High-precision diode-laser-based temperature measurement for air refractive index compensation

We present a laser-based system to measure the refractive index of air over a long path length. In optical distance measurements it is essential to know the refractive index of air with high accuracy. Commonly, the refractive index of air is calculated from the properties of the ambient air using either Ciddor or Edlén equations, where the dominant uncertainty component is in most cases the air temperature. The method developed in this work utilises direct absorption spectroscopy of oxygen to measure the average temperature of air and of water vapor to measure relative humidity. The method allows measurement of temperature and humidity over the same beam path as in optical distance measurement, providing spatially well matching data. Indoor and outdoor measurements demonstrate the effectiveness of the method. In particular, we demonstrate an effective compensation of the refractive index of air in an interferometric length measurement at a time-variant and spatially non-homogenous temperature over a long time period. Further, we were able to demonstrate 7 mK RMS noise over a 67 m path length using 120 s sample time. To our knowledge, this is the best temperature precision reported for a spectroscopic temperature measurement.

Pre-harvest measurement of pine stands for sawing production planning.

To enhance the utilization of the wood, the sawmills are forced to place more emphasis on planning to master the whole production chain from the forest to the end product. One significant obstacle to integrating the forest-sawmill-market production chain is the lack of appropriate information about forest stands. Since the wood procurement point of view in forest planning systems has been almost totally disregarded there has been a great need to develop an easy and efficient pre-harvest measurement method, allowing separate measurement of stands prior to harvesting. The main purpose of this study was to develop a measurement method for pine stands which forest managers could use in describing the properties of the standing trees for sawing production planning. Study materials were collected from ten Scots pine stands (Pinus sylvestris) located in North Häme and South Pohjanmaa, in southern Finland. The data comprise test sawing data on 314 pine stems, dbh and height measures of all trees and measures of the quality parameters of pine sawlog stems in all ten study stands as well as the locations of all trees in six stands. The study was divided into four sub-studies which deal with pine quality prediction, construction of diameter and dead branch height distributions, sampling designs and applying height and crown height models. The final proposal for the pre-harvest measurement method is a synthesis of the individual sub-studies. Quality analysis resulted in choosing dbh, distance from stump height to the first dead branch (dead branch height), crown height and tree height as the most appropriate quality characteristics of Scots pine. Dbh and dead branch height are measured from each pine sample tree while height and crown height are derived from dbh measures by aid of mixed height and crown height models. Pine and spruce diameter distribution as well as dead branch height distribution are most effectively predicted by the kernel function. Roughly 25 sample trees seems to be appropriate in pure pine stands. In mixed stands the number of sample trees needs to be increased in proportion to the intensity of pines in order to attain the same level of accuracy.

Routine Measurement of Health-Related Quality of Life in Assessing Cost-Effectiveness in Secondary Health Care

Aims: The aims of this study were 1) to identify and describe health economic studies that have used quality-adjusted life years (QALYs) based on actual measurements of patients' health-related quality of life (HRQoL); 2) to test the feasibility of routine collection of health-related quality of life (HRQoL) data as an indicator of effectiveness of secondary health care; and 3) to establish and compare the cost-utility of three large-volume surgical procedures in a real-world setting in the Helsinki University Central Hospital, a large referral hospital providing secondary and tertiary health-care services for a population of approximately 1.4 million. Patients and methods: So as to identify studies that have used QALYs as an outcome measure, a systematic search of the literature was performed using the Medline, Embase, CINAHL, SCI and Cochrane Library electronic databases. Initial screening of the identified articles involved two reviewers independently reading the abstracts; the full-text articles were also evaluated independently by two reviewers, with a third reviewer used in cases where the two reviewers could not agree a consensus on which articles should be included. The feasibility of routinely evaluating the cost-effectiveness of secondary health care was tested by setting up a system for collecting HRQoL data on approximately 4 900 patients' HRQoL before and after operative treatments performed in the hospital. The HRQoL data used as an indicator of treatment effectiveness was combined with diagnostic and financial indicators routinely collected in the hospital. To compare the cost-effectiveness of three surgical interventions, 712 patients admitted for routine operative treatment completed the 15D HRQoL questionnaire before and also 3-12 months after the operation. QALYs were calculated using the obtained utility data and expected remaining life years of the patients. Direct hospital costs were obtained from the clinical patient administration database of the hospital and a cost-utility analysis was performed from the perspective of the provider of secondary health care services. Main results: The systematic review (Study I) showed that although QALYs gained are considered an important measure of the effectiveness of health care, the number of studies in which QALYs are based on actual measurements of patients' HRQoL is still fairly limited. Of the reviewed full-text articles, only 70 reported QALYs based on actual before after measurements using a valid HRQoL instrument. Collection of simple cost-effectiveness data in secondary health care is feasible and could easily be expanded and performed on a routine basis (Study II). It allows meaningful comparisons between various treatments and provides a means for allocating limited health care resources. The cost per QALY gained was 2 770 for cervical operations and 1 740 for lumbar operations. In cases where surgery was delayed the cost per QALY was doubled (Study III). The cost per QALY ranges between subgroups in cataract surgery (Study IV). The cost per QALY gained was 5 130 for patients having both eyes operated on and 8 210 for patients with only one eye operated on during the 6-month follow-up. In patients whose first eye had been operated on previous to the study period, the mean HRQoL deteriorated after surgery, thus precluding the establishment of the cost per QALY. In arthroplasty patients (Study V) the mean cost per QALY gained in a one-year period was 6 710 for primary hip replacement, 52 270 for revision hip replacement, and 14 000 for primary knee replacement. Conclusions: Although the importance of cost-utility analyses has during recent years been stressed, there are only a limited number of studies in which the evaluation is based on patients own assessment of the treatment effectiveness. Most of the cost-effectiveness and cost-utility analyses are based on modeling that employs expert opinion regarding the outcome of treatment, not on patient-derived assessments. Routine collection of effectiveness information from patients entering treatment in secondary health care turned out to be easy enough and did not, for instance, require additional personnel on the wards in which the study was executed. The mean patient response rate was more than 70 %, suggesting that patients were happy to participate and appreciated the fact that the hospital showed an interest in their well-being even after the actual treatment episode had ended. Spinal surgery leads to a statistically significant and clinically important improvement in HRQoL. The cost per QALY gained was reasonable, at less than half of that observed for instance for hip replacement surgery. However, prolonged waiting for an operation approximately doubled the cost per QALY gained from the surgical intervention. The mean utility gain following routine cataract surgery in a real world setting was relatively small and confined mostly to patients who had had both eyes operated on. The cost of cataract surgery per QALY gained was higher than previously reported and was associated with considerable degree of uncertainty. Hip and knee replacement both improve HRQoL. The cost per QALY gained from knee replacement is two-fold compared to hip replacement. Cost-utility results from the three studied specialties showed that there is great variation in the cost-utility of surgical interventions performed in a real-world setting even when only common, widely accepted interventions are considered. However, the cost per QALY of all the studied interventions, except for revision hip arthroplasty, was well below 50 000, this figure being sometimes cited in the literature as a threshold level for the cost-effectiveness of an intervention. Based on the present study it may be concluded that routine evaluation of the cost-utility of secondary health care is feasible and produces information essential for a rational and balanced allocation of scarce health care resources.

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.

Wind drift of snowfall between the radar volume and ground

This study evaluates how the advection of precipitation, or wind drift, between the radar volume and ground affects radar measurements of precipitation. Normally precipitation is assumed to fall vertically to the ground from the contributing volume, and thus the radar measurement represents the geographical location immediately below. In this study radar measurements are corrected using hydrometeor trajectories calculated from measured and forecasted winds, and the effect of trajectory-correction on the radar measurements is evaluated. Wind drift statistics for Finland are compiled using sounding data from two weather stations spanning two years. For each sounding, the hydrometeor phase at ground level is estimated and drift distance calculated using different originating level heights. This way the drift statistics are constructed as a function of range from radar and elevation angle. On average, wind drift of 1 km was exceeded at approximately 60 km distance, while drift of 10 km was exceeded at 100 km distance. Trajectories were calculated using model winds in order to produce a trajectory-corrected ground field from radar PPI images. It was found that at the upwind side from the radar the effective measuring area was reduced as some trajectories exited the radar volume scan. In the downwind side areas near the edge of the radar measuring area experience improved precipitation detection. The effect of trajectory-correction is most prominent in instant measurements and diminishes when accumulating over longer time periods. Furthermore, measurements of intensive and small scale precipitation patterns benefit most from wind drift correction. The contribution of wind drift on the uncertainty of estimated Ze (S) - relationship was studied by simulating the effect of different error sources to the uncertainty in the relationship coefficients a and b. The overall uncertainty was assumed to consist of systematic errors of both the radar and the gauge, as well as errors by turbulence at the gauge orifice and by wind drift of precipitation. The focus of the analysis is error associated with wind drift, which was determined by describing the spatial structure of the reflectivity field using spatial autocovariance (or variogram). This spatial structure was then used with calculated drift distances to estimate the variance in radar measurement produced by precipitation drift, relative to the other error sources. It was found that error by wind drift was of similar magnitude with error by turbulence at gauge orifice at all ranges from radar, with systematic errors of the instruments being a minor issue. The correction method presented in the study could be used in radar nowcasting products to improve the estimation of visibility and local precipitation intensities. The method however only considers pure snow, and for operational purposes some improvements are desirable, such as melting layer detection, VPR correction and taking solid state hydrometeor type into account, which would improve the estimation of vertical velocities of the hydrometeors.