Imputation of single-tree attributes using airborne laser scanning-based height, intensity, and alpha shape metrics

Forest inventories based on single-tree interpretation of airborne laser scanning (ALS) data often rely on an allometric estimation chain in which inaccuracies in the estimates of the diameter at breast height (DBH) propagate to other characteristics of interest such as the stem volume. Our purpose was to test nearest neighbor imputation by the k-Most Similar Neighbor (k-MSN) and the Random Forest (RF) methods for the simultaneous estimation of species, DBH, height and stem volume using ALS data. The predictors included computational alpha shape metrics and variables based on the height and intensity distributions in the ALS data. Separate data sets covering 1898 and 1249 dominant to intermediate trees in a typical Scandinavian stand structure were used for training and validation, respectively. RF proved to be a flexible method with an ability to handle 1846 predictors with no need for their reduction. Classification of Scots pine, Norway spruce and deciduous trees showed an accuracy of 78%, and the estimates of DBH, height and volume had root mean square errors of 13%, 3%, and 31%, respectively, when evaluated against the validation data. The two selection strategies implemented here reduced the number of candidate variables effectively without any substantial effect on the accuracy relative to the use of all predictors. Differences in k-MSN and RF imputations were marginal when the reduced sets of variables were used. Estimation accuracies could be maintained practically unchanged with only 12.5% of the initial reference data (237 trees), provided the distribution of the observations was similar in the reference and target data. Since we used information collected in the field for extracting the ALS point clouds for individual trees, our results represent an optimal case and should nevertheless be validated against automated tree delineation.     

Perspectives on personal learning environments held by vocational students

This article focuses on personal learning environments (PLEs). The idea with PLEs is to put students in a more central position in the learning process by allowing them to design their own learning environments and by emphasising the self-regulated nature of the learning. This study describes the structure, functions and challenges of PLEs made by 33 students from vocational and polytechnic level schools in Eastern Finland after the first year of using them. Document and artefact analysis revealed that students built their PLEs for: mirroring the conventional learning environment; as an environment for reflection; as an environment to showcase skills; and as an environment for collaboration and networking. Student reflections indicate that building and using a PLE is a challenging task which requires specific teacher and pedagogical support. Designing a PLE demands both ICT skills and an awareness of one’s own learning methods.     

Extracting Conditionally Heteroskedastic Components using Independent Component Analysis

In the independent component model, the multivariate data are assumed to be a mixture of mutually independent latent components. The independent component analysis (ICA) then aims at estimating these latent components. In this article, we study an ICA method which combines the use of linear and quadratic autocorrelations to enable efficient estimation of various kinds of stationary time series. Statistical properties of the estimator are studied by finding its limiting distribution under general conditions, and the asymptotic variances are derived in the case of ARMA-GARCH model. We use the asymptotic results and a finite sample simulation study to compare different choices of a weight coefficient. As it is often of interest to identify all those components which exhibit stochastic volatility features we suggest a test statistic for this problem. We also show that a slightly modified version of the principal volatility component analysis can be seen as an ICA method. Finally, we apply the estimators in analysing a data set which consists of time series of exchange rates of seven currencies to US dollar. Supporting information including proofs of the theorems is available online.     

Plant sterols in vegetables,fruits and berries

The plant sterol contents of the most important vegetables, fruits and berries available in Finland were determined by capillary gas chromatography. The sample preparation procedure included both acid and alkaline hydrolysis to liberate sterols from their conjugates. The plant sterol contents of fresh vegetables ranged from 51 to 370 mg kg^?1 fresh weight (fw) in samples obtained from retail sale. The highest contents (>300 mg kg^?1) were measured in broccoli, Brussels sprouts, cauliflower and dill and the lowest (51 mg kg^?1) in potato. The range of sterol contents on a dry weight (dw) basis was high, 246–4100 mg kg^?1 dw. Considerable variation was also observed when individual samples of some vegetables were compared. Sitosterol was the main sterol (proportion 43–86%) in all vegetables except cucumber and spinach, in which Δ⁷‐sterols dominated. The total sterol contents were in the range 116–228 mg kg^?1 fw in all fresh fruits except avocado, which contained more sterols, 752 mg kg^?1 fw. In fresh berries the corresponding range was 60–279 m kg^?1 fw. The wild berries lingonberry and blueberry were better plant sterol sources than the cultivated berries blackcurrant, redcurrant and strawberry. In fruits and berries the proportion of sitosterol ranged from 61–93% total sterols. On the basis of the results, the contribution of vegetables, fruits and berries to the total average daily plant sterol intake was estimated to be ca 60 mg. © 2003 Society of Chemical Industry     

Improvements and Modifications to Room‐Temperature Fabrication Method for Dielectric Li2MoO4 Ceramics

Dielectric properties of lithium molybdate disks fabricated by moistening water‐soluble Li₂MoO₄ powder, compressing it, and postprocessing the samples at 120°C, were improved by the optimization of powder particle size, sample pressing pressure, and postprocessing time. It appeared that the postprocessing temperature of the Li₂MoO₄ ceramics could be chosen so as to be applicable to the associated integrated materials as long as the postprocessing time was adequately adjusted to ensure the removal of the residual water. In addition, the dielectric properties of Li₂MoO₄ ceramic were modified with an inclusion of suitable additives. For example, at 1 GHz the relative permittivity of Li₂MoO₄ disks fabricated at room temperature and postprocessed at 120°C was increased from 6.4 to 8.8 with an addition of 10 vol% of rutile TiO₂ and to 9.7 with an addition of 10 vol% of BaTiO₃. At the same time the loss tangent value increased from 0.0006 to 0.0014 and to 0.011, respectively.     

Fast direct solution of the Helmholtz equation with a perfectly matched layer or an absorbing boundary condition

We consider the efficient numerical solution of the Helmholtz equation in a rectangular domain with a perfectly matched layer (PML) or an absorbing boundary condition (ABC). Standard bilinear (trilinear) finite‐element discretization on an orthogonal mesh leads to a separable system of linear equations for which we describe a cyclic reduction‐type fast direct solver. We present numerical studies to estimate the reflection of waves caused by an absorbing boundary and a PML, and we optimize certain parameters of the layer to minimize the reflection. Copyright © 2003 John Wiley & Sons, Ltd.     

Repetitive control of synchronized operations for process applications

Repetitive control (RC) algorithms for a plant, which contain pairs of complex conjugate poles at low frequency, resulting in a resonant system, is the subject area of this paper where the experimental results given are for a gantry robot and conveyor system in which the gantry is required to transfer payloads to a constant velocity conveyor by performing a repeating ‘pick and place’ operation. Initially, the gantry robot is controlled by means of a PID feedback controller in parallel with a proportional (P‐type) repetitive feed‐forward loop, while the conveyor operates under proportional feedback control. It is found that the RC system is unable to achieve long‐term performance. The performance degrades within a relatively small number of repetitions due to the build up of resonant frequencies in the learning loop. To prevent this, a batch aliasing technique, originally developed for iterative learning control, is modified to work in the RC framework, and is implemented in real‐time. The superior performance potential of the aliasing system is demonstrated experimentally. In the second part of this paper, multi‐machine systems, are considered where the critical new factor is the relative error between the conveyor and the robot. Here a second supervisory learning loop is proposed for use to shift the reference trajectory of one machine so that the relative placement error is also reduced. Again, supporting experimental results are given. Copyright © 2006 John Wiley & Sons, Ltd.     

P‐type iterative learning control for systems that contain resonance

The effect of iterative learning control (ILC) on a plant containing resonance has been experimentally investigated using an industrial gantry robot. The plant is controlled by a PID controller and a P‐type learning controller in a parallel configuration. It is demonstrated that the learning controller can cause the amplitude of resonant frequencies to grow at each trial, leading to instability. The reasons for this growth are analysed both theoretically and experimentally. In order to solve the problem with a resonance, a straightforward aliasing technique is developed which is experimentally shown to suppress the increase of resonant amplitudes. The novel aliasing technique is compared with three filtering methods, the aliasing technique giving the best experimental performance. Finally, it is found that additional velocity feedback combined with the aliasing technique can further help to limit the effect of residual resonance. Due to the straightforward implementation of these algorithms, they should be highly applicable to industrial systems. Copyright © 2005 John Wiley & Sons, Ltd.     

Kinds of mutations induced by 3-chloro-4-(dichloromethyl)-5-hydroxy-2(5H)-furanone (MX) in the hprt gene of Chinese hamster ovary cells

The kinds of mutations induced by 3-chloro-4-(dichloromethyl)-5-hydroxy-2(5H)-furanone (MX) in the protein coding region of the hprt gene of Chinese hamster ovary (CHO) cells were determined by direct sequencing of polymerase chain reaction (PCR)-amplified cDNA. Primary mutations were found in 15 of 19 of the mutants: 11 were G:C-->T:A transversions, two were A:T-->T:A transversions and two were deletions of single G:C base pairs (-1 frameshifts). The remaining four mutants had large alterations in the cDNA that were explained by mRNA splicing errors. A group of control mutants had more diverse hprt cDNA alterations than MX-induced mutants. Transversions yielding an A:T base pair were the predominant type of MX-induced mutations, in agreement with previous findings in bacteria. This specificity may be explained by the 'A rule', that DNA polymerases preferentially insert adenine nucleotides opposite non-instructional lesions.