DMDW Assignment III Sem I 2014_15 Class:BE IT

MGM’s College of Engineering, Nanded.
Department of IT
Semester I (2014-15)
Class: BE(IT)       Subject: DMDW         Assignment III
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1. Discuss the essential steps of apriori algorithm.

2. Define: 1) Support 2) Confidence. From the following database, find out the items with Support ≥ 40 %.

Tid	Items
T1	M, O, N, K
T2	D,O,N
T3	M, A, K, E
T4	M, U, C, Y
T5	C,O,O,K

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

4. Explain the requirements for data mining GUI.

5.  List the ways to improve the efficiency of apriori algorithm.

6. Give the comparison between Classification and Clustering.

7. What are Iceberg queries? Explain with an example.

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

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

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

11. State and explain the Bayesian algorithm.

12. Explain the decision tree induction algorithm.

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

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

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

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

2014-15 DMDW Assignment II

MGM’s College of Engineering, Nanded.
Department of IT
Semester I (2014-15)
Class: BE(IT)       Subject: DMDW         Assignment II
________________________________________________________

1.   Define data mining? Elaborate the characteristics of DM output.

2.   Discuss the different forms of data preprocessing in DM.

3.   Imagine that you need to analyze MGM_Student exam data. You find that many tuples have no recorded value for several attributes, such as student percentage. How can you go about filling in the missing values for this attribute?

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

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

6.   What is data transformation? What functions are performed in data transformation?

7.   (a) Define Min-max normalization. Suppose the minimum and maximum   values for the attribute percentage are 40 and 85, respectively. Using min-max normalization, transform and map value Rs. 76 to the range [0.0, 1.0].

(b) Define z-score normalization. The mean and standard deviation of the values for the attribute salary are Rs.44000 and Rs. 8900, respectively.Using z-score normalization transform a value of Rs. 55000.

8.   Suppose that the data for analysis includes the attribute percentage. The percentage values for the data tuples are (in increasing order) 11, 13, 14,14, 17, 18, 18, 19, 20, 20, 23, 23, 23, 23, 28, 31,31, 33, 33, 33, 33, 34, 38, 43, 44, 50, 68.
(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.).

9. For the data set of Q.8 above
(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?

10. 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?

11.Define the following DM functionalities: characterization, discrimination, association and correlation analysis. Give examples of each DM functionality, using a real-life database with which you are familiar.

12.Define classification, prediction, clustering, and evolution analysis. Give  examples of each using a real-life database with which you are familiar.

13. List and describe the five primitives for specifying a data mining task.

14. 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.

15.What is KDD? Enlist and explain the stages of KDD.

16. Use the two methods below to normalize the following group of data: 

    200,300,400,600,1000
    (a) min-max normalization by setting min=0 and max=1
    (b) z-score normalization

Faculty Incharge: Hashmi S A

2014-15 (SEM I) BE IT DMDW Assignment I

MGM’s College of Engineering, Nanded.
Department of IT
Semester I (2014-15)
Class: BE(IT)       Subject: DMDW         Assignment I

1.What are the differences between OLTP and OLAP? Elaborate

2. Enlist and explain the properties of DW.

3.Why a DW should be integrated and time-variant?

4.Briefly compare snowflake schema, fact constellation schema, star schema, and starnet query model with appropriate example.

5. List the major steps involved in ETL process.

6.Explain the differences between ROLAP AND MOLAP.

7. Describe the operations roll-up, drill-down, slice and dice, and pivot with proper example.

8. Draw and explain the three-tier data warehousing architecture.

9. What back-end tools and utilities are used in DW? Why?

10. What are the contents of DW metadata? Why metadata is important in DW?

11.What is bitmap indexing? What are the benefits of bitmap indexing? Create bitmap index for item and city for the following table:

TID	Item	City
T1	Hotdog	Mumbai
T2	Sauce	Pune
T3	Burger	Mumbai
T5	Hotdog	Nagpur
T6	Sauce	Nagpur

12. How are measures categorized in DW schema?

13. What are the usages of DW? Explain.

14.Suppose that a data warehouse consists of the three dimensions time,doctor, and patient, and the two measures count and charge, where charge is the fee that a doctor charges a patient for a visit.

(a) Enumerate three classes of schemas that are popularly used for modeling data warehouses.

(b) Draw a schema diagram for the above data warehouse using one of the schema classes listed in (a).

15.        For the above DW in Q14 , perform the following:

(a) Starting with the base cuboid [day, doctor, patient], what specific OLAP operations should be performed in order to list the total fee collected by each doctor in 2004?

(b) To obtain the same list, write an SQL query assuming the data are stored in a relational database with the schema fee (day, month, year, doctor, hospital, patient,count, charge).

16. 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.When at the
      lowest conceptual level (e.g., for a given student, course,
      semester, and instructor combination), the avg grade measure
     stores the actual course grade of the student. At higher conceptual
      levels, avg grade stores the average grade for the given
      combination.

(a) Draw a snowflake schema diagram for the data warehouse.

(b) Starting with the base cuboid [student, course, semester,
     instructor], what specific OLAP operations (e.g., roll-up from
     semester to year) should one perform in order to list the
      average grade of CS courses for each Big University student.

    17.   Suppose that a data warehouse consists of the four dimensions,
           date, spectator, location, and game, and the two measures, count
           and charge, where charge is the fare that a spectator pays when
           watching a game on a given date. Spectators may be 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, spectator, location, game],
         what specific OLAP operations should one perform in order to list
          the total charge paid by student spectators at GM_Place in 2004?
        (c) Bitmap indexing is useful in data warehousing. Taking this cube
          as an example,briefly discuss advantages and problems of using
          a bitmap index structure.

    18.  A company is using OLAP to provide monthly 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 20
           products, 10 branches and five years of monthly data?

Faculty Incharge: Hashmi S A

Semester II 2013-14 Assignment III Subject: MC Class: BE(IT)

MGM’s College of Engineering, Nanded.
Department of IT
Semester II (2013-14)
Class: BE(IT)       Subject: MC         Assignment III
________________________________________________________

1. Explain DHCP in detail.

2. Explain traditional TCP in detail.

3. What is encapsulation? Explain GRE in mobile IP.

4. Explain push and pull operation of WAP.

5. With neat diagram, explain the architecture of Wireless sensor networks.

6. Explain the difference between Web and WAP programming models.

7. List the entities of mobile IP and describe the data transfer from a fixed node to mobile node using mobile IP.

8. How does Indirect TCP isolate problems on the wireless links? What are the drawbacks of this solution?

9. Explain the memory management of Palm OS and Windows CE.

10. Explain snooping TCP with its advantages and disadvantages.

11. What are the applications of WSN? Explain the difference between MANET and WSN.

12. What are the requirements of routing protocols for WSN?

13. Draw and explain IP-in-IP encapsulation in mobile IP.

14. Draw and explain WAP protocol stack. What are the functions of WAP Gateway and Why it is required?

15. Give the comparison between I-TCP, M-TCP and Snooping TCP.

16. Assume a fixed internet connection with a round trip time of 20ms and an error rate 1/100000. Calculate the upper bound on TCP’s bandwidth for a maximum segment size of 1000 byte.

Faculty Incharge: Hashmi S A

Class: BE(IT) 2013-14 Subject: MC Assignment II

MGM’s College of Engineering, Nanded.
Department of IT
Semester II (2013-14)
Class: BE(IT)       Subject: MC         Assignment II
________________________________________________________

1. Explain traffic channel and control channel used in GSM.

2. Write a short note on IMT-2000.

3. Explain UMTS system architecture.

4. Draw and explain system architecture of GSM.

5. Explain DECT protocol architecture with suitable diagram.

6. Write a note on TETRA with its frame structure.

7. Define handover. What are the reasons for handover and also explain types of
    handover?

8. Draw and explain the GPRS architecture reference model.

9. What is authentication? Discuss how it is carried out in Bluetooth security.

10. How Bluetooth Piconet and scatternet are formed? Explain.

11. Draw and explain Bluetooth protocol stack.

12. Which physical interface is used in Bluetooth headset? Why?

13. A mobile handset is designed with Bluetooth interface, specify the
     interfaces required for this device. Justify, why you need this interface.

14. How the power is saved in Bluetooth device? Enlist and explain the states of
      Bluetooth devices.

15. What are the functions of LMP and L2CAP in Bluetooth standard?

16. Draw and explain GSM and GPRS protocol reference model.

Faculty Incharge: Hashmi S A

MC Assignment I Class : BE (IT) Semester II 2013-14

Class : BE (IT) Semester II  2013-14

Assignment I

Subject: MC

1. Explain multiplexing with its four types.

2.Compare IR and radio transmission with their advantages and drawbacks.

3.Explain three versions of IEEE PHY Layer.

4.Discuss DFWMAC-DCF with CSMA/CA.

5.Explain path loss of radio signal.

6.Compare Infrastrucure and Adhoc architectures of IEEE 802.11.

7. What additional functions are needed for wireless MAC and Why?

8. Draw and explain the IEEE 802.11 FHSS frame format.

9. A data of 20 bytes is transmitted on IEEE 802.11 MAC. Calculate the frame size for FHSS and DSSS frames.

10.How priorities are defined in IEEE 802.11 MAC ? Explain different IFS for priorities.

11. Explain the working of classical and slotted ALOHA.

12. How the hidden and exposed termainals problem is solved in 802.11 MAC?

13. How RTS/CTS based media access mechanism works ? Explain.

14.Compare FDMA, SDMA, TDMA and CDMA.

15.Draw and explain IEEE 802.11 MAC packet structure.

16. The first 8 bits of frame control of 802.11 MAC are :

       00010000

       What is the type and function of this frame ?

*****************************All The Best***************************************

Faculty Incharge: Hashmi S A