Question Papers

1. USN
Max. Marks:100
Note: Arcs;w,er sny FIVE full questions"
Discuss the content architecture with respect trr mobile computing with a neat sketch.
(10 Marks)
List and explain the main elements of iS-95 along with the reference architecture model.
(10 Marks)
What is meant by handover? Discuss various types of handover and handover procedure in
GSM. (10 Marks)
Define SMS. List and explain unique characteristics of SMS. (06 Marks)
Write a short note on WiMAX. (04 Marks)
Networks and Mobile Gornputing
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Fourth Semester
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Time: 3 hrs.
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a. With a neat diagram, explain server synchronization smart client architecture. (10 Marks)
b. What are device emulators? Write various features of device emulators. Also discuss any
two device emulators in brief. (10 Marks)
a. Explain palm OS architecture with a neat sketch. (10 Marks)
b. Write the smart client development cycle. Explain needs analysis and design phase in detail.
(10 Nfarks)
a. List the components of PDA. Explain each of them in detail.
b. Briefly explain discovery, registration and tunneling operations in mobile IP.
a. Discuss various steps involved in processing a wireless request in detail.
b. Explain WAP programming rnodel using a wireless gateway.
c. Explain various benefits of WAP.
What is the necessity of XHTML in wireless internet applications? How
from HTML?
What is meant by CDC 7 Discuss three CDC profiles.
Discuss several security features built into MIDP2.0 to protect the users
applications.
a. Explain MID let life cycle with states and context methods.
b. Explain the following low-level GUI components :
i) Canvas
ii) Game API
iii) Sprite
iv) Tilled layer.
(10 Marks)
(10 Marks)
(10 Marks)
(06 Marks)
(04 Marks)
XHTML differs
(06 Marks)
(07 Marks)
from rogue
(07 Marks)
(10 Marks)
la.
b.
c.
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(10 Marks)

2. USN
Time: 3 hrs.
I a. Explain the steps
b. Describe the find
Fourth Semester M.Tech. Degree
Machine Learning
Note: Answer ilny FIVE fall questions.
in designing a learning system.
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Marks:100
(10 Maiks)
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- S algorithm. Explain its working, taking the enjoy
trainins insta iven belo
a. Explain the concepts of entropy and information gain.
b. Describe the ID3 algorithm for decision tree learning.
c. Give decision trees to represent the following Boolean functions:
i) A&& -B
ii) A"[B &&c1
iii) A xoR B
iv) [e a &B]" [c & &D]
a. Explain the differentiable sigmoid threshold unit.
b. Consider two perceptrons defined by the threshold expression oo *orXr
(10 Marks)
(06 Marks)
(10 Marks)
(04 Marks)
(06 Marks)
* CIzX, ) 0,
perception A has weight values
0o:1,0r.=2,0,:1
and perceptron B has weight values
0o:0,0r=2,0, =1
True or False? Perceptron A is more-generai-than perceptron B.
c' Explain the back propagation algorithm. Why is it not likely to be trapped in
a. Explain the terms genetic algorithms and genetic programming.
b. Explain GA, a prototyping genetic algorithm.
c. Explain stacking of blocks problem and genetic programming solution.
a. Explain naive Bayes classifier.
i Erpier;, r:irslake Ltrund nrodel tirr iearning and appl)'it to FIND-S algorithm.
a- Describe K-EAREST EIGHBOUR learning alqorithm tbr continuous valued target
functions. Dtscuss one ntaior drariback of this aleorithm and hou'it can be corrected.
(04 Marks)
local minima?
(10 Marks)
(05 Marks)
(10 Marks)
(05 Marks)
(IO Marks)
(10 Marks)
b. -rite th.. FOIL :letrrirltin tr-rr learning rule sets
functitrn trf inner lurt)p.
a. .hat is i'euribrcentent leanring'.,
b. Erplain the Q ttincrion and Q leaming algorithm.
c. Compare urducrir e leanring anci anah'tical learniirg.
'rite short note on:
a. Bavesian belief netrvorks.
b. Occam's Razor and minimum description principle.
c. Case based learning.
*****
(12 Nlarks)
and erplain the purpose of outer loop and the
(08 Marks)
(06 Marks)
(10 Marks)
(04 Marks)
(06 NIarks)
(06 NIarks)
(08 Marks)
nstances qlven w:
Example Skv Air temp Humidity Wind Water Forecast Eniov sport
I Sunny Warm Normal Strong Warm Same Yes
2 Sunny Warm Hish Strong Warm Same Yes
J Rainy Cold Hish Strong Warm Chanee No
4 Sunny Warm Hieh Strong Warm Chanse Yes