Browsing by Author "Yildirim M.S."
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Item Prediction of pedal cyclists and pedestrian fatalities from total monthly accidents and registered private car numbers(Warsaw University of Technology, 2015) Ghasemlou K.; Aydin M.M.; Yildirim M.S.Accident prevention is relatively a complex issue considering the effectiveness of the injury prevention technologies as well as more detailed assessment of the complex interactions between the road condition, vehicle and human factor. For many years, highway agencies and vehicle manufacturers showed great efforts to reduce the injuries resulting from the vehicle crashes. Many researchers used a broad range of methods to evaluate the impact of several factors on traffic accidents and injuries. Recent developments lead up to capable for determining the effects of these factors. According to World Health Organization (WHO), cyclists and pedestrians comprise respectively 1.6% and 16.3% in traffic crash fatalities in 2013. Also in Turkey crash fatalities for pedestrian and cyclists are respectively 20.6% and 3% according to Turkish Statistical Institute data in 2013. The relationship between cycling and pedestrian rates and injury rates over time is also unknown. This paper aims to predict the crash severity with the traffic injury data of the Konya City in Turkey by implementing the Artificial Neural Networks (ANN), Regression Trees (RT) and Multiple Linear Regression modelling (MLRM) method.Item Estimation of Container Traffic at Seaports by Using Several Soft Computing Methods: A Case of Turkish Seaports(Hindawi Limited, 2017) Gökkuş Ü.; Yildirim M.S.; Aydin M.M.Container traffic forecasting is important for the operations and the design steps of a seaport facility. In this study, performances of the novel soft computing models were compared for the container traffic forecasting of principal Turkish seaports (Istanbul, Izmir, and Mersin seaports) with excessive container traffic. Four forecasting models were implemented based on Artificial Neural Network with Artificial Bee Colony and Levenberg-Marquardt Algorithms (ANN-ABC and ANN-LM), Multiple Nonlinear Regression with Genetic Algorithm (MNR-GA), and Least Square Support Vector Machine (LSSVM). Forecasts were carried out by using the past records of the gross domestic product, exports, and population of the Turkey as indicators of socioeconomic and demographic status. Performances of the forecasting models were evaluated with several performance metrics. Considering the testing period, the LSSVM, ANN-ABC, and ANN-LM models performed better than the MNR-GA model considering overall fitting and prediction performances of the extreme values in the testing data. The LSSVM model was found to be more reliable compared to the ANN models. Forecasting part of the study suggested that container traffic of the seaports will be increased up to 60%, 67%, and 95% at the 2023 for the Izmir, Mersin, and Istanbul seaports considering official growth scenarios of Turkey. © 2017 Ümit Gökkuş et al.Item Wind load design of hangar-type closed steel structures with different roof pitches using abaqus CAE software(UIKTEN - Association for Information Communication Technology Education and Science, 2017) Çiftçioğlu A.Ö.; Yildizel S.A.; Yildirim M.S.; Doğan E.Structures convert the kinetic energy available in the air into potential energy which is in the form of pressure and suction forces reducing or fully stopping its motion. The potential impact of the wind depends on the geometric properties and pertinacity of a building, the angle of the wind flow, its strength and velocity. Design gains importance for tall buildings against the impact of the resonance along with the force based on pressure. Relevant calculations are made in Turkey based on the TS 498 Wind Load Velocity Criterion and this standard is currently being updated. This study develops the wind load design of hangar-type closed steel structures with different roof pitches using Abaqus CAE software. © 2017 Aybike Özyüksel Çiftçioğlu et al.Item Prediction of Concrete and Steel Materials Contained by Cantilever Retaining Wall by Modeling the Artificial Neural Networks(Pouyan Press, 2018) Gokkus U.; Yildirim M.S.; Yilmazoglu A.In this study, the Artificial Neural Network (ANN) application is implemented for predicting the required concrete volume and amount of the steel reinforcement within the inversed-T-shaped and stem-stepped reinforced concrete (RC) walls. For this aim, seven-different RC wall designs were approached differentiated within the wall heights and various internal friction angles of backfill materials. Each RC wall is proportionally designed and subjected to active lateral earth pressure defined with the Mononobe-Okabe approach foreseen by Turkish Specification for Building to be Built in Seismic Zones (TSC-2007). Following the stability analysis of the RC retaining walls, the structural and reinforced concrete analyses are performed according to the Turkish Standard on Requirements for Design and Construction in Reinforced Concrete Structures (TS500-2000). Input parameters such as concrete volumes, weights of the steel bars, soil and wall material properties are subjected to the ANN modeling. The prediction of the concrete volume and amount of the steel bars are achieved with the implementation of the ANN model trained with the Artificial Bee Colony (ABC) algorithm. As a result of this study, it is revealed that ANN models are useful for verifying the existing RC retaining wall designs or performing preliminary designs for the L-shaped and stem-stepped cantilever retaining walls. © 2018 The Authors. Published by Pouyan Press.Item Germline landscape of BRCAs by 7-site collaborations as a BRCA consortium in Turkey(Churchill Livingstone, 2022) Bisgin A.; Sag S.O.; Dogan M.E.; Yildirim M.S.; Gumus A.A.; Akkus N.; Balasar O.; Durmaz C.D.; Ersoz R.; Altiner S.; Alemdar A.; Aliyeva L.; Boga I.; Cam F.S.; Dogan B.; Esbah O.; Hanta A.; Mujde C.; Ornek C.; Ozer S.; Rencuzogullari C.; Sonmezler O.; Bozdogan S.T.; Dundar M.; Temel S.G.BRCA1/2 mutations play a significant role in cancer pathogenesis and predisposition particularly in breast, ovarian and prostate cancers. Thus, germline analysis of BRCA1 and BRCA2 is essential for clinical management strategies aiming at the identification of recurrent and novel mutations that could be used as a first screening approach. We analyzed germline variants of BRCA1/2 genes for 2168 individuals who had cancer diagnosis or high risk assessment due to BRCAs related cancers, referred to 10 health care centers distributed across 7 regions covering the Turkish landscape. Overall, 68 and 157 distinct mutations were identified in BRCA1 and BRCA2, respectively. Twenty-two novel variants were reported from both genes while BRCA2 showed higher mutational heterogeneity. We herein report the collective data as BRCA Turkish consortium that confirm the molecular heterogeneity in BRCAs among Turkish population, and also as the first study presenting the both geographical, demographical and gene based landscape of all recurrent and novel mutations which some might be a founder effect in comparison to global databases. This wider perspective leads to the most accurate variant interpretations which pave the way for the more precise and efficient management affecting the clinical and molecular aspects. © 2022 The Authors