A Fast and Memory-Efficient Direct Rendering Method for Polynomial-Based Implicit Surfaces

Three-dimensional surfaces are typically modeled as implicit surfaces.However,direct rendering of implicit surfaces is not simple,especially when such surfaces contain finely detailed shapes.One approach is ray-casting,where the field of the implicit surface is assumed to be piecewise polynomials defined on the grid of a rectangular domain.A critical issue for direct rendering based on ray-casting is the computational cost of finding intersections between surfaces and rays.In particular,ray-casting requires many function evaluations along each ray,severely slowing the rendering speed.In this paper,a method is proposed to achieve direct rendering of polynomial-based implicit surfaces in real-time by strategically narrowing the search range and designing the shader to exploit the structure of piecewise polynomials.In experiments,the proposed method achieved a high framerate performance for different test cases,with a speed-up factor ranging from 1.1 to 218.2.In addition,the proposed method demonstrated better efficiency with high cell resolution.In terms of memory consumption,the proposed method saved between 90.94%and 99.64%in different test cases.Generally,the proposed method became more memoryefficient as the cell resolution increased.

Robust zero-watermarking algorithm based on discrete wavelet transform and daisy descriptors for encrypted medical image

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.

Biomass Control via UV Lamp Application and Nutrient Supply Restriction in the Biofiltration of Gaseous VOCs

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.

Simulation and Analysis of Cascading Faults in Integrated Heat and Electricity Systems Considering Degradation Characteristics

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.

Zero Watermarking Algorithm for Medical Image Based on Resnet50-DCT

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.

Application of 3D Scanned Big Data of Large-scale Cultural Heritage Objects Based on Noise-robust Transparent Visualization

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).

Interactive Restoration of Three-Dimensional Implicit Surface with Irregular Parts

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.

A potential new tool to enhance translational success rate in stroke research by backcrossing techniques in transgenic mice

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.

Robust Watermarking Algorithm for Medical Images Based on Non-Subsampled Shearlet Transform and Schur Decomposition

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.

Vision‐audio fusion SLAM in dynamic environments

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.

Robust Multi-Watermarking Algorithm for Medical Images Based on GoogLeNet and Henon Map

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.

Robust Watermarking Algorithm for Medical Volume Data Based on Polar Cosine Transform and 3D-DCT

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.

Platform Strategies of the Chinese Commercial Drone Manufacturer:A Theoretical and Empirical Study of Ecosystem Development

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.

A Multi-Watermarking Algorithm for Medical Images Using Inception V3 and DCT

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.

恒力法测量制动对兔髌韧带截面面积的影响

目的：介绍一种测量软组织截面面积的装置和方法。方法：用测微仪对膝关节制动前后兔髌韧带截面面积进行反复测量。结果：测微仪的变异系数在０．９％以下，制动６周后髌韧带的截面面积明显增大。

密度指数：形状指数在描述三维图像时的推广

针对将形状指数(SI)应用于三维图像时缺乏对应的推广形式,常通过计算三维图像的3个截面的SI来组合表达,导致在肠道肿瘤检测等应用中造成了大量的误检的问题,研究了三维情形SI的推广.首先选取球坐标系表达的单位球面以消除灰度变化尺度的影响;然后分析了球面的6个等价区域,并选取其一作为灰度变化的表征区域;由于SI原有的表达式不利于推广到三维空间,因此推导了一种等价的表达式,并通过分析此表达式在三维情形的推广,得到了描述三维图像局部灰度变化的指标——密度指数(DI).通过研究DI所表征区域的几何特性,得到了一条具有重要性质的曲线——逆Z线,并分析了其上典型特征点所对应的灰度变化模式.仿真实验结果表明,对于肠道肿瘤检测的典型情况,使用DI检测的误检率明显低于SI.

Microstructures and mechanical properties of extruded 2024 aluminum alloy reinforced by FeNiCrCoAl_3 particles

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.

Effect of mechanical alloying and sintering process on microstructure and mechanical properties of Al-Ni-Y-Co-La alloy

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）.

Effect of mechanical alloying time and rotation speed on evolution of CNTs/Al-2024 composite powders

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.

改进的灰色模型在中国能源消费及其CO_2排放预测中的研究(英文)

中国高速的经济发展导致了快速的能源消费和地球温暖化气体的排放量。本文应用灰色理论建立了中国的终端能源消费量的动态预测模型，同时应用等维递补及带有马尔科夫链符号估计的残差修正，对原始模型进行了改进。后验检验的结果证明了改进的预测模型具有较高的计算精度。预测结果表明，两种经济发展情况（高速及低速）下，从2000年到2030年期间的终端能源消费量的平均增长率将分别达到3．06％和2．18％，2030年CO2 的排放量将分别达到2000年的 2． 15及 1．60倍。其中工业及居民生活的能源消费量的增加速度快于其他部门。这表明了中国将要加快其工业化及都市化的进程．终端消费中，煤炭的消费量所占的比例将要逐年减少，而电力的比例则将逐年增大。