This study examined the effect of altitude on bending creep behavior of hornbeam lumber (Carpinus betulus). For this purpose, 9 hornbeam trees from three different altitudes (400, 800 and 1100 m) in ...the northern forests of Iran were selected. Clear samples were cut from mature wood in diameter at breast height (DBH). 108 prepared samples (dimensions: 2.5 × 2.5 × 41 cm) were conditioned at room temperature of 20 ºC and two relative humidities (RH) of 65 % and 95 %. First, the maximum bending load was determined by three-point static bending tests in acclimatized room and then flexural creep parameters, such as relative creep, creep modulus and creep factor, at 20 % of the maximum bending load, were calculated. Results indicated that at 65 % RH, the effect of altitude on creep parameters was significant. The maximum values of relative creep and creep factor were observed at the altitude of 800 m, and the minimum values at the altitude of 400 m. The maximum values of creep modulus were observed at the altitude of 400 m and the minimum values at the altitude of 800 m. Also, at 95 % RH, the effect of altitude on creep modulus was significant but it was not significant on relative creep and creep factor. The maximum creep modulus was observed at the altitude of 400 and the minimum at the altitude of 800 m.
This study aimed to investigation the effect of altitude on the bending creep behavior of hornbeam lumber (Carpinus betuluse). For this purpose, 9 hornbeam trees from three different altitudes (400, ...800 and 1100m) from forestry projects of Meshelak Nowshahr were selected. 54 Clear samples were cut at mature wood in diameter breast height (DBH). The prepared samples (dimensions: 2.5 × 2.5 × 41cm) in a room at temperature of 20 C and relative humidity (RH) 65 % were conditioned. Afterward 3 weeks conditioning, relative creep and creep modulus using the four points flexural creep test in 20% maximum of deflection load were measured. Results indicated that, the effects of altitude on creep parameters was significant so as the maximum and the minimum relative creep observed in 800 and 400m altitudes, and the maximum and the minimum creep modulus observed in 400 and 800m altitudes, respectively. Analysis of variance (ANOVA) results indicated that the altitude has significant effect on the flexural strength and modulus of elasticity, which in turn caused decreasing the creep parameters.
U radu su prikazani rezultati istraživanja utjecaja nadmorske visine staništa stabala na puzanje drva graba (Carpinus betuluse) pri savijanju. Za istraživanje je odabrano devet stabala graba iz šuma ...na sjeveru Irana, i to na tri različite lokacije – nanadmorskoj visini 400, 800 i 1100 m. Uzeti su čisti uzorci zrelog drva na visini prsnog promjera (DBH). Ukupno 108 pripremljenih uzoraka (dimenzija 2,5 × 2,5 × 41 cm) kondicionirano je pri sobnoj temperaturi od 20 °C i uz dvije relativne vlažnosti zraka (RH), 65 i 95 %. Najprije je napravljen statički test savijanja u tri točke te određeno maksimalno opterećenje (čvrstoća na savijanje) u aklimatiziranoj prostoriji. Potom su izračunani parametri puzanja pri savijanju kao što su relativno puzanje, modul puzanja i faktor puzanja u području 20 % maksimalnog opterećenja savijanja. Rezultati istraživanja na uzorcima kondicioniranim pri 65 % relativne vlažnosti zraka pokazali su da je utjecaj nadmorske visine na parametre puzanja bio značajan. Maksimalne vrijednosti relativnog puzanja i faktora puzanja zabilježene su za uzorke s nadmorske visine 800 m, a minimalne vrijednosti za uzorke s nadmorske visine 400 m. Maksimalne vrijednosti modula puzanja zabilježene su za uzorske drva s nadmorske visine 400 m, a minimalne za one s nadmorske visine 800 m. Također, na uzorcima kondicioniranim pri 95 % relativne vlažnosti zraka utjecaj nadmorske visine na modul puzanja bio je značajan, ali se taj utjecaj nije pokazao značajnim za parametre relativnog puzanja i faktora puzanja. Najveći modul puzanja zabilježen je na uzorcima s nadmorske visine 400 m, a najmanji na uzorcima s nadmorske visine 800 m.
As long as a computer system is connected to the Internet, it is susceptible to attack as a victim. In computer networks, it becomes important to manage the network based on parameters such as ...network size and network data. Firewalls are devices that help network administrators in this case to establish security in the network, and can be based on the rules that the firewall is based on. It is configured to control incoming and outgoing network traffic. Firewalls can be considered the most vital components of the network in establishing security. Firat University introduced a dataset containing firewall logs with multiple classes for firewall decisions. This study uses data mining techniques to improve the validation performance of classification using various machine learning algorithms like neural networks, deep learning, and kNN. The experimental results show more than 10% improvement according to precision and recall rates among various folding scenarios used in related works with minor improvement in accuracy, too. The decision tree algorithm is fast and explainable versus other algorithms.
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