Istanbul Technical University

About: Istanbul Technical University is a education organization based out in Istanbul, Turkey. It is known for research contribution in the topics: Fuzzy logic & Large Hadron Collider. The organization has 12889 authors who have published 25081 publications receiving 518242 citations. The organization is also known as: İstanbul Teknik Üniversitesi & Technical University of Istanbul.

Celebrating 40 years anaerobic sludge bed reactors for industrial wastewater treatment

Abstract: In the last 40 years, anaerobic sludge bed reactor technology evolved from localized lab-scale trials to worldwide successful implementations at a variety of industries. High-rate sludge bed reactors are characterized by a very small foot print and high applicable volumetric loading rates. Best performances are obtained when the sludge bed consists of highly active and well settleable granular sludge. Sludge granulation provides a rich microbial diversity, high biomass concentration, high solids retention time, good settling characteristics, reduction in both the operation costs and reactor volume, and high tolerance to inhibitors and temperature changes. However, sludge granulation cannot be guaranteed on every type of industrial wastewater. Especially in the last two decades, various types of high-rate anaerobic reactor configurations have been developed that are less dependent on the presence of granular sludge, and many of them are currently successfully applied for the treatment of various kinds of industrial wastewaters worldwide. This study discusses the evolution of anaerobic sludge bed technology for the treatment of industrial wastewaters in the last four decades, focusing on granular sludge bed systems.

Labeled Pseudo-Projective Dependency Parsing with Support Vector Machines

Abstract: We use SVM classifiers to predict the next action of a deterministic parser that builds labeled projective dependency graphs in an incremental fashion. Non-projective dependencies are captured indirectly by projectivizing the training data for the classifiers and applying an inverse transformation to the output of the parser. We present evaluation results and an error analysis focusing on Swedish and Turkish.

The Meandering Current Mobility Model and its Impact on Underwater Mobile Sensor Networks

Abstract: Underwater mobile acoustic sensor networks are promising tools for the exploration of the oceans. These networks require new robust solutions for fundamental issues such as: localization service for data tagging and networking protocols for communication. All these tasks are closely related with connectivity, coverage and deployment of the network. A realistic mobility model that can capture the physical movement of the sensor nodes with ocean currents gives better understanding on the above problems. In this paper, we propose a novel physically-inspired mobility model which is representative of underwater environments. We study how the model affects a range-based localization protocol, and its impact on the coverage and connectivity of the network under different deployment scenarios.