Database Applications Research Articles

The Role of Database Applications of Digital Archive Management in The Era of Society 5.0

We will encounter many technologies in the 4.0 revolution era, such as cloud computing, artificial intelligence, the internet, 5G, digitalization, and big data. All of these technologies have potential in the world of education. Based on information about some of the problems faced by teachers at ASPAPI Member Vocational Schools in the DKI Jakarta area, they must be addressed as soon as possible as a solution to increasing knowledge, abilities, and skills in running database applications on digital archives as one of the development and utilization of information and communication technology in the Industrial Revolution 4.0 era and the 5.0 social era. Therefore, the community service team tries to offer solutions to these problems through the following main activities: 1) increasing the understanding and skills of ASPAPI Member Vocational High School teachers in the DKI Jakarta area, 2) increasing abilities in teaching and learning activities for digital archives, especially the use of database applications. The method used for providing training consists of planning, action execution, observation, and reflection. We generate an application called Dive Apps, where these apps can manage archives with a digitalization system and can also be used by teachers in archival learning.

A self-study on identification of etiology of Anemia in pregnancy

Anemia in medical literature could be defined as when levels of hemoglobin are below two standard derivation of the mean for age and gender of patients. During pregnancy many women lacks the sufficient amount of iron which is needed for 2 & 3 trimesters due to significant changes in increase in volume of blood to support the growth of baby, person could suffer from anemia. Based on several researches conducted it have been stated that anemia is one of the most common complications which could occur in pregnancy.A systemic self-study was planned to determine and review the possible cause of Anemia during pregnancy. With the application of electronic databases we searched PubMed, Google Scholar, Web of Science, Clinical Trial Gov, Medline Plus, health line, John Hopkins Medicine which were published in English language. This systemic self-study have reviewed the facts which were published earlier to determine the cause of anemia during pregnancy. Vast analysis was made to determine the cause of anemia during pregnancy.We observed and concluded the fact that anemia during pregnancy occurs due to iron and folate deficiency. In more than 50 percent of studies conducted in pregnant women, we observed that one who have less adequate diet and did not received any prenatal iron and folate supplement have the chances to suffer from iron deficiency and folate deficiency anemia.We conclude by delivery of very important message that adequate iron and folate intake is very crucial for both mother and child during pregnancy. Healthcare professionals must provide proper nutritional advice and essential supplementation which is required at their first consultation with mother’s which lowers and minimalizes the risk of anemia related complications in future.

Establishment and Application of a General Back-Analysis Database for Determining the Mechanical Parameters of Surrounding Rock

Establishment and Application of a General Back-Analysis Database for Determining the Mechanical Parameters of Surrounding Rock

Design of Web-Based Hajj Manasik Supervision Certification Information System

In the discussion of this research, the motivation to design a certification information system at the Regional Office (Kanwil) of the West Java Ministry of Religion seeks to resolve, and reduce the problem of the certification system which is not yet effective and far from efficient. The activities of implementing certification for offline (face-to-face) Hajj ritual supervisors, and processing certification data traditionally affect the results of recording certification and implementing the assessment process. Thus, the proposed system is generated through a website-based platform and is run online. The research method uses the System Development Life Cycle (SDLC) with the Waterfall model approach which consists of 5 stages, namely, a) Analysis b) Design c) Implementation d) Maintenance e) Planning. The programming language used is (PHP), and the database application uses a data processor (Mysql) as the database (RDBMS). In addition, to support this system design tool, it uses the UML (Unifed Modeling Language) method by using two diagrams according to design needs, namely Use Case Diagrams and Activity Diagrams. This research produces a Web-Based Certification Information System design that can simplify the certification implementation process, as well as simplify the presentation of certification data and its processing. The system of certification of Manasik Hajj supervisor have been test with a method. Black box testing is the most method to ensure the application is suitable scenario test. This Web-Based Hajj Manasik Supervisor Certification Information System at the West Java Ministry of Religion Regional Office makes it easier to improve the implementation of certification. The design of this system can reduce in addition to overcoming the obstacles of implementing certification to be more accurate.

Food Composition Data and Tools Online and Their Use in Research and Policy: EuroFIR AISBL Contribution in 2022.

Food, nutrition, and health are linked, and detailed knowledge of nutrient compositions and bioactive characteristics is needed to understand these relationships. Additionally, increasingly these data are required by database systems and applications. This communication aims to describe the contribution to databases and nutrition fields as well as the activities of EuroFIR AISBL; this member-based, non-profit association was founded to ensure sustained advocacy for food information in Europe and facilitate improved data quality, storage, and access as well as encouraging wider exploitation of food composition data for both research and commercial purposes. In addition to the description of its role and main objectives, a snapshot of EuroFIR AISBL's activities over the years is also given using a quantitative research literature analysis approach. The focus of this communication is to provide descriptions and updates of EuroFIR's online tools, i.e., FoodEXplorer, eBASIS, and PlantLIBRA, by highlighting the main uses and applications. Integrating food-related infrastructures and databases, following standardized and harmonized approaches, and considering interoperability and metrological principles are significant challenges. Ongoing activities and future plans of EuroFIR AISBL are highlighted, including, for instance, work within the Food Nutrition Security Cloud (FNS-Cloud) to make food, nutrition, and (food) security data more findable, accessible, interoperable, and ultimately reusable.

Construction and application of time-effect assessment database for experiments on war-traumatized animals

Abstract Background High-quality real war trauma data are important, but they are still lacking. Using the database to realize the networked, systematic, standardized, and dynamic management of war injury animal experimental data can provide a real and reliable supplement for the research of war injury treatment. Methods Through demand analysis, module design, architecture design, compilation and debugging, and other processes, JAVA language development tools were used to develop a time-effect assessment database for experiments on war-traumatized animals, where the browser/server architecture (B/S architecture) is used as the technical architecture and SQL Server as the database management system. Results A time-effect assessment database for experiments on war-traumatized animals that features reasonable structural design, rich data resources, and convenient use has been established, in which case efficient collection, storage, display, retrieval, and management of animal experimental data have been achieved. At present, the database is running well and has good data quality.

Application of ecosystem-specific reference databases for increased taxonomic resolution in soil microbial profiling.

Intensive agriculture systems have paved the way for a growing human population. However, the abundant use of mineral fertilizers and pesticides may negatively impact nutrient cycles and biodiversity. One potential alternative is to harness beneficial relationships between plants and plant-associated rhizobacteria to increase nutrient-use efficiency and provide pathogen resistance. Plant-associated microbiota profiling can be achieved using high-throughput 16S rRNA gene amplicon sequencing. However, interrogation of these data is limited by confident taxonomic classifications at high taxonomic resolution (genus- or species level) with the commonly applied universal reference databases. High-throughput full-length 16S rRNA gene sequencing combined with automated taxonomy assignment (AutoTax) can be used to create amplicon sequence variant resolved ecosystems-specific reference databases that are superior to the traditional universal reference databases. This approach was used here to create a custom reference database for bacteria and archaea based on 987,353 full-length 16S rRNA genes from Askov and Cologne soils. We evaluated the performance of the database using short-read amplicon data and found that it resulted in the increased genus- and species-level classification compared to commonly use universal reference databases. The custom database was utilized to evaluate the ecosystem-specific primer bias and taxonomic resolution of amplicon primers targeting the V5-V7 region of the 16S rRNA gene commonly used within the plant microbiome field. Finally, we demonstrate the benefits of custom ecosystem-specific databases through the analysis of V5-V7 amplicon data to identify new plant-associated microbes for two legumes and two cereal species.

The Construction and Application of Dynamic Population Database Based on “Suishenma Code”

The construction and application of dynamic population database based on“Suishenma code”,Based on the community, units, buildings, residential areas, residential buildings and public places existing “changsuo code”. It makes use of image recognition, wireless encryption, big data and cloud storage technology to make it become the terminal of mobile personnel data collection, recognition and processing analysis. Meanwhile, the real-time dynamic matching database of people and houses is recorded and generated to form the corresponding relationship between people and places of activity. The construction of the system mainly covers the interior of buildings such as residential areas, units and houses with intensive human activities, social cases and high incidence of livelihood cases, make up the"Xueliang、 Tianyan、Anke Project" monitoring blind spots, and can be used for the prevention and control of the epidemic and other emergencies trace source and early warning. The construction of this program serves the following areas: Tianyan project, major emergencies, housing management, special crowd management, public publicity, residents services and government services.

Assessing the effectiveness of the NIST DART-MS Forensics Database and Data Interpretation Tool for designer drug screening with alternative instrumentation

The increasing prevalence of designer drugs has contributed towards the adoption of rapid screening techniques, such as direct analysis in real time-mass spectrometry (DART-MS). Recently, the National Institute of Standards and Technology (NIST) developed a DART-MS Forensics Database and Data Interpretation Tool (DIT) to assist practitioners with the interpretation of seized drug mixtures. However, this resource was only designed for DART ionization coupled with AccuTOF high-resolution mass spectrometers. This study assesses the effectiveness of the NIST DART-MS Forensics Database and DIT for mixture interpretation using other soft ionization sources, such as electrospray ionization (ESI), and coupling DART to an Agilent 6530 quadrupole time-of-flight (Q-TOF) mass spectrometer. As the seized drug community continues to shift towards the use of in-source collision-induced dissociation (IS-CID) with single-stage mass spectrometers coupled with soft ionization sources, it is imperative to understand the similarity of the generated IS-CID fragment ion spectra and the effectiveness of the DIT for seized drug screening using instrumentation other than the DART-AccuTOF.Pearson product-moment correlations (PPMCs) revealed a high degree of spectral similarity between the ESI-IS-CID and DART-IS-CID fragment ion spectra collected across a range of activation conditions. The 95% confidence interval for the average highest PPMC coefficient across the 12 designer drugs in this study was 0.9295 ± 0.0031. More importantly, nearly identical mixture interpretation results were obtained when the ESI-IS-CID and DART-IS-CID fragment ion spectra were analyzed with the DIT. In all cases, the DIT was able to identify a potential library match with at least two match types between the low and high IS-CID spectra for all compounds present in each mixture. Demonstrating the potential applicability of the NIST DART-MS Forensics Database and DIT for the screening of seized drug mixtures using instrumentation other than the DART-AccuTOF provides support for the expanded applicability of this freely available resource.

FSOLAP: A fuzzy logic-based spatial OLAP framework for effective predictive analytics

Nowadays, with the rise in sensor technology, the amount of spatial and temporal data increases day by day. Fast, effective, and accurate analysis and prediction of collected data have become more essential than ever. Spatial Online Analytical Processing (SOLAP) emerged to perform data mining on spatial and temporal data that naturally contains the hierarchical structure used in many complex applications. In addition, uncertainty and fuzziness are inherently essential elements of data in many complex data applications, particularly in spatial–temporal database applications. In this study, FSOLAP is proposed as a new fuzzy SOLAP-based framework to compose the benefits of fuzzy logic and SOLAP concepts and is extended with inference capability to the framework to support predictive analytics. The predictive accuracy and resource utilization performance of FSOLAP are compared using real data with some well-known machine learning techniques such as Support Vector Machine, Random Forest, and Fuzzy Random Forest. The extensive experimental results show that the FSOLAP framework for the predictive analytics of various spatiotemporal events in big meteorological databases is considerably more accurate and scalable than using conventional machine learning techniques.

The Development and Application of a HPTLC-Derived Database for the Identification of Phenolics in Honey.

This study reports on the development and validation of a HPTLC-derived database to identify phenolic compounds in honey. Two database sets are developed to contain the profiles of 107 standard compounds. Rich data in the form of Rf values, colour hues (H°) at 254 nm and 366 nm, at 366 nm after derivatising with natural product PEG reagent, and at 366 nm and white light after derivatising with vanillin–sulfuric acid reagent, λ max and λ min values in their fluorescence and λ max values in their UV-Vis spectra as well as λ max values in their fluorescence and UV-Vis spectra after derivatisation are used as filtering parameters to identify potential matches in a honey sample. A spectral overlay system is also developed to confirm these matches. The adopted filtering approach is used to validate the database application using positive and negative controls and also by comparing matches with those identified via HPLC-DAD. Manuka honey is used as the test honey and leptosperine, mandelic acid, kojic acid, lepteridine, gallic acid, epigallocatechin gallate, 2,3,4-trihydroxybenzoic acid, o-anisic acid and methyl syringate are identified in the honey using the HPTLC-derived database.

Online schema evolution is (almost) free for snapshot databases

Modern database applications often change their schemas to keep up with the changing requirements. However, support for online and transactional schema evolution remains challenging in existing database systems. Specifically, prior work often takes ad hoc approaches to schema evolution with "patches" applied to existing systems, leading to many corner cases and often incomplete functionality. Applications therefore often have to carefully schedule downtimes for schema changes, sacrificing availability. This paper presents Tesseract, a new approach to online and transactional schema evolution without the aforementioned drawbacks. We design Tesseract based on a key observation: in widely used multi-versioned database systems, schema evolution can be modeled as data modification operations that change the entire table, i.e., data-definition-as-modification (DDaM). This allows us to support schema almost "for free" by leveraging the concurrency control protocol. By simple tweaks to existing snapshot isolation protocols, on a 40-core server we show that under a variety of workloads, Tesseract is able to provide online, transactional schema evolution without service downtime, and retain high application performance when schema evolution is in progress.

Designing a Honey Quality Tool Based on Gas Sensor and Color Sensor

Honey has many benefits. Thus, honey counterfeiting often occurs with the ever-increasing demand. However, many do not know how to distinguish between real and fake honey, even honey breeders and hunters find it difficult to tell the difference. The honey used to test the quality of honey is honey produced by Apis dorsata bees or wild bees, the nectar consumed by these bees is the kesambi tree, the kesambi tree that grows a lot on the slopes of Mount Tambora, Bima district. Honey contains a lot of antioxidants such as vitamin C, pinocembrin, chrysin, pinobaksin, catalase, and many other ingredients that are very beneficial for the health of the body. Testing the authenticity of honey using two sensors, namely a gas sensor and a color sensor, the tool has been connected to a database and web application to display test data. The web application can be accessed from any location as long as it is connected to the internet network. The results of the research are the ideal distance for measurements is carried out as far as 2 cm. The success rate in testing pure honey with a mixture of honey has different values, such as the value of pure honey has a gas sensor voltage of 3.3 volts while the value of mixed honey with 50% pure honey and 50% sugar, the value of the gas sensor voltage is 2.54 volts. Mixed honey has a voltage below 3 volts. The results of the color sensor test, namely the sensor output have different values, the RGB value for pure honey is red 206, green 246, and blue 182 while the RGB value for mixed honey is for 20% pure honey and 80% sugar mixture produces an RGB value of Red 156, Green 210, Blue 171. The color sensor can distinguish between real honey and mixed honey for trigona honey.

Development and application of a Japanese vaccine database for comparative assessments in the post-authorization phase: The Vaccine Effectiveness, Networking, and Universal Safety (VENUS) study

BackgroundJapan currently lacks a data platform that can support quantitative assessments of the causal relationships between vaccines and adverse events. This study describes the development and application of the Vaccine Effectiveness, Networking, and Universal Safety (VENUS) Study to facilitate such assessments. MethodsA database was created by linking public insurance enrollees’ claims data with vaccination records acquired from participating municipalities. To provide an overview of the study data, we produced descriptive statistics of sex, age, and vaccinations. We also conducted a pilot study using the database to assess influenza vaccine safety during the 2018/2019 season among older persons (≥65 years) residing in a single municipality. ResultsOur database was created using data from approximately 1.12 million individuals in 7 municipalities between 2013 and 2020. The data during fiscal year 2018 included 853,016 individuals (male: 363,079, female: 489,937) with a median age of 70 years (interquartile range: 52–79). We obtained information on 17 vaccine types, including the pneumococcal vaccine and influenza vaccine. In the pilot study, we analyzed 48,723 vaccinated persons matched with 48,723 unvaccinated persons. The only adverse event that occurred in both groups was Bell’s palsy, which had an adjusted incidence rate ratio of 1.21 (95 % confidence interval: 0.48–3.07). ConclusionsThe VENUS Study is Japan’s first healthcare data platform that enables comparative assessments of vaccinated and unvaccinated persons in large samples covering all age groups. Efforts are underway to increase the number of participating municipalities and to generate evidence on vaccine effectiveness and safety.

Revealing the differences in collision cross section values of small organic molecules acquired by different instrumental designs and prediction models

The number of open access databases containing experimental and predicted collision cross section (CCS) values is rising and leads to their increased use for compound identification. However, the reproducibility of reference values with different instrumental designs and the comparison between predicted and experimental CCS values is still under evaluation.This study compared experimental CCS values of 56 small molecules (Contaminants of Emerging Concern) acquired by both drift tube (DT) and travelling wave (TW) ion mobility mass spectrometry (IM-MS). The TWIM-MS included two instrumental designs (Synapt G2 and VION). The experimental TWCCSN2 values obtained by the TWIM-MS systems showed absolute percent errors (APEs) < 2% in comparison to experimental DTIMS data, indicating a good correlation between the datasets. Furthermore, TWCCSN2 values of [M − H]- ions presented the lowest APEs. An influence of the compound class on APEs was observed.The applicability of prediction models based on artificial neural networks (ANN) and multivariate adaptive regression splines (MARS), both built using TWIM-MS data, was investigated for the first time for the prediction of DTCCSN2 values. For [M+H]+ and [M − H]- ions, the 95th percentile confidence intervals of observed APEs were comparable to values reported for both models indicating a good applicability for DTIMS predictions.For the prediction of DTCCSN2 values of [M+Na]+ ions, the MARS based model provided the best results with 73.9% of the ions showing APEs below the threshold reported for [M+Na]+. Finally, recommendations for database transfer and applications of prediction models for future DTIMS studies are made.

Carbon Footprint Research Based on Input-Output Model-A Global Scientometric Visualization Analysis.

Reducing the effect of mankind’s activities on the climate and improving adaptability to global warming have become urgent matters. The carbon footprint (CF), derived from the concept of ecological footprint, has been used to assess the threat of climate change in recent years. As a “top to bottom” method, input–output analysis (IOA) has become a universally applicable CF assessment tool for tracing the carbon footprint embodied in economic activities. A wide range of CF studies from the perspective of the IOA model have been presented and have made great progress. It is crucial to have a better understanding of what the relevant research focuses on in this field, yet so far a systematic synopsis of the literature is missing. The purpose of this paper is to explore the knowledge structure and frontier trends in respect of the IOA model applied to CF research using scientometric visualization analysis. The main findings of this paper are as follows. (1) Published articles show a two-stage increase in the period 2008 to 2021, and present a complex academic network of countries, authors, and institutions in this important domain. (2) The classic studies are mainly divided into three categories: literature reviews, database application introduction, and CF accounting in different scales. (3) The research hotspots and trends show that the research scales tend to be more microscopic and applications of models tend to be more detailed. In addition, supply-chain analysis and driver-factor analysis will probably become the main research directions in the future.

ONe Index for All Kernels (ONIAK)

In this work, we formulate and solve a new type of approximate nearest neighbor search (ANNS) problems called ANNS after linear transformation (ALT). In ANNS-ALT, we search for the vector (in a dataset) that, after being linearly transformed by a user-specified query matrix, is closest to a query vector. It is a very general mother problem in the sense that a wide range of baby ANNS problems that have important applications in databases and machine learning can be reduced to and solved as ANNS-ALT, or its dual that we call ANNS-ALTD. We propose a novel and computationally efficient solution, called ONe Index for All Kernels (ONIAK), to ANNS-ALT and all its baby problems when the data dimension d is not too large (say d ≤ 200). In ONIAK, a universal index is built, once and for all, for answering all future ANNS-ALT queries that can have distinct query matrices. We show by experiments that, when d is not too large, ONIAK has better query performance than linear scan on the mother problem (of ANNS-ALT), and has query performances comparable to those of the state-of-the-art solutions on the baby problems. However, the algorithmic technique behind this universal index approach suffers from a so-called dimension blowup problem that can make the indexing time prohibitively long for a large dataset. We propose a novel algorithmic technique, called fast GOE quadratic form (FGoeQF), that completely solves the (prohibitively long indexing time) fallout of the dimension blowup problem. We also propose a Johnson-Lindenstrauss transform (JLT) based ANNS-ALT (and ANNS-ALTD) solution that significantly outperforms any competitor when d is large.

The Application of Data Encryption Technology in Computer Network Communication Security

With the development of computer network and the popularization of information system, the security of databases, as platforms for centralized storage and sharing of information system data, has increasingly become a serious problem in the field of information security, so data encryption technology has come into people’s sight. However, the current data encryption technology still has certain shortcomings, such as the inconsistency of the code text of the encryption and decryption technology, and the low efficiency of decoding and encryption. The purpose of this paper is to study the application of data encryption technology in computer network communication to provide better suggestions and explore better methods for improving network communication security system. This article, through the analysis of the database threat model and database application system structure, puts forward a design scheme of database encryption system model. A complete database encryption system can be divided into five logic modules: a key storage module, key engine module, key information module, key management module, and data storage module, and provides an in-depth analysis of the various parts and implementation details related to these modules. Finally, the designed encryption system model is programmed to be implemented; with the help of online examination system, the function and performance of the encryption system were tested; and the transmission efficiency of data encryption is maintained at more than 95%, which proves the effectiveness of the system.

LiDAR Platform for Acquisition of 3D Plant Phenotyping Database.

Currently, there are no free databases of 3D point clouds and images for seedling phenotyping. Therefore, this paper describes a platform for seedling scanning using 3D Lidar with which a database was acquired for use in plant phenotyping research. In total, 362 maize seedlings were recorded using an RGB camera and a SICK LMS4121R-13000 laser scanner with angular resolutions of 45° and 0.5° respectively. The scanned plants are diverse, with seedling captures ranging from less than 10 cm to 40 cm, and ranging from 7 to 24 days after planting in different light conditions in an indoor setting. The point clouds were processed to remove noise and imperfections with a mean absolute precision error of 0.03 cm, synchronized with the images, and time-stamped. The database includes the raw and processed data and manually assigned stem and leaf labels. As an example of a database application, a Random Forest classifier was employed to identify seedling parts based on morphological descriptors, with an accuracy of 89.41%.

Revolutionising Collection Management at the National Museum of Namibia

Despite its aridity, Namibia contains a surprisingly species-rich biota with high levels of endemism and an unprecedented land portion of intact wilderness. However, as a developing country, the expanding human population is increasing pressure on the country’s rich, but severely understudied ecosystems. An efficient flow of baseline biodiversity data is key for facilitating biosystematics and biogeographic research, which inform conservation planning and sustainable development. The National Museum of Nambia (NMNW) is the custodian of important specimen collections representing Namibian biodiversity, with holdings of about 500 000 specimens from a broad range of vertebrate and invertebrate groups. The NMNW is increasing its drive to make these data available to the necessary stakeholders to facilitate research and conservation assessments, based on digitised specimen collections. The first digitisation initiatives , in the 1980s and 1990s, used software such as FileMaker Pro. These collection-specific database development projects were not aligned with each other or standardised, and resulted in separately developed, heterogeneous databases. Recent changes in research priorities, standards (e.g., Darwin Core Darwin Core Task Group 2009), and data-types (e.g. multimedia files, genomic samples and DNA sequences) now necessitate the use of the latest technologies to revolutionise collection management and data management, facilitate workflows and integrate data into a single platform. We describe plans to implement Specify software (Specify Collections Consortium 2022) for collections / biodiversity data management at NMNW. We will form a small team to execute the required data cleansing and migration operations in-house, to develop a Specify database to manage the herpetology collection, in the first instance. Proper management of genomic and image metadata, and the longevity of database management in a staff-constrained environment, will require special database design considerations. Of particular importance is the representation of both individual organisms and the specimen-lots containing them, and we describe the capability of Specify software to handle such data. We also describe the approach that will be followed in introducing new users to a conceptually complex database schema and application. This will draw from previous experience in developing Specify databases for, and undertaking training courses with, several natural history museums in South Africa.