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FUZZY MCDM APPROACH FOR ORAL EXAMINATION IN ERASMUS STUDENT SELECTION PROCESS

Year 2013, Issue: 032, 21 - 40, 31.12.2013

Abstract

In recent years, the mobility has become one of the most important goals of the European Union (EU). Erasmus (European Region Action Scheme for the Mobility of University Students) Program is the EU program which encourages Higher Education Institutions to cooperate with each other. This program conducts short-term exchange of students and staff. The student selection process has a critical role to achieve effectively corporations among universities which are at least one in EU. The purpose of this article is to score and rank the students at the oral examination for the Erasmus Student Mobility. The evaluation of the students by an oral examination is not easier than a written exam. The evaluation process according to an oral exam is a Multiple-Criteria Decision Making (MCDM) process including group decision-making with tangible and intangible criteria. In this study, the students were evaluated by fuzzy Analytic Hierarchy Process (AHP) method and the results obtained from fuzzy AHP were compared with the results achieved from Rubric.

References

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  • [2] V. Papatsiba, “Student mobility in Europe: An academic, cultural and mental journey? Some conceptual reflections and empirical findings”, International Perspectives on Higher Education Research, 3, 29–65, (2005).
  • [3] G. Taillefer, “Reading for academic purposes: The literacy practices of British, French and Spanish Law and Economics students as background for study abroad”, Journal of Research in Reading, 28, 435–451, (2005).
  • [4] Z.J. Wang, and K.W. Li, “Goal programming approaches to deriving interval weights based on interval fuzzy preference relations”, Information Sciences, 193, 180–198, (2012).
  • [5] T.L. Saaty, “The analytic hierarchy process”, New York: McGraw-Hill, (1980).
  • [6] C.K.Kwong, and H. Bai, “A fuzzy AHP approach to the determination of importance weights of customer requirements quality function deployment”, Journal of Intelligent Manufacturing, 13, 367- 377, (2001).
  • [7] C.S. Yu, “A GP-AHP method for solving group decision-making fuzzy AHP problems, Computers and Operations Research”, Volume 29, 14, 1969–2001, (2002).
  • [8] D.Y. Chang, “Applications of the extent analysis method on fuzzy AHP”, Eur. J. Oper. Res., 95, 649– 655, (1996).
  • [9] Z. Taha, and S. Rostam, “A hybrid fuzzy AHP-PROMETHEE decision support system for machine tool selection in flexible manufacturing cell”, Journal of Intelligent Manufacturing, 23, 2137-2149, (2012).
  • [10] A. Yazdani-Chamzini, and S.H. Yakhchali, “Tunnel Boring Machine (TBM) selection using fuzzy multicriteria decision making methods”, Tunnelling and Underground Space Technology, 30, 194-204, (2012).
  • [11] A. Samvedi, V. Jain, and F.T.S. Chan, “An integrated approach for machine tool selection using fuzzy analytical hierarchy process and grey relational analysis”, International Journal of Production Research, 50, 3211-3221, (2012).
  • [12] H.C. Rajput, A.S. Milani, and A. Labun, “Including time dependency and ANOVA in decisionmaking using the revised fuzzy AHP: A case study on wafer fabrication process selection”, Applied Soft Computing, 11, 5099-5109, (2011).
  • [13] Z. Taha, and S. Rostam, “A fuzzy AHP-ANN-based decision support system for machine tool selection in a flexible manufacturing cell”, International Journal of Advanced Manufacturing Technology, 57, 719-733, (2011).
  • [14] S. Kiris, and O. Ustun, “An integrated approach for stock evaluation and portfolio optimization”, Optimization, 61, 423-441, (2012).
  • [15] T.T. Nguyen, and L. Gordon-Brown, “Constrained Fuzzy Hierarchical Analysis for Portfolio Selection Under Higher Moments”, IEEE Transactions on Fuzzy Systems, 20, 666-682, (2002).
  • [16] C. Kubat, and B. Yuce, “A hybrid intelligent approach for supply chain management system”, Journal Of Intelligent Manufacturing, 23, 1237-1244, (2012).
  • [17] K.Shaw, R. Shankar, S.S.Yadav, and L.S.Thakur, “Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain”, Expert Systems with Applications, 39, 8182-8192, (2012).
  • [18] A.Zouggari, and L.Benyoucef, “Simulation based fuzzy TOPSIS approach for group multi-criteria supplier selection problem”, Engineering Applications of Artificial Intelligence, 25, 507-519, (2012).
  • [19] G.Buyukozkan, “An integrated fuzzy multi-criteria group decision-making approach for green supplier evaluation”, International Journal of Production Research, 50, 2892-2909, (2012).
  • [20] Z.Chen, and W.Yang, “An MAGDM based on constrained FAHP and FTOPSIS and its application to supplier selection”, Mathematical and Computer Modeling, 54, 2802-2815, (2011).
  • [21] G.N. Yucenur, O.Vayvay, and N.C. Demirel, “Supplier selection problem in global supply chains by AHP and ANP approaches under fuzzy environment”, International Journal of Advanced Manufacturing Technology, 56, 823-833, (2011).
  • [22] O.Kilincci, and S.A. Onal, “Fuzzy AHP approach for supplier selection in a washing machine company”,Expert Systems with Applications, 38, 9656-9664, (2011).
  • [23] D.Choudhary, and R.Shankar, “An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India”, Energy,42,510-521, (2012).
  • [24] A.Ozdagoglu, “A multi-criteria decision-making methodology on the selection of facility location: fuzzy ANP”, International Journal of Advanced Manufacturing Technology,59, 787-803, (2012).
  • [25] M.C. Yu,M.Goh,,and H.C. Lin, “Fuzzy multi-objective vendor selection under lean procurement”, European Journal of Operational Research, 219, 305-311, (2012).
  • [26] A.Nazari, M.M. Salarirad, and A.A. Bazzazi, “Landfill site selection by decision-making tools based on fuzzy multi-attribute decision-making method”, Environmental Earth Sciences, 65, 1631-1642, (2012).
  • [27] J.Petkovic, Z.Sevarac, M.L.Jaksic, and S.Marinkovic, “Application of fuzzy AHP method for choosing a technology within service company”, Technics Technologies Education Management- Ttem, 7, 332-341, (2012).
  • [28] V.Shahhosseini, and M.H. Sebt, “Competency-based selection and assignment of human resources to construction projects”, Scientia Iranica, 18, 163-180, (2011).
  • [29] Z.Güngör, G.Serhadlıoğlu, and S.E. Kesen, “A fuzzy AHP approach to personnel selection problem”, Applied Soft Computing, 9, 641-646, (2009).
  • [30] M.Celik, A.Kandakoglu,and D.Er, “Structuring fuzzy integrated multi-stages evaluation model on academic personnel recruitment in MET institutions”, Expert Systems with Applications, 36, 6918–6927, (2009).
  • [31] A.Ozdagoglu, “Analysis of selection criteria for manufacturing employees using fuzzy-AHP”, İşletme Fakültesi Dergisi, Cilt 9, Sayı 1,141-160, (2008).
  • [32] O.Aydın, “FMCDM for personnel assignment in Turkish Armed Forces”, Asia-Pacific Journal Operational Research, Vol. 25, No. 1,75-87, (2008).
  • [33] G. Capaldo, and G. Zollo, “Applying fuzzy logic to personnel assessment: A case study”, Omega:The International Journal Of Management Science, 29, 585-597, (2001).
  • [34] E.E. Karsak, “A fuzzy multiple objective programming approach for personnel selection”, Systems, Man, and Cybernetics, IEEE International Conference, 3, 2007–2012, (2000).
  • [35] G.S.Liang, and M.J. Wang, “Personnel placement in a fuzzy environment”, Computers & Operations Research, 19(2), 107–121, (1992).
  • [36] C.H. Yeh, “The selection of multiattribute decision making methods for scholarship student selection”, International Journal of Selection And Assessment, 11, 289-296, (2003).
  • [37] C.H.Yeh, andY.H. Chang,“Validating Multiattribute Decision Making Methods for Supporting Group Decisions”, 2008 IEEE Conference on Cybernetics And Intelligent Systems, Vols 1 and 2, 342-347,(2008).
  • [38] M.S.B. Yusoff, A.F.A.Rahim, R.A.Aziz, M.N.M. Pa, , S.C.Mey, R.Ja'afar, and Ab.R. Esa, “The Validity and Reliability of the USM Personality Inventory (USMaP-i): Its Use to Identify Personality of Future Medical Students”, International Medical Journal, 18, 283-287, (2011).
  • [39] O.Bodger, A.Byrne, P.A.Evans, S.Rees, G.Jones, C.Cowell, M.B. Gravenor, and R.Williams, “Graduate Entry Medicine: Selection Criteria and Student Performance”, Plos One, 6, e27161, (2011).
  • [40] T.Buyse, and F.Lievens, “Situational Judgment Tests as a New Tool for Dental Student Selection”, Journal of Dental Education, 75, 743-749, (2011).
  • [41] T.Altunok, O.Ozpeynirci, Y.Kazancoglu, and R.Yilmaz, “Comparative Analysis of Multicriteria Decision Making Methods for Postgraduate Student Selection”, Eğitim Araştırmaları-Eurasian Journal of Educational Research, 10, 1-15, (2010).
  • [42] D.F.Li, G.H. Chen, and Z.G. Huang, “Linear programming method for multi-attribute group decision making using IF sets”, Information Sciences, 180, 1591–1609, (2010).
  • [43] T.Y. Hsieh,S.T.Lu, and G.H.Tzeng, “Fuzzy MCDM approach for planning and design tenders selection in public office buildings”,International Journal of Project Management, 22, 573-584, (2004).
  • [44] A.Derzsi, N.Derzsy, E.Káptalan, and Z.Néda, “Topology of the Erasmus student mobility network”, Physica A390, 2601–2610, (2011).
  • [45] C.R.Gonzalez, R.B. Mesanza, and P.Mariel, “The determinants of international student mobility flows: an empirical study on the Erasmus programme”,High Educ 62:413–430, (2011).
  • [46] H.Goodrich, “Understanding Rubrics”, Educational Leadership, Vol. 54, p14-17, 4p, (1996).
  • [47] C.R.Whittaker, S.J.Salend, and D.Duhaney, “Creating Instructional Rubrics for Inclusive Classroom”, Teaching Exceptional Children, 34, 2: 8–13, (2001).
  • [48] L.M. Schreiber, D.P. Gregory, and L.R. Shibley, “The Development and Test of the Public Speaking Competence Rubric”, Communication Education, Vol. 61, No. 3, pp. 205-233, (2012).
  • [49] P.W. Airasian, “Classroom Assesment”, Mc Graw Hill, Boston College, (2001).
  • [50] G.R. Taylor, “Informal Classroom Assesment Strategies For Teachers”, The Scarecrow Pres, Lanham, Maryland, and Oxford, (2003).
  • [51] A.Campbell, “Application of ICT and Rubrics to the Assessment Process Where Professional Judgments is Involved: The Features Of An E-Marking Tool”,Assessment and Evaluation in Higher Education, 30, 5, 529–537, (2005).
  • [52] J.J. Buckley, “Ranking alternatives using fuzzy numbers”, Fuzzy Sets and Systems, 17 (1), 233-247, (1985).
  • [53] P.J.M.Laarhoven, and W.Pedrycz, “A fuzzy extension of Saaty’s priority theory”, Fuzzy Sets and Systems, 11 (3), 229-241, (1983).
  • [54] S.J.Chen, and C.L. Hwang, “Fuzzy multiple attribute decision making, methods and applications”, In: Lecture notes in economics and mathematical systems, vol. 375, New York: Springer, (1993).

ERASMUS ÖĞRENCİ SEÇİM SÜRECİNDE SÖZLÜ MÜLAKAT İÇİN BULANIK ÇOK ÖLÇÜTLÜ KARAR VERME YAKLAŞIMI

Year 2013, Issue: 032, 21 - 40, 31.12.2013

Abstract

Son yıllarda, öğrenim ve staj hareketliliği, Avrupa Birliği (AB)’nin en önemli hedeflerinden biri olmuştur. Erasmus (Üniversite Öğrencilerinin Hareketliliği için Avrupa Bölgesi Eylem Planı) Programı, Yükseköğretim Kurumları’nın karşılıklı işbirliğini teşvik eden AB programıdır. Bu program, öğrencilerin ve personelin kısa süreli değişimini yürütür. Öğrenci seçme süreci, en az biri AB’de olan üniversiteler arasındaki işbirliğini etkili bir şekilde yürütmede kritik bir role sahiptir. Makalenin amacı, Erasmus Öğrenci Hareketliliği sözlü mülakatında öğrencileri puanlamak ve sıralamaktır. Sözlü mülakatla öğrencileri değerlendirme yazılı sınavla değerlendirme kadar zordur. Bir sözlü mülakata göre değerlendirme süreci, soyut ve somut ölçütlerle grup karar vermeyi içeren Çok Ölçütlü Karar Verme (ÇÖKV) sürecidir. Bu çalışmada, öğrenciler, bulanık Analitik Hiyerarşi Süreci (AHS) yöntemi ile değerlendirildi ve bulanık AHS ile elde edilen sonuçlar, Rubrik’den elde edilen sonuçlarla karşılaştırıldı.

References

  • [1] B.C.Camiciottoli, “Meeting the challenges of European student mobility: Preparing Italian Erasmus students for business lectures in English”, English for Specific Purposes, 29, 268–280, (2010).
  • [2] V. Papatsiba, “Student mobility in Europe: An academic, cultural and mental journey? Some conceptual reflections and empirical findings”, International Perspectives on Higher Education Research, 3, 29–65, (2005).
  • [3] G. Taillefer, “Reading for academic purposes: The literacy practices of British, French and Spanish Law and Economics students as background for study abroad”, Journal of Research in Reading, 28, 435–451, (2005).
  • [4] Z.J. Wang, and K.W. Li, “Goal programming approaches to deriving interval weights based on interval fuzzy preference relations”, Information Sciences, 193, 180–198, (2012).
  • [5] T.L. Saaty, “The analytic hierarchy process”, New York: McGraw-Hill, (1980).
  • [6] C.K.Kwong, and H. Bai, “A fuzzy AHP approach to the determination of importance weights of customer requirements quality function deployment”, Journal of Intelligent Manufacturing, 13, 367- 377, (2001).
  • [7] C.S. Yu, “A GP-AHP method for solving group decision-making fuzzy AHP problems, Computers and Operations Research”, Volume 29, 14, 1969–2001, (2002).
  • [8] D.Y. Chang, “Applications of the extent analysis method on fuzzy AHP”, Eur. J. Oper. Res., 95, 649– 655, (1996).
  • [9] Z. Taha, and S. Rostam, “A hybrid fuzzy AHP-PROMETHEE decision support system for machine tool selection in flexible manufacturing cell”, Journal of Intelligent Manufacturing, 23, 2137-2149, (2012).
  • [10] A. Yazdani-Chamzini, and S.H. Yakhchali, “Tunnel Boring Machine (TBM) selection using fuzzy multicriteria decision making methods”, Tunnelling and Underground Space Technology, 30, 194-204, (2012).
  • [11] A. Samvedi, V. Jain, and F.T.S. Chan, “An integrated approach for machine tool selection using fuzzy analytical hierarchy process and grey relational analysis”, International Journal of Production Research, 50, 3211-3221, (2012).
  • [12] H.C. Rajput, A.S. Milani, and A. Labun, “Including time dependency and ANOVA in decisionmaking using the revised fuzzy AHP: A case study on wafer fabrication process selection”, Applied Soft Computing, 11, 5099-5109, (2011).
  • [13] Z. Taha, and S. Rostam, “A fuzzy AHP-ANN-based decision support system for machine tool selection in a flexible manufacturing cell”, International Journal of Advanced Manufacturing Technology, 57, 719-733, (2011).
  • [14] S. Kiris, and O. Ustun, “An integrated approach for stock evaluation and portfolio optimization”, Optimization, 61, 423-441, (2012).
  • [15] T.T. Nguyen, and L. Gordon-Brown, “Constrained Fuzzy Hierarchical Analysis for Portfolio Selection Under Higher Moments”, IEEE Transactions on Fuzzy Systems, 20, 666-682, (2002).
  • [16] C. Kubat, and B. Yuce, “A hybrid intelligent approach for supply chain management system”, Journal Of Intelligent Manufacturing, 23, 1237-1244, (2012).
  • [17] K.Shaw, R. Shankar, S.S.Yadav, and L.S.Thakur, “Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain”, Expert Systems with Applications, 39, 8182-8192, (2012).
  • [18] A.Zouggari, and L.Benyoucef, “Simulation based fuzzy TOPSIS approach for group multi-criteria supplier selection problem”, Engineering Applications of Artificial Intelligence, 25, 507-519, (2012).
  • [19] G.Buyukozkan, “An integrated fuzzy multi-criteria group decision-making approach for green supplier evaluation”, International Journal of Production Research, 50, 2892-2909, (2012).
  • [20] Z.Chen, and W.Yang, “An MAGDM based on constrained FAHP and FTOPSIS and its application to supplier selection”, Mathematical and Computer Modeling, 54, 2802-2815, (2011).
  • [21] G.N. Yucenur, O.Vayvay, and N.C. Demirel, “Supplier selection problem in global supply chains by AHP and ANP approaches under fuzzy environment”, International Journal of Advanced Manufacturing Technology, 56, 823-833, (2011).
  • [22] O.Kilincci, and S.A. Onal, “Fuzzy AHP approach for supplier selection in a washing machine company”,Expert Systems with Applications, 38, 9656-9664, (2011).
  • [23] D.Choudhary, and R.Shankar, “An STEEP-fuzzy AHP-TOPSIS framework for evaluation and selection of thermal power plant location: A case study from India”, Energy,42,510-521, (2012).
  • [24] A.Ozdagoglu, “A multi-criteria decision-making methodology on the selection of facility location: fuzzy ANP”, International Journal of Advanced Manufacturing Technology,59, 787-803, (2012).
  • [25] M.C. Yu,M.Goh,,and H.C. Lin, “Fuzzy multi-objective vendor selection under lean procurement”, European Journal of Operational Research, 219, 305-311, (2012).
  • [26] A.Nazari, M.M. Salarirad, and A.A. Bazzazi, “Landfill site selection by decision-making tools based on fuzzy multi-attribute decision-making method”, Environmental Earth Sciences, 65, 1631-1642, (2012).
  • [27] J.Petkovic, Z.Sevarac, M.L.Jaksic, and S.Marinkovic, “Application of fuzzy AHP method for choosing a technology within service company”, Technics Technologies Education Management- Ttem, 7, 332-341, (2012).
  • [28] V.Shahhosseini, and M.H. Sebt, “Competency-based selection and assignment of human resources to construction projects”, Scientia Iranica, 18, 163-180, (2011).
  • [29] Z.Güngör, G.Serhadlıoğlu, and S.E. Kesen, “A fuzzy AHP approach to personnel selection problem”, Applied Soft Computing, 9, 641-646, (2009).
  • [30] M.Celik, A.Kandakoglu,and D.Er, “Structuring fuzzy integrated multi-stages evaluation model on academic personnel recruitment in MET institutions”, Expert Systems with Applications, 36, 6918–6927, (2009).
  • [31] A.Ozdagoglu, “Analysis of selection criteria for manufacturing employees using fuzzy-AHP”, İşletme Fakültesi Dergisi, Cilt 9, Sayı 1,141-160, (2008).
  • [32] O.Aydın, “FMCDM for personnel assignment in Turkish Armed Forces”, Asia-Pacific Journal Operational Research, Vol. 25, No. 1,75-87, (2008).
  • [33] G. Capaldo, and G. Zollo, “Applying fuzzy logic to personnel assessment: A case study”, Omega:The International Journal Of Management Science, 29, 585-597, (2001).
  • [34] E.E. Karsak, “A fuzzy multiple objective programming approach for personnel selection”, Systems, Man, and Cybernetics, IEEE International Conference, 3, 2007–2012, (2000).
  • [35] G.S.Liang, and M.J. Wang, “Personnel placement in a fuzzy environment”, Computers & Operations Research, 19(2), 107–121, (1992).
  • [36] C.H. Yeh, “The selection of multiattribute decision making methods for scholarship student selection”, International Journal of Selection And Assessment, 11, 289-296, (2003).
  • [37] C.H.Yeh, andY.H. Chang,“Validating Multiattribute Decision Making Methods for Supporting Group Decisions”, 2008 IEEE Conference on Cybernetics And Intelligent Systems, Vols 1 and 2, 342-347,(2008).
  • [38] M.S.B. Yusoff, A.F.A.Rahim, R.A.Aziz, M.N.M. Pa, , S.C.Mey, R.Ja'afar, and Ab.R. Esa, “The Validity and Reliability of the USM Personality Inventory (USMaP-i): Its Use to Identify Personality of Future Medical Students”, International Medical Journal, 18, 283-287, (2011).
  • [39] O.Bodger, A.Byrne, P.A.Evans, S.Rees, G.Jones, C.Cowell, M.B. Gravenor, and R.Williams, “Graduate Entry Medicine: Selection Criteria and Student Performance”, Plos One, 6, e27161, (2011).
  • [40] T.Buyse, and F.Lievens, “Situational Judgment Tests as a New Tool for Dental Student Selection”, Journal of Dental Education, 75, 743-749, (2011).
  • [41] T.Altunok, O.Ozpeynirci, Y.Kazancoglu, and R.Yilmaz, “Comparative Analysis of Multicriteria Decision Making Methods for Postgraduate Student Selection”, Eğitim Araştırmaları-Eurasian Journal of Educational Research, 10, 1-15, (2010).
  • [42] D.F.Li, G.H. Chen, and Z.G. Huang, “Linear programming method for multi-attribute group decision making using IF sets”, Information Sciences, 180, 1591–1609, (2010).
  • [43] T.Y. Hsieh,S.T.Lu, and G.H.Tzeng, “Fuzzy MCDM approach for planning and design tenders selection in public office buildings”,International Journal of Project Management, 22, 573-584, (2004).
  • [44] A.Derzsi, N.Derzsy, E.Káptalan, and Z.Néda, “Topology of the Erasmus student mobility network”, Physica A390, 2601–2610, (2011).
  • [45] C.R.Gonzalez, R.B. Mesanza, and P.Mariel, “The determinants of international student mobility flows: an empirical study on the Erasmus programme”,High Educ 62:413–430, (2011).
  • [46] H.Goodrich, “Understanding Rubrics”, Educational Leadership, Vol. 54, p14-17, 4p, (1996).
  • [47] C.R.Whittaker, S.J.Salend, and D.Duhaney, “Creating Instructional Rubrics for Inclusive Classroom”, Teaching Exceptional Children, 34, 2: 8–13, (2001).
  • [48] L.M. Schreiber, D.P. Gregory, and L.R. Shibley, “The Development and Test of the Public Speaking Competence Rubric”, Communication Education, Vol. 61, No. 3, pp. 205-233, (2012).
  • [49] P.W. Airasian, “Classroom Assesment”, Mc Graw Hill, Boston College, (2001).
  • [50] G.R. Taylor, “Informal Classroom Assesment Strategies For Teachers”, The Scarecrow Pres, Lanham, Maryland, and Oxford, (2003).
  • [51] A.Campbell, “Application of ICT and Rubrics to the Assessment Process Where Professional Judgments is Involved: The Features Of An E-Marking Tool”,Assessment and Evaluation in Higher Education, 30, 5, 529–537, (2005).
  • [52] J.J. Buckley, “Ranking alternatives using fuzzy numbers”, Fuzzy Sets and Systems, 17 (1), 233-247, (1985).
  • [53] P.J.M.Laarhoven, and W.Pedrycz, “A fuzzy extension of Saaty’s priority theory”, Fuzzy Sets and Systems, 11 (3), 229-241, (1983).
  • [54] S.J.Chen, and C.L. Hwang, “Fuzzy multiple attribute decision making, methods and applications”, In: Lecture notes in economics and mathematical systems, vol. 375, New York: Springer, (1993).
There are 54 citations in total.

Details

Primary Language English
Subjects Engineering, Industrial Engineering
Journal Section Articles
Authors

Harun Taşkın

Özden Üstün

Derya Deliktaş

Publication Date December 31, 2013
Published in Issue Year 2013 Issue: 032

Cite

APA Taşkın, H., Üstün, Ö., & Deliktaş, D. (2013). FUZZY MCDM APPROACH FOR ORAL EXAMINATION IN ERASMUS STUDENT SELECTION PROCESS. Journal of Science and Technology of Dumlupınar University(032), 21-40.

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