A study on effects of security risks on acceptance of enterprise cloud service: moderating of employment and non-employment using PLS multiple group analysis

This paper analyzed the effects of security risk factors fit for cloud computing paradigm on the acceptance of enterprise cloud service with intent to illuminate the factors for vitalizing the adoption of corporate cloud services in the future. The acceptance intention was set as a dependent variable. Independent variables were set in reference to the technology acceptance theory. Security risks were categorized into compliance risk, information leakage risk, troubleshooting risk and service discontinuation risk to design a model for analysis.     

Future Proof: The Transition to Digital at IFI Archive

Informed by research over the past two years and the work of colleagues in peer institutions, the IFI Irish Film Archive developed a six-year Digital Preservation and Access strategy which launched in 2014. Fundamental to this Strategy was the design and installation of digital archive tools for long term preservation and the redesign of workflow practices to facilitate accession and management of high resolution digital film and broadcast assets and associated metadata. This article outlines the steps taken and standards applied in developing a future proof digital audiovisual archive.     

Business Intelligence Acceptance: The Prominence of Organizational Factors

The specifics of business intelligence systems compared to operational IS motivate the necessity to research the business intelligence systems acceptance determinants separately. The authors followed an exploratory approach in order to conceptualize a business intelligence acceptance model. Their findings show that in the Business Intelligence Systems context, there is a significant emphasis on organizational factors, such as result demonstrability, social influence, and facilitating conditions with sufficient resources that help build an adequate information culture all substantially influencing the effective acceptance of business intelligence systems.     

The Price of Anarchy in Network Creation Games Is (Mostly) Constant

We study the price of anarchy and the structure of equilibria in network creation games. A network creation game is played by n players {1,2,…,n}, each identified with a vertex of a graph (network), where the strategy of player i, i=1,…,n, is to build some edges adjacent to i. The cost of building an edge is α>0, a fixed parameter of the game. The goal of every player is to minimize its creation cost plus its usage cost. The creation cost of player i is α times the number of built edges. In the SumGame variant, the usage cost of player i is the sum of distances from i to every node of the resulting graph. In the MaxGame variant, the usage cost is the eccentricity of i in the resulting graph of the game. In this paper we improve previously known bounds on the price of anarchy of the game (of both variants) for various ranges of α, and give new insights into the structure of equilibria for various values of α. The two main results of the paper show that for α>273?n all equilibria in SumGame are trees and thus the price of anarchy is constant, and that for α>129 all equilibria in MaxGame are trees and the price of anarchy is constant. For SumGame this answers (almost completely) one of the fundamental open problems in the field—is price of anarchy of the network creation game constant for all values of α?—in an affirmative way, up to a tiny range of α.     

From big smartphone data to worldwide research: The Mobile Data Challenge

This paper presents an overview of the Mobile Data Challenge (MDC), a large-scale research initiative aimed at generating innovations around smartphone-based research, as well as community-based evaluation of mobile data analysis methodologies. First, we review the Lausanne Data Collection Campaign (LDCC), an initiative to collect unique longitudinal smartphone dataset for the MDC. Then, we introduce the Open and Dedicated Tracks of the MDC, describe the specific datasets used in each of them, discuss the key design and implementation aspects introduced in order to generate privacy-preserving and scientifically relevant mobile data resources for wider use by the research community, and summarize the main research trends found among the 100+ challenge submissions. We finalize by discussing the main lessons learned from the participation of several hundred researchers worldwide in the MDC Tracks.     

Workflows for Heliophysics

In this paper we describe how we have introduced workflows into the working practices of a community for whom the concept of workflows is very new, namely the heliophysics community. Heliophysics is a branch of astrophysics which studies the Sun and the interactions between the Sun and the planets, by tracking solar events as they travel throughout the Solar system. Heliophysics produces two major challenges for workflow technology. Firstly it is a systems science where research is currently developed by many different communities who need reliable data models and metadata to be able to work together. Thus it has major challenges in the semantics of workflows. Secondly, the problem of time is critical in heliophysics; the workflows must take account of the propagation of events outwards from the sun. They have to address the four dimensional nature of space and time in terms of the indexing of data. We discuss how we have built an environment for Heliophysics workflows building on and extending the Taverna workflow system and utilising the myExperiment site for sharing workflows. We also describe how we have integrated the workflows into the existing practices of the communities involved in Heliophysics by developing a web portal which can hide the technical details from the users, who can concentrate on the data from their scientific point of view rather than on the methods used to integrate and process the data. This work has been developed in the EU Framework 7 project HELIO, and is being disseminated to the worldwide Heliophysics community, since Heliophysics requires integration of effort on a global scale.     

Human interaction discovery in smartphone proximity networks

Since humans are fundamentally social beings and interact frequently with others in their daily life, understanding social context is of primary importance in building context-aware applications. In this paper, using smartphone Bluetooth as a proximity sensor to create social networks, we present a probabilistic approach to mine human interaction types in real life. Our analysis is conducted on Bluetooth data continuously sensed with smartphones for over one year from 40 individuals who are professionally or personally related. The results show that the model can automatically discover a variety of social contexts. We objectively validated our model by studying its predictive and retrieval performance.     

Tensor Clustering for Rendering Many‐Light Animations

Rendering animations of scenes with deformable objects, camera motion, and complex illumination, including indirect lighting and arbitrary shading, is a long‐standing challenge. Prior work has shown that complex lighting can be accurately approximated by a large collection of point lights. In this formulation, rendering of animation sequences becomes the problem of efficiently shading many surface samples from many lights across several frames. This paper presents a tensor formulation of the animated many‐light problem, where each element of the tensor expresses the contribution of one light to one pixel in one frame. We sparsely sample rows and columns of the tensor, and introduce a clustering algorithm to select a small number of representative lights to efficiently approximate the animation. Our algorithm achieves efficiency by reusing representatives across frames, while minimizing temporal flicker. We demonstrate our algorithm in a variety of scenes that include deformable objects, complex illumination and arbitrary shading and show that a surprisingly small number of representative lights is sufficient for high quality rendering. We believe out algorithm will find practical use in applications that require fast previews of complex animation.     

An integral system‐ergonomic approach for IT‐based process management in complex work environments by example of manufacturing and health care

Recent trends in manufacturing and health care move these two work systems closer together from a system ergonomics point of view. Individual treatment of products, especially patients, by specialists in a distributed environment demand information technology (IT)‐based support suitable for complex systems. IT‐based support of processes in complex systems is difficult due to the lack of standard processes. IT support also means to rethink processes to use efficiency potentials. Close cooperation of users and software developers is needed to increase the ergonomic quality of the system. Therefore, suitable tools are needed: UML is available as the standard industry modeling language, Zope/Plone as the quasi‐standard for content management systems, SimPy as an object‐oriented simulation tool for event‐triggered processes, and ACT‐R as a powerful cognitive architecture for simulation of human information processes. The integration of these tools enables system‐ergonomic support of processes in the complex work system as well as of the development and deployment process. It is the base of an integral system‐ergonomic approach for IT‐based process management. Knowledge gained during process analysis either enters models or leads to the extension and adaptation of the tool chain. The models serve as basis for discussion among system ergonomists, programmers, and specialists from the work system. Further, they are understood by simulation and process support tools. Transcoding efforts between humans with different professional backgrounds and machines are reduced, and the flexibility demanded by complex systems is met. © 2008 Wiley Periodicals, Inc.