Pose-based SLAM with probabilistic scan matching algorithm using a mechanical scanned imaging sonar

This paper proposes a pose-based algorithm to solve the full SLAM problem for an autonomous underwater vehicle (AUV), navigating in an unknown and possibly unstructured environment. The technique incorporate probabilistic scan matching with range scans gathered from a mechanical scanning imaging sonar (MSIS) and the robot dead-reckoning displacements estimated from a Doppler velocity log (DVL) and a motion reference unit (MRU). The proposed method utilizes two extended Kalman filters (EKF). The first, estimates the local path travelled by the robot while grabbing the scan as well as its uncertainty and provides position estimates for correcting the distortions that the vehicle motion produces in the acoustic images. The second is an augment state EKF that estimates and keeps the registered scans poses. The raw data from the sensors are processed and fused in-line. No priory structural information or initial pose are considered. The algorithm has been tested on an AUV guided along a 600 m path within a marina environment, showing the viability of the proposed approach

A concurrent region growing algorithm guided by circumscribed contours

Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach

Shout and Act: an Algorithm for Digital Objects Preservation Inspired from Rescue Robots

We adapt the Shout and Act algorithm to Digital Objects Preservation where agents explore file systems looking for digital objects to be preserved (victims). When they find something they “shout” so that agent mates can hear it. The louder the shout, the urgent or most important the finding is. Louder shouts can also refer to closeness. We perform several experiments to show that this system works very scalably, showing that heterogeneous teams of agents outperform homogeneous ones over a wide range of tasks complexity. The target at-risk documents are MS Office documents (including an RTF file) with Excel content or in Excel format. Thus, an interesting conclusion from the experiments is that fewer heterogeneous (varying skills) agents can equal the performance of many homogeneous (combined super-skilled) agents, implying significant performance increases with lower overall cost growth. Our results impact the design of Digital Objects Preservation teams: a properly designed combination of heterogeneous teams is cheaper and more scalable when confronted with uncertain maps of digital objects that need to be preserved. A cost pyramid is proposed for engineers to use for modeling the most effective agent combinations

An energy efficient vertical handover decision algorithm

As wireless communications evolve towards heterogeneousnetworks, mobile terminals have been enabled tohandover seamlessly from one network to another. At the sametime, the continuous increase in the terminal power consumptionhas resulted in an ever-decreasing battery lifetime. To that end,the network selection is expected to play a key role on howto minimize the energy consumption, and thus to extend theterminal lifetime. Hitherto, terminals select the network thatprovides the highest received power. However, it has been provedthat this solution does not provide the highest energy efficiency.Thus, this paper proposes an energy efficient vertical handoveralgorithm that selects the most energy efficient network thatminimizes the uplink power consumption. The performance of theproposed algorithm is evaluated through extensive simulationsand it is shown to achieve high energy efficiency gains comparedto the conventional approach.

Stress testing and risk evaluation of new capacity payment algorithm proposed by Market Council

In the Russian Wholesale Market, electricity and capacity are traded separately. Capacity is a special good, the sale of which obliges suppliers to keep their generating equipment ready to produce the quantity of electricity indicated by the System Operator. The purpose of the formation of capacity trading was the maintenance of reliable and uninterrupted delivery of electricity in the wholesale market. The price of capacity reflects constant investments in construction, modernization and maintenance of power plants. So, the capacity sale creates favorable conditions to attract investments in the energy sector because it guarantees the investor that his investments will be returned.

Solving Leontief Input-Output Model with Trapezoidal Fuzzy Numbers and Gauss-Seidel Algorithm

In this work a fuzzy linear system is used to solve Leontief input-output model with fuzzy entries. For solving this model, we assume that the consumption matrix from di erent sectors of the economy and demand are known. These assumptions heavily depend on the information obtained from the industries. Hence uncertainties are involved in this information. The aim of this work is to model these uncertainties and to address them by fuzzy entries such as fuzzy numbers and LR-type fuzzy numbers (triangular and trapezoidal). Fuzzy linear system has been developed using fuzzy data and it is solved using Gauss-Seidel algorithm. Numerical examples show the e ciency of this algorithm. The famous example from Prof. Leontief, where he solved the production levels for U.S. economy in 1958, is also further analyzed.

GAMS MINLP Solver comparisons and some improvements to the AlphaECP algorithm

I doktorsavhandlingen undersöks förmågan att lösa hos ett antal lösare för optimeringsproblem och ett antal svårigheter med att göra en rättvis lösarjämförelse avslöjas. Dessutom framläggs några förbättringar som utförts på en av lösarna som heter GAMS/AlphaECP. Optimering innebär, i det här sammanhanget, att finna den bästa möjliga lösningen på ett problem. Den undersökta klassen av problem kan karaktäriseras som svårlöst och förekommer inom ett flertal industriområden. Målet har varit att undersöka om det finns en lösare som är universellt snabbare och hittar lösningar med högre kvalitet än någon av de andra lösarna. Det kommersiella optimeringssystemet GAMS (General Algebraic Modeling System) och omfattande problembibliotek har använts för att jämföra lösare. Förbättringarna som presenterats har utförts på GAMS/AlphaECP lösaren som baserar sig på skärplansmetoden Extended Cutting Plane (ECP). ECP-metoden har utvecklats främst av professor Tapio Westerlund på Anläggnings- och systemteknik vid Åbo Akademi.

Software for calculation of reservoir active capacity with the sequent-peak algorithm

It is presented a software developed with Delphi programming language to compute the reservoir's annual regulated active storage, based on the sequent-peak algorithm. Mathematical models used for that purpose generally require extended hydrological series. Usually, the analysis of those series is performed with spreadsheets or graphical representations. Based on that, it was developed a software for calculation of reservoir active capacity. An example calculation is shown by 30-years (from 1977 to 2009) monthly mean flow historical data, from Corrente River, located at São Francisco River Basin, Brazil. As an additional tool, an interface was developed to manage water resources, helping to manipulate data and to point out information that it would be of interest to the user. Moreover, with that interface irrigation districts where water consumption is higher can be analyzed as a function of specific seasonal water demands situations. From a practical application, it is possible to conclude that the program provides the calculation originally proposed. It was designed to keep information organized and retrievable at any time, and to show simulation on seasonal water demands throughout the year, contributing with the elements of study concerning reservoir projects. This program, with its functionality, is an important tool for decision making in the water resources management.

Algorithm to determine the intersection curves between bezier surfaces by the solution of multivariable polynomial system and the differential marching method

The determination of the intersection curve between Bézier Surfaces may be seen as the composition of two separated problems: determining initial points and tracing the intersection curve from these points. The Bézier Surface is represented by a parametric function (polynomial with two variables) that maps a point in the tridimensional space from the bidimensional parametric space. In this article, it is proposed an algorithm to determine the initial points of the intersection curve of Bézier Surfaces, based on the solution of polynomial systems with the Projected Polyhedral Method, followed by a method for tracing the intersection curves (Marching Method with differential equations). In order to allow the use of the Projected Polyhedral Method, the equations of the system must be represented in terms of the Bernstein basis, and towards this goal it is proposed a robust and reliable algorithm to exactly transform a multivariable polynomial in terms of power basis to a polynomial written in terms of Bernstein basis .

Numerical Simulation of the Cavitation in the Hydrodynamic Lubrication of Journal Bearings: a Parallel Algorithm

In this paper we present an algorithm for the numerical simulation of the cavitation in the hydrodynamic lubrication of journal bearings. Despite the fact that this physical process is usually modelled as a free boundary problem, we adopted the equivalent variational inequality formulation. We propose a two-level iterative algorithm, where the outer iteration is associated to the penalty method, used to transform the variational inequality into a variational equation, and the inner iteration is associated to the conjugate gradient method, used to solve the linear system generated by applying the finite element method to the variational equation. This inner part was implemented using the element by element strategy, which is easily parallelized. We analyse the behavior of two physical parameters and discuss some numerical results. Also, we analyse some results related to the performance of a parallel implementation of the algorithm.

Expression of CD40 ligand, interferon-gamma and Fas ligand genes in endomyocardial biopsies of human cardiac allografts: correlation with acute rejection

The purpose of the present study was to investigate the expression (mRNA) of CD40 ligand (CD40L), interferon-gamma (IFN-gamma) and Fas ligand (FasL) genes in human cardiac allografts in relation to the occurrence of acute cardiac allograft rejection as well as its possible value in predicting acute rejection. The mRNA levels were determined by a semiquantitative reverse transcriptase-polymerase chain reaction method in 39 samples of endomyocardial biopsies obtained from 10 adult cardiac transplant recipients within the first six months after transplantation. Biopsies with ongoing acute rejection showed significantly higher CD40L, IFN-gamma and FasL mRNA expression than biopsies without rejection. The median values of mRNA expression in biopsies with and without rejection were 0.116 and zero for CD40L (P<0.003), 0.080 and zero for IFN-gamma (P<0.0009), and 0.156 and zero for FasL (P<0.002), respectively. In addition, the levels of IFN-gamma mRNA were significantly increased 7 to 15 days before the appearance of histological evidence of rejection (median of 0.086 in pre-rejection biopsies), i.e., they presented a predictive value. This study provides further evidence of heightened expression of immune activation genes during rejection and shows that some of these markers may present predictive value for the occurrence of acute rejection.

The role of CD8+ T cells during allograft rejection

Organ transplantation can be considered as replacement therapy for patients with end-stage organ failure. The percent of one-year allograft survival has increased due, among other factors, to a better understanding of the rejection process and new immunosuppressive drugs. Immunosuppressive therapy used in transplantation prevents activation and proliferation of alloreactive T lymphocytes, although not fully preventing chronic rejection. Recognition by recipient T cells of alloantigens expressed by donor tissues initiates immune destruction of allogeneic transplants. However, there is controversy concerning the relative contribution of CD4+ and CD8+ T cells to allograft rejection. Some animal models indicate that there is an absolute requirement for CD4+ T cells in allogeneic rejection, whereas in others CD4-depleted mice reject certain types of allografts. Moreover, there is evidence that CD8+ T cells are more resistant to immunotherapy and tolerance induction protocols. An intense focal infiltration of mainly CD8+CTLA4+ T lymphocytes during kidney rejection has been described in patients. This suggests that CD8+ T cells could escape from immunosuppression and participate in the rejection process. Our group is primarily interested in the immune mechanisms involved in allograft rejection. Thus, we believe that a better understanding of the role of CD8+ T cells in allograft rejection could indicate new targets for immunotherapy in transplantation. Therefore, the objective of the present review was to focus on the role of the CD8+ T cell population in the rejection of allogeneic tissue.

The Rejection of Prioritarianism

Since the late 1990’s, a group of moral doctrines called prioritarianism has received a lot of interest from many moral philosophers. Many contemporary moral philosophers are attracted to prioritarianism to such an extent that they can be called prioritarians. In this book, however, I reject prioritarianism, including not only “pure” prioritarianism but also hybrid prioritarian views which mix one or more non-prioritarian elements with prioritarianism. This book largely revolves around certain problems and complications of prioritarianism and its particular forms. Those problems and complications are connected to risk, impartiality, the arbitrariness of prioritarian weightings and possible future individuals. On the one hand, I challenge prioritarianism through targeted objections to various specific forms of prioritarianism. All those targeted objections are connected to risk or possible future individuals. It seems to me that together they give good grounds for believing that prioritarianism is not the way to go. On the other hand, I challenge prioritarianism by pointing out and discussing certain general problems of prioritarianism. Those general problems are connected to impartiality and the arbitrariness of prioritarian weightings. They may give additional grounds for believing that all prioritarian views should be rejected. Prioritarianism can be seen as a type of weighted utilitarianism and thus as an extension of utilitarianism. Utilitarianism is morally ultimately concerned, and morally ultimately concerned only, with some kind of maximization of utility or expected utility. Prioritarianism, on the other hand, is morally ultimately concerned, and morally ultimately concerned only, with some kind of maximization of priority-weighted utility, expected priority-weighted utility or priority-weighted expected utility. Thus prioritarianism, unlike utilitarianism, is a distribution-sensitive moral view. Besides rejecting prioritarianism, I reject also various other distribution-sensitive moral views in this book. However, I do not reject distribution-sensitivity in morality, as I end up endorsing a type of distribution-sensitive hybrid utilitarianism which mixes non-utilitarian elements with utilitarianism.

Induction of oral tolerance and the effect of interleukin-4 on murine skin allograft rejection

We studied the effect of oral and portal vein administration of alloantigens on mouse skin allograft survival. Graft receptor BALB/c mice received spleen cells (30, 90, 150 or 375 x 10(6)) from donor C57BL/6 mice intragastrically on three successive days, starting seven days before the skin graft. Allograft survival was significantly increased with the feeding of 150 x 10(6) allogeneic spleen cells by one gavage (median survival of 12 vs 14 days, P <= 0.005) or when 300 x 10(6) cells were given in six gavage (12 vs 14 days, P < 0.04). A similar effect was observed when 150 x 10(6) spleen cells were injected into the portal vein (12 vs 14 days, P <= 0.03). Furthermore, prolonged allograft survival was observed with subcutaneous (12 vs 16 days, P <= 0.002) or systemic (12 vs 15 days, P <= 0.016) application of murine interleukin-4 (IL-4), alone or in combination with spleen cell injection into the portal vein (12 vs 18 days, P <= 0.0018). Taken together, these results showed that tolerance induction with spleen cells expressing fully incompatible antigens by oral administration or intraportal injection partially down-modulates skin allograft rejection. Furthermore, these findings demonstrated for the first time the effect of subcutaneous or systemic IL-4 application on allograft skin survival suggesting its use as a beneficial support therapy in combination with a tolerance induction protocol.