Technological Educational Institute of Western Macedonia

About: Technological Educational Institute of Western Macedonia is a based out in . It is known for research contribution in the topics: Catalysis & Symplectic geometry. The organization has 291 authors who have published 522 publications receiving 7682 citations. The organization is also known as: TEI of West Macedonia & TEI of Western Macedonia.

Social network analysis and social capital in marketing: theory and practical implementation

Abstract: The application of social network analysis in marketing can provide marketers with valuable insights for developing communication and branding strategies by building up social capital in social networking sites (SNSs) as Facebook. In this paper, the main characteristics and definitions of social capital and social network analysis (SNA) are reviewed and discussed, including the importance of social capital for marketing and branding in SNSs. SNA is used to analyse the network structure of a famous Greek brand page, and the activity (comments) of its members during a period of two months in 2013. The interactions between consumers, the content generated by the firm and the posts commenting on this content are presented and analysed in terms of SNA and marketing, highlighting the importance of content creation in attracting users to like and comment increasing engagement. The implications and applications of the use of SNA results and of social capital as a way of building brand loyalty in marketing decisions and planning are discussed, and suggestions for further research are offered.

Combination of high resolution melting (HRM) analysis and SSR molecular markers speeds up plum genotyping: case study genotyping the Greek plum GeneBank collection

Abstract: In a germplasm bank collection the conservation and characterization of genetic resources is a prerequisite in order to use the material in breeding projects aiming the creation of new cultivars. In the present study, 54 Prunus salicina domestica and Prunus domestica genotypes (including seven Greek cultivars), maintained in the ex situ National Genebank Collection of Greece, were classified using microsatellite (simple sequence repeat, SSR) markers on high resolution melting (HRM) analysis. The SSR primer pairs were chosen from the published literature as originally designed on Prunus species. This combined approach was used to genotype all plum accessions of the collection highlighting the benefits of either method (HRM and SSRs) for cultivar identification. Dendrograms for P. domestica and P. salicina and a combined one with all the genotypes assayed were produced. A total of 15 from the 19 P. domestica accessions analysed, including all the Greek accessions but ‘Avgati Skopelou’, were grouped into the same clade in the combined dendrogram, whereas the remaining four were dispersed into the P. salinica clades. Bayesian structure analysis confirmed that ‘Avgati Skopelou’ differs from the rest of the Greek plum cultivars since it was not grouped into the same cluster. The combination of HRM and SSRs, provided a considerably faster, cost-effective, closed-tube microsatellite genotyping method for molecular characterization of plum cultivars.

A hybrid ANN/GA/ANFIS model for very short-term PV power forecasting

Abstract: The aim of this work is to develop a robust model for short-term prediction of Photovoltaics (PV) generation. The model is structured with algorithms that belong to the technical field of computational intelligence. This approach provides the potential to form a forecasting system with high flexibility, efficiency and customization. The paper examines various combinations of inputs, in order to fully investigate the influence of exogenous variables on the PV predicted time series. Simulation results indicate that the proposed model can be successfully implemented in the decision making process of retailers, distribution system operators, prosumers and others, to fully exploit the generation capacity of grid connected PV systems in day-ahead electricity markets. Out of the different combinations of inputs studied, the one that involves the panels' temperature together with historical PV power values lead to lower predictions errors.

Performance and evaluation of a coupled prognostic model TAPM over a mountainous complex terrain industrial area

Abstract: Atmospheric modeling is considered an important tool with several applications such as prediction of air pollution levels, air quality management, and environmental impact assessment studies. Therefore, evaluation studies must be continuously made, in order to improve the accuracy and the approaches of the air quality models. In the present work, an attempt is made to examine the air pollution model (TAPM) efficiency in simulating the surface meteorology, as well as the SO2 concentrations in a mountainous complex terrain industrial area. Three configurations under different circumstances, firstly with default datasets, secondly with data assimilation, and thirdly with updated land use, ran in order to investigate the surface meteorology for a 3-year period (2009–2011) and one configuration applied to predict SO2 concentration levels for the year of 2011.The modeled hourly averaged meteorological and SO2 concentration values were statistically compared with those from five monitoring stations across the domain to evaluate the model’s performance. Statistical measures showed that the surface temperature and relative humidity are predicted well in all three simulations, with index of agreement (IOA) higher than 0.94 and 0.70 correspondingly, in all monitoring sites, while an overprediction of extreme low temperature values is noted, with mountain altitudes to have an important role. However, the results also showed that the model’s performance is related to the configuration regarding the wind. TAPM default dataset predicted better the wind variables in the center of the simulation than in the boundaries, while improvement in the boundary horizontal winds implied the performance of TAPM with updated land use. TAPM assimilation predicted the wind variables fairly good in the whole domain with IOA higher than 0.83 for the wind speed and higher than 0.85 for the horizontal wind components. Finally, the SO2 concentrations were assessed by the model with IOA varied from 0.37 to 0.57, mostly dependent on the grid/monitoring station of the simulated domain. The present study can be used, with relevant adaptations, as a user guideline for future conducting simulations in mountainous complex terrain.