Adaptive Bacteria Colony Picking in Unstructured Environments Using Intensity Histogram and Unascertained LS-SVM Classifier

Features analysis is an important task which can significantly affect the performance of automatic bacteria colony picking. Unstructured environments also affect the automatic colony screening. This paper presents a novel approach for adaptive colony segmentation in unstructured environments by treating the detected peaks of intensity histograms as a morphological feature of images. In order to avoid disturbing peaks, an entropy based mean shift filter is introduced to smooth images as a preprocessing step. The relevance and importance of these features can be determined in an improved support vector machine classifier using unascertained least square estimation. Experimental results show that the proposed unascertained least square support vector machine (ULSSVM) has better recognition accuracy than the other state-of-the-art techniques, and its training process takes less time than most of the traditional approaches presented in this paper.

Freeing order processes in Northern Ireland: Painfully slow

Greg Kelly and Dominic McSherry describe the timescales involved in achieving freeing orders for 23 children in Northern Ireland between 1996 and 1999. There was delay at all stages in the process. The delays were particularly pronounced in social services and social services/legal services processes. The authors conclude that if adoption is to be made available to more children from state care, current arrangements, including legislation, will need revision and reform.