Real Time Systems - Syllabus

Overview of E-commerce and its significance in the digital age.

Understanding the differences between E-business and E-commerce.

Key characteristics and benefits of E-commerce.

Types of E-commerce models and their applications.

Understanding the concept of exceptions and how they are used in Java programming. This topic covers the basics of exceptions and their importance in error handling.

Best practices for using exceptions in Java programming, including when to use them and how to handle them effectively.

Creating custom exceptions in Java to handle specific error scenarios, and how to use them in programming.

Using the try-catch block to catch and handle exceptions in Java, including how to write effective catch blocks.

Understanding how to throw and re-throw exceptions in Java using the throw and throws keywords.

Learn how to design relational databases using ER-to-relational mapping, including mapping of regular entities, weak entities, relationship types, multivalued attributes, and N-ary relationships.

Understand informal design guidelines for relational schemas, including semantics of attributes in relations, redundant information in tuples and update anomalies, NULL values in tuples, and generation of spurious tuples.

Study functional dependencies, including definition, inference rules, Armstrong's axioms, attribute closure, equivalence of functional dependencies, and minimal sets of functional dependencies.

Explore normal forms based on primary keys, including First Normal Form, Second Normal Form, Third Normal Form, and their general definitions.

Learn about Boyce-Codd Normal Form, a higher normal form that ensures a relational schema is in a good structure.

Understand multivalued dependency and Fourth Normal Form, which eliminates multivalued dependencies in a relational schema.

Study properties of relational decomposition, including attribute preservation, dependency preservation, and loss-less/non-additive join.

This topic explores the various applications of recursion in problem-solving, including tree traversals and dynamic programming.

This topic explores the relationship between sociology and social policy, and how sociological principles are applied in social planning to address social issues.

This topic examines various social problems, including their causes, consequences, and potential solutions, using sociological theories and perspectives.

Applications of data warehousing and data mining in the agriculture sector, including decision support systems and precision agriculture.

Using data warehousing and data mining to support rural development initiatives, including poverty reduction and infrastructure planning.

Applications of data warehousing and data mining in the health sector, including disease surveillance and healthcare management.

Using data warehousing and data mining to support urban and regional planning, including transportation planning and infrastructure development.

Applications of data warehousing and data mining in the education sector, including student performance analysis and educational resource planning.

Using data warehousing and data mining to support commerce and trade initiatives, including market analysis and trade policy development.

Exploring other sectors where data warehousing and data mining can be applied, including energy, environment, and public safety.

This topic covers the fundamental technologies used on the client-side of web development, including HTML, CSS, and JavaScript.

This topic explores the use of JQuery, a popular JavaScript library, for client-side scripting and DOM manipulation.

This topic discusses the importance of form validation and how to implement it using ASP.NET Core, including client-side and server-side validation techniques.

This topic introduces Single Page Application (SPA) frameworks, including Angular and React, and their role in building dynamic and interactive client-side applications.

SaaS implementation issues, key characteristics of SaaS, benefits of the SaaS model.

A cloud service model framework.

Creating custom objects with properties and methods.

Graphic presentation involves using graphs such as histograms, frequency polygons, and frequency curves to present data. It is a visual way of presenting data, making it easy to understand and analyze.

A histogram is a type of graph that uses bars to represent the frequency of different ranges of values. It is commonly used to display continuous data.

A frequency polygon is a type of graph that uses lines to connect the points representing the frequency of different ranges of values. It is commonly used to display continuous data.

This topic covers various project management techniques used to plan, organize, and control projects. It includes developing project management plans and implementing, monitoring, and controlling projects.

This topic focuses on creating an environment that fosters collaboration and teamwork. It includes communications planning, organizing and conducting effective meetings, and other collaborative development strategies.

Methods of communication between processes, including race conditions and critical sections.

Techniques for achieving mutual exclusion, including busy waiting, sleep and wakeup, semaphores, monitors, and message passing.

Solutions to classic inter-process communication problems, including producer-consumer, sleeping barber, and dining philosopher problems.

Goals and techniques for scheduling processes, including batch, interactive, and real-time systems.

This topic covers deadlock prevention techniques, which ensure that deadlocks cannot occur by preventing one of the necessary conditions for deadlock.

This topic discusses deadlock avoidance techniques, which ensure that the system will never enter a deadlock state.

Learn how to design relational databases using ER-to-relational mapping, including mapping of regular entities, weak entities, relationship types, multivalued attributes, and N-ary relationships.

Understand informal design guidelines for relational schemas, including semantics of attributes in relations, redundant information in tuples and update anomalies, NULL values in tuples, and generation of spurious tuples.

Study functional dependencies, including definition, inference rules, Armstrong's axioms, attribute closure, equivalence of functional dependencies, and minimal sets of functional dependencies.

Explore normal forms based on primary keys, including First Normal Form, Second Normal Form, Third Normal Form, and their general definitions.

Learn about Boyce-Codd Normal Form, a higher normal form that ensures a relational schema is in a good structure.

Understand multivalued dependency and Fourth Normal Form, which eliminates multivalued dependencies in a relational schema.

Study properties of relational decomposition, including attribute preservation, dependency preservation, and loss-less/non-additive join.

This topic explores the various applications of recursion in problem-solving, including tree traversals and dynamic programming.

This topic discusses the efficiency of recursive algorithms, including time and space complexity analysis.

Optimization techniques for network flows, including maximal flows, minimal cuts, and the Max Flow-Min Cut Theorem.

This topic discusses the importance of controlling concurrent accesses to data objects in real-time systems and presents techniques for achieving this control.

Introduction to multiple correlation, its concept, and application in statistics. Exploring the relationship between multiple variables.

Understanding partial correlation, its concept, and application in statistics. Analyzing the relationship between two variables while controlling for other variables.

Basic concepts and principles of multiple linear regression, including model formulation and estimation. Understanding the relationship between multiple independent variables and a dependent variable.

Testing hypotheses in multiple regression, including significance testing and confidence intervals. Evaluating the overall fit and significance of the regression model.

Testing the overall significance of the regression model, including F-test and p-value interpretation. Determining whether the regression model is a good fit to the data.

Testing the significance of individual regression coefficients, including t-test and p-value interpretation. Evaluating the contribution of each independent variable to the regression model.

Learn how to design relational databases using ER-to-relational mapping, including mapping of regular entities, weak entities, relationship types, multivalued attributes, and N-ary relationships.

Understand informal design guidelines for relational schemas, including semantics of attributes in relations, redundant information in tuples and update anomalies, NULL values in tuples, and generation of spurious tuples.

Study functional dependencies, including definition, inference rules, Armstrong's axioms, attribute closure, equivalence of functional dependencies, and minimal sets of functional dependencies.

Explore normal forms based on primary keys, including First Normal Form, Second Normal Form, Third Normal Form, and their general definitions.

Learn about Boyce-Codd Normal Form, a higher normal form that ensures a relational schema is in a good structure.

Understand multivalued dependency and Fourth Normal Form, which eliminates multivalued dependencies in a relational schema.

Study properties of relational decomposition, including attribute preservation, dependency preservation, and loss-less/non-additive join.