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
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
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
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
BACKGROUND Laparoscopic distal pancreatectomy(LDP)has emerged as the preferred approach for both benign and malignant lesions located in the pancreatic body and tail.Nevertheless,a notable deficiency persists in the a...BACKGROUND Laparoscopic distal pancreatectomy(LDP)has emerged as the preferred approach for both benign and malignant lesions located in the pancreatic body and tail.Nevertheless,a notable deficiency persists in the absence of a standardized,procedure-specific metric for evaluating and comparing surgical quality.A composite measure termed“textbook outcome(TO)”,which encompasses key short-term endpoints,has been validated in laparoscopic pancreatoduodenectomy but has not yet been established in dedicated LDP cohorts.The definition and prediction of TO in this context could aid in facilitating cross-institutional benchmarking and fostering advancements in quality improvement.AIM To establish procedure-specific criteria for TO and identify independent predictors of TO failure in patients undergoing LDP.METHODS Consecutive patients who underwent LDP at a single high-volume pancreatic center between January 2015 and August 2022 were retrospectively analyzed.TO was defined as the absence of clinically relevant postoperative pancreatic fistula(grade B/C),post-pancreatectomy hemorrhage(grade B/C),severe complications(Clavien-Dindo≥III),readmission within 30 days,and in-hospital or 30-day mortality.Multivariable logistic regression was employed to identify independent predictors of TO failure,and a nomogram was constructed and internally validated.RESULTS Among 405 eligible patients,286(70.6%)attained TO.Multivariable analysis revealed that female sex[odds ratio(OR)=0.62,95%confidence interval(CI):0.39-0.99]conferred a protective effect,while preoperative endoscopic ultrasound-guided fine-needle aspiration(OR=2.66,95%CI:1.05-6.73),pancreatic portal hypertension(OR=2.81,95%CI:1.06-7.45),and cystic-solid(OR=2.51,95%CI:1.34-4.69)or solid lesions(OR=1.91,95%CI:1.06-3.44)were independently associated with TO failure(all P<0.05).The derived nomogram exhibited modest discrimination and calibration when assessed in both the training and validation datasets.CONCLUSION The proposed LDP-specific definition of TO is feasible and discriminative,and the developed nomogram provides an objective tool for individualized risk assessment.展开更多
As a key carrier for the implementation of the core quality of"aesthetic creativity",the effective realization of the aesthetic value of language textbook illustrations is facing the real problems of practic...As a key carrier for the implementation of the core quality of"aesthetic creativity",the effective realization of the aesthetic value of language textbook illustrations is facing the real problems of practical disconnection and theoretical gap.Based on the theories of semiotics,embodied cognition and cultural reproduction,this paper innovatively puts forward the concept of"transformation mechanism of aesthetic education",constructs a three-phase The study analyzes the dynamic transformation process of illustrations from image symbols to students'aesthetic experience.The study explains the essential characteristics of illustration as a dual symbolic system of"likenessregulation",reveals the cognitive ladder of"perception-cognition-creation"and the path of realization of embodied cognition,and points out that the current aesthetic education of illustration has the problem of instrumentalization,and that the current aesthetic education of illustration has the problem of instrumentalization.The study points out that the current aesthetic education of illustrations is plagued by instrumental alienation,cultural hegemony and aesthetic flattening,and proposes a"three-in-one"education path from the dimensions of teachers,teaching materials and culture,including improving teachers'aesthetic education,reconstructing the principles of teaching materials and dynamic revision mechanism,and constructing classroom aesthetic education communities.The study provides new perspectives and practical guidance for exploring the aesthetic value of language textbook illustrations and bridging the gap between the theories of aesthetics and pedagogy,aiming to promote the return of aesthetic education to the nature of"reconstruction of experience",and to cultivate students'aesthetic literacy and sound personality.展开更多
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
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
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
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
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
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
BACKGROUND To investigate the preoperative factors influencing textbook outcomes(TO)in Intrahepatic cholangiocarcinoma(ICC)patients and evaluate the feasibility of an interpretable machine learning model for preoperat...BACKGROUND To investigate the preoperative factors influencing textbook outcomes(TO)in Intrahepatic cholangiocarcinoma(ICC)patients and evaluate the feasibility of an interpretable machine learning model for preoperative prediction of TO,we developed a machine learning model for preoperative prediction of TO and used the SHapley Additive exPlanations(SHAP)technique to illustrate the prediction process.AIM To analyze the factors influencing textbook outcomes before surgery and to establish interpretable machine learning models for preoperative prediction.METHODS A total of 376 patients diagnosed with ICC were retrospectively collected from four major medical institutions in China,covering the period from 2011 to 2017.Logistic regression analysis was conducted to identify preoperative variables associated with achieving TO.Based on these variables,an EXtreme Gradient Boosting(XGBoost)machine learning prediction model was constructed using the XGBoost package.The SHAP(package:Shapviz)algorithm was employed to visualize each variable's contribution to the model's predictions.Kaplan-Meier survival analysis was performed to compare the prognostic differences between the TO-achieving and non-TO-achieving groups.RESULTS Among 376 patients,287 were included in the training group and 89 in the validation group.Logistic regression identified the following preoperative variables influencing TO:Child-Pugh classification,Eastern Cooperative Oncology Group(ECOG)score,hepatitis B,and tumor size.The XGBoost prediction model demonstrated high accuracy in internal validation(AUC=0.8825)and external validation(AUC=0.8346).Survival analysis revealed that the disease-free survival rates for patients achieving TO at 1,2,and 3 years were 64.2%,56.8%,and 43.4%,respectively.CONCLUSION Child-Pugh classification,ECOG score,hepatitis B,and tumor size are preoperative predictors of TO.In both the training group and the validation group,the machine learning model had certain effectiveness in predicting TO before surgery.The SHAP algorithm provided intuitive visualization of the machine learning prediction process,enhancing its interpretability.展开更多
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
This study first analyzes four distinct forms of Fujian folk dance,highlighting the notable differences in their cultural characteristics and dance qualities.It then categorizes these dance forms to align with textboo...This study first analyzes four distinct forms of Fujian folk dance,highlighting the notable differences in their cultural characteristics and dance qualities.It then categorizes these dance forms to align with textbook construction,discussing in depth the principles guiding the development of textbooks that correspond to these classifications.展开更多
“Five education”is pivotal for students’all-round development.However,primary English teaching currently faces challenges including the superficial implementation of“Five education”.This study employed action res...“Five education”is pivotal for students’all-round development.However,primary English teaching currently faces challenges including the superficial implementation of“Five education”.This study employed action research to explore practical methods for integrating English picture book with textbook to implement“Five education”.Through two rounds of iterative action research,a three-stage activity-based teaching path was developed and refined,enabling the progressive infusion of“Five education”objectives across the learning cycle.Findings demonstrated that this integrated approach-particularly when supported by strategies such as picture book background videos and audio-edited narrative connections-effectively deepened the implementation of“Five education”,mitigated student reading fatigue,and significantly improved students’reading fluency and labor initiative,thus provided a replicable practical paradigm for realizing“Five education simultaneously”.展开更多
BACKGROUND Textbook outcome(TO),an emerging composite metric for surgical quality assessment,has recently gained recognition for evaluating perioperative results.Laparoscopic transcystic common bile duct exploration(L...BACKGROUND Textbook outcome(TO),an emerging composite metric for surgical quality assessment,has recently gained recognition for evaluating perioperative results.Laparoscopic transcystic common bile duct exploration(LTCBDE)has become a widely adopted minimally invasive technique for treating cholecystolithiasis with choledocholithiasis.Despite its growing clinical application,TO has not yet been formally defined for LTCBDE,nor have its failure-associated risk factors been systematically examined.AIM To define TO for LTCBDE,establish standardized criteria,and identify risk factors for TO failure via logistic regression.METHODS A retrospective cohort of 388 patients who underwent LTCBDE in combination with laparoscopic cholecystectomy at the Department of Biliopancreatic Surgery,Tongji Hospital,from January 2018 to October 2024,was analyzed.The study delineated TO criteria for LTCBDE,calculated the rate of TO achievement,and employed logistic regression to determine independent predictors of TO failure.RESULTS TO was defined as the absence of the following seven criteria:Conversion to open surgery,postoperative complications(Clavien-Dindo grade≥2),biliary leakage(International Study Group of Pancreatic Surgery/International Study Group of Liver Surgery grade B/C),delayed removal of drainage tube(>4 days),postoperative interventions,prolonged length of stay(>7 days),and 30-day readmission or mortality.Among 388 patients,276(71.1%)achieved TO.The primary causes of TO failure included delayed removal of drainage tube(94 cases,83.9%),prolonged length of stay(50 cases,44.6%).Multivariate analysis revealed four independent risk factors for TO failure:Preoperative endoscopic retrograde cholangiopancreatography(P=0.022),advanced age(P=0.010),prolonged anesthesia time(P<0.001),and elevated preoperative alkaline phosphatase levels(P=0.048).These findings suggest that applying the concept of TO to LTCBDE enhances surgical quality evaluation and supports early identification of high-risk patients,facilitating personalized clinical decisions and optimizing individual management.展开更多
Based on the ADDIE model,we explored the integration path between Understanding Contemporary China:An English Reading and Writing Textbook and the main textbook of college English reading.Firstly,the basis of textbook...Based on the ADDIE model,we explored the integration path between Understanding Contemporary China:An English Reading and Writing Textbook and the main textbook of college English reading.Firstly,the basis of textbook integration was analyzed,followed by an explanation of the overall design scheme of textbook integration,and then a series of teaching resources were initially developed and used in teaching practice.Through testing,it was found that the integrative teaching of the two sets of textbooks under the ADDIE model achieved good teaching results,and promoted the three aspects of reading literacy,disciplinary literacy,and value leadership.展开更多
文摘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.
基金Shanxi Province Higher Education Science and Technology Innovation Fund Project(2022-676)Shanxi Soft Science Program Research Fund Project(2016041008-6)。
文摘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.
文摘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.
文摘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.
文摘BACKGROUND Laparoscopic distal pancreatectomy(LDP)has emerged as the preferred approach for both benign and malignant lesions located in the pancreatic body and tail.Nevertheless,a notable deficiency persists in the absence of a standardized,procedure-specific metric for evaluating and comparing surgical quality.A composite measure termed“textbook outcome(TO)”,which encompasses key short-term endpoints,has been validated in laparoscopic pancreatoduodenectomy but has not yet been established in dedicated LDP cohorts.The definition and prediction of TO in this context could aid in facilitating cross-institutional benchmarking and fostering advancements in quality improvement.AIM To establish procedure-specific criteria for TO and identify independent predictors of TO failure in patients undergoing LDP.METHODS Consecutive patients who underwent LDP at a single high-volume pancreatic center between January 2015 and August 2022 were retrospectively analyzed.TO was defined as the absence of clinically relevant postoperative pancreatic fistula(grade B/C),post-pancreatectomy hemorrhage(grade B/C),severe complications(Clavien-Dindo≥III),readmission within 30 days,and in-hospital or 30-day mortality.Multivariable logistic regression was employed to identify independent predictors of TO failure,and a nomogram was constructed and internally validated.RESULTS Among 405 eligible patients,286(70.6%)attained TO.Multivariable analysis revealed that female sex[odds ratio(OR)=0.62,95%confidence interval(CI):0.39-0.99]conferred a protective effect,while preoperative endoscopic ultrasound-guided fine-needle aspiration(OR=2.66,95%CI:1.05-6.73),pancreatic portal hypertension(OR=2.81,95%CI:1.06-7.45),and cystic-solid(OR=2.51,95%CI:1.34-4.69)or solid lesions(OR=1.91,95%CI:1.06-3.44)were independently associated with TO failure(all P<0.05).The derived nomogram exhibited modest discrimination and calibration when assessed in both the training and validation datasets.CONCLUSION The proposed LDP-specific definition of TO is feasible and discriminative,and the developed nomogram provides an objective tool for individualized risk assessment.
基金The 2026 Annual Project for the Improvement of Educational and Research Capabilities of Primary and Secondary School Teachers in Guangdong Province titled"Breaking Boundaries,Integration,and Empowerment:Innovative Practice Research on Teacher Training Courses for the Synergy of Aesthetic Education and Moral Education"(Host:Wenjiang Zhang)。
文摘As a key carrier for the implementation of the core quality of"aesthetic creativity",the effective realization of the aesthetic value of language textbook illustrations is facing the real problems of practical disconnection and theoretical gap.Based on the theories of semiotics,embodied cognition and cultural reproduction,this paper innovatively puts forward the concept of"transformation mechanism of aesthetic education",constructs a three-phase The study analyzes the dynamic transformation process of illustrations from image symbols to students'aesthetic experience.The study explains the essential characteristics of illustration as a dual symbolic system of"likenessregulation",reveals the cognitive ladder of"perception-cognition-creation"and the path of realization of embodied cognition,and points out that the current aesthetic education of illustration has the problem of instrumentalization,and that the current aesthetic education of illustration has the problem of instrumentalization.The study points out that the current aesthetic education of illustrations is plagued by instrumental alienation,cultural hegemony and aesthetic flattening,and proposes a"three-in-one"education path from the dimensions of teachers,teaching materials and culture,including improving teachers'aesthetic education,reconstructing the principles of teaching materials and dynamic revision mechanism,and constructing classroom aesthetic education communities.The study provides new perspectives and practical guidance for exploring the aesthetic value of language textbook illustrations and bridging the gap between the theories of aesthetics and pedagogy,aiming to promote the return of aesthetic education to the nature of"reconstruction of experience",and to cultivate students'aesthetic literacy and sound personality.
文摘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.
基金Supported by National Key Research and Development Program of China (Grant No.2018YFB1700704)National Natural Science Foundation of China (Grant No.52075068)。
文摘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.
基金financially supported by the National Natural Science Foundation of China(No.61303216,No.61272457,No.U1401251,and No.61373172)the National High Technology Research and Development Program of China(863 Program)(No.2012AA013102)National 111 Program of China B16037 and B08038
文摘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.
基金the National Nat-ural Science Foundation of China under Grants 61771163the Natural Science Foundation for Out-standing Young Scholars of Heilongjiang Province un-der Grant YQ2020F001the Science and Technol-ogy on Communication Networks Laboratory under Grants SXX19641X072 and SXX18641X028.(Cor-respondence author:Min Jia)。
文摘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.
文摘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.
基金supported by the National Natural Science Foundation of China(Grant No.61309005)the Basic and Frontier Research Program of Chongqing(Grant No.cstc2014jcyj A40015)
文摘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.
基金Supported by National Key Research and Development Program,No.2022YFC2407304Major Research Project for Middle-Aged and Young Scientists of Fujian Provincial Health Commission,No.2021ZQNZD013+2 种基金The National Natural Science Foundation of China,No.62275050Fujian Province Science and Technology Innovation Joint Fund Project,No.2019Y9108Major Science and Technology Projects of Fujian Province,No.2021YZ036017.
文摘BACKGROUND To investigate the preoperative factors influencing textbook outcomes(TO)in Intrahepatic cholangiocarcinoma(ICC)patients and evaluate the feasibility of an interpretable machine learning model for preoperative prediction of TO,we developed a machine learning model for preoperative prediction of TO and used the SHapley Additive exPlanations(SHAP)technique to illustrate the prediction process.AIM To analyze the factors influencing textbook outcomes before surgery and to establish interpretable machine learning models for preoperative prediction.METHODS A total of 376 patients diagnosed with ICC were retrospectively collected from four major medical institutions in China,covering the period from 2011 to 2017.Logistic regression analysis was conducted to identify preoperative variables associated with achieving TO.Based on these variables,an EXtreme Gradient Boosting(XGBoost)machine learning prediction model was constructed using the XGBoost package.The SHAP(package:Shapviz)algorithm was employed to visualize each variable's contribution to the model's predictions.Kaplan-Meier survival analysis was performed to compare the prognostic differences between the TO-achieving and non-TO-achieving groups.RESULTS Among 376 patients,287 were included in the training group and 89 in the validation group.Logistic regression identified the following preoperative variables influencing TO:Child-Pugh classification,Eastern Cooperative Oncology Group(ECOG)score,hepatitis B,and tumor size.The XGBoost prediction model demonstrated high accuracy in internal validation(AUC=0.8825)and external validation(AUC=0.8346).Survival analysis revealed that the disease-free survival rates for patients achieving TO at 1,2,and 3 years were 64.2%,56.8%,and 43.4%,respectively.CONCLUSION Child-Pugh classification,ECOG score,hepatitis B,and tumor size are preoperative predictors of TO.In both the training group and the validation group,the machine learning model had certain effectiveness in predicting TO before surgery.The SHAP algorithm provided intuitive visualization of the machine learning prediction process,enhancing its interpretability.
基金supported by the National Key Research and Development Program of China(Grant No.2021YFC2802501)the National Natural Science Foundation of China(Grant Nos.42175154 and 42305084)+1 种基金the Hunan Provincial Natural Science Foundation of China(Grant No.2024JJ2058)Research Project of the National University of Defense Technology(Grant No.202401-YJRC-XX-030)。
文摘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.
文摘This study first analyzes four distinct forms of Fujian folk dance,highlighting the notable differences in their cultural characteristics and dance qualities.It then categorizes these dance forms to align with textbook construction,discussing in depth the principles guiding the development of textbooks that correspond to these classifications.
基金this paper is funded by Project Information:2023 Guangdong Undergraduate Colleges and Universities Teaching Quality and Teaching Reform Project Construction Project,Project Name:Action Research on Whole-area Nurturing of English Reading Teaching in Universities,Secondary and Primary Schools under the Perspective of Discipline Nurturing.Project serial number:895.
文摘“Five education”is pivotal for students’all-round development.However,primary English teaching currently faces challenges including the superficial implementation of“Five education”.This study employed action research to explore practical methods for integrating English picture book with textbook to implement“Five education”.Through two rounds of iterative action research,a three-stage activity-based teaching path was developed and refined,enabling the progressive infusion of“Five education”objectives across the learning cycle.Findings demonstrated that this integrated approach-particularly when supported by strategies such as picture book background videos and audio-edited narrative connections-effectively deepened the implementation of“Five education”,mitigated student reading fatigue,and significantly improved students’reading fluency and labor initiative,thus provided a replicable practical paradigm for realizing“Five education simultaneously”.
文摘BACKGROUND Textbook outcome(TO),an emerging composite metric for surgical quality assessment,has recently gained recognition for evaluating perioperative results.Laparoscopic transcystic common bile duct exploration(LTCBDE)has become a widely adopted minimally invasive technique for treating cholecystolithiasis with choledocholithiasis.Despite its growing clinical application,TO has not yet been formally defined for LTCBDE,nor have its failure-associated risk factors been systematically examined.AIM To define TO for LTCBDE,establish standardized criteria,and identify risk factors for TO failure via logistic regression.METHODS A retrospective cohort of 388 patients who underwent LTCBDE in combination with laparoscopic cholecystectomy at the Department of Biliopancreatic Surgery,Tongji Hospital,from January 2018 to October 2024,was analyzed.The study delineated TO criteria for LTCBDE,calculated the rate of TO achievement,and employed logistic regression to determine independent predictors of TO failure.RESULTS TO was defined as the absence of the following seven criteria:Conversion to open surgery,postoperative complications(Clavien-Dindo grade≥2),biliary leakage(International Study Group of Pancreatic Surgery/International Study Group of Liver Surgery grade B/C),delayed removal of drainage tube(>4 days),postoperative interventions,prolonged length of stay(>7 days),and 30-day readmission or mortality.Among 388 patients,276(71.1%)achieved TO.The primary causes of TO failure included delayed removal of drainage tube(94 cases,83.9%),prolonged length of stay(50 cases,44.6%).Multivariate analysis revealed four independent risk factors for TO failure:Preoperative endoscopic retrograde cholangiopancreatography(P=0.022),advanced age(P=0.010),prolonged anesthesia time(P<0.001),and elevated preoperative alkaline phosphatase levels(P=0.048).These findings suggest that applying the concept of TO to LTCBDE enhances surgical quality evaluation and supports early identification of high-risk patients,facilitating personalized clinical decisions and optimizing individual management.
基金funded by Project Information:2022 Guangzhou Municipal Higher Education Teaching Research and Reform Key Research Project:“Innovation and Practice of English Reading Curriculum Ideological and Political in Colleges and Universities:A Study on the Integration of Understanding Contemporary China:An English Reading and Writing Textbook and English Reading Teaching”(2023JGZDXM001).
文摘Based on the ADDIE model,we explored the integration path between Understanding Contemporary China:An English Reading and Writing Textbook and the main textbook of college English reading.Firstly,the basis of textbook integration was analyzed,followed by an explanation of the overall design scheme of textbook integration,and then a series of teaching resources were initially developed and used in teaching practice.Through testing,it was found that the integrative teaching of the two sets of textbooks under the ADDIE model achieved good teaching results,and promoted the three aspects of reading literacy,disciplinary literacy,and value leadership.
