الصفحة 1
الصفحة 1
International conference on terrain and geohazard challenges facing onshore oil and gas pipelines : Evaluation, routing, resign, construction, operation ; Proceedings of a three day international conference on terrain and geohazard challenges facing onshore oil and gas pipelines, organised by the Institution of Civil Engineers in association with BP Exploration and held at the Institution of Civil Engineers, London, UK, on 2 – 4 June 2004
To access global oil and gas deposits, major pipelines must traverse remote regions with extreme terrains. There are a significant number of pipeline projects, active or planned, in tropical jungles, mountains and deserts, in permafrost and in areas of wetland. Each of these natural environments is associated with a range of geohazards, which may include landslides, soil erosion, karst, river migration, and seismic or volcanic activity. At the same time, society demands increasing availability and reliability of supply, together with improved environmental standards, all making for substantial challenges.
DevOps Tools for Java Developers : Best Practices from Source Code to Production Containers
Explore software lifecycle best practices Use DevSecOps methodologies to facilitate software development and delivery Understand the business value of DevSecOps best practices Manage and secure software dependencies Develop and deploy applications using containers and cloud native technologies Manage and administrate source control repositories and development processes Use automation to set up and administer build pipelines Identify common deployment patterns and antipatterns Maintain and monitor software after deployment
Data science on the Google cloud platform : Implementing end-to-end real-time data pipelines : From ingest to machine learning
Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build using Google Cloud Platform (GCP). This hands-on guide shows data engineers and data scientists how to implement an end-to-end data pipeline with cloud native tools on GCP. You'll work through a sample business decision by employing a variety of data science approaches. Follow along by building a data pipeline in your own project on GCP, and discover how to solve data science problems in a transformative and more collaborative way. Employ best practices in building highly scalable data and ML pipelines on Google Cloud Automate and schedule data ingest using Cloud Run Create and populate a dashboard in Data Studio Build a real-time analytics pipeline using Pub/Sub, Dataflow, and BigQuery Conduct interactive data exploration with BigQuery Create a Bayesian model with Spark on Cloud Dataproc Forecast time series and do anomaly detection with BigQuery ML Aggregate within time windows with Dataflow Train explainable machine learning models with Vertex AI Operationalize ML with Vertex AI Pipelines
