This project is aimed at developing an online application for the College Management System Dept. of the college. The system is an online application that can be accessed throughout the organization and outside as well with proper login provided. This system can be used as an application for the TPO of the college to manage the student information with regards to placement and college managing. The college management and staff logging should be able to upload their information in the form of a CV and student record and college department record uploaded. Visitor’s college staff representatives logging in may also access/search any information put up by Students.
The document describes a project report on an Employee Management System created by a student named Vishal Kumar. It includes an introduction describing the project, objectives, proposed system, and phases of the system development life cycle used to create the software. The project uses SDLC methodology and includes phases for initiation, concept development, planning, design, implementation, testing, and maintenance.
the project is school managments system is also us by every school managment easy to store data electronicly so it is most important part our school mnagment
This ppt is report of School Management System by the students of RR Polytechnic Bangalore
if you need Source code email us
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we will feel glad to share it with you
The document describes the table structure for a library database, including tables for users, books, news, faculties, languages, genders, semesters, cities, roles, categories, publishers, authors, sections, deposits, ebooks, and copies. Each table listing includes the field names and data types. The document also notes that it was prepared and analyzed by Abdul Rahman Sherzad and designed by Yasin.
This document provides an overview of database system concepts and architecture. It discusses data models, schemas, instances, and states. It also describes the three-schema architecture, data independence, DBMS languages and interfaces, database system utilities and tools, and centralized and client-server architectures. Key classification of DBMSs are also covered.
This document discusses entity relationship (ER) modeling. It defines key concepts in ER modeling including entities, attributes, relationships, and ER diagram notations. Entities can be people, places, objects or concepts and are grouped into entity types. Attributes provide information about entities. Relationships define how entities are connected. Common relationship types are one-to-one, one-to-many, many-to-one, and many-to-many. ER diagrams use notations like boxes, lines, and crow's foot symbols to visually depict entities, attributes, and relationships in a database design. The document also covers entity classification, primary keys, foreign keys, and potential problems in ER modeling.
This document provides an overview of UML class diagrams, including their purpose and essential elements. A UML class diagram visually describes the structure of a system by showing classes, attributes, operations, and relationships. Key elements include classes, associations, generalization, dependencies, and notes. The document also provides examples and tips for creating UML class diagrams.
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...Raj vardhan
The Relational Data Model and Relational Database Constraints
Ch5 (Navathe 4th edition)/ Ch7 (Navathe 3rd edition)
Example of STUDENT Relation(figure 5.1)
The document defines various entity-related concepts in database management systems (DBMS). It states that an entity can represent real-world objects like professors or students in a college database. Entities have attributes that describe their properties. It distinguishes between strong and weak entities, where strong entities have primary keys and weak entities depend on strong entities. It also defines entity sets, attributes, different types of keys like primary keys, foreign keys and composite keys.
This document summarizes a school management system project submitted in partial fulfillment of a computer science degree. The project involved developing both a windows and web-based application to automate school management tasks like student registration, attendance tracking, report generation, and timetable production. The windows app handles offline registration and report generation while the web app allows teachers to record attendance and parents to view student status online. The system was designed to meet functional requirements like registration, attendance, reporting and timetabling as well as non-functional needs such as security, usability and performance. It was implemented using technologies like Java for the windows app and PHP for the web app, accessing a shared database.
This document describes an online placement cell system that allows students to upload their profiles, companies to post vacancies, and an administrator to approve registrations. It contains sections on the introduction, existing system, proposed system, modules, database tables, forms, and data flow diagram. The key modules are administrator, user, and company modules. The administrator approves registrations, the user can view notifications and apply for jobs, and the company can post vacancies and view applicant details.
The document describes a project report for a Student Information Management System. The system allows education institutes to easily maintain student records by solving problems with manual systems where information is scattered and redundant. The project aims to strengthen students' technical skills by having them complete a project according to university guidelines. Key features of the system include student registration, attendance tracking, timetable generation, and report generation. It was developed using technologies like HTML, PHP and allows authorized users to securely access and update student information.
This documentation have all the details about school management system, even in this document have DFD,ERD,FDD digram that are useful to create database. to get more details about this product plz mail me on ([email protected]) thanks.....
BI in the Cloud - Microsoft Power BI Overview and DemoChristopher Foot
RDX Insights Series Presentation focusing on Microsoft Power BI in the cloud. We begin with a high-level overview of the Microsoft BI product suite and discuss the SSIS/SSAS/SSRS tech stack and Power BI. The webinar continues with a deep dive into Power BI and includes instructions on how to use the product to capture, model, analyze and visualize business data. We end the webinar with a Power BI demo highlighting some of its most beneficial and interesting features.
Student management system project report c++Student
This document describes a student management system project that uses C++ and file handling. The system allows users to create, read, modify and delete student records which are stored in files. It also generates reports like grade reports and displays individual or all student data. The system ensures correct data is input and stored through validation checks. It utilizes common functions for file handling and output formatting.
This document describes a student management system that allows schools to store and access information about students. The system's objectives are to disseminate information and encourage accountability and retention of information. It allows student database management, maintaining academic activities, and storing individual student information. The system is designed for both admin and user access. Admin can add, update, delete student information and see student lists while users can only view individual information. Features include cloud access and profile management. The system scope includes course management, scheduling, registration, grading and reporting.
The document discusses SQL operators including arithmetic, comparison, and logical operators. It provides examples of each type of operator including AND, OR, NOT, LIKE, BETWEEN, IN, EXISTS, ALL, and ANY. It also gives the basic syntax of the CREATE DATABASE statement in SQL to create a new database called testDB.
This document describes an online job portal system project submitted to MicroRoot POC Technology Pvt. Ltd. The project includes an introduction, requirement analysis, system design, and conclusion. The system design section includes use case diagrams, sequence diagrams, data flow diagrams, and screenshots of the proposed user interfaces. The system is intended to allow job seekers to search and apply for jobs, and employers to post jobs. It will be developed using technologies like PHP, MySQL, Joomla, AJAX, and jQuery.
The document describes a student database management system created for T.B.G. Polytechnic in Ambajogai, India. The system was created to streamline processes like registration, admission, class and staff management by utilizing a database instead of manual records. The system uses a graphical user interface and database features for easy data entry, retrieval, and manipulation compared to paper records. This saves time and reduces paperwork.
The document describes an Academic Management System (AMS) project presented by students. The AMS allows a college to maintain student, staff, fees, and exam information electronically. It aims to simplify information management and allow quick access to records. The project involved designing the system using tools like Rational Rose, writing code in Java/JSP, and testing the software. Key modules include administration, student, faculty, and department functions. The system uses a database, login authentication, and allows generating reports. The document outlines objectives, outcomes, schedule, architecture, and design diagrams for the AMS.
The Capability Maturity Model Integration (CMMI) provides organizations with guidelines for improving their processes. It defines key process areas and maturity levels for activities like project planning, risk management, and configuration management. An organization is appraised against CMMI practices rather than certified. The appraisal determines their maturity level or capability level to identify improvement areas. CMMI uses both staged and continuous appraisal approaches.
This document outlines a proposed student inquiry system created by a group of students. The system was created to automate and simplify the manual student record keeping process. It allows authorized users to access, add, update, and search student records stored in a database. Key features include reducing costs and errors, and allowing easy access and tracking of student information. The system requirements, software requirements, functional and non-functional requirements, and modules are described. The goal is to create a user-friendly system to easily manage student records for educational institutions.
A proposal for the automation of attendance systemAj Aligonero
This research paper analyzes introducing an automated attendance system using biometrics at Laguna Northwestern College. Currently, attendance is taken manually, taking up class time. The researchers hypothesize that an automated system using fingerprint or facial recognition would reduce time spent on attendance and improve monitoring of student attendance. If implemented, key benefits would be increased security, less proxy attendance, and reduced human error. The study scope is limited to analyzing student attendance management. It provides little information on biometric hardware costs and school facility usage.
The document provides an overview of entity-relationship (E-R) modeling concepts including:
- Entity sets represent collections of real-world entities that share common properties
- Relationship sets define associations between entity sets
- Attributes provide additional information about entities and relationships
- Keys uniquely identify entities and relationships
- Cardinalities constrain how entities can participate in relationships
- E-R diagrams visually depict entity sets, attributes, relationships and constraints.
Database management chapter 2 power pointmistydake
This chapter introduces structured query language (SQL) and its use in retrieving and manipulating data from relational databases. The chapter objectives cover understanding SQL concepts like the SELECT-FROM-WHERE framework for queries, different SQL clauses and functions, and using SQL to query single and multiple tables. Examples are provided to illustrate SQL queries against sample data from tables representing sales data of a fictional outdoor retail company. The chapter also shows how to execute SQL queries using Microsoft Access, SQL Server, Oracle, and MySQL database tools.
This document provides an overview of database system concepts and architecture. It discusses data models, schemas, instances, and states. It also describes the three-schema architecture, data independence, DBMS languages and interfaces, database system utilities and tools, and centralized and client-server architectures. Key classification of DBMSs are also covered.
This document discusses entity relationship (ER) modeling. It defines key concepts in ER modeling including entities, attributes, relationships, and ER diagram notations. Entities can be people, places, objects or concepts and are grouped into entity types. Attributes provide information about entities. Relationships define how entities are connected. Common relationship types are one-to-one, one-to-many, many-to-one, and many-to-many. ER diagrams use notations like boxes, lines, and crow's foot symbols to visually depict entities, attributes, and relationships in a database design. The document also covers entity classification, primary keys, foreign keys, and potential problems in ER modeling.
This document provides an overview of UML class diagrams, including their purpose and essential elements. A UML class diagram visually describes the structure of a system by showing classes, attributes, operations, and relationships. Key elements include classes, associations, generalization, dependencies, and notes. The document also provides examples and tips for creating UML class diagrams.
The Relational Data Model and Relational Database Constraints Ch5 (Navathe 4t...Raj vardhan
The Relational Data Model and Relational Database Constraints
Ch5 (Navathe 4th edition)/ Ch7 (Navathe 3rd edition)
Example of STUDENT Relation(figure 5.1)
The document defines various entity-related concepts in database management systems (DBMS). It states that an entity can represent real-world objects like professors or students in a college database. Entities have attributes that describe their properties. It distinguishes between strong and weak entities, where strong entities have primary keys and weak entities depend on strong entities. It also defines entity sets, attributes, different types of keys like primary keys, foreign keys and composite keys.
This document summarizes a school management system project submitted in partial fulfillment of a computer science degree. The project involved developing both a windows and web-based application to automate school management tasks like student registration, attendance tracking, report generation, and timetable production. The windows app handles offline registration and report generation while the web app allows teachers to record attendance and parents to view student status online. The system was designed to meet functional requirements like registration, attendance, reporting and timetabling as well as non-functional needs such as security, usability and performance. It was implemented using technologies like Java for the windows app and PHP for the web app, accessing a shared database.
This document describes an online placement cell system that allows students to upload their profiles, companies to post vacancies, and an administrator to approve registrations. It contains sections on the introduction, existing system, proposed system, modules, database tables, forms, and data flow diagram. The key modules are administrator, user, and company modules. The administrator approves registrations, the user can view notifications and apply for jobs, and the company can post vacancies and view applicant details.
The document describes a project report for a Student Information Management System. The system allows education institutes to easily maintain student records by solving problems with manual systems where information is scattered and redundant. The project aims to strengthen students' technical skills by having them complete a project according to university guidelines. Key features of the system include student registration, attendance tracking, timetable generation, and report generation. It was developed using technologies like HTML, PHP and allows authorized users to securely access and update student information.
This documentation have all the details about school management system, even in this document have DFD,ERD,FDD digram that are useful to create database. to get more details about this product plz mail me on ([email protected]) thanks.....
BI in the Cloud - Microsoft Power BI Overview and DemoChristopher Foot
RDX Insights Series Presentation focusing on Microsoft Power BI in the cloud. We begin with a high-level overview of the Microsoft BI product suite and discuss the SSIS/SSAS/SSRS tech stack and Power BI. The webinar continues with a deep dive into Power BI and includes instructions on how to use the product to capture, model, analyze and visualize business data. We end the webinar with a Power BI demo highlighting some of its most beneficial and interesting features.
Student management system project report c++Student
This document describes a student management system project that uses C++ and file handling. The system allows users to create, read, modify and delete student records which are stored in files. It also generates reports like grade reports and displays individual or all student data. The system ensures correct data is input and stored through validation checks. It utilizes common functions for file handling and output formatting.
This document describes a student management system that allows schools to store and access information about students. The system's objectives are to disseminate information and encourage accountability and retention of information. It allows student database management, maintaining academic activities, and storing individual student information. The system is designed for both admin and user access. Admin can add, update, delete student information and see student lists while users can only view individual information. Features include cloud access and profile management. The system scope includes course management, scheduling, registration, grading and reporting.
The document discusses SQL operators including arithmetic, comparison, and logical operators. It provides examples of each type of operator including AND, OR, NOT, LIKE, BETWEEN, IN, EXISTS, ALL, and ANY. It also gives the basic syntax of the CREATE DATABASE statement in SQL to create a new database called testDB.
This document describes an online job portal system project submitted to MicroRoot POC Technology Pvt. Ltd. The project includes an introduction, requirement analysis, system design, and conclusion. The system design section includes use case diagrams, sequence diagrams, data flow diagrams, and screenshots of the proposed user interfaces. The system is intended to allow job seekers to search and apply for jobs, and employers to post jobs. It will be developed using technologies like PHP, MySQL, Joomla, AJAX, and jQuery.
The document describes a student database management system created for T.B.G. Polytechnic in Ambajogai, India. The system was created to streamline processes like registration, admission, class and staff management by utilizing a database instead of manual records. The system uses a graphical user interface and database features for easy data entry, retrieval, and manipulation compared to paper records. This saves time and reduces paperwork.
The document describes an Academic Management System (AMS) project presented by students. The AMS allows a college to maintain student, staff, fees, and exam information electronically. It aims to simplify information management and allow quick access to records. The project involved designing the system using tools like Rational Rose, writing code in Java/JSP, and testing the software. Key modules include administration, student, faculty, and department functions. The system uses a database, login authentication, and allows generating reports. The document outlines objectives, outcomes, schedule, architecture, and design diagrams for the AMS.
The Capability Maturity Model Integration (CMMI) provides organizations with guidelines for improving their processes. It defines key process areas and maturity levels for activities like project planning, risk management, and configuration management. An organization is appraised against CMMI practices rather than certified. The appraisal determines their maturity level or capability level to identify improvement areas. CMMI uses both staged and continuous appraisal approaches.
This document outlines a proposed student inquiry system created by a group of students. The system was created to automate and simplify the manual student record keeping process. It allows authorized users to access, add, update, and search student records stored in a database. Key features include reducing costs and errors, and allowing easy access and tracking of student information. The system requirements, software requirements, functional and non-functional requirements, and modules are described. The goal is to create a user-friendly system to easily manage student records for educational institutions.
A proposal for the automation of attendance systemAj Aligonero
This research paper analyzes introducing an automated attendance system using biometrics at Laguna Northwestern College. Currently, attendance is taken manually, taking up class time. The researchers hypothesize that an automated system using fingerprint or facial recognition would reduce time spent on attendance and improve monitoring of student attendance. If implemented, key benefits would be increased security, less proxy attendance, and reduced human error. The study scope is limited to analyzing student attendance management. It provides little information on biometric hardware costs and school facility usage.
The document provides an overview of entity-relationship (E-R) modeling concepts including:
- Entity sets represent collections of real-world entities that share common properties
- Relationship sets define associations between entity sets
- Attributes provide additional information about entities and relationships
- Keys uniquely identify entities and relationships
- Cardinalities constrain how entities can participate in relationships
- E-R diagrams visually depict entity sets, attributes, relationships and constraints.
Database management chapter 2 power pointmistydake
This chapter introduces structured query language (SQL) and its use in retrieving and manipulating data from relational databases. The chapter objectives cover understanding SQL concepts like the SELECT-FROM-WHERE framework for queries, different SQL clauses and functions, and using SQL to query single and multiple tables. Examples are provided to illustrate SQL queries against sample data from tables representing sales data of a fictional outdoor retail company. The chapter also shows how to execute SQL queries using Microsoft Access, SQL Server, Oracle, and MySQL database tools.
The document discusses entity relationship (ER) modeling concepts including:
- Entities, attributes, and relationships can be represented graphically in ER diagrams
- Relationships have cardinalities like one-to-one, one-to-many, many-to-many that specify how entities are associated
- Weak entities depend on other entities and cannot be uniquely identified without attributes from the associated entity
The document provides an overview of entity-relationship (ER) modeling concepts including:
- Entity sets and relationship sets which form the basic constructs of an ER model
- Attributes, keys, and cardinality constraints which provide further details on entities and relationships
- ER diagrams which visually depict the ER model through graphical symbols
- Additional ER modeling features such as weak entities, specialization, and aggregation
The document concludes by discussing how an ER schema can be reduced to tables to represent the data in a relational database.
Database management chapter 1 power pointmistydake
This chapter introduces databases and their key characteristics. It describes how data is stored and organized in tables with rows and columns. The chapter outlines the components of database systems like Microsoft Access and enterprise-level systems. These include the database itself, which stores data and metadata, as well as the database management system and query language. The chapter provides examples of common database applications and concludes with a brief history of database development.
This document discusses bi-connected components in graphs. It defines an articulation point as a vertex in a connected graph whose removal would disconnect the graph. A bi-connected component is a maximal subgraph that contains no articulation points. The document presents algorithms for identifying articulation points and bi-connected components in a graph using depth-first search (DFS). It introduces the concepts of tree edges, back edges, forward edges and cross edges in a DFS tree and explains how to use these edge types to determine if a vertex is an articulation point based on the minimum discovery time of its descendant vertices.
The document discusses the relational model of databases. It defines key concepts like relations, tuples, attributes, domains, and keys. It provides an example database schema for an auction application with relations for owners, items, bids, and buyers. It explains that a relation is a set of tuples with a common schema where each tuple maps attribute names to values from predefined domains. It also defines the different types of keys like superkeys and primary keys.
The document discusses how to convert ER diagrams to relational databases. It explains that each entity set maps to a table, while relationship sets can map to tables or be represented within other tables by adding attributes. It also covers handling special cases like one-to-one/many relationships, composite attributes, and specialization/aggregation. The document provides SQL commands for creating tables, adding constraints, and altering or dropping tables during the conversion process.
This document summarizes a talk on managing your tech career and tracking your tech skills. The talk covered finding your path in the industry, building your personal brand, evolving your mindset, and tracking emerging technologies. It discussed understanding the different roles and paths available, developing your career narrative, maintaining an online presence, participating in communities, and dealing with imposter syndrome. The talk emphasized the importance of continuous learning, building a technology radar to track new tools and platforms, and appreciating how your skills fit within the broader tech ecosystem.
The document discusses the SQL standard and its components. It describes how SQL is used to define schemas, manipulate data, write queries involving single or multiple tables, and perform other operations. Key topics covered include data definition language, data manipulation language, data types, integrity constraints, queries, subqueries, and set operations in SQL. Examples of SQL commands for creating tables, inserting data, and writing various types of queries are also provided.
Best Practices for Database Schema DesignIron Speed
The document provides best practices for database schema design to optimize use with the Iron Speed Designer application development tool. It recommends normalizing data, using separate lookup tables, declaring primary and foreign keys, creating views and indexes, and using naming conventions. Following these practices results in Iron Speed Designer generating more sophisticated and easily maintained web applications from the database schema.
Normalizing a database involves organizing data to:
1) Avoid duplicate values and inconsistent dependencies by separating data into multiple tables.
2) Ensure each table describes a single entity or "thing".
3) Achieve third normal form where data is organized into tables such that each non-key attribute is dependent only on the primary key.
The document discusses the relational data model structure and operations. It describes the key concepts of the relational data model including relations, attributes, tuples/rows, domains, schemas, keys such as candidate keys and foreign keys. It also explains the basic relational algebra operations like selection, projection, union, set difference, intersection and cartesian product along with examples.
Webinar: Build an Application Series - Session 2 - Getting StartedMongoDB
This session - presented by Matthew Bates, Solutions Architect & Consulting Engineer at MongoDB - will cover an outline of an application, schema design decisions, application functionality and design for scale out.
About the speaker
Matthew Bates is a Solutions Architect in the EMEA region for MongoDB and helps advise customers how to best use and make the most out of MongoDB in their organisations. He has a background in solutions for the acquisition, management and exploitation of big data in government and public sector and telco industries through his previous roles at consultancy firms and a major European telco. He's a Java and Python coder and has a BSc(Hons) in Computer Science from the University of Nottingham.
Next in the Series:
February 20th 2014
Build an Application Series - Session 3 - Interacting with the database:
This webinar will discuss queries and updates and the interaction between an application and a database
March 6th 2014
Build an Application Series - Session 4 - Indexing:
This session will focus on indexing strategies for the application, including geo spatial and full text search
March 20th 2014
Build an Application Series - Session 5 - Reporting in your application:
This session covers Reporting and Aggregation Framework and Building application usage reports
April 3th 2014
Operations for your application - Session 6 - Deploying the application:
By this stage, we will have built the application. Now we need to deploy it. We will discuss architecture for High Availability and scale out
April 17th 2014
Operations for your application - Session 7 - Backup and DR:
This webinar will discuss back up and restore options. Learn what you should do in the event of a failure and how to perform a backup and recovery of the data in your applications
May 6th 2014
Operations for your application - Session 8 - Monitoring and Performance Tuning:
The final webinar of the series will discuss what metrics are important and how to manage and monitor your application for key performance.
The document discusses different types of MySQL replication including asynchronous, semi-synchronous, and synchronous. It provides pros and cons of each type and describes how they handle transaction ordering, parallelism, flow control, and consistency. The key points are that asynchronous replication has potential for data loss and stale reads, semi-synchronous reduces but does not eliminate data loss risk, while SchoonerSQL's synchronous replication guarantees no data loss and failover without stalled transactions.
This document discusses distributed Postgres including multi-master replication, distributed transactions, and high availability/auto failover. It explores existing implementations like Postgres-XC and proposes a transaction manager API and time-stamp based approach to enable distributed transactions without a central bottleneck. The document also outlines a multimaster implementation built on logical replication, a transaction replay pool, and Raft-based storage for failure handling and distributed deadlocks. Performance is approximately half of standalone Postgres with the same read speeds and capabilities for node recovery and network partition handling.
The document discusses database design principles, noting that designers should understand technology limitations, gather all relevant data about their project, and map out the database design on paper before implementing it in a computer system. It also provides examples of attributes and tables to store different types of data, emphasizing the importance of planning the database design to account for all necessary data entities and attributes.
The document discusses database design and the design process. It explains that database design involves determining the logical structure of tables and relationships between data elements. The design process consists of steps like determining relationships between data, dividing information into tables, specifying primary keys, and applying normalization rules. The document also covers entity-relationship diagrams and designing inputs and outputs, including input controls and designing report formats.
The document provides an overview of the Entity-Relationship (E/R) model, a conceptual data modeling technique. It describes the key concepts of the E/R model including entities, attributes, relationships, cardinalities, participation constraints, weak entities and E/R diagrams. The E/R model is used to describe a database at the conceptual level and provides a rigorous yet understandable representation of data. An example E/R schema for modeling student, course, department and other data for an educational institution is presented to demonstrate how the concepts are applied.
The Entity-Relationship (E/R) model is a conceptual data modeling technique used to describe and design the data requirements of an information system. The E/R model uses entities, attributes, and relationships to model the real world entities and relationships between entities of an organization or system. The E/R model diagrammatically represents entities as rectangles, attributes as ellipses, and relationships as diamonds. This allows for a graphical depiction of the entities, attributes, and relationships within a system.
The document discusses the relational model of data, which was proposed by Edgar F. Codd in the 1970s. It presents the key concepts of the relational model including relation schemes, relation instances, keys, foreign keys, and referential integrity constraints. It also introduces relational algebra operations such as select, project, join, and set operations that allow querying of relational databases and provides examples to illustrate how they work. Finally, it discusses how relational algebra provides the foundation for query optimization and execution in relational database management systems.
The document discusses the Entity Relationship Model and its key concepts including entities, attributes, relationships, keys, and cardinalities. It explains how ER diagrams visually depict these concepts through symbols like rectangles for entities and diamonds for relationships. The ER model is used for conceptual database design and captures the logical properties and meanings within an organization's domain.
This document provides an overview of entity/relationship modeling and ER diagrams. It discusses key concepts such as entities, attributes, relationships, and how to represent them in ER diagrams. An example of modeling a university database is used to demonstrate how to identify entities, attributes, relationships from a description and represent them in an ER diagram. Guidelines are provided for determining whether something should be an entity or attribute. The document also discusses modeling one-to-one relationships and how redundant relationships can be merged.
The document discusses entity relationship (ER) models and describes the key concepts including entities, attributes, relationships, keys, ER diagrams, weak entities, and mapping constraints. It provides examples of an ER model for a university database that includes the entities of students, courses, and professors. The model shows the relationships between these entities, their attributes, cardinalities, and a sample ER diagram. Overall, the document provides an overview of ER models and demonstrates how to design an ER schema for a database using a university example.
The document discusses entity-relationship (E-R) modeling which is used for conceptual database design. It describes how E-R modeling involves identifying entities, attributes, and relationships between entities. These components are represented in an E-R diagram using graphical symbols like rectangles for entities and diamonds for relationships. An example E-R diagram is provided for a university database with entities for departments, programs, courses, lecturers, and students and relationships such as "offers" and "teaches".
The document discusses the Entity Relationship (ER) model, which was introduced in 1976 to define the conceptual view of a database. The ER model represents real-world entities and relationships between entities using entity sets, attributes, and relationship types. These constructs allow the ER model to map to a relational database schema and serve as a design tool for database developers and a communication tool for users. Key ER modeling concepts covered include entities, attributes, relationships, cardinalities, and participation constraints.
The document discusses the key features of the entity-relationship (E-R) model. The E-R model allows users to describe data in terms of objects and relationships. It provides concepts like entities, attributes, and relationships that make it easy to model real-world data. Entities represent objects, attributes describe entity features, and relationships define connections between entities. The document also discusses different types of relationships and modeling techniques like generalization, specialization, and aggregation.
1) The document describes an entity-relationship (ER) diagram for a university database. It identifies the main entities as Department, Course, Module, Lecturer, and Student.
2) The key relationships are that a Department offers multiple Courses, a Course includes multiple Modules, a Lecturer teaches multiple Modules, and a Student enrolls in a Course and takes the Modules required to complete it.
3) The document explains the different components of an ER diagram, including entities, relationships, attributes, keys, and relationship types (one-to-one, one-to-many, many-to-many). It provides examples of how to map an ER diagram to database tables.
The document discusses Relational Database Management Systems (RDBMS) and Entity-Relationship (ER) modeling. It describes the key components of an ER diagram including entities, attributes, relationships and relationship types. It provides examples of how to model real-world systems, such as modeling students and addresses in a school database. It also discusses entity keys like primary keys and foreign keys and how they are used to uniquely identify records and link tables in a relational database.
This document provides an introduction to conceptual modeling in database design. It discusses the stages of database design including data analysis, conceptual design, logical design, and physical design. The conceptual and logical models are explained using an example of a university database. Key aspects of conceptual modeling using the entity-relationship model are covered, including entities, attributes, relationships, keys, participation constraints, and weak/strong entities. Design principles are presented for reducing redundancy and choosing between entities and attributes.
This document discusses entity relationship (ER) diagrams and modeling concepts. It defines entities, attributes, relationships and cardinalities. It also covers ER diagram notation for representing these concepts visually including different relationship types. Finally, it discusses transforming an ER diagram into a relational database schema by mapping entities to tables, relationships to tables, and ensuring integrity through keys and constraints.
In tube drawing process, a tube is pulled out through a die and a plug to reduce its diameter and thickness as per the requirement. Dimensional accuracy of cold drawn tubes plays a vital role in the further quality of end products and controlling rejection in manufacturing processes of these end products. Springback phenomenon is the elastic strain recovery after removal of forming loads, causes geometrical inaccuracies in drawn tubes. Further, this leads to difficulty in achieving close dimensional tolerances. In the present work springback of EN 8 D tube material is studied for various cold drawing parameters. The process parameters in this work include die semi-angle, land width and drawing speed. The experimentation is done using Taguchi’s L36 orthogonal array, and then optimization is done in data analysis software Minitab 17. The results of ANOVA shows that 15 degrees die semi-angle,5 mm land width and 6 m/min drawing speed yields least springback. Furthermore, optimization algorithms named Particle Swarm Optimization (PSO), Simulated Annealing (SA) and Genetic Algorithm (GA) are applied which shows that 15 degrees die semi-angle, 10 mm land width and 8 m/min drawing speed results in minimal springback with almost 10.5 % improvement. Finally, the results of experimentation are validated with Finite Element Analysis technique using ANSYS.
ELectronics Boards & Product Testing_Shiju.pdfShiju Jacob
This presentation provides a high level insight about DFT analysis and test coverage calculation, finalizing test strategy, and types of tests at different levels of the product.
Concept of Problem Solving, Introduction to Algorithms, Characteristics of Algorithms, Introduction to Data Structure, Data Structure Classification (Linear and Non-linear, Static and Dynamic, Persistent and Ephemeral data structures), Time complexity and Space complexity, Asymptotic Notation - The Big-O, Omega and Theta notation, Algorithmic upper bounds, lower bounds, Best, Worst and Average case analysis of an Algorithm, Abstract Data Types (ADT)
π0.5: a Vision-Language-Action Model with Open-World GeneralizationNABLAS株式会社
今回の資料「Transfusion / π0 / π0.5」は、画像・言語・アクションを統合するロボット基盤モデルについて紹介しています。
拡散×自己回帰を融合したTransformerをベースに、π0.5ではオープンワールドでの推論・計画も可能に。
This presentation introduces robot foundation models that integrate vision, language, and action.
Built on a Transformer combining diffusion and autoregression, π0.5 enables reasoning and planning in open-world settings.
Passenger car unit (PCU) of a vehicle type depends on vehicular characteristics, stream characteristics, roadway characteristics, environmental factors, climate conditions and control conditions. Keeping in view various factors affecting PCU, a model was developed taking a volume to capacity ratio and percentage share of particular vehicle type as independent parameters. A microscopic traffic simulation model VISSIM has been used in present study for generating traffic flow data which some time very difficult to obtain from field survey. A comparison study was carried out with the purpose of verifying when the adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and multiple linear regression (MLR) models are appropriate for prediction of PCUs of different vehicle types. From the results observed that ANFIS model estimates were closer to the corresponding simulated PCU values compared to MLR and ANN models. It is concluded that the ANFIS model showed greater potential in predicting PCUs from v/c ratio and proportional share for all type of vehicles whereas MLR and ANN models did not perform well.
International Journal of Distributed and Parallel systems (IJDPS)samueljackson3773
The growth of Internet and other web technologies requires the development of new
algorithms and architectures for parallel and distributed computing. International journal of
Distributed and parallel systems is a bimonthly open access peer-reviewed journal aims to
publish high quality scientific papers arising from original research and development from
the international community in the areas of parallel and distributed systems. IJDPS serves
as a platform for engineers and researchers to present new ideas and system technology,
with an interactive and friendly, but strongly professional atmosphere.
The role of the lexical analyzer
Specification of tokens
Finite state machines
From a regular expressions to an NFA
Convert NFA to DFA
Transforming grammars and regular expressions
Transforming automata to grammars
Language for specifying lexical analyzers
2. Prof P Sreenivasa Kumar
Department of CS&E, IITM
2
Entity-Relationship (E/R) Model
Widely used conceptual level data model
• proposed by Peter P Chen in 1970s
Data model to describe the database system at the requirements
collection stage
• high level description.
• easy to understand for the enterprise managers.
• rigorous enough to be used for system building.
Concepts available in the model
• entities and attributes of entities.
• relationships between entities.
• diagrammatic notation.
3. Prof P Sreenivasa Kumar
Department of CS&E, IITM
3
Entities
Entity - a thing (animate or inanimate) of independent
physical or conceptual existence and distinguishable.
In the University database context, an individual
student, faculty member, a class room, a course
are entities.
Entity Set or Entity Type-
Collection of entities all having the same properties.
Student entity set – collection of all student entities.
Course entity set – collection of all course entities.
4. Prof P Sreenivasa Kumar
Department of CS&E, IITM
4
Attributes
Each entity is described by a set of attributes/properties.
student entity
StudName – name of the student.
RollNumber – the roll number of the student.
Sex – the gender of the student etc.
All entities in an Entity set/type have the same set of attributes.
Chosen set of attributes – amount of detail in modeling.
5. Prof P Sreenivasa Kumar
Department of CS&E, IITM
5
Types of Attributes (1/2)
• Simple Attributes
having atomic or indivisible values.
example: Dept – a string
PhoneNumber – an eight digit number
• Composite Attributes
having several components in the value.
example: Qualification with components
(DegreeName, Year, UniversityName)
• Derived Attributes
Attribute value is dependent on some other attribute.
example: Age depends on DateOf Birth.
So age is a derived attribute.
6. Prof P Sreenivasa Kumar
Department of CS&E, IITM
6
Types of Attributes (2/2)
• Single-valued
having only one value rather than a set of values.
for instance, PlaceOfBirth – single string value.
• Multi-valued
having a set of values rather than a single value.
for instance, CoursesEnrolled attribute for student
EmailAddress attribute for student
PreviousDegree attribute for student.
• Attributes can be:
simple single-valued, simple multi-valued,
composite single-valued or composite multi-valued.
7. Prof P Sreenivasa Kumar
Department of CS&E, IITM
7
Diagrammatic Notation for Entities
entity - rectangle
attribute - ellipse connected to rectangle
multi-valued attribute - double ellipse
composite attribute - ellipse connected to ellipse
derived attribute - dashed ellipse
EmailAddress
AdmissionYear
Program
Student
RollNumber
StudName
Lname
Fname Mname
Sex
Age DateOfBirth
8. Prof P Sreenivasa Kumar
Department of CS&E, IITM
8
Domains of Attributes
Each attribute takes values from a set called its domain
For instance, studentAge – {17,18, …, 55}
HomeAddress – character strings of length 35
Domain of composite attributes –
cross product of domains of component attributes
Domain of multi-valued attributes –
set of subsets of values from the basic domain
9. Prof P Sreenivasa Kumar
Department of CS&E, IITM
9
Entity Sets and Key Attributes
• Key – an attribute or a collection of attributes whose value(s)
uniquely identify an entity in the entity set.
• For instance,
• RollNumber - Key for Student entity set
• EmpID - Key for Faculty entity set
• HostelName, RoomNo - Key for Student entity set
(assuming that each student gets to stay in a single room)
• A key for an entity set may have more than one attribute.
• An entity set may have more than one key.
• Keys can be determined only from the meaning of the
attributes in the entity type.
• Determined by the designers
10. Prof P Sreenivasa Kumar
Department of CS&E, IITM
10
Relationships
• When two or more entities are associated with each other,
we have an instance of a Relationship.
• E.g.: student Ramesh enrolls in Discrete Mathematics course
• Relationship enrolls has Student and Course as the
participating entity sets.
• Formally, enrolls ⊆ Student × Course
• (s,c) ∈ enrolls ⇔ Student ‘s’ has enrolled in Course ‘c’
• Tuples in enrolls – relationship instances
• enrolls is called a relationship Type/Set.
11. Prof P Sreenivasa Kumar
Department of CS&E, IITM
11
Degree of a relationship
• Degree : the number of participating entities.
• Degree 2: binary
• Degree 3: ternary
• Degree n: n-ary
• Binary relationships are very common and widely used.
12. Prof P Sreenivasa Kumar
Department of CS&E, IITM
12
Diagrammatic Notation for Relationships
Relationship – diamond shaped box
Rectangle of each participating entity is connected by a line to
this diamond. Name of the relationship is written in the box.
A
C
B
R
13. Prof P Sreenivasa Kumar
Department of CS&E, IITM
13
Binary Relationships and Cardinality Ratio
E1
E2
R
• The number of entities from E2 that an entity from E1 can
possibly be associated thru R (and vice-versa) determines
the cardinality ratio of R.
• Four possibilities are usually specified:
• one-to-one (1:1)
• one-to-many (1:N)
• many-to-one (N:1)
• many-to-many (M:N)
M N
14. Prof P Sreenivasa Kumar
Department of CS&E, IITM
14
Cardinality Ratios
• One-to-one: An E1 entity may be associated with at
most one E2 entity and similarly
an E2 entity may be associated with at
most one E1 entity.
• One-to-many: An E1 entity may be associated with
many E2 entities whereas an E2 entity may
be associated with at most one E1 entity.
• Many-to-one: … ( similar to above)
• Many-to-many: Many E1 entities may be associated with a
single E2 entity and a single E1 entity
may be associated with many E2 entities.
15. Prof P Sreenivasa Kumar
Department of CS&E, IITM
15
Cardinality Ratio – example (one-to-one)
Teaches
ResidesIn
Professor Course
CourseID NamePhoneName
Sex
Address
Name
RollNo
Address
Student
Hostel
Room
HostelName
RoomNo
1 1
1 1
Credits
16. Prof P Sreenivasa Kumar
Department of CS&E, IITM
16
Cardinality Ratio – example (many-to-one/one-to-many)
belongsTo
guides
Professor Department
Name Location
PhoneName
Sex
Address
Name
Sex
Address
Professor
Student
Name RoomNo
1 N
N 1
Phone
Address (one-to-many)
(many-to-one)
17. Prof P Sreenivasa Kumar
Department of CS&E, IITM
17
Cardinality Ratio – example (many-to-many)
Student Courseenrolls
Name RollNo
Address
Name
CourseId
Credits
ProfessorSex
Name Phone
Address
SponsoredProject
Name Sponser
Value Duration
Start
Date
End
Date
worksFor
M N
M N
18. Prof P Sreenivasa Kumar
Department of CS&E, IITM
18
Participation Constraints
• An entity set may participate in a relation either totally or
partially.
• Total participation: Every entity in the set is involved in
some association (or tuple) of the relationship.
• Partial participation: Not all entities in the set are involved
in association (or tuples) of the relationship.
Notation:
E1 E2R
total partial
19. Prof P Sreenivasa Kumar
Department of CS&E, IITM
19
Example of total/partial Participation
belongsTo
guides
Professor Department
Name Location
PhoneName
Sex
Address
Name
Sex
Address
Professor
Student
Name RoomNo
1 N
N 1
Phone
Address
one-to-many
(many-to-one)
20. Prof P Sreenivasa Kumar
Department of CS&E, IITM
20
Structural Constraints
• Cardinality Ratio and Participation Constraints are together
called Structural Constraints.
• They are called constraints as the data must satisfy them to be
consistent with the requirements.
• Min-Max notation: pair of numbers (m,n) placed on the line
connecting an entity to the relationship.
• m: the minimum number of times a particular entity must
appear in the relationship tuples at any point of time
• 0 – partial participation
• ≥ 1 – total participation
• n: similarly, the maximum number of times a particular entity
can appear in the relationship tuples at any point of time
21. Prof P Sreenivasa Kumar
Department of CS&E, IITM
21
Comparing the Notations
E1 E2R
E1 E2R
N 1
(1,1) (0,N)
is equivalent to
22. Prof P Sreenivasa Kumar
Department of CS&E, IITM
22
Attributes for Relationship Types
Relationship types can also have attributes.
properties of the association of entities.
Student Courseenrolls
Grade
M N
grade gives the letter grade (S,A,B, etc.) earned by
the student for a course.
neither an attribute of student nor that of course.
23. Prof P Sreenivasa Kumar
Department of CS&E, IITM
23
Attributes for Relationship Types – More Examples
belongsToProfessor Department
joinDate
N 1
SponsoredProjectProfessor worksFor
percentTime
M N
24. Prof P Sreenivasa Kumar
Department of CS&E, IITM
24
Recursive Relationships and Role Names
• Recursive relationship: An entity set relating to itself
gives rise to a recursive relationship
• E.g., the relationship prereqOf is an example of a recursive
relationship on the entity Course
• Role Names – used to specify the exact role in which the
entity participates in the relationships
• Essential in case of recursive relationships
• Can be optionally specified in non-recursive cases
Course
prereqOf
prerequisite
course
Role Names
25. Prof P Sreenivasa Kumar
Department of CS&E, IITM
25
Weak Entity Sets
Weak Entity Set: An entity set whose members owe their
existence to some entity in a strong entity set.
entities are not of independent existence.
each weak entity is associated with some entity of the
owner entity set through a special relationship.
weak entity set may not have a key attribute.
S
Owner entity
Identifying relationship
Always total
WR
Double wall
box
26. Prof P Sreenivasa Kumar
Department of CS&E, IITM
26
Weak Entity Sets - Example
Course Section
has
Section
Name
CourseID
Credits
SectionNo
Year
SemesterNo
RoomNo
ClassTimeProfessor
A popular course may have
several sections each taught
by a different professor and
having its own class room
and meeting times
Partial key:
Uniquely identifies a section
among the set of sections
of a particular course
27. Prof P Sreenivasa Kumar
Department of CS&E, IITM
27
Complete Example for E/R schema: Specifications (1/2)
In an educational institute, there are several departments and
students belong to one of them. Each department has a unique
department number, a name, a location, phone number and is
headed by a professor. Professors have a unique employee Id,
name, phone number.
We like to keep track of the following details regarding students:
name, unique roll number, sex, phone number, date of birth,
age and one or more email addresses. Students have a local
address consisting of the hostel name and the room number.
They also have home address consisting of house number,
street, city and PIN. It is assumed that all students reside in the
hostels.
28. Prof P Sreenivasa Kumar
Department of CS&E, IITM
28
Complete Example for E/R schema: Specifications (2/2)
A course taught in a semester of the year is called a section. There
can be several sections of the same course in a semester; these
are identified by the section number. Each section is taught by a
different professor and has its own timings and a room to meet.
Students enroll for several sections in a semester.
Each course has a name, number of credits and the department that
offers it. A course may have other courses as pre-requisites i.e,
courses to be completed before it can be enrolled in.
Professors also undertake research projects. These are sponsored
by funding agencies and have a specific start date, end date and
amount of money given. More than one professor can be
involved in a project. Also a professor may be simultaneously
working on several projects. A project has a unique projectId.
29. Prof P Sreenivasa Kumar
Department of CS&E, IITM
29
StudentName
RollNo
Address
Street
City
HNo
LocalAddress
HostelName
RoomNo
EmailId
Age
DateOfBirth
Entities - Student
PIN
Sex
30. Prof P Sreenivasa Kumar
Department of CS&E, IITM
30
Entities – Department and Course
Department
Name
Location
Phone
HOD
Course
CourseID
Credits
Name
DeptNo
31. Prof P Sreenivasa Kumar
Department of CS&E, IITM
31
Professor
Name
ProfID
PhoneNumber
Project Sponsor
Amount
EndDateStartDate
Section
ClassRoomSectionID
Entities – Professor, Project and Sections
Timing
ProjectId
32. Prof P Sreenivasa Kumar
Department of CS&E, IITM
32
E/R Diagram showing relationships
Student Department
Course Professor
works
On
Project
hasSection
Section
prerequisite
Of
teaches
enrolls works
For
belongs
To
N 1
N
N
N
N
N
N
M
M M
1
1
1
offers
1
N
33. Prof P Sreenivasa Kumar
Department of CS&E, IITM
33
Design Choices: Attribute versus Relationship
• Should offering department be an attribute of a course or
should we create a relationship between Course and Dept
entities called, say, offers ?
• Later approach is preferable when the necessary entity,
in this case the Department, already exists.
• Should class room be an attribute of Section or
should we create an entity called ClassRoom and
have a relationship, say, meetsIn,
connecting Section and ClassRoom?
• In this case, the option of making classRoom as an attribute
of Section is better as we do not want to give a lot of
importance to class room and make it a an entity.
34. Prof P Sreenivasa Kumar
Department of CS&E, IITM
34
Design Choices:
Weak entity versus composite multi-valued attributes
• Note that section could be a composite multi-valued attribute
of Course entity.
• However, if so, section can not participate in relationships,
such as, enrolls with Student entity.
• In general, if a thing, even though not of independent existence,
participates in other relationships on its own, it is best
captured as a weak entity.
• If the above is not the case, composite multi-valued
attribute may be enough.
35. Prof P Sreenivasa Kumar
Department of CS&E, IITM
35
Ternary Relationships
Relationship instance (c, p, j) indicates that
company c supplies a component p that is made use of by the project j
Company Component
Project
supply
serves uses
canSupply
36. Prof P Sreenivasa Kumar
Department of CS&E, IITM
36
Ternary Relationships
(c,p) in canSupply, (j,p) in uses, (c,j) in serves may not together imply (c,p,j) is
in supply. Whereas the other way round is of course true.
Company Component
Project
supply
serves uses
canSupply
The binary
relationships
together do not
convey the
same meaning
as supply