As a sub-discipline of Artificial Intelligence, deep neural networks have received enormous interest in research and industrial applications over the last decades owing to their highly successful performance in addressing ...

Composite materials have increasing application areas in today's industry and daily life due to their low density structure and high mechanical properties. Also, thermalstability and electrical conductivity can be improved ...

With the recent advancements in the field of Computer Vision, the central tasks such as object detection, segmentation or object tracking methods attain all-time high accuracies in natural image sets such as ImageNet, COCO, ...

Classification algorithms are employed in a wide range of real-world problems such as obstacle detection, fraud detection, medical diagnosis, spam detection, speech recognition, image processing, intrusion detection, and ...

Protein secondary structure prediction is important for understanding protein structure and function. PSSP can be seen as a bridge between amino acid sequence and 3D structure of a protein. Many methods have been performed ...

There is an increasing interest in using Underwater Acoustic Sensor Networks (UASNs) for various oceanographic applications, such as pollution monitoring, seismic monitoring, environmental data collection, offshore ...

The subject of Mode-Locked Lasers has experienced a massive growth over the last two decades. Previously meant as the source of ultra-short optical pulses, its concepts have recently expanded to be applicable in areas ...

Direct ceramic microfiltration (DCMF) is an effective technology to pre-concentrate organic matter (OM) for the subsequent anaerobic energy-recovering processes and a fast, cost-effective, easy treatment process for municipal ...

In this thesis, we examine a selling environment where a manufacturer-controlled retailer and an independent retailer sell a slow-moving A item. The manufacturer offers the independent retailer price protection against ...

Protein fragment selection is an important step in predicting the three-dimensional (3D) structure of proteins. Selecting the right fragments contributes significantly to accurate prediction of 3D structure. In this thesis, ...