Visual Method Research Articles

Improvement of the Endotracheal Intubation Skill of Nurse Anesthesia Students Using Visual Self-evaluation in Iran: A Randomized Controlled Study

Background: One of the feedback methods is visual self-evaluation, which is a type of immediate feedback provided after a task. It is at the level of self-regulation. Mastery in learning requires accurate evaluation of clinical skills, and visual self-evaluation can help learners to master the stages of skill implementation. Objectives: The present study investigated the effect of visual self-evaluation on the endotracheal intubation skill of nurse anesthesia students of Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran. Methods: This randomized controlled study was conducted in April and May of 2023. 63 second- and third-year nurse anesthesia students were allocated to the intervention (visual self-evaluation) and control (conventional methods) groups according to the academic year, using stratified random sampling. The skill of endotracheal intubation was taught using visual self-evaluation method in the intervention group while the same skill was taught in the control group based on the conventional methods, i.e. lecture, practical training, and practice on the mannequin under the supervision of the instructor. Visual self-evaluation and conventional teaching methods were compared in terms of learning outcomes. The endotracheal intubation skill evaluation checklist developed by hart was used to evaluate endotracheal intubation skill. The students of the intervention group also completed a questionnaire to measure their satisfaction with the visual self-evaluation method. Results: The students with a mean age of 21.53 ± 3.65 years, participated in this study. About 73% of the participants were women. The mean scores of students in the post-test compared to the pre-test in both intervention (23.56 ± 2.68 at baseline and increased to 28.87 ± 4.80) and control (24.03 ± 2.22 at baseline and increased to 25.19 ± 2.46) groups increased significantly (P < 0.001), but the mean post-test scores of the intervention group were significantly higher than those of the control group (P < 0.001). Also, the mean satisfaction score in the intervention group was 40.79 ± 1.22 out of a maximum of 50, which indicates a very high satisfaction with the adoption of visual self-evaluation method in clinical education. Conclusions: The use of visual self-evaluation not only had a significant effect on improving the clinical skill of nurse anesthesia students but also was effective in helping them learn self-regulation and achieve mastery and independence. This method is recommended as a low-cost and effective method to be used along with other educational methods.

A New Method for Lateral Visualization of the Primary Cilia on the Surfaces of Cells Cultured on White Glass Rods

A New Method for Lateral Visualization of the Primary Cilia on the Surfaces of Cells Cultured on White Glass Rods

Methods for Visualization and Analysis of the Microstructure of a Fibrous Composite Material

Methods for Visualization and Analysis of the Microstructure of a Fibrous Composite Material

A Tomato Sorting Automation Prototype Based on Color

Abstract—The process of sorting tomatoes can be done using visual methods by paying attention to color. The purpose of this research is to improve the process of sorting tomatoes based on color in distinguishing ripe tomatoes and immature tomatoes. Streamline the time of sorting tomato fruit in order to avoid losses due to spoilage. This research method is with a sample of tomato fruit taken RGB value through TCS 3200 color sensor according to the level of maturity. After the RGB value is obtained, it will be processed into the Arduino Uno to obtain maturity information through the rules that have been made and sorted using a servo motor. The results of this study indicate that a good condition for detecting tomato fruit is with a closer distance to the fruit with a dark background. This is because there is no excess light reflection so that the TCS sensor can take RGB values well and reduce the occurrence of misreading of ripeness information in the sorting process. Keywords— Tomato, Sensor TCS 3200, Arduino uno, Motor Servo.

Feminist participatory action research to co-develop localised health promotion in Indonesia

ABSTRACT Women’s expertise and knowledge can help prevent stunting in impoverished areas with limited resources. Through focus group discussions and photovoice methods, feminist participatory action research (FPAR) explored the perspectives of mothers and community health workers (posyandu) in the development of maternal and community health promotion. Six steps of FPAR were applied: the collection of media on stunting health promotion in public health centres; the building of trust and partnerships with posyandu cadres and mothers; the conducting of focus group discussions with posyandu cadres and mothers of young children to develop local language media through participatory visual methods; the co-designing of media content using online design tools; the dissemination of posters and leaflets to the community through mobile health promotion; and the redevelopment of media content for policy makers. We were able to co-develop effective strategies and solutions for the prevention of stunting that were based on women’s lived experiences.

Comparative Evaluation of Morphological Characteristics of Root Surfaces after Scaling and Root Planing under Naked Eye and Magnification: An In vitro Scanning Electron Microscope Study

Abstract Introduction: The primary aetiologies of periodontitis include bacterial plaque and calculus. Effective periodontal treatment necessitates the thorough removal of these deposits through scaling and root planing (SRP) using manual and ultrasonic instruments. However, the roughness introduced by these instruments can impact bacterial colonisation, plaque formation and calculus deposition. This study aims to evaluate and compare the morphological characteristics of root surfaces after SRP performed under the naked eye and magnification using a scanning electron microscope (SEM). Materials and Methods: This in vitro study included single-rooted extracted teeth from patients with chronic generalised or localised periodontitis. The teeth were divided into two main groups: manual instrumentation with Gracey curettes and ultrasonic instrumentation. Each group was further subdivided based on the method of visualisation during SRP: naked eye, dental loupes (×2.5 magnification) and dental operating microscope (×12 magnification). The samples were evaluated for root surface roughness, remaining calculus and smear layer presence using indices such as the remaining calculus index (RCI) and roughness and loss of tooth substance index. Results: A total of 60 samples were analysed, with 30 samples in each main group, further divided into three subgroups of 10 each. The results indicated statistically non-significant differences in smear layer presence between groups. However, significant differences were observed in root surface roughness and remaining calculus between manual and ultrasonic instrumentation, particularly under higher magnifications. Ultrasonic instrumentation under magnification provided smoother root surfaces compared to manual instrumentation, although manual instrumentation showed lesser RCI in comparison to ultrasonic instrumentation. Conclusion: SRP performed under magnification, particularly with ultrasonic instruments, results in smoother root surfaces with less remaining calculus. The use of magnifying tools such as dental loupes and operating microscopes enhances the efficacy of periodontal treatment by providing better visualisation and illumination.

Mastering trust and commitment in the virtual age

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings This study investigated virtual team members’ perception of trust and commitment when using computer-mediated communication across different industries. The results showed that communication method significantly impacted trust and commitment levels, while industry type alone did not produce significant differences. Visual communication methods consistently demonstrated higher trust scores across all industries compared to non-visual methods. Key managerial insights emanating from the findings emphasize the importance of strategic tool selection and the universal benefits of visual communication tools in building trust across virtual teams, regardless of industry context. Originality/value The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Navigation methods using airlandscape data for small UAVs

The purpose of the research. UAVs are widely used in such fields as military, intelligence, and research. As a result, the issue of their use in electronic warfare conditions and the presence of various interference, both man-made and natural, is acute. Thus, the need for UAV navigation using visual data increases.The purpose is study of the main negative factors affecting the quality of aerial photography images and methods for eliminating them to construct a correct orthomosaic for UAV visual navigation.Methods. Mathematical methods are proposed to eliminate negative distortions in UAV camera images using various image transformation approaches. After applying these methods to the original images, corrected versions are obtained, which are used to construct the tile covering. Tiled coverage created from processed images provides continuous and uniform coverage of the area collected during the UAV’s flight. This allows you to obtain exact coordinates of images and objects on them.Results. An analysis of the main methods for eliminating negative factors that distort images during aerial photography for the visual navigation of UAVs, as well as a brief overview of the visual navigation methods themselves.Conclusion. To successfully implement visual navigation of a UAV, it is necessary to apply a number of methods for converting aerial photography images, as well as the use of certain algorithms for visual navigation. It is concluded that in addition to the use of mathematical and software algorithms, it will also be necessary to analyze and study the necessary computing power for the use of the entire hardware and software complex on board the UAV, taking into account its weight-dimensional properties.

Legal dissemination protections in community-based participatory health equity research.

There are legal protections for nurse researchers at public universities who employ community-based participatory research (CBPR) in research about social or health inequities. Dissemination of CBPR research data by researchers or participants may divulge unjust laws and create an imperative for university involvement. What are United States-based legal dissemination protections for CBPR health equity nurse researchers? Three case examples employing CBPR are examined: 1) a mixed methods study with participants reporting illegal discrimination in a municipal initiative about capacity building in community-based organizations serving children; 2) a visual methods study exposing potential clean air law violations in environmental justice research; and 3) a study examining workload violations and illegal discrimination among hotel workers. The cases involved participants from protected social class backgrounds. The research is described with respect to: background, funding, research purpose, and research team; research participants' power and legal vulnerability; dissemination of relevant research information balancing vulnerability and power; research dissemination issues; potential legal issues involved; and laws researchers may use. IRB approval was obtained for the studies. Using a social justice ethical framework, studies highlight actual or potential legal aspects of data dissemination in the context of gathering data about injustice. Legal protections for research data dissemination, whistleblower protection, research advancement protection, anti-harassment protection, false claims, defamation, and visual data liabilities are described. Knowledge of legal research data dissemination protections is an essential competency for nurse researchers invested in uplifting social justice.

In-Situ visual reconstruction of strut profiles in pulsed wire arc additive manufacturing of lattice structures

ABSTRACT The wire arc additive manufacturing (WAAM) process often results in geometric inaccuracies in the produced struts, highlighting the need for in-situ monitoring. Industrial cameras struggle to capture accurate images due to interference from arc light and metal radiation. This study introduces a real-time visual reconstruction method that leverages regions of interest (ROI) to enhance profile accuracy. Initially, the melt pool is analyzed and segmented from a series of frames to establish an initial strut profile. This profile then serves as the ROI for segmenting the solidified weld bead regions, yielding a more precise strut profile. Comparative analysis shows that the proposed method achieves a high Intersection Over Union (IOU) score of 0.911 and an Average Symmetric Surface Distance (ASD) error of 0.355 mm, demonstrating both accuracy and robustness. Additionally, the inclination angle and diameter are extracted from the reconstructed profiles.

Research on the 3D Visualization Method of Web-Based Seismic Wave CT Results and the Application in Underground Caverns

Research on the 3D Visualization Method of Web-Based Seismic Wave CT Results and the Application in Underground Caverns

Less gets more attention: A novel human-centered MR remote collaboration assembly method with information recommendation and visual enhancement

Mixed reality remote collaboration assembly is a type of computer-supported collaborative assembly work that uses mixed reality technology to enable spatial information and collaboration status sharing among geographically distributed collaborators, including remote experts and local users. However, due to the abundance of mixed virtual and real-world information in the MR space and the limitations imposed by narrow field-of-view augmented reality (AR) glasses, users face challenges in effectively focusing on relevant and valuable visual information. Our research aims to enhance users' visual attention to critical guidance information in MR collaborative assembly tasks, thereby improving the clear expression of instructions and facilitating the transmission of collaborative intention. We developed the Information Recommendation and Visual Enhancement System (IRVES) through an assembly process information hierarchy division mechanism, a content-based information recommendation system, and a gesture interaction-based information visual enhancement method. IRVES can leverage the guidance expertise and preferences of remote experts to recommend information to filter out irrelevant information and present the key information that the remote expert conveys to the local user in an intuitive way through visual enhancement. We conducted a user study experiment of a collaborative assembly task of a small engine in a laboratory environment. The experimental results indicate that IRVES outperforms traditional MR remote collaborative assembly methods (VG3DV) in terms of time performance, operational errors, cognitive performance and user experience. Our research contributes a human-centered information visualization approach for remote experts and local users, providing a novel method and idea for designing visual information interfaces in MR remote collaboration assembly tasks.

The view of intertextuality in graphic design

This study aims to reveal the existence of the concept of intertextuality in the field of graphic design. No product produced by humans can be considered independent of previous products; this situation demonstrates that past experiences and social interactions play an inevitable role in product creation. Especially in the production of literary works, individuals create new works influenced by previous ones. This interaction is defined by the concept of "intertextuality." The initial studies on intertextuality began within the framework of Bakhtin's "Conversationalism" theory and were later developed by theorists such as Kristeva, Barthes, Jenny, and Genette. With Genette's classification, the concept of intertextuality has become multidimensional. It has been found that this concept is not limited to literary products but also exists in fields such as music, painting, sculpture, architecture, and moving media. In this context, the special day designs shared by non-governmental organizations operating in Turkey on the Instagram platform were examined using visual intertextuality methods developed by Werne. The results showed that methods such as "Attaching to Image," "Framing Image and Text," and "Encouraging Thought in Image" were actively used. Additionally, it was determined that "Visual Citation" and "Clustering" methods were also employed, although less frequently.

Exploring structural variances in monatomic metallic glasses using machine learning and molecular dynamics simulation.

BCC and FCC metals have different glass-forming abilities (GFA) and exhibit different characteristics during the glass transition. However, the structural origin of their different GFAs is still not clear. Here, we explored the structures of eight monatomic metallic glasses by combining molecular dynamics (MD) simulations and machine learning (ML). Our findings reveal that, despite their common long-range disordered atomic structure, metallic glasses can be further classified into two distinct categories indicating an underlying structural order within the disorder. Using machine learning, we found that BCC liquids can sample more diverse glass states than FCC liquids. Furthermore, glasses formed from BCC metals (GFFBs) exhibit a higher degree of disorder than glasses formed from FCC metals (GFFFs). These findings highlight the inherent differences between GFFFs and GFFBs, which help explain the different glass-forming abilities of FCC and BCC metals. Additionally, our results demonstrate the promising potential of computer vision and ML methods in exploring material structures. Classical molecular dynamics simulations were employed to generate configurations of GFFBs and GFFFs, and the simulations were performed using the LAMMPS code. Inter-atomic interactions were described using a classical embedded atom model (EAM) potential. The initial configuration of the model consists of 32,000 atoms in a three-dimensional (3D) cubic box with periodic boundary conditions applied in all three directions. For machine learning, we utilized an unsupervised machine learning method along with MobileNetV2 for classifying glass structures. Image entropy and image distances were used to measure the structural differences of the metallic glasses.

Nanoindentation of nano-SiC/Si hybrid crystals and AlN, AlGaN, GaN, Ga<sup>2</sup>O<sup>3</sup> thin films on nano-SiC/Si

The review presents systematization and analysis of experimental data on nanoindentation (NI) of a whole class of new materials – wide-gap AlN, GaN, AlGaN and β-Ga2O3 heterostructures formed on a hybrid substrate of a new SiC/Si type, which were synthesized by the method of coordinated atom substitution. The deformational and mechanical properties of the investigated materials are described in detail. The methodology of the NI is described, and both advantages and disadvantages of the NI method were analyzed. The description of the apparatus to conduct the experiments on NI was given. The basic provisions of a new model for describing the deformation properties of a nanoscale rigid two-layer structure on a porous elastic base were proposed. The original method of visualization of residual (after mechanical interaction) deformation in transparent and translucent materials was described. Experimentally determined values of elastic moduli and hardness of SiC nanoscale layers on Si formed by the method of coordinated substitution on three main crystal planes of Si, namely (100), (110) and (111), and elastic moduli and characteristics (elastic modulus, hardness, strength) of surface layers of semiconductor heterostructures AlN/SiC/Si, AlGaN/SiC/Si, AlGaN/AlN/SiC/Si, GaN/SiC/Si and GaN/AlN/SiC/Si grown on SiC/Si hybrid substrates. The unique mechanical properties of a new material β-Ga2O3 formed on SiC layers grown on Si surfaces of orientations (100), (110) and (111) were described.

Efficiency of International Law Mechanisms for Human Rights Protection in Education

Objectives. The study deals with international law mechanisms for human rights protection in education. The aim of the study is to analyse and evaluate the effectiveness of international law mechanisms for human rights protection in education. Theoretical Framework: The theoretical basis of the research was made up of the scientific works of scientists, quality and qualitative indicators of research, and the regulatory and legal framework. Methods: The research employed the method of comparison, visual graphic methods, a set of methods of processing, comprehension and interpretation of information. Results and Discussion: The study established the most common types of violations in the field of education, in particular: violation of the right of national minorities to education; impossibility of choosing the language of instruction; failure to provide inclusive education; discrimination against people with mental illness. Specific manifestations of the effectiveness of international law mechanisms for the human rights protection in the field of education are singled out, in particular: increasing public awareness and transparency of government activity, etc. Research Implications: The study gave grounds to draw the conclusions regarding the difficulty of proving the existence of violations in education. Attention is drawn to the subjectivity of the European Court of Human Rights (ECHR) and the ambiguous interpretation of norms enshrined in international legal acts. Originality/Value: The research is original, based on official data and the author's own conclusions, and has practical significance.

QLTI-07. COLLABORATIVE RESEARCH SUITE FOR GENOMIC ANALYSIS, DATA REPORTING AND WORKFLOW CUSTOMISATION

Abstract The genomic analysis pipeline involves multiple stages, including data extraction, transformation, and loading (ETL), exploratory data analysis (EDA), machine learning (ML) modeling, and reporting. The ETL stage involves data profiling and quality control measures to ensure data integrity and consistency. The EDA stage employs statistical and visualization methods to understand data distribution, identify patterns, and detect anomalies. Machine learning modelling involves supervised classification techniques, such as logistic regression and support vector machines (SVMs), to predict tumour classification and develop gene signatures. Unsupervised classification techniques, such as K-means clustering and Hierarchical clustering, identify patterns and relationships in genomic data. Quality metrics evaluate data completeness, accuracy, and consistency, ensuring data reliability and validity. The integration of data science techniques into a comprehensive framework can be achieved with the development of Application Dashboards that provide real-time insights into genomic data across every stage of the analysis pipeline. This enables clinical researchers and bioinformaticians to make informed decisions quickly, improving turn-around time and accelerating the discovery of new insights. In contrast to conventional methods of using stand-alone scripts, these dashboards offer a reusable and scalable solution, allowing for easy modification and adaptation to new datasets and analysis pipelines, thereby reducing development effort and increasing productivity. The dashboards constitute a centralized platform for data visualization, exploration, and analysis, facilitating collaboration and communication among research team members. With customizable and interactive visualizations, users can explore genomic data from multiple dimensions and the integration of multiple sources, including genomic and transcriptomic data. The technologies used to power this Research suite include Streamlit for Web App development, Python for data analysis, Opensearch for data storage and other utility libraries for reporting.

Visualizing the Philippines’ SDG 11.3.1 Status and Progress Using Open-Source Geospatial Software and Earth Observation Datasets

Abstract. This paper presents the development and implementation of a web GIS-based application designed to visualize the status and progress of Sustainable Development Goals (SDGs). Focusing specifically on SDG 11.3.1, which pertains to sustainable urbanization, we propose a prototype (accessible at https://ccgeoinformatics.github.io/sdg1131ph/) that leverages open-source geospatial software and earth observation (EO) datasets. By following the "where-when-what-how" framework of SDG visualization system development, we address the need for effective visualization methods while showcasing the potential of accessible datasets and technology in supporting sustainable development monitoring efforts across different administrative levels. We demonstrate the feasibility of the system in aiding policymakers and stakeholders in their decision-making processes toward achieving the SDGs by 2030. Additionally, our work exemplified how open-source software and EO datasets can address the challenges associated with SDG reporting, particularly in areas where both data and visualization tools are scarce or inaccessible. This paper also contributes to the ongoing discourse on SDG visualization and underscores the importance of localized analysis and visualization in understanding and addressing the challenges of sustainable urbanization using the example of the Philippines.

Global Semantic Localization from Abstract Ellipse-Ellipsoid Model and Object-Level Instance Topology

Robust and highly accurate localization using a camera is a challenging task when appearance varies significantly. In indoor environments, changes in illumination and object occlusion can have a significant impact on visual localization. In this paper, we propose a visual localization method based on an ellipse-ellipsoid model, combined with object-level instance topology and alignment. First, we develop a CNN-based (Convolutional Neural Network) ellipse prediction network, DEllipse-Net, which integrates depth information with RGB data to estimate the projection of ellipsoids onto images. Second, we model environments using 3D (Three-dimensional) ellipsoids, instance topology, and ellipsoid descriptors. Finally, the detected ellipses are aligned with the ellipsoids in the environment through semantic object association, and 6-DoF (Degree of Freedom) pose estimation is performed using the ellipse-ellipsoid model. In the bounding box noise experiment, DEllipse-Net demonstrates higher robustness compared to other methods, achieving the highest prediction accuracy for 11 out of 23 objects in ellipse prediction. In the localization test with 15 pixels of noise, we achieve ATE (Absolute Translation Error) and ARE (Absolute Rotation Error) of 0.077 m and 2.70∘ in the fr2_desk sequence. Additionally, DEllipse-Net is lightweight and highly portable, with a model size of only 18.6 MB, and a single model can handle all objects. In the object-level instance topology and alignment experiment, our topology and alignment methods significantly enhance the global localization accuracy of the ellipse-ellipsoid model. In experiments involving lighting changes and occlusions, our method achieves more robust global localization compared to the classical bag-of-words based localization method and other ellipse-ellipsoid localization methods.

Impact of Learning Styles on Students’ Retention of Information

This study investigates the impact of Visual, Auditory, and Kinesthetic (VAK) teaching methods on student retention within the context of China's evolving educational landscape. Acknowledging the country's significant strides in educational reforms and technological integration, the research aims to empirically determine the effectiveness of these teaching methodologies have on enhancing student engagement and information retention. The study is of critical importance as it seeks to inform educational practices and policies, with the goal of improving instructional strategies to align with diverse learning preferences. The research fills a notable gap in the empirical literature regarding the comparative impact of VAK methods on student retention in China, where traditional lecture-based methods are still predominantly employed. Findings from this study could influence teacher training programs and contribute to the development of a more inclusive educational system that caters to the varied learning styles of students. Through a synthesis of existing literature and the researcher's observations of differing engagement and retention rates with traditional versus varied teaching methods, the study provides valuable insights into the potential benefits of integrating visual, auditory, and kinesthetic elements into teaching practice. The research aligns with a body of studies that have demonstrated the effectiveness of VAK methods in enhancing learning outcomes, although it acknowledges the variability in outcomes based on context, subject matter, and individual learner differences. This paper also recognizes the importance of ongoing assessment and customization of teaching strategies to meet the specific needs of students in diverse educational settings.