Most unsupervised or semisupervised hyperspectral anomaly detection(HAD)methods train background reconstruction models in the original spectral domain.However,due to the noise and spatial resolution limitations,there ...Most unsupervised or semisupervised hyperspectral anomaly detection(HAD)methods train background reconstruction models in the original spectral domain.However,due to the noise and spatial resolution limitations,there may be a lack of discrimination between backgrounds and anomalies.This makes it easy for the autoencoder to capture the lowlevel features shared between the two,thereby increasing the difficulty of separating anomalies from the backgrounds,which runs counter to the purpose of HAD.To this end,the authors map the original spectrums to the fractional Fourier domain(FrFD)and reformulate it as a mapping task in which restoration errors are employed to distinguish background and anomaly.This study proposes a novel frequency‐to‐spectrum mapping generative adversarial network for HAD.Specifically,the depth separable features of backgrounds and anomalies are enhanced in the FrFD.Due to the semisupervised approach,FTSGAN needs to learn the embedded features of the backgrounds,thus mapping and restoring them from the FrFD to the original spectral domain.This strategy effectively prevents the model from focussing on the numerical equivalence of input and output,and restricts the ability of FTSGAN to restore anomalies.The comparison and analysis of the experiments verify that the proposed method is competitive.展开更多
To balance the manufacturing cost and customizability of automotive parts,a hybrid manufacturing process combining die-casting and selective laser melting(SLM)is proposed:starting with a conventional cast substrate,SL...To balance the manufacturing cost and customizability of automotive parts,a hybrid manufacturing process combining die-casting and selective laser melting(SLM)is proposed:starting with a conventional cast substrate,SLM is utilized to add additional geometric elements on top of it.For this hybrid process,the first priority is to prepare a substrate surface suitable for the subsequent SLM addition of the top-on elements.In this study,the original cast surface of AlSi7Mg was processed by sandblasting,wire electro-discharge machining,and laser remelting,respectively.Then,additional AlSi7Mg components were built on both the original cast and treated surfaces through SLM.After hybrid builds,these surfaces and resultant interfaces were examined by optical and scanning electron microscopes.Results indicate that the defect-free metallurgical joint between the cast and additively added parts can be formed on all surfaces except for the one processed by electro-discharge machining.The observed epitaxial grain growth crossing the interface implies a strong connection between the cast and the SLMed component.Despite these benefits,also mismatches in microstructure,residual stress level and element distribution between the two parts are identified.After a comprehensive assessment,laser remelting with no additional machining is recommended as the optimal surface treatment preceding SLM fabrication,because of its user-friendly operation,low cost,and high industrial feasibility.展开更多
Anomaly detection(AD)is an important task in a broad range of domains.A popular choice for AD are Deep Support Vector Data Description models.When learning such models,normal data is mapped close to and anomalous data...Anomaly detection(AD)is an important task in a broad range of domains.A popular choice for AD are Deep Support Vector Data Description models.When learning such models,normal data is mapped close to and anomalous data is mapped far from a center,in some latent space,enabling the construction of a sphere to separate both types of data.Empirically,it was observed:(i)that the center and radius of such sphere largely depend on the training data and model initialization which leads to difficulties when selecting a threshold,and(ii)that the center and radius of this sphere strongly impact the model AD performance on unseen data.In this work,a more robust AD solution is proposed that(i)defines a sphere with a fixed radius and margin in some latent space and(ii)enforces the encoder,which maps the input to a latent space,to encode the normal data in a small sphere and the anomalous data outside a larger sphere,with the same center.Experimental results indicate that the proposed algorithm attains higher performance compared to alternatives,and that the difference in size of the two spheres has a minor impact on the performance.展开更多
This paper presents an original theoretical framework to model steel material properties in continuous casting line process. Specific properties arising from non-Newtonian dynamics are herein used to indicate the natu...This paper presents an original theoretical framework to model steel material properties in continuous casting line process. Specific properties arising from non-Newtonian dynamics are herein used to indicate the natural convergence of distributed parameter systems to fractional order transfer function models. Data driven identification from a real continuous casting line is used to identify model of the electromagnetic actuator device to control flow velocity of liquid steel. To ensure product specifications, a fractional order control is designed and validated on the system. A projection of the closed loop performance onto the quality assessment at end production line is also given in this paper.展开更多
Cr-doped V_(2)O_(3) thin film shows a huge resistivity change with controlled epitaxial strain at room temperature as a result of a gradual Mott metal-insulator phase transition with strain.This novel piezoresistive t...Cr-doped V_(2)O_(3) thin film shows a huge resistivity change with controlled epitaxial strain at room temperature as a result of a gradual Mott metal-insulator phase transition with strain.This novel piezoresistive transduction principle makes Cr-doped V_(2)O_(3) thin film an appealing piezoresistive material.To investigate the piezoresistivity of Cr-doped V_(2)O_(3) thin film for implementation in MEMS sensor applications,the resistance change of differently orientated Cr-doped V_(2)O_(3) thin film piezoresistors with external strain change was measured.With a longitudinal gauge factor of 222 and a transversal gauge factor of 217 at room temperature,isotropic piezoresistivity coefficients were discovered.This results in a significant orientation-independent resistance change with stress for Cr-doped V_(2)O_(3) thin film piezoresistors,potentially useful for new sensor applications.To demonstrate the integration of this new piezoresistive material in sensor applications,a micromachined pressure sensor with Cr-doped V_(2)O_(3) thin film piezoresistors was designed,fabricated and characterized.At 20℃,a sensitivity,offset,temperature coefficient of sensitivity and temperature coefficient of offset of 21.81 mV/V/bar,-25.73 mV/V,-0.076 mV/V/bar/℃ and 0.182 mV/V/℃,respectively,were measured.This work paves the way for further research on this promising piezoresistive transduction principle for use in MEMS sensor applications.展开更多
Transportation networks are sized to efficiently achieve some set of service objectives.Under particular circumstances,such as the COVID-19 pandemic,the demand for transportation can significantly change,both qualitat...Transportation networks are sized to efficiently achieve some set of service objectives.Under particular circumstances,such as the COVID-19 pandemic,the demand for transportation can significantly change,both qualitatively and quantitatively,resulting in an over-capacitated and less efficient network.In this paper,we address this issue by proposing a framework for resizing the network to efficiently cope with the new demand.The framework includes a model to determine an optimal transportation sub-network that guarantees the following:(i)the minimal access time from any node of the urban network to the new sub-network has not excessively increased compared to that of the original transportation network;(ii)the delay induced on any itinerary by the removal of nodes from the original transportation network has not excessively increased;and(iii)the number of removed nodes from the transportation network is within a preset known factor.A solution is optimal if it induces a minimal global delay.We modelled this problem as a Mixed Integer Linear Program and applied it to the public bus transportation network of Lyon,France,in a case study.In order to respond to operational issues,the framework also includes a decision tool that helps the network planners to decide which bus lines to close and which ones to leave open according to specific trade-off preferences.The results on real data in Lyon show that the optimal sub-network from the MILP model can be used to feed the decision tool,leading to operational scenarios for network planners.展开更多
基金supported by the National Natural Science Foundation of China under Grant 62161160336Grant 41871245in part by the Belgium Vlaio project(AI ICON‐2021‐0599:Smart industrial spectral cameras via artificial intelligence).
文摘Most unsupervised or semisupervised hyperspectral anomaly detection(HAD)methods train background reconstruction models in the original spectral domain.However,due to the noise and spatial resolution limitations,there may be a lack of discrimination between backgrounds and anomalies.This makes it easy for the autoencoder to capture the lowlevel features shared between the two,thereby increasing the difficulty of separating anomalies from the backgrounds,which runs counter to the purpose of HAD.To this end,the authors map the original spectrums to the fractional Fourier domain(FrFD)and reformulate it as a mapping task in which restoration errors are employed to distinguish background and anomaly.This study proposes a novel frequency‐to‐spectrum mapping generative adversarial network for HAD.Specifically,the depth separable features of backgrounds and anomalies are enhanced in the FrFD.Due to the semisupervised approach,FTSGAN needs to learn the embedded features of the backgrounds,thus mapping and restoring them from the FrFD to the original spectral domain.This strategy effectively prevents the model from focussing on the numerical equivalence of input and output,and restricts the ability of FTSGAN to restore anomalies.The comparison and analysis of the experiments verify that the proposed method is competitive.
基金financially supported by the Ford Motor Com-pany under Ford-KU Leuven University Research Alliance Frame-work KUL-0025 fortheproject‘Incremental Additive Manufacturing for Metal Applications’.Haiyang Fan also appreciates the financial support of the China Scholarship Council(CSC)(No.201606050132).
文摘To balance the manufacturing cost and customizability of automotive parts,a hybrid manufacturing process combining die-casting and selective laser melting(SLM)is proposed:starting with a conventional cast substrate,SLM is utilized to add additional geometric elements on top of it.For this hybrid process,the first priority is to prepare a substrate surface suitable for the subsequent SLM addition of the top-on elements.In this study,the original cast surface of AlSi7Mg was processed by sandblasting,wire electro-discharge machining,and laser remelting,respectively.Then,additional AlSi7Mg components were built on both the original cast and treated surfaces through SLM.After hybrid builds,these surfaces and resultant interfaces were examined by optical and scanning electron microscopes.Results indicate that the defect-free metallurgical joint between the cast and additively added parts can be formed on all surfaces except for the one processed by electro-discharge machining.The observed epitaxial grain growth crossing the interface implies a strong connection between the cast and the SLMed component.Despite these benefits,also mismatches in microstructure,residual stress level and element distribution between the two parts are identified.After a comprehensive assessment,laser remelting with no additional machining is recommended as the optimal surface treatment preceding SLM fabrication,because of its user-friendly operation,low cost,and high industrial feasibility.
基金This research received funding from the Flemish Government(AI Research Program)This research has received support of Flanders Make,the strategic research center for the manufacturing industry.
文摘Anomaly detection(AD)is an important task in a broad range of domains.A popular choice for AD are Deep Support Vector Data Description models.When learning such models,normal data is mapped close to and anomalous data is mapped far from a center,in some latent space,enabling the construction of a sphere to separate both types of data.Empirically,it was observed:(i)that the center and radius of such sphere largely depend on the training data and model initialization which leads to difficulties when selecting a threshold,and(ii)that the center and radius of this sphere strongly impact the model AD performance on unseen data.In this work,a more robust AD solution is proposed that(i)defines a sphere with a fixed radius and margin in some latent space and(ii)enforces the encoder,which maps the input to a latent space,to encode the normal data in a small sphere and the anomalous data outside a larger sphere,with the same center.Experimental results indicate that the proposed algorithm attains higher performance compared to alternatives,and that the difference in size of the two spheres has a minor impact on the performance.
基金supported by Research Foundation Flanders(FWO)(1S04719N,12X6819N)partially supported by a grant of the Ministry of Research+2 种基金Innovation and DigitizationCNCS-UEFISCDIproject number PN-Ⅲ-P1-1.1-PD-2021-0204,within PNCDIⅢ。
文摘This paper presents an original theoretical framework to model steel material properties in continuous casting line process. Specific properties arising from non-Newtonian dynamics are herein used to indicate the natural convergence of distributed parameter systems to fractional order transfer function models. Data driven identification from a real continuous casting line is used to identify model of the electromagnetic actuator device to control flow velocity of liquid steel. To ensure product specifications, a fractional order control is designed and validated on the system. A projection of the closed loop performance onto the quality assessment at end production line is also given in this paper.
文摘Cr-doped V_(2)O_(3) thin film shows a huge resistivity change with controlled epitaxial strain at room temperature as a result of a gradual Mott metal-insulator phase transition with strain.This novel piezoresistive transduction principle makes Cr-doped V_(2)O_(3) thin film an appealing piezoresistive material.To investigate the piezoresistivity of Cr-doped V_(2)O_(3) thin film for implementation in MEMS sensor applications,the resistance change of differently orientated Cr-doped V_(2)O_(3) thin film piezoresistors with external strain change was measured.With a longitudinal gauge factor of 222 and a transversal gauge factor of 217 at room temperature,isotropic piezoresistivity coefficients were discovered.This results in a significant orientation-independent resistance change with stress for Cr-doped V_(2)O_(3) thin film piezoresistors,potentially useful for new sensor applications.To demonstrate the integration of this new piezoresistive material in sensor applications,a micromachined pressure sensor with Cr-doped V_(2)O_(3) thin film piezoresistors was designed,fabricated and characterized.At 20℃,a sensitivity,offset,temperature coefficient of sensitivity and temperature coefficient of offset of 21.81 mV/V/bar,-25.73 mV/V,-0.076 mV/V/bar/℃ and 0.182 mV/V/℃,respectively,were measured.This work paves the way for further research on this promising piezoresistive transduction principle for use in MEMS sensor applications.
基金supported by the Smart Lab LABILITY of the University Gustave Eiffel,funded by the Region Ile de France(Grant No.20012741)by the French ANR research project PROMENADE(Grant No.ANR-18-CE22-0008).
文摘Transportation networks are sized to efficiently achieve some set of service objectives.Under particular circumstances,such as the COVID-19 pandemic,the demand for transportation can significantly change,both qualitatively and quantitatively,resulting in an over-capacitated and less efficient network.In this paper,we address this issue by proposing a framework for resizing the network to efficiently cope with the new demand.The framework includes a model to determine an optimal transportation sub-network that guarantees the following:(i)the minimal access time from any node of the urban network to the new sub-network has not excessively increased compared to that of the original transportation network;(ii)the delay induced on any itinerary by the removal of nodes from the original transportation network has not excessively increased;and(iii)the number of removed nodes from the transportation network is within a preset known factor.A solution is optimal if it induces a minimal global delay.We modelled this problem as a Mixed Integer Linear Program and applied it to the public bus transportation network of Lyon,France,in a case study.In order to respond to operational issues,the framework also includes a decision tool that helps the network planners to decide which bus lines to close and which ones to leave open according to specific trade-off preferences.The results on real data in Lyon show that the optimal sub-network from the MILP model can be used to feed the decision tool,leading to operational scenarios for network planners.
