Introducing New Methodologies for Identifying Design Patterns for Internationalization and Localization

This paper describes a new methodology for deriving interaction design patterns from an analysis of ethnographic data. It suggests using inductive and deductive analysis processes to identify and articulate patterns that address the needs of culturally diverse users of interactive, collaborative systems. This might inform the internationalization and localization process of computer supported collaboration systems

It is all me: the effect of viewpoint on visual-vestibular recalibration

Participants performed a visual–vestibular motor recalibration task in virtual reality. The task consisted of keeping the extended arm and hand stable in space during a whole-body rotation induced by a robotic wheelchair. Performance was first quantified in a pre-test in which no visual feedback was available during the rotation. During the subsequent adaptation phase, optical flow resulting from body rotation was provided. This visual feedback was manipulated to create the illusion of a smaller rotational movement than actually occurred, hereby altering the visual–vestibular mapping. The effects of the adaptation phase on hand stabilization performance were measured during a post-test that was identical to the pre-test. Three different groups of subjects were exposed to different perspectives on the visual scene, i.e., first-person, top view, or mirror view. Sensorimotor adaptation occurred for all three viewpoint conditions, performance in the post-test session showing a marked under-compensation relative to the pre-test performance. In other words, all viewpoints gave rise to a remapping between vestibular input and the motor output required to stabilize the arm. Furthermore, the first-person and mirror view adaptation induced a significant decrease in variability of the stabilization performance. Such variability reduction was not observed for the top view adaptation. These results suggest that even if all three viewpoints can evoke substantial adaptation aftereffects, the more naturalistic first-person view and the richer mirror view should be preferred when reducing motor variability constitutes an important issue

ARTIFICIAL INTELLIGENCE-ENABLED MULTI-MISSION RESOURCE ALLOCATION TACTICAL DECISION AID

The Department of Defense supports many military platforms that execute multiple missions simultaneously. Platforms such as watercraft, aircraft, and land convoys support multiple missions over domains such as air and missile defense, anti-submarine warfare, strike operations, fires in support of ground operations, intelligence sensing and reconnaissance. However, major challenges to the human decision-maker exist in allocating these multi-mission resources such as the growth in battle-tempo, scale, and complexity of available platforms. This capstone study seeks to apply systems engineering to analyze the multi-mission resource allocation (MMRA) problem set to further enable artificial intelligence (AI) and machine learning tools to aid human decision-makers for initial and dynamic re-planning. To approach this problem, the study characterizes inputs and outputs of a potential MMRA process, then analyzes the scalability and complexity across three unique use cases: directed energy convoy protection, aviation support, and a carrier strike group. The critical findings of these diverse use cases were then assessed for similarities and differences to further understand commonalities for a joint AI-enabled MMRA tool.Civilian, Department of the ArmyCivilian, Department of the ArmyCivilian, Department of the NavyApproved for public release. Distribution is unlimited

Conceptual mechanization studies for a horizon definition spacecraft attitude control subsystem, phase A, part II, 10 October 1966 - 29 May 1967

Attitude control subsystem for spin stabilized spacecraft for mapping earths infrared horizon radiance profiles in 15 micron carbon dioxide absorption ban

BEDLAM: A Synthetic Dataset of Bodies Exhibiting Detailed Lifelike Animated Motion

We show, for the first time, that neural networks trained only on synthetic data achieve state-of-the-art accuracy on the problem of 3D human pose and shape (HPS) estimation from real images. Previous synthetic datasets have been small, unrealistic, or lacked realistic clothing. Achieving sufficient realism is non-trivial and we show how to do this for full bodies in motion. Specifically, our BEDLAM dataset contains monocular RGB videos with ground-truth 3D bodies in SMPL-X format. It includes a diversity of body shapes, motions, skin tones, hair, and clothing. The clothing is realistically simulated on the moving bodies using commercial clothing physics simulation. We render varying numbers of people in realistic scenes with varied lighting and camera motions. We then train various HPS regressors using BEDLAM and achieve state-of-the-art accuracy on real-image benchmarks despite training with synthetic data. We use BEDLAM to gain insights into what model design choices are important for accuracy. With good synthetic training data, we find that a basic method like HMR approaches the accuracy of the current SOTA method (CLIFF). BEDLAM is useful for a variety of tasks and all images, ground truth bodies, 3D clothing, support code, and more are available for research purposes. Additionally, we provide detailed information about our synthetic data generation pipeline, enabling others to generate their own datasets. See the project page: https://bedlam.is.tue.mpg.de/

Causal deep learning models for studying the Earth system

Earth is a complex non-linear dynamical system. Despite decades of research and considerable scientific and methodological progress, many processes and relations between Earth system variables remain poorly understood. Current approaches for studying relations in the Earth system rely either on numerical simulations or statistical approaches. However, there are several inherent limitations to existing approaches, including high computational costs, uncertainties in numerical models, strong assumptions about linearity or locality, and the fallacy of correlation and causality. Here, we propose a novel methodology combining deep learning (DL) and principles of causality research in an attempt to overcome these limitations. On the one hand, we employ the recent idea of training and analyzing DL models to gain new scientific insights into relations between input and target variables. On the other hand, we use the fact that a statistical model learns the causal effect of an input variable on a target variable if suitable additional input variables are included. As an illustrative example, we apply the methodology to study soil-moisture–precipitation coupling in ERA5 climate reanalysis data across Europe. We demonstrate that, harnessing the great power and flexibility of DL models, the proposed methodology may yield new scientific insights into complex non-linear and non-local coupling mechanisms in the Earth system.</p

A transitividade de verbos de elocução à luz do Funcionalismo.

Esta dissertação aborda o fenômeno da transitividade em notas sociais, com vistas a entender melhor o comportamento de verbos de elocução comumente usados nesses textos. Para dar conta do estudo que pretendemos empreender, partimos das proposições tradicionais no que tange à transitividade, também consideramos as abordagens descritivas e elegemos como referencial teórico a perspectiva funcionalista da linguagem, dentro da qual encontra-se uma concepção de transitividade formulada por Hopper e Thompson (1980). Ao relacionar as referidas vertentes teóricas, percebemos a necessidade de ampliar, ou até atualizar, a maneira como a transitividade é concebida. Diante disso, a empreitada assumida por nós se justifica, pois propomos um estudo da transitividade para além do olhar normativo e objetivamos compreender melhor o funcionamento dos verbos de elocução e a transitividade das orações que os abrigam em um contexto de uso. O corpus elegido para este estudo foram as notas sociais publicadas na seção Planeta Pop, do caderno AT2, do jornal A Tribuna, que são pequenos textos noticiando alguma informação sobre a vida de pessoas famosas no meio artístico e de nacionalidade estrangeira, tendo os verbos de elocução como um componente essencial. A metodologia adotada foi a de observar, descrever e analisar o fenômeno eleito para nossa investigação. Dessa forma, após reunirmos os dados, visualizamos as ocorrências dos verbos de elocução, buscando descrever o ambiente em que se inserem para, então, aferirmos a transitividade das orações e demonstrarmos, por meio de alguns exemplos, a dinâmica de uso desses verbos e das orações em relação à transitividade. A pesquisa revelou um alto grau de transitividade nas cláusulas que formam as notas sociais e que os verbos de elocução não revelam um objeto sintático paciente, ou seja, que sofre a transferência da ação verbal, o que justifica o fato de, no que se refere aos Parâmetros de Transitividade de Hopper e Thompson (1980), não identificarmos, em nenhuma das orações analisadas, o afetamento e a individuação do objeto

Introducing Ionic Current Detection for X Ray Absorption Spectroscopy in Liquid Cells

Photons and electrons are two common relaxation products upon X ray absorption, enabling fluorescence yield and electron yield detections for X ray absorption spectroscopy XAS . The ions that are created during the electron yield process are relaxation products too, which are exploited in this study to produce ion yield for XA detection. The ionic currents measured in a liquid cell filled with water or iron III nitrate aqueous solutions exhibit characteristic O K edge and Fe L edge absorption profiles as a function of excitation energy. Application of two electrodes installed in the cell is crucial for obtaining the XA spectra of the liquids behind membranes. Using a single electrode can only probe the species adsorbed on the membrane surface. The ionic current detection, termed as total ion yield TIY in this study, also produces an undistorted Fe L edge XA spectrum, indicating its promising role as a novel detection method for XAS studies in liquid cell