Delegating and Distributing Morality: Can We Inscribe Privacy Protection in a Machine?

This paper addresses the question of delegation of morality to a machine, through a consideration of whether or not non-humans can be considered to be moral. The aspect of morality under consideration here is protection of privacy. The topic is introduced through two cases where there was a failure in sharing and retaining personal data protected by UK data protection law, with tragic consequences. In some sense this can be regarded as a failure in the process of delegating morality to a computer database. In the UK, the issues that these cases raise have resulted in legislation designed to protect children which allows for the creation of a huge database for children. Paradoxically, we have the situation where we failed to use digital data in enforcing the law to protect children, yet we may now rely heavily on digital technologies to care for children. I draw on the work of Floridi, Sanders, Collins, Kusch, Latour and Akrich, a spectrum of work stretching from philosophy to sociology of technology and the “seamless web” or “actor–network” approach to studies of technology. Intentionality is considered, but not deemed necessary for meaningful moral behaviour. Floridi’s and Sanders’ concept of “distributed morality” accords with the network of agency characterized by actor–network approaches. The paper concludes that enfranchizing non-humans, in the shape of computer databases of personal data, as moral agents is not necessarily problematic but a balance of delegation of morality must be made between human and non-human actors

Deep transfer learning application for automated ischemic classification in posterior fossa CT images

Abstract—Computed Tomography (CT) imaging is one of the conventional tools used to diagnose ischemic in Posterior Fossa (PF). Radiologist commonly diagnoses ischemic in PF through CT imaging manually. However, such a procedure could be strenuous and time consuming for large scale images, depending on the expertise and ischemic visibility. With the rapid development of computer technology, automatic image classification based on Machine Learning (ML) is widely been developed as a second opinion to the ischemic diagnosis. The practical performance of ML is challenged by the emergence of deep learning applications in healthcare. In this study, we evaluate the performance of deep transfer learning models of Convolutional Neural Network (CNN); VGG-16, GoogleNet and ResNet-50 to classify the normal and abnormal (ischemic) brain CT images of PF. This is the first study that intensively studies the application of deep transfer learning for automated ischemic classification in the posterior part of brain CT images. The experimental results show that ResNet-50 is capable to achieve the highest accuracy performance in comparison to other proposed models. Overall, this automatic classification provides a convenient and time-saving tool for improving medical diagnosis

Integrated Environmental Process Planning for the Design & Manufacture of Automotive Components

Advanced Product Quality Planning (APQP) logic is widely used by manufacturers for the design and manufacture of automotive components. Manufacturers are increasingly finding difficulties to incorporate environmental considerations in the broad range of products that they manufacture. Therefore, there is a need for a systematic method for environmental process planning to evaluate product configurations and their associated environmental impact. The framework and models discussed in this paper can deal with a variety of product characteristics and environmental impacts through a selection of Environmental Performance Indicators (EPIs) for a final product configuration. The framework and models have been applied in a real-life application and have proven that changes in product design or process selection can reduce the product's environmental impact and increase process efficiency. Hence, manufacturers can use the framework and models during the Advanced Product Quality Planning (APQP) process to benchmark each product variation that they manufacture in a standardised manner and realise cost saving opportunities

Sublinearly space bounded iterative arrays

Iterative arrays (IAs) are a, parallel computational model with a sequential processing of the input. They are one-dimensional arrays of interacting identical deterministic finite automata. In this note, realtime-lAs with sublinear space bounds are used to accept formal languages. The existence of a proper hierarchy of space complexity classes between logarithmic anel linear space bounds is proved. Furthermore, an optimal spacc lower bound for non-regular language recognition is shown. Key words: Iterative arrays, cellular automata, space bounded computations, decidability questions, formal languages, theory of computatio

Team-oriented process programming

Team-oriented process programming promises to provide significant support for the planning, directing, and controlling of software engineering projects. In this paper we apply process programming to software engineering teams and show how this can provide powerful new capabilities for the management of software projects. We identify key issues which must be addressed to apply process programming to teams, and present our vision for team-oriented process programming

Ground Systems Development Environment (GSDE) interface requirements and prototyping plan

This report describes the data collection and requirements analysis effort of the Ground System Development Environment (GSDE) Interface Requirements study. It identifies potential problems in the interfaces among applications and processors in the heterogeneous systems that comprises the GSDE. It describes possible strategies for addressing those problems. It also identifies areas for further research and prototyping to demonstrate the capabilities and feasibility of those strategies and defines a plan for building the necessary software prototypes

Engineering polymer informatics: Towards the computer-aided design of polymers

The computer-aided design of polymers is one of the holy grails of modern chemical informatics and of significant interest for a number of communities in polymer science. The paper outlines a vision for the in silico design of polymers and presents an information model for polymers based on modern semantic web technologies, thus laying the foundations for achieving the vision