A Cooperative Development System for an Interactive Introductory Programming Course

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    We present a system for a cooperative development of computer programs that was created for the lab sessions of an introductory programming course at the University of Ljubljana, Slovenia. The system relieved the students from the tedious task of retyping programs developed by the teaching assistant and enabled them to cooperate with the teaching assistant in solving programming problems. We thus made the lab sessions more efficient and interactive and brought them closer to the spirit of active learning approaches

    Computational models for prediction of yeast strain potential for winemaking from phenotypic profiles

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    Saccharomyces cerevisiae strains from diverse natural habitats harbour a vast amount of phenotypic diversity, driven by interactions between yeast and the respective environment. In grape juice fermentations, strains are exposed to a wide array of biotic and abiotic stressors, which may lead to strain selection and generate naturally arising strain diversity. Certain phenotypes are of particular interest for the winemaking industry and could be identified by screening of large number of different strains. The objective of the present work was to use data mining approaches to identify those phenotypic tests that are most useful to predict a strain's potential for winemaking. We have constituted a S. cerevisiae collection comprising 172 strains of worldwide geographical origins or technological applications. Their phenotype was screened by considering 30 physiological traits that are important from an oenological point of view. Growth in the presence of potassium bisulphite, growth at 40 °C, and resistance to ethanol were mostly contributing to strain variability, as shown by the principal component analysis. In the hierarchical clustering of phenotypic profiles the strains isolated from the same wines and vineyards were scattered throughout all clusters, whereas commercial winemaking strains tended to co-cluster. Mann-Whitney test revealed significant associations between phenotypic results and strain's technological application or origin. Naïve Bayesian classifier identified 3 of the 30 phenotypic tests of growth in iprodion (0.05 mg/mL), cycloheximide (0.1 µg/mL) and potassium bisulphite (150 mg/mL) that provided most information for the assignment of a strain to the group of commercial strains. The probability of a strain to be assigned to this group was 27% using the entire phenotypic profile and increased to 95%, when only results from the three tests were considered. Results show the usefulness of computational approaches to simplify strain selection procedures

    Part-level object recognition using superquadrics

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    This paper proposes a technique for object recognition using superquadric built models. Superquadrics, which are three-dimensional models suitable for part-level representation of objects, are reconstructed from range images using the recover-and-select paradigm. Using interpretation trees, the presence of an object from the model database can be hypothesized. These hypotheses are verified by projecting and re-fitting the object model to the range image of the scene which at the same time enables a better localization of the object in the scene

    FragViz: visualization of fragmented networks

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    BACKGROUND Researchers in systems biology use network visualization to summarize the results of their analysis. Such networks often include unconnected components, which popular network alignment algorithms place arbitrarily with respect to the rest of the network. This can lead to misinterpretations due to the proximity of otherwise unrelated elements. RESULTS We propose a new network layout optimization technique called FragViz which can incorporate additional information on relations between unconnected network components. It uses a two-step approach by first arranging the nodes within each of the components and then placing the components so that their proximity in the network corresponds to their relatedness. In the experimental study with the leukemia gene networks we demonstrate that FragViz can obtain network layouts which are more interpretable and hold additional information that could not be exposed using classical network layout optimization algorithms. CONCLUSIONS Network visualization relies on computational techniques for proper placement of objects under consideration. These algorithms need to be fast so that they can be incorporated in responsive interfaces required by the explorative data analysis environments. Our layout optimization technique FragViz meets these requirements and specifically addresses the visualization of fragmented networks, for which standard algorithms do not consider similarities between unconnected components. The experiments confirmed the claims on speed and accuracy of the proposed solution

    Does replication groups scoring reduce false positive rate in SNP interaction discovery?

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    BACKGROUNG. Computational methods that infer single nucleotide polymorphism (SNP) interactions from phenotype data may uncover new biological mechanisms in non-Mendelian diseases. However, practical aspects of such analysis face many problems. Present experimental studies typically use SNP arrays with hundreds of thousands of SNPs but record only hundreds of samples. Candidate SNP pairs inferred by interaction analysis may include a high proportion of false positives. Recently, Gayan et al. (2008) proposed to reduce the number of false positives by combining results of interaction analysis performed on subsets of data (replication groups), rather than analyzing the entire data set directly. If performing as hypothesized, replication groups scoring could improve interaction analysis and also any type of feature ranking and selection procedure in systems biology. Because Gayan et al. do not compare their approach to the standard interaction analysis techniques, we here investigate if replication groups indeed reduce the number of reported false positive interactions. RESULTS. A set of simulated and false interaction-imputed experimental SNP data sets were used to compare the inference of SNP-SNP interactions by means of replication groups to the standard approach where the entire data set was directly used to score all candidate SNP pairs. In all our experiments, the inference of interactions from the entire data set (e.g. without using the replication groups) reported fewer false positives. CONCLUSIONS. With respect to the direct scoring approach the utility of replication groups does not reduce false positive rates, and may, depending on the data set, often perform worse

    Piano Crossing - Walking on a Keyboard

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    Piano Crossing is an interactive art installation which turns a pedestrian crossing marked with white stripes into a piano keyboard so that pedestrians can generate music by walking over it. Matching tones are generated when a pedestrian is over a particular stripe or key. A digital camera is directed at the crossing from above. A special computer vision application was developed that maps the stripes of the pedestrian crossing to piano keys and which detects over which key is the center of gravity of every pedestrian in the image at any given moment. Special black stripes are added to the crossing, which represent also the black piano keys. The application consists of two parts: (1) initialization, where the model of the abstract piano keyboard is mapped to the image of the pedestrian crossing and (2) the detection of pedestrians on the crossing so that musical tones can be generated according to their locations. The art installation Piano crossing was presented to the public for the first time during the 51st Jazz Festival in Ljubljana in July 2010

    Biomechanical and clinical alterations of the hip joint following femoral neck fracture and implantation of bipolar hip endoprosthesis

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    The implantation of a bipolar partial hip endoprosthesis is a treatment of choice for displaced medial femoral neck fracture. We present an experimental study which asses and compare biomechanical and clinical status through period before and after hip fracture and implantation of bipolar partial hip endoprosthesis. This study encompassed 75 patients who suffered from an acute medial femoral neck fracture and were treated with the implantation of a bipolar partial hip endoprosthesis. Their biomechanical status (stress distribution on the hip joint weight bearing area) and clinical status (Harris Hip Score) were estimated for the time prior to the injury and assessed at the follow-up examination that was, on average, carried out 40 months after the operation. Despite ageing, the observed Harris Hip Score at the follow-up examination was higher than that estimated prior to the injury (77.9 > 69.6; p = 0.006). Similarly, the hip stress distribution was reduced (2.7 MPa < 2.3 MPa; p = 0.001). While this reduction can be attributed to a loss of weight due to late ageing, the principal improvement came from the operative treatment and corresponding restoration of the biomechanical properties of the hip joint. The implantation of a bipolar partial hip endoprosthesis for patients with displaced medial femoral neck fractures improves the biomechanical and clinical features of the hip, what should have on mind during making decision about treatment

    New components of the Dictyostelium PKA pathway revealed by Bayesian analysis of expression data

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    BACKGROUND: Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant information about genetic networks, but mining the data is not a trivial task. Algorithms that infer Bayesian networks from expression data are powerful tools for learning complex genetic networks, since they can incorporate prior knowledge and uncover higher-order dependencies among genes. However, these algorithms are computationally demanding, so novel techniques that allow targeted exploration for discovering new members of known pathways are essential. RESULTS: Here we describe a Bayesian network approach that addresses a specific network within a large dataset to discover new components. Our algorithm draws individual genes from a large gene-expression repository, and ranks them as potential members of a known pathway. We apply this method to discover new components of the cAMP-dependent protein kinase (PKA) pathway, a central regulator of Dictyostelium discoideum development. The PKA network is well studied in D. discoideum but the transcriptional networks that regulate PKA activity and the transcriptional outcomes of PKA function are largely unknown. Most of the genes highly ranked by our method encode either known components of the PKA pathway or are good candidates. We tested 5 uncharacterized highly ranked genes by creating mutant strains and identified a candidate cAMP-response element-binding protein, yet undiscovered in D. discoideum, and a histidine kinase, a candidate upstream regulator of PKA activity. CONCLUSIONS: The single-gene expansion method is useful in identifying new components of known pathways. The method takes advantage of the Bayesian framework to incorporate prior biological knowledge and discovers higher-order dependencies among genes while greatly reducing the computational resources required to process high-throughput datasets

    Problems regarding implementation of e-learning

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    When considering the implementation of e-learning into our system of education, attention must be paid to the demands to be met at different levels. It is a known fact that the difficulty of implementation varies from primary school to university. In primary schools, e-learning is only a supplement to traditional lessons, while at university tutorials can be made up entirely of e-learning elements. However, High School falls between these two levels - the extent of e-learning is not adequately defined and its implementation is much more problematic than one would expect. Ideally, the progress of a student’s comprehension should grow linearly from primary school to university. This would also allow for a gradual increase in the e-learning content of lessons. However, the reality in education is quite different. It must be recognised that the transition between primary and high school, and between high school and university is not as smooth as it should be. There exists a large gap in a student’s comprehension at these two stages of transition, which for many students results in a reduced level of achievement. This happens because, before the transitional stage, students are not as competent in their independent learning skills as the next stage would require. A decrease in overall success rates is seen very early in the first year of these stages of transition (the first year of high school and the first year at university). This gap in a student’s comprehension at these transitional stages results in further difficulties because of the increased use of e-learning in the stage that follows. Students have enough problems developing their learning capabilities and further changes (however positive) can also lead to a reduced level of achievement. When considering implementation into the system of education, all three levels must be coordinated in order to reduce the large disparities that cause so many problems

    Digital Characterization of observers using computer vision in real-time

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    We present implementation of a system for digital characterization. The term digital characterization is used to describe the functions of an intelligent system for displaying selected visual information on a computer screen. The system tracks and characterizes the viewers by analyzing the images of their faces taken by the camera attached to the screen, using the real-time computer vision methods. Non-contact interaction between system and observer is performed according to observer’s characteristics (e.g. gender, age group), estimation of observer’s distance and location relative to the camera. The system also performs logging and visualization of recorded data. The system is designed for real time application using standard computer hardware
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