bluuebunny/crossref_metadata_2025 huggingface dataset:
Five core areas to focus infection prevention and transmission risk breaches training based on quarantine staff orientation sessions: A qualitative study
Authors: Sheedy Angela Dawn , Fitzgerald Alison Claire , Black Diann Elizabeth , Scott Joy Antoinette , Rettie Fiona Mary
Published: November 2023

Background & Aim: Breach awareness in relation to types, mitigation, and reporting should be a routine part of infection prevention training. Understanding breaches can reduce risk of disease transmission to staff and communities when contextualized to the infectious disease, environment, and situation. At a large-scale Australian COVID-19 quarantine facility, this study examined the core personal protective equipment and infection prevention breaches new quarantine workers identified during their site orientation to inform future breach training.
Methods & Materials: Through the application of a qualitative approach, the project implemented a descriptive thematic analysis to identify the different types of breaches staff presented. An additional summative content analysis method was applied to determine if the breaches staff identified were breaching and if the risk level staff allocated to the breach was mapped to the risk of disease transmission. Data were collected from 30 orientation sessions and included 603 breach risk responses for analysis.
Results: There were five core breach areas identified: donning and doffing of personal protective equipment, failure of personal protective equipment or lack of equipment, environmental factors, staff behaviors, and resident behaviors. The breach allocations by staff demonstrated knowledge deficits across health and non-health staff in disease transmission, particularly in the actual level of the risk for transmission.
Conclusion:  Breaches awareness in relation to types, mitigation and reporting should be a routine part of infection prevention training. The five areas of breaches present an adaptable foundation to base infection prevention breach training for any health facility. When contextualised to the communicable disease, environment and situation, understanding breaches can reduce the risk of disease transmission to staff and communities.
Effect of transitional nursing care on quality of life among patients with type 2 diabetes: A meta-analysis of randomized controlled trials
Authors: Putri Alfiani Rahmi , Pimolkatekul Saranya , Wibawa Yan Adi , Thanh Nguyen Ngoc , Lawrence Tirza Jo , Nugraha Gautama Made Satya
Published: November 2023

Background & Aims: Type 2 diabetes accounts for 95% of all diabetes cases worldwide, and its prevalence continues to rise. The constant management of blood glucose levels can be burdensome, further deteriorating patients' quality of life. This study aims to determine the effect of transitional nursing care on the quality of life among adults with type 2 diabetes.
Methods & Materials: We conducted a meta-analysis of randomized controlled trials (RCTs) to determine the effectiveness of transitional nursing care on the quality of life of adults with type 2 diabetes. We searched for published Randomized Controlled Trials (RCTs) on PubMed, Embase, CINAHL, and the Cochrane Library. The process of study selection spanned from March 2023 to April 2023. Data synthesis was performed using Review Manager 5.4 to generate pooled effect size estimates.
Results: A total of six studies were included in our analysis. Our results showed that transitional care significantly improved the quality of life of adults with type 2 diabetes (SMD= 0.55, 95% CI: 0.15, 0.95, Z= 2.72, p= 0.007). Compared to usual care, transitional care also significantly lowered HbA1c levels (MD= -0.39, 95% CI: -0.70, -0.07, Z= 2.41, p= 0.02).
Conclusion: Our research identified that transitional nursing care significantly improved the quality of life among adults with type 2 diabetes. Nurses should take into account our positive findings when implementing this care model for these patients. We suggest that future researchers carry out more studies with a focus on transitional nursing care for patients with type 2 diabetes to investigate its impacts further.
A thematic analysis of professionalism from the perspective of nurse managers
Authors: Žiaková Katarína , Kohanová Dominika , Čáp Juraj , Kurucová Radka
Published: November 2023

Background & Aim: Professionalism is a multidimensional and dynamic concept that can be understood and interpreted differently in time, job position, or culture. Our study investigated how nurse managers interpret and understand professionalism in the Slovak sociocultural context.
Methods & Materials: This qualitative study adopted an interpretive design. The sample consisted of seven nurse managers working in the selected university hospital in Slovakia. Data were collected between November and December 2021 using semi-structured interviews. Data were analyzed using reflexive thematic analysis.
Results: The reflexive thematic analysis resulted in developing six key themes specified in twenty-one sub-themes: Developing and maintaining professionalism; Challenges and problems of professionalism in nursing; Teamwork; Violation of professionalism; Requirements to become a nurse professional; Social status of nurses. These themes represent the perception of nurse managers of professionalism as a complex phenomenon grounded in the background and attitudes of nurses, socialization, quality of teamwork, profession requirements wrestling with the shortage of nurses, dominance of medicine, and lack of respect for the profession of nurses.
Conclusion: Together with other healthcare managers, nurse managers should continuously support and guide novice nurses and nursing students, share knowledge and skills, overcome stereotypes, support teamwork through strengthening nurse-patient collaboration or building collegian relationships, and improve the social status and recognition of nurses in society.
Functional capacity and its associated factors in older adults in the rural area in Brazil
Authors: Costa Lima Eveline Fontes , Oliveira da Silva Ezequiel , Silva Fhon Jack Roberto
Published: November 2023

Background & Aim: Aging leads to bodily changes and impairment of functional capacity in older adults. The objective was to analyze the association between socio-demographic and health data, cognitive impairment, and risk of sarcopenia with functional capacity in older adults enrolled in the Family Health Strategies in the rural area of the municipality of Picos, Piauí, Brazil.
Methods & Materials:  This is a quantitative and cross-sectional study that was developed with 320 older adults attending the Family Health Strategies located in the rural area of Picos, Piauí, Brazil. The participants were people 60 years old, registered in the Family Health Strategies, and living in a rural area. Data was collected in the older adults’ homes using the following instruments: Demographic profile, Self-reported illnesses, Mini-Mental State Examination, Barthel Index, Lawton and Brody Scale, and SARC-F.
Results: It was found that 70% had cognitive impairment, 53.8% were at risk of sarcopenia, with a mean of 93.72 (SD=11.84) points for basic activities daily living, and 77.8% with partial dependence for instrumental activities daily living with a mean of 16.79 (SD=3.79) points. In the multivariate multiple regression, it was identified that there was an association between Basic Activities of Daily Living and Instrumental Activities of Daily Living with age (p<0.001), number of children (p=0,025), education (p=0.003), monthly income (p=0.018), number of diseases (p<0.001), sarcopenia (p<0.001) and cognitive status (p<0.001).
Conclusion: A high prevalence of functional disability was identified in elderly people living in the rural area of ​​Picos, Piauí, Brazil. Therefore, it is important to pay attention to factors associated with dependence on daily activities.
The level of teamwork and associated factors in the selected hospitals from the nurses' perspective: A cross-sectional study
Authors: Kohanová Dominika , Solgajová Andrea , Lušňáková Miriam , Bartoníčková Daniela
Published: November 2023

Background & Aim: Teamwork represents a fundamental prerequisite for providing quality and safe care. This study aimed to determine the level of teamwork and the factors that influence the level of teamwork in selected hospitals in the Slovak Republic.
Methods & Materials: The descriptive cross-sectional study included 207 nurses from 12 departments of three district hospitals in the Slovak Republic. Data were collected between November 2022 and February 2023 using a questionnaire that evaluated nursing teamwork, the Nursing Teamwork Survey. Data were analyzed using descriptive and inferential statistics.
Results: Nurses evaluated the level of teamwork as (3.74± 0.64), which means ideal less than 75% of the time during the last working shift. The best-rated subscale was the Shared mental model (4.17± 0.49), while the worst-rated subscale was Team orientation (2.47± 0.85). Differences in teamwork level were found based on unit type, education, number of hours worked, number of overtime hours, and perceived staff adequacy (p≤ 0.05). The correlation analysis revealed associations between teamwork and job satisfaction, teamwork satisfaction, subjective quality evaluation, and patient safety, as well as with the number of patients in the last shift, including the number of admitted and discharged patients.
Conclusion: By regularly determining teamwork levels, it is possible to identify the strengths and weaknesses of nursing teams. Analyzing team weaknesses and implementing targeted measures can lead to strengthening teamwork and improving team functioning.
The Tacticality of Working Capital
Authors: N. Emongor Elizabeth
Published: November 2023

In today's dynamic and competitive business landscape, the effective management of working capital has emerged as a critical factor for the success and sustainability of organizations. Literature review has shown that working capital management can be an effective survival tool in a tough macroeconomic environment where businesses can enhance their ability to meet short-term obligations, improve cash flow, and ultimately achieve long-term success. As businesses strive to maintain financial stability and optimize operational efficiency, tactical working capital management has taken center stage. This research sheds light on the importance of working capital management and how it affects companies. The study goes on to demonstrate that working capital management may influence the performance of a firm and therefore its strategic management can enhance business sustainability.
Corporate Tax Saving Strategy and Share Price Performance
Authors: Olade, IZEVBEKHAI Monday , Oshone MOMODU WASEELA
Published: November 2023

This study ascertained how corporate tax saving strategy affect share price performance. It examined how debt tax shield, non-debt tax shield, and effective tax rate affect share price performance. The secondary source of data collection was adopted in the study where the purposive sampling technique was used to select a sample size of twelve (12) listed industrial goods firms in Nigeria. Ordinary Least Square regression analysis was used in this study and the findings revealed that non-debt tax shield has significant effect on share price performance of listed industrial goods firms in Nigeria and that effective tax rate has significant effect on share price performance of listed industrial goods firms in Nigeria. The study concluded that crucial component of fiscal policy that has a great impact on both the social and economic development of a nation, hence, tax savings demands attention from managers at all levels of management. The study recommended that Nigerian government needs subsidize cost of debt-financing for the companies operating in the country’s capital market and that stakeholders should develop the financial markets and make it accessible for firms to obtain long-term financing for economic growth and development.
Analysis of the effectiveness of social distancing policies on reduction of COVID-19 infection risks
Authors:   The Association of Korea Counseling Psychology Education Welfare, HAN Ji-Won , LYM Young-Bin
Published: November 2023

This study analyzed the effectiveness of the social distancing policy among thecountermeasures against the coronavirus(COVID-19). To this end, the study employed theworld's most popular COVID-19 government response index at Oxford University and differenttypes of social distancing policies enforced by the Korean government. Total population andweekly floating population at each municipality were considered as control variables. Meanwhile, the COVID-19 confirmed cases per millions were adopted as a dependent variable. From January 2021 to April 2022 (when the social distancing policy was lifted), we collecteddata from 16 metropolitan cities and provinces across the country, excluding Jeju Island, on aweekly basis. Two types of panel models were considered in this study: one with one-week lagthat accounts for the incubation period of COVID-19 infection and the other without a lag. Asa result, we identified that both models showed a reduction in infection risks when the socialdistancing policy (i.e., a ban on private gathering) was intensified.
The Effect Of The Educational Program On Rational Antibiotic Use On The Knowledge And Attitude Levels Of Health Technician Students
Authors: ÇELEBİ İsmet , GÜN İskender
Published: November 2023

Aim: The aim of this study is to measure the effect of the education program concerning rational antibiotic use on the knowledge-attitude levels of health technician students towards rational antibiotic use.

Method: This intervention study has been conducted with vocational school students (control group: 437, intervention group: 403) enrolled in the same health services program at two universities in Ankara. The dependent variable of the study was the Knowledge-Attitude Scale towards Rational Antibiotic Use and the independent variables were the control and intervention groups. The educational program applied in this study included the definitions of and distinction between infections, the flu and a cold, the effect mechanism and types of antibiotics, the consequences of irrational antibiotic use, antibiotic resistance and rational and irrational use of antibiotics.

Result: Both the knowledge and attitude mean scores of the intervention group on the final test were found to be statistically significant and higher than the mean scores of the pre-test. When the final test and retention test score averages of the intervention group were examined, it was found that there was no statistically significant difference between the mean knowledge score and mean attitude score on the final tests and retention tests

Conclusion: This study is the first educational intervention study in Turkey concerning the rational use of antibiotics by health technician candidates. As a result of this study, a significant increase was observed in knowledge-attitude levels on rational antibiotic use after the intervention training concerning rational antibiotic use and in terms of retention.
Practical Application of Local Estimations: Singularity Removal in the Solution of the Global Illumination Equation
Authors: Budak Vladimir Pavlovich , Grimailo A.V. , Zheltov Victor Sergeevich , Yakushev S.A.
Published: November 2023

The work is devoted to the elimination of the singularity in the local-estimation-based solution of the global illumination equation. The presence of the singularity prevents the practical application of this method and the creation of software based on it. A method is proposed to eliminate this problem by averaging the sought value in a certain neighbourhood of the point of interest. The transition to averaging occurs only at small distances between the collision point and the point of interest. In other cases, the calculation is conducted according to the usual local estimation algorithm. The results of the light distribution modelling in the modified Cornell box scene are presented as visualizations for different values of the number of rays, threshold of transition to averaging and the averaging sphere (neighbourhood) radius. The proposed method and the results obtained open the way for the practical program realization of local estimations.
Optimization of Multilevel Spatial Partitioning Accelerating Structure of Hash Tables and Kd-tree
Authors: Lysykh A.I. , Kinev I.E. , Zhdanov Dmitri Dmitrievich
Published: November 2023

This research conducts an in-depth analysis of existing types of spatial partitioning acceleration structures. It investigates the properties and characteristics of the original combined spatial partitioning structure, based on hash tables and kd-trees. Three types of use cases for this structure are identified: dynamic, balanced, and static. Methods for optimizing the structure construction and cell search algorithms are proposed. For each of the three usage scenarios, algorithms for determining the size and placement levels of hash tables are introduced. An analysis of the optimal parameter values for these algorithms in each usage case is performed. Furthermore, a comparative efficiency analysis of the modified structure against the original combined structure and kd-tree is carried out. The comparison reveals that the resulting structure significantly enhances cell search efficiency for the considered types of structure usage.
Mixed Reality Surgical Navigation Method
Authors: Madaliev A. , Ivanov V.M.
Published: November 2023

The aim of the study is to present the features of our own new mixed reality surgical navigation method. The paper describes the workflow from the stage of preoperative patient scanning to postoperative patient scanning. Potential sources of positioning errors are identified, design and software approaches to reduce their impact are described: the implementation of the unity of the location of markers, the execution of markers. The applied approach for estimating the cumulative positioning error is described. As a result of the implementation of these approaches in practice, the value of the total navigation error was less than 2 mm, and more than 80 successful operations were performed in this way. This value of navigation error is sufficient for most surgical operations, but is unacceptable in neurosurgery. The study can be useful for improving similar systems, as well as for designing mixed reality systems in other scientific fields.
Computer Graphics in the Simulation of Gas-discharge Plasma
Authors: Budak Vladimir Pavlovich , Zheleznov I.I.
Published: November 2023

This article discusses the importance of the development of specialized software and hardware complexes for data visualization and improvement of algorithms for their representation in the simulation of low-temperature gas-discharge plasma radiation and related physical processes. The problems of creating a specialized distributed environment for solving problems of modeling a gas discharge are considered. Visualization using computer graphics made it possible to visually evaluate the data obtained and make the necessary adjustments in the process of constructing the grid in the interaction mode. The paper presents the results of visualization of a self-consistent model of mercury-argon plasma in a coaxial microwave discharge. The use of local cross-sections of the computational visualization area made it possible to reveal the internal structure and features of the distribution of the electric field and the concentration of electrons in the discharge tube. The obtained data formed the basis for optimizing the design of a coaxial gas-discharge source of bactericidal UV radiation.
Study of the Flow Generated by a Sliding Discharge by Means of a Convolutional Neural Network
Authors: Znamenskaya Irina Alexandrovna , Doroshchenko Igor Alexandrovich , Sysoev Nikolai Nikolaevich
Published: November 2023

A quantitative study has been made of the flow with shock waves generated in air by a sliding surface discharge with a duration of less than one microsecond. The flow was visualized using the shadowgraph method, the process was recorded at a rate of 124,000 frames/s, the exposure time was 1 ?s. The aim of this work is to study the dynamics of a cylindrical blast wave generated during a discharge and a region bounded by a contact surface. Each experiment allowed several hundred images to be taken of a transient gas-dynamic process with a duration of up to 1 ms. A YOLOv8 convolutional neural network was trained and used to determine the positions of the discontinuities. A data set with 984 markups was marked. The model on the mAP50 metric achieved 0.887 and the mAP50-95 was 0.557. The model was used to automatically measure the vertical dimensions of the contact discontinuity. It expands at times of up to 0.4 - 0.8 ms to a vertical size of 5 - 11 mm. The x-t plots and the velocities of the cylindrical shock waves were measured. It is shown that at t < 1 ms the main reason for the development of the flow is the blast wind behind the blast wave. It is shown that the use of computer vision can significantly speed up the analysis of high-speed visualizations and the extraction of quantitative information.
Luminance Distribution Visualization Across the Twilight Sky
Authors: Budak Vladimir Pavlovich , Smirnov Pavel Alexandrovich
Published: November 2023

Visualization of the twilight sky is a good representation for the tasks of the meteorological conditions analysis, astronomical observations, navigation, driving conditions, some tasks of the lighting engineering and lighting design. A qualitative solution for this problem requires the calculation of the distribution of color coordinates, one of the main components of which is lightness. If for the daytime sky the modeling of this component is recognized as sufficiently good and does not have any particular difficulties, then for the twilight environment a reliable mathematical model based on the real physical characteristics of the atmosphere requires significant computational resources. The problem here is that the Independent Pixel Approximation (IPA) method and the simplification of the model to a flat layered medium for the twilight zone becomes inaccurate due to the peculiarities of the direction of incidence of the rays to the boundary of the atmosphere and the entry of radiation into a special region where it is necessary to consider its spherical shape, i.e., accurate 3D atmosphere model. A solution to this problem is proposed by extracting the anisotropic part based on a small-angle modification of the spherical harmonics method and solving the smooth part in diffusion approximation in the Comsol Multiphysics environment. The obtained picture of the luminance distribution visualization coincides qualitatively with G.V. Rosenberg's monograph “Twilight” data.
Automatic Creation and Annotation of RGB-D Images for Training Machine Vision Systems
Authors: Zhdanov Andrei Dmitrievich , Zhdanov Dmitri Dmitrievich , Khilik E.D.
Published: November 2023

Due to the active development of artificial intelligence technologies, machine vision, and deep learning, as well as the emergence of RGB?D cameras that allow you to get a three-dimensional image of the scene, more and more attention is paid to various tasks of processing three-dimensional data. One of these problems is the problem of point cloud segmentation, which is used in various fields, from robotics to architecture, and is solved by machine vision methods. The training of machine vision systems requires the creation and annotation of datasets, which takes up a significant part of the design and development time. In this paper, it is proposed to automate the process of creating a dataset using a scripting interpreter and realistic rendering computer systems, which can significantly reduce the time required to create a dataset. An example of creating a dataset, training a neural network on this dataset, and using a network trained on this dataset to classify objects in a scene image is given.
On the Visualization of the Ensemble of Parametric Numerical Solutions Using Tensor Decomposition
Authors: Alexeev Alexey Kirillovich , Bondarev Alexander Evgenyevich , Pyatakova Yu.S.
Published: November 2023

An approximation of the tensor obtained at a discretization of the multidimensional function on a uniform grid is addressed from the viewpoint of the storage and treating the result of the parametric computations in the CFD problems. The tensor decompositions are considered for this purpose. The new algorithm of the calculation of the canonical decomposition using the gradient descent for an approximately decomposable goal functional. This algorithm applies an ensemble of points on the hyperplane orthogonal to the computed core of the canonical decomposition (”umbrella”) that enables its flexible application for the approximation of the tensors with a priori unknown rank. This algorithm is naturally transferred on such tensor decomposition as the tensor train. The results of the numerical tests are presented for model six-dimensional functions and for the ensemble of the numerical solutions for two-dimensional Euler equations. These equations describe the flow of the compressible gas with two crossing shock waves. Mach number and the the flow deflection angles are considered as the flow parameters.
Measuring the Phenomenon of Presence with a Break-in-Presence Counter
Authors: Averbukh Natalya Vladimirovna , Provkov N.S. , Starodubtsev Iliya Sergeevich
Published: November 2023

The paper presents a methodology of presence state estimation for virtual reality environments based on presence counter method. The presence counter is based on counting breaks in presence: moments when the subject just experienced presence, was subjectively inside virtual reality (state V), but this state was broken, and the subject felt himself in ordinary reality, in the laboratory (state R). A generalized mathematical model based on Markov random processes is given, which allows to calculate the probability of presence state on the basis of discrete data using continuous time. The description of a pilot experiment in virtual reality, conducted to verify the described methodology. As part of a pilot experiment, subjects move around a virtual Asian park and shoot at round vases they see. The hits are being counted. Also, sound distractors are turned on for the subjects - signals that return them from state V (the sence of being in virtual reality) to state R (the sence of being in ordinary reality), in fact, stimulating breaks in presence. The results of the pilot study and its prospects are discussed.
Graphical Neural Networks and Image Verification Problems
Authors: Bondareva Nikole Alexandrovna
Published: November 2023

The paper offers an overview of modern text-to-image graphical neural networks and text-to-image image retrieval. The paper discusses a number of problems arising in the use of text-to-image networks and possible methods for their solution. One of the actual tasks related to the study of graphical neural network technologies becomes the study of neural network images and identification of images obtained with the help of neural networks among other graphical content. We propose approaches to solving problems aimed at solving the problem of verification of media materials and developing algorithms to detect artificial (neural network) origin of photo and video materials. The rapid development of neural network technologies in this area can have a significant impact on society, the market of professions and the media, which makes the task of identifying neural network images among other graphic content particularly relevant.
Development of a Visualization System for Civil Aircraft
Authors: Barladyan Boris Khaimovich , Deryabin Nikolay Borisovich , Voloboy Alexey Gennadievich , Galaktionov Vladimir Alexandrovich , Shapiro Lev Zalmanovich , Valiev Ildar Vagizovich , Solodelov Y.A
Published: November 2023

The instrument panels of modern aircraft are created according to the concept of a "glass cockpit". This new interface concept enhances the perception of critical flight information by integrating it into one multi-functional display that provides a cohesive, easy-to-read view of flight information. The paper deals with the problems that arise in the development of a certified visualization system for the pilot's display, designed to work on civil aircraft under the Russian real-time operating system JetOS. It is shown that we have successfully solved the problems of multi-window visualization of many aviation applications with an acceptable speed on a promising aviation computing platform. The article lists several algorithmic solutions that allow achieving the required rendering speed, as well as outlines ways for further work.
3D visualization of HPC Tasks Scheduling Algorithm
Authors: Vasev Pavel Alexandrovich
Published: November 2023

The paper is devoted to the issue of visualization of the algorithm for scheduling parallel tasks. Task planning is a key part of the online visualization and parallel programming environment developed by the author. When programming a parallel version of one application task, a suspicion arose that the scheduling algorithm does not optimally distribute the load between the performers. In this connection, it was decided to visualize its work in order to see the overall picture and possible problem areas of the algorithm. The display view works in three-dimensional space and visualizes the assignment of tasks with dots. The coordinates of the points are determined by the logical time, the sequence number of the core (performer), and the sequence number of the data block from the decomposition of the task. The color of the dots is set by the task type. Dependencies between data tasks are shown in segments. The constructed view of the display successfully coped with the task, and the planning algorithm was improved.
On Dependence of Bert Embeddings on the Syntactic Structure of a Sentence
Authors: Klyshinsky Eduard Stanislavovich , Vasilyeva V.V. , Karpik Olesya Vladimirovna , Belobokova Yu.A.
Published: November 2023

Experiments demonstrate that Bert embeddings are reflecting syntactic structure of a sentence. In this paper we conduct some experiments demonstrating dependency between cosine similarity of Bert embeddings and position of neighbouring words with consideration of a consistency structure of a sentence. Our experiments demonstrated that Bert embeddings are dependent on the number of started and finished consistencies between those words. The more the number of borders of consistencies, the less is the cosine similarity; finished borders take more influence than started ones. Increasing the distance between words up to 3 cosine similarity decreases. Moreover, we have found that Bert model assigns very close vectors which cosine similarity does not fall less than 0.6. The Word2Vec model, which takes not a context of a word into consideration, does not demonstrate such a behaviour.
Segmentation and Visualization of Water Pollution Based on the K-means Method
Authors: Khasanov M.B. , Diane S.A.K.
Published: November 2023

The paper presents a study of the current state of water pollution detection systems. A formalization of the centroid map for a three-channel aerial photograph is proposed. An example of using the Kmeans algorithm for clustering terrain and water areas on test aerial photographs is considered. The visualization of the results of clustering of aerial photographs for a different number of centroids is given as well as the results of pollution segmentation. A block diagram of the clustering algorithm is presented. Its advantages and disadvantages are identified. The structure of the developed software using Python and cross-platform computer graphics libraries is described. An assessment of the accuracy of using the clustering algorithm using the F1-measure is performed. Preliminary experimental studies showed that the inclusion of an expert in the contour of decision-making allows increasing the flexibility of the program, due to the possibility of selecting a target area, choosing the number of clusters and segmentation accuracy.
The Gauss-Newton Method in the Problems of Optimizing the Phase Function Calculation Based on the Hilbert Diagnostic Data
Authors: Arbuzov Eduard Vitalievich , Arbuzov Vitaliy Anisiforovich , Dubnishchev Yuri Nikolaevich , Zolotukhina Olga Sergeevna
Published: November 2023

The problem of reconstructing the phase function in the Hilbert diagnostics of gaseous, condensed and reacting media is discussed in the paper. The method for restoring the phase disturbances structure of a probing light field based on the iterative Gauss-Newton algorithm is proposed. It does not require the definition of second derivatives and significantly reduces the number of computes. The method consists in successive selection of the phase profile given by the Bezier curve and calculation of the hilbertogram. The reliability of the results is the coincidence of the reference and reconstructed hilbertograms local extrema. The Jacobian matrix of the nonlinear integral operator of the Hilbert visualization is calculated. The proposed algorithm has been certified on test functions. The development of the method and its applications is associated with the processing of experimental results, including complex structures, where the phase function is represented by several Bezier polynomials.
The Gershberg-Papulis Method in the Problem of Phase Structure Reconstruction from Low-angle Hilbertograms
Authors: Arbuzov Eduard Vitalievich , Arbuzov Vitaliy Anisiforovich , Dubnishchev Yuri Nikolaevich , Zolotukhina Olga Sergeevna , Lapikov Michael , Lukashov Vladimir
Published: November 2023

The possibility of processing small-view hilbertograms by the Gershberg-Papulis method to restore the refractive index of phase objects is discussed. The method consists in iterative transitions from estimating a function in the Fourier plane to estimating it in a coordinate space with an adjustment using a priori information. The spectrum of the function is determined on the entire frequency plane as an iterative process result Numerical simulation of the refractive index reconstruction for various test functions was performed using the Gershberg-Papulis method using Radon data known for four angles. Experimental studies on the Hilbert diagnostics example of reacting media (flames) in a high-speed shooting mode (up to 2000 frames per second) were performed using a four-angle tomographic complex implemented on the basis of an upgraded IAB-463M shadow device.
To Adapt Data Fabric Technology to Visual Analytics Systems Development in the Field of Digital Medicine
Authors: Chuprina Svetlana Igorevna
Published: November 2023

The paper proposes an innovative approach to expanding the application scope of Data Fabric technology, which is currently used almost exclusively for the creation of corporate data warehouses. The approach provides access to digital data of a particular person not on the principles of their consolidation from heterogeneous sources, but on the principles of virtual integration. Services of such Data Fabric make available on-demand access to data coming from wearable personal devices, and data extracting from laboratory clinical research documents, questionnaires, electronic health records instead of information about corporation units, products, services provided, etc. These personal data are rendered related to the certain systems of human organism, and the relationships reflect both paradigmatic, causal and temporal dependencies between the data, and lines of "communication" corresponding to the basic physiological systems of the human body. The concept of a "personal data fabric" is introduced and the application of this concept to data semantic integration, aggregation and visual analytics in the field of digital 4P-medicine is described.
Deep Learning for Segmentation of Cement Spots in Core Images
Authors: Bolotov Ivan , Tolstaya Ekaterina , Mezghani Mokhles , Khalifa Aqeel
Published: November 2023

Detecting anhydrite spots on core images is an important task in oil&gas industry due to the impact of anhydrite on overall reservoir quality and production potential of hydrocarbon reservoirs. Accurate identification of anhydrite spots helps to differentiate zones of high and low permeability and identify areas with reduced reservoir quality. Traditional segmentation algorithms are often not accurate for anhydrite segmentation. Therefore, deep learning methods are promising to obtain stable and reliable segmentation results. However, the required training data are not always available. Within the presented research, we suggested utilizing synthetic data and preprocessing techniques to extend the training data for the task at hand. Our methodology for anhydrite segmentation relying on state-of-the-art neural networks showcased the ability to detect and delineate anhydrite spots of varying shapes and sizes on example of representative experimental data. Integrating proposed method into a comprehensive reservoir analysis could enhance the pipeline of geological analysis.
Measurement of Quantitative Characteristics of Schooling Movement of Fish by Computer Vision Methods
Authors: Bujakas V.I. , Glotov M.D. , Selyukov A.S. , Malyutina T.A.
Published: November 2023

In the study of the mechanisms of schooling behavior of fish, it becomes necessary to process large amounts of visual information. Early this processing was done mostly by hand. The paper study the possibility of automating the processing of observation results using the open CV computer vision package. Both individual frames and video fragments (scenes) of observations were processed. To process individual frames, a program was written for automatically counting the number of fishes in a school, another programs were written for determining the position of fishes and the degree of polarization of a group. During processing fragments of observations (scenes) the video scenes of fright of the school and video scenes of interaction between the predator and the school were considered. When studying the fright scene, a program for determining the speed of movement of individuals, a programs for calculating the kinetic energy of an individual moving and the kinetic energy of a group of fishes were built. The concept of the fright’s magnitude caused by a short local perturbation is introduced, and a method is proposed for numerically measuring the magnitude of the fright. When studying the scene of interaction between a predator and a school, a program for tracking the movement of an individual in a school was built. The proposed methods can be used in constructing and identifying the parameters of mathematical models of schooling fish movement.
Virtual Prototyping of Measurement Setup for Complex Light Scattering Properties
Authors: Sokolov Vadim Gennadjevich , Potemin Igor Stanislavovich , Zhdanov Dmitri Dmitrievich , Pozdnyakov Sergey Georgievich , Voloboy Alexey Gennadievich
Published: November 2023

The objects with complex light scattering, for example, light guiding plates with surface and volume microstructures are widely used in modern optical devices and computer graphics. Typically, such properties are described with Bi-Directional Scattering Distribution Function (BSDF) which totally describes the dependence of scattering properties on illumination and observation conditions. The precise BSDF measurements require complex setups with high resolution and launching numerous measurements in the entire angular space. The virtual prototyping of BSDF measurement devices is a difficult and problematic task because of the very small efficiency of similar systems. In the given paper the optimal and more effective ways to simulate such devices are presented based on example of patented scheme for portable BSDF measurements setup, including tolerance calculation and accuracy estimation.
Combined Algorithm for Combining Point Clouds
Authors: Efimov Aleksey Igorevich , Kryuchkova T.N. , Yaroslavtseva A.I.
Published: November 2023

The issues of combining three-dimensional surfaces and three-dimensional point clouds are important for solving a number of applied problems: three-dimensional reconstruction of the underlying surface of aircraft, construction of three-dimensional models of objects and a number of others. The report deals with the registration of point clouds, in particular, the algorithm of rigid registration of three-dimensional clouds. A software implementation of an iterative algorithm for combining three-dimensional point clouds is described, its main advantages and disadvantages are analyzed, and a modification of the ICP algorithm is proposed, including preliminary combination of the corresponding parts of the clouds using an approach based on three-dimensional descriptors of key points. The use of a combined algorithm for combining three-dimensional clouds allows you to build dense three-dimensional models of objects based on their separate disparate stereo images. The accuracy and time estimates of the proposed approaches are presented.
Visual Navigation for the Inspection of Industrial Underwater Structures Using a Virtual Coordinate Network
Authors: Kudryashov A.P.
Published: November 2023

Inspection of underwater industrial infrastructure facilities using autonomous uninhabited underwater vehicles (AUVs) requires high accuracy of AUV navigation relative to the objects being inspected. Along with traditional navigation aids based on the inertial navigation system and sonars, technologies based on video information processing are being actively developed today. Methods based on visual odometry can provide higher navigation accuracy in conditions of local maneuvering at small distances to objects. However, during long-term movements of the AUV, such methods tend to accumulate errors in the calculation of the trajectory. Therefore, this paper proposes a navigation method that can significantly improve the accuracy of AUV movement in the coordinate space of the inspected object due to the generation and use of a virtual network of coordinate reference to an underwater object.
Self-supervised Algorithms for Anomaly Detection on X-Rays
Authors: Saibodalov Marat , Karandashev Iakov
Published: November 2023

In this paper, we consider the problem of prohibited objects detection on X-Ray images obtained by personal inspection scanners. Such scanners are often used on objects that require increased security control. The available data has a number of problems, which are described and addressed in the text. In this paper we consider only self-supervised anomaly detection algorithms. We are using several architectures of autoencoders and comparing them with the state-of-the-art algorithm Patch SVDD, which could be designed and trained on our data from scratch. Unlike supervised learning algorithms, which are often used for such problems, these models do not require a large amount of labeled data for training.
Classification and Recognition of Ground Objects in the Stream of Radar Frames Based on a Neural Network Approach in the Forward Field of View of Airborne Radars of a Multi-position System
Authors: Nenashev V.A. , Nenashev S.A.
Published: November 2023

Classification and recognition of ground objects in the stream of radar frames based on a neural network approach in the forward field of view of the onboard radar of a multi-position system. This article discusses the features of effective classification and recognition of ground objects in the video stream of radar frames formed in the forward field of view of the on-board radar of a multi- position system. The issues of building spatially distributed systems for on-board radar automated monitoring of the earth's surface are covered, modern requirements for the resolution of radar frames are determined, and the features of the formation of a video stream of radar frames for the implementation of a system for classifying and recognizing ground objects are discussed. To solve these problems, technical vision methods are used, in particular, radar frame segmentation for detecting, classifying and distinguishing ground objects against the background, as well as neural network methods implemented in the algorithms for complex processing of streaming data in the onboard multi-position system of aviation monitoring of the earth's surface. These methods allow, at the first stage of processing video frames, to quickly select each object into a class, while separating the static background in the video stream of radar frames. At the second stage, in order to recognize objects of the selected class, technical vision tools are used based on the use of multilayer neural networks. As a result, a method for classifying and recognizing ground objects in a stream of radar frames based on a neural network approach is described, and recommendations are given for their further practical use.
Study of Algorithms Based on YOLO Neural Network Architecture in the Problem of Polyp Detection on Colonoscopic Video Data
Authors: Khryashev V.V. , Kotov N.V. , Priorov A.L.
Published: November 2023

An analysis was made of the use of neural network algorithms for the detection of colon polyps obtained during colonoscopy. The Kvasir-SEG image database was used to train and test deep machine learning algorithms. The networks YOLOv6, YOLOR, YOLOv7, YOLOv7X, YOLOv8 previously trained on the basis of MS COCO images were used as neural network architectures. Due to the small volume of images in the Kvasir-SEG database, data augmentation was used. As a result of applying the detection algorithms to the test set of endoscopic images, the highest values of the metrics AP@[0,25..0,75] equal to 98,4 and AP@0,50 equal to 98,6 were obtained for the neural network detector based on the YOLOv8 network. According to the results of comparing the proposed algorithms with analogues, the YOLOv8 assessment showed an increase in the results for the AP@[0.25..0.75] metric by 5.9 in searches with the previous model НАООYL. The results obtained can be used in the development of a video stream analysis system in an endoscopic system operating in real time during colonoscopy studies
Dataset Extension for Neural Networks Training for the Mitochondrial Segmentation Problem of the Brain Electron Microscopy
Authors: Yashin K.E. , Sokolov N.A. , Vasiliev Evgeni Pavlovich , Getmanskaya A.A.
Published: November 2023

This paper presents the adaptation of a diffusion neural network to generate a labeled synthetic dataset of electron microscopy of the brain. A model was trained can generate images and markup for them at the same time, which is an undoubted advantage of the chosen approach. Using the trained model, a set of labeled images was generated. The synthetic images are visually very similar to the original ones, the FID similarity metric between the synthetic and original datasets is 27.1. A simplified U-Net segmentation model trained on a mixed data set (original data + synthetic data) obtained a Dice score of 0.856 versus 0.858 on the original training set. Despite the good quality of synthetic data, their use in training the segmentation network does not improve the segmentation results.
Viewpoint Selection for Texture Reconstruction with Inverse Rendering
Authors: Sanzharov Vadim Vladimirovich , Frolov Vladimir Alexandrovich
Published: November 2023

Viewpoint selection methods have a variety of applications in different fields of computer graphics and computer vision, including shape retrieval, scientific visualization, image-based modeling and others. In this paper we investigate the applicability of existing viewpoint selection methods to the problem of textures reconstruction using inverse rendering. First, we use forward rendering to produce path-traced images of a textured object. Then we apply different view quality metrics to select a set of images for texture reconstruction. Finally, we perform material and texture reconstruction using these image sets and evaluate the quality of the results. We show that using viewpoint selection methods allows to achieve faster inverse rendering times while maintaining quality of the results.