Edgar Codd at IBM invented the relational database model in 1970 based on 13 rules. A relational database management system (RDBMS) stores data in related tables. RDBMSs help make data easy to store, retrieve, and combine in useful ways. Common RDBMSs include Microsoft SQL Server, Oracle, MySQL, and PostgreSQL. Tables are related through primary and foreign keys, which help enforce referential integrity.
Database normalization is the process of refining the data in accordance with a series of normal forms. This is done to reduce data redundancy and improve data integrity. This process divides large tables into small tables and links them using relationships.
Here is the link of full article: https://www.support.dbagenesis.com/post/database-normalization
Dbms architecture
Three level architecture is also called ANSI/SPARC architecture or three schema architecture
This framework is used for describing the structure of specific database systems (small systems may not support all aspects of the architecture)
In this architecture the database schemas can be defined at three levels explained in next slide
Database normalization is the process of refining the data in accordance with a series of normal forms. This is done to reduce data redundancy and improve data integrity. This process divides large tables into small tables and links them using relationships.
Here is the link of full article: https://www.support.dbagenesis.com/post/database-normalization
Dbms architecture
Three level architecture is also called ANSI/SPARC architecture or three schema architecture
This framework is used for describing the structure of specific database systems (small systems may not support all aspects of the architecture)
In this architecture the database schemas can be defined at three levels explained in next slide
Data:
– Raw facts; building blocks of information
– Unprocessed information
Information:
– Data processed to reveal meaning
• Accurate, relevant, and timely information is key
to good decision making.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
CFD Simulation of By-pass Flow in a HRSG module by R&R Consult.pptxR&R Consult
CFD analysis is incredibly effective at solving mysteries and improving the performance of complex systems!
Here's a great example: At a large natural gas-fired power plant, where they use waste heat to generate steam and energy, they were puzzled that their boiler wasn't producing as much steam as expected.
R&R and Tetra Engineering Group Inc. were asked to solve the issue with reduced steam production.
An inspection had shown that a significant amount of hot flue gas was bypassing the boiler tubes, where the heat was supposed to be transferred.
R&R Consult conducted a CFD analysis, which revealed that 6.3% of the flue gas was bypassing the boiler tubes without transferring heat. The analysis also showed that the flue gas was instead being directed along the sides of the boiler and between the modules that were supposed to capture the heat. This was the cause of the reduced performance.
Based on our results, Tetra Engineering installed covering plates to reduce the bypass flow. This improved the boiler's performance and increased electricity production.
It is always satisfying when we can help solve complex challenges like this. Do your systems also need a check-up or optimization? Give us a call!
Work done in cooperation with James Malloy and David Moelling from Tetra Engineering.
More examples of our work https://www.r-r-consult.dk/en/cases-en/
NO1 Uk best vashikaran specialist in delhi vashikaran baba near me online vas...Amil Baba Dawood bangali
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Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
2. Relational DBMS
Edgar F. Codd at IBM invented the relational database
in 1970. Called Father of RDBMS.
The main elements of RDBMS are based on Codd’s 13
rules for a relational system.
Tables (or relations) are related to each other by
sharing common characteristics
3. RDBMS
A database management system that stores data in the
form of related tables is called Relational Database
Management System.
The goal of RDBMS is to make data easy to store &
retrieve
Relational databases help solve problems as they are
designed to create tables & then combine the
information in interesting ways to create valid
information.
4. RDBMS
Typical RDBMS include
Microsoft Access
Microsoft SQL Server
Sybase (The forerunner of Microsoft SQL Server)
IBM DB2
Oracle
Ingres
MySQL
Postgresql etc
5. RDBMS
Relation Instance:- snapshot of DB
Example:
Schema :- Logical design of DB.
Example:
Account-schema = (account-number, branch-name,
balance)
Branch-schema = (branch-name, branch-city, assets)
Customer-schema = (customer-name, customer-street,
customer-city)
10. Integrity Constraint
An integrity constraint (IC) is a condition specified on
a database schema and restricts the data that can be
stored in an instance of the database.
If a database instance satisfies all the integrity
constraints specifies on the database schema, it is
a legal instance.
A DBMS permits only legal instances to be stored in the
database.
11. Integrity Constraint
Domain Constraints:
A relation schema specifies the domain of each field in
the relation instance. These domain constraints in the
schema specify the condition that each instance of the
relation has to satisfy.
Example:
create domain Dollars numeric(12,2)
create domain Pounds numeric(12,2)
define the domains Dollars and Pounds to be decimal
numbers with a total of 12 digits, two of which are
placed after the decimal point.
12. Integrity Constraint
Referential Integrity:
ensure that a value that appears in one relation for a
given set of attributes also appears for a certain set of
attributes in another relation.
Example: SQL
branch-name char(15) references branch
13. Key Constraints
Super Key:
An attribute, or set of attributes, that uniquely identifies a
tuple within a relation.
However, a super key may contain additional attributes that
are not necessary for a unique identification.
Candidate Key:
A super key such that no proper subset is a super key within
the relation. There are two parts of the candidate key
definition:
i. Two distinct tuples in a legal instance cannot have identical
values in all the fields of a key.
ii. No subset of the set of fields in a candidate key is a unique
identifier for a tuple.
14. Key Constraints
Primary Key:
The candidate key that is selected to identify tuples
uniquely within the relation.
The candidate keys that are not selected as the primary
key are called as alternate keys.
Features of the primary key:
1. Primary key will not allow duplicate values.
2.Primary key will not allow null values.
3. Only one primary key is allowed per table.
15. Key Constraints
Foreign Key:
Foreign keys represent the relationships between tables.
A foreign key is a column (or a group of columns)
whose values are derived from the primary key of some
other table.
Features of foreign key:
1. Records cannot be inserted into a detail table if
corresponding records in the master table do not exist.
2. Records of the master table cannot be deleted or
updated if corresponding records in the detail table
actually exist.
16. Integrity Constraint
Assertions:
An assertion is a predicate expressing a condition that we
wish the database always to satisfy.
create assertion <assertion-name> check <predicate>
Example :
create assertion sum-constraint check
(not exists (select * from branch
where (select sum(amount) from loan
where loan.branch-name = branch.branch-name)
>= (select sum(balance) from account
where account.branch-name = branch.branch-name)))
17. Integrity Constraint
Triggers:
A trigger is a statement that the system executes
automatically as a side effect of a modification to the
database.
To design a trigger mechanism, we must meet two
requirements:
1. Specify when a trigger is to be executed. This is broken
up into an event that causes the trigger to be checked
and a condition that must be satisfied for trigger
execution to proceed.
2. Specify the actions to be taken when the trigger
executes.
18. Integrity Constraint
Triggers:
Example: define a trigger that replaces the blank value
in a phone number field of an inserted tuple by the
null value.
create trigger setnull-trigger before update on r
referencing new row as nrow for each row when
nrow.phone-number = ’ ’ set nrow.phone-number = null
21. Relational Algebra
Select (σ) :
(a) Example: select those tuples of the loan relation
where the branch is “Perryridge,”
σbranch-name =“Perryridge” (loan)
(b) Example: find those tuples pertaining to loans of
more than $1200 made by the Perryridge branch
σbranch-name =“Perryridge”∧ amount>1200 (loan)
22. Relational Algebra
Project(Π)
Example: list all loan numbers and the amount of the
loan as
Πloan-number, amount(loan)
Union(∪)
Example: find the names of all bank customers who hav
either an account or a loan or both.
Πcustomer-name (borrower ) ∪ Πcustomer-name (depositor)
borrower : Customers with a loan in the bank
23. Relational Algebra
Set Difference (-)
Example: find all customers of the bank who have an account
but not a loan
Πcustomer-name (depositor) − Πcustomer-name (borrower )
Cartesian-Product (X)
Example: find the names of all customers who have a loan at
the Perryridge branch.
3. Πcustomer-name (σborrower .loan-number =loan.loan-number
(σbranch-name =“Perryridge” (borrower × loan)))
24. Relational Algebra
Rename (ρ)
relational-algebra expression E,
ρ x (E)
returns the result of expression E under the name x.
Additional operations are:
• Set intersection
• Assignment
• Natural join
25. Relational Calculus
Tuple Relational Calculus
A query in the tuple relational calculus is expressed as
{t | P(t)}
the set of all tuples t such that predicate P is true for t.
Domain Relational Calculus
An expression in the domain relational calculus is of the form
{< x1, x2, . . . , xn > | P(x1, x2, . . . , xn)}
where x1, x2, . . . , xn represent domain variables. P represents a
formula composed of atoms, as was the case in the tuple
relational calculus.
Editor's Notes
relation schema corresponds to the programming-language notion of type definition.
relation instance corresponds to the programming language notion of a value of a variable.
A database schema, along with primary key and foreign key dependencies, can be depicted pictorially by schema diagrams.
E-R diagrams do not show foreign key attributes explicitly, whereas schema diagrams show them explicity.
Mapping Entity
Mapping Relation
Domain definitions can be physical & Logical.
Such constraints may also prohibit the use of null values for particular attributes.
Thus, the domain of a field is essentially the type of that field.
Values of one domain can be cast (that is, converted) to another domain.
Example : If the attribute A or relation r is of type Dollars, we can convert it to Pounds by writing
cast r.A as Pounds
By default, a foreign key references the primary key attributes of the referenced table. SQL also supports a version of the references clause where a list of attributes of the referenced relation can be specified explicitly. The specified list of attributes must be declared as a candidate key of the referenced relation.
(k1,k2,k3,k4) – superkey –unique identifier for tuple
k1 – primary key
k2, k3 – candidate key also alternate key
K1,k2,k3 – not candiate key
The table in which foreign key is defined is called a Foreign table or Details table. The table that defines the primary key and is referenced by the foreign key is called the Primary table or Master table.
Domain constraints and referential-integrity constraints are special forms of assertions.
When an assertion is created, the system tests it for validity. If the assertion is valid, then any future modification to the database is allowed only if it does not cause that assertion to be violated.
The above model of triggers is referred to as the event-condition-action model for triggers.
Trigger limited use:
For example, suppose an insert trigger on a relation has an action that causes another (new) insert on the same relation. The insert action then triggers yet another insert action, and so on ad infinitum.
Database systems typically limit the length of such chains of triggers (for example to 16 or 32), and consider longer chains of triggering an error.
The relational algebra is a procedural query language. It consists of a set of operations that take one or two relations as input and produce a new relation as their result.
In general, we allow comparisons using =, =, <, ≤, >, ≥ in the selection predicate.
Furthermore, we can combine several predicates into a larger predicate by using the
connectives and (∧), or (∨), and not (￢).
Exercise: find all customers who have the same name as their loan officer, we can write
σcustomer-name =banker-name(loan-officer)
Since relations are sets, duplicate values are eliminated
Composition of Relational Operations
Example : “Find those customers who live in Harrison.”
Πcustomer-name (σcustomer-city =“Harrison” (customer))
Cartesian-Product Example We need the information in both the loan relation and the borrower relation to do so.
Cartesian-product operation associates every tuple of loan with every tuple of borrower,
1. σbranch-name =“Perryridge”(borrower × loan)
2. σborrower .loan-number =loan.loan-number (σbranch-name =“Perryridge”(borrower × loan))
Rename Operation Excellent Example Further reading from korth
The tuple relational calculus, by contrast, is a nonprocedural query language.
Following our earlier notation, we use t[A] to denote the value of tuple t on attribute A, andwe use t ∈ r to denote that tuple t is in relation r.
