Time Series Analysis and Forecasting

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• MELEK ACAR

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• ÖMER KAAN BAYKAN

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• RESUL DAŞ

We investigate anomaly detection in an unsupervised framework and introduce long short-term memory (LSTM) neural network-based algorithms. In particular, given variable length data sequences, we first pass these sequences through our LSTM-based structure and obtain fixed-length sequences. We then find a decision funct…

Falls are a serious public health problem and possibly life threatening for people in fall risk groups. We develop an automated fall detection system with wearable motion sensor units fitted to the subjects' body at six different positions. Each unit comprises three tri-axial devices (accelerometer, gyroscope, and mag…

• BİLLUR BARSHAN ÖZAKTAŞ

Falls are a serious public health problem and possibly life threatening for people in fall risk groups. We develop an automated fall detection system with wearable motion sensor units fitted to the subjects' body at six different positions. Each unit comprises three tri-axial devices (accelerometer, gyroscope, and mag…

• AHMET TURAN ÖZDEMİR

Time series classification is an important task with many challenging applications. A nearest neighbor (NN) classifier with dynamic time warping (DTW) distance is a strong solution in this context. On the other hand, feature-based approaches have been proposed as both classifiers and to provide insight into the series…

• MUSTAFA GÖKÇE BAYDOĞAN

This study provides a comparative assessment on the different techniques of classifying human activities performed while wearing inertial and magnetic sensor units on the chest, arms and legs. The gyroscope, accelerometer and the magnetometer in each unit are tri-axial. Naive Bayesian classifier, artificial neural net…

• BİLLUR BARSHAN ÖZAKTAŞ

Forecasting the evolution of complex systems is noted as one of the 10 grand challenges of modern science. Time series data from complex systems capture the dynamic behaviors and causalities of the underlying processes and provide a tractable means to predict and monitor system state evolution. However, the nonlinear…

• ÖMER FARUK BEYCA

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In this study, spatiotemporal changes in Lake Burdur from 1987 to 2011 were evaluated using multi-temporal Landsat TM and ETM+ images. Support Vector Machine (SVM) classification and spectral water indexing, including the Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI) and Automated Water Extraction In…

• GÜLCAN SARP
• MEHMET ÖZÇELİK

ÖZETYeni, beklenmedik veya tahmin edilemeyen uyaranlar dikkati istem dışı olarak üzerlerine çekerek bir oriyantasyon yanıtı oluştururlar. Yenilik paradigması; klasik oddball paradig¬masındaki sık gelen standart ve nadir gelen hedef uyaranlar arasına beklenmedik ve sü¬rekli değişen özellikte hedef olmayan, yeni uyaranl…