Stratigraphy of the MSGBC Basin in the Western Part of Thies by Pixelation and Website Simulation (Senegal, West Africa)

During this research work we developed another approach to digital mapping using the pixelation technic. This unprecedented digital mapping of the basin MSGBC in Senegal required the compilation of numerous geological data consisting of seismic lines and oil and hydraulic log reports. These spatial reference data include geological information from the surface to the top of the Campanian. The mapped terrains are composed of the Post-Paleocene Complex (PPC), the Paleocene, the Maastrichtian, and the Campanian. The nearest neighbor method has been used to establish the spatial distribution of the different geological formations. Histograms of values were used to determine the confidence intervals of the mapping. They were used to locate areas of low relative error and to apply the 3D digital mapping technique. For instance, Diender Guedj has been mapped at 1:25,000. The result of this mapping is extracted and processed using the DBMS (MySQL) software. The latter allowed both to determine Paleocene gab and update data. And then the database is processed. The programming languages PHP and Javascript have been used to simulate a website.

结合Pixel2style2Pixel的年龄转化方法

年龄转化在刑侦、人脸识别等领域有着重要作用。常见的年龄转化方法需要使用成对带有年龄注释的数据集进行训练,并且存在生成图像质量低、年龄语义信息不够解耦等问题。针对上述问题,在Pix2style2Pix的训练框架中,引入年龄识别、contextual损失函数,对整体损失函数做出符合年龄转化的改进,提取年龄信息并保证图像质量。改进编码网络配合损失函数对潜在空间的图像进行编辑,提出一种基于Pixel2style2Pixel的年龄转化方法。通过FFHQ、CelebA数据集,对所提方法进行验证,实验结果表明,在不采用成对年龄注释的训练集下,改进后的损失函数能生成更符合期望年龄的转化图像,人脸相似度距离为0.346、FID为45.69、SSIM为0.593 6、PSNR为19.64 dB,均优于对比方法,证明所提方法能够生成高质量、年龄语义高度解耦的转化结果。

Monitoring Surface Deformation Using Distributed Scatterers InSAR

In the past two decades,extensive and in-depth research has been conducted on Time Series InSAR technology with the advancement of high-performance SAR satellites and the accumulation of big SAR data.The introduction of distributed scatterers in Distributed Scatterers InSAR(DS-InSAR)has significantly expanded the application scenarios of InSAR geodetic measurement by increasing the number of measurement points.This study traces the history of DS-InSAR,presents the definition and characteristics of distributed scatterers,and focuses on exploring the relationships and distinctions among proposed algorithms in two crucial steps:statistically homogeneous pixel selection and phase optimization.Additionally,the latest research progress in this field is tracked and the possible development direction in the future is discussed.Through simulation experiments and two real InSAR case studies,the proposed algorithms are compared and verified,and the advantages of DS-InSAR in deformation measurement practice are demonstrated.This work not only offers insights into current trends and focal points for theoretical research on DS-InSAR but also provides practical cases and guidance for applied research.

OML:an online multi-particle locating method for high-resolution single-event effects studies

Identifying sensitive areas in integrated circuits susceptible to single-event effects(SEE)is crucial for improving radiation hardness.This study presents an online multi-track location(OML)framework to enhance the high-resolution online trajectory detection for the Hi’Beam-SEE system,which aims to localize SEE-sensitive positions on the IC at the micrometer scale and in real time.We employed a reparameterization method to accelerate the inference speed,merging the branches of the backbone of the location in the deployment scenario.Additionally,we designed an irregular convolution kernel,an attention mechanism,and a fused loss function to improve the positioning accuracy.OML demonstrates exceptional realtime processing capabilities,achieving a positioning accuracy of 1.83μm in processing data generated by the Hi’Beam-SEE system at 163 frames per second per GPU.

Double quantum images encryption scheme based on chaotic system

This paper explores a double quantum images representation(DNEQR)model that allows for simultaneous storage of two digital images in a quantum superposition state.Additionally,a new type of two-dimensional hyperchaotic system based on sine and logistic maps is investigated,offering a wider parameter space and better chaotic behavior compared to the sine and logistic maps.Based on the DNEQR model and the hyperchaotic system,a double quantum images encryption algorithm is proposed.Firstly,two classical plaintext images are transformed into quantum states using the DNEQR model.Then,the proposed hyperchaotic system is employed to iteratively generate pseudo-random sequences.These chaotic sequences are utilized to perform pixel value and position operations on the quantum image,resulting in changes to both pixel values and positions.Finally,the ciphertext image can be obtained by qubit-level diffusion using two XOR operations between the position-permutated image and the pseudo-random sequences.The corresponding quantum circuits are also given.Experimental results demonstrate that the proposed scheme ensures the security of the images during transmission,improves the encryption efficiency,and enhances anti-interference and anti-attack capabilities.

Effect of multiple coulomb scattering on the beam tests of silicon pixel detectors

In the research and development of new silicon pixel detectors,a collimated monoenergetic charged-particle test beam equipped with a high-resolution pixel-beam telescope is crucial for prototype verification and performance evaluation.When the beam energy is low,the effect of multiple Coulomb scattering on the measured resolution of the Device Under Test(DUT)must be considered to accurately evaluate the performance of the pixel chips and detectors.This study aimed to investigate the effect of multiple Coulomb scattering on the measured resolution,particularly at low beam energies.Simulations were conducted using Allpix^(2) to study the effects of multiple Coulomb scattering under different beam energies,material budgets,and telescope layouts.The simulations also provided the minimum energy at which the effect of multiple Coulomb scattering could be ignored.Compared with the results of a five-layer detector system tested with an electron beam at DESY,the simulation results were consistent with the beam test results,confirming the reliability of the simulations.

High-Secured Image LSB Steganography Using AVL-Tree with Random RGB Channel Substitution

Random pixel selection is one of the image steganography methods that has achieved significant success in enhancing the robustness of hidden data.This property makes it difficult for steganalysts’powerful data extraction tools to detect the hidden data and ensures high-quality stego image generation.However,using a seed key to generate non-repeated sequential numbers takes a long time because it requires specific mathematical equations.In addition,these numbers may cluster in certain ranges.The hidden data in these clustered pixels will reduce the image quality,which steganalysis tools can detect.Therefore,this paper proposes a data structure that safeguards the steganographic model data and maintains the quality of the stego image.This paper employs the AdelsonVelsky and Landis(AVL)tree data structure algorithm to implement the randomization pixel selection technique for data concealment.The AVL tree algorithm provides several advantages for image steganography.Firstly,it ensures balanced tree structures,which leads to efficient data retrieval and insertion operations.Secondly,the self-balancing nature of AVL trees minimizes clustering by maintaining an even distribution of pixels,thereby preserving the stego image quality.The data structure employs the pixel indicator technique for Red,Green,and Blue(RGB)channel extraction.The green channel serves as the foundation for building a balanced binary tree.First,the sender identifies the colored cover image and secret data.The sender will use the two least significant bits(2-LSB)of RGB channels to conceal the data’s size and associated information.The next step is to create a balanced binary tree based on the green channel.Utilizing the channel pixel indicator on the LSB of the green channel,we can conceal bits in the 2-LSB of the red or blue channel.The first four levels of the data structure tree will mask the data size,while subsequent levels will conceal the remaining digits of secret data.After embedding the bits in the binary tree level by level,the model restores the AVL tree to create the stego image.Ultimately,the receiver receives this stego image through the public channel,enabling secret data recovery without stego or crypto keys.This method ensures that the stego image appears unsuspicious to potential attackers.Without an extraction algorithm,a third party cannot extract the original secret information from an intercepted stego image.Experimental results showed high levels of imperceptibility and security.

Image encryption algorithm based on multiple chaotic systems and improved Joseph block scrambling

With the rapid development of digital information technology,images are increasingly used in various fields.To ensure the security of image data,prevent unauthorized tampering and leakage,maintain personal privacy,and protect intellectual property rights,this study proposes an innovative color image encryption algorithm.Initially,the Mersenne Twister algorithm is utilized to generate high-quality pseudo-random numbers,establishing a robust basis for subsequent operations.Subsequently,two distinct chaotic systems,the autonomous non-Hamiltonian chaotic system and the tentlogistic-cosine chaotic mapping,are employed to produce chaotic random sequences.These chaotic sequences are used to control the encoding and decoding process of the DNA,effectively scrambling the image pixels.Furthermore,the complexity of the encryption process is enhanced through improved Joseph block scrambling.Thorough experimental verification,research,and analysis,the average value of the information entropy test data reaches as high as 7.999.Additionally,the average value of the number of pixels change rate(NPCR)test data is 99.6101%,which closely approaches the ideal value of 99.6094%.This algorithm not only guarantees image quality but also substantially raises the difficulty of decryption.

西安电子科技大学陈晓峰团队研究成果被USENIX Security收录

近日,第33届USENIX Security Symposium (USENIX Security 2024)在美国费城召开。西安电子科技大学网络与信息安全学院陈晓峰教授团队的最新研究成果“Pixel+and Pixel++:Compact and Efficient Forward-Secure Multi-Signatures for Po S Blockchain Consensus”被大会全文录用。该研究成果由西安电子科技大学、南开大学和伍伦贡大学(University of Wollongong)合作完成,第一作者为陈晓峰教授合作指导的博士后魏江宏。

Hi'CT:a pixel sensor-based device for ion tomography

Carbon ions,commonly referred to as particle therapy,have become increasingly popular in the last decade.Accurately predicting the range of ions in tissues is important for the precise delivery of doses in heavy-ion radiotherapy.Range uncertainty is currently the largest contributor to dose uncertainty in normal tissues,leading to the use of safety margins in treatment planning.One potential method is the direct relative stopping measurement(RSP)with ions.Heavy-ion CT(Hi′CT),a compact segmented full digital tomography detector using monolithic active pixel sensors,was designed and evaluated using a 430 MeV/u high-energy carbon ion pencil beam in Geant4.The precise position of the individual carbon ion track can be recorded and reconstructed using a 30μm×30μm small pixel pitch size.Two types of customized image reconstruction algorithms were developed,and their performances were evaluated using three different modules of CAT-PHAN 600-series phantoms.The RSP measurement accuracy of the tracking algorithm for different types of materials in the CTP404 module was less than 1%.In terms of spatial resolution,the tracking algorithm could achieve a 20%modulation transfer function normalization value of CTP528 imaging results at 5 lp/cm,which is significantly better than that of the fast imaging algorithm(3 lp/cm).The density resolution obtained using the tracking algorithm of the customized CTP515 was approximately 10.5%.In conclusion,a compact digital Hi'CT system was designed,and its nominal performance was evaluated in a simulation.The RSP resolution and image quality provide potential feasibility for scanning most parts of an adult body or pediatric patient,particularly for head and neck tumor treatment.

Electronics system for the cosmic X-ray polarization detector

This study presents an electronics system for cosmic X-ray polarization detection(CXPD).The CXPD was designed as a high-sensitivity soft X-ray polarimeter with a measurement energy range of 2-10 keV carried by a CubeSat.A stable and functionally complete electronics system under power and space constraints is a key challenge.The complete CXPD electronics system(CXPDES)comprises hardware and firmware.CXPDES adopts a three-layer electronic board structure based on functionality and available space.Two gas pixel detectors(GPDs)were placed on the top layer board,and CXPDES provided the GPDs with voltages up to-4000 V.Each GPD signal was digitized,compressed,encoded,and stored before being transmitted to the ground.The CXPDES provided stable and high-speed communication based on a scheme that separated command and data transmission,and it supports the CXPDES in-orbit upgrade.In addition,environmental monitors,silicon photomultiplier(SiPM)triggers,power management,GPDs configuration,and mode switches were included in the overall operating logic of the CXPDES.The results obtained by testing the CXPDES showed that it satisfied all the requirements of CXPD.The CXPDES provides design experience and technological readiness for future large-area X-ray polarimetry missions.

单图像超分辨率多尺度特征融合网络

提出一种用于单图像超分辨率任务的多尺度特征融合网络,该网络包含特征下采样、多尺度特征融合和增加额外约束方案。首先,构建了包含Pixel⁃Unshuffle操作的特征下采样模块获得浅层多尺度特征,进一步学习深层多尺度特征融合,并通过多尺度特征融合提高超分辨率性能。此外,使用包含Pixel⁃Unshuffle操作的特征下采样模块从SR图像中重建LR图像,并计算其与LR图像之间的损失增加额外约束。大量的实验证明,提出的方法与现有的方法相比表现出具有竞争力的性能。

A Novel Detection Method for Pavement Crack with Encoder-Decoder Architecture

As a current popular method,intelligent detection of cracks is of great significance to road safety,so deep learning has gradually attracted attention in the field of crack image detection.The nonlinear structure,low contrast and discontinuity of cracks bring great challenges to existing crack detection methods based on deep learning.Therefore,an end-to-end deep convolutional neural network(AttentionCrack)is proposed for automatic crack detection to overcome the inaccuracy of boundary location between crack and non-crack pixels.The AttentionCrack network is built on U-Net based encoder-decoder architecture,and an attention mechanism is incorporated into the multi-scale convolutional feature to enhance the recognition of crack region.Additionally,a dilated convolution module is introduced in the encoder-decoder architecture to reduce the loss of crack detail due to the pooling operation in the encoder network.Furthermore,since up-sampling will lead to the loss of crack boundary information in the decoder network,a depthwise separable residual module is proposed to capture the boundary information of pavement crack.The AttentionCrack net on public pavement crack image datasets named CrackSegNet and Crack500 is trained and tested,the results demonstrate that the AttentionCrack achieves F1 score over 0.70 on the CrackSegNet and 0.71 on the Crack500 in average and outperforms the current state-of-the-art methods.

An online fast multi-track locating algorithm for high-resolution single-event effect test platform

To improve the efficiency and accuracy of single-event effect(SEE)research at the Heavy Ion Research Facility at Lanzhou,Hi’Beam-SEE must precisely localize the position at which each heavy ion hitting the integrated circuit(IC)causes SEE.In this study,we propose a fast multi-track location(FML)method based on deep learning to locate the position of each particle track with high speed and accuracy.FML can process a vast amount of data supplied by Hi’Beam-SEE online,revealing sensitive areas in real time.FML is a slot-based object-centric encoder-decoder structure in which each slot can learn the location information of each track in the image.To make the method more accurate for real data,we designed an algorithm to generate a simulated dataset with a distribution similar to that of the real data,which was then used to train the model.Extensive comparison experiments demonstrated that the FML method,which has the best performance on simulated datasets,has high accuracy on real datasets as well.In particular,FML can reach 238 fps and a standard error of 1.6237μm.This study discusses the design and performance of FML.

Pixel 2940nm点阵激光联合他克莫司软膏治疗肢端型白癜风的临床观察

目的:观察Pixel 2 940 nm点阵激光联合他克莫司软膏治疗肢端型白癜风的临床效果。方法:选取梅州市第二中医医院2019年5月-2021年5月收治的肢端型白癜风患者62例为研究对象,按照随机数字表法将其分为治疗组和对照组,各31例。对照组予以他克莫司软膏治疗,治疗组予以Pixel 2 940 nm点阵激光联合他克莫司软膏治疗。两组均以12周为1个疗程,共治疗2个疗程。对比两组临床疗效、不良反应发生率和复发率。结果:治疗12、24周后,治疗组总有效率(45.16%、70.97%)均明显高于对照组(19.35%、41.94%)(P<0.05);治疗期间对照组不良反应发生率为12.90%,明显低于治疗组的41.94%(P<0.05);治疗组复发率为4.55%(1/22),低于对照组的61.54%(8/13)(P<0.05)。结论:Pixel 2 940 nm点阵激光联合他克莫司软膏治疗肢端型白癜风虽会增加不良反应,但见效快,临床疗效好,能够显著降低复发率,值得在临床上推广应用。

Optimization of desert lake information extraction from remote sensing images using cellular automata

Desert lakes are important wetland resources in the blown-sand area of western China and play a significant role in maintain-ing the regional ecological environment.However,large-scale coal mining in recent years has considerably impacted the deposition condition of several lakes.Rapid and accurate extraction of lake information based on satellite images is crucial for developing protective measures against desertification.However,the spatial resolution of these images often leads to mixed pixels near water boundaries,affecting extraction precision.Traditional pixel unmixing methods mainly obtain water coverage information in a mixed pixel,making it difficult to accurately describe the spatial distribution.In this paper,the cellular automata(CA)model was adopted in order to realize lake information extraction at a sub-pixel level.A mining area in Shenmu City,Shaanxi Province,China is selected as the research region,using the image of Sentinel-2 as the data source and the high spatial resolution UAV image as the reference.First,water coverage of mixed pixels in the Sentinel-2 image was calculated with the dimidiate pixel model and the fully constrained least squares(FCLS)method.Second,the mixed pixels were subdivided to form the cellular space at a sub-pixel level and the transition rules are constructed based on the water coverage information and spatial correlation.Lastly,the process was implemented using Python and IDL,with the ArcGIS and ENVI software being used for validation.The experiments show that the CA model can improve the sub-pixel positioning accuracy for lake bodies in mixed pixel image and improve classification accuracy.The FCLS-CA model has a higher accuracy and is able to identify most water bodies in the study area,and is therefore suitable for desert lake monitor-ing in mining areas.

Efficient Technique for Image Cryptography Using Sudoku Keys

This paper proposes a cryptographic technique on images based on the Sudoku solution.Sudoku is a number puzzle,which needs applying defined protocols and filling the empty boxes with numbers.Given a small size of numbers as input,solving the sudoku puzzle yields an expanded big size of numbers,which can be used as a key for the Encryption/Decryption of images.In this way,the given small size of numbers can be stored as the prime key,which means the key is compact.A prime key clue in the sudoku puzzle always leads to only one solution,which means the key is always stable.This feature is the background for the paper,where the Sudoku puzzle output can be innovatively introduced in image cryptography.Sudoku solution is expanded to any size image using a sequence of expansion techniques that involve filling of the number matrix,Linear X-Y rotational shifting,and reverse shifting based on a standard zig-zag pattern.The crypto key for an image dictates the details of positions,where the image pixels have to be shuffled.Shuffling is made at two levels,namely pixel and sub-pixel(RGB)levels for an image,with the latter having more effective Encryption.The brought-out technique falls under the Image scrambling method with partial diffusion.Performance metrics are impressive and are given by a Histogram deviation of 0.997,a Correlation coefficient of 10−2 and an NPCR of 99.98%.Hence,it is evident that the image cryptography with the sudoku kept in place is more efficient against Plaintext and Differential attacks.

Adaptive Noise Detector and Partition Filter for Image Restoration

The random-value impulse noise(RVIN)detection approach in image denoising,which is dependent on manually defined detection thresholds or local window information,does not have strong generalization performance and cannot successfully cope with damaged pictures with high noise levels.The fusion of the K-means clustering approach in the noise detection stage is reviewed in this research,and the internal relationship between the flat region and the detail area of the damaged picture is thoroughly explored to suggest an unique two-stage method for gray image denoising.Based on the concept of pixel clustering and grouping,all pixels in the damaged picture are separated into various groups based on gray distance similarity features,and the best detection threshold of each group is solved to identify the noise.In the noise reduction step,a partition decision filter based on the gray value characteristics of pixels in the flat and detail areas is given.For the noise pixels in flat and detail areas,local consensus index(LCI)weighted filter and edge direction filter are designed respectively to recover the pixels damaged by the RVIN.The experimental results show that the accuracy of the proposed noise detection method is more than 90%,and is superior to most mainstream methods.At the same time,the proposed filtering method not only has good noise reduction and generalization performance for natural images and medical images with medium and high noise but also is superior to other advanced filtering technologies in visual effect and objective quality evaluation.

Development and preliminary results of a large-pixel two-layer LaBr_(3) Compton camera prototype

Lanthanum bromide(LaBr_(3))crystal has a high energy resolution and time resolution and has been used in Compton cameras(CCs)over the past few decades.However,LaBr_(3) crystal arrays are difficult to process because LaBr_(3) is easy to crack and break;thus,few LaBr_(3)-based CC prototypes have been built.In this study,we designed and fabricated a large-pixel LaBr_(3) CC prototype and evaluated its performance with regard to position,energy,and angular resolution.We used two 10×10 LaBr_(3) crystal arrays with a pixel size of 5 mm×5 mm,silicon photomultipliers(SiPMs),and corresponding decoding circuits to construct our prototype.Additionally,a framework based on a Voronoi diagram and a lookup table was developed for list-mode projection data acquisition.Monte Carlo(MC)simulations based on Geant4 and experiments were conducted to evaluate the performance of our CC prototype.The lateral position resolution was 5 mm,and the maximum deviation in the depth direction was 2.5 and 5 mm for the scatterer and absorber,respectively.The corresponding measured energy resolu-tions were 7.65%and 8.44%,respectively,at 511 keV.The experimental results of ^(137)Cs point-like sources were consistent with the MC simulation results with regard to the spatial positions and full widths at half maximum(FWHMs).The angular resolution of the fabricated prototype was approximately 6°when a point-like ^(137)Cs source was centrally placed at a distance of 5 cm from the scatterer.We proposed and investigated a large-pixel LaBr_(3) CC for the first time and verified its feasibility for use in accurate spatial positioning of radiative sources with a high angular resolution.The proposed CC can satisfy the requirements of radiative source imaging and positioning in the nuclear industry and medical applications.

Simulation study of BESⅢwith stitched CMOS pixel detector using AcTs

The reconstruction of the tracks of charged particles with high precision is crucial for HEP experiments to achieve their physics goals.The BESⅢdrift chamber,which is used as the tracking detector of the BESⅢexperiment,has suffered from aging effects resulting in degraded tracking performance after operation for approximately 15 years.To preserve and enhance the tracking performance of BESⅢ,one of the proposals is to add one layer of a thin cylindrical CMOS pixel sensor based on state-of-the-art stitching technology between the beam pipe and the drift chamber.The improvement in the tracking performance of BESⅢwith such an additional pixel detector compared to that with only the existing drift chamber was studied using the modern common tracking software Acts,which provides a set of detector-agnostic and highly performant tracking algorithms that have demonstrated promising performance for a few high-energy physics and nuclear physics experiments.