Implementation Of Database Research Articles

Compositional Analysis and Mechanical Recycling of Polymer Fractions Recovered via the Industrial Sorting of Post-Consumer Plastic Waste: A Case Study toward the Implementation of Artificial Intelligence Databases.

Nowadays, society is oriented toward reducing the production of plastics, which have a significant impact on the environment. In this context, the recycling of existing plastic objects is currently a fundamental step in the mitigation of pollution. Very recently, the outstanding development of artificial intelligence (AI) has concerned and continues to involve a large part of the industrial and informatics sectors. The opportunity to implement big data in the frame of recycling processes is oriented toward the improvement and the optimization of the reproduction of plastic objects, possibly with enhanced properties and durability. Here, a deep cataloguing, characterization and recycling of plastic wastes provided by an industrial sorting plant was performed. The potential improvement of the mechanical properties of the recycled polymers was assessed by the addition of coupling agents. On these bases, a classification system based on the collected results of the recycled materials' properties was developed, with the aim of laying the groundwork for the improvement of AI databases and helpfully supporting industrial recycling processes.

Plume: Efficient and Complete Black-Box Checking of Weak Isolation Levels

Modern databases embrace weak isolation levels to cater for highly available transactions. However, weak isolation bugs have recently manifested in many production databases. This raises the concern of whether database implementations actually deliver their promised isolation guarantees in practice. In this paper we present Plume, the first efficient, complete, black-box checker for weak isolation levels. Plume builds on modular, fine-grained, transactional anomalous patterns, with which we establish sound and complete characterizations of representative weak isolation levels, including read committed, read atomicity, and transactional causal consistency. Plume leverages a novel combination of two techniques, vectors and tree clocks, to accelerate isolation checking. Our extensive assessment shows that Plume can reproduce all known violations in a large collection of anomalous database execution histories, detect new isolation bugs in three production databases along with informative counterexamples, find more weak isolation anomalies than the state-of-the-art checkers, and efficiently validate isolation guarantees under a wide variety of workloads.

Prospects of Using Information Technologies in the Transformation of National Financial Reporting

This article covers the prospects of applying information technologies in the transformation of national financial reporting, their role and significance, achieving time and labor efficiency in the preparation of financial reports using software products, preventing errors when working with large volumes of data, and completing tasks faster and with higher quality using programs based on information technologies rather than traditional methods. Additionally, the article addresses issues such as creating opportunities for global access to data through the implementation of databases and cloud technologies. Additionally, the article mentions that the creation, presentation, interpretation, and transmission of a company's financial reports using digital technologies become much more efficient and faster. It is also mentioned that the integrity and reliability of a company’s financial reports are enhanced through software created with digital technologies. Additionally, these technologies allow for faster report generation and provide users with wide-ranging opportunities to access the reports from anywhere and make decisions. Additionally, the article discusses issues such as transforming the company’s accounting system based on international financial reporting standards and thereby entering the global market with accurate and reliable information. It is specifically emphasized that the application of international financial reporting standards in the preparation of financial reports, studying their importance and necessity, and researching their theoretical and methodological aspects, provide a priority in attracting users of these financial reports, mainly investors. Additionally, the article highlights that the presentation of transparent and fully disclosed information sets serves as a reliable source.

Information centralization and stock price crash risk: Cross-country evidence

Our study investigates whether access to corporate disclosure via a national database affects stock price crash risk. Exploiting the staggered implementation of national databases for corporate information dissemination (Officially Appointed Mechanisms, or OAMs) in the European Union countries, we find that stock price crash risk significantly decreases after regulated information disclosed by companies is required to be compiled in OAMs. Consistent with the notion that the centralization of regulated information allows investors to search and compare corporate disclosure across peer firms, we find that the observed effect is more pronounced in firms with more peer firms in the same industry. Further analyses show that this effect is stronger in firms with less transparent information environments and with more retail investors. Collectively, our study sheds light on the role of Regtech adoption in mitigating stock price crash risk.

Empowering Research With the American Heart Association Get With The Guidelines Registries Through Integration of a Database and Research Tools.

The American Heart Association's Get With The Guidelines (GWTG) has emerged as a vital resource in advancing the standards and practices of inpatient care across stroke, heart failure, coronary artery disease, atrial fibrillation, and resuscitation focus areas. The GWTG registry data have also created new opportunities for secondary use of real-world clinical data in biomedical research. Our goal was to implement a scalable database with an integrated user interface (UI) to improve GWTG data management and accessibility. The curation of registry data begins by going through a data processing and quality control pipeline programmed in Python. This pipeline includes data cleaning and record exclusion, variable derivation and unit harmonization, limited data set preparation, and documentation generation of the registry data. The database was built using PostgreSQL, and integrations between the database and the UI were built using the Django Web Framework in Python. Smaller subsets of data were created using SQLite database files for distribution purposes. Use cases of these tools are provided in the article. We implemented an automated data curation pipeline, centralized database, and UI application for the American Heart Association GWTG registry data. The database and the UI are accessible through a Precision Medicine Platform workspace. As of March 2024, the database contains over 13.2 million cleaned GWTG patient records. The SQLite subsets benefit researchers by optimizing data extraction and manipulation using Structured Query Language. The UI improves accessibility for nontechnical researchers by presenting data in a user-friendly tabular format with intuitive filtering options. With the implementation of the GWTG database and UI application, we addressed data management and accessibility concerns despite its growing scale. We have launched tools to provide streamlined access and accessibility of GWTG registry data to all researchers, regardless of familiarity or experience in coding.

Lethal effects and sex-specific tolerance of copper and cadmium in the buff-tailed bumble bee

Exposure to environmental pollutants, including trace metals, is a major driver of bee decline worldwide. While pesticides undergo standardised risk assessments (i.e., LD50) and the implementation of online databases, no such approaches exist for trace metals. Here, using acute oral exposure, we determined the LC50, LD50, and mass-standardised LD50 of copper and cadmium, essential and non-essential metals, respectively, in workers and males of the buff-tailed bumble bee. We also evaluated gut damage and sucrose consumption in workers post-exposure. Cadmium was more toxic than copper for workers at same doses, although both metals induced severe gut melanisation and reduced sucrose consumption at high concentrations. Males displayed higher tolerance to cadmium, but it was correlated to their higher body mass, emphasising the necessity for reporting mass-standardised LD50 for genuine sex comparisons in risk assessments. Our findings advocate for the establishment of databases focusing on metal-induced lethal effects on model bee species.

Design of Master Data Management in the Bank Using Consolidation Approach and Jaro Wrinkler

The main objective of this project is to introduce master data management into the PT XYZ database system through analysis, design, and implementation. A database life cycle (DBLC) approach, consisting of database analysis, design, implementation, and testing, is used for the design phase. Based on the analysis carried out, it was found that two databases belonging to PT XYZ did not have a master data management process, and there was an incomplete master data management and implementation process at PT XYZ. This project ended with the successful of implementation the master data management process, thereby reducing the time required for PT XYZ business process applications. So that all PT XYZ business process applications can produce clean and valid data.

Ontology Creation and Database Implementation for Lab-Scale Solid-State Battery Cells

New developments and publications on alkali metal solid-state batteries are being published at a high rate, with the total number of publications now in the thousands, but the search and analysis of the data in these publications is still largely done using key words and through careful reading of the article and the supporting information. The challenges of efficiently searching and extracting data from thousands of publications in a field are also present in other fields, such as perovskite solar cells, for which a large (>15,000) set of cell data has been entered into a database that continues to be updated.1 A database for alkali metal (e.g., based on Na+ and Li+ conduction) solid-state cells that could be easily searched and that facilitated advanced forms of data analysis could accelerate research progress, and is consistent with efforts such as definition of the “Principles of the Battery Data Genome” and the BIG-MAP project.2 In this talk, we describe our approach to creating an ontology and database for lab-scale solid-state cells, along with results to date. Key areas for the ontology include component material identities, material properties, component properties (e.g., active material loading, mass fractions, thicknesses), processing conditions for materials and the cell itself (e.g., ball milling time, sintering time), and both performance (e.g., rate capability) and degradation (e.g., cycle life). Results based on several hundred solid state cells in our database are presented in terms of histogram plots, violin plots, correlation plots, and other representations. We also describe our efforts to integrate our ontology and tool with broader efforts in the field, and to make it broadly useful to battery researchers.1. Nature Energy, volume 7, pages 107–115 (2022) and https://www.perovskitedatabase.com/2. Joule 6, 2253–2271, October 19, 2022 and https://www.big-map.eu/dissemination/battinfo

Preparing Cadastral Map Databases for Mosul District

Investigates the development and implementation of digital cadastral map databases for Mosul District, Iraq, addressing the transition from traditional paper-based systems to modern geospatial technologies. The research explores the integration of Geographic Information Systems (GIS), remote sensing, and Global Positioning System (GPS) technologies to enhance cadastral mapping processes. Encompass data collection from diverse sources, including high-resolution satellite imagery, aerial photography, and existing cadastral maps. A comprehensive analysis of data types— vector, raster, Triangulated Irregular Network (TIN), and tabular—is conducted to establish an optimal database structure. The study delineates the technical capabilities of GIS in data processing, spatial analysis, and model preparation, emphasizing the importance of data accuracy and consistency. A systematic approach to data entry, including map scanning, georeferencing, and digitization, is presented. The research outlines the creation of a multi-layered geographic database, incorporating both spatial and descriptive data. Protocols for database updating using satellite imagery and field surveys are developed, ensuring the currency and reliability of cadastral information. The results demonstrate significant improvements in data management, spatial analysis capabilities, and information accessibility compared to traditional methods. The study concludes that digital cadastral databases offer enhanced decision-making support for land administration and urban planning in Mosul District. Contributes to the body of knowledge on modernizing cadastral systems in developing regions, providing insights into technological integration, data standardization, and the challenges associated with transitioning to digital cadastral management systems. The findings have implications for policy makers and land administrators seeking to implement similar systems in comparable urban contexts.

TSDSystem: a framework to collect, archive and share time series data at volcanological observatories

This paper presents a framework designed to collect, archive, and share time series data coming from sensor networks at Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (Italy), which we have developed and called Time Series Database management System (TSDSystem). The framework proposes a flexible database model for the standardization of sensor networks data and implements an optimized technology for storage and retrieval of acquired time series data. It is designed for the implementation of multiparametric databases and then suitable for development in volcanological observatories worldwide. The proposed framework provides a web service to perform writing and reading data via a standard web communication protocol, which easily enables interaction with other instruments or automatic systems. All results provided by the TSDSystem web service are represented using common data formats in the context of online services. In particular, the station networks metadata representation follows a schema inspired by the International Federation of Digital Seismograph Networks, widely known in seismology. A web GUI (graphical user interface) is provided to test and document the web service. Additionally, basic built-in web applications are supplied with the web GUI to perform joint and synchronized time series data visualization as well as representation of stations on a geographical map. The web GUI also offers administration tools for data access policy management, creation of monitoring dashboards and data publication through web pages. The framework implements an authorization system that can be used to restrict both writing or reading operations. The TSDSystem can also be a useful tool for engineering surveillance systems. The implementing code of the framework is available with an open source license on a public repository together with a user manual.

Implementation of the pharmacovigilance database in the usage of antibiotics in a tertiary care hospital: A pilot study.

Antimicrobial resistance (AMR) has evolved into a severe public health issue that defies all current control strategies and needs multidisciplinary, creative solutions. Antimicrobial stewardship (AMS) activities demand a set of tools and abilities that can be used by health systems. In view of the growing AMR and the difficulty for the surveillance of it in the developing country, this study was conducted to incorporate pharmacovigilance (PV) in the AMS program. A cross-sectional pilot study was conducted to collect the PV database of antimicrobials induced adverse drug reactions (ADR) from the Adverse Drug Reactions Monitoring Center (AMC) of the institute for a period of 2 months from August 2022 to September 2022. The information from the database was analyzed to estimate the usage of antibiotics from the PV database from AMC and classified it under the Anatomical Therapeutic Chemical, to assess the rationality of the antimicrobial's usage based on "Access," "Watch," and "Reserve" (AWaRe) classification, and to assess the ADR of the antibiotics. The analysis was done by using the SPSS version 20.0 for Windows. The results showed that the prevalence of ADRs were more in adults' population with preponderance in female. The antibiotics usage was as per with World Health Organization standard and most of the antibiotics used were from the Access group of AWaRe classifications. Tetracyclines and penicillins were the most used antibiotic group of drugs. The number of patients included in the study was 70. Most of the causality assessment was "possible" (62.85%). In the study, almost 90% of the drug was withdrawn and 70% of the patients were in the recovering stage. Using existing PV approaches to address usage of antibiotics and AMR issues would allow PV to progress as a field, and governments will get a stronger return on their PV investments.

Efficient deep-learning model for predicting mechanical strength of carbon nanotube-reinforced cementitious composites: Database acquisition, framework development and implementation

In response to the growing demand for accurate models predicting the mechanical strength of carbon nanotube (CNT) reinforced cementitious composites, this study introduces a precise deep-learning model. The model, built upon a comprehensive dataset of 219 entries, incorporates 14 input variables considering various composites, cement types, and CNT characteristics. Notably, analysis of the data demonstrates a nuanced understanding of material properties, covering cementitious composites with compressive strength (CS) and flexural strength (FS) ranging from 15 to 140 MPa and 3–17 MPa, respectively. Employing a regularized deep learning neural network architecture, the model exhibits promising performance metrics, with the training dataset showcasing the lowest mean absolute error (MAE) of 2.036. The training and validation datasets demonstrate a high correlation coefficient (0.991 and 0.917, respectively). However, higher MAE values are observed for the testing and validation datasets, indicating potential limitations in generalization. Furthermore, the model's robustness is highlighted by its ability to surpass earlier studies in accuracy for validation datasets. The study elucidates a nonlinear trend in FS and the influence of CNT size on CS, with implications for material design and construction practices.

Pengembangan Sistem Informasi Perpustakaan Peminjaman dan Pengembalian Buku Berbasis Website Interaktif

Library SMA Negeri 1 Mlati still not accurate in data maintenance, so that impact on often happened mistake or not discipline in delay of return of book. In addition to obtaining information relating to the collection of books takes a long time. So that the System will run the System that can help librarians SMA Negeri 1 Mlati in the process of management of computerized data administration and System that can provide information to the librarian of SMA Negeri 1 Mlati for borrowers who have not returned the book. The purpose to facilitate officers in processing transactions and maintain data collection of books on the Library SMA Negeri 1 Mlati. The system development method used is the Prototype methodology which includes the identification of user needs, prototype creation, prototype testing, and prototype improvement. For data collection method using observation and interview method. For system model used is Context Diagram, Data Flow Diagram (DFD) and Entity Relationship Diagram (ERD). The software for the design and implementation of the program using Apache as a web server, mySQL as a database server, Sublime Text 3 as a writing editor programming language PHP and HTML. Results or output to be achieved that is generated library system that can handle data administration, data maintenance, and information borrower books on the library. The final stage is to implement an information system that includes the implementation of software, hardware, database and interface of the resulting system.

Организация информационно-аналитического обеспечения оперативно-розыскной деятельности органов внутренних дел по розыску лиц, пропавших без вести, в условиях контртеррористической операции и вооруженных конфликтов

The planning and implementation of operational search activities play a pivotal role in the search for missing persons amidst counter-terrorist operations and armed conflicts. Key to these efforts is the utilization of data that can aid in the identification or recognition of the missing individual. Such data includes physical descriptions in the form of verbal portraits or photographic impressions, basic identifying information, fingerprint cards, and handwriting samples. These pieces of information serve to individualize the sought-after person and can be instrumental in their identification. The establishment of new databases of operational search information, including databases of genomic codes of individuals, could prove to be a valuable tool in obtaining information about unidentified bodies and linking them to missing persons. However, the implementation of such databases raises a number of technical, legal, and ethical issues that must be considered. This article aims to examine the specifics of organizing information and analytical support for the operational activities of internal affairs bodies in the search for missing persons in conditions of counter-terrorist operations and armed conflicts, utilizing available resources accessible to operatives. In conclusion, the effective organization of information and analytical support is paramount in facilitating the search for missing persons within the challenging contexts of counter-terrorist operations and armed conflicts. Leveraging various data sources, including physical descriptions and emerging technologies like genomic databases, offers promising avenues for enhancing identification processes. However, the integration of such resources necessitates careful navigation of technical, legal, and ethical considerations. By addressing these complexities, internal affairs bodies can optimize their operational efforts and contribute significantly to resolving cases of missing individuals amidst complex security environments.

Exoesqueletos de Rehabilitación: una Revisión Sistemática de Literatura

The accelerated evolution of technology in the last decade has enabled breakthroughs in fields of science such as medicine, robotics, bionics and rehabilitation by integrating knowledge and techniques from these areas. Rehabilitation exoskeletons are examples of multidisciplinary integration in the development of physiotherapeutic intervention tools that have shown significant results in patients with neurological diseases. This systematic literature review presents the advances, developments and characteristics of these devices and their current situation, specifically those that have the greatest impact on their co-citation and co-occurrence so that the works integrated into the research are verifiable and reliable. This is done through the implementation of a methodology for the elaboration of the state of the art on the subject of rehabilitation exoskeletons, based on the implementation of scientific databases, systematised digital bibliometric tools and their systemic integration. The scientific literature on rehabilitation exoskeletons was compiled from papers published between January 2014 and 30 November 2023, which were retrieved from the Web of Science. The first stage was to define the inclusion and exclusion criteria in order to limit the search within the scientific database, and the second stage was to process the information and works obtained in order to process them using the CiteSpace software, as a result of this stage, the co-occurrence analysis was obtained, a graphical network was generated and a co-citation analysis, subsequently with the data obtained from the previous stages, the PRISMA method was implemented. As a third step, the results obtained from the 1511 publications and 108,512 reference citations dealing with rehabilitation exoskeletons are presented. A discussion of the main characteristics, advances, limitations, challenges and trends of these devices is presented.

Implementation of Relational Database in the STEAM-Problem Based Learning Model in Algorithm and Programming

Currently, digital technology is developing in all fields. The development of this technology certainly has a significant impact on the world of education. A suitable learning model is needed, especially in the Algorithm and Programming course, to face global challenges in the Industrial Revolution 4.0. Students are expected to have skills that include critical and creative thinking in solving problems, communication, and collaboration with the support of technology. The STEAM-Problem Based Learning model can be used in the Algorithm and Programming learning process with seven syntaxes: preparation and knowledge identification; problem identification; plan solution; create and test products; communicate; evaluation and feedback and giving rewards. All activities carried out in the learning process by lecturers and students can be stored in a database. This research attempts to determine the validity of the STEAM-Problem Based Learning database design, which will be implemented in the Algorithm and Programming course. The data analysis technique used is validity analysis, which is based on assessing the data obtained through a questionnaire or a questionnaire using a Likert scale. Data was processed using Aiken’s V validity coefficient formula to test the expert’s judgment. Assessment indicators include correctness, consistency, relevance, completeness, and minimality. The results of the study show that the validity test on the STEAM-Problem Based Learning database design is valid, so it is feasible to implement it in algorithm and programming learning.

Lessons learnt from the construction and implementation of a prospective ventral hernia database.

The New England VA Hernia Registry was created in 2011 to prospectively collect relevant details of ventral hernia repairs, with the intention to assess and improve long term outcomes. The goal of this study is to assess registry compliance. All ventral hernia operations performed in five VA hospitals between 2011-2022 were obtained. We assessed compliance at the hospital and surgeon level. 3,516 cases were performed. Overall compliance with registry entry was 37.5%, ranging from 10.8% to 67.2% across hospitals. At the hospital level, there was a negative correlation between average yearly hernia volume per surgeon and registry compliance (r2 = 0.53). Surgeon compliance varied within hospitals and over time. Registry compliance was low and highly variable. Lack of interest, incentives, oversight, and surgeon turnover are possible factors for noncompliance. Building a registry with these factors in mind, providing timely feedback, and conducting frequent audits may improve compliance.

Application of Machine Learning Modeling for the Upstream Oil and Gas Industry Injury Rate Prediction

Introduction: Yearly, the International Labor Organization report indicates many workplace accident occurrences. The degree of the happenings depends on the workplace environment setting and the incident regulatory measures implemented. By the nature of its work environment, the oil and gas upstream sector is susceptible to high incident rates. In the current fierce business competition and practices, improving productivity, quality, and other processes, such as Safety, is vital. Implementing well-designed safety procedures is the key to managing and reducing the risk level of workplace incidents. Methods: Recently, the application of Machine learning (ML) modeling for accident/injury prediction has been reported in the construction, mining, transport, and health sectors. Likewise, the objective of this paper was to implement three machine-learning-based models to predict injury rates in a drilling operation. The petroleum safety authority of Norway provided the datasets. First, the dataset was pre-processed, and then the selected features and target dataset were used for the modeling. Finally, the model prediction and performance accuracy analysis were performed. Results: Results showed that multivariable regression (MVR), Random Forest (RF), and Artificial Neural Network (ANN) machine learning algorithms-based models predict the test data with R2 values of 0.9576, 0.793, and 0.97036, respectively. Conclusion: As the common saying goes, 'prevention is better than cure.' For this, implementing methods such as improved work processes and Health, Safety, and Environment (HSE) mitigation procedures, workplace injuries, and accidents allow for reducing the risk level of workplace injuries. The application of integrated machine learning tools, along with carefully built-in workplace accident database implementation, will provide early detection and possible remedial precautions that can be taken to prevent workplace injuries/accidents/fatalities. However, extensive research and development are required to deploy the method in real life. Combining Machine Learning modeling and carefully designed safety measures is vital for successful and robust predictive tools.

Update of the Minimum Information About BIobank Data Sharing (MIABIS) Core Terminology to the 3rd Version.

Introduction: The Minimum Information About BIobank Data Sharing (MIABIS) is a biobank-specific terminology enabling the sharing of biobank-related data for different purposes across a wide range of database implementations. After 4 years in use and with the first version of the individual-level MIABIS component Sample, Sample donor, and Event, it was necessary to revise the terminology, especially to include biobanks that work more in the data domain than with samples. Materials & Methods: Nine use-cases representing different types of biobanks, studies, and networks participated in the development work. They represent types of data, specific sample types, or levels of organization that were not included earlier in MIABIS. To support our revision of the Biobank entity, we conducted a survey of European biobanks to chart the services they provide. An important stakeholder group for biobanks include researchers as the main users of biobanks. To be able to render MIABIS more researcher-friendly, we collected different sample/data requests to analyze the terminology adjustment needs in detail. During the update process, the Core terminology was iteratively reviewed by a large group of experts until a consensus was reached. Results: With this update, MIABIS was adjusted to encompass data-driven biobanks and to include data collections, while also describing the services and capabilities biobanks offer to their users, besides the retrospective samples. The terminology was also extended to accommodate sample and data collections of nonhuman origin. Additionally, a set of organizational attributes was compiled to describe networks. Discussion: The usability of MIABIS Core v3 was increased by extending it to cover more topics of the biobanking domain. Additionally, the focus was on a more general terminology and harmonization of attributes with the individual-level entities Sample, Sample donor, and Event to keep the overall terminology minimal. With this work, the internal semantics of the MIABIS terminology was improved.

The Role of GIS Data Post-Processing in the Environmental Assessment: The Case of Umbria, Italy

The increasingly complex dynamics of urban planning require an innovative approach to land use suitability analyses and environmental assessments. Traditionally, these disciplines have provided a critical foundation for sustainable urban development, but the current acceleration of change requires renewed attention to technology and innovation. The integration of advanced territorial data is emerging as a key element to enrich the analysis and mapping of the landscape. This type of data allows for an updated and objective view of reality, providing urban planners and decision makers with a dynamic tool to quickly adapt to evolving urban needs. The use of new technologies increases the accuracy and effectiveness of these analyses, enabling more efficient and sustainable urban planning. This article explores how innovation and technology are transforming the field of land use suitability analyses and environmental assessments and provides real-life examples of how advanced territorial data can be used to model the landscape more accurately in the case of Umbria, a region in Italy characterised by a rich cultural history and picturesque landscapes. Umbria, with its unique geography and delicate environmental balance, provides a fertile ground for exploring how the implementation of territorial databases can contribute to the responsible management of industrial activities. This case study represents an important first step in applying a QGIS and Python geoprocessing approach to these issues. The methodology starts with the creation of territorial data and includes a post-processing phase using Python. This integrated approach not only provides an updated and objective view of the landscape but also represents the first instance in the literature of a study applied to such a small and environmentally rich region as Umbria.