Freeform User Interfaces for Graphical Computing

報告番号: 甲15222 ; 学位授与年月日: 2000-03-29 ; 学位の種別: 課程博士 ; 学位の種類: 博士(工学) ; 学位記番号: 博工第4717号 ; 研究科・専攻: 工学系研究科情報工学専

MOLNs: A cloud platform for interactive, reproducible and scalable spatial stochastic computational experiments in systems biology using PyURDME

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools, a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments

An application of the MPP to the interactive manipulation of stereo images of digital terrain models

Massively Parallel Processor algorithms were developed for the interactive manipulation of flat shaded digital terrain models defined over grids. The emphasis is on real time manipulation of stereo images. Standard graphics transformations are applied to a 128 x 128 grid of elevations followed by shading and a perspective projection to produce the right eye image. The surface is then rendered using a simple painter's algorithm for hidden surface removal. The left eye image is produced by rotating the surface 6 degs about the viewer's y axis followed by a perspective projection and rendering of the image as described above. The left and right eye images are then presented on a graphics device using standard stereo technology. Performance evaluations and comparisons are presented

Towards automated knowledge-based mapping between individual conceptualisations to empower personalisation of Geospatial Semantic Web

Geospatial domain is characterised by vagueness, especially in the semantic disambiguation of the concepts in the domain, which makes defining universally accepted geo- ontology an onerous task. This is compounded by the lack of appropriate methods and techniques where the individual semantic conceptualisations can be captured and compared to each other. With multiple user conceptualisations, efforts towards a reliable Geospatial Semantic Web, therefore, require personalisation where user diversity can be incorporated. The work presented in this paper is part of our ongoing research on applying commonsense reasoning to elicit and maintain models that represent users' conceptualisations. Such user models will enable taking into account the users' perspective of the real world and will empower personalisation algorithms for the Semantic Web. Intelligent information processing over the Semantic Web can be achieved if different conceptualisations can be integrated in a semantic environment and mismatches between different conceptualisations can be outlined. In this paper, a formal approach for detecting mismatches between a user's and an expert's conceptual model is outlined. The formalisation is used as the basis to develop algorithms to compare models defined in OWL. The algorithms are illustrated in a geographical domain using concepts from the SPACE ontology developed as part of the SWEET suite of ontologies for the Semantic Web by NASA, and are evaluated by comparing test cases of possible user misconceptions

Report from the MPP Working Group to the NASA Associate Administrator for Space Science and Applications

NASA's Office of Space Science and Applications (OSSA) gave a select group of scientists the opportunity to test and implement their computational algorithms on the Massively Parallel Processor (MPP) located at Goddard Space Flight Center, beginning in late 1985. One year later, the Working Group presented its report, which addressed the following: algorithms, programming languages, architecture, programming environments, the way theory relates, and performance measured. The findings point to a number of demonstrated computational techniques for which the MPP architecture is ideally suited. For example, besides executing much faster on the MPP than on conventional computers, systolic VLSI simulation (where distances are short), lattice simulation, neural network simulation, and image problems were found to be easier to program on the MPP's architecture than on a CYBER 205 or even a VAX. The report also makes technical recommendations covering all aspects of MPP use, and recommendations concerning the future of the MPP and machines based on similar architectures, expansion of the Working Group, and study of the role of future parallel processors for space station, EOS, and the Great Observatories era

Parallel software tools at Langley Research Center

This document gives a brief overview of parallel software tools available on the Intel iPSC/860 parallel computer at Langley Research Center. It is intended to provide a source of information that is somewhat more concise than vendor-supplied material on the purpose and use of various tools. Each of the chapters on tools is organized in a similar manner covering an overview of the functionality, access information, how to effectively use the tool, observations about the tool and how it compares to similar software, known problems or shortfalls with the software, and reference documentation. It is primarily intended for users of the iPSC/860 at Langley Research Center and is appropriate for both the experienced and novice user

Tool support for security-oriented virtual research collaborations

Collaboration is at the heart of e-Science and e-Research more generally. Successful collaborations must address both the needs of the end user researchers and the providers that make resources available. Usability and security are two fundamental requirements that are demanded by many collaborations and both concerns must be considered from both the researcher and resource provider perspective. In this paper we outline tools and methods developed at the National e-Science Centre (NeSC) that provide users with seamless, secure access to distributed resources through security-oriented research environments, whilst also allowing resource providers to define and enforce their own local access and usage policies through intuitive user interfaces. We describe these tools and illustrate their application in the ESRC-funded Data Management through e-Social Science (DAMES) and the JISC-funded SeeGEO projects

Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

Service oriented interactive media (SOIM) engines enabled by optimized resource sharing

In the same way as cloud computing, Software as a Service (SaaS) and Content Centric Networking (CCN) triggered a new class of software architectures fundamentally different from traditional desktop software, service oriented networking (SON) suggests a new class of media engine technologies, which we call Service Oriented Interactive Media (SOIM) engines. This includes a new approach for game engines and more generally interactive media engines for entertainment, training, educational and dashboard applications. Porting traditional game engines and interactive media engines to the cloud without fundamentally changing the architecture, as done frequently, can enable already various advantages of cloud computing for such kinds of applications, for example simple and transparent upgrading of content and unified user experience on all end-user devices. This paper discusses a new architecture for game engines and interactive media engines fundamentally designed for cloud and SON. Main advantages of SOIM engines are significantly higher resource efficiency, leading to a fraction of cloud hosting costs. SOIM engines achieve these benefits by multilayered data sharing, efficiently handling many input and output channels for video, audio, and 3D world synchronization, and smart user session and session slot management. Architecture and results of a prototype implementation of a SOIM engine are discussed