Modelling Modelled

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    A model is one of the most fundamental concepts: it is a formal and generalized explanation of a phenomenon. Only with models we can bridge the particulars and predict the unknown. Virtually all our intellectual work turns around finding models, evaluating models, using models. Because models are so pervasive, it makes sense to take a look at modelling itself. We will approach this problem, of course, by building a model of the process of modelling

    Algebraic integrability of confluent Neumann system

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    In this paper we study the Neumann system, which describes the harmonic oscillator (of arbitrary dimension) constrained to the sphere. In particular we will consider the confluent case where two eigenvalues of the potential coincide, which implies that the system has S1S^1 symmetry. We will prove complete algebraic integrability of the confluent Neumann system and show that its flow can be linearized on the generalized Jacobian torus of some singular algebraic curve. The symplectic reduction of S 1 action will be described and we will show that the general Rosochatius system is a symplectic quotient of the confluent Neumann system, where all the eigenvalues of the potential are double

    Machine learning for survival analysis: a case study on recurrence of prostate cancer

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    Machine learning techniques have recently received considerable attention, especially when used for the construction of prediction models from data. Despite their potential advantages over standard statistical methods, like their ability to model non-linear relationships and construct symbolic and interpretable models, their applications to survival analysis are at best rare, primarily because of the difficulty to appropriately handle censored data. In this paper we propose a schema that enables the use of classification methods — including machine learning classifiers — for survival analysis. To appropriately consider the follow-up time and censoring, we propose a technique that, for the patients for which the event did not occur and have short follow-up times, estimates their probability of event and assigns them a distribution of outcome accordingly. Since most machine learning techniques do not deal with outcome distributions, the schema is implemented using weighted examples. To show the utility of the proposed technique, we investigate a particular problem of building prognostic models for prostate cancer recurrence, where the sole prediction of the probability of event (and not its probability dependency on time) is of interest. A case study on preoperative and postoperative prostate cancer recurrence prediction shows that by incorpo- rating this weighting technique the machine learning tools stand beside modern statistical methods and may, by inducing symbolic recurrence models, provide further insight to relationships within the modeled data

    Nomograms for Visualizing Linear Support Vector Machines

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    Support vector machines are often considered to be black box learning algorithms. We show that for linear kernels it is possible to open this box and visually depict the content of the SVM classifier in high-dimensional space in the interactive format of a nomogram. We provide a cross-calibration method for obtaining probabilistic predictions from any SVM classifier, which control for the generalization error. If we employ logistic regression for calibration, the effect of each attribute can be represented on the log odds ratio scale. We also describe an approach to capturing nonlinear effects of continuous attributes with an ordinary linear kernel, and adapt the nomogram so that these nonlinear effects can be graphically rendered

    2D Versus 3D Colour Space Face Detection

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    Computer vision is one out of many areas that want to understand the process of human functionality and copy that process with intention to complement human life with intelligent machines. For better human-computer interaction it is necessary for the machine to see people. This can be achieved by employing face detection algorithms, like the one used in the installation "15 Seconds of Fame". Mentioned installation unites the areas of modern art and technology. Its algorithm is based on skin colour detection. One of the problems this and similar algorithms have to deal with is sensitivity to the illumination conditions under which the input image is captured. Hence illumination sensitivity influences face detection results. One of the aspects from which we can observe illumination influence is the choosing of the proper colour space. Since some colour spaces are designed to eliminate the influence of illumination when describing colour of an object, an idea of using such a colour space for skin-colour detection was taken under consideration and some of the methods were researched and tested

    Puzzle Game

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    The idea of the project was build at the University of Ljubljana, Faculty of Computer and Information Science, in scope of the course Communication Methods, in collaboration with Academy of Fine Arts and Design. It’s main goal was to build an interactive system between a user and a canvas, using only a projector, infra-red (IR) transmitter and IR camera. In other words, user will be able to play some game with IR transmitter, which will be recognized by IR camera, with the main window of the application displayed on the canvas. The game implemented in the project is a puzzle and it’s just for the purpose of showing, how the system can interact with it’s surroundings. Projector projects the image on to the canvas and the player standing in front of the canvas is choosing the particles of puzzle he wants to exchange. Game has more different puzzle images to be solved, each composed of different number of particles. Number of puzzle particles grows, when the puzzle is solved. The most significant part of the project was to develop a method that recognizes the position of the IR transmitter in the image acquired from the IR camera. We will describe used methods and the difficulties we came across. We will also describe all elements needed, from the software used to hardware. The aplication can be transformed into more complex interactive system

    15 seconds of fame

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    15 seconds of fame is an interactive installation that every 15 seconds generates a new pop-art portrait of a randomly selected viewer. The installation was inspired by Andy Warhol's ironical statement that In the future everybody will be famous for 15 minutes. The installation detects human faces and crops them from the wide-angle view of people standing before the installation. Pop-art portraits are then generated by applying randomly selected filters to a randomly chosen face from the audience. These portraits are then shown in 15-second intervals on the flat-panel computer monitor, which is framed as a painting

    Polymorphic members of the lag gene family mediate kin discrimination in Dictyostelium

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    Self and kin discrimination are observed in most kingdoms of life and are mediated by highly polymorphic plasma membrane proteins. Sequence polymorphism, which is essential for effective recognition, is maintained by balancing selection. Dictyostelium discoideum are social amoebas that propagate as unicellular organisms but aggregate upon starvation and form fruiting bodies with viable spores and dead stalk cells. Aggregative development exposes Dictyostelium to the perils of chimerism, including cheating, which raises questions about how the victims survive in nature and how social cooperation persists. Dictyostelids can minimize the cost of chimerism by preferential cooperation with kin, but the mechanisms of kin discrimination are largely unknown. Dictyostelium lag genes encode transmembrane proteins with multiple immunoglobulin (Ig) repeats that participate in cell adhesion and signaling. Here, we describe their role in kin discrimination. We show that lagB1 and lagC1 are highly polymorphic in natural populations and that their sequence dissimilarity correlates well with wild-strain segregation. Deleting lagB1 and lagC1 results in strain segregation in chimeras with wild-type cells, whereas elimination of the nearly invariant homolog lagD1 has no such consequences. These findings reveal an early evolutionary origin of kin discrimination and provide insight into the mechanism of social recognition and immunity

    Computerized segmentation of whole-body bone scintigrams and its use in automated diagnostics

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    Bone scintigraphy or whole-body bone scan is one of the most common diagnostic procedures in nuclear medicine used in the last 25 years. Pathological conditions, technically poor image resolution and artifacts necessitate that algorithms use su±cient background knowledge of anatomy and spatial relations of bones in order to work satisfactorily. A robust knowledge based methodology for detecting reference points of the main skeletal regions that is simultaneously applied on anterior and posterior whole-body bone scintigrams is presented. Expert knowledge is represented as a set of parameterized rules which are used to support standard image processing algorithms. Our study includes 467 consecutive, non-selected scintigrams, which is, to our knowledge the largest number of images ever used in such studies. Automatic analysis of whole-body bone scans using our segmentation algorithm gives more accurate and reliable results than previous studies. Obtained reference points are used for automatic segmentation of the skeleton, which is applied to automatic (machine learning) or manual (expert physicians) diagnostics. Preliminary experiments show that an expert system based on machine learning closely mimics the results of expert physicians

    Educational possibilities of the project Colour visualization of music

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    We propose a system of colour visualization of music based on a system of colour signs, which are connected to musical tones. Tones, which are in harmonic relationships, are represented by related colours. First, we outline the foundations on which the system of colour signs is based – the mathematical model of harmony. We discuss several possibilities of visual representation of expressive elements of music – melody, composition, rhythm and harmony. These relationships enabled us to develop a computer program that employs these elements for visualization. The program mimics human perception in which the parts are determined by the perception of the whole. Furthermore, the program enables the development of tools that can enhance music understanding during listening or performing. Music performance can acquire a new quality with the use of interactive coloured musical instruments, which by using colours show the performer different possibilities for forming musical harmonies and thereby change the composing of music into a game and attractive colour-aural journey. Here we stumble upon a challenge for educational science and methodology: how to use such upcoming multimedia tools. These tools would bring the processes of learning and playing a game closer together since playing games is a child’s most natural form of functioning. Furthermore, in the area of artistic creation we can once again establish a balance between our logical and intuitive nature
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