The interaction of representation and reasoning

Automated reasoning is an enabling technology for many applications of informatics. These applications include verifying that a computer program meets its specification; enabling a robot to form a plan to achieve a task and answering questions by combining information from diverse sources, e.g. on the Internet, etc. How is automated reasoning possible? Firstly, knowledge of a domain must be stored in a computer, usually in the form of logical formulae. This knowledge might, for instance, have been entered manually, retrieved from the Internet or perceived in the environment via sensors, such as cameras. Secondly, rules of inference are applied to old knowledge to derive new knowledge. Automated reasoning techniques have been adapted from logic, a branch of mathematics that was originally designed to formalize the reasoning of humans, especially mathematicians. My special interest is in the way that representation and reasoning interact. Successful reasoning is dependent on appropriate representation of both knowledge and successful methods of reasoning. Failures of reasoning can suggest changes of representation. This process of representational change can also be automated. We will illustrate the automation of representational change by drawing on recent work in my research group

A Formal Treatment of Hardware Wallets

Bitcoin, being the most successful cryptocurrency, has been repeatedly attacked with many users losing their funds. The industry\u27s response to securing the user\u27s assets is to offer tamper-resistant hardware wallets. Although such wallets are considered to be the most secure means for managing an account, no formal attempt has been previously done to identify, model and formally verify their properties. This paper provides the first formal model of the Bitcoin hardware wallet operations. We identify the properties and security parameters of a Bitcoin wallet and formally define them in the Universal Composition (UC) Framework. We present a modular treatment of a hardware wallet ecosystem, by realizing the wallet functionality in a hybrid setting defined by a set of protocols. This approach allows us to capture in detail the wallet\u27s components, their interaction and the potential threats. We deduce the wallet\u27s security by proving that it is secure under common cryptographic assumptions, provided that there is no deviation in the protocol execution. Finally, we define the attacks that are successful under a protocol deviation, and analyze the security of commercially available wallets

“What and how should we share?” An inter-method inter-observer comparison of measurement error with landmark-based craniometric datasets

The present study evaluates the precision and accuracy of photogrammetric 3D modeling of human crania in landmark acquisition and explores the limitations of combining datasets acquired by different observers and different measurement methods. Our working sample comprises 50 adult human crania, which were modeled with 3D photogrammetry. 3D coordinates of 56 landmarks were collected from the 3D models with Meshlab software and an existing corresponding dataset digitized with Microscribe-3DX has been utilized. Measurement error for landmark configurations and Inter Landmarks Distances (ILDs) for each type of landmarks has been assessed through least root mean squared deviation and mean absolute error respectively. Inter-observer error has been assessed on a sub-sample of 20 crania, which was also used for caliper measured ILDs. Between-methods Technical Error Measurement (TEM) based on ILDs has been calculated for evaluating the interchangeability for different datasets. Photogrammetric 3D models and Microscribe-3DX share identical rated accuracy regarding craniometric applications and both methods show increased accuracy in locating type I landmarks as opposed to types II and III. However, photogrammetric 3D models perform better in terms of inter-observer error sug-gesting higher reliability of measurements. Furthermore, ILDs are less prone to measurement error than landmark configu-rations. Finally, ILDs exhibit similar relative TEM of about 1.5% between Microscribe, caliper and 3D model based measurement methods. Combining datasets of landmark coordinates acquired from photogrammetric 3D models does not compromise the statistical integrity in terms of measurement error, which also applies to pooling ILD datasets from multiple methods. Nevertheless, compiling 3D datasets from multiple methods for 3DGM analysis should be done cautiously. © 2019 E. Schweizerbart’sche Verlagsbuchhandlung, 70176 Stuttgart, Germany

Influence of Filler Pore Structure and Polymer on the Performance of MOF-Based Mixed-Matrix Membranes for CO 2 Capture

International audienceMembrane gas separation units are gaining increasing attention owing to their relatively low energy consumption, ease of operation and environmental aspects. Metal-organic framework (MOF)-mixed matrix membranes (MMMs) are proposed as alternative materials delivering both the promising performance benefits from embedded MOF fillers and the processing features of polymers. In order to gain insight into the influence of MOF filler and polymer on membrane performance, eight different composites are studied by combining four MOFs and two polymers. MOF materials (NH2-MIL-53(Al), MIL-69(Al), MIL-96(Al) and ZIF-94(Zn)) with various chemical functionalities, topologies, and dimensionalities of porosity were employed as fillers, while two typical polymers with different permeability-selectivity properties (6FDA-DAM and Pebax) were deliberately selected as matrices. Separation results are rationalized on the basis of thorough characterization of the main components of the composites. The observed differences in membrane performance in the separation of CO2 from N2 are explained on the basis of gas solubility, diffusivity properties and compatibility between the filler and polymer phases