Correcció d'exercicis de lògica per l'ACME

La Universitat de Girona, i més concretament el Departament d’Informàtica i Matemàtica Aplicada, ja fa uns anys que ha posat en marxa el Projecte Avaluació Continuada i Millora de l’Ensenyament, també anomenat ACME. Aquest projecte és una plataforma d'e-learning, és a dir, un sistema d’aprenentatge a través de la xarxa que potencia la col•laboració digital i el bescanvi d’informació entre alumne i professor. El creixement que ha experimentat la plataforma, ha estat possible gràcies al disseny modular de l’aplicació, on cada nova funcionalitat que estava essent desenvolupada evolucionava de manera independent a la resta de la plataforma i sense comprometre’n el funcionament. Per afegir un nou mòdul a l’ACME, s’utilitzen els mòduls de base que confereixen l'estructura a la plataforma i les eines per incorporar nous mòduls, amb el que la implantació d’aquests a la plataforma és d’elevada senzillesa. Actualment, la majoria de les assignatures de primer del Grau d’Informàtica ja disposen d’exercicis adaptats a la plataforma, el que dóna una uniformitat en les eines i plataformes que utilitzen els alumnes en la seva formació. Però no hi són totes les assignatures, falta incloure l’assignatura de Lògica a la plataforma. D’aquesta manera, tant els alumnes com els professors de l’assignatura, podran treure profit dels beneficis esmentats que aporta l’ACME. Concretament, a l’assignatura de Lògica es disposava d’uns aplicatius a la plataforma Moodle de la Universitat de Girona on es guiava a l’alumne en la resolució dels exercicis. Aquest mètode és molt interessant com a mètode pedagògic per a l’aprenentatge inicial de l’assignatura, però no representa un repte real on els alumnes hagin d’aplicar els seus coneixements per a la seva realització. Els alumnes també disposaven d’un dossier on se’ls proposava uns exercicis molt complets, i a les pàgines finals d’aquest se’ls donava la solució. Aleshores, de manera voluntària els alumnes realitzaven els exercicis i comprovaven amb la solució si havien aprés a resoldre’ls. Per tant, tant els responsables de l'assignatura de Lògica com els responsables de la plataforma ACME van veure que es podrien desenvolupar eines a l'ACME per tal de corregir de forma automàtica els exercicis de l'assignatura. Incorporar l’assignatura de Lògica a l’ACME permet que els alumnes es vegin més involucrats a fer exercicis durant els curs de manera continuada, gràcies als terminis d’entrega, i facilita als professors la seva tasca deslliurant-los de les correccions i oferint-los-hi eines de seguiment

Weighted Shape-based Averaging with Neighborhood Prior Model for Multiple Atlas Fusion-based Medical Image Segmentation

In medical imaging, merging automated segmentations obtained from multiple atlases has become a standard practice for improving the accuracy. In this letter, we propose two new fusion methods: "Global Weighted Shape-Based Averaging" (GWSBA) and "Local Weighted Shape-Based Averaging" (LWSBA). These methods extend the well known Shape-Based Averaging (SBA) by additionally incorporating the similarity information between the reference (i.e., atlas) images and the target image to be segmented. We also propose a new spatially-varying similarity-weighted neighborhood prior model, and an edge-preserving smoothness term that can be used with many of the existing fusion methods. We first present our new Markov Random Field (MRF) based fusion framework that models the above mentioned information. The proposed methods are evaluated in the context of segmentation of lymph nodes in the head and neck 3D CT images, and they resulted in more accurate segmentations compared to the existing SBA.

Differential damage in the frontal cortex with aging, sporadic and familial Alzheimer's disease.

In order to understand relationships between executive and structural deficits in the frontal cortex of patients within normal aging or Alzheimer's disease, we studied frontal pathological changes in young and old controls compared to cases with sporadic (AD) or familial Alzheimer's disease (FAD). We performed a semi-automatic computer assisted analysis of the distribution of beta-amyloid (Abeta) deposits revealed by Abeta immunostaining as well as of neurofibrillary tangles (NFT) revealed by Gallyas silver staining in Brodman areas 10 (frontal polar), 12 (ventro-infero-median) and 24 (anterior cingular), using tissue samples from 5 FAD, 6 sporadic AD and 10 control brains. We also performed densitometric measurements of glial fibrillary acidic protein, principal compound of intermediate filaments of astrocytes, and of phosphorylated neurofilament H and M epitopes in areas 10 and 24. All regions studied seem almost completely spared in normal old controls, with only the oldest ones exhibiting a weak percentage of beta-amyloid deposit and hardly any NFT. On the contrary, all AD and FAD cases were severely damaged as shown by statistically significant increased percentages of beta-amyloid deposit, as well as by a high number of NFT. FAD cases (all from the same family) had statistically more beta-amyloid and GFAP than sporadic AD cases in both areas 10 and 24 and statistically more NFT only in area 24. The correlation between the percentage of beta-amyloid and the number of NFT was significant only for area 24. Altogether, these data suggest that the frontal cortex can be spared by AD type lesions in normal aging, but is severely damaged in sporadic and still more in familial Alzheimer's disease. The frontal regions appear to be differentially vulnerable, with area 12 having the less amyloid burden, area 24 the less NFT and area 10 having both more amyloid and more NFT. This pattern of damage in frontal regions may represent a strong neuroanatomical support for the deterioration of attention and cognitive capacities as well as for the presence of emotional and behavioral troubles in AD patients.

Ambulatory monitoring of physical activities in patients with Parkinson's disease.

A new ambulatory method of monitoring physical activities in Parkinson's disease (PD) patients is proposed based on a portable data-logger with three body-fixed inertial sensors. A group of ten PD patients treated with subthalamic nucleus deep brain stimulation (STN-DBS) and ten normal control subjects followed a protocol of typical daily activities and the whole period of the measurement was recorded by video. Walking periods were recognized using two sensors on shanks and lying periods were detected using a sensor on trunk. By calculating kinematics features of the trunk movements during the transitions between sitting and standing postures and using a statistical classifier, sit-to-stand (SiSt) and stand-to-sit (StSi) transitions were detected and separated from other body movements. Finally, a fuzzy classifier used this information to detect periods of sitting and standing. The proposed method showed a high sensitivity and specificity for the detection of basic body postures allocations: sitting, standing, lying, and walking periods, both in PD patients and healthy subjects. We found significant differences in parameters related to SiSt and StSi transitions between PD patients and controls and also between PD patients with and without STN-DBS turned on. We concluded that our method provides a simple, accurate, and effective means to objectively quantify physical activities in both normal and PD patients and may prove useful to assess the level of motor functions in the latter.

Learning spatial filters for multispectral image segmentation

We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.

Adaption of Courses and Learning Environment to the User Context in dotLRN

The explosive growth of Internet during the last years has been reflected in the ever-increasing amount of the diversity and heterogeneity of user preferences, types and features of devices and access networks. Usually the heterogeneity in the context of the users which request Web contents is not taken into account by the servers that deliver them implying that these contents will not always suit their needs. In the particular case of e-learning platforms this issue is especially critical due to the fact that it puts at stake the knowledge acquired by their users. In the following paper we present a system that aims to provide the dotLRN e-learning platform with the capability to adapt to its users context. By integrating dotLRN with a multi-agent hypermedia system, online courses being undertaken by students as well as their learning environment are adapted in real time

Searching for and positioning of contextualized learning objects

Learning object economies are marketplaces for the sharing and reuse of learning objects (LO). There are many motivations for stimulating the development of the LO economy. The main reason is the possibility of providing the right content, at the right time, to the right learner according to adequate quality standards in the context of a lifelong learning process; in fact, this is also the main objective of education. However, some barriers to the development of a LO economy, such as the granularity and editability of LO, must be overcome. Furthermore, some enablers, such as learning design generation and standards usage, must be promoted in order to enhance LO economy. For this article, we introduced the integration of distributed learning object repositories (DLOR) as sources of LO that could be placed in adaptive learning designs to assist teachers’ design work. Two main issues presented as a result: how to access distributed LO, and where to place the LO in the learning design. To address these issues, we introduced two processes: LORSE, a distributed LO searching process, and LOOK, a micro context-based positioning process, respectively. Using these processes, the teachers were able to reuse LO from different sources to semi-automatically generate an adaptive learning design without leaving their virtual environment. A layered evaluation yielded good results for the process of placing learning objects from controlled learning object repositories into a learning design, and permitting educators to define different open issues that must be covered when they use uncontrolled learning object repositories for this purpose. We verified the satisfaction users had with our solution

NQL, Natural Query Language

Desarrollo de un sistema capaz de procesar consultas en lenguaje natural introducidas por el usuario mediante el teclado. El sistema es capaz de responder a consultas en castellano, relacionadas con un dominio de aplicación representado mediante una base de datos relacional.

Wall motion estimation in intracranial aneurysms

The quantification of wall motion in cerebral aneurysms is becoming important owing to its potential connection to rupture, and as a way to incorporate the effects of vascular compliance in computational fluid dynamics (CFD) simulations.Most of papers report values obtained with experimental phantoms, simulated images, or animal models, but the information for real patients is limited. In this paper, we have combined non-rigid registration (IR) with signal processing techniques to measure pulsation in real patients from high frame rate digital subtraction angiography (DSA). We have obtained physiological meaningful waveforms with amplitudes in therange 0mm-0.3mm for a population of 18 patients including ruptured and unruptured aneurysms. Statistically significant differences in pulsation were found according to the rupture status, in agreement with differences in biomechanical properties reported in the literature.

A systolic array for linear MIMO detection based on an all-swap lattice reduction algorithm

A systolic array to implement lattice-reduction-aided lineardetection is proposed for a MIMO receiver. The lattice reductionalgorithm and the ensuing linear detections are operated in the same array, which can be hardware-efficient. All-swap lattice reduction algorithm (ASLR) is considered for the systolic design.ASLR is a variant of the LLL algorithm, which processes all lattice basis vectors within one iteration. Lattice-reduction-aided linear detection based on ASLR and LLL algorithms have very similarbit-error-rate performance, while ASLR is more time efficient inthe systolic array, especially for systems with a large number ofantennas.

Silver space-time trellis-coded modulation

Silver Code (SilC) was originally discovered in [1–4] for 2×2 multiple-input multiple-output (MIMO) transmission. It has non-vanishing minimum determinant 1/7, slightly lower than Golden code, but is fast-decodable, i.e., it allows reduced-complexity maximum likelihood decoding [5–7]. In this paper, we present a multidimensional trellis-coded modulation scheme for MIMO systems [11] based on set partitioning of the Silver Code, named Silver Space-Time Trellis Coded Modulation (SST-TCM). This lattice set partitioning is designed specifically to increase the minimum determinant. The branches of the outer trellis code are labeled with these partitions. Viterbi algorithm is applied for trellis decoding, while the branch metrics are computed by using a sphere-decoding algorithm. It is shown that the proposed SST-TCM performs very closely to the Golden Space-Time Trellis Coded Modulation (GST-TCM) scheme, yetwith a much reduced decoding complexity thanks to its fast-decoding property.

Multiuser detection with an unknown number of active users: receiver design

In multiuser detection, the set of users active at any time may be unknown to the receiver. In these conditions, optimum reception consists of detecting simultaneously the set of activeusers and their data, problem that can be solved exactly by applying random-set theory (RST) and Bayesian recursions (BR). However, implementation of optimum receivers may be limited by their complexity, which grows exponentially with the number of potential users. In this paper we examine three strategies leading to reduced-complexity receivers.In particular, we show how a simple approximation of BRs enables the use of Sphere Detection (SD) algorithm, whichexhibits satisfactory performance with limited complexity.