MCQ Bank

Subjects
All Subjects 56097 ACC311
Fundamentals of Auditing
F:210
210 ACC31Q
F:97
97 ACC501
Business Finance
F:248
248 ACC707
F:33
33 BIF101
Introduction to Bioinformatics
F:37
37 BIF401
Bioinformatics I
F:27
27 BIF401P
Bioinformatics I (Practical)
F:53
53 BIF501
Bioinformatics II
F:63
63 BIF501P
Bioinformatics II (Practical)
F:49
49 BIF601
Bioinformatics Computing I
F:25
25 BIF601P
Bioinformatics Computing I (Practical)
F:35
35 BIF602
Bioinformatics Computing II
F:3
3 BIF604
Special Topics in Bioinformatics
F:67
67 BIO101
Basic I-Biology
F:17
17 BIO102
Basic II-Chemistry
F:38
38 BIO201
M:30
30 BIO203
M:42
42 BIO303
M:29
29 BIO401
Biostatistics
F:24
24 BIO502
Genomics
F:20
20 BIO503
Biological Physics
M:30 F:48
78 BIO504P
Biochemistry I (Practical)
F:23
23 BIO504T
Biochemistry I (Theory)
F:12
12 BIO505P
Essentials of Genetics (Practical)
F:71
71 BIO505T
Essentials of Genetics (Theory)
F:11
11 BIO506P
Biochemistry II (Practical)
F:35
35 BIO506T
Biochemistry II (Theory)
F:16
16 BIO5101
Introduction to Biotechnology
F:25
25 BIO5105
Cell Biology
F:18
18 BIO601
Proteomics
F:20
20 BIO732
Gene Manipulation and Genetic Engineering
F:49
49 BNK601
Banking Laws & Practices
F:129
129 BNK603
Consumer Banking
F:115
115 BNK610
Islamic Banking Practices
F:69
69 BNK611
Economic Ideology in Islam
F:102
102 BNK612
Financial Jurisprudence in Islam
F:29
29 BNK613
Islamic Ethics in Business
F:23
23 BT101
Ecology, Biodiversity & Evolution-I
F:80
80 BT102
M:31 F:53
84 BT201
F:246
246 BT301
F:30
30 BT302
Immunology
M:55 F:35
90 BT401
Genetic Resources & Conservation
F:163
163 BT402
F:37
37 BT403
F:43
43 BT404
M:9
9 BT405
Nano Biotechnology
F:41
41 BT406
Research Methodology & Skill Enhancement
F:106
106 BT501
Health Biotechnology
F:141
141 BT503
Environment Biotechnology
F:74
74 BT504
Genomics and Proteomics
F:67
67 BT505
Biosensors
F:68
68 BT511P
Introduction to Biotechnology (Practical)
F:25
25 BT511T
F:27
27 BT512P
Microbial Biotechnology (Practical)
F:74
74 BT512T
Microbial Biotechnology (Theory)
F:170
170 BT513P
Principles of Biochemical Engineering (Practical)
F:71
71 BT513T
Principles of Biochemical Engineering (Theory)
F:37
37 BT601
Virology
F:69
69 BT603
F:21
21 BT604
F:19
19 BT605
Biosafety & Bioethics
F:58
58 BT611P
Food Biotechnology (Practical)
F:52
52 BT611T
Food Biotechnology (Theory)
F:55
55 BT612P
Fermentation Technology (Practical)
F:31
31 BT612T
Fermentation Technology (Theory)
F:12
12 BT613T
Agriculture Biotechnology (Theory)
F:28
28 BT614P
Industrial Biotechnology (Practical)
F:28
28 BT614T
Industrial Biotechnology (Theory)
F:37
37 CHE201
Physical Chemistry
F:77
77 CHE301
M:28
28 CS001
F:58
58 CS101
Introduction to Computing
F:751
751 CS201
Introduction to Programming
M:97 F:247
344 CS201P
Introduction to Programming (Practical)
F:200
200 CS202
F:192
192 CS204
F:77
77 CS205
Information Security
F:87
87 CS206
F:57
57 CS301
Data Structures
F:141
141 CS301P
Data Structures (Practical)
F:63
63 CS302
Digital Logic Design
F:192
192 CS302P
F:64
64 CS304
Object Oriented Programming
F:89
89 CS304P
Object Oriented Programming (Practical)
F:147
147 CS306
Introduction to Python
F:75
75 CS306P
Introduction to Python (Practical)
F:88
88 CS311
Introduction to Web Services Development
F:132
132 CS312
F:47
47 CS314
Introduction to Cellular Networks
F:84
84 CS315
F:57
57 CS401
F:117
117 CS401P
F:94
94 CS402
M:67 F:140
207 CS403
Database Management Systems
F:162
162 CS403P
Database Management Systems (Practical)
F:120
120 CS405
Database Programming using Oracle 11g
F:70
70 CS406
F:28
28 CS407
Routing and Switching
F:70
70 CS408
Human Computer Interaction
M:94 F:76
170 CS409
Introduction to Database Administration
F:43
43 CS409P
F:59
59 CS411
Visual Programming
F:100
100 CS420
Web Development for Portable Devices
F:106
106 CS431
Wireless Communication
F:43
43 CS432
F:80
80 CS435
Cloud Computing
F:46
46 CS441
F:73
73 CS442
Introduction to Data Science
F:29
29 CS501
F:120
120 CS502
Fundamentals of Algorithms
F:156
156 CS504
Software Engineering - I
F:179
179 CS505
F:49
49 CS505P
F:96
96 CS506
Web Design and Development
F:196
196 CS507
Information Systems
M:87 F:165
252 CS508
F:227
227 CS510
F:63
63 CS513
Advanced Data Analytics and Business Intelligence
F:128
128 CS514
F:23
23 CS521
F:26
26 CS525
F:25
25 CS601
Data Communication
F:137
137 CS602
Computer Graphics
F:105
105 CS603
F:62
62 CS603P
F:54
54 CS604
F:177
177 CS604P
F:86
86 CS605
F:82
82 CS606
F:194
194 CS607
Artificial Intelligence
F:134
134 CS607P
Artificial Intelligence (Practical)
F:108
108 CS608
F:75
75 CS609
F:89
89 CS610
Computer Networks
F:126
126 CS610P
F:100
100 CS611
F:78
78 CS614
Data Warehousing
F:126
126 CS615
F:121
121 CS620
Modelling and Simulation
F:62
62 CS621
F:38
38 CS625
Professional Practices
M:30 F:27
57 CS626
F:30
30 CS627
F:39
39 CS628
F:30
30 CS636
F:40
40 ECE101
Introduction to Early Childhood Education
F:69
69 ECE201
Language Development of the Child
F:47
47 ECE202
Physical Development of the Child
F:29
29 ECE203
Children Literature and Educational Games
F:56
56 ECE204
Independence, Self-Management and Ethics in Early Years
F:24
24 ECE301
Psycho Social Development of the Child
F:19
19 ECE302
Education for Sustainable Development in Early Childhood Education
F:21
21 ECE402
Trends and Issues in Early Childhood Education
F:48
48 ECO302
Principles of Microeconomics
F:36
36 ECO303
Principles of Macroeconomics
F:20
20 ECO401
Economics
F:383
383 ECO402
Microeconomics
F:99
99 ECO403
Macroeconomics
F:137
137 ECO404
Managerial Economics
F:129
129 ECO501
Development Economics
F:32
32 ECO601
Business Econometrics
F:40
40 ECO603
International Economics
F:53
53 ECO604
F:64
64 ECO605
F:30
30 ECO606
Mathematical Economics I
F:108
108 ECO607
F:182
182 ECO608
F:57
57 ECO609
F:48
48 ECO610
F:74
74 ECO612
F:21
21 ECO613
F:50
50 ECO614
F:47
47 ECO615
F:55
55 ECO616
F:68
68 ECO622
F:29
29 EDU101
Foundations of Education
M:155 F:72
227 EDU201
Learning Theories
F:95
95 EDU301
General Methods of Teaching
F:20
20 EDU302
Human Development and Learning
F:57
57 EDU303
Child Development
F:113
113 EDU304
Introduction to Guidance and Counseling
F:33
33 EDU305
Classroom Management
M:120 F:88
208 EDU306
Teaching of Social Studies and Islamiat in Early Years of Education
F:48
48 EDU401
Contemporary Issues and Trends in Education
M:122 F:117
239 EDU402
Curriculum Development
F:46
46 EDU403
Art, Crafts and Calligraphy
F:37
37 EDU405
Classroom Assessment
F:87
87 EDU406
Critical Thinking and reflective Practice
M:45 F:75
120 EDU407
Research Methods in Education
F:24
24 EDU410
Teaching of Literacy Skills
M:37 F:65
102 EDU411
Teaching of Urdu
F:312
312 EDU430
ICT in Education
M:276 F:147
423 EDU431
Test Development & Evaluation
M:33 F:62
95 EDU433
Professionalism in Teaching
M:84 F:66
150 EDU501
School, Community and Teacher
M:135 F:42
177 EDU505
M:29 F:41
70 EDU510
Teaching of Mathematics
F:15
15 EDU512
Teaching of Islamic Studies
F:86
86 EDU515
Teaching of Geography
F:12
12 EDU516
Teaching of English
M:31 F:54
85 EDU601
Philosophy of Education
F:129
129 EDU602
Educational Leadership and Management
F:52
52 EDU604
Comparative Education
F:103
103 EDU654
Addressing problems of learning through technology and pedagogy
M:98 F:25
123 EDU705
F:26
26 EDUA305
Classroom Management for Young Learners
F:52
52 EDUA402
Curriculum Development for Early Childhood Education
F:10
10 EDUA403
Teaching of Arts, Crafts & Calligraphy
F:49
49 EDUA405
Assessment and Evaluation in Early Years of Education
F:16
16 EDUA406
Reflective Practices and Critical Thinking in Early Years
F:47
47 EDUA411
Teaching of Urdu in Early Childhood
F:55
55 EDUA430
Use of Information and Communication Technology for Early Childhood Education
F:77
77 EDUA501
Role of School, Community & Teacher in Early Years of Education
F:32
32 EDUA510
Teaching of Mathematics in Early Childhood
F:11
11 EDUA516
Teaching of English in Early Childhood
F:51
51 EDUA601
Philosophical Foundations of Early Childhood Education
F:20
20 EDUA602
Leadership and Management of Early Childhood Education Programs
F:22
22 ENG001
F:417
417 ENG101
English Comprehension
F:344
344 ENG201
Business and Technical English Writing
M:47 F:289
336 ENG301
Business Communication
M:53 F:340
393 ENG401
F:63
63 ENG501
History of English Language
M:53 F:73
126 ENG502
Introduction to Linguistics
M:61 F:55
116 ENG503
Introduction to English Language Teaching
M:396 F:31
427 ENG504
Second Language Acquisition
F:44
44 ENG505
F:68
68 ENG506
World Englishes
F:60
60 ENG507
Phonetics and Phonology
F:64
64 ENG508
Semantics and Pragmatics
F:61
61 ENG509
Morphology and Syntax
M:17 F:50
67 ENG510
Sociolinguistics
F:41
41 ENG511
F:102
102 ENG512
F:44
44 ENG513
F:35
35 ENG514
F:57
57 ENG515
F:37
37 ENG516
F:50
50 ENG517
M:141 F:38
179 ENG518
M:17 F:65
82 ENG519
M:247 F:64
311 ENG520
M:116 F:112
228 ENG522
Applied Linguistics
M:38 F:92
130 ENG523
M:44 F:76
120 ENG524
M:20 F:48
68 ENG527
F:78
78 ENG529
M:15 F:34
49 ETH100
Effective Citizenship
F:145
145 ETH201
F:20
20 ETH202
Ethics (for Non-Muslims)
F:54
54 FIN611
Advanced Financial Accounting
F:113
113 FIN621
Financial Statement Analysis
F:168
168 FIN622
Corporate Finance
F:162
162 FIN623
Taxation Management
F:203
203 FIN624
Islamic Modes of Finance
F:99
99 FIN625
Credit & Risk Management
F:96
96 FIN630
F:217
217 FIN702
F:56
56 FIN703
F:104
104 FIN711
F:73
73 GSC101
General Science
F:423
423 GSC201
Teaching of General Science
F:47
47 GSCA201
Teaching of General Science in Early Years of Education
F:28
28 HRM613
Performance Management
F:59
59 HRM617
Training and Development
F:70
70 HRM624
Conflict Management
F:220
220 HRM626
Recruitment and selection
F:56
56 HRM627
Human Resource Development
F:300
300 HRM733
F:19
19 HRM737
F:20
20 ISL1151
F:126
126 ISL1252
F:87
87 ISL1253
F:73
73 ISL201
F:39
39 ISL202
Islamic Studies
F:903
903 ISL2351
F:24
24 ISL2352
F:84
84 ISL2453
F:26
26 ISL2454
F:52
52 IT430
E-Commerce
F:280
280 IT601
F:31
31 IT602
F:33
33 MB501P
Cell Biology (Practical)
F:48
48 MB502P
Molecular Biology (Practical)
F:111
111 MB502T
Molecular Biology (Theory)
M:119 F:67
186 MB503T
F:35
35 MB504P
Methods in Molecular Biology (Practical)
F:46
46 MB504T
Methods in Molecular Biology (Theory)
F:53
53 MCD401
F:10
10 MCD403
F:20
20 MCD504
Acting and Performance
F:80
80 MCM101
Introduction to Mass Communication
F:98
98 MCM301
Communication skills
F:66
66 MCM304
Mass Media in Pakistan
F:52
52 MCM310
Journalistic Writing
F:114
114 MCM311
Reporting and Sub-Editing
F:96
96 MCM401
Fundamentals of Public Relations
F:108
108 MCM411
Introduction to Broadcasting
F:76
76 MCM431
F:118
118 MCM501
Advertising for Print and Electronic Media
F:105
105 MCM511
Theories of Communication
F:44
44 MCM514
F:21
21 MCM515
F:21
21 MCM516
F:55
55 MCM517
F:68
68 MCM520
F:67
67 MCM532
F:42
42 MCM601
Media Management
F:99
99 MCM604
F:115
115 MCM610
Mass Communication Law & Ethics
F:85
85 MGMT611
Human Relations (alt. code=HRM611)
F:205
205 MGMT614
Supply Chain Management
F:43
43 MGMT615
Transportation & Logistics Management
F:42
42 MGMT617
Production Planning and Inventory Control
F:44
44 MGMT622
Management Skills
F:149
149 MGMT623
Leadership & Team Management - MGMT623 (alt. code=HRM623)
M:87 F:160
247 MGMT625
F:126
126 MGMT627
Project Management
F:130
130 MGMT628
F:234
234 MGMT629
F:99
99 MGMT630
F:112
112 MGMT631
Enterprise Resource Planning
F:43
43 MGT101
Financial Accounting
F:330
330 MGT111
Introduction to Public Administration
F:197
197 MGT201
Financial Management
F:110
110 MGT211
Introduction To Business
F:175
175 MGT301
Principles of Marketing
F:215
215 MGT302
Digital Marketing
F:39
39 MGT401
Financial Accounting II
F:30
30 MGT402
Cost & Management Accounting
F:107
107 MGT404
F:135
135 MGT411
Money & Banking
F:194
194 MGT415
Introduction to Business Analytics
F:86
86 MGT501
Human Resource Management
F:396
396 MGT502
Organizational Behaviour
M:167 F:555
722 MGT503
Principles of Management
F:325
325 MGT504
F:214
214 MGT510
Total Quality Management (alt. code=MGMT510)
M:100 F:561
661 MGT513
Public Administration in Pakistan
F:80
80 MGT520
International Business
F:231
231 MGT522
Introduction to Public Policy
F:116
116 MGT601
F:121
121 MGT602
Entrepreneurship
F:270
270 MGT603
Strategic Management
F:330
330 MGT604
Management of Financial Institutions (alt. code=BNK604)
F:123
123 MGT605
F:66
66 MGT610
M:20 F:231
251 MGT611
Business & Labor Law
F:122
122 MGT612
F:77
77 MGT613
Production / Operations Management
F:220
220 MGT621
F:114
114 MGT701
F:52
52 MGT703
F:46
46 MGT713
F:44
44 MGT714
F:71
71 MGT717
F:42
42 MGT723
F:20
20 MGT725
F:67
67 MGTE630
Knowledge Management
M:34 F:19
53 MIC501P
Microbiology (Practical)
F:71
71 MIC501T
Microbiology (Theory)
F:40
40 MKT501
Marketing Management
F:250
250 MKT529
Export Marketing
F:53
53 MKT530
Consumer Behaviour
F:71
71 MKT610
Customer Relationship Management
F:83
83 MKT621
Advertising & Promotion
F:94
94 MKT624
Brand Management
F:114
114 MKT627
Sales Management
F:61
61 MKT630
International Marketing
F:127
127 MKT703
F:37
37 MKT726
F:20
20 MTH001
F:276
276 MTH100
General Mathematics
F:216
216 MTH101
Calculus And Analytical Geometry
F:1292
1292 MTH102
F:32
32 MTH104
Sets and Logic
F:64
64 MTH201
F:68
68 MTH202
Discrete Mathematics
F:238
238 MTH301
F:406
406 MTH302
Business Mathematics & Statistics
F:778
778 MTH303
Mathematical Methods
F:160
160 MTH304
F:35
35 MTH401
F:226
226 MTH403
F:147
147 MTH404
F:41
41 MTH405
F:132
132 MTH501
Linear Algebra
F:366
366 MTH5101
Calculus I
F:27
27 MTH5102
Calculus II
F:12
12 MTH601
F:266
266 MTH603
F:160
160 MTH621
F:105
105 MTH622
F:62
62 MTH631
F:167
167 MTH632
F:97
97 MTH633
F:54
54 MTH634
F:67
67 MTH641
F:179
179 MTH642
F:76
76 MTH643
F:22
22 MTH644
F:101
101 MTH645
F:63
63 MTH646
F:91
91 MTH647
F:53
53 PAD603
F:60
60 PAK301
Pakistan Studies
M:10 F:155
165 PAK302
Pakistan Studies
F:131
131 PAK522
Ideology and Constitution of Pakistan
F:51
51 PHY101
Physics
F:626
626 PHY301
F:95
95 PSC201
International Relations
F:85
85 PSC401
F:48
48 PSY101
Introduction to Psychology
F:409
409 PSY401
F:166
166 PSY402
F:43
43 PSY403
Social Psychology
F:262
262 PSY404
Abnormal Psychology
F:137
137 PSY405
Personality Psychology
F:174
174 PSY406
Educational Psychology
M:182 F:244
426 PSY407
F:175
175 PSY408
F:207
207 PSY409
F:143
143 PSY502
History & Systems of Psychology
F:264
264 PSY504
Cognitive Psychology
F:126
126 PSY505
Developmental Psychology
F:108
108 PSY510
F:179
179 PSY511
Environmental Psychology
F:69
69 PSY512
Gender Issues in Psychology
F:192
192 PSY513
F:175
175 PSY514
F:104
104 PSY515
Cross Cultural Psychology
F:140
140 PSY516
F:88
88 PSY610
F:81
81 PSY611
Ethical Issues in Psychology
F:132
132 PSY631
F:116
116 PSY632
F:180
180 PSYP402
F:90
90 PSYP610
F:171
171 PSYP631
F:185
185 SE601
F:21
21 SE601P
F:61
61 SE602
F:36
36 SOC101
Introduction to Sociology
M:121 F:1279
1400 SOC201
Social Statistics
F:191
191 SOC301
Introduction to Social Work
F:63
63 SOC302
Sociological Theories
F:94
94 SOC401
Cultural Anthropology
M:137 F:143
280 SOC402
F:59
59 SOC403
Gender Studies
F:80
80 SOC404
Pakistani Society and Culture
F:109
109 SOC509
F:89
89 SOC601
F:45
45 SOC602
Sociology of Education
F:50
50 SOC603
Sociology of Development
F:50
50 SOC604
Community Development
F:61
61 SOC605
Population Dynamics
F:51
51 SOC606
F:45
45 SOC607
F:90
90 SOC608
F:57
57 SOC609
F:82
82 SOC610
Electronic Media & Virtual Community
F:86
86 SOC611
F:58
58 SOC612
F:60
60 SOC613
F:70
70 SOC614
F:46
46 SOC615
F:65
65 SOC616
F:40
40 SOC617
F:59
59 STA301
Statistics and Probability
F:402
402 STA302
Data Analytics and Business Intelligence
F:34
34 STA621
F:64
64 STA630
Research Methods
M:76 F:298
374 STA631
Inferential Statistics
F:29
29 STA641
Statistical Packages and its Applications
F:87
87 STA642
Probability Distributions
F:59
59 STAT404
F:29
29 URD100
Urdu Language
F:42
42 URD101
Urdu
F:158
158 ZOO102
F:9
9 ZOO103
F:10
10 ZOO403
F:50
50 ZOO501
F:23
23 ZOO501P
F:44
44 ZOO501T
Developmental Biology (Theory)
F:115
115 ZOO502
F:9
9 ZOO503
F:153
153 ZOO504
F:139
139 ZOO505
F:27
27 ZOO507
F:21
21 ZOO510
Economic Zoology
F:136
136 ZOO511P
F:56
56 ZOO511T
F:27
27 ZOO512P
Animal Diversity: Invertebrates
F:25
25 ZOO512T
Animal Diversity: Invertebrates (Theory)
F:248
248 ZOO513P
Animal Diversity: Chordates (Practical)
F:34
34 ZOO513T
Animal Diversity: Chordates (Theory)
F:10
10 ZOO516P
F:36
36 ZOO516T
Animal Form & Function-I (Theory)
F:42
42 ZOO517P
F:29
29 ZOO517T
F:74
74 ZOO518P
F:71
71 ZOO518T
F:20
20 ZOO519P
F:55
55 ZOO519T
Physiology (Theory)
F:17
17 ZOO603T
Fish Biology (Theory)
F:13
13
Koi subject nahi mila
Clear
56097 result(s)
MTH646 Final Term Unsolved
Q27

The Crank–Nicolson scheme is preferred over Forward Time Central Space (FTCS) scheme for time-dependent PDEs because:

  • A) It only works for nonlinear PDEs
  • B) It is explicit and easier to implement
  • C) It is second-order accurate in both time and space and unconditionally stable
  • D) It does not require a grid
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q28

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ReK/crEPAIuTYwxl0OyLKXJ+4UhLCinDsEkemmi9yiljFNdop8S+1/lmEfA54Ux5nJKaaJ/+Np/ehI6ZFZ/sxOU0kTfhZWfnkRdwgV3/ZMd8wi4NDHGXI4+5esHENQc79b+k680Apn153//h89Gv8LRvxNWcEp89FMe/qqRu3ojRZD9BZm5Y1yaGGMuh5RJmqTyIIOSOFffiKhkQQFN1yWFr1+/Rv3BdY6P/mUTUY2fvupf9BBMv3ky941LE2OMMcZMhEsTY4wxxkyESxNjjDHGTIRLE2OMMcZMhEsTY4wxxkyESxNjjDHGTIRLE2OMMcZMhEsTY4wxxkyESxNjjDHGTIRLE2OMMcZMhEsTY4wxxkyESxNjjDHGTIRLE2OMMcZMhEsTY4wxxkyESxNjjDHGTIRLE2OMMcZMhEsTY4wxxkyESxNjjDHGTIRLE2OMMcZMhEsTY4wxxkzELKXJx48f/1n48ePHaPprZBD+/Pkzmq7H79+/P3/+/O7dOw0xWk9zi/lu8f379w8fPmi4r1+/jtYjmF3pwpTVAmq5M37+/KnZEa7RdILD8P7lVjFmQtj22s8cZaNp7dDovOTRdwveuv/A6mgKX758GU3zMdFBqfN9p4xQavz06dOQj8AU+s9KMyf59esXmYbnkOtv3769f/9e7c/icL5XQUkRhxkIPzlQxo0TsHHxMD+BtwtpBj/xeQgvC5NlglrZQKcwCz3kxGF4r7JVzIvBSrHWrNqQX4MZfOh0r/SwlPTWD43Oyxx9t0P+k4+G/AbRMj0rHbwwE5UmVKP7OW8nQ2yB/i0KQ1wl35x8tHikV+d1ON+/R68Bzr8pKWj75mmqNLlFSIPnFqDXRREre2wrVZwJ77O2inl1XrIsZqzVR+kVS/MdulcqTUoV0g+NzgscfTdFD/UQNtha3EnQi5OZq6uJShMidd21VObYr98v4Lm5k01MbhtC4urz7fzlxy+eQB6wISwopDPX2n+Jyt+TETsM7+uWWWZm2DZv/VFaTW/90OhwJM6ctg9hgvsP9fyLe6a6el1mKU20ltctI/jsi83rfmDFmhLSmZc3odw/WN9ivgXKCDbf3+w/PCxPoA6jnWT81tF6DWGXw/A+a6uYh4J0ri8F2EWj6Q2ymt76oVF4gaPvpujzxs670jexuCzc5B+Zrl+a6HMn5BO51NfsaelES5QRbFlqUq7R0S3Qh/XSKLhFiHWXcOdinHa9NmR0bqGws58E/pBOpIwbRT/cCHZeS3ZliDp6f75Bnh0KEa5DIsJBPwuycSZSFOR/SauY7YfRVtAu2Am6Bt0FrR3IPUwpXFufuhhU5wJd6ItjZRELmA19lLnOCyFvoRg5DO/JrbK6vpzdsi9PEENn6TQoYccUjVEP0YICIoH6N3zv3vXPcNkC5InDqm9bZCdRZizM6haR0ZIphphVwFHDPelwa/Fxc5VPxiT7zCh5UcICCmphdLVITdegSMKW5/ylLyi2tJTHBHYCEpsqo/B2HwRj0UvOYIdVo0W3zoQ3c8FTueUVLRFMgQKNPRoZ7qKDb+F5d7XMd8sgOop/Xmh8poUQDXkhrAEX5e7+cNyNx4TYsuhclFAEimQhPzt03NqiGQ2KDl7RHTE2mx7kWGj+ZvsiT4drTPF33Fs2J7dimpoRxOMmsqusUR/lply/NAFNNcdCmzuWk0AjEjuJQOwIcUSwLz9LWGyCHjN6YVA2c3C1BRlay6+F1K1VWDAWksXQGjAW+toHGc1lCEdoaYeQOJwvRBiZGre4Rn/cO4G6lIgFCp2Mg/zMm08nSHGJ+DD9ISzsB+25O0FiDIEPoEaMMH1E2uUtQ0stQIF26eCPHs6+gkHZP/KtRGx1aWA/vGJ/q6yur9zAed1ljmpEjLAAnkfYucu1YogypvSw8JcuiChwFx31FVq4ONe4AN2CVd/GvUYxRS/05U/4z12cwW2J8lA2l0VeWWX5QBdunYyJLHALypZWrOQbFmihL9eAsnRwElHXW57jGzoaOmIbvcROQAIUsvNB9kHIB2A4xLwc+04qjJ1Y3CGfOJ+xT8sQFhi6GAGNG3ZWwUOs4arc665imaFjvvIt1jGgC8jVHEltg2xQ8Zc17GA5T21/OMWWxdJd7VvQ3S22Fnd/i2aIEiOuPsi0lIUuq8AtGhUBjEcX3QW5oRmBRmFXSBSxSRgFTa4xO+69CAchvgzNJOLF3BAhYgGIOViEj+WM6OTNJGKRhvw0Cqs75GVXhU2WhLvYjC7ac7ru4CTKuMHFaFqc7DtstXELbLKzh5A4nG/fc88aF7rNoIdOLXk4PTZDWOiH0WHQitnDnSCF8pAAjYwSx83q1BSx0AGt+OqTDz0IMpv3GOgRzRMUqz4UUNhassP1lX1a+tBaiKysmQ7haWpEDE21FAVsloVjuDh6nrX3uimNXg4yuqOTG9EpjwYt6MRmkJ28GXZi0ldTLXkWoNAxQdoZPeIjaCkuQfFcZpkyF2o5jK265LnLjb7Pofsg+9nVMiLIyZj+6tyDchc/ESFmBIj5fO5eaZPkLtAPjQ5+Ep8yOv6HKIWIHpp9oEDd87rrgS3hCvvAvEL/cDg6FmuIJRSFrcVV2A+3aEYKDBcOyJ+dhZb/+8cgW5EWXWOZCJRD71knwI042EaXoXjFo8g8CS4tES8CQTh0DdpeuaVvL7XEBoIe8QxDcDcfB/jAFhxCQyuan0agpayHtt3OZsqoPOp79HC+KOh0kwgKad5wh+wcEz10fYvjQJm79iuaQz4RtOfuBK1aeU5kJDujqeXNACViQJfSkulB6HsMcBiGkNgJr9jZKmfWV+7laAfFc1nLR57WpaxmnsXqwonn7r1uSvp9V2A2x1YtQ1hbZbXkeZ2PCah7j79CUZwBRPT700pjVmZetOSDhVjlcJ0JiIyUfQ7dB/XNw4EmO4QFxOykHtVuXxSbh0/lamRW9z8+5BXs6EgsDxQt0atHj1uYHUJDc+kPzhAW5GrOJsH+cD34W5sks7W4cuzMFg3kXlZgXbIRjRX+4x7O57UDxi0txJ9GlLHMdXYJupEe5Bdg72z9G5gJk+eCeTLJsgbcyruBVczxBZ0dQ1igJQdLWzwfWwWlmQi6ttSOPvZRQG3IT0NoFsH+M18o+yY4nK866gHgiSJu3NVmksIZ6ILZISQUinJLI8YCae7lCeQRpTH7cCZoIaJ2uBPKqgmUacwxx07xXyEtDtOyteKri4uY9xgoViUxiK3wBjtb5cz6orBqX57rFteYwmfIJy+m0Alr6pKDg37eb5nn7j1MoT+EBa1X9keLnh1QYHP8+yprTWkf8nZMZK3cKls6UHCye0LD5d0I3XOuaYktqtjmHXImIHqUwkjQfdBwZReVIbqT/VEtcFfBRwdrzz2fgV4l4H2bdbopDR0B1NTwClDGE7ZfGTrTY4uY9xVwFyO0o4zZ0bqwP5zCiIcSQd7u+AOri4t9Gk9u0QB/UKCvRBmJWEEZa9UgLfkYlJGgr5eMqJ3QYW3/BLgRNy9NmJguaFHImLlaAj1+EV/FrkczL4m2+M6isgnYdkN40t+p+7h7Zt/gFY0nF6nMKzicrxQEXnELZ8a9c7Cl6KvtVegHGZSHUHMvgxLPHFKQe0NY6EFDPL8TyqoJxXwIGycgBmlklYd8tOIKQvazrwLISA/+TniDna1yuL6yn90L5JIgVgSQOZZRdJQM4WlRIjiaaYl8cOhbAbW+iDgwhAVVafmI1yxyAMsqgzwJt3dicmZLC+aOe7T3ddFw5WntnpctqtjmECEeBqQYCboPmKIle6v9n4foTmKcIYawRlggnrqgRbFlLsX/7pV8yAcy9FB0ZCpPR87zl2vtTKE9jH5ZkQI6ObbaV32TYARNbhGWGP1wOHUZwoL8ZysOeY3VxT2/RTPyaghrxxED5bGYeDGoLgqviBamj/2+TzRHwd3DE+BG3Ko0YUqgyWuxiSBRpoWLstto79trNZpDXktFBe4S0yGc2FLczZsAdFaWLviZt8I+RAALQ0gczhcFWvafyX2whoXVLaWHpDy9+JNdUriyA3qMy2FEy2HQzu8EDZFXTdARC0NoiVb0Z1Ix3HrspZ+DoJa8CrC1bXbCG+D21lY5XF/ZX93e8nNnaLxFIR+COgEJr0RtgKyQedbek6m8B9RSFlG7YggLcikHlnBlO0D08p7ciYkGzasJ9M3dgQiwkeRMt8Otog9SjtABYp5deVLOBET7vExWdB+0HENYUBzyRi1O4gzi1voKBgK6MJyc33oqoXulI6tswhKKVTBVHgpawnnFqhwy+6CfI6lwYWfI/0VHR9g/HI67MIRl4YhDCUUBHbr0xdVYh1s00x9kPfvx1Gis7H+fvlrygyYj0tFjWJZMXfbX8QW4VWmi6THzWAxagKcoP1QCTW4N4b+xE71Fm2zrgO77APu0DGEN7mYftC1yC7BaNOZTZp9sgYc5vC2W++z0kOtxFdzdP2sK2nN5RwY9ODrs9sPVewEth0GTqTM7YXUIxTw/fquPE71ojBgSap55WiR2tH9iLDzXERkWhJwfQmInvGJ/qxyu7+ochbJCzqzYwc8hrD0aJIOcD3pIM8/aezIVo9NLabIsYlkL7ZMcnL5zegLeiUnfOX1L4xtLzKBccKvPiMbsgCih6wPRJWeXMwEpRvAkJtV9QKRxCItB/GFELkZTc7JvgI7MEtJwgxbA2/JUQveKXjQykSEvoJNdXaWY0mYOH1aXBpdWFx1KJJkycaAlgkPHHBnIDhwOJ2u6BsJFSwlFYWtx+87pW7TQ17FEWDb7MxLrwi0daxJFNrK6VfCZxrzBMFii9AIc7KSL0QOZt4Ui0te1rxnXtNDOxlVEeguB4/nEmiLI0ZYfqtCXCLEe3CorIaSgLvzFOIualwe0kP3R3QIjgBEMhjWuMbI/36xDL0bEzk4i7BB5ugzhv2CQWyjomcE4Y5VE1cMVLinUi9apoF2wE/IQ/eFRd4VFIQKpKXq0Mx0s4Izudph7+MC4XGCKFq4hoqGxuIg4iJ3wCvmztVUYgrtyfnV9sZ8jltHyMTvFmT2DmH3T8RTHKyBqXbjF0LQwL3pJh794EgE/9K2gUKCJHcxq4nRHlJNc0AIamr/ol32iXpiSSwyKWPbkEpK9mOx055bsa1BGlyl01AVQwH8UcFuN8jzbYV60aCICOzLF3tMqIO4HhGBqLJRxNSIP3QeNqOWgBc/Lcmw5ycbAz2w8Qzs68lwwrkYfckLt3Svsx5EFsqC7eUMG6KMQ/qOjnaC7AiN4pVFQ427ZBpkSSTTlGK4ico17iFxLXxsj+7Y/HNfo4zYGuZbDCgViXoWguBTxpwt9Yyx5ksfqaHTpi7AstLX4y6BqVwsT55ohsKCFlghcZCMYR0QN9zQvGrVMMkILvcqWexn+dfoWaIswySEvLcwwB1owczTZQ0NeVhdNYNMrWNGiIEqNLqw0fYEFyBtO6xGaoDVDX8vTQVlbQWp4m7sLKeRJ7cOg+EyX7PaZ+QJ9NTvac/czaMPlTVzQVkYHeBpz6EQPFw6gSWMcT2o8DNr5nZCHiCeBmNASIhC6JVr//+8PhTTlBiIKcWiuotWRGkPjTxZDJ9sUh+GFw62ys75c004QhtwgGgqU1HJwgFvYHMKCloDhYteVDcAqZwd2fOtgSsqxMcoiKoZENWziT7GpcNHOXS7QpNe4t3AmJltbWutFYwSKONDCWFlNPqAWUZJaPjFwgJbsvB7n7PBhQEB7VaFQi+g+QISFvyjIZtCdREEO7KydtsSZpxK6V0wEZVh9WLIzGYbAFH/lHn+5HveewJqCDCUOqyiSYQp9OSaRCWJNw8lg31c7w3FXm4pbipWGC3GVrcXd2aKroIORISzd6YjxIS/uaWp5V0RAtAraHhGfbkT6OBabE/BNlnFgZxfdlFuVJncJq5X3yrTojNg6IO4MHpt+UuiBPDzXLuNMeN/KVnkBlNj2TzfCxSIOwRjz8Lg0OQtlKScs5+yQJ0bJYPUD0P2hyQ7hCfIc2W4I1+YwvG9oq7wArMV+2UHVQrjyJzljzIPj0uQUnJ6fPn3ic/D8+f7n8k3h4xz0KhTiBcmv5XcqrFR+P3lFDsP7hrbKC6Cy4+Pul196xdXf7RtjHhaXJsfo6Czfxs0JH09Jig91ypP8qE70zSgwfcQblQWH4X1DW+VlUEAI2s73X/q2mxXc+f7eGPNQuDQxxhhjzES4NDHGGGPMRLg0McYYY8xEuDQxxhhjzES4NDHGGGPMRLg0McYYY8xEuDQxxhhjzES4NDHGGGPMRLg0McYYY8xEuDQxxhhjzES4NDHGGGPMRLg0McYYY8xEuDQxxhhjzES4NDHGGGPMRLg0McYYY8xEuDQxxhhjzES4NDHGGGPMRLg0McYYY8xEuDQxxhhjzES4NDHGGGPMRLg0McYYY8xEuDQxxhhjzES4NDHmFfjniT9//oym6zFM38b4q/Dx40fN6MePH6PJGHO/uDQx5nm8f//+3bt3Q7gUigYSLaaGfFVk/MOHD0O+C5gOk7qbYuuQ379/f/78+d9ybFlK12TmoXBpYswzIGGQKj59+jTkv+BadlbB+JcvX4ZwF3z8+PHOiq0dqMAof5kvF8A+YUFdnZjHwaWJMa+ASpxv374N+ar8/Pnz/jLZGyq2Pn/+jKss8ZCfj96XhAXtlhu9YzNmQlyaGPMKfP/+nWRDDTHkq0LFg3E+bQ/57fPr1y9m9FaKLSqJr1+/Ukl8+PCBhb5gIfTKZAgL+rUNcRiyMXeNSxPz9iBFce5zUpeP0TSCrkOHJIFIEcBZj8gRr1QRX+Tn4567YQGkEC0SQSJ2ZAQFshEi/pBUgIQknYBR9FoeuND1uLeB0pu6cMFY48YCI9LCWFLA83Hjf//DuBIbFqSgIGTwNuyjE+9vtuLGX7rEHGnpr3yySxhZLbxUk5XujEUL3SUqDeeWKLbCvTzfAOPyFiJchzthh2wQI31Z92FoLTTOcD1aj8BDupQJEnYae8yNuUtcmpg3Bjmeg56kopwxWp9eepMJuM46HPFkFImkB+UJdZGFnEERYQhLakEMfSwgRs6gnb7S4S/tiOiQw0jP0hH4QwvDKdcqzZTcU1C2lm/0oi9mdQuKQS5AtwBNfMO+0iG3MKVbgu7o0C77aKKAqa24qTLA7TzHYhNlXCL+2EGB6+xwRtNXoSDkgJwBuiPm7riBS/xVL1kIfaALRhhU1YOix/X+jPYzPZqhE6usW8+CgOAP0wE815LtoLFyfEAzKo3G3CsuTcxbhWRDKhrC04Fekg3ZiHxAjhnyUnzQUdc67iPDyQJIBG4hRi5RyiS7SBTSYRSyoFqUaHUN9FKe5kIt6lLsFDACQ1gSv6ou6AaZSMwRbzGOQuTR7g99UcjdUciZni45bnKYLqFTbDJ3xOxwUcjIWmRZ3ECE7ACiigwhhyNi3WG9nIiWMgRoRhHDrlDQEHk7IR5WFfswI4WFHZhnV9DQxbfVRmPulfWzw5j54aSOTAM6u3O6AlpyDga16FpdIklgjZxBSxQZ5MJc1qh2iZQves7AflQ/UEaBVTsF5drwJNMNZmQ8u11quN6dfJkVAIUcN5SLTdI8DOGpEMk1HN3z6mRUFoQ10r/CHnUAU8jGVbvkFtaFlghOMQiaY44eYp4RY9GytQTyP494ReQtDLkh5/k75IXVRmPuFZcm5k2i8z1/qO0f06WTX04oyaEpUQo67kljZCPlddppUX7KH5SVEctHZ40bOU8vLfKgZDhahrCgNLP/EVz+oIZyGBcY5NYQGsVJTTlXCfKHdmC+qktypdLjVmxqjlEKSFQ1xjWmGAJW6yqBvlYBH9DMCwHcyv5oUXJLKbbwBAXVGZiSmP3vM5IOow/5v6gUy7vrKmBWuwX/83QKKpuyt6A9EyEy5r5xaWLeJDqpI/mRYxCV7QId8aozhJJcHPo5I9KXC7WoC9mrZAIyCnl0CE+QI/O4ympKkwKxOFYy6xak+chkkURXZ5opTmrKkWXVXchzohE1h+hxKzY1x0iuGkKghk0sbGV9gaamQIR1QYuirfz9r9ITeMjdcFJTyMUW7tEi6MvCZeehzwg/6TWEhkYsRi4Gz5kaI0KPdodxNZEhL2CBxryvjLljXJqYNwkHNyf1EDY+U+o7kSEs6LNyKWjIFiQD0gYtpA3ZoaWkrp4RAVOyMOT2cbynGbVsfdnRUR2AWYnqnkcsFOPKsjFldQ9rqyhuubZYtRkpVsGPSuUMxBYYgvJIdog/UaKFi5K8ac+VXCm2AFHLt0WZkVZ5J4baXTkCl4GrGpqAn68qGLfPSC6VyBhzr7g0MW8SjunI9+Rd8hwt5fQnn9E4hKcyIqdYkB3SADk7WkhatEQ6F0rqpfop7w+AjjCEpywYrpJ1lKuKnQxdsgXIFmRwq7boTiqlDSFVY0NewKWc88oUVm32WiEHn1HC4VXkFbMIs7QAnuSaQ6DJrSE8VUKxXqBCZwgL6GR/yoz6qhVwDIWL6wA64gAj4hWjXFDiMF8ciB2IBb3ikmjM3ePSxLxJOKmBI5sUxZEd2RFRxYdSOCiH8Rd9UkXJEzSikzO9euVMLLCgdhJG1Dc9hyFqFG5paFKUXEUNV5UXsYOIneIPaC6RofVlRM6jGMGgBuUvpsIfrlHWuEJJjgtuyQgtuKTuqury9GlHP7d0m//m+SXTU+Io9eJPzAX/EbPDHZSxKSNCfvJ3yE9E2Iec/GEg1VjZQ/zH+bzQWzPKu6WgQaOAQxODpVTdgbHoqwhfBmPhAINihIlgkJCed8CYt45LE/MmIfNxWAOnNmc3Jzh5ThlIOQkFZRe1o0lCinQVKM3ndlpICUNIoEM7pkhmkSRoobuuhdIeg5LP1IKyfKCj0lXYWc1eypfqAiiXNI9BJXLdpXYJ/+lIY56O4oC1qHW4KzWge/gpEGnPry66TVVL2AzHcEmTAvQPk2guJgQtRLIHRGNlJzGOJrC44RXXtKCJV5hSo+gz6rulI3/Q4S9q2dWXgRGfFVJj7gmXJuY+IZ1wpm8lHmOMMdPi0sTcJ3zihCEYY4x5O7g0MXfIn+XHnv2HC8YYY+bHpYm5Q/Tzgnfp/1pnjDHmreDSxBhjjDET4dLEGGOMMRPh0sQYY4wxE+HSxBhjjDET4dLEGGOMMRPh0sQYY4wxE+HSxBhjjDET4dLEGGOMMRPh0sQYY4wxE+HSxBhjjDET4dLEGGOMMRPh0sQYY4wxE+HSxBhjjDET4dLEGGOMMRPh0sQYY4wxE+HSxBhjjDET4dLEGGOMMRPh0sQYY4wxE+HSxBhjjDET4dLEGGOMMRPh0sQYY4wx0/C///0f4uAUyrHPPUIAAAAASUVORK5CYII=

  • A) Crank-Nicolson scheme
  • B) Forward difference
  • C) Central difference
  • D) Backward difference
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q29

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 .

  • A) Elimination
  • B) None of these
  • C) Iteration
  • D) Reduction
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q30

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 .

  • A) less
  • B) equal
  • C) none of these
  • D) more
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q31

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

  • A) data:image/png;base64,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.
  • B) data:image/png;base64,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.
  • C) data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAPkAAABNCAIAAADrdlWkAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAhoSURBVHhe7ZxRddwwEEVLIRhKoRwKIRhKIQzCoAyCIAhCIATCIBzS232zPopkyZbsXXlXcz96VrIs22+exqNNmh9fjjMG7nVnFNzrzii4151RcK87o+Bed0bBve6MgnvdGQX3ujMK7nVnFNzrzii4151RcK87o9Do9c/Pzz9//vw48fj4+P7+bgcS3t7eGKCRv3//tt7vvLy8/Pr1i5HW3hUm5wYuNPkWEA1BkOXh4QExkdQOJEgfafj8/Gy9AWMKWEuL1wkS4fn79+/0GaF1KAKZCA//8hm9iKj6Jwgw8eb0j48P67oAxOnnz5/p1TuCJugmA0mlp6cnHYrgthmJzmjFU0jMiWEFbKDF64grows+E6p03RMGgpTL5YIgQSGl1SLfpBPKKMeJFjcZvgz16rNGAKrSP5vLxe4CAioxpzXOHE3ABnao13PxkO3CVRHBKSyGfRMSpiEk1viO7vP19dXaRwIpuLc0X+At+sNVEXIJAYE5Zz19ZAHXcCmvEwByQyFO5Imcps3oDVN4k3BLuZXQl1mv00QisPZ3LiEgc2p1RdGcOKyAa2jxuhRBaETh4eWwUB1FLiQtRnOVD2kDNTk0vRBYLerhuuqZ5f9lvpP6QBfNLb9rwj2obgE+oA8fQjVYsTo6ESXUnICA/qc1YvsB0PYgrUxCGKwLhUTbg+MI2EC110nYqIb5pOMk0GTNCToLKXa2QmVyDIqnOZGr0KPsxchynEQh/IIgMSCXtK4GrpU4Kj+m1BB5SNrm7jZX4jM5p0g3xtAzxSi3/Q3JTSsOImAb1V5Xvgmjop7IYeU4QTnNTPmDyVG/nNEnFKfF9M+c1uiBXEiyCO+TuwJrnNEayC3dsoCAGozR5da7c3FabqmvgM3UeV0JKaoN5PXIYYsptiyZ8geiV8mKgRbTP9MyzBo9ULkS1QZ6WGucKadYDpXFUQiYdr3Rec9wSjn9M6CvgM3UeV0bl8jBs5lgMcVytBwqaVqYIUJxSmv0CMaANXrAQ0U3oIWdOqycYjmlLKBerQTC2ivQV2fROoxgAFjjpqi7acSNnlOC1sYJOKsQKsK/OEOE3jnlOAFjwBo94OrRg6tWibaeuQUwkc4TIeOWk3QEgzlFu4gcDABr3BRbva5MH6mjOJVTLANyoZLR1xTfIYpToWoSjOn7Ck4fnPtJb0kVSGHppvOEcCJzkiyq8gWDmdYaGboL2Mwmr+c8rYxCtKw9Ry5ty+icqzwdZbsC4b2x9nL5jDEFi1yB6AZynlYSQQ1rJxTee9Kfc7X+1+eL8N5QfnalhWNuizqvhyYmg/5PGnM/oF6ME4TWFCq4QSUm0/KZqfgQFp1646eT6z3AXTEPk88m+FzFdU1CcdATy6bJAsidHLLGHKmAoACBYjTVdfK9xgDnzk5OJyC4gptG9ggCNlPndcBqhIEH5l8+p3KABlgjg/JZmLYVJyw7zam0xGyhs+X11MqM0XUJZLoShC6aO3odeDrMjaW4E/zEU9uBAC17HsTac6QCghYSEln7XJYwVRip2XUCWnscUoqx3oAjCNhMtdcXUZzCTDwLUiLrbEorI6NYoxICz3qwxoHRslduztEsICDCYoBmuRUBZ9nf64rTbLqKUIZmbVh7BQrwmslT9P5dvwHoiNLzojINAgI6oGFDbr4hAWfZ2evozrpn9Vt7CUbC7OtyFqLbZvQtWfDKVNXEtQICGb3B6FcWEBFUaEHbDafs6XWV18ixXnpG8khE66IloDLZTRgdKbjVsOAuc5cCarXrcsqeXL329ZWyfw3TAKmaaPGE1t4VJicxNEwuxS90V/tyTAGbwdxgjXNVvH2lHcLrx+SGvH5P8IJC9qiEo4fUbo1W3OtZGrxORUH5QU7iRLh0aXGXaMMdVXEoSedGMd3rWWq9jtEJCelHp2j3sn7rcjfw1Iuwx7DRCdItkl371Kq8k+Jez1LrdcVjyj2cGBadzkpmbX1tr3Oxe8KeKk+V1zV4cf90uvL9YE+1K4fw+t0jQRex0d/B5Rzy6nw7j6ffa4p+YuVevyxK1Sv11ebJGmODDovgXRudMLs3ldc3bn48PFmqvM5I7G4NZwNkdMSMqkF6tm9+3OtZqrz+/4cfvhPdA5L3wwlrnwMRZfoG3OtZqryuN6+qTKKlH2QO+IXjLug3h0ntCPhx+qNau4jZ3+v4g4zIs/Hv9rW7I1VeJxLanupBnp6etv/+xhoOq95GsLueiwQv09uBDXT2Oo/BkpUt5JVoA96RKq934cjqHZCeXsdGrN1wybKIox06gfQQzrJGPSfkWPW6vlqyxgmVbtepB26dVD0n5NBeJ3WRqzx+K3Gvl+ksDcUJFScRwtPs58Jo6XMIr2wdckRBPeCotnfT/1t9X/cXj++Vnl7Xb7TxL9KDfjhM2Ozw+VeZ7+nrhR0pq0fVp68vWADq5DMfGMPy0JjR6OZ1fctBhKx97iE21s78WQgH1qgnpCFZg0OMx/F2YDy6eV0v33DTqWiRqKx9/h5t5PDkWKOe0LuR8ekyGI0+Xtc3iZH6aRanuARrOGdWqjdBPzJ6yujjdSWhqBAneHROIeEDTVK7ms7EGvUmyOuU6cPW6CFH8bpyVehsUlQaUQfWqCdkdG1bPa8fxeuKR1iAcpQeRqoZ7sMGZ416IKNT2yhr+Ba/295UtTjJBmTrl+9/0EsFKIcYQMaiaQecJfWU5kEJgjF8RkM+jJwyunmdrKNspJBM+XuCwKgGJaiekyLK6umPB9GPhurRl/EoyYnqGZBuXnecK+Ned0bBve6MgnvdGQX3ujMK7nVnFNzrzii4151RcK87o+Bed0bBve6MgnvdGQX3ujMK7nVnFNzrzii4151RcK87o+Bed0bBve6MwdfXP90YQ2C3oEcSAAAAAElFTkSuQmCC.
  • D) data:image/png;base64,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.
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q32

The boundary conditions $u(0,y)=0$ and $u(1,y)=y$ for the differential equation $\frac{\partial ^ 2 u}{\partial x ^2} + \frac{\partial ^ 2 u}{\partial y ^2} = 0$ shows that the length of $x$ is

  • A) 1
  • B) 0
  • C) 0.5
  • D) 2
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q33

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  • A) data:image/png;base64,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.
  • B) data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAOwAAAAwCAIAAACdTQEXAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAUwSURBVHhe7ZjRVeQwDEWnBWqgBXqgBGqgBTqgAzqgAiqgARqgA3qAu/NEjidOHDkknniP7seelWNiWXqWlTl9B0HnhIiD7gkRB90TIg66J0QcdE+IOOie44r44+Pj4eHh6enJ7OAXInN7e/v6+mr2Es/Pz8z/+voy+3i8vLzc39+/v7+bXclBRUzcb25u/HlqD5rggBF6s9vy+fnJ0nd3d2VpInfmUAuYb0PXBqVyonK9avzx8dHsGupEjKpOp9Pe1ZH3o2ASYPbxeHt7I+KEopmIqVUsx79mnyHlBR0jXMK4ThZ7gJ84wy5gsugyge2scLhOxHKCFJq9BDmuTTPbY4nD1mACTWFDwewLP2t3txoWZbnRwcYZPOGR2ZfgG0/NuDZohhOFq/w7J2JggzwdndVF9m0n/km4Ms2HCn0Ot4RCrMNWu7vN0d2Ya+JQtUDNj1oa/lMQMVAoEfrc9TLJsUS87iBehYOImGTjRl6MVfPMOBJErCxianatBrwi1nUGVQ3xWcMVaeblLJHvkI3RLfFI2SJzamzIk4oN6ld0qOJtmulmIta+gI9dG7pEE8w4I2XnvhEZ5ZEoqdTpA5qRvb9zBuRtQcQw6XyBikqs/fsbYsCVKm+YzBJm/KLQD8KVXrmbABNwiUdM4BFm1YqraVmJdYDnEp+ffPk2Ej3xIYyESB0IQcN5/ZXezyPN3BWleG4vQv6Y4aBiqjSkzsYJHoMZDnh/4RJUtyS9aiQtzwKzasXVSCht1mIV1jIjA7HyNG1/NTJ3I0vEvHNQ7dwFuAfaS3ktzfErrULEKKbcZmntReauReApLzEjg0uQCen+MXFp2K0qMSqXmaPsLlLwYcApYk3zYH8wBXssLKRNpVHVyJxQVIzS+UqcGVPw1ENZmkJrlWd65qR4RUzx471pzfOAN2CGA5aYmy8HOEhmT0mW2sNIm09yqbNqd+vQNgs9a62IdX0NtxlgpoHdFSJW8E145qR4RaxvxjRSHvAGzHDAEnPzcwck2bRHV9de1fCsppmI822OqBKxakHqtgJ7qA87z5wUr4gLcSmAN2CGA5YAMy7J+7Zcsly7zX5jxhNWr9rdOrTNtHCOUGrynjiV9UBeCxTYwiHZFiLGch4Rb98T672FUE7CX4EZDrSKGZfoEjTjDHpNe/TFhnhbmol48WTmx1u+TYo4n6yY12Z2NVquLOI812W8U3npirYJj8EMB3mIB0YOcEwZSXt0ZY438Ijx4dN7J+Tq8IPrfgwbR5STPzjkKc97hgEGeZT6PIzw8r1LAKnhTLLc5EZEwfk5XCKWPlbsEFeqvBmEaPYv+bh+JxoVG6WTfyePwSZwNtgRq6SwYu7zVrBHluC0TCZeKU8Ps5CTqViFvDXjjCKJtlgon78VxIctsNAAK+JkXmvU8BRUnuMSseJY9d7VsFUwI1iCpJCa/NBKmm1+qNkWDiT6rjpOLhHr28LfaP8FFd02B6Z3yLTqmdmXME452K+47oGyP7pgF1kWsbrPuUjtAVcPudm7qf0PoLgUZKoGtNmX7t9hI2wnb40WWRAx70W+7SXFWWTRqMdzIFBaWyhfj2SNOWSwzS36F6jBOnIrro5ZEasAAyfjKkWRXbH0fh9M/UI6qFjOfhdNUBEO3ldQrThpeWfvxNUTB8GRCREH3RMiDronRBx0T4g46J4QcdA9IeKge0LEQfeEiIPuCREH3RMiDronRBx0T4g46J4QcdA9IeKge0LEQfeEiIPuCREH3RMiDronRBx0T4g46Jzv7x82mPYWsAlIbAAAAABJRU5ErkJggg==.
  • C) data:image/png;base64,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.
  • D) data:image/png;base64,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.
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q34

The PDE $\frac{\partial ^ 2 u}{\partial x ^2} + \frac{\partial ^ 2 u}{\partial y ^2} = 0$ is _______________

  • A) Elliptic
  • B) Hyperbolic
  • C) Parabolic
  • D) Non-linear
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q35

The black points are known by the given boundary conditions with a PDE $\frac{\partial ^ 2 u}{\partial x ^2} + \frac{\partial ^ 2 u}{\partial y ^2} = xe^y$, and The pointsdisplayed by the red dots are to be calculated by Finite Difference Scheme. We got a ____________matrix from Finite Difference Scheme data:image/png;base64,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

  • A) $9 \times 9$
  • B) $6 \times 6$
  • C) $3 \times 3$
  • D) $3 \times 6$
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q36

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  • A) data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAdwAAAAtCAIAAACLeE2qAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAkxSURBVHhe7Zlhmd0gEEVroRpqoR4qoRpqoQ7WQR2sgiqogRqog3rYnn2X5aOEEJKQPF72nh/7BZLA3JlhIG8/vBhjjBkGF2VjjBkIF2VjjBkIF2VjjBkIF2VjjBkIF2VjjBkIF2VjjBkIF2VjjBkIF2VjjBkIF2VjjBkIF2VjjBkIF+WXp6enT58+/f37N7TNYBAdYnSXAP38+fPz58/8DW0zGF+/fv327dufP39C+xK0FmWWxMePHz98uFQR//37N0uOuF4sqBeD3Pv+/TvpR7xC1/EwKYlBevz69St0mSH58eMHufH8/BzaZ8GMHBcoiczOxtDx0NBaZElQpr9SUaYQy5uhbcaGNXBmXaYcw12O52YtZMXJdZlTAsVQM7JtM3vHbGkqsny+Mau2hdD1+Hz58gVFoXEhSBHCdMnzHSeDc35oenp6woeX/H4i7SE0LgTnZUJ2zp5NYjBXep5TwvA3tPexXGRZA1Rk6jKzQuh9cFS5zv/kOYELF2Uthl6pP4cS/qqfUFctysCGfY40HZPT/zSwGdDT65C3XGQ5ngAXzArqfHRQxMILjWtx4aIMfCQeHbgzz1znc+GirFp5QuBIQibKPqTogS6fcQtFVj+iaybNqn6gUz1ZjHk+7dEz0MXcLsjyaWrK1xDaNyjfaQ9v6Zlh/yO/qig/nGR9Jx665cgnofFG/FJMz+k6H8UeeR4YQT0DQjQhNKo8nGQZk1p7EJIcGm/o190umZkPnaJ/hVGX1ZyaIi+kJxd9YKY9cxXwjswFD1OxnFvpZitfpz3kH4+Ns8dkSF1jcjycZFWKQxce4xfTlUm5pa9G8fz8nPWcYN5ObjW5dTE+luSWUiNFi9QH0TOh8Qav0Hl4UX6NXmJc0ZSsU59+aY/KdBdbe6HAxM0mJfOszgVpD1CzRl51mJoZXOexJEvdcT/4avy06ER0K10RPJb1ULNG3rABa1OD6zycZGwjV0PjMJgFQuMNfEJnumo2M1uU9cNF+rtJNIVbcYlm33p4BOiJQeLJLAm4W1/h3OWZ7CebiBKlhfDCBI1fdJ9+loq3WPySw3FAPdzKUhB1mcC+SO/c/yT3e2ODZDkwNA6gIlm3Kg7nbgtRb4bGL+YnHuBWnFqnDXyVfrlzN31Xo83NJXiFQUKjNwyOAYsU9cLDSX4Vc2RmiuIscnVdeCOzAliHmrtIDINM0acuqwhfc4seGUdQGSc1VDGLC74IuzFvhcYBpBZm6JYO0UpBRPE31RuvBXepa6HRDJ6h/DFaaM+jj4/0x4Q68nBRXZENkulJl2UjXSRLXcsg29D4md4It2JmokVy6FQP7xZ3r7RnCq8UD+Z1WEGstfYoRzB4lfceSzJTR9uOoziLjqcbIjJlhYCiKQRJphAGfI3jQD3cpVptKFhHo7wpui+tRyQfxqMr9iBtQzHKYEBGUwhXLY9G0DWnrkhHybxSVNRRstQd4Teh8aV9CkWBu1zwGNnOHoa71AMIxF26Pg6mRr4saY9yhHdXee9MyRhW9Hy7ZB6IthVhfD1Tp+4iWZIdGvRiaOxjxSjFWSUSTxEqKeGaHg47XGA9C1JPAg9wqyJY78KhyS2b58KvWxgQjwD0sLFzTU8aiRjg0G6DkamDXOCHiiuExse3od2AJPA3tJdYJTkGqDg+gxQVdZQsAzgKhHZvNP6ckfRzlwuKkfJHOYCLuMhOf/SDHiuidyFdI4vgGSqj7CxGoc4tAgshSDlTMnMV322XzAPUnNA4DFQzkVJa6BMTF4X2PvYWZX1pski0i9JDtOjBj/RkHiQSuhXaJTSghjoIRbcYfhmP0zE+bgxc3zK5kDGEYXMkNGZozCB70vAv0pK7KWslEz6eLy4qHq4r0pihMUNdMhZytxi7XjD+nJFajWR7DLrSFXvwWOYTmRpdWoQBtxWRtVGOtIQg5UzJGFaJ7KJklZdV6rZBcjIRQkL7zSer1mmF1qIswZCFQZ6C1CD1TIuvBqnHTMEOjWOoB+9m+39nMZ6kp1h86azvMRUYds6GiNxLnQrtBhZzd8qr4GbJ6C32A7GrK7op3iVZW8IqdWtBHVOExv8gkFvkZzRP1sI0q1WhsvWSgTfStd3OhiiLlhCknCmZW3uKsmavjNARTGUuajHXmIR/Vnm1TlNR5tyqn1GAudNjrDyVeZme4rqV1+qnYMbvKG8OpsCSYvbQP/3VBadPzVZxT3cjZXCRaa7chC4o1YCh0cZi7k7h+UbJQGTT8n2yZGbHsNA4BhkwrTigW1qKQt4ubsx0Lp6CMy/hHHqKZAHdEGXREoKUB5KsDXvVCWYzLBamIxWZEckoKhaTbaxb8DvZELOD0AfIzs+Nlj2mQsvyaHnmTKb7UAqBq1vbIqfyDOvthPQgoMySbjzbyHavKYtVpsKed49jp2TiXgnuouS+x9U7cmpRxmX1j7VFv3cEY7Lj4VpIoD2nNgyA0JgBb5ywRbWjAM0dRroU5Ypk3sXhHY8kc2BARWYjjJAeMKdoltBYyZkrpZ2dkonvXOihLlkjj+aQbZxalPEah2Vynb+xJw0DEaXnhFUHHIhY4XsOROQQRwOs3fCzoGZnV0gP2q8VK6lZOhgWv6PvhVIfyfht+onA3dT+jJ2SlRs7C2U7RFbBDe2VqIIghK8KfVjIdborSBumCI2V6FM9XTt3Zyp5WkbrksmEiqKKZKVNfT94IE4tyqxkfEdgYq5nruTW4u8bHSGWpAipMK0vLZB52M8IqyqFMjVDt7Akre8qQ9tsOwiUqrBq1WXMFeWdkrUHMG+6vI9Gey1Kt03K6yQGNsfzB86hqWtBc8OZAI/JgZFBSvNUsuKero66ZKQVtdQlK2cuU5Hh1KKcQRQJUroCt6XpHrCBALP2uAhd94OcTg+JJ29Rd6FFMj3E6C4BYu/JLNwMpSpWK9Dhrri3XQb8hvdC4xjJJAwVY6iDy37uWZTJ0XQXZeERs4v5tx2SNc1XnTL6ZvBovB/JZHV62mCDeQ87LhrjVvpOJHfhnkU5onLc60jy6Kg26XgYuq7Ou5Ksj3EqVHoiuTbvUPIehijKxhhjhIuyMcYMhIuyMcYMhIuyMcYMhIuyMcYMhIuyMcYMhIuyMcYMhIuyMcYMhIuyMcYMhIuyMcYMhIuyMcYMw8vLP1QpQZFflwQEAAAAAElFTkSuQmCC.
  • B) data:image/png;base64,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.
  • C) data:image/png;base64,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.
  • D) data:image/png;base64,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.
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q37

What is the primary condition for the convergence of the Gauss-Seidel method when solving elliptic PDEs?

  • A) The initial guess must be close to the solution.
  • B) The time step must be sufficiently small.
  • C) The coefficient matrix must be symmetric.
  • D) The system of equations must be diagonally dominant.
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q38

Which of the following equation represents 2D Poisson partial differential equation?

  • A) data:image/png;base64,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.
  • B) data:image/png;base64,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.
  • C) data:image/png;base64,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.
  • D) data:image/png;base64,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.
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q39

The Partial Differential Equation $\frac{\partial ^ 2 u}{\partial x ^2} + \frac{\partial ^ 2 u}{\partial y ^2} = f(x,y)$ is

  • A) Legendre Differential Equation
  • B) Cauchy-Euler Differential Equation
  • C) Poisson Differential Equation
  • D) Laplace Differential Equation
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q40

When using the Gauss-Seidel method to solve the linear system arising from the finite difference discretization of the Laplace PDE, what is the primary advantage of this method?

  • A) It is more suitable for non-linear systems compared to linear systems.
  • B) It does not require the solution of any matrix equations.
  • C) It requires fewer iterations than the Jacobi method for convergence.
  • D) It directly solves the system of equations without needing an iterative approach.
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MTH646 Final Term Unsolved
Q41

Which of the following is a correct update formula for the Gauss-Seidel iteration in solving the finite difference equations for the Laplace PDE?

  • A) $u_{i,j}^{(k+1)} = \frac{1}{4} \left( u_{i+1,j}^{(k+1)} + u_{i-1,j}^{(k+1)} + u_{i,j+1}^{(k)} + u_{i,j-1}^{(k)} \right)$
  • B) $u_{i,j}^{(k+1)} = \frac{1}{4} \left( u_{i+1,j}^{(k)} + u_{i-1,j}^{(k)} + u_{i,j+1}^{(k+1)} + u_{i,j-1}^{(k+1)} \right)$
  • C) $u_{i,j}^{(k+1)} = \frac{1}{4} \left( u_{i+1,j}^{(k+1)} + u_{i-1,j}^{(k)} + u_{i,j+1}^{(k)} + u_{i,j-1}^{(k)} \right)$
  • D) $u_{i,j}^{(k+1)} = \frac{1}{4} \left( u_{i+1,j}^{(k)} + u_{i-1,j}^{(k+1)} + u_{i,j+1}^{(k)} + u_{i,j-1}^{(k)} \right)$
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MTH646 Final Term Unsolved
Q42

The Poisson Differential Equation $\frac{\partial ^ 2 u}{\partial x ^2} + \frac{\partial ^ 2 u}{\partial y ^2} = f(x,y)$ becomes Laplace Differential Equation when

  • A) $f(x,y)=xe^y$
  • B) $f(x,y)=e^x$
  • C) $f(x,y)=1$
  • D) $f(x,y)=0$
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MTH646 Final Term Unsolved
Q43

Poisson’s partial differential equation is a type of…………………. partial equation.

  • A) Hyperbolic
  • B) Elliptical
  • C) Parabolic
  • D) None of these
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MTH646 Final Term Unsolved
Q44

The Partial Differential Equation $\frac{\partial ^ 2 u}{\partial x ^2} + \frac{\partial ^ 2 u}{\partial y ^2} = xe^y$ is

  • A) Non-homogeneous
  • B) Heat Equation
  • C) Homogeneous
  • D) Non-Linear
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MTH646 Final Term Unsolved
Q45

The discretized form of 2D Laplace PDE for the nonuniform grid spacing in both direction is given by the equation,

  • A) data:image/png;base64,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.
  • B) data:image/png;base64,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.
  • C) data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAj4AAABDCAIAAAATc5jNAAAAAXNSR0IArs4c6QAAAARnQU1BAACxjwv8YQUAAAAJcEhZcwAADsMAAA7DAcdvqGQAAAsaSURBVHhe7Z1bdes6AEQPhWIohXAohGIohTAogzIogiK4BErgMAiH3n0yqpcqybLk2K6dNfujK5JlPUaPsRzH/fNljDHGHApblzHGmINh6zLGGHMwbF3GGGMOhq3LGGPMwbB1GWOMORi2LmOMMQfD1mWMMeZg7MW6/vvvv5eXl4eHhz9//jw+Pr6+voYDxhhjzE/2Yl041ul0+vv37+VyeX5+Jvj5+RmOGWOMMRFbWBc7KqxIYE4h9icc+vj40Gel98bLGGNMkY12XTgWbvT4+BjCVfAwEnvXZYwxpshG1nW5XHCj5+fnEB6HlDjcy8tLCBtjjDE/2ci6dA/w7e0thEfAt06nk33LGGNMhY2s6/X1FevCwEK4hH3LGGNMCxtZlx4aDIER8C3AwELYGGOMKbGRdT08PDw9PfGB7dfj4yM2dj6fdUgQjH3r7e3NTxgaY4wpsoV16fFCzIm9l56A1yZsuH+oBAm2LmOMMUW2sK7393esiI3X8Mutlq++jDHGmCJbWBf7LYwqvkOoXdfYz5ONMcaYCltY1+l0SoyKHVjjz5ONMcaYhC2sC9/CvULg6+vz85MYPwRvjDFmHqtbl36MHBvV29sbMe/v7yFsjDHG9LC6demJjNio/EWXMcaYW1jdumRU8bt0n56eiLlcLh8fH75taIwxppfVrevhSghc0YvhiTyfz353hjHGmF62eEzDGGOMWZBVrEtvezr0jor604q73BTqwZkBv7XEGPMrhDXoit4U2M60dbF8v7+/Pz8/Pzw8qAw+j70I4/Pz83Q6keAoT2HQuvP5nKumeJp8f//xUtZlxzLG7ARWpOWtS09VvLy8aAuiR9shdy/sirX+QE9efHx86F3AY6rh2ffnXrYuY8yuqCzCYzRZV5Ip5kRJuUWR7CjvyMCG2RpSW+pcV03JZNv3ga1rDMvSixXrxYoVqS/CReZ814X0eUlaEI/yQ+Pz+ax/2axqV1RjK3lno83WNYZl6cWK9WLFiiDLdtaV7Lr0ZVgIHIdJ64LT6XTEpo1h6xrDsvRixXqxYkUmF+GcOdal1+myAobw9f7bjLL3QIt1yaqH9rJjIxjHgL4CHGJ0CpBYMftBTY7nj35pl0TqVZNDjM6C+HWUd0bc3jpHHwNLQeusWBe0zorl0ITVrUvLXKIUUhLZ2CW7QjWvq6Ymx60jPTG65Sj0/V8co5EXD7vbUbmT1Dui2FmaA2ydQ/j7v6zFMbkOd0ZX635rDOwKK9aLFStCE2hsCLTRZ116hjAvQwtfLOhR0DpeV01p4hukam88BJEliSF9b2dsg5qTzJ9cB0wridHzlvf0xEpCLkuFQ4+BpbBivVixIjSqtxUd1sWadbqSL16SOHd+Im8n5BWh4iZp0aLduuI0yf6DNV0P2Q+bUSRikMWCqM4hUEKlbPCciwqKRz8kt3z1cAqNim8PcjQ+S/nEbVwc8o+vGJaFzFsYa+CMMWDFOLrsrLkd8rdi7VAW+S++TJFny3Id09pINBrzLZBeYx2wZ9QTvdalmOFmGuOJvozTIEiSJ8HYBnLYs5LDBr8hU+WH+TBAJNNAn5nMQJ2JVAxncTTufXV6cTzU4cShoAr6sm3GVp4JT49Q4RBupijLGDPGgBXrVYxgfdaMsbZijfnn7FMxxqTmewiPM3uZqisWN6qRVuuiYRQ89o4MqkXZM4b+r6PBUVctT6NNiWJou8YKfxXDUQbZmFa3QP6UO0l9bqg5eRrqTDwfSKC+1m10HaV1LHD6PBsmHvmQ+ZDtslBzJFJD+BximynKMsaCY0A9EgI/WUqxMUGsWC835v9bio2BaSnnoaDZkENxCLUoNqP0JvUnnZbGk6C9S/aD5kBdNaXBvEP4is5i3NAl6jCCfNaH+DpOp0OxX4USDPcBVkX1yTuLahPPB8aZjqpb6Xc+DJd+4l91O3scrUivqcK5IXYEVUZztR0EpBQ1sKL2GL0tIn3jGAASj+WvCodAxIKKcagoyG4VU5WgWCsdDYGIBRUr0pV/Ec76FcXG4HoUa+EDuYEix1D+Y8tUsehGxTg0WXrCtPpSLZGbyHgtk2pdXbITVPO6askdZ4EmXPJw4tCRCKJkeW6k4RD9F8IZunGhMbQ2Y52l+uPQw2TWJQspaWxSeWkybx9GhpwbAuNQaHK50IgamM+iSdTYEGigawxUFFOFQ6DE7YpxekWQfSpWmTUbKFanMf8cNTYEGlhKsUnILc8wob5McagyhOqKcWiy9IRp9ela5RuDoPwNKa67zhllx+CF6E4nkY/G07wO6EWdTbmV4pQm6RUaSySr/HCi+obK0xbFDJBD/eJOU3HGHeQZqKx8/gz1H6qhlJAvuFqI5/VRfRAPkCbZuDSiaif91QJn5bJU6BoDFcVU4RAocbtiHKoIsk/FKrNmA8XqNOafw1m/otgkFAQhMIJkH1umOFQZQnXFODRZekJT7xZJSiJIZHFmqtKAQ4SoDE6nM9RypZ83pBpBfVU4hl6n70OKCOKpWwh8o9PjXlS1i5fV5FC/uKv367Jo/FFiCH+Ty66URU2IjHtTKYsk4wRaGqsMNR7ENbMyIcU3+bmNcFYuS4WuMWDF4JZZsyvFWvIvwln7VIyYPDIhb7VyKxJSfFNXjEOTpSfMUb8Iu0iKH9tL6ihb3RDOoN7xEjmjJSvBoKEyXaMtATuvKCP+jZqt2qsBfUuLYNKMK9QHsWhJM0a+JO2BimKqcAiUuF2xuiA7VKw+azZQrM4t565EyzpToWUJqqeh9MoQmhyfk6UnLKk+ZY/dedNQa9xIqQ9W3XW1Q6PYchUb1YjaHl835ZCArg2BlVF9bizulg5qmfb/pshcL1cDK7PoV6gopgqHQInbFasLskPFVKWxWbOBYnVa8t+YumKTtKhB/pV1g6OVIVRXjEO9fbGk+n+vD3QULy1V78a5weaMS9Rb3GIpWGuo9uzRINR2moMyuj2djBJt7Ip3ANZAQ7wyBCdRDlSYS7zeqzx0oO2cHg+GfFgzkIo3KlvgxBsbuDh1xXQ0BDIWUSw5PWGHiqmB8ayJ2UCxCsX8f526YnW0dLPxiE+kjRACDctURZBJxTgUl9XCaPfPg+bhOlQi0U71DoEq6L4H39IIoDtvH51oomExrFmoEd87lUH2jrbZ0CKKu2WdQhz6aMbMp9wEyUtlyE1pQJMkX+In0TCLuaWZC1JXTD0SAj9RK2LmKTacmLBbxfJZE7OBYmMoz5iisNtTV2wMKZmgQ73LFEeLUlyz/EGejEiKC4E2FrYuYJYySpI7h2jK1A2BcXbiW0D9acVKNaGN8cUL44PiQmB9ksG6h6WKBT1e0zf28iNixXqxYr1ssEz9W4C++X3rytEFzjBuWDpxMmL4yyFFAgmSmLuEa6L4skhG0nWhdGewfHDJEgLXIDMkjjEJVqwXK9bL/pepLayLBsfNZivDuIHYpbD32Lf40GvCh0OjAR12cotmD+iChjVlDzvvQ2DFerFiXex2mdrCuhglNF62xHBhH5qPG6QhTczdW5cxxph5bGFdeBVWxAc2XlhU5RkVY4wxZpLVrYvdlXZRgq16OGCMMcbMYnXr0q3Sl+s3ok/XJ3Hv/kEMY4wxq7K6db1efyinZzT0vMbbPl6TYYwx5qCsbl3xTuvv9T+nxT9zM8YYY3pZ3boeroTA9yMbl8uFvZcfCjfGGDODda2LzVayzdLvt8C+ZYwxZh6r77qMMcaYZbF1GWOMORi2LmOMMQfD1mWMMeZg2LqMMcYcDFuXMcaYg2HrMsYYczBsXcYYYw6GrcsYY8yh+Pr6H6qZTA73CV10AAAAAElFTkSuQmCC.
  • D) data:image/png;base64,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.
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q46

Gauss-Seidel method is also known as………. Method.

  • A) Gauss Jorden
  • B) Jacobi’s iterative
  • C) Successive displacement
  • D) Gauss elimination
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
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