Integration of speech-processing technologies into Activobank's client interaction process

This dissertation analyzes the possibilities of utilizing speech-processing technologies to transform the user experience of ActivoBank’s customers while using remote banking solutions. The technologies are examined through different criteria to determine if they support the bank’s goals and strategy and whether they should be incorporated in the bank’s offering. These criteria include the alignment with ActivoBank’s values, the suitability of the technology providers, the benefits these technologies entail, potential risks, appeal to the customers and impact on customer satisfaction. The analysis suggests that ActivoBank might not be in a position to adopt these technologies at this point in time.

Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Gd2O3: Eu3+/PPO/POPOP/PS composites for digital imaging radiation detectors

Polymer based scintillator composites have been produced by combining polystyrene (PS) and Gd2O3:Eu3+ scintillator nanoparticles. Polystyrene has been used since it is a flexible and stable binder matrix, resistant to thermal and light deterioration and with suitable optical properties. Gd2O3:Eu3+ has been selected as scintillator material due to its wide band gap, high density and visible light yield. The optical, thermal and electrical characteristics of the composites were studied as a function of filler content, together with their performance as scintillator material. Additionally 1wt.% of 2,5 dipheniloxazol (PPO) and 0.01wt.% of (1,4-bis(2-(5-phenioxazolil))-benzol (POPOP) were introduced in the polymer matrix in order to strongly improve light yield, i.e. the measured intensity of the output visible radiation, under X-ray irradiation. Whereas increasing scintillator filler concentration (from 0.25wt.% to 7.5wt.%) increases scintillator light yield, decreases the optical transparency of the composite. The addition of PPO and POPOP, strongly increased the overall 2 transduction performance of the composite due to specific absorption and re-emission processes. It is thus shown that Gd2O3:Eu3+/PPO/POPOP/PS composites in 0.25 wt.% of scintillator content with fluorescence molecules is suitable for the development of innovate large area X-ray radiation detectors with huge demand from the industries.

SOFHIA: a CAD environment to design digital control systems

"Series Title: IFIP - The International Federation for Information Processing, ISSN 1868-4238"

FISHji: new ImageJ macros for the quantification of fluorescence in epifluorescence images

Fluorescence in situ hybridization (FISH) is based on the use of fluorescent staining dyes, however, the signal intensity of the images obtained by microscopy is seldom quantified with accuracy by the researcher. The development of innovative digital image processing programs and tools has been trying to overcome this problem, however, the determination of fluorescent intensity in microscopy images still has issues due to the lack of precision in the results and the complexity of existing software. This work presents FISHji, a set of new ImageJ methods for automated quantification of fluorescence in images obtained by epifluorescence microscopy. To validate the methods, results obtained by FISHji were compared with results obtained by flow cytometry. The mean correlation between FISHji and flow cytometry was high and significant, showing that the imaging methods are able to accurately assess the signal intensity of fluorescence images. FISHji are available for non-commercial use at http://paginas.fe.up.pt/nazevedo/.

Basic components of cortical processing are shared in visual and auditory modality

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2009

Downstream processing of influenza whole-virions for vaccine production

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2009

Patrimoni Digital de Catalunya, a year and a half experience

E-repositories are part of the e-science, and they are based on the e-infrastructure. The Centre de Supercomputació de Catalunya (CESCA) together with the Consorci de Biblioteques Universitàries de Catalunya (CBUC) started in 1999 a cooperative repository, named TDR, to file, in digital format, the full-text of the read thesis at the universities of our country in order to spread them worldwide in open access, while at the same time, preserving the intellectual copyright of the authors. Since then, four additional cooperative repositories have been created: RECERCAT for research papers; RACO for scientific, cultural and erudite Catalan magazines; MDC for Catalan digital collections of pictures, maps, posters and old magazines; and PADICAT for archiving Catalan digital web content; The main objective of the latter is to archive Catalan web sites. That is, PADICAT collects, processes and provides permanent access to the entire cultural, scientific and general output of Catalonia in digital format. The repository manager is the Biblioteca de Catalunya, as the institution responsible for compiling, processing and distributing the bibliographic heritage of Catalonia, while CESCA is the technology partner. On September 11th, 2006 the repository went into operation for the general public, with some thirty websites archived. After one year and a half, it has 2.720 captures of more than 1.000 websites. This includes 34 million files (HTML, images...) and two terabytes of data. The objective of this paper is to present PADICAT and our experience developing and managing it.We describe the repository briefly, we explain the technology used to implement it and we comment our experiences during its first year and a half.

Comparative study of human erythrocytes by digital holographic microscopy, confocal microscopy, and impedance volume analyzer.

Red blood cell (RBC) parameters such as morphology, volume, refractive index, and hemoglobin content are of great importance for diagnostic purposes. Existing approaches require complicated calibration procedures and robust cell perturbation. As a result, reference values for normal RBC differ depending on the method used. We present a way for measuring parameters of intact individual RBCs by using digital holographic microscopy (DHM), a new interferometric and label-free technique with nanometric axial sensitivity. The results are compared with values achieved by conventional techniques for RBC of the same donor and previously published figures. A DHM equipped with a laser diode (lambda = 663 nm) was used to record holograms in an off-axis geometry. Measurements of both RBC refractive indices and volumes were achieved via monitoring the quantitative phase map of RBC by means of a sequential perfusion of two isotonic solutions with different refractive indices obtained by the use of Nycodenz (decoupling procedure). Volume of RBCs labeled by membrane dye Dil was analyzed by confocal microscopy. The mean cell volume (MCV), red blood cell distribution width (RDW), and mean cell hemoglobin concentration (MCHC) were also measured with an impedance volume analyzer. DHM yielded RBC refractive index n = 1.418 +/- 0.012, volume 83 +/- 14 fl, MCH = 29.9 pg, and MCHC 362 +/- 40 g/l. Erythrocyte MCV, MCH, and MCHC achieved by an impedance volume analyzer were 82 fl, 28.6 pg, and 349 g/l, respectively. Confocal microscopy yielded 91 +/- 17 fl for RBC volume. In conclusion, DHM in combination with a decoupling procedure allows measuring noninvasively volume, refractive index, and hemoglobin content of single-living RBCs with a high accuracy.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

MSight: an image analysis software for liquid chromatography-mass spectrometry.

Images obtained from high-throughput mass spectrometry (MS) contain information that remains hidden when looking at a single spectrum at a time. Image processing of liquid chromatography-MS datasets can be extremely useful for quality control, experimental monitoring and knowledge extraction. The importance of imaging in differential analysis of proteomic experiments has already been established through two-dimensional gels and can now be foreseen with MS images. We present MSight, a new software designed to construct and manipulate MS images, as well as to facilitate their analysis and comparison.

Structured output SVM for remote sensing image classification

In the recent years, kernel methods have revealed very powerful tools in many application domains in general and in remote sensing image classification in particular. The special characteristics of remote sensing images (high dimension, few labeled samples and different noise sources) are efficiently dealt with kernel machines. In this paper, we propose the use of structured output learning to improve remote sensing image classification based on kernels. Structured output learning is concerned with the design of machine learning algorithms that not only implement input-output mapping, but also take into account the relations between output labels, thus generalizing unstructured kernel methods. We analyze the framework and introduce it to the remote sensing community. Output similarity is here encoded into SVM classifiers by modifying the model loss function and the kernel function either independently or jointly. Experiments on a very high resolution (VHR) image classification problem shows promising results and opens a wide field of research with structured output kernel methods.

Inexperienced sonographers can successfully visualize and assess a three-dimensional image of the fetal face using a standardized ultrasound protocol

Introduction: A standardized three-dimensional ultrasonographic (3DUS) protocol is described that allows fetal face reconstruction. Ability to identify cleft lip with 3DUS using this protocol was assessed by operators with minimal 3DUS experience. Material and Methods: 260 stored volumes of fetal face were analyzed using a standardized protocol by operators with different levels of competence in 3DUS. The outcomes studied were: (1) the performance of post-processing 3D face volumes for the detection of facial clefts; (2) the ability of a resident with minimal 3DUS experience to reconstruct the acquired facial volumes, and (3) the time needed to reconstruct each plane to allow proper diagnosis of a cleft. Results: The three orthogonal planes of the fetal face (axial, sagittal and coronal) were adequately reconstructed with similar performance when acquired by a maternal-fetal medicine specialist or by residents with minimal experience (72 vs. 76%, p = 0.629). The learning curve for manipulation of 3DUS volumes of the fetal face corresponds to 30 cases and is independent of the operator's level of experience. Discussion: The learning curve for the standardized protocol we describe is short, even for inexperienced sonographers. This technique might decrease the length of anatomy ultrasounds and improve the ability to visualize fetal face anomalies.

Advantages of digital holographic microscopy for real-time full field absolute phase imaging

Different interferometric techniques were developed last decade to obtain full field, quantitative, and absolute phase imaging, such as phase-shifting, Fourier phase microscopy, Hilbert phase microscopy or digital holographic microscopy (DHM). Although, these techniques are very similar, DHM combines several advantages. In contrast, to phase shifting, DHM is indeed capable of single-shot hologram recording allowing a real-time absolute phase imaging. On the other hand, unlike to Fourier phase or Hilbert phase microscopy, DHM does not require to record in focus images of the specimen on the digital detector (CCD or CMOS camera), because a numerical focalization adjustment can be performed by a numerical wavefront propagation. Consequently, the depth of view of high NA microscope objectives is numerically extended. For example, two different biological cells, floating at different depths in a liquid, can be focalized numerically from the same digital hologram. Moreover, the numerical propagation associated to digital optics and automatic fitting procedures, permits vibrations insensitive full- field phase imaging and the complete compensation for a priori any image distortion or/and phase aberrations introduced for example by imperfections of holders or perfusion chamber. Examples of real-time full-field phase images of biological cells have been demonstrated. ©2008 COPYRIGHT SPIE

Red blood cell structure and dynamics explored with digital holographic microspcopy

Digital holographic microscopy (DHM) is a technique that allows obtaining, from a single recorded hologram, quantitative phase image of living cell with interferometric accuracy. Specifically the optical phase shift induced by the specimen on the transmitted wave front can be regarded as a powerful endogenous contrast agent, depending on both the thickness and the refractive index of the sample. Thanks to a decoupling procedure cell thickness and intracellular refractive index can be measured separately. Consequently, Mean corpuscular volume (MCV) and mean corpuscular hemoglobin concentration (MCHC), two highly relevant clinical parameters, have been measured non-invasively at a single cell level. The DHM nanometric axial and microsecond temporal sensitivities have permitted to measure the red blood cell membrane fluctuations (CMF) on the whole cell surface. ©2009 COPYRIGHT SPIE--The International Society for Optical Engineering.