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Publication Metadata only A 35--μm pitch IR thermo-mechanical MEMS sensor with AC-coupled optical readout(IEEE-Inst Electrical Electronics Engineers Inc, 2015) Ferhanoğlu, Onur; Torun, Hamdi; N/A; Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Adiyan, Ulaş; Çivitçi, Fehmi; Ürey, Hakan; PhD Student; Researcher; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Sciences; College of Engineering; N/A; 194282; 8579A thermo-mechanical MEMS detector with 35-mu m pixel pitch is designed, fabricated, and characterized. This fabricated design has one of the smallest pixel sizes among the IR thermo-mechanical MEMS sensors in the literature. The working principle of the MEMS detector is based on the bimaterial effect that creates a deflection when exposed to IR radiation in the 812-mu m waveband. The nanometer level out of plane mechanical motion is observed in response to IR heating of the pixel, which is detected by a diffraction grating-based optical readout. Performance of MEMS sensor arrays with optical readout have been limited by a large DC bias that accompanies a small AC signal. We developed a novel optical setup to reduce the DC term and the related noise using an AC-coupled detection scheme. Detailed noise characterization of the pixel and the readout system is reported in this paper. The noise equivalent temperature difference of our detector is measured as 216 mK using f/0.86 lens with the AC-coupled optical readout. Finally, we obtained a thermal image using a single MEMS pixel combined with a scanning configuration. Despite the reduced pixel size, the measured noise levels are comparable to the state-of-the-art thermo-mechanical IR sensors.Publication Open Access A cartridge based sensor array platform for multiple coagulation measurements from plasma(Royal Society of Chemistry (RSC), 2015) Bulut, Serpil; Yaralioglu, G. G.; Department of Electrical and Electronics Engineering; Department of Molecular Biology and Genetics; Department of Chemical and Biological Engineering; Çakmak, Onur; Ermek, Erhan; Kılınç, Necmettin; Barış, İbrahim; Kavaklı, İbrahim Halil; Ürey, Hakan; PhD Student; Other; Researcher; Teaching Faculty; Faculty Member; Department of Electrical and Electronics Engineering; Department of Molecular Biology and Genetics; Department of Chemical and Biological Engineering; College of Engineering; Graduate School of Sciences and Engineering; College of Sciences; N/A; 109991; N/A; 111629; 40319; 8579This paper proposes a MEMS-based sensor array enabling multiple clot-time tests for plasma in one disposable microfluidic cartridge. The versatile LoC (Lab-on-Chip) platform technology is demonstrated here for real-time coagulation tests (activated Partial Thromboplastin Time (aPTT) and Prothrombin Time (PT)). The system has a reader unit and a disposable cartridge. The reader has no electrical connections to the cartridge. This enables simple and low-cost cartridge designs and avoids reliability problems associated with electrical connections. The cartridge consists of microfluidic channels and MEMS microcantilevers placed in each channel. The microcantilevers are made of electroplated nickel. They are actuated remotely using an external electro-coil and the read-out is also conducted remotely using a laser. The phase difference between the cantilever oscillation and the coil drive is monitored in real time. During coagulation, the viscosity of the blood plasma increases resulting in a change in the phase read-out. The proposed assay was tested on human and control plasma samples for PT and aPTT measurements. PT and aPTT measurements from control plasma samples are comparable with the manufacturer's datasheet and the commercial reference device. The measurement system has an overall 7.28% and 6.33% CV for PT and aPTT, respectively. For further implementation, the microfluidic channels of the cartridge were functionalized for PT and aPTT tests by drying specific reagents in each channel. Since simultaneous PT and aPTT measurements are needed in order to properly evaluate the coagulation system, one of the most prominent features of the proposed assay is enabling parallel measurement of different coagulation parameters. Additionally, the design of the cartridge and the read-out system as well as the obtained reproducible results with 10 mu l of the plasma samples suggest an opportunity for a possible point-of-care application.Publication Metadata only A class of bounded component analysis algorithms for the separation of both independent and dependent sources(IEEE-inst Electrical Electronics Engineers inc, 2013) Department of Electrical and Electronics Engineering; Erdoğan, Alper Tunga; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 41624Bounded Component analysis (BCa) is a recent approach which enables the separation of both dependent and independent signals from their mixtures. in this approach, under the practical source boundedness assumption, the widely used statistical independence assumption is replaced by a more generic domain separability assumption. This article introduces a geometric framework for the development of Bounded Component analysis algorithms. Two main geometric objects related to the separator output samples, namely Principal Hyper-Ellipsoid and Bounding Hyper-Rectangle, Are introduced. the maximization of the volume ratio of these objects, and its extensions, Are introduced as relevant optimization problems for Bounded Component analysis. the article also provides corresponding iterative algorithms for both real and complex sources. the numerical examples illustrate the potential advantage of the proposed BCa framework in terms of correlated source separation capability as well as performance improvement for short data records.Publication Metadata only A communication theoretical analysis of synaptic multiple-access channel in hippocampal-cortical neurons(IEEE-Inst Electrical Electronics Engineers Inc, 2013) N/A; N/A; Department of Electrical and Electronics Engineering; Malak, Derya; Akan, Özgür Barış; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 6647Communication between neurons occurs via transmission of neural spike trains through junctional structures, either electrical or chemical synapses, providing connections among nerve terminals. Since neural communication is achieved at synapses, the process of neurotransmission is called synaptic communication. Learning and memory processes are based on the changes in strength and connectivity of neural networks which usually contain multiple synaptic connections. In this paper, we investigate multiple-access neuro-spike communication channel, in which the neural signal, i.e., the action potential, is transmitted through multiple synaptic paths directed to a common postsynaptic neuron terminal. Synaptic transmission is initiated with random vesicle release process from presynaptic neurons to synaptic paths. Each synaptic channel is characterized by its impulse response and the number of available postsynaptic receptors. Here, we model the multiple-access synaptic communication channel, and investigate the information rate per spike at the postsynaptic neuron, and how postsynaptic rate is enhanced compared to single terminal synaptic communication channel. Furthermore, we analyze the synaptic transmission performance by incorporating the role of correlation among presynaptic terminals, and point out the postsynaptic rate improvement.Publication Metadata only A convolutive bounded component analysis framework for potentially nonstationary independent and/or dependent sources(IEEE-Inst Electrical Electronics Engineers Inc, 2015) İnan, Hüseyin A.; Department of Electrical and Electronics Engineering; Erdoğan, Alper Tunga; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 41624Bounded Component Analysis (BCA) is a recent framework which enables development of methods for the separation of dependent as well as independent sources from their mixtures. This paper extends a recent geometric BCA approach introduced for the instantaneous mixing problem to the convolutive mixing problem. The paper proposes novel deterministic convolutive BCA frameworks for the blind source extraction and blind source separation of convolutive mixtures of sources which allows the sources to be potentially nonstationary. The global maximizers of the proposed deterministic BCA optimization settings are proved to be perfect separators. The paper also illustrates that the iterative algorithms corresponding to these frameworks are capable of extracting/separating convolutive mixtures of not only independent sources but also dependent (even correlated) sources in both component (space) and sample (time) dimensions through simulations based on a Copula distributed source system. In addition, even when the sources are independent, it is shown that the proposed BCA approach have the potential to provide improvement in separation performance especially for short data records based on the setups involving convolutive mixtures of digital communication sources.Publication Metadata only A cross-layer QoS-aware communication framework in cognitive radio sensor networks for smart grid applications(IEEE-Inst Electrical Electronics Engineers Inc, 2013) Shah, Ghalib A.; Güngör, Vehbi Çağrı; Department of Electrical and Electronics Engineering; Akan, Özgür Barış; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 6647Electromagnetic interference, equipment noise, multi-path effects and obstructions in harsh smart grid environments make the quality-of-service (QoS) communication a challenging task for WSN-based smart grid applications. To address these challenges, a cognitive communication based cross-layer framework has been proposed. The proposed framework exploits the emerging cognitive radio technology to mitigate the noisy and congested spectrum bands, yielding reliable and high capacity links for wireless communication in smart grids. To meet the QoS requirements of diverse smart grid applications, it differentiates the traffic flows into different priority classes according to their QoS needs and maintains three dimensional service queues attributing delay, bandwidth and reliability of data. The problem is formulated as a Lyapunov drift optimization with the objective of maximizing the weighted service of the traffic flows belonging to different classes. A suboptimal distributed control algorithm (DCA) is presented to efficiently support QoS through channel control, flow control, scheduling and routing decisions. In particular, the contributions of this paper are three folds; employing dynamic spectrum access to mitigate with the channel impairments, defining multi-attribute priority classes and designing a distributed control algorithm for data delivery that maximizes the network utility under QoS constraints. Performance evaluations in ns-2 reveal that the proposed framework achieves required QoS communication in smart grid.Publication Metadata only A fast blind equalization method based on subgradient projections(IEEE, 2004) N/A; N/A; Department of Electrical and Electronics Engineering; Kızılkale, Can; Erdoğan, Alper Tunga; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 41624A novel blind equalization method based on a subgradient search over a convex cost surface is proposed. This is an alternative to the existing iterative blind equalization approaches such as the Constant Modulus Algorithm (CMA) which mostly suffer from the convergence problems caused by their non-convex cost functions. The proposed method is an iterative algorithm, for both real and complex constellations, with a very simple update rule that minimizes the l(infinity) norm of the equalizer output under a linear constraint on the equalizer coefficients. The algorithm has a nice convergence behavior attributed to the convex l(infinity) cost surface. Examples are provided to illustrate the algorithm's performance.Publication Open Access A fast, accurate, and separable method for fitting a Gaussian function(Institute of Electrical and Electronics Engineers (IEEE), 2019) Al-Nahhal Ibrahim; Dobre Octavia A.; Moloney Cecilia; Ikki Salama; Department of Electrical and Electronics Engineering; Başar, Ertuğrul; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 149116Publication Metadata only A flexible multiple description coding framework for adaptive peer-to-peer video streaming(IEEE-Inst Electrical Electronics Engineers Inc, 2007) Akyol, Emrah; Civanlar, M. Reha; Department of Electrical and Electronics Engineering; Tekalp, Ahmet Murat; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 26207Efficient peer-to-peer (P2P) video streaming is a challenging task due to time-varying nature of both the number of available peers and network/channel conditions. This paper proposes a novel adaptive P2P video streaming system, which features: i) a new flexible multiple-description coding (F-MDC) framework, such that the number of base and enhancement descriptions, and the rate and redundancy level of each description can be adapted on the fly (by only post-processing of the encoded bitstream), and ii) a new adaptive TCP-friendly rate-controlled (TFRC), on-demand, many-to-one P2P video streaming solution based on the proposed F-MDC framework. We extend the highly scalable video coder [17], [18] to MDC within the proposed F-MDC framework. Optimization of the design parameters of the proposed F-MDC method is discussed within the context of the proposed adaptive P2P streaming solution, where the number and quality of available streaming peers/paths are a priori unknown and vary in time. Experimental results, by means of NS-2 network simulation of a P2P video streaming system, show that adaptation of the number, type of descriptions and the rate and redundancy level of each description according to network conditions yields significantly superior performance when compared to other scalable MDC schemes using a fixed number of descriptions/layers with fixed rate and redundancy level.Publication Open Access A hybrid architecture for federated and centralized learning(Institute of Electrical and Electronics Engineers (IEEE), 2022) Elbir, Ahmet M.; Papazafeiropoulos, Anastasios K.; Kourtessis, Pandelis; Chatzinotas, Symeon; Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 7211Many of the machine learning tasks rely on centralized learning (CL), which requires the transmission of local datasets from the clients to a parameter server (PS) entailing huge communication overhead. To overcome this, federated learning (FL) has been suggested as a promising tool, wherein the clients send only the model updates to the PS instead of the whole dataset. However, FL demands powerful computational resources from the clients. In practice, not all the clients have sufficient computational resources to participate in training. To address this common scenario, we propose a more efficient approach called hybrid federated and centralized learning (HFCL), wherein only the clients with sufficient resources employ FL, while the remaining ones send their datasets to the PS, which computes the model on behalf of them. Then, the model parameters are aggregated at the PS. To improve the efficiency of dataset transmission, we propose two different techniques: i) increased computation-per-client and ii) sequential data transmission. Notably, the HFCL frameworks outperform FL with up to 20% improvement in the learning accuracy when only half of the clients perform FL while having 50% less communication overhead than CL since all the clients collaborate on the learning process with their datasets.