Visual Representation and Cognitive Models in Information Visualization

As a branch of computer science,information visualization aims to help users understand and analyze complex data through graphical interfaces and interactive technologies.Information visualization primarily includes various visual structures such as time-series structures,spatial relationship structures,statistical distribution structures,and geographic map structures,each with unique functions and application scenarios.To better explain the cognitive process of visualization,researchers have proposed various cognitive models based on interaction mechanisms,visual perception steps,and novice use of visualization.These models help understand user cognition in information visualization,enhancing the effectiveness of data analysis and decision-making.

Evaluating the use of three-dimensional reconstruction visualization technology for precise laparoscopic resection in gastroesophageal junction cancer

BACKGROUND Laparoscopic gastrectomy for esophagogastric junction(EGJ)carcinoma enables the removal of the carcinoma at the junction between the stomach and esophagus while preserving the gastric function,thereby providing patients with better treatment outcomes and quality of life.Nonetheless,this surgical technique also presents some challenges and limitations.Therefore,three-dimensional reconstruction visualization technology(3D RVT)has been introduced into the procedure,providing doctors with more comprehensive and intuitive anatomical information that helps with surgical planning,navigation,and outcome evaluation.AIM To discuss the application and advantages of 3D RVT in precise laparoscopic resection of EGJ carcinomas.METHODS Data were obtained from the electronic or paper-based medical records at The First Affiliated Hospital of Hebei North University from January 2020 to June 2022.A total of 120 patients diagnosed with EGJ carcinoma were included in the study.Of these,68 underwent laparoscopic resection after computed tomography(CT)-enhanced scanning and were categorized into the 2D group,whereas 52 underwent laparoscopic resection after CT-enhanced scanning and 3D RVT and were categorized into the 3D group.This study had two outcome measures:the deviation between tumor-related factors(such as maximum tumor diameter and infiltration length)in 3D RVT and clinical reality,and surgical outcome indicators(such as operative time,intraoperative blood loss,number of lymph node dissections,R0 resection rate,postoperative hospital stay,postoperative gas discharge time,drainage tube removal time,and related complications)between the 2D and 3D groups.RESULTS Among patients included in the 3D group,27 had a maximum tumor diameter of less than 3 cm,whereas 25 had a diameter of 3 cm or more.In actual surgical observations,24 had a diameter of less than 3 cm,whereas 28 had a diameter of 3 cm or more.The findings were consistent between the two methods(χ^(2)=0.346,P=0.556),with a kappa consistency coefficient of 0.808.With respect to infiltration length,in the 3D group,23 patients had a length of less than 5 cm,whereas 29 had a length of 5 cm or more.In actual surgical observations,20 cases had a length of less than 5 cm,whereas 32 had a length of 5 cm or more.The findings were consistent between the two methods(χ^(2)=0.357,P=0.550),with a kappa consistency coefficient of 0.486.Pearson correlation analysis showed that the maximum tumor diameter and infiltration length measured using 3D RVT were positively correlated with clinical observations during surgery(r=0.814 and 0.490,both P<0.05).The 3D group had a shorter operative time(157.02±8.38 vs 183.16±23.87),less intraoperative blood loss(83.65±14.22 vs 110.94±22.05),and higher number of lymph node dissections(28.98±2.82 vs 23.56±2.77)and R0 resection rate(80.77%vs 61.64%)than the 2D group.Furthermore,the 3D group had shorter hospital stay[8(8,9)vs 13(14,16)],time to gas passage[3(3,4)vs 4(5,5)],and drainage tube removal time[4(4,5)vs 6(6,7)]than the 2D group.The complication rate was lower in the 3D group(11.54%)than in the 2D group(26.47%)(χ^(2)=4.106,P<0.05).CONCLUSION Using 3D RVT,doctors can gain a more comprehensive and intuitive understanding of the anatomy and related lesions of EGJ carcinomas,thus enabling more accurate surgical planning.

Survey of lightweighting methods of huge 3D models for online Web3D visualization

Background With the rapid development of Web3D technologies, the online Web3D visualization, particularly for complex models or scenes, has been in a great demand. Owing to the major conflict between the Web3D system load and resource consumption in the processing of these huge models, the huge 3D model lightweighting methods for online Web3D visualization are reviewed in this paper. Methods By observing the geometry redundancy introduced by man-made operations in the modeling procedure, several categories of light-weighting related work that aim at reducing the amount of data and resource consumption are elaborated for Web3D visualization. Results By comparing perspectives, the characteristics of each method are summarized, and among the reviewed methods, the geometric redundancy removal that achieves the lightweight goal by detecting and removing the repeated components is an appropriate method for current online Web3D visualization. Meanwhile, the learning algorithm, still in improvement period at present, is our expected future research topic. Conclusions Various aspects should be considered in an efficient lightweight method for online Web3D visualization, such as characteristics of original data, combination or extension of existing methods, scheduling strategy, cache man-agement, and rendering mechanism. Meanwhile, innovation methods, particularly the learning algorithm, are worth exploring.

Filter and Embedded Feature Selection Methods to Meet Big Data Visualization Challenges

This study focuses on meeting the challenges of big data visualization by using of data reduction methods based the feature selection methods.To reduce the volume of big data and minimize model training time(Tt)while maintaining data quality.We contributed to meeting the challenges of big data visualization using the embedded method based“Select from model(SFM)”method by using“Random forest Importance algorithm(RFI)”and comparing it with the filter method by using“Select percentile(SP)”method based chi square“Chi2”tool for selecting the most important features,which are then fed into a classification process using the logistic regression(LR)algorithm and the k-nearest neighbor(KNN)algorithm.Thus,the classification accuracy(AC)performance of LRis also compared to theKNN approach in python on eight data sets to see which method produces the best rating when feature selection methods are applied.Consequently,the study concluded that the feature selection methods have a significant impact on the analysis and visualization of the data after removing the repetitive data and the data that do not affect the goal.After making several comparisons,the study suggests(SFMLR)using SFM based on RFI algorithm for feature selection,with LR algorithm for data classify.The proposal proved its efficacy by comparing its results with recent literature.

DATA MODEL AND VISUALIZATION OF 3D CITY LANDSCAPE BASED ON INTEGRATED DATABASES

Data acquisition and modeling are the two important, difficult and costful aspects in a Cybercity project. 2D-GIS is mature and can manage a lot of spatial data. Thus 3D-GIS should make the best of data and technology of 2D-GIS. Construction of a useful synthetic environment requires integration of multiple types of information like DEM, texture images and 3D representation of objects such as buildings. In this paper, the method for 3D city landscape data model and visualization based on integrated databases is presented. Since the data volume of raster are very huge, special strategies(for example, pyramid gridded method) must be adopted in order to manage raster data efficiently. Three different methods of data acquisition, the proper data structure and a simple modeling method are presented as well. At last, a pilot project of Shanghai Cybercity is illustrated.

Physical modeling and visualization of soil liquefaction under high confining stress

The mechanisms of seismically-induced liquefaction of granular soils underhigh confining stresses are still not fully understood. Evaluation of these mechanisms is generallybased on extrapolation of observed behavior at shallow depths. Three centrifuge model tests wereconducted at RPI's experimental facility to investigate the effects of confining stresses on thedynamic response of a deep horizontal deposit of saturated sand. Liquefaction was observed at highconfining stresses in each of the tests. A system identification procedure was used to estimate theassociated shear strain and stress time histories. These histories revealed a response marked byshear strength degradation and dilative patterns. The recorded accelerations and pore pressures wereemployed to generate visual animations of the models. These visualizations revealed a liquefactionfront traveling downward and leading to large shear strains and isolation of upper soil layers.

3D visualization model and key techniques for digital mine

Digital mine is the inevitable outcome of the information processing, and is also a complicated system engineering. Firstly, for the 3D visualization application of the digital mine, the ground and underground integrative visualization framework model was proposed based on the mine entity database. So, the visualization problem was availably resolved, as well as the professional analytical ability was improved. Secondly, aiming at the irregularities, non-uniformity, dynamics of mine entities, mix modeling method based on the entity character was put forward, in which 3D expression of mine entities was realized. Lastly, the 3D visualization project for a copper mine was experimentally studied. Satisfactory results were acquired, and the rationality of visualization model and feasibility of 3D modeling were validated.

Development and application of a two-dimensional water quality model for the Daqinghe River Mouth of the Dianchi Lake

Water quality models are important tools to support the optimization of aquatic ecosystem rehabilitation programs and assess their efficiency. Basing on the flow conditions of the Daqinghe River Mouth of the Dianchi Lake, China, a two-dimensional water quality model was developed in the research. The hydrodynamics module was numerically solved by the alternating direction iteration （ADI） method. The parameters of the water quality module were obtained through the in situ experiments and the laboratory analyses that were conducted from 2006 to 2007. The model was calibrated and verified by the observation data in 2007. Among the four modelled key variables, i.e., water level, COD （in CODcr）, NH4＋-N and PO43-P the minimum value of the coefficient of determination （COD） was 0.69, indicating the model performed reasonably well. The developed model was then applied to simulate the water quality changes at a downstream cross-section assuming that the designed restoration programs were implemented. According to the simulated results, the restoration programs could cut down the loads of COD and PO43-P about 15%. Such a load reduction, unfortunately, would have very little effect on the NH4^＋-N removal. Moreover, the water quality at the outlet cross-section would be still in class V （3838-02）, indicating more measures should be taken to further reduce the loads. The study demonstrated the capability of water quality models to support aquatic ecosystem restorations.

Simulation of two-dimensional interior ballistics model of solid propellant electrothermal-chem ical launch with discharge rod plasma generator

Instead of the capillary plasma generator(CPG),a discharge rod plasma generator(DRPG)is used in the30 mm electrothermal-chemical(ETC)gun to improve the ignition uniformity of the solid propellant.An axisymmetric two-dimensional interior ballistics model of the solid propellant ETC gun(2D-IB-SPETCG)is presented to describe the process of the ETC launch.Both calculated pressure and projectile muzzle velocity accord well with the experimental results.The feasibility of the 2D-IB-SPETCG model is proved.Depending on the experimental data and initial parameters,detailed distribution of the ballistics parameters can be simulated.With the distribution of pressure and temperature of the gas phase and the propellant,the influence of plasma during the ignition process can be analyzed.Because of the radial flowing plasma,the propellant in the area of the DRPG is ignited within 0.01 ms,while all propellant in the chamber is ignited within 0.09 ms.The radial ignition delay time is much less than the axial delay time.During the ignition process,the radial pressure difference is less than 5 MPa at the place 0.025 m away from the breech.The radial ignition uniformity is proved.The temperature of the gas increases from several thousand K(conventional ignition)to several ten thousand K(plasma ignition).Compare the distribution of the density and temperature of the gas,we know that low density and high temperature gas appears near the exits of the DRPG,while high density and low temperature gas appears at the wall near the breech.The simulation of the 2D-IB-SPETCG model is an effective way to investigate the interior ballistics process of the ETC launch.The 2D-IB-SPETC model can be used for prediction and improvement of experiments.

Performance assessment of two-dimensional hydraulic models for generation of flood inundation maps in mountain river basins

Hydraulic models for the generation of flood inundation maps are not commonly applied in mountain river basins because of the difficulty in modeling the hydraulic behavior and the complex topography. This paper presents a comparative analysis of the performance of four twodimensional hydraulic models (HEC-RAS 2D, Iber 2D, Flood Modeller 2D, and PCSWMM 2D) with respect to the generation of flood inundation maps. The study area covers a 5-km reach of the Santa B-arbara River located in the Ecuadorian Andes, at 2330 masl, in Gualaceo. The model's performance was evaluated based on the water surface elevation and flood extent, in terms of the mean absolute difference and measure of fit. The analysis revealed that, for a given case, Iber 2D has the best performance in simulating the water level and inundation for flood events with 20- and 50-year return periods, respectively, followed by Flood Modeller 2D, HEC-RAS 2D, and PCSWMM 2D in terms of their performance. Grid resolution, the way in which hydraulic structures are mimicked, the model code, and the default value of the parameters are considered the main sources of prediction uncertainty.

HIGH RESOLUTION PARAMETRIC MODELLING FOR TWO-DIMENSIONAL RADAR TARGET USING PRONY ALGORITHM

On the conditions of low-resolution radar, a parametric model for two-dimensional radar target is described here according to the theory of electromagnetic scattering and the geometrical theory of diffraction. A high resolution estimation algorithm to extract the model parameters is also developed by building the relation of the scattering model and Prony model. The analysis of Cramer-Rao bound and simulation show that the method here has better statistical performance. The simulated analysis also indicates that the accurate extraction of the diffraction coefficient of scattering center is restricted by signal to noise ratio, radar center frequency and radar bandwidth.

A Numerical Algorithm Based on Quadratic Finite Element for Two-Dimensional Nonlinear Time Fractional Thermal Diffusion Model

In this article,a high-order scheme,which is formulated by combining the quadratic finite element method in space with a second-order time discrete scheme,is developed for looking for the numerical solution of a two-dimensional nonlinear time fractional thermal diffusion model.The time Caputo fractional derivative is approximated by using the L2-1formula,the first-order derivative and nonlinear term are discretized by some second-order approximation formulas,and the quadratic finite element is used to approximate the spatial direction.The error accuracy O(h3+
t2)is obtained,which is verified by the numerical results.

Visualization of Landscape Changes in a 3D Environment Using the Storytelling Approach—The Example of the City of Pristina

This study proposes a detailed concept of how landscape changes can be transferred and communicated in a 3D environment using the storytelling approach. In 2018, Mocnik and Fairbairn argued that maps are good for representing a geographic space but texts have a better benefit than maps for telling a story [1]. A framework is presented on how a landscape change can be retrieved out of textual descriptions. A prototype of a 3D model with a projection on top of it was developed. The case study tells the story of the landscape change in the city of Pristina. The key element of the visualization is a timeline. Several media like cadastral maps, orthophotos, texts, graphics, and background sound are used and combined in an animated light show and the visualization was evaluated within a user study.

Intelligent Deep Convolutional Neural Network Based Object DetectionModel for Visually Challenged People

Artificial Intelligence(AI)and Computer Vision(CV)advancements have led to many useful methodologies in recent years,particularly to help visually-challenged people.Object detection includes a variety of challenges,for example,handlingmultiple class images,images that get augmented when captured by a camera and so on.The test images include all these variants as well.These detection models alert them about their surroundings when they want to walk independently.This study compares four CNN-based pre-trainedmodels:ResidualNetwork(ResNet-50),Inception v3,DenseConvolutional Network(DenseNet-121),and SqueezeNet,predominantly used in image recognition applications.Based on the analysis performed on these test images,the study infers that Inception V3 outperformed other pre-trained models in terms of accuracy and speed.To further improve the performance of the Inception v3 model,the thermal exchange optimization(TEO)algorithm is applied to tune the hyperparameters(number of epochs,batch size,and learning rate)showing the novelty of the work.Better accuracy was achieved owing to the inclusion of an auxiliary classifier as a regularizer,hyperparameter optimizer,and factorization approach.Additionally,Inception V3 can handle images of different sizes.This makes Inception V3 the optimum model for assisting visually challenged people in real-world communication when integrated with Internet of Things(IoT)-based devices.

Global Two-Dimensional Chemistry Model and Simulation of Atmospheric Chemical Composition

A global two-dimensional zonally averaged chemistry model is developed to study the chemi-cal composition of atmosphere. The region of the model is from 90°S to 90°N and from the ground to the altitude of 20 km with a resolution of 5° x 1 km. The wind field is residual circulation calcu-lated from diabatic rate. 34 species and 104 chemical and photochemical reactions are considered in the model. The sources of CH4, CO and NOx, which are divided into seasonal sources and non-seasonal sources, are parameterized as a function of latitude and time. The chemical composi-tion of atmosphere was simulated with emission level of CH4, CO and NOx in 1990. The results are compared with observations and other model results, showing that the model is successful to simu-late the atmospheric chemical composition and distribution of CH4. Key words Global two-dimensional chemistry model - Atmospheric composition - Emission This work was supported by the State Key Program for basic research “ Climate Dynamics and Cli-mate Prediction Theory” (Pandeng-yu-21).The authors would like to express their thanks to the National Oceanic and Atmospheric Administration (NOAA), Climate Monitoring and Diagnostics Laboratory (CMDL), Carbon Cycle Group for providing the observational data of CO and CH4.

Comprehensive two-dimensional river ice model based on boundary-fitted coordinate transformation method

River ice is a natural phenomenon in cold regions, influenced by meteorology, geomorphology, and hydraulic conditions. River ice processes involve complex interactions between hydrodynamic, mechanical, and thermal processes, and they are also influenced by weather and hydrologic conditions. Because natural rivers are serpentine, with bends, narrows, and straight reaches, the commonly-used one-dimensional river ice models and two-dimensional models based on the rectangular Cartesian coordinates are incapable of simulating the physical phenomena accurately. In order to accurately simulate the complicated river geometry and overcome the difficulties of numerical simulation resulting from both complex boundaries and differences between length and width scales, a two-dimensional river ice numerical model based on a boundary-fitted coordinate transformation method was developed. The presented model considers the influence of the frazil ice accumulation under ice cover and the shape of the leading edge of ice cover during the freezing process. The model is capable of determining the velocity field, the distribution of water temperature, the concentration distribution of frazil ice, the transport of floating ice, the progression, stability, and thawing of ice cover, and the transport, accumulation, and erosion of ice under ice cover. A MacCormack scheme was used to solve the equations numerically. The model was validated with field observations from the Hequ Reach of the Yellow River. Comparison of simulation results with field data indicates that the model is capable of simulating the river ice process with high accuracy.

Modeling Tracer Flow Characteristics in Different Types of Pores: Visualization and Mathematical Modeling

Structure of porous media and fluid distribution in rocks can significantly affect the transport characteristics during the process of microscale tracer flow.To clarify the effect of micro heterogeneity on aqueous tracer transport,this paper demonstrates microscopic experiments at pore level and proposes an improved mathematical model for tracer transport.The visualization results show a faster tracer movement into movable water than it into bound water,and quicker occupancy in flowing pores than in storage pores caused by the difference of tracer velocity.Moreover,the proposed mathematical model includes the effects of bound water and flowing porosity by applying interstitial flow velocity expression.The new model also distinguishes flowing and storage pores,accounting for different tracer transport mechanisms(dispersion,diffusion and adsorption)in different types of pores.The resulting analytical solution better matches with tracer production data than the standard model.The residual sum of squares(RSS)from the new model is 0.0005,which is 100 times smaller than the RSS from the standard model.The sensitivity analysis indicates that the dispersion coefficient and flowing porosity shows a negative correlation with the tracer breakthrough time and the increasing slope,whereas the superficial velocity and bound water saturation show a positive correlation.

A Systematic Review of Computer Vision Techniques for Quality Control in End-of-Line Visual Inspection of Antenna Parts

The rapid evolution of wireless communication technologies has underscored the critical role of antennas in ensuring seamless connectivity.Antenna defects,ranging from manufacturing imperfections to environmental wear,pose significant challenges to the reliability and performance of communication systems.This review paper navigates the landscape of antenna defect detection,emphasizing the need for a nuanced understanding of various defect types and the associated challenges in visual detection.This review paper serves as a valuable resource for researchers,engineers,and practitioners engaged in the design and maintenance of communication systems.The insights presented here pave the way for enhanced reliability in antenna systems through targeted defect detection measures.In this study,a comprehensive literature analysis on computer vision algorithms that are employed in end-of-line visual inspection of antenna parts is presented.The PRISMA principles will be followed throughout the review,and its goals are to provide a summary of recent research,identify relevant computer vision techniques,and evaluate how effective these techniques are in discovering defects during inspections.It contains articles from scholarly journals as well as papers presented at conferences up until June 2023.This research utilized search phrases that were relevant,and papers were chosen based on whether or not they met certain inclusion and exclusion criteria.In this study,several different computer vision approaches,such as feature extraction and defect classification,are broken down and analyzed.Additionally,their applicability and performance are discussed.The review highlights the significance of utilizing a wide variety of datasets and measurement criteria.The findings of this study add to the existing body of knowledge and point researchers in the direction of promising new areas of investigation,such as real-time inspection systems and multispectral imaging.This review,on its whole,offers a complete study of computer vision approaches for quality control in antenna parts.It does so by providing helpful insights and drawing attention to areas that require additional exploration.

DETERMINATION OF PARAMETERS IN A TWO-DIMENSIONAL MODEL FOR FIXED-BED ADSORBERS

A new method is proposed for the determination of the parameters in a two-dimensionalmodel which characterizes the properties of axial and radial mixing and mass transport in afixed-bed adsorber.Parameter estimation for the model is carried out with methane-air-5A molecularsieve in a bed under the condition of step injection of tracer from a point on the main axis of thebed by the curve fitting method in the time domain.