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.

The release of hemoglobin from mechanically stressed erythrocytes into plasma is a general side effect of extracorporeal therapies, such as extracorporeal membrane oxygenation or hemodialysis. In many reported cases dialysis patients showed elevated cell-free plasma hemoglobin (CPH) levels which are associated with pathophysiological effects. In this in vitro study, the CPH clearance capacity of various filters with different permeability profiles was measured. Simulated dialysis treatments were conducted and clearance was calculated from variations in CPH concentrations over time by measuring plasma absorbance at 405 nm. Conventional high-flux filters exhibited no detectable clearance of CPH. High-flux filters with extended permeability exhibited clearances between 5.8 ± 1.2 and 12.7 ± 1.7 ml/min when tested with plasma and between 5.8 ± 1.2 and 11.3 ± 1.6 ml/min when tested with whole blood. septeX high-cutoff filters had clearances between 13.8 ± 1.8 and 15.5 ± 1.7 ml/min when tested with plasma and of 22.6 ± 2.9 ml/min when tested with whole blood. This study demonstrated that filters with extended permeability and the septeX filter enable CPH removal when used as in chronic and acute settings.

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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 Instıtute 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.

In parallel to the economic developments, the importance of road transportation was significantly increased in

Various factors (illegal parking, the existence of a bus stop, road surface deformations etc.) generally cause blockage on traffic flow at signalized intersections. These factors have a negative effect on capacity of signalized intersections. This study examines the blockage effect of a bus stop and a road surface deformation on capacity of a signalized intersection by implementing a Cell Transmission Model (CTM). Study has conducted extensive simulation experiments that captures traffic parametres and evaluates complex traffic flow interactions on signalized intersections using cell transmission concept. In analyses, boundary conditions were defined by means of input and output cells with infinite sizes and proper capacity values. It is assumed that vehicles have instantaneous acceleration and deceleration properties such as vehicles' movement or stop instantaneously from their current situation when encountered a bottleneck situation. The results of simulation experiments indicate that if blockage on traffic flow is far from the signalized intersections, negative effects on the capacity were decreased. Also results pointed that the dominant factor was considered as the distance between the surface deformation area/bus stop and signalized intersection for the capacity change.

Previous studies have shown that road surface conditions are an important factor for road quality. To provide quality on road surface, it should be observed steadily and repaired as necessarily. There are many process to determine road surface condition. Using a smart phone to collect data is an alternative and simple application because of it's low cost, wider population coverage property and easy utilization. This paper explores the utilization of Roadroid, a simple android application, as a low cost vehicle-based solution for road surface condition monitoring with using sensors from smartphones. In the scope of this study, site experiments have been conducted to collect data using acceleration and GPS properties of a smartphone in a specific (passenger car) vehicle type. This method was evaluated with 3259 km urban and rural road data collected from the site experiments in Turkey, and it was seen from the results that average 84.4% of Turkish roads have good, 7.9% have satisfactory, 3.8 have unsatisfactory and 3.8% have poor road roughness conditions. It shows that approximately 4% of Turkish roads need maintenance urgently. Also experimental study results confirm that Roadroid have a great potential to evaluate road surface roughness condition correctly, even under obstacle like, potholes, manholes and decelerating marks.

Abstract