Raster Image Research Articles

«Большие данные» цифрового архива: диалог с растровой рукописью

The article reflects the current trends in working with the digital heritage of Russian literature, examines the process of forming virtual archives as a gradual accumulation of the “big data” of scientific research, i. e. unrecognized information array of raster documents containing tens of thousands of images. The research analyzes the specifics of scientific work in the field of ego-documentary heritage that arose at the turn of the 20th – 21st centuries (a corpus of diary entries, workbooks, notebooks, correspondence), the principles of publication and modern standards of digitization of archival heritage. The study and practicing of the three most promising virtual resources on the history of Russian literature of the mid-19th – first half of the 20th centuries allows to formulate specific tasks and methods of visualization of a large corpus of raster images of archival documents, as well as previously untapped possibilities of search engine automation. Much attention is paid to the transition from the graphical elements of the raster image of the manuscript to semantic ones, which allow the use of data mining elements for an unrecognized data array.

VULNERABILIDADE AMBIENTAL NO ENTORNO DO MONUMENTO NATURAL DO ITABIRA, ES, BRASIL

ABSTRACT The institution of biological value areas through the creation of Natural Protected Areas is an essential tool for protecting the country’s environmental resources to face advanced anthropic development in natural areas, either to increase agriculture production or for economic growth. Environmental vulnerability studies combined with geotechnological tools have been vital to identifying the most vulnerable areas and consequently help Conservation Units protection. This study aimed to analyze environmental vulnerability at the buffer zone of Itabira Natural Monument (MONAI) in Cachoeiro de Itapemirim, Brazil. The necessary methodological steps for this study were as follows: a) Photointerpretation of land use; b) Anthropic variables selection; c) Application of Euclidean distance function in variables vector images; d) Application of fuzzy membership function in variables raster images; e) Application of Analytical Hierarchical Process (AHP); and f) Spatial classification of environmental vulnerability around MONAI. Land use conflicts reveal a relevant presence of pasture areas, representing 49.80% of the buffer zone. This fact corroborates with its Euclidean distance value, which showed the lowest linear value, 836 meters. Eight anthropic variables have been incorporated, highlighting crops, urban areas, exposed soil and pasture. Jenks natural breaks defined five vulnerability classes. According to the results, 57.14% of the entire MONAI buffer zone is represented by the high and very high classes. The outdated law creation of MONAI and the need for a management plan result in a vulnerable buffer zone. The present study can support management plan formulation and assist MONAI’s buffer zone delimitation.

Feature Extraction Method of EEG Signals Evaluating Spatial Cognition of Community Elderly with Permutation Conditional Mutual Information Common Space Model.

In order to improve the traditional common space pattern (CSP) algorithm pattern in EEG feature extraction, this study proposes a feature extraction method of EEG signals based on permutation conditional mutual information common space pattern (PCMICSP), which used the sum of the permutation condition mutual information matrices of each lead to replacing the mixed spatial covariance matrix in the traditional CSP algorithm, and its eigenvectors and eigenvalues are used to construct a new spatial filter. Then the spatial features in the different time domains and frequency domains are combined to construct the two-dimensional pixel map, Finally, a convolutional neural network (CNN) is used for binary classification. The EEG signals of 7 community elderly before and after spatial cognitive training in virtual reality (VR) scenes were used as the test data set. The average classification accuracy of the PCMICSP algorithm for pre-test and post-test EEG signals is 98%, which was higher than that of CSP based on CMI (conditional mutual information), CSP based on MI (mutual information), and traditional CSP in the combination of four frequency bands. Compared with the traditional CSP method, PCMICSP can be used as a more effective method to extract the spatial features of EEG signals. Therefore, this paper provides a new approach to solving the strict linear hypothesis of CSP and can be used as a valuable biomarker for the spatial cognitive evaluation of the elderly in the community.

The effect of red fruit oil (Pandanus conoideus Lamk.) emulgel on angiogenesis and collagen density in incisive wound healing in mice (Mus musculus).

Pandanus conoideus Lamk. or commonly known as red fruit oil (RFO) can be used to accelerate wound healing because it contains tocopherols, carotenoids, oleic acid, linoleic acid, and linolenic acid. The RFO in this study was formulated in the form of an emulgel because it has the most convenient and effective drug delivery system. The aims of this study were to determine the activity of RFO emulgel on increasing the amount of angiogenesis and collagen density in incised wound healing and to determine the optimal dose of RFO emulgel to increase the amount of angiogenesis and collagen density in incised wound healing. This was a true experimental study with a posttest only control group design that included five treatment groups: a positive control group (10% povidone-iodine), a negative control (gel base), and three groups that varied the concentration of RFO emulgel used at 5%, 10%, and 15%. Parameters observed were the amount of angiogenesis using Image Raster software and the percentage of areas of collagen density using ImageJ software. The data were analyzed using a one-way ANOVA test and continued with the least significant difference test. The results of this study showed that RFO emulgel was able to increase the amount of angiogenesis and collagen density in the wound healing process with P = 0.000. An increase in the amount of angiogenesis and collagen density occurred in mice treated with RFO compared to the positive and negative control groups. It can be concluded that RFO emulgel has activity toward increasing the amount of angiogenesis and collagen density in the wound healing of mice incisions. The optimal dose concentration of RFO emulgel for increasing the amount of angiogenesis and collagen density in incision wound healing was shown in RFO emulgel with a concentration of 15%.

Cryoprotective Effects of Longan Honey on Preantral Follicle Integrity of Rat Ovary Post Vitrification

BACKGROUND: Longan honey (LH) has the potential as a natural extracellular cryoprotectant to maintain the integrity of intact preantral follicles against the cryoinjury during ovarian vitrification. OBJECTIVE: This research determined the cryoprotective effects of logan honey on preantral follicles integrity of rat ovary post-vitrification. MATERIALS AND METHODS: After vitrification, the follicle index was determined by observing the ovarian histological sections made using the paraffin method with hematoxylin-eosin staining and analyzed using Optilab 3.0 and Image Raster software. RESULTS: The results showed that the combination of ethylene glycol (EG) with LH and a dose variation of 7.5%-15% (KP1-KP4) increased the density of follicles, the number of intact follicles in G2 and G3, with a decrease in the atretic follicles in G1 better compared to the use of EG only (KKP1-KKP2). The differences in the histological structur e of preantral follicles affected the doses of LH needed by each type of follicle to maintain the integrity of the follicular structure from cryoinjury effects. The comparison of the G2 total follicle index values were KKP1 (90.7±18.3), KKP2 (115.6±9.9) < KP1 (193.6±10.7), KP2 (189.3±10.5), KP3 (182.2±27.1) and KP4 (169.4±8.8). Among the variations in the dose of LH 7.5%-15%, the highest increase in the G3 index value was found in primary (51.653±9.791), tertiary (43.119±8.786), secondary (33.885±4.745), and primordial (28.670±2.516) follicles of KP3 (7.5% of LH). CONCLUSION: The primary and tertiary follicular stages maintain the best integrity and can be used after the vitrification of rat ovaries.

A dataset of water transparency of Sanya River based on Sentinel-2 data during 2019–2021

As one of the most important water quality parameters on the radar screen of environmental protection sectors, water transparency reveals the turbidity degree of water and plays an important role in the primary productivity of water body and water ecosystem. As an independent island water system, Hainan Province has abundant surface inland water resources and plentiful river runoff. However, due to the influence of dry and wet monsoons and topography, the aquatic systems are characterized by uneven spatial and temporal distribution, and there are few studies on the water quality of inland water bodies on Hainan Island. In this study, we took Sanya River in Sanya, Hainan Province as the study area, and used the QAAv6-based semi-analytic model to retrieve the water transparency of Sanya River in time series from 2019 to 2021 based on the GEE cloud computing platform and the massive Sentinel-2 surface reflectance data stored in Google Cloud. With regard to the extraction of dynamic water area from Sanya River, we adopted the algorithm combining the normalized water body index NDWI with OTUS automatic threshold segmentation to extract the small river water. The data are stored in GeoTiff raster format, and the pixel transparency value and coordinate information are stored at the same time for easy reading and analysis by relevant GIS software. The inversion of long time series transparency based on the GEE cloud database is highly efficient. The dataset can serve as valuable scientific evidence for the water quality monitoring, water pollution control, and aquatic ecological protection of Sanya River.

An algorithm for steganographic embedding of encrypted files in raster images

The aim of this paper is proposing a method for the application of algorithms for hiding an encrypted file inside of a digital image for cybersecurity purposes. The originality of the method is expressed in the possibility of studying the mathematical algorithms for creating computer graphics. The development of a comprehensive algorithm should contribute to the practical realization of the method proposed. It emphasizes on built-in algorithms in software systems for creating computer graphics and the advantages of steganographic embedding by opensource products that hides any archive file in a digital image. Its application contribution is supported by practical examples of software hiding and archiving an encrypted file in a graphic image.

A methodology for empirical research and analysis in the field of cybersecurity

This article is considered to be a continuation of a publication by the author devoted to an algorithm for steganographic embedding of encrypted files in raster images (Yearbook Telecommunication, №9, 2022). The aim of this paper is proposing a methodology for empirical research and analysis on the field of cybersecurity which to contribute to various areas in cybersecurity. Its originality is expressed in the joint application of methods for research and analysis realized by various simulation environments for conducting experiments. This methodology has a specific structure as it is conditionally divided into two major parts depending on the type of the simulation process and software products used – a study of the direct impact of cyberattacks on communication networks by the method of the agent-based modelling and a study of potential steganography attacks using software for simulation of Artificial Neural Networks (ANNs) for the purposes of steganalysis.

Automatic Segmentation of Bulk Material Heaps Using Color, Texture, and Topography from Aerial Data and Deep Learning-Based Computer Vision

This article proposes a novel approach to segment instances of bulk material heaps in aerial data using deep learning-based computer vision and transfer learning to automate material inventory procedures in the construction-, mining-, and material-handling industry. The proposed method uses information about color, texture, and surface topography as input features for a supervised computer vision algorithm. The approach neither relies on hand-crafted assumptions on the general shape of heaps, nor does it solely rely on surface material type recognition. Therefore, the method is able to (1) segment heaps with “atypical” shapes, (2) segment heaps that stand on a surface made of the same material as the heap itself, (3) segment individual heaps of the same material type that border each other, and (4) differentiate between artificial heaps and other objects of similar shape like natural hills. To utilize well-established segmentation algorithms for raster-grid-based data structures, this study proposes a pre-processing step to remove all overhanging occlusions from a 3D surface scan and convert it into a 2.5D raster format. Preliminary results demonstrate the general feasibility of the approach. The average F1 score computed on the test set was 0.70 regarding object detection and 0.90 regarding the pixelwise segmentation.

SKILLS OF WORKING WITH PHOTO AND VIDEO MATERIALS AS A COMPONENT OF TEACHER'S ICT COMPETENCE IN DISTANCE LEARNING

The article deals with the urgent problem of increasing the level of teacher's information, communication and technological competence in the conditions of the use of all levels of distance learning technologies in educational institutions. The article considers the essence of the concept of teacher's ICT competence and establishes that its necessary component is the ability to present educational material, using the necessary ICT tools for this.
 The results of a survey of teachers of the Ukrainian language and literature, as well as physics, astronomy and computer science, conducted during the postgraduate training courses for teachers organized at Zhytomyr Ivan Franko State University during September-December 2021, are presented. As a result of the survey, it was found out which teaching materials have been used by the teachers in the process of distance learning, and what with difficulties they meet during the lessons in a distance format. It was found that the majority of teachers have used ready-made presentations, illustrative and video materials taken from the Internet, and the greatest difficulties for them were the creation of their own photo or video materials and multimedia presentations.
 It is proposed to hold thematic classes with teachers during their postgraduate training courses. The content of the classes is given, namely: the peculiarities of working with Internet catalogs of photo and video files; the review of the most popular online services for creating infographics, editing raster and vector images; the technology of preparation and installation of video materials; the artistic approach to building the composition of the frame and the psychology of its perception by the viewer.
 Thus, the implementation of the proposed approaches in the practice of the institutions that carry out postgraduate education of teachers will contribute to the development of ICT competence in the teachers, which will positively affect the quality of conducting educational and extracurricular activities in the conditions of distance learning. The perspective of further research is to study the possibilities of increasing the level of ICT competence in the teachers by using online learning management systems.

Image Processing Based Pattern Recognition and Computerized Embroidery Machine

In the last decades, embroidery getting much attention in industries and academics. Although the technique is very old, it is still very much adopted. The current era of machine learning and smart devices makes this method even more attractive, easy to adopt and high accuracy. The proposed research work aims to highlight the implementation of new smart devices in this field, and the work is based on microcontrollers. Adopting the proposed work will be very easy and feasible to transform from the old sewing machine to a new smart method. Using smart devices, it is very easy and precise to get the embroidery fulfilling the user's demands. It gives simple raster images, which are used to convert into digital images to portray any new product. The current work is a novel idea of generating simple images rather than complicated ones, which are difficult to draw. In our method, we introduce the digitization process to input any image file used for vectorizing raster images, where vector images can easily convert into a DST embroidery file, a commonly used embroidery format originally from Tajima. It also has a Gcode file. The machine runs on a Gcode file which can be easily generated and runs on a product.

Two-Dimensional Block Trees

Abstract The Block Tree is a data structure for representing repetitive sequences in compressed space, which reaches space comparable with that of Lempel–Ziv compression while retaining fast direct access to any position in the sequence. In this paper, we generalize Block Trees to two dimensions, in order to exploit repetitive patterns in the representation of images, matrices and other kinds of bidimensional data. We demonstrate the practicality of the two-dimensional Block Trees (2D-BTs) in representing the adjacency matrices of Web graphs, and raster images in GIS applications. For this purpose, we integrate our 2D-BT with the $k^2$-tree—an efficient structure that exploits clustering and sparseness to compress adjacency matrices—so that it also exploits repetitive patterns. Our experiments show that this structure uses 60–80% of the space of the original $k^2$-tree, while being 30% faster to three times slower when accessing cells.

PENGOLAHAN CITRA AQUA MODIS UNTUK PEMBUATAN PETA ZONA TANGKAPAN IKAN PERAIRAN MUARA KINTAP KALIMANTAN SELATAN

Potency fish in an area can be predicted based on the condition of oceanographic waters, namely by utilizing sea surface temperature data. This research utilizes sea surface temperature from the Aqua MODIS image acquisition in 2018 in identifying potential areas of fish catch zone. The purpose of the study was to prove the remote sensing technology digital image processing method for making sea surface temperature maps tested with survey data in the field hot spot productivity fishing ground 2015. The surface grids system method is a structure matrix used for recording relations between the topology contained between data points implicitly. Utilization surfer software as a means of digital data conversion process raster image into metric vector data. This technique aims to analyze spatial objects based on the area (boundary). Spatial snalysis with overlay technique visualizes the selected zone in isoline at 29.5°C - 31°C. This empirical evidence is used as a reference for making maps from january to june 2018. Based on spatial analysis, fish catch zones in march, april and may are potential times in the sea waters of Kintap subdistrict, Tanah Laut District. Processing methods of digital images using aqua image MODIS are proven to be applicable as a method of making a fishing ground zone map. Presented on a scale of 1:1.000.000 on A3 paper. The results of spatial measurements show that the largest area of the potential fishing ground zone is in april, reaching 11.188,29 Km2.

Создание растров высокой информативности по данным лазерного сканирования и аэрофотосъемки

The paper is focused on scenario and terrain modeling using the results of aerial laser scanning combined with digital aerial photography. The advantages and disadvantages of these technologies are discussed in regard to the construction of large-scale topographic maps. The generalized sequence of cameral processing aerial survey data is investigated. Based on our research, we believe that developing a combined technique of presenting Lidar survey and aerial photography materials is feasible; it could simplify and speed up the operator`s (cartographer`s) work. The novelty of the research is the formation of algorithms for creating original raster images containing more information on the terrain in each section than the orthophotoplane familiar to the interested user. The criteria for the object composition of materials are worked out taking into account the specifics of the methods under consideration, variants of information combinations are formulated for broader opportunities of analyzing and interpreting the data on the territory. Various approaches to the implementation of these ideas are shown. Examples of testing developments are given.

A Comparative Analysis of Drivers Impacting Urban Densification for Cross Regional Scenarios in Brussels Metropolitan Area

Our research aims at unveiling the various drivers that can have an impact on urban densification. Unlike the usual logistic modelling techniques, our study considers multi-level built-up densities ranging from low to high built-up density. The commonly used dataset for a number of present studies is based on raster images. Our study uses vector-based cadastral data to create maps for the years 2000, 2010 and 2020 in order to better trace densification. Furthermore, our study addresses the situation of a metropolitan area, Brussels, that spreads over three different regions that are developing independent land-planning policies. Since the state reform of 1993, Belgium has undergone a significant political transformation with a decentralization of land-planning policies from the state level to regional authorities. This reform allowed a progressive divergence of planning policies between the three regions, i.e., Flanders, the Brussels Capital Region and Wallonia. According to our findings, all the controlling factors exhibit distinct variation over all their density classes for the three regions. This may be due to differences in socioeconomic, territorial, and regulatory factors. For Flanders and the Brussels Capital Region, slope and distance to roadways are the most significant drivers explaining densification, whereas densification in Wallonia is predominantly influenced by land-use policies, especially the zoning regime. These results highlight the impact of considering cross-regional divergences in the implementation of planning policies at the metropolitan level, especially in those metropolitan areas that are expanding into different regions with divergent planning policies.

COMPARISON OF CLASSICAL AND INNOVATIVE METHODS OF WEAKLY CORRELATED INFORMATION PATTERNS SEARCH IN BITMAP IMAGES

The article presents a classification of weakly correlated information patterns in raster images searching methods, a comparative analysis of the effectiveness of classical and innovative methods using deep learning technologies, confirmed by experiment.

APPLICATION OF AHP AND GIS FOR OPTIMAL SOLAR SITE IDENTIFICATION IN MADHESH PROVINCE, NEPAL

Solar-based renewable energy adoption is in its early stage in the power system of Nepal complying with its commitment to carbon neutrality. The government of Nepal has declared a goal of setting up solar power plants of at least 200 MW in Madhesh Province, but the selection of optimal sites will be the decisive factor in achieving this goal. Therefore, rigorous investigation is necessary for optimal site selection. A three-step framework combining the Analytic Hierarchy Process (AHP) and the Geographical Information System (GIS) has been adopted to identify the optimal location for solar power plant installation in Madhesh Province. The framework includes the creation of weighted individual raster images for the different criteria, images of restricted areas for solar installation, and a combination of all the rasters into a single raster using GIS-based software. The weights of the criteria and sub-criteria have been evaluated using the AHP model, which is an expert judgments-based model. The criteria considered were solar irradiance, annual mean temperature, distance from the road, distance from the substation, distance from the urban area, elevation, aspect, and land use. The results were graded from the least preferred area to the most highly suitable area. The most highly suitable areas were in the Saptari, Siraha, Dhanusa, and Mahottari districts, while the districts in the western region of the province had less suitable areas. Thus, the province’s eastern region is most suitable for installing solar power plants.

Objects outline delineation by nonliniear filtration methods for boundary pixels

A processing of border pixel from pixel map originate problem while work with outline objects segmentation algorithm on bitmap images, which are based on 2D convolution operation. The problem correspond with addition set of pixels which are outside pixel matrix border of processing image. This problem is actual also in other algorithms, which have a common feature – 2D convolution operation. The level of importance are defined by multi used nonlinear filters to border pixels and then union a few images without distortions at the boundaries. The existing methods of pixel set redefining on pre processing step are primitive and affects on subsequent stages of processing. This affects exist between methods of redefining border pixels and algorithms of outline objects segmentation: Sharra, Pruitta, Sobel. The object of investigation is pixel map of halftone image. The subject of investigation is relation assessment between algorithms of outline objects segmentation with methods redefining border pixels. The main target is describing of features special methods to redefining border pixels which positively affecting the subsequent evaluation of the responses for this pixels by algorithms of outline objects segmentation. Analysis, the influence of the algorithm for the outline objects segmentation on the boundary pixels from the preliminary selection of methods of redefinition is carried out by example of combining several satellite images along the outline of urban infrastructure. For simplicity and by necessary of large data volume visualization (pixel half tone matrix size) presented graphs: halftone codes for redefining and border pixels, pixels requests for the algorithm of outline objects segmentation. By analysis criteria and characteristics of an effective method of redefining boundary pixels are described with correspond affects on algorithms of outline objects segmentation on bitmap images.

Measuring Photon Rings with the ngEHT

General relativity predicts that images of optically thin accretion flows around black holes should generically have a “photon ring”, composed of a series of increasingly sharp subrings that correspond to increasingly strongly lensed emission near the black hole. Because the effects of lensing are determined by the spacetime curvature, the photon ring provides a pathway to precise measurements of the black hole properties and tests of the Kerr metric. We explore the prospects for detecting and measuring the photon ring using very long baseline interferometry (VLBI) with the Event Horizon Telescope (EHT) and the next-generation EHT (ngEHT). We present a series of tests using idealized self-fits to simple geometrical models and show that the EHT observations in 2017 and 2022 lack the angular resolution and sensitivity to detect the photon ring, while the improved coverage and angular resolution of ngEHT at 230 GHz and 345 GHz is sufficient for these models. We then analyze detection prospects using more realistic images from general relativistic magnetohydrodynamic simulations by applying “hybrid imaging”, which simultaneously models two components: a flexible raster image (to capture the direct emission) and a ring component. Using the Bayesian VLBI modeling package Comrade.jl, we show that the results of hybrid imaging must be interpreted with extreme caution for both photon ring detection and measurement—hybrid imaging readily produces false positives for a photon ring, and its ring measurements do not directly correspond to the properties of the photon ring.

<strong>Effectiveness of natural lip balm cinnamon <em>(Cinnamomum burmannii)</em> in accelerating the incision wound healing process in <em> rattus norvegicus </em> </strong>

ABSTRACT Introduction: Cinnamomum burmannii is commonly used in the treatment and is thought to be an anti-inflammation medicinal herb that may hasten recovery. Lip wound healing is a critical need for aesthetic performance. The purpose of this study is to evaluate the efficacy of natural lip balm C. Burmannii has been shown to speed up the healing of incision wounds in rats (Rattus norvegicus). Methods: This research was carried out in the laboratory biomedical Faculty of Medicine, Universitas Islam Bandung. In twenty-seven male rats weighing 200-300 g, a lip mucous incision of 10 mm length and 4 mm depth was surgically created. Simple random sampling was used to divide the animals into three treatment groups based on wound treatment after lip incision (The control group applied distillation water, the first group applied a lip balm placebo/base, and the second group applied natural lip balm C. burmannii) and then divided into three observation times (days 3rd, 7th, and14th). A lip biopsy was performed during each observation time to determine the success of the therapy. The macroscopic examination was carried out by counting the number of lip wounds that were closed around, while the microscopic examination was carried out by counting epithelialization with a Leica microscope and image raster software. Result: The length of the lip wound has greatly decreased in the C. Burmannii group with a p-value of 0,048 (p<0.05, and epithelialization was comparable across the board. Conclusion: The use of Cinnamomum burmannii natural lip balm is effective in accelerating lip wound healing by bringing the lip wound closer together. Effectiveness of Natural lip balm Cinnamon (Cinnamomum burmannii) in accelerating the incision wound healing process in Rattus norvegicus.Keywords: natural lip balm cinnamomum burmannii; wound closer; epithelialization