Dynamic Visualization Techniques Research Articles

Enhancing IT Project Portfolio Management Through Dynamic Dashboard Visualization and Integrated Chatbot and Mathematical ML Model for Strategic Decision Making

This project paper presents an innovative approach to enhance IT Project Portfolio Management (IT PPM) using dynamic dashboard visualization and machine learning (ML) techniques. Effective IT PPM is essential for organizations to align IT projects with business objectives and optimize resource allocation. However, conventional methods often lack innovation and real-time visibility, leading to suboptimal decision-making and costly software investments. The objective of this project is to develop a dynamic dashboard visualization system integrated with a machine learning model derived from the Meta-Portfolio Method (MPM). The MPM leverages advanced analytics and historical project data to dynamically allocate resources and prioritize projects based on risk-return profiles. By incorporating the MPM into the dashboard, organizations gain real-time insights into project status, progress, and resource allocation, enabling informed decision-making and proactive portfolio optimization. The ML model derived from the MPM analyzes historical project data, including success rates, resource intensity, criticality, regulatory compliance, and portfolio diversification, to predict optimal project selection and resource allocation. By dynamically adapting to changing market conditions and project dynamics, the ML model facilitates strategic decision-making and enhances portfolio performance. Through the integration of dynamic dashboard visualization and ML-driven decision support, organizations can streamline IT PPM processes, improve project outcomes, and achieve strategic objectives effectively and efficiently. This innovative approach empowers organizations to navigate the complexities of IT project portfolios with agility, foresight, and confidence.

A taxonomy of didactic roles of dynamic visualization in animated mathematics videos

Abstract In recent years, a multitude of innovative educational videos focusing on mathematics and employing dynamic visualization techniques have been published on YouTube. From a sample of videos, we develop a taxonomy of didactical roles of dynamic visuals and supporting animation techniques. The taxonomy is constructed through an open coding approach, involving an iterative process of defining, analysing and refining the codes. Additionally, we conducted an interview with a video creator about the intended roles of dynamic visuals employed in his animations. The taxonomy encompasses the following categories of roles: connect objects, (co)vary objects, dynamic concept visualization, dynamic process visualization, symbol sense, connect to reality and generalization. These roles are implemented through animation techniques like moving and morphing. The nomenclature of these roles suggests their affiliation with various mathematics education research perspectives, including covariational thinking, concept–process duality, symbol sense and conversion between registers. The taxonomy serves as a foundational framework for further research into the learning outcome and effectiveness of dynamic visualization in educational mathematics videos.

In situ Electrical Impedance Tomography for Visualizing Water Transportation in Hygroscopic Aerogels.

The global water crisis demands immediate attention, and atmospheric water harvesting (AWH) provides a viable alternative. However, studying the real-time subtle relationship between water absorption, diffusion, and internal structure for hygroscopic materials is challenging. Herein, a dynamic visualization technique is proposed that utilizes an in situ electrical impedance tomography (EIT) system and a precise reconstruction algorithm to achieve real-time monitoring of the water sorption process within aerogels from an internal microstructural perspective. These results can be inferred that composites' pore sizes affecting the kinetics of their moisture absorption. In addition, the diffusion path of moisture absorption and the distribution of stored moisture inside aerogels exhibit intrinsic self-selective behavior, where the fiber skeleton of the aerogel plays a crucial role. In summary, this work proposes a generic EIT-based technique for the in situ and dynamic monitoring of the hygroscopic process, pointing to an entirely new approach regarding research on AWH materials.

Thermal removal mechanism of paraffin deposits: Impact of flowrate on removal efficiency

Active heating is increasingly explored as a cost-effective strategy for managing wax deposition in production flowlines. While these methods are commonplace throughout the industry to maintain or raise the temperature of the production fluid above the wax appearance temperature (WAT), there are no clear guidelines for wax removal using active heating. In this study, a novel dynamic microscopic visualization technique is used to observe the effects of the flow regime on the removal process. At high enough temperatures, 50.6 °C and 43.3 °C, 100% removal is observed in both turbulent and laminar cases. A removal temperature of 37.0 °C resulted in 72.5% removal under turbulent conditions, and 97% removal under laminar conditions. No reduction in thickness was observed in either case when removing at a temperature of 30.6 °C. Turbulent conditions were also shown to significantly increase the heating time required before detachment compared to laminar conditions at the same removal temperature. The turbulent experiments required 2.7 times as long for detachment to occur when removal temperatures were raised to 43.3 °C, and 4.6 times as long when temperatures were raised to 37.0 °C. Turbulent conditions are also shown to require higher temperatures to trigger the removal process, likely due to the harder deposits formed at higher flow rates. This analysis sheds light on the impact flow regime and deposit properties have on the removal process. The results obtained in this study enhance the understanding of the impact of flow on thermal removal and this knowledge is necessary for accurate removal modeling.

Engage, Explore, Enlighten: Proposing an Interactive Visualization and Analysis Model (IVAm) in Quantitative Research

The landscape of quantitative research is getting transformed by increasing complexity of data as well as growing demand for knowledge that is accessible. Users often find it hard to engage with traditional methods used in analyzing and presenting data thus giving shallow insights. IVAm is a new concept that calls for the integration of dynamic data visualization techniques to promote better interpretation, accessibility, and engagement with data. IVAm is not just about having tools; it advocates for a comprehensive approach that nurtures user-centric interaction, encourages transparency, and enables different audiences to use data so as to make informed decisions. The paper discusses the theoretical underpinnings, key principles, and methodological framework behind IVAm which can revolutionize how data are presented, enhance understanding and increase the reach of quantitative research. Lastly, it highlights some of the challenges faced by this approach as well as its future directions thereby setting grounds for further development and application of IVAm.

Visualization of thermal removal mechanism of paraffin deposits: Providing guidelines for minimum temperature requirements

Active heating is increasingly explored as a cost-effective strategy for managing wax deposition in production flowlines. While active heating is widely used across the industry to maintain or raise the temperature of the production fluid above the wax appearance temperature (WAT), there exists no clear understanding of the mechanism and guidelines for wax removal using active heating technology. Currently, operators tend to aim for temperatures far above the WAT to ensure removal. There is an interest in the finding of the actual temperature targets. If these can be defined, lowering current operational targets, reducing energy requirements, and therefore reducing costs becomes possible. To this end, a novel dynamic microscopic visualization technique is employed to understand the removal mechanism as the deposit is exposed to varying removal temperatures. As the removal temperature is raised to WAT + 54 % the deposit underwent 100 % removal, while increasing it to WAT + 12 % resulted in 97 % removal throughout the experiment. Raising the removal temperature to WAT − 7 % resulted in no removal.A mechanism for thermal removal is proposed based on visual evidence for a counter-diffusion process preceding detachment. During removal, the deposit becomes less dense with wax crystals over time, lowering its yield stress until a point where shear forces from the flow can strip and carry away large chunks of wax deposit. Higher removal temperatures require less time for detachment to occur. Increasing the coolant temperature to WAT + 54 % required only 8 min for detachment to occur, while increasing it to WAT + 12 % extended this time to 46 min. Deposit yield stress and fluid shear stresses are used to determine the minimum removal temperature for active heating. The pipe wall needs to be raised at least to this temperature for removal to occur. The higher the wall temperature is raised above this value, the faster the removal will occur. Understanding this mechanism can inform the development of accurate removal models and improve production economics.

Developing and testing a web-based platform for visualizing flow in a watershed

Abstract Thanks to the rapid development of internet technology and computer hardware, it is now possible to use web services to provide visual simulations of flow field calculation results. Visualization technology can display complex water flow data and the laws that govern water flow through graphical means, and can be used to solve scientific and engineering problems related to water conservancy. In this study, we developed a platform for visualizing flow in a watershed based on a Cesium rendering framework with Browser/Server (B/S) architecture that used isosurface, particles, texture-based, and dynamic flow visualization techniques to visualize scalar field, vector field, and dynamic flow field data. Furthermore, our performance test results indicate that the rendering performance meets the practical application requirements for visualizing large-scale flow fields by employing frame interpolation and viewpoint-based dynamic rendering techniques. The results from testing the water flow visualization platform in the Beijiang River Basin, Guangdong Province, China, demonstrated that the platform performed well on different devices and that the running frame rate reached 50–60 fps. These findings can be used to guide further development and applications of web-side flow field visualization technology.

Animation as a dynamic visualization technique for improving process model comprehension

Process models are widely used for various system analysis and design activities, but it is challenging for stakeholders to understand these complex artifacts. In this work, we focus on the use of dynamic visualization techniques, in particular animation, to help reduce users’ cognitive load when making sense of process models. We built on the principles of the cognitive theory of multimedia learning, cognitive load theory, and cognitive dimensions framework to develop an adaptive animation solution. Our experiments suggested that process model comprehension improves when users of process models are provided with animation features; the effect is moderated by process modeling expertise according to a U-shape. Our study contributes to the field of conceptual modeling by making a strong case for the use of animation to support complex problem-solving tasks. Moreover, our animation solution offers ample opportunities for being integrated into industrial modeling tools.

Reminiscing the Legendary P. Ramlee through Data Visualization Technique

P.Ramlee is a nickname for Tan Sri Datuk Amar Teuku Zakaria bin Teuku Nyak Putih. He is an evergreen and legendary Malaysian film actor, director, singer, songwriter, composer, and producer. Although the films related to him are mostly black and white, they are still the favourite characters of today's youth. To this day, the jokes and the pieces of advice contained in his work are still relevant in the current society. Due to his great contribution to the film industry and music literature, he is regarded as a famous icon of Malaysia entertainment. Acknowledging his contributions, many research works have been conducted and reported in academic journals but most of these works concentrated on the literary perspective of his artefacts. On the contrary, this paper provides additional knowledge on interactive and dynamic visualization techniques of the P.Ramlee unstructured data. The output of the work presented in this paper provides a fundamental knowledge on the design and implementation for effective visual data analytics.

Unsteady flow characteristics regarding hump instability in the first stage of a multistage pump-turbine in pump mode

Abstract This article reports the fluid-dynamical analyses of unsteady flow in the first stage of a multistage pump-turbine where hump instability occurs. This stage can be seen as a centrifugal pump with multistage guide vanes in pump mode. Experimental and numerical approaches are adopted to contribute the understanding of the highly complex flow regime inner the test pump. In the experimental test, both dynamic pressure measurement and flow visualization techniques are adopted. A commercial code with detached eddy simulation (DES) model is used to compute the flow regime. The frequency analysis indicates that two unsteady flow patterns with a constant frequency occur in the hump instability region. The numerical and experimental unsteady flow fields are analysed to study the fluid-dynamical features of these unsteady patterns, in order to investigate the origin and reveal their contributions to the hump instability.

TMNVis: Visual analysis of evolution in temporal multivariate network at multiple granularities

Temporal (Dynamic) multivariate networks consist of objects and relationships with a variety of attributes, and the networks change over time. Exploring such kind of networks in visualization is of great significance and full of challenges as its time-varying and multivariate nature. Most of the existing dynamic network visualization techniques focus on the topological structure evolution lacking of exploration on the multivariate data (multiple attributes) thoroughly, and do not cover comprehensive analyses on multiple granularities. In this paper, we propose TMNVis, an interactive visualization system to explore the evolution of temporal multivariate network. Firstly we list a series of tasks on three granularities: global level, subgroup level and individual level. Secondly three main views, which rely mainly on timeline-based method while animation subsidiary, are designed to resolve the analysis tasks. Thirdly we design a series of flexible interactions and develop a prototype system. At last we verify the effectiveness and usefulness of TMNVis using a real-world academic collaboration data.

Dynamic Visualization of Time-Based Changes to Data Generated by Reddit.com: The Real Time Conversation Project

With the increased amount of data generated by social networking sites there is also increased difficulty in the analysis of this data, including time-based changes, which can provide unique insights in social network analysis. Information visualization is a vital tool in assisting social scientists with analysis of large quantities of data; however, the gathering, formatting, and visualizing of time-related data from social networking sites still remains an obstacle. This research explores the process of gathering time-based data in real time and using dynamic visualization techniques to visualize and analyze time-based changes in data generated by discussions on the social networking site Reddit. The outcome culminates in our deliverable, the Real Time Conversation Project. KEYWORDS: Visualization; Network Analysis; Social Network; Reddit; Gephi

The dynamic graph wall: visualizing evolving graphs with multiple visual metaphors

Visualizing dynamic graphs is challenging due to the many data dimensions to be displayed such as graph vertices and edges with their attached weights or attributes and the additional time dimension. Moreover, edge directions with multiplicities and the graph topology are also important inherent features. However, in many dynamic graph visualization techniques each graph in a sequence is treated the same way, i.e., it is visually encoded in the same visual metaphor or even in the same layout. This visualization strategy can be problematic if the graphs are changing topologically over time, i.e., if a sparse graph becomes denser and denser over time or a star pattern is changing into a dense cluster of connected vertices. Such a dynamic graph data scenario demands for a visualization approach which is able to adapt the applied visual metaphor to each graph separately. In this paper we describe the dynamic graph wall to solve this problem by using multiple visual metaphors for dynamic graphs which are computed automatically by algorithms analysing each individual graph based on a given repertoire of graph features. The biggest issue in this technique for the graph dynamics, however, is the preservation of the viewer’s mental map at metaphor changes, i.e., to guide him through the graph changes with the goal to explore the data for time-varying patterns. To reach this goal we support the analyst by an interactive highlighting feature but we also display graphs in comparative metaphor rows to visually investigate the commonalities and differences over time. Graphical Abstract text

EgoSlider: Visual Analysis of Egocentric Network Evolution.

Ego-network, which represents relationships between a specific individual, i.e., the ego, and people connected to it, i.e., alters, is a critical target to study in social network analysis. Evolutionary patterns of ego-networks along time provide huge insights to many domains such as sociology, anthropology, and psychology. However, the analysis of dynamic ego-networks remains challenging due to its complicated time-varying graph structures, for example: alters come and leave, ties grow stronger and fade away, and alter communities merge and split. Most of the existing dynamic graph visualization techniques mainly focus on topological changes of the entire network, which is not adequate for egocentric analytical tasks. In this paper, we present egoSlider, a visual analysis system for exploring and comparing dynamic ego-networks. egoSlider provides a holistic picture of the data through multiple interactively coordinated views, revealing ego-network evolutionary patterns at three different layers: a macroscopic level for summarizing the entire ego-network data, a mesoscopic level for overviewing specific individuals' ego-network evolutions, and a microscopic level for displaying detailed temporal information of egos and their alters. We demonstrate the effectiveness of egoSlider with a usage scenario with the DBLP publication records. Also, a controlled user study indicates that in general egoSlider outperforms a baseline visualization of dynamic networks for completing egocentric analytical tasks.

Visual Exploration of Sparse Traffic Trajectory Data.

In this paper, we present a visual analysis system to explore sparse traffic trajectory data recorded by transportation cells. Such data contains the movements of nearly all moving vehicles on the major roads of a city. Therefore it is very suitable for macro-traffic analysis. However, the vehicle movements are recorded only when they pass through the cells. The exact tracks between two consecutive cells are unknown. To deal with such uncertainties, we first design a local animation, showing the vehicle movements only in the vicinity of cells. Besides, we ignore the micro-behaviors of individual vehicles, and focus on the macro-traffic patterns. We apply existing trajectory aggregation techniques to the dataset, studying cell status pattern and inter-cell flow pattern. Beyond that, we propose to study the correlation between these two patterns with dynamic graph visualization techniques. It allows us to check how traffic congestion on one cell is correlated with traffic flows on neighbouring links, and with route selection in its neighbourhood. Case studies show the effectiveness of our system.

A new dynamic visualization technique for system dynamics simulations

This article addresses a main research question in System Dynamics, the correct understanding of the relationship between model structure and behavior, from a new perspective: the field of Information Visualization. We propose a new dynamic visualization technique that is different from the current static visualization techniques. The technique was applied to a classical case and tested through visual and interactive software built as proof of concept. The case illustrated the potential of the new technique to confront the problem by providing the user a visual experience in real time, so his/her understanding could be more direct and immediate. This visualization technique could be adapted and generalized to other simulation methodologies.

Study on Flexible Dynamic Visualization Techniques

With the requirement of intelligent performances, flexible dynamic visualization techniques are proposed and their definition and connotation are illustrated. The techniques combine the traditional visualization technique with the flexible dynamic idea and made of two layers of theoretical models of flexible dynamic visualization, thus closing a technical gap in the field. The efficiency of these techniques is proved by their application in the development of a teaching demonstration system in computer science and technology. It is concluded that these techniques not only improve the discipline construction and classroom instruction of computer science and technology, but also serve as a model for their application in other disciplines and fields.

Parallel Edge Splatting for Scalable Dynamic Graph Visualization

We present a novel dynamic graph visualization technique based on node-link diagrams. The graphs are drawn side-byside from left to right as a sequence of narrow stripes that are placed perpendicular to the horizontal time line. The hierarchically organized vertices of the graphs are arranged on vertical, parallel lines that bound the stripes; directed edges connect these vertices from left to right. To address massive overplotting of edges in huge graphs, we employ a splatting approach that transforms the edges to a pixel-based scalar field. This field represents the edge densities in a scalable way and is depicted by non-linear color mapping. The visualization method is complemented by interaction techniques that support data exploration by aggregation, filtering, brushing, and selective data zooming. Furthermore, we formalize graph patterns so that they can be interactively highlighted on demand. A case study on software releases explores the evolution of call graphs extracted from the JUnit open source software project. In a second application, we demonstrate the scalability of our approach by applying it to a bibliography dataset containing more than 1.5 million paper titles from 60 years of research history producing a vast amount of relations between title words.

Neutron Visual Sensing Techniques Using the High Intensity Neutron Sources

In this manuscript, the fundamentals and merits of neutron visual sensing techniques, high-speed consecutive visual sensing technique, high-speed-scanning dynamic 3D visualization technique, multi-beam 3D velocimetry technique and energy-selective neutron imaging technique are summarized. These techniques have been developed mainly for the R&D of the nuclear energy system using the high-flux research reactors, JRR-3 and JRR-4, and a high-intensity pulsed neutron source, J-PARC. Very unique visualization and measurement, e.g. dynamic 3D velosimetry in JRR-4 were successfully carried out by these neutron visual sensing techniques. An energy-selective neutron imaging, e.g. the neutron resonance absorption imaging in J-PARC is extremely unique and newly developed visualization and measurement technique. Analytical investigation for the feasibility of multiphase flow experiment in J-PARC was also reported using a Monte Carlo neutron simulation code. It was confirmed from the analytical work that the measurement error of the void fraction of two-phase flow can be reduced by the energy-selective neutron imaging technique.

Visual Analysis of Dynamic Data Streams

For scientific data visualizations, real-time data streams present many interesting challenges when compared to static data. Real-time data are dynamic, transient, high-volume and temporal. Effective visualizations need to be able to accommodate dynamic data behavior as well as Abstract and present the data in ways that make sense to and are usable by humans. The Visual Content Analysis of Real-Time Data Streams project at the Pacific Northwest National Laboratory is researching and prototyping dynamic visualization techniques and tools to help facilitate human understanding and comprehension of high-volume, real-time data. The general strategy of the project is to develop and evolve visual contexts that will organize and orient high-volume dynamic data in conceptual and perceptive views. The goal is to allow users to quickly grasp dynamic data in forms that are intuitive and natural without requiring intensive training in the use of specific visualization or analysis tools and methods. Thus far, the project has prototyped five different visualization prototypes that represent and convey dynamic data through human-recognizable contexts and paradigms such as hierarchies, relationships, time and geography. We describe the design considerations and unique features of these dynamic visualization prototypes as well as our findings in the exploration and evaluation of their use.