Closing the gap between guidance and practice, an investigation of the relevance of design guidance to practitioners using object-oriented technologies

This thesis investigates if object oriented guidance is relevant in practice, and how this affects software that is produced. This is achieved by surveying practitioners and studying how constructs such as interfaces and inheritance are used in open-source systems. Surveyed practitioners framed 'good design' in terms of impact on development and maintenance. Recognition of quality requires practitioner judgement (individually and as a group), and principles are valued over rules. Time constraints heighten sensitivity to the rework cost of poor design decisions. Examination of open source systems highlights the use of interface and inheritance. There is some evidence of 'textbook' use of these structures, and much use is simple. Outliers are widespread indicating a pragmatic approach. Design is found to reflect the pressures of practice - high-level decisions justify 'designed' structures and architecture, while uncertainty leads to deferred design decisions - simpler structures, repetition, and unconsolidated design. Sub-populations of structures can be identified which may represent common trade-offs. Useful insights are gained into practitioner attitude to design guidance. Patterns of use and structure are identified which may aid in assessment and comprehension of object oriented systems.This thesis investigates if object oriented guidance is relevant in practice, and how this affects software that is produced. This is achieved by surveying practitioners and studying how constructs such as interfaces and inheritance are used in open-source systems. Surveyed practitioners framed 'good design' in terms of impact on development and maintenance. Recognition of quality requires practitioner judgement (individually and as a group), and principles are valued over rules. Time constraints heighten sensitivity to the rework cost of poor design decisions. Examination of open source systems highlights the use of interface and inheritance. There is some evidence of 'textbook' use of these structures, and much use is simple. Outliers are widespread indicating a pragmatic approach. Design is found to reflect the pressures of practice - high-level decisions justify 'designed' structures and architecture, while uncertainty leads to deferred design decisions - simpler structures, repetition, and unconsolidated design. Sub-populations of structures can be identified which may represent common trade-offs. Useful insights are gained into practitioner attitude to design guidance. Patterns of use and structure are identified which may aid in assessment and comprehension of object oriented systems

Automated classification of three-dimensional reconstructions of coral reefs using convolutional neural networks

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hopkinson, B. M., King, A. C., Owen, D. P., Johnson-Roberson, M., Long, M. H., & Bhandarkar, S. M. Automated classification of three-dimensional reconstructions of coral reefs using convolutional neural networks. PLoS One, 15(3), (2020): e0230671, doi: 10.1371/journal.pone.0230671.Coral reefs are biologically diverse and structurally complex ecosystems, which have been severally affected by human actions. Consequently, there is a need for rapid ecological assessment of coral reefs, but current approaches require time consuming manual analysis, either during a dive survey or on images collected during a survey. Reef structural complexity is essential for ecological function but is challenging to measure and often relegated to simple metrics such as rugosity. Recent advances in computer vision and machine learning offer the potential to alleviate some of these limitations. We developed an approach to automatically classify 3D reconstructions of reef sections and assessed the accuracy of this approach. 3D reconstructions of reef sections were generated using commercial Structure-from-Motion software with images extracted from video surveys. To generate a 3D classified map, locations on the 3D reconstruction were mapped back into the original images to extract multiple views of the location. Several approaches were tested to merge information from multiple views of a point into a single classification, all of which used convolutional neural networks to classify or extract features from the images, but differ in the strategy employed for merging information. Approaches to merging information entailed voting, probability averaging, and a learned neural-network layer. All approaches performed similarly achieving overall classification accuracies of ~96% and >90% accuracy on most classes. With this high classification accuracy, these approaches are suitable for many ecological applications.This study was funded by grants from the Alfred P. Sloan Foundation (BMH, BR2014-049; https://sloan.org), and the National Science Foundation (MHL, OCE-1657727; https://www.nsf.gov). The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript

Modeling a description logic vocabulary for cancer research

AbstractThe National Cancer Institute has developed the NCI Thesaurus, a biomedical vocabulary for cancer research, covering terminology across a wide range of cancer research domains. A major design goal of the NCI Thesaurus is to facilitate translational research. We describe: the features of Ontylog, a description logic used to build NCI Thesaurus; our methodology for enhancing the terminology through collaboration between ontologists and domain experts, and for addressing certain real world challenges arising in modeling the Thesaurus; and finally, we describe the conversion of NCI Thesaurus from Ontylog into Web Ontology Language Lite. Ontylog has proven well suited for constructing big biomedical vocabularies. We have capitalized on the Ontylog constructs Kind and Role in the collaboration process described in this paper to facilitate communication between ontologists and domain experts. The artifacts and processes developed by NCI for collaboration may be useful in other biomedical terminology development efforts

A Semantic Information Management Approach for Improving Bridge Maintenance based on Advanced Constraint Management

Bridge rehabilitation projects are important for transportation infrastructures. This research proposes a novel information management approach based on state-of-the-art deep learning models and ontologies. The approach can automatically extract, integrate, complete, and search for project knowledge buried in unstructured text documents. The approach on the one hand facilitates implementation of modern management approaches, i.e., advanced working packaging to delivery success bridge rehabilitation projects, on the other hand improves information management practices in the construction industry

Deep learning with 3D and label geometry

A fine-grained understanding of an image is two-fold: visual understanding and semantic understanding. The former strives to understand the intrinsic properties of the object in the image, whereas the latter aims at associating the diverse objects with certain semantics. All of these form the basis of an in-depth understanding of images. Today’s default architectures of deep convolutional networks have already shown a remarkable ability in capturing the 2D visual appearances of images, and mapping visual content to semantic classes thereafter. However, research on fine-grained image understanding, such as inferring the intrinsic 3D information and more structured semantics, is less explored. In this thesis, we look at the problems by asking "How to better utilize geometry for better image understanding?" In the first part, we research visual image understanding with 3D geometry. We show that it is possible to automatically explain a variety of visual contents in the image with texture-free 3D shapes. Furthermore, we develop a deep learning framework to reliably recover a set of 3D geometric attributes, such as the pose of an object and the surface normal of its shape, from a 2D image. In the second part, we explore label geometry for semantic image understanding. We find that a set of image classification problems have geometrically similar probability spaces. Therefore, label geometry is introduced, unifying one-vs.-rest classification, multi-label classification, and out-of-distribution classification in one framework. Moreover, we show that learned hierarchical label geometries can balance the accuracy and specificity of an image classifier

HILT : High-Level Thesaurus Project. Phase IV and Embedding Project Extension : Final Report

Ensuring that Higher Education (HE) and Further Education (FE) users of the JISC IE can find appropriate learning, research and information resources by subject search and browse in an environment where most national and institutional service providers - usually for very good local reasons - use different subject schemes to describe their resources is a major challenge facing the JISC domain (and, indeed, other domains beyond JISC). Encouraging the use of standard terminologies in some services (institutional repositories, for example) is a related challenge. Under the auspices of the HILT project, JISC has been investigating mechanisms to assist the community with this problem through a JISC Shared Infrastructure Service that would help optimise the value obtained from expenditure on content and services by facilitating subject-search-based resource sharing to benefit users in the learning and research communities. The project has been through a number of phases, with work from earlier phases reported, both in published work elsewhere, and in project reports (see the project website: http://hilt.cdlr.strath.ac.uk/). HILT Phase IV had two elements - the core project, whose focus was 'to research, investigate and develop pilot solutions for problems pertaining to cross-searching multi-subject scheme information environments, as well as providing a variety of other terminological searching aids', and a short extension to encompass the pilot embedding of routines to interact with HILT M2M services in the user interfaces of various information services serving the JISC community. Both elements contributed to the developments summarised in this report

Second CLIPS Conference Proceedings, volume 1

Topics covered at the 2nd CLIPS Conference held at the Johnson Space Center, September 23-25, 1991 are given. Topics include rule groupings, fault detection using expert systems, decision making using expert systems, knowledge representation, computer aided design and debugging expert systems