Disc Filter External Models in an Integrated Simulation Environment

Työssä tutkittiin kiekkosuodattimeen liittyviä ulkoisia simulointimalleja integroidussa simulointiympäristössä. Työn tarkoituksena oli parantaa olemassa olevaa mekanistista kiekkosuodatinmallia. Malli laadittiin dynaamiseen paperiteollisuuden tarpeisiin tehtyyn simulaattoriin (APMS), jossa olevaan alkuperäiseen mekanistiseen malliin tehtiin ulkoinen lisämalli, joka käyttää hyväkseen kiekkosuodatinvalmistajan mittaustuloksia. Laitetiedon saatavuutta suodattimien käyttäjille parannettiin luomalla Internetissä sijaitsevalle palvelimelle kiekkosuodattimen laitetietomäärittelyt. Suodatinvalmistaja voi palvella asiakkaitaan viemällä laitetiedot palvelimelle ja yhdistämällä laitetiedon simulointimalliin. Tämä on mahdollista Internetin ylitse käytettävän integroidun simulointiympäristön avulla, jonka on tarkoitus kokonaisvaltaisesti yhdistää simulointi ja prosessisuunnittelu. Suunnittelijalle tarjotaan työkalut, joilla dynaaminen simulointi, tasesimulointi ja kaavioiden piirtäminen onnistuu prosessilaitetiedon ollessa saatavilla. Nämä työkalut on tarkoitus toteuttaa projektissa nimeltä Galleria, jossa luodaan prosessimalli- ja laitetietopalvelin Internetiin. Gallerian käyttöliittymän avulla prosessisuunnittelija voi käyttää erilaisia simulointiohjelmistoja ja niihin luotuja valmiita malleja, sekä saada käsiinsä ajan tasalla olevaa laitetietoa. Ulkoinen kiekkosuodatinmalli laskee suodosvirtaamat ja suodosten pitoisuudet likaiselle, kirkkaalle ja superkirkkaalle suodokselle. Mallin syöttöparametrit ovat kiekkojen pyörimisnopeus, sisään tulevan syötön pitoisuus, suotautuvuus (freeness) ja säätöparametri, jolla säädetään likaisen ja kirkkaan suodoksen keskinäinen suhde. Suotautuvuus kertoo mistä massasta on kyse. Mitä suurempi suotautuvuus on, sitä paremmin massa suodattuu ja sitä puhtaampia suodokset yleensä ovat. Mallin parametrit viritettiin regressioanalyysillä ja valmistajan palautetta apuna käyttäen. Käyttäjä voi valita haluaako hän käyttää ulkoista vai alkuperäistä mallia. Alkuperäinen malli täytyy ensin alustaa antamalla sille nominaaliset toimintapisteet virtaamille ja pitoisuuksille tietyllä pyörimisnopeudella. Ulkoisen mallin yhtälöitä voi käyttää alkuperäisen mallin alustamiseen, jos alkuperäinen malli toimii ulkoista paremmin. Ulkoista mallia voi käyttää myös ilman simulointiohjelmaa Galleria-palvelimelta käsin. Käyttäjälle avautuu näin mahdollisuus tarkastella kiekkosuodattimien parametreja ja nähdä suotautumistulokset oman työasemansa ääreltä mistä tahansa, kunhan Internetyhteys on olemassa. Työn tuloksena kiekkosuodattimien laitetiedon saatavuus käyttäjille parani ja alkuperäisen simulointimallin rajoituksia ja puutteita vähennettiin.

Privacy-friendly Business Models for Location-Based Mobile Services

This paper presents a theoretical model to analyze the privacy issues around location based mobile business models. We report the results of an exploratory field experiment in Switzerland that assessed the factors driving user payoff in mobile business. We found that (1) the personal data disclosed has a negative effect on user payoff; (2) the amount of personalization available has a direct and positive effect, as well as a moderating effect on user payoff; (3) the amount of control over user's personal data has a direct and positive effect, as well as a moderating effect on user payoff. The results suggest that privacy protection could be the main value proposition in the B2C mobile market. From our theoretical model we derive a set of guidelines to design a privacy-friendly business model pattern for third-party services. We discuss four examples to show the mobile platform can play a key role in the implementation of these new business models.

USER'S GUIDE FOR ADVANCED PROCESS SIMULATION SOFTWARE APROS 5

Tässä diplomityössä tehtiin käyttäjän opas kehittyneelle prosessisimulointiohjelmistolle APROS 5. Opas on osa VTT Energialle tehtävää APROS 5 käyttäjän koulutuspakettia, joka julkaistaan myöhemmin CD-ROM -muotoisena. Prosessisimulointiohjelmistoa AAPROS 5 voidaan käyttää termohydraulisten prosessien, automaatiopiirien ja sähköjärjestelmien mallinnuksessa. Ohjelma sisältää myös neutroniikkamallin ydinreaktorin käyttäytymisen mallintamiseksi. APROS:in aikaisemmilla UNIX-ympäristössä toimivilla versioilla on toteutettu useita ydinvoimalaitosten turvallisuustutkimukseen liittyviä analyysejä ja sekä ydinvoimalaitosten että konventionaalisten voimalaitosten koulutussimulaattoreita. APROS 5 toimii Windows NT -ympäristössä ja on oleellisesti erilainen käyttää kuin aikaisemmat versiot. Tämän myötä syntyi tarve uudelle käyttäjän oppaalle. Käyttäjän oppaassa esitetään APROS 5:n tärkeimmät toiminnot, mallinnuksen periaatteet ja termohydraulisten ja neutroniikan ratkaisumallit. Lisäksi oppaassa esitetään esimerkki, jossa mallinnetaan yksinkertaistettu VVER-440 -tyyppisen ydinvoimalaitoksen primääripiiri. Yksityiskohtaisempaa tietoa ohjelmistosta on saatavilla APROS 5 -dokumentaatiosta.

Adaptive MCMC methods with applications in environmental and geophysical models

This work presents new, efficient Markov chain Monte Carlo (MCMC) simulation methods for statistical analysis in various modelling applications. When using MCMC methods, the model is simulated repeatedly to explore the probability distribution describing the uncertainties in model parameters and predictions. In adaptive MCMC methods based on the Metropolis-Hastings algorithm, the proposal distribution needed by the algorithm learns from the target distribution as the simulation proceeds. Adaptive MCMC methods have been subject of intensive research lately, as they open a way for essentially easier use of the methodology. The lack of user-friendly computer programs has been a main obstacle for wider acceptance of the methods. This work provides two new adaptive MCMC methods: DRAM and AARJ. The DRAM method has been built especially to work in high dimensional and non-linear problems. The AARJ method is an extension to DRAM for model selection problems, where the mathematical formulation of the model is uncertain and we want simultaneously to fit several different models to the same observations. The methods were developed while keeping in mind the needs of modelling applications typical in environmental sciences. The development work has been pursued while working with several application projects. The applications presented in this work are: a winter time oxygen concentration model for Lake Tuusulanjärvi and adaptive control of the aerator; a nutrition model for Lake Pyhäjärvi and lake management planning; validation of the algorithms of the GOMOS ozone remote sensing instrument on board the Envisat satellite of European Space Agency and the study of the effects of aerosol model selection on the GOMOS algorithm.

Adjusting for the environment in DEA: a comparison of alternative models based on empirical data

Due to the existence of free software and pedagogical guides, the use of Data Envelopment Analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run their own efficiency analysis. Within DEA, several alternative models allow for an environmental adjustment. Four alternative models, each user-friendly and easily accessible to practitioners and decision makers, are performed using empirical data of 90 primary schools in the State of Geneva, Switzerland. Results show that the majority of alternative models deliver divergent results. From a political and a managerial standpoint, these diverging results could lead to potentially ineffective decisions. As no consensus emerges on the best model to use, practitioners and decision makers may be tempted to select the model that is right for them, in other words, the model that best reflects their own preferences. Further studies should investigate how an appropriate multi-criteria decision analysis method could help decision makers to select the right model.

Disconnect.Me. User Engagement and Facebook

In the beginning of its 10th year of existence Facebook has engaged and connected 1.2 billion monthly active users. This article-based dissertation Disconnect.Me – User Engagement and Facebook approaches this engagement from the opposite direction: disconnection. The research articles focus on social media specific phenomena including leaving Facebook, tactical media works such as Web 2.0 SuicideMachine, memorializing dead Facebook users and Facebook trolling. The media theoretical framework for this study is built around affect theory, software studies, biopolitics as well as different critical studies of new media. The argument is that disconnection is a necessary condition of social media connectivity and exploring social media through disconnection – as an empirical phenomenon, future potential and theoretical notion – helps us to understand how users are engaged with social media, its uses and subsequent business models. The results of the study indicate that engagement is a relation that precedes user participation, a notion often used to conceptualize social media. Furthermore, this engagement turns the focus from users’ actions towards the platform and how the platform actively controls users and their behavior. Facebook aims to engage new users and maintain the old ones by renewing its platform and user interface. User engagement with the platform is thus social but also technical and affective. When engaged, the user is positioned to algorithmic connectivity where machinc processes mine user data. This data is but sold also used to affect and engage other users. In the heart of this study is the notion that our networked engagements matter and disconnection can bring us to the current limits of network culture.

Comparison study of two competing models of an all mechanical power transmission system

A comparison between two competing models of an all mechanical power transmission system is studied by using Dymola –software as the simulation tool. This tool is compared with Matlab/ Simulink –software by using functionality, user-friendliness and price as comparison criteria. In this research we assume that the torque is balanceable and transmission ratios are calculated. Using kinematic connection sketches of the two transmission models, simulation models are built into the Dymola simulation environment. Models of transmission systems are modified according to simulation results to achieve a continuous variable transmission ratio. Simulation results are compared between the two transmission systems. The main features of Dymola and MATLAB/ Simulink are compared. Advantages and disadvantages of the two softwares are analyzed and compared.

Linguistic models for decision support

Linguistic modelling is a rather new branch of mathematics that is still undergoing rapid development. It is closely related to fuzzy set theory and fuzzy logic, but knowledge and experience from other fields of mathematics, as well as other fields of science including linguistics and behavioral sciences, is also necessary to build appropriate mathematical models. This topic has received considerable attention as it provides tools for mathematical representation of the most common means of human communication - natural language. Adding a natural language level to mathematical models can provide an interface between the mathematical representation of the modelled system and the user of the model - one that is sufficiently easy to use and understand, but yet conveys all the information necessary to avoid misinterpretations. It is, however, not a trivial task and the link between the linguistic and computational level of such models has to be established and maintained properly during the whole modelling process. In this thesis, we focus on the relationship between the linguistic and the mathematical level of decision support models. We discuss several important issues concerning the mathematical representation of meaning of linguistic expressions, their transformation into the language of mathematics and the retranslation of mathematical outputs back into natural language. In the first part of the thesis, our view of the linguistic modelling for decision support is presented and the main guidelines for building linguistic models for real-life decision support that are the basis of our modeling methodology are outlined. From the theoretical point of view, the issues of representation of meaning of linguistic terms, computations with these representations and the retranslation process back into the linguistic level (linguistic approximation) are studied in this part of the thesis. We focus on the reasonability of operations with the meanings of linguistic terms, the correspondence of the linguistic and mathematical level of the models and on proper presentation of appropriate outputs. We also discuss several issues concerning the ethical aspects of decision support - particularly the loss of meaning due to the transformation of mathematical outputs into natural language and the issue or responsibility for the final decisions. In the second part several case studies of real-life problems are presented. These provide background and necessary context and motivation for the mathematical results and models presented in this part. A linguistic decision support model for disaster management is presented here – formulated as a fuzzy linear programming problem and a heuristic solution to it is proposed. Uncertainty of outputs, expert knowledge concerning disaster response practice and the necessity of obtaining outputs that are easy to interpret (and available in very short time) are reflected in the design of the model. Saaty’s analytic hierarchy process (AHP) is considered in two case studies - first in the context of the evaluation of works of art, where a weak consistency condition is introduced and an adaptation of AHP for large matrices of preference intensities is presented. The second AHP case-study deals with the fuzzified version of AHP and its use for evaluation purposes – particularly the integration of peer-review into the evaluation of R&D outputs is considered. In the context of HR management, we present a fuzzy rule based evaluation model (academic faculty evaluation is considered) constructed to provide outputs that do not require linguistic approximation and are easily transformed into graphical information. This is achieved by designing a specific form of fuzzy inference. Finally the last case study is from the area of humanities - psychological diagnostics is considered and a linguistic fuzzy model for the interpretation of outputs of multidimensional questionnaires is suggested. The issue of the quality of data in mathematical classification models is also studied here. A modification of the receiver operating characteristics (ROC) method is presented to reflect variable quality of data instances in the validation set during classifier performance assessment. Twelve publications on which the author participated are appended as a third part of this thesis. These summarize the mathematical results and provide a closer insight into the issues of the practicalapplications that are considered in the second part of the thesis.

A System for Models of First Order Theories

If you want to know whether a property is true or not in a specific algebraic structure,you need to test that property on the given structure. This can be done by hand, which can be cumbersome and erroneous. In addition, the time consumed in testing depends on the size of the structure where the property is applied. We present an implementation of a system for finding counterexamples and testing properties of models of first-order theories. This system is supposed to provide a convenient and paperless environment for researchers and students investigating or studying such models and algebraic structures in particular. To implement a first-order theory in the system, a suitable first-order language.( and some axioms are required. The components of a language are given by a collection of variables, a set of predicate symbols, and a set of operation symbols. Variables and operation symbols are used to build terms. Terms, predicate symbols, and the usual logical connectives are used to build formulas. A first-order theory now consists of a language together with a set of closed formulas, i.e. formulas without free occurrences of variables. The set of formulas is also called the axioms of the theory. The system uses several different formats to allow the user to specify languages, to define axioms and theories and to create models. Besides the obvious operations and tests on these structures, we have introduced the notion of a functor between classes of models in order to generate more co~plex models from given ones automatically. As an example, we will use the system to create several lattices structures starting from a model of the theory of pre-orders.

The Human in the Loop: User Participation in Self-Adaptive Software

Self-adaptive software provides a profound solution for adapting applications to changing contexts in dynamic and heterogeneous environments. Having emerged from Autonomic Computing, it incorporates fully autonomous decision making based on predefined structural and behavioural models. The most common approach for architectural runtime adaptation is the MAPE-K adaptation loop implementing an external adaptation manager without manual user control. However, it has turned out that adaptation behaviour lacks acceptance if it does not correspond to a user’s expectations – particularly for Ubiquitous Computing scenarios with user interaction. Adaptations can be irritating and distracting if they are not appropriate for a certain situation. In general, uncertainty during development and at run-time causes problems with users being outside the adaptation loop. In a literature study, we analyse publications about self-adaptive software research. The results show a discrepancy between the motivated application domains, the maturity of examples, and the quality of evaluations on the one hand and the provided solutions on the other hand. Only few publications analysed the impact of their work on the user, but many employ user-oriented examples for motivation and demonstration. To incorporate the user within the adaptation loop and to deal with uncertainty, our proposed solutions enable user participation for interactive selfadaptive software while at the same time maintaining the benefits of intelligent autonomous behaviour. We define three dimensions of user participation, namely temporal, behavioural, and structural user participation. This dissertation contributes solutions for user participation in the temporal and behavioural dimension. The temporal dimension addresses the moment of adaptation which is classically determined by the self-adaptive system. We provide mechanisms allowing users to influence or to define the moment of adaptation. With our solution, users can have full control over the moment of adaptation or the self-adaptive software considers the user’s situation more appropriately. The behavioural dimension addresses the actual adaptation logic and the resulting run-time behaviour. Application behaviour is established during development and does not necessarily match the run-time expectations. Our contributions are three distinct solutions which allow users to make changes to the application’s runtime behaviour: dynamic utility functions, fuzzy-based reasoning, and learning-based reasoning. The foundation of our work is a notification and feedback solution that improves intelligibility and controllability of self-adaptive applications by implementing a bi-directional communication between self-adaptive software and the user. The different mechanisms from the temporal and behavioural participation dimension require the notification and feedback solution to inform users on adaptation actions and to provide a mechanism to influence adaptations. Case studies show the feasibility of the developed solutions. Moreover, an extensive user study with 62 participants was conducted to evaluate the impact of notifications before and after adaptations. Although the study revealed that there is no preference for a particular notification design, participants clearly appreciated intelligibility and controllability over autonomous adaptations.

Jmodels: Java models of earth system regulation

The JModel suite consists of a number of models of aspects of the Earth System. They can all be run from the JModels website. They are written in the Java language for maximum portability, and are capable of running on most computing platforms including Windows, MacOS and Unix/Linux. The models are controlled via graphical user interfaces (GUI), so no knowledge of computer programming is required to run them. The models currently available from the JModels website are: Ocean phosphorus cycle Ocean nitrogen and phosphorus cycles Ocean silicon and phosphorus cycles Ocean and atmosphere carbon cycle Energy radiation balance model (under development) The main purpose of the models is to investigate how material and energy cycles of the Earth system are regulated and controlled by different feedbacks. While the central focus is on these feedbacks and Earth System stabilisation, the models can also be used in other ways. These resources have been developed by: National Oceanography Centre, Southampton project led by Toby Tyrrell and Andrew Yool, focus on how the Earth system works.

Running climate models on grids using G-Rex

Compute grids are used widely in many areas of environmental science, but there has been limited uptake of grid computing by the climate modelling community, partly because the characteristics of many climate models make them difficult to use with popular grid middleware systems. In particular, climate models usually produce large volumes of output data, and running them also involves complicated workflows implemented as shell scripts. A new grid middleware system that is well suited to climate modelling applications is presented in this paper. Grid Remote Execution (G-Rex) allows climate models to be deployed as Web services on remote computer systems and then launched and controlled as if they were running on the user's own computer. Output from the model is transferred back to the user while the run is in progress to prevent it from accumulating on the remote system and to allow the user to monitor the model. G-Rex has a REST architectural style, featuring a Java client program that can easily be incorporated into existing scientific workflow scripts. Some technical details of G-Rex are presented, with examples of its use by climate modellers.

Grid Remote Execution (G-Rex) of Climate Models

G-Rex is light-weight Java middleware that allows scientific applications deployed on remote computer systems to be launched and controlled as if they are running on the user's own computer. G-Rex is particularly suited to ocean and climate modelling applications because output from the model is transferred back to the user while the run is in progress, which prevents the accumulation of large amounts of data on the remote cluster. The G-Rex server is a RESTful Web application that runs inside a servlet container on the remote system, and the client component is a Java command line program that can easily be incorporated into existing scientific work-flow scripts. The NEMO and POLCOMS ocean models have been deployed as G-Rex services in the NERC Cluster Grid, and G-Rex is the core grid middleware in the GCEP and GCOMS e-science projects.

Running Climate Models On The NERC Cluster Grid Using G-Rex

Compute grids are used widely in many areas of environmental science, but there has been limited uptake of grid computing by the climate modelling community, partly because the characteristics of many climate models make them difficult to use with popular grid middleware systems. In particular, climate models usually produce large volumes of output data, and running them usually involves complicated workflows implemented as shell scripts. For example, NEMO (Smith et al. 2008) is a state-of-the-art ocean model that is used currently for operational ocean forecasting in France, and will soon be used in the UK for both ocean forecasting and climate modelling. On a typical modern cluster, a particular one year global ocean simulation at 1-degree resolution takes about three hours when running on 40 processors, and produces roughly 20 GB of output as 50000 separate files. 50-year simulations are common, during which the model is resubmitted as a new job after each year. Running NEMO relies on a set of complicated shell scripts and command utilities for data pre-processing and post-processing prior to job resubmission. Grid Remote Execution (G-Rex) is a pure Java grid middleware system that allows scientific applications to be deployed as Web services on remote computer systems, and then launched and controlled as if they are running on the user's own computer. Although G-Rex is general purpose middleware it has two key features that make it particularly suitable for remote execution of climate models: (1) Output from the model is transferred back to the user while the run is in progress to prevent it from accumulating on the remote system and to allow the user to monitor the model; (2) The client component is a command-line program that can easily be incorporated into existing model work-flow scripts. G-Rex has a REST (Fielding, 2000) architectural style, which allows client programs to be very simple and lightweight and allows users to interact with model runs using only a basic HTTP client (such as a Web browser or the curl utility) if they wish. This design also allows for new client interfaces to be developed in other programming languages with relatively little effort. The G-Rex server is a standard Web application that runs inside a servlet container such as Apache Tomcat and is therefore easy to install and maintain by system administrators. G-Rex is employed as the middleware for the NERC1 Cluster Grid, a small grid of HPC2 clusters belonging to collaborating NERC research institutes. Currently the NEMO (Smith et al. 2008) and POLCOMS (Holt et al, 2008) ocean models are installed, and there are plans to install the Hadley Centre’s HadCM3 model for use in the decadal climate prediction project GCEP (Haines et al., 2008). The science projects involving NEMO on the Grid have a particular focus on data assimilation (Smith et al. 2008), a technique that involves constraining model simulations with observations. The POLCOMS model will play an important part in the GCOMS project (Holt et al, 2008), which aims to simulate the world’s coastal oceans. A typical use of G-Rex by a scientist to run a climate model on the NERC Cluster Grid proceeds as follows :(1) The scientist prepares input files on his or her local machine. (2) Using information provided by the Grid’s Ganglia3 monitoring system, the scientist selects an appropriate compute resource. (3) The scientist runs the relevant workflow script on his or her local machine. This is unmodified except that calls to run the model (e.g. with “mpirun”) are simply replaced with calls to "GRexRun" (4) The G-Rex middleware automatically handles the uploading of input files to the remote resource, and the downloading of output files back to the user, including their deletion from the remote system, during the run. (5) The scientist monitors the output files, using familiar analysis and visualization tools on his or her own local machine. G-Rex is well suited to climate modelling because it addresses many of the middleware usability issues that have led to limited uptake of grid computing by climate scientists. It is a lightweight, low-impact and easy-to-install solution that is currently designed for use in relatively small grids such as the NERC Cluster Grid. A current topic of research is the use of G-Rex as an easy-to-use front-end to larger-scale Grid resources such as the UK National Grid service.

Identification of nonlinear systems using generalized kernel models

Nonlinear system identification is considered using a generalized kernel regression model. Unlike the standard kernel model, which employs a fixed common variance for all the kernel regressors, each kernel regressor in the generalized kernel model has an individually tuned diagonal covariance matrix that is determined by maximizing the correlation between the training data and the regressor using a repeated guided random search based on boosting optimization. An efficient construction algorithm based on orthogonal forward regression with leave-one-out (LOO) test statistic and local regularization (LR) is then used to select a parsimonious generalized kernel regression model from the resulting full regression matrix. The proposed modeling algorithm is fully automatic and the user is not required to specify any criterion to terminate the construction procedure. Experimental results involving two real data sets demonstrate the effectiveness of the proposed nonlinear system identification approach.