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CONGRUENCE BETWEEN ACTUAL/SOCIAL SELF-IMAGES, AND BRAND IMAGES OF PREFERRED HOTELS
Young-Jun YOO,Alexander GRUNEWALD 세계문화관광학회 2007 Conference Proceedings Vol.8 No.0
This study's purpose is twofold: (1) to examine how the self-images of hotel users are related to the brand images of their preferred hotels, and (2) to examine the level of congruity between actual/social self-images and preferred hotels' images. It was found that generally self-images (i.e. actual and social), as rated by the respondents do not significantly differ, but significant deviations were found in specific attributes. Social self-image shows higher positive congruity with hotels' brand image than the consumers' actual self-image. It is suggested that from a marketing standpoint a consumer's social self-image is of greater importance, than the actual self-image.
Modelling fresh properties of self-compacting concrete using neural network technique
Mohammed Sonebi,Steffen Grunewald,Abdulkadir Cevik,Joost Walraven 사단법인 한국계산역학회 2016 Computers and Concrete, An International Journal Vol.18 No.4
The purpose of this paper is to investigate the feasibility of using artificial neural network programming for the prediction of the fresh properties of self-compacting concrete. The input parameters of the neural network were the mix composition influencing the fresh properties of self-compacting concrete namely, the cement content, the dosages of limestone powder and water, fine aggregate, coarse aggregate, and superplasticizer, and other parameter of time of testing (5, 30 and 60 minutes after addition of water). The model is based on a multilayer feed forward neural network. The details of the proposed ANN with its architecture, training and validation are presented in this paper. Six outputs of the ANN models related to the fresh properties were the slump flow, T50, T60, V-funnel flow time, Orimet flow time, and blocking ratio (L-box). The effectiveness of the trained ANN is evaluated by comparing its responses with the experimental data that were used in the training process. The dosage of water was varied from 188 to 208 L/m3, the dosage of SP from 3.8 to 5.8 kg/m3, and the volume of coarse aggregates from 220 to 360 L/m3 (587 to 961 kg/m3). In total twenty mixes were used to measure the fresh properties with different mix compositions. ANN performed well and provided very good correlation coefficients (R2) above 0.957 for slump flow, T50, V-funnel flow time, Orimet flow time, and L-box blocking ratio. The predicting results for T60 was slightly lower (R2=0.823). With the calculated models these properties of new mixes within the practical range of the input variables used in the training can be predicted with an absolute error for slump flow, T50, T60, V-funnel flow time, Orimet flow time, and L-box ratio of 3.3%, 13%, 16%, 14%, 15%, and 22%, respectively. The results show that the ANN model can predict accurately the fresh properties of SCC.
Stier, Sebastian,Totzke, Gudrun,Grunewald, Elisabeth,Neuhaus, Thomas,Fronhoffs, Stefan,Schoneborn, Silke,Vetter, Hans,Ko, Yon Korean Society for Biochemistry and Molecular Biol 2005 Journal of biochemistry and molecular biology Vol.38 No.4
TNF-$\alpha$ plays a pivotal role in inflammation processes which are mainly regulated by endothelial cells. While TNF-$\alpha$ induces apoptosis of several cell types like tumor cells, endothelial cells are resistant to TNFa mediated cell death. The cytotoxic effects of TNF-$\alpha$ on most cells are only evident if RNA or protein synthesis is inhibited, suggesting that de novo RNA or protein synthesis protect cells from TNF-$\alpha$ cytotoxicity, presumably by NF-${\kappa}B$ mediated induction of protective genes. However, the cytoprotective genes involved in NF-${\kappa}B$ dependent endothelial cell survival have not been sufficiently identified. In the present study, the suppression subtractive hybridization (SSH) method was employed to identify rarely transcribed TNF-$\alpha$ inducible genes in human arterial endothelial cells related to cell survival and cell cycle. The TNF-$\alpha$-induced expression of the RNA binding protein $p54^{nrb}$ and the 14-3-3 protein HS1 as shown here for the first time may contribute to the TNF-$\alpha$ mediated cell protection of endothelial cells. These genes have been shown to play pivotal roles in cell survival and cell cycle control in different experimental settings. The concerted expression of these genes together with other genes related to cell protection and cell cycle like DnaJ, $p21^{cip1}$ and the ubiquitin activating enzyme E1 demonstrates the identification of new genes in the context of TNF-$\alpha$ induced gene expression patterns mediating the prosurvival effect of TNF-$\alpha$ in endothelial cells.