Object-oriented development of client / server application: case study of service control software

Tässä työssä on esitetty sen ohjelmiston kehittämisen prosessi, joka on tarkoitettu annettavien palveluiden valvottavaksi käyttäen prototyyppimallia. Raportti sisältää vaatimusten, kohteisiin suunnatun analyysin ja suunnittelun, realisointiprosessien kuvauksen ja prototyypin testauksen. Ohjelmiston käyttöala – antavien palveluiden valvonta. Vaatimukset sovellukselle analysoitiin ohjelmistomarkkinoiden perusteella sekä ohjelmiston engineeringin periaatteiden mukaisesti. Ohjelmiston prototyyppi on realisoitu käyttäen asiakas-/palvelinhybridimallia sekä ralaatiokantaa. Kehitetty ohjelmisto on tarkoitettu venäläisille tietokonekerhoille, jotka erikoistuvat pelipalvelinten antamiseen.

Mobile E-commerce business model – A value web based approach to business models in mobile gaming industry

Tämän tutkimuksen tavoitteena oli tutkia langattomien internet palveluiden arvoverkkoa ja liiketoimintamalleja. Tutkimus oli luonteeltaan kvalitatiivinen ja siinä käytettiin strategiana konstruktiivista case-tutkimusta. Esimerkkipalveluna oli Treasure Hunters matkapuhelinpeli. Tutkimus muodostui teoreettisesta ja empiirisestä osasta. Teoriaosassa liitettiin innovaatio, liiketoimintamallit ja arvoverkko käsitteellisesti toisiinsa, sekä luotiin perusta liiketoimintamallien kehittämiselle. Empiirisessä osassa keskityttiin ensin liiketoimintamallien luomiseen kehitettyjen innovaatioiden pohjalta. Lopuksi pyrittiin määrittämään arvoverkko palvelun toteuttamiseksi. Tutkimusmenetelminä käytettiin innovaatiosessiota, haastatteluja ja lomakekyselyä. Tulosten pohjalta muodostettiin useita liiketoimintakonsepteja sekä kuvaus arvoverkon perusmallista langattomille peleille. Loppupäätelmänä todettiin että langattomat palvelut vaativat toteutuakseen useista toimijoista koostuvan arvoverkon.

Minimal requirements for parameters to be used for the development of predictive models for microbial source tracking. The example of the pair somatic coliphages and phages infecting Bacteroides

Several methods and approaches for measuring parameters to determine fecal sources of pollution in water have been developed in recent years. No single microbial or chemical parameter has proved sufficient to determine the source of fecal pollution. Combinations of parameters involving at least one discriminating indicator and one universal fecal indicator offer the most promising solutions for qualitative and quantitative analyses. The universal (nondiscriminating) fecal indicator provides quantitative information regarding the fecal load. The discriminating indicator contributes to the identification of a specific source. The relative values of the parameters derived from both kinds of indicators could provide information regarding the contribution to the total fecal load from each origin. It is also essential that both parameters characteristically persist in the environment for similar periods. Numerical analysis, such as inductive learning methods, could be used to select the most suitable and the lowest number of parameters to develop predictive models. These combinations of parameters provide information on factors affecting the models, such as dilution, specific types of animal source, persistence of microbial tracers, and complex mixtures from different sources. The combined use of the enumeration of somatic coliphages and the enumeration of Bacteroides-phages using different host specific strains (one from humans and another from pigs), both selected using the suggested approach, provides a feasible model for quantitative and qualitative analyses of fecal source identification.

Novel micropatterns mechanically control fibrotic reactions at the surface of silicone implants.

Over the past decade, various implantable devices have been developed to treat diseases that were previously difficult to manage such diabetes, chronic pain, and neurodegenerative disorders. However, translation of these novel technologies into clinical practice is often difficult because fibrotic encapsulation and/or rejection impairs device function after body implantation. Ideally, cells of the host tissue should perceive the surface of the implant being similar to the normal extracellular matrix. Here, we developed an innovative approach to provide implant surfaces with adhesive protein micropatterns. The patterns were designed to promote adhesion of fibroblasts and macrophages by simultaneously suppressing fibrogenic activation of both cell types. In a rat model, subcutaneously implanted silicone pads provided with the novel micropatterns caused 6-fold lower formation of inflammatory giant cells compared with clinical grade, uncoated, or collagen-coated silicone implants. We further show that micropatterning of implants resulted in 2-3-fold reduced numbers of pro-fibrotic myofibroblast by inhibiting their mechanical activation. Our novel approach allows controlled cell attachment to implant surfaces, representing a critical advance for enhanced biointegration of implantable medical devices.

Microscopic-macroscopic approach for binding energies with the Wigner-Kirkwood method. II. Deformed nuclei

The binding energies of deformed even-even nuclei have been analyzed within the framework of a recently proposed microscopic-macroscopic model. We have used the semiclassical Wigner-Kirkwood ̄h expansion up to fourth order, instead of the usual Strutinsky averaging scheme, to compute the shell corrections in a deformed Woods-Saxon potential including the spin-orbit contribution. For a large set of 561 even-even nuclei with Z 8 and N 8, we find an rms deviation from the experiment of 610 keV in binding energies, comparable to the one found for the same set of nuclei using the finite range droplet model of Moller and Nix (656 keV). As applications of our model, we explore its predictive power near the proton and neutron drip lines as well as in the superheavy mass region. Next, we systematically explore the fourth-order Wigner-Kirkwood corrections to the smooth part of the energy. It is found that the ratio of the fourth-order to the second-order corrections behaves in a very regular manner as a function of the asymmetry parameter I=(N−Z)/A. This allows us to absorb the fourth-order corrections into the second-order contributions to the binding energy, which enables us us to simplify and speed up the calculation of deformed nuclei.

Impact of model complexity on cross-temporal transferability in Maxent species distribution models: An assessment using paleobotanical data

Maximum entropy modeling (Maxent) is a widely used algorithm for predicting species distributions across space and time. Properly assessing the uncertainty in such predictions is non-trivial and requires validation with independent datasets. Notably, model complexity (number of model parameters) remains a major concern in relation to overfitting and, hence, transferability of Maxent models. An emerging approach is to validate the cross-temporal transferability of model predictions using paleoecological data. In this study, we assess the effect of model complexity on the performance of Maxent projections across time using two European plant species (Alnus giutinosa (L.) Gaertn. and Corylus avellana L) with an extensive late Quaternary fossil record in Spain as a study case. We fit 110 models with different levels of complexity under present time and tested model performance using AUC (area under the receiver operating characteristic curve) and AlCc (corrected Akaike Information Criterion) through the standard procedure of randomly partitioning current occurrence data. We then compared these results to an independent validation by projecting the models to mid-Holocene (6000 years before present) climatic conditions in Spain to assess their ability to predict fossil pollen presence-absence and abundance. We find that calibrating Maxent models with default settings result in the generation of overly complex models. While model performance increased with model complexity when predicting current distributions, it was higher with intermediate complexity when predicting mid-Holocene distributions. Hence, models of intermediate complexity resulted in the best trade-off to predict species distributions across time. Reliable temporal model transferability is especially relevant for forecasting species distributions under future climate change. Consequently, species-specific model tuning should be used to find the best modeling settings to control for complexity, notably with paleoecological data to independently validate model projections. For cross-temporal projections of species distributions for which paleoecological data is not available, models of intermediate complexity should be selected.

Financial Modeling to Support Organizational Control

Tutkimus tarkastelee taloudellisia mallintamismahdollisuuksia metsäteollisuuden liiketoimintayksikössä. Tavoitteena on suunnitella ja luoda taloudellinen malli liiketoimintayksikölle, jonka avulla sen tuloksen analysoiminen ja ennustaminen on mahdollista. Tutkimusta tarkastellaan konstruktiivisen tutkimusmenetelmän avulla. Teoreettinen viitekehys tarkastelee olemassa olevan informaation muotoilemista keskittyen tiedon jalostamisen tarpeisiin, päätöksenteon asettamiin vaatimuksiin sekä mallintamiseen. Toiseksi, teoria esittää informaatiolle asetettavia vaatimuksia organisatorisen ohjauksen näkökulmasta.Empiirinen tieto kerätään osallistuvan havainnoinnin avulla hyödyntäen epävirallisia keskusteluja, tietojärjestelmiä ja laskentatoimen dokumentteja. Tulokset osoittavat, että liikevoiton ennustaminen mallin avulla on vaikeaa, koska taustalla vaikuttavien muuttujien määrä on suuri. Tästä johtuen malli täytyykin rakentaa niin, että se tarkastelee liikevoittoa niin yksityiskohtaisella tasolla kuin mahdollista. Testauksessa mallin tarkkuus osoittautui sitä paremmaksi, mitä tarkemmalla tasolla ennustaminen tapahtui. Lisäksi testaus osoitti, että malli on käyttökelpoinen liiketoiminnan ohjauksessa lyhyellä aikavälillä. Näin se luo myös pohjan pitkän aikavälin ennustamiselle.

On the Analysis and Control of a Linear Synchronous Servomotor with a Flexible Load

Industry's growing need for higher productivity is placing new demands on mechanisms connected with electrical motors, because these can easily lead to vibration problems due to fast dynamics. Furthermore, the nonlinear effects caused by a motor frequently reduce servo stability, which diminishes the controller's ability to predict and maintain speed. Hence, the flexibility of a mechanism and its control has become an important area of research. The basic approach in control system engineering is to assume that the mechanism connected to a motor is rigid, so that vibrations in the tool mechanism, reel, gripper or any apparatus connected to the motor are not taken into account. This might reduce the ability of the machine system to carry out its assignment and shorten the lifetime of the equipment. Nonetheless, it is usually more important to know how the mechanism, or in other words the load on the motor, behaves. A nonlinear load control method for a permanent magnet linear synchronous motor is developed and implemented in the thesis. The purpose of the controller is to track a flexible load to the desired velocity reference as fast as possible and without awkward oscillations. The control method is based on an adaptive backstepping algorithm with its stability ensured by the Lyapunov stability theorem. As a reference controller for the backstepping method, a hybrid neural controller is introduced in which the linear motor itself is controlled by a conventional PI velocity controller and the vibration of the associated flexible mechanism is suppressed from an outer control loop using a compensation signal from a multilayer perceptron network. To avoid the local minimum problem entailed in neural networks, the initial weights are searched for offline by means of a differential evolution algorithm. The states of a mechanical system for controllers are estimated using the Kalman filter. The theoretical results obtained from the control design are validated with the lumped mass model for a mechanism. Generalization of the mechanism allows the methods derived here to be widely implemented in machine automation. The control algorithms are first designed in a specially introduced nonlinear simulation model and then implemented in the physical linear motor using a DSP (Digital Signal Processor) application. The measurements prove that both controllers are capable of suppressing vibration, but that the backstepping method is superior to others due to its accuracy of response and stability properties.

Physician behavioral adaptability: A model to outstrip a "one size fits all" approach

Objective: Based on a literature review, we propose a model of physician behavioral adaptability (PBA) with the goal of inspiring new research. PBA means that the physician adapts his or her behavior according to patients' different preferences. The PBA model shows how physicians infer patients' preferences and adapt their interaction behavior from one patient to the other. We claim that patients will benefit from better outcomes if their physicians show behavioral adaptability rather than a "one size fits all" approach. Method: This literature review is based on a literature search of the PsycINFO1 and MEDLINE1 databases. Results: The literature review and first results stemming from the authors' research support the validity and viability of parts of the PBA model. There is evidence suggesting that physicians are able to show behavioral flexibility when interacting with their different patients, that a match between patients' preferences and physician behavior is related to better consultation outcomes, and that physician behavioral adaptability is related to better consultation outcomes. Practice implications: Training of physicians' behavioral flexibility and their ability to infer patients' preferences can facilitate physician behavioral adaptability and positive patient outcomes.

Validation of and comparison between a semidistributed rainfall-runoff hydrological model (PREVAH) and a spatially distributed snow-evolution model (SnowModel) for snow cover prediction in mountain ecosystems

Snow cover is an important control in mountain environments and a shift of the snow-free period triggered by climate warming can strongly impact ecosystem dynamics. Changing snow patterns can have severe effects on alpine plant distribution and diversity. It thus becomes urgent to provide spatially explicit assessments of snow cover changes that can be incorporated into correlative or empirical species distribution models (SDMs). Here, we provide for the first time a with a lower overestimation comparison of two physically based snow distribution models (PREVAH and SnowModel) to produce snow cover maps (SCMs) at a fine spatial resolution in a mountain landscape in Austria. SCMs have been evaluated with SPOT-HRVIR images and predictions of snow water equivalent from the two models with ground measurements. Finally, SCMs of the two models have been compared under a climate warming scenario for the end of the century. The predictive performances of PREVAH and SnowModel were similar when validated with the SPOT images. However, the tendency to overestimate snow cover was slightly lower with SnowModel during the accumulation period, whereas it was lower with PREVAH during the melting period. The rate of true positives during the melting period was two times higher on average with SnowModel with a lower overestimation of snow water equivalent. Our results allow for recommending the use of SnowModel in SDMs because it better captures persisting snow patches at the end of the snow season, which is important when modelling the response of species to long-lasting snow cover and evaluating whether they might survive under climate change.

Moths behaving like butterflies. Evolutionary loss of long range attractant pheromones in Castniid Moths: A Paysandisia archon model

Background: In the course of evolution butterflies and moths developed two different reproductive behaviors. Whereas butterflies rely on visual stimuli for mate location, moths use the"female calling plus male seduction" system, in which females release long-range sex pheromones to attract conspecific males. There are few exceptions from this pattern but in all cases known female moths possess sex pheromone glands which apparently have been lost in female butterflies. In the day-flying moth family Castniidae ("butterfly-moths"), which includes some important crop pests, no pheromones have been found so far. Methodology/Principal Findings: Using a multidisciplinary approach we described the steps involved in the courtship of P. archon, showing that visual cues are the only ones used for mate location; showed that the morphology and fine structure of the antennae of this moth are strikingly similar to those of butterflies, with male sensilla apparently not suited to detect female-released long range pheromones; showed that its females lack pheromone-producing glands, and identified three compounds as putative male sex pheromone (MSP) components of P. archon, released from the proximal halves of male forewings and hindwings. Conclusions/Significance: This study provides evidence for the first time in Lepidoptera that females of a moth do not produce any pheromone to attract males, and that mate location is achieved only visually by patrolling males, which may release a pheromone at short distance, putatively a mixture of Z,E-farnesal, E,E-farnesal, and (E,Z)-2,13-octadecadienol. The outlined behavior, long thought to be unique to butterflies, is likely to be widespread in Castniidae implying a novel, unparalleled butterfly-like reproductive behavior in moths. This will also have practical implications in applied entomology since it signifies that the monitoring/control of castniid pests should not be based on the use of female-produced pheromones, as it is usually done in many moths.

Analysis of Earnings, Stock Prices and Bond Yields: The Fed Model Approach

Prediction of the stock market valuation is a common interest to all market participants. Theoretically sound market valuation can be achieved by discounting future earnings of equities to present. Competing valuation models seek to find variables that affect the equity market valuation in a way that the market valuation can be explained and also variables that could be used to predict market valuation. In this paper we test the contemporaneous relationship between stock prices, forward looking earnings and long-term government bond yields. We test this so-called Fed model in a long- and short-term time series analysis. In order to test the dynamics of the relationship, we use the cointegration framework. The data used in this study spans over four decades of various market conditions between 1964-2007, using data from United States. The empirical results of our analysis do not give support for the Fed model. We are able to show that the long-term government bonds do not play statistically significant role in this relationship. The effect of forward earnings yield on the stock market prices is significant and thus we suggest the use of standard valuation ratios when trying to predict the future paths of equity prices. Also, changes in the long-term government bond yields do not have significant short-term impact on stock prices.

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Predicting overall service quality: a structural equation modelling approach

In this article, the results of a modified SERVQUAL questionnaire (Parasuraman et al., 1991) are reported. The modifications consisted in substituting questionnaire items particularly suited to a specific service (banking) and context (county of Girona, Spain) for the original rather general and abstract items. These modifications led to more interpretable factors which accounted for a higher percentage of item variance. The data were submitted to various structural equation models which made it possible to conclude that the questionnaire contains items with a high measurement quality with respect to five identified dimensions of service quality which differ from those specified by Parasuraman et al. And are specific to the banking service. The two dimensions relating to the behaviour of employees have the greatest predictive power on overall quality and satisfaction ratings, which enables managers to use a low-cost reduced version of the questionnaire to monitor quality on a regular basis. It was also found that satisfaction and overall quality were perfectly correlated thus showing that customers do not perceive these concepts as being distinct