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Permanent URI for this collectionhttps://hdl.handle.net/20.500.14288/3
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Publication Metadata only Analysis and optimization of duty-cycle in preamble-based random access networks(Springer, 2013) Fischione, C.; Park, P.; Department of Electrical and Electronics Engineering; Ergen, Sinem Çöleri; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 7211Duty-cycling has been proposed as an effective mechanism for reducing the energy consumption in wireless sensor networks (WSNs). Asynchronous duty-cycle protocols where the receiver wakes up periodically to check whether there is a transmission and the sender transmits preambles to check if the receiver is awake are widely used in WSNs due to the elimination of complex control mechanisms for topology discovery and synchronization. However, the intrinsic simplicity of the asynchronous mechanism has the drawback of smaller energy saving potential that requires the optimization of the duty cycle parameters. In this paper, we propose a novel method for the optimization of the duty-cycle parameters in preamble-based random access networks based on the accurate modeling of delay, reliability and energy consumption as a function of listen time, sleep time, traffic rate and medium access control (MAC) protocol parameters. The challenges for modeling are the random access MAC and the sleep policy of the receivers, which make it impossible to determine the exact time of data packet transmissions, and thus difficult to investigate the performance indicators given by the delay, reliability and energy consumption to successfully receive packets. An analysis of these indicators is developed as a function of the relevant parameters of the network and it is used in the minimization of the energy consumption subject to delay and reliability requirements. The optimization provides significant reduction of the energy consumption compared to the previously proposed protocols in the literature.Publication Metadata only Design and characterization of micromachined sensor array integrated with CMOS based optical readout(Elsevier Science Sa, 2014) Temiz, Yüksel; Leblebici, Yusuf; Torun, Hamdi; N/A; N/A; N/A; Department of Electrical and Electronics Engineering; Department of Electrical and Electronics Engineering; Erarslan, Refik Burak; Adiyan, Ulaş; Lüleç, Sevil Zeynep; Ölçer, Selim; Ürey, Hakan; Other; PhD Student; Master Student; Other; Faculty Member; Department of Electrical and Electronics Engineering; N/A; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; N/A; N/A; N/A; N/A; 8579This paper reports a micro electro-mechanical system (MEMS) based sensor array integrated with CMOSbased optical readout. The integrated architecture has several unique features. MEMS devices are passive and there are no electrical connections to the MEMS sensor array. Thus, the architecture is scalable to large array formats for parallel measurement applications and can even be made as a disposable cartridge in the future using self-aligning features. A CMOS-based readout integrated circuit (ROIC) is integrated to the MEMS chip. Via holes are defined on ROIC by customized post-processing and MEMS chip is thinned down by a grinding process to enable integrated optical readout. A diffraction grating interferometerbased optical readout is realized by pixel-level illumination of the MEMS chip through the via holes and by capturing the reflected light using a photodetector array on the CMOS chip. A model for the optical readout principle has been developed using Fourier optics. (C) 2013 Elsevier B.V. All rights reserved.Publication Metadata only Gray-level-embedded lossless image compression(2003) Çelik, Mehmet Utku; Sharma, Gaurav; Department of Electrical and Electronics Engineering; Tekalp, Ahmet Murat; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 26207A level-embedded lossless compression method for continuous-tone still images is presented. Level (bit-plane) scalability is achieved by separating the image into two layers before compression and excellent compression performance is obtained by exploiting both spatial and inter-level correlations. A comparison of the proposed scheme with a number of scalable and non-scalable lossless image compression algorithms is performed to benchmark its performance. The results indicate that the level-embedded compression incurs only a small penalty in compression efficiency over non-scalable lossless compression, while offering the significant benefit of level-scalability.Publication Metadata only Precision density and viscosity measurement using two cantilevers with different widths(2015) Kılınç, Necmettin; Yaralıoğlu, G. G.; N/A; Department of Mechanical Engineering; Department of Electrical and Electronics Engineering; Çakmak, Onur; Ermek, Erhan; Ürey, Hakan; PhD Student; Other; Faculty Member; Department of Mechanical Engineering; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Sciences; College of Engineering; N/A; N/A; 8579Weintroduceanovelmethodforfastmeasurementofliquidviscosityanddensityusingtwocantilevers withdifferentgeometries.Ourmethodcanbeusedforreal-timemonitoringinlabonchipsystemsand offerhighaccuracyforalargerangeofdensitiesandviscosities.Themeasurementprincipleisbasedon trackingtheoscillationfrequenciesoftwocantileverswithaphase-lockedloop(PLL)andcomparingwith referencemeasurementswithaknownfluid.Asetofequationsandasimplealgorithmisdevelopedto relatethedensityandtheviscositytothefrequencyshiftsofthecantilevers.Wefoundthattheeffectof thedensityandtheviscositycanbewellseparatedifcantilevershavedifferentwidths.Intheexperiments, twoNickelmicrocantilevers(widths25 mand100 m,length:200 m,thickness:1.75 m)werefully immersedintheliquidandthetemperaturewascontrolled.TheactuationwasusinganexternalelectrocoilandtheoscillationsweremonitoredusinglaserDopplervibrometer.Thus,electricalconnectionsto thecantileversarenotrequired,enablingmeasurementsalsoinconductiveliquids.ThePLLisusedto setthephasedifferenceto90◦betweentheactuatorandthesensor.Calibrationmeasurementswere performedusingglycerolandethyleneglycolsolutionswithknowndensitiesandviscosities.Themeasurementerrorwiththenewmethodwaslowerthan3%indensityintherange995–1150kg/m3and 4.6%inviscosityintherange0.935–4mPa.s.Basedonthesignal-to-noiseratio,theminimumdetectable differenceintheviscosityis1 Pa.sandthedensityis0.18kg/m3.Furtherimprovementsintherange andtheaccuracyarepossibleusing3ormorecantileverswithdifferentgeometries.Publication Metadata only Automatic classification,of musical genres using inter-genre similarity(IEEE-Inst Electrical Electronics Engineers Inc, 2007) Bağcı, Ulaş; Department of Computer Engineering; Erzin, Engin; Faculty Member; Department of Computer Engineering; College of Engineering; 34503Musical genre classification is an essential tool for music information retrieval systems and it has potential to become a highly demanded application in various media platforms. Two important problems of the automatic musical genre classification are feature extraction and classifier design. In this letter, we propose two novel classifiers using inter-genre similarity (IGS) modeling and investigate the use of dynamic timbral texture features in order to improve automatic musical genre classification performance. Inter-genre similarity is modeled over hard-to-classify samples of the musical genre feature space. In the classification, samples within inter-genre similarity class are eliminated to reduce inter-genre confusion and to improve genre classification performance. Experimental results show that the proposed classifiers provide better classification rates than the existing methods.Publication Metadata only Repetitive control of an XYZ piezo-stage for faster nano-scanning: numerical simulations and experiments(Pergamon-Elsevier Science Ltd, 2011) Necipoğlu, Serkan; Güvenç, Levent; N/A; Department of Mechanical Engineering; N/A; Cebeci, Selman; Başdoğan, Çağatay; Has, Yunus Emre; Master Student; Faculty Member; Master Student; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; College of Engineering; Graduate School of Sciences and Engineering; N/A; 125489; N/AA repetitive controller (RC) is implemented to control the Z-axis movements of a piezo-scanner used for AFM scanning and then tested through scan experiments and numerical simulations. The experimental and simulation results show that the RC compensates phase delays better than the standard PI controller at high scan speeds, which leads to less scan error and lower interaction forces between the scanning probe and the surface being scanned. Since the AFM experiments are not perfectly repeatable in the physical world, the optimum phase compensators of the RC resulting this performance are determined through the numerical simulations performed in MATLAB/Simulink. Furthermore, the numerical simulations are also performed to show that the proposed RC is robust and does not require re-tuning of these compensators when the consecutive scan lines are not similar and a change occurs in the probe characteristics. (C) 2011 Elsevier Ltd. All rights reserved.Publication Metadata only Architectures for multi-threaded MVC-compliant multi-view video decoding and benchmark tests(Elsevier, 2010) Aksay, Anıl; Akar, Gözde Bozdağı; N/A; Department of Electrical and Electronics Engineering; Gürler, Cihat Göktuğ; Tekalp, Ahmet Murat; PhD Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 262073D video based on stereo/multi-view representations is becoming widely popular. Real-time encoding/decoding of such video is an important concern as the number and spatial/temporal resolution of views increase. We present a systematic method for design and optimization of multi-threaded multi-view video encoding/decoding algorithms using multi-core processors and provide benchmark results for real-time decoding. The proposed multi-core decoding architectures are compliant with the current MVC extension of H.264/AVC international standard, and enable multi-threaded processing with negligible loss of encoding efficiency and minimum processing overhead. Benchmark results show that multi-core processors and multi-threading decoding are necessary for real-time high-definition multi-view video decoding and display. (C) 2010 Elsevier B.V. All rights reserved.Publication Metadata only Characterization of fluid mixtures at high pressures using frequency response of microcantilevers(2017) Bozkurt, Asuman Aşıkoğlu; Jonas, Alexandr; Department of Chemical and Biological Engineering; N/A; Department of Physics; Department of Mechanical Engineering; Department of Chemical and Biological Engineering; Eris, Gamze; Baloch, Shadi Khan; Kiraz, Alper; Alaca, Burhanettin Erdem; Erkey, Can; Researcher; PhD Student; Faculty Memeber; Faculty Member; Faculty Member; Department of Physics; Department of Mechanical Engineering; Department of Chemical and Biological Engineering; Koç University Tüpraş Energy Center (KUTEM) / Koç Üniversitesi Tüpraş Enerji Merkezi (KÜTEM); Koç University Surface Science and Technology Center (KUYTAM) / Koç Üniversitesi Yüzey Teknolojileri Araştırmaları Merkezi (KUYTAM); College of Engineering; Graduate School of Sciences and Engineering; College of Sciences; College of Engineering; College of Engineering; N/A; N/A; 22542; 115108; 29633The frequency response of ferromagnetic nickel microcantilevers immersed in binary mixtures of carbon dioxide (CO2) and nitrogen (N-2) at 308 K and pressures up to 23 MPa was investigated. Experimental data were analyzed using the model developed by Sader for a clamped oscillatory beam immersed in a fluid and a very good agreement between the measured resonant frequencies and quality factors (Q factors) and the theoretical predictions of the model with cantilever characteristic parameters regressed from experimental data was observed. This suggested that the data could be used to simultaneously measure the density and the viscosity of fluid mixtures over a wide range of pressures. Subsequently, density and viscosity of binary mixtures of CO2 and N-2 were determined using N-2 as the reference fluid and compared to the predictions of Gerg equation of state and Chung equation, respectively. For the studied fluids with different compositions, the average relative difference between the experimental density values and the values predicted using Gerg equation of state and NIST database ranged from 1.0 to 13%. The average relative difference between the experimental viscosity values and the values obtained using Chung equation and NIST database ranged from 2.4 to 15%. Since the resonant frequency and Q factor were found to vary with composition at a fixed temperature and pressure, the technique can in principle also be used to measure the composition of a binary mixture at a fixed temperature and pressure. The study represents the first systematic attempt to use microcantilevers for the characterization of high-pressure fluid mixtures and paves the way for devising portable sensors for in-line monitoring of thermophysical properties and composition of fluid mixtures under a wide range of environmental conditions. (C) 2017 Elsevier B.V. All rights reserved.Publication Metadata only Automatic detection of road types from the third military mapping survey of Austria-Hungary historical map series with deep convolutional neural networks(IEEE-inst Electrical Electronics Engineers inc, 2021) N/A; N/A; Department of History; Can, Yekta Said; Gerrits, Petrus Johannes; Kabadayı, Mustafa Erdem; Resercher; Master Student; Faculty Member; Department of History; College of Social Sciences and Humanities; Graduate School of Social Sciences and Humanities; College of Social Sciences and Humanities; N/A; N/A; 33267With the increased amount of digitized historical documents, information extraction from them gains pace. Historical maps contain valuable information about historical, geographical and economic aspects of an era. Retrieving information from historical maps is more challenging than processing modern maps due to lower image quality, degradation of documents and the massive amount of non-annotated digital map archives. Convolutional Neural Networks (CNN) solved many image processing challenges with great success, but they require a vast amount of annotated data. for historical maps, this means an unprecedented scale of manual data entry and annotation. in this study, we first manually annotated the Third Military Mapping Survey of austria-Hungary historical map series conducted between 1884 and 1918 and made them publicly accessible. We recognized different road types and their pixel-wise positions automatically by using a CNN architecture and achieved promising results.Publication Metadata only An adaptive admittance controller for collaborative drilling with a robot based on subtask classification via deep learning(Elsevier, 2022) Aydin, Yusuf; N/A; N/A; N/A; Department of Mechanical Engineering; Güler, Berk; Niaz, Pouya Pourakbarian; Madani, Alireza; Başdoğan, Çağatay; Master Student; Master Student; Master Student; Faculty Member; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; N/A; 125489In this paper, we propose a supervised learning approach based on an Artificial Neural Network (ANN) model for real-time classification of subtasks in a physical human-robot interaction (pHRI) task involving contact with a stiff environment. In this regard, we consider three subtasks for a given pHRI task: Idle, Driving, and Contact. Based on this classification, the parameters of an admittance controller that regulates the interaction between human and robot are adjusted adaptively in real time to make the robot more transparent to the operator (i.e. less resistant) during the Driving phase and more stable during the Contact phase. The Idle phase is primarily used to detect the initiation of task. Experimental results have shown that the ANN model can learn to detect the subtasks under different admittance controller conditions with an accuracy of 98% for 12 participants. Finally, we show that the admittance adaptation based on the proposed subtask classifier leads to 20% lower human effort (i.e. higher transparency) in the Driving phase and 25% lower oscillation amplitude (i.e. higher stability) during drilling in the Contact phase compared to an admittance controller with fixed parameters.