A Comparative study of SQL Databases and NoSQL Databases for E-Commerce

With the advent of E-Commerce, businesses persistently examine various ways to improvise and accomplish their demands with web engineering that provide notable resolution. The progress in economic status demands colossal databases that store the data efficiently. The databases currently used are relational or non-relational. Both these types have their benefits and limitations that influence the overall processing of data. Non-relational databases are referred to as NoSQL-not only SQL, and Relational databases are known as SQL-Structured Query Language. It has been suggested in many studies that NoSQL databases surpass SQL databases. Our paper aims to evaluate these claims by analyzing the CRUD [Create, Read, Update, Delete] operations executed by both database types. Keywords: NoSQL, SQL, Non-relational Databases, MySQL, E-Commerce, MongoDb , Relational Databases

Diagnósticos de enfermagem prevalentes de pacientes em cuidados paliativos: uma mineração de dados

Introdução: o cuidado paliativo é centrado no paciente e inclui abordagens para o alívio dos sintomas e redução fisiológica e sofrimento psíquico associado à doença. Neste contexto, o diagnóstico de enfermagem (DE) estabelece bases para a seleção de intervenções de enfermagem para alcançar resultados nesta população, pelos quais o enfermeiro é responsável. Objetivo: identificar os DE prevalentes em pacientes em cuidados paliativos, perfil sociodemográfico e clínico de pacientes adultos hospitalizados que receberam consultorias em cuidados paliativos em unidades clínicas e cirúrgicas registrados em prontuário eletrônico. Método: estudo observacional retrospectivo com uso secundário de dados. A população do estudo foi composta por todos os adultos internados nas unidades clínicas e cirúrgicas de um hospital universitário entre junho de 2014 e julho de 2019, totalizando aproximadamente 51.000 prontuários únicos. A amostra compreendeu os pacientes que receberam consultorias em cuidados paliativos durante a internação. A análise dos dados foi realizada por meio do Structured Query Language (SQL). Resultados: foram eleitos 91 diferentes diagnósticos de enfermagem distintos para a amostra do estudo. Destes, três DE foram prevalentes: Risco de quedas esteve presente na prescrição de 1350 pacientes, Integridade tissular prejudicada em 1073 prescrições e Dor aguda em 1032. Conclusão: espera-se que a metodologia adotada nesta pesquisa apoie o processo de tomada de decisão dos profissionais de saúde, a fim de melhorar a eficácia no cuidado paliativo e otimizar o processo de segurança do paciente.

A Natural Language Interface to Relational Databases Using an Online Analytic Processing Hypercube

Structured Query Language (SQL) is commonly used in Relational Database Management Systems (RDBMS) and is currently one of the most popular data definition and manipulation languages. Its core functionality is implemented, with only some minor variations, throughout all RDBMS products. It is an effective tool in the process of managing and querying data in relational databases. This paper describes a method to effectively automate the conversion of a data query from a Natural Language Query (NLQ) to Structured Query Language (SQL) with Online Analytical Processing (OLAP) cube data warehouse objects. To obtain or manipulate the data from relational databases, the user must be familiar with SQL and must also write an appropriate and valid SQL statement. However, users who are not familiar with SQL are unable to obtain relevant data through relational databases. To address this, we propose a Natural Language Processing (NLP) model to convert an NLQ into an SQL query. This allows novice users to obtain the required data without having to know any complicated SQL details. The model is also capable of handling complex queries using the OLAP cube technique, which allows data to be pre-calculated and stored in a multi-dimensional and ready-to-use format. A multi-dimensional cube (hypercube) is used to connect with the NLP interface, thereby eliminating long-running data queries and enabling self-service business intelligence. The study demonstrated how the use of hypercube technology helps to increase the system response speed and the ability to process very complex query sentences. The system achieved impressive performance in terms of NLP and the accuracy of generating different query sentences. Using OLAP hypercube technology, the study achieved distinguished results compared to previous studies in terms of the speed of the response of the model to NLQ analysis, the generation of complex SQL statements, and the dynamic display of the results. As a plan for future work, it is recommended to use infinite-dimension (n-D) cubes instead of 4-D cubes to enable ingesting as much data as possible in a single object and to facilitate the execution of query statements that may be too complex in query interfaces running in a data warehouse. The study demonstrated how the use of hypercube technology helps to increase system response speed and process very complex query sentences.

DESENVOLVIMENTO DE UM OBJETO DE APRENDIZAGEM NO PADRÃO SCORM PARA O ENSINO DE BANCO DE DADOS INTEGRADO AO AMBIENTE VIRTUAL DE APRENDIZAGEM MOODLE

No aprendizado de programação, o aluno pode apresentar dificuldades em compreender a conceituação de algumas disciplinas, por exemplo Lógica de Programação, Estrutura de Dados e Banco de Dados. Assim, observa-se a necessidade de usar recursos eficientes para melhoria no ensino e aprendizagem de Banco de Dados, podendo resultar em: maior interesse do aluno na área; desenvolvimento de pesquisas voltadas ao ensino; e motivação nesse tipo de aplicação. Para isso, percebe-se a necessidade de implementar objetos de Aprendizagem (OAs) que forneçam e agreguem conhecimento. A criação do OA favorece o desenvolvimento das atividades, motivando os estudantes a interagir e refletir sobre os conteúdos abordados, ou seja, servem de apoio ao processo de ensino e aprendizagem. Com base neste contexto, o presente estudo teve como objetivo desenvolver um OA adaptado ao padrão SCORM para o ensino de banco de dados a ser integrado em um ambiente virtual de aprendizagem. O objeto de aprendizagem desenvolvido é composto por recursos como texto e imagens sobre conceitos de Structured Query Language (SQL), fazendo com que o aluno, através do seu uso consiga entender melhor conceitos que são abordados na disciplina de Banco de Dados.

Control Ports Authorities’ Equipment Based on RFID and SQL Security System

Equipment surveillance or tracking is a hard-to-accomplish mission for a multi-locations company. This study examines a complete security system in Alexandria and EL-Dekheila ports of Egypt, as case study, to track equipment location. The system uses RFID (radio frequency identification) and Arduino kit as hardware to detect equipment motion, and visual studio and SQL (structured query language) as software to produce reports. The original place of equipment is saved as a reference. IR and RFID sensors are used at every department’s gate for IT access and for detecting and decoding the received equipment’s RFID card and ID data. Visual studio and SQL help in issuing the report on each equipment’s location and movement time. The system sends instant email messages and cellular phone messages to the control room.

Research on Simufact simulation data processing system based on QT and MySQL

As the simulation data of the Simufact Additive software was inconvenient to process, QT and structured query language (MySQL) database were used to develop the database to solve the processing of the simulation data. The GUI interface that has the functions of processing and saving the simulation data was designed. The interface developed by QT was used to start the Simufact Additive software, connect to the MySQL database and save the simulation data. The results showed that using MySQL as the management of simulation data has achieved better results in the post-processing of simulation data.

Development of a Structured Query Language and Natural Language Processing Algorithm to Identify Lung Nodules in a Cancer Centre

Importance: The stratification of indeterminate lung nodules is a growing problem, but the burden of lung nodules on healthcare services is not well-described. Manual service evaluation and research cohort curation can be time-consuming and potentially improved by automation.Objective: To automate lung nodule identification in a tertiary cancer centre.Methods: This retrospective cohort study used Electronic Healthcare Records to identify CT reports generated between 31st October 2011 and 24th July 2020. A structured query language/natural language processing tool was developed to classify reports according to lung nodule status. Performance was externally validated. Sentences were used to train machine-learning classifiers to predict concerning nodule features in 2,000 patients.Results: 14,586 patients with lung nodules were identified. The cancer types most commonly associated with lung nodules were lung (39%), neuro-endocrine (38%), skin (35%), colorectal (33%) and sarcoma (33%). Lung nodule patients had a greater proportion of metastatic diagnoses (45 vs. 23%, p < 0.001), a higher mean post-baseline scan number (6.56 vs. 1.93, p < 0.001), and a shorter mean scan interval (4.1 vs. 5.9 months, p < 0.001) than those without nodules. Inter-observer agreement for sentence classification was 0.94 internally and 0.98 externally. Sensitivity and specificity for nodule identification were 93 and 99% internally, and 100 and 100% at external validation, respectively. A linear-support vector machine model predicted concerning sentence features with 94% accuracy.Conclusion: We have developed and validated an accurate tool for automated lung nodule identification that is valuable for service evaluation and research data acquisition.

Tipologi batas wilayah administrasi untuk memudahkan pengelolaan batas daerah di Indonesia

Abstrak Terhitung sejak 1945 – 2017, baru sekitar 48% dari 977 segmen batas daerah di Indonesia yang disahkan melalui Peraturan Menteri Dalam Negeri tentang batas daerah. Pengelolaan batas wilayah daerah sangat penting untuk berbagai urusan pembangunan misalnya pengelolaan sumber daya alam. Oleh karena itu, penelitian ini mengusulkan pendekatan baru untuk mendukung pengelolaan batas wilayah yang efisien yaitu melalui segmentasi berbasis tipologi batas wilayah. Tahapan analisis meliputi: membandingkan, memotong, dan mengelompokkan garis batas. Single Buffer Overlay Method digunakan untuk membandingkan unsur geografis pada Peta Rupabumi Indonesia (data referensi) dan garis batas 2017 (data yang diuji). Selanjutnya, dilakukan pemotongan garis sesuai hasil perbandingan. Pada akhirnya, garis tersebut dikelaskan berdasarkan tipologinya (igir, jalan, dan sungai) menggunakan metode SQL (Structured Query Language). Hasil penelitian menunjukkan bahwa mayoritas (41,8%) batas daerah di Indonesia tidak menggunakan unsur geografis tertentu sebagai penanda batasnya, sedangkan persentase penanda batas berupa sungai 35,9%, igir 16,4%, dan jalan 5,8%. Abstract Since 1945 – 2017, only 48% of 977 regional borderlines of Indonesia were legalized by The Ministry of Home Affairs. Properly managed intra-national boundaries are fundamental for development purposes e.g. natural resource management. Therefore, this research proposed a new approach to help managing the boundary efficiently through typology-based borderlines segmentation which was conducted by some stages: compare, split, and classify lines. Single Buffer Overlay Method used for comparison purpose by utilizing some geographical features on a topographic map as a referenced dataset and boundary line (2017 database) as a tested dataset. Then we split the lines based on the comparison result. Finally, each split line was classified into border typologies (road, ridge, and stream) by using the SQL (Structured Query Language) method. We found that most of The Indonesian administrative boundary segments (41.8%) did not use a geographical feature, while the boundary on the rivers 35.9%, ridges 16.4%, and roads 5.8%.