Interactive Visualization Environment Research Articles

ASSESSMENT OF THE FINANCIAL RESULT OF PUBLIC-PRIVATE PARTNERSHIP PROJECT IMPLEMENTATION USING THE EXAMPLE OF A CONCESSION AGREEMENT

The article is aimed at developing a methodological approach to improving the efficiency of assessing the financial results of implementing Ukrainian and European business projects. In this context, the object of study is a specific individual partnership and cooperation project. The research has established that one of the key informational aspects of such a partnership is the assessment and forecasting of the financial result. The goal of the research is to present the methodological approach to assessing financial performance for an individual project in the most detailed form possible. The article presents an approach based on modern simulation modelling methods, systems analysis methodology, and the method of composite seasonal indices. All modelling processes were conducted using MATLAB software. MATLAB is a high-level programming language and interactive environment for numerical computation, visualization, and programming. This program is widely used for modelling and data processing in fields such as engineering, scientific research, and mathematics. The research result is presented as an approach to the mathematical modelling of assessing the financial performance of partnership projects of Ukraine with representatives of EU business. It is necessary to emphasize that the presented research has limitations related to changes in Ukraine's hyperdynamic external environment provoked by war. Forecasts may vary depending on the development of military actions. Therefore, the prospects for further research should be directed towards improving the informational provision in the system of partnership and cooperation with EU countries to increase their own investment security.

VELMA: Verbalization Embodiment of LLM Agents for Vision and Language Navigation in Street View

Incremental decision making in real-world environments is one of the most challenging tasks in embodied artificial intelligence. One particularly demanding scenario is Vision and Language Navigation (VLN) which requires visual and natural language understanding as well as spatial and temporal reasoning capabilities. The embodied agent needs to ground its understanding of navigation instructions in observations of a real-world environment like Street View. Despite the impressive results of LLMs in other research areas, it is an ongoing problem of how to best connect them with an interactive visual environment. In this work, we propose VELMA, an embodied LLM agent that uses a verbalization of the trajectory and of visual environment observations as contextual prompt for the next action. Visual information is verbalized by a pipeline that extracts landmarks from the human written navigation instructions and uses CLIP to determine their visibility in the current panorama view. We show that VELMA is able to successfully follow navigation instructions in Street View with only two in-context examples. We further finetune the LLM agent on a few thousand examples and achieve around 25% relative improvement in task completion over the previous state-of-the-art for two datasets.

Research on the Application of Extended Reality in the Construction and Management of Landscape Engineering

Landscape engineering plays a crucial role in urban construction and the development of ecological civilization in China. It actively designs and modifies natural elements, such as water and mountains, acting as the primary living infrastructure. This field continually receives great recognition and praise. Recent academic research has prioritized the use of extended reality (XR) technology to create a real-time interactive visual environment to tackle the issues presented by the dynamic nature of landscape engineering. This paper utilizes the PRISMA method to filter out 68 research documents related to XR in landscape engineering construction and management for bibliometric analysis. A comprehensive review is conducted on the precise and efficient utilization of XR to solve various issues in the field of landscape engineering. Using Cite Space 6.2.R6 (a visual bibliometric software) to visualize knowledge structures and research topics, the analysis includes temporal and spatial examination, application scenario analysis, and technological hierarchy analysis. The paper summarizes the current challenges that XR still faces in the landscape engineering field and envisions extensible application scenarios for XR, providing a reference roadmap for the implementation of XR in landscape engineering.

Evaluation of 3D geovisualization of volumetric geospatial data in the form of horizontal planes using selected software

The main motivation of the paper is to provide an overview of 3D geovisualization capabilities of selected software and present selected methods of visualization of 3D geospa-tial data using horizontal planes. The paper is focused on the evaluation of software and meth-ods for the visualization of thematic geospatial data with an emphasis on visual analysis in 3D. Meteorological data of the ALADIN forecast model were used to create visualizations. The first part focuses on the evaluation of selected software in terms of 3D visualization capa-bilities. The evaluation encompasses software tools such as geographic information systems, web-based solutions, and 3D computer graphics software. The result is a comparison of these software in terms of suitability for visual analysis in 3D, for example in terms of spatial data support, 3D visualizations, or analytical functions. The second part is focused on the presen-tation of four methods of 3D data visualization using horizontal planes for visualizing thematic data, including single plane, multiple planes without transparency, multiple planes with trans-parency, and multiple planes overlay. These methods were evaluated based on graphical var-iables, both the original ones defined by Jacques Bertin and those added later by other car-tographers, to achieve the most optimal visual analysis in 3D. The article concludes by high-lighting the advantages and disadvantages of the different visualization methods, and their specifics in terms of graphical variables. The importance of interactive visualization environ-ments for fully utilizing the potential of these methods is emphasized.

Augmented reality based interactive table-top environment for real-time visualization of control theory concepts: An empirical study

Augmented reality based interactive table-top environment for real-time visualization of control theory concepts: An empirical study

Study on the Multi-Level Experiment Teaching of NAO Robot Combined with Virtual and Reality

NAO is the most well-known and widely used humanoid robot in education and research in the world. With the development of computer technology and cloud computing, and the establishment of artificial intelligence specialty, robot teaching is more important in artificial intelligence specialty. The artificial intelligence specialty is a new specialty just established in the talent training program of Chinese universities. Its purpose is to cultivate application-oriented talents in China's artificial intelligence industry and promote the construction of first-class disciplines of artificial intelligence. MATLAB is the commercial mathematical software. It is a high-level technical computing language and interactive environment for algorithm development, data visualization, data analysis and numerical calculation. It is widely used in the experimental teaching of NAO robot. In the teaching of robot theory, kinematics, trajectory planning, dynamics and control are relatively abstract and complex, and there are a lot of formula derivation and differential equations. In order to improve the quality of NAO experiment teaching, this paper analyzes the current situation and existing problems in NAO experiment teaching. In the exploration and practice of robot experiment teaching, NAO robot is taken as the research object, and MATLAB is used to carry out robot simulation and control experiments. The paper presents a multi-level experimental teaching method of NAO robot based on the combination of virtual and Reality. The multi-level includes three levels: basic experiment, design experiment and innovative experiment. The paper describes the design and implementation process of the three-level experimental teaching in detail, and gives the assessment methods, characteristics and effectiveness evaluation of the experimental teaching. The teaching results show that the teaching effect is good, can stimulate students' enthusiasm for learning, and help to cultivate students' programming ability and innovation ability.

Interactive Learning Environment Through Visualization to Promote Creative Thinking Among Non-Major Undergraduate Computer Science Students Learning Computer Programming Subject

This study aimed to investigate whether the experience of learning using a visual interactive learning environment through visualization impacts performance and dimensions of creative potential in terms of creative thinking. Sixteen (16) non-random non-major undergraduate computer science students learning computer programming subjects were exposed to a visual interactive learning environment through visualization in a pre-experimental single group pre-posttest research design. Before and after participants learn using visual interactive learning environment through visualization for six (6) weeks, they must complete three Visual tests and two verbal tasks of the Torrance Tests of Creative Thinking (TTCT). Both descriptive and inferential statistics were used to analyze the data. The study showed significant evidence that the performance and creative level of the students are better after learning using a visual interactive learning environment except for Verbal Fluency and Verbal Flexibility dimensions of Creative thinking. Implications of these findings for future research are discussed.

An Immersive Virtual Reality Platform Integrating Human ECOG & sEEG: Implementation & Noise Analysis.

Virtual reality (VR) offers a robust platform for human behavioral neuroscience, granting unprecedented experimental control over every aspect of an immersive and interactive visual environment. VR experiments have already integrated non-invasive neural recording modalities such as EEG and functional MRI to explore the neural correlates of human behavior and cognition. Integration with implanted electrodes would enable significant increase in spatial and temporal resolution of recorded neural signals and the option of direct brain stimulation for neurofeedback. In this paper, we discuss the first such implementation of a VR platform with implanted electrocorticography (ECoG) and stereo-electroencephalography ( sEEG) electrodes in human, in-patient subjects. Noise analyses were performed to evaluate the effect of the VR headset on neural data collected in two VR-naive subjects, one child and one adult, including both ECOG and sEEG electrodes. Results demonstrate an increase in line noise power (57-63Hz) while wearing the VR headset that is mitigated effectively by common average referencing (CAR), and no significant change in the noise floor bandpower (125-240Hz). To our knowledge, this study represents first demonstrations of VR immersion during invasive neural recording with in-patient human subjects. Clinical Relevance- Immersive virtual reality tasks were well-tolerated and the quality of clinical neural signals preserved during VR immersion with two in-patient invasive neural recording subjects.

A visual analytics approach for the assessment of information quality of performance models—a software review

In this paper we provide a review of the main functionalities of a Visual Analytics Environment (VAE) developed for the assessment of data and information quality in the context of performance evaluation of research organizations. Performing data and information quality tests are necessary procedures to ensure the bibliometric and research performance evaluation analysis of organizations have the necessary robustness. The proposed environment is helpful to guide the user to an Information Quality-aware development of Performance models. This interactive visual analytics environment offers to the user the possibility to produce and compare information quality-aware indicators, exploring and defining correct behavior, identifying anomalous cases from both data quality and information quality perspectives, and supporting the user in forming hypotheses on possible causes for those anomalies. The proposed approach, exploiting visual interactive exploration results in a more efficient process, minimizing the number of cases for which a manual investigation is needed. The illustration on European higher education institutions data demonstrates the use of the presented functionalities and their benefits.

Improved Interaction of BIM Models for Historic Buildings with a Game Engine Platform

For the purpose of the conservation and representation of cultural heritage, the development of a visual interactive environment to provide an integrated application suitable for collecting a wide range of big data information from historic blocks is regarded as an effective solution. In this study, the existing modeling of wooden building information is imported into a game engine as a practical study for the design of a user-friendly interactive interface design, a Unity integration platform is built, a Revit external application is developed, and cloud services architecture is set to solve the transmission and integration of information models between different platforms. In addition to strengthening the future application of historic building information modeling, this visual information-based interactive environment can help enhance communication and subsequent management of repairs, and bring opportunities for sustainable management and diversified applications to the research field of historic building restoration.

Efficient multi-objective simulated annealing algorithm for interactive layout problems

This paper presents an efficient simulated annealing algorithm for solving multi-objective layout problems where several rectangular components are placed, respecting non-overlap and non-protrusion constraints in the given space. Resolving layout problems can be very hard in some industrial cases because problems are over-constrained and computing feasible optimal layout designs are time consuming. In most practical problems, both real and virtual components exist. The virtual components represent the required accessible space allowing the user to access to the component. The virtual components can overlap with each other, while the overlap is not allowed for the real components. Considering the limited layout design space, the capacity of the layout problem is analyzed using constructive placing techniques. To explore the feasible layout space, a hybrid simulated annealing is proposed to determine the order of placement; then, a constructive placing strategy based on empty maximal space is developed. What’s more, an interactive visualization environment is introduced between the optimization and expert. The proposed algorithm is the first attempt to search feasible space of multi-objective layout design by constructive placing method.

Immersive 5G Virtual Reality Visualization Display System Based on Big-Data Digital City Technology

The virtual reality visual display system creates a realistic virtual product display system, allowing users to swim in a three-dimensional virtual environment and perform interactive operations, fully simulating the process of shopping selection and payment in reality, so that users have an immersive feeling. The purpose of this article is to realize the design of an immersive 5G virtual reality visual display system through big-data digital city technology. This paper uses big-data digital city technology to design and implement an immersive virtual reality visualization system from the three-dimensional display mode of vision, hearing, and touch, creating a real and interactive three-dimensional visualization environment for users to have a more intuitive visual experience. The experimental results of this paper show that the smoothness of the virtual reality visualization system test can reach 60FPS, the excellent rate reaches nearly 33%, and the model scene-realistic feedback excellent rate is about 62.5%.

The human hepatocyte TXG-MAPr: gene co-expression network modules to support mechanism-based risk assessment

Mechanism-based risk assessment is urged to advance and fully permeate into current safety assessment practices, possibly at early phases of drug safety testing. Toxicogenomics is a promising source of mechanisms-revealing data, but interpretative analysis tools specific for the testing systems (e.g. hepatocytes) are lacking. In this study, we present the TXG-MAPr webtool (available at https://txg-mapr.eu/WGCNA_PHH/TGGATEs_PHH/), an R-Shiny-based implementation of weighted gene co-expression network analysis (WGCNA) obtained from the Primary Human Hepatocytes (PHH) TG-GATEs dataset. The 398 gene co-expression networks (modules) were annotated with functional information (pathway enrichment, transcription factor) to reveal their mechanistic interpretation. Several well-known stress response pathways were captured in the modules, were perturbed by specific stressors and showed preservation in rat systems (rat primary hepatocytes and rat in vivo liver), with the exception of DNA damage and oxidative stress responses. A subset of 87 well-annotated and preserved modules was used to evaluate mechanisms of toxicity of endoplasmic reticulum (ER) stress and oxidative stress inducers, including cyclosporine A, tunicamycin and acetaminophen. In addition, module responses can be calculated from external datasets obtained with different hepatocyte cells and platforms, including targeted RNA-seq data, therefore, imputing biological responses from a limited gene set. As another application, donors’ sensitivity towards tunicamycin was investigated with the TXG-MAPr, identifying higher basal level of intrinsic immune response in donors with pre-existing liver pathology. In conclusion, we demonstrated that gene co-expression analysis coupled to an interactive visualization environment, the TXG-MAPr, is a promising approach to achieve mechanistic relevant, cross-species and cross-platform evaluation of toxicogenomic data.

Visualization of the Stress-Strain State of Shell Structures Using Virtual and Augmented Reality Technologies

The paper describes a mathematical model of changes in the geometry of thin-shell structures for visualization of the analysis data on their stress-strain state (SSS). Based on this mathematical model, a visualization module for shell SSS visualization using VR and AR technologies was developed. The interactive visualization environment Unity 2019.3 and C# programming language were used. The interactive visualization module makes a 3D image of a shell structure and visualizes the SSS either through heat maps over the shell or through the changes in the shell geometry on the basis of the shell type, its geometric characteristics, and SSS analysis data (transferred to the visualization module by means of a JSON file). While working on the visualization module, the authors developed a system of components that makes it possible to visualize any 3D surface with coordinate axes (including numbers with a pitch determined automatically), visualize heat maps with a graduated scale, visualize a mesh over the graph to improve the perception of the surface deformations. The middle surface can also be deformed on the basis of SSS analysis data. This solution increases the efficiency of the work of specialists in civil engineering and architecture and can be used when training specialists in courses on thin-shell structures and procedural geometry.

PINA 3.0: mining cancer interactome.

Protein–protein interactions (PPIs) are crucial to mediate biological functions, and understanding PPIs in cancer type-specific context could help decipher the underlying molecular mechanisms of tumorigenesis and identify potential therapeutic options. Therefore, we update the Protein Interaction Network Analysis (PINA) platform to version 3.0, to integrate the unified human interactome with RNA-seq transcriptomes and mass spectrometry-based proteomes across tens of cancer types. A number of new analytical utilities were developed to help characterize the cancer context for a PPI network, which includes inferring proteins with expression specificity and identifying candidate prognosis biomarkers, putative cancer drivers, and therapeutic targets for a specific cancer type; as well as identifying pairs of co-expressing interacting proteins across cancer types. Furthermore, a brand-new web interface has been designed to integrate these new utilities within an interactive network visualization environment, which allows users to quickly and comprehensively investigate the roles of human interacting proteins in a cancer type-specific context. PINA is freely available at https://omics.bjcancer.org/pina/.

Visualization Environment for Federated Knowledge Graphs: Development of an Interactive Biomedical Query Language and Web Application Interface.

BackgroundEfforts are underway to semantically integrate large biomedical knowledge graphs using common upper-level ontologies to federate graph-oriented application programming interfaces (APIs) to the data. However, federation poses several challenges, including query routing to appropriate knowledge sources, generation and evaluation of answer subsets, semantic merger of those answer subsets, and visualization and exploration of results.ObjectiveWe aimed to develop an interactive environment for query, visualization, and deep exploration of federated knowledge graphs.MethodsWe developed a biomedical query language and web application interphase—termed as Translator Query Language (TranQL)—to query semantically federated knowledge graphs and explore query results. TranQL uses the Biolink data model as an upper-level biomedical ontology and an API standard that has been adopted by the Biomedical Data Translator Consortium to specify a protocol for expressing a query as a graph of Biolink data elements compiled from statements in the TranQL query language. Queries are mapped to federated knowledge sources, and answers are merged into a knowledge graph, with mappings between the knowledge graph and specific elements of the query. The TranQL interactive web application includes a user interface to support user exploration of the federated knowledge graph.ResultsWe developed 2 real-world use cases to validate TranQL and address biomedical questions of relevance to translational science. The use cases posed questions that traversed 2 federated Translator API endpoints: Integrated Clinical and Environmental Exposures Service (ICEES) and Reasoning Over Biomedical Objects linked in Knowledge Oriented Pathways (ROBOKOP). ICEES provides open access to observational clinical and environmental data, and ROBOKOP provides access to linked biomedical entities, such as “gene,” “chemical substance,” and “disease,” that are derived largely from curated public data sources. We successfully posed queries to TranQL that traversed these endpoints and retrieved answers that we visualized and evaluated.ConclusionsTranQL can be used to ask questions of relevance to translational science, rapidly obtain answers that require assertions from a federation of knowledge sources, and provide valuable insights for translational research and clinical practice.

Talk2Nav: Long-Range Vision-and-Language Navigation with Dual Attention and Spatial Memory

The role of robots in society keeps expanding, bringing with it the necessity of interacting and communicating with humans. In order to keep such interaction intuitive, we provide automatic wayfinding based on verbal navigational instructions. Our first contribution is the creation of a large-scale dataset with verbal navigation instructions. To this end, we have developed an interactive visual navigation environment based on Google Street View; we further design an annotation method to highlight mined anchor landmarks and local directions between them in order to help annotators formulate typical, human references to those. The annotation task was crowdsourced on the AMT platform, to construct a new Talk2Nav dataset with 10, 714 routes. Our second contribution is a new learning method. Inspired by spatial cognition research on the mental conceptualization of navigational instructions, we introduce a soft dual attention mechanism defined over the segmented language instructions to jointly extract two partial instructions—one for matching the next upcoming visual landmark and the other for matching the local directions to the next landmark. On the similar lines, we also introduce spatial memory scheme to encode the local directional transitions. Our work takes advantage of the advance in two lines of research: mental formalization of verbal navigational instructions and training neural network agents for automatic way finding. Extensive experiments show that our method significantly outperforms previous navigation methods. For demo video, dataset and code, please refer to our project page .

Talk2Nav: Long-Range Vision-and-Language Navigation with Dual Attention and Spatial Memory

The role of robots in society keeps expanding, bringing with it the necessity of interacting and communicating with humans. In order to keep such interaction intuitive, we provide automatic wayfinding based on verbal navigational instructions. Our first contribution is the creation of a large-scale dataset with verbal navigation instructions. To this end, we have developed an interactive visual navigation environment based on Google Street View; we further design an annotation method to highlight mined anchor landmarks and local directions between them in order to help annotators formulate typical, human references to those. The annotation task was crowdsourced on the AMT platform, to construct a new Talk2Nav dataset with 10, 714 routes. Our second contribution is a new learning method. Inspired by spatial cognition research on the mental conceptualization of navigational instructions, we introduce a soft dual attention mechanism defined over the segmented language instructions to jointly extract two partial instructions—one for matching the next upcoming visual landmark and the other for matching the local directions to the next landmark. On the similar lines, we also introduce spatial memory scheme to encode the local directional transitions. Our work takes advantage of the advance in two lines of research: mental formalization of verbal navigational instructions and training neural network agents for automatic way finding. Extensive experiments show that our method significantly outperforms previous navigation methods. For demo video, dataset and code, please refer to our project page.

Test of Arabidopsis Space Transcriptome: A Discovery Environment to Explore Multiple Plant Biology Spaceflight Experiments.

Recent advances in the routine access to space along with increasing opportunities to perform plant growth experiments on board the International Space Station have led to an ever-increasing body of transcriptomic, proteomic, and epigenomic data from plants experiencing spaceflight. These datasets hold great promise to help understand how plant biology reacts to this unique environment. However, analyses that mine across such expanses of data are often complex to implement, being impeded by the sheer number of potential comparisons that are possible. Complexities in how the output of these multiple parallel analyses can be presented to the researcher in an accessible and intuitive form provides further barriers to such research. Recent developments in computational systems biology have led to rapid advances in interactive data visualization environments designed to perform just such tasks. However, to date none of these tools have been tailored to the analysis of the broad-ranging plant biology spaceflight data. We have therefore developed the Test Of Arabidopsis Space Transcriptome (TOAST) database (https://astrobiology.botany.wisc.edu/astrobotany-toast) to address this gap in our capabilities. TOAST is a relational database that uses the Qlik database management software to link plant biology, spaceflight-related omics datasets, and their associated metadata. This environment helps visualize relationships across multiple levels of experiments in an easy to use gene-centric platform. TOAST draws on data from The US National Aeronautics and Space Administration’s (NASA’s) GeneLab and other data repositories and also connects results to a suite of web-based analytical tools to facilitate further investigation of responses to spaceflight and related stresses. The TOAST graphical user interface allows for quick comparisons between plant spaceflight experiments using real-time, gene-specific queries, or by using functional gene ontology, Kyoto Encyclopedia of Genes and Genomes pathway, or other filtering systems to explore genetic networks of interest. Testing of the database shows that TOAST confirms patterns of gene expression already highlighted in the literature, such as revealing the modulation of oxidative stress-related responses across multiple plant spaceflight experiments. However, this data exploration environment can also drive new insights into patterns of spaceflight responsive gene expression. For example, TOAST analyses highlight changes to mitochondrial function as likely shared responses in many plant spaceflight experiments.

A Critical Approach to Digital Pedagogy - A Holistic Methodology in the Information Society

In the present, the use of info-communication technology has become a living communication reality that pervades everyday life. The relationship between the learning and teaching process to medialization and digital technology has become increasingly prominent. Since the spread of digital data, and especially the emergence of the World Wide Web, many phenomena and trends and could have been observed regarding the use of ICT in education. Some of these trends have reached on theirpeak the plateau of productivity since the 1990s, but more have proven to be merely fad. One of the most frequently used methods in the present is, for example, the flipped classroom, where students acquire the theory at home through digital curricula, while in the classroom they deepen their knowledge and interact with teachers. From the 2000s, e-learning has become a new educational environment which includes novel forms of learning and teaching supported by ICT, both in form,content, and methodology. In the present, E-learning continues to be a significant trend, and many teachers are just now discovering the benefits of the platform and some of them turn to blended learning (Kis-Tóth – Lengyelné, 2012).The use of a Learning Management Systems (LMS) relies on multimedia and linking texts - hypertext - while it requires interaction between the learner (user) and the text (information). Gamification supports the player within, where point systems, levels, and healthy competition between students play an essential role. Although not a traditional methodology, the use of social media and web 2.0 in education is becoming more and more important, students follow or write blogs, or edit Wikipedia. As it is observed that nowadays students’ attention can be maintained for a shorter period then in the case of previous generations, the use of micro-content in the transfer of knowledge adapts to the accelerated information-taking habits. In the universe of micro-content, the use of smaller curricula reinforces thepopularity of independent learning. Finally, current trends include the strengthening of the interactive visual learning environment, (Benedek, 2019) and the use of augmented reality content, or how Microsoft refers to it, mixed reality.The lesson of the past 30 years might be that using technology itself, without a sophisticated methodology that takes into account as many didactic aspects is not enough. The technology-centered approach teaching-learning process is just as much a mistake as the thinking that automatically assumes the effectiveness of learning organization due to the use of modern technology. Any methodology in which the demonstration is given prominence describes that its application, if unrelated to the process, can very easily become a dead end. The use of technology, unless it is based on methodological principles, does not lead to an increase in the efficiency of the learning process. By focusing merely on the application of technology, unrealistic expectations cannot be met.” (Ollé, 2013: 102.)