Cross-layer Assisted TCP Algorithms for Vertical Handoff

The ever expanding growth of the wireless access to the Internet in recent years has led to the proliferation of wireless and mobile devices to connect to the Internet. This has created the possibility of mobile devices equipped with multiple radio interfaces to connect to the Internet using any of several wireless access network technologies such as GPRS, WLAN and WiMAX in order to get the connectivity best suited for the application. These access networks are highly heterogeneous and they vary widely in their characteristics such as bandwidth, propagation delay and geographical coverage. The mechanism by which a mobile device switches between these access networks during an ongoing connection is referred to as vertical handoff and it often results in an abrupt and significant change in the access link characteristics. The most common Internet applications such as Web browsing and e-mail make use of the Transmission Control Protocol (TCP) as their transport protocol and the behaviour of TCP depends on the end-to-end path characteristics such as bandwidth and round-trip time (RTT). As the wireless access link is most likely the bottleneck of a TCP end-to-end path, the abrupt changes in the link characteristics due to a vertical handoff may affect TCP behaviour adversely degrading the performance of the application. The focus of this thesis is to study the effect of a vertical handoff on TCP behaviour and to propose algorithms that improve the handoff behaviour of TCP using cross-layer information about the changes in the access link characteristics. We begin this study by identifying the various problems of TCP due to a vertical handoff based on extensive simulation experiments. We use this study as a basis to develop cross-layer assisted TCP algorithms in handoff scenarios involving GPRS and WLAN access networks. We then extend the scope of the study by developing cross-layer assisted TCP algorithms in a broader context applicable to a wide range of bandwidth and delay changes during a handoff. And finally, the algorithms developed here are shown to be easily extendable to the multiple-TCP flow scenario. We evaluate the proposed algorithms by comparison with standard TCP (TCP SACK) and show that the proposed algorithms are effective in improving TCP behavior in vertical handoff involving a wide range of bandwidth and delay of the access networks. Our algorithms are easy to implement in real systems and they involve modifications to the TCP sender algorithm only. The proposed algorithms are conservative in nature and they do not adversely affect the performance of TCP in the absence of cross-layer information.

Algorithms for 13C metabolic flux analysis

The metabolism of an organism consists of a network of biochemical reactions that transform small molecules, or metabolites, into others in order to produce energy and building blocks for essential macromolecules. The goal of metabolic flux analysis is to uncover the rates, or the fluxes, of those biochemical reactions. In a steady state, the sum of the fluxes that produce an internal metabolite is equal to the sum of the fluxes that consume the same molecule. Thus the steady state imposes linear balance constraints to the fluxes. In general, the balance constraints imposed by the steady state are not sufficient to uncover all the fluxes of a metabolic network. The fluxes through cycles and alternative pathways between the same source and target metabolites remain unknown. More information about the fluxes can be obtained from isotopic labelling experiments, where a cell population is fed with labelled nutrients, such as glucose that contains 13C atoms. Labels are then transferred by biochemical reactions to other metabolites. The relative abundances of different labelling patterns in internal metabolites depend on the fluxes of pathways producing them. Thus, the relative abundances of different labelling patterns contain information about the fluxes that cannot be uncovered from the balance constraints derived from the steady state. The field of research that estimates the fluxes utilizing the measured constraints to the relative abundances of different labelling patterns induced by 13C labelled nutrients is called 13C metabolic flux analysis. There exist two approaches of 13C metabolic flux analysis. In the optimization approach, a non-linear optimization task, where candidate fluxes are iteratively generated until they fit to the measured abundances of different labelling patterns, is constructed. In the direct approach, linear balance constraints given by the steady state are augmented with linear constraints derived from the abundances of different labelling patterns of metabolites. Thus, mathematically involved non-linear optimization methods that can get stuck to the local optima can be avoided. On the other hand, the direct approach may require more measurement data than the optimization approach to obtain the same flux information. Furthermore, the optimization framework can easily be applied regardless of the labelling measurement technology and with all network topologies. In this thesis we present a formal computational framework for direct 13C metabolic flux analysis. The aim of our study is to construct as many linear constraints to the fluxes from the 13C labelling measurements using only computational methods that avoid non-linear techniques and are independent from the type of measurement data, the labelling of external nutrients and the topology of the metabolic network. The presented framework is the first representative of the direct approach for 13C metabolic flux analysis that is free from restricting assumptions made about these parameters.In our framework, measurement data is first propagated from the measured metabolites to other metabolites. The propagation is facilitated by the flow analysis of metabolite fragments in the network. Then new linear constraints to the fluxes are derived from the propagated data by applying the techniques of linear algebra.Based on the results of the fragment flow analysis, we also present an experiment planning method that selects sets of metabolites whose relative abundances of different labelling patterns are most useful for 13C metabolic flux analysis. Furthermore, we give computational tools to process raw 13C labelling data produced by tandem mass spectrometry to a form suitable for 13C metabolic flux analysis.

Mikä yliopisto-opiskelijaa kiihdyttää? : Opiskeluympäristöjen tutkimusta CASS-kokemusotantamenetelmällä flow-teoriaa ja ydintunneteorioita soveltaen

Flow experience is often defined either as an experience of high concentration and enjoyment or as a situation, where high challenges are matched with high skills. According to core-emotion theories, the experience of any emotion contains two core emotions: valence and arousal. Through an accurate mathematical model, the present study investigated, whether the experience of concentration and enjoyment is related to situations where both challenge and skills are high and in balance. Further, it was investigated what sort of core emotions are related to differing relationships between challenge and skills. Finally, university students’ experiences of their natural study environments were described in terms of core emotions and in terms of relationships between challenge and skills. Participants were 55 university students who participated two weeks research period. Altogether 3367 questionnaire answers were collected with the CASS experience-sampling method, operating in 3G-mobile phones. The relationship between challenge and skills (competence) was defined in an exact way in polar coordinates. An enjoyable and concentrated flow experience was defined as a sum variable of absorption, interest and enthusiasm. Core emotions were calculated with factor analysis from nine emotion variables. As expected, an experience of concentration and enjoyment was, on average, related to the situations where both challenge and skills were high and in balance. This was not, however, the case in every situation. Thus, it should be taken into consideration how flow experience is operationalised in experience sampling studies. When flow experience was defined as a situation of high challenge and high skills, it was often related to high valence and arousal emotions such as excitement or enthusiasm. A happier or a more tranquil enjoyment was related to situations of moderate challenge and high skills. Experiences differed clearly between various natural study environments. At lectures students were often bored or mentally absent, and did not experience challenges. In a small group students were often excited or enthusiastic, and showed optimal balance between challenge and skills. At library students felt satisfied and were engaged in highly challenging work.

Pelaamiskokemukset ja pelaamisen yksilöllisten merkitysten yhteys flow n kokemiseen

The main goal of this study was to explore experiences induced by playing digital games (i.e. meaning of playing). In addition, the study aimed at structuring the larger entities of gaming experience. This was done by using theory-driven and data grounded approaches. Previously gaming experiences have not been explored as a whole. The consideration of gaming experiences on the basis of psychological theories and studies has also been rare. The secondary goal of this study was to clarify, whether the individual meanings of playing are connected with flow experience in an occasional gaming situation. Flow is an enjoyable experience and usually activities that induce flow are gladly repeated. Previously, flow has been proved to be an essential concept in the context of playing, but the relations between meanings of playing and flow have not been studied. The relations between gender and gaming experiences were examined throughout the study, as well as the relationship between gaming frequency and experiences. The study was divided into two sections, of which the first was composed according to the main goals. Its data was gathered by using an Internet questionnaire. The other section covered the themes that were formulated on the basis of the secondary aims. In that section, the participants played a driving game for 40 minutes and then filled in a questionnaire, which measured flow related experiences. In both sections, the participants were mainly young Finnish adults. All the participants in the second section (n = 60) had already participated in the first section (n = 267). Both qualitative and quantitative research techniques were used in the study. In the first section, freely described gaming experiences were classified according to the grounded theory. After that, the most common categories were further classified into the basic structures of gaming experience, some according to the existing theories of experience structure and some according to the data (i.e. grounded theory). In the other section flow constructs were measured and used as grouping variables in a cluster analysis. Three meaningful groups were compared regarding the meanings of gaming that were explored in the first section. The descriptions of gaming experiences were classified into four main categories, which were conceptions of the gaming process, emotions, motivations and focused attention. All the theory-driven categories were found in the data. This frame of reference can be utilized in future when reliability and validity of already existing methods for measuring gaming experiences are considered or new methods will be developed. The connection between the individual relevance of gaming and flow was minor. However, as the scope was specified to relations between primary meanings of playing and flow, it was noticed that attributing enjoyment to gaming did not lead to the strongest flow-experiences. This implies that the issue should be studied more in future. As a whole this study proves that gamer-related research from numerous vantage points can benefit from concentrating on gaming experiences.

Psychophysiology of flow experience : An explorative study

This study explored the possibilities the psychophysiological methodology offer to flow research. Facial electromyography has often been used to index valence, and electrodermal activity to index arousal, the two basic dimensions of emotion. It was hypothesized that these measures can also be used to examine enjoyment, a basic component of flow experiment. A digital game was used to induce flow, and physiological activity of 32 subjects was measured continuously. Flow State Scale was used to assess flow. Activity of corrugator supercilii muscle, an index of negative valence, was negatively correlated with flow reports, as hypothesized. Contrary to hypothesis, skin conductance level, an index of arousal, was unrelated to self-reported flow. The results for association between flow and zygomaticus major and orbicularis oculi muscle activities, indices of positive valence, were inconclusive, possibly due to experimental design where only tonic measures were available. Psychophysiological methods are recommended for future studies of flow. Specifically, the time series approach may be particularly viable in examining the temporal aspects of flow, an area currently unexplored. Furthermore, it is suggested that digital game research would benefit from psychophysiological study of game-related flow.

Automatic Lameness Detection in a Milking Robot : Instrumentation, measurement software, algorithms for data analysis and a neural network model

The aim of this thesis is to develop a fully automatic lameness detection system that operates in a milking robot. The instrumentation, measurement software, algorithms for data analysis and a neural network model for lameness detection were developed. Automatic milking has become a common practice in dairy husbandry, and in the year 2006 about 4000 farms worldwide used over 6000 milking robots. There is a worldwide movement with the objective of fully automating every process from feeding to milking. Increase in automation is a consequence of increasing farm sizes, the demand for more efficient production and the growth of labour costs. As the level of automation increases, the time that the cattle keeper uses for monitoring animals often decreases. This has created a need for systems for automatically monitoring the health of farm animals. The popularity of milking robots also offers a new and unique possibility to monitor animals in a single confined space up to four times daily. Lameness is a crucial welfare issue in the modern dairy industry. Limb disorders cause serious welfare, health and economic problems especially in loose housing of cattle. Lameness causes losses in milk production and leads to early culling of animals. These costs could be reduced with early identification and treatment. At present, only a few methods for automatically detecting lameness have been developed, and the most common methods used for lameness detection and assessment are various visual locomotion scoring systems. The problem with locomotion scoring is that it needs experience to be conducted properly, it is labour intensive as an on-farm method and the results are subjective. A four balance system for measuring the leg load distribution of dairy cows during milking in order to detect lameness was developed and set up in the University of Helsinki Research farm Suitia. The leg weights of 73 cows were successfully recorded during almost 10,000 robotic milkings over a period of 5 months. The cows were locomotion scored weekly, and the lame cows were inspected clinically for hoof lesions. Unsuccessful measurements, caused by cows standing outside the balances, were removed from the data with a special algorithm, and the mean leg loads and the number of kicks during milking was calculated. In order to develop an expert system to automatically detect lameness cases, a model was needed. A probabilistic neural network (PNN) classifier model was chosen for the task. The data was divided in two parts and 5,074 measurements from 37 cows were used to train the model. The operation of the model was evaluated for its ability to detect lameness in the validating dataset, which had 4,868 measurements from 36 cows. The model was able to classify 96% of the measurements correctly as sound or lame cows, and 100% of the lameness cases in the validation data were identified. The number of measurements causing false alarms was 1.1%. The developed model has the potential to be used for on-farm decision support and can be used in a real-time lameness monitoring system.

Asymmetrical flow field-flow fractionation in the study of water-soluble macromolecules

Asymmetrical flow field-flow fractionation (AsFlFFF) was constructed, and its applicability to industrial, biochemical, and pharmaceutical applications was studied. The effect of several parameters, such as pH, ionic strength, temperature and the reactants mixing ratios on the particle sizes, molar masses, and the formation of aggregates of macromolecules was determined by AsFlFFF. In the case of industrial application AsFlFFF proved to be a valuable tool in the characterization of the hydrodynamic particle sizes, molar masses and phase transition behavior of various poly(N-isopropylacrylamide) (PNIPAM) polymers as a function of viscosity and phase transition temperatures. The effect of sodium chloride salt and the molar ratio of cationic and anionic polyelectrolytes on the hydrodynamic particle sizes of poly (methacryloxyethyl trimethylammonium chloride) and poly (ethylene oxide)-block-poly (sodium methacrylate) and their complexes were studied. The particle sizes of PNIPAM polymers, and polyelectrolyte complexes measured by AsFlFFF were in agreement with those obtained by dynamic light scattering. The molar masses of PNIPAM polymers obtained by AsFlFFF and size exclusion chromatography agreed also well. In addition, AsFlFFF proved to be a practical technique in thermo responsive behavior studies of polymers at temperatures up to about 50 oC. The suitability of AsFlFFF for biological, biomedical, and pharmaceutical applications was proved, upon studying the lipid-protein/peptide interactions, and the stability of liposomes at different temperatures. AsFlFFF was applied to the studies on the hydrophobic and electrostatic interactions between cytochrome c (a basic peripheral protein) and anionic lipid, and oleic acid, and sodium dodecyl sulphate surfactant. A miniaturized AsFlFFF constructed in this study was exploited in the elucidation of the effect of copper (II), pH, ionic strength, and vortexing on the particle sizes of low-density lipoproteins.

Topographical, structural and geophysical characterization of fracture zones: implications for groundwater flow and vulnerability

The main objective of this study is to evaluate selected geophysical, structural and topographic methods on regional, local, and tunnel and borehole scales, as indicators of the properties of fracture zones or fractures relevant to groundwater flow. Such information serves, for example, groundwater exploration and prediction of the risk of groundwater inflow in underground construction. This study aims to address how the features detected by these methods link to groundwater flow in qualitative and semi-quantitative terms and how well the methods reveal properties of fracturing affecting groundwater flow in the studied sites. The investigated areas are: (1) the Päijänne Tunnel for water-conveyance whose study serves as a verification of structures identified on regional and local scales; (2) the Oitti fuel spill site, to telescope across scales and compare geometries of structural assessment; and (3) Leppävirta, where fracturing and hydrogeological environment have been studied on the scale of a drilled well. The methods applied in this study include: the interpretation of lineaments from topographic data and their comparison with aeromagnetic data; the analysis of geological structures mapped in the Päijänne Tunnel; borehole video surveying; groundwater inflow measurements; groundwater level observations; and information on the tunnel s deterioration as demonstrated by block falls. The study combined geological and geotechnical information on relevant factors governing groundwater inflow into a tunnel and indicators of fracturing, as well as environmental datasets as overlays for spatial analysis using GIS. Geophysical borehole logging and fluid logging were used in Leppävirta to compare the responses of different methods to fracturing and other geological features on the scale of a drilled well. Results from some of the geophysical measurements of boreholes were affected by the large diameter (gamma radiation) or uneven surface (caliper) of these structures. However, different anomalies indicating more fractured upper part of the bedrock traversed by well HN4 in Leppävirta suggest that several methods can be used for detecting fracturing. Fracture trends appear to align similarly on different scales in the zone of the Päijänne Tunnel. For example, similarities of patterns were found between the regional magnetic trends, correlating with orientations of topographic lineaments interpreted as expressions of fracture zones. The same structural orientations as those of the larger structures on local or regional scales were observed in the tunnel, even though a match could not be made in every case. The size and orientation of the observation space (patch of terrain at the surface, tunnel section, or borehole), the characterization method, with its typical sensitivity, and the characteristics of the location, influence the identification of the fracture pattern. Through due consideration of the influence of the sampling geometry and by utilizing complementary fracture characterization methods in tandem, some of the complexities of the relationship between fracturing and groundwater flow can be addressed. The flow connections demonstrated by the response of the groundwater level in monitoring wells to pressure decrease in the tunnel and the transport of MTBE through fractures in bedrock in Oitti, highlight the importance of protecting the tunnel water from a risk of contamination. In general, the largest values of drawdown occurred in monitoring wells closest to the tunnel and/or close to the topographically interpreted fracture zones. It seems that, to some degree, the rate of inflow shows a positive correlation with the level of reinforcement, as both are connected with the fracturing in the bedrock. The following geological features increased the vulnerability of tunnel sections to pollution, especially when several factors affected the same locations: (1) fractured bedrock, particularly with associated groundwater inflow; (2) thin or permeable overburden above fractured rock; (3) a hydraulically conductive layer underneath the surface soil; and (4) a relatively thin bedrock roof above the tunnel. The observed anisotropy of the geological media should ideally be taken into account in the assessment of vulnerability of tunnel sections and eventually for directing protective measures.

Gene flow from transgenic plant populations: models and applications for risk assessment

The future use of genetically modified (GM) plants in food, feed and biomass production requires a careful consideration of possible risks related to the unintended spread of trangenes into new habitats. This may occur via introgression of the transgene to conventional genotypes, due to cross-pollination, and via the invasion of GM plants to new habitats. Assessment of possible environmental impacts of GM plants requires estimation of the level of gene flow from a GM population. Furthermore, management measures for reducing gene flow from GM populations are needed in order to prevent possible unwanted effects of transgenes on ecosystems. This work develops modeling tools for estimating gene flow from GM plant populations in boreal environments and for investigating the mechanisms of the gene flow process. To describe spatial dimensions of the gene flow, dispersal models are developed for the local and regional scale spread of pollen grains and seeds, with special emphasis on wind dispersal. This study provides tools for describing cross-pollination between GM and conventional populations and for estimating the levels of transgenic contamination of the conventional crops. For perennial populations, a modeling framework describing the dynamics of plants and genotypes is developed, in order to estimate the gene flow process over a sequence of years. The dispersal of airborne pollen and seeds cannot be easily controlled, and small amounts of these particles are likely to disperse over long distances. Wind dispersal processes are highly stochastic due to variation in atmospheric conditions, so that there may be considerable variation between individual dispersal patterns. This, in turn, is reflected to the large amount of variation in annual levels of cross-pollination between GM and conventional populations. Even though land-use practices have effects on the average levels of cross-pollination between GM and conventional fields, the level of transgenic contamination of a conventional crop remains highly stochastic. The demographic effects of a transgene have impacts on the establishment of trangenic plants amongst conventional genotypes of the same species. If the transgene gives a plant a considerable fitness advantage in comparison to conventional genotypes, the spread of transgenes to conventional population can be strongly increased. In such cases, dominance of the transgene considerably increases gene flow from GM to conventional populations, due to the enhanced fitness of heterozygous hybrids. The fitness of GM plants in conventional populations can be reduced by linking the selectively favoured primary transgene to a disfavoured mitigation transgene. Recombination between these transgenes is a major risk related to this technique, especially because it tends to take place amongst the conventional genotypes and thus promotes the establishment of invasive transgenic plants in conventional populations.

Bayesian statistical analysis of bacterial diversity

Bacteria play an important role in many ecological systems. The molecular characterization of bacteria using either cultivation-dependent or cultivation-independent methods reveals the large scale of bacterial diversity in natural communities, and the vastness of subpopulations within a species or genus. Understanding how bacterial diversity varies across different environments and also within populations should provide insights into many important questions of bacterial evolution and population dynamics. This thesis presents novel statistical methods for analyzing bacterial diversity using widely employed molecular fingerprinting techniques. The first objective of this thesis was to develop Bayesian clustering models to identify bacterial population structures. Bacterial isolates were identified using multilous sequence typing (MLST), and Bayesian clustering models were used to explore the evolutionary relationships among isolates. Our method involves the inference of genetic population structures via an unsupervised clustering framework where the dependence between loci is represented using graphical models. The population dynamics that generate such a population stratification were investigated using a stochastic model, in which homologous recombination between subpopulations can be quantified within a gene flow network. The second part of the thesis focuses on cluster analysis of community compositional data produced by two different cultivation-independent analyses: terminal restriction fragment length polymorphism (T-RFLP) analysis, and fatty acid methyl ester (FAME) analysis. The cluster analysis aims to group bacterial communities that are similar in composition, which is an important step for understanding the overall influences of environmental and ecological perturbations on bacterial diversity. A common feature of T-RFLP and FAME data is zero-inflation, which indicates that the observation of a zero value is much more frequent than would be expected, for example, from a Poisson distribution in the discrete case, or a Gaussian distribution in the continuous case. We provided two strategies for modeling zero-inflation in the clustering framework, which were validated by both synthetic and empirical complex data sets. We show in the thesis that our model that takes into account dependencies between loci in MLST data can produce better clustering results than those methods which assume independent loci. Furthermore, computer algorithms that are efficient in analyzing large scale data were adopted for meeting the increasing computational need. Our method that detects homologous recombination in subpopulations may provide a theoretical criterion for defining bacterial species. The clustering of bacterial community data include T-RFLP and FAME provides an initial effort for discovering the evolutionary dynamics that structure and maintain bacterial diversity in the natural environment.