Visualization Purposes Research Articles

Synergia danych fotogrametrycznych uzyskanych na podstawie zdjęć naziemnych oraz UAV

Methods of short-range digital photogrammetry and unmanned aerial vehicle imagining increasingly find more extensive usage in various types of measurements. In recent years, modern photogrammetric technologies have found wide application in recreating 3D models of any objects. The resulting 3D models can be a source of information that may be used for measurement, inventorying and cataloguing, as well as for visualisation purposes. New methods of acquiring spatial data have been developed, such as laser scanning, imaging using unmanned aerial vehicles or digital non-metric cameras. Synergy and the confluence of these data have expanded the existing measurement possibilities, finding application in 3D modelling, inventorying of monuments, or monument conservation. Photogrammetric methods are comparable to direct measurement methods in terms of their accuracy, as well as speed and cost. They have a number of advantages, including a shortened time required for taking a photo, which is greatly convenient when measuring moving objects. Other advantages of photogrammetric methods include the possibility of development and performing measurements in chamber conditions and the lack of restrictions pertaining to repeating the measurement when errors are found or a need arises to supplement them [Kurczyński and Preuss 2000]. One of the possibilities offered by photogrammetry is the ability to create 3D visualizations. The creation of a three-dimensional model facilitates presenting the inventoried object in a realistic, complete, and up-to-date manner. This paper presents an attempt to synergise data for modelling a three-dimensional architectural object based on photos obtained with the Nikon D7500 non-metric camera and with the DJI Mavic Air unmanned aerial vehicle.

Me! Me! Me! Me! A study and comparison of ego network representations

From social networks to brain connectivity, ego networks are a simple yet powerful approach to visualizing parts of a larger graph, i.e. those related to a selected focal node — the so-called “ego”. While surveys and comparisons of general graph visualization approaches exist in the literature, we note (i) the many conflicting results of comparisons of adjacency matrices and node-link diagrams, thus motivating further study, as well as (ii) the absence of such systematic comparisons for ego networks specifically. In this paper, we propose the development of empirical recommendations for ego network visualization strategies. First, we survey the literature across application domains and collect examples of network visualizations to identify the most common visual encodings, namely straight-line, radial, and layered node-link diagrams, as well as adjacency matrices. These representations are then applied to a representative, intermediate-sized network and subsequently compared in a large-scale, crowd-sourced user study in a mixed-methods analysis setup to investigate their impact on both user experience and performance. Within the limits of this study, and contrary to previous comparative investigations of adjacency matrices and node-link diagrams (outside of ego networks specifically), participants performed systematically worse when using adjacency matrices than those using node-link diagrammatic representations. Similar to previous comparisons of different node-link diagrams, we do not detect any notable differences in participant performance between the three node-link diagrams. Lastly, our quantitative and qualitative results indicate that participants found adjacency matrices harder to learn, use, and understand than node-link diagrams. We conclude that in terms of both participant experience and performance, a layered node-link diagrammatic representation appears to be the most preferable for ego network visualization purposes.

Hydration and solution properties of fluorescently labeled wheat arabinoxylans following enzymatic hydrolysis

Wheat arabinoxylan (AX) exhibits characteristics of high molecular weight (Mw), strong water absorption and water holding capacity, which significantly influence the hydration and solubility properties of wheat flour. However, challenges existed in visualizing the distribution of AX and quantifying water content accurately. This study investigated the effect of fluorescent labeling on the physicochemical properties of AX with different Mw. AX was initially degraded using xylanase, which resulted in the formation of AX fragments with different Mw. As the xylanase concentration increased, the Mw, degree of aggregation and apparent viscosity of AX decreased, whereas the water binding capacity, solubility and hydrophilicity increased. Enzymatically hydrolyzed AX was covalently linked to fluorescein isothiocyanate (FITC) through reductive amination modification, yielding AX-tyramine-FITC. Compared to AX, AXTF exhibited a slightly higher Mw, with a slight increase in water binding capacity and hydrophilicity, a significant increase in solubility. The degree of aggregation and apparent AX viscosity also increased slightly. The fluorescent labeling had a minor effect on AX properties, and the trend in AXTF properties with respect to Mw was consistent with that of AX. This study established a basis for the effect of AX with different Mw on the water migration pattern in the flour system, and provided a theoretical basis for the application of AX fluorescent labeling for visualization purposes.

Understanding the Impact of Gas Diffusion Layer Degradation on Water Inventory in Low Temperature PEM Fuel Cells for Heavy Duty Vehicles Application: Operando X-Ray and Neutron Imaging Study

Samples from two materials representing the condition at begin and end of life, were selected from testing of commercial, state-of-the-art PEM fuel cell stacks. Using small-area single cell setups specifically developed for visualization purposes, operando synchrotron and neutron imaging experiments to visualize water dynamics and distribution within these cells were performed. In this study, the effects of aging on water inventory in the gas diffusion layers throughout the lifespan of the cells are investigated. The findings provide insights into how aging influences water management, which is crucial for optimizing the performance and longevity of PEM fuel cells for heavy-duty applications.

Understanding the Impact of Gas Diffusion Layer Degradation on Water Inventory in Low Temperature PEM Fuel Cells for Heavy Duty Vehicles Application: Operando X-Ray and Neutron Imaging Study

Samples from two materials representing the condition at begin and end of life, were selected from testing of commercial, state-of-the-art PEM fuel cell stacks. Using small-area single cell setups specifically developed for visualization purposes, operando synchrotron and neutron imaging experiments to visualize water dynamics and distribution within these cells were performed. In this study, the effects of aging on water inventory in the gas diffusion layers throughout the lifespan of the cells are investigated. The findings provide insights into how aging influences water management, which is crucial for optimizing the performance and longevity of PEM fuel cells for heavy-duty applications.

Getting away from the cutoff in regression discontinuity designs

Regression discontinuity (RD) designs are highly popular in economic research because of their strong internal validity and straightforward intuition. While RD estimates are local in nature, several recent articles propose methods that generalize RD estimates to units outside a small neighborhood of the cutoff. In this article, I introduce the getaway package, which implements the method proposed by Angrist and Rokkanen (2015, Journal of the American Statistical Association 110: 1331-1344) to extrapolate treatment-effect estimates “away from the cutoff”, relying on a classical unconfoundedness condition. Additionally, the package features a data-driven algorithm designed to identify a set of covariates that fulfills the unconfoundedness assumption. It also incorporates a toolkit intended for testing and visualization purposes.

Trends in virtual influencers (VIs): A bibliometric analysis and SPAR-4-SLR protocol

This study aims to comprehensively understand qualitative and quantitative information about the current trends in VIs. It examines 106 articles published in Scopus-indexed journals between 2020 and 2024. The analysis was done with the help of Biblioshiny, an R-developed online application from the Bibliometrix package, and VOSviewer software for analytical and visualization purposes. This study was conducted using the SPAR-4-SLR protocol. The findings showed that recent years have been more productive, and many authors have demonstrated their interest in studying the VIs. Recent trends are social media, virtual reality, marketing, social networking, etc. The study employs a systematic review and bibliometric analysis to extract valuable insights from the extensive body of literature. These insights suggested several areas for future research, providing a roadmap for future researchers to proceed with their research in this area. The comprehensive scientific cartography of the area has yet to be presented; therefore, this study aims to synthesize the current knowledge frameworks within the field and determine the dominant research patterns in the specific area of investigation.

Use of the Alice Visual Programming Environment in Programming Education : A Descriptive Case Study

The process of learning a programming language is seen as complicated, especially for those who first start to learn programming language. For this reason, visual programming tools have begun to be used in educational environments. Visual programming tools purpose to concretize abstract programming language concepts. Alice program is one of the visual programming tools. The aim of this study is to determine the effects of the Alice program on programming learning in the education environment. The study group was 18 freshman students enrolled in the Object Based Programming I course at the vocational school computer technology department. The study lasted 8 weeks, with 4 hours each week. The teaching was realized on Gagne’s nine events of instruction model. At the end of the teaching process, two focus group interviews were conducted with the students to determine the obstructing and facilitating factors in using the Alice program. This study was utilized a descriptive case study. The data were analyzed by using the content analysis. When the results were examined; It was seen that the Alice program makes learning the basic code concepts easy and understanding programming logic, and increases the desire to learn programming. However, it was stated that the practicality of writing code could not be improved because code could not be written in the Alice program. It is thought that employing the Alice program is beneficial for enhancing comprehension of programming logic.

Exploring E-Government Development Index as an Indicator of Sustainability in the Gulf Region

The primary aim of this article is to assess the E-Government Development Index (EGDI) of Arab Gulf countries, and it elucidates the key obstacles impeding the progress of the Gulf countries in the e-government sector. The EGDI data for the Gulf countries have been obtained from the United Nations, and an online business intelligence tool has been utilized for visualization purposes to facilitate comprehension. The levels of indicators within EGDI have been examined upon effectively retrieving data and presenting it appropriately. The article discusses the key areas of improvement that require governments’ attention in the Gulf countries to enhance their EGDI score. This can be leveraged to advance to global standards, offering their citizens optimal governance. Countries in the Gulf region must recognize that the e-government effort encompasses more than simply the transformation of governance and the provision of high-quality services. Instead, it entails aligning with global trends and effectively competing with other nations regarding developmental advancements. Countries must adhere to prevailing e-government trends to ensure alignment with global standards and expedite national advancement.

The school management team’s role of defining the school vision and mission at a South African rural school

Schools in the rural context of Limpopo Province, South Africa have a plethora of challenges, which have a negative impact on learner achievement. This paper argues that for schools to triumph over the obstacles, effective school leaders are necessary Such leaders must define and communicate a clear vision and mission and work with stakeholders to achieve them. With these assumptions, this paper explores how members of the school management team (SMT) of a rural school in the Limpopo Province define and communicate their school’s vision and mission. Through the qualitative research method underpinned by the interpretive paradigm, a case research design was adopted and a single high school sampled to participate. Data were generated from semistructured interviews with seven SMT members, a focus-group discussion with six teachers, and an observation of the research site. The findings revealed that most participants could not articulate the school’s vision and mission. In addition, stakeholders were not involved in the processes of defining the vision and mission and communication methods in this regard were also ineffective. Lastly, the SMT viewed the vision and mission as fixed and did not review them. Based on these findings, I conclude that SMT members must understand that the vision and mission could serve more than a visual purpose when designed as guiding principles to direct smaller objectives within the organisation.

STRATEGIC DECISION SUPPORT: DEVELOPING A DASHBOARD FOR MANAGERIAL INSIGHTS IN HIGH-LEVEL TVET STUDENTS' ENROLMENT AT UNIVERSITI MALAYSIA PAHANG AL-SULTAN ABDULLAH

The purpose of this study was to create a dashboard with information visualisation to assist Universiti Malaysia Pahang Al-Sultan Abdullah (UMPSA) in managerial decision-making and to critically and hierarchically present data regarding the enrolment of Malaysian Diploma Vocational (MDV) students into high-level Technical Vocational Education and Training (TVET) programs at UMPSA. The Cross Industry Standard Process for Data Mining (CRISP-DM) model was applied in this research followed by dashboard development using Microsoft Power BI. The CRISP-DM model consists of six continuous and connected phases, namely business understanding, data understanding, data preparation, data modelling, data visualisation, and data synchronise and update. The data was obtained from the Undergraduate Records Management Unit, Centre for Academic Management, UMPSA. The database was used in the development of the dashboard to store information in the form of reports and for data visualisation purposes. The findings hope to assist the management of UMPSA in making better decisions and planning the enrolment process of prospective students. The dashboard outlines several initiatives and best practices that should be implemented by the Malaysian Government, the Ministry of Higher Education, and UMPSA through the UMPSA 2021–2025 Strategic Plan to empower the high-level TVET agenda.

Random Data Distribution for Efficient Parallel Point Cloud Processing

Abstract. Current point cloud data management systems and formats are heavily specialized and targeted solely towards visualization purposes and fail to address the diverse needs of progressive point cloud workflows like for example semantic segmentation using machine learning. We therefore propose a distributed data infrastructure for dynamic point cloud data management that can support interactive real-time visualization at scale while simultaneously serving as a platform for analytical tasks. By introducing random data distribution, we show that simple query fragmentation and efficient and effective parallelism at scale are possible. At the same time, arbitrary queries in space and time can be efficiently run over the infrastructure including query semantics which returns only a random sample of the query results or preferred points based on an importance dimension calculated, for example, from a local point density information as commonly done in point cloud visualization. To cope with the unknown amount of user-specific attributes and to support even multiple ways of deciding the importance of a given point (ground point removal, coverage of space, random subset) the system is designed to support all of them transparently as multidimensional range queries backed by spatial indices.

Multifactorial risk prediction analysis of liver metastasis in colorectal cancer: incorporating programmed cell death ligand 1 combined positive score and other factors

BackgroundThe occurrence of liver metastasis significantly impacts the prognosis of colorectal cancer. Existing research indicates that primary tumor location, vascular invasion, lymph node metastasis, and abnormal preoperative tumor markers are risk factors for colorectal cancer liver metastasis. Positive expression of PD-L1(Programmed Cell Death 1 Ligand 1) may serve as a favorable prognostic marker for nasopharyngeal and gastric cancers, where CPS（Combined Positive Score） quantifies the level of PD-L1 expression. Based on previous studies, exploring CPS as a potential risk factor for colorectal cancer liver metastasis and integrating other independent risk factors to establish a novel predictive model for colorectal cancer liver metastasis. MethodsA retrospective analysis was conducted on 437 colorectal cancer patients pathologically diagnosed at Xiangya Second Hospital, Central South University, from January 1, 2019, to December 31, 2021. Data were collected, including CPS, age, gender, primary tumor location, Ki-67 expression, pathological differentiation, neural invasion, vascular invasion, lymph node metastasis, and preoperative tumor markers.The optimal cut-off point for the continuous variable CPS was determined using the Youden index, and all CPS were dichotomized into high and low-risk groups based on this threshold (scores below the threshold were considered high-risk, and those above it were considered low-risk). Univariate logistic regression analysis was employed to identify risk factors for colorectal cancer liver metastasis, followed by the application of multivariate logistic regression analysis to integrate the selected risk factors.The predictive model established was validated through the construction of ROC (Receiver Operating Characteristic) curves, calibration curves, and DCA (Decision Curve Analysis). A nomogram was constructed for visualization purposes. ResultsThe determined cut-off point for PD-L1 CPS was 4.5, with scores below this threshold indicating high risk for colorectal cancer liver metastasis. Additionally, primary tumor origin other than the rectum, presence of pericolonic lymph node metastasis, and abnormal levels of tumor markers CEA and CA199 were identified as independent risk factors for colorectal cancer liver metastasis. The constructed clinical prediction model demonstrated good predictive ability and accuracy, with an area under the ROC curve of 0.871 (95% CI 0.838-0.904). ConclusionThe exploration and validation of CPS as a novel predictor for colorectal cancer liver metastasis were conducted. Based on this, a new clinical prediction model for colorectal cancer liver metastasis was developed by integrating other independent risk factors. The DCA, clinical impact curve, and nomogram graph constructed based on this model have significant clinical implications and provide guidance for clinical practice.

P28 Data-independent acquisition mass spectrometry improves spatially resolved analysis of the human skin proteome

Abstract Introduction and aims Proteomic analysis of the extracellular matrix (ECM) presents challenges because of the highly crosslinked and low-solubility nature of ECM proteins. Traditional homogenization and protein digestion approaches result in the loss of crucial information regarding protein localization and spatial relationships. To address this, spatially resolved proteomics emerges as a powerful tool for exploring heterogeneity within bulk tissues. This study aims to determine the minimum tissue volume required for comprehensive proteome coverage using data-independent acquisition mass spectrometry (DIA-MS) on skin tissue. The study focused on optimizing spatially resolved proteomic techniques to enhance depth-of-analysis while preserving spatial specificity. Methods Human abdominal skin biopsies were obtained from a single individual and subsequently cryosectioned. Histological assessment was performed through haematoxylin and eosin staining for visualization purposes. Laser-capture microdissection coupled with mass spectrometry facilitated the precise isolation of target regions. Comparative analyses were performed between data-dependent acquisition mass spectrometry (DDA-MS) and DIA-MS, with a particular emphasis on ECM proteins within the dermis. Results Our findings revealed an improvement in proteome coverage with DIA-MS compared with DDA-MS, in addition to clear scaling relationships between the depth-of-analysis and sample concentration. The Results demonstrated the superiority of DIA-MS in achieving robust and comprehensive proteomic profiles, even with minimal tissue volumes. Preliminary findings suggest the capability of DIA-MS in elucidating the complexities of the skin proteome with spatial resolution. Conclusions In conclusion, our study highlights the efficacy of DIA-MS in spatially resolved proteomics on skin tissue. The optimized approach presented here offers a reliable and efficient method for obtaining in-depth proteome information with minimal tissue requirements. These Results form the foundation for ongoing experiments, utilizing DIA-MS to advance spatially resolved proteomic analyses of human skin.

Spraying for the beauty: Pesticide use for visual appearance in apple production

AbstractPesticides are used to reduce yield losses and to enhance the visual quality of products. However, pesticide use raises concerns due to negative health and environmental effects, hence ambitious policy goals for their reduction have been established. Reducing pesticides which mainly focus on visual quality of products could be an efficient strategy to contribute to these goals, without reducing food production. However, the role of “cosmetic” pesticide use is so far not well documented and understood. Here, we quantify cosmetic pesticide use and the influence of supply chain characteristics on their use. We focus on table apple production, where the visual quality of products is a key aspect. Using a sample of 196 apple growers in Switzerland, we find that 23.5%–59.2% of growers use cosmetic pesticides for the apples’ visual appearance. Farms mainly marketing via intermediaries are 23.9‐29.6% more likely to spray cosmetic pesticides for visual purposes compared to farms mainly direct marketing. Our findings highlight the role of supply chains in farmer decision‐making, recommending a decrease in the focus on visual product quality, especially in retail environments, thus minimizing unnecessary and irreversible risks of pesticide exposure by farmers without compromising food security.

Strategic Employee Performance Analysis in the USA: Deploying Machine Learning Algorithms Intelligently

Strategic employee performance assessment assists organizations in steering productivity, affirming employee satisfaction, and accomplishing strategic organizational goals. Machine learning algorithms provide several benefits over mainstream techniques in assessing employee performance. This research paper aimed to explore the deployment of machine learning algorithms in assessing employee performance. The prime objective of employee performance analysis is to assess an employee's achievement during a specific time frame. The dataset for this research revolved around the leadership team of a global retailer's specific store level in the USA, extending over 18 months. The dataset for this study was subjected to Python programming software for intensive and comprehensive data analysis as well as for visualization purposes. From the experiment design, it was evident that XG-Boost seems to be the best-performing model overall. In particular, it had the greatest AUC for both holdout and training data (0.86 and 0.88, respectively), and it has a relatively low runtime (16 minutes) and maximum memory utilization (12%). By contrast, Random Forest displayed an average AUC for training data (0.79) but a lesser AUC for holdout data (0.51), which indicates that it may be overfitting the training data; besides, it had a longer runtime than XG-Boost.

Attitudes towards blood donation among students in different health sciences disciplines in Saudi Arabia.

The objective of this research undertaking was to examine the attitudes of King Khalid University undergraduates enrolled in various health disciplines regarding blood donation. Undergraduates of health disciplines participated in this study. The survey questions were administered through Google Forms, and the data was imported into GraphPad Prism for visualization and analytical purposes. A greater proportion of participants were male, with males accounting for 63.2% of the sample, while females accounted for 36.8%. The findings given in this research illustrate a wide range of attitudes regarding the practice of blood donation. A notable percentage of the participants had a favorable predisposition towards engaging in voluntary blood donation. Nevertheless, a significant degree of variability was observed among individuals with regards to their attitudes toward several variables, including fear, motivation, and their preferred location for making donations. The participants expressed negative attitudes against the practice of importing blood and the recognition of personal accountability in engaging in blood donation for the sake of society. One potential solution to address the unfavorable attitudes among students towards blood donation is the implementation of educational programs focused on blood donation and its associated benefits. Additionally, incorporating motivational strategies could further enhance the effectiveness of these initiatives. As a result, this could have a positive impact on students and those in their immediate vicinity.

Biochemical Aspects of Cell Staining

Aims: to revisited the biochemical aspects of basic, negative and positive staining by dyeing organic materials in the laboratory for the purpose of visualization, identification and even differentiation of object being analyzed. Discussion: The best analysis for cells is by staining. Staining allows detailed visualization of the part of the cell being examined. In principle, dyes have a chromophore root that will bind to the protein content in cells. This is the basis for discussing negative staining, basic staining and positive staining. Unfortunately, its widespread use also increases the health risks of users. Conclusion: Biochemical aspect of staining rely on the electric charged of the dye that bind the electronegative properties of proteins that build cell. Basic staining, negative staining and positive staining are widely used staining for research, clinical-laboratory service and also education. Unfortunately, some of these stains are hazardous with the potency of multiple health risk and continuous improvement in handling will prevent such risk to happen.

Immersive visualisation for a large metrological data set

A purpose of scientific visualisation is to facilitate the extraction of information within underlying data. Visualisation of a large data set requires an appropriate visualisation method where, instead of focusing on expected features, all acquired data are treated on an equal footing. Here, we identify critical differences between raw and processed data acquired from displacement measurements at the nanoscale. We illustrate the strength of immersive data visualisation in rapidly and intuitively identifying non-obvious data trends, supported by correlation with the associated measurement uncertainties. These insights can be directly leveraged for optimisation of instrumentation and measurement protocols, application of appropriate measurement corrections, and iterative experimental design changes.

VISUALIZATION OF MICROSERVICES-BASED INFORMATION SYSTEM ARCHITECTURES USING OPENTELEMETRY DATA

Within the framework of the presented article, the relevance and necessity of solving the problem of visualizing the architecture of information systems based on microservices is substantiated. This task is especially significant both for the process of developing new systems and for optimizing the operation of existing ones. To provide comprehensive and balanced up-to-date information about the structure and interaction of microservices, an approach is required that is focused on automatically collecting and processing information about the relationships between microservices and their internal structure for the purpose of subsequent visualization of architectural diagrams. The authors found that specialized software trace logs provide sufficient information for visualizing the architecture. In their article, the authors took a closer look at tracing issues in the context of OpenTelemetry, an open-source project designed specifically for collecting telemetry data from software and then analyzing it. The authors proposed the C4 model as a means for visualizing architecture. The C4 model is a relatively new approach to modeling software systems, which involves the development and representation of context, containers, components, code and their relationships. The main task that the authors set for themselves is to automate the process of creating C4 model diagrams based on data received from OpenTelemetry. This approach will significantly simplify the process of understanding the structure and dynamics of interaction between microservices within the system. The key result of the research is the development of algorithms for collecting and converting trace data to create C4 diagrams, as well as the creation of appropriate software that implements these algorithms.