Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our User Agreement and Privacy Policy.

Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our Privacy Policy and User Agreement for details.

Like this presentation? Why not share!

- Research Methods: Basic Concepts an... by Ahmed-Refat Refat 205945 views
- Project Method of Teaching by Mandeep Gill 101675 views
- Cloud computing : A promising platf... by Sai Natkar 87 views
- Basics of computer science by Paul Schmidt 4515 views
- Advantages and disadvantages of sci... by bernardsanch 52125 views
- Uses of Computers in Business by Margarita Sison 37733 views

2,494 views

Published on

How related to Computer Science?

Modeling

Theoretical Computer Science

Experimental Computer Science

Computer Simulation

No Downloads

Total views

2,494

On SlideShare

0

From Embeds

0

Number of Embeds

8

Shares

0

Downloads

141

Comments

0

Likes

3

No embeds

No notes for slide

- 1. 1 By : Parinda Rajapaksha Samudra Herath Isuri Udayangi Najini Harischandra
- 2. Roadmap Introduction Scientific Method How related to Computer Science? Modeling Theoretical Computer Science Experimental Computer Science Computer Simulation Pros & Cons 2
- 3. What is Science ? A systematic and logical approach to discovering how things in the universe work. It aims for measurable results through testing and analysis. It is not meant to prove theories, but rule out alternative explanations until a likely conclusion is reached 3
- 4. What is Science Cont… Science consists simply of the formulation and testing of hypotheses based on observational evidence. Science is useful and ongoing. 4
- 5. How related to Computer Science? Study of phenomena related to computers. Computing encompasses, - Computer Science - Computer Engineering - Software Engineering - Information Systems The purpose of Computing is the systematic study of algorithmic processes that describe and transform information their theory, analysis, design, efficiency and implementation 5
- 6. Scientific Method In 19th century. scientific method is the logical scheme used by scientists searching for answers to the questions It is used to produce scientific theories.. When conducting a research, scientists observe the scientific method to collect measurable, empirical evidence in an experiment related to a hypothesis. 6
- 7. Scientific Method Cont… The steps of the scientific method : 1. Pose the question in the context of existing knowledge (theory & observations) 2. Formulate a hypothesis as a tentative answer 3. Deduce consequences and make predictions 4. Test the hypothesis in a specific experiment/theory field •In case the hypothesis leads to contradictions and demands a radical change in the existing theoretical background, it has to be tested carefully 7
- 8. Scientific Method Cont… Rule: • loop 2-3-4 is repeated with modifications of the hypothesis until the agreement is obtained, which leads to 5. • If major discrepancies are found the process must start from the beginning, 1. 5. When consistency is obtained the hypothesis becomes a theory and provides a coherent set of propositions that define a new class of phenomena or a new theoretical concept 6. A theory is then becoming a framework within which observations/theoretical facts are explained and predictions are made 8
- 9. Scientific Method Cont… 9
- 10. Scientific Method Cont… Some key underpinnings to the scientific method: The hypothesis must be testable and falsifiable Deductive reasoning is the process of using true premises to reach a logical true conclusion dependent variable and an independent variable experimental group and a control group. 10
- 11. What is Computer Science? 11
- 12. Many definitions Study of algorithmic processes that describe and transform information Study of phenomena related to computers Study of information structures Study and management of complexity Mechanization of abstraction 12
- 13. Mixture of Engineering Mathematics Logic Management Generally CS is, Information theory concerned on transformation and interpretation of information 13
- 14. Computer science encompasses abstract mathematical thinking and includes an element of engineering. Finding solutions Designing skills 14
- 15. Sub-areas of Computer Science 1. Discrete Structures 2. Programming Fundamentals 3. Algorithms and Complexity 4. Programming Languages 5. Architecture and Organization 6. Operating Systems & etc.. 15
- 16. List expands as computer science develops.. 16
- 17. CS Objectives change with time Development of theories Practical experience in usage 17
- 18. Scientific methods of computer science Computer Science Theoretical Experimental Simulation 18
- 19. Common Method Modeling 19
- 20. Modeling Occur in Science Simplify a phenomenon Identify what is relevant Theoretical background 20
- 21. Simplified model of a phenomenon Description in symbolic language Observable/measurable consequence of a given change in a system 21
- 22. Question that come in the process How to model? Is the model appropriate? In what way model differs from “reality”? Validation: are the results valid? 22
- 23. Examples 23
- 24. Modeling process scheme follows the general scheme of scientific method presented before Theory, experiment and simulation are all about models of phenomena. 24
- 25. What is theoretical computer Science? Subset of general computer science and mathematics focus on more abstract or mathematical aspects of computing Includes the theory of computation Follows a very classical methodology of building theories with rigid definitions of Objects operations 25
- 26. Key recurring ideas of computing Conceptual and formal models Different levels of abstraction Efficiency 26
- 27. Data models Use to formulate different mathematical concepts CS data model – two aspects Values they can assume Operations on data 27
- 28. Typical data model examples Tree data model List data model Set data model Relational data model Graph data model Patterns, automata and regular expression 28
- 29. Physical science and computer science Do not compete with each other on which better explains the fundamental nature of information No new theories develop to reconcile theory with experimental results reveal unexpected phenomena No history of critical experiments that decide the validity of various theories 29
- 30. Design and analysis Methods are developed for algorithm design Measures are defined for computational resources Trade offs are explored Upper and lower resource bounds are proved 30
- 31. Main methodological themes Iteration – performing sequence of operations repeatedly Iterative constructs such as for /while statements Recursion – call themselves directly or indirectly Induction – definitions and proofs use basis and inductive step to encompass all possible cases. 31
- 32. Experimental Computer Science 32
- 33. What is experimental computer science? Three components define experimental science Observation Hypothesis testing Reproducibility 33
- 34. Experimental computer science Mathematical modeling of the behavior of computer systems 34
- 35. Fields of computer science use experiments Search Automatic theorem proving Planning NP complete problems Natural language Vision Games Machine learning 35
- 36. Computer Simulation 36
- 37. computation which comprises computer - based modeling and simulation, has become the third research methodology within CS Computational Science has emerged, at the intersection of Computer Science, applied mathematics, and science disciplines in both theoretical investigation and experimentation Computational Science 37
- 38. Computational Science Cont… Tools modeling with 3D visualization and computer simulation efficient handling of large data sets ability to access a variety of distributed resources collaborate with other experts over the Internet 38
- 39. Computational Science Cont… Computational science involves the use of computers (''supercomputers'') for visualization and simulation of complex and large-scale phenomena. If Computer Science has its basis in computability theory, then computational science has its basis in computer simulation 39
- 40. Computer Simulation Definition simulation: (computer science) the technique of representing the real world by a computer program; "a simulation should imitate the internal processes and not merely the results of the thing being simulated“ Computer simulation makes it possible to investigate regimes that are beyond current experimental capabilities study phenomena that cannot be replicated in laboratories, such as the evolution of the universe and Nano technology 40
- 41. Simulations 41
- 42. Key Areas Chaos and Complex Systems Virtual Reality Artificial Life Physically Based Modeling and Computer Animation 42
- 43. Advantages and Disadvantages Advantage You can test in many different ways, and the more times you test, the more accurate your results will be Disadvantage You can come up with different results which can disprove your hypothesis, and this leads to inconsistent conclusions 43
- 44. Wrap-Up Introduction Scientific Method How related to Computer Science? Modeling Theoretical Computer Science Experimental Computer Science Computer Simulation Pros & Cons 44
- 45. References 1. Some definitions of Science : http://www.gly.uga.edu/railsback/1122sciencedefns.html 2. Computing as a Discipline, Denning, P.J. et al. Commun. ACM 32, 1 (January 1989), 9 3. What is computer science ? : http://www.cs.mtu.edu/~john/whatiscs.html 45

No public clipboards found for this slide

×
### Save the most important slides with Clipping

Clipping is a handy way to collect and organize the most important slides from a presentation. You can keep your great finds in clipboards organized around topics.

Be the first to comment