Secure Data Sharing With AdHoc

In the scientific circles, there is pressing need to form temporary and dynamic collaborations to share diverse resources (e.g. data, an access to services, applications or various instruments). Theoretically, the traditional grid technologies respond to this need with the abstraction of a Virtual Organization (VO). In practice its procedures are characterized by latency, administrative overhead and are inconvenient to its users. We would like to propose the Manifesto for Secure Sharing. The main postulate is that users should be able to share data and resources by themselves without any intervention on the system administrator's side. In addition, operating an intuitive interface does not require IT skills. AdHoc is a resource sharing interface designed for users willing to share data or computational resources within seconds and almost effortlessly. The AdHoc application is built on the top of traditional security frameworks, such as the PKI X.509 certificate scheme, Globus GSI, gLite VOMS and Shibboleth. It enables users rapid and secure collaboration

Pinching sweaters on your phone – iShoogle : multi-gesture touchscreen fabric simulator using natural on-fabric gestures to communicate textile qualities

The inability to touch fabrics online frustrates consumers, who are used to evaluating physical textiles by engaging in complex, natural gestural interactions. When customers interact with physical fabrics, they combine cross-modal information about the fabric's look, sound and handle to build an impression of its physical qualities. But whenever an interaction with a fabric is limited (i.e. when watching clothes online) there is a perceptual gap between the fabric qualities perceived digitally and the actual fabric qualities that a person would perceive when interacting with the physical fabric. The goal of this thesis was to create a fabric simulator that minimized this perceptual gap, enabling accurate perception of the qualities of fabrics presented digitally. We designed iShoogle, a multi-gesture touch-screen sound-enabled fabric simulator that aimed to create an accurate representation of fabric qualities without the need for touching the physical fabric swatch. iShoogle uses on-screen gestures (inspired by natural on-fabric movements e.g. Crunching) to control pre-recorded videos and audio of fabrics being deformed (e.g. being Crunched). iShoogle creates an illusion of direct video manipulation and also direct manipulation of the displayed fabric. This thesis describes the results of nine studies leading towards the development and evaluation of iShoogle. In the first three studies, we combined expert and non-expert textile-descriptive words and grouped them into eight dimensions labelled with terms Crisp, Hard, Soft, Textured, Flexible, Furry, Rough and Smooth. These terms were used to rate fabric qualities throughout the thesis. We observed natural on-fabric gestures during a fabric handling study (Study 4) and used the results to design iShoogle's on-screen gestures. In Study 5 we examined iShoogle's performance and speed in a fabric handling task and in Study 6 we investigated users' preferences for sound playback interactivity. iShoogle's accuracy was then evaluated in the last three studies by comparing participants’ ratings of textile qualities when using iShoogle with ratings produced when handling physical swatches. We also described the recording and processing techniques for the video and audio content that iShoogle used. Finally, we described the iShoogle iPhone app that was released to the general public. Our evaluation studies showed that iShoogle significantly improved the accuracy of fabric perception in at least some cases. Further research could investigate which fabric qualities and which fabrics are particularly suited to be represented with iShoogle

A Toolkit For Storage Qos Provisioning For Data-Intensive Applications

This paper describes a programming toolkit developed in the PL-Grid project, named QStorMan, which supports storage QoS provisioning for data-intensive applications in distributed environments. QStorMan exploits knowledge-oriented methods for matching storage resources to non-functional requirements, which are defined for a data-intensive application. In order to support various usage scenarios, QStorMan provides two interfaces, such as programming libraries or a web portal. The interfaces allow to define the requirements either directly in an application source code or by using an intuitive graphical interface. The first way provides finer granularity, e.g., each portion of data processed by an application can define a different set of requirements. The second method is aimed at legacy applications support, which source code can not be modified. The toolkit has been evaluated using synthetic benchmarks and the production infrastructure of PL-Grid, in particular its storage infrastructure, which utilizes the Lustre file system

A SIMPLE MATHEMATICAL MODEL OF A SINGLE SCULLING TECHNIQUE

The results in sport in rowing depend on the two most important factors, such as the athlete physical features and the techniques of motion. The assessment and optimisation of rowing techniques are possible only when one disposes the reliable mathematical model predicting the results of the regatta that is the time of covering an assumed distance. A single scull participating in the 2000 meters distance regatta is our subject. The purpose of this study is to create a simplified mathematical model to simulate the rowing boat dynamics. The boat-rower system is treated as a material point here. The oar has a prescribed angular motion vs. oarlock depending on the time. The hydrodynamics force distribution to be developed on the oar’s blade has been modelled here. Then, the boat motion was described by a single nonlinear ordinary differential equation (NODE). The proposed simple model gives the possibilities of fast and reliable simulation of the single sculling technique and forecasts the result of rowing regattas

Localization of cancerous changes in images of breast tissue

Localization of cancerous changes in images o

The cloud application modelling and execution language (CAMEL)

Cloud computing provides ubiquitous networked access to a shared and virtualised pool of computing capabilities that can be provisioned with minimal management effort. Cloud applications are deployed on cloud infrastructures and delivered as services. The PaaSage project aims to facilitate the modelling and execution of cloud applications by leveraging model-driven engineering (MDE) and by exploiting multiple cloud infrastructures. The Cloud Application Modelling and Execution Language (CAMEL) is the core modelling and execution language developed in the PaaSage project and enables the specification of multiple aspects of cross-cloud applications (i.e., applications deployed across multiple private, public, or hybrid cloud infrastructures). By exploiting models at both design- and run-time, and by allowing both direct and programmatic manipulation of models, CAMEL enables the management of self-adaptive cross-cloud applications (i.e., cross-cloud applications that autonomously adapt to changes in the environment, requirements, and usage). In this paper, we describe the design and implementation of CAMEL, with emphasis on the integration of heterogeneous domain-specific languages (DSLs) that cover different aspects of self-adaptive cross-cloud applications. Moreover, we provide a real-world running example to illustrate how to specify models in a concrete textual syntax and how to dynamically adapt these models during the application life cycle. Finally, we provide an evaluation of CAMEL’s usability and usefulness, based on the technology acceptance model (TAM)

The cloud application modelling and execution language

Cloud computing offers a flexible pay-as-you-go model for provisioning application resources, which enables applications to scale on-demand based on the current workload. In many cases, though, users face the single vendor lock-in effect, missing opportunities for optimal and adaptive application deployment across multiple clouds. Several cloud modelling languages have been developed to support multi-cloud resource management, but still they lack holistic cloud management of all aspects and phases. This work defines the Cloud Application Modelling and Execution Language (CAMEL), which (i) allows users to specify the full set of design time aspects for multi-cloud applications, and (ii) supports the models@runtime paradigm that enables capturing an application’s current state facilitating its adaptive provisioning. CAMEL has been already used in many projects, domains and use cases due to its wide coverage of cloud management features. Finally, CAMEL has been positively evaluated in this work in terms of its usability and applicability in several domains (e.g., data farming, flight scheduling, financial services) based on the technology acceptance model (TAM)