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.

La contextualisation du discours radiophonique par des moyens prosodiques. L’exemple de cinq grands philosophes français du XXe siècle

"Radiodiskurssin kontekstualisointi prosodisin keinoin. Esimerkkinä viisi suurta ranskalaista 1900-luvun filosofia" Väitöskirja käsittelee puheen kontekstualisointia prosodisin keinoin. Toisin sanottuna työssä käsitellään sitä, miten puheen prosodiset piirteet (kuten sävelkulku, intensiteetti, tauot, kesto ja rytmi) ohjaavat puheen tulkintaa vanhastaan enemmän tutkittujen sana- ja lausemerkitysten ohella. Työssä keskitytään seitsemään prosodisesti merkittyyn kuvioon, jotka koostuvat yhden tai usean parametrin silmiinpistävistä muutoksista. Ilmiöitä käsitellään sekä niiden akustisten muotojen että tyypillisten esiintymisyhteyksien ja diskursiivisten tehtävien näkökulmasta. Aineisto koostuu radio-ohjelmista, joissa puhuu viisi suurta ranskalaista 1900-luvun filosofia: Gaston Bachelard, Albert Camus, Michel Foucault, Maurice Merleau-Ponty ja Jean-Paul Sartre. Ohjelmat on lähetetty eri radiokanavilla Ranskassa vuosina 1948–1973. Väitöskirjan tulokset osoittavat, että prosodisesti merkityt kuviot ovat moniulotteisia puheen ilmiöitä, joilla on keskeinen rooli sanotun kontekstualisoinnissa: ne voivat esimerkiksi nostaa tai laskea sanotun informaatioarvoa, ilmaista puhujan voimakasta tai heikkoa sitoutumista sanomaansa, ilmaista rakenteellisen kokonaisuuden jatkumista tai päättymistä, jne. Väitöskirja sisältää myös kontrastiivisia osia, joissa ilmiöitä verrataan erääseen klassisessa pianomusiikissa esiintyvään melodiseen kuvioon sekä erääseen suomen kielen prosodiseen ilmiöön. Tulokset viittaavat siihen, että tietynlaista melodista kuviota käytetään samankaltaisena jäsentämiskeinona sekä puheessa että klassisessa musiikissa. Lisäksi tulokset antavat viitteitä siitä, että tiettyjä melodisia muotoja käytetään samankaltaisten implikaatioiden luomiseen kahdessa niinkin erilaisessa kielessä kuin suomessa ja ranskassa. Yksi väitöskirjan osa käsittelee pisteen ja pilkun prosodista merkitsemistä puheessa. Tulosten mukaan pisteellä ja pilkulla on kummallakin oma suullinen prototyyppinsä: piste merkitään tyypillisesti sävelkulun laskulla ja tauolla, ja pilkku puolestaan sävelkulun nousulla ja tauolla. Merkittävimmät tulokset koskevat kuitenkin tapauksia, joissa välimerkki tulkitaan prosodisesti epätyypillisellä tavalla: sekä pisteellä että pilkulla vaikuttaisi olevan useita eri suullisia vastaavuuksia, ja välimerkkien tehtävät voivat muotoutua hyvin erilaisiksi niiden prosodisesta tulkinnasta riippuen.

Turning the Kaleidoscope - (E)FL Educational Experience and Inquiry as Auto/biography

This book is a study on learning, teaching/counselling, and research on the two. My quest has been to find a pedagogically-motivated way of researching learning and teaching interaction, and in particular counselling, in an autonomous language-learning environment. I have tried to develop a method that would make room for lived experience, meaning-making and narrating, because in my view these all characterise learning encounters between language learners and counsellors, and learners and their peers. Lived experience as a source of meaning, telling and co-telling becomes especially significant when we try to listen to the diverse personal and academic voices of the past as expressed in autobiographical narratives. I have aimed at researching various ALMS dialogues (Autonomous Learning Modules, University of Helsinki Language Centre English course and programme), and autobiographical narratives within them, in a way that shows respect for the participants, and that is relevant, reflective and, most importantly, self-reflexive. My interest has been in autobiographical telling in (E)FL [(English as a) foreign language], both in students first-person written texts on their language- learning histories and in the sharing of stories between learners and a counsellor. I have turned to narrative inquiry in my quest and have written the thesis as an experiential narrative. In particular, I have studied learners and counsellors in one and the same story, as characters in one narrative, in an attempt to avoid the impression that I am telling yet another separate, anecdotal story, retrospectively. Through narrative, I have shed light on the subjective dimensions of language learning and experience, and have come closer to understanding the emotional aspects of learning encounters. I have questioned and rejected a distanced and objective approach to describing learning and teaching/counselling. I have argued for a holistic and experiential approach to (E)FL encounters in which there is a need to see emotion and cognition as intertwined, and thus to appreciate learners and counsellors emotionally-charged experiences as integral to their identities. I have also argued for a way of describing such encounters as they are situated in history, time, autobiography, and the learning context. I have turned my gaze on various constellations of lived experience: the data was collected on various occasions and in various settings during one course and consists of videotaped group sessions, individual counselling sessions between students and their group counsellor, biographic narrative interviews with myself, open-ended personally-inspired reflection texts written by the students about their language-learning histories, and student logs and diaries. I do not consider data collection an unproblematic occasion, or innocent practice, and I defend the integrity of the research process. Research writing cannot be separated from narrative field work and analysing and interpreting the data. The foci in my work have turned to be the following: 1) describing ALMS encounters and specifying their narrative aspects; 2) reconceptualising learner and teacher autonomy in ALMS and in (E)FL; 2) developing (E)FL methodologically through a teacher-researcher s identity work; 4) research writing as a dialogical narrative process, and the thesis as an experiential narrative. Identity and writing as inquiry, and the deeply narrative and autobiographical nature of the (E)FL teaching/counselling/researching have come to the fore in this research. Research writing as a relational activity and its implications for situated ways of knowing and knowledge turned out to be important foci. I have also focussed on the context-bound and local teacher knowledge and ways of knowing about being a teacher, and I have argued for personal ways of knowing about, and learning and studying foreign languages. I discuss research as auto/biography: as a practising counsellor I use my own life and (E)FL experience to understand and interpret the stories of the research participants even though I was not involved in their course work. The supposedly static binaries of learner/teacher, and also learner autonomy/teacher autonomy, are thus brought into the discussion. I have highlighted the infinite variability and ever-changing nature of learning and teaching English, but the book is also of relevance to foreign language education in general.

Questions to Artificial Nature: A Philosophical Study of Interdisciplinary Models and their Functions in Scientific Practice

This thesis presents an interdisciplinary analysis of how models and simulations function in the production of scientific knowledge. The work is informed by three scholarly traditions: studies on models and simulations in philosophy of science, so-called micro-sociological laboratory studies within science and technology studies, and cultural-historical activity theory. Methodologically, I adopt a naturalist epistemology and combine philosophical analysis with a qualitative, empirical case study of infectious-disease modelling. This study has a dual perspective throughout the analysis: it specifies the modelling practices and examines the models as objects of research. The research questions addressed in this study are: 1) How are models constructed and what functions do they have in the production of scientific knowledge? 2) What is interdisciplinarity in model construction? 3) How do models become a general research tool and why is this process problematic? The core argument is that the mediating models as investigative instruments (cf. Morgan and Morrison 1999) take questions as a starting point, and hence their construction is intentionally guided. This argument applies the interrogative model of inquiry (e.g., Sintonen 2005; Hintikka 1981), which conceives of all knowledge acquisition as process of seeking answers to questions. The first question addresses simulation models as Artificial Nature, which is manipulated in order to answer questions that initiated the model building. This account develops further the "epistemology of simulation" (cf. Winsberg 2003) by showing the interrelatedness of researchers and their objects in the process of modelling. The second question clarifies why interdisciplinary research collaboration is demanding and difficult to maintain. The nature of the impediments to disciplinary interaction are examined by introducing the idea of object-oriented interdisciplinarity, which provides an analytical framework to study the changes in the degree of interdisciplinarity, the tools and research practices developed to support the collaboration, and the mode of collaboration in relation to the historically mutable object of research. As my interest is in the models as interdisciplinary objects, the third research problem seeks to answer my question of how we might characterise these objects, what is typical for them, and what kind of changes happen in the process of modelling. Here I examine the tension between specified, question-oriented models and more general models, and suggest that the specified models form a group of their own. I call these Tailor-made models, in opposition to the process of building a simulation platform that aims at generalisability and utility for health-policy. This tension also underlines the challenge of applying research results (or methods and tools) to discuss and solve problems in decision-making processes.

Representing the epistemic nature of teachers’ practical knowledge : The case of class teachers’ general pedagogy

The present study addressed the epistemology of teachers’ practical knowledge. Drawing from the literature, teachers’ practical knowledge is defined as all teachers’ cognitions (e.g., beliefs, values, motives, procedural knowing, and declarative knowledge) that guide their practice of teaching. The teachers’ reasoning that lies behind their practical knowledge is addressed to gain insight into its epistemic nature. I studied six class teachers’ practical knowledge; they teach in the metropolitan region of Helsinki. Relying on the assumptions of the phenomenographic inquiry, I collected and analyzed the data. I analyzed the data in two stages where the first stage involved an abductive procedure, and the second stage an inductive procedure for interpretation, and thus developed the system of categories. In the end, a quantitative analysis nested into the qualitative findings to study the patterns of the teachers’’ reasoning. The results indicated that teachers justified their practical knowledge based on morality and efficiency of action; efficiency of action was found to be presented in two different ways: authentic efficiency and naïve efficiency. The epistemic weight of morality was embedded in what I call “moral care”. The core intention of teachers in the moral care was the commitment that they felt about the “whole character” of students. From this perspective the “dignity” and the moral character of the students should not replaced for any other “instrumental price”. “Caring pedagogy” was the epistemic value of teachers’ reasoning in the authentic efficiency. The central idea in the caring pedagogy was teachers’ intentions to improve the “intellectual properties” of “all or most” of the students using “flexible” and “diverse” pedagogies. However, “regulating pedagogy” was the epistemic condition of practice in the cases corresponding to naïve efficiency. Teachers argued that an effective practical knowledge should regulate and manage the classroom activities, but the targets of the practical knowledge were mainly other “issues “or a certain percentage of the students. In these cases, the teachers’ arguments were mainly based on the notion of “what worked” regardless of reflecting on “what did not work”. Drawing from the theoretical background and the data, teachers’ practical knowledge calls for “praxial knowledge” when they used the epistemic conditions of “caring pedagogy” and “moral care”. It however calls for “practicable” epistemic status when teachers use the epistemic condition of regulating pedagogy. As such, praxial knowledge with the dimensions of caring pedagogy and moral care represents the “normative” perspective on teachers’ practical knowledge, and thus reflects a higher epistemic status in comparison to “practicable” knowledge, which represents a “descriptive” perception toward teachers’ practical knowledge and teaching.

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.

Beasts on Fields. Human-Wildlife Conflicts in Nature-Culture Borderlands

Human-wildlife conflicts are today an integral part of the rural development discourse. In this research, the main focus is on the spatial explanation which is not a very common approach in the reviewed literature. My research hypothesis is based on the assumption that human-wildlife conflicts occur when a wild animal crosses a perceived borderline between the nature and culture and enters into the realms of the other. The borderline between nature and culture marks a perceived division of spatial content in our senses of place. The animal subject that crosses this border becomes a subject out of place meaning that the animal is then spatially located in a space where it should not be or where it does not belong according to tradition, custom, rules, law, public opinion, prevailing discourse or some other criteria set by human beings. An appearance of a wild animal in a domesticated space brings an uncontrolled subject into that space where humans have previously commanded total control of all other natural elements. A wild animal out of place may also threaten the biosecurity of the place in question. I carried out a case study in the Liwale district in south-eastern Tanzania to test my hypothesis during June and July 2002. I also collected documents and carried out interviews in Dar es Salaam in 2003. I studied the human-wildlife conflicts in six rural villages, where a total of 183 persons participated in the village meetings. My research methods included semi-structured interviews, participatory mapping, questionnaire survey and Q- methodology. The rural communities in the Liwale district have a long-history of co-existing with wildlife and they still have traditional knowledge of wildlife management and hunting. Wildlife conservation through the establishment of game reserves during the colonial era has escalated human-wildlife conflicts in the Liwale district. This study shows that the villagers perceive some wild animals differently in their images of the African countryside than the district and regional level civil servants do. From the small scale subsistence farmers point of views, wild animals continue to challenge the separation of the wild (the forests) and the domestics spaces (the cultivated fields) by moving across the perceived borders in search of food and shelter. As a result, the farmers may loose their crops, livestock or even their own lives in the confrontations of wild animals. Human-wildlife conflicts in the Liwale district are manifold and cannot be explained simply on the basis of attitudes or perceived images of landscapes. However, the spatial explanation of these conflicts provides us some more understanding of why human-wildlife conflicts are so widely found across the world.

Problems and Algorithms for Sequence Segmentations

The analysis of sequential data is required in many diverse areas such as telecommunications, stock market analysis, and bioinformatics. A basic problem related to the analysis of sequential data is the sequence segmentation problem. A sequence segmentation is a partition of the sequence into a number of non-overlapping segments that cover all data points, such that each segment is as homogeneous as possible. This problem can be solved optimally using a standard dynamic programming algorithm. In the first part of the thesis, we present a new approximation algorithm for the sequence segmentation problem. This algorithm has smaller running time than the optimal dynamic programming algorithm, while it has bounded approximation ratio. The basic idea is to divide the input sequence into subsequences, solve the problem optimally in each subsequence, and then appropriately combine the solutions to the subproblems into one final solution. In the second part of the thesis, we study alternative segmentation models that are devised to better fit the data. More specifically, we focus on clustered segmentations and segmentations with rearrangements. While in the standard segmentation of a multidimensional sequence all dimensions share the same segment boundaries, in a clustered segmentation the multidimensional sequence is segmented in such a way that dimensions are allowed to form clusters. Each cluster of dimensions is then segmented separately. We formally define the problem of clustered segmentations and we experimentally show that segmenting sequences using this segmentation model, leads to solutions with smaller error for the same model cost. Segmentation with rearrangements is a novel variation to the segmentation problem: in addition to partitioning the sequence we also seek to apply a limited amount of reordering, so that the overall representation error is minimized. We formulate the problem of segmentation with rearrangements and we show that it is an NP-hard problem to solve or even to approximate. We devise effective algorithms for the proposed problem, combining ideas from dynamic programming and outlier detection algorithms in sequences. In the final part of the thesis, we discuss the problem of aggregating results of segmentation algorithms on the same set of data points. In this case, we are interested in producing a partitioning of the data that agrees as much as possible with the input partitions. We show that this problem can be solved optimally in polynomial time using dynamic programming. Furthermore, we show that not all data points are candidates for segment boundaries in the optimal solution.

Matrix Decomposition Methods for Data Mining : Computational Complexity and Algorithms

Matrix decompositions, where a given matrix is represented as a product of two other matrices, are regularly used in data mining. Most matrix decompositions have their roots in linear algebra, but the needs of data mining are not always those of linear algebra. In data mining one needs to have results that are interpretable -- and what is considered interpretable in data mining can be very different to what is considered interpretable in linear algebra. --- The purpose of this thesis is to study matrix decompositions that directly address the issue of interpretability. An example is a decomposition of binary matrices where the factor matrices are assumed to be binary and the matrix multiplication is Boolean. The restriction to binary factor matrices increases interpretability -- factor matrices are of the same type as the original matrix -- and allows the use of Boolean matrix multiplication, which is often more intuitive than normal matrix multiplication with binary matrices. Also several other decomposition methods are described, and the computational complexity of computing them is studied together with the hardness of approximating the related optimization problems. Based on these studies, algorithms for constructing the decompositions are proposed. Constructing the decompositions turns out to be computationally hard, and the proposed algorithms are mostly based on various heuristics. Nevertheless, the algorithms are shown to be capable of finding good results in empirical experiments conducted with both synthetic and real-world data.

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.