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.

Data fusion and matching by maximizing statistical dependencies

The core aim of machine learning is to make a computer program learn from the experience. Learning from data is usually defined as a task of learning regularities or patterns in data in order to extract useful information, or to learn the underlying concept. An important sub-field of machine learning is called multi-view learning where the task is to learn from multiple data sets or views describing the same underlying concept. A typical example of such scenario would be to study a biological concept using several biological measurements like gene expression, protein expression and metabolic profiles, or to classify web pages based on their content and the contents of their hyperlinks. In this thesis, novel problem formulations and methods for multi-view learning are presented. The contributions include a linear data fusion approach during exploratory data analysis, a new measure to evaluate different kinds of representations for textual data, and an extension of multi-view learning for novel scenarios where the correspondence of samples in the different views or data sets is not known in advance. In order to infer the one-to-one correspondence of samples between two views, a novel concept of multi-view matching is proposed. The matching algorithm is completely data-driven and is demonstrated in several applications such as matching of metabolites between humans and mice, and matching of sentences between documents in two languages.

Microbiological characterisation of soils : Evaluation of some critical steps in data collection and experimental design

The study of soil microbiota and their activities is central to the understanding of many ecosystem processes such as decomposition and nutrient cycling. The collection of microbiological data from soils generally involves several sequential steps of sampling, pretreatment and laboratory measurements. The reliability of results is dependent on reliable methods in every step. The aim of this thesis was to critically evaluate some central methods and procedures used in soil microbiological studies in order to increase our understanding of the factors that affect the measurement results and to provide guidance and new approaches for the design of experiments. The thesis focuses on four major themes: 1) soil microbiological heterogeneity and sampling, 2) storage of soil samples, 3) DNA extraction from soil, and 4) quantification of specific microbial groups by the most-probable-number (MPN) procedure. Soil heterogeneity and sampling are discussed as a single theme because knowledge on spatial (horizontal and vertical) and temporal variation is crucial when designing sampling procedures. Comparison of adjacent forest, meadow and cropped field plots showed that land use has a strong impact on the degree of horizontal variation of soil enzyme activities and bacterial community structure. However, regardless of the land use, the variation of microbiological characteristics appeared not to have predictable spatial structure at 0.5-10 m. Temporal and soil depth-related patterns were studied in relation to plant growth in cropped soil. The results showed that most enzyme activities and microbial biomass have a clear decreasing trend in the top 40 cm soil profile and a temporal pattern during the growing season. A new procedure for sampling of soil microbiological characteristics based on stratified sampling and pre-characterisation of samples was developed. A practical example demonstrated the potential of the new procedure to reduce the analysis efforts involved in laborious microbiological measurements without loss of precision. The investigation of storage of soil samples revealed that freezing (-20 °C) of small sample aliquots retains the activity of hydrolytic enzymes and the structure of the bacterial community in different soil matrices relatively well whereas air-drying cannot be recommended as a storage method for soil microbiological properties due to large reductions in activity. Freezing below -70 °C was the preferred method of storage for samples with high organic matter content. Comparison of different direct DNA extraction methods showed that the cell lysis treatment has a strong impact on the molecular size of DNA obtained and on the bacterial community structure detected. An improved MPN method for the enumeration of soil naphthalene degraders was introduced as an alternative to more complex MPN protocols or the DNA-based quantification approach. The main advantage of the new method is the simple protocol and the possibility to analyse a large number of samples and replicates simultaneously.

Widening Perspectives of Teacher Education : Studies on theory-practice relationship, reflection, research and professional development

This dissertation examined the research-based teacher education at the University of Helsinki from different theoretical and practical perspectives. Five studies focused on these perspectives separately as well as overlappingly. Study I focused on the reflection process of graduating teacher students. The data consisted of essays the students wrote as their last assignment before graduating, where their assignment was to examine their development as researchers during their MA thesis research process. The results indicated that the teacher students had analysed their own development thoroughly during the process and that they had reflected on theoretical as well as practical educational matters. The results also pointed out that, in the students’ opinion, personally conducted research is a significant learning process. -- Study II investigated teacher students’ workplace learning and the integration of theory and practice in teacher education. The students’ interviews focused on their learning of teacher’s work prior to education. The interviewees’ responses concerning their ‘surviving’ in teaching prior to teacher education were categorized into three categories: learning through experiences, school as a teacher learning environment, and case-specific learning. The survey part of the study focused on integration of theory and practice within the education process. The results showed that the students who worked while they studied took advantage of the studies and applied them to work. They set more demanding teaching goals and reflected on their work more theoretically. -- Study III examined practical aspects of the teacher students’ MA thesis research as well as the integration of theory and practice in teacher education. The participants were surveyed using a web-based survey which dealt with the participants’ teacher education experiences. According to the results, most of the students had chosen a practical topic for their MA thesis, one arising from their work environment, and most had chosen a research topic that would develop their own teaching. The results showed that the integration of theory and practice had taken place in much of the course work, but most obviously in the practicum periods, and also in the courses concerning the school subjects. The majority felt that the education had in some way been successful with regards to integration. -- Study IV explored the idea of considering teacher students’ MA thesis research as professional development. Twenty-three teachers were interviewed on the subject of their experiences of conducting research about their own work as teachers. The results of the interviews showed that the reasons for choosing the MA thesis research topic were multiple: practical, theoretical, personal, professional reasons, as well as outside effect. The objectives of the MA thesis research, besides graduating, were actual projects, developing the ability to work as teachers, conducting significant research, and sharing knowledge of the topic. The results indicated that an MA thesis can function as a tool for professional development, for example in finding ways for adjusting teaching, increasing interaction skills, gaining knowledge or improving reflection on theory and/or practice, strengthening self-confidence as a teacher, increasing researching skills or academic writing skills, as well as becoming critical and being able to read scientific and academic literature. -- Study V analysed teachers’ views of the impact of practitioner research. According to the results, the interviewees considered the benefits of practitioner research to be many, affecting teachers, pupils, parents, the working community, and the wider society. Most of the teachers indicated that they intended to continue to conduct research in the future. The results also showed that teachers often reflected personally and collectively, and viewed this as important. -- These five studies point out that MA thesis research is and can be a useful tool for increasing reflection doing with personal and professional development, as well as integrating theory and practice. The studies suggest that more advantage could be taken of the MA thesis research project. More integration of working and studying could and should be made possible for teacher students. This could be done in various ways within teacher education, but the MA thesis should be seen as a pedagogical possibility.

Efficient Content-based Routing, Mobility-aware Topologies, and Temporal Subspace Matching

Event-based systems are seen as good candidates for supporting distributed applications in dynamic and ubiquitous environments because they support decoupled and asynchronous many-to-many information dissemination. Event systems are widely used, because asynchronous messaging provides a flexible alternative to RPC (Remote Procedure Call). They are typically implemented using an overlay network of routers. A content-based router forwards event messages based on filters that are installed by subscribers and other routers. The filters are organized into a routing table in order to forward incoming events to proper subscribers and neighbouring routers. This thesis addresses the optimization of content-based routing tables organized using the covering relation and presents novel data structures and configurations for improving local and distributed operation. Data structures are needed for organizing filters into a routing table that supports efficient matching and runtime operation. We present novel results on dynamic filter merging and the integration of filter merging with content-based routing tables. In addition, the thesis examines the cost of client mobility using different protocols and routing topologies. We also present a new matching technique called temporal subspace matching. The technique combines two new features. The first feature, temporal operation, supports notifications, or content profiles, that persist in time. The second feature, subspace matching, allows more expressive semantics, because notifications may contain intervals and be defined as subspaces of the content space. We also present an application of temporal subspace matching pertaining to metadata-based continuous collection and object tracking.

When sharing becomes a liability: An intellectual capital approach to describing the dichotomy of knowledge protection versus sharing in intra- and interorganizational relationships

The tension created when companies are collaborating with competitors – sometimes termed co-opetition - has been subject of research within the network approach. As companies are collaborating with competitors, they need to simultaneously share and protect knowledge. The opportunistic behavior and learning intent of the partner may be underestimated, and collaboration may involve significant risks of loss of competitive edge. Contrastingly, the central tenet within the Intellectual Capital approach is that knowledge grows as it flows. The person sharing does not lose the knowledge and therefore knowledge has doubled from a company’s point of view. Value is created through the interplay of knowledge flows between and within three forms of intellectual capital: human, structural and relational capital. These are the points of departure for the research conducted in this thesis. The thesis investigates the tension between collaboration and competition through an Intellectual Capital lens, by identifying the actions taken to share and protect knowledge in interorganizational collaborative relationships. More specifically, it explores the tension in knowledge flows aimed at protecting and sharing knowledge, and their effect on the value creation of a company. It is assumed, that as two companies work closely together, the collaborative relationship becomes intertwined between the two partners and the intellectual capital flows of both companies are affected. The research finds that companies commonly protect knowledge also in close and long-term collaborative relationships. The knowledge flows identified are both collaborative and protective, with the result that they sometimes are counteracting and neutralize each other. The thesis contributes to the intellectual capital approach by expanding the understanding of knowledge protection in interorganizational relationships in three ways. First, departing from the research on co-opetition it shifts the focus from the internal view of the company as a repository of intellectual capital onto the collaborative relationships between competing companies. Second, instead of the traditional collaborative and sharing point of departure, it takes a competitive and protective perspective. Third, it identifies the intellectual capital flows as assets or liabilities depending on their effect on the value creation of the company. The actions taken to protect knowledge in an interorganizational relationship may decrease the value created in the company, which would make them liabilities.