Background: Chronic diseases continue to cause high morbidity and mortality in Saudi Arabia. Patients severing from diabetes mellitus, hypertension and associated complications have recently increased and most of thes...Background: Chronic diseases continue to cause high morbidity and mortality in Saudi Arabia. Patients severing from diabetes mellitus, hypertension and associated complications have recently increased and most of these patients find it extremely difficult to understand or cope with their illness. The objective of this study is to determine the level of patients’ enablement in chronic disease and its predictors. Methods: A community based cross-sectional study was conducted between December 2014 and January 2015. Six hundred and four (604) Patients attending the Chronic Disease Clinic in Alwazarat Health center were randomly selected to participate in the study. Patients aged 18 years and above, who willingly agreed to participate, were included in the study. Self-reported questionnaire was used to determine patient level of enablement. Descriptive statistics such as mean and median were calculated and binary logistic regression was employed to determine the predictors of patient’s enablement to chronic disease. Results: Our results show that five hundred and sixty five (565) out of (604) patients participated in the study with 86.6% response rate. Type 2 diabetes mellitus affecting 40.65% while hypertension affecting 37.79% of the patients in Al wazarat health center. Patient’s enablement to chronic disease was very low and ranged between 2.41 and 1.53 out of 5.0. Binary logistic regression shows that age (male: OR;0.84, 95% CI, 0.72 - 1.04, female. OR;1.04, 95% CI 0.88 - 1.39), marital status (male: OR;0.72, 95% CI 0.54 - 1.11, female: OR 1.01;95% CI 0.82 - 1.29), patient educational level and number of problems discussed with physician and consultation length between male patients and their physician were statistically significant and correlated with patients enablement to chronic disease (P < 0.05). Conclusion: This study shows that patient’s enablement in chronic disease is very low but constitutes an important arm in patients care management. It should be considered as a measurable patient outcome from healthcare services. More prospective studies on this important topic are highly recommended.展开更多
High-dimensional(HD)entanglement of photonic orbital angular momentum(OAM)is pivotal for advancing quantum communication and information processing,but its characterization remains significant challenges due to the co...High-dimensional(HD)entanglement of photonic orbital angular momentum(OAM)is pivotal for advancing quantum communication and information processing,but its characterization remains significant challenges due to the complexity of quantum state tomography and experimental limitations such as low photon counts caused by losses.Here,we propose a pre-trained physics-informed neural network(PTPINN)framework that enables efficient and rapid reconstruction of HD-OAM entangled states under low photon counts.Experimental results show that the fidelity of five-dimensional OAM entanglement reaches F=0.958±0.010 even with an exposure time as short as 50 ms.This highlights the capability of PTPINN to achieve high-precision quantum state reconstruction with limited photons,owing to its innovative designs,thus overcoming the reliance on high photon counts typical of traditional methods.Our method provides a practical and scalable solution for high-fidelity characterization of HD-OAM entanglement in environments with low photon numbers and high noise,paving the way for robust long-distance quantum information transmission.展开更多
This study investigated the application and the application value of intelligent emergency in emergency management in the big data environment.It addresses the neglect of the application value(performance)measurement ...This study investigated the application and the application value of intelligent emergency in emergency management in the big data environment.It addresses the neglect of the application value(performance)measurement of intelligent emergency,further improving the effectiveness of intelligent emergency management.First,approximately 3,900 documents from the intelligent emergency field are analyzed to determine the future research trend in intelligent emergency management.The socio-technical theory concerning technical and social systems is introduced.The emergency management system concepts of“technology enabling”and“enabling value creation”are defined according to bibliometric analysis and socio-technical theory.Second,a research framework that includes technology enabling and enabling value creation for the decision-making paradigm in emergency management according to the big data environment is constructed.A detailed analysis approach from intelligent emergency technology enabling to enabling value creation in emergency management is proposed.Finally,earthquake disasters are taken as examples,and specific analyses of the intelligent emergency enabling and enabling value creation are explored;enabling value creation is discussed based on measurable indicators.The clear concept of emergency management system technology enabling and enabling value creation,as well as the detailed analysis approach from intelligent emergency technology enabling to enabling value creation,provide a theoretical bases for scholars and practitioners to evaluate the value(performance)of intelligent emergency for the first time.展开更多
Translation regulation is an important layer of gene expression:Generation of genome-wide expression datasets at multi-omics levels in spatial,temporal,and cell-type resolution is essential for deciphering brain compl...Translation regulation is an important layer of gene expression:Generation of genome-wide expression datasets at multi-omics levels in spatial,temporal,and cell-type resolution is essential for deciphering brain complexity.Regulation of gene expression is a highly dynamic process aiming at the production of precise levels of gene products to guarantee optimal cellular function,in response to physiological cues.Speedy advances in next-generation sequencing enabled the understanding of epigenomic and transcriptomic dynamic landscapes of different brain regions along development,aging,and disease progression.However,the correlation of the“transcriptome”with protein levels is poor because numerous mRNAs are subjected to manipulation of their translation efficiency,to warrant a favorable result under certain conditions.Hence,it is widely accepted that regulation at the translation level is a vital layer of gene expression.Quantification of actively translated mRNA populations(i.e.,“translatome”)is a more reliable predictor of the“proteome”(Wang et al.,2020).展开更多
Artificial neural networks are capable of machine learning by simulating the hiera rchical structure of the human brain.To enable learning by brain and machine,it is essential to accurately identify and correct the pr...Artificial neural networks are capable of machine learning by simulating the hiera rchical structure of the human brain.To enable learning by brain and machine,it is essential to accurately identify and correct the prediction errors,referred to as credit assignment(Lillicrap et al.,2020).It is critical to develop artificial intelligence by understanding how the brain deals with credit assignment in neuroscience.展开更多
Digital avatars have become a standard feature on e-commerce platforms.As virtual hosts,they emulate human behavior,broadcast live programs without interruption,and present“Made in China”products to foreign consumer...Digital avatars have become a standard feature on e-commerce platforms.As virtual hosts,they emulate human behavior,broadcast live programs without interruption,and present“Made in China”products to foreign consumers,thanks to their proficiency in multiple languages.The impressive efficiency of these digital avatars is made possible by the colossal computing power that enables them to perform their functions.“This year,the storage requirements of the digital avatars have increased significantly,by approximately 500 times compared to last year.The current local storage capacity is no longer sufficient.”展开更多
The high-luminosity Superτ-Charm Factory(STCF)will be a crucial facility for charm-physics research,particularly for the precise measurement of electroweak parameters,measuring D^(0)-D^(-)^(0)mixing parameters,invest...The high-luminosity Superτ-Charm Factory(STCF)will be a crucial facility for charm-physics research,particularly for the precise measurement of electroweak parameters,measuring D^(0)-D^(-)^(0)mixing parameters,investigating conjugation–parity(CP)violation within the charm sector,searching for the rare and forbidden decays of charmed hadrons,and addressing other foundational questions related to charmed hadrons.With the world’s largest charm-threshold data,the STCF aims to achieve high sensitivity in studying the strong phase of neutral D mesons using quantum correlation,complementing studies at LHCb and Belle II,and contributing to the understanding of CP violations globally.The STCF will also enable world-leading precision in measuring the leptonic decays of charmed mesons and baryons,providing constraints on the Cabibbo–Kobayashi–Maskawa matrix and strong-force dynamics.Additionally,the STCF will explore charmed hadron spectroscopy.The advanced detector and clean experimental environment of the STCF will enable unprecedented precision,help address key challenges in the Standard Model,and facilitate the search for potential new physics.展开更多
Road infrastructure is facing significant digitalization challenges within the context of new infrastructure construction in China and worldwide.Among the advanced digital technologies,digital twin(DT)has gained promi...Road infrastructure is facing significant digitalization challenges within the context of new infrastructure construction in China and worldwide.Among the advanced digital technologies,digital twin(DT)has gained prominence across various engineering sectors,including the manufacturing and construction industries.Specifically,road engineering has demonstrated a growing interest in DT and has achieved promising results in DT-related applications over the past several years.This paper systematically introduces the development of DT and examines its current state in road engineering by reviewing research articles on DT-enabling technologies,such as model creation,condition sensing,data processing,and interaction,as well as its applications throughout the lifecycle of road infrastructure.The findings indicate that research has primarily focused on data perception and virtual model creation,while realtime data processing and interaction between physical and virtual models remain underexplored.DT in road engineering has been predominantly applied during the operation and maintenance phases,with limited attention given to the construction and demolition phases.Future efforts should focus on establishing uniform standards,developing innovative perception and data interaction techniques,optimizing development costs,and expanding the scope of lifecycle applications to facilitate the digital transformation of road engineering.This review provides a comprehensive overview of state-of-the-art advancements in this field and paves the way for leveraging DT in road infrastructure lifecycle management.展开更多
1.Data security in smart manufacturing The global manufacturing sector is undergoing a digital transformation as traditional systems-reliant on physical assets such as raw materials and labor-struggle to meet demands ...1.Data security in smart manufacturing The global manufacturing sector is undergoing a digital transformation as traditional systems-reliant on physical assets such as raw materials and labor-struggle to meet demands for greater flexibility and efficiency.The integration of advanced information technology facilitates smart manufacturing(SM),which optimizes production,management,and supply chains[1].展开更多
Currently,driven by the accelerated iteration of digital technologies such as big data,cloud computing,and artificial intelligence,the digital economy has become a crucial engine for generating new quality productive ...Currently,driven by the accelerated iteration of digital technologies such as big data,cloud computing,and artificial intelligence,the digital economy has become a crucial engine for generating new quality productive forces and promoting industrial upgrading.Building on a systematic review of the theoretical evolution and measurement methods of the digital economy and new quality productive forces,this paper outlines their enabling mechanisms,industrial synergy pathways,and policy practices,and summarizes regional disparities and spatial spillover effects.The main findings are as follows:First,the digital economy reshapes the traditional factor structure and significantly enhances total factor productivity through the permeation of data elements and technological innovation;Second,driven jointly by the consumer internet and the industrial internet,it optimizes supply–demand matching and service models while reducing operating costs and improving production efficiency;Third,policy environments and institutional coordination amplify the enabling effects,as evidenced notably in national big-data pilot zones and the“East Data West Computing”initiative.Looking ahead,empirical research should deepen the exploration of micro-level mechanisms and dynamic panel analyses,construct a measurement system of new quality productive forces that spans macro,meso,and micro scales,and investigate pathways for regional collaborative governance and green digital integration to address the complex challenges of the new era.展开更多
Artificial intelligence (AI) is almo st everywhere due to the rapid development of modern technology and popularity of intelligent devices.While control theory and machine learning techniques as two enabling technolog...Artificial intelligence (AI) is almo st everywhere due to the rapid development of modern technology and popularity of intelligent devices.While control theory and machine learning techniques as two enabling technologies have shown enormous power in their own right,a rapprochement of them is required to handle nonlinearity,uncertainty and scalability induced by high complexity of modern systems,huge quantity of real-time data,and large scale of agent networks.Journal of Automation and Intelligence (JAI) aims to provide a platform for researchers and practitioners from both academia and industry to exchange their ideas and present new developments across multiple disciplines relevant to automation and artificial intelligence with particular attention to machine learning.展开更多
Under the strategy of building an educational power country,the reform of higher mathematics teaching should take into account both value guidance and digital innovation.This study,guided by the“educationalist spirit...Under the strategy of building an educational power country,the reform of higher mathematics teaching should take into account both value guidance and digital innovation.This study,guided by the“educationalist spirit”,explores the integration of course ideological education into teaching and leverages digital innovation for empowerment.Analyzing the literature reveals that there is a gap in the connection between the“educationalist spirit”theory and the“digital and intelligent technology”practice.Therefore,a“spiritual guidance–technological empowerment”dual-wheel driving model is proposed,along with the corresponding framework and path.Research shows that this model can enhance teaching effectiveness and educational quality,providing an integrated path for cultivating top-notch innovative talents.展开更多
Decision Support Tool(DST)enables farmers to make site-specific crop management decisions;however,comprehensive calibration can be both costly and time-consuming.This study assessed the production and economic benefit...Decision Support Tool(DST)enables farmers to make site-specific crop management decisions;however,comprehensive calibration can be both costly and time-consuming.This study assessed the production and economic benefits of two calibrations of the Nutrient Expert(NE)tool for rice in Sri Lanka’s Alfisols:the basic calibration(Nutrient Expert Sri Lanka 1,NESL1)and the comprehensive calibration(Nutrient Expert Sri Lanka 2,NESL2).NESL1 was developed by adapting the South Indian version of NE to local conditions,while NESL2 was an updated version,using three years of data from 71 farmer fields.展开更多
A great deal of ocean sensor observation data exists, for a wide range of marine disciplines, derived from in situ and remote observing platforms, in real-time, near-real-time and delayed mode. Ocean monitoring is rou...A great deal of ocean sensor observation data exists, for a wide range of marine disciplines, derived from in situ and remote observing platforms, in real-time, near-real-time and delayed mode. Ocean monitoring is routinely completed using sensors and instruments. Standardization is the key requirement for exchanging information about ocean sensors and sensor data and for comparing and combining information from different sensor networks. One or more sensors are often physically integrated into a single ocean ‘instrument' device, which often brings in many challenges related to diverse sensor data formats, parameters units, different spatiotemporal resolution, application domains, data quality and sensors protocols. To face these challenges requires the standardization efforts aiming at facilitating the so-called Sensor Web, which making it easy to provide public access to sensor data and metadata information. In this paper, a Marine Sensor Web, based on SOA and EDA and integrating the MBARI's PUCK protocol, IEEE 1451 and OGC SWE 2.0, is illustrated with a five-layer architecture. The Web Service layer and Event Process layer are illustrated in detail with an actual example. The demo study has demonstrated that a standard-based system can be built to access sensors and marine instruments distributed globally using common Web browsers for monitoring the environment and oceanic conditions besides marine sensor data on the Web, this framework of Marine Sensor Web can also play an important role in many other domains' information integration.展开更多
文摘Background: Chronic diseases continue to cause high morbidity and mortality in Saudi Arabia. Patients severing from diabetes mellitus, hypertension and associated complications have recently increased and most of these patients find it extremely difficult to understand or cope with their illness. The objective of this study is to determine the level of patients’ enablement in chronic disease and its predictors. Methods: A community based cross-sectional study was conducted between December 2014 and January 2015. Six hundred and four (604) Patients attending the Chronic Disease Clinic in Alwazarat Health center were randomly selected to participate in the study. Patients aged 18 years and above, who willingly agreed to participate, were included in the study. Self-reported questionnaire was used to determine patient level of enablement. Descriptive statistics such as mean and median were calculated and binary logistic regression was employed to determine the predictors of patient’s enablement to chronic disease. Results: Our results show that five hundred and sixty five (565) out of (604) patients participated in the study with 86.6% response rate. Type 2 diabetes mellitus affecting 40.65% while hypertension affecting 37.79% of the patients in Al wazarat health center. Patient’s enablement to chronic disease was very low and ranged between 2.41 and 1.53 out of 5.0. Binary logistic regression shows that age (male: OR;0.84, 95% CI, 0.72 - 1.04, female. OR;1.04, 95% CI 0.88 - 1.39), marital status (male: OR;0.72, 95% CI 0.54 - 1.11, female: OR 1.01;95% CI 0.82 - 1.29), patient educational level and number of problems discussed with physician and consultation length between male patients and their physician were statistically significant and correlated with patients enablement to chronic disease (P < 0.05). Conclusion: This study shows that patient’s enablement in chronic disease is very low but constitutes an important arm in patients care management. It should be considered as a measurable patient outcome from healthcare services. More prospective studies on this important topic are highly recommended.
基金supported by the National Natural Science Foundation of China(12234009,12474328,12074196,11922406,and 12074197)。
文摘High-dimensional(HD)entanglement of photonic orbital angular momentum(OAM)is pivotal for advancing quantum communication and information processing,but its characterization remains significant challenges due to the complexity of quantum state tomography and experimental limitations such as low photon counts caused by losses.Here,we propose a pre-trained physics-informed neural network(PTPINN)framework that enables efficient and rapid reconstruction of HD-OAM entangled states under low photon counts.Experimental results show that the fidelity of five-dimensional OAM entanglement reaches F=0.958±0.010 even with an exposure time as short as 50 ms.This highlights the capability of PTPINN to achieve high-precision quantum state reconstruction with limited photons,owing to its innovative designs,thus overcoming the reliance on high photon counts typical of traditional methods.Our method provides a practical and scalable solution for high-fidelity characterization of HD-OAM entanglement in environments with low photon numbers and high noise,paving the way for robust long-distance quantum information transmission.
基金the National Natural Science Foundation of China(Grant No.:71771061).
文摘This study investigated the application and the application value of intelligent emergency in emergency management in the big data environment.It addresses the neglect of the application value(performance)measurement of intelligent emergency,further improving the effectiveness of intelligent emergency management.First,approximately 3,900 documents from the intelligent emergency field are analyzed to determine the future research trend in intelligent emergency management.The socio-technical theory concerning technical and social systems is introduced.The emergency management system concepts of“technology enabling”and“enabling value creation”are defined according to bibliometric analysis and socio-technical theory.Second,a research framework that includes technology enabling and enabling value creation for the decision-making paradigm in emergency management according to the big data environment is constructed.A detailed analysis approach from intelligent emergency technology enabling to enabling value creation in emergency management is proposed.Finally,earthquake disasters are taken as examples,and specific analyses of the intelligent emergency enabling and enabling value creation are explored;enabling value creation is discussed based on measurable indicators.The clear concept of emergency management system technology enabling and enabling value creation,as well as the detailed analysis approach from intelligent emergency technology enabling to enabling value creation,provide a theoretical bases for scholars and practitioners to evaluate the value(performance)of intelligent emergency for the first time.
基金funded by the Israel Science Foundation(grants No.1036/12 and 1228/20)(to OES).
文摘Translation regulation is an important layer of gene expression:Generation of genome-wide expression datasets at multi-omics levels in spatial,temporal,and cell-type resolution is essential for deciphering brain complexity.Regulation of gene expression is a highly dynamic process aiming at the production of precise levels of gene products to guarantee optimal cellular function,in response to physiological cues.Speedy advances in next-generation sequencing enabled the understanding of epigenomic and transcriptomic dynamic landscapes of different brain regions along development,aging,and disease progression.However,the correlation of the“transcriptome”with protein levels is poor because numerous mRNAs are subjected to manipulation of their translation efficiency,to warrant a favorable result under certain conditions.Hence,it is widely accepted that regulation at the translation level is a vital layer of gene expression.Quantification of actively translated mRNA populations(i.e.,“translatome”)is a more reliable predictor of the“proteome”(Wang et al.,2020).
基金supported by the National Natural Science Foundation of China,No.62276089。
文摘Artificial neural networks are capable of machine learning by simulating the hiera rchical structure of the human brain.To enable learning by brain and machine,it is essential to accurately identify and correct the prediction errors,referred to as credit assignment(Lillicrap et al.,2020).It is critical to develop artificial intelligence by understanding how the brain deals with credit assignment in neuroscience.
文摘Digital avatars have become a standard feature on e-commerce platforms.As virtual hosts,they emulate human behavior,broadcast live programs without interruption,and present“Made in China”products to foreign consumers,thanks to their proficiency in multiple languages.The impressive efficiency of these digital avatars is made possible by the colossal computing power that enables them to perform their functions.“This year,the storage requirements of the digital avatars have increased significantly,by approximately 500 times compared to last year.The current local storage capacity is no longer sufficient.”
文摘The high-luminosity Superτ-Charm Factory(STCF)will be a crucial facility for charm-physics research,particularly for the precise measurement of electroweak parameters,measuring D^(0)-D^(-)^(0)mixing parameters,investigating conjugation–parity(CP)violation within the charm sector,searching for the rare and forbidden decays of charmed hadrons,and addressing other foundational questions related to charmed hadrons.With the world’s largest charm-threshold data,the STCF aims to achieve high sensitivity in studying the strong phase of neutral D mesons using quantum correlation,complementing studies at LHCb and Belle II,and contributing to the understanding of CP violations globally.The STCF will also enable world-leading precision in measuring the leptonic decays of charmed mesons and baryons,providing constraints on the Cabibbo–Kobayashi–Maskawa matrix and strong-force dynamics.Additionally,the STCF will explore charmed hadron spectroscopy.The advanced detector and clean experimental environment of the STCF will enable unprecedented precision,help address key challenges in the Standard Model,and facilitate the search for potential new physics.
基金supported by the National Key Research and Development Program of China(2022YFB2602103 and 2023YFA1008900)。
文摘Road infrastructure is facing significant digitalization challenges within the context of new infrastructure construction in China and worldwide.Among the advanced digital technologies,digital twin(DT)has gained prominence across various engineering sectors,including the manufacturing and construction industries.Specifically,road engineering has demonstrated a growing interest in DT and has achieved promising results in DT-related applications over the past several years.This paper systematically introduces the development of DT and examines its current state in road engineering by reviewing research articles on DT-enabling technologies,such as model creation,condition sensing,data processing,and interaction,as well as its applications throughout the lifecycle of road infrastructure.The findings indicate that research has primarily focused on data perception and virtual model creation,while realtime data processing and interaction between physical and virtual models remain underexplored.DT in road engineering has been predominantly applied during the operation and maintenance phases,with limited attention given to the construction and demolition phases.Future efforts should focus on establishing uniform standards,developing innovative perception and data interaction techniques,optimizing development costs,and expanding the scope of lifecycle applications to facilitate the digital transformation of road engineering.This review provides a comprehensive overview of state-of-the-art advancements in this field and paves the way for leveraging DT in road infrastructure lifecycle management.
基金supported in part by the National Natural Science Foundation of China(62293511 and 62402256)in part by the Shandong Provincial Natural Science Foundation of China(ZR2024MF100)+1 种基金in part by the Taishan Scholars Program(tsqn202408239)in part by the Open Research Project of the State Key Laboratory of Industrial Control Technology,Zhejiang University,China(ICT2025B13).
文摘1.Data security in smart manufacturing The global manufacturing sector is undergoing a digital transformation as traditional systems-reliant on physical assets such as raw materials and labor-struggle to meet demands for greater flexibility and efficiency.The integration of advanced information technology facilitates smart manufacturing(SM),which optimizes production,management,and supply chains[1].
文摘Currently,driven by the accelerated iteration of digital technologies such as big data,cloud computing,and artificial intelligence,the digital economy has become a crucial engine for generating new quality productive forces and promoting industrial upgrading.Building on a systematic review of the theoretical evolution and measurement methods of the digital economy and new quality productive forces,this paper outlines their enabling mechanisms,industrial synergy pathways,and policy practices,and summarizes regional disparities and spatial spillover effects.The main findings are as follows:First,the digital economy reshapes the traditional factor structure and significantly enhances total factor productivity through the permeation of data elements and technological innovation;Second,driven jointly by the consumer internet and the industrial internet,it optimizes supply–demand matching and service models while reducing operating costs and improving production efficiency;Third,policy environments and institutional coordination amplify the enabling effects,as evidenced notably in national big-data pilot zones and the“East Data West Computing”initiative.Looking ahead,empirical research should deepen the exploration of micro-level mechanisms and dynamic panel analyses,construct a measurement system of new quality productive forces that spans macro,meso,and micro scales,and investigate pathways for regional collaborative governance and green digital integration to address the complex challenges of the new era.
文摘Artificial intelligence (AI) is almo st everywhere due to the rapid development of modern technology and popularity of intelligent devices.While control theory and machine learning techniques as two enabling technologies have shown enormous power in their own right,a rapprochement of them is required to handle nonlinearity,uncertainty and scalability induced by high complexity of modern systems,huge quantity of real-time data,and large scale of agent networks.Journal of Automation and Intelligence (JAI) aims to provide a platform for researchers and practitioners from both academia and industry to exchange their ideas and present new developments across multiple disciplines relevant to automation and artificial intelligence with particular attention to machine learning.
基金High-level talent start-up fund project of Gan Dong University,Research on Ideological and Political Education of Higher Mathematics under the Leadership of Educator Spirit(Project No.:12225000408)。
文摘Under the strategy of building an educational power country,the reform of higher mathematics teaching should take into account both value guidance and digital innovation.This study,guided by the“educationalist spirit”,explores the integration of course ideological education into teaching and leverages digital innovation for empowerment.Analyzing the literature reveals that there is a gap in the connection between the“educationalist spirit”theory and the“digital and intelligent technology”practice.Therefore,a“spiritual guidance–technological empowerment”dual-wheel driving model is proposed,along with the corresponding framework and path.Research shows that this model can enhance teaching effectiveness and educational quality,providing an integrated path for cultivating top-notch innovative talents.
基金supported by the National Research Council of Sri Lanka(Grant No.NRC TO 16-07).
文摘Decision Support Tool(DST)enables farmers to make site-specific crop management decisions;however,comprehensive calibration can be both costly and time-consuming.This study assessed the production and economic benefits of two calibrations of the Nutrient Expert(NE)tool for rice in Sri Lanka’s Alfisols:the basic calibration(Nutrient Expert Sri Lanka 1,NESL1)and the comprehensive calibration(Nutrient Expert Sri Lanka 2,NESL2).NESL1 was developed by adapting the South Indian version of NE to local conditions,while NESL2 was an updated version,using three years of data from 71 farmer fields.
基金supported by the open fund project ‘Research of Information Service of Marine Sensor Web’ (Grant No.2011002)the project ‘Research on Channel-Characteristics-Oriented Data Transmission Algorithm in USNs’ of NSF of China (Grant No.61202403)the projects ‘Research of Making Regulation of Testing Technology of Device Interface’ and ‘Development and Application of Real-Time and Long-Term Observation Network Under Nearshore and Adjacent Marine Areas’ of Public science and Technology Research Funds Projects of Ocean(Grant No.201305033-6,No.201105030)
文摘A great deal of ocean sensor observation data exists, for a wide range of marine disciplines, derived from in situ and remote observing platforms, in real-time, near-real-time and delayed mode. Ocean monitoring is routinely completed using sensors and instruments. Standardization is the key requirement for exchanging information about ocean sensors and sensor data and for comparing and combining information from different sensor networks. One or more sensors are often physically integrated into a single ocean ‘instrument' device, which often brings in many challenges related to diverse sensor data formats, parameters units, different spatiotemporal resolution, application domains, data quality and sensors protocols. To face these challenges requires the standardization efforts aiming at facilitating the so-called Sensor Web, which making it easy to provide public access to sensor data and metadata information. In this paper, a Marine Sensor Web, based on SOA and EDA and integrating the MBARI's PUCK protocol, IEEE 1451 and OGC SWE 2.0, is illustrated with a five-layer architecture. The Web Service layer and Event Process layer are illustrated in detail with an actual example. The demo study has demonstrated that a standard-based system can be built to access sensors and marine instruments distributed globally using common Web browsers for monitoring the environment and oceanic conditions besides marine sensor data on the Web, this framework of Marine Sensor Web can also play an important role in many other domains' information integration.
