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
Biofiltration may have clogging problems owing to excess biomass growth during the treatment of gaseous pollutants.In this study,we employed an UV(Ultraviolet)lamp and controlled the nutrient supply to conduct a biofi...Biofiltration may have clogging problems owing to excess biomass growth during the treatment of gaseous pollutants.In this study,we employed an UV(Ultraviolet)lamp and controlled the nutrient supply to conduct a biofiltration process for treating 2-butanone(MEK:Methyl Ethyl Ketone)and toluene in a gas stream.Two methods of UV lamp usage(direct and indirect irradiation)and several nutrient supply methods were tested.However,no clear effect was observed with either UV usage.Under the optimal conditions,97%of the MEK and 69%of the toluene gases were removed after 29 s of EBRT(Empty Bed Retention Time).The inlet loads were 18 and 19 mg/(m^(3)·h)for MEK and toluene,respectively.Under these conditions,23 g-N/(m^(3)·day)of nitrate-nitrogen was consumed.Excess biomass growth occurred during simultaneous excess nutrient supply and a persistent irrigation schedule.In this study,we demonstrated the effective use of a dense nitrate solution to deliver an appropriate amount of nutrients and moisture,and the optimal irrigation frequency was four times per week.展开更多
Cascading faults have been identified as the primary cause of multiple power outages in recent years.With the emergence of integrated energy systems(IES),the conventional approach to analyzing power grid cascading fau...Cascading faults have been identified as the primary cause of multiple power outages in recent years.With the emergence of integrated energy systems(IES),the conventional approach to analyzing power grid cascading faults is no longer appropriate.A cascading fault analysis method considering multi-energy coupling characteristics is of vital importance.In this study,an innovative analysis method for cascading faults in integrated heat and electricity systems(IHES)is proposed.It considers the degradation characteristics of transmission and energy supply com-ponents in the system to address the impact of component aging on cascading faults.Firstly,degradation models for the current carrying capacity of transmission lines,the water carrying capacity and insulation performance of thermal pipelines,as well as the performance of energy supply equipment during aging,are developed.Secondly,a simulation process for cascading faults in the IHES is proposed.It utilizes an overload-dominated development model to predict the propagation path of cascading faults while also considering network islanding,electric-heating rescheduling,and load shedding.The propagation of cascading faults is reflected in the form of fault chains.Finally,the results of cascading faults under different aging levels are analyzed through numerical examples,thereby verifying the effectiveness and rationality of the proposed model and method.展开更多
Osteogenesis imperfecta(OI)is a disorder of low bone mass and increased fracture risk due to a range of genetic variants that prominently include mutations in genes encoding typeⅠcollagen.While it is well known that ...Osteogenesis imperfecta(OI)is a disorder of low bone mass and increased fracture risk due to a range of genetic variants that prominently include mutations in genes encoding typeⅠcollagen.While it is well known that OI reflects defects in the activity of bone-forming osteoblasts,it is currently unclear whether OI also reflects defects in the many other cell types comprising bone,including defects in skeletal vascular endothelium or the skeletal stem cell populations that give rise to osteoblasts and whether correcting these broader defects could have therapeutic utility.展开更多
Medical images are used as a diagnostic tool, so protecting theirconfidentiality has long been a topic of study. From this, we propose aResnet50-DCT-based zero watermarking algorithm for use with medicalimages. To beg...Medical images are used as a diagnostic tool, so protecting theirconfidentiality has long been a topic of study. From this, we propose aResnet50-DCT-based zero watermarking algorithm for use with medicalimages. To begin, we use Resnet50, a pre-training network, to draw out thedeep features of medical images. Then the deep features are transformedby DCT transform and the perceptual hash function is used to generatethe feature vector. The original watermark is chaotic scrambled to get theencrypted watermark, and the watermark information is embedded into theoriginal medical image by XOR operation, and the logical key vector isobtained and saved at the same time. Similarly, the same feature extractionmethod is used to extract the deep features of the medical image to be testedand generate the feature vector. Later, the XOR operation is carried outbetween the feature vector and the logical key vector, and the encryptedwatermark is extracted and decrypted to get the restored watermark;thenormalized correlation coefficient (NC) of the original watermark and therestored watermark is calculated to determine the ownership and watermarkinformation of the medical image to be tested. After calculation, most ofthe NC values are greater than 0.50. The experimental results demonstratethe algorithm’s robustness, invisibility, and security, as well as its ability toaccurately extract watermark information. The algorithm also shows goodresistance to conventional attacks and geometric attacks.展开更多
Three-dimensional(3D) scanning technology has undergone remarkable developments in recent years.Data acquired by 3D scanning have the form of 3D point clouds.The 3D scanned point clouds have data sizes that can be con...Three-dimensional(3D) scanning technology has undergone remarkable developments in recent years.Data acquired by 3D scanning have the form of 3D point clouds.The 3D scanned point clouds have data sizes that can be considered big data.They also contain measurement noise inherent in measurement data.These properties of 3D scanned point clouds make many traditional CG/visualization techniques difficult.This paper reviewed our recent achievements in developing varieties of high-quality visualizations suitable for the visual analysis of 3D scanned point clouds.We demonstrated the effectiveness of the method by applying the visualizations to various cultural heritage objects.The main visualization targets used in this paper are the floats in the Gion Festival in Kyoto(the float parade is on the UNESCO Intangible Cultural Heritage List) and Borobudur Temple in Indonesia(a UNESCO World Heritage Site).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
Ischemic stroke is a leading disease of the central nervous system,frequently coupled to severe damage and dysfunction in patients.Animal models mimicking human stroke provide useful tools for studying the pathomechan...Ischemic stroke is a leading disease of the central nervous system,frequently coupled to severe damage and dysfunction in patients.Animal models mimicking human stroke provide useful tools for studying the pathomechanisms(e.g.,inflammation,neuroprotection,and neural regeneration),the treatment efficiency of various materials(e.g.,bioactive molecules or drugs),and transplantation usefulness by various cell types[e.g.,neural stem/progenitor cells(NSPCs),and mesenchymal or hematopoietic stem cells]under ischemic stroke.展开更多
With the development of digitalization in healthcare,more and more information is delivered and stored in digital form,facilitating people’s lives significantly.In the meanwhile,privacy leakage and security issues co...With the development of digitalization in healthcare,more and more information is delivered and stored in digital form,facilitating people’s lives significantly.In the meanwhile,privacy leakage and security issues come along with it.Zero watermarking can solve this problem well.To protect the security of medical information and improve the algorithm’s robustness,this paper proposes a robust watermarking algorithm for medical images based on Non-Subsampled Shearlet Transform(NSST)and Schur decomposition.Firstly,the low-frequency subband image of the original medical image is obtained by NSST and chunked.Secondly,the Schur decomposition of low-frequency blocks to get stable values,extracting the maximum absolute value of the diagonal elements of the upper triangle matrix after the Schur decom-position of each low-frequency block and constructing the transition matrix from it.Then,the mean of the matrix is compared to each element’s value,creating a feature matrix by combining perceptual hashing,and selecting 32 bits as the feature sequence.Finally,the feature vector is exclusive OR(XOR)operated with the encrypted watermark information to get the zero watermark and complete registration with a third-party copyright certification center.Experimental data show that the Normalized Correlation(NC)values of watermarks extracted in random carrier medical images are above 0.5,with higher robustness than traditional algorithms,especially against geometric attacks and achieve watermark information invisibility without altering the carrier medical image.展开更多
Moving humans,agents,and subjects bring many challenges to robot self‐localisation and environment perception.To adapt to dynamic environments,SLAM researchers typically apply several deep learning image segmentation...Moving humans,agents,and subjects bring many challenges to robot self‐localisation and environment perception.To adapt to dynamic environments,SLAM researchers typically apply several deep learning image segmentation models to eliminate these moving obstacles.However,these moving obstacle segmentation methods cost too much computation resource for the onboard processing of mobile robots.In the current industrial environment,mobile robot collaboration scenario,the noise of mobile robots could be easily found by on‐board audio‐sensing processors and the direction of sound sources can be effectively acquired by sound source estimation algorithms,but the distance estimation of sound sources is difficult.However,in the field of visual perception,the 3D structure information of the scene is relatively easy to obtain,but the recognition and segmentation of moving objects is more difficult.To address these problems,a novel vision‐audio fusion method that combines sound source localisation methods with a visual SLAM scheme is proposed,thereby eliminating the effect of dynamic obstacles on multi‐agent systems.Several heterogeneous robots experiments in different dynamic scenes indicate very stable self‐localisation and environment reconstruction performance of our method.展开更多
The field of medical images has been rapidly evolving since the advent of the digital medical information era.However,medical data is susceptible to leaks and hacks during transmission.This paper proposed a robust mul...The field of medical images has been rapidly evolving since the advent of the digital medical information era.However,medical data is susceptible to leaks and hacks during transmission.This paper proposed a robust multi-watermarking algorithm for medical images based on GoogLeNet transfer learning to protect the privacy of patient data during transmission and storage,as well as to increase the resistance to geometric attacks and the capacity of embedded watermarks of watermarking algorithms.First,a pre-trained GoogLeNet network is used in this paper,based on which the parameters of several previous layers of the network are fixed and the network is fine-tuned for the constructed medical dataset,so that the pre-trained network can further learn the deep convolutional features in the medical dataset,and then the trained network is used to extract the stable feature vectors of medical images.Then,a two-dimensional Henon chaos encryption technique,which is more sensitive to initial values,is used to encrypt multiple different types of watermarked private information.Finally,the feature vector of the image is logically operated with the encrypted multiple watermark information,and the obtained key is stored in a third party,thus achieving zero watermark embedding and blind extraction.The experimental results confirmthe robustness of the algorithm from the perspective ofmultiple types of watermarks,while also demonstrating the successful embedding ofmultiple watermarks for medical images,and show that the algorithm is more resistant to geometric attacks than some conventional watermarking algorithms.展开更多
The amount of 3D data stored and transmitted in the Internet of Medical Things(IoMT)is increasing,making protecting these medical data increasingly prominent.However,there are relatively few researches on 3D data wate...The amount of 3D data stored and transmitted in the Internet of Medical Things(IoMT)is increasing,making protecting these medical data increasingly prominent.However,there are relatively few researches on 3D data watermarking.Moreover,due to the particularity of medical data,strict data quality should be considered while protecting data security.To solve the problem,in the field of medical volume data,we proposed a robust watermarking algorithm based on Polar Cosine Transform and 3D-Discrete Cosine Transform(PCT and 3D-DCT).Each slice of the volume data was transformed by PCT to obtain feature row vector,and then the reshaped three-dimensional feature matrix was transformed by 3D-DCT.Based on the contour information of the volume data and the detail information of the inner slice,the visual feature vector was obtained by applying the per-ceptual hash.In addition,the watermark was encrypted by a multi-sensitive initial value Sine and Piecewise linear chaotic Mapping(SPM)system,and embedded as a zero watermark.The key was stored in a third party.Under the same experimental conditions,when the volume data is rotated by 80 degrees,cut 25%along the Z axis,and the JPEG compression quality is 1%,the Normalized Correlation Coefficient(NC)of the extracted watermark is 0.80,0.89,and 1.00 respectively,which are significantly higher than the comparison algorithm.展开更多
From the perspective of the business ecosystem,this paper analyzes the competitive advantage and platform strategy of Da-Jiang Innovations Science and Technology Co.,Ltd.(DJI),a Chinese commercial drone manufacturer t...From the perspective of the business ecosystem,this paper analyzes the competitive advantage and platform strategy of Da-Jiang Innovations Science and Technology Co.,Ltd.(DJI),a Chinese commercial drone manufacturer that is currently leading the global commercial drone industry.DJI was established in 2006 and developed the industry’s first core components such as drone control system.DJI released its“Phantom”in the United States in 2013 and occupied the global commercial drone market accounting for 70%in a short period of time.Its market share has maintained its superiority till present.During the inflection transition from the formation of a new ecosystem to expansion,DJI has defended and strengthened its core technology through a strong containment strategic action of competing with GoPro;therefore,DJI has obtained its hub position of multiple markets with bargaining power.In addition,DJI has entered the surrounding markets of corporate market from the general consumer market,and instilled its own product standards&design standards(reference design).Furthermore,it has stimulated and revitalized coexisting companies,individual&corporate customers for expanding the ecosystem of drone industry.展开更多
Medical images are a critical component of the diagnostic process for clinicians.Although the quality of medical photographs is essential to the accuracy of a physician’s diagnosis,they must be encrypted due to the c...Medical images are a critical component of the diagnostic process for clinicians.Although the quality of medical photographs is essential to the accuracy of a physician’s diagnosis,they must be encrypted due to the characteristics of digital storage and information leakage associated with medical images.Traditional watermark embedding algorithm embeds the watermark information into the medical image,which reduces the quality of the medical image and affects the physicians’judgment of patient diagnosis.In addition,watermarks in this method have weak robustness under high-intensity geometric attacks when the medical image is attacked and the watermarks are destroyed.This paper proposes a novel watermarking algorithm using the convolutional neural networks(CNN)Inception V3 and the discrete cosine transform(DCT)to address above mentioned problems.First,the medical image is input into the Inception V3 network,which has been structured by adjusting parameters,such as the size of the convolution kernels and the typical architecture of the convolution modules.Second,the coefficients extracted from the fully connected layer of the network are transformed by DCT to obtain the feature vector of the medical image.At last,the watermarks are encrypted using the logistic map system and hash function,and the keys are stored by a third party.The encrypted watermarks and the original image features are performed logical operations to realize the embedding of zero-watermark.In the experimental section,multiple watermarking schemes using three different types of watermarks were implemented to verify the effectiveness of the three proposed algorithms.Our NC values for all the images are more than 90%accurate which shows the robustness of the algorithm.Extensive experimental results demonstrate the robustness under both conventional and high-intensity geometric attacks of the proposed algorithm.展开更多
Different proportions of commercial 2024 aluminum alloy powder and FeNiCrCoA13 high entropy alloy （HEA） powder were ball-milled （BM） for different time. The powder was consolidated by hot extrusion method. The mic...Different proportions of commercial 2024 aluminum alloy powder and FeNiCrCoA13 high entropy alloy （HEA） powder were ball-milled （BM） for different time. The powder was consolidated by hot extrusion method. The microstructures of the milled powder and bulk alloy were examined by X-ray diffraction （XRD）, scanning electron microscopy （SEM） and transmission electron microscopy （TEM）. Mechanical properties of the extruded alloy were examined by mechanical testing machine. The results show that after BM, the particle size and microstructures of the mixed alloy powder change obviously. After 48 h BM, the average size of mixed powder is about 30 nm, and then after hot extrusion, the average size of grains reaches about 70 rim. The compressive strength of the extruded alloy reaches 710 MPa under certain conditions of milling time and composition. As a result of the identification of the nano-/micro-strueture-property relationship of the samples, such high strength is attributed mainly to the nanocrystalline grains of a（Al） and nanoscaled FeNiCrCoAl3 particles, and the fine secondary phase of Al2Cu and Fe-rich phases.展开更多
Al86Ni7Y4.5Co1La1.5 （mole fraction, %） alloy powder was produced by argon gas atomization process. After high-energy ball milling, the powder was consolidated by vacuum hot press sintering and spark plasma sintering...Al86Ni7Y4.5Co1La1.5 （mole fraction, %） alloy powder was produced by argon gas atomization process. After high-energy ball milling, the powder was consolidated by vacuum hot press sintering and spark plasma sintering （SPS） under different process conditions. The microstructure and morphology of the powder and consolidated bulk sample were examined by X-ray diffraction （XRD）, scanning electron microscopy （SEM） and transmission electron microscopy （TEM）. It is shown that amorphous phase appears when ball milling time is more than 100 h, and the bulk sample consolidated by SPS can maintain amorphous/ nanocrystalline microstructure but has lower relative density. A compressive strength of 650 MPa of Al86Ni7Y4.5Co1La1.5 nanostructured samples is achieved by vacuum hot extrusion （VHE）.展开更多
Carbon nanotubes （CNTs） reinforced aluminum matrix composites were fabricated by mechanical milling followed by hot extrusion. The commercial Al-2024 alloy with 1% CNTs was milled under various ball milling conditio...Carbon nanotubes （CNTs） reinforced aluminum matrix composites were fabricated by mechanical milling followed by hot extrusion. The commercial Al-2024 alloy with 1% CNTs was milled under various ball milling conditions. Microstructure evolution and mechanical properties of the milled powder and consolidated bulk materials were examined by X-ray diffraction （XRD）, field emission scanning electron microscopy （FESEM） and mechanical test. The effect of CNTs concentration and milling time on the microstructure of the CNTs/Al-2024 composites was studied. Based on the structural observation, the formation behavior of nanostructure in ball milled powder was discussed. The results show that the increment in the milling time and ration speed, for a fixed amount of CNTs, causes a reduction of the particle size of powders resulting from MM. The finest particle size was obtained after 15 h of milling. Moreover, the composite had an increase in tensile strength due to the small amount of CNTs addition.展开更多
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.
文摘Biofiltration may have clogging problems owing to excess biomass growth during the treatment of gaseous pollutants.In this study,we employed an UV(Ultraviolet)lamp and controlled the nutrient supply to conduct a biofiltration process for treating 2-butanone(MEK:Methyl Ethyl Ketone)and toluene in a gas stream.Two methods of UV lamp usage(direct and indirect irradiation)and several nutrient supply methods were tested.However,no clear effect was observed with either UV usage.Under the optimal conditions,97%of the MEK and 69%of the toluene gases were removed after 29 s of EBRT(Empty Bed Retention Time).The inlet loads were 18 and 19 mg/(m^(3)·h)for MEK and toluene,respectively.Under these conditions,23 g-N/(m^(3)·day)of nitrate-nitrogen was consumed.Excess biomass growth occurred during simultaneous excess nutrient supply and a persistent irrigation schedule.In this study,we demonstrated the effective use of a dense nitrate solution to deliver an appropriate amount of nutrients and moisture,and the optimal irrigation frequency was four times per week.
基金supported by Shanghai Rising-Star Program(No.22QA1403900)the National Natural Science Foundation of China(No.71804106)the Noncarbon Energy Conversion and Utilization Institute under the Shanghai Class IV Peak Disciplinary Development Program.
文摘Cascading faults have been identified as the primary cause of multiple power outages in recent years.With the emergence of integrated energy systems(IES),the conventional approach to analyzing power grid cascading faults is no longer appropriate.A cascading fault analysis method considering multi-energy coupling characteristics is of vital importance.In this study,an innovative analysis method for cascading faults in integrated heat and electricity systems(IHES)is proposed.It considers the degradation characteristics of transmission and energy supply com-ponents in the system to address the impact of component aging on cascading faults.Firstly,degradation models for the current carrying capacity of transmission lines,the water carrying capacity and insulation performance of thermal pipelines,as well as the performance of energy supply equipment during aging,are developed.Secondly,a simulation process for cascading faults in the IHES is proposed.It utilizes an overload-dominated development model to predict the propagation path of cascading faults while also considering network islanding,electric-heating rescheduling,and load shedding.The propagation of cascading faults is reflected in the form of fault chains.Finally,the results of cascading faults under different aging levels are analyzed through numerical examples,thereby verifying the effectiveness and rationality of the proposed model and method.
基金supported by the National Natural Science Foundation of China (81972034,92068104 and 82002262 to R.X.)the National Key R&D Program of China (2020YFA0112900 to R.X.)+5 种基金Project of Xiamen Cell Therapy Research Center (3502Z20214001 to R.X.)supported by a the NIH grant of US (R01AR075585,R01HD115274,R01CA282815 to M.B.G.)Career Award for Medical Scientists from the Burroughs Wellcome Funda Pershing Square Sohn Cancer Research Alliance and the Maximizing Innovation in Neuroscience Discovery (MIND)Prizesupported by a Jump Start Research Career Development Award from Weill Cornell Medicinea Study Abroad Scholarships from the Mogam Science Scholarship Foundation。
文摘Osteogenesis imperfecta(OI)is a disorder of low bone mass and increased fracture risk due to a range of genetic variants that prominently include mutations in genes encoding typeⅠcollagen.While it is well known that OI reflects defects in the activity of bone-forming osteoblasts,it is currently unclear whether OI also reflects defects in the many other cell types comprising bone,including defects in skeletal vascular endothelium or the skeletal stem cell populations that give rise to osteoblasts and whether correcting these broader defects could have therapeutic utility.
基金supported in part by the Natural Science Foundation of China under Grants 62063004the Key Research Project of Hainan Province under Grant ZDYF2021SHFZ093+1 种基金the Hainan Provincial Natural Science Foundation of China under Grants 2019RC018 and 619QN246the postdoctor research from Zhejiang Province under Grant ZJ2021028.
文摘Medical images are used as a diagnostic tool, so protecting theirconfidentiality has long been a topic of study. From this, we propose aResnet50-DCT-based zero watermarking algorithm for use with medicalimages. To begin, we use Resnet50, a pre-training network, to draw out thedeep features of medical images. Then the deep features are transformedby DCT transform and the perceptual hash function is used to generatethe feature vector. The original watermark is chaotic scrambled to get theencrypted watermark, and the watermark information is embedded into theoriginal medical image by XOR operation, and the logical key vector isobtained and saved at the same time. Similarly, the same feature extractionmethod is used to extract the deep features of the medical image to be testedand generate the feature vector. Later, the XOR operation is carried outbetween the feature vector and the logical key vector, and the encryptedwatermark is extracted and decrypted to get the restored watermark;thenormalized correlation coefficient (NC) of the original watermark and therestored watermark is calculated to determine the ownership and watermarkinformation of the medical image to be tested. After calculation, most ofthe NC values are greater than 0.50. The experimental results demonstratethe algorithm’s robustness, invisibility, and security, as well as its ability toaccurately extract watermark information. The algorithm also shows goodresistance to conventional attacks and geometric attacks.
文摘Three-dimensional(3D) scanning technology has undergone remarkable developments in recent years.Data acquired by 3D scanning have the form of 3D point clouds.The 3D scanned point clouds have data sizes that can be considered big data.They also contain measurement noise inherent in measurement data.These properties of 3D scanned point clouds make many traditional CG/visualization techniques difficult.This paper reviewed our recent achievements in developing varieties of high-quality visualizations suitable for the visual analysis of 3D scanned point clouds.We demonstrated the effectiveness of the method by applying the visualizations to various cultural heritage objects.The main visualization targets used in this paper are the floats in the Gion Festival in Kyoto(the float parade is on the UNESCO Intangible Cultural Heritage List) and Borobudur Temple in Indonesia(a UNESCO World Heritage Site).
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partially supported by Japan Society for the Promotion of Science (JSPS) KAKENHI (JP19K16934to AN-D)+5 种基金Grant-in-Aid for researchers, Hyogo College of Medicine (2018to AN-D)Hyogo College of Medicine Diversity Grant for Research Promotion under MEXT Funds for the Development of Human Resources in Science and Technology, Initiative for Realizing Diversity in the Research Environment (Characteristic-Compatible Type) (2020, 2021to AN-D)Grant-in-Aid for Graduate Students, Hyogo College of Medicine (2021to HN)
文摘Ischemic stroke is a leading disease of the central nervous system,frequently coupled to severe damage and dysfunction in patients.Animal models mimicking human stroke provide useful tools for studying the pathomechanisms(e.g.,inflammation,neuroprotection,and neural regeneration),the treatment efficiency of various materials(e.g.,bioactive molecules or drugs),and transplantation usefulness by various cell types[e.g.,neural stem/progenitor cells(NSPCs),and mesenchymal or hematopoietic stem cells]under ischemic stroke.
基金supported in part by the Natural Science Foundation of China under Grants 62063004the Key Research Project of Hainan Province under Grant ZDYF2021SHFZ093+1 种基金the Hainan Provincial Natural Science Foundation of China under Grants 2019RC018 and 619QN246the postdoctoral research from Zhejiang Province under Grant ZJ2021028.
文摘With the development of digitalization in healthcare,more and more information is delivered and stored in digital form,facilitating people’s lives significantly.In the meanwhile,privacy leakage and security issues come along with it.Zero watermarking can solve this problem well.To protect the security of medical information and improve the algorithm’s robustness,this paper proposes a robust watermarking algorithm for medical images based on Non-Subsampled Shearlet Transform(NSST)and Schur decomposition.Firstly,the low-frequency subband image of the original medical image is obtained by NSST and chunked.Secondly,the Schur decomposition of low-frequency blocks to get stable values,extracting the maximum absolute value of the diagonal elements of the upper triangle matrix after the Schur decom-position of each low-frequency block and constructing the transition matrix from it.Then,the mean of the matrix is compared to each element’s value,creating a feature matrix by combining perceptual hashing,and selecting 32 bits as the feature sequence.Finally,the feature vector is exclusive OR(XOR)operated with the encrypted watermark information to get the zero watermark and complete registration with a third-party copyright certification center.Experimental data show that the Normalized Correlation(NC)values of watermarks extracted in random carrier medical images are above 0.5,with higher robustness than traditional algorithms,especially against geometric attacks and achieve watermark information invisibility without altering the carrier medical image.
基金supported by the Shenzhen Science and Technology Program(JSGG20220606142803007)the Shenzhen Institute of Artificial Intelligence and Robotics for Society(AIRS).
文摘Moving humans,agents,and subjects bring many challenges to robot self‐localisation and environment perception.To adapt to dynamic environments,SLAM researchers typically apply several deep learning image segmentation models to eliminate these moving obstacles.However,these moving obstacle segmentation methods cost too much computation resource for the onboard processing of mobile robots.In the current industrial environment,mobile robot collaboration scenario,the noise of mobile robots could be easily found by on‐board audio‐sensing processors and the direction of sound sources can be effectively acquired by sound source estimation algorithms,but the distance estimation of sound sources is difficult.However,in the field of visual perception,the 3D structure information of the scene is relatively easy to obtain,but the recognition and segmentation of moving objects is more difficult.To address these problems,a novel vision‐audio fusion method that combines sound source localisation methods with a visual SLAM scheme is proposed,thereby eliminating the effect of dynamic obstacles on multi‐agent systems.Several heterogeneous robots experiments in different dynamic scenes indicate very stable self‐localisation and environment reconstruction performance of our method.
基金supported in part by the Natural Science Foundation of China under Grants 62063004the Key Research Project of Hainan Province under Grant ZDYF2021SHF Z093+1 种基金the Hainan Provincial Natural Science Foundation of China under Grants 2019RC018 and 619QN246the postdoctor research from Zhejiang Province under Grant ZJ2021028.
文摘The field of medical images has been rapidly evolving since the advent of the digital medical information era.However,medical data is susceptible to leaks and hacks during transmission.This paper proposed a robust multi-watermarking algorithm for medical images based on GoogLeNet transfer learning to protect the privacy of patient data during transmission and storage,as well as to increase the resistance to geometric attacks and the capacity of embedded watermarks of watermarking algorithms.First,a pre-trained GoogLeNet network is used in this paper,based on which the parameters of several previous layers of the network are fixed and the network is fine-tuned for the constructed medical dataset,so that the pre-trained network can further learn the deep convolutional features in the medical dataset,and then the trained network is used to extract the stable feature vectors of medical images.Then,a two-dimensional Henon chaos encryption technique,which is more sensitive to initial values,is used to encrypt multiple different types of watermarked private information.Finally,the feature vector of the image is logically operated with the encrypted multiple watermark information,and the obtained key is stored in a third party,thus achieving zero watermark embedding and blind extraction.The experimental results confirmthe robustness of the algorithm from the perspective ofmultiple types of watermarks,while also demonstrating the successful embedding ofmultiple watermarks for medical images,and show that the algorithm is more resistant to geometric attacks than some conventional watermarking algorithms.
基金supported in part by the Natural Science Foundation of China under Grants 62063004the Key Research Project of Hainan Province under Grant ZDYF2021SHFZ093+1 种基金the Hainan Provincial Natural Science Foundation of China under Grants 2019RC018 and 619QN246the postdoctor research from Zhejiang Province under Grant ZJ2021028.
文摘The amount of 3D data stored and transmitted in the Internet of Medical Things(IoMT)is increasing,making protecting these medical data increasingly prominent.However,there are relatively few researches on 3D data watermarking.Moreover,due to the particularity of medical data,strict data quality should be considered while protecting data security.To solve the problem,in the field of medical volume data,we proposed a robust watermarking algorithm based on Polar Cosine Transform and 3D-Discrete Cosine Transform(PCT and 3D-DCT).Each slice of the volume data was transformed by PCT to obtain feature row vector,and then the reshaped three-dimensional feature matrix was transformed by 3D-DCT.Based on the contour information of the volume data and the detail information of the inner slice,the visual feature vector was obtained by applying the per-ceptual hash.In addition,the watermark was encrypted by a multi-sensitive initial value Sine and Piecewise linear chaotic Mapping(SPM)system,and embedded as a zero watermark.The key was stored in a third party.Under the same experimental conditions,when the volume data is rotated by 80 degrees,cut 25%along the Z axis,and the JPEG compression quality is 1%,the Normalized Correlation Coefficient(NC)of the extracted watermark is 0.80,0.89,and 1.00 respectively,which are significantly higher than the comparison algorithm.
文摘From the perspective of the business ecosystem,this paper analyzes the competitive advantage and platform strategy of Da-Jiang Innovations Science and Technology Co.,Ltd.(DJI),a Chinese commercial drone manufacturer that is currently leading the global commercial drone industry.DJI was established in 2006 and developed the industry’s first core components such as drone control system.DJI released its“Phantom”in the United States in 2013 and occupied the global commercial drone market accounting for 70%in a short period of time.Its market share has maintained its superiority till present.During the inflection transition from the formation of a new ecosystem to expansion,DJI has defended and strengthened its core technology through a strong containment strategic action of competing with GoPro;therefore,DJI has obtained its hub position of multiple markets with bargaining power.In addition,DJI has entered the surrounding markets of corporate market from the general consumer market,and instilled its own product standards&design standards(reference design).Furthermore,it has stimulated and revitalized coexisting companies,individual&corporate customers for expanding the ecosystem of drone industry.
基金supported in part by Key Research Project of Hainan Province under Grant ZDYF2021SHFZ093the Natural Science Foundation of China under Grants 62063004 and 62162022+2 种基金the Hainan Provincial Natural Science Foundation of China under Grants 2019RC018,521QN206 and 619QN249the Major Scientific Project of Zhejiang Lab 2020ND8AD01the Scientific Research Foundation for Hainan University(No.KYQD(ZR)-21013).
文摘Medical images are a critical component of the diagnostic process for clinicians.Although the quality of medical photographs is essential to the accuracy of a physician’s diagnosis,they must be encrypted due to the characteristics of digital storage and information leakage associated with medical images.Traditional watermark embedding algorithm embeds the watermark information into the medical image,which reduces the quality of the medical image and affects the physicians’judgment of patient diagnosis.In addition,watermarks in this method have weak robustness under high-intensity geometric attacks when the medical image is attacked and the watermarks are destroyed.This paper proposes a novel watermarking algorithm using the convolutional neural networks(CNN)Inception V3 and the discrete cosine transform(DCT)to address above mentioned problems.First,the medical image is input into the Inception V3 network,which has been structured by adjusting parameters,such as the size of the convolution kernels and the typical architecture of the convolution modules.Second,the coefficients extracted from the fully connected layer of the network are transformed by DCT to obtain the feature vector of the medical image.At last,the watermarks are encrypted using the logistic map system and hash function,and the keys are stored by a third party.The encrypted watermarks and the original image features are performed logical operations to realize the embedding of zero-watermark.In the experimental section,multiple watermarking schemes using three different types of watermarks were implemented to verify the effectiveness of the three proposed algorithms.Our NC values for all the images are more than 90%accurate which shows the robustness of the algorithm.Extensive experimental results demonstrate the robustness under both conventional and high-intensity geometric attacks of the proposed algorithm.
基金Project(2012CB619503)supported by the Nation Basic Research Program of ChinaProject(2013AA031001)supported by the National High Technology Research and Development Program of ChinaProject(2012DFA50630)supported by the International Science&Technology Cooperation Program of China
文摘Different proportions of commercial 2024 aluminum alloy powder and FeNiCrCoA13 high entropy alloy （HEA） powder were ball-milled （BM） for different time. The powder was consolidated by hot extrusion method. The microstructures of the milled powder and bulk alloy were examined by X-ray diffraction （XRD）, scanning electron microscopy （SEM） and transmission electron microscopy （TEM）. Mechanical properties of the extruded alloy were examined by mechanical testing machine. The results show that after BM, the particle size and microstructures of the mixed alloy powder change obviously. After 48 h BM, the average size of mixed powder is about 30 nm, and then after hot extrusion, the average size of grains reaches about 70 rim. The compressive strength of the extruded alloy reaches 710 MPa under certain conditions of milling time and composition. As a result of the identification of the nano-/micro-strueture-property relationship of the samples, such high strength is attributed mainly to the nanocrystalline grains of a（Al） and nanoscaled FeNiCrCoAl3 particles, and the fine secondary phase of Al2Cu and Fe-rich phases.
基金Project(2012CB619503)supported by the National Basic Research Program of ChinaProject(2013AA031001)supported by the National High Technology Research and Development Program of ChinaProject(2012DFA50630)supported by the International Science&Technology Cooperation Program of China
文摘Al86Ni7Y4.5Co1La1.5 （mole fraction, %） alloy powder was produced by argon gas atomization process. After high-energy ball milling, the powder was consolidated by vacuum hot press sintering and spark plasma sintering （SPS） under different process conditions. The microstructure and morphology of the powder and consolidated bulk sample were examined by X-ray diffraction （XRD）, scanning electron microscopy （SEM） and transmission electron microscopy （TEM）. It is shown that amorphous phase appears when ball milling time is more than 100 h, and the bulk sample consolidated by SPS can maintain amorphous/ nanocrystalline microstructure but has lower relative density. A compressive strength of 650 MPa of Al86Ni7Y4.5Co1La1.5 nanostructured samples is achieved by vacuum hot extrusion （VHE）.
基金Project(2012CB619503)supported by the National Basic Research Program of ChinaProject(2013AA031001)supported by the National High-tech Research and Development Program of ChinaProject(2012DFA50630)supported by the International Science&Technology Cooperation Program of China
文摘Carbon nanotubes （CNTs） reinforced aluminum matrix composites were fabricated by mechanical milling followed by hot extrusion. The commercial Al-2024 alloy with 1% CNTs was milled under various ball milling conditions. Microstructure evolution and mechanical properties of the milled powder and consolidated bulk materials were examined by X-ray diffraction （XRD）, field emission scanning electron microscopy （FESEM） and mechanical test. The effect of CNTs concentration and milling time on the microstructure of the CNTs/Al-2024 composites was studied. Based on the structural observation, the formation behavior of nanostructure in ball milled powder was discussed. The results show that the increment in the milling time and ration speed, for a fixed amount of CNTs, causes a reduction of the particle size of powders resulting from MM. The finest particle size was obtained after 15 h of milling. Moreover, the composite had an increase in tensile strength due to the small amount of CNTs addition.
