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.

Written Cancer Narratives : An Ethnomedical Study of Cancer Patients' Thoughts, Emotions and Experiences

Since the second half of the 20th century, cancer has become a dominant disease in Western countries, endangering people regardless of age, gender, race or social status. Every year almost eight million people die of cancer worldwide. In Finland every fourth person is expected to fall ill with cancer at some stage of his or her life. During the 20th century, along with rapid changes in the medical system, people s awareness of cancer has increased a great deal. This has also influenced the image of cancer in popular discourse over the past decades. However, from the scientific point of view there is still much that is unclear about the disease. This thesis shows that this is a big problem for ordinary people, as, according to culture-bound illness ideology, people need an explanation about the origin of their illness in order to help them cope. The main aim of this thesis is to examine the process of being ill with cancer from the patient s point of view, in order to analyse attitudes and behaviour towards cancer and its significance and culture-bound images. This narrative-based study concentrates on patients voicings , which are important in understanding the cancer experience and when attempting to make it more open within current cultural and societal settings. The Kun sairastuin syöpään ( when I fell ill with cancer ) writing competition organised by Suomen Syöpäpotilaat ry (the Finnish Cancer Patients Association), Suomen Syöpäyhdistys ry (the Finnish Cancer Union), and Suomalaisen Kirjallisuuden Seuran kansanrunousarkisto (the Finnish Literary Society Folklore Archive) was announced on the 1st of May 1994 and lasted until the 30th of September 1994. As a result, a total of 672 cancer narratives, totalling 6384 pages, were received, filled with experiences relating to cancer. Written cancer narratives form a body of empirical data that is suitable for content or textual analysis. In this thesis, content analysis is adopted in order to become familiar with the texts and to preselect the themes and analytical units for further examination. I use multiple perspectives in order to interpret cancer patients ideas and reasoning. The ethnomedical approach unites popular health beliefs that originated in Finnish folk medicine, as well as connecting alternative medicine, which patients make use of, with biomedicine, the dominant form of medicine today. In addition to this, patients narratives, which are composed of various structural segments, are approached from the folklorist s perspective. In this way they can be seen as short pathographies, reconstructions of self-negotiation and individual decision making during the illness process. Above all, cancer patients writing describe their feelings, thoughts and experiences. Factors that appear insignificant to modern medicine, overwhelmed as it is by medical technologies that concentrate on dysfunctional tissue within diseased bodies. Ethnomedical study of cancer patients writings gives access to the human side of cancer discourse, and combines both medical, and popular, knowledge of cancer. In my view, the natural world and glimpses of tradition are bound together with one general aim within cancer narratives: to tackle the illness and mediate its meanings. Furthermore, the narrative approach reveals that participants write with the hope of offering a different interpretation of the cancer experience, and thus of confronting culturally pre-defined images and ideologies.