Nickel-manganese binary layered oxides with high working potential and low cost are potential candidates for sodium-ion batteries,but their electrochemical properties are highly related to compositional diversity.Dive...Nickel-manganese binary layered oxides with high working potential and low cost are potential candidates for sodium-ion batteries,but their electrochemical properties are highly related to compositional diversity.Diverse composite materials with various phase structures of P3,P2/P3,P2,P2/O3,and P2/P3/O3 were synthesized by manipulating the sodium content and calcination conditions,leading to the construction of a synthetic phase diagram for Na_(x)Ni_(0.25)Mn_(0.75)O_(2)(0.45≤x≤1.1).Then,we compared the electrochemical characteristics and structural evolution during the desodiation/sodiation process of P2,P2/P3,P2/03,and P2/P3/O3-Na_(x)Ni_(0.25)Mn_(0.75)O_(2).Among them,P2/P3-Na0.75Ni0.25Mn0.75O2exhibits the best rate capability of 90.9 mA h g^(-1)at 5 C,with an initial discharge capacity of 142.62 mA h g^(-1)at 0.1 C and a capacity retention rate of 78.25%after 100 cycles at 1 C in the voltage range of 2-4.3 V.The observed superior sodium storage performance of P2/P3 hybrids compared to other composite phases can be attributed to the enhanced Na^(+)transfer dynamic,reduction of the Jahn-teller effect,and improved reaction reversibility induced by the synergistic effect of P2 and P3 phases.The systematic research and exploration of phases in Na_(x)Ni_(0.25)Mn_(0.75)O_(2)provide new sights into high-performance nickel-manganese binary layered oxide for sodium-ion batteries.展开更多
We propose an arbitrary controlled-unitary(CU) gate and a bidirectional transfer scheme of quantum information(BTQI) for unknown photons.The proposed CU gate utilizes quantum non-demolition photon-number-resolving mea...We propose an arbitrary controlled-unitary(CU) gate and a bidirectional transfer scheme of quantum information(BTQI) for unknown photons.The proposed CU gate utilizes quantum non-demolition photon-number-resolving measurement based on the weak cross-Kerr nonlinearities(XKNLs) and two quantum bus beams;the proposed CU gate consists of consecutive operations of a controlled-path gate and a gathering-path gate.It is almost deterministic and is feasible with current technology when a strong amplitude of the coherent state and weak XKNLs are employed.Compared with the existing optical multi-qubit or controlled gates,which utilize XKNLs and homodyne detectors,the proposed CU gate can increase experimental realization feasibility and enhance robustness against decoherence.According to the CU gate,we present a BTQI scheme in which the two unknown states of photons between two parties(Alice and Bob) are mutually swapped by transferring only a single photon.Consequently,by using the proposed CU gate,it is possible to experimentally implement the BTQI scheme with a certain probability of success.展开更多
Cloud microphysical processes occur at the smallest end of scales among cloud-related processes and thus must be parameterized not only in large-scale global circulation models(GCMs)but also in various higher-resoluti...Cloud microphysical processes occur at the smallest end of scales among cloud-related processes and thus must be parameterized not only in large-scale global circulation models(GCMs)but also in various higher-resolution limited-area models such as cloud-resolving models(CRMs)and large-eddy simulation(LES)models.Instead of giving a comprehensive review of existing microphysical parameterizations that have been developed over the years,this study concentrates purposely on several topics that we believe are understudied but hold great potential for further advancing bulk microphysics parameterizations:multi-moment bulk microphysics parameterizations and the role of the spectral shape of hydrometeor size distributions;discrete vs“continuous”representation of hydrometeor types;turbulence-microphysics interactions including turbulent entrainment-mixing processes and stochastic condensation;theoretical foundations for the mathematical expressions used to describe hydrometeor size distributions and hydrometeor morphology;and approaches for developing bulk microphysics parameterizations.Also presented are the spectral bin scheme and particle-based scheme(especially,super-droplet method)for representing explicit microphysics.Their advantages and disadvantages are elucidated for constructing cloud models with detailed microphysics that are essential to developing processes understanding and bulk microphysics parameterizations.Particle-resolved direct numerical simulation(DNS)models are described as an emerging technique to investigate turbulence-microphysics interactions at the most fundamental level by tracking individual particles and resolving the smallest turbulent eddies in turbulent clouds.Outstanding challenges and future research directions are explored as well.展开更多
Implicit surface generation based on the interpolation of surface points is one of the well-known modeling methods in the area of computer graphics.Several methods for the implicit surface reconstruction from surface ...Implicit surface generation based on the interpolation of surface points is one of the well-known modeling methods in the area of computer graphics.Several methods for the implicit surface reconstruction from surface points have been proposed on the basis of radial basis functions,a weighted sum of local functions,splines,wavelets,and combinations of them.However,if the surface points contain errors or are sparsely distributed,irregular components,such as curvature-shaped redundant bulges and unexpectedly generated high-frequency components,are commonly seen.This paper presents a framework for restoring irregular components generated on and around surfaces.Users are assumed to specify local masks that cover irregular components and parameters that determine the degree of restoration.The algorithm in this paper removes the defects based on the user-specific masks and parameters.Experiments have shown that the proposed methods can effectively remove redundant protrusions and jaggy noise.展开更多
In the intricate network environment,the secure transmission of medical images faces challenges such as information leakage and malicious tampering,significantly impacting the accuracy of disease diagnoses by medical ...In the intricate network environment,the secure transmission of medical images faces challenges such as information leakage and malicious tampering,significantly impacting the accuracy of disease diagnoses by medical professionals.To address this problem,the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi-stage discrete wavelet transform(DWT),Daisy descriptor,and discrete cosine transform(DCT).The algorithm initially encrypts the original medical image through DWT-DCT and Logistic mapping.Subsequently,a 3-stage DWT transformation is applied to the encrypted medical image,with the centre point of the LL3 sub-band within its low-frequency component serving as the sampling point.The Daisy descriptor matrix for this point is then computed.Finally,a DCT transformation is performed on the Daisy descriptor matrix,and the low-frequency portion is processed using the perceptual hashing algorithm to generate a 32-bit binary feature vector for the medical image.This scheme utilises cryptographic knowledge and zero-watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image,which meets the basic re-quirements of medical image watermarking.The embedding and extraction of water-marks are accomplished in a mere 0.160 and 0.411s,respectively,with minimal computational overhead.Simulation results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks,with a notable performance in resisting rotation attacks.展开更多
Deep neural networks perform well in image recognition,object recognition,pattern analysis,and speech recog-nition.In military applications,deep neural networks can detect equipment and recognize objects.In military e...Deep neural networks perform well in image recognition,object recognition,pattern analysis,and speech recog-nition.In military applications,deep neural networks can detect equipment and recognize objects.In military equipment,it is necessary to detect and recognize rifle management,which is an important piece of equipment,using deep neural networks.There have been no previous studies on the detection of real rifle numbers using real rifle image datasets.In this study,we propose a method for detecting and recognizing rifle numbers when rifle image data are insufficient.The proposed method was designed to improve the recognition rate of a specific dataset using data fusion and transfer learningmethods.In the proposed method,real rifle images and existing digit images are fusedas trainingdata,andthe final layer is transferredto theYolov5 algorithmmodel.The detectionand recognition performance of rifle numbers was improved and analyzed using rifle image and numerical datasets.We used actual rifle image data(K-2 rifle)and numeric image datasets,as an experimental environment.TensorFlow was used as the machine learning library.Experimental results show that the proposed method maintains 84.42% accuracy,73.54% precision,81.81% recall,and 77.46% F1-score in detecting and recognizing rifle numbers.The proposed method is effective in detecting rifle numbers.展开更多
Road traffic safety can decrease when drivers drive in a low-visibility environment.The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means...Road traffic safety can decrease when drivers drive in a low-visibility environment.The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents.To tackle the challenges posed by the low recognition accuracy and the substan-tial computational burden associated with current infrared pedestrian-vehicle detection methods,an infrared pedestrian-vehicle detection method A proposal is presented,based on an enhanced version of You Only Look Once version 5(YOLOv5).First,A head specifically designed for detecting small targets has been integrated into the model to make full use of shallow feature information to enhance the accuracy in detecting small targets.Second,the Focal Generalized Intersection over Union(GIoU)is employed as an alternative to the original loss function to address issues related to target overlap and category imbalance.Third,the distribution shift convolution optimization feature extraction operator is used to alleviate the computational burden of the model without significantly compromising detection accuracy.The test results of the improved algorithm show that its average accuracy(mAP)reaches 90.1%.Specifically,the Giga Floating Point Operations Per second(GFLOPs)of the improved algorithm is only 9.1.In contrast,the improved algorithms outperformed the other algorithms on similar GFLOPs,such as YOLOv6n(11.9),YOLOv8n(8.7),YOLOv7t(13.2)and YOLOv5s(16.0).The mAPs that are 4.4%,3%,3.5%,and 1.7%greater than those of these algorithms show that the improved algorithm achieves higher accuracy in target detection tasks under similar computational resource overhead.On the other hand,compared with other algorithms such as YOLOv8l(91.1%),YOLOv6l(89.5%),YOLOv7(90.8%),and YOLOv3(90.1%),the improved algorithm needs only 5.5%,2.3%,8.6%,and 2.3%,respectively,of the GFLOPs.The improved algorithm has shown significant advancements in balancing accuracy and computational efficiency,making it promising for practical use in resource-limited scenarios.展开更多
This study reviews the recent advances in data-driven polarimetric imaging technologies based on a wide range of practical applications.The widespread international research and activity in polarimetric imaging techni...This study reviews the recent advances in data-driven polarimetric imaging technologies based on a wide range of practical applications.The widespread international research and activity in polarimetric imaging techniques demonstrate their broad applications and interest.Polarization information is increasingly incorporated into convolutional neural networks(CNN)as a supplemental feature of objects to improve performance in computer vision task applications.Polarimetric imaging and deep learning can extract abundant information to address various challenges.Therefore,this article briefly reviews recent developments in data-driven polarimetric imaging,including polarimetric descattering,3D imaging,reflection removal,target detection,and biomedical imaging.Furthermore,we synthetically analyze the input,datasets,and loss functions and list the existing datasets and loss functions with an evaluation of their advantages and disadvantages.We also highlight the significance of data-driven polarimetric imaging in future research and development.展开更多
This study experimentally investigates a jet flow issued into a two-layer density-stratified fluid in a tank and the resultant mixing phenomena. The upper and lower fluids are water and a NaCl- water solution, respect...This study experimentally investigates a jet flow issued into a two-layer density-stratified fluid in a tank and the resultant mixing phenomena. The upper and lower fluids are water and a NaCl- water solution, respectively, with the lower fluid issued vertically upward from a circular nozzle mounted on the tank bottom. Experimental highlights of the jet behavior and mixing phenomena are classified into three patterns according to the jet Reynolds number and mass concentration of the NaCl-water solution. The internal density current clearly occurs along the density interface, and the maximum jet height is predicted by the Froude number defined by the density difference between the upper and lower fluids. The effect of fluid thickness on the maximum jet height is also clarified.展开更多
Assays of stress enzymes related to active oxygen species were performed by using an in vitro preparation from the liver of a monkey (Japanese Macaque). Ge-132, an organic germanium compound, viz. poly-trans-[(2-carbo...Assays of stress enzymes related to active oxygen species were performed by using an in vitro preparation from the liver of a monkey (Japanese Macaque). Ge-132, an organic germanium compound, viz. poly-trans-[(2-carboxyethyl) germasesquioxane] [(GeCH2CH2COOH)2O3]n, suppressed the activities of NADH-dependent oxidase and NADPH-dependent oxidase [NAD(P)H-OD] and xanthine oxidase (XOD) as superoxide-forming enzymes, while promoting the activities of superoxide dismutase (SOD) as a superoxide-scavenging enzyme and catalase (CAT) as an enzyme responsible for degradation of hydrogen peroxide (H2O2). The evidence suggests that the levels of active oxygen species such as and H2O2 would be reduced by Ge-132. The possible connection between Ge-132 and activities of stress enzymes is discussed on the basis of these results.展开更多
AIM To perform automatic gastric cancer risk classificationusing photofluorography for realizing effective mass screening as a preliminary study. METHODS We used data for 2100 subjects including X-ray images, pepsinog...AIM To perform automatic gastric cancer risk classificationusing photofluorography for realizing effective mass screening as a preliminary study. METHODS We used data for 2100 subjects including X-ray images, pepsinogen Ⅰ and Ⅱ levels, PGⅠ/PGⅡ ratio, Helicobacter pylori (H. pylori) antibody, H. pylori eradication history and interview sheets. We performed two-stage classification with our system. In the first stage, H. pylori infection status classification was performed, and H. pylori-infected subjects were automatically detected. In the second stage, we performed atrophic level classification to validate the effectiveness of our system.RESULTS Sensitivity, specificity and Youden index(YI) of H. pylori infection status classification were 0.884, 0.895 and 0.779, respectively, in the first stage. In the second stage, sensitivity, specificity and YI of atrophic level classification for H. pylori-infected subjects were 0.777, 0.824 and 0.601, respectively. CONCLUSION Although further improvements of the system are needed, experimental results indicated the effectiveness of machine learning techniques for estimation of gastric cancer risk.展开更多
This study aims to develop an economic evaluation method for installing photovoltaic power generation in ordinary homes using GIS (Geographic Information Systems). The conclusions can be summarized in the following th...This study aims to develop an economic evaluation method for installing photovoltaic power generation in ordinary homes using GIS (Geographic Information Systems). The conclusions can be summarized in the following three points: 1) This method determines the profit and loss and payback period in order to evaluate the installation of photovoltaic power generation, taking into account the price of equipment, solar battery module conversion efficiency, subsidy, electricity purchase price, service life and rate for selling electricity. 2) The proposed evaluation method was applied to Kanagawa Prefecture in Japan, providing plural scenarios. Using a solar battery module conversion efficiency of more than 15%, it is possible to make the payback period shorter than the 20-year service life and anticipate a profit in almost the whole area. 3) The areas suitable for photovoltaic power generation are Kawasaki City and Ninomiya-machi. It is necessary to adopt measures to increase the subsidy and install photovoltaic power generating systems in specific places in areas where subsidies are not provided in enough amounts.展开更多
Demands for low-energy microcontrollers have been increasing in recent years. Since most microcontrollers achieve user programmability by integrating nonvolatile (NV) memories such as flash memories for storing their ...Demands for low-energy microcontrollers have been increasing in recent years. Since most microcontrollers achieve user programmability by integrating nonvolatile (NV) memories such as flash memories for storing their programs, the large power consumption required in accessing an NV memory has become a major problem. This problem becomes critical when the power supply voltage of NV microcontrollers is decreased. We can solve this problem by introducing an instruction cache, thus reducing the access frequency of the NV memory. Unlike general-purpose microprocessors, microcontrollers used for real-time applications in embedded systems must accurately calculate program execution time prior to its execution. Therefore, we introduce a “transparent” instruction cache, which does not change the existing NV microcontroller’s cycle-level execution time, for reducing power and energy consumption, but not for improving the processing speed. We have conducted detailed microar chitecture design based on the architecture of a major industrial microcontroller, and we evaluated power and energy consumption for several benchmark programs. Our evaluation shows that the proposed instruction cache can successfully reduce energy consumption in a fairly wide range of practical NV microcontroller configurations.展开更多
This study experimentally explores the flow around a cylinder with circular cross-section placed inside a bubble plume. Small gas bubbles with diameter smaller than 0.06 mm are released from electrodes on the bottom o...This study experimentally explores the flow around a cylinder with circular cross-section placed inside a bubble plume. Small gas bubbles with diameter smaller than 0.06 mm are released from electrodes on the bottom of a water tank by electrolysis of water. The bubbles induce water flow around them as they rise because of buoyancy. Inside the generated bubble plume, a cylinder with diameter D of 30 mm is placed at 6.5D above the electrodes. The bubbles and water flow around the cylinder are visualized, and the bubble velocity distribution is measured. The experiments elucidate the bubble behavior around the cylinder, the separated shear layers originating at the cylinder surface, their roll-up, the bubble entrainment in the resultant large-scale eddies behind the cylinder, and the vortex shedding from the cylinder.展开更多
This paper presents a self-contained description on the configuration of propagator method(PM)to calculate the electron velocity distribution function(EVDF) of electron swarms in gases under DC electric and magnetic f...This paper presents a self-contained description on the configuration of propagator method(PM)to calculate the electron velocity distribution function(EVDF) of electron swarms in gases under DC electric and magnetic fields crossed at a right angle. Velocity space is divided into cells with respect to three polar coordinates v,θ and f. The number of electrons in each cell is stored in three-dimensional arrays. The changes of electron velocity due to acceleration by the electric and magnetic fields and scattering by gas molecules are treated as intercellular electron transfers on the basis of the Boltzmann equation and are represented using operators called the propagators or Green’s functions. The collision propagator, assuming isotropic scattering, is basically unchanged from conventional PMs performed under electric fields without magnetic fields. On the other hand, the acceleration propagator is customized for rotational acceleration under the action of the Lorentz force. The acceleration propagator specific to the present cell configuration is analytically derived. The mean electron energy and average electron velocity vector in a model gas and SF6 were derived from the EVDF as a demonstration of the PM under the Hall deflection and they were in a fine agreement with those obtained by Monte Carlo simulations. A strategy for fast relaxation is discussed, and extension of the PM for the EVDF under AC electric and DC/AC magnetic fields is outlined as well.展开更多
基金supported by project from the National Natural Science Foundation of China(21805018)by the Sichuan Science and Technology Program(2022ZHCG0018,2023NSFSC0117,2023ZHCG0060)+1 种基金the Yibin Science and Technology Program(2022JB005)project funded by the China Postdoctoral Science Foundation(2022M722704)。
文摘Nickel-manganese binary layered oxides with high working potential and low cost are potential candidates for sodium-ion batteries,but their electrochemical properties are highly related to compositional diversity.Diverse composite materials with various phase structures of P3,P2/P3,P2,P2/O3,and P2/P3/O3 were synthesized by manipulating the sodium content and calcination conditions,leading to the construction of a synthetic phase diagram for Na_(x)Ni_(0.25)Mn_(0.75)O_(2)(0.45≤x≤1.1).Then,we compared the electrochemical characteristics and structural evolution during the desodiation/sodiation process of P2,P2/P3,P2/03,and P2/P3/O3-Na_(x)Ni_(0.25)Mn_(0.75)O_(2).Among them,P2/P3-Na0.75Ni0.25Mn0.75O2exhibits the best rate capability of 90.9 mA h g^(-1)at 5 C,with an initial discharge capacity of 142.62 mA h g^(-1)at 0.1 C and a capacity retention rate of 78.25%after 100 cycles at 1 C in the voltage range of 2-4.3 V.The observed superior sodium storage performance of P2/P3 hybrids compared to other composite phases can be attributed to the enhanced Na^(+)transfer dynamic,reduction of the Jahn-teller effect,and improved reaction reversibility induced by the synergistic effect of P2 and P3 phases.The systematic research and exploration of phases in Na_(x)Ni_(0.25)Mn_(0.75)O_(2)provide new sights into high-performance nickel-manganese binary layered oxide for sodium-ion batteries.
文摘We propose an arbitrary controlled-unitary(CU) gate and a bidirectional transfer scheme of quantum information(BTQI) for unknown photons.The proposed CU gate utilizes quantum non-demolition photon-number-resolving measurement based on the weak cross-Kerr nonlinearities(XKNLs) and two quantum bus beams;the proposed CU gate consists of consecutive operations of a controlled-path gate and a gathering-path gate.It is almost deterministic and is feasible with current technology when a strong amplitude of the coherent state and weak XKNLs are employed.Compared with the existing optical multi-qubit or controlled gates,which utilize XKNLs and homodyne detectors,the proposed CU gate can increase experimental realization feasibility and enhance robustness against decoherence.According to the CU gate,we present a BTQI scheme in which the two unknown states of photons between two parties(Alice and Bob) are mutually swapped by transferring only a single photon.Consequently,by using the proposed CU gate,it is possible to experimentally implement the BTQI scheme with a certain probability of success.
基金supported by the US Department of Energy(DOE)’s Office of Science Atmospheric Systems Research(ASR)Programthe Office of Energy Efficiency and Renewable Energy(EERE)Solar Energy Technologies Office(SETO)award(33504)+3 种基金the Brookhaven National Laboratory(BNL)’s Laboratory Directed Research&Development Program(LDRD)(22-065)The Brookhaven National Laboratory is operated by the Brookhaven Science Associates,LLC(BSA),for the US Department of Energy under Contract No.DESC0012704supported by JSPS KAKENHI Grant No.26286089MEXT KAKENHI Grant No.18H04448。
文摘Cloud microphysical processes occur at the smallest end of scales among cloud-related processes and thus must be parameterized not only in large-scale global circulation models(GCMs)but also in various higher-resolution limited-area models such as cloud-resolving models(CRMs)and large-eddy simulation(LES)models.Instead of giving a comprehensive review of existing microphysical parameterizations that have been developed over the years,this study concentrates purposely on several topics that we believe are understudied but hold great potential for further advancing bulk microphysics parameterizations:multi-moment bulk microphysics parameterizations and the role of the spectral shape of hydrometeor size distributions;discrete vs“continuous”representation of hydrometeor types;turbulence-microphysics interactions including turbulent entrainment-mixing processes and stochastic condensation;theoretical foundations for the mathematical expressions used to describe hydrometeor size distributions and hydrometeor morphology;and approaches for developing bulk microphysics parameterizations.Also presented are the spectral bin scheme and particle-based scheme(especially,super-droplet method)for representing explicit microphysics.Their advantages and disadvantages are elucidated for constructing cloud models with detailed microphysics that are essential to developing processes understanding and bulk microphysics parameterizations.Particle-resolved direct numerical simulation(DNS)models are described as an emerging technique to investigate turbulence-microphysics interactions at the most fundamental level by tracking individual particles and resolving the smallest turbulent eddies in turbulent clouds.Outstanding challenges and future research directions are explored as well.
文摘Implicit surface generation based on the interpolation of surface points is one of the well-known modeling methods in the area of computer graphics.Several methods for the implicit surface reconstruction from surface points have been proposed on the basis of radial basis functions,a weighted sum of local functions,splines,wavelets,and combinations of them.However,if the surface points contain errors or are sparsely distributed,irregular components,such as curvature-shaped redundant bulges and unexpectedly generated high-frequency components,are commonly seen.This paper presents a framework for restoring irregular components generated on and around surfaces.Users are assumed to specify local masks that cover irregular components and parameters that determine the degree of restoration.The algorithm in this paper removes the defects based on the user-specific masks and parameters.Experiments have shown that the proposed methods can effectively remove redundant protrusions and jaggy noise.
基金National Natural Science Foundation of China,Grant/Award Numbers:62063004,62350410483Key Research and Development Project of Hainan Province,Grant/Award Number:ZDYF2021SHFZ093Zhejiang Provincial Postdoctoral Science Foundation,Grant/Award Number:ZJ2021028。
文摘In the intricate network environment,the secure transmission of medical images faces challenges such as information leakage and malicious tampering,significantly impacting the accuracy of disease diagnoses by medical professionals.To address this problem,the authors propose a robust feature watermarking algorithm for encrypted medical images based on multi-stage discrete wavelet transform(DWT),Daisy descriptor,and discrete cosine transform(DCT).The algorithm initially encrypts the original medical image through DWT-DCT and Logistic mapping.Subsequently,a 3-stage DWT transformation is applied to the encrypted medical image,with the centre point of the LL3 sub-band within its low-frequency component serving as the sampling point.The Daisy descriptor matrix for this point is then computed.Finally,a DCT transformation is performed on the Daisy descriptor matrix,and the low-frequency portion is processed using the perceptual hashing algorithm to generate a 32-bit binary feature vector for the medical image.This scheme utilises cryptographic knowledge and zero-watermarking technique to embed watermarks without modifying medical images and can extract the watermark from test images without the original image,which meets the basic re-quirements of medical image watermarking.The embedding and extraction of water-marks are accomplished in a mere 0.160 and 0.411s,respectively,with minimal computational overhead.Simulation results demonstrate the robustness of the algorithm against both conventional attacks and geometric attacks,with a notable performance in resisting rotation attacks.
基金supported by the Future Strategy and Technology Research Institute(RN:23-AI-04)of Korea Military Academythe Hwarang-Dae Research Institute(RN:2023B1015)of Korea Military Academy,and Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2021R1I1A1A01040308).
文摘Deep neural networks perform well in image recognition,object recognition,pattern analysis,and speech recog-nition.In military applications,deep neural networks can detect equipment and recognize objects.In military equipment,it is necessary to detect and recognize rifle management,which is an important piece of equipment,using deep neural networks.There have been no previous studies on the detection of real rifle numbers using real rifle image datasets.In this study,we propose a method for detecting and recognizing rifle numbers when rifle image data are insufficient.The proposed method was designed to improve the recognition rate of a specific dataset using data fusion and transfer learningmethods.In the proposed method,real rifle images and existing digit images are fusedas trainingdata,andthe final layer is transferredto theYolov5 algorithmmodel.The detectionand recognition performance of rifle numbers was improved and analyzed using rifle image and numerical datasets.We used actual rifle image data(K-2 rifle)and numeric image datasets,as an experimental environment.TensorFlow was used as the machine learning library.Experimental results show that the proposed method maintains 84.42% accuracy,73.54% precision,81.81% recall,and 77.46% F1-score in detecting and recognizing rifle numbers.The proposed method is effective in detecting rifle numbers.
文摘Road traffic safety can decrease when drivers drive in a low-visibility environment.The application of visual perception technology to detect vehicles and pedestrians in infrared images proves to be an effective means of reducing the risk of accidents.To tackle the challenges posed by the low recognition accuracy and the substan-tial computational burden associated with current infrared pedestrian-vehicle detection methods,an infrared pedestrian-vehicle detection method A proposal is presented,based on an enhanced version of You Only Look Once version 5(YOLOv5).First,A head specifically designed for detecting small targets has been integrated into the model to make full use of shallow feature information to enhance the accuracy in detecting small targets.Second,the Focal Generalized Intersection over Union(GIoU)is employed as an alternative to the original loss function to address issues related to target overlap and category imbalance.Third,the distribution shift convolution optimization feature extraction operator is used to alleviate the computational burden of the model without significantly compromising detection accuracy.The test results of the improved algorithm show that its average accuracy(mAP)reaches 90.1%.Specifically,the Giga Floating Point Operations Per second(GFLOPs)of the improved algorithm is only 9.1.In contrast,the improved algorithms outperformed the other algorithms on similar GFLOPs,such as YOLOv6n(11.9),YOLOv8n(8.7),YOLOv7t(13.2)and YOLOv5s(16.0).The mAPs that are 4.4%,3%,3.5%,and 1.7%greater than those of these algorithms show that the improved algorithm achieves higher accuracy in target detection tasks under similar computational resource overhead.On the other hand,compared with other algorithms such as YOLOv8l(91.1%),YOLOv6l(89.5%),YOLOv7(90.8%),and YOLOv3(90.1%),the improved algorithm needs only 5.5%,2.3%,8.6%,and 2.3%,respectively,of the GFLOPs.The improved algorithm has shown significant advancements in balancing accuracy and computational efficiency,making it promising for practical use in resource-limited scenarios.
基金support from the National Natural Science Foundation of China(Nos.62205259,62075175,61975254,62375212,62005203 and 62105254)the Open Research Fund of CAS Key Laboratory of Space Precision Measurement Technology(No.B022420004)the Fundamental Research Funds for the Central Universities(No.ZYTS23125).
文摘This study reviews the recent advances in data-driven polarimetric imaging technologies based on a wide range of practical applications.The widespread international research and activity in polarimetric imaging techniques demonstrate their broad applications and interest.Polarization information is increasingly incorporated into convolutional neural networks(CNN)as a supplemental feature of objects to improve performance in computer vision task applications.Polarimetric imaging and deep learning can extract abundant information to address various challenges.Therefore,this article briefly reviews recent developments in data-driven polarimetric imaging,including polarimetric descattering,3D imaging,reflection removal,target detection,and biomedical imaging.Furthermore,we synthetically analyze the input,datasets,and loss functions and list the existing datasets and loss functions with an evaluation of their advantages and disadvantages.We also highlight the significance of data-driven polarimetric imaging in future research and development.
文摘This study experimentally investigates a jet flow issued into a two-layer density-stratified fluid in a tank and the resultant mixing phenomena. The upper and lower fluids are water and a NaCl- water solution, respectively, with the lower fluid issued vertically upward from a circular nozzle mounted on the tank bottom. Experimental highlights of the jet behavior and mixing phenomena are classified into three patterns according to the jet Reynolds number and mass concentration of the NaCl-water solution. The internal density current clearly occurs along the density interface, and the maximum jet height is predicted by the Froude number defined by the density difference between the upper and lower fluids. The effect of fluid thickness on the maximum jet height is also clarified.
文摘Assays of stress enzymes related to active oxygen species were performed by using an in vitro preparation from the liver of a monkey (Japanese Macaque). Ge-132, an organic germanium compound, viz. poly-trans-[(2-carboxyethyl) germasesquioxane] [(GeCH2CH2COOH)2O3]n, suppressed the activities of NADH-dependent oxidase and NADPH-dependent oxidase [NAD(P)H-OD] and xanthine oxidase (XOD) as superoxide-forming enzymes, while promoting the activities of superoxide dismutase (SOD) as a superoxide-scavenging enzyme and catalase (CAT) as an enzyme responsible for degradation of hydrogen peroxide (H2O2). The evidence suggests that the levels of active oxygen species such as and H2O2 would be reduced by Ge-132. The possible connection between Ge-132 and activities of stress enzymes is discussed on the basis of these results.
文摘AIM To perform automatic gastric cancer risk classificationusing photofluorography for realizing effective mass screening as a preliminary study. METHODS We used data for 2100 subjects including X-ray images, pepsinogen Ⅰ and Ⅱ levels, PGⅠ/PGⅡ ratio, Helicobacter pylori (H. pylori) antibody, H. pylori eradication history and interview sheets. We performed two-stage classification with our system. In the first stage, H. pylori infection status classification was performed, and H. pylori-infected subjects were automatically detected. In the second stage, we performed atrophic level classification to validate the effectiveness of our system.RESULTS Sensitivity, specificity and Youden index(YI) of H. pylori infection status classification were 0.884, 0.895 and 0.779, respectively, in the first stage. In the second stage, sensitivity, specificity and YI of atrophic level classification for H. pylori-infected subjects were 0.777, 0.824 and 0.601, respectively. CONCLUSION Although further improvements of the system are needed, experimental results indicated the effectiveness of machine learning techniques for estimation of gastric cancer risk.
文摘This study aims to develop an economic evaluation method for installing photovoltaic power generation in ordinary homes using GIS (Geographic Information Systems). The conclusions can be summarized in the following three points: 1) This method determines the profit and loss and payback period in order to evaluate the installation of photovoltaic power generation, taking into account the price of equipment, solar battery module conversion efficiency, subsidy, electricity purchase price, service life and rate for selling electricity. 2) The proposed evaluation method was applied to Kanagawa Prefecture in Japan, providing plural scenarios. Using a solar battery module conversion efficiency of more than 15%, it is possible to make the payback period shorter than the 20-year service life and anticipate a profit in almost the whole area. 3) The areas suitable for photovoltaic power generation are Kawasaki City and Ninomiya-machi. It is necessary to adopt measures to increase the subsidy and install photovoltaic power generating systems in specific places in areas where subsidies are not provided in enough amounts.
文摘Demands for low-energy microcontrollers have been increasing in recent years. Since most microcontrollers achieve user programmability by integrating nonvolatile (NV) memories such as flash memories for storing their programs, the large power consumption required in accessing an NV memory has become a major problem. This problem becomes critical when the power supply voltage of NV microcontrollers is decreased. We can solve this problem by introducing an instruction cache, thus reducing the access frequency of the NV memory. Unlike general-purpose microprocessors, microcontrollers used for real-time applications in embedded systems must accurately calculate program execution time prior to its execution. Therefore, we introduce a “transparent” instruction cache, which does not change the existing NV microcontroller’s cycle-level execution time, for reducing power and energy consumption, but not for improving the processing speed. We have conducted detailed microar chitecture design based on the architecture of a major industrial microcontroller, and we evaluated power and energy consumption for several benchmark programs. Our evaluation shows that the proposed instruction cache can successfully reduce energy consumption in a fairly wide range of practical NV microcontroller configurations.
文摘This study experimentally explores the flow around a cylinder with circular cross-section placed inside a bubble plume. Small gas bubbles with diameter smaller than 0.06 mm are released from electrodes on the bottom of a water tank by electrolysis of water. The bubbles induce water flow around them as they rise because of buoyancy. Inside the generated bubble plume, a cylinder with diameter D of 30 mm is placed at 6.5D above the electrodes. The bubbles and water flow around the cylinder are visualized, and the bubble velocity distribution is measured. The experiments elucidate the bubble behavior around the cylinder, the separated shear layers originating at the cylinder surface, their roll-up, the bubble entrainment in the resultant large-scale eddies behind the cylinder, and the vortex shedding from the cylinder.
文摘This paper presents a self-contained description on the configuration of propagator method(PM)to calculate the electron velocity distribution function(EVDF) of electron swarms in gases under DC electric and magnetic fields crossed at a right angle. Velocity space is divided into cells with respect to three polar coordinates v,θ and f. The number of electrons in each cell is stored in three-dimensional arrays. The changes of electron velocity due to acceleration by the electric and magnetic fields and scattering by gas molecules are treated as intercellular electron transfers on the basis of the Boltzmann equation and are represented using operators called the propagators or Green’s functions. The collision propagator, assuming isotropic scattering, is basically unchanged from conventional PMs performed under electric fields without magnetic fields. On the other hand, the acceleration propagator is customized for rotational acceleration under the action of the Lorentz force. The acceleration propagator specific to the present cell configuration is analytically derived. The mean electron energy and average electron velocity vector in a model gas and SF6 were derived from the EVDF as a demonstration of the PM under the Hall deflection and they were in a fine agreement with those obtained by Monte Carlo simulations. A strategy for fast relaxation is discussed, and extension of the PM for the EVDF under AC electric and DC/AC magnetic fields is outlined as well.
