Leaf galls in our native trees and shrubs

Plant galls constitute a branch of study and research which has been to me a subject of much interest for some time. At the start of this work, it was intended to include Plant galls in general, but after some months this was found to be too comprehensive a field and would in fact take a great many years to study fully. Even leaf galls alone, both of herbs and trees provide so large a field of investigation that ultimately I decided to confine my attention to those or our native trees and shrubs. Upon looking up the literature on this subject, it will be found that in nearly all cases, either the gall is described fully and mere mention made or the agent concerned in its production, or vice versa. This state of things is most unsatisfactory, as in studying galls, both the gall-maker and the gall formation must be examined in detail before it is safe to apply nomenclature. This work, therefore, sets out to give accurate and scientific descriptions of both galls and gall-makers. The difficulties encountered are manifold; firstly, our trees are all deciduous, hence, the collecting period is necessarily restricted to that time of the year between the appearance of the buds and the fall of the leaf. Secondly, the rearing of imagines is always difficult, especially in the case or the autumn gall; more will be said on this matter later. Lastly, due to war-time conditions much trouble was experienced in obtaining suitable literature and many invaluable books on this subject were unprocurable. The Plates at the back have all been copied from original material except in the case or the Phytoptid mites which have been sketched with the help of illustrations, the reason for this being the difficulty of making suitable mounts of these minute creatures, Where possible all stages or at least larva and imago have been sketched, together with the host plant and the type of gall-formation produced. Slides have also been made of most larvae and the imagines attached to cards and pinned on to pith or cork in the usual manner.

Power system parameters forecasting using Hilbert-Huang transform and machine learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.