A Comparison of Algorithms for Learning Hidden Variables in Normal Graphs

A Bayesian factor graph reduced to normal form consists in the interconnection of diverter units (or equal constraint units) and Single-Input/Single-Output (SISO) blocks. In this framework localized adaptation rules are explicitly derived from a constrained maximum likelihood (ML) formulation and from a minimum KL-divergence criterion using KKT conditions. The learning algorithms are compared with two other updating equations based on a Viterbi-like and on a variational approximation respectively. The performance of the various algorithm is verified on synthetic data sets for various architectures. The objective of this paper is to provide the programmer with explicit algorithms for rapid deployment of Bayesian graphs in the applications.Comment: Submitted for journal publicatio

Towards Building Deep Networks with Bayesian Factor Graphs

We propose a Multi-Layer Network based on the Bayesian framework of the Factor Graphs in Reduced Normal Form (FGrn) applied to a two-dimensional lattice. The Latent Variable Model (LVM) is the basic building block of a quadtree hierarchy built on top of a bottom layer of random variables that represent pixels of an image, a feature map, or more generally a collection of spatially distributed discrete variables. The multi-layer architecture implements a hierarchical data representation that, via belief propagation, can be used for learning and inference. Typical uses are pattern completion, correction and classification. The FGrn paradigm provides great flexibility and modularity and appears as a promising candidate for building deep networks: the system can be easily extended by introducing new and different (in cardinality and in type) variables. Prior knowledge, or supervised information, can be introduced at different scales. The FGrn paradigm provides a handy way for building all kinds of architectures by interconnecting only three types of units: Single Input Single Output (SISO) blocks, Sources and Replicators. The network is designed like a circuit diagram and the belief messages flow bidirectionally in the whole system. The learning algorithms operate only locally within each block. The framework is demonstrated in this paper in a three-layer structure applied to images extracted from a standard data set.Comment: Submitted for journal publicatio

3-D Hand Pose Estimation from Kinect's Point Cloud Using Appearance Matching

We present a novel appearance-based approach for pose estimation of a human hand using the point clouds provided by the low-cost Microsoft Kinect sensor. Both the free-hand case, in which the hand is isolated from the surrounding environment, and the hand-object case, in which the different types of interactions are classified, have been considered. The hand-object case is clearly the most challenging task having to deal with multiple tracks. The approach proposed here belongs to the class of partial pose estimation where the estimated pose in a frame is used for the initialization of the next one. The pose estimation is obtained by applying a modified version of the Iterative Closest Point (ICP) algorithm to synthetic models to obtain the rigid transformation that aligns each model with respect to the input data. The proposed framework uses a "pure" point cloud as provided by the Kinect sensor without any other information such as RGB values or normal vector components. For this reason, the proposed method can also be applied to data obtained from other types of depth sensor, or RGB-D camera

Semantic Cross-View Matching

Matching cross-view images is challenging because the appearance and viewpoints are significantly different. While low-level features based on gradient orientations or filter responses can drastically vary with such changes in viewpoint, semantic information of images however shows an invariant characteristic in this respect. Consequently, semantically labeled regions can be used for performing cross-view matching. In this paper, we therefore explore this idea and propose an automatic method for detecting and representing the semantic information of an RGB image with the goal of performing cross-view matching with a (non-RGB) geographic information system (GIS). A segmented image forms the input to our system with segments assigned to semantic concepts such as traffic signs, lakes, roads, foliage, etc. We design a descriptor to robustly capture both, the presence of semantic concepts and the spatial layout of those segments. Pairwise distances between the descriptors extracted from the GIS map and the query image are then used to generate a shortlist of the most promising locations with similar semantic concepts in a consistent spatial layout. An experimental evaluation with challenging query images and a large urban area shows promising results

Low-complexity dominance-based Sphere Decoder for MIMO Systems

The sphere decoder (SD) is an attractive low-complexity alternative to maximum likelihood (ML) detection in a variety of communication systems. It is also employed in multiple-input multiple-output (MIMO) systems where the computational complexity of the optimum detector grows exponentially with the number of transmit antennas. We propose an enhanced version of the SD based on an additional cost function derived from conditions on worst case interference, that we call dominance conditions. The proposed detector, the king sphere decoder (KSD), has a computational complexity that results to be not larger than the complexity of the sphere decoder and numerical simulations show that the complexity reduction is usually quite significant

K-Trek: A Peer-to-Peer Approach To Distribute Knowledge In Large Environments

In this paper, we explore an architecture, called K-Trek, that enables mobile users to travel across knowledge distributed over a large geographical area (ranging from large public buildings to a national park). Our aim is providing, dis-tributing, and enriching the environment with location-sensitive information for use by agents on board of mobile and static devices. Local interactions among K-Trek devices and the distribution of information in the larger environment adopt some typical peer-to-peer patterns and techniques. We introduce the architecture, discuss some of its potential knowledge management applications, and present a few experimental results obtained with simulation

A stacked autoencoder-based convolutional and recurrent deep neural network for detecting cyberattacks in interconnected power control systems

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The role of diallyl thiosulfinate associated with nuciferine and diosgenin in the treatment of premature ejaculation: a pilot study

Objective: To assess the efficacy and safety of an association of diallyl thiosulfinate with nuciferine and diosgenin in the treatment of a group of patients suffering from premature ejaculation (PE), primary or secondary to erectile dysfunction (ED). Materials and methods: From July 2015 to October 2016, 143 patients (mean age 25.3; range 18-39) affected by PE completed the study and were finally analyzed in this phase I study. All patients, after clinical assessment and laboratory evaluation were asked to take an association of diallyl thiosulfinate with nuciferine and diosgenin as oral tablet, once a day, on alternate days, for three months. At the baseline and after three months of treatment, each patient was asked to complete the following questionnaires: International Index of Erectile Function (IIEF-5), Premature Ejaculation Diagnostic Tool (PEDT), Male Sexual Health Questionnaire (MSHQ). Results: A statistical significant improvement in terms of erectile function, comparing the IIEF-5 value at baseline and follow-up visit was found (respectively IIEF-5: 8.7 vs 14.01; p < 0.001). Moreover, at follow-up visit, 97/143 men (67.8%) referred a subjective improvement of the erection quality and a better control of the ejaculation (PROs). The IELT improved too between the baseline evaluation and the follow-up visit (p < 0.001). Conclusion: In conclusion, our study, even if supported by preliminary results, showed how Diallyl Thiosulfinate, Nuciferine and Diosgenin is able to improve the control of ejaculation in patients suffering from PE, primary or secondary to ED without any significant adverse effects

Negative Pressure Wound Therapy applied to a cholecystoparietal fistula: How to treat a rare complication of a common condition - a case report

A cholecystoparietal fistula is an uncommon complication of gallstone disease as a result of neglected gallbladder disease).The subcutaneous abdominal wall abscess, derived from this condition, might be wide and hard to treat, especially in elderly and debilitated patients. The best management of cholecystoparietal fistula depends on its etiology and may require medical, surgical, or endoscopic treatment. Negative Pressure Wound Therapy (NPWT) is a valuable support therapy that can improve the prognosis of the disease and the patient’s outcome. We report the case of an 89-year-old female patient affected by a spontaneous cholecystoparietal fistula with a wide abdominal wall abscess treated by a one-stage surgical approach combined with NPWT over the resulting skin loss