Generation Of Graphics Research Articles

An Easily Accessible, Semi-Automated Approach to Creating Personalized Normative Feedback and Risk Feedback Graphics.

Personalized normative feedback interventions show efficacy in reducing health risk behaviors (e.g., alcohol use, sexual aggression). However, complex personalized normative feedback interventions may require manual methods of inputting participant data into graphics, which introduces error, and automated approaches require substantial technical costs and funding and may limit the types of feedback that can be provided. To make personalized normative feedback more accessible, we outline a method of using easily accessible software programs including IBM Statistical Package for the Social Sciences (SPSS), Microsoft Excel, and Microsoft PowerPoint, to create and display complex personalized normative feedback graphics. We also describe methods through which personalized normative feedback graphics can be created within a larger preventive intervention for alcohol and sexual assault in college men. We first provide step-by-step instructions for collecting data and then creating semi-automated syntax files within SPSS and Excel to merge participant data into complex personalized normative feedback graphics in Excel. To do so, we append annotated syntax in text and in supplemental material. Next, we outline the process of creating risk feedback graphics, whereby individual items or exact wording of items are displayed back to the participant. Finally, we provide guidance regarding the process of translating graphics from Excel for viewing via PowerPoint without having to manually update PowerPoint slides for each presentation. Via the described syntax and graphic generation, researchers are then able to create semi-automated personalized normative feedback and risk feedback graphics. This tutorial may help in increasing the dissemination of complex personalized normative feedback interventions.

Vector Graphics Generation with LLMs: Approaches and Models

Vector Graphics Generation with LLMs: Approaches and Models

Determination of hydrostatic pressure on the plane surface of an arbitrary non-simmetrical form by the three-command method K123

Competitive struggle in the conditions of wide access to unlimited amounts of information and computerization of all branches of production and services imposes strict requirements on specialized knowledge, practical skills and general mathematical culture of future engineers. The online program of modern multivariate engineering calculation of the problem of determining the force of hydrostatic pressure on an element of a flat asymmetric surface with a curvilinear face is presented - https://www.k123.org.ua/jeh5.html. Algorithms are implemented according to the author's method of three commands K123 (c) Yu.D. Kopanytsia (hereinafter the K123 method). A client-server solution based on CGI technology with a web form for inputting source data has been implemented. The results of the online calculation were performed according to the new analytical dependencies obtained on the basis of the author's method K123. In parallel, the numerical algorithms of the author's method of three K123 commands and the conclusions of the corresponding calculations in tabular form were implemented. Realized generation of graphics by the server program based on the coordinates of the points obtained by iterative calculations according to the algorithms of the numerical implementation of the K123 method. The relative error of iterative calculations and the estimation of the accuracy of the result are automatically determined based on the proposed exact analytical dependencies.

JCVI: A versatile toolkit for comparative genomics analysis.

The life cycle of genome builds spans interlocking pillars of assembly, annotation, and comparative genomics to drive biological insights. While tools exist to address each pillar separately, there is a growing need for tools to integrate different pillars of a genome project holistically. For example, comparative approaches can provide quality control of assembly or annotation; genome assembly, in turn, can help to identify artifacts that may complicate the interpretation of genome comparisons. The JCVI library is a versatile Python-based library that offers a suite of tools that excel across these pillars. Featuring a modular design, the JCVI library provides high-level utilities for tasks such as format parsing, graphics generation, and manipulation of genome assemblies and annotations. Supporting genomics algorithms like MCscan and ALLMAPS are widely employed in building genome releases, producing publication-ready figures for quality assessment and evolutionary inference. Developed and maintained collaboratively, the JCVI library emphasizes quality and reusability.

Development of MetaXplore: An Interactive Tool for Targeted Metagenomic Analysis.

Over the last decades, the analysis of complex microbial communities by high-throughput sequencing of marker gene amplicons has become routine work for many research groups. However, the main challenges faced by scientists who want to make use of the generated sequencing datasets are the lack of expertise to select a suitable pipeline and the need for bioinformatics or programming skills to apply it. Here, we present MetaXplore, an interactive, user-friendly platform that enables the discovery and visualization of amplicon sequencing data. Currently, it provides a set of well-documented choices for downstream analysis, including alpha and beta diversity analysis, taxonomic composition, differential abundance analysis, identification of the core microbiome within a population, and biomarker analysis. These features are presented in a user-friendly format that facilitates easy customization and the generation of publication-quality graphics. MetaXplore is implemented entirely in the R language using the Shiny framework. It can be easily used locally on any system with R installed, including Windows, Mac OS, and most Linux distributions, or remotely via a web server without bioinformatic expertise. It can also be used as a framework for advanced users who can modify and expand the tool.

Anemia in Heart Failure: A Perspective from 20-Year Bibliometric Analysis.

Anemia in patients with heart failure (HF) is a growing concern. However, there has no bibliometric analysis in this area up to now. The aim of this study is to explore the status and trends in the field of anemia in HF through the bibliometric analysis, and to provide an outlook on future research. We retrieved publications from the Web of Science Core Collection database, and the following data analysis and visualization tools were utilized to perform data processing, statistical computing and graphics generation: VOSviewer (v.1.6.18), CiteSpace (v.6.2 R5), Scimago Graphica (v.1.0.36), Biblimatrix and Microsoft Excel. We identified a total of 3490 publications from 2004 to 2023. The publications in the field of anemia in HF are growing steadily. The United States, the United Kingdom, and Italy were the leading countries in this area. Stefan D Anker, as the most influential author, held the most total citations and publications. Harvard University was the most productive institution in this area. The European Journal of Heart Failure had published the most papers. Through the analysis of co-citations, 14 major clusters based on cluster labels were identified. Keyword analysis showed that mortality, outcome, prevalence, and risk were the most frequent keywords, and the potential research hotspots in the future will be intravenous iron and iron deficiency. This study provides a comprehensive analysis of countries, authors, institutions, journals, co-cited references, and keywords in the field of anemia in HF through bibliometric analysis and data visualization. The status, hotspots and future trends in this field offer a reference for in-depth research. Further studies are necessary in the future to broaden the spectrum of research in this field, to evaluate comprehensive approaches to treating anemia in patients with HF, and to find rational targets for the management of anemia.

The Investigation of Deep Learning Models Utilized in Vector Graphics Manipulation

Vector graphics, 2D or 3D, hold paramount significance across various professional domains, including graphic design, web design, architecture, and engineering. However, traditional methods of creating vector graphics are characterized by low efficiency. This review explores the integration of some deep learning models designed for 2D and 3D vector graphics generation and manipulation, summarizing their main tasks and methods. In terms of 2D vector graphics, this review examines advanced models, including Convolutional Neural Networks, Generative Adversarial Networks, and more, for diverse tasks such as font or icon generation and image manipulation. For 3D vector graphics, this paper assesses the progress achieved in models tailored for point cloud and image reconstruction, as well as 3D shape generation, using approaches such as Variational Autoencoders, Multi-Layer Perceptrons, and Transformers. This review also assesses their progress and limitations, acknowledging a comprehensive overview of deep learning models in vector graphic manipulation, and emphasizing their potential impact on the design industry while recognizing the challenges ahead.

Integrated Reporting and Group Decision-Making for Sustainable Development: A Bibliometric Review

The demands of society are constantly evolving, imposing significant pressures on business organizations within the context of sustainable development policy. As a result, organizations have begun to move towards promoting information disclosure through integrated reporting, transitioning from sustainability reports to financial reports. Simultaneously, decisions made to address specific problems are no longer the sole responsibility of a single individual. Challenges now revolve around group decision-making with the aim of achieving a consensus solution. To comprehend the landscape of integrated reporting and group decision-making in the scientific literature concerning sustainable development, a bibliometric review was conducted across major scientific databases from 2008 to 2023. The analysis utilized Bibliometrix, based on the R language, and Biblioshiny for graphic generation. The results indicate a quantitative increase in publications addressing integrated reporting and group decision-making in the context of sustainable development. However, a thematic isolation among existing studies was evident, pointing to an opportunity for future research to bridge the gap and establish more robust connections between the subjects. 
 Keywords: integrated reporting, group decision-making, sustainable development, bibliometric review

Electric field-driven up-and-down motion of the flexible tail of Al13+ cluster system-a nano-scale flipper.

Dynamic metal nanoclusters have become a hot area of research in the field of nanoscience and nanotechnology due to their potential applications in micro devices. One such dynamic cluster is a quasi-planar ground state (GS) Al13+ cluster which exhibits anelectric field driven up and down flipping motion of the flexible tail which oscillates with respect to the mean plane. A Car-Parrinello molecular dynamics (CPMD) simulation has been carried out to understand the nature of dynamics of the cluster. CPMD simulation study reveals that the flexible tail region of the Al13+ isomeric system (two ground states M1, M2 and a transition state TS connecting them) can be engaged in a systematic up down flipping motion by the application of a transverse electric field. A saw tooth electric field of amplitude 5.19V/nm is sufficient to induce the up-and-down flipping oscillation of the cluster, which has an average oscillation frequency of around 20 THz. AIM, NICS and AdNDP analyses also have been carried out to understand the fluxional nature of the cluster from the electronic structural perspective. Electronic structural analysis of selected optimized intermediate states in the presence of transverse electric field has also been analyzed to correlate the electronic structure with the dynamic nature of the cluster. Single-point energies of all intermediate states between two minima of Al13+ clusters connected through a transition state cluster. Optimized geometries of Al13+ clusters in the presence of electric field of different strengths have been carried out by using the Gaussian 03 package. 6-311 + G(d) basis set and B3LYP hybrid density functional have been utilized for these studies. To establish the flipping motion, Car-Parrinello molecular dynamics (CPMD) has been performed using the cp.x module of the Quantum ESPRESSO 6.3.0 program package using the Perdew-Burke-Ernzerhof (PBE) functional, plane-wave basis set and ultrasoft pseudopotentials. ORTEP-3 and POV ray-3.7 software packages have been used for visualization and graphics generation. Atoms in molecule (AIM), Adaptive Natural Density Partitioning (AdNDP) analysis have been carried out using Multiwfn 3.7 program package.

Fractal Art Graphic Generation Based on Deep Learning Driven Intelligence

Fractal Art Graphic Generation Based on Deep Learning Driven Intelligence

Analysis and Research on Rice Disease Identification Method Based on Deep Learning

Rice is one of the most important food crops in China and around the world. However, with the continuous transformation of human activities, the quality of climate, soil, and water sources has also changed, and disease affecting rice has become increasingly serious. Traditional artificial pest identification methods have been unable to adapt to the occurrence of a large number of diseases, and artificial naked eye identification also increases the uncertainty of the identification results, and cannot “suit the remedy to the case”, which will not cure the disease, or even achieve half the result with half the effort. In the incidence range of rice diseases, rice blast, rice false smut, and bacterial blight have the highest incidence rate, the greatest harm, and are the most representative. Therefore, this paper mainly focuses on the above three categories. In this paper, the identification of rice diseases is further studied. First, sample pictures of rice blast, rice false smut, and bacterial leaf blight diseases are collected. Due to the differences in the distance and light of the sample photos, their size and angle is biased. Therefore, some means are needed to unify the specifications of these images, so as to improve the efficiency of network model recognition. Neural network recognition needs to absorb many sample images to classify and learn features. The main research objects of this paper are rice blast, rice false smut, and bacterial wilt. Therefore, this paper also expands the data set for this kind of disease, and unifies the specifications through size cutting, angle change, and vertical symmetrical mirror image processing. Then, we built a new network model based on deep learning to realize the parameter initialization design. The accuracy of the rice disease identification model built at the beginning does not satisfy the practical requirements. In order to upgrade the model in depth, this experiment increases the entry point of analysis and research, and integrates four parameters: iteration times, batch size, learning rate, and optimization algorithm in order to strive for the optimization of the experimental results. In this study, the confusion matrix is selected as the evaluation standard, and experimental results with more objectivity and reference value are obtained through the horizontal comparison of visual graphics generator (VGG) and residual network (ResNet), two highly referential network models. The results show that the recognition accuracy of the optimized model is 98.64%, which achieves the goal of accurately identifying diseases.

Visually Impaired Children with Special Educational Needs: Identifying Suitable Tactile Graphics Learning Materials

How to design and generate tactile graphics that have clear semantic meaning and are easy for visually impaired children to recognise using their sense of touch in special education is currently a challenge in China. This study summarises the advantages and disadvantages in different technologies for tactile graphics generation by analysing 12 papers in the last ten years on tactile graphics in education field. The insight from this work will help researchers, design professionals, visually impaired children and educators in China to make informed decisions about what they should focus on, how they should do it, and why they should do so.

Possibilities of Use for Fractal Techniques as Parameters of Graphic Analysis

Image processing remains an area that has impact on the software industry and is a field that is permanently developing in both IT and industrial contexts. Nowadays, the demand for fast computing times is becoming increasingly difficult to fulfill in the case of massive computing systems. This article proposes a particular case of efficiency for a specifically developed model for fractal generations. From the point of view of graphic analysis, the application can generate a series of fractal images. This process is analyzed and compared in this study from a programming perspective in terms of both the results at the processor level and the graphical generation possibilities. This paper presents the structure of the software and its implementation for generating fractal images using the Mandelbrot set. Starting from the complex mathematical set, the component iterations of the Mandelbrot algorithm lead to optimization variants for the calculation. The article consists of a presentation of an optimization variant based on applying parallel calculations for fractal generation. The method used in the study assumes a high grade of accuracy regarding the selected mathematical model for fractal generation and does not characterize a method specially built for a certain kind of image. A series of scenarios are analyzed, and details related to differences in terms of calculation times, starting from the more efficient proposed variant, are presented. The developed software implementation is parallelization-based and is optimized for generating a wide variety of fractal images while also providing a test package for the generated environment. The influence of parallel programming is highlighted in terms of its difference to sequential programming to, in turn, highlight recent methods of speeding up computing times. The purpose of the article is to combine the complexity of the mathematical calculation behind the fractal sets with programming techniques to provides an analysis of the graphic results from the point of view of the use of computing resources and working time.

The Use of a Roadheader Simulator in Research of Dynamics and Energy-Consumption of Excavating Underground Roadways and Tunnels

Boom-type roadheaders are commonly used for excavation of roadways in underground mines, tunnels, and other architectural structures using trenchless techniques, as well as sinking shafts and occasionally excavating the harder soil and softer formations in cut and cover construction. The main research and development of these machines is to offer solutions for automatic control. This refers to automation or robotization of the operation, and raises the possibility of their eventual unmanned operation. This article presents a roadheader research simulator which implements experimentally verified mathematical models describing the dynamics of a roadheader in operation and the rock cutting process. Due to very high computational requirements, a distributed system comprising several workstations connected via TCP/IP was used. Both the visualization of the roadheader in the heading face of the excavation and the graphic simulation of the course of the rock-cutting process were carried out using the Autodesk Inventor Professional 2022 graphics engine. It provided the simulator with a virtual scene environment and enabled the control of the roadheader model’s movement during the simulated cutting process, including the generation of breakout graphics in the heading face while drilling a roadway or tunnel. The presented roadheader simulator enables the determination of various time characteristics, for example, dynamic loads, power demand, efficiency, energy consumption, and others. It is still under development.

Digital Media Art Creation Based on Virtual Reality and Semantic Feature Fusion

With the development of the times and science and technology, virtual reality technology as a high-tech technology has gone into people’s vision and deeps into every aspect of people’s lives and plays a more and more important role. In today’s era, with the rapid development of digital new media technology and the gradual formation of a diversified media pattern, virtual reality technology generates a three-dimensional realistic virtual environment with its three-dimensional graphics generation technology, multisensing interaction technology, and high-resolution display technology. A special interactive device is required to enter the virtual environment. This is a brand-new comprehensive information technology, which is more and more widely used in various important fields of modern digital media design. This paper introduces a variety of digital media to promote the creation of virtual reality creation technology. Virtual reality technology in digital media art is more convenient, and more creative forms continue to emerge. The popularity of the virtual reality technology will undoubtedly promote the progress and development of the times and gives the digital media art more forms and volumes. In this paper, using virtual reality technology to digital media art, the forms of technology are summarized, and the way to cite examples is illustrated. This paper is aimed at analyzing and summarizing the virtual reality technology in the digital media art application, and virtual reality technology can give more valuable things in the digital media art creation and also hope to be able to bring some thinking and creative inspiration to writers or readers.

Real-Time Probabilistic Tropical Cyclone Forecasting in the Cloud

Abstract Despite improvements in predicting the track and intensity of tropical cyclones (TCs), these storms with major societal and economic impacts continue to pose challenges for statically provisioned computational resources. The number of active storms varies from day to day, leading to regular bursts of irregular computational loads atop an already busy production schedule for weather prediction centers. The emergence of high-resolution ensemble TC prediction to quantify the uncertainty in track and intensity exacerbates this problem by requiring multiple forecasts run for each storm, each representing a possible outcome. With more than a decade of progress in the literature describing research and real-time numerical weather prediction in the cloud, we set out to evaluate if the commercial cloud environment could cope with the unique demands of TC ensemble forecasts. We describe a demonstration using a high-performance computing environment within the Microsoft Azure cloud to test dynamic resource provisioning to address time-varying resource challenges. We deployed existing operational models, implemented a combination of vendor-provided and open-source tools to orchestrate the cycling production workflows, and developed techniques for automatic error handling to keep production on schedule with minimal operator intervention. Despite challenges, our production pipeline from data ingest, forecast integration, graphics generation, and dissemination via social media was able to produce real-time forecasts of storm track and intensity with product latencies commensurate with existing operational forecasting systems.

Development of an Eco-Design Tool for a Circular Approach to Building Renovation Projects

Considering the construction sector’s impact on the environment, it is necessary amongst other measures to change the way in which new construction or renovation projects of buildings are designed and how solutions are proposed and integrated. Nowadays, an effort is being made by designers to implement more sustainable and circular design in buildings, but because of the lack of tools that can provide designers with knowledge about the impacts of the solutions to be chosen, the sustainability factor does not enter in the decision-making process as a key factor. In this sense, the development of an eco-design tool and procedure for the decision-making process will allow designers to integrate into the design phase a circular design methodology and, in a practical way, will also promote sustainability and circularity concepts as a decision factor in the construction of buildings. The present work introduces an eco-design tool that was developed to integrate circularity and sustainability information into building-renovation projects. This tool enables the evaluation and comparison of solutions based on information provided by Environmental Product Declarations (EPD) or other LCA-based calculations as well as life cycle costing information, through the generation of radar graphics that simplify the overall analysis at the decision moment. The tool was tested in a simple case study of a building renovation process and allowed designers to understand the environmental and economic impacts that each competing solution carries, either related to the materials removed from the building or to the materials coming into the buildings being renovated. In this test application, the eco-design tool proved to be able to gather quantitative information regarding environmental and economic impacts, facilitating designers to access knowledge on the different solutions impacts and help them to make a design choice based on sustainability and circularity considerations.

Application of Traditional Chinese Elements in Visual Communication Design Based on Somatosensory Interaction Parameterisation

In recent years, the interdisciplinary exploration of combining traditional visual communication design with somatosensory interaction technology has become a new form of artistic expression. In order to explore the feasibility of somatosensory interaction technology in visual communication design, this study proposes a 2D dynamic graphic generation method based on somatosensory interaction parameterisation and uses traditional Chinese elements as an example for specific applications in visual communication design. Firstly, the motion parameters recognised using the Kinect somatosensory interaction device are bound to the function variables used to generate the images in the development environment, thus enabling human somatosensory interaction with different characters in the scene. Secondly, a linear discriminant analysis based on kernel functions is used to reduce the dimensionality of the vector space, thus solving the problem of real-time and accurate capture of human movements. Then, using the skeletal parameter binding technique, the association between the motion parameters of the somatosensory interaction and the two-dimensional dynamic graphics is achieved. The experimental results show that the visual communication technique based on somatosensory interaction has a high recognition accuracy. Distinguished from traditional digital video, the proposed method can greatly enrich the visual representation of traditional Chinese elements.

An Improved Visual Attention Model for Automated Vehicle License Plate Number Recognition Using Computer Vision

The role of an automatic licensed plate detection system (ALPDS) cannot be over-emphasized in the world today. The need for an automated system for vehicle license plate number recognition is important for security challenges. Therefore, this paper provides a smart system for vehicle license number recognition using Computer Vision. The system was trained using images of vehicles license numbers as training data. The training images were first annotated using the Visual Graphic Generator (VGG) annotation tool, after the annotation process, the trained images were pre-processed using the OpenCV library for conversion and masking of images. TesseractOCR was then used in extracting just texts from the images. The pre-processed and segmented images were then used in training the Mask R-CNN from a pre-trained weight. The result of the proposed system shows how the Mask R-CNN model was trained in ten training steps. The mask R-CNN model obtained accuracy and a loss value for each training step. The mask R-CNN model was evaluated using both training and test data. For the training and testing data, the Mask R-CNN was evaluated in terms of accuracy and loss. The evaluation was done using graphs. The results from the graph show that the Mask R-CNN had a better accuracy result in both training and testing data. The accuracy for training data was that of 95.25% and the accuracy for the testing data was 97.69%. For real-time vehicle license plate number recognition, we deployed our proposed model to the web. Here, we built a web application that allows real-time surveillance video. Our model was tested on different vehicles in the car park. The result of the mask R-CNN on the test shows how the Mask R-CNN model was used in not just capturing and extracting the vehicle’s license plate number but predicting the characters that appeared on the vehicle’s license plate number. We also compared our proposed system with another existing system. The comparison was done in terms of accuracy, loss, and precision. The result of our proposed model gave us an accuracy of 97.69%, which is higher than the existing system (85%). This study can further be improved by using the Internet of Things in performing live video streaming and also providing a database system that will be storing the predicted vehicle numbers for cars that are detected.

Three-Dimensional Visualization Analysis of Distributed Virtual Reality Taking into Account Grid Scientific Computing Model

With the in-depth development of the application of virtual reality technology, people have higher and higher requirements for the complexity and realism of virtual scene, which far exceeds the real-time processing ability of computer graphics hardware. Back to this, there is an urgent need to solve the contradiction between the complexity of the scene and the real-time interaction. In this paper, the real-time visualization of real-time distributed virtual reality is studied in many aspects. Starting with the analysis of the characteristics of real-time visualization technology of distributed virtual reality, this paper studies the system structure of real-time distributed virtual reality, puts forward the idea of realizing real-time distributed virtual reality visualization, introduces grid scientific computing model, and constructs a three-dimensional vertical visualization platform of distributed virtual reality. The visual analysis of virtual reality is carried out for the corresponding slope and corresponding geological conditions; the comprehensive analysis of spatial distribution is carried out by using three-dimensional visualization, the relevant contents of real-time display, and the generation and real-time display of realistic graphics. In order to increase the realism of 3D image, visibility judgment, and blanking technology, the level of detail model and texture mapping is used. The simulation results show that the grid scientific computing model is effective and can support the three-dimensional visual analysis of distributed virtual reality.