The operation of distribution system with the components in deteriorating condition makes the system reliability worsen. It is important to find the solution for balancing failure cost and maintenance benefits such as...The operation of distribution system with the components in deteriorating condition makes the system reliability worsen. It is important to find the solution for balancing failure cost and maintenance benefits such as down-time and reliability. In this paper, time to replace the components in optimum condition based on constant-interval replacement mode is investigated. The optimal replacement time is mainly depended on component’s reliability and the cost ration of preventive replacement and failure replacement. In this paper, equipment inspection method and Weibull Analysis is applied to obtain the accurate reliability estimation. Weibull Analysis is applied with constant-interval replacement model to investigate the optimum replacement time for each component considering the different cost ratios. According to the quantitative results, the determination of the optimal replacement time (OPT) can minimize the total downtime and failure cost. Consequently, the reliability of the system is maximized and estimation also becomes more accurate due to sufficient approach.展开更多
Transmitting a longitudinal wave and a traverse wave into a composite material in a molten state has been studied in the online control of the composite material which cannot be evaluated by a conventional ultrasonic ...Transmitting a longitudinal wave and a traverse wave into a composite material in a molten state has been studied in the online control of the composite material which cannot be evaluated by a conventional ultrasonic sensor as a final analysis, using the difference in the propagation characteristics of both modes. It is especially expected that measurement of the physical quantity which was not able to be conventionally measured can be performed by carrying out coincidence measurement of the ultrasonic wave in both modes. Therefore, in this research study, an ultrasonic probe, which can simultaneously transmit and receive a longitudinal wave and a traverse wave has been developed using an electromagnetic acoustic transducer (EMAT) because it has the advantage of measuring high temperature samples. In this study, two methods have been compared. The 1st method uses a traverse wave EMAT that travels in a vertical direction and a bar wave by which the low order mode is equivalent to longitudinal wave vibration. The other method is to carry out the mode conversion of the traverse wave by a traverse wave-EMAT. The longitudinal converted from the transverse wave are spread in the axis direction. As the experimental results of both optimizations of the drive conditions, it has been confirmed that the 2nd mode conversion method was promising. This paper reports about the trial process and the experimental results.展开更多
A smartphone-based context-aware augmentative and alternative communication(AAC) was applied was in order to enhance the user's experience by providing simple, adaptive, and intuitive interfaces. Various potential...A smartphone-based context-aware augmentative and alternative communication(AAC) was applied was in order to enhance the user's experience by providing simple, adaptive, and intuitive interfaces. Various potential context-aware technologies and AAC usage scenarios were studied, and an efficient communication system was developed by combining smartphone's multimedia functions and its optimized sensor technologies. The experimental results show that context-awareness accuracy is achieved up to 97%.展开更多
By using a Fourier series expansion method combined with Chew＇s perfectly matched layers （PMLs）, we analyze the frequency and quality factor of a micro-cavity on a two-dimensional photonic crystal is analyzed. Comp...By using a Fourier series expansion method combined with Chew＇s perfectly matched layers （PMLs）, we analyze the frequency and quality factor of a micro-cavity on a two-dimensional photonic crystal is analyzed. Compared with the results by the method without PML and finite-difference time-domain （FDTD） based on supercell approximation, it can be shown that by the present method with PMLs, the resonant frequency and the quality factor values can be calculated satisfyingly and the characteristics of the micro-cavity can be obtained by changing the size and permittivity of the point defect in the micro-cavity.展开更多
Wide-area damping controllers(WADCs)help in damping poorly damped inter-area oscillations(IAOs)using wide-area measurements.However,the vulnerability of the communication network makes the WADC susceptible to maliciou...Wide-area damping controllers(WADCs)help in damping poorly damped inter-area oscillations(IAOs)using wide-area measurements.However,the vulnerability of the communication network makes the WADC susceptible to malicious dynamic attacks.Existing cyber-resilient WADC solutions rely on accurate power system models or extensive simulation data for training the machine learning(ML)model,which are difficult to obtain for large-scale power system.This paper proposes a novel non-intrusive hybrid two-stage detection framework that mitigates these limitations by eliminating the need for realtime access to large system data or attack samples for training the ML model.In the first stage,an autoencoder is deployed at the actuator location to detect dynamic attacks with sharp gradient variations,e.g.,triangular,saw-tooth,pulse,ramp,and random attack signals.In the second stage,an unscented Kalman filter with unknown input estimation at the control center identifies smoothly varying dynamic attacks by estimating the control signal received by the actuator using synchrophasor measurements.A modified cosine similarity(MCS)metric is proposed to compare and quantify the similarity between the estimated control signal and the control signal sent by the WADC placed at the control center to detect any dynamic attacks.The MCS is designed to differentiate between events and dynamic attacks.The performance of the proposed framework has been validated on a hardware-in-the-loop(HIL)cyber-physical testbed built by using the OPAL-RT simulator and industry-grade hardware.展开更多
A sparsifying transform for use in Compressed Sensing (CS) is a vital piece of image reconstruction for Magnetic Resonance Imaging (MRI). Previously, Translation Invariant Wavelet Transforms (TIWT) have been shown to ...A sparsifying transform for use in Compressed Sensing (CS) is a vital piece of image reconstruction for Magnetic Resonance Imaging (MRI). Previously, Translation Invariant Wavelet Transforms (TIWT) have been shown to perform exceedingly well in CS by reducing repetitive line pattern image artifacts that may be observed when using orthogonal wavelets. To further establish its validity as a good sparsifying transform, the TIWT is comprehensively investigated and compared with Total Variation (TV), using six under-sampling patterns through simulation. Both trajectory and random mask based under-sampling of MRI data are reconstructed to demonstrate a comprehensive coverage of tests. Notably, the TIWT in CS reconstruction performs well for all varieties of under-sampling patterns tested, even for cases where TV does not improve the mean squared error. This improved Image Quality (IQ) gives confidence in applying this transform to more CS applications which will contribute to an even greater speed-up of a CS MRI scan. High vs low resolution time of flight MRI CS re-constructions are also analyzed showing how partial Fourier acquisitions must be carefully addressed in CS to prevent loss of IQ. In the spirit of reproducible research, novel software is introduced here as FastTestCS. It is a helpful tool to quickly develop and perform tests with many CS customizations. Easy integration and testing for the TIWT and TV minimization are exemplified. Simulations of 3D MRI datasets are shown to be efficiently distributed as a scalable solution for large studies. Comparisons in reconstruction computation time are made between the Wavelab toolbox and Gnu Scientific Library in FastTestCS that show a significant time savings factor of 60×. The addition of FastTestCS is proven to be a fast, flexible, portable and reproducible simulation aid for CS research.展开更多
Biodiesel as a renewable alternative to conventional diesel is a growing topic of interest due to its potential environmental benefits.It is typically produced from oilseed crops such as soybean,rapeseed,palm oil,or a...Biodiesel as a renewable alternative to conventional diesel is a growing topic of interest due to its potential environmental benefits.It is typically produced from oilseed crops such as soybean,rapeseed,palm oil,or animal fats.However,its sustainability is debated,primarily because of the reliance on edible oil feedstocks and associated economic and environmental concerns.This study explores alternative,non-edible feedstocks,such as algae and jatropha,that do not compete with food production,offering increased sustainability.Despite their potential,these feedstocks are hindered by high production costs.To address these challenges,innovative approaches in feedstock assessment are imperative for ensuring the long-term viability of biodiesel as an alternative fuel.This review examines explicitly the application of deep learning techniques in selecting and evaluating biodiesel feedstocks.It focuses on their production processes and the chemical and physical properties that impact biodiesel quality.Our comprehensive analysis demonstrates that ANNs provide significant insights into the feedstock assessment process,emerging as a potent tool for identifying new correlations within complex datasets.By leveraging this capability,ANNs can significantly advance biodiesel research,producing more sustainable and efficient feedstock production.The study concludes by highlighting the substantial potential of ANN modeling in contributing to renewable energy strategies and expanding biodiesel research,underscoring its vital role in accelerating the development of biodiesel as a sustainable fuel alternative.展开更多
Inexpe nsive copper nano particles are generally thought to possess weak and broad localized surface plasm on resonance(LSPR).The,present experimental and theoretical studies show that tailoring the Cu nanoparticle to...Inexpe nsive copper nano particles are generally thought to possess weak and broad localized surface plasm on resonance(LSPR).The,present experimental and theoretical studies show that tailoring the Cu nanoparticle to a cubic shape results in a single intense,narrow,and asymmetric LSPR line shape,which is even superior to round-shaped gold nanoparticles.In this study,the dielectric function of copper is decomposed into an interband transition component and a free-electron component.This allows interband transition-induced plasmon damping to be visualized both spectrally and by surface polarization charges.The results reveal that the LSPR of Cu nanocubes originates from the comer mode as it is spectrally separated from the interb and transitions.In additi on,the interband tran sitions lead to severe damping of the local electromagnetic field but the cubic corner LSPR mode survives.Cu nanocubes display an extinction coefficient comparable to the dipole mode of a gold nanosphere with the same volume and show a larger local electromagnetic field enhancement These results will guider-development of in expensive plasmonic copper-based nano materials.展开更多
Changes of Land Use and Land Cover(LULC)affect atmospheric,climatic,and biological spheres of the earth.Accurate LULC map offers detail information for resources management and intergovernmental cooperation to debate ...Changes of Land Use and Land Cover(LULC)affect atmospheric,climatic,and biological spheres of the earth.Accurate LULC map offers detail information for resources management and intergovernmental cooperation to debate global warming and biodiversity reduction.This paper examined effects of pansharpening and atmospheric correction on LULC classification.Object-Based Support Vector Machine(OB-SVM)and Pixel-Based Maximum Likelihood Classifier(PB-MLC)were applied for LULC classification.Results showed that atmospheric correction is not necessary for LULC classification if it is conducted in the original multispectral image.Nevertheless,pansharpening plays much more important roles on the classification accuracy than the atmospheric correction.It can help to increase classification accuracy by 12%on average compared to the ones without pansharpening.PB-MLC and OB-SVM achieved similar classification rate.This study indicated that the LULC classification accuracy using PB-MLC and OB-SVM is 82%and 89%respectively.A combination of atmospheric correction,pansharpening,and OB-SVM could offer promising LULC maps from WorldView-2 multispectral and panchromatic images.展开更多
In the industrial fields, many high temperature structures that require a non-destructive inspection exist. However, there are currently few sensors that can carry out non-destructive testing in a high temperature env...In the industrial fields, many high temperature structures that require a non-destructive inspection exist. However, there are currently few sensors that can carry out non-destructive testing in a high temperature environment. In particular, the ultrasonic sensor is normally not used at over 50 degrees Celsius. Also, a special sensor for high temperature is currently available, but there are various constraints;it has not yet reached a level that is useful in industry. Therefore, we have been developing a new sensor system using a long waveguide which can transmit an ultrasonic wave from a long distance. Especially, this study focuses on applying the developed technique to a pipe which is used in a nuclear power plant. Therefore, the best rectangular-shaped waveguide was studied and attempted to be wound around a pipe to be driven by an acoustic source of a guide wave. Finally, the L (0, 2) and T (0, 1)-mode guide waves were successfully detected by optimizing the shape of the opposite edge of the rectangular-shaped waveguide that could detect the reflected signal from an artificial defect machined into a test pipe.展开更多
The nondestructive inspection of a high temperature structure is required in order to guarantee its safety. However, there are no useful sensors for high temperature structures. Some of them cannot work at temperature...The nondestructive inspection of a high temperature structure is required in order to guarantee its safety. However, there are no useful sensors for high temperature structures. Some of them cannot work at temperatures over 50°C. Another concern is that they are too expensive to use. A sensing system, which can transmit and receive an ultrasonic wave that travels a long distance using a long waveguide, has been studied. We confirmed that the optimal guided ultrasonic wave could travel more than 10 m using an electromagnetic transducer (EMAT) with a thin Ni-sheet surrounded on the surface of the bar and a 2-mm diameter bar as the waveguide. However, we had the difficult problem of receiving the reflected ultrasonic wave from the inside of a test specimen. We tried to improve the trial inspection system using an acoustic horn. An experiment in which the temperature of the test block was heated to about 500°C has now been completed. Finally, the condition of the bend in the waveguide to pass without reflection was confirmed.展开更多
Objective and Impact Statement.There is a need to develop rodent coils capable of targeted brain stimulation for treating neuropsychiatric disorders and understanding brain mechanisms.We describe a novel rodent coil d...Objective and Impact Statement.There is a need to develop rodent coils capable of targeted brain stimulation for treating neuropsychiatric disorders and understanding brain mechanisms.We describe a novel rodent coil design to improve the focality for targeted stimulations in small rodent brains.Introduction.Transcranial magnetic stimulation(TMS)is becoming increasingly important for treating neuropsychiatric disorders and understanding brain mechanisms.Preclinical studies permit invasive manipulations and are essential for the mechanistic understanding of TMS effects and explorations of therapeutic outcomes in disease models.However,existing TMS tools lack focality for targeted stimulations.Notably,there has been limited fundamental research on developing coils capable of focal stimulation at deep brain regions on small animals like rodents.Methods.In this study,ferromagnetic cores are added to a novel angle-tuned coil design to enhance the coil performance regarding penetration depth and focality.Numerical simulations and experimental electric field measurements were conducted to optimize the coil design.Results.The proposed coil system demonstrated a significantly smaller stimulation spot size and enhanced electric field decay rate in comparison to existing coils.Adding the ferromagnetic core reduces the energy requirements up to 60%for rodent brain stimulation.The simulated results are validated with experimental measurements and demonstration of suprathreshold rodent limb excitation through targeted motor cortex activation.Conclusion.The newly developed coils are suitable tools for focal stimulations of the rodent brain due to their smaller stimulation spot size and improved electric field decay rate.展开更多
Moving target detection is one of the most basic tasks in computer vision.In conventional wisdom,the problem is solved by iterative optimization under either Matrix Decomposition(MD)or Matrix Factorization(MF)framewor...Moving target detection is one of the most basic tasks in computer vision.In conventional wisdom,the problem is solved by iterative optimization under either Matrix Decomposition(MD)or Matrix Factorization(MF)framework.MD utilizes foreground information to facilitate background recovery.MF uses noise-based weights to fine-tune the background.So both noise and foreground information contribute to the recovery of the background.To jointly exploit their advantages,inspired by two framework complementary characteristics,we propose to simultaneously exploit the advantages of these two optimizing approaches in a unified framework called Joint Matrix Decomposition and Factorization(JMDF).To improve background extraction,a fuzzy factorization is designed.The fuzzy membership of the background/foreground association is calculated during the factorization process to distinguish their contributions of both to background estimation.To describe the spatio-temporal continuity of foreground more accurately,we propose to incorporate the first order temporal difference into the group sparsity constraint adaptively.The temporal constraint is adjusted adaptively.Both foreground and the background are jointly estimated through an effective alternate optimization process,and the noise can be modeled with the specific probability distribution.The experimental results of vast real videos illustrate the effectiveness of our method.Compared with the current state-of-the-art technology,our method can usually form the clearer background and extract the more accurate foreground.Anti-noise experiments show the noise robustness of our method.展开更多
This paper presents a p-n heterojunction photoanode based on a p-type porphyrin metal-organic framework (MOF) thin film and an n-type rutile titanium dioxide nanorod array for photoelectrochemical water splitting. The...This paper presents a p-n heterojunction photoanode based on a p-type porphyrin metal-organic framework (MOF) thin film and an n-type rutile titanium dioxide nanorod array for photoelectrochemical water splitting. The TiO2@MOF core-shell n anorod array is formed by coati ng an 8 nm thick MOF layer on a vertically aligned TiO2 nanorod array scaffold via a layer-by-layer self-assembly method. This vertically aligned core-shell nanorod array enables a long optical path length but a short path length for extraction of photogenerated minority charge carriers (holes) from TiO2 to the electrolyte. A p-n junction is formed between TiO2 and MOF, which improves the extraction of photogenerated electr ons and holes out of the TiO2 nano rods. In additi on, the MOF coati ng sign ificantly improves the efficie ncy of charge in jecti on at the photoanode/electrolyte interface. Introduction of Co(lll) into the MOF layer further enhances the charge extraction in the photoanode and improves the charge injection efficiency. As a result, the photoelectrochemical cell with the TiO2@Co-MOF nanorod array photoanode exhibits a photocurrent density of 2.93 mA/cm^2 at 1.23 V (vs. RHE), which is ~ 2.7 times the photocurrent achieved with bare T1O2 nanorod array under irradiation of an unfiltered 300 W Xe lamp with an output power density of 100 mW/cm^2.展开更多
Effective exploration of spatiotemporal volumetric data sets remains a key challenge in scientific visualization.Although great advances have been made over the years,existing solutions typically focus on only one or ...Effective exploration of spatiotemporal volumetric data sets remains a key challenge in scientific visualization.Although great advances have been made over the years,existing solutions typically focus on only one or two aspects of data analysis and visualization.A streamlined workflow for analyzing time-varying data in a comprehensive and unified manner is still missing.Towards this goal,we present a novel approach for time-varying data visualization that encompasses keyframe identification,feature extraction and tracking under a single,unified framework.At the heart of our approach lies in the GPU-accelerated BlockMatch method,a dense block correspondence technique that extends the PatchMatch method from 2D pixels to 3D voxels.Based on the results of dense correspondence,we are able to identify keyframes from the time sequence using k-medoids clustering along with a bidirectional similarity measure.Furthermore,in conjunction with the graph cut algorithm,this framework enables us to perform fine-grained feature extraction and tracking.We tested our approach using several time-varying data sets to demonstrate its effectiveness and utility.展开更多
文摘The operation of distribution system with the components in deteriorating condition makes the system reliability worsen. It is important to find the solution for balancing failure cost and maintenance benefits such as down-time and reliability. In this paper, time to replace the components in optimum condition based on constant-interval replacement mode is investigated. The optimal replacement time is mainly depended on component’s reliability and the cost ration of preventive replacement and failure replacement. In this paper, equipment inspection method and Weibull Analysis is applied to obtain the accurate reliability estimation. Weibull Analysis is applied with constant-interval replacement model to investigate the optimum replacement time for each component considering the different cost ratios. According to the quantitative results, the determination of the optimal replacement time (OPT) can minimize the total downtime and failure cost. Consequently, the reliability of the system is maximized and estimation also becomes more accurate due to sufficient approach.
文摘Transmitting a longitudinal wave and a traverse wave into a composite material in a molten state has been studied in the online control of the composite material which cannot be evaluated by a conventional ultrasonic sensor as a final analysis, using the difference in the propagation characteristics of both modes. It is especially expected that measurement of the physical quantity which was not able to be conventionally measured can be performed by carrying out coincidence measurement of the ultrasonic wave in both modes. Therefore, in this research study, an ultrasonic probe, which can simultaneously transmit and receive a longitudinal wave and a traverse wave has been developed using an electromagnetic acoustic transducer (EMAT) because it has the advantage of measuring high temperature samples. In this study, two methods have been compared. The 1st method uses a traverse wave EMAT that travels in a vertical direction and a bar wave by which the low order mode is equivalent to longitudinal wave vibration. The other method is to carry out the mode conversion of the traverse wave by a traverse wave-EMAT. The longitudinal converted from the transverse wave are spread in the axis direction. As the experimental results of both optimizations of the drive conditions, it has been confirmed that the 2nd mode conversion method was promising. This paper reports about the trial process and the experimental results.
基金Project supported by the Changwon National University(2013-2014),Korea
文摘A smartphone-based context-aware augmentative and alternative communication(AAC) was applied was in order to enhance the user's experience by providing simple, adaptive, and intuitive interfaces. Various potential context-aware technologies and AAC usage scenarios were studied, and an efficient communication system was developed by combining smartphone's multimedia functions and its optimized sensor technologies. The experimental results show that context-awareness accuracy is achieved up to 97%.
文摘By using a Fourier series expansion method combined with Chew＇s perfectly matched layers （PMLs）, we analyze the frequency and quality factor of a micro-cavity on a two-dimensional photonic crystal is analyzed. Compared with the results by the method without PML and finite-difference time-domain （FDTD） based on supercell approximation, it can be shown that by the present method with PMLs, the resonant frequency and the quality factor values can be calculated satisfyingly and the characteristics of the micro-cavity can be obtained by changing the size and permittivity of the point defect in the micro-cavity.
基金supported in part by ANRF(No.CRG/2021/003827/EEC)SERB(No.SIRE/SIR/2022/000984)。
文摘Wide-area damping controllers(WADCs)help in damping poorly damped inter-area oscillations(IAOs)using wide-area measurements.However,the vulnerability of the communication network makes the WADC susceptible to malicious dynamic attacks.Existing cyber-resilient WADC solutions rely on accurate power system models or extensive simulation data for training the machine learning(ML)model,which are difficult to obtain for large-scale power system.This paper proposes a novel non-intrusive hybrid two-stage detection framework that mitigates these limitations by eliminating the need for realtime access to large system data or attack samples for training the ML model.In the first stage,an autoencoder is deployed at the actuator location to detect dynamic attacks with sharp gradient variations,e.g.,triangular,saw-tooth,pulse,ramp,and random attack signals.In the second stage,an unscented Kalman filter with unknown input estimation at the control center identifies smoothly varying dynamic attacks by estimating the control signal received by the actuator using synchrophasor measurements.A modified cosine similarity(MCS)metric is proposed to compare and quantify the similarity between the estimated control signal and the control signal sent by the WADC placed at the control center to detect any dynamic attacks.The MCS is designed to differentiate between events and dynamic attacks.The performance of the proposed framework has been validated on a hardware-in-the-loop(HIL)cyber-physical testbed built by using the OPAL-RT simulator and industry-grade hardware.
文摘A sparsifying transform for use in Compressed Sensing (CS) is a vital piece of image reconstruction for Magnetic Resonance Imaging (MRI). Previously, Translation Invariant Wavelet Transforms (TIWT) have been shown to perform exceedingly well in CS by reducing repetitive line pattern image artifacts that may be observed when using orthogonal wavelets. To further establish its validity as a good sparsifying transform, the TIWT is comprehensively investigated and compared with Total Variation (TV), using six under-sampling patterns through simulation. Both trajectory and random mask based under-sampling of MRI data are reconstructed to demonstrate a comprehensive coverage of tests. Notably, the TIWT in CS reconstruction performs well for all varieties of under-sampling patterns tested, even for cases where TV does not improve the mean squared error. This improved Image Quality (IQ) gives confidence in applying this transform to more CS applications which will contribute to an even greater speed-up of a CS MRI scan. High vs low resolution time of flight MRI CS re-constructions are also analyzed showing how partial Fourier acquisitions must be carefully addressed in CS to prevent loss of IQ. In the spirit of reproducible research, novel software is introduced here as FastTestCS. It is a helpful tool to quickly develop and perform tests with many CS customizations. Easy integration and testing for the TIWT and TV minimization are exemplified. Simulations of 3D MRI datasets are shown to be efficiently distributed as a scalable solution for large studies. Comparisons in reconstruction computation time are made between the Wavelab toolbox and Gnu Scientific Library in FastTestCS that show a significant time savings factor of 60×. The addition of FastTestCS is proven to be a fast, flexible, portable and reproducible simulation aid for CS research.
文摘Biodiesel as a renewable alternative to conventional diesel is a growing topic of interest due to its potential environmental benefits.It is typically produced from oilseed crops such as soybean,rapeseed,palm oil,or animal fats.However,its sustainability is debated,primarily because of the reliance on edible oil feedstocks and associated economic and environmental concerns.This study explores alternative,non-edible feedstocks,such as algae and jatropha,that do not compete with food production,offering increased sustainability.Despite their potential,these feedstocks are hindered by high production costs.To address these challenges,innovative approaches in feedstock assessment are imperative for ensuring the long-term viability of biodiesel as an alternative fuel.This review examines explicitly the application of deep learning techniques in selecting and evaluating biodiesel feedstocks.It focuses on their production processes and the chemical and physical properties that impact biodiesel quality.Our comprehensive analysis demonstrates that ANNs provide significant insights into the feedstock assessment process,emerging as a potent tool for identifying new correlations within complex datasets.By leveraging this capability,ANNs can significantly advance biodiesel research,producing more sustainable and efficient feedstock production.The study concludes by highlighting the substantial potential of ANN modeling in contributing to renewable energy strategies and expanding biodiesel research,underscoring its vital role in accelerating the development of biodiesel as a sustainable fuel alternative.
文摘Inexpe nsive copper nano particles are generally thought to possess weak and broad localized surface plasm on resonance(LSPR).The,present experimental and theoretical studies show that tailoring the Cu nanoparticle to a cubic shape results in a single intense,narrow,and asymmetric LSPR line shape,which is even superior to round-shaped gold nanoparticles.In this study,the dielectric function of copper is decomposed into an interband transition component and a free-electron component.This allows interband transition-induced plasmon damping to be visualized both spectrally and by surface polarization charges.The results reveal that the LSPR of Cu nanocubes originates from the comer mode as it is spectrally separated from the interb and transitions.In additi on,the interband tran sitions lead to severe damping of the local electromagnetic field but the cubic corner LSPR mode survives.Cu nanocubes display an extinction coefficient comparable to the dipole mode of a gold nanosphere with the same volume and show a larger local electromagnetic field enhancement These results will guider-development of in expensive plasmonic copper-based nano materials.
基金The authors would like to thank Aerial Survey Office,Forest Bureau of TaiwanROC for their supports in both financial and data collection under the project 102AS-13.3.1-FB-e3.
文摘Changes of Land Use and Land Cover(LULC)affect atmospheric,climatic,and biological spheres of the earth.Accurate LULC map offers detail information for resources management and intergovernmental cooperation to debate global warming and biodiversity reduction.This paper examined effects of pansharpening and atmospheric correction on LULC classification.Object-Based Support Vector Machine(OB-SVM)and Pixel-Based Maximum Likelihood Classifier(PB-MLC)were applied for LULC classification.Results showed that atmospheric correction is not necessary for LULC classification if it is conducted in the original multispectral image.Nevertheless,pansharpening plays much more important roles on the classification accuracy than the atmospheric correction.It can help to increase classification accuracy by 12%on average compared to the ones without pansharpening.PB-MLC and OB-SVM achieved similar classification rate.This study indicated that the LULC classification accuracy using PB-MLC and OB-SVM is 82%and 89%respectively.A combination of atmospheric correction,pansharpening,and OB-SVM could offer promising LULC maps from WorldView-2 multispectral and panchromatic images.
文摘In the industrial fields, many high temperature structures that require a non-destructive inspection exist. However, there are currently few sensors that can carry out non-destructive testing in a high temperature environment. In particular, the ultrasonic sensor is normally not used at over 50 degrees Celsius. Also, a special sensor for high temperature is currently available, but there are various constraints;it has not yet reached a level that is useful in industry. Therefore, we have been developing a new sensor system using a long waveguide which can transmit an ultrasonic wave from a long distance. Especially, this study focuses on applying the developed technique to a pipe which is used in a nuclear power plant. Therefore, the best rectangular-shaped waveguide was studied and attempted to be wound around a pipe to be driven by an acoustic source of a guide wave. Finally, the L (0, 2) and T (0, 1)-mode guide waves were successfully detected by optimizing the shape of the opposite edge of the rectangular-shaped waveguide that could detect the reflected signal from an artificial defect machined into a test pipe.
文摘The nondestructive inspection of a high temperature structure is required in order to guarantee its safety. However, there are no useful sensors for high temperature structures. Some of them cannot work at temperatures over 50°C. Another concern is that they are too expensive to use. A sensing system, which can transmit and receive an ultrasonic wave that travels a long distance using a long waveguide, has been studied. We confirmed that the optimal guided ultrasonic wave could travel more than 10 m using an electromagnetic transducer (EMAT) with a thin Ni-sheet surrounded on the surface of the bar and a 2-mm diameter bar as the waveguide. However, we had the difficult problem of receiving the reflected ultrasonic wave from the inside of a test specimen. We tried to improve the trial inspection system using an acoustic horn. An experiment in which the temperature of the test block was heated to about 500°C has now been completed. Finally, the condition of the bend in the waveguide to pass without reflection was confirmed.
基金supported by the NSF grant ECCS-1631820,NIH grants MH112180,MH108148,MH103222a Brain and Behavior Research Foundation grant.
文摘Objective and Impact Statement.There is a need to develop rodent coils capable of targeted brain stimulation for treating neuropsychiatric disorders and understanding brain mechanisms.We describe a novel rodent coil design to improve the focality for targeted stimulations in small rodent brains.Introduction.Transcranial magnetic stimulation(TMS)is becoming increasingly important for treating neuropsychiatric disorders and understanding brain mechanisms.Preclinical studies permit invasive manipulations and are essential for the mechanistic understanding of TMS effects and explorations of therapeutic outcomes in disease models.However,existing TMS tools lack focality for targeted stimulations.Notably,there has been limited fundamental research on developing coils capable of focal stimulation at deep brain regions on small animals like rodents.Methods.In this study,ferromagnetic cores are added to a novel angle-tuned coil design to enhance the coil performance regarding penetration depth and focality.Numerical simulations and experimental electric field measurements were conducted to optimize the coil design.Results.The proposed coil system demonstrated a significantly smaller stimulation spot size and enhanced electric field decay rate in comparison to existing coils.Adding the ferromagnetic core reduces the energy requirements up to 60%for rodent brain stimulation.The simulated results are validated with experimental measurements and demonstration of suprathreshold rodent limb excitation through targeted motor cortex activation.Conclusion.The newly developed coils are suitable tools for focal stimulations of the rodent brain due to their smaller stimulation spot size and improved electric field decay rate.
基金supported in part by the National Natural Science Foundation of China (Grant No.61902106)in part by the Natural Science Foundation of Hebei Province (No.F2020202028).
文摘Moving target detection is one of the most basic tasks in computer vision.In conventional wisdom,the problem is solved by iterative optimization under either Matrix Decomposition(MD)or Matrix Factorization(MF)framework.MD utilizes foreground information to facilitate background recovery.MF uses noise-based weights to fine-tune the background.So both noise and foreground information contribute to the recovery of the background.To jointly exploit their advantages,inspired by two framework complementary characteristics,we propose to simultaneously exploit the advantages of these two optimizing approaches in a unified framework called Joint Matrix Decomposition and Factorization(JMDF).To improve background extraction,a fuzzy factorization is designed.The fuzzy membership of the background/foreground association is calculated during the factorization process to distinguish their contributions of both to background estimation.To describe the spatio-temporal continuity of foreground more accurately,we propose to incorporate the first order temporal difference into the group sparsity constraint adaptively.The temporal constraint is adjusted adaptively.Both foreground and the background are jointly estimated through an effective alternate optimization process,and the noise can be modeled with the specific probability distribution.The experimental results of vast real videos illustrate the effectiveness of our method.Compared with the current state-of-the-art technology,our method can usually form the clearer background and extract the more accurate foreground.Anti-noise experiments show the noise robustness of our method.
文摘This paper presents a p-n heterojunction photoanode based on a p-type porphyrin metal-organic framework (MOF) thin film and an n-type rutile titanium dioxide nanorod array for photoelectrochemical water splitting. The TiO2@MOF core-shell n anorod array is formed by coati ng an 8 nm thick MOF layer on a vertically aligned TiO2 nanorod array scaffold via a layer-by-layer self-assembly method. This vertically aligned core-shell nanorod array enables a long optical path length but a short path length for extraction of photogenerated minority charge carriers (holes) from TiO2 to the electrolyte. A p-n junction is formed between TiO2 and MOF, which improves the extraction of photogenerated electr ons and holes out of the TiO2 nano rods. In additi on, the MOF coati ng sign ificantly improves the efficie ncy of charge in jecti on at the photoanode/electrolyte interface. Introduction of Co(lll) into the MOF layer further enhances the charge extraction in the photoanode and improves the charge injection efficiency. As a result, the photoelectrochemical cell with the TiO2@Co-MOF nanorod array photoanode exhibits a photocurrent density of 2.93 mA/cm^2 at 1.23 V (vs. RHE), which is ~ 2.7 times the photocurrent achieved with bare T1O2 nanorod array under irradiation of an unfiltered 300 W Xe lamp with an output power density of 100 mW/cm^2.
文摘Effective exploration of spatiotemporal volumetric data sets remains a key challenge in scientific visualization.Although great advances have been made over the years,existing solutions typically focus on only one or two aspects of data analysis and visualization.A streamlined workflow for analyzing time-varying data in a comprehensive and unified manner is still missing.Towards this goal,we present a novel approach for time-varying data visualization that encompasses keyframe identification,feature extraction and tracking under a single,unified framework.At the heart of our approach lies in the GPU-accelerated BlockMatch method,a dense block correspondence technique that extends the PatchMatch method from 2D pixels to 3D voxels.Based on the results of dense correspondence,we are able to identify keyframes from the time sequence using k-medoids clustering along with a bidirectional similarity measure.Furthermore,in conjunction with the graph cut algorithm,this framework enables us to perform fine-grained feature extraction and tracking.We tested our approach using several time-varying data sets to demonstrate its effectiveness and utility.
