy under system constraints,a greedy search algorithm is proposed after sensitivity analysis.Illustrative examples were presented to explain the process of calculating the transient probability of each system state and in turn,the availability and performance of the whole system.It was shown that the near-optimal redundancy solution could be obtained using the optimizationmethod.The comparison with optimization of the traditional mixed redundancy strategy proved that the system behavior was different using different kinds of mixed strategies and less redundancy was assigned for the new type of mixed strategy under the same system constraint. 展开更多
关键词 Mixed redundancy strategy monitoring reliability analysis Markov chain cloud-based system
暂未订购 下载PDF
A Cloud-Based Distributed System for Story Visualization Using Stable Diffusion 认领 引用
2
作者 Chuang-Chieh Lin Yung-Shen Huang Shih-Yeh Chen 《Computers, Materials & Continua》 SCIE EI 2026年第2期1751-1769,共19页
With the rapid development of generative artificial intelligence(GenAI),the task of story visualization,which transforms natural language narratives into coherent and consistent image sequences,has attracted growing r... With the rapid development of generative artificial intelligence(GenAI),the task of story visualization,which transforms natural language narratives into coherent and consistent image sequences,has attracted growing research attention.However,existing methods still face limitations in balancing multi-frame character consistency and generation efficiency,which restricts their feasibility for large-scale practical applications.To address this issue,this study proposes a modular cloud-based distributed system built on Stable Diffusion.By separating the character generation and story generation processes,and integratingmulti-feature control techniques,a cachingmechanism,and an asynchronous task queue architecture,the system enhances generation efficiency and scalability.The experimental design includes both automated and human evaluations of character consistency,performance testing,and multinode simulation.The results show that the proposed system outperforms the baseline model StoryGen in both CLIP-I and human evaluation metrics.In terms of performance,under the experimental environment of this study,dual-node deployment reduces average waiting time by approximately 19%,while the four-node simulation further reduces it by up to 65%.Overall,this study demonstrates the advantages of cloud-distributed GenAI in maintaining character consistency and reducing generation latency,highlighting its potential value inmulti-user collaborative story visualization applications. 展开更多
关键词 Stable diffusion story visualization generativeAI distributed computing cloud-based system character consistency
暂未订购 下载PDF
An Algorithm for Cloud-based Web Service Combination Optimization Through Plant Growth Simulation 认领 引用 被引量：1
3
作者 Li Qiang Qin Huawei +1 位作者 Qiao Bingqin Wu Ruifang 《系统仿真学报》 EI CAS CSCD 北大核心 2025年第2期462-473,共12页
In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-base... In order to improve the efficiency of cloud-based web services,an improved plant growth simulation algorithm scheduling model.This model first used mathematical methods to describe the relationships between cloud-based web services and the constraints of system resources.Then,a light-induced plant growth simulation algorithm was established.The performance of the algorithm was compared through several plant types,and the best plant model was selected as the setting for the system.Experimental results show that when the number of test cloud-based web services reaches 2048,the model being 2.14 times faster than PSO,2.8 times faster than the ant colony algorithm,2.9 times faster than the bee colony algorithm,and a remarkable 8.38 times faster than the genetic algorithm. 展开更多
关键词 cloud-based service scheduling algorithm resource constraint load optimization cloud computing plant growth simulation algorithm
暂未订购 下载PDF
Cloud-Based Deep Learning for Real-Time URL Anomaly Detection: LSTM/GRU and CNN/LSTM Models 认领 引用
4
作者 Ayman Noor 《Computer Systems Science & Engineering》 2025年第1期259-286,共28页
Precisely forecasting the performance of Deep Learning(DL)models,particularly in critical areas such as Uniform Resource Locator(URL)-based threat detection,aids in improving systems developed for difficult tasks.In c... Precisely forecasting the performance of Deep Learning(DL)models,particularly in critical areas such as Uniform Resource Locator(URL)-based threat detection,aids in improving systems developed for difficult tasks.In cybersecurity,recognizing harmful URLs is vital to lowering risks associated with phishing,malware,and other online-based attacks.Since it directly affects the model’s capacity to differentiate between benign and harmful URLs,finding the optimum mix of hyperparameters in DL models is a significant difficulty.Two commonly used architectures for sequential and spatial data processing,Long Short-Term Memory(LSTM)/Gated Recurrent Unit(GRU)and Convolutional Neural Network(CNN)/Long Short-Term Memory(LSTM)models are targeted in this study to have higher predictive capacity by modifying crucial hyperparameters such as learning rate,batch size,and dropout rate using cloud capability.Research finds the best settings for the models by testing 50 dropout rates(between 0.1 and 0.5)with different learning rates and batch sizes.Performances were measured in the form of accuracy,precision,recall,F1-score,and errors such as Mean Absolute Error(MAE),Mean Squared Error(MSE),Root Mean Squared Error(RMSE)and Mean Absolute Percent Error(MAPE).In our results,CNN/LSTM performed better often than LSTM/GRU,with up to 10%better F1-score and much lower MAPE when the learning rate was 0.001 and the dropout rate was 0.2.These results show the value of fine-tuning hyperparameters to increase model performance and reduce errors.Higher on many of the parameters,CNN/LSTM architecture became obvious as the more trustworthy one.It also discussed the importance of DL in enhancing URL attack detection mechanisms to provide increased accuracy and precision for real-world cybersecurity. 展开更多
关键词 Cloud-based anomaly detection focal loss dynamic threshold tuning LSTM GRU CNN
暂未订购 下载PDF
Prospects and Challenges of 5G Technology in Cloud-Based Control of Industrial Robots 认领 引用
5
作者 Zhou Yang 《信息工程期刊（中英文版）》 2025年第2期7-10,共4页
The integration of 5G technology with cloud-based control systems in industrial robots holds significant promise for the future of industrial automation.With its ultra-low latency,high data transfer speeds,and massive... The integration of 5G technology with cloud-based control systems in industrial robots holds significant promise for the future of industrial automation.With its ultra-low latency,high data transfer speeds,and massive connectivity,5G is poised to revolutionize real-time communication and coordination in manufacturing environments.This paper explores the prospects and challenges of applying 5G technology in industrial robots,focusing on cloud-based control systems that enable scalable,flexible,and efficient operations.Key advantages of 5G,including improved communication speed,enhanced real-time control,scalability,and predictive maintenance capabilities,are discussed.However,the transition to 5G also presents challenges,such as network reliability,security concerns,integration with legacy systems,and high implementation costs.The paper also examines case studies in the automotive,electronics,and aerospace industries,providing real-world examples of 5G adoption in industrial automation.The conclusion highlights key insights and outlines potential research directions for overcoming existing barriers and fully realizing the potential of 5G technology in industrial robot control. 展开更多
关键词 5G Technology Industrial Robots Cloud-Based Control Automation Predictive Maintenance Real-Time Communication
FunnelCloud:a cloud-based system for exploring tornado events 认领 引用 被引量：1
6
作者 Jie Lian Michael P.McGuire Todd W.Moore 《International Journal of Digital Earth》 SCIE EI 2017年第10期1030-1054,共25页
Recent research has shown an increase in the number of extreme tornado outbreaks per year.The characterization of the spatio-temporal pattern of tornado events is therefore a critical task in the analysis of meteorolo... Recent research has shown an increase in the number of extreme tornado outbreaks per year.The characterization of the spatio-temporal pattern of tornado events is therefore a critical task in the analysis of meteorological data.Currently,there are a large number of available meteorological datasets that can be used for such analysis.However,much of these data are distributed across multiple websites and are not accessible in a central location.This poses a significant challenge for a scientist who is interested in exploring meteorological patterns associated with tornado events.This paper presents a novel system which uses cloud-based technology for integrating,storing,exploring,analyzing,and visualizing meteorological data associated with tornado outbreaks.The system employs a novel NoSQL database schema and web services architecture for data integration and provides a user friendly interface that allows scientists to explore the spatio-temporal pattern of tornado events.Furthermore,scientists can use this interface to analyze the relationship between different meteorological variables and properties of tornado outbreaks using a number of spatio-temporal statistical and data mining methods.The efficacy of the system is demonstrated on a use case centered on the analysis of climatic indicators of large spatio-temporally clustered tornado outbreaks. 展开更多
关键词 tornado data warehouse cloud-based system NoSQL data integration spatio-temporal clustering web-mapping
Blockchain-Assisted Secure Fine-Grained Searchable Encryption for a Cloud-Based Healthcare Cyber-Physical System 认领 引用 被引量：28
7
作者 Mamta Brij B.Gupta +3 位作者 Kuan-Ching Li Victor C.M.Leun Kostas E.Psannis Shingo Yamaguchi 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2021年第12期1877-1890,共14页
The concept of sharing of personal health data over cloud storage in a healthcare-cyber physical system has become popular in recent times as it improves access quality.The privacy of health data can only be preserved... The concept of sharing of personal health data over cloud storage in a healthcare-cyber physical system has become popular in recent times as it improves access quality.The privacy of health data can only be preserved by keeping it in an encrypted form,but it affects usability and flexibility in terms of effective search.Attribute-based searchable encryption(ABSE)has proven its worth by providing fine-grained searching capabilities in the shared cloud storage.However,it is not practical to apply this scheme to the devices with limited resources and storage capacity because a typical ABSE involves serious computations.In a healthcare cloud-based cyber-physical system(CCPS),the data is often collected by resource-constraint devices;therefore,here also,we cannot directly apply ABSE schemes.In the proposed work,the inherent computational cost of the ABSE scheme is managed by executing the computationally intensive tasks of a typical ABSE scheme on the blockchain network.Thus,it makes the proposed scheme suitable for online storage and retrieval of personal health data in a typical CCPS.With the assistance of blockchain technology,the proposed scheme offers two main benefits.First,it is free from a trusted authority,which makes it genuinely decentralized and free from a single point of failure.Second,it is computationally efficient because the computational load is now distributed among the consensus nodes in the blockchain network.Specifically,the task of initializing the system,which is considered the most computationally intensive,and the task of partial search token generation,which is considered as the most frequent operation,is now the responsibility of the consensus nodes.This eliminates the need of the trusted authority and reduces the burden of data users,respectively.Further,in comparison to existing decentralized fine-grained searchable encryption schemes,the proposed scheme has achieved a significant reduction in storage and computational cost for the secret key associated with users.It has been verified both theoretically and practically in the performance analysis section. 展开更多
关键词 Cloud-based cyber-physical systems(CCPS) data encryption healthcare information search and retrieval keyword search public-key cryptosystems searchable encryption
暂未订购 下载PDF
Intelligent Spectrum Management Based on Radio Map for Cloud-Based Satellite and Terrestrial Spectrum Shared Networks 认领 引用 被引量：9
8
作者 Ximu Zhang Min Jia +1 位作者 Xuemai Gu Qing Guo 《China Communications》 SCIE EI CSCD 2021年第12期108-118,共11页
Cloud-based satellite and terrestrial spectrum shared networks(CB-STSSN)combines the triple advantages of efficient and flexible net-work management of heterogeneous cloud access(H-CRAN),vast coverage of satellite net... Cloud-based satellite and terrestrial spectrum shared networks(CB-STSSN)combines the triple advantages of efficient and flexible net-work management of heterogeneous cloud access(H-CRAN),vast coverage of satellite networks,and good communication quality of terrestrial networks.Thanks to the complementary coverage characteristics,any-time and anywhere high-speed communications can be achieved to meet the various needs of users.The scarcity of spectrum resources is a common prob-lem in both satellite and terrestrial networks.In or-der to improve resource utilization,the spectrum is shared not only within each component but also be-tween satellite beams and terrestrial cells,which intro-duces inter-component interferences.To this end,this paper first proposes an analytical framework which considers the inter-component interferences induced by spectrum sharing(SS).An intelligent SS scheme based on radio map(RM)consisting of LSTM-based beam prediction(BP),transfer learning-based spec-trum prediction(SP)and joint non-preemptive prior-ity and preemptive priority(J-NPAP)-based propor-tional fair spectrum allocation is than proposed.The simulation result shows that the spectrum utilization rate of CB-STSSN is improved and user blocking rate and waiting probability are decreased by the proposed scheme. 展开更多
关键词 cloud-based satellite and terrestrial spec-trum shared networks spectrum management inter-ference analysis spectrum utilization rate
暂未订购 下载PDF
DADOS:A Cloud-based Data-driven Design Optimization System 认领 引用 被引量：4
9
作者 Xueguan Song Shuo Wang +2 位作者 Yonggang Zhao Yin Liu Kunpeng Li 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2023年第2期50-66,共17页
This paper presents a cloud-based data-driven design optimization system,named DADOS,to help engineers and researchers improve a design or product easily and efficiently.DADOS has nearly 30 key algorithms,including th... This paper presents a cloud-based data-driven design optimization system,named DADOS,to help engineers and researchers improve a design or product easily and efficiently.DADOS has nearly 30 key algorithms,including the design of experiments,surrogate models,model validation and selection,prediction,optimization,and sensitivity analysis.Moreover,it also includes an exclusive ensemble surrogate modeling technique,the extended hybrid adaptive function,which can make use of the advantages of each surrogate and eliminate the effort of selecting the appropriate individual surrogate.To improve ease of use,DADOS provides a user-friendly graphical user interface and employed flow-based programming so that users can conduct design optimization just by dragging,dropping,and connecting algorithm blocks into a workflow instead of writing massive code.In addition,DADOS allows users to visualize the results to gain more insights into the design problems,allows multi-person collaborating on a project at the same time,and supports multi-disciplinary optimization.This paper also details the architecture and the user interface of DADOS.Two examples were employed to demonstrate how to use DADOS to conduct data-driven design optimization.Since DADOS is a cloud-based system,anyone can access DADOS at www.dados.com.cn using their web browser without the need for installation or powerful hardware. 展开更多
关键词 Data-driven Optimization Cloud-based software Design of experiments Surrogate model
暂未订购 下载PDF
Privacy Protection Based Access Control Scheme in Cloud-Based Services 认领 引用 被引量：3
10
作者 Kai Fan Qiong Tian +2 位作者 Junxiong Wang Hui Li Yintang Yang 《China Communications》 SCIE CSCD 2017年第1期61-71,共11页
With the rapid development of computer technology, cloud-based services have become a hot topic. They not only provide users with convenience, but also bring many security issues, such as data sharing and privacy issu... With the rapid development of computer technology, cloud-based services have become a hot topic. They not only provide users with convenience, but also bring many security issues, such as data sharing and privacy issue. In this paper, we present an access control system with privilege separation based on privacy protection(PS-ACS). In the PS-ACS scheme, we divide users into private domain(PRD) and public domain(PUD) logically. In PRD, to achieve read access permission and write access permission, we adopt the Key-Aggregate Encryption(KAE) and the Improved Attribute-based Signature(IABS) respectively. In PUD, we construct a new multi-authority ciphertext policy attribute-based encryption(CP-ABE) scheme with efficient decryption to avoid the issues of single point of failure and complicated key distribution, and design an efficient attribute revocation method for it. The analysis and simulation result show that our scheme is feasible and superior to protect users' privacy in cloud-based services. 展开更多
关键词 access control data sharing privacy protection cloud-based services
暂未订购 下载PDF
First Research on Cloud-Base Height over Zhongshan Station in East Antarctica Based on Ceilometer Data 认领 引用
11
作者 Jin YE Lei LIU +7 位作者 Xinyi LIU Jinfeng DING Hailing XIE Shuai HU Fanchang MENG Maoning TANG Qizhen SUN Jing ZHAO 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2025年第10期2173-2183,共11页
Antarctic clouds and their vertical structures play a significant role in influencing the regional radiation budget and ice mass balance;however,substantial uncertainties persist.Continuous monitoring and research are... Antarctic clouds and their vertical structures play a significant role in influencing the regional radiation budget and ice mass balance;however,substantial uncertainties persist.Continuous monitoring and research are essential for enhancing our understanding of these clouds.This study presents an analysis of cloud occurrence frequency and cloud-base heights(CBHs)at Zhongshan Station in East Antarctica for the first time,utilizing data from a C12 ceilometer covering the period from January 2022 to December 2023.The findings indicate that low clouds dominate at Zhongshan Station,with an average cloud occurrence frequency of 75%.Both the cloud occurrence frequency and CBH distribution exhibit distinct seasonal variations.Specifically,the cloud occurrence frequency during winter is higher than that observed in summer,while winter clouds can develop to greater heights.Over the Southern Ocean,the cloud occurrence frequency during summer surpasses that at Zhongshan Station,with clouds featuring lower CBHs and larger extinction coefficients.Furthermore,it is noteworthy that CBHs derived from the ceilometer are basically consistent with those obtained from radiosondes.Importantly,ERA5 demonstrates commendable performance in retrieving CBHs at Zhongshan Station when compared with ceilometer measurements. 展开更多
关键词 cloud-base height ceilometer Antarctica radiosonde ERA5
暂未订购 下载PDF
Toward Cloud-Based Parking Facility Management System: A Preliminary Study 认领 引用 被引量：1
12
作者 Chung-Yang Chen Wen-Lung Tsai Tzu-Yin Chen 《Journal of Electronic Science and Technology》 CAS 2013年第2期181-186,共6页
An e-tag used on the freeway is a kind of passive sensors composed of sensors and radio- frequency identification （RFID） tags. The principle of the electronic toll collection system is that the sensor emits radio wa... An e-tag used on the freeway is a kind of passive sensors composed of sensors and radio- frequency identification （RFID） tags. The principle of the electronic toll collection system is that the sensor emits radio waves touching the e-tag within a certain range, the e-tag will respond to the radio waves by induction, and the sensor will read and write information of the vehicles. Although the RFID technology is popularly used in campus management systems, there is no e-tag technology application used in a campus parking system. In this paper, we use the e-tag technology on a campus parking management system based on the cloud-based construction. By this, it helps to achieve automated and standardized management of the campus parking system, enhance management efficiency, reduce the residence time of the vehicles at the entrances and exits, and improve the efficiency of vehicles parked at the same time. 展开更多
关键词 Cloud-based construction e-tag parking facility management system radio-frequencyidentification.
暂未订购 下载PDF
Prediction of pressure coefficient distributions for basic aerodynamic configurations via point cloud characterization 认领 引用
13
作者 Qiming Guan Weiwei Zhang 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2026年第7期19-35,共17页
Data-driven approaches have shown great advantage in rapidly and accurately predicting pressure coefficient distributions,which is of crucial importance to efficient aircraft design.Nevertheless,most data-driven appro... Data-driven approaches have shown great advantage in rapidly and accurately predicting pressure coefficient distributions,which is of crucial importance to efficient aircraft design.Nevertheless,most data-driven approaches still encounter limitations in characterizing diverse aerodynamic configurations and adapting to varying grid densities,which have hindered their engineering applicability.In response to these challenges,this work adopts point clouds,a specific type of geometric data structure that is inherently suitable for uniformly characterizing diverse 2D/3D geometric shapes as the input for deep learning-based prediction of pressure coefficient distribution.By augmenting the dimensions of point cloud coordinates for local feature enhancement and utilizing the symmetric function“max pooling”to extract global features,the proposed aerodynamic model establishes the mapping between point cloud coordinates and pressure coefficients.Basic aerodynamic configurations like airfoils and wings are employed as test cases,the results demonstrate that the proposed model achieves both high accuracy and robust generalizability across variable geometries.For class-shape transformation-perturbed airfoils,the prediction error can be reduced to one-third of that of the conventional parameterization-based model.For airfoils selected in the University of Illinois Urbana-Champaign airfoil dataset,among which airfoil profiles are widely distributed,the average error of the proposed approach remains approximately 1.5%,whereas the parameterization-based model may fail.For wings,the prediction error still stays below 2.5%.Finally,the model exhibits strong robustness and generalizability across different point cloud densities.In conclusion,this work makes a breakthrough in predicting pressure coefficient distribution for variable geometric configurations,establishing the foundational framework for designing a large model capable of predicting distributed aerodynamic loads in aerospace applications. 展开更多
关键词 Data-driven Deep learning Pressure coefficient distribution prediction Point cloud Point cloud-based machine learning
暂未订购 下载PDF
Cloud-Base Distribution and Cirrus Properties Based on Micropulse Lidar Measurements at a Site in Southeastern China 认领 引用 被引量：2
14
作者 Jianjun LIU Zhanqing LI +1 位作者 ZHENG Youfei Maureen CRIBB 《Advances in Atmospheric Sciences》 SCIE CAS CSCD 2015年第7期991-1004,共14页
The cloud fraction （CF） and cloud-base heights （CBHs）, and cirrus properties, over a site in southeastern China from June 2008 to May 2009, are examined by a ground-based lidar. Results show that clouds occupied t... The cloud fraction （CF） and cloud-base heights （CBHs）, and cirrus properties, over a site in southeastern China from June 2008 to May 2009, are examined by a ground-based lidar. Results show that clouds occupied the sky 41% of the time. Significant seasonal variations in CF were found with a maximum/minimum during winter/summer and similar magnitudes of CF in spring and autumn. A distinct diurnal cycle in the overall mean CF was seen. Total, daytime, and nighttime annual mean CBHs were 3.05 ± 2.73 km, 2.46 ± 2.08 kin, and 3.51 ± 3.07 km, respectively. The lowest/highest CBH occurred around noon/midnight. Cirrus clouds were present ～36.2% of the time at night with the percentage increased in summer and decreased in spring. Annual mean values for cirrus geometrical properties were 8.89 ± 1.65 km, 9.80 ± 1.70 kin, 10.73 ± 1.86 km and 1.83± 0.91 km for the base, mid-cloud, top height, and the thickness, respectively. Seasonal variations in cirrus geometrical properties show a maximum/minimum in summer/winter for all cirrus geometrical parameters. The mean cirrus lidar ratio for all cirrus cases in our study was ～ 25 ± 17 sr, with a smooth seasonal trend. The cirrus optical depth ranged from 0.001 to 2.475, with a mean of 0.34 ± 0.33. Sub-visual, thin, and dense cirrus were observed in ～12%, 43%, and 45% of the cases, respectively. More frequent, thicker cirrus clouds occurred in summer than in any other season. The properties of cirrus cloud over the site are compared with other lidar-based retrievals of midlatitude cirrus cloud properties. 展开更多
关键词 cloud-base distribution cirrus propertfes lidar southeastern China
暂未订购 下载PDF
A critical review on pavement distress detection using images and point clouds from visual features to geometric modeling 认领 引用 被引量：2
15
作者 Jiayv Jing Xu Yang +4 位作者 Hang Cheng Xu Feng Hao Zheng Ioannis Brilakis Jiamei Liu 《Journal of Road Engineering》 EI CAS 2025年第4期583-606,共24页
Pavement distress detection plays a pivotal role in ensuring roadway safety,serviceability,and cost-effective infrastructure management.With rapid advancements in intelligent transportation systems,computer vision,and... Pavement distress detection plays a pivotal role in ensuring roadway safety,serviceability,and cost-effective infrastructure management.With rapid advancements in intelligent transportation systems,computer vision,and sensing technologies,non-contact detection approaches based on images and point clouds have become increasingly prominent due to their efficiency,objectivity,and scalability.This review systematically examines both image-based and point cloud-based methodologies,structured along the complete detection pipeline encompassing data acquisition,preprocessing,distress extraction,and geometric quantification.Image-based techniques rely on visual cues,such as texture,color,and edge continuity,to identify surface-level anomalies efficiently,benefiting from mature deep learning frameworks for classification,object detection,and pixel-level segmentation.In contrast,point cloud-based methods capture rich three-dimensional geometric and structural information,enabling detailed modeling of crack depth,rutting deformation,and surface irregularities.Although each modality can independently achieve satisfactory performance,their complementary strengths have driven a growing trend toward hybrid frameworks,combining image-based rapid screening with point cloud-based precision modeling,to enhance detection accuracy,robustness,and adaptability across varying conditions.Furthermore,this paper highlights persistent challenges,including multimodal data fusion,high equipment and labeling costs,computational complexity,and the need for standardized benchmarks.By synthesizing current progress and identifying key technical bottlenecks,this review provides a comprehensive foundation and forward-looking perspective for developing intelligent,efficient,and scalable pavement distress detection systems. 展开更多
关键词 Pavement distress detection Image-based methods Point cloud-based methods Deep learning Intelligent maintenance
暂未订购 下载PDF
A Knowledge-Enhanced Modular Method for Predicting Electric Vehicle Remaining Driving Range under Cold Conditions Utilizing Cloud-Based Big Data 认领 引用 被引量：1
16
作者 Yunfeng Hu Hong Liu +5 位作者 Yao Sun Xun Gong Fengxin Zhao Zhen Cheng Chong Zhang Ke Xu 《Automotive Innovation》 EI CSCD 2025年第3期786-798,共13页
Under cold conditions,the driving range of electric vehicles decreases significantly,and inaccuracies in the displayed remaining driving range(RDR)exacerbate range anxiety.This study proposes a knowledge-enhanced hier... Under cold conditions,the driving range of electric vehicles decreases significantly,and inaccuracies in the displayed remaining driving range(RDR)exacerbate range anxiety.This study proposes a knowledge-enhanced hierarchical framework that breaks down the RDR estimation problem into the prediction of energy consumption rate and effective energy coefficient.Both modules employ deep learning as their core models,using data sourced from a cloud-based big data platform with a focus on cold regions in Northeast China.To address real-world driving scenarios,the energy consumption rate module uses a switching mechanism:a base model,using region-specific collaborative features as inputs,is applied in the early stages of trips,while a sequential neural network is used in the later stages.The effective energy coefficient module incorporates battery degradation and environmental factors,correcting discrepancies in nominal battery energy under low-temperature and aging conditions.The model’s performance is validated using real-world data from 8 electric vehicles under cold conditions,demonstrating a 15–20%improvement in prediction accuracy over traditional methods,thereby enhancing RDR accuracy and reliability. 展开更多
关键词 Remaining driving range Electric vehicles Modular framework Energy consumption rate Effective energy coefficient Region-specific collaborative features Cloud-based big data
Artificial intelligence model on images of functional dyspepsia 认领 引用 被引量：2
17
作者 Hiroshi Mihara Sohachi Nanjo +3 位作者 Iori Motoo Takayuki Ando Haruka Fujinami Ichiro Yasuda 《Artificial Intelligence in Gastrointestinal Endoscopy》 2025年第1期1-11,共11页
BACKGROUND Recently,it has been suggested that the duodenum may be the pathological locus of functional dyspepsia(FD).Additionally,an image-based artificial intelligence(AI)model was shown to discriminate colonoscopy ... BACKGROUND Recently,it has been suggested that the duodenum may be the pathological locus of functional dyspepsia(FD).Additionally,an image-based artificial intelligence(AI)model was shown to discriminate colonoscopy images of irritable bowel syndrome from healthy subjects with an area under the curve(AUC)0.95.AIM To evaluate an AI model to distinguish duodenal images of FD patients from healthy subjects.METHODS Duodenal images were collected from hospital records and labeled as"functional dyspepsia"or non-FD in electronic medical records.Helicobacter pylori(HP)infection status was obtained from the Japan Endoscopy Database.Google Cloud AutoML Vision was used to classify four groups:FD/HP current infection(n=32),FD/HP uninfected(n=35),non-FD/HP current infection(n=39),and non-FD/HP uninfected(n=33).Patients with organic diseases(e.g.,cancer,ulcer,postoperative abdomen,reflux)and narrow-band or dye-spread images were excluded.Sensitivity,specificity,and AUC were calculated.RESULTS In total,484 images were randomly selected for FD/HP current infection,FD/HP uninfected,non-FD/current infection,and non-FD/HP uninfected.The overall AUC for the four groups was 0.47.The individual AUC values were as follows:FD/HP current infection(0.20),FD/HP uninfected(0.35),non-FD/current infection(0.46),and non-FD/HP uninfected(0.74).Next,using the same images,we constructed models to determine the presence or absence of FD in the HP-infected or uninfected patients.The model exhibited a sensitivity of 58.3%,specificity of 100%,positive predictive value of 100%,negative predictive value of 77.3%,and an AUC of 0.85 in HP uninfected patients.CONCLUSION We developed an image-based AI model to distinguish duodenal images of FD from healthy subjects,showing higher accuracy in HP-uninfected patients.These findings suggest AI-assisted endoscopic diagnosis of FD may be feasible. 展开更多
关键词 Artificial Intelligence Cloud-based Duodenum Functional dyspepsia
暂未订购 下载PDF
A Cloud-Based BPM Architecture with User-End Distribution of Non-Compute-Intensive Activities and Sensitive Data 认领 引用 被引量：7
18
作者 韩燕波 孙君意 +1 位作者 王桂玲 李厚福 《Journal of Computer Science & Technology》 SCIE EI 2010年第6期1157-1167,共11页
While cloud-based BPM（Business Process Management） shows potentials of inherent scalability and expenditure reduction,such issues as user autonomy,privacy protection and efficiency have popped up as major concerns.U... While cloud-based BPM（Business Process Management） shows potentials of inherent scalability and expenditure reduction,such issues as user autonomy,privacy protection and efficiency have popped up as major concerns.Users may have their own rudimentary or even full-edged BPM systems,which may be embodied by local EAI systems,at their end,but still intend to make use of cloud-side infrastructure services and BPM capabilities,which may appear as PaaS（Platform-as-a-Service） services,at the same time.A whole business process may contain a number of non-compute-intensive activities,for which cloud computing is over-provision.Moreover,some users fear data leakage and loss of privacy if their sensitive data is processed in the cloud.This paper proposes and analyzes a novel architecture of cloud-based BPM,which supports user-end distribution of non-compute-intensive activities and sensitive data.An approach to optimal distribution of activities and data for synthetically utilizing both user-end and cloud-side resources is discussed.Experimental results show that with the help of suitable distribution schemes,data privacy can be satisfactorily protected,and resources on both sides can be utilized at lower cost. 展开更多
关键词 cloud-based BPM user-end autonomy data privacy
暂未订购 下载PDF
Cloud-based data management system for automatic real-time data acquisition from large-scale laying-hen farms 认领 引用 被引量：5
19
作者 Chen Hongqian Hongwei Xin +4 位作者 Teng Guanghui Meng Chaoying Du Xiaodong Mao Taotao Wang Cheng 《International Journal of Agricultural and Biological Engineering》 SCIE 2016年第4期106-115,共10页
Management of poultry farms in China mostly relies on manual labor.Since such a large amount of valuable data for the production process either are saved incomplete or saved only as paper documents,making it very diff... Management of poultry farms in China mostly relies on manual labor.Since such a large amount of valuable data for the production process either are saved incomplete or saved only as paper documents,making it very difficult for data retrieve,processing and analysis.An integrated cloud-based data management system(CDMS)was proposed in this study,in which the asynchronous data transmission,distributed file system,and wireless network technology were used for information collection,management and sharing in large-scale egg production.The cloud-based platform can provide information technology infrastructures for different farms.The CDMS can also allocate the computing resources and storage space based on demand.A real-time data acquisition software was developed,which allowed farm management staff to submit reports through website or smartphone,enabled digitization of production data.The use of asynchronous transfer in the system can avoid potential data loss during the transmission between farms and the remote cloud data center.All the valid historical data of poultry farms can be stored to the remote cloud data center,and then eliminates the need for large server clusters on the farms.Users with proper identification can access the online data portal of the system through a browser or an APP from anywhere worldwide. 展开更多
关键词 cloud-based data management system(CDMS) egg production intensified laying-hen farms asynchronous data transmission metadata
Mode of Operation for Modification, Insertion, and Deletion of Encrypted Data 认领 引用
20
作者 Taek-Young Youn Nam-Su Jho 《Computers, Materials & Continua》 SCIE EI 2022年第10期151-164,共14页
Due to the development of 5G communication,many aspects of information technology(IT)services are changing.With the development of communication technologies such as 5G,it has become possible to provide IT services th... Due to the development of 5G communication,many aspects of information technology(IT)services are changing.With the development of communication technologies such as 5G,it has become possible to provide IT services that were difficult to provide in the past.One of the services made possible through this change is cloud-based collaboration.In order to support secure collaboration over cloud,encryption technology to securely manage dynamic data is essential.However,since the existing encryption technology is not suitable for encryption of dynamic data,a new technology that can provide encryption for dynamic data is required for secure cloudbased collaboration.In this paper,we propose a new encryption technology to support secure collaboration for dynamic data in the cloud.Specifically,we propose an encryption operation mode which can support data updates such as modification,addition,and deletion of encrypted data in an encrypted state.To support the dynamic update of encrypted data,we invent a new mode of operation technique named linked-block cipher(LBC).Basic idea of our work is to use an updatable random value so-called link to link two encrypted blocks.Due to the use of updatable random link values,we can modify,insert,and delete an encrypted data without decrypt it. 展开更多
关键词 Data encryption cloud-based collaboration dynamic data update
暂未订购 下载PDF
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈