Numerical study of hydromagnetic axisymmetric peristaltic flow at high Reynolds number and wave number View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

A. H. Hamid, Tariq Javed, N. Ali

ABSTRACT

The computational study of MHD peristaltic motion is investigated for axisymmetric flow problem. The developed model is present in the form of partial differential equations. Then obtained partial differential equations are transferred into stream-vorticity (ψ - ω) form. Then Galerkin Finite element method is used to find the computational results of governing problem. The current study is compared with the existing well-known results at low Reynolds number and wave number. It is revealed that the present results are in well agreement with existing results in the literature. So, it is effective for higher values of Reynolds number and wave number. The variations of streamline are present graphically against high Reynolds number. It concludes that high Reynolds number and Hartmann number increase pressure rise per unit wavelength in positive pumping region sharply. More... »

PAGES

139-147

Journal

TITLE

Biophysical Reviews

ISSUE

2

VOLUME

11

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s12551-019-00511-8

DOI

http://dx.doi.org/10.1007/s12551-019-00511-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112703563

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30863983


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0911", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Maritime Engineering", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/09", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Engineering", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "International Islamic University", 
          "id": "https://www.grid.ac/institutes/grid.411727.6", 
          "name": [
            "Department of Mathematics and Statistics, International Islamic University Islamabad, 44000, Islamabad, Pakistan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hamid", 
        "givenName": "A. H.", 
        "type": "Person"
      }, 
      {
        "familyName": "Javed", 
        "givenName": "Tariq", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "International Islamic University", 
          "id": "https://www.grid.ac/institutes/grid.411727.6", 
          "name": [
            "Department of Mathematics and Statistics, International Islamic University Islamabad, 44000, Islamabad, Pakistan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ali", 
        "givenName": "N.", 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.amc.2006.11.035", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009622603"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1146/annurev.fl.03.010171.000305", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1015617469"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1080/10618560290034681", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1018135278"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1299/kikaib.56.3633", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019717497"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0021-9290(70)90051-5", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021337487"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1155/s0161171203008056", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021928307"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0045-7930(94)00027-v", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023905934"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physleta.2007.09.061", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1024362933"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.mcm.2010.04.007", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1027347566"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.amc.2005.04.020", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034392534"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cnsns.2007.03.013", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1034716661"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physa.2006.02.029", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1042511564"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.physleta.2008.05.086", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047987962"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0020-7225(73)90029-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048507410"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0020-7225(73)90029-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048507410"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0096-3003(03)00672-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051347267"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0096-3003(03)00672-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051347267"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0021-9290(71)90036-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1051485280"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112082002304", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053815642"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112071002209", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053828396"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112071002209", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053828396"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112077001189", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053934926"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112069000899", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054063351"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112069000899", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054063351"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112071000958", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054073415"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112071000958", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054073415"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112071000958", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054073415"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112071000958", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054073415"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0022112088002149", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1054076474"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1063/1.1692474", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1057764255"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1115/1.3601290", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062132625"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2019-04", 
    "datePublishedReg": "2019-04-01", 
    "description": "The computational study of MHD peristaltic motion is investigated for axisymmetric flow problem. The developed model is present in the form of partial differential equations. Then obtained partial differential equations are transferred into stream-vorticity (\u03c8\u2009-\u2009\u03c9) form. Then Galerkin Finite element method is used to find the computational results of governing problem. The current study is compared with the existing well-known results at low Reynolds number and wave number. It is revealed that the present results are in well agreement with existing results in the literature. So, it is effective for higher values of Reynolds number and wave number. The variations of streamline are present graphically against high Reynolds number. It concludes that high Reynolds number and Hartmann number increase pressure rise per unit wavelength in positive pumping region sharply.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1007/s12551-019-00511-8", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": false, 
    "isPartOf": [
      {
        "id": "sg:journal.1041162", 
        "issn": [
          "1867-2450", 
          "1867-2469"
        ], 
        "name": "Biophysical Reviews", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "2", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "11"
      }
    ], 
    "name": "Numerical study of hydromagnetic axisymmetric peristaltic flow at high Reynolds number and wave number", 
    "pagination": "139-147", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "6e5712201ae834befc07554e6335e24c11750ad95cab976ee25a13191ef854bd"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "30863983"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101498573"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1007/s12551-019-00511-8"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1112703563"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1007/s12551-019-00511-8", 
      "https://app.dimensions.ai/details/publication/pub.1112703563"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T13:31", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000370_0000000370/records_46754_00000003.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1007%2Fs12551-019-00511-8"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/s12551-019-00511-8'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/s12551-019-00511-8'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/s12551-019-00511-8'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/s12551-019-00511-8'


 

This table displays all metadata directly associated to this object as RDF triples.

151 TRIPLES      21 PREDICATES      53 URIs      21 LITERALS      9 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1007/s12551-019-00511-8 schema:about anzsrc-for:09
2 anzsrc-for:0911
3 schema:author Nfa57208db42d43148cfceb328f50f0c2
4 schema:citation https://doi.org/10.1016/0020-7225(73)90029-3
5 https://doi.org/10.1016/0021-9290(70)90051-5
6 https://doi.org/10.1016/0021-9290(71)90036-4
7 https://doi.org/10.1016/0045-7930(94)00027-v
8 https://doi.org/10.1016/j.amc.2005.04.020
9 https://doi.org/10.1016/j.amc.2006.11.035
10 https://doi.org/10.1016/j.cnsns.2007.03.013
11 https://doi.org/10.1016/j.mcm.2010.04.007
12 https://doi.org/10.1016/j.physa.2006.02.029
13 https://doi.org/10.1016/j.physleta.2007.09.061
14 https://doi.org/10.1016/j.physleta.2008.05.086
15 https://doi.org/10.1016/s0096-3003(03)00672-6
16 https://doi.org/10.1017/s0022112069000899
17 https://doi.org/10.1017/s0022112071000958
18 https://doi.org/10.1017/s0022112071002209
19 https://doi.org/10.1017/s0022112077001189
20 https://doi.org/10.1017/s0022112082002304
21 https://doi.org/10.1017/s0022112088002149
22 https://doi.org/10.1063/1.1692474
23 https://doi.org/10.1080/10618560290034681
24 https://doi.org/10.1115/1.3601290
25 https://doi.org/10.1146/annurev.fl.03.010171.000305
26 https://doi.org/10.1155/s0161171203008056
27 https://doi.org/10.1299/kikaib.56.3633
28 schema:datePublished 2019-04
29 schema:datePublishedReg 2019-04-01
30 schema:description The computational study of MHD peristaltic motion is investigated for axisymmetric flow problem. The developed model is present in the form of partial differential equations. Then obtained partial differential equations are transferred into stream-vorticity (ψ - ω) form. Then Galerkin Finite element method is used to find the computational results of governing problem. The current study is compared with the existing well-known results at low Reynolds number and wave number. It is revealed that the present results are in well agreement with existing results in the literature. So, it is effective for higher values of Reynolds number and wave number. The variations of streamline are present graphically against high Reynolds number. It concludes that high Reynolds number and Hartmann number increase pressure rise per unit wavelength in positive pumping region sharply.
31 schema:genre research_article
32 schema:inLanguage en
33 schema:isAccessibleForFree false
34 schema:isPartOf N25a0073e2a324af6acdc4ab218d9d78b
35 N43301068fb364a109feed4e5c39c61b2
36 sg:journal.1041162
37 schema:name Numerical study of hydromagnetic axisymmetric peristaltic flow at high Reynolds number and wave number
38 schema:pagination 139-147
39 schema:productId N0344bf177ef34cb0b42cdd0ee2db2f4e
40 N23d8af7815744f0dba2bb500e4e582d0
41 N3bd0a6bf01684dc291215ea5a3f811fc
42 N5a834ccc13364014b83a2bff352c592f
43 N8ded4019923a40fea377f86c3692a3bc
44 schema:sameAs https://app.dimensions.ai/details/publication/pub.1112703563
45 https://doi.org/10.1007/s12551-019-00511-8
46 schema:sdDatePublished 2019-04-11T13:31
47 schema:sdLicense https://scigraph.springernature.com/explorer/license/
48 schema:sdPublisher N42fb4ffc171240628777d8defa54bd41
49 schema:url https://link.springer.com/10.1007%2Fs12551-019-00511-8
50 sgo:license sg:explorer/license/
51 sgo:sdDataset articles
52 rdf:type schema:ScholarlyArticle
53 N0344bf177ef34cb0b42cdd0ee2db2f4e schema:name nlm_unique_id
54 schema:value 101498573
55 rdf:type schema:PropertyValue
56 N132ecc7ec6ff4471a4df9a49e9d0cd07 schema:familyName Javed
57 schema:givenName Tariq
58 rdf:type schema:Person
59 N23d8af7815744f0dba2bb500e4e582d0 schema:name doi
60 schema:value 10.1007/s12551-019-00511-8
61 rdf:type schema:PropertyValue
62 N25a0073e2a324af6acdc4ab218d9d78b schema:issueNumber 2
63 rdf:type schema:PublicationIssue
64 N3bd0a6bf01684dc291215ea5a3f811fc schema:name pubmed_id
65 schema:value 30863983
66 rdf:type schema:PropertyValue
67 N42fb4ffc171240628777d8defa54bd41 schema:name Springer Nature - SN SciGraph project
68 rdf:type schema:Organization
69 N43301068fb364a109feed4e5c39c61b2 schema:volumeNumber 11
70 rdf:type schema:PublicationVolume
71 N5a834ccc13364014b83a2bff352c592f schema:name dimensions_id
72 schema:value pub.1112703563
73 rdf:type schema:PropertyValue
74 N8849cf432e194f3f893387657fafb945 rdf:first Nf4f6bc33547046d78a9bd1bb4274a05c
75 rdf:rest rdf:nil
76 N8ded4019923a40fea377f86c3692a3bc schema:name readcube_id
77 schema:value 6e5712201ae834befc07554e6335e24c11750ad95cab976ee25a13191ef854bd
78 rdf:type schema:PropertyValue
79 Naec79e9472264e19887c2635ec3168dd rdf:first N132ecc7ec6ff4471a4df9a49e9d0cd07
80 rdf:rest N8849cf432e194f3f893387657fafb945
81 Nb6963f63af99494f93c76143afe3df09 schema:affiliation https://www.grid.ac/institutes/grid.411727.6
82 schema:familyName Hamid
83 schema:givenName A. H.
84 rdf:type schema:Person
85 Nf4f6bc33547046d78a9bd1bb4274a05c schema:affiliation https://www.grid.ac/institutes/grid.411727.6
86 schema:familyName Ali
87 schema:givenName N.
88 rdf:type schema:Person
89 Nfa57208db42d43148cfceb328f50f0c2 rdf:first Nb6963f63af99494f93c76143afe3df09
90 rdf:rest Naec79e9472264e19887c2635ec3168dd
91 anzsrc-for:09 schema:inDefinedTermSet anzsrc-for:
92 schema:name Engineering
93 rdf:type schema:DefinedTerm
94 anzsrc-for:0911 schema:inDefinedTermSet anzsrc-for:
95 schema:name Maritime Engineering
96 rdf:type schema:DefinedTerm
97 sg:journal.1041162 schema:issn 1867-2450
98 1867-2469
99 schema:name Biophysical Reviews
100 rdf:type schema:Periodical
101 https://doi.org/10.1016/0020-7225(73)90029-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048507410
102 rdf:type schema:CreativeWork
103 https://doi.org/10.1016/0021-9290(70)90051-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021337487
104 rdf:type schema:CreativeWork
105 https://doi.org/10.1016/0021-9290(71)90036-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051485280
106 rdf:type schema:CreativeWork
107 https://doi.org/10.1016/0045-7930(94)00027-v schema:sameAs https://app.dimensions.ai/details/publication/pub.1023905934
108 rdf:type schema:CreativeWork
109 https://doi.org/10.1016/j.amc.2005.04.020 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034392534
110 rdf:type schema:CreativeWork
111 https://doi.org/10.1016/j.amc.2006.11.035 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009622603
112 rdf:type schema:CreativeWork
113 https://doi.org/10.1016/j.cnsns.2007.03.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034716661
114 rdf:type schema:CreativeWork
115 https://doi.org/10.1016/j.mcm.2010.04.007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1027347566
116 rdf:type schema:CreativeWork
117 https://doi.org/10.1016/j.physa.2006.02.029 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042511564
118 rdf:type schema:CreativeWork
119 https://doi.org/10.1016/j.physleta.2007.09.061 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024362933
120 rdf:type schema:CreativeWork
121 https://doi.org/10.1016/j.physleta.2008.05.086 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047987962
122 rdf:type schema:CreativeWork
123 https://doi.org/10.1016/s0096-3003(03)00672-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051347267
124 rdf:type schema:CreativeWork
125 https://doi.org/10.1017/s0022112069000899 schema:sameAs https://app.dimensions.ai/details/publication/pub.1054063351
126 rdf:type schema:CreativeWork
127 https://doi.org/10.1017/s0022112071000958 schema:sameAs https://app.dimensions.ai/details/publication/pub.1054073415
128 rdf:type schema:CreativeWork
129 https://doi.org/10.1017/s0022112071002209 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053828396
130 rdf:type schema:CreativeWork
131 https://doi.org/10.1017/s0022112077001189 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053934926
132 rdf:type schema:CreativeWork
133 https://doi.org/10.1017/s0022112082002304 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053815642
134 rdf:type schema:CreativeWork
135 https://doi.org/10.1017/s0022112088002149 schema:sameAs https://app.dimensions.ai/details/publication/pub.1054076474
136 rdf:type schema:CreativeWork
137 https://doi.org/10.1063/1.1692474 schema:sameAs https://app.dimensions.ai/details/publication/pub.1057764255
138 rdf:type schema:CreativeWork
139 https://doi.org/10.1080/10618560290034681 schema:sameAs https://app.dimensions.ai/details/publication/pub.1018135278
140 rdf:type schema:CreativeWork
141 https://doi.org/10.1115/1.3601290 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062132625
142 rdf:type schema:CreativeWork
143 https://doi.org/10.1146/annurev.fl.03.010171.000305 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015617469
144 rdf:type schema:CreativeWork
145 https://doi.org/10.1155/s0161171203008056 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021928307
146 rdf:type schema:CreativeWork
147 https://doi.org/10.1299/kikaib.56.3633 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019717497
148 rdf:type schema:CreativeWork
149 https://www.grid.ac/institutes/grid.411727.6 schema:alternateName International Islamic University
150 schema:name Department of Mathematics and Statistics, International Islamic University Islamabad, 44000, Islamabad, Pakistan
151 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...