nielit.gov.in : C Level Course Advanced Computer Graphics Paper 2017

Name of the Organisation : National Institute of Electronics & Information Technology
Examination : C Level Course
Document Type : Sample Question Paper
Year : 2017
Name of the Subject : Advanced Computer Graphics

Website : http://beta.nielit.gov.in/content/january-2017
Download Sample Question Paper : https://www.pdfquestion.in/uploads/13076-Graphics.pdf

C Level Course Advanced Computer Graphics Paper :

Time: 3 Hours
Total Marks: 100
Note :
1. Answer question 1 and any FOUR from questions 2 to 7.
2. Parts of the same question should be answered together and in the same sequence.

 Related : NIELIT  C Level Course Advanced Computer Networks Paper 2017 : www.pdfquestion.in/13086.html

1. a) Explain Parallel Projection in detail.
b) What are the different representations for polygon meshes?
c) What are the properties of Bezier Curve?
d) What is the difference between ambient, diffuse, and specular reflection?
e) How window-to-viewport coordinate transformation usually implemented?
f) What are the 2D Cues to Depth? Explain in detail.
g) Explain toning and show intensity level. (7×4)

2. a) Derive the basis matrix for Cubic Hermite Curve.
b) What is Gouraud shading model? Write down advantage and disadvantage of this model.
c) Define additive and subtractive colors giving an example of each. (9+5+4)

3. a) Rotate a triangle with vertices (10,20), (10,10), (20,10) about the origin by 30 degrees and then translate it by tx=5, ty=10.
b) A parametric cubic curve passes through the points (0,0), (2,4), (4,3), (5, -2) which are parametrized at t = 0, ¼, ¾, and 1, respectively. Determine the geometric coefficient matrix and the slope of the curve when t = 0.5. (9+9)

4. a) Use the Cohen Sutherland algorithm to clip line P1 (70,20) and P2(100,10) against a window lower left hand corner (50,10) and upper right hand corner (80,40).
b) Explain RGB color model.
c) Explain how Digital differential analyzer (DDA) line drawing algorithm works. (8+5+5)

5. a) Explain what are various ways to control animation?
b) Explain Sutherland Hodgman Algorithm in detail.
c) What is Animation? What are the various animation techniques? (6+6+6)

6. a) What is illumination? Explain the model used for illumination.
b) What is HSV color model? Draw HSV hexcone. (9+9)

7. Explain any three visible surface detection algorithms.
a) Scan-Line Method
b) Z-Buffer Algorithm
c) Depth-sort Algorithm
d) Binary Space Partitioning Trees (3×6)

C10-R4 : Software Systems :
1. a) Define feasibility study? List the salient features of feasibility report?
b) List the activities needed to be carried out during Project Initiation phase of the SDLC.
c) What are the objectives of Formal Technical Reviews (FTR)?
d) Develop a set of Use Cases for the Library Management System.

e) What are the factors that affect the Quality of the Software?
f) Requirements Gathering is an important step of Analysis. What are the dimensions of Requirements Gathering?
g) Discuss the role of Cohesion in the design of the Software? Explain the different types of Cohesion? (7×4)

2. a) What is the basic principle of prototype model? What are the prototyping approaches in software process development?
b) Differentiate between object oriented design and function oriented design.
c) Explain the following reliability model : (6+6+6)
i) Basic model
ii) Logarithmic
iii) Poisson Model

3. a) What is sequence of testing? What is testability? How is cyclomatic complexity useful in program test?
b) Explain various types of static and dynamic testing tools.
c) Compare and contrast between reliability and availability of software. (8+6+4)

4. a) What are the important roles of Conventional Component in the Software Architecture?
b) Differentiate between Class Diagram and Object Diagram.
c) What is the use of a data flow diagram? Explain the important concepts of data flow diagram. (6+6+6)

5. a) Explain the concept of bottom-up, top-down and hybrid design models.
b) Spiral model is a realistic approach to the development of large-scale systems and software. Justify and explain the model.
c) Define and explain various Object Oriented concepts used in Software Engineering. (4+8+6)

C9-R4: Soft Computing :
1. a) What is soft computing? Differentiate between soft computing and hard computing.
b) Genetic algorithms (GA) are different from traditional optimization methods. Highlight the key features of GA.
c) Explain Genetic Fuzzy Systems in brief.
d) Briefly discuss Roulette wheel selection method in GA.
e) Highlight some of the key characteristics of derivative free optimization
f) What are various application areas of Adaptive Neuro-Fuzzy Inference Systems (ANFIS)?
g) Define activation function and its types, applied for ANN problems. (7×4)

2. a) Elaborate fuzzy filtered neural networks? What are its advantages of use? Explain its applications.
b) Reinforcement learning is a popular method used in machine learning to produce intelligent programs. Justify the statement by giving a suitable example.
c) Briefly discuss Hill Climbing search technique. (6+6+6)

3. a) Simulated annealing (SA) is a probabilistic search technique. Briefly discuss SA. In order to apply the SA method to a specific problem, one must specify some parameters. Discuss those parameters in brief.
b) Discuss supervised and unsupervised learning techniques with suitable example. (12+6)

4. a) Considering a configuration of L-input neurons, m-hidden neurons, and n-output neurons, draw the architecture of Fuzzy Back Propagation System and discuss the computations carried out by each layer.
b) In context of Genetic Algorithms discuss the crossover operator and its types with example. (9+9)

5. a) Why Encoding for Genetic Algorithm based solution of a problem is required? Discuss Binary Encoding, Value Encoding, Permutation Encoding, and Tree Encoding with examples.
b) Briefly discuss Neuro–Genetic Hybrid system and its limitations. (12+6)

6. a) Discuss least square estimation technique and differentiate between linear and nonlinear least squares. Give appropriate example of each.
b) Define a Neuro-fuzzy system and briefly discuss its properties. (9+9)