An abstract formal basis for digital crowds

Distributed and Parallel Databases - Crowdsourcing, together with its related approaches, has become very popular in recent years. All crowdsourcing processes involve the participation of a digital...     

Was ist starke Authentisierung?

“Simply, people can no longer remember passwords good enough to reliably defend against dictionary attacks, and are much more secure if they choose a password too complicated to remember and then write it down. We’re all good at securing small pieces of paper. I recommend that people write their passwords down on a small piece of paper, and keep it with their other valuable small pieces of paper: in their wallet.”     

It's the Thought that Counts: The Mediating Effects of Information Processing in Virtual Team Decision Making

Abstract

Previous research shows that although collaboration technology can improve the exchange of information during team decision making, one of the challenges is that this better discussion often does not lead to better decisions. In this paper, we investigate the impact of individual information processing on team decision making. We investigated the effects of two types of collaboration technology when participants were either the member of a team majority or a team minority. There was little impact due to the majority/minority, but the use of collaboration technology that required users to categorize the comments they received from others resulted in increased information processing, which in turn led to better decisions and more satisfied participants.     

Tracking in object action space

In this paper we focus on the joint problem of tracking humans and recognizing human action in scenarios such as a kitchen scenario or a scenario where a robot cooperates with a human, e.g., for a manufacturing task. In these scenarios, the human directly interacts with objects physically by using/manipulating them or by, e.g., pointing at them such as in “Give me that…”. To recognize these types of human actions is difficult because (a) they ought to be recognized independent of scene parameters such as viewing direction and (b) the actions are parametric, where the parameters are either object-dependent or as, e.g., in the case of a pointing direction convey important information. One common way to achieve recognition is by using 3D human body tracking followed by action recognition based on the captured tracking data. For the kind of scenarios considered here we would like to argue that 3D body tracking and action recognition should be seen as an intertwined problem that is primed by the objects on which the actions are applied. In this paper, we are looking at human body tracking and action recognition from a object-driven perspective. Instead of the space of human body poses we consider the space of the object affordances, i.e., the space of possible actions that are applied on a given object. This way, 3D body tracking reduces to action tracking in the object (and context) primed parameter space of the object affordances. This reduces the high-dimensional joint-space to a low-dimensional action space. In our approach, we use parametric hidden Markov models to represent parametric movements; particle filtering is used to track in the space of action parameters. We demonstrate its effectiveness on synthetic and on real image sequences using human-upper body single arm actions that involve objects.     

Application of flow cytometry for examining phytoplankton succession in two eutrophic lakes

Flow cytometry has potential as a rapid assessment technique to evaluate phytoplankton biomass and species composition. It facilitates for multi-parameter analysis of individual cells on the basis of light scattering effects induced from cellular constituents, as well as auto-fluorescence. Fluorescence emission characteristics may be especially useful in classifying cyanobacteria as they contain phycoerythrin which emits light predominantly in the 550-600 nm waveband, chlorophyll-a (650-700 nm emission) and allophycocyanin (660 nm emission). The objective of our study was to assess the utility of flow cytometry for the rapid identification and sorting of freshwater algae and cyanobacteria species. Using a selection of laboratory-cultured freshwater algae and cyanobacteria species, this study demonstrated unique light scatter and fluorescent characteristics for each species examined, allowing for rapid species identification and sorting of mixed populations of laboratory cultures and samples from two lakes in the Rotorua region (New Zealand). Analysis of lake water samples collected over seven months demonstrated changes in abundance and community composition of phytoplankton in the two lakes and demonstrates that flow cytometry may be a useful technique for examining seasonal changes in phytoplankton composition.     

TeraGrid Science Gateways and Their Impact on Science

The Science Gateways program seeks to provide researchers with easy access to TeraGrid's high-performance computing resources. A look at four successful gateways illustrates the program's goals, challenges, and opportunities.     

Haptic two-finger contact with textiles

Real-time cloth simulation involves many computational challenges to be solved, particularly in the context of haptic applications, where high frame rates are necessary for obtaining a satisfying experience. In this paper, we present an interactive cloth simulation system that offers a compromise between a realistic physics-based simulation of fabrics and a haptic application meeting high requirements in terms of computation speed. Our system allows the user to interact with the fabric using two fingers. The required performance of the system is achieved by introducing an intermediate layer responsible for the simulation of the small part of the surface being in contact with the fingers. Additionally we separate the possible contact situations into different cases, each being individually handled by a specialised contact algorithm.

Resource allocation optimization for quantitative service differentiation on server clusters

The goal of service differentiation is to provide different service quality levels to meet changing system configuration and resource availability and to satisfy different requirements and expectations of applications and users. In this paper, we investigate the problem of quantitative service differentiation on cluster-based delay-sensitive servers. The goal is to support a system-wide service quality optimization with respect to resource allocation on a computer system while provisioning proportionality fairness to clients. We first propose and promote a square-root proportional differentiation model. Interestingly, both popular delay factors, queueing delay and slowdown, are reciprocally proportional to the allocated resource usage. We formulate the problem of quantitative service differentiation as a generalized resource allocation optimization towards the minimization of system delay, defined as the sum of weighted delay of client requests. We prove that the optimization-based resource allocation scheme essentially provides square-root proportional service differentiation to clients. We then study the problem of service differentiation provisioning from an important relative performance metric, slowdown. We give a closed-form expression of the expected slowdown of a popular heavy-tailed workload model with respect to resource allocation on a server cluster. We design a two-tier resource management framework, which integrates a dispatcher-based node partitioning scheme and a server-based adaptive process allocation scheme. We evaluate the resource allocation framework with different models via extensive simulations. Results show that the square-root proportional model provides service differentiation at a minimum cost of system delay. The two-tier resource allocation framework can provide fine-grained and predictable service differentiation on cluster-based servers.     

释放你的内在潜能

技术工人在当今的制造环境中是必不可少的。通过运用你的IT知识,可以消除时间和精力上的浪费。     

Waveform diversity via mutual information

A novel criterion for waveform diversity in radar systems is presented that is based on the information theoretic concept of Shannon mutual information (MI). In general, waveform diversity refers to adaptively changing a transmitted waveform based on the target and interference environment. MI is a measure of the information in a random variable or vector about another random variable or vector. It is shown herein that an MI framework provides the basis for a general and powerful criterion for evaluation of candidate waveforms, as well as design of waveforms. The criterion inherently includes radar system and scenario statistical information. In addition, the criterion reduces to a simple analytical function of a set of scalar parameters for the case of Gaussian-distributed proper random processes. It is shown that those scalar parameters are also the canonical correlations of the random variables in the MI expression that involves the received radar signal at two distinct time instants. This property suggests the possibility of new insights into waveform diversity using MI as a criterion. The concept is presented assuming a SAR system configuration, but can be extended to other radar modes and functions, as well as to other sensing applications.