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Institution

Istanbul Technical University

EducationIstanbul, Turkey
About: Istanbul Technical University is a education organization based out in Istanbul, Turkey. It is known for research contribution in the topics: Fuzzy logic & Large Hadron Collider. The organization has 12889 authors who have published 25081 publications receiving 518242 citations. The organization is also known as: İstanbul Teknik Üniversitesi & Technical University of Istanbul.


Papers
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Journal ArticleDOI
TL;DR: The anisotropy parameter (v2) of the particles is extracted by correlating charged tracks with respect to the event-plane reconstructed by using the energy deposited in forward-angle calorimeters, with the decline persisting up to at least pp(T)=40 GeV/c over the full centrality range measured.
Abstract: The azimuthal anisotropy of charged particles in PbPb collisions at nucleon-nucleon center-of-mass energy of 2.76 TeV is measured with the CMS detector at the LHC over an extended transverse momentum (pt) range up to approximately 60 GeV. The data cover both the low-pt region associated with hydrodynamic flow phenomena and the high-pt region where the anisotropies may reflect the path-length dependence of parton energy loss in the created medium. The anisotropy parameter (v2) of the particles is extracted by correlating charged tracks with respect to the event-plane reconstructed by using the energy deposited in forward-angle calorimeters. For the six bins of collision centrality studied, spanning the range of 0-60% most-central events, the observed v2 values are found to first increase with pt, reaching a maximum around pt = 3 GeV, and then to gradually decrease to almost zero, with the decline persisting up to at least pt = 40 GeV over the full centrality range measured.

142 citations

Journal ArticleDOI
TL;DR: In this article, a new approach based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is presented to overcome the supplier selection problem, where criteria that are determined for the problem are reduced by applying ANFIS input selection method.
Abstract: Supplier selection is a key task for firms, enabling them to achieve the objectives of a supply chain. Selecting a supplier is based on multiple conflicting factors, such as quality and cost, which are represented by a multi-criteria description of the problem. In this article, a new approach based on Adaptive Neuro-Fuzzy Inference System (ANFIS) is presented to overcome the supplier selection problem. First, criteria that are determined for the problem are reduced by applying ANFIS input selection method. Then, the ANFIS structure is built using data related to selected criteria and the output of the problem. The proposed method is illustrated by a case study in a textile firm. Finally, results obtained from the ANFIS approach we developed are compared with the results of the multiple regression method, demonstrating that the ANFIS method performed well.

142 citations

Journal ArticleDOI
TL;DR: Diels-Alder and hetero Diels–Alder reactions offer alternative pathways which allow for similarly efficient macromolecular conjugations, and combinations of these protocols afford the synthesis of more complex star polymer structures which previously had not been achievable.

142 citations

Journal ArticleDOI
TL;DR: This study tries to develop a multicriteria decision-making model which considers both the complexity and vagueness of strategic decisions.
Abstract: Strategic decisions such as mergers, acquisitions and joint ventures have a strong effect on firm performance. In order to be successful in highly competitive environments firms have to make right and on time strategic decisions. However, the nature of making the right strategic decision is complex and unstructured since there are many factors affecting such decisions. Moreover these factors are usually hard and vague to evaluate numerically. This study tries to develop a multicriteria decision-making model which considers both the complexity and vagueness of strategic decisions. The weights of the factors are determined by interval type-2 Fuzzy Analytic Hierarchy Process (AHP) and then the best strategy is selected by Hesitant Fuzzy TOPSIS using the determined weights. An application to a multinational consumer electronics company is presented.

142 citations

Journal ArticleDOI
TL;DR: In this article, a secondary infall model that takes into account the effect of ordered and random angular momentum, dynamical friction, and baryons adiabatic contraction (AC) is applied to structures on galactic scales and on clusters of galaxies scales.
Abstract: We study the cusp/core problem using a secondary infall model that takes into account the effect of ordered and random angular momentum, dynamical friction, and baryons adiabatic contraction (AC). The model is applied to structures on galactic scales (normal and dwarfs spiral galaxies) and on clusters of galaxies scales. Our analysis suggest that angular momentum and dynamical friction are able, on galactic scales, to overcome the competing effect of AC eliminating the cusp. The slope of density profile of inner halos flattens with decreasing halo mass and the profile is well approximated by a Burkert's profile. In order to obtain the Navarro-Frenk-White (NFW) profile, starting from the profiles obtained from our model, the magnitude of angular momentum and dynamical friction must be reduced with respect to the values predicted by the model itself. The rotation curves of four lower sideband galaxies from Gentile et al. are compared to the rotation curves obtained by the model in the present paper obtaining a good fit to the observational data. The time evolution of the density profile of a galaxy of 108-109 M ☉ shows that after a transient steepening, due to the AC, the density profile flattens to α 0. On cluster scales we observe a similar evolution of the dark matter (DM) density profile but in this case the density profile slope flattens to α 0.6 for a cluster of 1014 M ☉. The total mass profile, differently from that of DM, shows a central cusp well fitted by an NFW model.

141 citations


Authors

Showing all 13155 results

NameH-indexPapersCitations
David Miller2032573204840
H. S. Chen1792401178529
Hyun-Chul Kim1764076183227
J. N. Butler1722525175561
Andrea Bocci1722402176461
Bradley Cox1692150156200
Yang Gao1682047146301
J. E. Brau1621949157675
G. A. Cowan1592353172594
David Cameron1541586126067
Andrew D. Hamilton1511334105439
Jongmin Lee1502257134772
A. Artamonov1501858119791
Teresa Lenz1501718114725
Carlos Escobar148118495346
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023137
2022338
20211,860
20201,772
20191,834
20181,643