Database Applications Research Articles

Research on the Application of Speech Database based on Emotional Feature Extraction in International Chinese Education and Teaching

The advanced analysis of the relationship between acoustic and emotional characteristics of speech signals can effectively improve the interactivity and intelligence of computers. Given the current status of speech recognition and the problems encountered in international Chinese education, the study proposes to extract emotional characteristics to achieve speech construction of the database. Based on considering the emotional characteristics of speech, a hybrid algorithm based on spectral sequence context features is proposed. The DBN-BP algorithm is used to process emotional data of different dimensions, and a speech database is constructed. After testing and analyzing the algorithm model, it is found that the dynamic recognition accuracy of the DBN-BP model fused with emotional features is over 90%, and the negative emotion recognition rates in the three databases are all above 60%. At the same time, the accuracy rate of the model in the algorithm comparison experiment remains above 85%, the data information extraction is relatively complete, and the average test time of less than 1s is less than 3%. The speech database based on multi-emotional feature extraction can effectively provide a new reference for the improvement of the quality of Chinese international education and the improvement of the speech recognition system.

Research and Application of Legal Consultation database based on multimedia Network

In order to relieve the pressure of people's appeal for legal inquiry, the research and application of legal consultation database based on multimedia network is proposed. The legal consultation system designed in this essay, combined with the current situation of the legal industry, takes the Chinese question answering system as the prototype, combined with the open source data retrieval project Lucene.net, expands the data storage types. In this essay, the Chinese word segmentation system developed by Chinese Academy of Sciences is integrated into Lucene.Net platform to make up for its word segmentation deficiency. And the mutual information technology is used to make the legal related words with the same meaning be searched first. When extracting answers in Chinese question answering system, there are often "missing" and "wrong" answers. In this essay a method of sentence similarity calculation of questions and answers based on Latent Semantic analysis (LSA) is proposed, which uses spatial vector model as representation method and latent semantic analysis theory. A low-dimensional semantic space is constructed by using the dimension reduction method of singular value decomposition, and the sentence similarity between question and answer is computed on the semantic space. Experimental results show that most retrievals can be completed within 20 seconds, and the average unit retrieval time is kept at the millisecond level. Conclusion: This system has more accurate query accuracy and less running time.

Exploration of ideological and political education reform in the course of database principles and applications based on OBE concept

Curriculum ideological and political education is an important means to achieve the goal of cultivating morality and nurturing talents. Through the investigation of students' rational identification, emotional cognition, and behavioral tendencies in the early stage of ideological and political education in the course of "Database Principles and Applications", it was found that there are three main problems: weak ideological and political concepts in the course and insufficient value cognition of students; Lack of correlation between curriculum and ideological and political education, and insufficient emotional stimulation of students; The teaching method is single, and the effectiveness of ideological and political education in the curriculum is poor. This article mainly explores the use of OBE education philosophy to enhance teachers' ability to teach ideological and political education through the establishment of curriculum ideological and political concepts; Digging deep into ideological and political elements and reconstructing teaching content; Innovate ideological and political teaching methods and carry out effective teaching; Innovate the evaluation system for ideological and political education in courses, improve the effectiveness of ideological and political education in courses, and achieve educational goals.

Geological and technological viewpoint on 3D Deposit Model – examples of use in Pniówek Coal Mine

During the more than 3 years of the “Quality” program at JSW S.A., a geological database has been built from scratch, collecting data from all exploratory boreholes, roadway profiling and the results of chemical analyses in one place – placing particular emphasis on parameters affecting the quality of coke. Working with digital databases requires new competencies for geologists – the ability to efficiently obtain information ready for further processing. As intended, the geological model became the basis for forecasting the quantity and quality of mined coal used in coke production. In the course of the work, a discrepancy became apparent between the geological interpretation of the structure of the deposit – as understood by the assumptions of the geological documentation, and the technological conditions of mining. The article presents resulting changes in the approach to modeling lithology and quality parameters. In addition, examples of the application of the geological database and the geological model in the daily work of the geological department are presented.

Big Data and Neural Networks in Smart Grid - Part 1: The Impact of Measurement Differences on the Performance of Neural Network Identification Methodologies of Overhead Low-Voltage Broadband over Power Lines Networks

Until now, the neural network identification methodology for the branch number identification (NNIM-BNI) and the neural network identification methodology for the distribution line and branch line length approximation (NNIM-LLA) have approximated the number of branches and the distribution line and branch line lengths given the theoretical channel attenuation behavior of the examined overhead low-voltage broadband over powerlines (OV LV BPL) topologies [1], [2]. The impact of measurement differences that follow continuous uniform distribution (CUDs) of different intensities on the performance of NNIM-BNI and NNIM-LLA is assessed in this paper. The countermeasure of the application of OV LV BPL topology databases of higher accuracy is here investigated in the case of NNIM-LLA. The strong inherent mitigation efficiency of NNIM-BNI and NNIM-LLA against CUD measurement differences and especially against those of low intensities is the key finding of this paper. The other two findings that are going to be discussed in this paper are: (i) The dependence of the approximation Root-Mean-Square Deviation (RMSD) stability of NNIM-BNI and NNIM-LLA on the applied default operation settings; and (ii) the proposal of more elaborate countermeasure techniques from the literature against CUD measurement differences aiming at improving NNIM-LLA approximations.

Construction and practice of a blended teaching model based on MOOC+SPOC+Flipped classroom

With the rapid development of Internet technology, MOOC has played a certain role in promoting the realization of education equity in China. In order to further improve the quality of teaching, educators are constantly exploring better teaching models. This article aims to optimize the blended learning model by constructing a blended learning model of MOOC+SPOC+flipped classroom in the course of database principles and applications. To enhance the influence of classroom teaching, stimulate and enhance students' interest in learning, and provide reference for the improvement and development of the current blended learning model. At the same time, the specific strategies and practical experience used in the design and practice of MOOC+SPOC+flipped classroom provide valuable references for other teaching practices.

Proposed framework for enhancing integrity technique using distributed query operation

Database growth and Storage problems are main concern for large and small enterprises nowadays, which significantly influences the efficiency of database applications. Database archiving is one of the solutions available for management. Many issues have been identified as a result of the use of archive databases, including the elimination of inactive data from online transaction processing systems (OLTP), performance and integrity management. The aim of this paper is to propose a framework for storing OLTP and archiving data in a distributed database environment as part of an integrated system. Maintaining the integrity between an OLTP database and an archiving database is crucial, but even more critical is the performance of the required query. The main aspect of the proposed framework is that it will not only ensure data integrity for primary and unique keys between OLTP and archive database, but it will also improve query performance by introducing parallel processing and query execution plans to maintain that integrity.

Proposal for the Implementation of Database Systems Teaching in Pharmacy Courses in Terms of e-Health Support

In our paper, we will discuss the design and implementation of relational databases using MS Access. Relational database is one of the most widely used databases in terms of practice and information systems. We often encounter their implementation in many solutions, for example as hybrid OLAP databases of enterprise systems or also as OLTP systems - currently most of the classical database applications as we understand them. Their importance is therefore great from a modern point of view. In our paper, through the concrete example of a local pharmacy, we will try to create a practical application that will be fully functional, but will not require deep expertise; on the contrary, it will follow the modern trend that is noticeable in many other information systems, where the emphasis is on usage and not on lengthy training and close long-term professionalization. Our aim is to provide pharmacy students with knowledge, the acquisition of which will not go beyond a maximum of three 90-minute classes and yet provide practical knowledge of relational databases at more than a minimal level.

Antifeedant, Antifungal Cryptic Polyketides with Six Structural Frameworks from Tea Endophyte Daldinia eschscholtzii Propelled by the Antagonistic Coculture with Phytopathogen Colletotrichum pseudomajus and Different Culture Methods.

The antagonistic coculture with tea phytopathogen Colletotrichum pseudomajus induces antifungal cryptic metabolites from isogenesis endophyte Daldinia eschscholtzii against tea phytopathogens. Sixteen new polyketides with six structural frameworks including ten cryptic ones, named coldaldols A-C (1-3), collediol (5), and daldinrins A-L (10-20 and 23), were found from the coculture of C. pseudomajus and D. eschscholtzii by different culture methods. The unique framework of compounds 11 and 12 featured a benzopyran-C7 polyketone hybrid, and compounds 13-16 were characterized by the novel benzopyran dimer. The structures were determined mainly by spectroscopic methods, including extensive one-dimensional (1D), two-dimensional (2D) NMR, high resolution electrospray ionisation mass spectroscopy (HRESIMS), ECD calculation, and single-crystal X-ray diffraction. The configuration of acyclic compounds 5 and 18 were determined by application of the universal NMR database. Most compounds showed significant antifungal activities against the tea pathogens C. pseudomajus and Alternaria sp. with MICs of 1-8 μg/mL. Compound 12 had stronger antifungal activity than that of positive drug nystatin. The ether bond at C-4 of the benzopyran derivative increased the antifungal activity. Compounds 4-9 and 11-23 showed antifeedant activities against silkworms with feeding deterrence indices of 15-100% at the concentration of 50 μg/cm2.

Highly compressed image representation for classification and content retrieval

In this paper, we propose a new method of representing images using highly compressed features for classification and image content retrieval – called PCA-ResFeats. They are obtained by fusing high- and low-level features from the outputs of ResNet-50 residual blocks and applying to them principal component analysis, which leads to a significant reduction in dimensionality. Further on, by applying a floating-point compression, we are able to reduce the memory required to store a single image by up to 1,200 times compared to jpg images and 220 times compared to features obtained by simple output fusion of ResNet-50. As a result, the representation of a single image from the dataset can be as low as 35 bytes on average. In comparison with the classification results on features from fusion of the last ResNet-50 residual block, we achieve a comparable accuracy (no worse than five percentage points), while preserving two orders of magnitude data compression. We also tested our method in the content-based image retrieval task, achieving better results than other known methods using sparse features. Moreover, our method enables the creation of concise summaries of image content, which can find numerous applications in databases.

APPLYING THE CARE SETTING TRAJECTORY DATABASE TO STUDY END-OF-LIFE OUTCOMES IN PERSONS WITH DEMENTIA

Abstract This study highlights an application of the care setting trajectory database and our new, harmonized, self-reported race/ethnicity variable to evaluate the impact of home health care on later use of hospice and place of death in a large cohort of Medicare decedents. This study evaluated home health care use during the last 3 years of life as a predictor of death in the care of hospice for a cohort of 895,526 Medicare beneficiaries with dementia who died in 2019. The cohort was limited to beneficiaries continuously enrolled for at least 5 years, who were age 40 and older, and who lived in the U.S. fifty states, District of Columbia, or Puerto Rico at death. Co-variates included number of acute hospitalizations during the last 3 years of life, age at death, sex, race/ethnicity, comorbidities, insurance, rural/urban area, and state of residence. 54.5% of the cohort used home health care at any point during the last 3 years of life. Compared to beneficiaries who did not use home health care, those who received home health care were more likely to die at home (64.5% vs. 60%, OR 1.08) or in the care of hospice (65% vs. 58%, OR 1.05). Among beneficiaries who died with hospice, use of home hospice was more prevalent for those who had previously used home health care (53% vs. 49%). This study provides compelling evidence of the value of home health care as a strategy to improve end-of-life care quality among Medicare beneficiaries living with dementia.

APPLIED METHODS FOR HEALTH EQUITY AND END-OF-LIFE OUTCOMES RESEARCH USING MEDICARE DATA

Abstract This symposium brings together four related and complementary projects on the development of new data sources and methods to analyze the new data to study health equity and end-of-life outcomes research. The first abstract presents the development of the Care Setting Trajectory Database, which integrates data from various CMS data sources for Medicare beneficiaries to create a longitudinal care experience for older adults across healthcare settings. The second abstract describes the creation of a new race/ethnicity variable to augment the Medicare administrative data for minority populations using harmonized, self-reported race/ethnicity data. The third abstract describes the development of harmonized datasets to study geriatric syndromes’ prevalence, cost, and health outcomes over time. The fourth abstract identifies and predicts place of care trajectories during the last three years of life among Medicare beneficiaries, identifying dual trajectories of inpatient/institutional care and skilled home healthcare/home hospice. Finally, the fifth abstract includes an application of the care setting trajectory database and our new, harmonized, self-reported race/ethnicity variable to evaluate the impact of home health care on later use of hospice and place of death in a large cohort of Medicare decedents. This symposium introduces innovative approaches for harmonizing and merging CMS data sources for Medicare beneficiaries. The methodological advances described in this symposium aim to support health services researchers and policymakers to generate and evaluate research improving care coordination, continuity, and quality of life for older adults with serious illnesses.

Research on the Reform and Practice of Informatization Mode of Adult Higher and Continuing Education Academic Records Management in the Context of Three-Whole Parenting

Abstract Information technology reform is an important way for schools to realize efficient management and information technology should be introduced into the management of student registration files to accelerate the process of informationization of registration file management. This paper builds an informatization database of adult higher continuing education student registration file management based on informatization technology and carries out the design of the main business process of student registration files. The multi-layer stacked LSTM network in the ELMo model is utilized to learn the preprocessing of the text of the school records data, and the CART decision tree algorithm is improved based on the reinforcement learning mechanism in order to improve the classification prediction accuracy of the decision tree in the dataset. In order to verify the feasibility of the school registration file informationization database constructed in this paper, a test analysis is conducted for the application of data mining technology and informationization database. The results show that the check accuracy of the CART decision tree algorithm improved by the reinforcement learning mechanism is around 80%, and the throughput of this paper’s database reaches 4827ops/s when the data writing volume is 1*105GB. When the number of threads reaches 128, the throughput of this paper’s informative database is around 5486ops/s, and when the data volume reaches 12*105 entries, the database in this paper the query response time is around 602ms. Under the background of three-round education, it is necessary to fully integrate information technology with the management of school registration files, which will lead to the innovation of the informationization mode of the management of school registration files in adult higher education.

Identifying CD1c as a potential biomarker by the comprehensive exploration of tumor mutational burden and immune infiltration in diffuse large B cell lymphoma.

Tumor mutational burden (TMB) is a valuable prognostic biomarker. This study explored the predictive value of TMB and the potential association between TMB and immune infiltration in diffuse large B-cell lymphoma (DLBCL). We downloaded the gene expression profile, somatic mutation, and clinical data of DLBCL patients from The Cancer Genome Atlas (TCGA) database. We classified the samples into high-and low-TMB groups to identify differentially expressed genes (DEGs). Functional enrichment analyses were performed to determine the biological functions of the DEGs. We utilized the cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm to estimate the abundance of 22 immune cells, and the significant difference was determined by the Wilcoxon rank-sum test between the high- and low-TMB group. Hub gene had been screened as the prognostic TMB-related immune biomarker by the combination of the Immunology Database and Analysis Portal (ImmPort) database and the univariate Cox analysis from the Gene Expression Omnibus (GEO) database including six DLBCL datasets. Various database applications such as Tumor Immune Estimation Resource (TIMER), CellMiner, konckTF, and Genotype-Tissue Expression (GTEx) verified the functions of the target gene. Wet assay confirmed the target gene expression at RNA and protein levels in DLBCL tissue and cell samples. Single nucleotide polymorphism (SNP) occurred more frequently than insertion and deletion, and C > T was the most common single nucleotide variant (SNV) in DLBCL. Survival analysis showed that the high-TMB group conferred poor survival outcomes. A total of 62 DEGs were obtained, and 13 TMB-related immune genes were identified. Univariate Cox analysis results illustrated that CD1c mutation was associated with lower TMB and manifested a satisfactory clinical prognosis by analysis of large samples from the GEO database. In addition, infiltration levels of immune cells in the high-TMB group were lower. Using the TIMER database, we systematically analyzed that the expression of CD1c was positively correlated with B cells, neutrophils, and dendritic cells and negatively correlated with CD8+ T cells, CD4+ T cells, and macrophages. Drug sensitivity showed a significant positive correlation between CD1c expression level and clinical drug sensitivity from the CellMiner database. CREB1, AHR, and TOX were used to comprehensively explore the regulation of CD1c-related transcription factors and signaling pathways by the KnockTF database. We searched the GETx database to compare the mRNA expression levels of CD1c between DLBCL and normal tissues, and the results suggested a significant difference between them. Moreover, wet experiments were conducted to verify the high expression of CD1c in DLBCL at the RNA and protein levels. Higher TMB correlated with poor survival outcomes and inhibited the immune infiltrates in DLBCL. Our results suggest that CD1c is a TMB-related prognostic biomarker.

A database application framework toward data-driven vertical connectivity analysis of rivers

The description of complex river environments requires interdisciplinary approaches to collect and manage manifold data types and sources. Deriving comprehensive knowledge from complex data sources is challenging and necessitates not only knowledge of environmental science but also statistics and Software engineering. This study introduces a relational database framed in an application called River Analyst for creating and managing river data with open-source standards (Python3 and Django). We conceptualize data models of river environments, which describe sediment characteristics and hydraulics related to hyporheic exchange. River Analyst enabled us to derive novel insights for restoring rivers affected by so-called riverbed clogging, notably, fine sediment infiltration in the hyporheic zone. The database analysis reveals that clogging is not a dominant control process when the fraction of fine sediment exceeds 50%–55%. In conclusion, the new Software holds promise for data-informed advancements in augmenting knowledge to restore ecologically functional hydro-environments.

New naturally transgenic crop

Horizontal gene transfer from agrobacteria to plants turned out to be a much more widespread phenomenon than previously thought. In the first it was established in 2019 due to the application of bioinformatic methods and databases, then about 30 species of naturally transgenic plants were discovered [1]. The deposition of new nucleotide sequences of various plant species makes it possible to periodically update the list of naturally GMOs. Analysis of genomic and transcriptomic databases in 2023 revealed more than 50 new naturally transgenic plants and, thus, more than 100 species of nGMOs are currently known. And the share of naturally transgenic plants in relation to deposited species of terrestrial dicotyledonous plants is about 7%. Interestingly, this indicator retains its value regardless of the change in the number of organisms in the studied databases [2].
 Among the discovered new nGMOs there are species that have been cultivated by humans since ancient times and are important agricultural crops. Fruit crops include the following species of nGMOs: carambola (Averrhoa carambola L.), persimmon (Diospyros kaki Thunb.), wasabi (Eutrema japonicum (Miq.) Koidz.), raspberry (Rubus idaeus L.), Luffa acutangula (L.) Roxb. There are also many medicinal, ornamental and oilseed species among the naturally transgenic plants. Further study of these species would make it possible to establish what role horizontal gene transfer played in the appearance of traits in plants that were selected by humans.
 The obtained data can be further used to study the molecular evolution and the role of transgenes in naturally transgenic plants.

Phenolic compounds in leaves of <i>Tanacetum balsamita</i> L.

Tanacetum balsamita L. is a perennial rhizomatous plant of the Asteraceae family. T. balsamita is cultivated as medicinal, aromatic plants and food plant. Extract of costmary exhibits hepatoprotective, antiseptic and anthelmintic properties. The herb of T. balsamita contains essential oils and phenolic compounds. This species included in the "Biocollection of medicinal and aromatic plants of open and protected ground", Botanical garden of the VILAR. The main aim was to study the composition of phenolic compounds in the leaves of T. balsamita with application of ultra-performance liquid chromatography coupled with diode array detection and mass spectrometry. The object of the study was the leaves of T. balsamita. Samples were extracted with 1 ml of 80% aqueous acetone. An ultra-performance liquid chromatographic system with a photodiode detector and a triple quadrupole mass spectrometer was used for analysis of phenolic compounds. The UV and MS data of phenolic compounds were used for their identification or tentative characterization with application of mass spectrometry databases and data published in the literature.Results. The results obtained showed the presence in the leaves of 17 phenolic compounds. Five compounds were identified as caffeoylquinic, feruloylquinic and three dicaffeolquinic acid isomers, and two compounds as ferulic acid hexoside isomers. The leaves of T. balsamita contained also five luteolin derivatives, two chrysoeriol derivatives, and spinacetin/axillarin. Four compounds were not identified.

SISTEM PENDUKUNG KEPUTUSAN MENENTUKAN KELAYAKAN ARTIKEL JURNAL ILMIAH DENGAN METODE SIMPLE ADDITIVE WEIGHTING (SAW) (Studi Kasus : Lembaga Penerbit Fakultas Ekonomi dan Bisnis Universitas Trisakti)

Change the paradigm of scientific periodicals into electronic printed must follow its development by the author or publisher in Indonesian. The changes led to the accreditation process supported by technology article that qualified. In addition to the feasibility assessment, the article selection process was still using a manual system is not computerized. Issuing the Faculty of Economics and Business (LPFEB) Trisakti University requires a database application that can accommodate the editing process LPFEB article contained in Trisakti University. Management of scientific journals in the process of determining the feasibility of the journal to be published this takes quite a relatively long, making it difficult to assess the reviewer section. From the problems in the wake of website database based on PHP and MySQL using the SAW (Simple Additive Weighting) is capable of supporting the process of the ongoing feasibility assessment. With the construction of this database can facilitate reviewer in determining the feasibility of a scientific journal, so that the application site can be more efficient editing process.

APPLICATIONS OF KNOWLEDGE DISCOVERY AND DATABASE (KDD) IN CLINICAL DECISION SUPPORT SYSTEM

Applications of Knowledge Discovery and Database (KDD) in Clinical Decision Support Systems) is a research work that aims to develop a medical system that has the ability to detect and suggest cure for an ailment with minimal effort. Healthcare system has been a major source of worry across the globe in recent time due to emergence of different types of diseases and epidemics. The number of health care personnel in various hospitals falls short of the number required most especially in terms of specialists. The medical system in Nigeria today suffers from lack of fast, accurate, reliable and intelligent software solutions that can help healthcare practitioners make decisions that would solve urgent, and in some cases, complex medical problems in real-time. Also, the cost of processing and analyzing large volumes of data in a medical environment is high most especially in terms of time consumption. So in this research design and implement clinical decision support system using knowledge discovery in database (KDD) was the major focus. The design required a computerized database for storing medical records as well as software for improved intelligence-based medical procedures that were going to be simpler to use, versatile, adaptable, savvy, and effortless at combining and evaluating medical data, allowing medical practitioners at all levels to make realistic, intelligent, and real-time decisions on critical health issues. The system was designed using the Object-Oriented Design and Analysis Methodology (OOADM).

Implementation of California COVIDNet - a multi-sector collaboration for statewide SARS-CoV-2 genomic surveillance.

The SARS-CoV-2 pandemic represented a formidable scientific and technological challenge to public health due to its rapid spread and evolution. To meet these challenges and to characterize the virus over time, the State of California established the California SARS-CoV-2 Whole Genome Sequencing (WGS) Initiative, or "California COVIDNet". This initiative constituted an unprecedented multi-sector collaborative effort to achieve large-scale genomic surveillance of SARS-CoV-2 across California to monitor the spread of variants within the state, to detect new and emerging variants, and to characterize outbreaks in congregate, workplace, and other settings. California COVIDNet consists of 50 laboratory partners that include public health laboratories, private clinical diagnostic laboratories, and academic sequencing facilities as well as expert advisors, scientists, consultants, and contractors. Data management, sample sourcing and processing, and computational infrastructure were major challenges that had to be resolved in the midst of the pandemic chaos in order to conduct SARS-CoV-2 genomic surveillance. Data management, storage, and analytics needs were addressed with both conventional database applications and newer cloud-based data solutions, which also fulfilled computational requirements. Representative and randomly selected samples were sourced from state-sponsored community testing sites. Since March of 2021, California COVIDNet partners have contributed more than 450,000 SARS-CoV-2 genomes sequenced from remnant samples from both molecular and antigen tests. Combined with genomes from CDC-contracted WGS labs, there are currently nearly 800,000 genomes from all 61 local health jurisdictions (LHJs) in California in the COVIDNet sequence database. More than 5% of all reported positive tests in the state have been sequenced, with similar rates of sequencing across 5 major geographic regions in the state. Implementation of California COVIDNet revealed challenges and limitations in the public health system. These were overcome by engaging in novel partnerships that established a successful genomic surveillance program which provided valuable data to inform the COVID-19 public health response in California. Significantly, California COVIDNet has provided a foundational data framework and computational infrastructure needed to respond to future public health crises.