Flexible Multibody Simulation Approach in the Dynamic Analysis of Bone Strains Activity

The objective of this study is to show that bone strains due to dynamic mechanical loading during physical activity can be analysed using the flexible multibody simulation approach. Strains within the bone tissue play a major role in bone (re)modeling. Based on previous studies, it has been shown that dynamic loading seems to be more important for bone (re)modeling than static loading. The finite element method has been used previously to assess bone strains. However, the finite element method may be limited to static analysis of bone strains due to the expensive computation required for dynamic analysis, especially for a biomechanical system consisting of several bodies. Further, in vivo implementation of strain gauges on the surfaces of bone has been used previously in order to quantify the mechanical loading environment of the skeleton. However, in vivo strain measurement requires invasive methodology, which is challenging and limited to certain regions of superficial bones only, such as the anterior surface of the tibia. In this study, an alternative numerical approach to analyzing in vivo strains, based on the flexible multibody simulation approach, is proposed. In order to investigate the reliability of the proposed approach, three 3-dimensional musculoskeletal models where the right tibia is assumed to be flexible, are used as demonstration examples. The models are employed in a forward dynamics simulation in order to predict the tibial strains during walking on a level exercise. The flexible tibial model is developed using the actual geometry of the subject’s tibia, which is obtained from 3 dimensional reconstruction of Magnetic Resonance Images. Inverse dynamics simulation based on motion capture data obtained from walking at a constant velocity is used to calculate the desired contraction trajectory for each muscle. In the forward dynamics simulation, a proportional derivative servo controller is used to calculate each muscle force required to reproduce the motion, based on the desired muscle contraction trajectory obtained from the inverse dynamics simulation. Experimental measurements are used to verify the models and check the accuracy of the models in replicating the realistic mechanical loading environment measured from the walking test. The predicted strain results by the models show consistency with literature-based in vivo strain measurements. In conclusion, the non-invasive flexible multibody simulation approach may be used as a surrogate for experimental bone strain measurement, and thus be of use in detailed strain estimation of bones in different applications. Consequently, the information obtained from the present approach might be useful in clinical applications, including optimizing implant design and devising exercises to prevent bone fragility, accelerate fracture healing and reduce osteoporotic bone loss.

Haja-asutusalueen keskijänniteverkon kaapeloinnin ja automaation suunnittelumetodiikka

Tässä diplomityössä tutkitaan erilaisia keskijänniteverkon kehittämismenetelmiä sekä suunnittelua haja-asutusalueelle. Suunnittelumetodiikan perustana on vertailla sähköverkon käyttövarmuuden tunnuslukujen sekä kokonaiskustannusten kehittymistä erilaisilla investointiratkaisuilla. Lähemmässä tarkastelussa ovat erilaiset kaapelointimenetelmät sekä automaatiolaitteet kuten maastoon sijoitettavat katkaisijat sekä kauko-ohjattavat erottimet. Kehittämisratkaisujen vertailemiseksi sähköverkosta muodostetaan laskentaa varten malli, jonka avulla on mahdollista tarkastella mm. käyttövarmuuden tunnuslukujen sekä verkon kustannusten kehittymistä. Verkon kustannuksissa otetaan huomioon investointikustannukset, käyttö- ja kunnossapitokustannukset, viankorjauskustannukset sekä keskeytyskustannukset. Keskeytysten laskentaa varten toteutetaan erilliset laskentalohkot, jotta keskeytyskustannukset saadaan mallinnettua tarkasti. Kaapelointistrategia-analyysissä vertaillaan kaapeloinnin erilaisia toteuttamisperiaatteita. Erilaisia tutkittavia kaapelointimenetelmiä ovat vyörytysmenetelmä, vikaherkimpien kohteiden uusinta, vanhimpien kohteiden uusinta, täydellinen kaapelointi sekä optimiverkostoratkaisu, jossa on hyödynnetty keskijännitejohtojen kaapeloinnin lisäksi mm. automaatioratkaisuja ja 1000 V tekniikkaa. Kaapelointimenetelmiä vertailtaessa on havaittu, että vikaherkimmistä kohteista aloitettava saneeraus tuottaa parhaimman tuloksen, jos optimiratkaisua ei oteta huomioon.

Computing the persistent homology of range images with alpha shapes

Laser scanning is becoming an increasingly popular method for measuring 3D objects in industrial design. Laser scanners produce a cloud of 3D points. For CAD software to be able to use such data, however, this point cloud needs to be turned into a vector format. A popular way to do this is to triangulate the assumed surface of the point cloud using alpha shapes. Alpha shapes start from the convex hull of the point cloud and gradually refine it towards the true surface of the object. Often it is nontrivial to decide when to stop this refinement. One criterion for this is to do so when the homology of the object stops changing. This is known as the persistent homology of the object. The goal of this thesis is to develop a way to compute the homology of a given point cloud when processed with alpha shapes, and to infer from it when the persistent homology has been achieved. Practically, the computation of such a characteristic of the target might be applied to power line tower span analysis.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Statistical Analysis and Numerics of Heat Exchanger Models

The identifiability of the parameters of a heat exchanger model without phase change was studied in this Master’s thesis using synthetically made data. A fast, two-step Markov chain Monte Carlo method (MCMC) was tested with a couple of case studies and a heat exchanger model. The two-step MCMC-method worked well and decreased the computation time compared to the traditional MCMC-method. The effect of measurement accuracy of certain control variables to the identifiability of parameters was also studied. The accuracy used did not seem to have a remarkable effect to the identifiability of parameters. The use of the posterior distribution of parameters in different heat exchanger geometries was studied. It would be computationally most efficient to use the same posterior distribution among different geometries in the optimisation of heat exchanger networks. According to the results, this was possible in the case when the frontal surface areas were the same among different geometries. In the other cases the same posterior distribution can be used for optimisation too, but that will give a wider predictive distribution as a result. For condensing surface heat exchangers the numerical stability of the simulation model was studied. As a result, a stable algorithm was developed.

Formal Power Analysis of Systems-on-Chip

The design methods and languages targeted to modern System-on-Chip designs are facing tremendous pressure of the ever-increasing complexity, power, and speed requirements. To estimate any of these three metrics, there is a trade-off between accuracy and abstraction level of detail in which a system under design is analyzed. The more detailed the description, the more accurate the simulation will be, but, on the other hand, the more time consuming it will be. Moreover, a designer wants to make decisions as early as possible in the design flow to avoid costly design backtracking. To answer the challenges posed upon System-on-chip designs, this thesis introduces a formal, power aware framework, its development methods, and methods to constraint and analyze power consumption of the system under design. This thesis discusses on power analysis of synchronous and asynchronous systems not forgetting the communication aspects of these systems. The presented framework is built upon the Timed Action System formalism, which offer an environment to analyze and constraint the functional and temporal behavior of the system at high abstraction level. Furthermore, due to the complexity of System-on-Chip designs, the possibility to abstract unnecessary implementation details at higher abstraction levels is an essential part of the introduced design framework. With the encapsulation and abstraction techniques incorporated with the procedure based communication allows a designer to use the presented power aware framework in modeling these large scale systems. The introduced techniques also enable one to subdivide the development of communication and computation into own tasks. This property is taken into account in the power analysis part as well. Furthermore, the presented framework is developed in a way that it can be used throughout the design project. In other words, a designer is able to model and analyze systems from an abstract specification down to an implementable specification.

ContinuousMultimodal Global Optimization with Differential Evolution-Based Methods

Metaheuristic methods have become increasingly popular approaches in solving global optimization problems. From a practical viewpoint, it is often desirable to perform multimodal optimization which, enables the search of more than one optimal solution to the task at hand. Population-based metaheuristic methods offer a natural basis for multimodal optimization. The topic has received increasing interest especially in the evolutionary computation community. Several niching approaches have been suggested to allow multimodal optimization using evolutionary algorithms. Most global optimization approaches, including metaheuristics, contain global and local search phases. The requirement to locate several optima sets additional requirements for the design of algorithms to be effective in both respects in the context of multimodal optimization. In this thesis, several different multimodal optimization algorithms are studied in regard to how their implementation in the global and local search phases affect their performance in different problems. The study concentrates especially on variations of the Differential Evolution algorithm and their capabilities in multimodal optimization. To separate the global and local search search phases, three multimodal optimization algorithms are proposed, two of which hybridize the Differential Evolution with a local search method. As the theoretical background behind the operation of metaheuristics is not generally thoroughly understood, the research relies heavily on experimental studies in finding out the properties of different approaches. To achieve reliable experimental information, the experimental environment must be carefully chosen to contain appropriate and adequately varying problems. The available selection of multimodal test problems is, however, rather limited, and no general framework exists. As a part of this thesis, such a framework for generating tunable test functions for evaluating different methods of multimodal optimization experimentally is provided and used for testing the algorithms. The results demonstrate that an efficient local phase is essential for creating efficient multimodal optimization algorithms. Adding a suitable global phase has the potential to boost the performance significantly, but the weak local phase may invalidate the advantages gained from the global phase.

Demonstration Platform for Visual Quality Metrics

This thesis presents two graphical user interfaces for the project DigiQ - Fusion of Digital and Visual Print Quality, a project for computationally modeling the subjective human experience of print quality by measuring the image with certain metrics. After presenting the user interfaces, methods for reducing the computation time of several of the metrics and the image registration process required to compute the metrics, and details of their performance are given. The weighted sample method for the image registration process was able to signifigantly decrease the calculation times while resulting in some error. The random sampling method for the metrics greatly reduced calculation time while maintaining excellent accuracy, but worked with only two of the metrics.

Determining the location for a mobile device by utilization of local resources of the environment

The subject being analyzed of this Master’s Thesis is a development of a service that is used to define a current location of a mobile device. The service utilized data that is obtained from own GPS receiver in some possible cases and as well data from mobile devices which can be afforded for the current environment for acquisition of more precise position of the device. The computation environment is based on context of a mobile device. The service is implemented as an application for communicator series Nokia N8XX. The Master’s Thesis presents theoretical concept of the method and its practical implementation, architecture of the application, requirements and describes a process of its functionality. Also users’ work with application is presented and recommendations for possible future improvements are made.

Teknologiateollisuuden sopimusvalmistajayrityksen kustannuslaskennan kehittäminen

Työn päätavoitteena oli kohdeyrityksen kustannuslaskennan kehittäminen, jota varten selvitettiin toimintojen todelliset kustannukset sekä rakennettiin uusi taulukkolaskentaan perustuva hinnoittelumalli. Todellisten kustannukset selvitettiin toimintolaskennan avulla. Yrityksen aiempi kustannuslaskenta perustui perinteiseen lisäyslaskentaan. Työ jakaantui kahteen vaiheeseen: yrityksen kustannuslaskennan nykytilaselvitykseen ja toimintolaskennan toteuttamiseen. Ensimmäisen vaiheen teoriaosuudessa esiteltiin perinteisen kustannuslaskennan ja toimintolaskennan menetelmät sekä vertailtiin niitä keskenään. Empiriaosuudessa käsiteltiin yrityksen kustannusrakenne, tuotekustannuslaskenta, hinnoitteluprosessi ja eri hinnoittelukohteet. Nykytilaselvityksen perusteella laadittiin lista nykyisen kustannuslaskennan ja hinnoittelun kehitettävistä asioista. Kehittäminen päätettiin toteuttaa toimintolaskennan avulla. Toisessa vaiheessa esiteltiin toimintolaskennan toteuttamiseen ja käyttöönottoon liittyvä teoria. Tämän jälkeen suoritettiin toimintokustannusten laskeminen ja uuden hinnoittelumallin rakentaminen. Hinnoittelumallissa haettiin nopeutta uudella materiaalinlaskentatavalla. Työn tuloksina havaittiin, että toteutuneet kustannukset erosivat monen toiminnon kohdalla lisäyslaskennalla lasketuista kustannuksista ja tämä oli vääristänyt tuotteiden hinnoittelua. Toimintolaskennan käyttöönotolla yrityksen kustannuslaskenta ja tuotehinnoittelu saatettiin vastaamaan todellisia kustannuksia. Hinnoittelun nopeutumisella saavutettiin merkittäviä kustannussäästöjä.

On Undecidable Dynamical Properties of Reversible One-Dimensional Cellular Automata

Cellular automata are models for massively parallel computation. A cellular automaton consists of cells which are arranged in some kind of regular lattice and a local update rule which updates the state of each cell according to the states of the cell's neighbors on each step of the computation. This work focuses on reversible one-dimensional cellular automata in which the cells are arranged in a two-way in_nite line and the computation is reversible, that is, the previous states of the cells can be derived from the current ones. In this work it is shown that several properties of reversible one-dimensional cellular automata are algorithmically undecidable, that is, there exists no algorithm that would tell whether a given cellular automaton has the property or not. It is shown that the tiling problem of Wang tiles remains undecidable even in some very restricted special cases. It follows that it is undecidable whether some given states will always appear in computations by the given cellular automaton. It also follows that a weaker form of expansivity, which is a concept of dynamical systems, is an undecidable property for reversible one-dimensional cellular automata. It is shown that several properties of dynamical systems are undecidable for reversible one-dimensional cellular automata. It shown that sensitivity to initial conditions and topological mixing are undecidable properties. Furthermore, non-sensitive and mixing cellular automata are recursively inseparable. It follows that also chaotic behavior is an undecidable property for reversible one-dimensional cellular automata.

Automated, adaptive methods for forest inventory

Forest inventories are used to estimate forest characteristics and the condition of forest for many different applications: operational tree logging for forest industry, forest health state estimation, carbon balance estimation, land-cover and land use analysis in order to avoid forest degradation etc. Recent inventory methods are strongly based on remote sensing data combined with field sample measurements, which are used to define estimates covering the whole area of interest. Remote sensing data from satellites, aerial photographs or aerial laser scannings are used, depending on the scale of inventory. To be applicable in operational use, forest inventory methods need to be easily adjusted to local conditions of the study area at hand. All the data handling and parameter tuning should be objective and automated as much as possible. The methods also need to be robust when applied to different forest types. Since there generally are no extensive direct physical models connecting the remote sensing data from different sources to the forest parameters that are estimated, mathematical estimation models are of "black-box" type, connecting the independent auxiliary data to dependent response data with linear or nonlinear arbitrary models. To avoid redundant complexity and over-fitting of the model, which is based on up to hundreds of possibly collinear variables extracted from the auxiliary data, variable selection is needed. To connect the auxiliary data to the inventory parameters that are estimated, field work must be performed. In larger study areas with dense forests, field work is expensive, and should therefore be minimized. To get cost-efficient inventories, field work could partly be replaced with information from formerly measured sites, databases. The work in this thesis is devoted to the development of automated, adaptive computation methods for aerial forest inventory. The mathematical model parameter definition steps are automated, and the cost-efficiency is improved by setting up a procedure that utilizes databases in the estimation of new area characteristics.

Boundary identification in the domain of a parabolic partial differential equation

Bakgrunden och inspirationen till föreliggande studie är tidigare forskning i tillämpningar på randidentifiering i metallindustrin. Effektiv randidentifiering möjliggör mindre säkerhetsmarginaler och längre serviceintervall för apparaturen i industriella högtemperaturprocesser, utan ökad risk för materielhaverier. I idealfallet vore en metod för randidentifiering baserad på uppföljning av någon indirekt variabel som kan mätas rutinmässigt eller till en ringa kostnad. En dylik variabel för smältugnar är temperaturen i olika positioner i väggen. Denna kan utnyttjas som insignal till en randidentifieringsmetod för att övervaka ugnens väggtjocklek. Vi ger en bakgrund och motivering till valet av den geometriskt endimensionella dynamiska modellen för randidentifiering, som diskuteras i arbetets senare del, framom en flerdimensionell geometrisk beskrivning. I de aktuella industriella tillämpningarna är dynamiken samt fördelarna med en enkel modellstruktur viktigare än exakt geometrisk beskrivning. Lösningsmetoder för den s.k. sidledes värmeledningsekvationen har många saker gemensamt med randidentifiering. Därför studerar vi egenskaper hos lösningarna till denna ekvation, inverkan av mätfel och något som brukar kallas förorening av mätbrus, regularisering och allmännare följder av icke-välställdheten hos sidledes värmeledningsekvationen. Vi studerar en uppsättning av tre olika metoder för randidentifiering, av vilka de två första är utvecklade från en strikt matematisk och den tredje från en mera tillämpad utgångspunkt. Metoderna har olika egenskaper med specifika fördelar och nackdelar. De rent matematiskt baserade metoderna karakteriseras av god noggrannhet och låg numerisk kostnad, dock till priset av låg flexibilitet i formuleringen av den modellbeskrivande partiella differentialekvationen. Den tredje, mera tillämpade, metoden kännetecknas av en sämre noggrannhet förorsakad av en högre grad av icke-välställdhet hos den mera flexibla modellen. För denna gjordes även en ansats till feluppskattning, som senare kunde observeras överensstämma med praktiska beräkningar med metoden. Studien kan anses vara en god startpunkt och matematisk bas för utveckling av industriella tillämpningar av randidentifiering, speciellt mot hantering av olinjära och diskontinuerliga materialegenskaper och plötsliga förändringar orsakade av “nedfallande” väggmaterial. Med de behandlade metoderna förefaller det möjligt att uppnå en robust, snabb och tillräckligt noggrann metod av begränsad komplexitet för randidentifiering.

Finanssikriisin vaikutus yritysten investointitoimintaan – tapaustutkimus

Tutkimuksen tarkoituksena on perehtyä suomalaisten yritysten investointitoimintaan ja tutkia miten vuoden 2009 finanssikriisi on siihen vaikuttanut. Tutkimuksessa selvitetään myös yritysten investointiaktiivisuuteen vaikuttavia tekijöitä, investointiprosessia sekä yritysten käyttämiä investointien laskenta- ja riskimenetelmiä. Tutkimuksen teoreettinen viitekehys on rakennettu laskentatoimen investointikirjallisuuden pohjalta. Tutkimuksen empiirinen osuus koostuu sähkönsiirto- ja tilintarkastusyritysten johtohenkilöiden haastatteluista. Tutkimus osoitti, että suuria investointeja tekevät yritykset jatkavat investoimistaan aktiivisesti laman aikana, toisin kuin pieniä investointeja tekevät. Tutkimuksessa selvisi myös, että kohdeyritysten käytetyimmät investointien laskentamenetelmät ovat takaisinmaksuaika ja vaihtoehtolaskelmat. Tosin investointien riskin huomioiminen osoittautui alhaiseksi.

When to Utilize Software as a Service

Cloud computing enables on-demand network access to shared resources (e.g., computation, networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort. Cloud computing refers to both the applications delivered as services over the Internet and the hardware and system software in the data centers. Software as a service (SaaS) is part of cloud computing. It is one of the cloud service models. SaaS is software deployed as a hosted service and accessed over the Internet. In SaaS, the consumer uses the provider‘s applications running in the cloud. SaaS separates the possession and ownership of software from its use. The applications can be accessed from any device through a thin client interface. A typical SaaS application is used with a web browser based on monthly pricing. In this thesis, the characteristics of cloud computing and SaaS are presented. Also, a few implementation platforms for SaaS are discussed. Then, four different SaaS implementation cases and one transformation case are deliberated. The pros and cons of SaaS are studied. This is done based on literature references and analysis of the SaaS implementations and the transformation case. The analysis is done both from the customer‘s and service provider‘s point of view. In addition, the pros and cons of on-premises software are listed. The purpose of this thesis is to find when SaaS should be utilized and when it is better to choose a traditional on-premises software. The qualities of SaaS bring many benefits both for the customer as well as the provider. A customer should utilize SaaS when it provides cost savings, ease, and scalability over on-premises software. SaaS is reasonable when the customer does not need tailoring, but he only needs a simple, general-purpose service, and the application supports customer‘s core business. A provider should utilize SaaS when it offers cost savings, scalability, faster development, and wider customer base over on-premises software. It is wise to choose SaaS when the application is cheap, aimed at mass market, needs frequent updating, needs high performance computing, needs storing large amounts of data, or there is some other direct value from the cloud infrastructure.