From Physical Space to Visual Image Space

The theoretical framework of visual simulation in virtual reality is discussed. The new concept of visual image space is supposed. On the basis of visual image space, in visual perceptive sense, VR is considered as a spatial simulation. The objective of the spatial simulation is to transform physical space to visual image space. Last, the prototype system, surveying & mapping virtual Reality (SMVR), is developed, and the space simulation above is realized. By use of SMVR, the real 3D representation, 3D visual analysis, virtual plan and designs can be implemented.

Image space analysis for variational inequalities with cone constraints and applications to traffic equilibria

In this paper,the image space analysis (for short,ISA) is employed to investigate variational in- equalities (for short,VI) with cone constraints.Linear separation for VI with cone constraints is characterized by using the normal cone to a regularization of the image,and saddle points of the generalized Lagrangian func- tion.Lagrangian-type necessary and sufficient optimality conditions for VI with cone constraints are presented by using a separation theorem.Gap functions and weak sharpness for VI with cone constraints are also investi- gated.Finally,the obtained results are applied to standard and time-dependent traffic equilibria introduced by Daniele,Maugeri and Oettli.

Characterization of image spaces of Riemann-Liouville fractional integral operators on Sobolev spaces W^(m,p)(Ω)

Fractional operators are widely used in mathematical models describing abnormal and nonlocal phenomena.Although there are extensive numerical methods for solving the corresponding model problems,theoretical analysis such as the regularity result,or the relationship between the left-side and right-side fractional operators is seldom mentioned.Instead of considering the fractional derivative spaces,this paper starts from discussing the image spaces of Riemann-Liouville fractional integrals of L_(p)(Ω) functions,since the fractional derivative operators that are often used are all pseudo-differential.Then the high regularity situation-the image spaces of Riemann-Liouville fractional integral operators on the W^(m,p)(Ω) space is considered.Equivalent characterizations of the defined spaces,as well as those of the intersection of the left-side and right-side spaces are given.The behavior of the functions in the defined spaces at both the nearby boundary point/points and the points in the domain is demonstrated in a clear way.Besides,tempered fractional operators are shown to be reciprocal to the corresponding Riemann-Liouville fractional operators,which is expected to contribute some theoretical support for relevant numerical methods.Last,we also provide some instructions on how to take advantage of the introduced spaces when numerically solving fractional equations.

Deep learning approach to detect seizure using reconstructed phase space images

Epilepsy is a chronic neurological disorder that affects the function of the brain in people of all ages.It manifests in the electroencephalogram(EEG) signal which records the electrical activity of the brain.Various image processing,signal processing,and machine-learning based techniques are employed to analyze epilepsy,using spatial and temporal features.The nervous system that generates the EEG signal is considered nonlinear and the EEG signals exhibit chaotic behavior.In order to capture these nonlinear dynamics,we use reconstructed phase space(RPS) representation of the signal.Earlier studies have primarily addressed seizure detection as a binary classification(normal vs.ictal) problem and rarely as a ternary class(normal vs.interictal vs.ictal)problem.We employ transfer learning on a pre-trained deep neural network model and retrain it using RPS images of the EEG signal.The classification accuracy of the model for the binary classes is(98.5±1.5)% and(95±2)% for the ternary classes.The performance of the convolution neural network(CNN) model is better than the other existing statistical approach for all performance indicators such as accuracy,sensitivity,and specificity.The result of the proposed approach shows the prospect of employing RPS images with CNN for predicting epileptic seizures.

Possibilities of mapping neotectonic elements based on the interpretation of space images:A study of Fergana Depression

For the current geological mapping of individual territories,remote sensing and geographic information system(GIS)technologies are widely used.Taking the Fergana depression as an example,this paper aims to determine the possibilities of using remote sensing materials for mapping structural and geomorphological elements.Landsat-8 satellite imagery obtained on 11 spectral channels was used to highlight the decoding features.Fault zones,lineament zones,various uplifts,depressions,and structural material complexes of different ages were identified.Based on the in-depth analysis of geological and geophysical data,a geological schematic map of the Fergana depression was developed.Using geological landscape and automated methods for deciphering space images,the main neotectonic elements of the Fergana depression were identified:the southern step,northern marginal slope,central graben-syncline,flexurefault zones,local anticlinal zones,individual uplifts/depressions,and local shear zones.The results show a neotectonic map of the study area,which can be used as a tectonic basis for prospecting,seismic zoning mapping,and geological engineering development.

Improved astrometry of space debris with image restoration

In order to implement an observing strategy, image degradation that occurs during optical observation of space debris is ineluctable and has distinct characteris- tics. Image restoration is presented as a way to remove the influence of degradation in CCD images of space debris, based on assumed PSF models with the same F-WHM as images of the object. In the process of image restoration, the maximum entropy method is adopted. The results of reduction using observed raw CCD images indi- cate that the precision in estimating positions of objects is improved and the effects of degradation are reduced. Improving the astrometry of space debris using image restoration is effective and feasible.

The Digital Mapping of Ukrainian Soils on the Base of High Resolution Space Images

The first Ukrainian using experience of multispectral space scanning for digital soil mapping is described in this paper. Methodical approaches for detailed soil observation of Ukrainian forest regions are elaborated based on modem mapping principles. For the first time in Ukraine, digital soil maps based on GIS （geographic information system） were obtained for individual farms. In GIS based on space images and digital relief models, the medium-scale and large-scale soil maps were created by geo-statistical methods. According to elaborated methods, modem digital soil mapping should provide all combined works： remote sensing and traditional soil observations. The modem digital soil mapping should be based just on quantitative principles： on remote sensing data, geomorphologic field parameters, and chemical analyses. The methodological approaches, which were used for the first time in Ukraine during digital soil mapping by remote sensing methods, are described in this paper.

An image compression method for space multispectral time delay and integration charge coupled device camera

Multispectral time delay and integration charge coupled device （TDICCD） image compression requires a low- complexity encoder because it is usually completed on board where the energy and memory are limited. The Consultative Committee for Space Data Systems （CCSDS） has proposed an image data compression （CCSDS-IDC） algorithm which is so far most widely implemented in hardware. However, it cannot reduce spectral redundancy in mukispectral images. In this paper, we propose a low-complexity improved CCSDS-IDC （ICCSDS-IDC）-based distributed source coding （DSC） scheme for multispectral TDICCD image consisting of a few bands. Our scheme is based on an ICCSDS-IDC approach that uses a bit plane extractor to parse the differences in the original image and its wavelet transformed coefficient. The output of bit plane extractor will be encoded by a first order entropy coder. Low-density parity-check-based Slepian-Wolf （SW） coder is adopted to implement the DSC strategy. Experimental results on space multispectral TDICCD images show that the proposed scheme significantly outperforms the CCSDS-IDC-based coder in each band.

Rapid rupture characterization for the 2023 M_(S)6.2 Jishishan earthquake

On December 18, 2023, the M_(S)6.2 Jishishan earthquake occurred in the northeastern region of the QinghaiXizang Plateau, causing heavy casualties and property damage in Gansu and Qinghai Provinces. In this study,we integrate space imaging geodesy, finite fault inversion, and back-projection methods to decipher its rupture property, including fault geometry, coseismic slip distribution, rupture direction, and propagation speed. The results reveal that the seismogenic fault dips to the southwest at an angle of 29°. The major slip asperity is dominated by reverse slip and is concentrated within a depth range of 7–16 km, which explains the significant uplift near the epicenter observed by both the Sentinel-1 ascending and descending In SAR data. Moreover, the teleseismic array waveforms indicate a northwest propagating rupture with an overall slow rupture velocity of~1.91 km/s(AK array) or 1.01 km/s(AU array).

Glymphatic function and its influencing factors in different glucose metabolism states

BACKGROUND Dysfunction of the glymphatic system in the brain in different stages of altered glucose metabolism and its influencing factors are not well characterized.AIM To investigate the function of the glymphatic system and its clinical correlates in patients with different glucose metabolism states,the present study employed diffusion tensor imaging along the perivascular space(DTI-ALPS)index.METHODS Sample size was calculated using the pwr package in R software.This crosssectional study enrolled 22 patients with normal glucose metabolism(NGM),20 patients with prediabetes,and 22 patients with type 2 diabetes mellitus(T2DM).A 3.0T magnetic resonance imaging was used to evaluate the function of the glymphatic system.The mini-mental state examination(MMSE)was used to assess general cognitive function.The DTI-ALPS index of bilateral basal ganglia and the mean DTI-ALPS index was calculated.Further,the correlation between DTI-ALPS and clinical features was assessed.RESULTS The left-side,right-side,and mean DTI-ALPS index in the T2DM group were significantly lower than that in the NGM group.The right-side DTI-ALPS and mean DTI-ALPS index in the T2DM group were significantly lower than those in the prediabetes group.DTI-ALPS index lateralization was not observed.The MMSE score in the T2DM group was significantly lower than that in the NGM and prediabetes group.After controlling for sex,the left-side DTI-ALPS and mean DTI-ALPS index in the prediabetes group were positively correlated with 2-hour postprandial blood glucose level;the left-side DTI-ALPS index was negatively correlated with total cholesterol and low-density lipoprotein level.The right-side DTI-ALPS and mean DTI-ALPS index were negatively correlated with the glycosylated hemoglobin level and waist-to-hip ratio in the prediabetes group.The left-side,right-side,and mean DTI-ALPS index in the T2DM group were positively correlated with height.The left-side and mean DTIALPS index in the T2DM group were negatively correlated with high-density lipoprotein levels.CONCLUSION Cerebral glymphatic system dysfunction may mainly occur in the T2DM stage.Various clinical variables were found to affect the DTI-ALPS index in different glucose metabolism states.This study enhances our understanding of the pathophysiology of diabetic brain damage and provides some potential biological evidence for its early diagnosis.

Updating Strategy of Campus Space Based on Multi-source Data:A Case Study of West Campus of Yangtze University

Under the macro background of rapid urbanization and social transformation in China,campus space renewal has become an important practice and carrier for the sustainable development of schools.The study on campus space by big data and quantitative reflection of spatial distribution of applicable people in different areas of the campus can provide a certain scientific basis for campus space updating.West campus of Yangtze University is taken as research object.Based on cognitive map method,questionnaire survey method,behavior trajectory and correlation analysis method,the types and characteristics of campus space composition,campus satisfaction,usage and its relevance are analyzed.Research results show that ①the overall imageability of campus space is higher,which has a significantly positive correlation with the satisfaction of campus environment,and has no correlation with users’ behavior activities.The use frequency of non teaching areas varies greatly in different periods of time.②The correlation between the surrounding green vegetation and the image degree of campus landmarks is the most significant,and the coefficient is 0.886.③The correlation between spatial size suitability and regional image degree is the most significant,and the coefficient is 0.937.④The correlation between public activity facilities in the region and node image degree is the most significant,and the coefficient is 0.995.According to the research results,the corresponding solutions are put forward to provide scientific and quantitative reference suggestions for the renewal and transformation of the campus.

Continuous imaging space in three-dimensional integral imaging

We report an integral imaging method with continuous imaging space. This method simultaneously reconstructs real and virtual images in the virtual mode, with a minimum gap that separates the entire imaging space into real and virtual space. Experimental results show that the gap is reduced to 45% of that in a conventional integral imaging system with the same parameters.

A new source extraction algorithm for optical space debris observation

Specific challenges arise in the task of real-time automatic data reduction of optical space debris observations. Here we present an automatic technique that optimally detects and measures the sources from images of optical space debris ob- servations. We show that highly reliable and accurate results can be obtained on most images produced by our specific sensors, and due to optimizations, the whole pipeline works fast and efficiently. Tests demonstrate that the technique performs better than SExtractor from the point of view of fast and accurate detection, therefore it is well suited for data reduction of optical space debris observations.

Space debris tracking based on fuzzy running Gaussian average adaptive particle filter track-before-detect algorithm

Although tracking with a passive optical telescope is a powerful technique for space debris observation, it is limited by its sensitivity to dynamic background noise. Traditionally, in the field of astronomy, static background subtraction based on a median image technique has been used to extract moving space objects prior to the tracking operation, as this is computationally efficient. The main disadvantage of this technique is that it is not robust to variable illumination conditions. In this article, we propose an approach for tracking small and dim space debris in the context of a dynamic background via one of the optical telescopes that is part of the space surveillance network project, named the Asia- Pacific ground-based Optical Space Observation System or APOSOS. The approach combines a fuzzy running Gaussian average for robust moving-object extraction with dim-target tracking using a particle- filter-based track-before-detect method. The performance of the proposed algorithm is experimentally evaluated, and the results show that the scheme achieves a satisfactory level of accuracy for space debris tracking.

An improved astrometric calibration technique for space debris observation

An optical survey is the main technique for detecting space debris. Due to the specific character- istics of observation, the pointing errors and tracking errors of the telescope as well as image degradation may be significant, which make it difficult for astrometric calibration. Here we present an improved method that corrects the pointing and tracking errors, and measures the image position precisely. The pipeline is tested on a number of CCD images obtained from a 1-m telescope administered by Xinjiang Astronomical Observatory while observing a GPS satellite. The results show that the position measurement error of the background stars is around 0.1 pixel, while the time cost for a single frame is about 7.5 s; hence the relia- bility and accuracy of our method are demonstrated. In addition, our method shows a versatile and feasible way to perform space debris observation utilizing non-dedicated telescopes, which means more sensors could be involved and the ability to perform surveys could be improved.

Design and Implementation of Verification Code Identification Based on Anisotropic Heat Kernel

Many websites use verification codes to prevent users from using the machine automatically to register,login,malicious vote or irrigate but it brought great burden to the enterprises involved in internet marketing as entering the verification code manually.Improving the verification code security system needs the identification method as the corresponding testing system.We propose an anisotropic heat kernel equation group which can generate a heat source scale space during the kernel evolution based on infinite heat source axiom,design a multi-step anisotropic verification code identification algorithm which includes core procedure of building anisotropic heat kernel,settingwave energy information parameters,combing outverification codccharacters and corresponding peripheral procedure of gray scaling,binarizing,denoising,normalizing,segmenting and identifying,give out the detail criterion and parameter set.Actual test show the anisotropic heat kernel identification algorithm can be used on many kinds of verification code including text characters,mathematical,Chinese,voice,3D,programming,video,advertising,it has a higher rate of 25%and 50%than neural network and context matching algorithm separately for Yahoo site,49%and 60%for Captcha site,20%and 52%for Baidu site,60%and 65%for 3DTakers site,40%,and 51%.for MDP site.

Acquiring multi-spectral images by digital still cameras based on XYZLMS interim connection space

A method based on the XYZLMS interim connection space is proposed to accurately acquire the multi-spectral images by digital still cameras. The XYZLMS values are firstly predicted from RGB values by polynomial model with local training samples and then spectral reflectance is constructed from XYZLMS values by pseudo-inverse method. An experiment is implemented for multi-spectral image acquisition based on a commercial digital still camera. The results indicate that multi-spectral images can be accurately acquired except the very dark colors.

A Study on the Space Image of Chongqing Central City Based on Online Images

The development of media and information technology has exerted profound influences over the relationship between human cognition and physical environment.Using the online images of Chongqing Central City and its affiliated districts that are found via search engines,this paper analyzes the scope of their visual field and the typology and the frequency of their content variables and explores the features and the regional differences of the city’s space image,in order to expand and supplement the scope and the paradigm of city image study.The study finds that:(1)the visual field of the online images is significantly correlated with the economic status,spatial characteristics,and development level of the region;(2)the space image of certain districts of Chongqing Central City shown by the online images presents few local features;(3)the space image of mountains and rivers of Chongqing Central City and its affiliated districts is not sufficiently expressed by the online images;and(4)the Internet has become an important medium for city image study that can quickly identify the features and deficiencies of local image.It is proposed to highlight the role of publicity and communication of media technology in the field of planning,which can help to reach consensus among various parties in the dynamic process of urban development.

Astrometric calibration and source characterisation of the latest generation neuromorphic event-based cameras for space imaging

As an emerging approach to space situational awareness and space imaging,the practical use of an event-based camera(EBC)in space imaging for precise source analysis is still in its infancy.The nature of event-based space imaging and data collection needs to be further explored to develop more effective event-based space imaging systems and advance the capabilities of event-based tracking systems with improved target measurement models.Moreover,for event measurements to be meaningful,a framework must be investigated for EBC calibration to project events from pixel array coordinates in the image plane to coordinates in a target resident space object’s reference frame.In this paper,the traditional techniques of conventional astronomy are reconsidered to properly utilise the EBC for space imaging and space situational awareness.This paper presents the techniques and systems used for calibrating an EBC for reliable and accurate measurement acquisition.These techniques are vital in building event-based space imaging systems capable of real-world space situational awareness tasks.By calibrating sources detected using the EBC,the spatiotemporal characteristics of detected sources or“event sources”can be related to the photometric characteristics of the underlying astrophysical objects.Finally,these characteristics are analysed to establish a foundation for principled processing and observing techniques which appropriately exploit the capabilities of the EBC.