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Institution

Epoka University

EducationTirana, Albania
About: Epoka University is a education organization based out in Tirana, Albania. It is known for research contribution in the topics: Unreinforced masonry building & Brick. The organization has 175 authors who have published 318 publications receiving 1783 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, high compressive and flexural tensile strength of alkali activated fly ash geopolymer mortars were presented, where NaOH was used as alkali medium that provides high pH value.

223 citations

Journal ArticleDOI
TL;DR: In this paper, the authors focus on the different aspects of cell microenvironment such as surface micro-, nanotopography, extracellular matrix composition and distribution, controlled release of soluble factors, and mechanical stress/strain conditions and how these aspects and their interactions can be used to achieve a higher degree of control over cellular activities.
Abstract: In tissue engineering and regenerative medicine, the conditions in the immediate vicinity of the cells have a direct effect on cells' behaviour and subsequently on clinical outcomes. Physical, chemical, and biological control of cell microenvironment are of crucial importance for the ability to direct and control cell behaviour in 3-dimensional tissue engineering scaffolds spatially and temporally. In this review, we will focus on the different aspects of cell microenvironment such as surface micro-, nanotopography, extracellular matrix composition and distribution, controlled release of soluble factors, and mechanical stress/strain conditions and how these aspects and their interactions can be used to achieve a higher degree of control over cellular activities. The effect of these parameters on the cellular behaviour within tissue engineering context is discussed and how these parameters are used to develop engineered tissues is elaborated. Also, recent techniques developed for the monitoring of the cell microenvironment in vitro and in vivo are reviewed, together with recent tissue engineering applications where the control of cell microenvironment has been exploited. Cell microenvironment engineering and monitoring are crucial parts of tissue engineering efforts and systems which utilize different components of the cell microenvironment simultaneously can provide more functional engineered tissues in the near future.

156 citations

01 Jul 2014
TL;DR: This review will focus on the different aspects of cell microenvironment such as surface micro-, nanotopography, extracellular matrix composition and distribution, controlled release of soluble factors, and mechanical stress/strain conditions and how these aspects can be used to achieve a higher degree of control over cellular activities.
Abstract: n the immediate vicinity of the cells have a direct effect on cells’ behaviour and subsequently on clinical outcomes. Physical, chemical , and biological control of cell microenvironment are of crucial importance for the ability to direct and control cell behaviour in 3-dimensional tissue engineering scaffolds spatially and temporally. In this review, we will focus on the different aspects of cell microenvironment such as surface micro-, nanotopography, extracellular matrix composition and distribution, controlled release of soluble factors, and mechanical stress/strain conditions and how these aspects and their interactions can be used to achieve a higher degree of control over cellular activities. The effect of these parameters on the cellular behaviour within tissue engineering context is discussed and how these parameters are used to develop engineered tissues is elaborated. Also, recent techniques developed for the monitoring of the cell microenvironment in vitro and in vivo are reviewed, together with recent tissue engineering applications where the control of cell microenvironment has been exploited. Cell microenvironment engineering and monitoring are crucial parts of tissue engineering efforts and systems which utilize different components of the cell microenvironment simultaneously can provide more functional engineered tissues in the near future.

124 citations

Journal ArticleDOI
TL;DR: In this article, three materials are considered in four different ways for strengthening URM walls, textile reinforced mortars (TRM) plastering, applied on one and both faces of the wall, polypropylene fiber reinforced mortar plastering (PP-FRM), and ferrocement reinforced mortar plating.

78 citations

Proceedings ArticleDOI
11 Jun 2017
TL;DR: A systematic mapping study investigates existing research about implementations of computer vision approaches based on deep learning algorithms and Convolutional Neural Networks and proposes three different research direction related to: improving existing CNN implementations, using Recurrent Neural Networks (RNNs) for human pose estimation and finally relying on unsupervised learning paradigm to train NNs.
Abstract: Deep architectures with convolution structure have been found highly effective and commonly used in computer vision. With the introduction of Graphics Processing Unit (GPU) for general purpose issues, there has been an increasing attention towards exploiting GPU processing power for deep learning algorithms. Also, large amount of data online has made possible to train deep neural networks efficiently. The aim of this paper is to perform a systematic mapping study, in order to investigate existing research about implementations of computer vision approaches based on deep learning algorithms and Convolutional Neural Networks (CNN). We selected a total of 119 papers, which were classified according to field of interest, network type, learning paradigm, research and contribution type. Our study demonstrates that this field is a promising area for research. We choose human pose estimation in video frames as a possible computer vision task to explore in our research. After careful studying we propose three different research direction related to: improving existing CNN implementations, using Recurrent Neural Networks (RNNs) for human pose estimation and finally relying on unsupervised learning paradigm to train NNs.

69 citations


Authors

Showing all 178 results

NameH-indexPapersCitations
Hanifi Binici25852386
Dorina Pojani211251556
Dimitrios A. Karras182051820
Hasan Kaplan1760987
Maaruf Ali15931194
Hüseyin Bilgin1475604
Teoman Duman1442974
Ahmet Öztaş12201072
Endrit Hoxha1241509
Mehmet Ardiclioglu1123366
Yavuz Yardim1031301
Khalid Masood924261
Ilir Nase715128
Yunus Yıldız725130
Naqeeb Ur Rehman618146
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20233
20227
202145
202054
201926
201824