Visualization Model Research Articles

Flow and plugging behavior of foams in fractures of fractured reservoirs

The development of fractured reservoirs can benefit from the use of foams, as they can enter fractures to increase the flow resistance of high-permeability zones, thereby redirecting fluid flow toward low-permeability zones. This can reduce the leak-off of working fluids during flow and improve the reservoir stimulation efficiency. The fracture visualization models applicable to micro-scale foam flow are developed to fully reveal the flow and plugging behavior of foams in micro-fractures. The models are accompanied by the implementation of the micro-fracture foam flow experiments. The experiment results show that with the increasing flow rate and foaming agent concentration, foams become smaller, more homogeneous, stable, and capable of plugging micro-fractures. However, both significantly large and small gas-liquid ratios degrade these properties of foams. For optimal results, a gas/liquid flow rate of 100–150 μL/min, a gas-liquid ratio of 2–4, and a foaming agent concentration of higher than 0.75 wt% are recommended. During foam flow, foams preferably enter wider fractures, where they accumulate and become trapped, plugging the flow channels. This results in a diversion of the subsequent foams towards narrower fractures, leading to more effective plugging of the fractures.

An insight into the effect of primary hidden microfissures on mechanical behaviors and failure characteristics of brittle basalt

The anisotropy of mechanical properties of hard rocks is usually affected by the internal primary hidden microfissure structures, which tend to induce secondary rock fracture propagation even surrounding rock instabilities in deep underground excavation. This research attempts to reveal the control effect of primary hidden microfissures on the mechanical behaviors and failure characteristics of cryptocrystalline basalt with hidden microfissures (CBWHM) through a series of laboratory tests. Firstly, a geometric feature extraction method for primary hidden microfissures of basalt rock has been proposed, by which 20 groups of three-dimensional (3D) visualization models of cylindrical basalt samples were established, and the distribution location and volume crack rate (KV) of hidden microfissures were simultaneously determined. On this basis, a series of the uniaxial compression tests of basalt samples with synchronous acoustic emission (AE) were carried out. Results show that the location and development degree of primary hidden microfissures significantly control the mechanical characteristics of basalt, with the relevant micro-fracture events occurring earlier and throughout the whole loading process compared with intact samples. In general, there exists a uniaxial polynomial fitting relationship between the strength of basalt samples and KV. The larger the KV, the lower the peak strength (σc) of basalt, which could decrease by 30–50% compared to that of the intact rock when KV is more than 5‰. However, when the hidden microfissures with large dip angles are located close to the central axis, the influence of KV on the rock strength becomes less, but the crack propagation and failure morphology are still obviously controlled by the hidden microfissures. The statistical analysis results of surface cracks and rock fragment characteristics of the damaged basalt samples further show that the basalt rock is easy to expand, penetrate and eventually fail along the hidden microfissures under loading, and it is tensile fracture that controls the failure of CBWHM. With an increase of KV, the mass percentage (W) of the coarse particle of the sample fragments increases gradually, and the fractal dimension (D) of the rock fragments and KV of the hidden microfisures show an obvious logarithmic curve relationship. The research could provide effective guidance for the interpretation of the meso-mechanism of hard rock failures.

Analysis of the Evolution Trend of Segmentation of Online Public Opinion Based on Dynamic Tracking Technology

Abstract In this paper, the dynamic tracking technique is applied to analyze the triggering factors of online public opinion, modify the feature subsets and establish a basic database of sensitive information. The test of statistical characteristics of the evolution process of public opinion is realized by using the prediction of time series by the ANOVA algorithm, and on this basis, the smoothness of the model is realized by testing the parameters. In the process of establishing the quantitative index system, the seasonal difference algorithm is introduced to predict the development trend of public opinion on hot topics to realize the visualization model design. Finally, in order to verify the validity of the model, an experiment was conducted with Event A as an example. The results show that users can set a total of 4 keywords with an average word frequency of 0.03 Hz. The prediction accuracy in different periods can reach 88.73% on average, and the adaptation value can reach 0.8 percentage points on average. Thus, it can be seen that the trend analysis model of online public opinion evolution constructed in this paper can quantitatively analyze the mechanism of public opinion segmentation evolution and the trend prediction problem and provide a theoretical reference for the government to govern public opinion.

Target Netgrams: An Annulus-Constrained Stress Model for Radial Graph Visualization.

We present Target Netgrams as a visualization technique for radial layouts of graphs. Inspired by manually created target sociograms, we propose an annulus-constrained stress model that aims to position nodes onto the annuli between adjacent circles for indicating their radial hierarchy, while maintaining the network structure (clusters and neighborhoods) and improving readability as much as possible. This is achieved by having more space on the annuli than traditional layout techniques. By adapting stress majorization to this model, the layout is computed as a constrained least square optimization problem. Additional constraints (e.g., parent-child preservation, attribute-based clusters and structure-aware radii) are provided for exploring nodes, edges, and levels of interest. We demonstrate the effectiveness of our method through a comprehensive evaluation, a user study, and a case study.

A Bibliometric Analysis of Sharia Bonds (Sukuk) in Islamic Capital Market

Sharia bonds (Sukuk) are one of the products of the Islamic capital market; the development of Islamic bonds is rapid in countries where most of the population is Muslim, using Islamic law principles. This study systematically explores the development of Sharia bond research (Sukuk) in the Islamic capital market in the observation period for six years, namely from 2017 to 2022. Bibliometrics is a data analysis approach in this study using the VOSviewer application. Quantitative description is an analysis method used in this study to describe the econometric literature with a network visualization model on the topic to be discussed. The sample is obtained using the publish or perish application with data from Google Scholar and Scopus, so the data obtained is then sorted to become relevant sample data of 760 articles related to Sukuk in the Islamic capital market. The results of the first VOSviewer mapping are ten articles with the most citations, network visualization, overlay visualization, and density visualization, and there are five clusters between item relationships; the keyword "Sharia Bond" became a popular keyword during the observation period, so that Islamic Bonds have been in great demand as evidenced by the development of research related to Sharia bonds.

Risk and uncertainty assessment in software project management: integrating decision trees and Monte Carlo modeling

The evaluation of risk and uncertainty in the context of software project management is the subject of this paper. This paper discusses the difficulties faced by project managers in handling uncertainty brought on by the complex nature of software projects and the ever evolving requirements of technology. A review of the literature, data production, visualization, statistical analysis, and mathematical modeling are included in this study. The goal of this study is to create a methodical approach to assist project managers in making decisions by considering the inherent uncertainty in software development and to find approaches and procedures that may successfully reduce risks, improve decision-making, and eventually result in the implementation of successful projects. The following tasks were carried out: to evaluate risk and uncertainty by examining the state-of-the-art in decision theory and its applications in software project management; to develop an integrated strategy that blends Monte Carlo Simulation with Decision Trees to assess risk and uncertainty in software project management; to generate data, visualize it, and perform statistical analysis to comprehend how project outcomes, costs, and time are affected; to identify important variables affecting project results and decision-making using decision trees; to use Monte Carlo simulation to create project scenarios and weigh the likelihood of each; and to supply project managers with knowledge and suggestions to help them make informed decisions and successfully manage risks. Methods. To evaluate risk and uncertainty in software project management, this paper analyzes the decision theory approaches currently used as well as Decision Trees and Monte Carlo Simulation techniques. Results. This study offers thorough insights into how project results, costs, and duration vary among various techniques. The critical factors that have a substantial influence on project success are shown through decision trees. According to the study’s findings, combining decision theory and statistical analysis equips project managers to make wise decisions despite uncertainty. Conclusions. Project managers may improve decision making, risk reduction, and overall project success by applying these cutting-edge approaches. To adapt these techniques to unique software project management contexts and real-world situations, further study and implementation in practice are necessary. With the use of such techniques, the software development sector would be better able to manage the complexity of projects and provide good results within set financial and time parameters.

A Vector Field Visualization Method for Trajectory Big Data

With the rapid growth of trajectory big data, there is a need for more efficient methods to extract, analyze, and visualize these data. However, existing research on trajectory big data visualization mainly focuses on displaying trajectories for a specific period or showing spatial distribution characteristics of trajectory points in a single time slice using clustering, filtering, and other techniques. Therefore, this paper proposes a vector field visualization model for trajectory big data, aiming to effectively represent the inherent movement trends in the data and provide a more intuitive visualization of urban traffic congestion trends. The model utilizes the motion information of vehicles to create a travel vector grid and employs WebGL technology for vector field visualization rendering. The vector field effects are effectively displayed by generating many particles and simulating their movements. Furthermore, this research also designs and implements congestion trend point identification and hotspot congestion analysis, thus validating the practicality and effectiveness of trajectory big data vector field visualization. The results indicate that compared to traditional visualization methods, the vector field visualization method can demonstrate the direction and density changes in traffic flow and predict future traffic congestion. This work provides valuable data references and decision support for urban traffic management and planning.

Influence of pore structure characteristics on the gas permeability of concrete

The permeability of concrete is a key factor in determining its durability. Permeability of porous materials in general is determined by pore characteristics (e.g., porosity, pore size distribution, tortuosity, etc.). In this investigation, we attempted to observe the relationship between the pore characteristics and the permeability of concrete. Nuclear magnetic resonance (NMR), mercury intrusion porosimetry (MIP), nitrogen adsorption, and X-ray computed tomography (X-CT) were used to examine the microstructures of three concrete materials labeled C30, C45, and C50. The results show that the combined aperture size distribution curve generated by N2GA and MIP can more accurately depict the distribution of micro to macro pores in the sample than any single method alone. The three-dimensional visualization model reconstructed by X-CT can provide a more intuitive reflection of the distribution of large pores in concrete. The pore ratios measured by NMR and MIP both have satisfactory correlations with gas permeability, but the pore ratio measured by NMR has a stronger correlation with gas permeability. There is a good correlation between gas permeability and the pore ratios contributed by different segments measured by NMR. In addition, the inherent gas permeability coefficient has a slightly stronger correlation with the median pore size than with the critical pore size.

Establishing Riboglow-FLIM to visualize noncoding RNAs inside live zebrafish embryos

The central role of RNAs in health and disease calls for robust tools to visualize RNAs in living systems through fluorescence microscopy. Live zebrafish embryos are a popular system to investigate multicellular complexity as disease models. However, RNA visualization approaches in whole organisms are notably underdeveloped. Here, we establish our RNA tagging and imaging platform Riboglow-FLIM for complex cellular imaging applications by systematically evaluating FLIM capabilities. We use adherent mammalian cells as models for RNA visualization. Additional complexity of analyzing RNAs in whole mammalian animals is achieved by injecting these cells into a zebrafish embryo system for cell-by-cell analysis in this model of multicellularity. We first evaluate all variable elements of Riboglow-FLIM quantitatively before assessing optimal use in whole animals. In this way, we demonstrate that a model noncoding RNA can be detected robustly and quantitatively inside live zebrafish embryos using a far-red Cy5-based variant of the Riboglow platform. We can clearly resolve cell-to-cell heterogeneity of different RNA populations by this methodology, promising applicability in diverse fields.

Using the multiple linear regression based on the relative importance metric and data visualization models for assessing the ability of drought indices

Abstract In this study, the power of 12 of the most widely used meteorological drought indices was compared. For this purpose, the datasets of 12 stations (from 1967 to 2021) with different climatic conditions in Iran were used. For statistical analysis, multiple linear regression based on the relative importance metric introduced by the Lindeman, Merenda, Gold (MLR-LMG) and data visualization (DV) models were used. In the temporal assessment, the relative importance metrics (RIM) between the drought severity based on the different drought indices and the annual yield of rain-fed winter wheat (AYW) based on the fitted MLR-LMG model was investigated at the annual timescale in the chosen stations. In the spatial evaluation, the RIM between the drought severity based on the different drought indices and the AYW were investigated each year (1967, … , 2021). The results showed that in temporal assessment, the modified standardized precipitation evapotranspiration index (MSPEI) was the most suitable (58.33% of selected stations). Also, in spatial evaluation, the MSPEI and Z-score were the most efficient drought indices (65.45% and 27.27% of the years, respectively). The validation results of the fitted MLR-LMG models showed that the models were trustworthy in all stations and all years.

Factors of Employee Attrition: A Logistic Regression Approach

The problem of employee turnover has gradually become a common problem faced by companies around the world. Because it has several major negative impacts on the company's cultural and economic levels, it's urgent to solve this problem. In this paper, IBM's employee data is visualized to get the factors that affect employee attrition. At the same time, a predictive model based on logistic regression analysis was constructed to provide quantitative data for the impact of various factors on employee turnover. After multiple model evaluations, the goodness of fit and accuracy of the forecasting model were judged to be good. According to the data visualization and prediction model, the company's employee turnover factors were summarized, including both human resource factors and contextual factors such as age, salary, marital status. These influencing factors and the analysis of the relationship between them can be used as the theoretical basis for the company's future employee policies, providing direction and solutions for its work on reducing employee attrition.

Application of Data Visualization Interaction Technology in Aerospace Data Processing

A visualization and interactive network topology model are studied based on real-time features generated during spaceflight. Start by establishing a consistent set of data and logical interaction interfaces. This paper presents a method of scenario model construction and application programming based on virtual reality technology. The scene elements are extracted into two types of primitives, namely logical type and simulated object type. This provides a unified architecture for the editing and processing of graphic elements. This system can realize the automatic creation of the scene. Then the point cloud data obtained by sparse reconstruction of SFM is reconstructed to the Poisson surface. You get a dense, uniform grid. Experiments show that the proposed algorithm can realize the 3D reconstruction of non-cooperative objects. The spatial feature points obtained in the spatial positioning of non-cooperative objects can provide necessary technical support for its orbit positioning. The model can quickly generate new model scenario pages according to the characteristics of the task. This method changes the display mode, which can only be static or limited dynamic before. It has also improved the efficiency of space mission preparation.

Impact of Education in Indian & Foreign Universities by using SPSS method

The future of both countries and individuals is significantly influenced by education. In recent years, both Indian and foreign universities have experienced significant transformations that have had a profound impact on the education sector. This comparative analysis aims to examine the key changes and their consequences in Indian and foreign educational institutions. India, with its diverse cultural fabric and increasing focus on knowledge-driven industries, has witnessed a remarkable shift in its education system. Technological advancements have facilitated the adoption of online learning platforms, blended learning models, and personalized approaches to education. These developments have expanded access to quality education, bridging geographical barriers and reaching learners in remote areas. Similarly, foreign universities have also undergone noteworthy transformations. Globalization, digitalization, and the increasing demand for international education have prompted these institutions to diversify their programs, enhance cross-cultural experiences, and adopt innovative teaching methods. Furthermore, the growing emphasis on interdisciplinary studies and research collaborations has propelled foreign universities to the forefront of knowledge creation and dissemination. This analysis will explore the key factors driving the impact on education in both Indian and foreign universities, shedding light on the unique challenges and opportunities each system faces in the pursuit of educational excellence. Understanding the impact of changes in education in Indian and foreign universities is of significant importance for various stakeholders. Policymakers can benefit from this research to design effective strategies that promote accessibility, equity, and quality education. Educational institutions can gain insights into best practices, innovative teaching methods, and technological advancements to enhance their educational offerings. Students and parents can make informed decisions regarding educational choices and identify opportunities for global learning experiences. Ultimately, this research contributes to fostering educational excellence and meeting the evolving needs of learners in a rapidly changing world. “We are using SPSS (Statistical Package for the Social Sciences) which is a widely used software program for statistical analysis.” It provides tools for data management, data visualization, and statistical modeling, making it valuable for researchers and analysts in various fields, particularly in the social sciences. INPUT PARAMETERS taken as 1. Gender?, 2. Age?, 3.Qualification?, 4. Profession?, 5. Family status? OUTPUT PARAMETERS taken as 6. How satisfied are you with Indian universities?, 7. How would you rate the quality of education provided in Indian universities?, 8. How much advanced is education in foreign countries than India? , 9. How much does foreign infrastructure and facilities affect students?, 10. How much do you choose to be a student in foreign university or Indian University?, 11. How well can u afford a seat in foreign universities? The Cronbach's Alpha Reliability result is displayed here. The model's overall Cronbach's Alpha value is.675, which denotes a 68% dependability level. The Cronbach's Alpha value model with a score of at least 60% can be considered for analysis based on the literature study. Indian universities have shown improvement in recent years, but they still struggle with overall quality. Foreign universities are renowned for their high standards, advanced research facilities, and experienced faculty. The quality of education in foreign universities often attracts students globally. However, Indian universities play a crucial role in providing affordable education to a large population, contributing to social mobility and addressing the country's diverse educational needs.

Characteristics and Stabilization Mechanism of Three-Phase Foam: Improving Heavy Oil Recovery via Steam Stimulation through Two-Dimensional Visual Model

There is a problem of a rapid decline in production caused by the repeated heating of the near-wellbore zone during steam stimulation. Finding a suitable foam system to expand the area of the steam chamber and slow down the rapid production of hot water during the recovery process can effectively improve the effect of steam stimulation. In this paper, CGS foam was prepared with high-temperature-resistant surfactant GD, graphite particles, and clay particles. Through the study of foam properties, it was found that with the addition of particles, the strength of the foam’s liquid film, half-life time, and temperature resistance was greatly improved. The appropriate permeability of the CGS foam and the movement characteristics of it in formations with different permeabilities were studied through a plugging experiment with a sand pack. The plugging performances of the GD foam, CGS foam, and pure particles in a simulated reservoir were compared. The development of the steam cavity during the steam stimulation process and the influence of injecting GD foam and CGS foam on the flow in the simulated reservoir were studied through a two-dimensional visualization model. The temperature resistance and stability of the CGS foam were better than those of GD foam in the simulated formation.

Advancements in Oral Maxillofacial Surgery: A Comprehensive Review on 3D Printing and Virtual Surgical Planning

This comprehensive review explores the advancements in Orthognathic and Oral Maxillofacial Surgery, focusing on the integration of 3D Printing and Virtual Surgical Planning (VSP). Traditional surgical methods, while effective, come with inherent risks and complications, and can lead to variability in outcomes due to the reliance on the surgeon’s skill and experience. The shift towards patient-centric care necessitates personalized surgical methods, which can be achieved through advanced technology. The amalgamation of 3D printing and VSP revolutionizes surgical planning and implementation by providing tactile 3D models for visualization and planning, and accurately designed surgical guides for execution. This convergence of digital planning and physical modeling facilitates a more predictable, personalized, and precise surgical process. However, the adoption of these technologies presents challenges, including the need for extensive software training and the steep learning curve associated with computer-aided design programs. Despite these challenges, the integration of 3D printing and VSP paves the way for advanced patient care in orthognathic and oral maxillofacial surgery.

A New Approach to 3D Digital Evaluation and Analysis In Geological Engineering

The initial geological analysis of hydropower projects is greatly complicated by the existence of complex geological conditions. To adapt advances in informatization and digitalization to the needs of the engineering survey industry and to conduct geological analysis more intuitively, in the present study the development of “GeoBIM”, a geological 3D design platform based on the DSI modeling engine and a “graphics + data” architecture is rerported. GeoBIM realized the integration of 3D information in the whole process of geological work, from field data collection, model design, and analysis to approval. Taking the siting and construction of a hydropower station as an example, the field data collection and cataloging APP (boreholes, caverns, slopes) and web-side exploration monitoring platform of GeoBIM were used to build a 3D geological fine visualization model. The principle of dissipated energy was used to analyze the quality of the rock mass, which showed the spatial distribution characteristics of local geological conditions and rock mass quality, improving the efficiency and intuitiveness of engineering rock mass quality classification. GeoBIM was compared with traditional 2D geological analysis methods and actual conditions to demonstrate the rationale and intuitive use of the 3D digital evaluation method in geological engineering. Bangladesh J. Bot. 52(2): 679-688, 2023 (June) Special

„Wizualizacja otwarta” jako narzędzie demokratyzacji wiedzy

In this poster I compare two types of visualization that can be distinguished by the role of the viewer. In the first, which I call “closed visualization,” interpretation is seen as a decoding of meanings already set by the author. The other—“open visualization”—sees the viewer as an active co-creator of meanings. In its processual character, open visualization elicits the critical potential of the imagination and is open to new contexts and interpretations. As such, open visualization democratizes the production of knowledge by enabling the critical analysis of the spectator. Instead of the hegemonic production of discourse typical of closed visualization, it introduces a “diagonal perspectivism” that allows problems to be seen from differentiated perspectives. As examples of the mentioned models of visualization I will analyze two projects: Neil Halloran’s The Shadow Peace: The Nuclear Threat and Aby Warburg’s Mnemosyne Atlas.

In vivo real-time monitoring of the development of hypoxia and angiogenesis in cervical cancer

The growth of solid tumors is inevitably accompanied by hypoxia and angiogenesis. Understanding the true state of tissue hypoxia and angiogenesis during tumor progression will help further comprehend the tumor microenvironment and cancer therapy. Here, we provided a novel strategy for the long-term tracking of tumor hypoxia and angiogenesis in cervical cancer. The hypoxia response elements (HRE)-driven luciferase (LUC) reporter gene transfected cervical cancer cell lines were constructed for hypoxia visualization. The hypoxia response activity of HRE-driven LUC was verified in HeLa cells and then monitored via the HeLa-HRE-LUC tumor-bearing mouse models by bioluminescence imaging (BLI). An oxygen-sensitive nanoparticle was constructed for glycerol monooleate cubic liquid crystal material loaded with Ir(piq)3/IR780 and could be used for phosphorescence-fluorescence imaging. The imaging result showed that the nanoparticles labeled the low oxygen region overlapped with the BLI signal region detected by HRE-driven LUC in vivo, which confirmed that the hypoxia visualization platform could genuinely reflect the hypoxia level in vivo. The angiogenesis in vivo was reflected by changes in deoxygenated/oxygenated hemoglobin detected by photoacoustic imaging. Besides these, anticancer drug apigenin down-regulated HIF-1α and VEGF under hypoxia conditions and inhibited the tube formation in vitro. Then, the inhibition effects were verified in the hypoxia and angiogenesis visualization model in vivo. This study confirmed a novel in vivo real-time monitoring of tumor hypoxia and angiogenesis strategy, which can provide useful information for further research on cancer progression and anticancer therapy.

ShapeGraMM: On the fly procedural generation of massive models for real-time visualization

In this study, we propose ShapeGraMM (Shape Grammar for massive models), an expandable grammar that procedurally generates geometries in real-time to create 3D scenes of massive models. Procedural modeling has attracted attention for its ability to quickly create 3D scenes using a compact representation, which stores generation rules rather than an explicit representation of the scene. Our work is an extension of the Computer Generated Architecture (CGA) shape grammar specification. We introduce rules that will take the visibility of the camera into account and decide whether or not it should continue to generate. ShapeGraMM explores the repetitions and patterns present in massive models, helping it render scenes, reduce its memory footprint, and procedurally process the scene efficiently. We propose an engine implementation that generates scenes on the fly using ShapeGraMM, followed by its evaluation using massive real-world models. We conducted a case study testing our solution with large-scale CAD models of the oil & gas industry in the web context, which is a more limited platform than the desktop. In contrast to random models commonly generated by procedural generation methodologies, the original models of our study were modeled in a non-random method. Our results show that the solution has high performance and maintains a compact representation of the models offline and in runtime. The procedural engine renders a massive scene containing over 11 million objects at interactive frame rates.

On the complexity of the storyplan problem

We study the problem of representing a graph as a storyplan, a recently introduced model for dynamic graph visualization. It is based on a sequence of frames, each showing a subset of vertices and a planar drawing of their induced subgraphs, where vertices appear and disappear over time. Namely, in the StoryPlan problem, we are given a graph and we want to decide whether there exists a total vertex appearance order for which a storyplan exists. We prove that the problem is NP-complete, and complement this hardness with two parameterized algorithms, one in the vertex cover number and one in the feedback edge set number of the input graph. We prove that partial 3-trees always admit a storyplan, which can be computed in linear time. Finally, we show that the problem remains NP-complete if the vertex appearance order is given and we have to choose how to draw the frames.