Scientific intuition inspired by machine learning-generated hypotheses

Machine learning with application to questions in the physical sciences has become a widely used tool, successfully applied to classification, regression and optimization tasks in many areas. Research focus mostly lies in improving the accuracy of the machine learning models in numerical predictions, while scientific understanding is still almost exclusively generated by human researchers analysing numerical results and drawing conclusions. In this work, we shift the focus on the insights and the knowledge obtained by the machine learning models themselves. In particular, we study how it can be extracted and used to inspire human scientists to increase their intuitions and understanding of natural systems. We apply gradient boosting in decision trees to extract human-interpretable insights from big data sets from chemistry and physics. In chemistry, we not only rediscover widely know rules of thumb but also find new interesting motifs that tell us how to control solubility and energy levels of organic molecules. At the same time, in quantum physics, we gain new understanding on experiments for quantum entanglement. The ability to go beyond numerics and to enter the realm of scientific insight and hypothesis generation opens the door to use machine learning to accelerate the discovery of conceptual understanding in some of the most challenging domains of science

Scientific intuition inspired by machine learning-generated hypotheses

Machine learning with application to questions in the physical sciences has become a widely used tool, successfully applied to classification, regression and optimization tasks in many areas. Research focus mostly lies in improving the accuracy of the machine learning models in numerical predictions, while scientific understanding is still almost exclusively generated by human researchers analysing numerical results and drawing conclusions. In this work, we shift the focus on the insights and the knowledge obtained by the machine learning models themselves. In particular, we study how it can be extracted and used to inspire human scientists to increase their intuitions and understanding of natural systems. We apply gradient boosting in decision trees to extract human-interpretable insights from big data sets from chemistry and physics. In chemistry, we not only rediscover widely know rules of thumb but also find new interesting motifs that tell us how to control solubility and energy levels of organic molecules. At the same time, in quantum physics, we gain new understanding on experiments for quantum entanglement. The ability to go beyond numerics and to enter the realm of scientific insight and hypothesis generation opens the door to use machine learning to accelerate the discovery of conceptual understanding in some of the most challenging domains of science

A workflow demonstrator for processing catalysis research data

The UK Catalysis Hub (UKCH) is designing a virtual research environment to support data processing and analysis, the Catalysis Research Workbench (CRW). The development of this platform requires identifying the processing and analysis needs of the UKCH members and mapping them to potential solutions. This paper presents a proposal for a demonstrator to analyse the use of scientific workflows for large scale data processing. The demonstrator provides a concrete target to promote further discussion of the processing and analysis needs of the UKCH community. In this paper, we will discuss the main requirements for data processing elicited and the proposed adaptations that will be incorporated in the design of the CRW and how to integrate the proposed solutions with existing practices of the UKCH. The demonstrator has been used in discussion with researchers and in presentations to the UKCH community, generating increased interest and motivating further development

ICS Materials. Towards a re-Interpretation of material qualities through interactive, connected, and smart materials.

The domain of materials for design is changing under the influence of an increased technological advancement, miniaturization and democratization. Materials are becoming connected, augmented, computational, interactive, active, responsive, and dynamic. These are ICS Materials, an acronym that stands for Interactive, Connected and Smart. While labs around the world are experimenting with these new materials, there is the need to reflect on their potentials and impact on design. This paper is a first step in this direction: to interpret and describe the qualities of ICS materials, considering their experiential pattern, their expressive sensorial dimension, and their aesthetic of interaction. Through case studies, we analyse and classify these emerging ICS Materials and identified common characteristics, and challenges, e.g. the ability to change over time or their programmability by the designers and users. On that basis, we argue there is the need to reframe and redesign existing models to describe ICS materials, making their qualities emerge

KINE[SIS]TEM'17 From Nature to Architectural Matter

Kine[SiS]tem – From Kinesis + System. Kinesis is a non-linear movement or activity of an organism in response to a stimulus. A system is a set of interacting and interdependent agents forming a complex whole, delineated by its spatial and temporal boundaries, influenced by its environment. How can architectural systems moderate the external environment to enhance comfort conditions in a simple, sustainable and smart way? This is the starting question for the Kine[SiS]tem’17 – From Nature to Architectural Matter International Conference. For decades, architectural design was developed despite (and not with) the climate, based on mechanical heating and cooling. Today, the argument for net zero energy buildings needs very effective strategies to reduce energy requirements. The challenge ahead requires design processes that are built upon consolidated knowledge, make use of advanced technologies and are inspired by nature. These design processes should lead to responsive smart systems that deliver the best performance in each specific design scenario. To control solar radiation is one key factor in low-energy thermal comfort. Computational-controlled sensor-based kinetic surfaces are one of the possible answers to control solar energy in an effective way, within the scope of contradictory objectives throughout the year.FC

Art and Design Practices as a Driver for Deformable Controls, Textures and Screen Interactions

In this thesis, we demonstrate the innovative uses of deformable interfaces to help de-velop future digital art and design interactions. The great benefits of advancing digital art can often come at a cost of tactile feeling and physical expression, while traditional methods celebrate the diverse sets of physical tools and materials. We identified these sets of tools and materials to inform the development of new art and design interfaces that offer rich physical mediums for digital artist and designers. In order to bring forth these unique inter-actions, we draw on the latest advances in deformable interface technology. Therefore, our research contributes a set of understandings about how deformable interfaces can be har-nessed for art and design interfaces. We identify and discuss the following contributions: insights into tangible and digital practices of artists and designers; prototypes to probe the benefits and possibilities of deformable displays and materials in support of digital-physical art and design, user-centred evaluations of these prototypes to inform future developments, and broader insights into the deformable interface research.Each chapter of this thesis investigates a specific element of art and design, alongside an aspect of deformable interfaces resulting in a new prototype. We begin the thesis by studying the use of physical actuation to simulate artist tools in deformable surfaces. In this chapter, our evaluations highlight the merits of improved user experiences and insights into eyes-free interactions. We then turn to explore deformable textures. Driven by the tactile feeling of mixing paints, we present a gel-based interface that is capable of simulating the feeling of paints on the back of mobile devices. Our evaluations showed how artists endorsed the interactions and held potential for digital oil painting.Our final chapter presents research conducted with digital designers. We explore their colour picking processes and developed a digital version of physical swatches using a mod-ular screen system. This use of tangible proxies in digital-based processes brought a level of playfulness and held potential to support collaborative workflows across disciplines. To conclude, we share how our outcomes from these studies could help shape the broader space of art and design interactions and deformable interface research. We suggest future work and directions based on our findings

SciTech News Volume 71, No. 1 (2017)

Columns and Reports From the Editor 3 Division News Science-Technology Division 5 Chemistry Division 8 Engineering Division Aerospace Section of the Engineering Division 9 Architecture, Building Engineering, Construction and Design Section of the Engineering Division 11 Reviews Sci-Tech Book News Reviews 12 Advertisements IEEE

Designing an effective user interface for the Android tablet environment

With over 1.3 million applications on the Android marketplace, there is increasing competition between mobile applications for customer sales. As usability is a significant factor in an application’s success, many mobile developers refer to the Android design guidelines when designing the user interface (UI). These principles help to provide consistency of navigation and aesthetics, with the rest of the Android platform. However, misinterpretation of the abstract guidelines may mean that patterns and elements selected to organise content of an application do not improve the usability. Therefore, usability tests would be beneficial to ensure that an application meets objectives efficiently and improve on user experience. Usability testing is an important and crucial step in the mobile development process Many freelance developers, however, have limited resources for usability testing, even though the advantages of usability feedback during initial development stages are clear and can save time and money in the long-run. In this thesis, we investigate which method of usability testing is most useful for resource constrained mobile developers. To test the efficacy of Android guidelines, three alternate designs of a unique Android tablet application, Glycano, are developed. High-fidelity paper prototypes were presented to end-users for usability testing and to usability experts for heuristic evaluations. Both usability and heuristic tests demonstrated that following the Android guidelines aids in user familiarity and learnability. Regardless of the different UI designs of the three mockups, Android guidelines provided an initial level of usability by providing familiarity to proficient users and an intuitiveness of certain patterns to new users. However, efficiency in building Glycano schematics was an issue that arose consistently. Testing with end-users and experts, revealed several navigational problems. Usability experts uncovered more general UI problems than the end-user group, who focused more on the content of the application. More refinements and suggestions of additional features to enhance usability and user experience were provided by the experts. Use of usability experts would therefore be most advantageous in initial design stages of an application. Feedback from usability testing is, however, also beneficial and is more valuable than not performing any test at all