Graphical Display Research Articles

Multivariate Singular Spectrum Analysis by Robust Diagonalwise Low-Rank Approximation

Multivariate Singular Spectrum Analysis (MSSA) is a powerful and widely used nonparametric method for multivariate time series, which allows the analysis of complex temporal data from diverse fields such as finance, healthcare, ecology, and engineering. However, MSSA lacks robustness against outliers because it relies on the singular value decomposition, which is very sensitive to the presence of anomalous values. MSSA can then give biased results and lead to erroneous conclusions. In this article a new MSSA method is proposed, named RObust Diagonalwise Estimation of SSA (RODESSA), which is robust against the presence of cellwise and casewise outliers. In particular, the decomposition step of MSSA is replaced by a new robust low-rank approximation of the trajectory matrix that takes its special structure into account. A fast algorithm is constructed, and it is proved that each iteration step decreases the objective function. In order to visualize different types of outliers, a new graphical display is introduced, called an enhanced time series plot. An extensive Monte Carlo simulation study is performed to compare RODESSA with competing approaches in the literature. A real data example about temperature analysis in passenger railway vehicles demonstrates the practical utility of the proposed approach.

A new perspective on microRNA-guided gene regulation specificity, and its potential generalization to transcription factors and RNA-binding proteins.

Our conception of gene regulation specificity has undergone profound changes over the last 20years. Previously, regulators were considered to control few genes, recognized with exquisite specificity by a 'lock and key' mechanism. However, recentlygenome-wide exploration of regulator binding site occupancy (whether on DNA or RNA targets) revealed extensive lists of molecular targets for every studied regulator. Such poor biochemical specificity suggested that each regulator controls many genes, collectively contributing to biological phenotypes. Here, I propose a third model, whereby regulators' biological specificity is only partially due to 'lock and key' biochemistry. Rather, regulators affect many genes at the microscopic scale, but biological consequences for most interactions are attenuated at the mesoscopic scale: only a few regulatory events propagate from microscopic to macroscopic scale;others are made inconsequential by homeostatic mechanisms. This model is well supported by the microRNA literature, and data suggest that it extends to other regulators. It reconciles contradicting observations from biochemistry and comparative genomics on one hand and in vivo genetics on the other hand, but this conceptual unification is obscured by common misconceptions and counter-intuitive modes of graphical display. Profound understanding of gene regulation requires conceptual clarification, and better suited statistical analyses and graphical representation.

Seeing is believing: An Augmented Reality application for Palaeolithic rock art

By developing new recording methodologies, current rock art studies generate a large amount of graphic information about sites (tracings, photographs, three-dimensional reproductions) providing visibility of this fragile and little-known heritage, whose accessibility is often difficult or impossible for the general public. In addition, many rock art depictions are challenging to observe, due to the very nature of the artistic entities (fine engravings or faded paintings in karst environments or open-air sites with poor or changing light conditions), or to conservation problems derived from natural factors such as erosion and geological and biological processes, as well as from anthropic factors. These conditions make rock art depictions nearly indistinguishable in many places and on many objects today, except for experts. This difficulty of accessing and visualising rock art heritage, located in fragile environments and often challenging places such as caves or difficult-to-reach open-air sites, makes the information and knowledge generated by investigation of this heritage asset difficult to transfer to society in general, which is frequently unaware of the priceless value of this heritage. The present study proposes generating several mechanisms to transfer the results of research, restitution and documentation of rock art to society in general. An AR (Augmented Reality) application has been developed using LiDAR (Light Detection and Ranging) technology to address current challenges in implementing AR technologies in low-light environments. So far, this app has been developed in a Proof-of-Concept project at Spanish archaeological sites such as Hornos de la Peña (Cantabria), Domingo García (Segovia) and La Salud (Salamanca). This application will be particularly interesting for sites currently visited with or without a guide, allowing user interactivity and real-time reconstruction, for example, of the visibility of graphic motifs.

Optimizing mining projects: how business intelligence enhances data-driven decisions

The project management sector grapples with the challenge of handling a vast amount of information. Data compilation is essential to support effective decision-making processes by project managers. This paper emphasizes the significance of both project planning and execution monitoring. It concurrently explores the applicability of Business Intelligence (BI) software and its contributions to enhancing project management. The methodology employed a literature review combined with the authors' expertise in engineering projects. The findings reveal that BI offers substantial benefits. These include reducing the time required to transform large datasets into clear and concise graphical information that can be readily presented and dynamically adjusted to meet specific user needs. A study conducted in a mining company demonstrated a significant reduction in project management activities. By utilizing Power BI software, they achieved a 50% reduction in total time dedicated to project management activities. Additionally, there was a remarkable 83% reduction in the time spent on report issuance and updates. This outcome enables that project team members are aligned with consolidated information, facilitating real-time decision-making and fostering greater integration and productivity.

Use of wireless technologies in IoT projects

When it comes to creating projects based on the use of the Internet of Things (IoT), wireless sensor networks are often used. Edge computing in IoT technology reduces system response delays to sensor output signals and increases the network throughput. At the same time, a short-range sensor network can work locally without access to the Internet, while long-range networks, as a rule, require access to the Internet and use both edge and cloud computing. The paper shows the features of the application of both peripheral and cloud computing in the practical implementation of IoT projects with various methods of wireless data transmission. Specific examples show the possibility of data transmission over a short distance using ESP-NOW technology, nRF24L01 radio modules and creating a local Wi-Fi access point. The range of sensor data transmission between microcontrollers is practically determined for each proposed option. The calculation of the range of the LoRa radio line is carried out for the actual sensitivity values of the receiver. The Okamura-Hata radio wave propagation model is proposed to estimate the LoRa radio line’s total loss. The operational range of LoRa modules with different types of signal modulation is practically determined. The essence of edge computing combined with digital and analogue sensors is shown. Peculiarities of peripheral computing during the implementation of IoT projects for remote control of blood saturation of patients using wireless technologies are considered. An example of data transmission of the air quality control system through a gateway based on an ESP8266 microcontroller with a graphical display of measurements in the IoT cloud service ThingSpeak and Blynk was provided.

A peristaltic motion for pressure driven flow of Casson nanoliquid along with gyrotactic microorganisms in an entropic porous channel: A numerical study

Pump designs can be optimized for maximum energy efficiency, reduced waste, and enhanced overall performance by taking entropy factors into account. In this regard, the current investigation concentrates on examination of thermodynamic analysis for bio-convection peristaltic phenomenon of a non-Newtonian Casson nanofluid in an asymmetrical elastic channel by considering the generation of entropy. The pressure driven flow is managed by using lubrication approach and converting the system in to laboratory (wave) frame. The resulting findings of physical expressions together with the surface conditions are tackled by shooting numerical algorithm on conventional software Mathematica with the help of built-in tool (NDSolve). Graphical attitude of numerous physical quantities (entropy generation, Bejan number, and velocity profile, density of gyrotactic motile microorganisms and nanoparticles volume fraction) is also added and the results are equated with the existing literature. After detailed discussion on graphical display, it is concluded that with porosity of the medium helps to get the entropy generation reduced while, with the increase in bio-convection Peclet value, the micro-organisms’ density declines. The results of the study can be of great significance in the fields of nanotechnology, bio-microsystems and Bio-nano cooling phenomenon.

Research and Implementation of FPGA Image Compression Parallel Algorithm Based on CCSDS

High-pixel, high-resolution spectral images are an important source of key graphical information obtained from space remote sensing, however, with the dramatically expanding amount of graphical information, the limited transmission bandwidth and hardware resources are difficult to meet the demand for massive data, which makes real-time image lossless compression and transmission technology an important solution. For this reason, this paper is based on the CCSDS image lossless compression algorithm, using FPGA for the construction of image compression system, and proposes a method strategy based on parallel acceleration algorithm to realize the real time processing of large-capacity hyperspectral images. The simulation results show that hyperspectral river and mountain range images can be compressed with greatly improved compression efficiency while maintaining real time performance and accuracy.

FDIE: a graph-based framework for extracting design information from annotated building facade images

ABSTRACT Images of building facades, rich in design information, are important for architectural studies. In recent years, numerous studies have explored the automatic recognition and annotation of basic elements (e.g. windows) in these images. However, most application of the recognized elements remains at the pixel level, such as 3D reconstruction, and the design information hidden behind the elements cannot be processed using common data analysis methods because the annotations are still unstructured data. This prevents us from further discovering the composition pattern of building facades from the images. To enable the recognized elements to be analyzed, a framework for facade design information extraction (FDIE) from annotated building facade images based on graph theory is proposed in this paper. The design information is divided into three categories, i.e. graphic, relationship, and sum information, and extracted as structured data. An image restoration test demonstrates that more than 95% of the design information can be extracted using the FDIE. These structured data provide an important basis for intelligent analysis of composition pattern. Several examples and cases partly illustrate the application prospects of the extracted information. Other graph-based analysis methods are also expected to be applied to the extracted design information.

Improving the quality of newborn feeding documentation in an EHR using a mixed methods approach

IntroductionNewborn feeding is key to infant growth and survival. Accurate feeding documentation can inform care decisions and planning of care. A nutritional dashboard is available within the Electronic Health Record (EHR) which accumulates feeding data in a graphical display. PurposeTo improve the quality of newborn feeding documentation for post-natal ward babies and babies in the Neonatal Intensive Care Unit (NICU). Designand Methods: A multidisciplinary end user expert group (n = 38) was established. Qualitative thematic analyses from this group were used to design new feeding data entry and review elements. Quantitative pre-post design was used to assess feeding documentation for both post-natal ward baby charts (n = 134) and NICU baby charts (n = 188). Descriptive statistics and Pearson's chi-square were used to assess pre-post differences and statistical significance. The use of a nutritional dashboard was assessed using system audit logs and analyzed using Poisson regression testing. ResultsPost-natal ward babies had improvements in structured feeding documentation by 91.6% (from 17.9% to 34.3%) (p = 0.031). NICU data feeding documentation improved by 25% (from 72.3% to 90.4%) (p = 0.001). Use of the nutritional dashboard however reduced in the post period. ConclusionThis study has positively demonstrated improvements in the quality of newborn feeding documentation within the patient's EHR can be achieved through a collaborative multidisciplinary approach optimising EHR design. Practice implicationsThe benefit of a multidisciplinary approach to EHR design is paramount to promoting superior quality data entry compliant with individual workflows.

Design and Usability Testing of a Web-Based Intervention Module for Obesity: CoPT Nutri Trail

INTRODUCTION: Online interventions have emerged as innovative solutions to address health issues, notably obesity, while minimizing the necessity for in-person interactions during the recent COVID-19 pandemic. There is urgency in designing and developing an appropriate online intervention module within a web-based application. This study aims to describe the design process and usability of the online Canteen Operators, Parents, and Teachers (CoPT Nutri Trail) module for an upcoming school-based obesity intervention. MATERIALS AND METHODS: The design methodology consists of four phases: content development, design, web app development, and usability testing. The web application was designed to personalize usage for teachers, parents, and canteen operators to foster healthy environments for children. Thirteen experts, including teachers, nutritionists, and IT professionals, participated in the usability testing. RESULTS: All experts agreed that the design of the web application met the requirements of target users, requiring slight improvements in graphic design, language, and information elements. The web application tool was found acceptable, as the usability of alpha scores for all interface elements ranged from 68.2% to 86.6%, falling between good and very good scores. The content validation indices indicate good levels of validity (ranging from 0.83 to 1.00). CONCLUSION: The CoPT Nutri Trail web application is ready to be launched as a school-based intervention for obesity.

How Does Disgust Affect Mpox Prevention? Examining the Underlying Mechanisms of Perceived Severity and Perceived Susceptibility Moderated by Stigma

ABSTRACT The study aims to examine the influencing mechanism of incidental exposure to Disgusting Graphics Information (DGI) about Monkeypox (Mpox) on the intention of prevention behavior. This study first investigates the components of disgust and then examines the mechanism of disgust’s influence. The study uses a cross-sectional survey design among respondents who have been incidentally exposed to DGI about Mpox (N = 368). The results showed that disgust toward Mpox is the most effective component among other proposed ones (disgust toward graphics, information sources, and patients). Disgust not only positively influences prevention intention, but also indirectly influences prevention intention through perceived severity rather than perceived susceptibility. Moreover, moderated mediation was found, indicating that stigma toward patients prevents people from adopting preventive behaviors. Both theoretical and practical implications are discussed.

ГРАФИЧЕСКИЕ СРЕДСТВА ОПЕРАЦИОННЫХ СИСТЕМ

The methods of processing multimedia and graphical information in operating systems are studied using the example of MCI, API and GDI interfaces of Windows operating system. The interfaces of GDI and GDI+ graphics devices are examined in detail. The capabilities and features of the OpenGL graphics library, which is commonly used in the Windows operating system, are presented. The principles of operation of the GDI interface are given. Three types of drawing tools supported by the context of the GDI interface are examined in detail: pen, brush and font. The stages of coordination of logical and physical coordinate systems are considered. The OpenGL library graphics elements (bits arrays, polygons, segments, polylines, etc.), as well as basic geometric objects and a set of polyhedra: cube, cone, torus, octahedron, icosahedron, dodecahedron and tetrahedron are considered. As an example of OpenGL library usage, a three-dimensional graphics editor was studied. It works with three-dimensional objects of various types and allows reproduction of an object in two modes (lines and a solid surface), as well as performance of following operations with a graphic object: deformation, rotation, transpositionong along axes, loading and saving on hard drive.

Branding of retail enterprises

Branding is an integral part of the promotion and development of goods by retail trade enterprises (RTE). A comprehensive branding process is a key success factor, as it allows enterprises to identify themselves among compe­titors and attract a larger target audience. In this direction, it is important to substantiate the use of branding models aimed at increasing the competitiveness and RTE profitability. The aim of the article is to define the key concepts, the main components of branding, to substan­tiate the construction of a branding model and to characterize its elements. The following general scientific research methods were used such as analysis and synthesis, to present the main brand attributes; branding models and their characte­ristics; empirical, system and structural analysis and graphical display. The key concepts and basic branding principles have been defined, the main attributes (appearance of the product, its physical characteristics, brand name, logo, slogan, color scheme, fonts, character, music and sounds, related attributes) of the RTE brands have been analyzed. The process of choosing a positioning and its role in brand formation has been considered. The comparative characteristic of branding models has been presented, the main components, advantages and disadvantages of each model have been indicated. Based on the results, the author has developed his own model of RTE brand formation. The main advantages of using the developed model by the RTE and the main differences from other models have been indicated

Method for Constructing Neural Network Means for Recognizing Scenes of Political Extremism in Graphic Materials of Online Social Networks

Countering the spread of calls for political extremism through graphic content on online social networks is becoming an increasingly pressing problem that requires the development of new technological solutions, since traditional approaches to countering are based on the results of recognizing destructive content only in text messages. Since in modern conditions neural network tools for analyzing graphic information are considered the most effective, it is assumed that it is advisable to use such tools for analyzing images and video materials in online social networks, taking into account the need to adapt them to the expected conditions of use, which are determined by the wide variability in the size of graphic content, the presence of typical interference, limited computing resources of recognition tools. Using this thesis, a method has been proposed that makes it possible to implement the construction of neural network recognition tools adapted to the specified conditions. For recognition, the author's neural network model was used, which, due to the reasonable determination of the architectural parameters of the low-resource convolutional neural network of the MobileNetV2 type and the recurrent neural network of the LSTM type, which makes up its structure, ensures high accuracy of recognition of scenes of political extremism both in static images and in video materials under limited computing conditions resources. A mechanism was used to adapt the input field of the neural network model to the variability of the size of graphic resources, which provides for scaling within acceptable limits of the input graphic resource and, if necessary, filling the input field with zeros. Levelling out typical noise is ensured by using advanced solutions in the method for correcting brightness, contrast and eliminating blur of local areas in images of online social networks. Neural network tools developed on the basis of the proposed method for recognizing scenes of political extremism in graphic materials of online social networks demonstrate recognition accuracy at the level of the most well-known neural network models, while ensuring a reduction in resource intensity by more than 10 times. This allows the use of less powerful equipment, increases the speed of content analysis, and also opens up prospects for the development of easily scalable recognition tools, which ultimately ensures an increase in security and a reduction in the spread of extremist content on online social networks. It is advisable to correlate the paths for further research with the introduction of the Attention mechanism into the neural network model used in the method, which will make it possible to increase the efficiency of neural network analysis of video materials.

Algorithm for Automatic Layout of Graphic Language and Its Application in Graphic Design

When using traditional algorithms to describe graphic languages, the results obtained are not accurate due to the lack of strict standards. In this case, the size and position of the graphic display cannot be accurately determined. Aiming at these problems, we propose a new automatic typesetting algorithm for graphic languages. Use the constant method to calculate the display size of buffered images in graphic design. The ant colony algorithm is used to solve the optimal solution, so that the optimal display position of the graphics in the graphic design can be obtained. Graphics are powerful. For example, excellent graphics such as the presentation of forms, the expression and transmission of information, often make people feel relaxed and empathetic, shorten the distance between each other, and make communication smoother. As a result, graphic languages have become an important part of modern graphic design and are used more and more frequently. This paper attempts to analyze the representation of graphic language, aiming to demonstrate its important role in graphic design.

A guide to interpreting systematic reviews and meta-analyses in neurosurgery and surgery.

Systematic reviews (SRs) and meta-analyses (MAs) are methods of data analysis used to synthesize information presented in multiple publications on the same topic. A thorough understanding of the steps involved in conducting this type of research and approaches to data analysis is critical for appropriate understanding, interpretation, and application of the findings of these reviews. We reviewed reference texts in clinical neuroepidemiology, neurostatistics and research methods and other previously related articles on meta-analyses (MAs) in surgery. Based on existing theories and models and our cumulative years of expertise in conducting MAs, we have synthesized and presented a detailed pragmatic approach to interpreting MAs in Neurosurgery. Herein we have briefly defined SRs sand MAs and related terminologies, succinctly outlined the essential steps to conduct and critically appraise SRs and MAs. A practical approach to interpreting MAs for neurosurgeons is described in details. Based on summary outcome measures, we have used hypothetical examples to illustrate the Interpretation of the three commonest types of MAs in neurosurgery: MAs of Binary Outcome Measures (Pairwise MAs), MAs of proportions and MAs of Continuous Variables. Furthermore, we have elucidated on the concepts of heterogeneity, modeling, certainty, and bias essential for the robust and transparent interpretation of MAs. The basics for the Interpretation of Forest plots, the preferred graphical display of data in MAs are summarized. Additionally, a condensation of the assessment of the overall quality of methodology and reporting of MA and the applicability of evidence to patient care is presented. There is a paucity of pragmatic guides to appraise MAs for surgeons who are non-statisticians. This article serves as a detailed guide for the interpretation of systematic reviews and meta-analyses with examples of applications for clinical neurosurgeons.

Analysis of health warning signs on alcoholic beverage packaging using the eye-tracking method

Abstract Producers must mark packaging with various warning signs, including the harm of alcohol consumption. The most popular warnings inform about the required consumer age (e.g., “alcohol only for adults”), consequences of drunk driving (e.g., “don’t drink and drive”), and advisable abstaining from drinking during pregnancy. The study’s main objective was to analyse the perception of warning signs on alcoholic beverage packaging using the eye-tracking method, which allows the observation and measurement of the focus of study participants. The research positively verified the ability to use the eye-tracking method to assess the perception of warning signs. The obtained research results were used to investigate the perception of warning signs placed on glass beer bottles. The study showed that the presence of pictograms (i.e., graphic symbols) does not guarantee the focus of potential buyers’ attention. The obtained results clearly indicated that the efficiency of perception results from many elements, including the sign’s placement, size and colours, a connection between graphic and textual information, and the colour of the packaging material and label. The study’s results can be useful for non-profit organisations and other entities responsible for the social marketing of alcoholic beverages. Moreover, the study could be seen as a starting point for researchers, beverage packaging industry representatives, and policymakers to test, introduce and promote packaging innovation solutions. The research filled the gap by providing a better understanding of the effectiveness of warning signs on alcoholic beverage packaging and furnished clues as to how alcohol stakeholders and public institutions should react to enhance alcohol health literacy in society.

Analysis of packaging design its colour coding and labelling of contained sugar in dairy and cereal products

The purpose of developing the colour coding system is to create better awareness and help consumers monitor and understand the sugar content of foods. Our research focused on food products (dairy products and cereal products on the Slovenian market) that contain so-called hidden sugars, as these can cause many health risks. The aim of the study was to raise awareness of the sugar content in dairy products and cereals through a packaging design with a uniform labelling and coding system. During the process of this research, few answers were provided to the following questions: How can a labelling system be designed to be clear and impartial, what is the hierarchy and layout of food information on packaging, and how can the system be coherently integrated with existing packaging? The impact of the information design on the consumer in the food packaging industry, which helps in further execution, was analysed. Based on the research, variants of a multi-colour labelling system were created, differing in primary information graphics, colour, placement and formats. The packaging for an imaginary brand and the placement of the code system were designed. Finally, the packaging design was implemented in the 3D models for each food group. The result of this research is a collection of packaging models with a labelling system that informs consumers about sugar content, facilitates decision-making and helps them control their food intake. The colour-coded labels were applied to the packaging in a uniform and coherent manner, which can provide sufficient attention and information.

Visual word identification beyond common words: The role of font and letter case in brand names

While abstractionist theories of visual word recognition propose that perceptual elements like font and letter case are filtered out during lexical access, instance-based theories allow for the possibility that these surface details influence this process. To disentangle these accounts, we focused on brand names embedded in logotypes. The consistent visual presentation of brand names may render them much more susceptible to perceptual factors than common words. In the present study, we compared original and modified brand logos, varying in font or letter case. In Experiment 1, participants decided whether the stimuli corresponded to existing brand names or not, regardless of graphical information. In Experiment 2, participants had to categorize existing brand names semantically – whether they corresponded to a brand in the transportation sector or not. Both experiments showed longer response times for the modified brand names, regardless of font or letter-case changes. These findings challenge the notion that only abstract units drive visual word recognition. Instead, they favor those models that assume that, under some circumstances, the traces in lexical memory may contain surface perceptual information.

Wagner diagram for modeling O2 pathway—calculation and graphical display by the Helsinki O2 Pathway Tool

Objective. Maximal O2 uptake ( V˙O2max ) reflects the individual’s maximal rate of O2 transport and utilization through the integrated whole-body pathway composed of the lungs, heart, blood, circulation, and metabolically active tissues. As such, V˙O2max is strongly associated with physical capacity as well as overall health and thus acts as one predictor of physical performance and as a vital sign in determination of status and progress of numerous clinical conditions. Quantifying the contribution of single parts of the multistep O2 pathway to V˙O2max provides mechanistic insights into exercise (in)tolerance and into therapy-, training-, or disuse-induced adaptations at individual or group levels. We developed a desktop application (Helsinki O2 Pathway Tool—HO2PT) to model numerical and graphical display of the O2 pathway based on the ‘Wagner diagram’ originally formulated by Peter D. Wagner and his colleagues. Approach. The HO2PT was developed and programmed in Python to integrate the Fick principle and Fick’s law of diffusion into a computational system to import, calculate, graphically display, and export variables of the Wagner diagram. Main results. The HO2PT models O2 pathway both numerically and graphically according to the Wagner diagram and pertains to conditions under which the mitochondrial oxidative capacity of metabolically active tissues exceeds the capacity of the O2 transport system to deliver O2 to the mitochondria. The tool is based on the Python open source code and libraries and freely and publicly available online for Windows, macOS, and Linux operating systems. Significance. The HO2PT offers a novel functional and demonstrative platform for those interested in examining V˙O2max and its determinants by using the Wagner diagram. It will improve access to and usability of Wagner’s and his colleagues’ integrated physiological model and thereby benefit users across the wide spectrum of contexts such as scientific research, education, exercise testing, sports coaching, and clinical medicine.