Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of significant,novel,and high-impact research in the fields of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
While nuclear energy represents a low-carbon and high-efficiency energy source that plays a vital role in the global energy mix,the limitations of spent fuel reprocessing technology pose a major challenge to its susta...While nuclear energy represents a low-carbon and high-efficiency energy source that plays a vital role in the global energy mix,the limitations of spent fuel reprocessing technology pose a major challenge to its sustainable development.The PUREX(plutonium uranium redox extraction)process is currently the dominant nuclear fuel reprocessing technology in the world.However,the key extractant in this process is tributyl phosphate(TBP),which degrades under intense radiation,high temperatures,and strong acidity.This leads to the production of dibutyl phosphate,monobutyl phosphate,and other degradation byproducts,which may reduce the extraction efficiency and trigger third-phase formation and equipment corrosion.This paper systematically reviews the degradation mechanisms of TBP and its diluents,the analytical technique suitable for characterizing degradation products,and the impact of degradation products on the post-treatment process.Additionally,optimization strategies employed for suppressing third-phase formation are discussed.This study offers a theoretical foundation and technical insights in optimizing the PUREX process and ensuring the safe operation of the post-treatment process.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
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Agricultural Products Processing and Storage (ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature) is an international,pect-review ed open access journal with the a...Agricultural Products Processing and Storage (ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature) is an international,pect-review ed open access journal with the aim to offer a platform for the rapid dissemination of significant,novel,and high-impact research in the fields of agricultural product processing science,technology,engineering,and nutrition.Additio nally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and ...The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and mechanical vibration will be mixed in the original signal, which undoubtedly will affect the prediction accuracy. Therefore, in order to reduce the influence of vibration noise on the prediction accuracy, an adaptive Ensemble Empirical Mode Decomposition(EEMD) threshold filtering algorithm was applied to the original signal in this paper: the output signal was decomposed into a finite number of Intrinsic Mode Functions(IMF) from high frequency to low frequency by using the Empirical Mode Decomposition(EMD) algorithm which could effectively restrain the mode mixing phenomenon; then the demarcation point of high and low frequency IMF components were determined by Continuous Mean Square Error criterion(CMSE), the high frequency IMF components were denoised by wavelet threshold algorithm, and finally the signal was reconstructed. The algorithm was an improved algorithm based on the commonly used wavelet threshold. The two algorithms were used to denoise the original production signal respectively, the adaptive EEMD threshold filtering algorithm had significant advantages in three denoising performance indexes of signal denoising ratio, root mean square error and smoothness. The five field verification tests showed that the average error of field experiment was 1.994% and the maximum relative error was less than 3%. According to the test results, the relative error of the predicted yield per hectare was 2.97%, which was relative to the actual yield. The test results showed that the algorithm could effectively resist noise and improve the accuracy of prediction.展开更多
Lentil is a highly nutritious legume with an ample quantity of carbohydrates and good amount of proteins, minerals, vitamins, phytochemicals and fibres. Although it has been used as staple food since ancient times, it...Lentil is a highly nutritious legume with an ample quantity of carbohydrates and good amount of proteins, minerals, vitamins, phytochemicals and fibres. Although it has been used as staple food since ancient times, its usage has been limited in developed countries, especially due to the lower protein digestibility, presence of anti-nutritional factors, flatulence and poor cooking qualities. Processing of lentils including dehulling and splitting and isolation of major fractions, e.g., proteins and starches are some of the strategies that can be adopted to add value and increase consumption of these legumes. This review paper intends to provide detailed overview of lentil＇s global production, nutritional composition and processing methods of lentil. Methods of isolation/characterization of lentil protein and starch and their subsequent application in foods are also presented.展开更多
Tomatoes are one of the most important specialty crops in United States and tomato products constitute a significant part of the food industry. The quality of tomato paste and juice is evaluated through their viscosit...Tomatoes are one of the most important specialty crops in United States and tomato products constitute a significant part of the food industry. The quality of tomato paste and juice is evaluated through their viscosity, color, flavor and nutritional value. Four processing methods were selected for this study, in-cluding conventional hot break, waring blender with steam, steam injection, and high temperature with shear (HTS) in a twin-screw continuous processor. The HTS method applies high temperature with shear mixer during hot-break tomato processing that improves the efficiency of the extraction process and the resultant tomato products possessed higher consistency, viscosity, and ly-copene content. Lycopene is an excellent antioxidant with cancer-preventing properties. This work showed that HTS method, utilizing whole tomatoes, produced a superior tomato product with a better color, higher viscosity, and improved bioactive properties.展开更多
Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems,such as thermal power plants being studied in this work.Industrial processes are inherently d...Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems,such as thermal power plants being studied in this work.Industrial processes are inherently dynamic and need to be monitored using dynamic algorithms.Mainstream dynamic algorithms rely on concatenating current measurement with past data.This work proposes a new,alternative dynamic process monitoring algorithm,using dot product feature analysis(DPFA).DPFA computes the dot product of consecutive samples,thus naturally capturing the process dynamics through temporal correlation.At the same time,DPFA's online computational complexity is lower than not just existing dynamic algorithms,but also classical static algorithms(e.g.,principal component analysis and slow feature analysis).The detectability of the new algorithm is analyzed for three types of faults typically seen in process systems:sensor bias,process fault and gain change fault.Through experiments with a numerical example and real data from a thermal power plant,the DPFA algorithm is shown to be superior to the state-of-the-art methods,in terms of better monitoring performance(fault detection rate and false alarm rate)and lower computational complexity.展开更多
Observed rainfall is a very essential parameter for the analysis of rainfall,day to day weather forecast and its validation.The observed rainfall data is only available from five observatories of IMD;while no rainfall...Observed rainfall is a very essential parameter for the analysis of rainfall,day to day weather forecast and its validation.The observed rainfall data is only available from five observatories of IMD;while no rainfall data is available at various important locations in and around Delhi-NCR.However,the 24-hour rainfall data observed by Doppler Weather Radar(DWR)for entire Delhi and surrounding region(up to 150 km)is readily available in a pictorial form.In this paper,efforts have been made to derive/estimate the rainfall at desired locations using DWR hydrological products.Firstly,the rainfall at desired locations has been estimated from the precipitation accumulation product(PAC)of the DWR using image processing in Python language.After this,a linear regression model using the least square method has been developed in R language.Estimated and observed rainfall data of year 2018(July,August and September)was used to train the model.After this,the model was tested on rainfall data of year 2019(July,August and September)and validated.With the use of linear regression model,the error in mean rainfall estimation reduced by 46.58% and the error in max rainfall estimation reduced by 84.53% for the year 2019.The error in mean rainfall estimation reduced by 81.36% and the error in max rainfall estimation reduced by 33.81%for the year 2018.Thus,the rainfall can be estimated with a fair degree of accuracy at desired locations within the range of the Doppler Weather Radar using the radar rainfall products and the developed linear regression model.展开更多
The microstructure and mechanical properties of the compact strip production(CSP)processed quenching and partitioning(Q&P)steels were investigated through experimental methods to address the challenge of designing...The microstructure and mechanical properties of the compact strip production(CSP)processed quenching and partitioning(Q&P)steels were investigated through experimental methods to address the challenge of designing high-performance Q&P steels.Compared with the conventional process(CP)produced samples,with slightly reduced strength,the total elongation of the CSP produced samples was increased by nearly 7%.Microstructural analysis revealed that variations in austenite stability were not the primary cause for the differences in mechanical properties between the CSP and the CP.The CSP processed Q&P steel exhibited milder center segregation behavior in contrast to the CP processed Q&P steel.Consequently,in the CSP processed Q&P steel,a higher proportion of austenite and a lower proportion of martensite were observed at the center position,delaying the crack initiation in the central region and contributing to the enhanced ductility.The investigation into the CSP process reveals its effect on alleviation of segregation and enhancement of mechanical properties of the Q&P steel.展开更多
The net primary productivity(NPP)of forest ecosystems plays a crucial role in regulating the terrestrial carbon cycle under global climate change.While the temporal effect driven by ecosystem processes on NPP variatio...The net primary productivity(NPP)of forest ecosystems plays a crucial role in regulating the terrestrial carbon cycle under global climate change.While the temporal effect driven by ecosystem processes on NPP variations is well-documented,spatial variations(from local to regional scales)remain inadequately understood.To evaluate the scale-dependent effects of productivity,predictions from the Biome-BGC model were compared with moderate-resolution imaging spectroradiometer(MODIS)and biometric NPP data in a large temperate forest region at both local and regional levels.Linear mixed-effect models and variance partitioning analysis were used to quantify the effects of environmental heterogeneity and trait variation on simulated NPP at varying spatial scales.Results show that NPP had considerable predictability at the local scale,with a coefficient of determination(R^(2))of 0.37,but this predictability declined significantly to 0.02 at the regional scale.Environmental heterogeneity and photosynthetic traits collectively explained 94.8%of the local variation in NPP,which decreased to 86.7%regionally due to the reduced common effects among these variables.Locally,the leaf area index(LAI)predominated(34.6%),while at regional scales,the stomatal conductance and maximum carboxylation rate were more influential(41.1%).Our study suggests that environmental heterogeneity drives the photosynthetic processes that mediate NPP variations across spatial scales.Incorporating heterogeneous local conditions and trait variations into analyses could enhance future research on the relationship between climate and carbon cycles at larger scales.展开更多
Under the paradigm of Industry 5.0,intelligent manufacturing transcends mere efficiency enhancement by emphasizing human-machine collaboration,where human expertise plays a central role in assembly processes.Despite a...Under the paradigm of Industry 5.0,intelligent manufacturing transcends mere efficiency enhancement by emphasizing human-machine collaboration,where human expertise plays a central role in assembly processes.Despite advancements in intelligent and digital technologies,assembly process design still heavily relies on manual knowledge reuse,and inefficiencies and inconsistent quality in process documentation are caused.To address the aforementioned issues,this paper proposes a knowledge push method of complex product assembly process design based on distillation model-based dynamically enhanced graph and Bayesian network.First,an initial knowledge graph is constructed using a BERT-BiLSTM-CRF model trained with integrated human expertise and a fine-tuned large language model.Then,a confidence-based dynamic weighted fusion strategy is employed to achieve dynamic incremental construction of the knowledge graph with low resource consumption.Subsequently,a Bayesian network model is constructed based on the relationships between assembly components,assembly features,and operations.Bayesian network reasoning is used to push assembly process knowledge under different design requirements.Finally,the feasibility of the Bayesian network construction method and the effectiveness of Bayesian network reasoning are verified through a specific example,significantly improving the utilization of assembly process knowledge and the efficiency of assembly process design.展开更多
In order to provide certain references for further deepening the development of processing industry of agricultural products,this paper analyzed and elaborated the basic principles,construction priorities and safeguar...In order to provide certain references for further deepening the development of processing industry of agricultural products,this paper analyzed and elaborated the basic principles,construction priorities and safeguard measures of the development of deep processing industry of agricultural products in Nanchong City of Sichuan Province. Besides,it made a scientific planning for accelerating the deep processing of agricultural products in Nanchong City in 2018-2020,to ensure the full implementation of fine and deep processing of agricultural products.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
From the beginning of the 21^(st)century to 2013,the economic income of main business of agricultural products processing enterprises in China had maintained above double digits for a long time.The current traditional...From the beginning of the 21^(st)century to 2013,the economic income of main business of agricultural products processing enterprises in China had maintained above double digits for a long time.The current traditional high-speed growth will be transformed to high-quality,mediumhigh-speed development,and the development trend is in line with economic laws and macro situation characteristics.With the acceleration of spa-tial distribution and cluster development of agricultural processing industry,the late-mover advantages in the central and western regions of China are gradually emerging.With the support of Internet+and e-commerce online shopping platforms,the integrative development with related industries has been deepened.Led by the new concept of green development,the demand of processing industry of green,healthy,specific functional food(such as diabetes,hypertension and other specific groups)is booming.In the aspect of development strategy,it is appropriate to build multivariate information service platform,improve the technical cooperation platform,and provide software and hardware facilities for further development of agricultural product processing industry.Combined with local economic development advantages,resource advantages and industrial advantages and other factors,the way of differentiation,regionalization and characterization should be taken according to local conditions and following the law,so as to energize the rural revitalization.展开更多
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of significant,novel,and high-impact research in the fields of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
基金supported by the Youth Talent Project of China Nuclear Power Engineering Co.,Ltd.(KY24045).
文摘While nuclear energy represents a low-carbon and high-efficiency energy source that plays a vital role in the global energy mix,the limitations of spent fuel reprocessing technology pose a major challenge to its sustainable development.The PUREX(plutonium uranium redox extraction)process is currently the dominant nuclear fuel reprocessing technology in the world.However,the key extractant in this process is tributyl phosphate(TBP),which degrades under intense radiation,high temperatures,and strong acidity.This leads to the production of dibutyl phosphate,monobutyl phosphate,and other degradation byproducts,which may reduce the extraction efficiency and trigger third-phase formation and equipment corrosion.This paper systematically reviews the degradation mechanisms of TBP and its diluents,the analytical technique suitable for characterizing degradation products,and the impact of degradation products on the post-treatment process.Additionally,optimization strategies employed for suppressing third-phase formation are discussed.This study offers a theoretical foundation and technical insights in optimizing the PUREX process and ensuring the safe operation of the post-treatment process.
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.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘Agricultural Products Processing and Storage (ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature) is an international,pect-review ed open access journal with the aim to offer a platform for the rapid dissemination of significant,novel,and high-impact research in the fields of agricultural product processing science,technology,engineering,and nutrition.Additio nally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
基金Supported by National Science and Technology Support Program(2014BAD06B04-1-09)China Postdoctoral Fund(2016M601406)Heilongjiang Postdoctoral Fund(LBHZ15024)
文摘The grain production prediction is one of the most important links in precision agriculture. In the process of grain production prediction, mechanical noise caused by the factors of difference in field topography and mechanical vibration will be mixed in the original signal, which undoubtedly will affect the prediction accuracy. Therefore, in order to reduce the influence of vibration noise on the prediction accuracy, an adaptive Ensemble Empirical Mode Decomposition(EEMD) threshold filtering algorithm was applied to the original signal in this paper: the output signal was decomposed into a finite number of Intrinsic Mode Functions(IMF) from high frequency to low frequency by using the Empirical Mode Decomposition(EMD) algorithm which could effectively restrain the mode mixing phenomenon; then the demarcation point of high and low frequency IMF components were determined by Continuous Mean Square Error criterion(CMSE), the high frequency IMF components were denoised by wavelet threshold algorithm, and finally the signal was reconstructed. The algorithm was an improved algorithm based on the commonly used wavelet threshold. The two algorithms were used to denoise the original production signal respectively, the adaptive EEMD threshold filtering algorithm had significant advantages in three denoising performance indexes of signal denoising ratio, root mean square error and smoothness. The five field verification tests showed that the average error of field experiment was 1.994% and the maximum relative error was less than 3%. According to the test results, the relative error of the predicted yield per hectare was 2.97%, which was relative to the actual yield. The test results showed that the algorithm could effectively resist noise and improve the accuracy of prediction.
文摘Lentil is a highly nutritious legume with an ample quantity of carbohydrates and good amount of proteins, minerals, vitamins, phytochemicals and fibres. Although it has been used as staple food since ancient times, its usage has been limited in developed countries, especially due to the lower protein digestibility, presence of anti-nutritional factors, flatulence and poor cooking qualities. Processing of lentils including dehulling and splitting and isolation of major fractions, e.g., proteins and starches are some of the strategies that can be adopted to add value and increase consumption of these legumes. This review paper intends to provide detailed overview of lentil＇s global production, nutritional composition and processing methods of lentil. Methods of isolation/characterization of lentil protein and starch and their subsequent application in foods are also presented.
文摘Tomatoes are one of the most important specialty crops in United States and tomato products constitute a significant part of the food industry. The quality of tomato paste and juice is evaluated through their viscosity, color, flavor and nutritional value. Four processing methods were selected for this study, in-cluding conventional hot break, waring blender with steam, steam injection, and high temperature with shear (HTS) in a twin-screw continuous processor. The HTS method applies high temperature with shear mixer during hot-break tomato processing that improves the efficiency of the extraction process and the resultant tomato products possessed higher consistency, viscosity, and ly-copene content. Lycopene is an excellent antioxidant with cancer-preventing properties. This work showed that HTS method, utilizing whole tomatoes, produced a superior tomato product with a better color, higher viscosity, and improved bioactive properties.
基金supported in part by the National Science Fund for Distinguished Young Scholars of China(62225303)the National Natural Science Fundation of China(62303039,62433004)+2 种基金the China Postdoctoral Science Foundation(BX20230034,2023M730190)the Fundamental Research Funds for the Central Universities(buctrc202201,QNTD2023-01)the High Performance Computing Platform,College of Information Science and Technology,Beijing University of Chemical Technology
文摘Data-driven process monitoring is an effective approach to assure safe operation of modern manufacturing and energy systems,such as thermal power plants being studied in this work.Industrial processes are inherently dynamic and need to be monitored using dynamic algorithms.Mainstream dynamic algorithms rely on concatenating current measurement with past data.This work proposes a new,alternative dynamic process monitoring algorithm,using dot product feature analysis(DPFA).DPFA computes the dot product of consecutive samples,thus naturally capturing the process dynamics through temporal correlation.At the same time,DPFA's online computational complexity is lower than not just existing dynamic algorithms,but also classical static algorithms(e.g.,principal component analysis and slow feature analysis).The detectability of the new algorithm is analyzed for three types of faults typically seen in process systems:sensor bias,process fault and gain change fault.Through experiments with a numerical example and real data from a thermal power plant,the DPFA algorithm is shown to be superior to the state-of-the-art methods,in terms of better monitoring performance(fault detection rate and false alarm rate)and lower computational complexity.
文摘Observed rainfall is a very essential parameter for the analysis of rainfall,day to day weather forecast and its validation.The observed rainfall data is only available from five observatories of IMD;while no rainfall data is available at various important locations in and around Delhi-NCR.However,the 24-hour rainfall data observed by Doppler Weather Radar(DWR)for entire Delhi and surrounding region(up to 150 km)is readily available in a pictorial form.In this paper,efforts have been made to derive/estimate the rainfall at desired locations using DWR hydrological products.Firstly,the rainfall at desired locations has been estimated from the precipitation accumulation product(PAC)of the DWR using image processing in Python language.After this,a linear regression model using the least square method has been developed in R language.Estimated and observed rainfall data of year 2018(July,August and September)was used to train the model.After this,the model was tested on rainfall data of year 2019(July,August and September)and validated.With the use of linear regression model,the error in mean rainfall estimation reduced by 46.58% and the error in max rainfall estimation reduced by 84.53% for the year 2019.The error in mean rainfall estimation reduced by 81.36% and the error in max rainfall estimation reduced by 33.81%for the year 2018.Thus,the rainfall can be estimated with a fair degree of accuracy at desired locations within the range of the Doppler Weather Radar using the radar rainfall products and the developed linear regression model.
基金support from the National Key R&D Program of China(No.2021YFB3702403).
文摘The microstructure and mechanical properties of the compact strip production(CSP)processed quenching and partitioning(Q&P)steels were investigated through experimental methods to address the challenge of designing high-performance Q&P steels.Compared with the conventional process(CP)produced samples,with slightly reduced strength,the total elongation of the CSP produced samples was increased by nearly 7%.Microstructural analysis revealed that variations in austenite stability were not the primary cause for the differences in mechanical properties between the CSP and the CP.The CSP processed Q&P steel exhibited milder center segregation behavior in contrast to the CP processed Q&P steel.Consequently,in the CSP processed Q&P steel,a higher proportion of austenite and a lower proportion of martensite were observed at the center position,delaying the crack initiation in the central region and contributing to the enhanced ductility.The investigation into the CSP process reveals its effect on alleviation of segregation and enhancement of mechanical properties of the Q&P steel.
基金supported by the National Key R&D Program of China(No.2023YFF1304001-01)the Science and Technology Project of the Department of Transportation of Heilongjiang Province(No.HJK2023B024-3)the Program of National Natural Science Foundation of China(No.32371870).
文摘The net primary productivity(NPP)of forest ecosystems plays a crucial role in regulating the terrestrial carbon cycle under global climate change.While the temporal effect driven by ecosystem processes on NPP variations is well-documented,spatial variations(from local to regional scales)remain inadequately understood.To evaluate the scale-dependent effects of productivity,predictions from the Biome-BGC model were compared with moderate-resolution imaging spectroradiometer(MODIS)and biometric NPP data in a large temperate forest region at both local and regional levels.Linear mixed-effect models and variance partitioning analysis were used to quantify the effects of environmental heterogeneity and trait variation on simulated NPP at varying spatial scales.Results show that NPP had considerable predictability at the local scale,with a coefficient of determination(R^(2))of 0.37,but this predictability declined significantly to 0.02 at the regional scale.Environmental heterogeneity and photosynthetic traits collectively explained 94.8%of the local variation in NPP,which decreased to 86.7%regionally due to the reduced common effects among these variables.Locally,the leaf area index(LAI)predominated(34.6%),while at regional scales,the stomatal conductance and maximum carboxylation rate were more influential(41.1%).Our study suggests that environmental heterogeneity drives the photosynthetic processes that mediate NPP variations across spatial scales.Incorporating heterogeneous local conditions and trait variations into analyses could enhance future research on the relationship between climate and carbon cycles at larger scales.
基金Supported by National Key Research and Development Program(Grant No.2024YFB3312700)National Natural Science Foundation of China(Grant No.52405541)the Changzhou Municipal Sci&Tech Program(Grant No.CJ20241131)。
文摘Under the paradigm of Industry 5.0,intelligent manufacturing transcends mere efficiency enhancement by emphasizing human-machine collaboration,where human expertise plays a central role in assembly processes.Despite advancements in intelligent and digital technologies,assembly process design still heavily relies on manual knowledge reuse,and inefficiencies and inconsistent quality in process documentation are caused.To address the aforementioned issues,this paper proposes a knowledge push method of complex product assembly process design based on distillation model-based dynamically enhanced graph and Bayesian network.First,an initial knowledge graph is constructed using a BERT-BiLSTM-CRF model trained with integrated human expertise and a fine-tuned large language model.Then,a confidence-based dynamic weighted fusion strategy is employed to achieve dynamic incremental construction of the knowledge graph with low resource consumption.Subsequently,a Bayesian network model is constructed based on the relationships between assembly components,assembly features,and operations.Bayesian network reasoning is used to push assembly process knowledge under different design requirements.Finally,the feasibility of the Bayesian network construction method and the effectiveness of Bayesian network reasoning are verified through a specific example,significantly improving the utilization of assembly process knowledge and the efficiency of assembly process design.
基金Supported by the Project of National Modern Agriculture Demonstration Area of the Ministry of Agriculture "Nanchong City National Modern Agriculture Demonstration Area"[Nong Ji Fa(2010)22]Project of Nanchong City National Modern Agriculture Demonstration Area Agricultural Reform and Construction Pilot Demonstration Area of the Ministry of Agriculture and Ministry of Finance[Nong Cai Fa(2013)13]Project of Nanchong City Nanchong National Agricultural Science and Technology Park of Ministry of Science and Technology(Guo Ke Ban Nong(2015)9]
文摘In order to provide certain references for further deepening the development of processing industry of agricultural products,this paper analyzed and elaborated the basic principles,construction priorities and safeguard measures of the development of deep processing industry of agricultural products in Nanchong City of Sichuan Province. Besides,it made a scientific planning for accelerating the deep processing of agricultural products in Nanchong City in 2018-2020,to ensure the full implementation of fine and deep processing of agricultural products.
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.
文摘From the beginning of the 21^(st)century to 2013,the economic income of main business of agricultural products processing enterprises in China had maintained above double digits for a long time.The current traditional high-speed growth will be transformed to high-quality,mediumhigh-speed development,and the development trend is in line with economic laws and macro situation characteristics.With the acceleration of spa-tial distribution and cluster development of agricultural processing industry,the late-mover advantages in the central and western regions of China are gradually emerging.With the support of Internet+and e-commerce online shopping platforms,the integrative development with related industries has been deepened.Led by the new concept of green development,the demand of processing industry of green,healthy,specific functional food(such as diabetes,hypertension and other specific groups)is booming.In the aspect of development strategy,it is appropriate to build multivariate information service platform,improve the technical cooperation platform,and provide software and hardware facilities for further development of agricultural product processing industry.Combined with local economic development advantages,resource advantages and industrial advantages and other factors,the way of differentiation,regionalization and characterization should be taken according to local conditions and following the law,so as to energize the rural revitalization.
