The 5th IEEE International Conference on Applied System Innovation 2019 (IEEE ICASI 2019, https://2019.icasi-conf.net/), which was held in Fukuoka, Japan, on 11–15 April, 2019, provided a unified communication platform for a wide range of topics. This Special Issue entitled “Selected Papers from IEEE ICASI 2019” collected nine excellent papers presented on the applied sciences topic during the conference. Mechanical engineering and design innovations are academic and practical engineering fields that involve systematic technological materialization through scientific principles and engineering designs. Technological innovation by mechanical engineering includes information technology (IT)-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanoscience and nanotechnology. These new technologies that implant intelligence in machine systems represent an interdisciplinary area that combines conventional mechanical technology and new IT. The main goal of this Special Issue is to provide new scientific knowledge relevant to IT-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanoscience and nanotechnology.

Troubleshoot query performance issues, identify anti-patterns in your code, and write efficient T-SQL queries with this guide for T-SQL developers Key Features A definitive guide to mastering the techniques of writing efficient T-SQL code Learn query optimization fundamentals, query analysis, and how query structure impacts performance Discover insightful solutions to detect, analyze, and tune query performance issues Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionData professionals seeking to excel in Transact-SQL for Microsoft SQL Server and Azure SQL Database often lack comprehensive resources. Learn T-SQL Querying second edition focuses on indexing queries and crafting elegant T-SQL code enabling data professionals gain mastery in modern SQL Server versions (2022) and Azure SQL Database. The book covers new topics like logical statement processing flow, data access using indexes, and best practices for tuning T-SQL queries. Starting with query processing fundamentals, the book lays a foundation for writing performant T-SQL queries. You’ll explore the mechanics of the Query Optimizer and Query Execution Plans, learning to analyze execution plans for insights into current performance and scalability. Using dynamic management views (DMVs) and dynamic management functions (DMFs), you’ll build diagnostic queries. The book covers indexing and delves into SQL Server’s built-in tools to expedite resolution of T-SQL query performance and scalability issues. Hands-on examples will guide you to avoid UDF pitfalls and understand features like predicate SARGability, Query Store, and Query Tuning Assistant. By the end of this book, you‘ll have developed the ability to identify query performance bottlenecks, recognize anti-patterns, and avoid pitfallsWhat you will learn Identify opportunities to write well-formed T-SQL statements Familiarize yourself with the Cardinality Estimator for query optimization Create efficient indexes for your existing workloads Implement best practices for T-SQL querying Explore Query Execution Dynamic Management Views Utilize the latest performance optimization features in SQL Server 2017, 2019, and 2022 Safeguard query performance during upgrades to newer versions of SQL Server Who this book is for This book is for database administrators, database developers, data analysts, data scientists and T-SQL practitioners who want to master the art of writing efficient T-SQL code and troubleshooting query performance issues through practical examples. A basic understanding of T-SQL syntax, writing queries in SQL Server, and using the SQL Server Management Studio tool will be helpful to get started.

This two-volume set, LNCS 12858 and 12859, constitutes the thoroughly refereed proceedings of the 5th International Joint Conference, APWeb-WAIM 2021, held in Guangzhou, China, in August 2021. The 44 full papers presented together with 24 short papers, and 6 demonstration papers were carefully reviewed and selected from 184 submissions. The papers are organized around the following topics: Graph Mining; Data Mining; Data Management; Topic Model and Language Model Learning; Text Analysis; Text Classification; Machine Learning; Knowledge Graph; Emerging Data Processing Techniques; Information Extraction and Retrieval; Recommender System; Spatial and Spatio-Temporal Databases; and Demo.