Tugba Taskaya-Temizel

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A procedure for pre-processing non-stationary time series is proposed for modelling with a time-delay neural network (TDNN). The procedure stabilises the mean of the series and uses a Fast Fourier Transform (FFT) to determine the TDNN input size. Results of applying this procedure on five well-known data sets are compared with existing hybrid neural network(More)
Many researchers have argued that combining many models for forecasting gives better estimates than single time series models. For example, a hybrid architecture comprising an autoregressive integrated moving average model (ARIMA) and a neural network is a well-known technique that has recently been shown to give better forecasts by taking advantage of each(More)
Most financial time series processes are nonstationary and their frequency characteristics are time-dependant. In this paper we present a time series summarization and prediction framework to analyse volatile and high-frequency time series data. Multiscale wavelet analysis is used to separate out the trend, cyclical fluctuations and autocorrelational(More)
The importance of ballistic applications has been recently recognized due to the increasing crime and terrorism threats and incidents around the world. Ballistic image analysis is one of the application areas which requires immediate response with high precision from large databases. Here, the microscopic markings on cartridge case of a bullet obtained in a(More)
In this article, parallel implementation of a real-time intelligent video surveillance system on Graphics Processing Unit (GPU) is described. The system is based on background subtraction and composed of motion detection, camera sabotage detection (moved camera, out-of-focus camera and covered camera detection), abandoned object detection, and(More)
Time series often exhibit periodical patterns that can be analysed by conventional statistical techniques. These techniques rely upon an appropriate choice of model parameters that are often difficult to determine. Whilst neural networks also require an appropriate parameter configuration, they offer a way in which non-linear patterns may be modelled.(More)
Extraction of crowd dynamics from video is the fundamental step for automatic detection of abnormal events. However, it is difficult to obtain sufficient performance with object tracking due to occlusions and insufficient resolution of the objects in the scene. As a result, optical flow or feature tracking methods are preferred in crowd videos. These(More)
Özet. Son yıllarda mobil teknolojiler günlük rutin işleri gerçekleştirmek üzere sıkça kullanılmaya başlanmıştır. Mobil teknolojilerin bu denli hızla yaygınlaşması ise birçok sektör açısından ve akademik çalışmalar için kullanıcı verisi elde etmek üzere güvenilir bir kaynak haline gelmiştir. Mobil telefonlardan elde edilen veriler ile kullanıcıların(More)
The incorporation of pharmacogenomics information into the drug dosing estimation formulations has been shown to increase the accuracy in drug dosing and decrease the frequency of adverse drug effects in many studies in the literature. In this paper, an estimation framework based on the Bayesian structural equation modeling, which is driven by(More)
Road traffic congestions are one of the major problems in highly populated cities. In the recent years, GPS based solutions have become popular since people are able to see the traffic flow on streets instantaneously. However such systems are lack of intelligent reasoning regarding the traffic problems. As a result, one cannot anticipate the traffic(More)