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DAILY VERTICAL VARIATION IN PHYTOPLANKTON COMPOSITION OF A DRINKING WATER RESERVOIR (KADIKÖY RESERVOIR-EDİRNE) DURING SUMMER STRATIFICATION [PDF]
Trakya University Journal of Natural Sciences, 2018 This study is performed in August 2012 in Kadıköy Reservoir in Keşan district of Edirne. The deepest point of the reservoir when there is no water drown was chosen as the sampling station.
Burak Öterler
doaj +4 more sources
Reservoir Computing Using Complex Systems [PDF]
Indian Academy of Sciences Conference Series (2020) 3:1, 2022 Reservoir Computing is an emerging machine learning framework which is a versatile option for utilising physical systems for computation. In this paper, we demonstrate how a single node reservoir, made of a simple electronic circuit, can be employed for computation and explore the available options to improve the computational capability of the ...
arxiv +1 more source
THE PHYTOPLANKTON COMPOSITION of KADIKOY DAM LAKE (Keşan-EDİRNE)
Trakya University Journal of Natural Sciences, 2015 This study was carried out between June 2011 and May 2012 at different depths of three stations in Kadıköy Dam Lake in the Turkish Thrace. A total of seventyfour phytoplanktonic algal taxa belonging to Chlorophyta, Ochrophyta (Diatoms), Cyanobacteria ...
Burak Öterler
doaj +6 more sources
Attachment and Proliferation of Osteoblasts on Lithium‐Hydroxyapatite Composites
Advances in Materials Science and Engineering, Volume 2012, Issue 1, 2012., 2012 The biocompatibility and bioactivity properties of hydroxyapatites (HAs) modified through lithium addition were investigated. Hydroxyapatites obtained from bovine bone were mixed with lithium carbonate (Li), in the proportions of 0.25, 0.50, 1.00, and 2.00% wt, and sintered at 900°, 1000°, 1100°, 1200°, and 1300°C, creating LiHA samples. The osteoblast
Ana Paula M. Shainberg +8 more
wiley +1 more source
Time Shifts to Reduce the Size of Reservoir Computers [PDF]
, 2022 A reservoir computer is a type of dynamical system arranged to do computation. Typically, a reservoir computer is constructed by connecting a large number of nonlinear nodes in a network that includes recurrent connections. In order to achieve accurate results, the reservoir usually contains hundreds to thousands of nodes.
arxiv +1 more source
Hierarchical Architectures in Reservoir Computing Systems [PDF]
arXiv, 2021 Reservoir computing (RC) offers efficient temporal data processing with a low training cost by separating recurrent neural networks into a fixed network with recurrent connections and a trainable linear network. The quality of the fixed network, called reservoir, is the most important factor that determines the performance of the RC system.
arxiv
Passive frustrated nanomagnet reservoir computing [PDF]
, 2021 Reservoir computing (RC) has received recent interest because reservoir weights do not need to be trained, enabling extremely low-resource consumption implementations, which could have a transformative impact on edge computing and in-situ learning where resources are severely constrained. Ideally, a natural hardware reservoir should be passive, minimal,
arxiv +1 more source
Effects of magnetic fields on the Datta-Das spin field-effect transistor [PDF]
Phys. Rev. B 102, 115436 (2020), 2020 A Datta-Das spin field-effect transistor is built of a heterostructure with a Rashba spin-orbit interaction (SOI) at the interface (or quantum well) separating two possibly magnetized reservoirs. The particle and spin currents between the two reservoirs are driven by chemical potentials that are (possibly) different for each spin direction.
arxiv +1 more source
Using reservoir computers to distinguish chaotic signals [PDF]
Phys. Rev. E 98, 052209 (2018), 2018 Several recent papers have shown that reservoir computers are useful for analyzing and predicting dynamical systems. Reservoir computers have also been shown to be useful for various classification problems. In this work, a reservoir computer is used to identify one out of the 19 different Sprott systems.
arxiv +1 more source
Configured Quantum Reservoir Computing for Multi-Task Machine Learning [PDF]
arXiv, 2023 Amidst the rapid advancements in experimental technology, noise-intermediate-scale quantum (NISQ) devices have become increasingly programmable, offering versatile opportunities to leverage quantum computational advantage. Here we explore the intricate dynamics of programmable NISQ devices for quantum reservoir computing.
arxiv