Panel 10. Paper 10.1: From Understanding to Action for Conservation and Sustainability of a Rural Heritage Place: Kemer, Turkey

Kemer Village, a historic rural settlement situated in western Anatolia, is a very good representative of rural heritage places of this geography. Well-preserved buildings and settlement tissue of the village, provide invaluable information about spatial and architectural features, construction materials and techniques common to this geography. However, upper scale agricultural production and settlement policies, as well as changing ways of living in time, lead to depopulation, discard, alteration and even destruction of Kemer Village. Besides the physical aspects, its intangible aspects, like local living traditions, beliefs, rituals and indigenous knowledge, are also under the risk of disappearing. Although the population of the village decreased significantly in time, there are still inhabitants and local masons living in the village. Thus, it becomes possible to understand the factors, processes and dynamics of change in this rural settlement, so as to be able to define policies, strategies and actions for the conservation and sustainability. Although the common tendency to provide an economic development to prevent depopulation of the rural historic areas is to bring touristic activities, this decision disturbs the integrity of social and physical environment. In Kemer Village this tendency has not been initiated yet. Therefore, Kemer Village is on the border of being abandoned or being a touristic destination. This presentation explains the rural architectural and settlement features of the historical village of Kemer Village, together with indigenous knowledge on living and building traditions, resources and processes. It also discusses the factors, processes and dynamics affecting Kemer Village as an historic rural settlement, and consequently, proposes principles, policies, strategies and actions for the conservation and sustainability of rural heritage place by including all the decision makers, inhabitants and experts to the shared decision-making process

A new seasonal fuzzy time series method based on the multiplicative neuron model and SARIMA

When fuzzy time series include a seasonal component, conventional fuzzy time series models are not sufficient. For such fuzzy time series, lagged variables which are around the period of the time series should also be included in the model. Determining the lagged variables which will be in the forecasting model is a vital issue. Also, defining fuzzy relations is another important issue in the fuzzy time series approach. When the number of fuzzy lagged variables is large, using artificial neural networks to define fuzzy relations makes the operations easier and increases the forecasting accuracy. In this study, in order to deal with the problem of determining the lagged variables, and defining the fuzzy relations, a novel seasonal fuzzy time series approach based on SARIMA and the multiplicative neuron model is proposed. In the proposed method, the SARIMA method is exploited to choose the fuzzy lagged variables and multiplicative neuron model is employed to establish the fuzzy relations. To show the applicability of the proposed method, it is applied to the invoice sum accrued to health service providers. For comparison, the data is also analyzed with other fuzzy time series approaches in the literature. It is observed that the proposed method has the best forecasting accuracy with respect to other methods

Hepatitis B virus genotype D prevails in patients with persistently elevated or normal ALT levels in Turkey

Background: The clinical relevance of hepatits B virus (HBV) genotypes are poorly understood and it is unclear if the prevalence of HBV genotypes differs with the various clinical features of HBV carriers. The aim of our study was to examine the prevalence of the HBV genotype in a group of patients with chronic hepatitis B, compared to a group with chronic inactive hepatits B surface antigen (HbsAg) carriers