The 1990 progress report and future plans

This document describes the progress and plans of the Artificial Intelligence Research Branch (RIA) at ARC in 1990. Activities span a range from basic scientific research to engineering development and to fielded NASA applications, particularly those applications that are enabled by basic research carried out at RIA. Work is conducted in-house and through collaborative partners in academia and industry. Our major focus is on a limited number of research themes with a dual commitment to technical excellence and proven applicability to NASA short, medium, and long-term problems. RIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at JPL and AI applications groups at all NASA centers

Nature-inspired survivability: Prey-inspired survivability countermeasures for cloud computing security challenges

As cloud computing environments become complex, adversaries have become highly sophisticated and unpredictable. Moreover, they can easily increase attack power and persist longer before detection. Uncertain malicious actions, latent risks, Unobserved or Unobservable risks (UUURs) characterise this new threat domain. This thesis proposes prey-inspired survivability to address unpredictable security challenges borne out of UUURs. While survivability is a well-addressed phenomenon in non-extinct prey animals, applying prey survivability to cloud computing directly is challenging due to contradicting end goals. How to manage evolving survivability goals and requirements under contradicting environmental conditions adds to the challenges. To address these challenges, this thesis proposes a holistic taxonomy which integrate multiple and disparate perspectives of cloud security challenges. In addition, it proposes the TRIZ (Teorija Rezbenija Izobretatelskib Zadach) to derive prey-inspired solutions through resolving contradiction. First, it develops a 3-step process to facilitate interdomain transfer of concepts from nature to cloud. Moreover, TRIZ’s generic approach suggests specific solutions for cloud computing survivability. Then, the thesis presents the conceptual prey-inspired cloud computing survivability framework (Pi-CCSF), built upon TRIZ derived solutions. The framework run-time is pushed to the user-space to support evolving survivability design goals. Furthermore, a target-based decision-making technique (TBDM) is proposed to manage survivability decisions. To evaluate the prey-inspired survivability concept, Pi-CCSF simulator is developed and implemented. Evaluation results shows that escalating survivability actions improve the vitality of vulnerable and compromised virtual machines (VMs) by 5% and dramatically improve their overall survivability. Hypothesis testing conclusively supports the hypothesis that the escalation mechanisms can be applied to enhance the survivability of cloud computing systems. Numeric analysis of TBDM shows that by considering survivability preferences and attitudes (these directly impacts survivability actions), the TBDM method brings unpredictable survivability information closer to decision processes. This enables efficient execution of variable escalating survivability actions, which enables the Pi-CCSF’s decision system (DS) to focus upon decisions that achieve survivability outcomes under unpredictability imposed by UUUR

Donald P. Brutzman: a biography

Design and implement large-scale networked underwater virtual worlds using Web-accessible 3D graphics and network streams. Integrate sensors, models and datasets for real-time interactive use by scientists, underwater robots, ships and students of all ages

Advances in modelling of epithelial to mesenchymal transition

Epithelial to Mesenchymal Transition (EMT) is a cellular transformation process that is employed repeatedly and ubiquitously during vertebrate morphogenesis to build complex tissues and organs. Cellular transformations that occur during cancer cell invasion are phenotypically similar to developmental EMT, and involve the same molecular signalling pathways. EMT processes are diverse, but are characterised by: a loss of cell-cell adhesion; a gain in cell-matrix adhesion; an increase in cell motility; the secretion of proteases that degrade basement membrane proteins; an increased resistance to apoptosis; a loss of polarisation; increased production of extracellular matrix components; a change from a rounded to a fibroblastic morphology; and an invasive phenotype. This thesis focuses explicitly on endocardial EMT, which is the EMT that occurs during vertebrate embryonic heart development. The embryonic heart initially forms as a tube, with myocardium externally, endocardium internally, with these tissue layers separated by a thick extracellular matrix termed the cardiac jelly. Some of the endocardial cells in specific regions of the embryonic heart tube undergo EMT and invade the cardiac jelly. This causes cellularised swellings inside the embryonic heart tube termed the endocardial cushions. The emergence of the four chambered double pump heart of mammals involves a complex remodelling that the endocardial cushions play an active role in. Even while heart remodelling is taking place, the heart tube is operating as a single-circulation pump, and the endocardial cushions are performing a valve-like function that is critical to the survival of the embryo (Nomura-Kitabayashi et al. 2009). As the endocardial cushions grow and remodel, they become the valve leaflets of the foetal heart. The endocardial cushions also contribute tissue to the septa (walls) of the heart. Their correct formation is thus essential to the development of a fully functional, fully divided, double-pump system. It has been shown that genetic mutations that cause impaired endocardial EMT lead to the development of a range of congenital heart defects (Fischer et al. 2007). An extensive review is conducted of existing experimental investigations into endocardial EMT. The information extracted from this review is used to develop a multiscale conceptual model of endocardial EMT, including the major protein signalling pathways involved, and the cellular phenotypes that they induce or inhibit. After considering the requirements for computational simulations of EMT, and reviewing the various techniques and simulation packages available for multi-cell modelling, cellular Potts modelling is selected as having the most appropriate combination of features. The open source simulation platform Compucell3D is selected for model development, due to the flexibility, range of features provided and an existing implementation of multiscale models; that include subcellular models of reaction pathways. Based on the conceptual model of endocardial EMT, abstract computational simulations of key aspects are developed, in order to investigate qualitative behaviour under different simulated conditions. The abstract simulations include a 2D multiscale model of Notch signalling lateral induction, which is the mechanism by which the embryonic heart tube is patterned into cushion and non-cushion forming regions. Additionally, a 3D simulation is used to investigate the possible role of contact-inhibited mitosis, upregulated by the VEGF protein, in maintaining an epithelial phenotype. One particular in vitro investigation of endocardial EMT (Luna-Zurita et al. 2010) is used to develop quantitative simulations. The quantitative data used for fitting the simulations consist of cell shape metrics that are derived from simple processing of the imaging results. Single cell simulations are used to investigate the relationship between cell motility and cell shape in the cellular Potts model. The findings are then implemented in multi-cell models, in order to investigate the relationship between cell-cell adhesion, cell-matrix adhesion, cell motility and cell shape during EMT

Artificial Intelligence Research Branch future plans

This report contains information on the activities of the Artificial Intelligence Research Branch (FIA) at NASA Ames Research Center (ARC) in 1992, as well as planned work in 1993. These activities span a range from basic scientific research through engineering development to fielded NASA applications, particularly those applications that are enabled by basic research carried out in FIA. Work is conducted in-house and through collaborative partners in academia and industry. All of our work has research themes with a dual commitment to technical excellence and applicability to NASA short, medium, and long-term problems. FIA acts as the Agency's lead organization for research aspects of artificial intelligence, working closely with a second research laboratory at the Jet Propulsion Laboratory (JPL) and AI applications groups throughout all NASA centers. This report is organized along three major research themes: (1) Planning and Scheduling: deciding on a sequence of actions to achieve a set of complex goals and determining when to execute those actions and how to allocate resources to carry them out; (2) Machine Learning: techniques for forming theories about natural and man-made phenomena; and for improving the problem-solving performance of computational systems over time; and (3) Research on the acquisition, representation, and utilization of knowledge in support of diagnosis design of engineered systems and analysis of actual systems

A Modular and Open-Source Framework for Virtual Reality Visualisation and Interaction in Bioimaging

Life science today involves computational analysis of a large amount and variety of data, such as volumetric data acquired by state-of-the-art microscopes, or mesh data from analysis of such data or simulations. The advent of new imaging technologies, such as lightsheet microscopy, has resulted in the users being confronted with an ever-growing amount of data, with even terabytes of imaging data created within a day. With the possibility of gentler and more high-performance imaging, the spatiotemporal complexity of the model systems or processes of interest is increasing as well. Visualisation is often the first step in making sense of this data, and a crucial part of building and debugging analysis pipelines. It is therefore important that visualisations can be quickly prototyped, as well as developed or embedded into full applications. In order to better judge spatiotemporal relationships, immersive hardware, such as Virtual or Augmented Reality (VR/AR) headsets and associated controllers are becoming invaluable tools. In this work we present scenery, a modular and extensible visualisation framework for the Java VM that can handle mesh and large volumetric data, containing multiple views, timepoints, and color channels. scenery is free and open-source software, works on all major platforms, and uses the Vulkan or OpenGL rendering APIs. We introduce scenery's main features, and discuss its use with VR/AR hardware and in distributed rendering. In addition to the visualisation framework, we present a series of case studies, where scenery can provide tangible benefit in developmental and systems biology: With Bionic Tracking, we demonstrate a new technique for tracking cells in 4D volumetric datasets via tracking eye gaze in a virtual reality headset, with the potential to speed up manual tracking tasks by an order of magnitude. We further introduce ideas to move towards virtual reality-based laser ablation and perform a user study in order to gain insight into performance, acceptance and issues when performing ablation tasks with virtual reality hardware in fast developing specimen. To tame the amount of data originating from state-of-the-art volumetric microscopes, we present ideas how to render the highly-efficient Adaptive Particle Representation, and finally, we present sciview, an ImageJ2/Fiji plugin making the features of scenery available to a wider audience.:Abstract Foreword and Acknowledgements Overview and Contributions Part 1 - Introduction 1 Fluorescence Microscopy 2 Introduction to Visual Processing 3 A Short Introduction to Cross Reality 4 Eye Tracking and Gaze-based Interaction Part 2 - VR and AR for System Biology 5 scenery — VR/AR for Systems Biology 6 Rendering 7 Input Handling and Integration of External Hardware 8 Distributed Rendering 9 Miscellaneous Subsystems 10 Future Development Directions Part III - Case Studies C A S E S T U D I E S 11 Bionic Tracking: Using Eye Tracking for Cell Tracking 12 Towards Interactive Virtual Reality Laser Ablation 13 Rendering the Adaptive Particle Representation 14 sciview — Integrating scenery into ImageJ2 & Fiji Part IV - Conclusion 15 Conclusions and Outlook Backmatter & Appendices A Questionnaire for VR Ablation User Study B Full Correlations in VR Ablation Questionnaire C Questionnaire for Bionic Tracking User Study List of Tables List of Figures Bibliography Selbstständigkeitserklärun

Proceedings, MSVSCC 2012

Proceedings of the 6th Annual Modeling, Simulation & Visualization Student Capstone Conference held on April 19, 2012 at VMASC in Suffolk, Virginia