Intermediate Past BE : A Paradigm Reshaped With Data Drawn From HARES

In this paper, I look into a grammatical phenomenon found among speakers of the Cambridgeshire dialect of English. According to my hypothesis, the phenomenon is a new entry into the past BE verb paradigm in the English language. In my paper, I claim that the structure I have found complements the existing two verb forms, was and were, with a third verb form that I have labelled ‘intermediate past BE’. The paper is divided into two parts. In the first section, I introduce the theoretical ground for the study of variation, which is founded on empiricist principles. In variationist linguistics, the main claim is that heterogeneous language use is structured and ordered. In the last 50 years of history in modern linguistics, this claim is controversial. In the 1960s, the generativist movement spearheaded by Noam Chomsky diverted attention away from grammatical theories that are based on empirical observations. The generativists steered away from language diversity, variation and change in favour of generalisations, abstractions and universalist claims. The theoretical part of my paper goes through the main points of the variationist agenda and concludes that abandoning the concept of language variation in linguistics is harmful for both theory and methodology. In the method part of the paper, I present the Helsinki Archive of Regional English Speech (HARES) corpus. It is an audio archive that contains interviews conducted in England in the 1970s and 1980s. The interviews were done in accordance to methods used generally in traditional dialectology. The informants are mostly elderly male people who have lived in the same region throughout their lives and who have left school at an early age. The interviews are actually conversations: the interviewer allowed the informant to pick the topic of conversation to induce a maximally relaxed and comfortable atmosphere and thus allow the most natural dialect variant to emerge in the informant’s speech. In the paper, the corpus chapter introduces some of the transcription and annotation problems associated with spoken language corpora (especially those containing dialectal speech). Questions surrounding the concept of variation are present in this part of the paper too, as especially transcription work is troubled by the fundamental problem of having to describe the fluctuations of everyday speech in text. In the empirical section of the paper, I use HARES to analyse the speech of four informants, with special focus on the emergence of the intermediate past BE variant. My observations and the subsequent analysis permit me to claim that my hypothesis seems to hold. The intermediate variant occupies almost all contexts where one would expect was or were in the informants’ speech. This means that the new variant is integrated into the speakers’ grammars and exemplifies the kind of variation that is at the heart of this paper.

Laatutyöhön sitoutumisen edellytykset ammattikorkeakoulussa

The goal of this research was to establish the necessary conditions under which individuals are prepared to commit themselves to quality assurance work in the organisation of a Polytechnic. The conditions were studied using four main concepts: awareness of quality, commitment to the organisation, leadership and work welfare. First, individuals were asked to describe these four concepts. Then, relationships between the concepts were analysed in order to establish the conditions for the commitment of an individual towards quality assurance work (QA). The study group comprised the entire personnel of Helsinki Polytechnic, of which 341 (44.5%) individuals participated. Mixed methods were used as the methodological base. A questionnaire and interviews were used as the research methods. The data from the interviews were used for the validation of the results, as well as for completing the analysis. The results of these interviews and analyses were integrated using the concurrent nested design method. In addition, the questionnaire was used to separately analyse the impressions and meanings of the awareness of quality and leadership, because, according to the pre-understanding, impressions of phenomena expressed in terms of reality have an influence on the commitment to QA. In addition to statistical figures, principal component analysis was used as a description method. For comparisons between groups, one way variance analysis and effect size analysis were used. For explaining the analysis methods, forward regression analysis and structural modelling were applied. As a result of the research it was found that 51% of the conditions necessary for a commitment to QA were explained by an individual’s experience/belief that QA was a method of development, that QA was possible to participate in and that the meaning of quality included both product and process qualities. If analysed separately, other main concepts (commitment to the organisation, leadership and work welfare) played only a small part in explaining an individual’s commitment. In the context of this research, a structural path model of the main concepts was built. In the model, the concepts were interconnected by paths created as a result of a literature search covering the main concepts, as well as a result of an analysis of the empirical material of this thesis work. The path model explained 46% of the necessary conditions under which individuals are prepared to commit themselves to QA. The most important path for achieving a commitment stemmed from product and system quality emanating from the new goals of the Polytechnic, moved through the individual’s experience that QA is a method of the total development of quality and ended in a commitment to QA. The second most important path stemmed from the individual’s experience of belonging to a supportive work community, moved through the supportive value of the job and through affective commitment to the organisation and ended in a commitment to QA. The third path stemmed from an individual’s experiences in participating in QA, moved through collective system quality and through these to the supportive value of the job to affective commitment to the organisation and ended in a commitment to QA. The final path in the path model stemmed from leadership by empowerment, moved through collective system quality, the supportive value of the job and an affective commitment to the organisation, and again, ended in a commitment to QA. As a result of the research, it was found that the individual’s functional department was an important factor in explaining the differences between groups. Therefore, it was found that understanding the processing of part cultures in the organisation is important when developing QA. Likewise, learning-teaching paradigms proved to be a differentiating factor. Individuals thinking according to the humanistic-constructivistic paradigm showed more commitment to QA than technological-rational thinkers. Also, it was proved that the QA training program did not increase commitment, as the path model demonstrated that those who participated in training showed 34% commitment, whereas those who did not showed 55% commitment. As a summary of the results it can be said that the necessary conditions under which individuals are prepared to commit themselves to QA cannot be treated in a reductionistic way. Instead, the conditions must be treated as one totality, with all the main concepts interacting simultaneously. Also, the theoretical framework of quality must include its dynamic aspect, which means the development of the work of the individual and learning through auditing. In addition, this dynamism includes the reflection of the paradigm of the functions of the individual as well as that of all parts of the organisation. It is important to understand and manage the various ways of thinking and the cultural differences produced by the fragmentation of the organisation. Finally, it seems possible that the path model can be generalised for use in any organisation development project where the personnel should be committed.

Epidemiological data of seasonal variation in mood and behaviour

The aim of this study was to measure seasonal variation in mood and behaviour. The dual vulnerability and latitude effect hypothesis, the risk of increased appetite, weight and other seasonal symptoms to develop metabolic syndrome, and perception of low illumination in quality of life and mental well-being were assessed. These variations are prevalent in persons who live in high latitudes and need balancing of metabolic processes to adapt to environmental changes due to seasons. A randomized sample of 8028 adults aged 30 and over (55% women) participated in an epidemiological health examination study, The Health 2000, applying the probability proportional to population size method for a range of socio-demographic characteristics. They were present in a face-to-face interview at home and health status examination. The questionnaires included the modified versions of the Seasonal Pattern Assessment Questionnaire (SPAQ) and Beck Depression Inventory (BDI), the Health Related Quality of Life (HRQoL) instrument 15D, and the General Health Questionnaire (GHQ). The structured and computerized Munich Composite International Diagnostic Interview (M-CIDI) as part of the interview was used to assess diagnoses of mental disorders, and, the National Cholesterol Education Program Adult Treatment Panel III (NCEP-ATPIII) criteria were assessed using all the available information to detect metabolic syndrome. A key finding was that 85% of this nationwide representative sample had seasonal variation in mood and behaviour. Approximately 9% of the study population presented combined seasonal and depressive symptoms with a significant association between their scores, and 2.6% had symptoms that corresponded to Seasonal Affective Disorder (SAD) in severity. Seasonal variations in weight and appetite are two important components that increase the risk of metabolic syndrome. Other factors such as waist circumference and major depressive disorder contributed to the metabolic syndrome as well. Persons reported of having seasonal symptoms were associated with a poorer quality of life and compromised mental well-being, especially if indoors illumination at home and/or at work was experienced as being low. Seasonal and circadian misalignments are suggested to associate with metabolic disorders, and could be remarked if individuals perceive low illumination levels at home and/or at work that affect the health-related quality of life and mental well-being. Keywords: depression, health-related quality of life, illumination, latitude, mental well-being, metabolic syndrome, seasonal variation, winter.

Statistical analysis of the associations of hereditary factors with the risk of Type 1 diabetes and Diabetic Nephropathy based on the familial data collected through ascertaiment from population-based registers

In genetic epidemiology, population-based disease registries are commonly used to collect genotype or other risk factor information concerning affected subjects and their relatives. This work presents two new approaches for the statistical inference of ascertained data: a conditional and full likelihood approaches for the disease with variable age at onset phenotype using familial data obtained from population-based registry of incident cases. The aim is to obtain statistically reliable estimates of the general population parameters. The statistical analysis of familial data with variable age at onset becomes more complicated when some of the study subjects are non-susceptible, that is to say these subjects never get the disease. A statistical model for a variable age at onset with long-term survivors is proposed for studies of familial aggregation, using latent variable approach, as well as for prospective studies of genetic association studies with candidate genes. In addition, we explore the possibility of a genetic explanation of the observed increase in the incidence of Type 1 diabetes (T1D) in Finland in recent decades and the hypothesis of non-Mendelian transmission of T1D associated genes. Both classical and Bayesian statistical inference were used in the modelling and estimation. Despite the fact that this work contains five studies with different statistical models, they all concern data obtained from nationwide registries of T1D and genetics of T1D. In the analyses of T1D data, non-Mendelian transmission of T1D susceptibility alleles was not observed. In addition, non-Mendelian transmission of T1D susceptibility genes did not make a plausible explanation for the increase in T1D incidence in Finland. Instead, the Human Leucocyte Antigen associations with T1D were confirmed in the population-based analysis, which combines T1D registry information, reference sample of healthy subjects and birth cohort information of the Finnish population. Finally, a substantial familial variation in the susceptibility of T1D nephropathy was observed. The presented studies show the benefits of sophisticated statistical modelling to explore risk factors for complex diseases.

Management of multi-scale forest resource data over time

During the last decades there has been a global shift in forest management from a focus solely on timber management to ecosystem management that endorses all aspects of forest functions: ecological, economic and social. This has resulted in a shift in paradigm from sustained yield to sustained diversity of values, goods and benefits obtained at the same time, introducing new temporal and spatial scales into forest resource management. The purpose of the present dissertation was to develop methods that would enable spatial and temporal scales to be introduced into the storage, processing, access and utilization of forest resource data. The methods developed are based on a conceptual view of a forest as a hierarchically nested collection of objects that can have a dynamically changing set of attributes. The temporal aspect of the methods consists of lifetime management for the objects and their attributes and of a temporal succession linking the objects together. Development of the forest resource data processing method concentrated on the extensibility and configurability of the data content and model calculations, allowing for a diverse set of processing operations to be executed using the same framework. The contribution of this dissertation to the utilisation of multi-scale forest resource data lies in the development of a reference data generation method to support forest inventory methods in approaching single-tree resolution.

Estimation of local forest attributes, utilizing two-phase sampling and auxiliary data

This thesis examines the feasibility of a forest inventory method based on two-phase sampling in estimating forest attributes at the stand or substand levels for forest management purposes. The method is based on multi-source forest inventory combining auxiliary data consisting of remote sensing imagery or other geographic information and field measurements. Auxiliary data are utilized as first-phase data for covering all inventory units. Various methods were examined for improving the accuracy of the forest estimates. Pre-processing of auxiliary data in the form of correcting the spectral properties of aerial imagery was examined (I), as was the selection of aerial image features for estimating forest attributes (II). Various spatial units were compared for extracting image features in a remote sensing aided forest inventory utilizing very high resolution imagery (III). A number of data sources were combined and different weighting procedures were tested in estimating forest attributes (IV, V). Correction of the spectral properties of aerial images proved to be a straightforward and advantageous method for improving the correlation between the image features and the measured forest attributes. Testing different image features that can be extracted from aerial photographs (and other very high resolution images) showed that the images contain a wealth of relevant information that can be extracted only by utilizing the spatial organization of the image pixel values. Furthermore, careful selection of image features for the inventory task generally gives better results than inputting all extractable features to the estimation procedure. When the spatial units for extracting very high resolution image features were examined, an approach based on image segmentation generally showed advantages compared with a traditional sample plot-based approach. Combining several data sources resulted in more accurate estimates than any of the individual data sources alone. The best combined estimate can be derived by weighting the estimates produced by the individual data sources by the inverse values of their mean square errors. Despite the fact that the plot-level estimation accuracy in two-phase sampling inventory can be improved in many ways, the accuracy of forest estimates based mainly on single-view satellite and aerial imagery is a relatively poor basis for making stand-level management decisions.

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.