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Calibration Procedures and Experiments
Published in Howard E. Hesketh, Air And Waste Management, 2019
Wet test meters are frequently used as a laboratory standard. The time required for equilibration of water temperature and dissolved gases in the water and the bulk and weight of the meter makes it very difficult to use the wet test meter in the field. Wet test meters are very accurate, yet are classified as an intermediate standard, because they cannot be calibrated by physical dimensional measurement. Therefore, wet test meters must be calibrated against a primary standard. An easy-to-use, inexpensive method to calibrate the wet test meter is the displacement bottle technique. A Class A volumetric flask is used to measure the displaced water and is considered the primary standard.
Simulation and Modeling Tools for Fog Computing
Published in Ravi Tomar, Avita Katal, Susheela Dahiya, Niharika Singh, Tanupriya Choudhury, Fog Computing, 2023
Antonio A. T. R. Coutinho, Elisangela O. Carneiro, Fabíola Greve
FogDirSim is built on a microservices architecture consisting of a collection of independently deployable services that communicate via RESTful APIs. The simulator consists of four significant microservices (Forti, Pagiaro, and Brogi 2020), which are described as follows: API Gateway: This is implemented with the Python Flask micro-framework, and it exposes an API (FD) compliant with a feature-complete subset of the actual Cisco FogDirector API (FD). This micro-service also exposes a custom API (SIM) to retrieve data about the current simulation.Database: The database microservice manages two non-relational databases implemented with MongoDB. The first (InfrastructureDB) stores all the information about the monitored infrastructure devices and the probabilistic distributions of their available resources (CPU, RAM). The second database (SimulationDB) maintains state information about the simulated infrastructure resources and application deployments.Simulation engine: This is a discrete-event simulator implemented in Python. It runs a simulation loop that: (i) samples a particular state of the infrastructure and application workload based on the probability distributions defined in the database microservice; (ii) updates statistics on device and application status and checks for alerts triggered during the sampled state; and (iii) pops and executes the next client request to be simulated from the event queue.GUI: A web-based graphical user interface (GUI) displays key performance indicators (KPIs) for the currently running simulation. Additionally, it is responsible for data aggregation and computation of some of the results output by the simulator. The FogDirSim can be used to assist in determining when and where to migrate a particular application, how to handle failures and node workload variations best, how many application replicas are required to achieve the desired uptime, and how to reduce energy consumption caused by an inefficient management policy.
A guideline to implement a CPS architecture in an SME
Published in Production & Manufacturing Research, 2023
Jean-Rémi Piat, Christophe Danjou, Bruno Agard, Robert Beauchemin
The development of RESTFUL application can be done with Python using specific libraries including Flask for the body of the application and SQLalchemy for the SQL queries in the database. These libraries are compatible with the Json Web Token (JWT) authorization standard. Other technologies exist but depend on the skills of the development team.