This paper presents a novel approach for the removal of semi-transparent defects from images of historical or artistic importance. It combines Lie group transformations with human perception rules in order to make restoration more flexible and adaptable to defects having different physical or mechanical causes. In particular, the restoration process consists of an iterative procedure that gradually reduces the visual perception of the defect. It takes advantage from Lie groups that allow to define a redundant set of transformations from which it is possible to automatically select the ones that better invert the physical formation of the defect. Experimental results on movies and photographs, affected by line-scratches and semi-transparent blotches, have shown the potential of the proposed approach in giving new guidelines and trends for human perception-based restoration.

The objective of the paper is to embed perception rules into the kernel-based target tracking algorithm and to evaluate to what extent these rules are able to improve the original tracking algorithm, without any additional computational cost. To this aim, the target is represented through features that are related to its visual appearance; then, it is tracked in subsequent frames using a metric that, again, correlates well with the human visual perception (HVP). The use of HVP rules are twofold advantageous: it allows us to both increase tracking efficacy and considerably reduce the computational cost of the tracking process-thanks to the reduced size of the perceptual feature space. Various tests on video sequences have shown the stability and the robustness of the proposed framework, also in the presence of both other moving objects and partial or complete target occlusion in a limited number of subsequent frames.

This paper deals with the typical set of an image quality assessment (IQA) measure. In particular, it focuses on the well known and widely used Structural SIMilarity index (SSIM). In agreement with Information Theory, the visual distortion typical set is composed of the least amount of information necessary to estimate the quality of the distorted image. General criteria for an effective and fruitful computation of the set will be given. As it will be shown, the typical set allows to increase IQA efficiency by considerably speeding up its computation, thanks to the reduced number of image blocks used for the evaluation of the considered IQA metric. Copyright © 2014 SCITEPRESS.

Summary: We present RNASeqGUI R package, a graphical user interface (GUI) for the identification of differentially expressed genes across multiple biological conditions. This R package includes some wellk-nown RNA-Seq tools, available at www.bioconductor.org. RNASeqGUI package is not just a collection of some known methods and functions, but it is designed to guide the user during the entire analysis process. RNASeqGUI package is mainly addressed to those users who have little experience with command-line software. Therefore, thanks to RNASeqGUI, they can conduct analogous analyses using this simple graphical interface. Moreover, RNASeqGUI is also helpful for those who are expert R-users because it speeds up the usage of the included RNASeq methods drastically.

In this paper the phase behavior and pattern formation in a sheared nonideal fluid under a periodic potential is studied. An isothermal two-dimensional formulation of a lattice Boltzmann scheme for a liquid-vapor system with the van der Waals equation of state is presented and validated. Shear is applied by moving walls and the periodic potential varies along the flow direction. A region of the parameter space, where in the absence of flow a striped phase with oscillating density is stable, will be considered. At low shear rates the periodic patterns are preserved and slightly distorted by the flow. At high shear rates the striped phase loses its stability and traveling waves on the interface between the liquid and vapor regions are observed. These waves spread over the whole system with wavelength only depending on the length of the system. Velocity field patterns, characterized by a single vortex, will also be shown.

We assess the Lattice Boltzmann (LB) method versus centered finite-difference schemes for the solution of the advection-diffusion-reaction (ADR) Fisher's equation. It is found that the LB method performs significantly better than centered finite-difference schemes, a property we attribute to the near absence of dispersion errors.

Recently, synthetic aperture radar interferometry (InSAR) has been recognized as a promising tool to generate high-resolution maps of atmospherical precipitable water vapor temporal changes (Delta PWV) from the propagation delay of radar signal in atmosphere. The relationship between Delta PWV and propagation delay mainly depends on the vertical profiles of temperature and water vapor pressure. In this letter, we present a methodology to study the spatial and temporal variations of the temperature's vertical profile and generate more accurate high-resolution Delta PWV maps by means of InSAR.

The purpose of this article is to present a methodology to identify the sources of activity in brain networks from functional magnetic resonance imaging (fMRI) data using the multiset canonical correlation analysis algorithm. The aim is to lay the foundations for a screening marker to be used as indicator of mental diseases. Group analysis blind source separation methods have proved reliable to extract the latent sources underlying the brain activities but currently there is no recognized biomarker for mental disorders. Recent studies have identified alterations in the so called default mode network (DMN) that are common to several neuropsychiatric disorders, including schizophrenia. In particular, here we account for the hypothesis that the alterations in the DMN activity can be effectively highlighted by analyzing the transient states between two different tasks. A set of fMRI data acquired from 18 subjects performing working memory tasks is investigated for such purpose. Subjects are patients affected by schizophrenia for one half and healthy control subjects for the other. Under these conditions, the proposed methodology provides high discrimination performances in terms of classification error, thereby providing promising results for a preliminary tool able to monitor the disease state or to perform a prescreening for patients at risk for schizophrenia. © 2014 Wiley Periodicals, Inc.

Earth Observation (EO) mining systems aim at supporting efficient access and exploration of large volumes of image products. In this work, we address the problem of content-based image retrieval via example-based queries from Petabyte-scale EO data archives. To this end, we propose an interactive data mining system that relies on distributing unsupervised ingestion processes onto virtual machine instances in elastic, on-demand computing infrastructures that also support archive-scale content indexing via a "big data" analytics cluster-computing framework. In particular, we focus on the analysis of polarimetric SAR data, for which target decomposition theorems have proved fundamental in discovering patterns in data and in characterizing the ground scattering properties. Experiments are carried out on the publicly available UAVSAR full polarimetric data archive, whose basic products amount to about 0.64 PB of storage. We report the results of the tests performed by using a public IaaS. The obtained measures appear promising for data mapping and information retrieval applications.

The availability of omic data produced from international consortia, as well as from worldwide laboratories, is offering the possibility both to answer long-standing questions in biomedicine/molecular biology and to formulate novel hypotheses to test. However, the impact of such data is not fully exploited due to a limited availability of multi-omic data integration tools and methods. In this paper, we discuss the interplay between gene expression and epigenetic markers/transcription factors. We show how integrating ChIP-seq and RNA-seq data can help to elucidate gene regulatory mechanisms. In particular, we discuss the two following questions: (i) Can transcription factor occupancies or histone modification data predict gene expression? (ii) Can ChIP-seq and RNA-seq data be used to infer gene regulatory networks? We propose potential directions for statistical data integration. We discuss the importance of incorporating underestimated aspects (such as alternative splicing and long-range chromatin interactions). We also highlight the lack of data benchmarks and the need to develop tools for data integration from a statistical viewpoint, designed in the spirit of reproducible research.

The realization of innovative passengers transport services requires more and more often a greater flexibility and inexpensiveness of the service. To answer this request in many cases the physical solution is to realize a demand responsive transportation system (DRTS). A DRTS require the planning of travel paths (routing) and customers pick-up and drop-off times (scheduling) according to received requests, respecting the limited capacity of the fleet and time constraints (hard time windows) for each network's node, and the service time of the system. By the modelling point of view a DRTS can be effectively represented with a Dial-aride problem (DaRP). A DaRP derives from the Pick-up and Delivery Problem with Time Windows (PDPTW) and may operate according to a static or to a dynamic mode. In the static setting, all customers' requests are known beforehand and the DaRP returns the vehicles routing and the passengers pick up and drop off time scheduling. The static setting may be representative of a phase of reservation occurred the day before the execution of the service. But, if the reservation requests must be processed online, even during the booking process there may be a certain level ad dynamism. In fact, if the algorithm works online, it manages each and every incoming request separately, and accepts or refuses it immediately, without knowing anything about the following. The operative program is constantly updated after each received request without refusal to carry out previous accepted services. In the dynamic mode, customers' requests arrive when the service is already running and, consequently, the solution may change whilst the vehicle is already travelling. In this mode it is necessary that the schedule is updated when each new request arrives and that this is done in a short time to ensure that the potential customer will not leave the system before a possible answer. In this work, we describe a flexible people transport system capable of managing incoming transport demand in dynamic mode, using a solution architecture based on a two-stage algorithm to solve Dial-a-Ride Problem instances. In the first stage, a constructive heuristic algorithm quickly provides a feasible solution to accept the incoming demand. The algorithm in the second stage try to improve the solution evaluated at the first stage by using the time between two consecutive transportation events. The algorithm, unlike most of the works in the literature, use an objective function that optimizes the service punctuality.

One of the most important objectives of a manufacturing company is the optimization of the distribution of the produced goods considering the whole value chain. Unfortunately, in many companies the performance of the supply chain depends on many uncertain factors that are difficult to predict. The only way to face them is to adopt innovative solutions and tools that allow a swift response to the market changes. This paper analyzes the distribution processes managed by the logistics department of a large company producing and distributing petroleum products through the following main steps: crude oil's transportation typically from many countries to a refinery; refining process; maritime transportation from the refinery to three costal depots; road transport from depots to gas stations. The analyzed process is the primary supply, consisting in the maritime transport from the refinery to the coastal depots, liable to stochastic activities and events as weather condition. Through simulating the primary supply, we study the effects that the ship traffic generates on the overall variance of inventory levels at the costal depots with respect to specific inventory level targets, and analyze the impact of different tactical decision choices on the variance reduction. Reducing inventory's variance, through a better control of the distribution, allows the company to reduce inventory target levels and hence to reduce inventory costs in term of capital stock, while keeping the same risk level of stock out. The project is made of many phases: map all relevant processes to have a complete vision of transport's structure; conduct a statistical analysis to identify specific statistical distributions of every ships' process (delay, mooring, loading, etc.); model and simulate the primary supply using simulation software; use the model to make a "what-if" analysis. Within this project, it has been possible to realize a model that presents stochastic elements. All these phases are supported by six-sigma methodology, which focalizes on defects' process reduction by the control of its mean square deviation and following the stages of the DMAIC (Define Measure Analyze Improve Control). One of the what-if analysis which has been done consists in simulating the opening refinery's jetties h24, because currently these are closed during the night. Opening the jetties, will increase the capacity of some of the bottleneck resources for the oil distribution process, and thanks to the simulation model we can estimate quickly the effects on the oil transport system.

We review the main factors driving the calculation of the tangent height of spaceborne limb measurements: the ray-tracing method, the refractive index model and the assumed atmosphere. We find that commonly used ray tracing and refraction models are very accurate, at least in the mid-infrared. The factor with largest effect in the tangent height calculation is the assumed atmosphere. Using a climatological model in place of the real atmosphere may cause tangent height errors up to ± 200 m. Depending on the adopted retrieval scheme, these errors may have a significant impact on the derived profiles.