@book{55815, author = {{Kepper, Johannes and Roland, Perry D.}}, title = {{{Music Encoding Initiative Guidelines Version 2.1.0}}}, year = {{2013}}, } @inproceedings{55824, author = {{Kepper, Johannes and Roland, Perry D. and Röwenstrunk, Daniel}}, booktitle = {{Proceedings of Balisage: The Markup Conference 2013}}, title = {{{Musical Variants in Encoding, Analysis and Visualization}}}, doi = {{10.4242/BalisageVol10.Kepper01}}, year = {{2013}}, } @inproceedings{36920, abstract = {{In the electronic system development, energy consumption is clearly becoming one of the most important design concerns. From the system level point of view, Dynamic Power Management (DPM) and Dynamic Voltage and Frequency Scaling (DVFS) are two mostly applied techniques to adjust the tradeoff between the performance and power dissipation at runtime. In this paper, we study the problem of combined application of both techniques with regard to hard real-time systems running on cluster-based multi-core processors. To optimize the processor energy consumption, a heuristic based on simulated annealing with efficient termination criterion is proposed. The experiment results show that the proposed algorithm outperforms the existing approaches in terms of the energy reduction. }}, author = {{He, Da and Müller, Wolfgang}}, booktitle = {{Proceedings of the International Conference on Applied Computing (AC)}}, editor = {{Weghorn, Hans}}, isbn = {{978-989-8533-20-3 }}, keywords = {{Dynamic Power Management, Dynamic Voltage and Frequency Scaling, Hard Real-Time, Multi-core Processor}}, title = {{{An Energy-Efficient Heuristic for Hard Real-Time System on Multi-Core Processors}}}, year = {{2013}}, } @article{37283, author = {{Gerholz, K.-H. and Bödeker, J. and Eberhardt, A. and Kerstingtombroke, D. and Langeleh, D. and Temmen, Katrin}}, journal = {{Wirtschaft und Erziehung}}, pages = {{64--69}}, title = {{{Lehrerbildung praxisorientiert gestalten - Das Projekt InnoTrans Uni-BK}}}, year = {{2013}}, } @article{22584, author = {{Dang, Van-Son and Parala, Harish and Kim, Jin Hyun and Xu, Ke and Srinivasan, Nagendra B. and Edengeiser, Eugen and Havenith, Martina and Wieck, Andreas D. and de los Arcos de Pedro, Maria Teresa and Fischer, Roland. A. and Devi, Anjana}}, issn = {{1862-6300}}, journal = {{physica status solidi (a)}}, pages = {{416--424}}, title = {{{Electrical and optical properties of TiO2thin films prepared by plasma-enhanced atomic layer deposition}}}, doi = {{10.1002/pssa.201330115}}, year = {{2013}}, } @article{22593, author = {{Srinivasan, N.B. and Thiede, T.B. and de los Arcos de Pedro, Maria Teresa and Gwildies, V. and Krasnopolski, M. and Becker, H.-W. and Rogalla, D. and Devi, A. and Fischer, R.A.}}, issn = {{0257-8972}}, journal = {{Surface and Coatings Technology}}, pages = {{130--136}}, title = {{{Transition metal nitride thin films grown by MOCVD using amidinato based complexes [M(NtBu)2{(iPrN)2CMe}2] (M=Mo, W) as precursors}}}, doi = {{10.1016/j.surfcoat.2013.06.024}}, year = {{2013}}, } @article{22594, author = {{Will, Andreas and de los Arcos de Pedro, Maria Teresa and Corbella, Carles and Hecimovic, Ante and Machura, Patrick D and Winter, Jörg and von Keudell, Achim}}, issn = {{0022-3727}}, journal = {{Journal of Physics D: Applied Physics}}, title = {{{Target implantation and redeposition processes during high-power impulse magnetron sputtering of aluminum}}}, doi = {{10.1088/0022-3727/46/8/084009}}, year = {{2013}}, } @article{22595, author = {{Winter, J and Hecimovic, A and de los Arcos de Pedro, Maria Teresa and Böke, M and Schulz-von der Gathen, V}}, issn = {{0022-3727}}, journal = {{Journal of Physics D: Applied Physics}}, title = {{{Instabilities in high-power impulse magnetron plasmas: from stochasticity to periodicity}}}, doi = {{10.1088/0022-3727/46/8/084007}}, year = {{2013}}, } @inproceedings{38426, author = {{Koch, B. and Noé, Reinhold and Mirvoda, V. and Sandel, D.}}, booktitle = {{2013 OPTICAL FIBER COMMUNICATION CONFERENCE AND EXPOSITION AND THE NATIONAL FIBER OPTIC ENGINEERS CONFERENCE (OFC/NFOEC)}}, isbn = {{978-1-55752-962-6; 978-1-4799-0457-0}}, title = {{{First Endless Optical Polarization and Phase Tracker}}}, year = {{2013}}, } @article{38411, author = {{Koch, B. and Noé, Reinhold and Mirvoda, V. and Sandel, D.}}, issn = {{0013-5194}}, journal = {{ELECTRONICS LETTERS}}, number = {{7}}, pages = {{483--484}}, title = {{{20 krad/s endless optical polarisation and phase control}}}, doi = {{10.1049/el.2013.0485}}, volume = {{49}}, year = {{2013}}, } @inproceedings{38402, author = {{Puntsri, K. and Jan, O. and Al-Bermani, A. and Woerdehoff, C. and Sandel, D. and Hussin, S. and Panhwar, M. F. and Noé, Reinhold and Rueckert, U.}}, booktitle = {{2013 OPTICAL FIBER COMMUNICATION CONFERENCE AND EXPOSITION AND THE NATIONAL FIBER OPTIC ENGINEERS CONFERENCE (OFC/NFOEC)}}, isbn = {{978-1-55752-962-6; 978-1-4799-0457-0}}, title = {{{An Ultralow Complexity Algorithm for Frame Synchronization and IQ Alignment in CO-OFDM Systems}}}, year = {{2013}}, } @article{38319, author = {{Koch, Benjamin and Noé, Reinhold and Sandel, David and Mirvoda, Vitali and Omar, Jan and Puntsri, Kidsanapong}}, issn = {{1041-1135}}, journal = {{IEEE PHOTONICS TECHNOLOGY LETTERS}}, number = {{9}}, pages = {{798--801}}, title = {{{20-Gb/s PDM-RZ-DPSK Transmission With 40 krad/s Endless Optical Polarization Tracking}}}, doi = {{10.1109/LPT.2013.2251877}}, volume = {{25}}, year = {{2013}}, } @article{38230, author = {{Koch, Benjamin and Noé, Reinhold and Sandel, David and Mirvoda, Vitali and Omar, Jan and Puntsri, Kidsanapong}}, journal = {{IEEE Photonics Technology Letters}}, number = {{9}}, pages = {{798--801}}, title = {{{20-Gb/s PDM-RZ-DPSK Transmission With 40 krad/s Endless Optical Polarization Tracking}}}, doi = {{10.1109/LPT.2013.2251877}}, volume = {{25}}, year = {{2013}}, } @article{38369, author = {{Koch, Benjamin and Noé, Reinhold and Sandel, David and Mirvoda, Vitali and Omar, Jan and Puntsri, Kidsanapong}}, issn = {{1041-1135}}, journal = {{IEEE PHOTONICS TECHNOLOGY LETTERS}}, number = {{9}}, pages = {{798--801}}, title = {{{20-Gb/s PDM-RZ-DPSK Transmission With 40 krad/s Endless Optical Polarization Tracking}}}, doi = {{10.1109/LPT.2013.2251877}}, volume = {{25}}, year = {{2013}}, } @inproceedings{40798, abstract = {{Texture analysis of light scattering in tissue is proposed to obtain diagnostic information from breast cancer specimens. Light scattering measurements are minimally invasive, and allow the estimation of tissue morphology to guide the surgeon in resection surgeries. The usability of scatter signatures acquired with a micro-sampling reflectance spectral imaging system was improved utilizing an empirical approximation to the Mie theory to estimate the scattering power on a per-pixel basis. Co-occurrence analysis is then applied to the scattering power images to extract the textural features. A statistical analysis of the features demonstrated the suitability of the autocorrelation for the classification of notmalignant (normal epithelia and stroma, benign epithelia and stroma, inflammation), malignant (DCIS, IDC, ILC) and adipose tissue, since it reveals morphological information of tissue. Non-malignant tissue shows higher autocorrelation values while adipose tissue presents a very low autocorrelation on its scatter texture, being malignant the middle ground. Consequently, a fast linear classifier based on the consideration of just one straightforward feature is enough for providing relevant diagnostic information. A leave-one-out validation of the linear classifier on 29 samples with 48 regions of interest showed classification accuracies of 98.74% on adipose tissue, 82.67% on non-malignant tissue and 72.37% on malignant tissue, in comparison with the biopsy H and E gold standard. This demonstrates that autocorrelation analysis of scatter signatures is a very computationally efficient and automated approach to provide pathological information in real-time to guide surgeon during tissue resection.}}, author = {{Eguizabal, Alma and Laughney, Ashley M. and Garcia-Allende, P. Beatriz and Krishnaswamy, Venkataramanan and Wells, Wendy A. and Paulsen, Keith D. and Pogue, Brian W. and Lopez-Higuera, Jose and Conde, Olga M.}}, booktitle = {{SPIE Photonics West BIOS, VIII Biomedical Applications of Light Scattering}}, title = {{{Linear classifier and textural analysis of optical scattering images for tumor classification during breast cancer extraction}}}, year = {{2013}}, } @inproceedings{40799, abstract = {{Fractal analysis combined with a label-free scattering technique is proposed for describing the pathological architecture of tumors. Clinicians and pathologists are conventionally trained to classify abnormal features such as structural irregularities or high indices of mitosis. The potential of fractal analysis lies in the fact of being a morphometric measure of the irregular structures providing a measure of the object’s complexity and self-similarity. As cancer is characterized by disorder and irregularity in tissues, this measure could be related to tumor growth. Fractal analysis has been probed in the understanding of the tumor vasculature network. This work addresses the feasibility of applying fractal analysis to the scattering power map (as a physical modeling) and principal components (as a statistical modeling) provided by a localized reflectance spectroscopic system. Disorder, irregularity and cell size variation in tissue samples is translated into the scattering power and principal components magnitude and its fractal dimension is correlated with the pathologist assessment of the samples. The fractal dimension is computed applying the box-counting technique. Results show that fractal analysis of ex-vivo fresh tissue samples exhibits separated ranges of fractal dimension that could help classifier combining the fractal results with other morphological features. This contrast trend would help in the discrimination of tissues in the intraoperative context and may serve as a useful adjunct to surgeons.}}, author = {{Eguizabal, Alma and Laughney, Ashley M. and Krishnaswamy, Venkataramanan and Wells, Wendy A. and Paulsen, Keith D. and Pogue, Brian W. and Lopez-Higuera, Jose and Conde, Olga M.}}, booktitle = {{SPIE Photonics West BIOS, VIII Biomedical Applications of Light Scattering}}, title = {{{Fractal analysis of scatter imaging signatures to distinguish breast pathologies}}}, year = {{2013}}, } @article{40796, abstract = {{In this paper we study the existence of locally most powerful invariant tests (LMPIT) for the problem of testing the covariance structure of a set of Gaussian random vectors. The LMPIT is the optimal test for the case of close hypotheses, among those satisfying the invariances of the problem, and in practical scenarios can provide better performance than the typically used generalized likelihood ratio test (GLRT). The derivation of the LMPIT usually requires one to find the maximal invariant statistic for the detection problem and then derive its distribution under both hypotheses, which in general is a rather involved procedure. As an alternative, Wijsman’s theorem provides the ratio of the maximal invariant densities without even finding an explicit expression for the maximal invariant. We first consider the problem of testing whether a set of N-dimensional Gaussian random vectors are uncorrelated or not, and show that the LMPIT is given by the Frobenius norm of the sample coherence matrix. Second, we study the case in which the vectors under the null hypothesis are uncorrelated and identically distributed, that is, the sphericity test for Gaussian vectors, for which we show that the LMPIT is given by the Frobenius norm of a normalized version of the sample covariance matrix. Finally, some numerical examples illustrate the performance of the proposed tests, which provide better results than their GLRT counterparts.}}, author = {{Ramírez, D. and Vía, J. and Santamaría, I. and Scharf, L. L.}}, journal = {{IEEE Trans.\ Inform.\ Theory}}, number = {{4}}, pages = {{2128–2141}}, title = {{{Locally Most Powerful Invariant Tests for Correlation and Sphericity of Gaussian Vectors}}}, doi = {{10.1109/TIT.2012.2232705}}, volume = {{59}}, year = {{2013}}, } @inproceedings{40791, abstract = {{This work presents a variation of canonical correlation analysis (CCA), where the correlation coefficient between the instantaneous power of the projections is maximized, rather than between the projections themselves. The resulting optimization problem is not convex, and we have to resort to a sub-optimal approach. Concretely, we propose a two-step solution consisting of the singular value decomposition (SVD) of a "coherence" matrix followed by a rank-one matrix approximation. This technique is applied to blindly recovering signals in a model that is motivated by the study of neuronal dynamics in humans using electroencephalography (EEG) and magnetoencephalography (MEG). A distinctive feature of this model is that it allows recovery of amplitude-amplitude coupling between neuronal processes.}}, author = {{Ramírez, D. and Schreier, P. J. and Vía, J. and Nikulin, V. V.}}, booktitle = {{Proc.\ IEEE Int.\ Conf.\ Acoustics, Speech and Signal Process.}}, title = {{{Power-CCA: Maximizing the Correlation Coefficient between the Power of Projections}}}, doi = {{10.1109/ICASSP.2013.6638864}}, year = {{2013}}, } @article{40787, abstract = {{Breast tumors are blindly identified using Principal (PCA) and Independent Component Analysis (ICA) of localized reflectance measurements. No assumption of a particular theoretical model for the reflectance needs to be made, while the resulting features are proven to have discriminative power of breast pathologies. Normal, benign and malignant breast tissue types in lumpectomy specimens were imaged ex vivo and a surgeon-guided calibration of the system is proposed to overcome the limitations of the blind analysis. A simple, fast and linear classifier has been proposed where no training information is required for the diagnosis. A set of 29 breast tissue specimens have been diagnosed with a sensitivity of 96% and specificity of 95% when discriminating benign from malignant pathologies. The proposed hybrid combination PCA-ICA enhanced diagnostic discrimination, providing tumor probability maps, and intermediate PCA parameters reflected tissue optical properties.}}, author = {{Eguizabal, Alma and Laughney, Ashley M. and Garcia-Allende, P. Beatriz and Krishnaswamy, Venkataramanan and Wells, Wendy A. and Paulsen, Keith D. and Pogue, Brian W. and Lopez-Higuera, Jose M. and Conde, Olga M.}}, journal = {{Biomed. Opt. Express}}, number = {{7}}, pages = {{1104–1118}}, title = {{{Direct identification of breast cancer pathologies using blind separation of label-free localized reflectance measurements}}}, doi = {{10.1364/BOE.4.001104}}, volume = {{4}}, year = {{2013}}, } @inproceedings{42027, author = {{Jöns, Klaus D. and Atkinson, P. and Müller, M. and Heldmaier, M. and Ulrich, S. M. and Schmidt, O. G. and Michler, P.}}, number = {{1}}, pages = {{126--130}}, title = {{{Triggered Indistinguishable Single Photons with Narrow Line Widths from Site-Controlled Quantum Dots}}}, volume = {{13}}, year = {{2013}}, }