Object-oriented cohesion as a surrogate of software comprehension: An empirical study

The concept of software cohesion in both the procedural and object-oriented paradigm is well known and documented. What is not so well known or documented is the perception of what empirically constitutes a cohesive 'unit' by software engineers. In this paper, we describe an empirical investigation using object-oriented (OO) classes as a basis. Twenty-four subjects (drawn from IT experienced and IT inexperienced groups) were asked to rate ten classes sampled from two industrial systems in terms of their overall cohesiveness; a class environment was used to carry out the study. Four key results were observed. Firstly, class size (when expressed in terms of number of methods) did not tend to influence the perception of cohesion by any subjects. Secondly, well-commented classes were rated most highly amongst both IT experienced and inexperienced subjects. Thirdly, the empirical study suggests that cohesion comprises a combination of various class factors including low coupling, small numbers of attributes and well-commented methods, rather than any single, individual class feature per se. Finally, the research supports the view that cohesion is a subjective concept reflecting a cognitive combination of class features; as such it is a surrogate for class comprehension

Literature-based priors for gene regulatory networks

Motivation: The use of prior knowledge to improve gene regulatory network modelling has often been proposed. In this paper we present the first research on the massive incorporation of prior knowledge from literature for Bayesian network learning of gene networks. As the publication rate of scientific papers grows, updating online databases, which have been proposed as potential prior knowledge in past rese-arch, becomes increasingly challenging. The novelty of our approach lies in the use of gene-pair association scores that describe the over-lap in the contexts in which the genes are mentioned, generated from a large database of scientific literature, harnessing the information contained in a huge number of documents into a simple, clear format. Results: We present a method to transform such literature-based gene association scores to network prior probabilities, and apply it to learn gene sub-networks for yeast, E. coli and Human organisms. We also investigate the effect of weighting the influence of the prior know-ledge. Our findings show that literature-based priors can improve both the number of true regulatory interactions present in the network and the accuracy of expression value prediction on genes, in comparison to a network learnt solely from expression data. Networks learnt with priors also show an improved biological interpretation, with identified subnetworks that coincide with known biological pathways. Contact

Extracting predictive models from marked-p free-text documents at the Royal Botanic Gardens, Kew, London

In this paper we explore the combination of text-mining, un-supervised and supervised learning to extract predictive models from a corpus of digitised historical floras. These documents deal with the nomenclature, geographical distribution, ecology and comparative morphology of the species of a region. Here we exploit the fact that portions of text in the floras are marked up as different types of trait and habitat. We infer models from these different texts that can predict different habitat-types based upon the traits of plant species. We also integrate plant taxonomy data in order to assist in the validation of our models. We have shown that by clustering text describing the habitat of different floras we can identify a number of important and distinct habitats that are associated with particular families of species along with statistical significance scores. We have also shown that by using these discovered habitat-types as labels for supervised learning we can predict them based upon a subset of traits, identified using wrapper feature selection

Spiral cracks in drying precipitates

We investigate the formation of spiral crack patterns during the desiccation of thin layers of precipitates in contact with a substrate. This symmetry-breaking fracturing mode is found to arise naturally not from torsion forces, but from a propagating stress front induced by the fold-up of the fragments. We model their formation mechanism using a coarse-grain model for fragmentation and successfully reproduce the spiral cracks. Fittings of experimental and simulation data show that the spirals are logarithmic, corresponding to constant deviation from a circular crack path. Theoretical aspects of the logarithmic spirals are discussed. In particular we show that this occurs generally when the crack speed is proportional to the propagating speed of stress front.Comment: 4 pages, 5 figures, RevTe

Alleviation of pressure pulse effects for trains entering tunnels. Volume 1: Summary

The degree to which it is possible to attenuate the effects of pressure pulses on the passengers in trains entering tunnels by modifying the normally abrupt portal of a constant-diameter single track tunnel was investigated. Although the suggested modifications to the tunnel entrance portal may not appreciably decrease the magnitude of the pressure rise, they are very effective in reducing the discomfort to the human ear by substantially decreasing the rate of pressure rise to that which the normal ear can accommodate. Qualitative comparison was made of this portal modification approach with other approaches: decreasing the train speed or sealing the cars. The optimum approach, which is dependent upon the conditions and requirements of each particular rail system, is likely to be the portal modification one for a rapid rail mass transit system

Algorithmic Bias? An Empirical Study of Apparent Gender-Based Discrimination in the Display of STEM Career Ads

We explore data from a field test of how an algorithm delivered ads promoting job opportunities in the Science, Technology, Engineering and Math (STEM) fields. This ad was explicitly intended to be gender-neutral in its delivery. Empirically, however, fewer women saw the ad than men. This happened because younger women are a prized demographic and are more expensive to show ads to. An algorithm which simply optimizes cost-effectiveness in ad delivery will deliver ads that were intended to be gender-neutral in an apparently discriminatory way, due to crowding out. We show that this empirical regularity extends to other major digital platforms

Concentration of atomic hydrogen diffused into silicon in the temperature range 900–1300 °C

Boron-doped Czochralski silicon samples with [B]~1017 cm−3 have been heated at various temperatures in the range 800–1300 °C in an atmosphere of hydrogen and then quenched. The concentration of [H-B] pairs was measured by infrared localized vibrational mode spectroscopy. It was concluded that the solubility of atomic hydrogen is greater than [Hs] = 5.6 × 1018 exp( − 0.95 eV/kT)cm−3 at the temperatures investigated

Five New Species of Orchesella (Collembola: Entomobryidae)

This paper describes 5 species of the genus Orchesella (Collembola: Entomobryidae) new to science. The chaetotaxy of the abdomen as well as the antennal pin seta are used systematically for the first time in the taxonomy of the genus

Temperature effects on the 15-85-micron spectra of olivines and pyroxenes

Far-infrared spectra of laboratory silicates are normally obtained at room temperature even though the grains responsible for astronomical silicate emission bands seen at wavelengths >20 micron are likely to be at temperatures below ~150 K. In order to investigate the effect of temperature on silicate spectra, we have obtained absorption spectra of powdered forsterite and olivine, along with two orthoenstatites and diopside clinopyroxene, at 3.5+-0.5 K and at room temperature (295+-2K). To determine the changes in the spectra the resolution must be increased from 1 to 0.25 cm^-1 at both temperatures since a reduction in temperature reduces the phonon density, thereby reducing the width of the infrared peaks. Several bands observed at 295 K split at 3.5 K. At 3.5 K the widths of isolated single bands in olivine, enstatites and diopside are ~ 90% of their 295 K-widths. However, in forsterite the 3.5-K-widths of the 31-, 49- and 69-micron bands are, respectively, 90%, 45% and 31% of their 295 K widths. Due to an increase in phonon energy as the lattice contracts, 3.5-K-singlet peaks occur at shorter wavelengths than do the corresponding 295-K peaks; the magnitude of the wavelength shift increases from \~ 0-0.2 micron at 25 micron to ~0.9 micron at 80 micron. Changes in the relative absorbances of spectral peaks are also observed. The temperature dependence of lambda_pk and bandwidth shows promise as a means to deduce characteristic temperatures of mineralogically distinct grain populations. In addition, the observed changes in band strength with temperature will affect estimates of grain masses and relative mineral abundances inferred using room-temperature laboratory data.Comment: 11 pages, 7 figures including figures 3a and 3b. includes latex and eps files. Accepted by MNRAS on 15th March 200