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In this study the thermal conductivity of different wood materials was determined. For this purpose, Scots pine (Pinus sylvestris L.), Uludag fir (Abies Bornmülleriana Matff), Oriental beech (Fagus orientalis L), Oak (Quercus robur L.), and Chestnut of Anatolia (Castanea sativa Mill.) woods were used. In the test, the thermal conductivity of the woods was measured according to procedure of ASTM C 1113-99 standards. The lowest thermal conductivity was obtained in the perpendicular direction of Scots pine samples as 0.156 Kcal/mh°C. The highest thermal conductivity was obtained from perpendicular direction of samples in Oriental beech as 0.331 Kcal/mh°C.

WOS: 000389620600007 This research investigates the prediction of modulus of elasticity (MOE) properties, which is the most important properties in many applications, of the oriented strand board (OSB) produced under different conditions (pressing time, pressing pressure, pressing temperature and adhesive ratios) by multiple regression, artificial neural network (ANN) and adaptive Neurofuzzy inference system (ANFIS). Software computing techniques are now being used instead of statistical methods. It was found that the constructed ANFIS exhibited a higher performance than multiple regression and ANN for predicting MOE.Software computing techniques are very useful for precision industrial applications and, also determining which method gives the highest accurate result. TUBITAK (The Scientific and Technological Research Council of Turkey)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [111O290] This research project would not have been possible without the support of organization. So, this research was supported by TUBITAK (The Scientific and Technological Research Council of Turkey, project number: 111O290). I offer my sincere appreciation for the provided opportunities by this government agency.