Real-time state estimation of laboratory flows

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Earth, Atmospheric, and Planetary Sciences, 2007."June 2007."Includes bibliographical references (p. 51).In this project, we use a real time computer model to simulate a differentially heated laboratory annulus. The laboratory annulus allows us to study chaotic flows typical of the atmosphere. Our objective is to bring the numerical model into close alignment with the laboratory system. Parameter estimation and data assimilation of real time model runs with the tank experiment can be used to improve numerical model fidelity, provided the model operates in real time and the model parameters are in acceptable regimes. We describe how to modify the default configuration of the MITgcm to tackle this new problem. We also run laboratory experiments. Using an iterative process, we update the model parameters (such as diffusion and viscosity), and observe that in at least some regimes, there is excellent agreement between observations and simulations. Much of this effort required the development of infrastructure, which is discussed in this document. Finally, we create and test a complete, real-time system, with data sent across the network from a parallel computer running the numerical model to the laboratory computer, where data assimilation takes place. We further modify the model to allow it to pause mid-run, and restart with the most recent state estimates of velocity and temperature.by Scott Stransky.S.M

"Make Them Change it Every Week!": A Qualitative Exploration of Online Developer Advice on Usable and Secure Authentication

Usable and secure authentication on the web and beyond is mission-critical. While password-based authentication is still widespread, users have trouble dealing with potentially hundreds of online accounts and their passwords. Alternatives or extensions such as multi-factor authentication have their own challenges and find only limited adoption. Finding the right balance between security and usability is challenging for developers. Previous work found that developers use online resources to inform security decisions when writing code. Similar to other areas, lots of authentication advice for developers is available online, including blog posts, discussions on Stack Overflow, research papers, or guidelines by institutions like OWASP or NIST. We are the first to explore developer advice on authentication that affects usable security for end-users. Based on a survey with 18 professional web developers, we obtained 406 documents and qualitatively analyzed 272 contained pieces of advice in depth. We aim to understand the accessibility and quality of online advice and provide insights into how online advice might contribute to (in)secure and (un)usable authentication. We find that advice is scattered and that finding recommendable, consistent advice is a challenge for developers, among others. The most common advice is for password-based authentication, but little for more modern alternatives. Unfortunately, many pieces of advice are debatable (e.g., complex password policies), outdated (e.g., enforcing regular password changes), or contradicting and might lead to unusable or insecure authentication. Based on our findings, we make recommendations for developers, advice providers, official institutions, and academia on how to improve online advice for developers.Comment: Extended version of the paper that appears at ACM CCS 2023. 18 pages, 4 figures, 11 table

Forestry Bulletin No. 12: Pine Seedling Survival and Growth Response to Soils of the Texas Post-Oak Belt

An analysis of the methods and materials in relation to pine seedling survival, including a section on results and discussion.https://scholarworks.sfasu.edu/forestrybulletins/1020/thumbnail.jp

Stock Identification Methods Working Group (SIMWG)

The Stock Identification Methods Working Group (SIMWG) reviews new methods for the defi-nition and investigation of stock structure and provides advice to other ICES expert groups on how to interpret patterns of population structure. The identification of the spatial boundaries of exploited stocks is a fundamental requirement before any stock assessment or modelling can be contemplated, and therefore lies at the heart of resource management. SIMWG continues to provide annual updates on recent applications of stock identification methods to species assessed by ICES and on advances in stock identification methods. Based on the wide expertise of SIMWG members, the group provides reviews of recent literature on genetics, growth marks in calcified structures, life history parameters, morphometrics/ me-ristics, tagging, otolith shape, otolith chemistry, parasites and interdisciplinary approaches. A key activity of SIMWG is to address requests by ICES working groups for technical advice on issues of stock identity. In 2020, the working group reviewed the outcome of the Workshop on Stock Identification of North Sea Cod (WKNSCodID). SIMWG contributes to the general understanding of the biological features of the north Atlantic ecosystem through its work to describe fish population structure. Additionally, SIMWG’s annual reviews on advances in stock identification methods keeps ICES members abreast of best prac-tices in this field of study. SIMWG expert reviews on questions of stock structure for particular ICES species are directly relevant to the appropriate definition of stock and contribute to the accuracy of stock assessment and effectiveness of management actions. We see an important role for SIMWG in the future as ICES copes with the shifting distributions of fishery resources and questions regarding the appropriate definition of fish stocks. Understanding stock structure is a fundamental requirement before any assessment or modelling on a stock can be contemplated and SIMWG will continue to work with ICES expert groups to address pressing stock identifica-tion issues

Effects of radiation damage and inelastic scattering on single-particle imaging of hydrated proteins with an X-ray Free-Electron Laser

We present a computational case study of X-ray single-particle imaging of hydrated proteins on an example of 2-Nitrogenase–Iron protein covered with water layers of various thickness, using a start-to-end simulation platform and experimental parameters of the SPB/SFX instrument at the European X-ray Free-Electron Laser facility. The simulations identify an optimal thickness of the water layer at which the effective resolution for imaging the hydrated sample becomes significantly higher than for the non-hydrated sample. This effect is lost when the water layer becomes too thick. Even though the detailed results presented pertain to the specific sample studied, the trends which we identify should also hold in a general case. We expect these findings will guide future single-particle imaging experiments using hydrated proteins

Classification of time series by shapelet transformation

Time-series classification (TSC) problems present a specific challenge for classification algorithms: how to measure similarity between series. A \emph{shapelet} is a time-series subsequence that allows for TSC based on local, phase-independent similarity in shape. Shapelet-based classification uses the similarity between a shapelet and a series as a discriminatory feature. One benefit of the shapelet approach is that shapelets are comprehensible, and can offer insight into the problem domain. The original shapelet-based classifier embeds the shapelet-discovery algorithm in a decision tree, and uses information gain to assess the quality of candidates, finding a new shapelet at each node of the tree through an enumerative search. Subsequent research has focused mainly on techniques to speed up the search. We examine how best to use the shapelet primitive to construct classifiers. We propose a single-scan shapelet algorithm that finds the best $k$ shapelets, which are used to produce a transformed dataset, where each of the $k$ features represent the distance between a time series and a shapelet. The primary advantages over the embedded approach are that the transformed data can be used in conjunction with any classifier, and that there is no recursive search for shapelets. We demonstrate that the transformed data, in conjunction with more complex classifiers, gives greater accuracy than the embedded shapelet tree. We also evaluate three similarity measures that produce equivalent results to information gain in less time. Finally, we show that by conducting post-transform clustering of shapelets, we can enhance the interpretability of the transformed data. We conduct our experiments on 29 datasets: 17 from the UCR repository, and 12 we provide ourselve