Stability of an unsupported vertical circular excavation in clays under undrained condition

By using the axisymmetric finite elements static limit analysis formulation, proposed recently by the authors, the stability numbers (gamma H/c(o)) for an unsupported vertical circular excavation in clays, whose cohesion increases with depth, have been determined under undrained condition; gamma = unit weight, H., height of the excavation and c(o) = cohesion along ground surface. The results are obtained for various values of H/b and m; where b = the radius of the excavation and m = a non-dimensional parameter which accounts for the rate of the increase of cohesion with depth. The values of the stability numbers increase continuously both with increases in H/b and m. The results obtained in this study compare well with those available in literature.(C) 2009 Elsevier Ltd. All rights reserved.

A voltage-sensorless control method to balance the input currents of a three-wire boost rectifier under unbalanced input voltages condition

This paper proposes a control method that can balance the input currents of the three-phase three-wire boost rectifier under unbalanced input voltage condition. The control objective is to operate the rectifier in the high-power-factor mode under balanced input voltage condition but to give overriding priority to the current balance function in case of unbalance in the input voltage. The control structure has been divided into two major functional blocks. The inner loop current-mode controller implements resistor emulation to achieve high-power-factor operation on each of the two orthogonal axes of the stationary reference frame. The outer control loop performs magnitude scaling and phase-shifting operations on current of one of the axes to make it balanced with the current on the other axis. The coefficients of scaling and shifting functions are determined by two closed-loop prportional-integral (PI) controllers that impose the conditions of input current balance as PI references. The control algorithm is simple and high performing. It does not require input voltage sensing and transformation of the control variables into a rotating reference frame. The simulation results on a MATLAB-SIMULINK platform validate the proposed control strategy. In implementation Texas Instrument's digital signal processor TMS320F24OF is used as the digital controller. The control algorithm for high-power-factor operation is tested on a prototype boost rectifier under nominal and unbalanced input voltage conditions.

Methodological perspectives for register-based health system performance assessment : Developing a hip fracture monitoring system in Finland

The resources of health systems are limited. There is a need for information concerning the performance of the health system for the purposes of decision-making. This study is about utilization of administrative registers in the context of health system performance evaluation. In order to address this issue, a multidisciplinary methodological framework for register-based data analysis is defined. Because the fixed structure of register-based data indirectly determines constraints on the theoretical constructs, it is essential to elaborate the whole analytic process with respect to the data. The fundamental methodological concepts and theories are synthesized into a data sensitive approach which helps to understand and overcome the problems that are likely to be encountered during a register-based data analyzing process. A pragmatically useful health system performance monitoring should produce valid information about the volume of the problems, about the use of services and about the effectiveness of provided services. A conceptual model for hip fracture performance assessment is constructed and the validity of Finnish registers as a data source for the purposes of performance assessment of hip fracture treatment is confirmed. Solutions to several pragmatic problems related to the development of a register-based hip fracture incidence surveillance system are proposed. The monitoring of effectiveness of treatment is shown to be possible in terms of care episodes. Finally, an example on the justification of a more detailed performance indicator to be used in the profiling of providers is given. In conclusion, it is possible to produce useful and valid information on health system performance by using Finnish register-based data. However, that seems to be far more complicated than is typically assumed. The perspectives given in this study introduce a necessary basis for further work and help in the routine implementation of a hip fracture monitoring system in Finland.

Effect of boundary condition description on convergence of solution in a boundary-value problem

It is well known that the numerical accuracy of a series solution to a boundary-value problem by the direct method depends on the technique of approximate satisfaction of the boundary conditions and on the stage of truncation of the series. On the other hand, it does not appear to be generally recognized that, when the boundary conditions can be described in alternative equivalent forms, the convergence of the solution is significantly affected by the actual form in which they are stated. The importance of the last aspect is studied for three different techniques of computing the deflections of simply supported regular polygonal plates under uniform pressure. It is also shown that it is sometimes possible to modify the technique of analysis to make the accuracy independent of the description of the boundary conditions.

An intelligent approach using support vector machines for monitoring and identification of faults on transmission systems

Power system disturbances are often caused by faults on transmission lines. When faults occur in a power system, the protective relays detect the fault and initiate tripping of appropriate circuit breakers, which isolate the affected part from the rest of the power system. Generally Extra High Voltage (EHV) transmission substations in power systems are connected with multiple transmission lines to neighboring substations. In some cases mal-operation of relays can happen under varying operating conditions, because of inappropriate coordination of relay settings. Due to these actions the power system margins for contingencies are decreasing. Hence, power system protective relaying reliability becomes increasingly important. In this paper an approach is presented using Support Vector Machine (SVM) as an intelligent tool for identifying the faulted line that is emanating from a substation and finding the distance from the substation. Results on 24-bus equivalent EHV system, part of Indian southern grid, are presented for illustration purpose. This approach is particularly important to avoid mal-operation of relays following a disturbance in the neighboring line connected to the same substation and assuring secure operation of the power systems.

Tool wear monitoring using ant behaviour

In this paper we show the applicability of Ant Colony Optimisation (ACO) techniques for pattern classification problem that arises in tool wear monitoring. In an earlier study, artificial neural networks and genetic programming have been successfully applied to tool wear monitoring problem. ACO is a recent addition to evolutionary computation technique that has gained attention for its ability to extract the underlying data relationships and express them in form of simple rules. Rules are extracted for data classification using training set of data points. These rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in ACO based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The classification accuracy obtained in ACO based approach is as good as obtained in other biologically inspired techniques.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications.

Tests for Cointegration Rank and the Initial Condition

Many economic events involve initial observations that substantially deviate from long-run steady state. Initial conditions of this type have been found to impact diversely on the power of univariate unit root tests, whereas the impact on multivariate tests is largely unknown. This paper investigates the impact of the initial condition on tests for cointegration rank. We compare the local power of the widely used likelihood ratio (LR) test with the local power of a test based on the eigenvalues of the companion matrix. We find that the power of the LR test is increasing in the magnitude of the initial condition, whereas the power of the other test is decreasing. The behaviour of the tests is investigated in an application to price convergence.

Filter design using radial basis function neural network and genetic algorithm for improved operational health monitoring

The problem of denoising damage indicator signals for improved operational health monitoring of systems is addressed by applying soft computing methods to design filters. Since measured data in operational settings is contaminated with noise and outliers, pattern recognition algorithms for fault detection and isolation can give false alarms. A direct approach to improving the fault detection and isolation is to remove noise and outliers from time series of measured data or damage indicators before performing fault detection and isolation. Many popular signal-processing approaches do not work well with damage indicator signals, which can contain sudden changes due to abrupt faults and non-Gaussian outliers. Signal-processing algorithms based on radial basis function (RBF) neural network and weighted recursive median (WRM) filters are explored for denoising simulated time series. The RBF neural network filter is developed using a K-means clustering algorithm and is much less computationally expensive to develop than feedforward neural networks trained using backpropagation. The nonlinear multimodal integer-programming problem of selecting optimal integer weights of the WRM filter is solved using genetic algorithm. Numerical results are obtained for helicopter rotor structural damage indicators based on simulated frequencies. Test signals consider low order polynomial growth of damage indicators with time to simulate gradual or incipient faults and step changes in the signal to simulate abrupt faults. Noise and outliers are added to the test signals. The WRM and RBF filters result in a noise reduction of 54 - 71 and 59 - 73% for the test signals considered in this study, respectively. Their performance is much better than the moving average FIR filter, which causes significant feature distortion and has poor outlier removal capabilities and shows the potential of soft computing methods for specific signal-processing applications. (C) 2005 Elsevier B. V. All rights reserved.

Geriatrisen lääkehoidon koulutustarpeet perusterveydenhuollossa - Moniammatillisen täydennyskoulutuksen suunnittelu LOST-alueen kotihoidon henkilöstölle

Sosiaali- ja terveysministeriön 2006 julkaiseman vanhustyön ja geriatrisen lääkehoidon kehittämistä koskevan selvityksen yhtenä tärkeänä huolenaiheena oli iäkkäiden lääkehoidon useat epäkohdat, kuten iäkkäitä hoitavien hoitajien lääkeosaamiseen liittyvät puutteet ja ongelmat. Yksi keino parantaa iäkkäitä hoitavien eri tahojen lääkehoito-osaamista on täydennyskoulutus, johon kaikilla sosiaali- ja terveydenhuollon ammattiryhmillä on oikeus ja velvollisuus. Täydennyskoulutuksella pystytään myös kehittämään organisaatioiden toimintaa ja tuottamaan uusia, parempia palveluita. Tutkimuksessa selvitettiin Lohjan, Siuntion, Inkoon ja Karjalohjan muodostaman sosiaali- ja terveydenhuollon yhteistoiminta-alueen LOSTin kotihoidon yksiköiden iäkkäiden lääkehoitoihin liittyviä koulutustarpeita. Tämän tutkimuksen avulla syvennettiin samalle tutkimusryhmälle tehdyn kyselytutkimuksen tuloksia. Tutkimusaineistona käytettiin LOST-alueen kotihoidon yksiköiden hoitajille (n=150) farmaseutin lopputyönä tehtyä kyselyaineistoa sekä työntekijöille (n=6) ja esimiehille (n=6) tehtyjä erillisiä ryhmäkeskusteluja. Lisäksi näkökulman laajentamiseksi ja moniammatillisuuden korostamiseksi aineistona käytettiin kotihoidon asiakkaita hoitavien lääkärien (n=4) teemahaastatteluja. Kyselyaineistosta analysoitiin erikseen sairaanhoitajien, lähihoitajien ja kodinhoitajien koulutustarpeet. Samat asiat nousivat esille kunkin ammattiryhmän tuloksissa. Tärkeimpinä lääkehoito-osaamiseen liittyvinä teoreettisina koulutettavina asioina kyselystä nousivat esille iäkkäiden farmakokinetiikka ja lääkkeiden käyttöön liittyvät erityispiirteet, lääkkeiden vaikutukset, lääkkeiden haittavaikutukset sekä lääkkeiden yhteisvaikutukset ja yhteensopivuus. Lisäksi teoreettisista taidoista nousi hoitotyön etiikkaan liittyvät tarkkuus ja huolellisuus työssä. Käytännön taidoista tärkeimpinä koulutettavina aiheina kyselystä nousivat asiakkaiden lääkehoidon ja voinnin seuranta, lääkkeiden jakaminen sekä lääkkeiden annosteluun liittyen se, että annostellaan oikeaa lääkettä ja vahvuutta, oikea annos ja oikeaan aikaan sekä oikeat antotavat. Ryhmäkeskusteluista ja lääkärien teemahaastatteluista haettiin syvempää ymmärrystä kyselyn tuloksiin. Yksi tärkeimmistä tämän laadullisen tutkimuksen löydöksistä oli kotihoidon yhteistyöhön liittyvät epäkohdat. Lääkehoitojen toteuttamista ja seurantaa voitaisiin tulosten perusteella parantaa lääkärien ja kotihoidon hoitajien yhteisellä koulutuksella. Tärkeimpiä sairauksia tai oireita, joihin hoitajat toivoisivat yhteisiä toimintakäytäntöjä, ovat diabetes, sydän- ja verisuonisairaudet, kipu, muistisairaudet sekä psyykensairaudet. Lisäksi koulutusaiheiksi tutkimuksesta nousivat iäkkäiden lääkehoidon erityispiirteet, lääkkeiden antoreitit ja lääkemuodot. Kyselyn sekä ryhmäkeskustelujen ja lääkärien teemahaastattelujen tuloksista tehtiin lopuksi synteesi, jonka lopputuloksena LOST-alueen kotihoidon hoitohenkilöstölle sekä kotihoidon lääkäreille koottiin yhteinen tarvelähtöinen täydennyskoulutussuunnitelma. Suunnitelma tehtiin aineistosta nousseiden koulutusaiheiden pohjalta, eikä siihen lisätty aiheita tutkimuksen ulkopuolelta.

Monitoring Indigenous Tropical Montane Forests in the Taita Hills Using Airborne Digital Camera Imagery

The loss and degradation of forest cover is currently a globally recognised problem. The fragmentation of forests is further affecting the biodiversity and well-being of the ecosystems also in Kenya. This study focuses on two indigenous tropical montane forests in the Taita Hills in southeastern Kenya. The study is a part of the TAITA-project within the Department of Geography in the University of Helsinki. The study forests, Ngangao and Chawia, are studied by remote sensing and GIS methods. The main data includes black and white aerial photography from 1955 and true colour digital camera data from 2004. This data is used to produce aerial mosaics from the study areas. The land cover of these study areas is studied by visual interpretation, pixel-based supervised classification and object-oriented supervised classification. The change of the forest cover is studied with GIS methods using the visual interpretations from 1955 and 2004. Furthermore, the present state of the study forests is assessed with leaf area index and canopy closure parameters retrieved from hemispherical photographs as well as with additional, previously collected forest health monitoring data. The canopy parameters are also compared with textural parameters from digital aerial mosaics. This study concludes that the classification of forest areas by using true colour data is not an easy task although the digital aerial mosaics are proved to be very accurate. The best classifications are still achieved with visual interpretation methods as the accuracies of the pixel-based and object-oriented supervised classification methods are not satisfying. According to the change detection of the land cover in the study areas, the area of indigenous woodland in both forests has decreased in 1955 2004. However in Ngangao, the overall woodland area has grown mainly because of plantations of exotic species. In general, the land cover of both study areas is more fragmented in 2004 than in 1955. Although the forest area has decreased, forests seem to have a more optimistic future than before. This is due to the increasing appreciation of the forest areas.

Exact analysis of Burgers equation on semiline with flux condition at the origin

The initial boundary value problem for the Burgers equation in the domain x greater-or-equal, slanted 0, t > 0 with flux boundary condition at x = 0 has been solved exactly. The behaviour of the solution as t tends to infinity is studied and the “asymptotic profile at infinity” is obtained. In addition, the uniqueness of the solution of the initial boundary value problem is proved and its inviscid limit as var epsilon → 0 is obtained.