The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in ...The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in regional centers for teaching and training professions will depend on the acceptance of this technology by young executive trainees. This article discusses the potential benefits of adopting AI in executive training institutions in Morocco, specifically focusing on CRMEF Casablanca Settat. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors influencing the acceptance of artificial intelligence in regional centers for teaching professions and training in Morocco. To achieve this, a structural equation modeling approach was used to quantitatively describe the impact of each factor on AI adoption, utilizing data collected from 173 young executive trainees. The results indicate that perceived ease of use, perceived usefulness, trainer influence, and personal innovativeness influence the intention to use artificial intelligence. Our research provides managers of CRMEFs with a set of practical recommendations to enhance the implementation conditions of an artificial intelligence system. It aims to understand which factors should be considered in designing an artificial intelligence system within regional centers for teaching professions and training (CRMEFs).展开更多
Based on four phases of TM images acquired in 1990, 1995, 2000 and 2005, this paper took Kitakyushu in Japan as a case study to analyze spatial change of land use landscape and corresponding effects on environmental i...Based on four phases of TM images acquired in 1990, 1995, 2000 and 2005, this paper took Kitakyushu in Japan as a case study to analyze spatial change of land use landscape and corresponding effects on environmental issues guided by landscape ecology theory in virtue of combining technology of Remote Sensing with GIS. Firstly, land use types were divided into 6 classes (farmland, mountain, forestland, water body, urban land and unused land) according to national classification standard of land use, comprehensible ability of TM image and purpose of this study. Secondly, following the theory of landscape ecology analysis, 11 typical landscape indices were abstracted to evaluate the environmental effects and spatial feature changes of land use. Research results indicated that land use has grown more and more diversified and unbalanced, human activities have disturbed the landscape more seriously. Finally, transfer matrix of Markov was applied to forecast change process of land use in the future different periods, and then potential land use changes were also simulated from 2010 to 2050. Results showed that conversion tendency for all types of land use in Kitakyushu into urban construction land were enhanced. The study was anticipated to help local authorities better understand and address a complex land use system, and develop improved land use management strategies that could better balance urban expansion and ecological conservation.展开更多
Climate effects of land use change in China as simulated by a regional climate model (RegCM2) are investigated. The model is nested in one-way mode within a global coupled atmosphere-ocean model (CSIRO R21L9 AOGCM). T...Climate effects of land use change in China as simulated by a regional climate model (RegCM2) are investigated. The model is nested in one-way mode within a global coupled atmosphere-ocean model (CSIRO R21L9 AOGCM). Two multi-year simulations, one with current land use and the other with potential vegetation cover, are conducted. Statistically significant changes of precipitation, surface air temperature, and daily maximum and daily minimum temperature are analyzed based on the difference between the two simulations. The simulated effects of land use change over China include a decrease of mean annual precipitation over Northwest China, a region with a prevalence of arid and semi-arid areas; an increase of mean annual surface air temperature over some areas; and a decrease of temperature along coastal areas. Summer mean daily maximum temperature increases in many locations, while winter mean daily minimum temperature decreases in East China and increases in Northwest China. The upper soil moisture decreases significantly across China. The results indicate that the same land use change may cause different climate effects in different regions depending on the surrounding environment and climate characteristics.展开更多
As the central component of rotating machine,the performance reliability assessment and remaining useful lifetime prediction of bearing are of crucial importance in condition-based maintenance to reduce the maintenanc...As the central component of rotating machine,the performance reliability assessment and remaining useful lifetime prediction of bearing are of crucial importance in condition-based maintenance to reduce the maintenance cost and improve the reliability.A prognostic algorithm to assess the reliability and forecast the remaining useful lifetime(RUL) of bearings was proposed,consisting of three phases.Online vibration and temperature signals of bearings in normal state were measured during the manufacturing process and the most useful time-dependent features of vibration signals were extracted based on correlation analysis(feature selection step).Time series analysis based on neural network,as an identification model,was used to predict the features of bearing vibration signals at any horizons(feature prediction step).Furthermore,according to the features,degradation factor was defined.The proportional hazard model was generated to estimate the survival function and forecast the RUL of the bearing(RUL prediction step).The positive results show that the plausibility and effectiveness of the proposed approach can facilitate bearing reliability estimation and RUL prediction.展开更多
The remaining useful life(RUL) prediction of mechanical products has been widely studied for online system performance reliability, device remanufacturing, and product safety(safety awareness and safety improvement). ...The remaining useful life(RUL) prediction of mechanical products has been widely studied for online system performance reliability, device remanufacturing, and product safety(safety awareness and safety improvement). These studies incorporated many di erent models, algorithms, and techniques for modeling and assessment. In this paper, methods of RUL assessment are summarized and expounded upon using two major methods: physics model based and data driven based methods. The advantages and disadvantages of each of these methods are deliberated and compared as well. Due to the intricacy of failure mechanism in system, and di culty in physics degradation observation, RUL assessment based on observations of performance variables turns into a science in evaluating the degradation. A modeling method from control systems, the state space model(SSM), as a first order hidden Markov, is presented. In the context of non-linear and non-Gaussian systems, the SSM methodology is capable of performing remaining life assessment by using Bayesian estimation(sequential Monte Carlo). Being e ective for non-linear and non-Gaussian dynamics, the methodology can perform the assessment recursively online for applications in CBM(condition based maintenance), PHM(prognostics and health management), remanufacturing, and system performance reliability. Finally, the discussion raises concerns regarding online sensing data for SSM modeling and assessment of RUL.展开更多
This paper presents an index system and a method for calculating the comprehensive index of land-use degree. The latest data form two projects titled "Remote sensing Macro Investigation and Dynamic Study of Natio...This paper presents an index system and a method for calculating the comprehensive index of land-use degree. The latest data form two projects titled "Remote sensing Macro Investigation and Dynamic Study of National Resources and Environment" and "Resources and Environment Database of China" have been fully applied. In addition, this paper analyzes the regularity of the regional differentiation of land-use degree in China and the socio-economic and physical factors which affect the change of land-use degree in China. The "polar" model and the "longitude-distance" model of land-use degree of China are also developed.展开更多
[目的]为揭示窟野河流域径流对土地利用变化的响应,并预测未来径流变化。[方法]以窟野河流域为研究区,基于SWAT和PLUS模型,通过2000年、2005年、2010年、2015年、2020年和预测得到的自然发展情景下2025年、2030年7期土地利用数据,定量...[目的]为揭示窟野河流域径流对土地利用变化的响应,并预测未来径流变化。[方法]以窟野河流域为研究区,基于SWAT和PLUS模型,通过2000年、2005年、2010年、2015年、2020年和预测得到的自然发展情景下2025年、2030年7期土地利用数据,定量分析径流在不同土地利用情景下的变化。[结果](1)SWAT模型率定期和验证期的R 2和NS均>0.7;PLUS模型总体精度为0.8774,Kappa系数为0.8021,2个模型在窟野河流域适用性较好;(2)2000—2020年,窟野河流域林地、建设用地面积分别增加102.92,600.90 km 2,耕地、草地、水域和未利用地分别减少277.15,366.25,40.44,19.98 km 2;(3)窟野河流域年平均径流深整体呈现“上游低,下游高,西部低,东部高”的空间分布格局;(4)在保证其他输入数据不变的情况下,改变土地利用数据,情景分析结果表明,林地、草地面积减少会促进径流,建设用地面积增加同样会促进径流;(5)自然发展情景下,2025年和2030年窟野河流域土地利用空间分布格局未发生显著变化,仍以耕地和草地为主,年平均径流量较2020年分别增加3.21%,5.00%。[结论]土地利用与径流变化关系密切,情景分析角度下,林地、草地对径流起抑制作用,建设用地对径流起促进作用。未来自然发展情景下,随土地利用变化,径流呈增加态势,研究结果可为窟野河流域的土地利用结构优化和水土资源的合理规划提供科学依据。展开更多
Nowadays, spatial simulation on land use patterns is one of the key contents of LUCC. Modeling is an important tool for simulating land use patterns due to its ability to integrate measurements of changes in land cove...Nowadays, spatial simulation on land use patterns is one of the key contents of LUCC. Modeling is an important tool for simulating land use patterns due to its ability to integrate measurements of changes in land cover and the associated drivers. The conventional regression model can only analyze the correlation between land use types and driving factors but cannot depict the spatial autocorrelation characteristics. Land uses in Yongding County, which is located in the typical karst mountain areas in northwestern Hunan province, were investigated by means of modeling the spatial autocorrelation of land use types with the purpose of deriving better spatial land use patterns on the basis of terrain characteristics and infrastructural conditions. Through incorporating components describing the spatial autocorrelation into a conventional logistic model, we constructed a regression model (Autologistic model), and used this model to simulate and analyze the spatial land use patterns in Yongding County. According to the comparison with the conventional logistic model without considering the spatial autocorrelation, this model showed better goodness and higher accuracy of fitting. The distribution of arable land, wood land, built-up land and unused land yielded areas under the ROC curves (AUC) was improved to 0.893, 0.940, 0.907 and 0.863 respectively with the autologistic model. It is argued that the improved model based on autologistic method was reasonable to a certain extent. Meanwhile, these analysis results could provide valuable information for modeling future land use change scenarios with actual conditions of local and regional land use, and the probability maps of land use types obtained from this study could also support government decision-making on land use management for Yongding County and other similar areas.展开更多
文摘The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in regional centers for teaching and training professions will depend on the acceptance of this technology by young executive trainees. This article discusses the potential benefits of adopting AI in executive training institutions in Morocco, specifically focusing on CRMEF Casablanca Settat. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors influencing the acceptance of artificial intelligence in regional centers for teaching professions and training in Morocco. To achieve this, a structural equation modeling approach was used to quantitatively describe the impact of each factor on AI adoption, utilizing data collected from 173 young executive trainees. The results indicate that perceived ease of use, perceived usefulness, trainer influence, and personal innovativeness influence the intention to use artificial intelligence. Our research provides managers of CRMEFs with a set of practical recommendations to enhance the implementation conditions of an artificial intelligence system. It aims to understand which factors should be considered in designing an artificial intelligence system within regional centers for teaching professions and training (CRMEFs).
基金Sasakawa Scientific Foundation of Japan, No.20-238 National Basic Research Program of China (973 Program), No.2006CB403200+1 种基金 National Natural Science Foundation of China, No.40261002 No.40561006
文摘Based on four phases of TM images acquired in 1990, 1995, 2000 and 2005, this paper took Kitakyushu in Japan as a case study to analyze spatial change of land use landscape and corresponding effects on environmental issues guided by landscape ecology theory in virtue of combining technology of Remote Sensing with GIS. Firstly, land use types were divided into 6 classes (farmland, mountain, forestland, water body, urban land and unused land) according to national classification standard of land use, comprehensible ability of TM image and purpose of this study. Secondly, following the theory of landscape ecology analysis, 11 typical landscape indices were abstracted to evaluate the environmental effects and spatial feature changes of land use. Research results indicated that land use has grown more and more diversified and unbalanced, human activities have disturbed the landscape more seriously. Finally, transfer matrix of Markov was applied to forecast change process of land use in the future different periods, and then potential land use changes were also simulated from 2010 to 2050. Results showed that conversion tendency for all types of land use in Kitakyushu into urban construction land were enhanced. The study was anticipated to help local authorities better understand and address a complex land use system, and develop improved land use management strategies that could better balance urban expansion and ecological conservation.
文摘Climate effects of land use change in China as simulated by a regional climate model (RegCM2) are investigated. The model is nested in one-way mode within a global coupled atmosphere-ocean model (CSIRO R21L9 AOGCM). Two multi-year simulations, one with current land use and the other with potential vegetation cover, are conducted. Statistically significant changes of precipitation, surface air temperature, and daily maximum and daily minimum temperature are analyzed based on the difference between the two simulations. The simulated effects of land use change over China include a decrease of mean annual precipitation over Northwest China, a region with a prevalence of arid and semi-arid areas; an increase of mean annual surface air temperature over some areas; and a decrease of temperature along coastal areas. Summer mean daily maximum temperature increases in many locations, while winter mean daily minimum temperature decreases in East China and increases in Northwest China. The upper soil moisture decreases significantly across China. The results indicate that the same land use change may cause different climate effects in different regions depending on the surrounding environment and climate characteristics.
基金Project(61174115)supported by the National Natural Science Foundation of ChinaProject(L2013001)supported by Scientific Research Program of Liaoning Provincial Education Department,China
文摘As the central component of rotating machine,the performance reliability assessment and remaining useful lifetime prediction of bearing are of crucial importance in condition-based maintenance to reduce the maintenance cost and improve the reliability.A prognostic algorithm to assess the reliability and forecast the remaining useful lifetime(RUL) of bearings was proposed,consisting of three phases.Online vibration and temperature signals of bearings in normal state were measured during the manufacturing process and the most useful time-dependent features of vibration signals were extracted based on correlation analysis(feature selection step).Time series analysis based on neural network,as an identification model,was used to predict the features of bearing vibration signals at any horizons(feature prediction step).Furthermore,according to the features,degradation factor was defined.The proportional hazard model was generated to estimate the survival function and forecast the RUL of the bearing(RUL prediction step).The positive results show that the plausibility and effectiveness of the proposed approach can facilitate bearing reliability estimation and RUL prediction.
基金Supported by Fundamental Research Funds for the Central Universities of China(Grant No.DUT17GF214)
文摘The remaining useful life(RUL) prediction of mechanical products has been widely studied for online system performance reliability, device remanufacturing, and product safety(safety awareness and safety improvement). These studies incorporated many di erent models, algorithms, and techniques for modeling and assessment. In this paper, methods of RUL assessment are summarized and expounded upon using two major methods: physics model based and data driven based methods. The advantages and disadvantages of each of these methods are deliberated and compared as well. Due to the intricacy of failure mechanism in system, and di culty in physics degradation observation, RUL assessment based on observations of performance variables turns into a science in evaluating the degradation. A modeling method from control systems, the state space model(SSM), as a first order hidden Markov, is presented. In the context of non-linear and non-Gaussian systems, the SSM methodology is capable of performing remaining life assessment by using Bayesian estimation(sequential Monte Carlo). Being e ective for non-linear and non-Gaussian dynamics, the methodology can perform the assessment recursively online for applications in CBM(condition based maintenance), PHM(prognostics and health management), remanufacturing, and system performance reliability. Finally, the discussion raises concerns regarding online sensing data for SSM modeling and assessment of RUL.
文摘This paper presents an index system and a method for calculating the comprehensive index of land-use degree. The latest data form two projects titled "Remote sensing Macro Investigation and Dynamic Study of National Resources and Environment" and "Resources and Environment Database of China" have been fully applied. In addition, this paper analyzes the regularity of the regional differentiation of land-use degree in China and the socio-economic and physical factors which affect the change of land-use degree in China. The "polar" model and the "longitude-distance" model of land-use degree of China are also developed.
文摘[目的]为揭示窟野河流域径流对土地利用变化的响应,并预测未来径流变化。[方法]以窟野河流域为研究区,基于SWAT和PLUS模型,通过2000年、2005年、2010年、2015年、2020年和预测得到的自然发展情景下2025年、2030年7期土地利用数据,定量分析径流在不同土地利用情景下的变化。[结果](1)SWAT模型率定期和验证期的R 2和NS均>0.7;PLUS模型总体精度为0.8774,Kappa系数为0.8021,2个模型在窟野河流域适用性较好;(2)2000—2020年,窟野河流域林地、建设用地面积分别增加102.92,600.90 km 2,耕地、草地、水域和未利用地分别减少277.15,366.25,40.44,19.98 km 2;(3)窟野河流域年平均径流深整体呈现“上游低,下游高,西部低,东部高”的空间分布格局;(4)在保证其他输入数据不变的情况下,改变土地利用数据,情景分析结果表明,林地、草地面积减少会促进径流,建设用地面积增加同样会促进径流;(5)自然发展情景下,2025年和2030年窟野河流域土地利用空间分布格局未发生显著变化,仍以耕地和草地为主,年平均径流量较2020年分别增加3.21%,5.00%。[结论]土地利用与径流变化关系密切,情景分析角度下,林地、草地对径流起抑制作用,建设用地对径流起促进作用。未来自然发展情景下,随土地利用变化,径流呈增加态势,研究结果可为窟野河流域的土地利用结构优化和水土资源的合理规划提供科学依据。
基金National High Technology Research and Development Program of China, No.2008AA12Z106 National Natural Science Foundation of China, No.40801166 No.40771198
文摘Nowadays, spatial simulation on land use patterns is one of the key contents of LUCC. Modeling is an important tool for simulating land use patterns due to its ability to integrate measurements of changes in land cover and the associated drivers. The conventional regression model can only analyze the correlation between land use types and driving factors but cannot depict the spatial autocorrelation characteristics. Land uses in Yongding County, which is located in the typical karst mountain areas in northwestern Hunan province, were investigated by means of modeling the spatial autocorrelation of land use types with the purpose of deriving better spatial land use patterns on the basis of terrain characteristics and infrastructural conditions. Through incorporating components describing the spatial autocorrelation into a conventional logistic model, we constructed a regression model (Autologistic model), and used this model to simulate and analyze the spatial land use patterns in Yongding County. According to the comparison with the conventional logistic model without considering the spatial autocorrelation, this model showed better goodness and higher accuracy of fitting. The distribution of arable land, wood land, built-up land and unused land yielded areas under the ROC curves (AUC) was improved to 0.893, 0.940, 0.907 and 0.863 respectively with the autologistic model. It is argued that the improved model based on autologistic method was reasonable to a certain extent. Meanwhile, these analysis results could provide valuable information for modeling future land use change scenarios with actual conditions of local and regional land use, and the probability maps of land use types obtained from this study could also support government decision-making on land use management for Yongding County and other similar areas.