The failure of cracking is one of the main concerns regarding the performance of hot mix asphalt (HMA). Since the characteristic of the materials of the mixtures has impact on their cracking potential, the main conception of this research is to evaluate the effect of the type of size and additive percentage of crumb rubber modified (CRM) on the resistance of mixtures to crack at mid and low temperatures. For this purpose, rubber bitumen containing 10% and 15% crumb rubber with fine and coarse sizes with wet process was prepared. Asphalt mixtures with dense and gap grading were designed by using rubber bitumen produced by superpave method. The three-points bending test of semicircle bending sample (SCB) was used to evaluate the fracture characteristics of asphalt mixtures at low and middle temperatures (25°C and -12°C). Accordingly, the failure characteristics of asphalt mixtures were evaluated in two modes with short-term and long-term aging. The failure test results indicated that the produced mixtures with crumb rubbers additive have high resourcing resistance compared to control mixtures (without crumb rubber additive), were also revealed. Mixtures with dense grading and fine crumb rubber have high fracture resistance compared to mix with gap grading and coarse crumb rubber. Also, the increasing of the percentage of crumb rubber improved the resistance of the mixed failure. In general, it can be stated that the addition of crumb rubber increases the fracture resistance of asphalt mixtures which can improve its performance before cracking at mid and low temperatures.

ÖzetBu çalışmada; makaleye konu olarak ele alınan Afganistan'ın önemli bir şehri olan Mezar-ı-şerifte bulunan iki kavşakdaki mevcut durum ve sinyalize sistemle revize edilerek elde edilen yeni yapı, geometrik durumda yapılan değişiklikler de dikkate alınarak iki farklı VISSIM ve SIDRA yazılımları kullanılarak, gecikme süreleri ve kuyruklama uzunlukları ile ilgili parametreler çerçevesinde analiz edilmiştir. Bu anlamda, mevcut durum ve geometrik iyileştirme senaryolarına dahil edilen sinyal koordinasyonu ile, şimdiki ve gelecekteki gecikme süreleri ve kuyruk uzunluklarının azaltılması sayesinde trafik açısından hizmet seviyesinin iyileştirilmesi içerikli analizler yapılmıştır.Araştırmada elde edilen bulgulara göre, geometrik tasarım iyileştirilmesinden önce incelenen birinci ve ikinci kavşak arasında koordinasyon sağlanması durumunda, sistem için toplam taşıt gecikmelerinde yüzde 3,36'a varan düşüşler görülmüştür. Geometrik tasarım iyileştirildikten sonra ise sistem için toplam taşıt gecikmelerinde yüzde 8,85'a varan iyileştirmeler görülmüştür. Mevcut durum ile iyileştirilmiş durum kıyaslandığında, iyileştirilmiş durumda koordinasyon öncesi sistem (ağ) için toplam taşıt gecikmelerinde yüzde 51,78'a, koordinasyon sonrası ise toplam taşıt gecikmelerinde de yüzde 54,51'e ulaşan düşüşler görülmüştür.In this study; delay times and queue length parameters were analysed for the new structure obtained by revising the current geometric situation and signalling system at two intersections in an important city of Afghanistan, Mezar-i-Sheriff, using two different VISSIM and SIDRA softwares. In addition to present and improved geometry scenarios, the traffic characteristics of the current and future cases to improve the service level of the network by reducing delay time and queue lengths through signal coordination were also investigated.According to the analytical findings of the study, it was found that if the coordination is carried out between the first and the second intersection of Marmul Street before the improved geometric design, the total vehicle delays for the system decreased by up to 3.36 percent. After improving the geometric design, total vehicle delays for the system decreased by up to 8.85 percent. When the current and the improved situation are compared, it was seen that, in the improved case, the delays in the total vehicle delays for the pre-coordination and after coordination system (network) decreased 51.78 and 54.51 percent, respectively.

The lives of approximately 1.3 million people are cut short every year as a result of road traffic crashes. Between 20 and 50 million people suffer non-fatal injuries, with many incurring a disability as a result of their injury. The risk of dying in a road traffic crash is more than 3 times higher in low-income countries than in high-income countries [1]. In Turkey, 18% of traffic accidents was related to pedestrian-vehicle collisions in urban roads in 2020. In addition, 20% of death toll caused by accidents is pedestrians in 2020 [2]. This study deals with the some of classifiers to forecast the number of injuries as a result of traffic accidents. The classifier’s performance ratios were also examined.

Awareness about the price of precious metals and the correct prediction on the process of taking decision can bring facilities, and purchasing them in the global market and recognizing the specific time of dealing can cause investment. In this article comparison of the performance of Artificial Neural Networks and Fuzzy Inference Systems in predicting the price of the precious metals (Case Study: Gold, Silver, Platinum and Palladium).has been pointed. The information about each of these metals (Gold, Silver, Platinum and Palladium) is monthly considered from 1998 until 2018 including 360 data. Thus, by examining different influential variables, National Product Parameters, Time, getting higher the value of USD dollar against the Canadian dollar, global production and global reserves of precious metals are chosen as influential variables. In this research, implementation of (ANFIS) is made for the prediction model by using Artificial and Fuzzy Neural Model. Evaluation of models by using coefficient values, the average set of squares and the square root of the average set of the squares in order of the values for Gold 0.9964 , 0.000268 & 0.01637 for silver 0.987, 0.000092 & 0.0096, for platinum 0.9976, 0.000209 & 0.01448 and for palladium 0.99, 0.0001 & 0.01 have been achieved. As a result, while the best predictive model for the price of gold and platinum is Artificial Neural Networks, the model of ANFIS is suggested for the silver and palladium.

Dünya’da her yıl trafik kazaları nedeniyle 1,35 milyon kişi hayatını kaybetmekte, 20-50 milyon kişi ise yaralanmaktadır. Çocuk ve genç (5-29 yaş arası) ölüm nedenlerinin başında trafik kazaları gelmektedir. Savunmasız yol kullanıcıları olarak tanımlanan yayalar, bisikletliler, 2-3 tekerlekli motosiklet kullanıcıları tüm kazalarda hayatını kaybedenlerin yüzde ellisini oluşturmakta olup, düşük gelirli ülkelerin payı yüksek gelirli ülkelere göre daha fazla olmaktadır [1]. Trafik kazalarının neden olduğu bu kayıpların azaltılması için bilimsel çalışmalara, bulgulara ve sonucunda önlemlere gereksinim duyulmaktadır. Elimizde bulunan raporlara, verilere göre trafik kazalarında hatalı görünen başlıca öge sürücülerdir. Bu çalışmada, Türkiye'de gerçekleşen kazaların dağılımı ve literatürde yer alan kazalarla ilgili yapılan çalışmalar irdelenmiş, veri madenciliği konseptinde yapılması planlanan çalışmanın altlığı oluşturulmuştur.