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Publication Open Access 3D microprinting of iron platinum nanoparticle-based magnetic mobile microrobots(Wiley, 2021) Giltinan, Joshua; Sridhar, Varun; Bozüyük, Uğur; Sheehan, Devin; Department of Mechanical Engineering; Sitti, Metin; Faculty Member; Department of Mechanical Engineering; School of Medicine; College of Engineering; 297104Wireless magnetic microrobots are envisioned to revolutionize minimally invasive medicine. While many promising medical magnetic microrobots are proposed, the ones using hard magnetic materials are not mostly biocompatible, and the ones using biocompatible soft magnetic nanoparticles are magnetically very weak and, therefore, difficult to actuate. Thus, biocompatible hard magnetic micro/nanomaterials are essential toward easy-to-actuate and clinically viable 3D medical microrobots. To fill such crucial gap, this study proposes ferromagnetic and biocompatible iron platinum (FePt) nanoparticle-based 3D microprinting of microrobots using the two-photon polymerization technique. A modified one-pot synthesis method is presented for producing FePt nanoparticles in large volumes and 3D printing of helical microswimmers made from biocompatible trimethylolpropane ethoxylate triacrylate (PETA) polymer with embedded FePt nanoparticles. The 30 mu m long helical magnetic microswimmers are able to swim at speeds of over five body lengths per second at 200Hz, making them the fastest helical swimmer in the tens of micrometer length scale at the corresponding low-magnitude actuation fields of 5-10mT. It is also experimentally in vitro verified that the synthesized FePt nanoparticles are biocompatible. Thus, such 3D-printed microrobots are biocompatible and easy to actuate toward creating clinically viable future medical microrobots.
Publication Metadata only A deterministic analysis of an online convex mixture of experts algorithm(Institute of Electrical and Electronics Engineers (IEEE), 2015) Özkan, Hüseyin; Dönmez, Mehmet A.; N/A; Tunç, Sait; Master Student; Graduate School of Sciences and Engineering; N/AWe analyze an online learning algorithm that adaptively combines outputs of two constituent algorithms (or the experts) running in parallel to estimate an unknown desired signal. This online learning algorithm is shown to achieve and in some cases outperform the mean-square error (MSE) performance of the best constituent algorithm in the steady state. However, the MSE analysis of this algorithm in the literature uses approximations and relies on statistical models on the underlying signals. Hence, such an analysis may not be useful or valid for signals generated by various real-life systems that show high degrees of nonstationarity, limit cycles and that are even chaotic in many cases. In this brief, we produce results in an individual sequence manner. In particular, we relate the time-accumulated squared estimation error of this online algorithm at any time over any interval to the one of the optimal convex mixture of the constituent algorithms directly tuned to the underlying signal in a deterministic sense without any statistical assumptions. In this sense, our analysis provides the transient, steady-state, and tracking behavior of this algorithm in a strong sense without any approximations in the derivations or statistical assumptions on the underlying signals such that our results are guaranteed to hold. We illustrate the introduced results through examples.Publication Metadata only A dynamic path planning approach for multirobot sensor-based coverage considering energy constraints(IEEE-Inst Electrical Electronics Engineers Inc, 2014) Yazici, Ahmet; Parlaktuna, Osman; Sipahioglu, Aydin; N/A; Kirlik, Gökhan; PhD Student; Graduate School of Sciences and Engineering; N/AMultirobot sensor-based coverage path planning determines a tour for each robot in a team such that every point in a given workspace is covered by at least one robot using its sensors. In sensor-based coverage of narrow spaces, i.e., obstacles lie within the sensor range, a generalized Voronoi diagram (GVD)-based graph can be used to model the environment. A complete sensor-based coverage path plan for the robot team can be obtained by using the capacitated arc routing problem solution methods on the GVD-based graph. Unlike capacitated arc routing problem, sensor-based coverage problem requires to consider two types of edge demands. Therefore, modified Ulusoy algorithm is used to obtain mobile robot tours by taking into account two different energy consumption cases during sensor-based coverage. However, due to the partially unknown nature of the environment, the robots may encounter obstacles on their tours. This requires a replanning process that considers the remaining energy capacities and the current positions of the robots. In this paper, the modified Ulusoy algorithm is extended to incorporate this dynamic planning problem. A dynamic path-planning approach is proposed for multirobot sensor-based coverage of narrow environments by considering the energy capacities of the mobile robots. The approach is tested in a laboratory environment using Pioneer 3-DX mobile robots. Simulations are also conducted for a larger test environment.Publication Metadata only A robotic indenter for minimally invasive measurement and characterization of soft tissue response(Elsevier, 2007) Avtan, Levent; Düzgün, Oktay; N/A; N/A; Department of Mechanical Engineering; Samur, Evren; Sedef, Mert; Başdoğan, Çağatay; Master Student; Master Student; Faculty Member; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering College of Engineering; 192890; N/A; 125489The lack of experimental data in current literature on material properties of soft tissues in living condition has been a significant obstacle in the development of realistic soft tissue models for virtual reality based surgical simulators used in medical training. A robotic indenter was developed for minimally invasive measurement of soft tissue properties in abdominal region during a laparoscopic surgery. Using the robotic indenter, force versus displacement and force versus time responses of pig liver under static and dynamic loading conditions were successfully measured to characterize its material properties in three consecutive steps. First, the effective elastic modulus of pig liver was estimated as 10-15 kPa from the force versus displacement data of static indentations based on the small deformation assumption. Then, the stress relaxation function, relating the variation of stress with respect to time, was determined from the force versus time response data via curve fitting. Finally, an inverse finite element solution was developed using ANSYS finite element package to estimate the optimum values of viscoelastic and nonlinear hyperelastic material properties of pig liver through iterations. The initial estimates of the material properties for the iterations were extracted from the experimental data for faster convergence of the solutions.Publication Metadata only A stochastic framework for rate-distortion optimized video coding over error-prone networks(IEEE-Inst Electrical Electronics Engineers Inc, 2007) Harmanci, Oztan; Department of Electrical and Electronics Engineering; Tekalp, Ahmet Murat; Faculty Member; Department of Electrical and Electronics Engineering; College of Engineering; 26207This paper proposes a complete stochastic framework for RD optimal encoder design for video over error-prone networks, which applies to any motion-compensated predictive video codec. The distortion measure has been taken as the mean square error over an ensemble of channels given an estimate of the instantaneous packet loss probability. We show that 1) the optimal motion compensated prediction, in the MSE sense, requires computation of the expected value of the reference frames, and 2) calculation of the MSE (distortion measure) requires computation of the second moment of the reference frames. We propose a recursive procedure for the computation of both the expected value and second moment of the reference frames, which are together called the stochastic frame buffer. Furthermore, we propose a stochastic RD optimization method for selection of the optimal macroblock mode and motion vectors given the instantaneous packet loss probability. If available, channel feedback can also be incorporated into the proposed stochastic framework. However, the proposed framework does not require a feedback channel to exist, and when it exists, it does not have to be lossless. In the absence of any packet losses, the proposed stochastic framework reduces to the well-known deterministic RD optimization procedures. One possible application of the optimal stochastic framework would be for multicast streaming to an ensemble of receivers. Experimental results indicate that the proposed framework outperforms other available error tracking and control schemes.Publication Metadata only Analysis of head gesture and prosody patterns for prosody-driven head-gesture animation(IEEE Computer Soc, 2008) Sargin, Mehmet Emre; Department of Computer Engineering; Department of Computer Engineering; Department of Electrical and Electronics Engineering; Yemez, Yücel; Erzin, Engin; Tekalp, Ahmet Murat; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Department of Electrical and Electronics Engineering; College of Engineering; College of Engineering; College of Engineering; 107907; 34503; 26207We propose a new two-stage framework for joint analysis of head gesture and speech prosody patterns of a speaker toward automatic realistic synthesis of head gestures from speech prosody. In the first stage analysis, we perform Hidden Markov Model (HMM)-based unsupervised temporal segmentation of head gesture and speech prosody features separately to determine elementary head gesture and speech prosody patterns, respectively, for a particular speaker. In the second stage, joint analysis of correlations between these elementary head gesture and prosody patterns is performed using Multistream HMMs to determine an audio-visual mapping model. The resulting audio-visual mapping model is then employed to synthesize natural head gestures from arbitrary input test speech given a head model for the speaker. In the synthesis stage, the audio-visual mapping model is used to predict a sequence of gesture patterns from the prosody pattern sequence computed for the input test speech. The Euler angles associated with each gesture pattern are then applied to animate the speaker head model. Objective and subjective evaluations indicate that the proposed synthesis by analysis scheme provides natural looking head gestures for the speaker with any input test speech, as well as in "prosody transplant" and "gesture transplant" scenarios.Publication Metadata only Characterization of frequency-dependent material properties of human liver and its pathologies using an impact hammer(Elsevier, 2011) Dogusoy, Gulen; Tokat, Yaman; N/A; N/A; Department of Mechanical Engineering; Özcan, Mustafa Umut; Öcal, Sina; Başdoğan, Çağatay; Master Student; Master Student; Faculty Member; Department of Mechanical Engineering; Graduate School of Sciences and Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; N/A; 125489The current methods for characterization of frequency-dependent material properties of human liver are very limited. In fact, there is almost no data available in the literature showing the variation in dynamic elastic modulus of healthy or diseased human liver as a function of excitation frequency. We show that frequency-dependent dynamic material properties of a whole human liver can be easily and efficiently characterized by an impact hammer. The procedure only involves a light impact force applied to the tested liver by a hand-held hammer. The results of our experiments conducted with 15 human livers harvested from the patients having some form of liver disease show that the proposed approach can successfully differentiate the level of fibrosis in human liver. We found that the storage moduli of the livers having no fibrosis (F0) and that of the cirrhotic livers (F4) varied from 10 to 20 kPa and 20 to 50 kPa for the frequency range of 0-80 Hz, respectively.Publication Metadata only Convolutive bounded component analysis algorithms for independent and dependent source separation(IEEE-inst Electrical Electronics Engineers inc, 2015) N/A; N/A; Department of Electrical and Electronics Engineering; İnan, Hüseyin Atahan; Erdoğan, Alper Tunga; Master Student; Faculty Member; Department of Electrical and Electronics Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 41624Bounded component analysis (BCa) is a framework that can be considered as a more general framework than independent component analysis (ICa) under the boundedness constraint on sources. Using this framework, it is possible to separate dependent as well as independent components from their mixtures. in this paper, As an extension of a recently introduced instantaneous BCa approach, we introduce a family of convolutive BCa criteria and corresponding algorithms. We prove that the global optima of the proposed criteria, under generic BCa assumptions, Are equivalent to a set of perfect separators. the algorithms introduced in this paper are capable of separating not only the independent sources but also the sources that are dependent/correlated in both component (space) and sample (time) dimensions. therefore, under the condition that the sources are bounded, they can be considered as extended convolutive ICa algorithms with additional dependent/correlated source separation capability. Furthermore, they have potential to provide improvement in separation performance, especially for short data records. This paper offers examples to illustrate the space-time correlated source separation capability through a copula distribution-based example. in addition, A frequency-selective Multiple input Multiple Output equalization example demonstrates the clear performance advantage of the proposed BCa approach over the state-of-the-art ICa-based approaches in setups involving convolutive mixtures of digital communication sources.Publication Metadata only Discriminative analysis of lip motion features for speaker identification and speech-reading(Ieee-Inst Electrical Electronics Engineers Inc, 2006) N/A; Department of Computer Engineering; Department of Computer Engineering; Department of Computer Engineering; Çetingül, Hasan Ertan; Yemez, Yücel; Erzin, Engin; Tekalp, Ahmet Murat; Master Student; Faculty Member; Faculty Member; Faculty Member; Department of Computer Engineering; Graduate School of Sciences and Engineering; College of Engineering; College of Engineering; College of Engineering; N/A; 107907; 34503; 26207There have been several studies that jointly use audio, lip intensity, and lip geometry information for speaker identification and speech-reading applications. This paper proposes using explicit lip motion information, instead of or in addition to lip intensity and/or geometry information, for speaker identification and speech-reading within a unified feature selection and discrimination analysis framework, and addresses two important issues: 1) Is using explicit lip motion information useful, and, 2) if so, what are the best lip motion features for these two applications? The best lip motion features for speaker identification are considered to be those that result in the highest discrimination of individual speakers in a population, whereas for speech-reading, the best features are those providing the highest phoneme/word/phrase recognition rate. Several lip motion feature candidates have been considered including dense motion features within a bounding box about the lip, lip contour motion features, and combination of these with lip shape features. Furthermore, a novel two-stage, spatial, and temporal discrimination analysis is introduced to select the best lip motion features for speaker identification and speech-reading applications. Experimental results using an hidden-Markov-model-based recognition system indicate that using explicit lip motion information provides additional performance gains in both applications, and lip motion features prove more valuable in the case of speech-reading application.Publication Metadata only Efficient multitask multiple kernel learning with application to cancer research(Ieee-Inst Electrical Electronics Engineers Inc, 2022) N/A; N/A; Department of Industrial Engineering; Rahimi, Arezou; Gönen, Mehmet; PhD Student; Faculty Member; Department of Industrial Engineering; Graduate School of Sciences and Engineering; College of Engineering; N/A; 237468Multitask multiple kernel learning (MKL) algorithms combine the capabilities of incorporating different data sources into the prediction model and using the data from one task to improve the accuracy on others. However, these methods do not necessarily produce interpretable results. Restricting the solutions to the set of interpretable solutions increases the computational burden of the learning problem significantly, leading to computationally prohibitive run times for some important biomedical applications. That is why we propose a multitask MKL formulation with a clustering of tasks and develop a highly time-efficient solution approach for it. Our solution method is based on the Benders decomposition and treating the clustering problem as finding a given number of tree structures in a graph; hence, it is called the forest formulation. We use our method to discriminate early-stage and late-stage cancers using genomic data and gene sets and compare our algorithm against two other algorithms. The two other algorithms are based on different approaches for linearization of the problem while all algorithms make use of the cutting-plane method. Our results indicate that as the number of tasks and/or the number of desired clusters increase, the forest formulation becomes increasingly favorable in terms of computational performance.
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