The progress of science and technology has promoted the process of agricultural mechanization. As one of the traditional basic industries and pillar industries in our country, agriculture is closely related to the pro...The progress of science and technology has promoted the process of agricultural mechanization. As one of the traditional basic industries and pillar industries in our country, agriculture is closely related to the production, life and social stability of our people. In order to improve the level of China's agricultural mechanization more effectively and achieve better and faster development, the combination of big data technology and agricultural mechanization production and processing is implemented. In this paper, the characteristics of big data technology are analyzed at first, then the problems in the combination of big data technology and agricultural mechanization production and processing are explained, the application examples of big data technology in agricultural mechanization production and processing are given, and finally the development prospect of the application of big data technology in agricultural mechanization production and processing is prospected.展开更多
In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in...In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them.These bounding boxes are subsequently passed to a YOLOv11 classification model,which analyzes cropped images and assigns class labels.An additional counting module automatically tallies the detected fruits,offering a near-instantaneous estimation of quantity.The experimental results suggest high precision and recall for detection,high classification accuracy(across 15 classes),and near-perfect counting in real time.This paper presents a multi-stage pipeline for date fruit detection,classification,and automated counting,employing YOLOv11-based models to achieve high accuracy while maintaining real-time throughput.The results demonstrated that the detection precision exceeded 90%,the classification accuracy approached 92%,and the counting module correlated closely with the manual tallies.These findings confirm the potential of reducing manual labour and enhancing operational efficiency in post-harvesting processes.Future studies will include dataset expansion,user-centric interfaces,and integration with harvesting robotics.展开更多
Three-dimensional(3D)single molecule localization microscopy(SMLM)plays an important role in biomedical applications,but its data processing is very complicated.Deep learning is a potential tool to solve this problem....Three-dimensional(3D)single molecule localization microscopy(SMLM)plays an important role in biomedical applications,but its data processing is very complicated.Deep learning is a potential tool to solve this problem.As the state of art 3D super-resolution localization algorithm based on deep learning,FD-DeepLoc algorithm reported recently still has a gap with the expected goal of online image processing,even though it has greatly improved the data processing throughput.In this paper,a new algorithm Lite-FD-DeepLoc is developed on the basis of FD-DeepLoc algorithm to meet the online image processing requirements of 3D SMLM.This new algorithm uses the feature compression method to reduce the parameters of the model,and combines it with pipeline programming to accelerate the inference process of the deep learning model.The simulated data processing results show that the image processing speed of Lite-FD-DeepLoc is about twice as fast as that of FD-DeepLoc with a slight decrease in localization accuracy,which can realize real-time processing of 256×256 pixels size images.The results of biological experimental data processing imply that Lite-FD-DeepLoc can successfully analyze the data based on astigmatism and saddle point engineering,and the global resolution of the reconstructed image is equivalent to or even better than FD-DeepLoc algorithm.展开更多
Energy efficiency data from ethylene production equipment are of high dimension, dynamic and time sequential, so their evaluation is affected by many factors. Abnormal data from ethylene production are eliminated thro...Energy efficiency data from ethylene production equipment are of high dimension, dynamic and time sequential, so their evaluation is affected by many factors. Abnormal data from ethylene production are eliminated through consistency test, making the data consumption uniform to improve the comparability of data. Due to the limit of input and output data of decision making unit in data envelopment analysis(DEA), the energy efficiency data from the same technology in a certain year are disposed monthly using DEA. The DEA data of energy efficiency from the same technology are weighted and fused using analytic hierarchy process. The energy efficiency data from different technologies are evaluated by their relative effectiveness to find the direction of energy saving and consumption reduction.展开更多
The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1...The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1） investigate the morphological features and geological structures at the landing site; （2） integrated in-situ analysis of minerals and chemical compositions; （3） integrated exploration of the structure of the lunar interior; （4） exploration of the lunar-terrestrial space environment, lunar sur- face environment and acquire Moon-based ultraviolet astronomical observations. The Ground Research and Application System （GRAS） is in charge of data acquisition and pre-processing, management of the payload in orbit, and managing the data products and their applications. The Data Pre-processing Subsystem （DPS） is a part of GRAS. The task of DPS is the pre-processing of raw data from the eight instruments that are part of CE-3, including channel processing, unpacking, package sorting, calibration and correction, identification of geographical location, calculation of probe azimuth angle, probe zenith angle, solar azimuth angle, and solar zenith angle and so on, and conducting quality checks. These processes produce Level 0, Level 1 and Level 2 data. The computing platform of this subsystem is comprised of a high-performance computing cluster, including a real-time subsystem used for processing Level 0 data and a post-time subsystem for generating Level 1 and Level 2 data. This paper de- scribes the CE-3 data pre-processing method, the data pre-processing subsystem, data classification, data validity and data products that are used for scientific studies.展开更多
Cloud Computing as a disruptive technology, provides a dynamic, elastic and promising computing climate to tackle the challenges of big data processing and analytics. Hadoop and MapReduce are the widely used open sour...Cloud Computing as a disruptive technology, provides a dynamic, elastic and promising computing climate to tackle the challenges of big data processing and analytics. Hadoop and MapReduce are the widely used open source frameworks in Cloud Computing for storing and processing big data in the scalable fashion. Spark is the latest parallel computing engine working together with Hadoop that exceeds MapReduce performance via its in-memory computing and high level programming features. In this paper, we present our design and implementation of a productive, domain-specific big data analytics cloud platform on top of Hadoop and Spark. To increase user’s productivity, we created a variety of data processing templates to simplify the programming efforts. We have conducted experiments for its productivity and performance with a few basic but representative data processing algorithms in the petroleum industry. Geophysicists can use the platform to productively design and implement scalable seismic data processing algorithms without handling the details of data management and the complexity of parallelism. The Cloud platform generates a complete data processing application based on user’s kernel program and simple configurations, allocates resources and executes it in parallel on top of Spark and Hadoop.展开更多
The RR soybean was quantitatively detected by ABI Prism 7300 sequence detector with PCR primers and fluorescence probes were designed according to the sequences of endogenous Lectin gene and exogenous CP4-EPSPS gene, ...The RR soybean was quantitatively detected by ABI Prism 7300 sequence detector with PCR primers and fluorescence probes were designed according to the sequences of endogenous Lectin gene and exogenous CP4-EPSPS gene, and the PCR systems were based on SYBR Green I and TaqMan. The standard curve of ACt between CP4-EPSPS gene and Lectin gene of the RR soybean in standard materials was generated and a linear regression equation was obtained. Quantification methods were optimized through two different real-time PCR chemistries, i.e. SYBR Green I and TaqMan, and the RR soybean contents were quantified in five standard samples and seven highly processed products by the two assays. Both methods are proved to be specific, highly sensitive and reliable for both identification and quantification of soybean DNA. The results indicate that the two optimized PCR system can be used for the practical quantitative detection of RR soybean in highly processed products.展开更多
In the course of network supported collaborative design,the data processing plays a very vital role.Much effort has been spent in this area,and many kinds of approaches have been proposed.Based on the correlative mate...In the course of network supported collaborative design,the data processing plays a very vital role.Much effort has been spent in this area,and many kinds of approaches have been proposed.Based on the correlative materials,this paper presents extensible markup language(XML)based strategy for several important problems of data processing in network supported collaborative design,such as the representation of standard for the exchange of product model data(STEP)with XML in the product information expression and the management of XML documents using relational database.The paper gives a detailed exposition on how to clarify the mapping between XML structure and the relationship database structure and how XML-QL queries can be translated into structured query language(SQL)queries.Finally,the structure of data processing system based on XML is presented.展开更多
Before the implementation of product data management (PDM) system, person model and enterprise process model (EPM) must be firstly established. For the convenience of project management, all the related users must be ...Before the implementation of product data management (PDM) system, person model and enterprise process model (EPM) must be firstly established. For the convenience of project management, all the related users must be allocated to the “Person User Role Group” net. Based on the person model and the direction of information flow, the EPM is established subsequently. The EPM consists of several release levels, in which the access controls are defined. The EPM procedure shows the blueprint of the workflow process structure. The establishment of person model and EPM in an enterprise has been instanced at the end of this paper.展开更多
A rapidly deployable dense seismic monitoring system which is capable of transmitting acquired data in real time and analyzing data automatically is crucial in seismic hazard mitigation after a major earthquake.Howeve...A rapidly deployable dense seismic monitoring system which is capable of transmitting acquired data in real time and analyzing data automatically is crucial in seismic hazard mitigation after a major earthquake.However,it is rather difficult for current seismic nodal stations to transmit data in real time for an extended period of time,and it usually takes a great amount of time to process the acquired data manually.To monitor earthquakes in real time flexibly,we develop a mobile integrated seismic monitoring system consisting of newly developed nodal units with 4G telemetry and a real-time AI-assisted automatic data processing workflow.The integrated system is convenient for deployment and has been successfully applied in monitoring the aftershocks of the Yangbi M_(S) 6.4 earthquake occurred on May 21,2021 in Yangbi County,Dali,Yunnan in southwest China.The acquired seismic data are transmitted almost in real time through the 4G cellular network,and then processed automat-ically for event detection,positioning,magnitude calculation and source mechanism inversion.From tens of seconds to a couple of minutes at most,the final seismic attributes can be presented remotely to the end users through the integrated system.From May 27 to June 17,the real-time system has detected and located 7905 aftershocks in the Yangbi area before the internal batteries exhausted,far more than the catalog provided by China Earthquake Networks Center using the regional permanent stations.The initial application of this inte-grated real-time monitoring system is promising,and we anticipate the advent of a new era for Real-time Intelligent Array Seismology(RIAS),for better monitoring and understanding the subsurface dynamic pro-cesses caused by Earth's internal forces as well as anthropogenic activities.展开更多
In this paper, we introduce a system architecture for a patient centered mobile health monitoring (PCMHM) system that deploys different sensors to determine patients’ activities, medical conditions, and the cause of ...In this paper, we introduce a system architecture for a patient centered mobile health monitoring (PCMHM) system that deploys different sensors to determine patients’ activities, medical conditions, and the cause of an emergency event. This system combines and analyzes sensor data to produce the patients’ detailed health information in real-time. A central computational node with data analyzing capability is used for sensor data integration and analysis. In addition to medical sensors, surrounding environmental sensors are also utilized to enhance the interpretation of the data and to improve medical diagnosis. The PCMHM system has the ability to provide on-demand health information of patients via the Internet, track real-time daily activities and patients’ health condition. This system also includes the capability for assessing patients’ posture and fall detection.展开更多
Cultural and creative education products play a crucial role in modern education,as they can enhance students’creativity and cultural understanding.In the field of cultural and creative product development,Artificial...Cultural and creative education products play a crucial role in modern education,as they can enhance students’creativity and cultural understanding.In the field of cultural and creative product development,Artificial Intelligence Generated Content(AIGC)has not yet been maturely applied,while data-driven design methods can achieve personalized and efficient design outputs,thus facilitating the creative generation and rapid iteration of AIGC.This study aims to explore the application of AIGC in the development of cultural and creative education products,and to form a future-oriented design process transformation in combination with rapid output of data analysis.By building a database of cultural elements and user preferences related to educational aspects in cultural and creative education products,training the AIGC system using machine learning technology,and submitting the design drafts formed in the near term to designers for further optimization,the product is finally subjected to user feedback and market testing,with products that are highly accepted by users as the final output.The research results show that the use of AIGC can not only promote innovation in cultural and creative education products,improve design efficiency and product diversity,but also inspire more creative inspiration for designers.The advantage of data analysis further enhances the accuracy of product development and market response speed,achieving effective transformation of the design process.Moreover,this research provides valuable references for educational management in terms of resource allocation and curriculum design.展开更多
With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This...With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This study aims to explore the development strategies of real-time data analysis and decision-support systems,and analyze their application status and future development trends in various industries.The article first reviews the basic concepts and importance of real-time data analysis and decision-support systems,and then discusses in detail the key technical aspects such as system architecture,data collection and processing,analysis methods,and visualization techniques.展开更多
This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving ...This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving average behavior—SARMA(1,1)L under exponential white noise.Unlike previous works that rely on simplified models such as AR(1)or assume independence,this research derives for the first time an exact two-sided Average Run Length(ARL)formula for theModified EWMAchart under SARMA(1,1)L conditions,using a mathematically rigorous Fredholm integral approach.The derived formulas are validated against numerical integral equation(NIE)solutions,showing strong agreement and significantly reduced computational burden.Additionally,a performance comparison index(PCI)is introduced to assess the chart’s detection capability.Results demonstrate that the proposed method exhibits superior sensitivity to mean shifts in autocorrelated environments,outperforming existing approaches.The findings offer a new,efficient framework for real-time quality control in complex seasonal processes,with potential applications in environmental monitoring and intelligent manufacturing systems.展开更多
In concurrent engineering, effective process management is the key to improve the efficiency and quality of product development. Although in project management system, workflow management system and PDM system, proces...In concurrent engineering, effective process management is the key to improve the efficiency and quality of product development. Although in project management system, workflow management system and PDM system, process management functions are provided, they can not meet the needs of product development. In this paper, we integrate the project management, workflow management and product management technique together and a concurrent engineering oriented integrated product development process management system is proposed. The system structure, integrated product development model and running method are introduced. The practice proves this system is powerful in supporting product development process.展开更多
文摘The progress of science and technology has promoted the process of agricultural mechanization. As one of the traditional basic industries and pillar industries in our country, agriculture is closely related to the production, life and social stability of our people. In order to improve the level of China's agricultural mechanization more effectively and achieve better and faster development, the combination of big data technology and agricultural mechanization production and processing is implemented. In this paper, the characteristics of big data technology are analyzed at first, then the problems in the combination of big data technology and agricultural mechanization production and processing are explained, the application examples of big data technology in agricultural mechanization production and processing are given, and finally the development prospect of the application of big data technology in agricultural mechanization production and processing is prospected.
基金supported by the Deanship of Scientific Research,Vice Presidency for Graduate Studies and Scientific Research,King Faisal University,Saudi Arabia,Grant No.KFU250098.
文摘In this study,an automated multimodal system for detecting,classifying,and dating fruit was developed using a two-stage YOLOv11 pipeline.In the first stage,the YOLOv11 detection model locates individual date fruits in real time by drawing bounding boxes around them.These bounding boxes are subsequently passed to a YOLOv11 classification model,which analyzes cropped images and assigns class labels.An additional counting module automatically tallies the detected fruits,offering a near-instantaneous estimation of quantity.The experimental results suggest high precision and recall for detection,high classification accuracy(across 15 classes),and near-perfect counting in real time.This paper presents a multi-stage pipeline for date fruit detection,classification,and automated counting,employing YOLOv11-based models to achieve high accuracy while maintaining real-time throughput.The results demonstrated that the detection precision exceeded 90%,the classification accuracy approached 92%,and the counting module correlated closely with the manual tallies.These findings confirm the potential of reducing manual labour and enhancing operational efficiency in post-harvesting processes.Future studies will include dataset expansion,user-centric interfaces,and integration with harvesting robotics.
基金supported by the Start-up Fund from Hainan University(No.KYQD(ZR)-20077)。
文摘Three-dimensional(3D)single molecule localization microscopy(SMLM)plays an important role in biomedical applications,but its data processing is very complicated.Deep learning is a potential tool to solve this problem.As the state of art 3D super-resolution localization algorithm based on deep learning,FD-DeepLoc algorithm reported recently still has a gap with the expected goal of online image processing,even though it has greatly improved the data processing throughput.In this paper,a new algorithm Lite-FD-DeepLoc is developed on the basis of FD-DeepLoc algorithm to meet the online image processing requirements of 3D SMLM.This new algorithm uses the feature compression method to reduce the parameters of the model,and combines it with pipeline programming to accelerate the inference process of the deep learning model.The simulated data processing results show that the image processing speed of Lite-FD-DeepLoc is about twice as fast as that of FD-DeepLoc with a slight decrease in localization accuracy,which can realize real-time processing of 256×256 pixels size images.The results of biological experimental data processing imply that Lite-FD-DeepLoc can successfully analyze the data based on astigmatism and saddle point engineering,and the global resolution of the reconstructed image is equivalent to or even better than FD-DeepLoc algorithm.
基金Supported by the National Natural Science Foundation of China(61374166)the Doctoral Fund of Ministry of Education of China(20120010110010)the Fundamental Research Funds for the Central Universities(YS1404)
文摘Energy efficiency data from ethylene production equipment are of high dimension, dynamic and time sequential, so their evaluation is affected by many factors. Abnormal data from ethylene production are eliminated through consistency test, making the data consumption uniform to improve the comparability of data. Due to the limit of input and output data of decision making unit in data envelopment analysis(DEA), the energy efficiency data from the same technology in a certain year are disposed monthly using DEA. The DEA data of energy efficiency from the same technology are weighted and fused using analytic hierarchy process. The energy efficiency data from different technologies are evaluated by their relative effectiveness to find the direction of energy saving and consumption reduction.
文摘The Chang＇e-3 （CE-3） mission is China＇s first exploration mission on the surface of the Moon that uses a lander and a rover. Eight instruments that form the scientific payloads have the following objectives： （1） investigate the morphological features and geological structures at the landing site; （2） integrated in-situ analysis of minerals and chemical compositions; （3） integrated exploration of the structure of the lunar interior; （4） exploration of the lunar-terrestrial space environment, lunar sur- face environment and acquire Moon-based ultraviolet astronomical observations. The Ground Research and Application System （GRAS） is in charge of data acquisition and pre-processing, management of the payload in orbit, and managing the data products and their applications. The Data Pre-processing Subsystem （DPS） is a part of GRAS. The task of DPS is the pre-processing of raw data from the eight instruments that are part of CE-3, including channel processing, unpacking, package sorting, calibration and correction, identification of geographical location, calculation of probe azimuth angle, probe zenith angle, solar azimuth angle, and solar zenith angle and so on, and conducting quality checks. These processes produce Level 0, Level 1 and Level 2 data. The computing platform of this subsystem is comprised of a high-performance computing cluster, including a real-time subsystem used for processing Level 0 data and a post-time subsystem for generating Level 1 and Level 2 data. This paper de- scribes the CE-3 data pre-processing method, the data pre-processing subsystem, data classification, data validity and data products that are used for scientific studies.
文摘Cloud Computing as a disruptive technology, provides a dynamic, elastic and promising computing climate to tackle the challenges of big data processing and analytics. Hadoop and MapReduce are the widely used open source frameworks in Cloud Computing for storing and processing big data in the scalable fashion. Spark is the latest parallel computing engine working together with Hadoop that exceeds MapReduce performance via its in-memory computing and high level programming features. In this paper, we present our design and implementation of a productive, domain-specific big data analytics cloud platform on top of Hadoop and Spark. To increase user’s productivity, we created a variety of data processing templates to simplify the programming efforts. We have conducted experiments for its productivity and performance with a few basic but representative data processing algorithms in the petroleum industry. Geophysicists can use the platform to productively design and implement scalable seismic data processing algorithms without handling the details of data management and the complexity of parallelism. The Cloud platform generates a complete data processing application based on user’s kernel program and simple configurations, allocates resources and executes it in parallel on top of Spark and Hadoop.
基金Supported by the Innovative Team Funds of Northeast Agricultural University (CXT004-3-2)Foundation of Heilongjiang Educational Committee(11511030)
文摘The RR soybean was quantitatively detected by ABI Prism 7300 sequence detector with PCR primers and fluorescence probes were designed according to the sequences of endogenous Lectin gene and exogenous CP4-EPSPS gene, and the PCR systems were based on SYBR Green I and TaqMan. The standard curve of ACt between CP4-EPSPS gene and Lectin gene of the RR soybean in standard materials was generated and a linear regression equation was obtained. Quantification methods were optimized through two different real-time PCR chemistries, i.e. SYBR Green I and TaqMan, and the RR soybean contents were quantified in five standard samples and seven highly processed products by the two assays. Both methods are proved to be specific, highly sensitive and reliable for both identification and quantification of soybean DNA. The results indicate that the two optimized PCR system can be used for the practical quantitative detection of RR soybean in highly processed products.
基金supported by National High Technology Research and Development Program of China(863 Program)(No.AA420060)
文摘In the course of network supported collaborative design,the data processing plays a very vital role.Much effort has been spent in this area,and many kinds of approaches have been proposed.Based on the correlative materials,this paper presents extensible markup language(XML)based strategy for several important problems of data processing in network supported collaborative design,such as the representation of standard for the exchange of product model data(STEP)with XML in the product information expression and the management of XML documents using relational database.The paper gives a detailed exposition on how to clarify the mapping between XML structure and the relationship database structure and how XML-QL queries can be translated into structured query language(SQL)queries.Finally,the structure of data processing system based on XML is presented.
文摘Before the implementation of product data management (PDM) system, person model and enterprise process model (EPM) must be firstly established. For the convenience of project management, all the related users must be allocated to the “Person User Role Group” net. Based on the person model and the direction of information flow, the EPM is established subsequently. The EPM consists of several release levels, in which the access controls are defined. The EPM procedure shows the blueprint of the workflow process structure. The establishment of person model and EPM in an enterprise has been instanced at the end of this paper.
基金supported by the National Natural Science Foundation of China (under grants 41874048,41790464,41790462).
文摘A rapidly deployable dense seismic monitoring system which is capable of transmitting acquired data in real time and analyzing data automatically is crucial in seismic hazard mitigation after a major earthquake.However,it is rather difficult for current seismic nodal stations to transmit data in real time for an extended period of time,and it usually takes a great amount of time to process the acquired data manually.To monitor earthquakes in real time flexibly,we develop a mobile integrated seismic monitoring system consisting of newly developed nodal units with 4G telemetry and a real-time AI-assisted automatic data processing workflow.The integrated system is convenient for deployment and has been successfully applied in monitoring the aftershocks of the Yangbi M_(S) 6.4 earthquake occurred on May 21,2021 in Yangbi County,Dali,Yunnan in southwest China.The acquired seismic data are transmitted almost in real time through the 4G cellular network,and then processed automat-ically for event detection,positioning,magnitude calculation and source mechanism inversion.From tens of seconds to a couple of minutes at most,the final seismic attributes can be presented remotely to the end users through the integrated system.From May 27 to June 17,the real-time system has detected and located 7905 aftershocks in the Yangbi area before the internal batteries exhausted,far more than the catalog provided by China Earthquake Networks Center using the regional permanent stations.The initial application of this inte-grated real-time monitoring system is promising,and we anticipate the advent of a new era for Real-time Intelligent Array Seismology(RIAS),for better monitoring and understanding the subsurface dynamic pro-cesses caused by Earth's internal forces as well as anthropogenic activities.
文摘In this paper, we introduce a system architecture for a patient centered mobile health monitoring (PCMHM) system that deploys different sensors to determine patients’ activities, medical conditions, and the cause of an emergency event. This system combines and analyzes sensor data to produce the patients’ detailed health information in real-time. A central computational node with data analyzing capability is used for sensor data integration and analysis. In addition to medical sensors, surrounding environmental sensors are also utilized to enhance the interpretation of the data and to improve medical diagnosis. The PCMHM system has the ability to provide on-demand health information of patients via the Internet, track real-time daily activities and patients’ health condition. This system also includes the capability for assessing patients’ posture and fall detection.
基金2024 University Teachers Innovation Fund Project:Research on Decoding and Differentiated Innovation Strategies of Dunhuang Cultural and Creative Symbols under IP Cross-border Collaboration Background2023 Northwest Normal University“Course Ideological and Political Education”Demonstration Construction Project:DemonstrationDemonstration Course of Folk Art and Crafts.
文摘Cultural and creative education products play a crucial role in modern education,as they can enhance students’creativity and cultural understanding.In the field of cultural and creative product development,Artificial Intelligence Generated Content(AIGC)has not yet been maturely applied,while data-driven design methods can achieve personalized and efficient design outputs,thus facilitating the creative generation and rapid iteration of AIGC.This study aims to explore the application of AIGC in the development of cultural and creative education products,and to form a future-oriented design process transformation in combination with rapid output of data analysis.By building a database of cultural elements and user preferences related to educational aspects in cultural and creative education products,training the AIGC system using machine learning technology,and submitting the design drafts formed in the near term to designers for further optimization,the product is finally subjected to user feedback and market testing,with products that are highly accepted by users as the final output.The research results show that the use of AIGC can not only promote innovation in cultural and creative education products,improve design efficiency and product diversity,but also inspire more creative inspiration for designers.The advantage of data analysis further enhances the accuracy of product development and market response speed,achieving effective transformation of the design process.Moreover,this research provides valuable references for educational management in terms of resource allocation and curriculum design.
文摘With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This study aims to explore the development strategies of real-time data analysis and decision-support systems,and analyze their application status and future development trends in various industries.The article first reviews the basic concepts and importance of real-time data analysis and decision-support systems,and then discusses in detail the key technical aspects such as system architecture,data collection and processing,analysis methods,and visualization techniques.
基金financially by the National Research Council of Thailand(NRCT)under Contract No.N42A670894.
文摘This study presents an innovative development of the exponentially weighted moving average(EWMA)control chart,explicitly adapted for the examination of time series data distinguished by seasonal autoregressive moving average behavior—SARMA(1,1)L under exponential white noise.Unlike previous works that rely on simplified models such as AR(1)or assume independence,this research derives for the first time an exact two-sided Average Run Length(ARL)formula for theModified EWMAchart under SARMA(1,1)L conditions,using a mathematically rigorous Fredholm integral approach.The derived formulas are validated against numerical integral equation(NIE)solutions,showing strong agreement and significantly reduced computational burden.Additionally,a performance comparison index(PCI)is introduced to assess the chart’s detection capability.Results demonstrate that the proposed method exhibits superior sensitivity to mean shifts in autocorrelated environments,outperforming existing approaches.The findings offer a new,efficient framework for real-time quality control in complex seasonal processes,with potential applications in environmental monitoring and intelligent manufacturing systems.
文摘In concurrent engineering, effective process management is the key to improve the efficiency and quality of product development. Although in project management system, workflow management system and PDM system, process management functions are provided, they can not meet the needs of product development. In this paper, we integrate the project management, workflow management and product management technique together and a concurrent engineering oriented integrated product development process management system is proposed. The system structure, integrated product development model and running method are introduced. The practice proves this system is powerful in supporting product development process.
