This document summarizes the key points about database normalization from Chapter 3 of an unknown textbook. It discusses:
1. The reasons for normalizing a database, including improving accuracy, efficiency, and making queries and reports easier.
2. The concept of normalization as a sequence of steps to improve database design by putting relations into a more desirable form and removing duplication.
3. The three normal forms - first, second, and third - and how to achieve each by removing certain types of dependencies between attributes.
4. An example of normalizing a table through a three-step process to convert it into third normal form.
The document discusses normalization of databases. It explains the different normal forms including 1NF, 2NF, 3NF, BCNF and 4NF. It defines functional dependencies and different types of anomalies like insertion, deletion and update anomalies. Examples are provided to show how relations can be transformed from lower to higher normal forms by eliminating anomalies through decomposition. The goal of normalization is to produce well-structured relations by eliminating redundancies and anomalies.
The document discusses different normal forms for organizing data in a database, including 1NF, 2NF, 3NF, and BCNF. 1NF requires attributes to be atomic and no repeating groups. 2NF removes partial dependencies by requiring non-prime attributes to depend on the whole primary key. 3NF removes non-key attributes that are not dependent on the primary key. BCNF is stronger than 3NF and requires all determinants to be candidate keys. Examples are provided to illustrate how relations can be decomposed to satisfy 3NF and BCNF.
The document discusses database normalization. It defines normalization as a process of organizing data in a database to eliminate redundancy and undesirable characteristics like insertion, update, and deletion anomalies. The goals of normalization are stated as eliminating redundant data and ensuring logical data storage. Several normal forms are described - 1st, 2nd, 3rd normal form, and Boyce-Codd normal form. The stages of normalization are outlined and examples are provided to illustrate normalization techniques.
The document discusses the Normal Forms 3NF and BCNF. It defines 3NF as removing columns that are not dependent on the primary key. BCNF is defined as requiring that every determinant must be a candidate key. An example shows a relation transformed into BCNF by removing a violating functional dependency and creating two new relations.
Normalization is a process of organizing data to reduce redundancy and improve data integrity. It involves decomposing relations with anomalies into smaller, well-structured relations by identifying functional dependencies and applying normal forms. The normal forms are first normal form (1NF), second normal form (2NF), third normal form (3NF) and Boyce-Codd normal form (BCNF). Each normal form adds additional rules to reduce redundancy through a multi-step process of identifying dependencies and extracting subsets of data into new relations.
The PPT would provide the Database Normalization is to restructure the logical data model of a database to:
Eliminate Redundancy
Organize Data Efficiently
Reduce the potential for Data Anomalies.
Normalization is the process of reducing data duplication in a database. It involves separating relations into multiple tables to eliminate anomalies like insertion, deletion, and modification anomalies. The document describes the process of normalizing a sample "ClientRental" table from an unnormalized form to first, second, and third normal form through removing repeating groups and splitting tables based on functional dependencies between attributes.
Normalization is the process of reorganizing data in a database so that it meets two basic requirements:
(1) There is no redundancy of data (all data is stored in only one place),
(2) data dependencies are logical (all related data items are stored together).
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@ Kindly Follow my Instagram Page to discuss about your mental health problems-
-----> https://instagram.com/mentality_streak?utm_medium=copy_link
@ Appreciate my work:
-----> behance.net/burhanahmed1
Thank-you !
The document discusses normalization of databases. It explains the different normal forms including 1NF, 2NF, 3NF, BCNF and 4NF. It defines functional dependencies and different types of anomalies like insertion, deletion and update anomalies. Examples are provided to show how relations can be transformed from lower to higher normal forms by eliminating anomalies through decomposition. The goal of normalization is to produce well-structured relations by eliminating redundancies and anomalies.
The document discusses different normal forms for organizing data in a database, including 1NF, 2NF, 3NF, and BCNF. 1NF requires attributes to be atomic and no repeating groups. 2NF removes partial dependencies by requiring non-prime attributes to depend on the whole primary key. 3NF removes non-key attributes that are not dependent on the primary key. BCNF is stronger than 3NF and requires all determinants to be candidate keys. Examples are provided to illustrate how relations can be decomposed to satisfy 3NF and BCNF.
The document discusses database normalization. It defines normalization as a process of organizing data in a database to eliminate redundancy and undesirable characteristics like insertion, update, and deletion anomalies. The goals of normalization are stated as eliminating redundant data and ensuring logical data storage. Several normal forms are described - 1st, 2nd, 3rd normal form, and Boyce-Codd normal form. The stages of normalization are outlined and examples are provided to illustrate normalization techniques.
The document discusses the Normal Forms 3NF and BCNF. It defines 3NF as removing columns that are not dependent on the primary key. BCNF is defined as requiring that every determinant must be a candidate key. An example shows a relation transformed into BCNF by removing a violating functional dependency and creating two new relations.
Normalization is a process of organizing data to reduce redundancy and improve data integrity. It involves decomposing relations with anomalies into smaller, well-structured relations by identifying functional dependencies and applying normal forms. The normal forms are first normal form (1NF), second normal form (2NF), third normal form (3NF) and Boyce-Codd normal form (BCNF). Each normal form adds additional rules to reduce redundancy through a multi-step process of identifying dependencies and extracting subsets of data into new relations.
The PPT would provide the Database Normalization is to restructure the logical data model of a database to:
Eliminate Redundancy
Organize Data Efficiently
Reduce the potential for Data Anomalies.
Normalization is the process of reducing data duplication in a database. It involves separating relations into multiple tables to eliminate anomalies like insertion, deletion, and modification anomalies. The document describes the process of normalizing a sample "ClientRental" table from an unnormalized form to first, second, and third normal form through removing repeating groups and splitting tables based on functional dependencies between attributes.
Normalization is the process of reorganizing data in a database so that it meets two basic requirements:
(1) There is no redundancy of data (all data is stored in only one place),
(2) data dependencies are logical (all related data items are stored together).
↓↓↓↓ Read More:
@ Kindly Follow my Instagram Page to discuss about your mental health problems-
-----> https://instagram.com/mentality_streak?utm_medium=copy_link
@ Appreciate my work:
-----> behance.net/burhanahmed1
Thank-you !
The document discusses database normalization. It begins by explaining the first normal form (1NF), which requires data to be atomic and for each row to have a unique primary key. An example employee database is provided, and steps are taken to transform it into 1NF by creating individual rows for each employee. The document then covers the second normal form (2NF), which requires the database to be in 1NF and for non-key attributes to depend on the whole primary key. To achieve 2NF, repeating groups like city and state are extracted into separate tables. Finally, the third normal form (3NF) is discussed, requiring attributes to depend transitively on the primary key. An order database is used as an example, and
BigDansing is a big data cleansing system that can process large datasets using declarative quality rules and user defined functions (UDFs). It provides a generic abstraction that separates logical operators from physical operators to make the system independent and allow for multiple physical optimizations. The key logical operators are Scope, Block, Iterate, Detect, and GenFix which can represent most data quality rules. BigDansing automatically translates rules into logical plans and can consolidate plans for improved I/O performance. It was able to process 1.9 billion rows to find 13 billion violations in under 3 hours using 16 small machines, much faster than related work.
The document discusses database normalization. Some key points:
1. Normalization is the process of structuring data to reduce redundancy and dependency. It involves restructuring tables to meet higher forms of normalization like 1NF, 2NF, 3NF, BCNF, and others.
2. The levels of normalization address the amount of redundancy in data. Higher levels restrict more complex dependencies between attributes.
3. Examples demonstrate how to decompose tables to eliminate transitive functional dependencies and conform to higher normal forms like 2NF and 3NF. This involves moving attributes to new tables and establishing foreign keys.
INTRODUCTION
3NF and BCNF
Decomposition requirements
Lossless join decomposition
Dependency preserving decomposition
Disk pack features
Records and Files
Ordered and Unordered files
2NF,NF,3NF,BCNF
1. The document discusses database normalization, which involves restructuring tables to remove redundant data and organize related data.
2. It describes various forms of normalization including first normal form (1NF), second normal form (2NF), third normal form (3NF), and Boyce-Codd normal form (BCNF).
3. The goal of higher normalization forms is to minimize duplicate data and optimize the relationship between different attributes and tables.
1. The document discusses database normalization, which involves restructuring tables to remove redundant data and organize them according to different normal forms.
2. It describes the goals and characteristics of normalized databases as well as different normal forms including 1NF, 2NF, 3NF, BCNF, 4NF and 5NF.
3. Examples are provided to illustrate functional dependencies and how to decompose tables to higher normal forms by removing attributes dependent on subsets of candidate keys.
1. The document discusses database normalization, which involves restructuring tables to remove redundant data and organize them according to different normal forms.
2. It describes the goals and characteristics of normalized databases as well as different normal forms including 1NF, 2NF, 3NF, BCNF, 4NF and 5NF.
3. Examples are provided to illustrate functional dependencies and how to decompose tables to higher normal forms by removing attributes dependent on subsets of candidate keys or that have transitive dependencies.
1. The document discusses database normalization, which involves restructuring tables to remove redundant data and organize related data.
2. It describes various forms of normalization including first normal form (1NF), second normal form (2NF), third normal form (3NF), and Boyce-Codd normal form (BCNF).
3. The goal of higher normalization forms is to minimize duplicate data and optimize the relationship between different attributes and tables.
1. The document discusses database normalization, which involves restructuring tables to remove redundant data and organize related data.
2. It describes various forms of normalization including first normal form (1NF), second normal form (2NF), third normal form (3NF), and Boyce-Codd normal form (BCNF).
3. The goal of higher normalization forms is to minimize duplicate data and optimize the relationship between different attributes and tables.
normalization-Normalization -Process of Divide Tablesdharawagh9999
1. The document discusses database normalization, which involves restructuring tables to remove redundant data and organize related data.
2. It describes various forms of normalization including first normal form (1NF), second normal form (2NF), third normal form (3NF), and Boyce-Codd normal form (BCNF).
3. The goal of higher normalization forms is to minimize duplicate data and optimize the relationship between different attributes and tables.
The document discusses normalization in databases. It defines normalization as removing redundant data from tables to improve storage efficiency, data integrity, and scalability. The document outlines the various normal forms including 1NF, 2NF, 3NF, BCNF, and higher normal forms. It provides examples to illustrate different normal forms. Advantages of normalization include reduced database size and better performance, while disadvantages are more tables to join and codes instead of real data.
The normal forms (NF) of relational database theory provide criteria for determining a table’s degree of vulnerability to logical inconsistencies and anomalies.
The document discusses database normalization and various normal forms including first normal form (1NF), second normal form (2NF), third normal form (3NF), and Boyce-Codd normal form (BCNF). It provides examples of tables that are and are not in different normal forms and describes how to decompose tables to higher normal forms by removing functional dependencies between non-key attributes or attributes within a candidate key.
This document provides an overview of database normalization. It defines normalization as reducing redundancy and ensuring logical data dependencies. The document outlines the various normal forms from 1NF to BCNF and provides examples of converting tables between normal forms by removing redundancy and separating logically unrelated data. Benefits of normalization include reduced data size, faster queries, and improved data integrity. Complexity increases with additional tables and relationships between tables.
The document discusses normalization, which is the process of converting complex data structures into simple structures to avoid data duplication. It describes the three main steps of normalization: first normal form (1NF), second normal form (2NF), and third normal form (3NF). The document provides examples of tables and explains how to normalize them by removing anomalies like repeating groups and partial/transitive dependencies between attributes. While there are several normal forms, 3NF is sufficient for most use cases and removes all transitive dependencies. Functional dependencies, which define relationships between attributes, are also discussed.
The document discusses database normalization. Some key points:
- Normalization is the process of structuring data to reduce redundancy and dependency. It involves decomposing tables to successively higher normal forms.
- Common normal forms include 1NF, 2NF, 3NF, BCNF, and 4NF. Higher normal forms impose stricter rules to further reduce anomalies.
- The goals of normalization are to minimize duplication, reduce data modification issues, and simplify queries. Properly normalized data has several desirable characteristics including scalar fields and minimal null values and data loss.
Mca ii-dbms-u-iv-structured query languageRai University
The document discusses various forms of database normalization including first normal form (1NF), second normal form (2NF), third normal form (3NF), Boyce-Codd normal form (BCNF), and fourth normal form (4NF). It provides examples of database schemas that are and are not in each normal form and describes how to decompose schemas into normal form through lossless normalization techniques.
An introduction to database Normalization. An essential part of logical database design for relational databases. The presentation also has little coverage of related concepts like functional dependency, data anomalies, dependency preservation and lossless decomposition.
The document discusses relational database design and normalization. It defines relational database design as grouping attributes to form good relation schemas. It describes two levels of relation schemas - the logical user view level and the storage base relation level. The criteria for good base relations include semantics of relation attributes, redundancy and data anomalies, and null values in tuples. The purpose of normalization is to avoid redundancy and data anomalies like insertion, deletion, and modification anomalies. The document outlines the stages of normalization from unnormalized to fifth normal form and provides examples of relations in first, second, third, and Boyce-Codd normal forms.
On Relevant Query Answering over Streaming and Distributed DataShima Zahmatkesh
This document discusses optimizing query evaluation over streaming and distributed data to continuously obtain relevant results while maintaining system reactiveness. It proposes approaches for queries with filter clauses and top-k queries. For queries with filters, maintenance policies like Filter Update Policy and combined policies improve performance. For top-k queries, the Super-MTK+N list and Top-k+N algorithm handle changes to distributed data. The AcquaTop framework applies different maintenance policies. Experimental results show the approaches achieve more relevant and accurate results than the state-of-the-art.
Distributed systems allow for parallel and distributed computing across multiple autonomous computers connected through a network. There are different types of distributed systems such as high performance computing systems, distributed information systems, and distributed systems for pervasive services. Processes and threads are important concepts in distributed systems - a process is the instance of a program in execution and has state information stored in a process control block, while threads are lightweight processes that execute concurrently within a process and share the same memory address space. Remote procedure calls allow processes on different machines to communicate and invoke procedures remotely through a client-server model.
This document discusses a lecture on computer vision given by Dr. Eng. Mahmoud Shams at Kafrelsheikh University. It defines computer vision as dealing with how computers understand digital images and videos, and seeks to automate tasks of the human visual system. The lecture covers classification of AI, evaluation of computer vision algorithms, common computer vision tasks like localization and segmentation, and why benchmarks are important. It also discusses sources of noise in images, performance metrics like mean square error and confusion matrices, and some top computer vision tools like OpenCV, TensorFlow, Keras and YOLO.
The document discusses database normalization. It begins by explaining the first normal form (1NF), which requires data to be atomic and for each row to have a unique primary key. An example employee database is provided, and steps are taken to transform it into 1NF by creating individual rows for each employee. The document then covers the second normal form (2NF), which requires the database to be in 1NF and for non-key attributes to depend on the whole primary key. To achieve 2NF, repeating groups like city and state are extracted into separate tables. Finally, the third normal form (3NF) is discussed, requiring attributes to depend transitively on the primary key. An order database is used as an example, and
BigDansing is a big data cleansing system that can process large datasets using declarative quality rules and user defined functions (UDFs). It provides a generic abstraction that separates logical operators from physical operators to make the system independent and allow for multiple physical optimizations. The key logical operators are Scope, Block, Iterate, Detect, and GenFix which can represent most data quality rules. BigDansing automatically translates rules into logical plans and can consolidate plans for improved I/O performance. It was able to process 1.9 billion rows to find 13 billion violations in under 3 hours using 16 small machines, much faster than related work.
The document discusses database normalization. Some key points:
1. Normalization is the process of structuring data to reduce redundancy and dependency. It involves restructuring tables to meet higher forms of normalization like 1NF, 2NF, 3NF, BCNF, and others.
2. The levels of normalization address the amount of redundancy in data. Higher levels restrict more complex dependencies between attributes.
3. Examples demonstrate how to decompose tables to eliminate transitive functional dependencies and conform to higher normal forms like 2NF and 3NF. This involves moving attributes to new tables and establishing foreign keys.
INTRODUCTION
3NF and BCNF
Decomposition requirements
Lossless join decomposition
Dependency preserving decomposition
Disk pack features
Records and Files
Ordered and Unordered files
2NF,NF,3NF,BCNF
1. The document discusses database normalization, which involves restructuring tables to remove redundant data and organize related data.
2. It describes various forms of normalization including first normal form (1NF), second normal form (2NF), third normal form (3NF), and Boyce-Codd normal form (BCNF).
3. The goal of higher normalization forms is to minimize duplicate data and optimize the relationship between different attributes and tables.
1. The document discusses database normalization, which involves restructuring tables to remove redundant data and organize them according to different normal forms.
2. It describes the goals and characteristics of normalized databases as well as different normal forms including 1NF, 2NF, 3NF, BCNF, 4NF and 5NF.
3. Examples are provided to illustrate functional dependencies and how to decompose tables to higher normal forms by removing attributes dependent on subsets of candidate keys.
1. The document discusses database normalization, which involves restructuring tables to remove redundant data and organize them according to different normal forms.
2. It describes the goals and characteristics of normalized databases as well as different normal forms including 1NF, 2NF, 3NF, BCNF, 4NF and 5NF.
3. Examples are provided to illustrate functional dependencies and how to decompose tables to higher normal forms by removing attributes dependent on subsets of candidate keys or that have transitive dependencies.
1. The document discusses database normalization, which involves restructuring tables to remove redundant data and organize related data.
2. It describes various forms of normalization including first normal form (1NF), second normal form (2NF), third normal form (3NF), and Boyce-Codd normal form (BCNF).
3. The goal of higher normalization forms is to minimize duplicate data and optimize the relationship between different attributes and tables.
1. The document discusses database normalization, which involves restructuring tables to remove redundant data and organize related data.
2. It describes various forms of normalization including first normal form (1NF), second normal form (2NF), third normal form (3NF), and Boyce-Codd normal form (BCNF).
3. The goal of higher normalization forms is to minimize duplicate data and optimize the relationship between different attributes and tables.
normalization-Normalization -Process of Divide Tablesdharawagh9999
1. The document discusses database normalization, which involves restructuring tables to remove redundant data and organize related data.
2. It describes various forms of normalization including first normal form (1NF), second normal form (2NF), third normal form (3NF), and Boyce-Codd normal form (BCNF).
3. The goal of higher normalization forms is to minimize duplicate data and optimize the relationship between different attributes and tables.
The document discusses normalization in databases. It defines normalization as removing redundant data from tables to improve storage efficiency, data integrity, and scalability. The document outlines the various normal forms including 1NF, 2NF, 3NF, BCNF, and higher normal forms. It provides examples to illustrate different normal forms. Advantages of normalization include reduced database size and better performance, while disadvantages are more tables to join and codes instead of real data.
The normal forms (NF) of relational database theory provide criteria for determining a table’s degree of vulnerability to logical inconsistencies and anomalies.
The document discusses database normalization and various normal forms including first normal form (1NF), second normal form (2NF), third normal form (3NF), and Boyce-Codd normal form (BCNF). It provides examples of tables that are and are not in different normal forms and describes how to decompose tables to higher normal forms by removing functional dependencies between non-key attributes or attributes within a candidate key.
This document provides an overview of database normalization. It defines normalization as reducing redundancy and ensuring logical data dependencies. The document outlines the various normal forms from 1NF to BCNF and provides examples of converting tables between normal forms by removing redundancy and separating logically unrelated data. Benefits of normalization include reduced data size, faster queries, and improved data integrity. Complexity increases with additional tables and relationships between tables.
The document discusses normalization, which is the process of converting complex data structures into simple structures to avoid data duplication. It describes the three main steps of normalization: first normal form (1NF), second normal form (2NF), and third normal form (3NF). The document provides examples of tables and explains how to normalize them by removing anomalies like repeating groups and partial/transitive dependencies between attributes. While there are several normal forms, 3NF is sufficient for most use cases and removes all transitive dependencies. Functional dependencies, which define relationships between attributes, are also discussed.
The document discusses database normalization. Some key points:
- Normalization is the process of structuring data to reduce redundancy and dependency. It involves decomposing tables to successively higher normal forms.
- Common normal forms include 1NF, 2NF, 3NF, BCNF, and 4NF. Higher normal forms impose stricter rules to further reduce anomalies.
- The goals of normalization are to minimize duplication, reduce data modification issues, and simplify queries. Properly normalized data has several desirable characteristics including scalar fields and minimal null values and data loss.
Mca ii-dbms-u-iv-structured query languageRai University
The document discusses various forms of database normalization including first normal form (1NF), second normal form (2NF), third normal form (3NF), Boyce-Codd normal form (BCNF), and fourth normal form (4NF). It provides examples of database schemas that are and are not in each normal form and describes how to decompose schemas into normal form through lossless normalization techniques.
An introduction to database Normalization. An essential part of logical database design for relational databases. The presentation also has little coverage of related concepts like functional dependency, data anomalies, dependency preservation and lossless decomposition.
The document discusses relational database design and normalization. It defines relational database design as grouping attributes to form good relation schemas. It describes two levels of relation schemas - the logical user view level and the storage base relation level. The criteria for good base relations include semantics of relation attributes, redundancy and data anomalies, and null values in tuples. The purpose of normalization is to avoid redundancy and data anomalies like insertion, deletion, and modification anomalies. The document outlines the stages of normalization from unnormalized to fifth normal form and provides examples of relations in first, second, third, and Boyce-Codd normal forms.
On Relevant Query Answering over Streaming and Distributed DataShima Zahmatkesh
This document discusses optimizing query evaluation over streaming and distributed data to continuously obtain relevant results while maintaining system reactiveness. It proposes approaches for queries with filter clauses and top-k queries. For queries with filters, maintenance policies like Filter Update Policy and combined policies improve performance. For top-k queries, the Super-MTK+N list and Top-k+N algorithm handle changes to distributed data. The AcquaTop framework applies different maintenance policies. Experimental results show the approaches achieve more relevant and accurate results than the state-of-the-art.
Distributed systems allow for parallel and distributed computing across multiple autonomous computers connected through a network. There are different types of distributed systems such as high performance computing systems, distributed information systems, and distributed systems for pervasive services. Processes and threads are important concepts in distributed systems - a process is the instance of a program in execution and has state information stored in a process control block, while threads are lightweight processes that execute concurrently within a process and share the same memory address space. Remote procedure calls allow processes on different machines to communicate and invoke procedures remotely through a client-server model.
This document discusses a lecture on computer vision given by Dr. Eng. Mahmoud Shams at Kafrelsheikh University. It defines computer vision as dealing with how computers understand digital images and videos, and seeks to automate tasks of the human visual system. The lecture covers classification of AI, evaluation of computer vision algorithms, common computer vision tasks like localization and segmentation, and why benchmarks are important. It also discusses sources of noise in images, performance metrics like mean square error and confusion matrices, and some top computer vision tools like OpenCV, TensorFlow, Keras and YOLO.
This document provides an overview of integration techniques in calculus, including integration by parts, trigonometric integrals, and tabular integration. Integration by parts uses the product rule to find antiderivatives of functions that are products, allowing one to integrate more complicated functions. Tabular integration provides a shortcut method for integrals where one factor differentiates to zero and the other integrates repeatedly. Examples are provided to demonstrate how to use these techniques to evaluate definite integrals.
This document covers various topics in web development including image formatting, image maps, iframes, tables, and forms. It provides code examples for inserting images and setting attributes like width, height and alignment. It also demonstrates how to create image maps using area shapes and coordinates. Tables are shown being constructed using table, caption, header, body and footer tags. Different form field types like text, date, color, checkboxes and file uploads are displayed along with their associated tags.
A device acquires an IP address from a DHCP server to connect to a network. The device broadcasts a DHCP discover message and waits for a DHCP offer with an available IP address. The device then sends a request to the DHCP server to accept the offer and assign the IP address. The DHCP server acknowledges and configures the device with the IP address and other network settings for a lease period, allowing the device to connect to the network.
This document discusses a lecture on computer vision given by Dr. Eng. Mahmoud Shams at Kafrelsheikh University. It defines computer vision as dealing with how computers understand digital images and videos, and seeks to automate tasks of the human visual system. The lecture covers classification of AI, evaluation of computer vision algorithms, common computer vision tasks like localization and segmentation, and why benchmarks are important. It also lists the top 10 computer vision tools for 2020 and discusses negative results in computer vision research.
This document provides an overview of biological databases and DNA sequencing. It discusses the main components of bioinformatics which include storing and retrieving DNA sequencing data using biological databases, and manipulating the data using various tools. The document outlines the three main types of biological databases - primary, secondary, and composite databases - and provides examples of each. It also gives examples of accessing DNA sequencing data from the NCBI database using accession numbers and FASTA format. Finally, it introduces the concepts of databases and database systems.
This document discusses binary arithmetic and how it works using boolean logic. It provides examples of adding binary numbers and what happens in overflow conditions when the results exceed the bit limit. The key concepts covered are:
1) Binary addition employs the same process as decimal addition, carrying values to the next column when the sum exceeds the base.
2) Overflow occurs when the result of an addition does not fit in the allocated bit space, with part of the value lost. Programs can detect overflow as an error.
3) Binary operations can be represented using boolean logic functions like AND, OR and NOT. Single bit adders use these functions with inputs A, B, and a carry in to calculate outputs for the
The document lists 4 Python programs to create: 1) A program to find the sum of squares of each element in a list using a for loop. 2) A program to print the 24 hours for each day of the week. 3) A program to print student grades based on the sum of scores in 5 subjects using the grade distribution of the university. 4) Repeat the student grading program for multiple students until the user presses the esc key.
This document provides an introduction to computational biology and bioinformatics. It discusses DNA replication requirements, repair enzymes, damage types including single and double base alterations, insertions and deletions. Mutation categories of somatic and germ-line mutations are described. DNA damage can occur through chemical or physical means, and is repaired through excision, recombinant or photoreactive repair. Steps of recognition, removal and repair are outlined for excision repair. Pairwise and multiple sequence alignment are also introduced to identify similar regions between DNA, RNA or protein sequences.
This document contains homework questions on Python functions. It asks the reader to write functions to: print their name, age and college with and without default arguments; print even numbers from a list; check if a number is prime; calculate a factorial; display an employee's name and salary with a default salary; accept a variable number of arguments; calculate addition and subtraction with a single return; and recursively calculate the sum from 0 to 10. It closes by thanking the reader and asking if they have any questions.
About Potato, The scientific name of the plant is Solanum tuberosum (L).Christina Parmionova
The potato is a starchy root vegetable native to the Americas that is consumed as a staple food in many parts of the world. Potatoes are tubers of the plant Solanum tuberosum, a perennial in the nightshade family Solanaceae. Wild potato species can be found from the southern United States to southern Chile
Synopsis (short abstract) In December 2023, the UN General Assembly proclaimed 30 May as the International Day of Potato.
Preliminary findings _OECD field visits to ten regions in the TSI EU mining r...OECDregions
Preliminary findings from OECD field visits for the project: Enhancing EU Mining Regional Ecosystems to Support the Green Transition and Secure Mineral Raw Materials Supply.
Jennifer Schaus and Associates hosts a complimentary webinar series on The FAR in 2024. Join the webinars on Wednesdays and Fridays at noon, eastern.
Recordings are on YouTube and the company website.
https://www.youtube.com/@jenniferschaus/videos
This report explores the significance of border towns and spaces for strengthening responses to young people on the move. In particular it explores the linkages of young people to local service centres with the aim of further developing service, protection, and support strategies for migrant children in border areas across the region. The report is based on a small-scale fieldwork study in the border towns of Chipata and Katete in Zambia conducted in July 2023. Border towns and spaces provide a rich source of information about issues related to the informal or irregular movement of young people across borders, including smuggling and trafficking. They can help build a picture of the nature and scope of the type of movement young migrants undertake and also the forms of protection available to them. Border towns and spaces also provide a lens through which we can better understand the vulnerabilities of young people on the move and, critically, the strategies they use to navigate challenges and access support.
The findings in this report highlight some of the key factors shaping the experiences and vulnerabilities of young people on the move – particularly their proximity to border spaces and how this affects the risks that they face. The report describes strategies that young people on the move employ to remain below the radar of visibility to state and non-state actors due to fear of arrest, detention, and deportation while also trying to keep themselves safe and access support in border towns. These strategies of (in)visibility provide a way to protect themselves yet at the same time also heighten some of the risks young people face as their vulnerabilities are not always recognised by those who could offer support.
In this report we show that the realities and challenges of life and migration in this region and in Zambia need to be better understood for support to be strengthened and tuned to meet the specific needs of young people on the move. This includes understanding the role of state and non-state stakeholders, the impact of laws and policies and, critically, the experiences of the young people themselves. We provide recommendations for immediate action, recommendations for programming to support young people on the move in the two towns that would reduce risk for young people in this area, and recommendations for longer term policy advocacy.
Combined Illegal, Unregulated and Unreported (IUU) Vessel List.Christina Parmionova
The best available, up-to-date information on all fishing and related vessels that appear on the illegal, unregulated, and unreported (IUU) fishing vessel lists published by Regional Fisheries Management Organisations (RFMOs) and related organisations. The aim of the site is to improve the effectiveness of the original IUU lists as a tool for a wide variety of stakeholders to better understand and combat illegal fishing and broader fisheries crime.
To date, the following regional organisations maintain or share lists of vessels that have been found to carry out or support IUU fishing within their own or adjacent convention areas and/or species of competence:
Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR)
Commission for the Conservation of Southern Bluefin Tuna (CCSBT)
General Fisheries Commission for the Mediterranean (GFCM)
Inter-American Tropical Tuna Commission (IATTC)
International Commission for the Conservation of Atlantic Tunas (ICCAT)
Indian Ocean Tuna Commission (IOTC)
Northwest Atlantic Fisheries Organisation (NAFO)
North East Atlantic Fisheries Commission (NEAFC)
North Pacific Fisheries Commission (NPFC)
South East Atlantic Fisheries Organisation (SEAFO)
South Pacific Regional Fisheries Management Organisation (SPRFMO)
Southern Indian Ocean Fisheries Agreement (SIOFA)
Western and Central Pacific Fisheries Commission (WCPFC)
The Combined IUU Fishing Vessel List merges all these sources into one list that provides a single reference point to identify whether a vessel is currently IUU listed. Vessels that have been IUU listed in the past and subsequently delisted (for example because of a change in ownership, or because the vessel is no longer in service) are also retained on the site, so that the site contains a full historic record of IUU listed fishing vessels.
Unlike the IUU lists published on individual RFMO websites, which may update vessel details infrequently or not at all, the Combined IUU Fishing Vessel List is kept up to date with the best available information regarding changes to vessel identity, flag state, ownership, location, and operations.
Food safety, prepare for the unexpected - So what can be done in order to be ready to address food safety, food Consumers, food producers and manufacturers, food transporters, food businesses, food retailers can ...
3. 1. Why Normalize?
• If your database is not normalized, it can be inaccurate,
slow, inefficient.
• It might not produce the data you expect, or want
(update and delete anomalies).
• It makes creating queries, forms, and reports are much
easier to design.
4. 4
• Normalization: sequence of steps by which RDB is both created and improved.
Advantages of Normalization:
1. Get relations in more desirable form.
2. Make database more accurate and efficient.
3. Make creating queries easier.
4. Remove duplication.
2. Normalization
5. 5
• Normalization: sequence of steps by which RDB is both created and improved.
2. Normalization (Normalization Flow)
6. • A relation is said to be in first normal form if the data is held in a two-
dimensional table with each attribute represented by an atomic value.
• The intersection of a row and a column must contain an indivisible value.
• Each row and column position in the table there exists one value, never a set
of values.
• All attributes are atomic - any single attribute must not be composed of
multiple attributes.
6
First Normal Form (1NF)
7. The data we would want to store could be expressed as:
Project
No
Project Name Employee No Employee Name Rate
category
Rate
1203 Madagascar
travel site
11 Jessica Brookes A £90
12 Andy Evans B £80
16 Max Fat C £70
1506 Online estate
agency
11 Jessica Brookes A £90
17 Alex Branton B £80
7
First Normal Form (1NF)
8. • The intersection of a row and a column must contain an
indivisible value
Project
No.
Project Name Employee
No.
Employee
Name
Rate
category
Rate
1203 Madagascar
travel site
11 Jessica
Brookes
A £90
1203 Madagascar
travel site
12 Andy Evans B £80
1203 Madagascat
travel site
16 Max Fat C £70
1506 Online estate
agency
11 Jessica
Brookes
A £90
1506 Online estate
agency
17 Alex Branton B £70
8
Project
No.
Project Name Employee
No.
Solution
9. Three problems become apparent with our current model:
Tables in a RDBMS use a simple grid structure
• All tables in an RDBMS need a key
• Data entry should be kept to a minimum
• Redundant data
9
First Normal Form (1NF)
10. 10
1NF:
• Relation is said to be in 1NF if data is held in a table with each attribute is
represented by atomic value.
2NF:
• Relation is said to be in 2NF if:
1) It is in 1NF.
2) Remove partial dependency.
Normalization (Normalization Flow)
11. 11
3NF:
• Relation is said to be in 3NF if:
1) It is in 2NF.
2) Remove transitive dependency.
Normalization (Normalization Flow)
12. 12
Partial dependency: when non-key attribute is determined by a part, but not all
composite P.K.
Transitive dependency: when non-key attribute determines another non-key
attribute.
3. Dependencies
13. • A relation is said to be in second normal form if the relation
(1) is in 1NF and (2) all attributes that are not part of the
primary key are completely functionally dependent on the
primary key. (Partial dependencies must be removed)
• Second Normal Form (2NF) the relation must be in 1NF and each
non key attribute must be fully dependent on the whole key (not a
subset of the key).
13
Second normal form 2NF
14. Third normal form 3NF
• A relation is said to be in 3NF if it (1) is in 2NF and (2) no
attributes that are not part of the primary key are transitively
dependent on the primary key.
• The key then to move 2NF relations into 3NF is removing any
transitive dependencies that may exist in the relations.
14
15. Dependencies: Definitions
• Partial Dependency – when an non-key attribute is determined by a
part, but not the whole, of a COMPOSITE primary key.
15
CUSTOMER
Cust_ID Name Order_ID
101 AT&T 1234
101 AT&T 156
125 Cisco 1250
Partial
Dependency
16. • Transitive Dependency – when a non-key attribute determines
another non-key attribute.
16
EMPLOYEE
Emp_ID F_Name L_Name Dept_ID Dept_Name
111 Mary Jones 1 Acct
122 Sarah Smith 2 Mktg
Transitive
Dependency
Dependencies: Definitions
20. 3 NF
20
.
Service Place
Service Type
Service Date
.
12/2002
3/2000
11/99
Service Type
Service Place
Service Type
Transitive Dependency
21. 21
• What is meant by third normal form (3NF)? Examine the following table to
check if it is in 3NF. If yes, explain your answer. Otherwise convert the table
into 3NF.
4. Normalization Example
Client_no CName PropertyNo Address rent_start rent_end rent ownerNo oName
CR76 John kay
PG4
PG16
6 st.G
5 Novar
1-Jul-00
1-Sep-02
31-Aug-01
1-Sep-02
350
450
C040
C093
Tina
Tony
CR56 Aline Set
PG4
PG36
PG16
6 st.G
2 Manor
5 Novar
1-Sep-99
10-oct-00
1-Nov-02
10-Jun-00
1-Dec-01
1-Aug-03
350
370
450
C040
C093
C093
Tina
Tony
Tony
22. 22
Solution:
3NF: Relation is said to be in 3NF if:
1) It is in 2NF.
2) Remove transitive dependency.
• It is not in 3NF.
4. Normalization Example (Ex.1): Solution
23. 23
1) 1NF: make each attribute is represented by atomic value.
4. Normalization Example (Ex.1): Solution
Client_no CName PropertyNo Address rent_start rent_end rent ownerNo oName
CR76
CR76
John kay
John kay
PG4
PG16
6 st.G
5 Novar
1-Jul-00
1-Sep-02
31-Aug-01
1-Sep-02
350
450
C040
C093
Tina
Tony
CR56
CR56
CR56
Aline Set
Aline Set
Aline Set
PG4
PG36
PG16
6 st.G
2 Manor
5 Novar
1-Sep-99
10-oct-00
1-Nov-02
10-Jun-00
1-Dec-01
1-Aug-03
350
370
450
C040
C093
C093
Tina
Tony
Tony
24. 24
Choose Client_no + PropertyNo composite primary key
4. Normalization Example (Ex.1): Solution
Client_no PropertyNo CName Address rent_start rent_end rent ownerNo oName
CR76
CR76
PG4
PG16
John kay
John kay
6 st.G
5 Novar
1-Jul-00
1-Sep-02
31-Aug-01
1-Sep-02
350
450
C040
C093
Tina
Tony
CR56
CR56
CR56
PG4
PG36
PG16
Aline Set
Aline Set
Aline Set
6 st.G
2 Manor
5 Novar
1-Sep-99
10-oct-00
1-Nov-02
10-Jun-00
1-Dec-01
1-Aug-03
350
370
450
C040
C093
C093
Tina
Tony
Tony
27. 27
• Apply the various normalization steps to convert the following table into a
normal form.
4. Normalization Example (Ex.2)
Invoice
No.
Date
Cust.
No.
Cust.
Name
Cust.
Address
Cust.
City
Cust.
State
ItemID
Item
Description
Item.Q
ty
Item
Price
Item
Total
Order
total
price
125 9/13/2002 56 Foo, Inc.
23 Main
St,thorpleb
urg
thorpleb
urg
TX 563 56"Blue Fre 4 3.50 $ 14.00 $ 82.00 $
851 Spline End I 32 0.25 $ 8.00 $ 82.00 $
652 3' Red Fre 5 12.00 $ 60.00 $ 82.00 $
126 9/14/2002 2
Freens R
Us
1600
Pennsylva
nia
Washing
ton
DC 563 56"Blue Fre 500 3.50 $
1750.00
$
10750.0
0 $
652 3' Red Fre 750 12.00 $
9000.00
$
10750.0
0 $
28. 28
Solution:
• To be in 1NF
1) 1NF: make each attribute is represented by atomic value.
4. Normalization Example (Ex.2): Solution
Invoic
e No.
Date
Cust.No
.
Cust. Name
Cust.
Address
Cust. City
Cust.
State
ItemID
Item
Description
Item.Qt
y
Item Price Item Total
Order
total price
125 9/13/2002 56 Foo, Inc.
23 Main
St,thorplebur
g
thorplebur
g
TX 563 56"Blue Fre 4 3.50 $ 14.00 $ 82.00 $
125 9/13/2002 56 Foo, Inc.
23 Main
St,thorplebur
g
thorplebur
g
TX 851 Spline End I 32 0.25 $ 8.00 $ 82.00 $
125 9/13/2002 56 Foo, Inc.
23 Main
St,thorplebur
g
thorplebur
g
TX 652 3' Red Fre 5 12.00 $ 60.00 $ 82.00 $
126 9/14/2002 2
Freens R
Us
1600
Pennsylvani
a
Washingto
n
DC 563 56"Blue Fre 500 3.50 $ 1750.00 $
10750.00
$
126 9/14/2002 2
Freens R
Us
1600
Pennsylvani
a
Washingto
n
DC 652 3' Red Fre 750 12.00 $ 9000.00 $
10750.00
$
29. 29
Choose Invoice No. + ItemID composite primary key
4. Normalization Example (Ex.2): Solution
Invoice
No.
ItemID Date Cust.No. Cust. Name Cust. Address Cust. City
Cust.
State
Item
Description
Item.Qt
y
Item
Price
Item
Total
Order total price
125 563 9/13/2002 56 Foo, Inc.
23 Main
St,thorplebur
g
thorplebu
rg
TX 56"Blue Fre 4 3.50 $ 14.00 $ 82.00 $
125 851 9/13/2002 56 Foo, Inc.
23 Main
St,thorplebur
g
thorplebu
rg
TX Spline End I 32 0.25 $ 8.00 $ 82.00 $
125 652 9/13/2002 56 Foo, Inc.
23 Main
St,thorplebur
g
thorplebu
rg
TX 3' Red Fre 5 12.00 $ 60.00 $ 82.00 $
126 563 9/14/2002 2
Freens R
Us
1600
Pennsylvania
Washingt
on
DC 56"Blue Fre 500 3.50 $
1750.0
0 $
10750.00 $
126 652 9/14/2002 2
Freens R
Us
1600
Pennsylvania
Washingt
on
DC 3' Red Fre 750 12.00 $
9000.0
0 $
10750.00 $
30. 30
2) 2NF: remove partial dependency
Invoice No. Date, Cust.No., Cust. Name, Cust. Address, Cust. City, Cust. State, Order
total price
ItemID Item Description, Item Price
Invoice No. + ItemID Item.Qty, Item Total
4. Normalization Example (Ex.2): Solution
Invoice No. ItemID Item.Qty Item Total
125 563 4 14.00 $
125 851 32 8.00 $
125 652 5 60.00 $
126 563 500 1750.00 $
126 652 750 9000.00 $
Invoice
No.
Date
Cust.N
o.
Cust.
Name
Cust.
Address
Cust.
City
Cust.
State
Order total
price
125 9/13/2002 56
Foo,
Inc.
23 Main
St,thorple
burg
thorple
burg
TX 82.00 $
126 9/14/2002 2
Freens
R Us
1600
Pennsylv
ania
Washi
ngton
DC 10750.00 $
ItemID Item Description Item Price
563 56"Blue Fre 3.50 $
851 Spline End I 0.25 $
652 3' Red Fre 12.00 $
31. 31
3) 3NF: Tables are in 3 NF as there is no transitive dependency
4. Normalization Example (Ex.2): Solution