Implementation of the Rijndael-AES algorithm on a Sage-Math worksheet

La principal motivació d'aquest treball ha estat implementar l'algoritme Rijndael-AES en un full Sage-math, paquet de software matemàtic de lliure distribució i en actual desenvolupament, aprofitant les seves eines i funcionalitats integrades.

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

Characterisation of the LMS200 laser beam under the influence of blockage surfaces. Influence on 3D scanning of tree orchards

The geometric characterisation of tree orchards is a high-precision activity comprising the accurate measurement and knowledge of the geometry and structure of the trees. Different types of sensors can be used to perform this characterisation. In this work a terrestrial LIDAR sensor (SICK LMS200) whose emission source was a 905-nm pulsed laser diode was used. Given the known dimensions of the laser beam cross-section (with diameters ranging from 12 mm at the point of emission to 47.2 mm at a distance of 8 m), and the known dimensions of the elements that make up the crops under study (flowers, leaves, fruits, branches, trunks), it was anticipated that, for much of the time, the laser beam would only partially hit a foreground target/object, with the consequent problem of mixed pixels or edge effects. Understanding what happens in such situations was the principal objective of this work. With this in mind, a series of tests were set up to determine the geometry of the emitted beam and to determine the response of the sensor to different beam blockage scenarios. The main conclusions that were drawn from the results obtained were: (i) in a partial beam blockage scenario, the distance value given by the sensor depends more on the blocked radiant power than on the blocked surface area; (ii) there is an area that influences the measurements obtained that is dependent on the percentage of blockage and which ranges from 1.5 to 2.5 m with respect to the foreground target/object. If the laser beam impacts on a second target/object located within this range, this will affect the measurement given by the sensor. To interpret the information obtained from the point clouds provided by the LIDAR sensors, such as the volume occupied and the enclosing area, it is necessary to know the resolution and the process for obtaining this mesh of points and also to be aware of the problem associated with mixed pixels.

Diffraction grating couplers milled in Si3N4 rib waveguides with a focused ion beam

Focused ion beam milling is a processing technology which allows flexible direct writing of nanometer scale features efficiently substituting electron beam lithography. No mask need results in ability for patterns writing even on fragile micromechanical devices. In this work we studied the abilities of the tool for fabrication of diffraction grating couplers in silicon nitride waveguides. The gratings were fabricated on a chip with extra fragile cantilevers of sub micron thickness. Optical characterization of the couplers was done using excitation of the waveguides in visible range by focused Gaussian beams of different waist sizes. Influence of Ga+ implantation on the device performance was studied.

A Gradient based algorithm for blind inversion of Wiener System using multi-variate score functions

A Wiener system is a linear time-invariant filter, followed by an invertible nonlinear distortion. Assuming that the input signal is an independent and identically distributed (iid) sequence, we propose an algorithm for estimating the input signal only by observing the output of the Wiener system. The algorithm is based on minimizing the mutual information of the output samples, by means of a steepest descent gradient approach.

Improving algorithm speed in PNL mixture separation and Wiener system inversion

This paper proposes a very simple method for increasing the algorithm speed for separating sources from PNL mixtures or invertingWiener systems. The method is based on a pertinent initialization of the inverse system, whose computational cost is very low. The nonlinear part is roughly approximated by pushing the observations to be Gaussian; this method provides a surprisingly good approximation even when the basic assumption is not fully satisfied. The linear part is initialized so that outputs are decorrelated. Experiments shows the impressive speed improvement.

Changes of Root Length and Root-to-Crown Ratio after Apical Surgery: An Analysis by Using Cone-beam Computed Tomography.

INTRODUCTION: Apical surgery is an important treatment option for teeth with post-treatment periodontitis. Although apical surgery involves root-end resection, no morphometric data are yet available about root-end resection and its impact on the root-to-crown ratio (RCR). The present study assessed the length of apicectomy and calculated the loss of root length and changes of RCR after apical surgery. METHODS: In a prospective clinical study, cone-beam computed tomography scans were taken preoperatively and postoperatively. From these images, the crown and root lengths of 61 roots (54 teeth in 47 patients) were measured before and after apical surgery. Data were collected relative to the cementoenamel junction (CEJ) as well as to the crestal bone level (CBL). One observer took all measurements twice (to calculate the intraobserver variability), and the means were used for further analysis. The following parameters were assessed for all treated teeth as well as for specific tooth groups: length of root-end resection and percentage change of root length, preoperative and postoperative RCRs, and percentage change of RCR after apical surgery. RESULTS: The mean length of root-end resection was 3.58 ± 1.43 mm (relative to the CBL). This amounted to a loss of 33.2% of clinical and 26% of anatomic root length. There was an overall significant difference between the tooth groups (P < .05). There was also a statistically significant difference comparing mandibular and maxillary teeth (P < .05), but not for incisors/canines versus premolars/molars (P = .125). The mean preoperative and postoperative RCRs (relative to CEJ) were 1.83 and 1.35, respectively (P < .001). With regard to the CBL reference, the mean preoperative and postoperative RCRs were 1.08 and 0.71 (CBL), respectively (P < .001). The calculated changes of RCR after apical surgery were 24.8% relative to CEJ and 33.3% relative to CBL (P < .001). Across the different tooth groups, the mean RCR was not significantly different (P = .244 for CEJ and 0.114 for CBL). CONCLUSIONS: This CBCT-based study demonstrated that the RCR is significantly changed after root-end resection in apical surgery irrespective of the clinical (CBL) or anatomic (CEJ) reference levels. The lowest, and thus clinically most critical, postoperative RCR was observed in maxillary incisors. Future clinical studies need to show the impact of resection length and RCR changes on the outcome of apical surgery.

An efficient total variation algorithm for super-resolution in fetal brain MRI with adaptive regularization.

Although fetal anatomy can be adequately viewed in new multi-slice MR images, many critical limitations remain for quantitative data analysis. To this end, several research groups have recently developed advanced image processing methods, often denoted by super-resolution (SR) techniques, to reconstruct from a set of clinical low-resolution (LR) images, a high-resolution (HR) motion-free volume. It is usually modeled as an inverse problem where the regularization term plays a central role in the reconstruction quality. Literature has been quite attracted by Total Variation energies because of their ability in edge preserving but only standard explicit steepest gradient techniques have been applied for optimization. In a preliminary work, it has been shown that novel fast convex optimization techniques could be successfully applied to design an efficient Total Variation optimization algorithm for the super-resolution problem. In this work, two major contributions are presented. Firstly, we will briefly review the Bayesian and Variational dual formulations of current state-of-the-art methods dedicated to fetal MRI reconstruction. Secondly, we present an extensive quantitative evaluation of our SR algorithm previously introduced on both simulated fetal and real clinical data (with both normal and pathological subjects). Specifically, we study the robustness of regularization terms in front of residual registration errors and we also present a novel strategy for automatically select the weight of the regularization as regards the data fidelity term. Our results show that our TV implementation is highly robust in front of motion artifacts and that it offers the best trade-off between speed and accuracy for fetal MRI recovery as in comparison with state-of-the art methods.

New Algorithm for Managing Childhood Illness Using Mobile Technology (ALMANACH): A Controlled Non-Inferiority Study on Clinical Outcome and Antibiotic Use in Tanzania.

INTRODUCTION: The decline of malaria and scale-up of rapid diagnostic tests calls for a revision of IMCI. A new algorithm (ALMANACH) running on mobile technology was developed based on the latest evidence. The objective was to ensure that ALMANACH was safe, while keeping a low rate of antibiotic prescription. METHODS: Consecutive children aged 2-59 months with acute illness were managed using ALMANACH (2 intervention facilities), or standard practice (2 control facilities) in Tanzania. Primary outcomes were proportion of children cured at day 7 and who received antibiotics on day 0. RESULTS: 130/842 (15∙4%) in ALMANACH and 241/623 (38∙7%) in control arm were diagnosed with an infection in need for antibiotic, while 3∙8% and 9∙6% had malaria. 815/838 (97∙3%;96∙1-98.4%) were cured at D7 using ALMANACH versus 573/623 (92∙0%;89∙8-94∙1%) using standard practice (p<0∙001). Of 23 children not cured at D7 using ALMANACH, 44% had skin problems, 30% pneumonia, 26% upper respiratory infection and 13% likely viral infection at D0. Secondary hospitalization occurred for one child using ALMANACH and one who eventually died using standard practice. At D0, antibiotics were prescribed to 15∙4% (12∙9-17∙9%) using ALMANACH versus 84∙3% (81∙4-87∙1%) using standard practice (p<0∙001). 2∙3% (1∙3-3.3) versus 3∙2% (1∙8-4∙6%) received an antibiotic secondarily. CONCLUSION: Management of children using ALMANACH improve clinical outcome and reduce antibiotic prescription by 80%. This was achieved through more accurate diagnoses and hence better identification of children in need of antibiotic treatment or not. The building on mobile technology allows easy access and rapid update of the decision chart. TRIAL REGISTRATION: Pan African Clinical Trials Registry PACTR201011000262218.

Managing the Sick Child in the Era of Declining Malaria Transmission: Development of ALMANACH, an Electronic Algorithm for Appropriate Use of Antimicrobials.

OBJECTIVE: To review the available knowledge on epidemiology and diagnoses of acute infections in children aged 2 to 59 months in primary care setting and develop an electronic algorithm for the Integrated Management of Childhood Illness to reach optimal clinical outcome and rational use of medicines. METHODS: A structured literature review in Medline, Embase and the Cochrane Database of Systematic Review (CDRS) looked for available estimations of diseases prevalence in outpatients aged 2-59 months, and for available evidence on i) accuracy of clinical predictors, and ii) performance of point-of-care tests for targeted diseases. A new algorithm for the management of childhood illness (ALMANACH) was designed based on evidence retrieved and results of a study on etiologies of fever in Tanzanian children outpatients. FINDINGS: The major changes in ALMANACH compared to IMCI (2008 version) are the following: i) assessment of 10 danger signs, ii) classification of non-severe children into febrile and non-febrile illness, the latter receiving no antibiotics, iii) classification of pneumonia based on a respiratory rate threshold of 50 assessed twice for febrile children 12-59 months; iv) malaria rapid diagnostic test performed for all febrile children. In the absence of identified source of fever at the end of the assessment, v) urine dipstick performed for febrile children <2 years to consider urinary tract infection, vi) classification of 'possible typhoid' for febrile children >2 years with abdominal tenderness; and lastly vii) classification of 'likely viral infection' in case of negative results. CONCLUSION: This smartphone-run algorithm based on new evidence and two point-of-care tests should improve the quality of care of <5 year children and lead to more rational use of antimicrobials.

Derivation of an observer model adapted to irregular signals based on convolution channels.

Anthropomorphic model observers are mathe- matical algorithms which are applied to images with the ultimate goal of predicting human signal detection and classification accuracy across varieties of backgrounds, image acquisitions and display conditions. A limitation of current channelized model observers is their inability to handle irregularly-shaped signals, which are common in clinical images, without a high number of directional channels. Here, we derive a new linear model observer based on convolution channels which we refer to as the "Filtered Channel observer" (FCO), as an extension of the channelized Hotelling observer (CHO) and the nonprewhitening with an eye filter (NPWE) observer. In analogy to the CHO, this linear model observer can take the form of a single template with an external noise term. To compare with human observers, we tested signals with irregular and asymmetrical shapes spanning the size of lesions down to those of microcalfications in 4-AFC breast tomosynthesis detection tasks, with three different contrasts for each case. Whereas humans uniformly outperformed conventional CHOs, the FCO observer outperformed humans for every signal with only one exception. Additive internal noise in the models allowed us to degrade model performance and match human performance. We could not match all the human performances with a model with a single internal noise component for all signal shape, size and contrast conditions. This suggests that either the internal noise might vary across signals or that the model cannot entirely capture the human detection strategy. However, the FCO model offers an efficient way to apprehend human observer performance for a non-symmetric signal.

The effect on lower spine muscle activation of walking on a narrow beam in virtual reality

To what extent do people behave in immersive virtual environments as they would in similar situations in a physical environment? There are many ways to address this question, ranging from questionnaires, behavioral studies, and the use of physiological measures. Here, we compare the onsets of muscle activity using surface electromyography (EMG) while participants were walking under three different conditions: on a normal floor surface, on a narrow ribbon along the floor, and on a narrow platform raised off the floor. The same situation was rendered in an immersive virtual environment (IVE) Cave-like system, and 12 participants did the three types of walking in a counter-balanced within-groups design. The mean number of EMG activity onsets per unit time followed the same pattern in the virtual environment as in the physical environment-significantly higher for walking on the platform compared to walking on the floor. Even though participants knew that they were in fact really walking at floor level in the virtual environment condition, the visual illusion of walking on a raised platform was sufficient to influence their behavior in a measurable way. This opens up the door for this technique to be used in gait and posture related scenarios including rehabilitation.