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检索条件"主题词=NoSQL Databases"

共 338 条记录，以下是121-130 订阅

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Optimizing Machine Learning Training: A Comparative Study of Storage Types for Efficient Large Dataset Processing

Optimizing Machine Learning Training: A Comparative Study of...

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Proceedings of the International Convention MIPRO

作者： Luka Lasic Aleksander Radovan Branko Mihaljević RIT Croatia Algebra University College

ISBN: (数字)9798350382501

ISBN: (纸本)9798350382518

This research paper explores various storage types suitable for handling large datasets within machine learning projects. The study focuses on a comparison of performance metrics, specifically focusing on the read operations from storage employing textual files, relational databases, and nosql databases. In the realm of machine learning projects, the significance of efficiently reading extensive datasets is vital. This research seeks to describe alternative approaches to the varying sizes of datasets, recognizing that the time required to train machine learning models is related to the efficiency of data retrieval. The methodology employed for this comparative analysis encompasses the utilization of datasets of different sizes, measurement of read operation durations, iterative measurements for precision, and computation of average read operation durations. The results show that the storage type decisions need to depend on a specific size of the dataset, as well as certain characteristics, thereby optimizing the length of the training process for machine learning models. By aligning storage choices with dataset dimensions, the results of this research help to make a better decision related to choosing the right dataset storage type, thereby contributing to the overall efficiency and efficacy of machine learning systems.

关键词： Training Computational modeling Scalability nosql databases Focusing Machine learning Relational databases

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A Case Study of Cloud Query Performance Comparison Between SQL and nosql Database

A Case Study of Cloud Query Performance Comparison Between S...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Sheng Chai Zhengrui Qin School of Computer Science and Information Systems Northwest Missouri State University Maryville MO USA

ISBN: (数字)9798331504946

ISBN: (纸本)9798331504953

Large volumes of data present a significant challenge and can lead to high costs for organizations. As datasets grow, the operational efficiency of applications tends to decline, which can result in customer attrition. Therefore, enhancing the performance of applications is crucial for capturing increasingly large amounts of customer data. Cloud computing services provide a practical solution to this performance issue by effectively managing both SQL and nosql databases. This paper outlines a case study aimed at identifying the most effective method for improving application performance with large and continuously expanding datasets. To achieve this, the query performance of SQL and nosql systems are compared. The comparison involves measuring the runtimes of queries executed on SQL and nosql databases hosted in the cloud, using the TPC benchmark. The experiment assesses the response times of both database types, ultimately indicating which method performs better.

关键词： Cloud computing Runtime Costs databases nosql databases Organizations Benchmark testing Time factors Intelligent agents

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Graduate Programs in Computing at the University of Brasilia: Comparison of Academic Papers and Collaborations by Gender

Graduate Programs in Computing at the University of Brasilia...

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Frontiers in Education (FIE) Conference

作者： Mariana Alencar do Vale Maristela Holanda Celia G. Ralha Aleteia Araujo Dilma Da Silva Depart. of Computer Science Universidade de Brasília Brasilia Brasil Depart. of Computer Science Universidade de Brasília Brasília DF Brazil Depart. of Computer Science and Engineering Texas A&M University College Station TX U.S.

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

The computing field has a low level of gender diver-sity, being predominantly male. This diversity gap is reflected at different academic levels, ranging from undergraduate degrees to master's and doctoral qualifications. As in other parts of the world, the University of Brasilia, one of the top 10 universities in Brazil, has a low rate of women in Computing in its graduate programs. According to data from CAPES (Coordination for the Improvement of Higher Education Personnel in Brazil), the computing area is one of the areas of Exact Sciences with the lowest number of women proportionally in Brazil. In this context, this paper aims to present an analysis of the number of publications and scientific collaborations related to the gender of researchers in the Graduate Program in Informatics (PPG I) at the University of Brasilia. To develop this research, technologies such as scraping were used to collect data from the program's professors, articles published (only full papers in conferences and academic journals) by them and names of the people who collaborated in the preparation of the articles, a database graph-based nosql was used to generate the relationship networks. A relationship network was created, in which it was possible to analyze the relationship level of each professor in the program. As initial results, the average number of articles published is the same by gender, we did not find significant differences in the number of publications between men and women. In the study we only counted the number of publications, we did not analyze the impact of the publications. Regarding collaborations, initial results indicate that women are more collaborative than men in the program, with a higher degree of collaboration than the average for male researchers. In general, in the partial results, collaboration networks for journals and conferences present the same result, that female researchers proportionally collaborate more than men, both internally (publications co

关键词： nosql databases Education Collaboration Production Medical services Distance measurement Personnel Informatics Qualifications Gender issues

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SQL and nosql Object-Database Mapping Using Property Graphs in Relational Cases

SQL and NoSQL Object-Database Mapping Using Property Graphs ...

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International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)

作者： Billy Montolalu Siti Rochimah Daniel Siahaan Informatics Department Institut Teknologi Sepuluh Nopember Surabaya Indonesia

ISBN: (数字)9798350355314

ISBN: (纸本)9798350355321

This paper discusses the inherent challenges of SQL and nosql object mapping, primarily focusing on the heterogeneity of data models and its impact on database relationship. In nosql databases, relationships between entities can be defined using references or embedded objects. Each method has its advantages and trade-offs, and different nosql DBMS adopt different strategies based on their design principles and use cases. We examine how different SQL Database Management Systems (DBMS) handle relationships between entities, specifically comparing the use of embedded objects in MongoDB with the graph-based reference system in Neo4J. Object mapping is built using property graphs that represent the schema in the database. The framework was tested using the hospital information system medical record module. The results of this study show that the object mapping that has been built can run query commands on three distinct types of databases: MySQL, MongoDB, and Neo4j.

关键词： Electrical engineering Computer science Hospitals nosql databases Focusing Data models Informatics

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Digitization of Medical Data: LLM-Based Data Entry, Cleansing, and Visualization Solutions

Digitization of Medical Data: LLM-Based Data Entry, Cleansin...

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Learning and Technology Conference (L&T)

作者： Mahmoud Amgad Bahaa Shamoon Hagar Mekhemar Rodeen Mostafa Toqa Tamer Habiba Mohamed Sahar Fawzi Center for Informatics Science (CIS) School of Information Technology and Computer Science Nile University Sheikh Zayed City Giza Egypt

ISBN: (数字)9798331532215

ISBN: (纸本)9798331532222

Healthcare data management faces several challenges, including errors from manual data entry, variations in data quality, and an increasing need for advanced tools to efficiently handle large datasets. This paper introduces Data-Care, an innovative application designed to automate medical record digitization by leveraging advanced technologies such as Large Language Models (LLMs), Optical Character Recognition (OCR), and nosql databases. Together, these technologies significantly reduce the need for manual input, minimizing errors and enhancing data accuracy. A key feature of Data-Care is its data cleansing module, which resolves issues like data inconsistencies and missing values, ensuring the integrity and accuracy of the dataset. Additionally, the application provides a powerful offline visualization tool, enabling healthcare professionals to generate comprehensive reports that support informed decision-making and streamline workflows across various healthcare processes. Extensive performance tests demonstrated that the integration of LLMs and OCR in Data-Care achieved accuracy rates between 76% and 93%, depending on the quality of the input data. These results underscore Data-Care's capacity to improve both the speed and accuracy of data entry, offering a robust solution for the digitization and management of healthcare data.

关键词： Accuracy Data integrity nosql databases Large language models Optical character recognition Decision making Data visualization Medical services Manuals Usability

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Mastering nosql Through SQL Foundations

Mastering NoSQL Through SQL Foundations

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IEEE Integrated STEM Education Conference (ISEC)

作者： Xavier Amparo Ching-Yu Huang Department of Computer Science and Technology Kean University Union United States of America

ISBN: (数字)9798350352801

ISBN: (纸本)9798350352818

Database management systems are a cornerstone of software engineering projects. These systems are often run using MySQL, often used for relational and structured data or nosql for unstructured or semi-structured data. nosql is often used for real-time analysis of big data, content management systems, and document management systems. Many companies such as Google or Facebook have their own nosql databases that they use for their businesses, with BigTable and Cassandra being the examples for the aforementioned corporate entities. MongoDB is an open-source document database classified as a nosql database and is the platform used for nosql in this study. This study aims to compare nosql and MySQL. This study is also to understand the best way to teach nosql in classrooms to students as right now, nosql is not typically taught as its own topic or course subject in classes, with MySQL taking priority. A comparison between both MySQL and nosql can help with examining the effects of how the prior knowledge from taking a class that utilizes MySQL can be used to learn nosql. An accessible method for learning the management system exists in the form of MongoDB, an accessible platform for students to interact with and learn the language.

关键词： Structured Query Language Content management Social networking (online) nosql databases Education Real-time systems Registers

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A Cost-Effective Air Quality Monitoring System for the Global South

A Cost-Effective Air Quality Monitoring System for the Globa...

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IEEE Canada International Humanitarian Technology Conference (IHTC)

作者： Ryan Mckenzie Antonio Cervello Vongani Chabalala Isaiah Chiraira Thuso Mathaha Lotta Mayana Nkosiphendule Njara Jude Kong Ling Cheng Bruce Mellado School of Physics University of the Witwatersrand Johannesburg RSA Institut de Física Corpuscular University of Valencia Valencia Spain School of Electrical and Information Engineering University of the Witwatersrand Johannesburg RSA Dalla Lana School of Public Health University of Toronto Toronto Canada

ISBN: (数字)9798350354645

ISBN: (纸本)9798350354652

Air quality monitoring is crucial for mitigating the health risks associated with ambient air pollution, particularly in low- and middle-income countries, where resources for such systems are often limited. Traditional monitoring solutions are expensive, resulting in sparse data coverage and inequitable access to air quality information. This paper introduces the AI_r system, developed by the South African Consortium of Air Quality Monitoring (SACAQM), as a cost-effective air quality monitoring solution designed for the Global South. Leveraging Internet-of-Things (IoT) technology and low-cost sensors, the system establishes a dense network that provides high-resolution, real-time air quality data. The architecture includes clustered Wireless Sensor Networks (WSNs) Long-Term Evolution (LTE) communication, with data stored in a nosql database and accessed via an interactive dashboard. Calibration against established air quality systems, such as the South African Air Quality Information System (SAAQIS), ensures data accuracy and reliability. Additionally, the system integrates Artificial Intelligence (AI) techniques, including Graph Neural Networks (GNNs), to model and predict air quality trends. The system has been successfully piloted with sensor deployments in schools in Soweto, Johannesburg. The AI_r system aims to democratize access to critical air quality data, supporting public health initiatives and policy development to improve air quality, particularly for vulnerable populations.

关键词： Wireless sensor networks nosql databases Predictive models Air quality Sensor systems Real-time systems Reliability Artificial intelligence Public healthcare Monitoring

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A Method for Accelerating Encrypted Data Search in Laravel Applications Using a Coded Search Parameter

A Method for Accelerating Encrypted Data Search in Laravel A...

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Telecommunications Forum (TELFOR)

作者： A. Muratovic A. Tanovic Faculty of Engineering and Natural Science University of Zenica Zenica Bosnia and Herzegovina Faculty of Electrical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina

ISBN: (数字)9798350391060

ISBN: (纸本)9798350391077

Efficiently searching encrypted data within web applications presents a significant challenge for software engineers, primarily because traditional search methods necessitate decrypting each record individually to check for matches, leading to considerable computational overhead. The authors in this paper introduce an optimized search methodology for encrypted data in Laravel web applications by implementing a Coded Search Parameter (CSP). By incorporating an additional attribute into the MySQL database entity, which stores a coded representation of the initial character of the encrypted data - we substantially reduce server resource consumption and search time. During the search process, the algorithm initially executes a query filtered by the CSP attribute value, effectively narrowing down potential matches before decrypting the now reduced set of records. This approach also ensures that personal data remains protected without compromising data security. In this paper we provide a detailed exposition of the CSP method's implementation, evaluate its impact on search efficiency and present performance improvement analyses compared to traditional encrypted data search methods. Based on the research findings, it is concluded that the CSP method in Laravel applications significantly reduces search time for encrypted data, achieving an average acceleration of 73.58%.

关键词： Matched filters Search methods System performance nosql databases Distributed databases Filtering algorithms Software Telecommunications Cryptography Servers

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Layered Data Pipeline for Context-Aware Electronic Health Records and Healthcare Services

Layered Data Pipeline for Context-Aware Electronic Health Re...

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International Conference on e-health Networking, Applications and Services (HealthCom)

作者： Ahmed Khaled Muhammad Bangash Department of Computer Science Northeastern Illinois University Chicago IL USA

ISBN: (数字)9798350350548

ISBN: (纸本)9798350350555

Recent advances in healthcare have provided a wide range of medical devices and biosensors that collect biomedical data from patients during different monitoring phases. At the same time, data repositories and data-oriented frameworks are needed to store, manage, analyze, and act upon the collected data to enable a wide range of healthcare services. However, storing raw medical data (e.g., hospital visits, vital signs) with no context offers incomplete information to the medical staff and facilities to efficiently offer services. Along with the raw data challenge, given the heterogeneity of the collected medical data and the medical services to be offered, utilizing one form of data repository can be challenging. In this paper, we propose layered data pipeline that targets these challenges through two main aspects. The first aspect is to build Context-aware Electronic Health Records (EHRs) that link the collected medical data with the context for a more concrete and profound image of the patient's medical status. The second aspect is to build a data pipeline that utilizes a set of databases to store, manage, and represent the EHRs and specific sub-portions to enable both patient-oriented and collective-oriented healthcare services. Patient-oriented services focus on individual EHRs for customized and tailored healthcare assistance, while collective-oriented services consider an anonymous collection of EHRs linked together to build a knowledge graph. The proposed system comprises three layers, where each layer builds parts of the context-aware EHRs and hosts certain stages of the data pipeline. The system is a work in progress, and in this paper, we discuss the main components of the proposed system, define the high-level structure of context-aware EHR, and present the proposed data pipeline through a proof-of-concept implementation for certain features.

关键词： Medical devices databases Hospitals nosql databases Pipelines Medical services Knowledge graphs Electronic medical records Monitoring Biomedical imaging

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EHR Data Persistence for a Nationwide Shared Medical Record: An Overview

EHR Data Persistence for a Nationwide Shared Medical Record:...

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International Conference on Wireless Networks and Mobile Communications (WINCOM)

作者： Latifa OUFKIR Asma EL HAMZAOUI Laboratory of Research in Information Technology and Telecommunication (LRIT) Rabat IT Center Faculty of Sciences Mohammed V University Rabat Morocco Smart Embedded Enterprise and Distributed Systems (SEEDS) Institut National des Postes et Télécommunications Rabat Morocco

ISBN: (数字)9798350377866

ISBN: (纸本)9798350377873

Electronic health records (EHR) are considered the backbone of modern health system. When they are implemented effectively at scale, they hold the promise of enhancing healthcare services' quality and efficiency. However, EHR implementations vary based on factors such as EHR usage scenarios and technological capacities, resulting in varying volumes, complexity, and types of healthcare data. Consequently, the data storage model and query capabilities must align with these variations to achieve desired outcomes. This paper reviews the standardized EHR data persistence based on existing EHR literature and discusses its appropriateness for current healthcare usage scenarios including nationwide access. Insights into relevant literature reveal that nosql databases are more appropriate for current EHR usage scenarios. However, choosing among nosql databases’ persistence depends on the use case it is intended for in addition to the standards used for data integration between systems. Accordingly, clinical usage scenarios are best served with document stores for standardized EHR following the dual model. For population-based queries, JSON stores provide a good balance between storage capacity, query performance, and flexibility. The graph-based model presents a good solution for nationwide access considering the workload and the interconnected healthcare data nature and structure. One way to respond to the conflicting data persistence requirements is the multi-model database (MMDB) concept in both its forms: polyglot and multi-model databases.

关键词： Runtime databases Reviews Wireless networks nosql databases Medical services Mobile communication

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