Application of fuzzy AHP approach to selection of organizational structure with consideration to contextual dimensions

The literature of organizational structure design is relatively rich along with conceptual and complex patterns. This complexity arising from the number of elements and numerous relations in addition to the nature of variables. Thereby, the lack of operational decision-making models is felt to propose adequate structural designs in practice. In this article, the researchers employ a fuzzy multi attribute decision making model (FMADM) to select the most suitable organizational structure based on expert’s judgments and by deploying contextual dimensions of the organization. Since the organizational changes especially in the structural levels are along with resistances among involved staffs, the implementation of this model is a supportive tool in addition to help the managers to make a qualified decision and change.©2012 the Authors. Published by De Gruyter Open. Open Access under the Creative Commons Attribution–NonCommercial–NoDerivatives 4.0 International (CC BY–NC–ND 4.0) license, https://creativecommons.org/licenses/by-nc-nd/4.0/fi=vertaisarvioitu|en=peerReviewed

Knowledge sharing: a survey, assessment and directions for future research: individual behavior perspective

One of the most important areas of knowledge management studies is knowledge sharing. Measured in terms of number of scientific articles and organization-s applications, knowledge sharing stands as an example of success in the field. This paper reviews the related papers in the context of the underlying individual behavioral variables to providea direction framework for future research and writing.©2012 World Academy of Science, Engineering and Technology. Open Access under the Creative Commons Attribution(CC BY) license, https://creativecommons.org/licenses/by/4.0/. Anyone may copy, distribute, or reuse these articles, as long as the author and original source are properly cited.fi=vertaisarvioitu|en=peerReviewed

Prestressed Concrete Thermal Behaviour

The structural fire safety capacity of concrete is very complicated because concrete materials have considerable variations. Constitutive relationships for prestressed normal-strength concrete (NSC) and high-strength concrete (HSC) subjected to fire are needed to provide efficient modelling and to meet specific fire-performance criteria of the behaviour for prestressed concrete structures exposed to fire. In this paper, formulations for estimating the parameters affecting the behaviour of unconfined prestressed concrete at high temperatures are proposed. These formulations include residual compression strength, initial modulus of elasticity, peak strain, thermal strain, transient creep strain and the compressive stressstrain relationship at elevated temperatures. The proposed constitutive relationships are verified with available experimental data and existing models. The proposed relationships are general and rational, and show good agreement with the experimental data. More tests are needed to further verify and improve the proposed constitutive relationships

Experimental and numerical study of time-dependent behaviour of reinforced self-compacting concrete slabs

University of Technology, Sydney. Faculty of Engineering and Information Technology.Developments in concrete technology provide engineers, designers, suppliers and contractors with new methods of approaching engineering problems. Many of these developments are engineered solutions to technical and commercial problems, by either improving the current practices or overcoming limitations in the existing technology. One of the developments is Self-Compacting Concrete (SCC). SCC refers to a ‘highly flowable, non-segregating concrete that can be spread into place, fill the formwork, and encapsulate the reinforcement without the aid of any mechanical consolidation’ as defined by the American Concrete Institute (ACI). SCC is regarded as one of the most promising developments in concrete technology due to significant advantages over Conventional Concrete (CC). Many different factors can influence a decision to adopt SCC over CC ranging from structural performance to associated costs. These decisions should be well informed and based on a sound understanding of such factors. In addition, Fibre Reinforced Self-Compacting Concrete (FRSCC) is a relatively new composite material which congregates the benefits of the SCC technology with the profits derived from the fibre addition to a brittle cementitious matrix. Fibres improve many of the properties of SCC elements including tensile strength, ductility, toughness, energy absorption capacity, fracture toughness and cracking. For a structure (made by CC, SCC and FRSCC) to remain serviceable, crack widths must be small enough to be acceptable from an aesthetic point of view, to avoid waterproofing and deterioration problems by preventing the ingress of water and harmful substances. Crack control is therefore an important aspect of the design of reinforced concrete structures at the serviceability limit state. Limited researches have been undertaken to understand cracking and crack control of SCC and FRSCC members. Since, the time-dependent mechanisms of SCC and FRSCC are still not completely understood; a reliable and universally accepted design procedure for cracking and crack control SCC and FRSCC members has not been developed yet. There exists a need for both theoretical and experimental research to study the critical factors which affect the time-dependant crack of SCC and FRSCC members. In this study cracking caused by external loads in reinforced SCC and FRSCC slabs is examined experimentally and analytically. The mechanisms associated with the flexural cracking due to the combined effects of constant sustained service loads and shrinkage are observed. One of the primary objectives of this study is to develop analytical models that accurately predict the hardened mechanical properties of SCC and FRSCC. Subsequently, these models have been successfully applied to simulate time-dependent cracking of SCC and FRSCC one-way slabs. Series of tests on eight prismatic, singly reinforced concrete one-way slabs subjected to monotonically increasing loads or to constant sustained service loads for up to 240 days, were conducted. An analytical model is presented to simulate instantaneous and time-dependant flexural cracking of SCC and FRSCC members. It should be emphasized that any analytical model developed for calculation of crack width and crack spacing of reinforced SCC and FRSCC slabs must be calibrated by experimental data and verified by utilizing Finite Element Method (FEM). The analytical predictions of crack width and crack spacing for the SCC and FRSCC one way slabs are in reasonably good agreement with the experimental observations

Effects of specimen size and shape on compressive and tensile strengths of selfcompacting concrete with or without fibres

Self-compacting concrete (SCC) can be placed and compacted under its own weight. Modifications in the mix design of SCC may significantly influence the material's mechanical properties. Therefore, it is vital to investigate whether all the assumed hypotheses about conventional concrete also hold true for SCC structures. This paper discusses an experimental programme that was carried out to study the effects of specimen size and shape on the compressive and tensile strength of SCC and fibre reinforced SCC. For this purpose, cube specimens with 100 and 150 mm dimensions and cylinder specimens with 100 3 200 and 150 3 300 mm dimensions were casted. The experimental programme examined four SCC mixtures: plain SCC, and steel-, polypropylene- and hybrid-fibre reinforced SCC. Compressive and tensile strengths were tested after 3, 7, 14, 28 and 56 days. The paper also investigates correlations between compressive and tensile strengths and the size and shape of the specimen

Deep learning approaches for segmentation of multiple sclerosis lesions on brain MRI

Multiple Sclerosis (MS) is a demyelinating disease of the central nervous system which causes lesions in brain tissues, especially visible in white matter with magnetic resonance imaging (MRI). The diagnosis of MS lesions, which is often performed visually with MRI, is an important task as it can help characterizing the progression of the disease and monitoring the efficacy of a candidate treatment. automatic detection and segmentation of MS lesions from MRI images offer the potential for a faster and more cost-effective performance which could also be immune to expert bias segmentation. In this thesis, we study automated approaches to segment MS lesions from MRI images. The thesis begins with a review of the existing literature on MS lesion segmentation and discusses their general limitations. We then propose three novel approaches that rely on Convolutional Neural Networks (CNNs) to segment MS lesions. The first approach demonstrates that the parameters of a CNN learned from natural images, transfer well to the tasks of MS lesion segmentation. In the second approach, we describe a novel multi-branch CNN architecture with end-to-end training that can take advantage of each MRI modalities individually. In that work, we also investigated the combination of MRI modalities leading to the best segmentation performance. In the third approach, we show an effective and novel generalization method for MS lesion segmentation when data are collected from multiple MRI scanning sites and as suffer from (site-)domain shifts. Finally, this thesis concludes with open questions that may benefit from future work. This thesis demonstrates the potential role of CNNs as a common methodological building block to address clinical problems in MS segmentation