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CUSTOMER_CODE
SMUDE
DIVISION_CODE
SMUDE
EVENT_CODE
APR2016
ASSESSMENT_CODE MC0077_APR2016
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
3123
QUESTION_TEXT
Discuss the classification of data in Fuzzy Databases
SCHEME OF
EVALUATION
1.Crisp: there is no vagueness
2.Fuzzy: there is vagueness in the information and this can be divided
into two subparts
a.Approximate value: the information data is not totally vague and there
is some approximate value, which is known and the data, lies near that
value.
b.Linguistic variable: it is a variable that apart from representing a fuzzy
number also representing a fuzzy number also represents linguistic
concepts interpreted in a particular context. A linguistic variable is fully
characterized by a quintuple<v, T, X, g, m> (10 marks)
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
74079
QUESTION_TEXT
List and explain various normal forms.
SCHEME OF
EVALUATION
Normal Forms
Relations are classified based upon the types of anomalies to which they're
vulnerable. A database that's in the first normal form is vulnerable to all types
of anomalies, while a database that's in the domain/key normal form has no
modification anomalies.
First Normal Form
Any table having any relation is said to be in the first normal form. The criteria
that must be met to be considered relational is that the cells of the table must
contain only single values, and repeat groups or arrays are not allowed as
values.
Second Normal Form
If all a relational database's non-key attributes are dependent on all of the key,
then the database is considered to meet the criteria for being in the second
normal form.
Third Normal FormA database is in the third normal form if it meets the
criteria for a second normal form and has no transitive dependencies.
Boyce-Codd Normal Form
A database that meets third normal form criteria and every determinant in the
database is a candidate key, it's said to be in the Boyce-Codd Normal Form.
This normal form solves the issue of functional dependencies.
Fourth Normal Form
Fourth Normal Form (4NF) is an extension of BCNF for functional and multivalued dependencies. A schema is in 4NF if the left hand side of every nontrivial functional or multi-valued dependency is a super-key.
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
74080
QUESTION_TEXT
Write a note on
a. indexes
b. views
SCHEME OF
EVALUATION
Indexes
Consider, for example, a rule-based technique for query optimization that
states that indexed access to data is preferable to a full table scan.
Q2: SELECT *
FROM Patient
WHERE Patient.SSN = 11111111
Q3: SELECT *
FROM Patient
WHERE Patient.Name = “Doe, John Q.”
Selectivity
A more significant problem occurs when more than one condition is used in a
conjunctive selection. In this case the selectivity of each condition must be
considered.
Q4: SELECT *
FROM Patient
WHERE Age = 45 AND Gender = M
Q5: SELECT *
FROM Patient
WHERE Gender = M AND Age = 45
In this query, the Age attribute is specified first.
This query specifies Gender first.
3 Uniformity
In many cases the actual data does not follow a uniform distribution. Consider the
case where 95% of the patients live in the province of New Brunswick and the
remaining 5% live in 199 different states and countries of the world.
Q6: SELECT *
FROM Patient
WHERE Area = “Ontario” AND Age = 45
Q7: SELECT *
FROM Patient
WHERE Area = “New Brunswick” AND Age = 45
Disjunctive Clauses
A disjunctive clause occurs when simple conditions are connected by the OR logical
connective rather than AND. These clauses are much harder to process and optimize.
Q8: SELECT *
FROM Patient
WHERE Doctor = 1234 OR Area = “Ontario”
Q9: SELECT *
FROM Patient
WHERE Doctor = 1234 AND Area = “Ontario”
Join Selectivity
The JOIN operation is one of the most time consuming operations in query
processing. A join operation matches two tables across domain compatible attributes.
Q10: SELECT *
FROM Patient, Physician
WHERE Patient.SSN = Physician.Dr_SSN
Q11: SELECT *
FROM Patient, Physician
WHERE Physician.Dr_SSN = Patient.SSN
Views
A view in SQL is a single table that is derived from other tables. A view can be
considered as a virtual table or as a stored query. A view is often used to specify a
frequently used query.
CREATE VIEW DrService (Dr, Specialty, Age, TotCost) AS
SELECT Provider, Specialty,Age,Sum(Cost)
FROM Patient, Physician, Treatment
WHERE SSN = Dr_SSN AND DrNum = Provider
GROUP BY Provider
Q12: SELECT *
FROM DrService
WHERE Specialty = “Opthamologist”
Q13: SELECT *
FROM Physician
WHERE Specialty = “Opthamologist”
QUESTION_T
DESCRIPTIVE_QUESTION
YPE
QUESTION_ID 74081
QUESTION_T
Briefly explain the characteristics of text documents and characteristics of images.
EXT
SCHEME OF
EVALUATION
Characteristics of Text Documents
Text documents can be considered semi-structured in the sense that they are
constructed from a defined term vocabulary according to known grammatical rules
for forming sentences and paragraphs. As documents, they also share some
common elements such as an author, title, date of origin, a (set of) title(s), and
perhaps a recipient. A text document can be described from 3 perspectives:
1. Semantic content of the document, i.e. representation of its meaning,
2. Context of the document, e.g. its author, publisher
3. Structure of the document, e.g. its language, style, length, ...
Context and structure descriptors can be given as regular attributes of the document
and can be modeled using any structural data model. Modeling the semantic content
is more difficult.
Characteristics of Images
Image documents are represented as unstructured data, actually by a bit or pixel
(picture element) string. As opposed to text documents, they do not have a standard
'vocabulary' or grammar that can be used for automatic interpretation of the semantic
content, or meaning of the image. Instead, most image management systems use
manual annotations, such as title/caption, keywords and/or text descriptions, to
capture semantic interpretation. Since an image can be viewed as a document, the
same types of metadata as used in Dublin Core can capture context metadata, while
structural descriptors would include such characteristics as size in height and width,
materials used, and implementation format.
In addition to text annotations, the semantic content of images can be described by
content descriptors, frequently called features. Image features can be classified
according to their level of abstraction, or distance from the actual physical content of
the image:
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
74084
QUESTION_TEXT
Explain Conservative timestamp ordering algorithm s
SCHEME OF
EVALUATION
Conservative Timestamp Ordering Algorithms
The basic TO algorithm tries to execute an operation as soon as it is accepted;
it is therefore "aggressive" and "progressive". Conservative algorithms, on the
other hand, delay each operation until there is an assurance that no operation
with a smaller timestamp can arrive at that scheduler.
1) Each transaction is executed at one site only and does not activate
remote programs. It can only issue read or write requests to remote sites.
2) A site i must receive all the read requests from a different site j in
timestamp order. Similarly, a site i must receive all the write requests from a
different site j in timestamp order.
3) Assume that a site i has at least one buffered read and one buffered write
operation from each other site of the network. Because of requirement 2, site i
knows that there are no older requests which can arrive from any site. The
concurrency controller at site i behave therefore in the following way:
a. For a read operation R that arrives at site i:
If there is some write operation W buffered at site i such that TS(R) >
TS(W), then R is buffered until these writes are executed, else R is executed.
b. For a write operation W that arrives at site i:
If there is some read operation R buffered at site i such that
TS(W) > TS(R) or there is some write operation W' buffered at site i such that
TS(W) > TS(W'), then W is buffered until these operations are executed, else
W is executed.
QUESTION_TYPE
DESCRIPTIVE_QUESTION
QUESTION_ID
112441
QUESTION_TEXT
Write a note on Database Tuning
Performance is the way a computer system behaves given a particular
work load. Performance is measured in terms of system response time,
throughput, and availability. Performance is also affected by: The
resources available in your system and How well those resources are
used and shared.
(3 marks)
In general, you tune your system to improve its cost-benefit ratio.
Specific goals could include: Processing a larger, or more demanding,
work load without increasing processing costs.
(2 marks)
SCHEME OF
EVALUATION
For example, to increase the work load without buying new hardware or
using more processor time:
>
Obtaining faster system response times, or higher throughput,
without increasing processing costs.
>
Reducing processing costs without degrading service to your
users.
(2 marks)
Translating performance from technical terms to economic terms is
difficult. Performance tuning certainly costs money in terms of user time
as well as processor time, so before you undertake a tuning project,
weighs its costs against its possible benefits. Some of these benefits are
tangible: More efficient use of resources.The ability to add more users to
the system.
(3 marks)