Learning kernels for support vector machines with polynomial powers of sigmoid

In the pattern recognition research field, Support Vector Machines (SVM) have been an effectiveness tool for classification purposes, being successively employed in many applications. The SVM input data is transformed into a high dimensional space using some kernel functions where linear separation is more likely. However, there are some computational drawbacks associated to SVM. One of them is the computational burden required to find out the more adequate parameters for the kernel mapping considering each non-linearly separable input data space, which reflects the performance of SVM. This paper introduces the Polynomial Powers of Sigmoid for SVM kernel mapping, and it shows their advantages over well-known kernel functions using real and synthetic datasets.

Preliminary diagnosis of ophtalmological diseases through machine learning techniques

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Percolated non-Newtonian flow for silicone obtained from exfoliated bioinorganic layered double hydroxide intercalated with amino acid

A simple and scalable procedure was used to obtain thin, stable, homogeneous, and easy-to-handle films composed of silicone derived from dimethicones containing dispersed hydrotalcite-type materials previously organo-modified with amino acids. The absence of the typical X-ray pattern of the bioinorganic LDH filler suggested an exfoliation process that was further indirectly evidenced by a drastic change in the rheological behavior, which turned from a quasi-Newtonian behavior for the silicone free of LDH filler to an extensive developed gel-like structure for the nanocomposite derivatives. Visualized by the shear-thinning exponent of the complex viscosity in the low-frequency range, the percolation threshold was evident for filler loading as low as <5 w/W%, suggesting the presence of a largely developed interface between the filler and the polymer. The increase of more than one order of magnitude in viscosity was explained by the rather strong attrition phenomenon between the tethered amino acid anions and the silicone chains. UVB radiation absorption profiles make such bioinorganic polymer nanocomposites potentially applicable in skin protection. Thermo-gravimetric analysis revealed significant improvement in the thermal stability, especially in the final step of the polymer combustion, thus underlining the role of the hybrid material as a thermal retardant agent. (C) 2011 Elsevier B.V. All rights reserved.

Particle Competition and Cooperation in Networks for Semi-Supervised Learning

Semi-supervised learning is one of the important topics in machine learning, concerning with pattern classification where only a small subset of data is labeled. In this paper, a new network-based (or graph-based) semi-supervised classification model is proposed. It employs a combined random-greedy walk of particles, with competition and cooperation mechanisms, to propagate class labels to the whole network. Due to the competition mechanism, the proposed model has a local label spreading fashion, i.e., each particle only visits a portion of nodes potentially belonging to it, while it is not allowed to visit those nodes definitely occupied by particles of other classes. In this way, a "divide-and-conquer" effect is naturally embedded in the model. As a result, the proposed model can achieve a good classification rate while exhibiting low computational complexity order in comparison to other network-based semi-supervised algorithms. Computer simulations carried out for synthetic and real-world data sets provide a numeric quantification of the performance of the method.

DIGITAL LIBRARIES AND LEARNING OBJECTS REPOSITORIES

Discusses the technological changes that affects learning organizations as well as the human, technical, legal and sustainable aspects regarding learning objects repositories creation, maintenance and use. It presents concepts of information objects and learning objects, the functional requirements needed to their storage at Learning Management Systems. The role of Metadata is reviewed concerning learning objects creation and retrieval, followed by considerations about learning object repositories models, community participation/collaborative strategies and potential derived metrics/indicators. As a result of this desktop research, it can be said that not only technical competencies are critical to any learning objects repository implementation, but it urges that an engaged community of interest be establish as a key to support a learning object repository project. On that matter, researchers are applying Activity Theory (Vygostky, Luria y Leontiev) in order to seek joint perceptions and actions involving learning objects repository users, curators and managers, perceived as critical assets to a successful proposal.

The pattern recognition receptors expressed on neutrophils and the associated cytokine profile from different aged patients with Candida-related denture stomatitis

This study evaluated the expression of pattern recognition receptors (PRRs) and activation factors associated with salivary and blood neutrophils from different aged patients diagnosed with Candida-related denture stomatitis (DS). Expression of neutrophil PRRs was determined by flow cytometry and immunofluorescence, and the levels of selected cytokines that influence immune activation were determined by ELISA. The salivary (but not the serum derived) neutrophils of individuals with DS were found to have an increased expression of CD69 regardless of the age of the patient compared to patients without DS. However, these salivary neutrophils had a lower expression of CD66b and CD64. Expression of TLR2 was lower on the salivary-and serum-derived neutrophils from elderly individuals compared to the neutrophils of younger subjects, regardless of whether the individual had DS. Salivary interleukin (IL)-4 was elevated in both of the elderly subject groups (with or without DS). Only elderly DS patients were observed to have increased serum IL-4 levels and reduced salivary IL-12 levels. Younger DS patients showed an increase in salivary IL-10 levels, and both the saliva and the serum levels of IFN-gamma were increased in all of the younger subjects. Our data demonstrated that changes in both the oral immune cells and the protein components could be associated with DS. Furthermore, changes in the blood-derived factors were more associated with age than DS status. (C) 2012 Elsevier Inc. All rights reserved.

Novelty, but Not Operant Aversive Learning, Enhances Fos and Egr-1 Expression in the Medial Prefrontal Cortex and Hippocampal Areas of Rats

Immediate early genes (IEG) are presumed to be activated in response to stress, novelty, and learning. Evidence supports the involvement of prefrontal and hippocampal areas in stress and learning, but also in the detection of novel events. This study examined whether a previous experience with shocks changes the pattern of Fos and Egr-1 expression in the medial prefrontal cortex (mPFC), the hippocampal cornus ammonis 1 (CA1), and dentate gyrus (DG) of adult male Wistar rats that learned to escape in an operant aversive test. Subjects previously exposed to inescapable footshocks that learned to escape from Shocks were assigned to the treated group (EXP). Subjects from Group Novelty (NOV) rested undisturbed during treatment and also learned to escape in the test. The nonshock group (NSH) rested undisturbed in both sessions. Standard immunohistochemistry procedures were used to detect the proteins in brain sections. The results show that a previous experience with shocks changed the pattern of IEG expression, then demonstrating c-fos and egr-1 induction as experience-dependent events. Compared with NSH and EXP an enhanced Fos expression was detected in the mPFC and CA1 subfield of Group NOV, which also exhibited increased Egr-1 expression in the mPFC and DG in comparison to NSH. No differences were found in the DG for Fos, or in the CA1 for Egr-1. Novelty, and not the operant aversive escape learning, seems to have generated IEG induction. The results suggest novel stimuli as a possible confounding factor in studies on Fos and/or Egr-1 expression in aversive conditions.

Pattern-based segmentation of digital documents: model and implementation

This thesis proposes a new document model, according to which any document can be segmented in some independent components and transformed in a pattern-based projection, that only uses a very small set of objects and composition rules. The point is that such a normalized document expresses the same fundamental information of the original one, in a simple, clear and unambiguous way. The central part of my work consists of discussing that model, investigating how a digital document can be segmented, and how a segmented version can be used to implement advanced tools of conversion. I present seven patterns which are versatile enough to capture the most relevant documents’ structures, and whose minimality and rigour make that implementation possible. The abstract model is then instantiated into an actual markup language, called IML. IML is a general and extensible language, which basically adopts an XHTML syntax, able to capture a posteriori the only content of a digital document. It is compared with other languages and proposals, in order to clarify its role and objectives. Finally, I present some systems built upon these ideas. These applications are evaluated in terms of users’ advantages, workflow improvements and impact over the overall quality of the output. In particular, they cover heterogeneous content management processes: from web editing to collaboration (IsaWiki and WikiFactory), from e-learning (IsaLearning) to professional printing (IsaPress).

Automatic (data-based) learning of expressive indicators for machine failure detection : a proposal

Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

Project-based learning using robots with open-source hardware and software

[EN]One of the main issues of the current education system is the lack of student motivation. This aspect together with the permanent change that the Information and Communications Technologies involve represents a major challenge for the teacher: to continuously update contents and to keep awake the student’s interest. A tremendously useful tool in classrooms consists on the integration of projects with participative and collaborative dynamics, where the teacher acts mainly as a guidance to the student activity instead of being a mere knowledge and evaluation transmitter. As a specific example of project based learning, the EDUROVs project consists on building an economic underwater robot using low cost materials, but allowing the integration and programming of many accessories and sensors with minimum budget using opensource hardware and software.

Scheduler-dependent inter-cell interference and its impact on LTE uplink performance at flow level

The Long Term Evolution (LTE) cellular technology is expected to extend the capacity and improve the performance of current 3G cellular networks. Among the key mechanisms in LTE responsible for traffic management is the packet scheduler, which handles the allocation of resources to active flows in both the frequency and time dimension. This paper investigates for various scheduling scheme how they affect the inter-cell interference characteristics and how the interference in turn affects the user’s performance. A special focus in the analysis is on the impact of flow-level dynamics resulting from the random user behaviour. For this we use a hybrid analytical/simulation approach which enables fast evaluation of flow-level performance measures. Most interestingly, our findings show that the scheduling policy significantly affects the inter-cell interference pattern but that the scheduler specific pattern has little impact on the flow-level performance.

Continuous flow left ventricular assist devices: a valid option for heart failure patients

Recent outstanding clinical advances with new mechanical circulatory systems (MCS) have led to additional strategies in the treatment of end stage heart failure (HF). Heart transplantation (HTx) can be postponed and for certain patients even replaced by smaller implantable left ventricular assist devices (LVAD). Mechanical support of the failing left ventricle enables appropriate hemodynamic stabilisation and recovery of secondary organ failure, often seen in these severely ill patients. These new devices may be of great help to bridge patients until a suitable cardiac allograft is available but are also discussed as definitive treatment for patients who do not qualify for transplantation. Main indications for LVAD implantation are bridge to recovery, bridge to transplantation or destination therapy. LVAD may be an important tool for patients with an expected prolonged period on the waiting list, for instance those with blood group 0 or B, with a body weight over 90 kg and those with potentially reversible secondary organ failure and pulmonary artery hypertension. However, LVAD implantation means an additional heart operation with inherent peri-operative risks and complications during the waiting period. Finally, cardiac transplantation in patients with prior implantation of a LVAD represents a surgical challenge. This review summarises the current knowledge about LVAD and continuous flow devices especially since the latter have been increasingly used worldwide in the most recent years. The review is also based on the institutional experience at Berne University Hospital between 2000 and 2012. Apart from short-term devices (Impella, Cardiac Assist, Deltastream and ECMO) which were used in approximately 150 cases, 85 pulsatile long-term LVAD, RVAD or bi-VAD and 44 non-pulsatile LVAD (mainly HeartMateII and HeartWare) were implanted. After an initial learning curve, one-year mortality dropped to 10.4% in the last 58 patients.

The Impact of Gender and Pedagogy on the Development of Self-Regulated Learning Strategies in Undergraduate Engineering Classrooms

The purpose of this paper is to examine ways in which pedagogy and gender of instructor impact the development of self-regulated learning strategies as assessed by the Motivated Strategies for Learning Questionnaire (MSLQ) in male and female undergraduate engineering students. Pedagogy was operationalized as two general formats: lecture plus active learning techniques or problem-base/project-based learning. One hundred seventy-six students from four universities participated in the study. Within-group analyses found significant differences with regard to pedagogy, instructors’ gender, and student gender on the learning strategies and motivation subscales as operationalized by the MSLQ. Male and females students reported significant post-test differences with regard to the gender of instructor and the style of pedagogy. The results of this study showed a pattern where more positive responses for students of both genders were found with the same-gendered instructor. The results also suggested that male students responded more positively to project and problem-based courses with changes evidenced in motivation strategies and resource management. Female students showed decreases in resource management in these two types of courses. Further, female students reported increases in the lecture with active learning courses.