As smart manufacturing and Industry 4.0 continue to evolve,fault diagnosis of mechanical equipment has become crucial for ensuring production safety and optimizing equipment utilization.To address the challenge of cro...As smart manufacturing and Industry 4.0 continue to evolve,fault diagnosis of mechanical equipment has become crucial for ensuring production safety and optimizing equipment utilization.To address the challenge of cross-domain adaptation in intelligent diagnostic models under varying operational conditions,this paper introduces the CNN-1D-KAN model,which combines a 1D Convolutional Neural Network(1D-CNN)with a Kolmogorov–Arnold Network(KAN).The novelty of this approach lies in replacing the traditional 1D-CNN’s final fully connected layer with a KANLinear layer,leveraging KAN’s advanced nonlinear processing and function approximation capabilities while maintaining the simplicity of linear transformations.Experimental results on the CWRU dataset demonstrate that,under stable load conditions,the CNN-1D-KAN model achieves high accuracy,averaging 96.67%.Furthermore,the model exhibits strong transfer generalization and robustness across varying load conditions,sustaining an average accuracy of 90.21%.When compared to traditional neural networks(e.g.,1D-CNN and Multi-Layer Perceptron)and other domain adaptation models(e.g.,KAN Convolutions and KAN),the CNN-1D-KAN consistently outperforms in both accuracy and F1 scores across diverse load scenarios.Particularly in handling complex cross-domain data,it excels in diagnostic performance.This study provides an effective solution for cross-domain fault diagnosis in Industrial Internet systems,offering a theoretical foundation to enhance the reliability and stability of intelligent manufacturing processes,thus supporting the future advancement of industrial IoT applications.展开更多
The development of next-generation electromagnetic wave(EMW)absorbers requires a shift in interface design.By employing hierarchical work function programming,we propose an approach to tune interfacial polarization dy...The development of next-generation electromagnetic wave(EMW)absorbers requires a shift in interface design.By employing hierarchical work function programming,we propose an approach to tune interfacial polarization dynamics.This method utilizes multi-gradient work functions to guide carrier migration and polarization effectively,thereby enhancing energy dissipation under alternating electromagnetic fields.Here,we constructed a 1T/2H-MoS_(2)/PPy/VS_(2) composite absorber with integrated gradient interfaces.The composite achieved a powerful absorption(RLmin)of-58.59 dB at 2.3 mm,and an effective absorption bandwidth(EAB)of 7.44 GHz at 2.5 mm,demonstrating improved broadband absorption.Radar cross-section(RCS)simulations show an EMW loss of-7.2 dB m^(2) at 0°,highlighting its potential for stealth and communication applications.This study introduces hierarchical work function programming as a promising strategy in EMW absorber design,contributing to advancements in material performance and functionality.展开更多
This study examined the relationship between inclusive leadership and authenticity at work in racial minority groups of South Africa,taking into account the mediating role of psychological safety and the moderator rol...This study examined the relationship between inclusive leadership and authenticity at work in racial minority groups of South Africa,taking into account the mediating role of psychological safety and the moderator role of gender,in that relationship.The sample was composed of 94 employees predominantly working in the professional services sector from South Africa(41.5%females;mean age=37.1),who self-identified as racial minority groups(coloured/black/Indian).Results indicate that inclusive leadership has no direct effect on authenticity at work;however,psychological safety fully mediates this relationship.Regarding the moderation effect of gender,results showed that males are more likely to diminish their self-alienation(a specific component of authenticity at work)when levels of psychological safety are higher.These results are consistent with Social Identity Theory,which posits that individuals derive part of their self-concept from their membership in social groups.In contexts where inclusive leadership fosters psychological safety,individuals(particularly men in traditionally male-dominated work environments)may feel a stronger sense of belonging and group identity,which in turn enhances their willingness to express their authentic selves and reduces self-alienation.Practical implications for companies include the need to improve leadership styles to foster more of an inclusive and psychologically safe culture,where minority groups can be authentic and flourish.展开更多
Background:As an important indicator of subjective well-being(SWB),decent work is a key guarantee for the sustainable development of teachers and their psychological health and work quality.Faced with the rapid develo...Background:As an important indicator of subjective well-being(SWB),decent work is a key guarantee for the sustainable development of teachers and their psychological health and work quality.Faced with the rapid development of artificial intelligence and the global labor market,vocational college teachers are facing challenges such as workload pressure and limited career development,which may harm their well-being.This study aims to localize the measurement method of decent work in Chinese vocational education based on the theory of the Psychology of Working Theory,and explore the relationship mechanism between organizational support,career adaptability,decent work,and job satisfaction among vocational college teachers.Methods:A cross-sectional survey was conducted with 422 HVCU teachers in China(202 male,220 female)using the localized Perceived Organizational Support Scale,Career Adaptability Scale,Decent Work Scale,and Job Satisfaction Scale.Results:The overall level of HVCU teachers’decent work was above the median(Mean=4.09,SD=0.69),laying a foundation for their SWB.Decent work significantly and positively predicted job satisfaction(β=0.620,p<0.001).Organizational support(r=0.58,p<0.001)and career adaptability(r=0.82,p<0.001)can positively affect decent work,and further improve job satisfaction(collective R2 rising from 38.3%to 41.1%).Bootstrap analysis confirmed these mediating effects were robust.Conclusions:This study confirms that the combined effects of organizational support and career adaptability can enhance decent work,further improving teachers’job satisfaction and subsequent subjective well-being.Besides,this study provides an empirical basis for improving the well-being of higher vocational teachers and the sustainable development of vocational education,and has practical significance for improving the teacher incentive policy.展开更多
In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector,the recovery of waste heat from diesel engines has become a critical area of focus.This study provided an exhausti...In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector,the recovery of waste heat from diesel engines has become a critical area of focus.This study provided an exhaustive thermodynamic analysis optimizing Organic Rankine Cycle(ORC)systems forwaste heat recovery fromdiesel engines.Thestudy assessed the performance of five candidateworking fluids—R11,R123,R113,R245fa,and R141b—under a range of operating conditions,specifically varying overheat temperatures and evaporation pressures.The results indicated that the choice of working fluid substantially influences the system’s exergetic efficiency,net output power,and thermal efficiency.R245fa showed an outstanding net output power of 30.39 kW at high overheat conditions,outperforming R11,which is significant for high-temperature waste heat recovery.At lower temperatures,R11 and R113 demonstrated higher exergetic efficiencies,with R11 reaching a peak exergetic efficiency of 7.4%at an evaporation pressure of 10 bar and an overheat of 10℃.The study also revealed that controlling the overheat and optimizing the evaporation pressure are crucial for enhancing the net output power of the ORC system.Specifically,at an evaporation pressure of 30 bar and an overheat of 0℃,R113 exhibited the lowest exergetic destruction of 544.5 kJ/kg,making it a suitable choice for minimizing irreversible losses.These findings are instrumental for understanding the performance of ORC systems in waste heat recovery applications and offer valuable insights for the design and operation of more efficient and environmentally friendly diesel engine systems.展开更多
Drogue detection is a fundamental issue during the close docking phase of autonomous aerial refueling（AAR）. To cope with this issue, a novel and effective method based on deep learning with convolutional neural netw...Drogue detection is a fundamental issue during the close docking phase of autonomous aerial refueling（AAR）. To cope with this issue, a novel and effective method based on deep learning with convolutional neural networks（CNNs） is proposed. In order to ensure its robustness and wide application, a deep learning dataset of images was prepared by utilizing real data of ‘‘Probe and Drogue＂ aerial refueling, which contains diverse drogues in various environmental conditions without artificial features placed on the drogues. By employing deep learning ideas and graphics processing units（GPUs）, a model for drogue detection using a Caffe deep learning framework with CNNs was designed to ensure the method＇s accuracy and real-time performance. Experiments were conducted to demonstrate the effectiveness of the proposed method, and results based on real AAR data compare its performance to other methods, validating the accuracy, speed, and robustness of its drogue detection ability.展开更多
In order to improve safety,economy efficiency and design automation degree of air route in terminal airspace,Three-dimensional(3D)planning of routes network is investigated.A waypoint probability search method is prop...In order to improve safety,economy efficiency and design automation degree of air route in terminal airspace,Three-dimensional(3D)planning of routes network is investigated.A waypoint probability search method is proposed to optimize individual flight path.Through updating horizontal pheromones by negative feedback factors,an antcolony algorithm of path searching in 3Dterminal airspace is implemented.The principle of optimization sequence of arrival and departure routes is analyzed.Each route is optimized successively,and the overall optimization of the whole route network is finally achieved.A case study shows that it takes about 63 sto optimize 8arrival and departure routes,and the operation efficiency can be significantly improved with desirable safety and economy.展开更多
There is a global movement calling for the integration of Western medicine（WM）and traditional Chinese medicine（TCM）[1].The World Health Organization suggests that health care would be improved by integrating tradi...There is a global movement calling for the integration of Western medicine（WM）and traditional Chinese medicine（TCM）[1].The World Health Organization suggests that health care would be improved by integrating traditional and complementary medicines into the practices of health care service delivery and self-health care[1].The WM and TCM are commonly integrated in the contemporary practice of medicine in China.展开更多
A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG tempe...A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG temperature and its gradient are set as input and the FOG bias drift is set as the expected output. A 2-5-1 network trained with IUKF algorithm is established. The IUKF algorithm is developed on the basis of the unscented Kalman filter （UKF）. The weight and bias vectors of the hidden layer are set as the state of the UKF and its process and measurement equations are deduced according to the network architecture. To solve the unavoidable estimation deviation of the mean and covariance of the states in the UKF algorithm, iterative computation is introduced into the UKF after the measurement update. While the measure- ment noise R is extended into the state vectors before iteration in order to meet the statistic orthogonality of estimate and mea- surement noise. The IUKF algorithm can provide the optimized estimation for the neural network because of its state expansion and iteration. Temperature rise （-20-20℃） and drop （70-20℃） tests for FOG are carried out in an attemperator. The temperature drift model is built with neural network, and it is trained respectively with BP, UKF and IUKF algorithms. The results prove that the proposed model has higher precision compared with the back- propagation （BP） and UKF network models.展开更多
As device-to-device(D2D) communications usually reuses the resource of cellular networks, call admission control(CAC) and power control are crucial problems. However in most power control schemes, total data rates or ...As device-to-device(D2D) communications usually reuses the resource of cellular networks, call admission control(CAC) and power control are crucial problems. However in most power control schemes, total data rates or throughput are regarded as optimization criterion. In this paper, a combining call admission control(CAC) and power control scheme under guaranteeing QoS of every user equipment(UE) is proposed. First, a simple CAC scheme is introduced. Then based on the CAC scheme, a combining call admission control and power control scheme is proposed. Next, the performance of the proposed scheme is evaluated. Finally, maximum DUE pair number and average transmitting power is calculated. Simulation results show that D2 D communications with the proposed combining call admission control and power control scheme can effectively improve the maximum DUE pair number under the premise of meeting necessary QoS.展开更多
A new thermal ring-opening polymerization technique for 1, 1, 3, 3-tetra-ph enyl-1, 3-disilacyclobutane （TPDC） based on the use of metal nanoparticles produced by pulsed laser ablation was investigated. This method ...A new thermal ring-opening polymerization technique for 1, 1, 3, 3-tetra-ph enyl-1, 3-disilacyclobutane （TPDC） based on the use of metal nanoparticles produced by pulsed laser ablation was investigated. This method facilitates the synthesis of polydiphenysilylenemethyle （PDPhSM） thin film, which is difficult to make by conventional methods because of its insolubility and high melting point. TPDC was first evaporated on silicon substrates and then exposed to metal nanoparticles deposition by pulsed laser ablation prior to heat treatment.The TPDC films with metal nanoparticles were heated in an electric furnace in air atmosphere to induce ring-opening polymerization of TPDC. The film thicknesses before and after polymerization were measured by a stylus profilometer. Since the polymerization process competes with re-evaporation of TPDC during the heating, the thickness ratio of the polymer to the monomer was defined as the polymerization efficiency, which depends greatly on the technology conditions. Therefore, a well trained radial base function neural network model was constructed to approach the complex nonlinear relationship. Moreover, a particle swarm algorithm was firstly introduced to search for an optimum technology directly from RBF neural network model. This ensures that the fabrication of thin film with appropriate properties using pulsed laser ablation requires no in-depth understanding of the entire behavior of the technology conditions.展开更多
The aim of this study is to examine the small-world properties of functional brain networks inChinese to English simultaneous interpreting(SI)using functional near-infrared spectroscopy(INIRS),In particular,the fNIRS ...The aim of this study is to examine the small-world properties of functional brain networks inChinese to English simultaneous interpreting(SI)using functional near-infrared spectroscopy(INIRS),In particular,the fNIRS neuroimaging combined with complex network analysis wasperformed to extract the features of functional brain networks underling three translationstrategies associated with Chinese to English SI:"transcoding"that takes the"shortcut"linkingtranslation equivalents between Chinese and the English,code-mixing"that basically does notinvolve blingual procesing,and"transphrasingn that takes the long route"involving amonolingual processing of meaning in Chinese and then another monolingual processing ofmeaning in English.Our results demonstrated that the small-world net work topology was able todistinguish well bet ween the transcoding,code-mixing and transphrasing strategies related toChinese to English SI.展开更多
This paper studies synchronization of all nodes in a fractional-order complex dynamic network. An adaptive control strategy for synchronizing a dynamic network is proposed. Based on the Lyapunov stability theory, this...This paper studies synchronization of all nodes in a fractional-order complex dynamic network. An adaptive control strategy for synchronizing a dynamic network is proposed. Based on the Lyapunov stability theory, this paper shows that tracking errors of all nodes in a fractional-order complex network converge to zero. This simple yet prac- tical scheme can be used in many networks such as small-world networks and scale-free networks. Unlike the existing methods which assume the coupling configuration among the nodes of the network with diffusivity, symmetry, balance, or irreducibility, in this case, these assumptions are unnecessary, and the proposed adaptive strategy is more feasible. Two examples are presented to illustrate effectiveness of the proposed method.展开更多
Software.defined networking(SDN) enables third.part companies to participate in the network function innovations. A number of instances for one network function will inevitably co.exist in the network. Although some o...Software.defined networking(SDN) enables third.part companies to participate in the network function innovations. A number of instances for one network function will inevitably co.exist in the network. Although some orchestration architecture has been proposed to chain network functions, rare works are focused on how to optimize this process. In this paper, we propose an optimized model for network function orchestration, function combination model(FCM). Our main contributions are as following. First, network functions are featured with a new abstraction, and are open to external providers. And FCM identifies network functions using unique type, and organizes their instances distributed over the network with the appropriate way. Second, with the specialized demands, we can combine function instances under the global network views, and formulate it into the problem of Boolean linear program(BLP). A simulated annealing algorithm is designed to approach optimal solution for this BLP. Finally, the numerical experiment demonstrates that our model can create outstanding composite schemas efficiently.展开更多
A developmental research has been carried out to deal with the high performance of Cu-Cr-Zr-Mg lead frame alloy by artificial neural network (ANN). Using the cold working to assist in the aging hardening can improve t...A developmental research has been carried out to deal with the high performance of Cu-Cr-Zr-Mg lead frame alloy by artificial neural network (ANN). Using the cold working to assist in the aging hardening can improve the the hardness and electrical conductivity properties of Cu-Cr-Zr-Mg lead frame alloy. This paper studies the effect of different extent of cold working on the aging properties by a supervised ANN to model the non-linear relationship between processing parameters and the properties. The back-propagation (BP) training algorithm is improved by Levenberg-Marquardt algorithm. A basic repository on the domain knowledge of cold worked aging processes is established via sufficient data mining by the network. The predicted values of the ANN coincide well with the tested data. So an important foundation has been laid for prediction and optimum controlling the rolling and aging properties of Cu-Cr-Zr-Mg alloy.展开更多
The ability to recall and recognize facts we experienced in the past is based on a complex mechanism in which several cerebral regions are implicated. Neuroimaging and lesion studies agree in identifying the frontal l...The ability to recall and recognize facts we experienced in the past is based on a complex mechanism in which several cerebral regions are implicated. Neuroimaging and lesion studies agree in identifying the frontal lobe as a crucial structure for memory processes, and in particular for working memory and episodic memory and their relationships. Furthermore, with the introduction of transcranial magnetic stimulation （TMS） a new way was proposed to investigate the relationships between brain correlates, memory functions and behavior. The aim of this review is to present the main findings that have emerged from experiments which used the TMS technique for memory analysis. They mainly focused on the role of the dorsolateral prefrontal cortex in memory process. Furthermore, we present state-of-the-art evidence supporting a possible use of TMS in the clinic. Specifically we focus on the treatment of memory deficits in depression and anxiety disorders.展开更多
The adaptive coupled synchronization method for non-autonomous systems is proposed. This method can avoid estimating the value of coupling coefficient. Under the uniform Lipschitz assumption, we derive the asymptotica...The adaptive coupled synchronization method for non-autonomous systems is proposed. This method can avoid estimating the value of coupling coefficient. Under the uniform Lipschitz assumption, we derive the asymptotical synchronization for a general coupling ring network with N identical non-autonomous systems~ even when N is large enough. Strict theoretical proofs are given. Numerical simulations illustrate the effectiveness of the present method.展开更多
The global adaptive H∞ synchronization is intensively investigated for the general delayed complex dynamical networks. The network under consideration contains unknown but bounded nonlinear coupling functions, time-v...The global adaptive H∞ synchronization is intensively investigated for the general delayed complex dynamical networks. The network under consideration contains unknown but bounded nonlinear coupling functions, time-varying delay, and external disturbance. Based on the Lyapunov stability theory, linear matrix inequality （LMI） optimization technique and adaptive control, several global adaptive H∞ synchronization schemes are estab- lished, which guarantee robust asymptotical synchronization of noise-perturbed network as well as a prescribed robust H∞ per- formance level. Finally, numerical simulations have shown the feasibility and effectiveness of the proposed techniques.展开更多
基金supported by the Science and Technology Research Program of Chongqing Municipal Education Commission(Grant Nos.KJQN202100812,KJQN202215901,KJQN202400812).
文摘As smart manufacturing and Industry 4.0 continue to evolve,fault diagnosis of mechanical equipment has become crucial for ensuring production safety and optimizing equipment utilization.To address the challenge of cross-domain adaptation in intelligent diagnostic models under varying operational conditions,this paper introduces the CNN-1D-KAN model,which combines a 1D Convolutional Neural Network(1D-CNN)with a Kolmogorov–Arnold Network(KAN).The novelty of this approach lies in replacing the traditional 1D-CNN’s final fully connected layer with a KANLinear layer,leveraging KAN’s advanced nonlinear processing and function approximation capabilities while maintaining the simplicity of linear transformations.Experimental results on the CWRU dataset demonstrate that,under stable load conditions,the CNN-1D-KAN model achieves high accuracy,averaging 96.67%.Furthermore,the model exhibits strong transfer generalization and robustness across varying load conditions,sustaining an average accuracy of 90.21%.When compared to traditional neural networks(e.g.,1D-CNN and Multi-Layer Perceptron)and other domain adaptation models(e.g.,KAN Convolutions and KAN),the CNN-1D-KAN consistently outperforms in both accuracy and F1 scores across diverse load scenarios.Particularly in handling complex cross-domain data,it excels in diagnostic performance.This study provides an effective solution for cross-domain fault diagnosis in Industrial Internet systems,offering a theoretical foundation to enhance the reliability and stability of intelligent manufacturing processes,thus supporting the future advancement of industrial IoT applications.
基金supported by the National Natural Science Foundation of China(Nos.22275156,52025132,21,621,091,52300138,22021001 and 22121001)the Fundamental Research Funds for the Central Universities of China(No.20720220019)+2 种基金the National Science Foundation of Fujian Province of China(No.2022J02059)the 111 Project(Nos.B17027,B16029)the New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘The development of next-generation electromagnetic wave(EMW)absorbers requires a shift in interface design.By employing hierarchical work function programming,we propose an approach to tune interfacial polarization dynamics.This method utilizes multi-gradient work functions to guide carrier migration and polarization effectively,thereby enhancing energy dissipation under alternating electromagnetic fields.Here,we constructed a 1T/2H-MoS_(2)/PPy/VS_(2) composite absorber with integrated gradient interfaces.The composite achieved a powerful absorption(RLmin)of-58.59 dB at 2.3 mm,and an effective absorption bandwidth(EAB)of 7.44 GHz at 2.5 mm,demonstrating improved broadband absorption.Radar cross-section(RCS)simulations show an EMW loss of-7.2 dB m^(2) at 0°,highlighting its potential for stealth and communication applications.This study introduces hierarchical work function programming as a promising strategy in EMW absorber design,contributing to advancements in material performance and functionality.
文摘This study examined the relationship between inclusive leadership and authenticity at work in racial minority groups of South Africa,taking into account the mediating role of psychological safety and the moderator role of gender,in that relationship.The sample was composed of 94 employees predominantly working in the professional services sector from South Africa(41.5%females;mean age=37.1),who self-identified as racial minority groups(coloured/black/Indian).Results indicate that inclusive leadership has no direct effect on authenticity at work;however,psychological safety fully mediates this relationship.Regarding the moderation effect of gender,results showed that males are more likely to diminish their self-alienation(a specific component of authenticity at work)when levels of psychological safety are higher.These results are consistent with Social Identity Theory,which posits that individuals derive part of their self-concept from their membership in social groups.In contexts where inclusive leadership fosters psychological safety,individuals(particularly men in traditionally male-dominated work environments)may feel a stronger sense of belonging and group identity,which in turn enhances their willingness to express their authentic selves and reduces self-alienation.Practical implications for companies include the need to improve leadership styles to foster more of an inclusive and psychologically safe culture,where minority groups can be authentic and flourish.
基金funded by Nanjing University of Posts and Telecommunications Humanities and Social Sciences Research Fund Project(NYY222055)Special research project on teaching reform of innovation and entrepreneurship education in Nanjing University of Posts and Telecommunications(GCSJG202528)+2 种基金General Subject of Educational Science Planning in Jiangsu Province(C/2024/01/76)General project of educational science research in Shanghai(C24288)Key funded project of Shandong Vocational Education Teaching Reform Research in 2022(2022052).
文摘Background:As an important indicator of subjective well-being(SWB),decent work is a key guarantee for the sustainable development of teachers and their psychological health and work quality.Faced with the rapid development of artificial intelligence and the global labor market,vocational college teachers are facing challenges such as workload pressure and limited career development,which may harm their well-being.This study aims to localize the measurement method of decent work in Chinese vocational education based on the theory of the Psychology of Working Theory,and explore the relationship mechanism between organizational support,career adaptability,decent work,and job satisfaction among vocational college teachers.Methods:A cross-sectional survey was conducted with 422 HVCU teachers in China(202 male,220 female)using the localized Perceived Organizational Support Scale,Career Adaptability Scale,Decent Work Scale,and Job Satisfaction Scale.Results:The overall level of HVCU teachers’decent work was above the median(Mean=4.09,SD=0.69),laying a foundation for their SWB.Decent work significantly and positively predicted job satisfaction(β=0.620,p<0.001).Organizational support(r=0.58,p<0.001)and career adaptability(r=0.82,p<0.001)can positively affect decent work,and further improve job satisfaction(collective R2 rising from 38.3%to 41.1%).Bootstrap analysis confirmed these mediating effects were robust.Conclusions:This study confirms that the combined effects of organizational support and career adaptability can enhance decent work,further improving teachers’job satisfaction and subsequent subjective well-being.Besides,this study provides an empirical basis for improving the well-being of higher vocational teachers and the sustainable development of vocational education,and has practical significance for improving the teacher incentive policy.
基金funded by the Huaiyin Institute of Technology—Institute of Smart Energy.
文摘In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector,the recovery of waste heat from diesel engines has become a critical area of focus.This study provided an exhaustive thermodynamic analysis optimizing Organic Rankine Cycle(ORC)systems forwaste heat recovery fromdiesel engines.Thestudy assessed the performance of five candidateworking fluids—R11,R123,R113,R245fa,and R141b—under a range of operating conditions,specifically varying overheat temperatures and evaporation pressures.The results indicated that the choice of working fluid substantially influences the system’s exergetic efficiency,net output power,and thermal efficiency.R245fa showed an outstanding net output power of 30.39 kW at high overheat conditions,outperforming R11,which is significant for high-temperature waste heat recovery.At lower temperatures,R11 and R113 demonstrated higher exergetic efficiencies,with R11 reaching a peak exergetic efficiency of 7.4%at an evaporation pressure of 10 bar and an overheat of 10℃.The study also revealed that controlling the overheat and optimizing the evaporation pressure are crucial for enhancing the net output power of the ORC system.Specifically,at an evaporation pressure of 30 bar and an overheat of 0℃,R113 exhibited the lowest exergetic destruction of 544.5 kJ/kg,making it a suitable choice for minimizing irreversible losses.These findings are instrumental for understanding the performance of ORC systems in waste heat recovery applications and offer valuable insights for the design and operation of more efficient and environmentally friendly diesel engine systems.
基金co-supported by the National Basic Research Program of China (Nos. 2012CB316301, 2013CB329403)the National Natural Science Foundation of China (Nos. 61473307, 61304120, 61273023, 61332007)
文摘Drogue detection is a fundamental issue during the close docking phase of autonomous aerial refueling（AAR）. To cope with this issue, a novel and effective method based on deep learning with convolutional neural networks（CNNs） is proposed. In order to ensure its robustness and wide application, a deep learning dataset of images was prepared by utilizing real data of ‘‘Probe and Drogue＂ aerial refueling, which contains diverse drogues in various environmental conditions without artificial features placed on the drogues. By employing deep learning ideas and graphics processing units（GPUs）, a model for drogue detection using a Caffe deep learning framework with CNNs was designed to ensure the method＇s accuracy and real-time performance. Experiments were conducted to demonstrate the effectiveness of the proposed method, and results based on real AAR data compare its performance to other methods, validating the accuracy, speed, and robustness of its drogue detection ability.
基金supported by the National Natural Science Foundation of China(No.61039001)the State Technology Supporting Plan(No.2011BAH24B08)the Fundamental Research Funds for the Central Universities (No.ZXH2011A002)
文摘In order to improve safety,economy efficiency and design automation degree of air route in terminal airspace,Three-dimensional(3D)planning of routes network is investigated.A waypoint probability search method is proposed to optimize individual flight path.Through updating horizontal pheromones by negative feedback factors,an antcolony algorithm of path searching in 3Dterminal airspace is implemented.The principle of optimization sequence of arrival and departure routes is analyzed.Each route is optimized successively,and the overall optimization of the whole route network is finally achieved.A case study shows that it takes about 63 sto optimize 8arrival and departure routes,and the operation efficiency can be significantly improved with desirable safety and economy.
文摘There is a global movement calling for the integration of Western medicine（WM）and traditional Chinese medicine（TCM）[1].The World Health Organization suggests that health care would be improved by integrating traditional and complementary medicines into the practices of health care service delivery and self-health care[1].The WM and TCM are commonly integrated in the contemporary practice of medicine in China.
基金supported by the National Natural Science Foundation of China(6110418440904018)+3 种基金the National Key Scientific Instrument and Equipment Development Project(2011YQ12004502)the Research Foundation of General Armament Department(201300000008)the Doctor Innovation Fund of Naval University of Engineering(HGBSCXJJ2011008)the Youth Natural Science Foundation of Naval University of Engineering(HGDQNJJ12028)
文摘A novel neural network based on iterated unscented Kalman filter （IUKF） algorithm is established to model and com- pensate for the fiber optic gyro （FOG） bias drift caused by temperature. In the network, FOG temperature and its gradient are set as input and the FOG bias drift is set as the expected output. A 2-5-1 network trained with IUKF algorithm is established. The IUKF algorithm is developed on the basis of the unscented Kalman filter （UKF）. The weight and bias vectors of the hidden layer are set as the state of the UKF and its process and measurement equations are deduced according to the network architecture. To solve the unavoidable estimation deviation of the mean and covariance of the states in the UKF algorithm, iterative computation is introduced into the UKF after the measurement update. While the measure- ment noise R is extended into the state vectors before iteration in order to meet the statistic orthogonality of estimate and mea- surement noise. The IUKF algorithm can provide the optimized estimation for the neural network because of its state expansion and iteration. Temperature rise （-20-20℃） and drop （70-20℃） tests for FOG are carried out in an attemperator. The temperature drift model is built with neural network, and it is trained respectively with BP, UKF and IUKF algorithms. The results prove that the proposed model has higher precision compared with the back- propagation （BP） and UKF network models.
基金supported in part by the Project of National Natural Science Foundation of China (61301110)Project of Shanghai Key Laboratory of Intelligent Information Processing, China [grant number IIPL-2014-005]+1 种基金the Project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutionsthe Project of Jiangsu Overseas Research & Training Program for University Prominent Young & Middle-Aged Teachers and Presidents
文摘As device-to-device(D2D) communications usually reuses the resource of cellular networks, call admission control(CAC) and power control are crucial problems. However in most power control schemes, total data rates or throughput are regarded as optimization criterion. In this paper, a combining call admission control(CAC) and power control scheme under guaranteeing QoS of every user equipment(UE) is proposed. First, a simple CAC scheme is introduced. Then based on the CAC scheme, a combining call admission control and power control scheme is proposed. Next, the performance of the proposed scheme is evaluated. Finally, maximum DUE pair number and average transmitting power is calculated. Simulation results show that D2 D communications with the proposed combining call admission control and power control scheme can effectively improve the maximum DUE pair number under the premise of meeting necessary QoS.
基金Funded by the Zhejiang Provincial Natural Science Foundation of China(No.R405031)Jiaxing Science Planning Project(2009 2007)the Educa-tion Department of Zhejiang Province (No.20051441)
文摘A new thermal ring-opening polymerization technique for 1, 1, 3, 3-tetra-ph enyl-1, 3-disilacyclobutane （TPDC） based on the use of metal nanoparticles produced by pulsed laser ablation was investigated. This method facilitates the synthesis of polydiphenysilylenemethyle （PDPhSM） thin film, which is difficult to make by conventional methods because of its insolubility and high melting point. TPDC was first evaporated on silicon substrates and then exposed to metal nanoparticles deposition by pulsed laser ablation prior to heat treatment.The TPDC films with metal nanoparticles were heated in an electric furnace in air atmosphere to induce ring-opening polymerization of TPDC. The film thicknesses before and after polymerization were measured by a stylus profilometer. Since the polymerization process competes with re-evaporation of TPDC during the heating, the thickness ratio of the polymer to the monomer was defined as the polymerization efficiency, which depends greatly on the technology conditions. Therefore, a well trained radial base function neural network model was constructed to approach the complex nonlinear relationship. Moreover, a particle swarm algorithm was firstly introduced to search for an optimum technology directly from RBF neural network model. This ensures that the fabrication of thin film with appropriate properties using pulsed laser ablation requires no in-depth understanding of the entire behavior of the technology conditions.
基金supported by MYRG2016-00110-FHS,MYRG2015-00036-FHS and MYRG2015-00150-FAH grants from the University of MacaoFDCT 026/2014/A1 and FDCT 025/2015/A1 grants from the Macao government.
文摘The aim of this study is to examine the small-world properties of functional brain networks inChinese to English simultaneous interpreting(SI)using functional near-infrared spectroscopy(INIRS),In particular,the fNIRS neuroimaging combined with complex network analysis wasperformed to extract the features of functional brain networks underling three translationstrategies associated with Chinese to English SI:"transcoding"that takes the"shortcut"linkingtranslation equivalents between Chinese and the English,code-mixing"that basically does notinvolve blingual procesing,and"transphrasingn that takes the long route"involving amonolingual processing of meaning in Chinese and then another monolingual processing ofmeaning in English.Our results demonstrated that the small-world net work topology was able todistinguish well bet ween the transcoding,code-mixing and transphrasing strategies related toChinese to English SI.
基金Project supported by the National Natural Science Foundation of China(Nos.11672231 and11672233)the Natural Science Foundation of Shaanxi Province(No.2016JM1010)+1 种基金the Fundamental Research Funds for the Central Universities(No.3102017AX008)the Seed Foundation of Innovation and Creation for Graduate Students at the Northwestern Polytechnical University of China(No.Z2017187)
文摘This paper studies synchronization of all nodes in a fractional-order complex dynamic network. An adaptive control strategy for synchronizing a dynamic network is proposed. Based on the Lyapunov stability theory, this paper shows that tracking errors of all nodes in a fractional-order complex network converge to zero. This simple yet prac- tical scheme can be used in many networks such as small-world networks and scale-free networks. Unlike the existing methods which assume the coupling configuration among the nodes of the network with diffusivity, symmetry, balance, or irreducibility, in this case, these assumptions are unnecessary, and the proposed adaptive strategy is more feasible. Two examples are presented to illustrate effectiveness of the proposed method.
基金supported by the China Postdoctoral Fund Project (No.44603)the National Natural Science Foundation of China (No.61309020)+1 种基金the National key Research and Development Program of China (No.2016YFB0800100, 2016YFB0800101)the National Natural Science Fund for Creative Research Groups Project(No.61521003)
文摘Software.defined networking(SDN) enables third.part companies to participate in the network function innovations. A number of instances for one network function will inevitably co.exist in the network. Although some orchestration architecture has been proposed to chain network functions, rare works are focused on how to optimize this process. In this paper, we propose an optimized model for network function orchestration, function combination model(FCM). Our main contributions are as following. First, network functions are featured with a new abstraction, and are open to external providers. And FCM identifies network functions using unique type, and organizes their instances distributed over the network with the appropriate way. Second, with the specialized demands, we can combine function instances under the global network views, and formulate it into the problem of Boolean linear program(BLP). A simulated annealing algorithm is designed to approach optimal solution for this BLP. Finally, the numerical experiment demonstrates that our model can create outstanding composite schemas efficiently.
基金supported by National High Technical Research and Development Programme of China(No.2002AA331112)supported by the Doctorate Foundation of Northwestern Polytechnical University.
文摘A developmental research has been carried out to deal with the high performance of Cu-Cr-Zr-Mg lead frame alloy by artificial neural network (ANN). Using the cold working to assist in the aging hardening can improve the the hardness and electrical conductivity properties of Cu-Cr-Zr-Mg lead frame alloy. This paper studies the effect of different extent of cold working on the aging properties by a supervised ANN to model the non-linear relationship between processing parameters and the properties. The back-propagation (BP) training algorithm is improved by Levenberg-Marquardt algorithm. A basic repository on the domain knowledge of cold worked aging processes is established via sufficient data mining by the network. The predicted values of the ANN coincide well with the tested data. So an important foundation has been laid for prediction and optimum controlling the rolling and aging properties of Cu-Cr-Zr-Mg alloy.
文摘The ability to recall and recognize facts we experienced in the past is based on a complex mechanism in which several cerebral regions are implicated. Neuroimaging and lesion studies agree in identifying the frontal lobe as a crucial structure for memory processes, and in particular for working memory and episodic memory and their relationships. Furthermore, with the introduction of transcranial magnetic stimulation （TMS） a new way was proposed to investigate the relationships between brain correlates, memory functions and behavior. The aim of this review is to present the main findings that have emerged from experiments which used the TMS technique for memory analysis. They mainly focused on the role of the dorsolateral prefrontal cortex in memory process. Furthermore, we present state-of-the-art evidence supporting a possible use of TMS in the clinic. Specifically we focus on the treatment of memory deficits in depression and anxiety disorders.
基金Project supported by the National Natural Science Foundation of China(Grant No10372054)the Science Foundation of Jiangnan University,China(Grant No000408)
文摘The adaptive coupled synchronization method for non-autonomous systems is proposed. This method can avoid estimating the value of coupling coefficient. Under the uniform Lipschitz assumption, we derive the asymptotical synchronization for a general coupling ring network with N identical non-autonomous systems~ even when N is large enough. Strict theoretical proofs are given. Numerical simulations illustrate the effectiveness of the present method.
基金Supported by the National Natural Science Foundation of China (60904060,61104127)the Open Foundation of Hubei Province Key Laboratory of Systems Science in Metallurgical Process (C201010)
文摘The global adaptive H∞ synchronization is intensively investigated for the general delayed complex dynamical networks. The network under consideration contains unknown but bounded nonlinear coupling functions, time-varying delay, and external disturbance. Based on the Lyapunov stability theory, linear matrix inequality （LMI） optimization technique and adaptive control, several global adaptive H∞ synchronization schemes are estab- lished, which guarantee robust asymptotical synchronization of noise-perturbed network as well as a prescribed robust H∞ per- formance level. Finally, numerical simulations have shown the feasibility and effectiveness of the proposed techniques.
