XML Database Research Articles

Thermodynamic modeling with uncertainty quantification using the modified quasichemical model in quadruplet approximation: Implementation into PyCalphad and ESPEI

The modified quasichemical model in the quadruplet approximation (MQMQA) considers the first- and the second-nearest-neighbor coordination and interactions, particularly useful in describing short-range ordering (SRO) in complex liquids such as molten salts, slag in metal processing, and electrolytic solutions. The present work implements the MQMQA into the Python based open-source software PyCalphad for thermodynamic calculations. This endeavor facilitates the development of MQMQA-based thermodynamic database with uncertainty quantification (UQ) and propagation (UP) using the open-source software ESPEI. A new database structure based on Extensible Markup Language (XML) is proposed for ESPEI evaluation of MQMQA model parameters. Using the KF-NiF2, KCl-NaCl-MgCl2, and CaCl2-CaF2-LiCl-LiF salt systems as examples, we demonstrate the successful implementation of MQMQA in PyCalphad through thermodynamic calculations of Gibbs energy, equilibrium quadruplet fractions, and phase diagram, as well as database development with UQ and UP using ESPEI. Furthermore, as an application of the present implementation, both the LiF–TbF3 and LiF-HoF3 systems have been modeled by MQMQA for the first time, which are in good agreement with experiments. The present implementation hence offers an open-source capability for performing CALPHAD modeling for complex liquids with SRO using MQMQA plus a new XML database structure.

Occupational health assessment summary designed for semantic interoperability

BackgroundGeopolitical and economic crises force a growing number of people to leave their countries and search better employment opportunities abroad. Meanwhile, the highly competitive labor market provides opportunities for employees to change workplaces and job positions. Health assessment data collected during the occupational history is an essential resource for developing efficient occupational disease prevention strategies as well as for ensuring the physical and psychological well-being of newly appointed workers. The diversity in data representation is source for interoperability problems that are insufficiently explored in the existing literature. ObjectivesThis research aims to design a worker’s occupational health assessment summary (OHAS) dataset that satisfies the requirements of an international standard for semantic interoperability in the use case for exchanging extracts of such data. The focus is on the need for a common OHAS standard at EU level allowing seamless exchange of OHAS at both cross-border and at the worker’s country of origin level. ResultsThis paper proposes a novelty systematic approach ensuring semantic interoperability in the exchange of OHAS. Two use cases are explored in terms of UML sequence diagram. The OHAS dataset reflects common data requirements established in the national legislation of EU countries. Finally, an EN 13606 archetype of OHAS is designed by satisfying the requirements for semantic interoperability in the exchange of clinical data. Semantic interoperability of OHAS is demonstrated with realistic use case data. ConclusionsThe designed static, non-volatile and reusable information model of OHAS developed in this paper allows to create EN 13606 archetype instances that are valid with respect to the Reference model and the datatypes of this standard. Thus, basic activities in the OHAS use case can be implemented in software, for example, by means of a native XML database as well as integrated into existing information systems.

Strategies and Approaches for Generating Identical Extensive XML Tree Instances

In recent years, XML has become the de facto internet wire language. Data may be organized and given context with the use of XML. A well-organized document facilitates the transformation of raw data into actionable intelligence. In B2B1 applications, the XML data is sent and created. This implies the need for fast query processing on XML data. The processing of XML tree sample queries (XTPQ) that provide an efficient response (also known as sample matching) is a topic of active study in the XML database field.DOM (Parser) may be used to transform an XML document into a tree representation. Extensible Markup Language (XML) query languages like XPath and XQuery use tree samples (twigs) to express query results.XML query processing focuses mostly on effectively locating all instances of twig 1 samples inside an XML database. Numerous techniques for matching such tree samples have been presented in recent years. In this study, we survey recent developments in XTPQ processing. This summary will begin by introducing several algorithms for twig sample matching and then go on to provide some background on holistic techniques to process XTPQ.

Parallel processing of E-Atheer algorithm using pthread paradigm

The development in the field of computer technology, and the increase in the growth rate of database, alongside the extraction of certain data from a huge pool of database involve intricate and complex processes. The processes comprise text mining, pattern recognition, retrieval of information and text processing. Thus, the need for enhancing the performance of string matching algorithms is required, which is considered as one of the challenges to the researchers. Consequently, one of the resolution to address this problem is the parallelization for exact string matching algorithms. In this study, we implemented the parallel exact string matching algorithm termed as E-Atheer with multi-core processing utilizing Pthread (POSIX) for the reduction of time consumption. The Pitch, XML, Protein, and DNA database types are utilized to test the impact of the proposed parallel algorithm. The parallelization algorithm obtained positive results in the parallel execution time, and a more superior expediting capabilities, in comparison to the sequential result. The Pitch database indicated optimal results in parallel execution time, and when utilizing long and short pattern lengths. The DNA database indicated optimal speedup performance when utilizing short and long pattern length, meanwhile the XML and Protein on the other hand indicated the worst results.

Searching for Researchers: an Ontology-based NoSQL Database System Approach and Practical Implementation

This work presents the design and implementation of two web-based search systems, Busc@NIMA and Quem@PUC. Both systems allow the identification of research and development projects, besides existing competencies in laboratories and departments involving professors and researchers at PUC-Rio University. Our applications are based on a list of search-related terms that are matched to the dataset composed of PUC-Rio’s Lattes CVs offered courses, information from administrative systems, and specific keywords that are input by the professors/researchers themselves. To integrate all the needed data, we consider multiple database and search technologies, such as XML, RDF, TripleStores, and Relational Databases. Search results include professor’s name, academic papers, teaching activities, contact links, keywords, and laboratories of those involved with the subject represented by the set of keywords input. We describe the main features that show how our systems work.

Implementation of a workbench platform for the management of smart contracts in BlockChain nodes on Azure Cloud

Objectives: Analyze, design and build backend components (web API, XML web service and database) and frontend (website) with Microsoft technology that allow the integration of a functional workbench platform to automate the launch of compiled smart contracts in blockchain nodes hosted in Azure Cloud so that they can be used by companies in general. Methodology: The SCRUM methodology was applied for the agile development of the technological products of the backend and frontend, because it adapted very well to the nature of this research, since in each iteration there was always an update of the tools, programming components, testing and configuring services to achieve goals. Contribution: It is shown that the development platform integrated by the solidity language, Azure cloud blockchain, the Visual Studio .Net IDE and the SQL Server database manager allowed to design and build a blockchain workbench platform easily exploitable by companies to validate their processes and generate transparency in the handling of their information.

Construction and Knowledge Mining of Traditional Chinese Medicine Ancient Books Bibliographic Abstracts Database Based on Genetic Algorithm and BP Neural Network

With the rapid development of modern science technology and Internet technology, the establishment of a unified and standardized bibliographic summary database to realize the exchange and resource sharing of ancient Chinese medicine bibliography, is the inevitable trend of ancient Chinese medicine bibliography digital service. Firstly, this paper formulates the bibliographic metadata specification of traditional Chinese medicine ancient books (TCMAB), extracts each cataloging file into an XML document in line with the bibliographic metadata specification of TCMAB. Secondly, this paper realizes the unified description of ancient book resources in the database system of TCMAB, uses the native XML database eXist to store and manage the XML documents of all traditional Chinese medicine ancient book resources, and integrates the multimedia data with XML data. Finally, genetic algorithm and BP neural network are used for knowledge mining and discovery, the overall model design of TCMAB bibliographic abstracts database system is proposed based on the construction process of knowledge map. The system platform adopts B/S mode, eXist database management system, PowerSSP streaming media and video server for audio video processing.

Modeling a Born-Digital Factoid Prosopography using the TEI and Linked Data

Although the TEI has traditionally been used for encoding text, its combination of structured and semi-structured data has made it a compelling choice for born-digital, linked-data resources as well. Our intent here is to demonstrate the advantages it offers for digital prosopographies along with a model that can be used for them. Syriac Persons, Events, and Relations (SPEAR) is a born-digital prosopography project in the field of Syriac studies. Where traditional prosopographies focused on prose descriptions of individual persons of significance, SPEAR follows recent developments in research methodologies that instead produce prosopographical factoids. Factoids are structured data about persons drawn from the analysis of historical texts. Most factoid prosopographies use relational databases to model data. Instead, SPEAR uses a customized TEI schema to model factoids that can be queried and visualized in an XML database as well as serialized in HTML for human viewers and in RDF for data sharing. The TEI’s provisions for structured and semi-structured data make it ideal for encoding data from heterogeneous historical source material. Moreover, its linking capabilities connect SPEAR data to related data sets. By modeling prosopographical factoids, and not the source texts themselves, SPEAR offers an example of how a born-digital, data-oriented approach to using the TEI can circumvent some of the challenges posed by the tree structure of XML. It also disrupts traditional understandings of data and stand-off markup through combining linked open data approaches with the use of the TEI.

APLIKASI PENCARIAN JASA PANGKAS RAMBUT DI BANDAR LAMPUNG MENGGUNAKAN ALGORITMA A-STAR BERBASIS ANDROID

Along with the development of car technology for various purposes. Such as online motorcycle taxis, delivery of goods, delivery services and so on. This potential can be developed in other lines such as barbershop services. By using an android-based application designed with the A* Algorithm, it can help the community to find the nearest barbershop route. It can also help barbershops to promote barber shops. The system is designed using extreme programming and UML methods and is built using the JAVA, XML, PHP and MySQL database programming languages. Then the application is tested using the blackbox method so that the application can run optimally.

Performance Appraisal Management System of University Administrators Based on Hybrid Cloud

Aiming at the problems of poor functionality, high occupancy, and low real-time performance of the currently designed performance appraisal management system for university administrators, a performance appraisal management system for university administrators based on hybrid cloud is designed. According to the characteristics of hybrid cloud technology, the overall functional requirements and feasibility of the system are analyzed, and the assessment scheme of administrative personnel according to the provisions of relevant documents is analyzed. The performance appraisal index system is designed using an analytic hierarchy process. Using the hybrid cloud architecture and B/S mode based on each component as a service model and J2EE development framework, the basic information management subsystem of administrative personnel, performance appraisal information management subsystem, information analysis and data mining subsystem, and platform system management subsystem are developed. Using XML technology and database technology, the system is integrated with the performance appraisal management system of administrators in colleges and universities. Through the design of data flow diagram and E-R diagram, the design of performance appraisal management system for university administrators based on hybrid cloud is realized. The experimental results show that the proposed method has good functionality, can effectively reduce the system occupancy, and can improve the real-time performance of the system.

EnzymeML-a data exchange format for biocatalysis and enzymology.

EnzymeML is an XML-based data exchange format that supports the comprehensive documentation of enzymatic data by describing reaction conditions, time courses of substrate and product concentrations, the kinetic model, and the estimated kinetic constants. EnzymeML is based on the Systems Biology Markup Language, which was extended by implementing the STRENDA Guidelines. An EnzymeML document serves as a container to transfer data between experimental platforms, modeling tools, and databases. EnzymeML supports the scientific community by introducing a standardized data exchange format to make enzymatic data findable, accessible, interoperable, and reusable according to the FAIR data principles. An application programming interface in Python supports the integration of software tools for data acquisition, data analysis, and publication. The feasibility of a seamless data flow using EnzymeML is demonstrated by creating an EnzymeML document from a structured spreadsheet or from a STRENDA DB database entry, by kinetic modeling using the modeling platform COPASI, and by uploading to the enzymatic reaction kinetics database SABIO-RK.

Open-source feature detection for non-target LC-MS analytics.

Non-target screening techniques using high-resolution mass spectrometers become more and more important for environmental sciences. Highly reliable and sophisticated software solutions are required to deal with the large amount of data obtained from such analyses. Processing of high-resolution LC-HRMS data was performed upon conversion into an open, XML-based data format followed by an automated assignment of chromatographic peaks using the open-source programming language R. Raw data from three different LC-HRMS systems were processed as a proof of principle. We present a simple and straightforward algorithm to extract chromatographic peaks from previously m/z-centroided data based on the open-source programming language R and C++. The working principle and processing parameters are explained in detail. A ready-to-use script is provided in the supporting information. The developed algorithm enables a comprehensible automated peak picking of non-target LC-MS data. Application to three completely different HRMS raw data files showed reasonable False Positives and False Negatives detection and moderate calculation times.

Ζητήματα σχεδιασμού και υλοποίησης ηλεκτρονικών λεξικών της νέας ελληνικής

This paper presents the design and compilation of two online specialized dictionaries of Modern Greek: (1) Modern Greek Words of Ancient Origin and Changed Meaning (MAG) http://www.ocean.upatras.gr/mag/ and (2) Dictionary of Youth Slang http://lexislang.neurolingo.gr/index.php. Those dictionaries are “collaborative”, built by university students according to specific lexicographic guidelines. For the implementation of the two applications, which carried out with continuous formative evaluation, the prototyping method was used. Their construction was based on the free-to-use HTML, XML, Javascript, PHP languages and MySQL database and the applications are running on World Wide Web. Both of them seem to have on the one hand a potential for the timeless recording of the youth language and for the utilization of the content in the language course of the last grades of primary and secondary school, on the other.

PubMed Central as a platform for the survival of open-access biomedical society journals published in Korea

Twenty-one years have passed since PubMed Central (PMC) launched. The present case study describes Korean editors’ history of participation in PMC and their contributions to PMC. The three main turning points in the history of Korean editors’ involvement with PMC were as follows: first, the production of PMC XML files and deposition starting in 2008; second, thorough evaluations of applying journals since 2014; and third, the feasibility of non-English journals being indexed in PMC starting in 2019. The importance of PMC is further shown by the fact that KoreaMed Synapse, a full-text XML database of biomedical journals in Korea that was launched in 2007, was created by benchmarking PMC. Scholarly societies or institutes publish 724 (34.2%) of the 2,119 PMC journals without embargo in June 2021. Out of those 724 journals, 127 (17.5%) are published in Korea. PMC has helped local journals receive more citations from researchers worldwide, increasing their likelihood of being indexed in international databases. The number of submissions from international researchers has increased, thereby making it possible for journals to achieve international diversity. As the best full-text platform of biomedical journals, PMC has provided an excellent opportunity for biomedical journal editors in Korea to change their journals’ language to English and produce full-text JATS (Journal Article Tag Suite) XML files. These factors have made Korea the second-ranked country in terms of no-embargo PMC journals published by academic societies or institutes.

A State of the Art of Databases to Improve the Storage Efficiency on Cloud Computing

The distributed computing is huge gatherings of remote servers are organized to permit the incorporated information stockpiling. It has the access of computer services, resources and can be classified as public, private and reserved. In this study, we explored various types of Data bases used in cloud computing with respect to the category of Knowledge database, XML database, Online databases and Real-Time databases to improve the storage and data efficacy.

A Study on Image Search System using Semantics Based on Smartphone

Image semantic retrieval has been a crux to bridge "semantic gap" between the simple visual features and the abundant semantics delivered by a image. Effective image retrieval using semantics is one of the major challenges in image retrieval. We suggest a semantic retrieval and clustering method of image using image annotation user interface. And also design and implement a image semantic search management system that facilitates image management and semantic retrieval, which fully relies on the MPEG-7 standard as information base, and using a native XML database, which is Berkeley DB XML.

The Forgotten Document-Oriented Database Management Systems: An Overview and Benchmark of Native XML DODBMSes in Comparison with JSON DODBMSes

In the current context of Big Data, a multitude of new NoSQL solutions for storing, managing, and extracting information and patterns from semi-structured data have been proposed and implemented. These solutions were developed to relieve the issue of rigid data structures present in relational databases, by introducing semi-structured and flexible schema design. As current data generated by different sources and devices, especially from IoT sensors and actuators, use either XML or JSON format, depending on the application, database technologies that store and query semi-structured data in XML format are needed. Thus, Native XML Databases, which were initially designed to manipulate XML data using standardized querying languages, i.e., XQuery and XPath, were rebranded as NoSQL Document-Oriented Databases Systems. Currently, the majority of these solutions have been replaced with the more modern JSON based Database Management Systems. However, we believe that XML-based solutions can still deliver performance in executing complex queries on heterogeneous collections. Unfortunately nowadays, research lacks a clear comparison of the scalability and performance for database technologies that store and query documents in XML versus the more modern JSON format. Moreover, to the best of our knowledge, there are no Big Data-compliant benchmarks for such database technologies. In this paper, we present a comparison for selected Document-Oriented Database Systems that either use the XML format to encode documents, i.e., BaseX, eXist-db, and Sedna, or the JSON format, i.e., MongoDB, CouchDB, and Couchbase. To underline the performance differences we also propose a benchmark that uses a heterogeneous complex schema on a large DBLP corpus.

Wireless Network Communication in the XML Metadata Storage of Wushu Historical Archives

The wireless communication network has a huge promotion effect on data processing. As an important standard for internet data transmission, XML markup language is currently widely used in the internet. The rapid development of XML has brought fresh blood to the research of database. This article is aimed at studying the application of wireless network communication in the storage of the XML metadata database of Wushu Historical Archives. One part uses data load‐balancing algorithms and two‐way path constraint algorithms to conduct research on the metadata storage of XML databases, such as document size, document loading, and document query. Combining wireless technology and comparing with SGML and HTML, it highlights the flexibility and importance of XML database. The other part analyzes the XML database of Wushu Historical Archives itself and uses questionnaire surveys combined with the experience of 30 users randomly checked to provide constructive suggestions for the construction of XML database, such as strengthening the operation page design, text, and graphics. The experimental results show that the time consumed by the XML database in the case of bidirectional path indexing is 0.37 s, and the time consumed in the case of unidirectional path indexing is 0.27 s. This data shows that the application of wireless network communication technology has played an important role in the easy update and flexibility of the XML database. The data load capacity presented by the two path indexes is inconsistent; the current experience of XML database mainly focuses on the copy of the database quantity.

Automatic Arabic Named Entity Extraction and Classification for Information Retrieval

This article tries to explain our rule-based Arabic Named Entity recognition (NER) and classification system. It is based on lists of classified proper names (PN) and particularly on syntactico-semantic patterns resulting in fine classification of Arabic NE. These patterns use syntactico-semantic combination of morpho-syntactic and syntactic entities. It also uses lexical classification of trigger words and NE extensions. These linguistic data are essential not only to name entity extraction but also to the taxonomic classification and to determining the NE frontiers. Our method is also based on the contextualisation and on the notion of NE class attributes and values. Inspired from X-bar theory and immediate constituents, we built a rule-based NER system composed of five levels of syntactico-semantic combination. We also show how the fine NE annotations in our system output (XML database) is exploited in information retrieval and information extraction.

Development of EEG measurement and processing system in LabVIEW development environment

AbstractOur research team has developed a system and methodology for measuring psycho-physiological parameters, which can be used to determine the level of fatigue and fitness of the person being measured. This article describes the electroencephalography (EEG) part of this system. This article covers the technical and mathematical background of EEG measurement, the selection and implementation of the measurement tool in the development environment, and the development of the measurement and processing algorithm. The result is a system that can detect, digitize, and process the digitized signal from the brain, and save the processed signal in an XML database.