KR Using structured objects: Semantic nets, frames

Institution Jomo Kenyatta University of Science and Technology
Course Information Technol...
Year 3rd Year
Semester Unknown
Posted By Jeff Odhiambo
File Type ppt
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Description

Knowledge Representation (KR) using structured objects, such as semantic nets and frames, involves organizing and representing knowledge in a way that mimics human understanding. A semantic net is a graph-based structure where concepts are represented as nodes, and relationships between them are represented as edges. This approach enables the modeling of associative relationships and hierarchies between concepts, providing a way to represent facts and the context in which they hold true. Frames, on the other hand, are data structures that contain slots or attributes, each of which holds values or pointers to other frames. Frames are useful for representing stereotypical situations, allowing the encoding of more complex, object-oriented knowledge. Both structures help capture knowledge in a way that is understandable and manipulable by machines, facilitating reasoning and inference in artificial intelligence applications.
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SMA 2371: Partial Differential Equations (Complete Notes, Examples & Solutions) – JKUAT Biostatistics Year 2 Semester 2
These are comprehensive and well-organized lecture notes for SMA 2371: Partial Differential Equations (PDE) offered to BSc. Biostatistics Year 2 Semester 2 students at JKUAT. The notes are neatly arranged from lecture one to the final topics, making them ideal for class learning, revision, CAT preparation, and final examinations. The notes include detailed explanations, worked examples, step-by-step mathematical derivations, solved exercises, and applications of Partial Differential Equations. Topics covered include: • Review of basic concepts and partial derivatives • Jacobians, surfaces and curves in three dimensions • Simultaneous first-order differential equations • Methods of solving symmetric differential equations • Orthogonal trajectories • Pfaffian differential equations • Linear first-order partial differential equations • Formation of PDEs • Elimination of arbitrary constants and arbitrary functions • Heat, Wave, Laplace and Poisson equations • Separation of variables • Fourier and Laplace Transform methods • Numerous worked examples, tutorial questions and examination-style problems with solutions. These notes are suitable for JKUAT students and other university students studying Mathematics, Statistics, Biostatistics, Engineering, Applied Mathematics or related courses. They are an excellent revision resource for CATs and final examinations.
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