Searching patterns in painting images with computer vision techniques

This paper presents a pattern recognition method focused on paintings images. The purpose is construct a system able to recognize authors or art styles based on common elements of his work (here called patterns). The method is based on comparing images that contain the same or similar patterns. It uses different computer vision techniques, like SIFT and SURF, to describe the patterns in descriptors, K-Means to classify and simplify these descriptors, and RANSAC to determine and detect good results. The method are good to find patterns of known images but not so good if they are not.

A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.

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

Distributed all-atom simulations of intrinsically unstructured proteins

The Computational Biophysics Group at the Universitat Pompeu Fabra (GRIB-UPF) hosts two unique computational resources dedicated to the execution of large scale molecular dynamics (MD) simulations: (a) the ACMD molecular-dynamics software, used on standard personal computers with graphical processing units (GPUs); and (b) the GPUGRID. net computing network, supported by users distributed worldwide that volunteer GPUs for biomedical research. We leveraged these resources and developed studies, protocols and open-source software to elucidate energetics and pathways of a number of biomolecular systems, with a special focus on flexible proteins with many degrees of freedom. First, we characterized ion permeation through the bactericidal model protein Gramicidin A conducting one of the largest studies to date with the steered MD biasing methodology. Next, we addressed an open problem in structural biology, the determination of drug-protein association kinetics; we reconstructed the binding free energy, association, and dissaciociation rates of a drug like model system through a spatial decomposition and a Makov-chain analysis. The work was published in the Proceedings of the National Academy of Sciences and become one of the few landmark papers elucidating a ligand-binding pathway. Furthermore, we investigated the unstructured Kinase Inducible Domain (KID), a 28-peptide central to signalling and transcriptional response; the kinetics of this challenging system was modelled with a Markovian approach in collaboration with Frank Noe’s group at the Freie University of Berlin. The impact of the funding includes three peer-reviewed publication on high-impact journals; three more papers under review; four MD analysis components, released as open-source software; MD protocols; didactic material, and code for the hosting group.

Existential behavioural therapy for informal caregivers of palliative patients: a randomised controlled trial.

BACKGROUND: Existential behavioural therapy (EBT) was developed to support informal caregivers of palliative patients in the last stage of life and during bereavement as a manualised group psychotherapy comprising six sessions. We tested the effectiveness of EBT on mental stress and quality of life (QOL). METHODS: Informal caregivers were randomly assigned (1:1) to EBT or a treatment-as-usual control group using computer-generated numbers in blocks of 10. Primary outcomes were assessed with the Brief Symptom Inventory (subscales somatisation, anxiety and depression), the Satisfaction with Life Scale (SWLS), the WHOQOL-BREF and a numeric rating scale for QOL (QOL-NRS, range 0-10). Data were collected at baseline, pre-treatment, post-treatment and follow-ups after 3 and 12âeuro0/00months. Treatment effects were assessed with a multivariate analysis of covariance. RESULTS: Out of 160 relatives, 81 were assigned to EBT and 79 to the control group. Participants were 54.5âeuro0/00±âeuro0/0013.2âeuro0/00years old; 69.9% were female. The multivariate model was significant for the pre-/post-comparison (pâeuro0/00=âeuro0/000.005) and the pre-/12-month comparison (pâeuro0/00=âeuro0/000.05) but not for the pre-/3-month comparison. Medium to large effects on anxiety and QOL (SWLS, WHOQOL-BREF, QOL-NRS) were found at post-treatment; medium effects on depression and QOL (QOL-NRS) emerged in the 12-month follow-up. No adverse effects of the intervention were observed. CONCLUSION: Existential behavioural therapy appears to exert beneficial effects on distress and QOL of informal caregivers of palliative patients. Further longitudinal evidence is needed to confirm these findings. Copyright © 2013 John Wiley & Sons, Ltd.

The use of expert systems on the differential diagnosis of urinary incontinence

The differential diagnosis of urinary incontinence classes is sometimes difficult to establish. As a rule, only the results of urodynamic testing allow an accurate diagnosis. However, this exam is not always feasible, because it requires special equipment, and also trained personnel to lead and interpret the exam. Some expert systems have been developed to assist health professionals in this field. Therefore, the aims of this paper are to present the definition of Artificial Intelligence; to explain what Expert System and System for Decision Support are and its application in the field of health and to discuss some expert systems for differential diagnosis of urinary incontinence. It is concluded that expert systems may be useful not only for teaching purposes, but also as decision support in daily clinical practice. Despite this, for several reasons, health professionals usually hesitate to use the computer expert system to support their decision making process.

Dialogic learning and interactive groups: an IMS LD template integrated in runtime systems

Dialogic learning and interactive groups have proved to be a useful methodological approach appliedin educational situations for lifelong adult learners. The principles of this approach stress theimportance of dialogue and equal participation also when designing the training activities. This paperadopts these principles as the basis for a configurable template that can be integrated in runtimesystems. The template is formulated as a meta-UoL which can be interpreted by IMS Learning Designplayers. This template serves as a guide to flexibly select and edit the activities at runtime (on the fly).The meta-UoL has been used successfully by a practitioner so as to create a real-life example, withpositive and encouraging results

A WiMAX-based implementation of network MIMO for indoor wireless systems

It is well known that multiple-input multiple-output (MIMO) techniques can bring numerous benefits, such as higher spectral efficiency, to point-to-point wireless links. More recently, there has been interest in extending MIMO concepts tomultiuser wireless systems. Our focus in this paper is on network MIMO, a family of techniques whereby each end user in a wireless access network is served through several access points within its range of influence. By tightly coordinating the transmission and reception of signals at multiple access points, network MIMO can transcend the limits on spectral efficiency imposed by cochannel interference. Taking prior information-theoretic analyses of networkMIMO to the next level, we quantify the spectral efficiency gains obtainable under realistic propagation and operational conditions in a typical indoor deployment. Our study relies on detailed simulations and, for specificity, is conducted largely within the physical-layer framework of the IEEE 802.16e Mobile WiMAX system. Furthermore,to facilitate the coordination between access points, we assume that a high-capacity local area network, such as Gigabit Ethernet,connects all the access points. Our results confirm that network MIMO stands to provide a multiple-fold increase in spectralefficiency under these conditions.

Computational Representation of Collaborative Learning Flow Patterns Using IMS Learning Design

The identification and integration of reusable and customizable CSCL (Computer Supported Collaborative Learning) may benefit from the capture of best practices in collaborative learning structuring. The authors have proposed CLFPs (Collaborative Learning Flow Patterns) as a way of collecting these best practices. To facilitate the process of CLFPs by software systems, the paper proposes to specify these patterns using IMS Learning Design (IMS-LD). Thus, teachers without technical knowledge can particularize and integrate CSCL tools. Nevertheless, the support of IMS-LD for describing collaborative learning activities has some deficiencies: the collaborative tools that can be defined in these activities are limited. Thus, this paper proposes and discusses an extension to IMS-LD that enables to specify several characteristics of the use of tools that mediate collaboration. In order to obtain a Unit of Learning based on a CLFP, a three stage process is also proposed. A CLFP-based Unit of Learning example is used to illustrate the process and the need of the proposed extension.

Towards reusability and tailorability in collaborative learning systems using IMS-LD and grid services

CSCL applications are complex distributed systems that posespecial requirements towards achieving success in educationalsettings. Flexible and efficient design of collaborative activitiesby educators is a key precondition in order to provide CSCL tailorable systems, capable of adapting to the needs of eachparticular learning environment. Furthermore, some parts ofthose CSCL systems should be reused as often as possible inorder to reduce development costs. In addition, it may be necessary to employ special hardware devices, computational resources that reside in other organizations, or even exceed thepossibilities of one specific organization. Therefore, theproposal of this paper is twofold: collecting collaborativelearning designs (scripting) provided by educators, based onwell-known best practices (collaborative learning flow patterns) in a standard way (IMS-LD) in order to guide the tailoring of CSCL systems by selecting and integrating reusable CSCL software units; and, implementing those units in the form of grid services offered by third party providers. More specifically, this paper outlines a grid-based CSCL system having these features and illustrates its potential scope and applicability by means of a sample collaborative learning scenario.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

Relay card for capacitance measurements

In this bachelor's thesis a relay card for capacitance measurements was designed, built and tested. The study was made for the research and development laboratory of VTI Technologies, which manufactures capacitive silicon micro electro mechanical accelerometers and pressure sensors. As the size of the sensors is decreasing the capacitance value of the sensors also decreases. The decreased capacitance causes a need for new and more accurate measurement systems. The technology used in the instrument measuring the capacitance dictates a framework how the relay card should be designed, thus the operating principle of the instrument must be known. To achieve accurate results the measurement instrument and its functions needed to be used correctly. The relay card was designed using printed circuit board design methods that minimize interference coupling to the measurement. The relay card that was designed in this study is modular. It consists of a separate CPU card, which was used to control the add-on cards connected to it. The CPU card was controlled from a computer through a serial bus. Two add-on cards for the CPU card were designed in this study. The first one was the measurement card, which could be used to measure 32 capacitive sensors. The second add-on card was the MUX card, which could be used to switch between two measurement cards. The capacitance measurements carried out through the MUX card and the measurement cards were characterized with a series of test measurements. The test measurement data was then analysed. The relay card design was confirmed to work and offer accurate measurement results up to a measurement frequency of 10 MHz. The length of the measurement cables limited the measurement frequency.

Controlled nerve growth factor release from multi-ply alginate/chitosan-based nerve conduits.

The delivery kinetics of growth factors has been suggested to play an important role in the regeneration of peripheral nerves following axotomy. In this context, we designed a nerve conduit (NC) with adjustable release kinetics of nerve growth factor (NGF). A multi-ply system was designed where NC consisting of a polyelectrolyte alginate/chitosan complex was coated with layers of poly(lactide-co-glycolide) (PLGA) to control the release of embedded NGF. Prior to assessing the in vitro NGF release from NC, various release test media, with and without stabilizers for NGF, were evaluated to ensure adequate quantification of NGF by ELISA. Citrate (pH 5.0) and acetate (pH 5.5) buffered saline solutions containing 0.05% Tween 20 yielded the most reliable results for ELISA active NGF. The in vitro release experiments revealed that the best results in terms of reproducibility and release control were achieved when the NGF was embedded between two PLGA layers and the ends of the NC tightly sealed by the PLGA coatings. The release kinetics could be efficiently adjusted by accommodating NGF at different radial locations within the NC. A sustained release of bioactive NGF in the low nanogram per day range was obtained for at least 15days. In conclusion, the developed multi-ply NGF loaded NC is considered a suitable candidate for future implantation studies to gain insight into the relationship between local growth factor availability and nerve regeneration.

Computerized advice on drug dosage to improve prescribing practice.

BACKGROUND: Maintaining therapeutic concentrations of drugs with a narrow therapeutic window is a complex task. Several computer systems have been designed to help doctors determine optimum drug dosage. Significant improvements in health care could be achieved if computer advice improved health outcomes and could be implemented in routine practice in a cost effective fashion. This is an updated version of an earlier Cochrane systematic review, by Walton et al, published in 2001. OBJECTIVES: To assess whether computerised advice on drug dosage has beneficial effects on the process or outcome of health care. SEARCH STRATEGY: We searched the Cochrane Effective Practice and Organisation of Care Group specialized register (June 1996 to December 2006), MEDLINE (1966 to December 2006), EMBASE (1980 to December 2006), hand searched the journal Therapeutic Drug Monitoring (1979 to March 2007) and the Journal of the American Medical Informatics Association (1996 to March 2007) as well as reference lists from primary articles. SELECTION CRITERIA: Randomized controlled trials, controlled trials, controlled before and after studies and interrupted time series analyses of computerized advice on drug dosage were included. The participants were health professionals responsible for patient care. The outcomes were: any objectively measured change in the behaviour of the health care provider (such as changes in the dose of drug used); any change in the health of patients resulting from computerized advice (such as adverse reactions to drugs). DATA COLLECTION AND ANALYSIS: Two reviewers independently extracted data and assessed study quality. MAIN RESULTS: Twenty-six comparisons (23 articles) were included (as compared to fifteen comparisons in the original review) including a wide range of drugs in inpatient and outpatient settings. Interventions usually targeted doctors although some studies attempted to influence prescriptions by pharmacists and nurses. Although all studies used reliable outcome measures, their quality was generally low. Computerized advice for drug dosage gave significant benefits by:1.increasing the initial dose (standardised mean difference 1.12, 95% CI 0.33 to 1.92)2.increasing serum concentrations (standradised mean difference 1.12, 95% CI 0.43 to 1.82)3.reducing the time to therapeutic stabilisation (standardised mean difference -0.55, 95%CI -1.03 to -0.08)4.reducing the risk of toxic drug level (rate ratio 0.45, 95% CI 0.30 to 0.70)5.reducing the length of hospital stay (standardised mean difference -0.35, 95% CI -0.52 to -0.17). AUTHORS' CONCLUSIONS: This review suggests that computerized advice for drug dosage has some benefits: it increased the initial dose of drug, increased serum drug concentrations and led to a more rapid therapeutic control. It also reduced the risk of toxic drug levels and the length of time spent in the hospital. However, it had no effect on adverse reactions. In addition, there was no evidence to suggest that some decision support technical features (such as its integration into a computer physician order entry system) or aspects of organization of care (such as the setting) could optimise the effect of computerised advice.