Benjamin Green

Yixiao Zhang, Adam Kortylewski, Qing Liu et al.

The field of computational pathology has witnessed great advancements since deep neural networks have been widely applied. These networks usually require large numbers of annotated data to train vast parameters. However, it takes significant effort to annotate a large histopathology dataset. We introduce a light-weight and interpretable model for nuclei detection and weakly-supervised segmentation. It only requires annotations on isolated nucleus, rather than on all nuclei in the dataset. Besides, it is a generative compositional model that first locates parts of nucleus, then learns the spatial correlation of the parts to further locate the nucleus. This process brings interpretability in its prediction. Empirical results on an in-house dataset show that in detection, the proposed method achieved comparable or better performance than its deep network counterparts, especially when the annotated data is limited. It also outperforms popular weakly-supervised segmentation methods. The proposed method could be an alternative solution for the data-hungry problem of deep learning methods.

Uchenna D Ani, Jeremy M Watson, Benjamin Green et al.

This paper presents a mapping framework for design factors and implementation process for building credible Industrial Control Systems (ICS) security testbeds. The resilience of ICSs has become a critical concern to operators and governments following widely publicised cyber security events. The inability to apply conventional Information Technology security practice to ICSs further compounds challenges in adequately securing critical systems. To overcome these challenges, and do so without impacting live environments, testbeds for the exploration, development and evaluation of security controls are widely used. However, how a testbed is designed and its attributes, can directly impact not only its viability but also its credibility as a whole. Through a combined systematic and thematic analysis and mapping of ICS security testbed design attributes, this paper suggests that the expertise of human experimenters, design objectives, the implementation approach, architectural coverage, core characteristics, and evaluation methods; are considerations that can help establish or enhance confidence, trustworthiness and acceptance; thus, credibility of ICS security testbeds.