Object-oriented Database Research Articles

Разработка способов представления на картах инфраструктуры для средств индивидуальной мобильности в г. Москве

The number of cyclists and users of personal mobility aids in Moscow is growing every year, while building the necessary facilities, providing security and managing the cycling network has not always kept pace with such rapid growth. The construction of infrastructure for means of individual mobility involves planning and designing it depending on the places of attraction of target audiences (universities, transport hubs, parks and the most popular streets for cyclists). At the same time, a cartographic vision of the problem is necessary at all stages. A review of works on the possibilities of depicting cycling infrastructure and the movement of cyclists on the streets of the city shows little experience in presenting this topic on maps. The main function of existing maps is to display the actual position of linear and point objects of cycling without a spatial analysis of their position. The article shows the possibilities of infrastructure mapping for means of individual mobility and solves the problem of finding reliable and up-to-date sources of statistical and cartographic data. The information collected in the course of urban and field surveys of the urban space of Moscow was processed and systematized. A database of bicycle infrastructure objects has been formed, which includes vector and raster representations of data, the results of field and statistical studies. Based on it, methods for visualizing the obtained data have been developed. The paper formulates the basic requirements for the cartographic basis for creating infrastructure maps, shows various techniques and ways of depicting phenomena, which made it possible to clearly demonstrate the results of the study. Considering the visualization possibilities found, maps of the cycling infrastructure were compiled, highlighting its main elements and types.

60 років базам даних (заключна частина)

The article provides an overview of research and development of databases since their appearance in the 60s of the last century to the present time. The following stages are distinguished: the emergence formation and rapid development, the era of relational databases, extended relational databases, post-relational databases and big data. At the stage of formation, the systems IDS, IMS, Total and Adabas are described. At the stage of rapid development, issues of ANSI/X3/ SPARC database architecture, CODASYL proposals, concepts and languages of conceptual modeling are highlighted. At the stage of the era of relational databases, the results of E. Codd’s scientific activities, the theory of dependencies and normal forms, query languages, experimental research and development, optimization and standardization, and transaction management are revealed. The extended relational databases phase is devoted to describing temporal, spatial, deductive, active, object, distributed and statistical databases, array databases, and database machines and data warehouses. At the next stage, the problems of post-relational databases are disclosed, namely, NOSQL-, NewSQL- and ontological databases. The sixth stage is devoted to the disclosure of the causes of occurrence, characteristic properties, classification, principles of work, methods and technologies of big data. Finally, the last section provides a brief overview of database research and development in the Soviet Union.

CoRAE: Energy Compaction-Based Correlation Pattern Recognition Training Using AutoEncoder

Automatic Target Recognition (ATR) using Correlation Pattern Recognition (CPR) in IoT-based applications encounters limitations like limited memory and inadequate computational resources. One reason is the required quantity of reference templates for each target/object to cover all features of a target/object. To mitigate the issue of reference templates per target/object without accuracy degradation, this paper proposes <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">energy compaction-based CPR autoencoder-training</i> . Additionally, a newly proposed performance metric known as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Peak Energy Gain (PEG)</i> estimates the quality of the correlation plane and the feature compression capability CPR methods. The proposed, composite filtering strategy, Eigen Maximum Average Correlation Height (EMACH), and Extended Eigen Maximum Average Correlation Height ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">E</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> MACH) are vigorously validated using publicly available biometric and object image databases. By training a single reference template, the proposed training method achieves 97.97% mean accuracy with the second-best approach of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">E</i> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> MACH that attains 53.04% mean accuracy on the Pose Estimation Database. For bio-metric fingerprint verification, the mean Equal Error Rate (EER) of the proposed approach and the composite strategy is 3% and 29.69%, respectively on the FVC2002DB1A database. Similarly, the mean EER of the proposed approach and the composite strategy is 10.55% and 26.32%, respectively on the FVC2006IA database. For FEI faces dataset, the proposed method achieves 1.41% mean EER, and the composite filtering approach achieves 21.43% mean EER. On the University of Tehran Iris database, the proposed autoencoder-based methodology obtains 19.07%, and 18.07% mean EER on the left and right side iris instances, respectively. The comparative results for each dataset demonstrate superiority of AE-based method over the state-of-the-art CPR methods.

Hybrid Graph Partitioning with OLB Approach in Distributed Transactions

Online Transaction Processing (OLTP) gets support from data partitioning to achieve better performance and scalability. The primary objective of database and application developers is to provide scalable and reliable database systems. This research presents a novel method for data partitioning and load balancing for scalable transactions. Data is efficiently partitioned using the hybrid graph partitioning method. Optimized load balancing (OLB) approach is applied to calculate the weight factor, average workload, and partition efficiency. The presented approach is appropriate for various online data transaction applications. The quality of the proposed approach is examined using OLTP database benchmark. The performance of the proposed methodology significantly outperformed with respect to metrics like throughput, response time, and CPU utilization.

Managing 3D GIS Data for Indoor Environment Using Property Graph Database

With the diversification of three-dimensional (3D) urban space data sources and data collection methods, the Open Geospatial Consortium published 3D spatial data standards in Geography Markup Language (GML). Among them, IndoorGML is a data model for expressing the topological relationship between indoor spaces with advantages in terms of semantic information storage and navigation applications. Conversion into a suitable binary file must be accomplished to use the IndoorGML documents through integration with other data. This study proposes a method of generating graph database objects from the documents of IndoorGML to promote usability and interoperability. The labeled property graph model is designed to reflect IndoorGML’s multilayered graph concept. Moreover, in the proposed graph model, the geometry of physical indoor spaces is segregated into separate surfaces. All elements from IndoorGML are managed with specific labels in Neo4j, the most dominant graph database. By applying the proposed method, the graph database is constructed using the officially distributed IndoorGML documents of three buildings. The number of generated graph objects is determined to confirm whether the IndoorGML features are accurately converted into graph database objects. Furthermore, the utility of the constructed graph database is verified through two scenario-based routing tests consisting of finding the optimal room with the lowest route cost and allocating indoor spaces for patrolling to outdoor security offices through indoor and outdoor data integration. In conclusion, this study confirms that the utility of IndoorGML can be promoted using a graph database system in data integration, data queries, and pathfinding applications while preserving data topology and interoperability.

Molecular Mechanism of L-Pyroglutamic Acid Interaction with the Human Sour Receptor.

Taste is classified into five types, each of which has evolved to play its respective role in mammalian survival. Sour taste is one of the important ways to judge whether food has gone bad, and the sour taste receptor (PKD2L1) is the gene behind it. Here, we investigated whether L-pyroglutamic acid interacts with sour taste receptors through electrophysiology and mutation experiments using Xenopus oocytes. R299 of hPKD2L1 was revealed to be involved in L-pyroglutamic acid binding in a concentration-dependent manner. As a result, it is possible to objectify the change in signal intensity according to the concentration of L-pyroglutamic acid, an active ingredient involved in the taste of kimchi, at the molecular level. Since the taste of other ingredients can also be measured with the method used in this experiment, it is expected that an objective database of taste can be created.

Astronomical Surveys, Catalogues, Archives, Databases and Virtual Observatories

Astronomical surveys and catalogs are the main sources for the discovery of new objects, both Galactic and extragalactic. Archives and Databases maintain billions of astronomical objects; planets, comets, stars, exoplanets, nebulae, galaxies, and quasars. We will review the current background in astronomy for further all-sky or large-area studies. Modern astronomy is characterized by multiwavelength (MW) studies (from gamma-ray to radio) and Big Data (data acquisition, storage, mining and analysis). Present astronomical databases and archives contain billions of objects observed at various wavelengths, and the vast amount of data on them allows new studies and discoveries. Surveys are the main source also for accumulation of observational data for further analysis, interpretation, and achieving scientific results. We review the main characteristics of astronomical surveys (homogeneity, completeness, sensitivity, etc.), compare photographic and digital eras of astronomical studies (including the development of wide-field observations), and describe the present state of MW surveys. Among others, Fermi-GLAST, INTEGRAL (gamma-ray), ROSAT, Chandra, XMM (X-ray), GALEX (UV), DSS1/2, SDSS, Hubble, Gaia (optical), 2MASS, IRAS, AKARI, WISE, Herschel (IR), NVSS and FIRST (radio) surveys and major astronomical archives and databases will be presented and discussed, as well as surveys and databases for variable and transit objects.

A tool for developing a plan for the renovation and remediation of cultural heritage buildings

Cultural heritage monuments are, to a large extent, public goods of collective consumption, and their preservation is in the public interest of the society as a whole. The benefits arising from the owner's investment and resulting from the existence and the use of a cultural heritage monument are usually not ``consumed'' solely by the owner, but, to a greater or lesser extent, by the whole society or a particular group. In the case of the renovation and remediation of cultural heritage buildings, the life-cycle costs are determined in the operational phase, before the intended renovation or remediation. They should be used to select an economically sustainable solution, with the maximum potential to preserve the cultural and historical value. The paper presents the application designed for the elaboration of plans for the renovation and remediation of cultural heritage monuments, developed in the form of a web interface. The application processes data at the level of individual structural elements. For faster and more comfortable users' work, a database of type objects is used, which combines primary data from the level of structural elements.

Object-based childhood history from museums to university: the Latvian project

ABSTRACT The project “Representation of Childhood at the Museums of Latvia, Integrated in the E-Learning Environment of Higher Education” was a response to the need for sources in the history of education that would accommodate the interests of students in educational sciences. The article aims at sharing the project experience in (1) mapping the history of childhood in museums, (2) building the digitised museum objects database, (3) integrating the database in learning environment, and (4) reflecting on the lessons learned through the project. The mapping was done in 30 museums, digitising 1190 artefacts and creating a “draft” database, which in 2021 was used by 74 master’s students in educational sciences at the University of Latvia. We concluded that object-based childhood interpretation entails subjectivism in both the creation of museum collections and the choice of objects for the database. The objects selected by students revealed that educational science students are interested in less attractive sources for exhibitions as educational documentation and statistics. The project findings draw attention to the gaps in childhood history, for example, children with special needs are still “invisible”, the material culture created by children themselves is poorly exhibited and the question about the 1990s as the “end” of childhood history in Latvia is open. The students’ work with the database revealed challenges in history didactics; for example, how to prepare students for the “translation” of modern educational concepts into the language of history. Further development of the education history database depends on technical solutions, as well as on engaging students in systematic feeding of the database.

Missing Person Identification using Machine Learning with Python

Abstract: With advances in computing and telecommunications technologies, digital images and video are playing key roles in the present information era. This system uses powerful python algorithm through which the detection and recognition of face is very easy and efficient. Human face is an important biometric object in image and video databases of surveillance systems. Detecting and locating human faces and facial features in an image or image sequence are important tasks in dynamic environments, such as videos, where noise conditions, illuminations, locations of subjects and pose can vary significantly from frame to frame. we want to identify the person based on face data base which we have already created in own data. After that we want to start identification of face using face recognition package. Finally, we will do comparison with data base and we will say weather that person is missing person or unknown person.

IoT Based on Potholes and Speed Breakers Detection and Alert System

In a world where 90 percent of people travel by road, the safety of the same becomes of utmost importance. And two of the most major issues a road traveler faces are Potholes and speed breakers. The total number of road accident deaths due to potholes in 2018, 2019, and 2020 stood at 2015, 2140 and 1471, respectively. Although speed breakers are intended to prevent traffic accidents, 49.6 per cent of crashes still happen in areas where there are speed breakers.&#x0D; This paper aims to present a method for locating, identifying, and documenting speed breakers and potholes. The suggested method will employ driving information collected by various sensors, such as vibrations, jerks, bumps, changes in distance from the base of the vehicle, etc., to detect and then store the location of the object in an online database. Additionally, a stream of images of the object spotted will be simultaneously taken and uploaded to a server, to analyze using an Image Detection model. This model will facilitate the live detection of potholes and speed breakers more accurately than previous solutions.&#x0D; Once this data is added to a database, it will be effectively used by government agencies to repair the roads as well as by daily commuters to avoid the route with more obstacles, when the database is supplied to mapping services like Google Maps.

OPRACOWANIE WSKAŹNIKÓW JAKOŚCI ŻYCIA W MIEŚCIE NA PODSTAWIE BAZ DANYCH PRZESTRZENNYCH

The subject of the study is the analysis of using the Topographic Objects Database (BDOT10k) and the Local Data Bank (BDL) to monitor sustainable development and quality of life in the city. The usefulness of this data was tested on the example of quality of life indicators in the city of Kielce and its neighborhood. The databases were analyzed in terms of their scope, relevance, and level of spatial aggregation. The study used the hierarchical analysis (AHP) and multi-criteria evaluation (MCE) method. The issue under consideration was presented in the form of a hierarchy, with a quality of life at the top. The lowest level of the hierarchy is formed by selected indicators defined in the standard ISO 37120. The methodology for calculating and visualization of each indicator is presented illustrating the diversity of life quality in the Kielce Functional Area.

Approximating the evolution of rotating moving regions using Bezier curves

The region interpolation methods proposed in the moving objects databases literature impose restrictions that can have a significant impact on the representation of the evolution of moving regions, in particular, when a rotation occurs between two observations. In this paper, we propose a data model for moving regions that allows moving segments to rotate and change their length during their evolution between two observations and uses quadratic Bezier curves to define the trajectories of their endpoints. This introduces a new class of moving regions called rotating moving regions (rmregions). We present algorithms for operations involving rmregions and we propose a strategy to allow different interpolation methods to be used in the context of moving objects databases by approximating the interpolations they create using rmregions. We demonstrate our strategy using a reference implementation and compare results obtained when using the strategy presented here and the region interpolation methods and the spatiotemporal operations proposed in the state-of-the-art. Experimental results show that our strategy can be used to complement the region interpolation methods proposed in the moving objects databases literature.

The detection of magnetic chemically peculiar stars using Gaia BP/RP spectra

Context. The magnetic chemically peculiar (mCP) stars of the upper main sequence are perfectly suited to studying the effects of rotation, diffusion, mass-loss, accretion, and pulsation in the presence of an organized stellar magnetic field. Therefore, many important models can only be tested with this star group. Aims. In this case study we investigate the possibility of detecting the characteristic 520 nm flux depression of mCP stars using low-resolution BP/RP spectra of the Gaia mission. This would enable us to effectively search for these objects in the ever-increasing database. Methods. We employed the tool of Δa photometry to trace the 520 nm flux depression for 1240 known mCP and 387 normal-type objects including binaries. To this end, we folded the filter curves with the BP/RP spectra and generated the well-established color-color diagram. Results. It is clearly possible to distinguish mCP stars from normal-type objects. The detection rate is almost 95% for B- and A-type objects. It then drops for cooler-type stars, which is in line with models of the 520 nm flux depression. Conclusions. The BP/RP spectra are clearly qualified to efficiently search for and detect mCP stars.

Developing a system for diagnosing diabetes mellitus using bigdata

Diabetes is among the socially significant diseases, which leads to high costs for the diagnosis and treatment of diabetes. Diagnosis and treatment of diabetes is currently one of the important tasks in medicine at the present stage of development of medical services. An important direction in the development of medical services for the population is the development and implementation of various problem-oriented information systems. Similar systems developed earlier did not cover the entire amount of heterogeneous information that is collected when diagnosing and prescribing the course of diabetes treatment, nor did they use technologies and cloud services as tools for Big Data. In this article, let’s make use of the predictive analytic to forecast and categorize the type of diabetes which offers an effective method for treating and curing patients at a reduced cost, with improved results such as affordability and availability. An information system platform has been developed and configured to manage the Hadoop cluster, as well as a non-relational database that uses and processes unstructured data in various formats. All experimental research, development of methods and algorithms, as well as solving computational problems were implemented using software languages for application development. The novelty lies in the research of distributed computing models that provide efficient execution of developed algorithms using the conceptual model of the processes of search, extraction and analysis of unstructured data in large data sets. The practical implementation of algorithms was carried out on the basis of methods of object-oriented programming and object-oriented databases

KEGG for taxonomy-based analysis of pathways and genomes.

KEGG (https://www.kegg.jp) is a manually curated database resource integrating various biological objects categorized into systems, genomic, chemical and health information. Each object (database entry) is identified by the KEGG identifier (kid), which generally takes the form of a prefix followed by a five-digit number, and can be retrieved by appending /entry/kid in the URL. The KEGG pathway map viewer, the Brite hierarchy viewer and the newly released KEGG genome browser can be launched by appending /pathway/kid, /brite/kid and /genome/kid, respectively, in the URL. Together with an improved annotation procedure for KO (KEGG Orthology) assignment, an increasing number of eukaryotic genomes have been included in KEGG for better representation of organisms in the taxonomic tree. Multiple taxonomy files are generated for classification of KEGG organisms and viruses, and the Brite hierarchy viewer is used for taxonomy mapping, a variant of Brite mapping in the new KEGG Mapper suite. The taxonomy mapping enables analysis of, for example, how functional links of genes in the pathway and physical links of genes on the chromosome are conserved among organism groups.

FAIR Digital Objects in Official Statistics

FAIR Digital Objects in Official Statistics

НЕМАТЕРІАЛЬНА КУЛЬТУРНА СПАДЩИНА УКРАЇНЦІВ (РЕГІОНАЛЬНИЙ АНАЛІЗ ПРОЯВУ)

The problems of fixation and preservation of the objects and phenomena related to the intangible cultural heritage of Ukraine are considered in the article. The history of mapping the ethnocultural monuments, especially in the realm of spiritual culture is revealed. An experience of popularization of the intangible heritage objects, as well as the concepts and approaches to the existence of a living tradition developed by scholars of the Institute of Geography of the National Academy of Sciences of Ukraine, is analyzed. Attention is drawn to such issues as ideological pressure on the customary and ritual culture of Ukrainians during the years of the totalitarian regime, as well as to the danger of the spread of pseudo-folklore phenomena, and the need to create an electronic database of the intangible cultural heritage objects. The problems of regional manifestations of ancient and living practices existence of customary culture and the requirement to substantiate more clearly the selection criteria with the aim to include the traditions, holidays and ceremonies, trades and handicrafts, monuments of music and song traditions in the national list.

Usefulness of OSM and BDOT10k Data for Developing Tactile Maps of Historic Parks

A map, being a scaled-down image of a fragment of the Earth, reflects the actual relationships between objects in a way that allows for comprehensive exploration of large areas. In particular, a map is an ideal tool for exploring the layout of historic parks, as it shows their character according to their style. Depending on the style of the parks, their maps will differ in terms of the appropriate selection of the scope of content and the system of cartographic signs. Nowadays, distribution maps of parks for the visually impaired are increasingly popular. Depending on the purpose of a map, it is essential to obtain the relevant spatial data before creating it. Spatial data are also important to convey knowledge about the form of the given park and its function, elements, small garden architecture, plant compositions, and garden arrangements. The purpose of this study is to assess the usefulness of OSM (OpenStreetMap) and BDOT10k (the Topographic Objects Database) data for the development of tactile maps of historic parks, with five garden styles. Data features, such as accessibility of spatial objects and descriptive attributes, including names that allow identification of the object type or completeness of object occurrence, were taken into consideration. The assessment was conducted for three levels of map detail and separately for each garden style. The results showed that almost half of the tactile maps’ content items could be taken from BDOT10k or OSM. The Data Usefulness Index (DUI) confirmed a slight advantage of BDOT10k, taking almost the same values as OSM (0.49:0.48 at the first level of map detail and 0.40:0.38 at the second level of map detail). Complementing information on park objects obtained from OSM and BDOT10k data with data from orthophotomaps or field measurements makes it possible to develop maps that convey information about the composition of a park as a whole and about the cultural assets that blind or visually impaired people have not yet been able to fully experience in a direct way.

Exploring Landscape Composition Using 2D and 3D Open Urban Vectorial Data

Methods and tools for assessing the visual impact of objects such as high-rises are rarely used in planning, despite the increase in opportunities to develop automated visual assessments, now that 3D urban data are acquired and used by municipalities as well as made available through open data portals. This paper presents a new method for assessing city visibility using a 3D model on a metropolitan scale. This method measures the view composition in terms of city objects visible from a given viewpoint and produces a georeferenced and semantically rich database of those visible objects in order to propose a thematic vision of the city and its urban landscape. As far as computational efficiency is concerned and considering the large amount of data needed, the method relies on a dedicated system of automatic data organization for analyzing visibility over vast areas (hundreds of square kilometers), offering various possibilities for uses on different scales. In terms of operational uses, as shown in our paper, the various results produced by the method (quantitative data, georeferenced databases and 3D schematic images) allow for a wide spectrum of applications in urban planning.