An analysis of the application of AI to the development of intelligent aids for flight crew tasks

This report presents the results of a study aimed at developing a basis for applying artificial intelligence to the flight deck environment of commercial transport aircraft. In particular, the study was comprised of four tasks: (1) analysis of flight crew tasks, (2) survey of the state-of-the-art of relevant artificial intelligence areas, (3) identification of human factors issues relevant to intelligent cockpit aids, and (4) identification of artificial intelligence areas requiring further research

Robust 2D Assembly Sequencing via Geometric Planning with Learned Scores

To compute robust 2D assembly plans, we present an approach that combines geometric planning with a deep neural network. We train the network using the Box2D physics simulator with added stochastic noise to yield robustness scores--the success probabilities of planned assembly motions. As running a simulation for every assembly motion is impractical, we train a convolutional neural network to map assembly operations, given as an image pair of the subassemblies before and after they are mated, to a robustness score. The neural network prediction is used within a planner to quickly prune out motions that are not robust. We demonstrate this approach on two-handed planar assemblies, where the motions are one-step translations. Results suggest that the neural network can learn robustness to plan robust sequences an order of magnitude faster than physics simulation.Comment: Presented at the 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE

Review of Systems Engineering (SE) Methods and Their Application to Wave Energy Technology Development

The design of effective and economically viable wave energy devices involves complex decision-making about the product based on conceptual design information, including stakeholder requirements, functions, components and technical parameters. The great diversity of concepts makes it extremely difficult to create fair comparisons of the relative merits of the many different designs. Conventional design approaches have proved insufficient to guarantee wave energy technologies meet their technical and economic goals. Systems engineering can provide a suitable framework to overcome the obstacles towards a successful wave energy technology. The main objective of this work is to review the well-established systems engineering approaches that have been successfully implemented in complex engineering problems and to what extent they have been applied to wave energy technology development. The paper first reviews how system information can be organised in different design domains to guide the synthesis and analysis activities and the definition of requirements and metrics, as well as the search for solutions and decision-making. Then, an exhaustive literature review on the application of systems engineering approaches to wave energy development is presented per design domain. Finally, a set of conclusions is drawn, along with some suggestions for improving the effectiveness of wave energy technology development.Authors would like to thank the Basque Government through the research groups IT1314‐19 and GIU19/276 and the Scottish Government for the support of Wave Energy Scotland

Social technology and human health

human development, technology

Identifying disabilities in children by means of a brief 'observation of function' for use in developing countries

This study was an offshoot of a collaborative survey called the 'Rapid Epidemiological Assessment of Childhood Disabilities' (REA) undertaken in three developing countries, Bangladesh, Jamaica and Pakistan, aiming to develop a screening procedure for two-to-nine year old children for disabilities of movement, hearing, vision, speech, cognition and epilepsy. To facilitate physicians doing comprehensive neurodevelopmental assessments of large numbers of children within the community, this study aimed to verify whether a brief procedure of observing children perform a simple set of tasks, called the 'Observation of Function' (OF), could identify disability validly and reliably (first part of the study). Subsequently, the OF was used by community workers (CWs) doing field work, to verify whether they too could use it validly and reliably (second part of the study). The analysis of the first part was done on 1626 children from five sites in Bangladesh, who had either been screened positive by the REA study or assessed as controls. Over half of the total number of disabilities were identified by the procedure, including most serious problems. It did best for motor disabilities; hearing and vision were the least identified, especially isolated problems. Significantly more younger children were identified. The yield of the OF was best when combined with the mother's history. The CWs did not do as well with the procedure. Poor sensitivity in case identification was seen as an absence of 'internalized standards' of child development. However, some problems were identified consistently, as evidenced by the high reliability scores, suggesting future potential for improving the capacity of the CWs for using the OF. Thus this study suggests that the OF can be a valuable neuroepidemiological tool to be used by physicians during field work. It may also aid them in busy clinical settings to focus on function-specific evaluation. The value of involving CWs in the screening as well as the evaluatory (OF) stage of identifying childhood disabilities in developing countries holds practical significance, and ways of improving their further training is discussed

Getting Things Done: The Science behind Stress-Free Productivity

Allen (2001) proposed the “Getting Things Done” (GTD) method for personal productivity enhancement, and reduction of the stress caused by information overload. This paper argues that recent insights in psychology and cognitive science support and extend GTD’s recommendations. We first summarize GTD with the help of a flowchart. We then review the theories of situated, embodied and distributed cognition that purport to explain how the brain processes information and plans actions in the real world. The conclusion is that the brain heavily relies on the environment, to function as an external memory, a trigger for actions, and a source of affordances, disturbances and feedback. We then show how these principles are practically implemented in GTD, with its focus on organizing tasks into “actionable” external memories, and on opportunistic, situation-dependent execution. Finally, we propose an extension of GTD to support collaborative work, inspired by the concept of stigmergy

A blockchain-IoT platform for the smart pallet pooling management

Pallet management as a backbone of logistics and supply chain activities is essential to supply chain parties, while a number of regulations, standards and operational constraints are considered in daily operations. In recent years, pallet pooling has been unconventionally advocated to manage pallets in a closed-loop system to enhance the sustainability and operational effectiveness, but pitfalls in terms of service reliability, quality compliance and pallet limitation when using a single service provider may occur. Therefore, this study incorporates a decentralisation mechanism into the pallet management to formulate a technological eco-system for pallet pooling, namely Pallet as a Service (PalletaaS), raised by the foundation of consortium blockchain and Internet of things (IoT). Consortium blockchain is regarded as the blockchain 3.0 to facilitate more industrial applications, except cryptocurrency, and the synergy of integrating a consortium blockchain and IoT is thus investigated. The corresponding layered architecture is proposed to structure the system deployment in the industry, in which the location-inventory-routing problem for pallet pooling is formulated. To demonstrate the values of this study, a case analysis to illustrate the human–computer interaction and pallet pooling operations is conducted. Overall, this study standardises the decentralised pallet management in the closed-loop mechanism, resulting in a constructive impact to sustainable development in the logistics industry

A Guide for the Implementation of a Commnity-Based Instructional Model to Teach Students with Severe Handicaps

The need for and implementation of a community-based model for teaching language and communication skills to students with severe disabilities was studied. A guide was presented that includes a list of critical issues and solutions for a school district to consider prior to the implementation of a community-based instructional model. Suggestions and resources were included to be used by teachers to help make decisions about selecting appropriate instructional materials and strategies for teaching students with severe disabilities

Frustration in Biomolecules

Biomolecules are the prime information processing elements of living matter. Most of these inanimate systems are polymers that compute their structures and dynamics using as input seemingly random character strings of their sequence, following which they coalesce and perform integrated cellular functions. In large computational systems with a finite interaction-codes, the appearance of conflicting goals is inevitable. Simple conflicting forces can lead to quite complex structures and behaviors, leading to the concept of "frustration" in condensed matter. We present here some basic ideas about frustration in biomolecules and how the frustration concept leads to a better appreciation of many aspects of the architecture of biomolecules, and how structure connects to function. These ideas are simultaneously both seductively simple and perilously subtle to grasp completely. The energy landscape theory of protein folding provides a framework for quantifying frustration in large systems and has been implemented at many levels of description. We first review the notion of frustration from the areas of abstract logic and its uses in simple condensed matter systems. We discuss then how the frustration concept applies specifically to heteropolymers, testing folding landscape theory in computer simulations of protein models and in experimentally accessible systems. Studying the aspects of frustration averaged over many proteins provides ways to infer energy functions useful for reliable structure prediction. We discuss how frustration affects folding, how a large part of the biological functions of proteins are related to subtle local frustration effects and how frustration influences the appearance of metastable states, the nature of binding processes, catalysis and allosteric transitions. We hope to illustrate how Frustration is a fundamental concept in relating function to structural biology.Comment: 97 pages, 30 figure