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Database querying using SQL
Published in Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton, Texts in Statistical Science, 2017
Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
MySQL is based on a client-server model. This means that there is a database server that stores the data and executes queries. It can be located on the user’s local computer or on a remote server. We will be connecting to the server located at scidb.smith.edu. To retrieve data from the server, one can connect to it via any number of client programs. One can of course use the command-line mysql program, or the official GUI application: MySQL Workbench. While we encourage the reader to explore both options—we most often use the Workbench for MySQL development—the output you will see in this presentation comes directly from the MySQL command line client.
Database querying using SQL
Published in Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton, Modern Data Science with R, 2021
Benjamin S. Baumer, Daniel T. Kaplan, Nicholas J. Horton
MySQL is based on a client-server model. This means that there is a database server that stores the data and executes queries. It can be located on the user’s local computer or on a remote server. We will be connecting to a server hosted by Amazon Web Services. To retrieve data from the server, one can connect to it via any number of client programs. One can of course use the command-line mysql program, or the official GUI application: MySQL Workbench. While we encourage the reader to explore both options—we most often use the Workbench for MySQL development—the output you will see in this presentation comes directly from the MySQL command line client.
Implementing a web-based optimized artificial intelligence system with metaheuristic optimization for improving building energy performance
Published in Journal of Asian Architecture and Building Engineering, 2023
Ngoc-Tri Ngo, Ngoc-Son Truong, Thi Thu Ha Truong, Anh-Duc Pham, Nhat-To Huynh
The data layer aims to collect and store data. Collected data involves energy consumption data, weather data, and building information. The cloud database system in Amazon RBS was used to store data and the MySQL workbench was used to connect with the database system in Amazon RBS. The collected data can be accessed and played easily with the MySQL workbench. The analytics layer was used to preprocess the raw data, such as dealing with the missing data, extracting temporal data, and feature selection. The hybrid AI model was developed in the analytics layer to predict future energy consumption in buildings. Notably, the hybrid AI model takes advantage of SVR-based machine learning model and an optimization algorithm to enhance the efficacy of the prediction task. This layer performed the data analytics to produce useful information for monitoring and predicting energy use in buildings. A web-based system is developed and integrated within the decision-support information layer. The layer of decision-support information visualized insights and information that were derived from the analytics layer.
Development of an augmented reality-based process management system: The case of a natural gas power plant
Published in IISE Transactions, 2022
Mustafa Esengün, Alp Üstündağ, Gökhan İnce
After designing the structure of the proposed framework, all modules, user interfaces and backend engine were implemented. In the implementation phase, following software were used:Microsoft Visual Studio: Implementation of the web interface, backend and batches of the web platform, backend of the mobile application.MySQL Workbench: Implementation of the database of the system including tables and procedures.DevExpress: Implementation of the front-end interface elements of the web platform.Unity3D: Implementation of the mobile application and the WebGL application to be used in the 3D editor interface in the web platform, where the process managers upload and manage the augmentations.Vuforia SDK: Implementation of the marker-based AR functionality in the mobile application.