McqMate
| 101. |
The intent of project metrics is: |
| A. | minimization of development schedule |
| B. | for strategic purposes |
| C. | assessing project quality on ongoing basis |
| D. | minimization of development schedule and assessing project quality on ongoing basis |
| Answer» D. minimization of development schedule and assessing project quality on ongoing basis | |
| Explanation: a project metric is a quantitative measure of the degree to which a system, component or process possesses an attribute. | |
| 102. |
Which of the following is not a direct measure of SE process? |
| A. | efficiency |
| B. | cost |
| C. | effort applied |
| D. | all of the mentioned |
| Answer» A. efficiency | |
| Explanation: efficiency is an indirect measure. | |
| 103. |
Which of the following is an indirect measure of product? |
| A. | quality |
| B. | complexity |
| C. | reliability |
| D. | all of the mentioned |
| Answer» D. all of the mentioned | |
| Explanation: all the mentioned options are indirect measures of a product. | |
| 104. |
In size oriented metrics, metrics are developed based on the |
| A. | number of functions |
| B. | number of user inputs |
| C. | number of lines of code |
| D. | amount of memory usage |
| Answer» C. number of lines of code | |
| Explanation: none. | |
| 105. |
Which of the following is not an information domain required for determining function point in FPA ? |
| A. | number of user input |
| B. | number of user inquiries |
| C. | number of external interfaces |
| D. | number of errors |
| Answer» D. number of errors | |
| Explanation: fpa includes five domains namely input, output, inquiries, interface and logical files. | |
| 106. |
Usability can be measured in terms of: |
| A. | intellectual skill to learn the system |
| B. | time required to become moderately efficient in system usage |
| C. | net increase in productivity |
| D. | all of the mentioned |
| Answer» D. all of the mentioned | |
| Explanation: none. | |
| 107. |
A graphical technique for finding if changes and variation in metrics data are meaningful is known as |
| A. | dre (defect removal efficiency) |
| B. | function points analysis |
| C. | control chart |
| D. | all of the mentioned |
| Answer» C. control chart | |
| Explanation: others options are formulas. | |
| 108. |
Defects removal efficiency (DRE)depends on: |
| A. | e – errors found before software delivery |
| B. | d – defects found after delivery to user |
| C. | both e and d |
| D. | varies with project |
| Answer» C. both e and d | |
| Explanation: dre = e / (e + d). | |
| 109. |
What’s the role of lyaopunov fuction? |
| A. | to determine stability |
| B. | to determine convergence |
| C. | both stability & convergence |
| D. | none of the mentioned |
| Answer» A. to determine stability | |
| Explanation: lyapunov is an energy function. | |
| 110. |
Explanation: It is sufficient but not necessary condition. |
| A. | v(x) >=0 |
| B. | v(x) <=0 |
| C. | v(x) =0 |
| D. | none of the mentioned |
| Answer» B. v(x) <=0 | |
| Explanation: it is the condition for existence for lyapunov function. | |
| 111. |
What does cohen grossberg theorem? |
| A. | shows the stability of fixed weight autoassociative networks |
| B. | shows the stability of adaptive autoaassociative networks |
| C. | shows the stability of adaptive heteroassociative networks |
| D. | none of the mentioned |
| Answer» A. shows the stability of fixed weight autoassociative networks | |
| Explanation: cohen grossberg theorem shows the stability of fixed weight autoassociative networks. | |
| 112. |
What does cohen grossberg kosko theorem? |
| A. | shows the stability of fixed weight autoassociative networks |
| B. | shows the stability of adaptive autoaassociative networks |
| C. | shows the stability of adaptive heteroassociative networks |
| D. | none of the mentioned |
| Answer» B. shows the stability of adaptive autoaassociative networks | |
| Explanation: cohen grossberg kosko shows the stability of adaptive autoaassociative networks. | |
| 113. |
What does 3rd theorem that describe the stability of a set of nonlinear dynamical systems? |
| A. | shows the stability of fixed weight autoassociative networks |
| B. | shows the stability of adaptive autoaassociative networks |
| C. | shows the stability of adaptive heteroassociative networks |
| D. | none of the mentioned |
| Answer» C. shows the stability of adaptive heteroassociative networks | |
| Explanation: 3rd theorem of nonlinear dynamical systems, shows the stability of adaptive heteroassociative networks. | |
| 114. |
What happens during recall in neural networks? |
| A. | weight changes are suppressed |
| B. | input to the network determines the output activation |
| C. | both process has to happen |
| D. | none of the mentioned |
| Answer» C. both process has to happen | |
| Explanation: follows from basic definition of recall in a network. | |
| 115. |
In nearest neighbour case, the stored pattern closest to input pattern is recalled, where does it occurs? |
| A. | feedback pattern classification |
| B. | feedforward pattern classification |
| C. | can be feedback or feedforward |
| D. | none of the mentioned |
| Answer» B. feedforward pattern classification | |
| Explanation: it is a case of feedforward networks. | |
| 116. |
What is the field of Natural Language Processing (NLP)? |
| A. | computer science |
| B. | artificial intelligence |
| C. | linguistics |
| D. | all of the mentioned |
| Answer» D. all of the mentioned | |
| Explanation: none. | |
| 117. |
What is the main challenge/s of NLP? |
| A. | handling ambiguity of sentences |
| B. | handling tokenization |
| C. | handling pos-tagging |
| D. | all of the mentioned |
| Answer» A. handling ambiguity of sentences | |
| Explanation: there are enormous ambiguity exists when processing natural language. | |
| 118. |
Choose form the following areas where NLP can be useful. |
| A. | automatic text summarization |
| B. | automatic question-answering systems |
| C. | information retrieval |
| D. | all of the mentioned |
| Answer» D. all of the mentioned | |
| Explanation: none. | |
| 119. |
Which of the following includes major tasks of NLP? |
| A. | automatic summarization |
| B. | discourse analysis |
| C. | machine translation |
| D. | all of the mentioned |
| Answer» D. all of the mentioned | |
| Explanation: there is even bigger list of tasks | |
| 120. |
What is Coreference Resolution? |
| A. | anaphora resolution |
| B. | given a sentence or larger chunk of text, determine which words (“mentions”) refer to the same objects (“entities”) |
| C. | all of the mentioned |
| D. | none of the mentioned |
| Answer» B. given a sentence or larger chunk of text, determine which words (“mentions”) refer to the same objects (“entities”) | |
| Explanation: anaphora resolution is a specific type of coreference resolution. | |
| 121. |
What is Machine Translation? |
| A. | converts one human language to another |
| B. | converts human language to machine language |
| C. | converts any human language to english |
| D. | converts machine language to human language |
| Answer» A. converts one human language to another | |
| Explanation: the best known example of machine translation is google translator. | |
| 122. |
What is Morphological Segmentation? |
| A. | does discourse analysis |
| B. | separate words into individual morphemes and identify the class of the morphemes |
| C. | is an extension of propositional logic |
| D. | none of the mentioned |
| Answer» B. separate words into individual morphemes and identify the class of the morphemes | |
| Explanation: none. | |
| 123. |
Which of the following clustering type has characteristic shown in the below figure? |
| A. | partitional |
| B. | hierarchical |
| C. | naive bayes |
| D. | none of the mentioned |
| Answer» B. hierarchical | |
| Explanation: hierarchical clustering groups data over a variety of scales by creating a cluster tree or dendrogram. | |
| 124. |
Point out the correct statement. |
| A. | the choice of an appropriate metric will influence the shape of the clusters |
| B. | hierarchical clustering is also called hca |
| C. | in general, the merges and splits are determined in a greedy manner |
| D. | all of the mentioned |
| Answer» D. all of the mentioned | |
| Explanation: some elements may be close to one another according to one distance and farther away according to another. | |
| 125. |
Which of the following is finally produced by Hierarchical Clustering? |
| A. | final estimate of cluster centroids |
| B. | tree showing how close things are to each other |
| C. | assignment of each point to clusters |
| D. | all of the mentioned |
| Answer» B. tree showing how close things are to each other | |
| Explanation: hierarchical clustering is an agglomerative approach. | |
| 126. |
Which of the following is required by K- means clustering? |
| A. | defined distance metric |
| B. | number of clusters |
| C. | initial guess as to cluster centroids |
| D. | all of the mentioned |
| Answer» D. all of the mentioned | |
| Explanation: k-means clustering follows partitioning approach. | |
| 127. |
Point out the wrong statement. |
| A. | k-means clustering is a method of vector quantization |
| B. | k-means clustering aims to partition n observations into k clusters |
| C. | k-nearest neighbor is same as k-means |
| D. | none of the mentioned |
| Answer» C. k-nearest neighbor is same as k-means | |
| Explanation: k-nearest neighbor has nothing to do with k-means. | |
| 128. |
Which of the following combination is incorrect? |
| A. | continuous – euclidean distance |
| B. | continuous – correlation similarity |
| C. | binary – manhattan distance |
| D. | none of the mentioned |
| Answer» D. none of the mentioned | |
| Explanation: you should choose a distance/similarity that makes sense for your problem. | |
| 129. |
Which of the following function is used for k-means clustering? |
| A. | k-means |
| B. | k-mean |
| C. | heatmap |
| D. | none of the mentioned |
| Answer» A. k-means | |
| Explanation: k-means requires a number of clusters. | |
| 130. |
Which of the following clustering requires merging approach? |
| A. | partitional |
| B. | hierarchical |
| C. | naive bayes |
| D. | none of the mentioned |
| Answer» B. hierarchical | |
| Explanation: hierarchical clustering requires a defined distance as well. | |
| 131. |
What is Machine learning? |
| A. | the autonomous acquisition of knowledge through the use of computer programs |
| B. | the autonomous acquisition of knowledge through the use of manual programs |
| C. | the selective acquisition of knowledge through the use of computer programs |
| D. | the selective acquisition of knowledge through the use of manual programs |
| Answer» A. the autonomous acquisition of knowledge through the use of computer programs | |
| Explanation: machine learning is the autonomous acquisition of knowledge through the use of computer programs. | |
| 132. |
Which of the factors affect the performance of learner system does not include? |
| A. | representation scheme used |
| B. | training scenario |
| C. | type of feedback |
| D. | good data structures |
| Answer» D. good data structures | |
| Explanation: factors that affect the performance of learner system does not include good data structures. | |
| 133. |
Different learning methods does not include? |
| A. | memorization |
| B. | analogy |
| C. | deduction |
| D. | introduction |
| Answer» D. introduction | |
| Explanation: different learning methods does not include the introduction. | |
| 134. |
In language understanding, the levels of knowledge that does not include? |
| A. | phonological |
| B. | syntactic |
| C. | empirical |
| D. | logical |
| Answer» C. empirical | |
| Explanation: in language understanding, the levels of knowledge that does not include empirical knowledge. | |
| 135. |
A model of language consists of the categories which does not include? |
| A. | language units |
| B. | role structure of units |
| C. | system constraints |
| D. | structural units |
| Answer» D. structural units | |
| Explanation: a model of language consists of the categories which does not include structural units. | |
| 136. |
What is a top-down parser? |
| A. | begins by hypothesizing a sentence (the symbol s) and successively predicting lower level constituents until individual preterminal symbols are written |
| B. | begins by hypothesizing a sentence (the symbol s) and successively predicting upper level constituents until individual preterminal symbols are written |
| C. | begins by hypothesizing lower level constituents and successively predicting a sentence (the symbol s) |
| D. | begins by hypothesizing upper level constituents and successively predicting a sentence (the symbol s) |
| Answer» A. begins by hypothesizing a sentence (the symbol s) and successively predicting lower level constituents until individual preterminal symbols are written | |
| Explanation: a top-down parser begins by hypothesizing a sentence (the symbol s) and successively predicting lower level constituents until individual preterminal symbols are written. | |
| 137. |
Among the following which is not a horn clause? |
| A. | p |
| B. | Øp v q |
| C. | p → q |
| D. | p → Øq |
| Answer» D. p → Øq | |
| Explanation: p → Øq is not a horn clause. | |
| 138. |
The action ‘STACK(A, B)’ of a robot arm specify to |
| A. | place block b on block a |
| B. | place blocks a, b on the table in that order |
| C. | place blocks b, a on the table in that order |
| D. | place block a on block b |
| Answer» D. place block a on block b | |
| Explanation: the action ‘stack(a,b)’ of a robot arm specify to place block a on block b. | |
| 139. |
A is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. |
| A. | decision tree |
| B. | graphs |
| C. | trees |
| D. | neural networks |
| Answer» A. decision tree | |
| Explanation: refer the definition of decision tree. | |
| 140. |
Choose from the following that are Decision Tree nodes? |
| A. | decision nodes |
| B. | end nodes |
| C. | chance nodes |
| D. | all of the mentioned |
| Answer» D. all of the mentioned | |
| Explanation: none. | |
| 141. |
Decision Nodes are represented by |
| A. | disks |
| B. | squares |
| C. | circles |
| D. | triangles |
| Answer» B. squares | |
| Explanation: none. | |
| 142. |
Chance Nodes are represented by |
| A. | disks |
| B. | squares |
| C. | circles |
| D. | triangles |
| Answer» C. circles | |
| Explanation: none. | |
| 143. |
End Nodes are represented by |
| A. | disks |
| B. | squares |
| C. | circles |
| D. | triangles |
| Answer» D. triangles | |
| Explanation: none. | |
| 144. |
Which of the following are the advantage/s of Decision Trees? |
| A. | possible scenarios can be added |
| B. | use a white box model, if given result is provided by a model |
| C. | worst, best and expected values can be determined for different scenarios |
| D. | all of the mentioned |
| Answer» D. all of the mentioned | |
| Explanation: none. | |
| 145. |
Which of the given statements is incorrect about global gene regulation? |
| A. | one way to obtain useful information about a genome is to determine which genes are induced or repressed in response to a phase of the cell cycle |
| B. | sets of a gene whose expression rises and falls under the same condition are likely to have a related function |
| C. | sets of a gene whose expression rises and falls under the same condition are likely to have dissimilar functions |
| D. | cell cycle is a developmental phase, or a response to the environment |
| Answer» C. sets of a gene whose expression rises and falls under the same condition are likely to have dissimilar functions | |
| Explanation: in addition, a pattern of gene expression may also be an indicator of | |
| 146. |
Which of the given statements is incorrect about Microarray (or microchip) analysis? |
| A. | it is a new technology in which all of the genes of an organism are represented by oligonucleotide sequences spread out in an 80 x 80 array on microscope slides |
| B. | the oligonucleotide sequences cannot be synthesized directly on the slide |
| C. | the oligonucleotides are collectively hybridized to a labeled cdna library prepared by reverse-transcribing mrna from cells |
| D. | the amount of label binding to each oligonucleotide spot reflects the amount of mrna in the cell |
| Answer» B. the oligonucleotide sequences cannot be synthesized directly on the slide | |
| Explanation: the oligonucleotide sequences can also be synthesized directly on the slide at densities of up to one million per square centimeter. genes that are responding the same way to an environmental signal, in this case the addition of serum to serum-starved skin cells are clustered together in a display. from this analysis, a set of genes that responds in an identical manner may be identified. | |
| 147. |
In cluster analysis of microarray data– A node is created between the scoring pair, and the gene expressed profiles of these two genes are averaged and the joined elements are weighted by the of elements they contain. |
| A. | lowest, frequency |
| B. | average, sequence |
| C. | lowest, number |
| D. | highest, number |
| Answer» D. highest, number | |
| Explanation: the node is created as mentioned. the matrix is then updated replacing the two joined elements by the node. | |
| 148. |
In cluster analysis of microarray data– For n genes, the process is repeated times until a single element remains. |
| A. | n2 |
| B. | n |
| C. | n-1 |
| D. | n-4 |
| Answer» C. n-1 | |
| Explanation: this number of iterations gives the best results. in the final dendrogram, the order of genes within a cluster is determined by simple weighting schemes, e.g., average | |
| 149. |
Which of the following is the task of project indicators: |
| A. | help in assessment of status of ongoing project |
| B. | track potential risk |
| C. | help in assessment of status of ongoing project & track potential risk |
| D. | none of the mentioned |
| Answer» C. help in assessment of status of ongoing project & track potential risk | |
| Explanation: none. | |
| 150. |
Which of the following is caused by careless handling? |
| A. | systematic error |
| B. | gross error |
| C. | random error |
| D. | none of the mentioned |
| Answer» B. gross error | |
| Explanation: gross errors are mostly due to lack of knowledge, judgment and care on the part of the experiment. that is gross error is caused by careless handling. | |
| 151. |
Which of the following is not a fundamental quantity? |
| A. | length |
| B. | angle |
| C. | time |
| D. | luminous intensity |
| Answer» B. angle | |
| Explanation: derived units are those expressed in terms of fundamental units. primary or | |
| 152. |
Which standard is fixed and used for industrial laboratories? |
| A. | international standard |
| B. | primary standard |
| C. | secondary standard |
| D. | working standard |
| Answer» C. secondary standard | |
| Explanation: secondary standards are fixed and used in industrial laboratories. working standards as its name suggests is used for day to day measurements. international standards are accepted internationally and primary standards are used in different parts of world which will not be accessible outside for calibration. | |
| 153. |
Which of the following error is caused by poor calibration of the instrument? |
| A. | random error |
| B. | gross error |
| C. | systematic error |
| D. | precision error |
| Answer» C. systematic error | |
| Explanation: systematic errors are caused by poor calibration of instruments. | |
| 154. |
How systematic errors are eliminated? |
| A. | frequent measurement |
| B. | replacement of instrument |
| C. | finding mean of reading |
| D. | finding variance of reading |
| Answer» B. replacement of instrument | |
| Explanation: the possible way of eliminating systematic error is the replacement of instruments. systematic errors are caused by poor instrument calibration. | |
| 155. |
Which of the following represents an SI unit of luminous intensity? |
| A. | lumen |
| B. | candela |
| C. | dioptre |
| D. | none of the mentioned |
| Answer» B. candela | |
| Explanation: si unit of luminous intensity is candela represented by cd. luminous intensity is a photometric quantity. | |
| 156. |
Starting position of an object is represented as x=5.1±0.2m and finishing position as y=6.9±0.3m. What will be the displacement and error in displacement? |
| A. | displacement = 1m, error = 0.5m |
| B. | displacement = 2m, error = 0.36m |
| C. | displacement = 1.8m, error = 0.36m |
| D. | displacement = 1.5m, error = 0.4m |
| Answer» C. displacement = 1.8m, error = 0.36m | |
| Explanation: displacement between two positions represented as x±Δx and y±Δy is iy-xi and error in displacement is (Δx2 +Δy2)1/2. | |
| 157. |
The maximum number of indexes on MyISAM table is |
| A. | 0 |
| B. | 1 |
| C. | 2 |
| D. | more than 1 |
| Answer» D. more than 1 | |
| Explanation: in mysql, for a myisam table, there can be more than one indexes. the data rows of the myisam table are stored in a data file and the index values are stored in a separate index file. | |
| 158. |
The data rows of a MyISAM table are stored in |
| A. | data file |
| B. | index file |
| C. | log file |
| D. | error file |
| Answer» A. data file | |
| Explanation: the data rows of the myisam table are stored in a data file and the index values are stored in a separate index file. in mysql, for a myisam table, there can be more than one indexes. | |
| 159. |
In a single table (with 10 columns) join query the number of values needed to examine per column is |
| A. | 1 |
| B. | 10 |
| C. | 0 |
| D. | 2 |
| Answer» B. 10 | |
| Explanation: for indexing in the context of performing joins, in a single table query, the number of values that are needed to be examined per column is the number of rows in the table. | |
| 160. |
FROM tbl_1 INNER JOIN tbl_2 WHERE tbl_1.i1 = tbl_2.i2; |
| A. | 14 |
| B. | 2 |
| C. | 1 |
| D. | 48 |
| Answer» D. 48 | |
| Explanation: in mysql, when the tables are unindexed, the searches are run through all the possible combinations. in this case, the search space is 8 x 6 = 48, the product of the number of rows. | |
| 161. |
MyISAM, InnoDB, TRANSACTION |
| A. | 0 |
| B. | 1 |
| C. | 2 |
| D. | 3 |
| Answer» B. 1 | |
| Explanation: in mysql, all the myisam tables shared tablespace files size if bound by the operating system file size limits. for innodb tables shared tablespaces, it is not bound by this factor. | |
| 162. |
If a column contains 7 values and 6 distinct values, the cardinality is |
| A. | 7 |
| B. | 6 |
| C. | 13 |
| D. | 1 |
| Answer» B. 6 | |
| Explanation: in mysql, the cardinality of a column is the number of distinct values that it contains. a column that contains the values 1, 2, 3, 4, 4, 5, 6 has a cardinality of six and not seven. | |
| 163. |
For a table having 4 columns, the number of columns to which hash function is applied when using hash indexes is |
| A. | 1 |
| B. | 2 |
| C. | 3 |
| D. | 4 |
| Answer» D. 4 | |
| Explanation: in mysql, for the hash indexes, a hash function is applied to each of the column values. the resulting hash values are stored in the index and used to perform lookups on it. | |
| 164. |
The slow query log is written as |
| A. | numbers |
| B. | text |
| C. | image |
| D. | graph |
| Answer» B. text | |
| Explanation: in mysql, the slow query log is written as text, so it is viewable with any file display program. the mysqldumpslow utility can also be used to summarize the contents of the same. | |
| 165. |
In ordered indices the file containing the records is sequentially ordered, a is an index whose search key also defines the sequential order of the file. |
| A. | clustered index |
| B. | structured index |
| C. | unstructured index |
| D. | nonclustered index |
| Answer» A. clustered index | |
| Explanation: clustering index are also called primary indices; the term primary index may appear to denote an index on a primary key, but | |
| 166. |
Indices whose search key specifies an order different from the sequential order of the file are called indices. |
| A. | nonclustered |
| B. | secondary |
| C. | all of the mentioned |
| D. | none of the mentioned |
| Answer» C. all of the mentioned | |
| Explanation: nonclustering index is also called secondary indices. | |
| 167. |
An consists of a search-key value and pointers to one or more records with that value as their search-key value. |
| A. | index entry |
| B. | index hash |
| C. | index cluster |
| D. | index map |
| Answer» A. index entry | |
| Explanation: the pointer to a record consists of the identifier of a disk block and an offset within the disk block to identify the record within the block. | |
| 168. |
In a clustering index, the index record contains the search-key value and a pointer to the first data record with that search- key value and the rest of the records will be in the sequential pointers. |
| A. | dense |
| B. | sparse |
| C. | straight |
| D. | continuous |
| Answer» A. dense | |
| Explanation: in a dense nonclustering index, the index must store a list of pointers to all records with the same search-key value. | |
| 169. |
Incase the indices values are larger, index is created for these values of the index. This is called |
| A. | pointed index |
| B. | sequential index |
| C. | multilevel index |
| D. | multiple index |
| Answer» C. multilevel index | |
| Explanation: indices with two or more levels are called multilevel indices. | |
| 170. |
A search key containing more than one attribute is referred to as a search key. |
| A. | simple |
| B. | composite |
| C. | compound |
| D. | secondary |
| Answer» B. composite | |
| Explanation: the structure of the index is the same as that of any other index, the only difference being that the search key is not a single attribute, but rather is a list of attributes. | |
| 171. |
In B+ tree the node which points to another node is called |
| A. | leaf node |
| B. | external node |
| C. | final node |
| D. | internal node |
| Answer» D. internal node | |
| Explanation: nonleaf nodes are also referred to as internal nodes. | |
| 172. |
appears for only some of the search-key values. |
| A. | dense |
| B. | sparse |
| C. | straight |
| D. | continuous |
| Answer» A. dense | |
| Explanation: sparse indices can be used only if | |
| 173. |
return index; |
| A. | o(nlogn) |
| B. | o(logn) |
| C. | o(n) |
| D. | o(1) |
| Answer» C. o(n) | |
| Explanation: worst case is when the desired | |
| 174. |
OLAP stands for |
| A. | online analytical processing |
| B. | online analysis processing |
| C. | online transaction processing |
| D. | online aggregate processing |
| Answer» A. online analytical processing | |
| Explanation: olap is the manipulation of information to support decision making. | |
| 175. |
data. |
| A. | multidimensional |
| B. | singledimensional |
| C. | measured |
| D. | dimensional |
| Answer» A. multidimensional | |
| Explanation: given a relation used for data analysis, we can identify some of its attributes | |
| 176. |
The generalization of cross-tab which is represented visually is which is also called as data cube. |
| A. | two dimensional cube |
| B. | multidimensional cube |
| C. | n-dimensional cube |
| D. | cuboid |
| Answer» A. two dimensional cube | |
| Explanation: each cell in the cube is identified for the values for the three dimensional attributes. | |
| 177. |
The process of viewing the cross-tab (Single dimensional) with a fixed value of one attribute is |
| A. | slicing |
| B. | dicing |
| C. | pivoting |
| D. | both slicing and dicing |
| Answer» A. slicing | |
| Explanation: the slice operation selects one particular dimension from a given cube and provides a new sub-cube. dice selects two or more dimensions from a given cube and provides a new sub-cube. | |
| 178. |
The operation of moving from finer- granularity data to a coarser granularity (by means of aggregation) is called a |
| A. | rollup |
| B. | drill down |
| C. | dicing |
| D. | pivoting |
| Answer» A. rollup | |
| Explanation: the opposite operation—that of moving fromcoarser-granularity data to finer- granularity data—is called a drill down. | |
| 179. |
In SQL the cross-tabs are created using |
| A. | slice |
| B. | dice |
| C. | pivot |
| D. | all of the mentioned |
| Answer» A. slice | |
| Explanation: pivot (sum(quantity) for color in (’dark’,’pastel’,’white’)). | |
| 180. |
This can be achieved by using which of the following ? |
| A. | group by rollup |
| B. | group by cubic |
| C. | group by |
| D. | none of the mentioned |
| Answer» D. none of the mentioned | |
| Explanation: ‘group by cube’ is used . | |
| 181. |
What do data warehouses support? |
| A. | olap |
| B. | oltp |
| C. | olap and oltp |
| D. | operational databases |
| Answer» A. olap | |
| Explanation: none. 9. | |
| 182. |
How many grouping is possible in this rollup? |
| A. | 8 |
| B. | 4 |
| C. | 2 |
| D. | 1 |
| Answer» B. 4 | |
| Explanation: { (item name, color, clothes size), (item name, color), (item name), () }. | |
| 183. |
Which one of the following is the right syntax for DECODE? |
| A. | decode (search, expression, result [, search, result]… [, default]) |
| B. | decode (expression, result [, search, result]… [, default], search) |
| C. | decode (search, result [, search, result]… [, default], expression) |
| D. | decode (expression, search, result [, search, result]… [, default]) |
| Answer» D. decode (expression, search, result [, search, result]… [, default]) | |
| Explanation: none. | |
| 184. |
A piece of icon or image on a web page associated with another webpage is called |
| A. | url |
| B. | hyperlink |
| C. | plugin |
| D. | extension |
| Answer» B. hyperlink | |
| Explanation: urls are locators for resources present on the world wide web. a plugin provides extra functionality to the webpage. an extension provides modification allowance for the core functionality of a webpage. hyperlink is piece of icon or image on a web page associated with another webpage. | |
| 185. |
Dynamic web page |
| A. | is same every time whenever it displays |
| B. | generates on demand by a program or a request from browser |
| C. | both is same every time whenever it displays and generates on demand by a program or a request from browser |
| D. | is different always in a predefined order |
| Answer» B. generates on demand by a program or a request from browser | |
| Explanation: a dynamic web page provides different content every time the user opens it based on some events like new additions or time of the day. languages such as javascript are used to respond to client-side events while languages such as php as used to respond to server-side events. | |
| 186. |
What is a web browser? |
| A. | a program that can display a web page |
| B. | a program used to view html documents |
| C. | it enables user to access the resources of internet |
| D. | all of the mentioned |
| Answer» D. all of the mentioned | |
| Explanation: a web browser is an application program that is used to access the world wide web resources, applications and websites. some examples of web browsers are google chrome, internet explorer and safari. | |
| 187. |
Common gateway interface is used to |
| A. | generate executable files from web content by web server |
| B. | generate web pages |
| C. | stream videos |
| D. | download media files |
| Answer» A. generate executable files from web content by web server | |
| Explanation: cgi is an interface through servers can run execute console-based executable files on a web server that generates dynamic web pages. a cgi script executes only when a request is made. the script then generates html. | |
| 188. |
URL stands for |
| A. | unique reference label |
| B. | uniform reference label |
| C. | uniform resource locator |
| D. | unique resource locator |
| Answer» C. uniform resource locator | |
| Explanation: the uniform resource locator is a locator for the resource to be located by http on the world wide web. the url is derived from the uniform resource identifier. | |
| 189. |
A web cookie is a small piece of data that is |
| A. | sent from a website and stored in user’s web browser while a user is browsing a website |
| B. | sent from user and stored in the server while a user is browsing a website |
| C. | sent from root server to all servers |
| D. | sent from the root server to other root servers |
| Answer» A. sent from a website and stored in user’s web browser while a user is browsing a website | |
| Explanation: a web cookie is a small piece of data sent from a website and stored in user’s web browser while a user is browsing the website and is used to remember stateful information about the user’s operations on the website. this can help the website provide a better browsing experience to the user. | |
| 190. |
Which one of the following is not used to generate dynamic web pages? |
| A. | php |
| B. | asp.net |
| C. | jsp |
| D. | css |
| Answer» D. css | |
| Explanation: css alone cannot be used to generate dynamic web pages as it does not provide many event handling functions. it can be used along with javascript to generate dynamic web pages which are visually compelling. | |
| 191. |
An alternative to JavaScript on windows platform is |
| A. | vbscript |
| B. | asp.net |
| C. | jsp |
| D. | php |
| Answer» A. vbscript | |
| Explanation: vbscript is a general-purpose, | |
| 192. |
The set of loosely connected computers are called as |
| A. | lan |
| B. | wan |
| C. | workstation |
| D. | cluster |
| Answer» D. cluster | |
| Explanation: in a computer cluster all the participating computers work together on a particular task. | |
| 193. |
What is document object model (DOM)? |
| A. | convention for representing and interacting with objects in html documents |
| B. | application programming interface |
| C. | hierarchy of objects in asp.net |
| D. | scripting language |
| Answer» A. convention for representing and interacting with objects in html documents | |
| Explanation: dom is a hierarchical model i.e. a tree used to represent an html or xml document. every node of the tree an object that represents a part of the document. | |
| 194. |
AJAX stands for |
| A. | asynchronous javascript and xml |
| B. | advanced jsp and xml |
| C. | asynchronous jsp and xml |
| D. | advanced javascript and xml |
| Answer» A. asynchronous javascript and xml | |
| Explanation: ajax is a group of technologies that works on the client-side to create asynchronous web applications. it is used to modify only a part of a webpage and not the whole webpage whenever some event occurs. | |
| 195. |
TOPIC 4.2 SEARCH ENGINE ARCHITECTURES |
| A. | utp |
| B. | rj-45 |
| C. | stp |
| D. | coaxial cable |
| Answer» B. rj-45 | |
| Explanation: the computers are connected to each other using a lan connector cable. | |
| 196. |
The computer cluster architecture emerged as a result of |
| A. | isa |
| B. | workstation |
| C. | super computers |
| D. | distributed systems |
| Answer» D. distributed systems | |
| Explanation: a distributed system is a computer system spread out over a geographic area. | |
| 197. |
The software which governs the group of computers is |
| A. | driver rd45 |
| B. | interface ui |
| C. | clustering middleware |
| D. | distributor |
| Answer» C. clustering middleware | |
| Explanation: the software helps to project a single system image to the user. | |
| 198. |
approach. |
| A. | beowolf |
| B. | sequoia |
| C. | stone |
| D. | none of the mentioned |
| Answer» A. beowolf | |
| Explanation: none. | |
| 199. |
The cluster formation in which the work is divided equally among the systems is |
| A. | load-configuration |
| B. | load-division |
| C. | light head |
| D. | both load-configuration and load-division |
| Answer» A. load-configuration | |
| Explanation: this approach the work gets divided among the systems equally. | |
| 200. |
approach is used. |
| A. | load configuration |
| B. | fifo |
| C. | bankers algorithm |
| D. | round robin |
| Answer» D. round robin | |
| Explanation: by using this approach the performance of the cluster can be enhanced. | |
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