基于多尺度Scale-Unet的单样本图像翻译

随着生成对抗网络(GAN)的发展,基于单样本的无监督图像到图像翻译(UI2I)取得了重大进展。然而,以前方法无法捕获图像中的复杂纹理并保留原始内容信息。为解决这个问题,提出了一种基于尺度可变U-Net结构(Scale—Unet)的新型单样本图像翻译结构SUGAN。所提出的SUGAN使用Scale—Unet作为生成器,利用多尺度结构和渐进方法不断改进网络结构,以从粗到细地学习图像特征。同时,提出了尺度像素损失scale-pixel来更好地约束保留原始内容信息,防止信息丢失。实验表明,与SinGAN、TuiGAN、TSIT、StyTR2等公共数据集Summer■Winter、Horse■Zebra上的方法相比,该方法生成图像的SIFID值平均降低了30%。所提方法可更好地保留图像内容信息,同时生成详细逼真的高质量图像。

带干扰项的ARZ交通流模型的时滞控制与ISS稳定性

针对线性化之后的ARZ交通流模型,已有文献通常基于如下假设:一是系统的平衡态恰好等于自由流的速度,二是进入上游路段的交通量恰好等于交通需求的数学期望,三是边界反馈不考虑时滞因素的影响.该文抛开各类限制条件,结合时滞边界控制策略,建立了具有模型漂移项和边界扰动项的PDE-PDE无穷维耦合闭环系统.具体地,采用算子半群理论,将闭环系统改写为抽象发展方程的形式;结合线性系统解与控制算子的允许性理论,证明了闭环系统的适定性;构造加权ISS-Lyapunov函数,证明了闭环系统的输入-状态稳定性(ISS),得到了反馈参数的耗散性条件.通过数值仿真实验,进一步验证本文设计的时滞控制器的有效性与参数条件的可行性.

ISS特征融合NDT的点云配准研究

点云配准技术在三维重建、自动驾驶领域中起着重要作用。针对正态分布变换(NDT)算法点云配准数据量较大时,配准效率低和配准精度受到初始位姿影响较大的问题,提出一种内部形状描述子(ISS)特征点融合NDT的点云配准方法。首先利用ISS算法对点云进行特征点提取,然后计算特征点处的快速点特征直方图(FPFH)来描述特征点处的局部几何信息,再利用随机采样一致初始配准算法(SAC-IA)进行粗配准,在粗配准后目标点云与源点云获得一个初始变换位姿,最后将该初始变换提供给NDT算法进行精配准。通过对数据集进行不同算法下的对比实验,证明该算法可以有效地提高点云的配准精度和配准效率。

Uncertainties of landslide susceptibility prediction:influences of different study area scales and mapping unit scales

This study aims to investigate the effects of different mapping unit scales and study area scales on the uncertainty rules of landslide susceptibility prediction(LSP).To illustrate various study area scales,Ganzhou City in China,its eastern region(Ganzhou East),and Ruijin County in Ganzhou East were chosen.Different mapping unit scales are represented by grid units with spatial resolution of 30 and 60 m,as well as slope units that were extracted by multi-scale segmentation method.The 3855 landslide locations and 21 typical environmental factors in Ganzhou City are first determined to create spatial datasets with input-outputs.Then,landslide susceptibility maps(LSMs)of Ganzhou City,Ganzhou East and Ruijin County are pro-duced using a support vector machine(SVM)and random forest(RF),respectively.The LSMs of the above three regions are then extracted by mask from the LSM of Ganzhou City,along with the LSMs of Ruijin County from Ganzhou East.Additionally,LSMs of Ruijin at various mapping unit scales are generated in accordance.Accuracy and landslide suscepti-bility indexes(LSIs)distribution are used to express LSP uncertainties.The LSP uncertainties under grid units significantly decrease as study area scales decrease from Ganzhou City,Ganzhou East to Ruijin County,whereas those under slope units are less affected by study area scales.Of course,attentions should also be paid to the broader representativeness of large study areas.The LSP accuracy of slope units increases by about 6%–10%compared with those under grid units with 30 m and 60 m resolution in the same study area's scale.The significance of environmental factors exhibits an averaging trend as study area scale increases from small to large.The importance of environmental factors varies greatly with the 60 m grid unit,but it tends to be consistent to some extent in the 30 m grid unit and the slope unit.

A real-time performance improvement method for composite time scale

The composite time scale(CTS)provides a stable,accurate,and reliable time scale for modern society.The improvement of CTS’s real-time performance will improve its stability,which strengths related applications’performance.Aiming at this goal,a method achieved by determining the optimal calculation interval and accelerating adjustment stage is proposed in this paper.The determinants of the CTS’s calculation interval(characteristics of the clock ensemble,the measurement noise,the time and frequency synchronization system’s noise and the auxiliary output generator noise floor)are studied and the optimal calculation interval is obtained.We also investigate the effect of ensemble algorithm’s initial parameters on the CTS’s adjustment stage.A strategy to get the reasonable initial parameters of ensemble algorithm is designed.The results show that the adjustment stage can be finished rapidly or even can be shorten to zero with reasonable initial parameters.On this basis,we experimentally generate a distributed CTS with a calculation interval of 500 s and its stability outperforms those of the member clocks when the averaging time is longer than1700 s.The experimental result proves that the CTS’s real-time performance is significantly improved.

Rate-limiting factors in hydrate decomposition through depressurization across various scales:A mini-review

Natural gas hydrate is an energy resource for methane that has a carbon quantity twice more than all traditional fossil fuels combined.However,their practical application in the field has been limited due to the challenges of long-term preparation,high costs and associated risks.Experimental studies,on the other hand,offer a safe and cost-effective means of exploring the mechanisms of hydrate dissociation and optimizing exploitation conditions.Gas hydrate decomposition is a complicated process along with intrinsic kinetics,mass transfer and heat transfer,which are the influencing factors for hydrate decomposition rate.The identification of the rate-limiting factor for hydrate dissociation during depressurization varies with the scale of the reservoir,making it challenging to extrapolate findings from laboratory experiments to the actual exploitation.This review aims to summarize current knowledge of investigations on hydrate decomposition on the subject of the research scale(core scale,middle scale,large scale and field tests)and to analyze determining factors for decomposition rate,considering the various research scales and their associated influencing factors.

High Sensitivity Submicron Scale Temperature Sensor Based on Perovskite Nanoplatelet Lasers

Submicron scale temperature sensors are crucial for a range of applications,particularly in micro and na-noscale environments.One promising solution involves the use of active whispering gallery mode(WGM)microresonators.These resonators can be remotely excited and read out using free-space structures,simplifying the process of sensing.In this study,we present a submicron-scale temperature sensor with a remarkable sensitivity up to 185 pm/℃based on a trian-gular MAPbI3 nanoplatelet(NPL)laser.Notably,as temperature changes,the peak wavelength of the laser line shifts lin-early.This unique characteristic allows for precise temperature sensing by tracking the peak wavelength of the NPL laser.The optical modes are confined within the perovskite NPL,which measures just 85 nm in height,due to total internal reflec-tion.Our NPL laser boasts several key features,including a high Q of~2610 and a low laser threshold of about 19.8μJ·cm^(−2).The combination of exceptional sensitivity and ultra-small size makes our WGM device an ideal candidate for integration into systems that demand compact temperature sensors.This advancement paves the way for significant prog-ress in the development of ultrasmall temperature sensors,opening new possibilities across various fields.

Scale-space effect and scale hybridization in image intelligent recognition of geological discontinuities on rock slopes

Geological discontinuity(GD)plays a pivotal role in determining the catastrophic mechanical failure of jointed rock masses.Accurate and efficient acquisition of GD networks is essential for characterizing and understanding the progressive damage mechanisms of slopes based on monitoring image data.Inspired by recent advances in computer vision,deep learning(DL)models have been widely utilized for image-based fracture identification.The multi-scale characteristics,image resolution and annotation quality of images will cause a scale-space effect(SSE)that makes features indistinguishable from noise,directly affecting the accuracy.However,this effect has not received adequate attention.Herein,we try to address this gap by collecting slope images at various proportional scales and constructing multi-scale datasets using image processing techniques.Next,we quantify the intensity of feature signals using metrics such as peak signal-to-noise ratio(PSNR)and structural similarity(SSIM).Combining these metrics with the scale-space theory,we investigate the influence of the SSE on the differentiation of multi-scale features and the accuracy of recognition.It is found that augmenting the image's detail capacity does not always yield benefits for vision-based recognition models.In light of these observations,we propose a scale hybridization approach based on the diffusion mechanism of scale-space representation.The results show that scale hybridization strengthens the tolerance of multi-scale feature recognition under complex environmental noise interference and significantly enhances the recognition accuracy of GD.It also facilitates the objective understanding,description and analysis of the rock behavior and stability of slopes from the perspective of image data.

Scale effect removal and range migration correction for hypersonic target coherent detection

The detection of hypersonic targets usually confronts range migration(RM)issue before coherent integration(CI).The traditional methods aiming at correcting RM to obtain CI mainly considers the narrow-band radar condition.However,with the increasing requirement of far-range detection,the time bandwidth product,which is corresponding to radar’s mean power,should be promoted in actual application.Thus,the echo signal generates the scale effect(SE)at large time bandwidth product situation,influencing the intra and inter pulse integration performance.To eliminate SE and correct RM,this paper proposes an effective algorithm,i.e.,scaled location rotation transform(ScLRT).The ScLRT can remove SE to obtain the matching pulse compression(PC)as well as correct RM to complete CI via the location rotation transform,being implemented by seeking the actual rotation angle.Compared to the traditional coherent detection algorithms,Sc LRT can address the SE problem to achieve better detection/estimation capabilities.At last,this paper gives several simulations to assess the viability of ScLRT.

Validity,Reliability,and Measurement Invariance of the Thai Smartphone Application-Based Addiction Scale and Bergen Social Media Addiction Scale

Background:In recent years,there has been increased research interest in both smartphone addiction and social media addiction as well as the development of psychometric instruments to assess these constructs.However,there is a lack of psychometric evaluation for instruments assessing smartphone addiction and social media addiction in Thailand.The present study evaluated the psychometric properties and gender measurement invariance of the Thai version of the Smartphone Application-Based Addiction Scale(SABAS)and Bergen Social Media Addiction Scale(BSMAS).Method:A total of 801 Thai university students participated in an online survey from January 2022 to July 2022 which included demographic information,SABAS,BSMAS,and the Internet Gaming Disorder Scale-Short Form(IGDS9-SF).Results:Confirmatory Factor Analyses(CFAs)found that both the SABAS and BSMAS had a one-factor structure.Findings demonstrated adequate psychometric properties of both instruments and also supported measurement invariance across genders.Moreover,scores on the SABAS and BSMAS were correlated with scores on the IGDS9-SF.Conclusion:The results indicated that the SABAS and BSMAS are useful psychometric instruments for assessing the risk of smartphone addiction and social media addiction among Thai young adults.

Scale offers the possibility of identifying adherence to lifestyle interventions in patients with non-alcoholic fatty liver disease

Nonalcoholic fatty liver disease(NAFLD)is the most common chronic liver disorder,and dietary and lifestyle interventions remain the mainstays of NAFLD therapy.Zeng et al established a prediction system to evaluate adherence to lifestyle interventions in patients with NAFLD and choose optimal management.Here,we discuss the application scenarios of the scale and the areas warranting further attention,aiming to provide a possible reference for clinical recommend-ations.

Towards a profile-based writing scale for a local post-admission ESL writing assessment

Post-admission language tests tend to have a restricted range of proficiency levels among test-takers due to considerations made during the admission selection process.Although range restriction can present challenges for proficiency-focused assessment,it can also bring opportunities to zoom in on fine-grained performance profiles of test-takers.This study reports on the validation of a profile-based rating scale for an ESL writing placement test in a US university.The profile-based rating scale was created by employing a three-staged,hybrid scale development approach,to provide not only accurate placement decisions but also fine-grained diagnostic information regarding ESL students’writing performance profiles.The scale strikes a balance between argument development and lexico-grammar,to better account for the range of writing performances among test-takers.To gather validity evidence for the profile-based rating scale,this study employs a sequential,mixed-methods approach to examine the quality of test-taker performances across profiles and rater perceptions on the scale.Nine certified raters were recruited to conduct independent evaluations of lexicogrammar and argumentation on a sample of 150 test-taker performances.These evaluations were subjected to many-facet Rasch measurement analysis to examine the differences across writing performance profiles included in the rating scale.Next,semi-structured,follow-up interviews were conducted with the raters,to complement the quantitative findings on the usability and effectiveness of the scale.The findings provide supportive evidence for the validity of the profile-based rating scale.I argue that by focusing on performance profiles,post-admission language tests can strengthen the alignment across curriculum,instruction,and assessment in ESL writing programs.

Performance Improvement of Kenaf/Glass Polymer Hybrid Composites by Effective Application of Fish Scale Powder as Filler:A Novel Approach

Modern technology for developing new items made from renewable resources is becoming more and more popular as a result of rising environmental concern.Recently,contemporary polymer composites have included the hybridization of natural fibers with synthetic ones,along with the inclusion of a variety of biowaste filler for developing sustainable goods.In this work,the kenaf/glass hybrid polyester composites are strengthened by the addition of fish scale(FS),which is taken from the fishs outermost layer of skin.Five different stacked-order laminates,such as KKKK,KGKG,GKKG,KGGK,and GGGG,are fabricated by using the hand lay-up method with four different weight concentrations of filler content:0%,5%,10%,and 15%.Mechanical possessions such as tensile,flexural,impact strength and micro-hardness have been evaluated through experimentation in accordance with ASTM standards.The experimental findings revealed that,the tensile strength and micro-hardness value of KGKG laminates with 15wt% of FS filler are found to be maximum of 118.72 MPa and 17.82 HV respectively which are 39.67%and 26.11%greater than that of KGKG laminates without FS filler.However,the flexural and impact strength of same laminates with 10 wt% FS filler exhibited a maximum value of 142.77 MPa and 62.08 kJ/m^(2).In order to corroborate its applicability for structural and building materials in open environment,the dimensional stability of the composite has been studied through moisture absorption test.The influences of FS filler loading on dimensional stability and resistance to moisture absorption capacity of laminates are also investigated.The experimental results reflected that the addition of FS-filler has significantly improved the dimensional stability of the laminates in moist environment by reducing the moisture absorption tendency.To further support the mode of failures,a fractography investigation of fractured surfaces was conducted.

Water as a Standard Substance of a Logarithmic Poison Scale

The lethal dose LD50 represents the most important experimental value for acute toxicity. The simple logarithmic calculation of -log10 LD50 = value leads to the possible poison power pLD. As with the pH or pK value, respectively, for acid or the scale of earthquake intensities the logarithm helps making large differences of orders of magnitude easier to understand since they are more comparable. The higher the pLD value, the higher is the power of poison. An increase of the pLD value by 1 stands for a tenfold increase in toxicity. The lethal acute dose for water, one of the most important and at the same time non-toxic substances of all, is about one tenth of the body weight. This leads to a possible pLD value for water of 1, an ideal starting value for a logarithmic poison scale.

Characterization of Small-Scale Farmers and Assessment of Their Access to Crop Production Information in Selected Counties of Kenya

Small-scale farming accounts for 78% of total agricultural production in Kenya and contributes to 23.5% of the country’s GDP. Their crop production activities are mostly rainfed subsistence with any surplus being sold to bring in some income. Timely decisions on farm practices such as farm preparation and planting are critical determinants of the seasonal outcomes. In Kenya, most small-scale farmers have no reliable source of information that would help them make timely and accurate decisions. County governments have extension officers who are mandated with giving farmers advisory services to farmers but they are not able to reach most farmers due to facilitation constraints. The mode and format of sharing information is also critical since it’s important to ensure that it’s timely, well-understood and usable. This study sought to assess access to geospatial derived and other crop production information by farmers in four selected counties of Kenya. Specific objectives were to determine the profile of small-scale farmers in terms of age, education and farm size;to determine the type of information that is made available to them by County and Sub-County extension officers including the format and mode of provision;and to determine if the information provided was useful in terms of accuracy, timeliness and adequacy. The results indicated that over 80% of the farmers were over 35 years of age and over 56% were male. Majority had attained primary education (34%) or secondary education (29%) and most farmers in all the counties grew maize (71%). Notably, fellow farmers were a source of information (71%) with the frequency of sharing information being mostly seasonal (37%) and when information was available (43%). Over 66% of interviewed farmers indicating that they faced challenges while using provided information. The results from the study are insightful and helpful in determining effective ways of providing farmers with useful information to ensure maximum benefits.

Factors affecting land dissection density in geomorphological regions of China

Land dissection density(LDD)provides morphological evidence regarding prior intense soil erosion and quantifies the distribution of land dissections.A comprehensive understanding of the potential factors influencing the spatial pattern and value of the LDD is vital in geological disasters,soil erosion,and other related domains.Land dissection phenomena in China affects large areas with different morphological,pedological,and climatic characteristics.Prior studies have focused on the potential factors influencing the LDD at a watershed scale.However,these results are insufficient to reflect the status quo of dissection development and its primary influencing factors on a national scale.LDD’s spatial patterns and the dominant factors at a regional scale in millions of square kilometers remain to be ascertained.This study used the geomorphon-based method and the geographical detector model to quantify the spatial pattern of LDD over China and identify the dominant factors affecting this pattern in China’s six first-order geomorphological regions(GR1~GR6).The results yield the following findings:(1)LDD in China ranges from 0~4.55 km/km^(2),which is larger in central and eastern regions than in other regions of China;(2)dominant factors and their dominant risk subcategories vary with each geomorphological region’s primary internal and external forces;(3)the influence of natural factors is more significant on the large regional scale in millions of square kilometers compared to anthropogenic factors;relief degree of land surface(RDLS)is dominant in GR1,GR2,and GR5;the slope is dominant in GR6,soil type is dominant in GR3 and GR4,and lithology plays a critical role in the dominant interactions of GR3,GR4,and GR6;(4)the interactions between factors on LDD’s spatial pattern have a more significant effect than individual factors.

Scale dependence of forest fragmentation and its climate sensitivity in a semi-arid mountain:Comparing Landsat,Sentinel and Google Earth data

Landscape fragmentation is generally viewed as an indicator of environmental stresses or risks,but the fragmentation intensity assessment also depends on the scale of data and the definition of spatial unit.This study aimed to explore the scale-dependence of forest fragmentation intensity along a moisture gradient in Yinshan Mountain of North China,and to estimate environmental sensitivity of forest fragmentation in this semi-arid landscape.We developed an automatic classification algorithm using simple linear iterative clustering(SLIC)and Gaussian mixture model(GMM),and extracted tree canopy patches from Google Earth images(GEI),with an accuracy of 89.2%in the study area.Then we convert the tree canopy patches to forest category according to definition of forest that tree density greater than 10%,and compared it with forest categories from global land use datasets,FROM-GLC10 and GlobeLand30,with spatial resolutions of 10 m and 30 m,respectively.We found that the FROM-GLC10 and GlobeLand30 datasets underestimated the forest area in Yinshan Mountain by 16.88%and 21.06%,respectively;and the ratio of open forest(OF,10%<tree coverage<40%)to closed forest(CF,tree coverage>40%)areas in the underestimated part was 2:1.The underestimations concentrated in warmer and drier areas occupied mostly by large coverage of OFs with severely fragmented canopies.Fragmentation intensity of canopies positively correlated with spring temperature while negatively correlated with summer precipitation and terrain slope.When summer precipitation was less than 300 mm or spring temperature higher than 4℃,canopy fragmentation intensity rose drastically,while the forest area percentage kept stable.Our study suggested that the spatial configuration,e.g.,sparseness,is more sensitive to drought stress than area percentage.This highlights the importance of data resolution and proper fragmentation measurements for forest patterns and environmental interpretation,which is the base of reliable ecosystem predictions with regard to the future climate scenarios.

A sub-grid scale model for Burgers turbulence based on the artificial neural network method

The present study proposes a sub-grid scale model for the one-dimensional Burgers turbulence based on the neuralnetwork and deep learning method.The filtered data of the direct numerical simulation is used to establish thetraining data set,the validation data set,and the test data set.The artificial neural network(ANN)methodand Back Propagation method are employed to train parameters in the ANN.The developed ANN is applied toconstruct the sub-grid scale model for the large eddy simulation of the Burgers turbulence in the one-dimensionalspace.The proposed model well predicts the time correlation and the space correlation of the Burgers turbulence.

Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control

Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.

Small-scale fire tests in the underwater tunnel section model with new sidewall smoke extraction

The Shenzhen–Zhongshan Bridge is a 24‐km‐long bridge and tunnel system,including a 6.8-km-long super cross section subsea tunnel.To solve the smoke exhaust problem of a super large cross-section subsea tunnel,the tunnel has a new smoke exhaust system that combines a horizontal smoke exhaust cross section at the top and sidewall smoke exhaust holes.In order to evaluate the potential fire hazards of this type of tunnel,a 1:30 tunnel model was established and 140 smallscale experiments on underwater tunnel fires were conducted.By changing the fire power,fire location,and fan operation mode,different scenarios of submarine immersed tunnel fire were simulated and the related key parameters such as fire smoke diffusion behavior and smoke temperature distribution were studied.On this basis,the optimal smoke control strategy was proposed for different fire scenarios.The research results indicate that the new smoke exhaust system can fully utilize the smoke flow characteristics,significantly improve smoke exhaust efficiency,and increase available evacuation time,thus further enhancing the fire safety of super large cross-section subsea tunnels.