Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be so...Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.展开更多
Remote sensing tools are becoming increasingly important for providing spatial information on water use by different ecosystems. Despite significant advances in remote sensing based evapotranspiration(ET) models in re...Remote sensing tools are becoming increasingly important for providing spatial information on water use by different ecosystems. Despite significant advances in remote sensing based evapotranspiration(ET) models in recent years, important information gaps still exist on the accuracy of the models particularly in arid and semi-arid environments. In this study, we evaluated the Penman-Monteith based MOD16 and the modified Priestley-Taylor(PT-JPL) models at the daily time step against three measured ET datasets. We used data from two summer and one winter rainfall sites in South Africa. One site was dominated by native broad leaf and the other by fine leafed deciduous savanna tree species and C4 grasses. The third site was in the winter rainfall Cape region and had shrubby fynbos vegetation. Actual ET was measured using open-path eddy covariance systems at the summer rainfall sites while a surface energy balance system utilizing the large aperture boundary layer scintillometer was used in the Cape. Model performance varied between sites and between years with the worst estimates(R2<0.50 and RMSE>0.80 mm/d) observed during years with prolonged mid-summer dry spells in the summer rainfall areas. Sensitivity tests on MOD16 showed that the leaf area index, surface conductance and radiation budget parameters had the largest effect on simulated ET. MOD16 ET predictions were improved by:(1) reformulating the emissivity expressions in the net radiation equation;(2) incorporating representative surface conductance values;and(3) including a soil moisture stress function in the transpiration sub-model. Implementing these changes increased the accuracy of MOD16 daily ET predictions at all sites. However, similar adjustments to the PT-JPL model yielded minimal improvements. We conclude that the MOD16 ET model has the potential to accurately predict water use in arid environments provided soil water stress and accurate biome-specific parameters are incorporated.展开更多
During a hypothetical severe accident of light water reactors,the reactor pressure vessel(RPV) could fail due to its creep under the influence of high-temperature corium.Hence,modelling of creep behavior of the RPV is...During a hypothetical severe accident of light water reactors,the reactor pressure vessel(RPV) could fail due to its creep under the influence of high-temperature corium.Hence,modelling of creep behavior of the RPV is paramount to reactor safety analysis since it predicts the transition point of accident progression from in-vessel to ex-vessel phase.In the present study we proposed a new creep model for the classical French RPV steel 16 MND5,which is adapted from the "theta-projection model" and contains all three stages of a creep process.Creep curves are expressed as a function of time with five model parameters θ_i(i=1-4 and m).A model parameter dataset was constructed by fitting experimental creep curves into this function.To correlate the creep curves for different temperatures and stress loads,we directly interpolate the model’s parameters θ_i(i=1-4 and m) from this dataset,in contrast to the conventional "theta-projection model" which employs an extra single correlation for each θ_i(i=1-4 andm),to better accommodate all experimental curves over the wide ranges of temperature and stress loads.We also put a constraint on the trend of the creep strain that it would monotonically increase with temperature and stress load.A good agreement was achieved between each experimental creep curve and corresponding model’s prediction.The widely used time-hardening and strain-hardening models were performing reasonably well in the new method.展开更多
Beyond 3G (B3G) system, the future mobile communication system, is envisioned as a user-centric, open, and convergent information infrastructure capable of providing personalized services. It is extremely important to...Beyond 3G (B3G) system, the future mobile communication system, is envisioned as a user-centric, open, and convergent information infrastructure capable of providing personalized services. It is extremely important to develop service models and architectures for B3G system. A three-dimension service model is proposed. The dimensions are identified as service support scope, service capability definition, and adaptive feature elements. Then, the hierarchical service architecture for B3G is introduced. The enabling technologies for B3G service architecture are discussed in this paper, such as Virtual Home Environment (VHE), service support environment, service openness, distributed computing, intelligent technology, and profile.展开更多
Microgrid stability analysis is a critical issue especially due to the inverters’low-inertia nature.The voltage and current control loops influences on stability are researched frequently most of which focus on mediu...Microgrid stability analysis is a critical issue especially due to the inverters’low-inertia nature.The voltage and current control loops influences on stability are researched frequently most of which focus on medium and high-frequency characteristic.Although the complete state-space model aims at low-frequency characteristic,it is too complicated and the calculation amount is huge with the scale of the microgrid increasing.One available reduced-order model of an inverter is simple,but it is suitable for only single inverter without network dynamic in microgrid.To fill in these gaps,a novel modeling method is proposed in this paper to investigate the low-frequency instability phenomenon and describe the whole DG connected system including network.In consideration of the high penetration level of induction motor(IM)loads and constant power(CP)loads in practical applications,the low-frequency mathematical model of IM and CP loads on the basis of static load is also built in this paper.Simulation and experimental results verify the effectiveness of the proposed model.展开更多
This paper discusses a comparative study of two modeling methods based on multimodel approach. The first is based on C-means clustering algorithm and the second is based on K-means clustering algorithm. The two method...This paper discusses a comparative study of two modeling methods based on multimodel approach. The first is based on C-means clustering algorithm and the second is based on K-means clustering algorithm. The two methods are experimentally applied to an induction motor. The multimodel modeling consists in representing the IM through a finite number of local models. This number of models has to be initially fixed, for which a subtractive clustering is necessary. Then both C-means and K-means clustering are exploited to determine the clusters. These clusters will be then exploited on the basis of structural and parametric identification to determine the local models that are combined, finally, to form the multimodel. The experimental study is based on MATLAB/SIMULINK environment and a DSpace scheme with DS1104 controller board. Experimental results approve that the multimodel based on K-means clustering algorithm is the most efficient.展开更多
The aim of this study was to develop an adequate mathematical model for long-term forecasting of technological progress and economic growth in the digital age (2020-2050). In addition, the task was to develop a model ...The aim of this study was to develop an adequate mathematical model for long-term forecasting of technological progress and economic growth in the digital age (2020-2050). In addition, the task was to develop a model for forecast calculations of labor productivity in the symbiosis of “man + intelligent machine”, where an intelligent machine (IM) is understood as a computer or robot equipped with elements of artificial intelligence (AI), as well as in the digital economy as a whole. In the course of the study, it was shown that in order to implement its goals the Schumpeter-Kondratiev innovation and cycle theory on forming long waves (LW) of economic development influenced by a powerful cluster of economic technologies engendered by industrial revolutions is most appropriate for a long-term forecasting of technological progress and economic growth. The Solow neoclassical model of economic growth, synchronized with LW, gives the opportunity to forecast economic dynamics of technologically advanced countries with a greater precision up to 30 years, the time which correlates with the continuation of LW. In the information and digital age, the key role among the main factors of growth (capital, labour and technological progress) is played by the latter. The authors have developed an information model which allows for forecasting technological progress basing on growth rates of endogenous technological information in economics. The main regimes of producing technological information, corresponding to the eras of information and digital economies, are given in the article, as well as the Lagrangians that engender them. The model is verified on the example of the 5<sup>th</sup> information LW for the US economy (1982-2018) and it has had highly accurate approximation for both technological progress and economic growth. A number of new results were obtained using the developed information models for forecasting technological progress. The forecasting trajectory of economic growth of developed countries (on the example of the USA) on the upward stage of the 6<sup>th</sup> LW (2018-2042), engendered by the digital technologies of the 4<sup>th</sup> Industrial Revolution is given. It is also demonstrated that the symbiosis of human and intelligent machine (IM) is the driving force in the digital economy, where man plays the leading role organizing effective and efficient mutual work. Authors suggest a mathematical model for calculating labour productivity in the digital economy, where the symbiosis of “human + IM” is widely used. The calculations carried out with the help of the model show: 1) the symbiosis of “human + IM” from the very beginning lets to realize the possibilities of increasing work performance in the economy with the help of digital technologies;2) the largest labour productivity is achieved in the symbiosis of “human + IM”, where man labour prevails, and the lowest labour productivity is seen where the largest part of the work is performed by IM;3) developed countries may achieve labour productivity of 3% per year by the mid-2020s, which has all the chances to stay up to the 2040s.展开更多
Solid phase microextraction(SPME)in combination with high-resolution mass spectrometry was employed for the determination of metabolomic profile of mouse melanoma growth within in vitro 2D,in vitro 3D,and in vivo mode...Solid phase microextraction(SPME)in combination with high-resolution mass spectrometry was employed for the determination of metabolomic profile of mouse melanoma growth within in vitro 2D,in vitro 3D,and in vivo models.Such multi-model approach had never been investigated before.Due to the low-invasiveness of SPME,it was possible to perform time-course analysis,which allowed building time profile of biochemical reactions in the studied material.Such approach does not require the multiplication of samples as subsequent analyses are performed from the very same cell culture or from the same individual.SPME already reduces the number of animals required for experiment;therefore,it is with good concordance with the 3Rs rule(replacement,reduction,and refinement).Among tested models,the largest number of compounds was found within the in vitro 2D cell culture model,while in vivo and in vitro 3D models had the lowest number of detected compounds.These results may be connected with a higher metabolic rate,as well as lower integrity of the in vitro 2D model compared to the in vitro 3D model resulting in a lower number of compounds released into medium in the latter model.In terms of in vitro-in vivo extrapolation,the in vitro 2D model performed more similar to in vivo model compared to in vitro 3D model;however,it might have been due to the fact that only compounds secreted to medium were investigated.Thus,in further experiments to obtain full metabolome information,the intraspheroidal assessment or spheroid dissociation would be necessary.展开更多
Tractor model BY 304-16 is a four-wheel-drive tractor which is of a newdesign based on model BY 284-16,and gained national assessment in April 1996.At present the product has begun to be exportedto the United States. ...Tractor model BY 304-16 is a four-wheel-drive tractor which is of a newdesign based on model BY 284-16,and gained national assessment in April 1996.At present the product has begun to be exportedto the United States. A direct injection, 3-cylinder dieselengine 395 is used in this tractor, with itsmaximum traction force reaching 9.37KN,its rated output power reaching 30HP, andits maximum output power reaching 35HP.展开更多
To enhance the stability of helicopter maneuvers during task execution,a composite trajectory tracking controller design based on the implicit model(IM)and linear active disturbance rejection control(LADRC)is proposed...To enhance the stability of helicopter maneuvers during task execution,a composite trajectory tracking controller design based on the implicit model(IM)and linear active disturbance rejection control(LADRC)is proposed.Initially,aerodynamic models of the main and tail rotor are created using the blade element theory and the uniform inflow assumption.Subsequently,a comprehensive flight dynamic model of the helicopter is established through fitting aerodynamic force fitting.Subsequently,for precise helicopter maneuvering,including the spiral,spiral up,and Ranversman maneuver,a regular trim is undertaken,followed by minor perturbation linearization at the trim point.Utilizing the linearized model,controllers are created for the IM attitude inner loop and LADRC position outer loop of the helicopter.Ultimately,a comparison is made between the maneuver trajectory tracking results of the IM‑LADRC and the conventional proportional-integral-derivative(PID)control method is performed.Experimental results demonstrate that utilizing the post-trim minor perturbation linearized model in combination with the IM‑LADRC method can achieve higher precision in tracking results,thus enhancing the accuracy of helicopter maneuver execution.展开更多
为探究直接复热、水浴复热、微波复热和汽蒸复热方式对川菜回锅肉风味的影响,该研究以智能感官技术中的电子鼻和电子舌与氨基酸分析仪和顶空气相色谱-离子迁移谱(HS-GC-IMS)相结合,对回锅肉在4种复热方式处理下的风味特征进行了系统分...为探究直接复热、水浴复热、微波复热和汽蒸复热方式对川菜回锅肉风味的影响,该研究以智能感官技术中的电子鼻和电子舌与氨基酸分析仪和顶空气相色谱-离子迁移谱(HS-GC-IMS)相结合,对回锅肉在4种复热方式处理下的风味特征进行了系统分析。结果表明,电子鼻和电子舌能有效识别回锅肉的香气与口感特征;其中微波复热显著提升了回锅肉的营养价值。该研究共检测到17种游离氨基酸,经微波复热处理后的回锅肉总游离氨基酸含量达到最高值(202.08±6.68)mg/g。偏最小二乘判别分析(partial least squares discriminant analysis,PLS-DA)模型显示直接复热与汽蒸复热之间的风味差异最显著,根据变量重要性投影(variable importance in projection,VIP)值,筛选出22种关键差异香气物质,包括1-戊烯-3-醇、顺-2-戊烯醇等,可作为区分不同复热方式回锅肉香气特征的挥发性标志物。该研究为回锅肉的复热方式提供了重要理论依据,并为进一步探究不同复热方式对回锅肉风味的影响提供了数据支持。展开更多
The analysis of Android malware shows that this threat is constantly increasing and is a real threat to mobile devices since traditional approaches,such as signature-based detection,are no longer effective due to the ...The analysis of Android malware shows that this threat is constantly increasing and is a real threat to mobile devices since traditional approaches,such as signature-based detection,are no longer effective due to the continuously advancing level of sophistication.To resolve this problem,efficient and flexible malware detection tools are needed.This work examines the possibility of employing deep CNNs to detect Android malware by transforming network traffic into image data representations.Moreover,the dataset used in this study is the CIC-AndMal2017,which contains 20,000 instances of network traffic across five distinct malware categories:a.Trojan,b.Adware,c.Ransomware,d.Spyware,e.Worm.These network traffic features are then converted to image formats for deep learning,which is applied in a CNN framework,including the VGG16 pre-trained model.In addition,our approach yielded high performance,yielding an accuracy of 0.92,accuracy of 99.1%,precision of 98.2%,recall of 99.5%,and F1 score of 98.7%.Subsequent improvements to the classification model through changes within the VGG19 framework improved the classification rate to 99.25%.Through the results obtained,it is clear that CNNs are a very effective way to classify Android malware,providing greater accuracy than conventional techniques.The success of this approach also shows the applicability of deep learning in mobile security along with the direction for the future advancement of the real-time detection system and other deeper learning techniques to counter the increasing number of threats emerging in the future.展开更多
基金Heilongjiang Provincial Natural Science Foundation of China (LH2021F009)。
文摘Anti-jamming performance evaluation has recently received significant attention. For Link-16, the anti-jamming performance evaluation and selection of the optimal anti-jamming technologies are urgent problems to be solved. A comprehensive evaluation method is proposed, which combines grey relational analysis (GRA) and cloud model, to evaluate the anti-jamming performances of Link-16. Firstly, on the basis of establishing the anti-jamming performance evaluation indicator system of Link-16, the linear combination of analytic hierarchy process(AHP) and entropy weight method (EWM) are used to calculate the combined weight. Secondly, the qualitative and quantitative concept transformation model, i.e., the cloud model, is introduced to evaluate the anti-jamming abilities of Link-16 under each jamming scheme. In addition, GRA calculates the correlation degree between evaluation indicators and the anti-jamming performance of Link-16, and assesses the best anti-jamming technology. Finally, simulation results prove that the proposed evaluation model can achieve the objective of feasible and practical evaluation, which opens up a novel way for the research of anti-jamming performance evaluations of Link-16.
基金supported by the South African Parliamentary Grant to the Council for Scientific and Industrial Research Project (ECHS014, EEEO024, ECHS058 and ECHS052)
文摘Remote sensing tools are becoming increasingly important for providing spatial information on water use by different ecosystems. Despite significant advances in remote sensing based evapotranspiration(ET) models in recent years, important information gaps still exist on the accuracy of the models particularly in arid and semi-arid environments. In this study, we evaluated the Penman-Monteith based MOD16 and the modified Priestley-Taylor(PT-JPL) models at the daily time step against three measured ET datasets. We used data from two summer and one winter rainfall sites in South Africa. One site was dominated by native broad leaf and the other by fine leafed deciduous savanna tree species and C4 grasses. The third site was in the winter rainfall Cape region and had shrubby fynbos vegetation. Actual ET was measured using open-path eddy covariance systems at the summer rainfall sites while a surface energy balance system utilizing the large aperture boundary layer scintillometer was used in the Cape. Model performance varied between sites and between years with the worst estimates(R2<0.50 and RMSE>0.80 mm/d) observed during years with prolonged mid-summer dry spells in the summer rainfall areas. Sensitivity tests on MOD16 showed that the leaf area index, surface conductance and radiation budget parameters had the largest effect on simulated ET. MOD16 ET predictions were improved by:(1) reformulating the emissivity expressions in the net radiation equation;(2) incorporating representative surface conductance values;and(3) including a soil moisture stress function in the transpiration sub-model. Implementing these changes increased the accuracy of MOD16 daily ET predictions at all sites. However, similar adjustments to the PT-JPL model yielded minimal improvements. We conclude that the MOD16 ET model has the potential to accurately predict water use in arid environments provided soil water stress and accurate biome-specific parameters are incorporated.
基金support from the research programs of APRI,ENSI and NKSsupport of the scholarship awarded by the China Scholarship Council(CSC)。
文摘During a hypothetical severe accident of light water reactors,the reactor pressure vessel(RPV) could fail due to its creep under the influence of high-temperature corium.Hence,modelling of creep behavior of the RPV is paramount to reactor safety analysis since it predicts the transition point of accident progression from in-vessel to ex-vessel phase.In the present study we proposed a new creep model for the classical French RPV steel 16 MND5,which is adapted from the "theta-projection model" and contains all three stages of a creep process.Creep curves are expressed as a function of time with five model parameters θ_i(i=1-4 and m).A model parameter dataset was constructed by fitting experimental creep curves into this function.To correlate the creep curves for different temperatures and stress loads,we directly interpolate the model’s parameters θ_i(i=1-4 and m) from this dataset,in contrast to the conventional "theta-projection model" which employs an extra single correlation for each θ_i(i=1-4 andm),to better accommodate all experimental curves over the wide ranges of temperature and stress loads.We also put a constraint on the trend of the creep strain that it would monotonically increase with temperature and stress load.A good agreement was achieved between each experimental creep curve and corresponding model’s prediction.The widely used time-hardening and strain-hardening models were performing reasonably well in the new method.
基金Project ofNational "863" Plan of China (No.2004AA119030)
文摘Beyond 3G (B3G) system, the future mobile communication system, is envisioned as a user-centric, open, and convergent information infrastructure capable of providing personalized services. It is extremely important to develop service models and architectures for B3G system. A three-dimension service model is proposed. The dimensions are identified as service support scope, service capability definition, and adaptive feature elements. Then, the hierarchical service architecture for B3G is introduced. The enabling technologies for B3G service architecture are discussed in this paper, such as Virtual Home Environment (VHE), service support environment, service openness, distributed computing, intelligent technology, and profile.
基金This work was supported by the National key research and development plan 2016YFB0900300National Natural Science Foundation of China under Grant51677162Natural Science Foundation of Hebei Province E2017203337。
文摘Microgrid stability analysis is a critical issue especially due to the inverters’low-inertia nature.The voltage and current control loops influences on stability are researched frequently most of which focus on medium and high-frequency characteristic.Although the complete state-space model aims at low-frequency characteristic,it is too complicated and the calculation amount is huge with the scale of the microgrid increasing.One available reduced-order model of an inverter is simple,but it is suitable for only single inverter without network dynamic in microgrid.To fill in these gaps,a novel modeling method is proposed in this paper to investigate the low-frequency instability phenomenon and describe the whole DG connected system including network.In consideration of the high penetration level of induction motor(IM)loads and constant power(CP)loads in practical applications,the low-frequency mathematical model of IM and CP loads on the basis of static load is also built in this paper.Simulation and experimental results verify the effectiveness of the proposed model.
文摘This paper discusses a comparative study of two modeling methods based on multimodel approach. The first is based on C-means clustering algorithm and the second is based on K-means clustering algorithm. The two methods are experimentally applied to an induction motor. The multimodel modeling consists in representing the IM through a finite number of local models. This number of models has to be initially fixed, for which a subtractive clustering is necessary. Then both C-means and K-means clustering are exploited to determine the clusters. These clusters will be then exploited on the basis of structural and parametric identification to determine the local models that are combined, finally, to form the multimodel. The experimental study is based on MATLAB/SIMULINK environment and a DSpace scheme with DS1104 controller board. Experimental results approve that the multimodel based on K-means clustering algorithm is the most efficient.
文摘The aim of this study was to develop an adequate mathematical model for long-term forecasting of technological progress and economic growth in the digital age (2020-2050). In addition, the task was to develop a model for forecast calculations of labor productivity in the symbiosis of “man + intelligent machine”, where an intelligent machine (IM) is understood as a computer or robot equipped with elements of artificial intelligence (AI), as well as in the digital economy as a whole. In the course of the study, it was shown that in order to implement its goals the Schumpeter-Kondratiev innovation and cycle theory on forming long waves (LW) of economic development influenced by a powerful cluster of economic technologies engendered by industrial revolutions is most appropriate for a long-term forecasting of technological progress and economic growth. The Solow neoclassical model of economic growth, synchronized with LW, gives the opportunity to forecast economic dynamics of technologically advanced countries with a greater precision up to 30 years, the time which correlates with the continuation of LW. In the information and digital age, the key role among the main factors of growth (capital, labour and technological progress) is played by the latter. The authors have developed an information model which allows for forecasting technological progress basing on growth rates of endogenous technological information in economics. The main regimes of producing technological information, corresponding to the eras of information and digital economies, are given in the article, as well as the Lagrangians that engender them. The model is verified on the example of the 5<sup>th</sup> information LW for the US economy (1982-2018) and it has had highly accurate approximation for both technological progress and economic growth. A number of new results were obtained using the developed information models for forecasting technological progress. The forecasting trajectory of economic growth of developed countries (on the example of the USA) on the upward stage of the 6<sup>th</sup> LW (2018-2042), engendered by the digital technologies of the 4<sup>th</sup> Industrial Revolution is given. It is also demonstrated that the symbiosis of human and intelligent machine (IM) is the driving force in the digital economy, where man plays the leading role organizing effective and efficient mutual work. Authors suggest a mathematical model for calculating labour productivity in the digital economy, where the symbiosis of “human + IM” is widely used. The calculations carried out with the help of the model show: 1) the symbiosis of “human + IM” from the very beginning lets to realize the possibilities of increasing work performance in the economy with the help of digital technologies;2) the largest labour productivity is achieved in the symbiosis of “human + IM”, where man labour prevails, and the lowest labour productivity is seen where the largest part of the work is performed by IM;3) developed countries may achieve labour productivity of 3% per year by the mid-2020s, which has all the chances to stay up to the 2040s.
基金This work has been funded by the statutory grant from Nicolaus Copernicus University(Grant No.:451).
文摘Solid phase microextraction(SPME)in combination with high-resolution mass spectrometry was employed for the determination of metabolomic profile of mouse melanoma growth within in vitro 2D,in vitro 3D,and in vivo models.Such multi-model approach had never been investigated before.Due to the low-invasiveness of SPME,it was possible to perform time-course analysis,which allowed building time profile of biochemical reactions in the studied material.Such approach does not require the multiplication of samples as subsequent analyses are performed from the very same cell culture or from the same individual.SPME already reduces the number of animals required for experiment;therefore,it is with good concordance with the 3Rs rule(replacement,reduction,and refinement).Among tested models,the largest number of compounds was found within the in vitro 2D cell culture model,while in vivo and in vitro 3D models had the lowest number of detected compounds.These results may be connected with a higher metabolic rate,as well as lower integrity of the in vitro 2D model compared to the in vitro 3D model resulting in a lower number of compounds released into medium in the latter model.In terms of in vitro-in vivo extrapolation,the in vitro 2D model performed more similar to in vivo model compared to in vitro 3D model;however,it might have been due to the fact that only compounds secreted to medium were investigated.Thus,in further experiments to obtain full metabolome information,the intraspheroidal assessment or spheroid dissociation would be necessary.
文摘Tractor model BY 304-16 is a four-wheel-drive tractor which is of a newdesign based on model BY 284-16,and gained national assessment in April 1996.At present the product has begun to be exportedto the United States. A direct injection, 3-cylinder dieselengine 395 is used in this tractor, with itsmaximum traction force reaching 9.37KN,its rated output power reaching 30HP, andits maximum output power reaching 35HP.
基金supported in part by the National Natural Science Foundation of China(No.12032012)the Key Discipline Construction Project of Colleges and Universities in Jiangsu Province.
文摘To enhance the stability of helicopter maneuvers during task execution,a composite trajectory tracking controller design based on the implicit model(IM)and linear active disturbance rejection control(LADRC)is proposed.Initially,aerodynamic models of the main and tail rotor are created using the blade element theory and the uniform inflow assumption.Subsequently,a comprehensive flight dynamic model of the helicopter is established through fitting aerodynamic force fitting.Subsequently,for precise helicopter maneuvering,including the spiral,spiral up,and Ranversman maneuver,a regular trim is undertaken,followed by minor perturbation linearization at the trim point.Utilizing the linearized model,controllers are created for the IM attitude inner loop and LADRC position outer loop of the helicopter.Ultimately,a comparison is made between the maneuver trajectory tracking results of the IM‑LADRC and the conventional proportional-integral-derivative(PID)control method is performed.Experimental results demonstrate that utilizing the post-trim minor perturbation linearized model in combination with the IM‑LADRC method can achieve higher precision in tracking results,thus enhancing the accuracy of helicopter maneuver execution.
文摘为探究直接复热、水浴复热、微波复热和汽蒸复热方式对川菜回锅肉风味的影响,该研究以智能感官技术中的电子鼻和电子舌与氨基酸分析仪和顶空气相色谱-离子迁移谱(HS-GC-IMS)相结合,对回锅肉在4种复热方式处理下的风味特征进行了系统分析。结果表明,电子鼻和电子舌能有效识别回锅肉的香气与口感特征;其中微波复热显著提升了回锅肉的营养价值。该研究共检测到17种游离氨基酸,经微波复热处理后的回锅肉总游离氨基酸含量达到最高值(202.08±6.68)mg/g。偏最小二乘判别分析(partial least squares discriminant analysis,PLS-DA)模型显示直接复热与汽蒸复热之间的风味差异最显著,根据变量重要性投影(variable importance in projection,VIP)值,筛选出22种关键差异香气物质,包括1-戊烯-3-醇、顺-2-戊烯醇等,可作为区分不同复热方式回锅肉香气特征的挥发性标志物。该研究为回锅肉的复热方式提供了重要理论依据,并为进一步探究不同复热方式对回锅肉风味的影响提供了数据支持。
基金funded by the Deanship of Scientific Research at Princess Nourah bint Abdulrahman University,through the Research Funding Program,Grant No.(FRP-1443-15).
文摘The analysis of Android malware shows that this threat is constantly increasing and is a real threat to mobile devices since traditional approaches,such as signature-based detection,are no longer effective due to the continuously advancing level of sophistication.To resolve this problem,efficient and flexible malware detection tools are needed.This work examines the possibility of employing deep CNNs to detect Android malware by transforming network traffic into image data representations.Moreover,the dataset used in this study is the CIC-AndMal2017,which contains 20,000 instances of network traffic across five distinct malware categories:a.Trojan,b.Adware,c.Ransomware,d.Spyware,e.Worm.These network traffic features are then converted to image formats for deep learning,which is applied in a CNN framework,including the VGG16 pre-trained model.In addition,our approach yielded high performance,yielding an accuracy of 0.92,accuracy of 99.1%,precision of 98.2%,recall of 99.5%,and F1 score of 98.7%.Subsequent improvements to the classification model through changes within the VGG19 framework improved the classification rate to 99.25%.Through the results obtained,it is clear that CNNs are a very effective way to classify Android malware,providing greater accuracy than conventional techniques.The success of this approach also shows the applicability of deep learning in mobile security along with the direction for the future advancement of the real-time detection system and other deeper learning techniques to counter the increasing number of threats emerging in the future.
