2015-16 Subject: A C N Assignment II Class: TE(IT)

MGM’s College of Engineering, Nanded.
Department of IT
Semester II (2015-16)
Class: TE(IT)       Subject: A C N       Assignment II

1.      Draw and explain ARP and RARP protocol format.

2.      Draw and explain the header format of IPv4.

3.      Explain classful addressing in TCP/IP.

4.      Explain the concept of (i) datagram encapsulation, (ii) network MTU, (iii) and multiplexing at IP and TCP layers.

5.      Change the following IPv4 addresses from binary to hexadecimal notation.

i)10000001  00001011  00001011  11101111

ii)11000001  10000011  00011011  11111111

6.      What is proxy ARP? Explain with example.

7.      What is ARP? Exaplain ARP cache timeout.

8.      For the following addresses, find the class, the block and the range of addresses:

(i)                 10.1.1.1     (ii) 147.55.1.1  (iii) 215.121.74.1

9.      Calculate the checksum for the following IP datagram

4	5	0	35
2F			0	0
4	17		0
198.169.11.2
195.167.19.9

10.  Change the following IP addresses from dotted-decimal notation to binary notation.

(i)                 115.57.45.80  (ii)  215.210.211.198  (iii)  71.15.10.12

11.  Find the error, if any, in the following IP addresses:

(i)                 110.075.79.85   (ii)  75.91.279.15  (iii)  260.074.155.261

12.  Find the class of the following IP addresses, and give explanation for it:

(i)                 11000001  10000011   00011011 11111111

(ii)               00100001  00001011   00001011 11101111

(iii)             10010001 00001011   00001011 11101111

13.  Define : (i) Multihomed host (ii) Directed broadcast address (iii) Limited broadcast address (iv) Loopback address.

14.  (a) An IP packet has arrived with the first 8 bits as shown:

                                       ç  01100010

     The receiver discards the packet. Why?

(b) In an IP packet, the value of HLEN is 1010 in binary. How many bytes of options are being carried by this packet?

15.  (a) In an IP packet, the value of HLEN is 5 (decimal) and the value of the total length field is 28 (decimal). How many bytes of data are being carried by this packet?

(b) In an IP packet, the value of HLEN is 0A (hex) and the value of the total length field is 0A2F (hex). How many bytes of data are being carried by this packet?

16.  An IP packet has arrived with the hexadecimal digits as shown below:

ç  450000380d3a00000201bb6ec0a802034a7de2f4

How many hops can this packet travel before being dropped, The data belong to what upper layer protocol, What is identification value, what is the value for checksum, what is source and destination address?

Faculty Incharge: Hashmi S A

Class: BE(IT) Subject: MC Assignment-I Semester II (2015-16)

MGM’s College of Engineering, Nanded.
Department of IT
Semester II (2015-16)
Class: BE(IT)       Subject: MC         Assignment I
________________________________________________________

1.     Give comparison between FDMA, TDMA, SDMA and CDMA.

2.     What are the design goals of wireless LAN? Why?

3.     What are advantages of radio communication over IR communication?

4.     Enlist applications of mobile and wireless communication.

5.     What are the drawbacks of mobile and wireless communication? Explain.

6.     Give comparison between wireless networks and fixed networks.

7.     What are the different digital modulation techniques? Discuss in brief.

8.     Compare 802.3 and 802.11 standards.

9.     Draw and explain IEEE 802.11 infrastructure-based architecture.

10. Draw and explain IEEE 802.11 ad-hoc architecture.

11.  State and explain the functions of 802.11 layers

12.  What additional functions are required for wireless MAC protocol? Why?

13.  Draw and explain IEEE 802.11 FHSS frame format.

14. What are the similarities and differences between 802.11 FHSS and DSSS frame formats?

15.  A ftp protocol delivers a pdf file of 10MB on 802.11 network having 2Mbps speed. Calculate the size of FHSS, DSSS frames and time required for transmission.

16. Calculate Ethernet frame size for the above transmission of Q.15.

Faculty Incharge: Hashmi S A

Class: TE(IT) Subject: A C N Assignment I Semester II (2015-16)

MGM’s College of Engineering, Nanded.
Department of IT
Semester II (2015-16)
Class: TE(IT)       Subject: A C N       Assignment I

1.      Draw the architecture of Internet. Explain its components.

2.      Enlist and explain the properties of internet.

3.      What services are provided by network-level of internet? Discuss in detail.

4.      Explain in detail application-level services of internet.

5.      Draw and explain different fields of Ethernet frame.

6.      Compare connection-oriented and connectionless delivery systems.

7.      Enlist the advantages and drawbacks of packet-switching networks.

8.      What are the advantages of circuit-switching networks over packet-switching? Why?

9.      Explain the layers of network protocol used for World Wide Web.

10.  What connecting devices are used at layer-1, layer-2, and layer-3 in internet? Explain their characteristics and functions.

11.  What addresses are used at layer-1, layer-2, and layer-3 in internet? Explain briefly.

12.  Explain the application programs at your site that use TCP/IP.

13.  What is Ethernet address? What are its properties?

14.  Calculate the time required to download a 2GB file on an internet having speed of 100Mbps.

15.  What is an IP address? What are the desirable properties of IP address? What is signified by prefix and suffix of IP address?

16.  What are the differences between Ethernet address and IP address?

Faculty Incharge: Hashmi S A

Assignment III DMDW 2015-16 BEIT

MGM’s College of Engineering, Nanded.
Department of IT
Semester I (2015-16)
Class: BE(IT)       Subject: DMDW         Assignment III
_________________________________________________________________

1.  For the following transaction database, find out the frequent itemsets with support  ≥ 50 %.

Tid	Items
T1	N, P, O, M
T2	E,P,O
T3	N, B, M, F
T4	N, V, D, Z
T5	D,P,P,M
T6	P, O

2. Discuss the essential steps of apriori algorithm.

3. For the above transaction database, find the itemsets having confidence ≥ 60 %.

4. What are the differences between Classification, Clustering & Prediction ?

5. What are the various forms of presenting and visualizing the discovered patterns?

6. What is information gain? How Information Gain is calculated?

7. For the following dataset, calculate Information Gain for attribute age.

 

 

8. Discuss the Multilevel Association Rules mining for transaction database.

9. State and explain the Bayesian algorithm.

10. Create a Naïve Bayesian Classifier for the following dataset. Classify the sample      X={ rain, hot, high, false }

                                               

                      

      

11.Explain the decision tree induction algorithm.

12. What are the different techniques to calculate the distance between patterns?

13. Explain the different types of cluster analysis methods and discuss their features.

14. Describe k-means algorithm and discuss its strengths and weaknesses.

15. Discuss the taxonomy of web mining.
16. The following table shows a set of paired data where x is the number of years of work experience of a college graduate and y is corresponding salary of the graduate. There is a linear relationship between the two variables, x and y. Use Straight-line regression method with least squares and predict the salary of a college graduate with 10 years of experience.

x years experience	y salary (in $1000s)
5	32
10	59
11	66
15	74
5	38
8	45
13	61
23	92
3	22
18	85

      

Faculty Incharge: Hashmi S A

Semester I (2015-16) Assignment II Class: BE(IT) Subject: DMDW

MGM’s College of Engineering, Nanded.
Department of IT
Semester I (2015-16)
Class: BE(IT)       Subject: DMDW         Assignment II
___________________________________________________________________________

1

     1.What is data mining? What features are expected from a of DM output.

2   2.Why data preprocessing is needed in DM? Explain the different forms of data preprocessing.

3   3.Consider that you have to analyze EMart_Customer  sales data. You find that many tuples have no   recorded value for several attributes, such as customer total_amount. How can you fill the missing   values for this attribute?

4   4.Given a numerical attribute such as total_amount in the above data set, how can we smooth out the data to remove the noise?

5   5.Suppose that the data for analysis includes the attribute total_marks. Which distributive, algebraic and holistic measures will be used for data analysis?

6   6.(a) Define Min-max normalization. Suppose the minimum and maximum values for the attribute total_sales are Rs.40000 and Rs.85000, respectively. Using min-max normalization, transform and map value Rs. 76000 to the range [0.0, 1.0].

(b) Define z-score normalization. The mean and standard deviation of the values for the attribute total_marks are 4400 and 890, respectively. Using z-score normalization to transform value 5500.

7   7.Suppose that the data for analysis includes the attribute marks. The marks values for the data tuples are (in increasing order) 13, 15, 16, 16, 19, 20, 20, 21, 22, 22, 25, 25, 25, 25, 30, 33,33, 35, 35, 35, 35, 36, 40, 45, 46, 52, 70.

    (a) What is the mean of the data? What is the median?

    (b) What is the mode of the data? Comment on the data’s modality (i.e., bimodal, trimodal, etc.).

8.For the data set of Q.8 abov

   (c) What is the midrange of the data?

   (d) Can you find (roughly) the first quartile (Q1) and the third quartile (Q3) of the
           data?

9. For the data set of Q.8 above

   (e) Give the five-number summary of the data.

   (f) Show a boxplot of the data.

   (g) How is a quantile-quantile plot different from a quantile plot?

10.  Define the following DM functionalities:characterization,discrimination,association and correlation analysis.

11.  Explain five primitives of data mining with an appropriate example.

12.  Describe the differences between the following approaches for the integration of a 

data mining  system with a database or DW system: no coupling, loose coupling,semitight coupling, and tight coupling.13.What is KDD? Explain the stages of KDD with an appropriate example.

14.Use the two methods below to normalize the following group of data: 2000,3000,4000,6000,10000

       (a) min-max normalization by setting min=0 and max=1

       (b) z-score normalization

15. Define (i) Association rule mining (ii) Support  (iii) Confidence.

16. Enlist applications of Data Mining and Association rule mining.

Faculty Incharge: Hashmi S A

SEM I 2015-16 Subject:DMDW Class:BE(IT) Assignment I

MGM’s College of Engineering, Nanded.
Department of IT
Semester I (2015-16)
Class: BE(IT)       Subject: DMDW         Assignment I

1. Define data warehouse. Explain the characteristics of DW.
2. Compare DBMs with DW.
3. Draw and explain star schema with an example.
4. Enlist the features of snowflake and fact constellation schema with appropriate
    example.
5. What are the major components of data warehouse architecture? Explain with
    block diagram.
6. Describe the OLAP operations with an appropriate example.
7. Draw and explain ROLAP, MOLAP and HOLAP models of DW.
8. Suppose that a data warehouse consists of the three dimensions Time,
    Trainer, and Trainee, and the two measures count and Fee, where fee is  
     charged by the trainer for training.
    Draw a star and snowflake schema diagram for the above data warehouse.
9. Why metadata is important for DW?
10. What back-end tools and utilities are used in DW? Why?
11. Enlist and explain the applications of DW.
12. A company is using DW to provide quarterly summary information about its
      products and branch sales to the company managers. How many different
      aggregates would be required to fill data cube on product, branches and
      dates if there are 50 products, 5 branches and 7 years of monthly data?
13. Draw starnet query model for above DW (Q. No.12) by considering additional
      3 more dimensions.
14. What is bitmap indexing? What are the benefits of bitmap indexing? Create
      bitmap index for rank and class for the following table:

TID	Rank	Class
T1	First	BE
T2	Second	ME
T3	Distinction	BE
T5	First	HSC
T6	Second	HSC

15. Suppose that a data warehouse for Big University consists of the following
      four dimensions: student, course, semester, and instructor, and two
      measures count and avg grade. What issues are important in building this
      DW?

16. Suppose that a data warehouse consists of the four dimensions, date,
     teams, location, and game, and the two measures, count and charge,
     where charge is the fare that a team pays when playing a game on a
     given date. Teams may be of students, adults, or seniors, with each
     category having its own charge rate.

(a) Draw a star schema diagram for the data warehouse.
(b) Starting with the base cuboid [date, teams, location, game],
      what specific OLAP operations should one perform in order to list
      the total charge paid by student teams at GM_Place in 2004?

Faculty Incharge: Hashmi S A

MGM’s College of Engineering, Nanded
Department of IT
BE (IT) – 2014-15 (Sem2)
MOBILE COMPUTING TERM WORK LIST

1. Design of WLAN.

2. Study of VSAT communication system.

3. Study of Broadcom Wireless device BCM4330.

4. Creation of Ad-hoc WLAN using IEEE 802.11.

5. Creation of Infrastructure –based WLAN using D- Link IEEE 802.11 Access Point DWL 2100AP.

6. Building an application for android phone.

7. To study and create Bluetooth network.

8. To study basic concepts of WAP, WAP architecture, application, etc.

9. To study basic tags of WML.

10. Simulation of WLAN using ns-2.

Faculty Incharge: Hashmi S A