Search results for "List"
showing 10 items of 4869 documents
Mean sets for building 3D probabilistic liver atlas from perfusion MR images
2012
This paper is concerned with liver atlas construction. One of the most important issues in the framework of computational abdominal anatomy is to define an atlas that provides a priori information for common medical task such as registration and segmentation. Unlike other approaches already proposed so far (to our knowledge), in this paper we propose to use the concept of random compact mean set to build probabilistic liver atlases. To accomplish this task a two-tier process was carried out. First a set of 3D images was manually segmented by a physician. We see the different 3D segmented shapes as a realization of a random compact set. Secondly, elements of two known definitions of mean set…
Bayesian Metanetwork for Context-Sensitive Feature Relevance
2006
Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of appropriate conditional dependency. However, depending on task and context, many attributes of the model might not be relevant. If a network has been learned across multiple contexts then all uncovered conditional dependencies are averaged over all contexts and cannot guarantee high predictive accuracy when applied to a concrete case. We are considering a context as a set of contextual attributes, which are not directly effect probability distribution of the target attributes, but they effect on a “relevance” of the predictive attributes towards tar…
The role of synergies within generative models of action execution and recognition: A computational perspective
2015
Controlling the body – given its huge number of degrees of freedom – poses severe computational challenges. Mounting evidence suggests that the brain alleviates this problem by exploiting “synergies”, or patterns of muscle activities (and/or movement dynamics and kinematics) that can be combined to control action, rather than controlling individual muscles of joints [1–10]. D’Ausilio et al. [11] explain how this view of motor organization based on synergies can profoundly change the way we interpret studies of action recognition in humans and monkeys, and in particular the controversy on the “granularity” of the mirror neuron system (MNs): whether it encodes either (lower) kinematic aspects…
A Scheme for Secure and Reliable Distributed Data Storage in Unattended WSNs
2010
Unattended Wireless Sensor Networks (UWSNs) operated in hostile environments face a risk on data security due to the absence of real-time communication between sensors and sinks, which imposes sensors to accumulate data till the next visit of a mobile sink to off-load the data. Thus, how to ensure forward secrecy, backward secrecy and reliability of the accumulated data is a great challenge. For example, if a sensor is compromised, pre-compromise data accumulated in the sensor is exposed to access. In addition, by holding key secrecy of the compromised sensor, attackers also can learn post-compromise data in the sensor. Furthermore, in practical UWSNs, once sensors stop working for accident…
Quality-preserving low-cost probabilistic 3D denoising with applications to Computed Tomography
2021
AbstractWe propose a pipeline for a synthetic generation of personalized Computer Tomography (CT) images, with a radiation exposure evaluation and a lifetime attributable risk (LAR) assessment. We perform a patient-specific performance evaluation for a broad range of denoising algorithms (including the most popular Deep Learning denoising approaches, wavelets-based methods, methods based on Mumford-Shah denoising etc.), focusing both on accessing the capability to reduce the patient-specific CT-induced LAR and on computational cost scalability. We introduce a parallel probabilistic Mumford-Shah denoising model (PMS), showing that it markedly-outperforms the compared common denoising methods…
Super-orthogonal space-time trellis codes with differential phase modulation for noncoherent mobile communication systems
2010
In this paper, we show how to design super-orthogonal space-time trellis codes (SOSTTCs) using the differential binary phase-shift keying (PSK) modulation for noncoherent communication systems, for which the knowledge of the channel state information (CSI) at the receiver is not necessary. Moreover, a new decoding algorithm with reduced decoding complexity is proposed. In all simulations, a geometric two-ring channel model is employed to evaluate the performance of the SOSTTCs. The simulation results show that the proposed decoding algorithm has the same decoding performance compared with the traditional decoding strategy, while the new algorithm reduces significantly the overall computing …
Gaussian Process Regression (GPR) Representation in Predictive Model Markup Language (PMML)
2017
International audience; This paper describes Gaussian process regression (GPR) models presented in predictive model markup language (PMML). PMML is an extensible-markup-language (XML) -based standard language used to represent data-mining and predictive analytic models, as well as pre- and post-processed data. The previous PMML version, PMML 4.2, did not provide capabilities for representing probabilistic (stochastic) machine-learning algorithms that are widely used for constructing predictive models taking the associated uncertainties into consideration. The newly released PMML version 4.3, which includes the GPR model, provides new features: confidence bounds and distribution for the pred…
Artificial mosaics
2005
Art often provides valuable insight that can be applied to technological innovations, especially in the fields of image processing and computer graphics. In this paper we present a method to transform a raster input image into a good-quality mosaic: an “artificial mosaic.” The creation of mosaics of artistic quality is challenging because the tiles that compose a mosaic, typically small polygons, must be packed tightly and yet must follow and emphasize orientations chosen by the artist. The proposed method can reproduce the colors of the original image and emphasize relevant boundaries by placing tiles along edge directions. No user intervention is needed to detect the boundaries: they are …
Tensions of student voice in higher education : Involving students in degree programme curricula design
2020
This paper considers the direct involvement of students in degree programme curricula design, specifically four computer science teacher students designing new curricula for the Faculty of Information Technology of the University of Jyväskylä. They participated in a project to make recommendations for the 2017–2020 master’s and bachelor’s programme curricula. We examined how these recommendations were implemented in the new curricula and what hindered student voice. The project led to major changes: making basic studies in mathematics optional, adding three new courses, and defining new learning goal descriptions for two master’s programmes. Several factors hindered student voice: insuffici…
Some Considerations Regarding the Role and Importance of Talent Management
2018
The fact that human resources are an indispensable, vital resource, is unanimously accepted. Human resources enhance, improve the other resources and stand at the origin of all the performances of the company, of the achievement of its mission and goals. Every organization needs the right and talented people, specialists. Not only does an individual’s talent matter, it makes a difference. It is what grants more value to the company. Successful organizations are the ones that know how to find talented people, how to attract them, how to keep them and, particularly, how to enhance their talents.