Task modeling for collaborative authoring

Motivation ?Task analysis for designing modern collaborative work needs a more fine grained approach. Especially in a complex task domain, like collaborative scientific authoring, when there is a single overall goal that can only be accomplished only by collaboration between multiple roles, each requiring its own expertise. We analyzed and re-considered roles, activities, and objects for design for complex collaboration contexts. Our main focus is on a generic approach to design for multiple roles and subtasks in a domain with a shared overall goal, which requires a detailed approach. Collaborative authoring is our current example. This research is incremental: an existing task analysis approach (GTA) is reconsidered by applying it to a case of complex collaboration. Our analysis shows that designing for collaboration indeed requires a refined approach to task modeling: GTA, in future, will need to consider tasks at the lowest level that can be delegated or mandates. These tasks need to be analyzed and redesigned in more in detail, along with the relevant task object.

Investigating the sensitivity of OSLD responses for varying field sizes across matched linear accelerators

When radiation therapy centres are equipped with two or more linear accelerators from the same vendor, they are usually beam-matched. This work tested the sensitivity of optically stimulated luminescence dosimeters (OSLDs) across matched linear accelerators. The responses were compared with an unshielded diode detector for varying field sizes. Clinical studies are currently done with thermoluminescent dosimeters (TLD), which absorb radiation then emit some levels of light determined by the radiation absorption when heated.

Interaction modeling using BPMN

Process choreographies describe interactions between different business partners and the dependencies between these interactions. While different proposals were made for capturing choreographies at an implementation level, it remains unclear how choreographies should be described on a conceptual level.While the Business Process Modeling Notation (BPMN) is already in use for describing choreographies in terms of interconnected interface behavior models, this paper will introduce interaction modeling using BPMN. Such interaction models do not suffer from incompatibility issues and are better suited for human modelers. BPMN extensions are proposed and a mapping from interaction models to interface behavior models is presented.

Facilitating query decomposition in query language modeling by association rule mining using multiple sliding windows

This paper presents a novel framework to further advance the recent trend of using query decomposition and high-order term relationships in query language modeling, which takes into account terms implicitly associated with different subsets of query terms. Existing approaches, most remarkably the language model based on the Information Flow method are however unable to capture multiple levels of associations and also suffer from a high computational overhead. In this paper, we propose to compute association rules from pseudo feedback documents that are segmented into variable length chunks via multiple sliding windows of different sizes. Extensive experiments have been conducted on various TREC collections and our approach significantly outperforms a baseline Query Likelihood language model, the Relevance Model and the Information Flow model.

Ozone-Induced Dissociation on a Modified Tandem Linear Ion-Trap : Observations of Different Reactivity for Isomeric Lipids

Ozone-induced dissociation (OzID) exploits the gas-phase reaction between mass-selected lipid ions and ozone vapor to determine the position(s) of unsaturation In this contribution, we describe the modification of a tandem linear ion-trap mass spectrometer specifically for OzID analyses wherein ozone vapor is supplied to the collision cell This instrumental configuration provides spatial separation between mass-selection, the ozonolysis reaction, and mass-analysis steps in the OzID process and thus delivers significant enhancements in speed and sensitivity (ca 30-fold) These improvements allow spectra revealing the double-bond position(s) within unsaturated lipids to be acquired within 1 s significantly enhancing the utility of OzID in high-throughput lipidomic protocols The stable ozone concentration afforded by this modified instrument also allows direct comparison of relative reactivity of isomeric lipids and reveals reactivity trends related to (1) double-bond position, (2) substitution position on the glycerol backbone, and (3) stereochemistry For cis- and trans-isomers, differences were also observed in the branching ratio of product ions arising from the gas-phase ozonolysis reaction, suggesting that relative ion abundances could be exploited as markers for double-bond geometry Additional activation energy applied to mass-selected lipid ions during injection into the collision cell (with ozone present) was found to yield spectra containing both OzID and classical-CID fragment ions This combination CID-OzID acquisition on an ostensibly simple monounsaturated phosphatidylcholine within a cow brain lipid extract provided evidence for up to four structurally distinct phospholipids differing in both double-bond position and sn-substitution U Am Soc Mass Spectrom 2010, 21, 1989-1999) (C) 2010 American Society for Mass Spectrometry

Dictionary learning and sparse coding on Grassmann manifolds : an extrinsic solution

Recent advances in computer vision and machine learning suggest that a wide range of problems can be addressed more appropriately by considering non-Euclidean geometry. In this paper we explore sparse dictionary learning over the space of linear subspaces, which form Riemannian structures known as Grassmann manifolds. To this end, we propose to embed Grassmann manifolds into the space of symmetric matrices by an isometric mapping, which enables us to devise a closed-form solution for updating a Grassmann dictionary, atom by atom. Furthermore, to handle non-linearity in data, we propose a kernelised version of the dictionary learning algorithm. Experiments on several classification tasks (face recognition, action recognition, dynamic texture classification) show that the proposed approach achieves considerable improvements in discrimination accuracy, in comparison to state-of-the-art methods such as kernelised Affine Hull Method and graph-embedding Grassmann discriminant analysis.

Conversion of linear to rhombic C-4 in the gas phase: A joint experimental and theoretical study

Charge reversal (CR) and neutralization reionization (NR) experiments carried out on a 4-sector mass spectrometer demonstrate that isotopically labeled, linear C-4 anion rearranges upon collisional oxidation. The cations and neutrals formed in these experiments exhibit differing degrees of isotopic scrambling in their fragmentation patterns, indicative of (at least) partial isomerization of both states. Theoretical studies, employing the CCSD(T)/aug-cc-pVDZ//B3LYP/6-31G(d) level of theory, favor conversion to the rhombic C-4 isomer on both cationic and neutral potential-energy surfaces with the rhombic structures predicted to be slightly more stable than the linear forms in each case. The combination of experiment with theory indicates that the elusive rhombic C-4 is formed as a cation and as a neutral following charge stripping of linear C-4(-)

Parameter estimation of structural commodity price models

Commodity price modeling is normally approached in terms of structural time-series models, in which the different components (states) have a financial interpretation. The parameters of these models can be estimated using maximum likelihood. This approach results in a non-linear parameter estimation problem and thus a key issue is how to obtain reliable initial estimates. In this paper, we focus on the initial parameter estimation problem for the Schwartz-Smith two-factor model commonly used in asset valuation. We propose the use of a two-step method. The first step considers a univariate model based only on the spot price and uses a transfer function model to obtain initial estimates of the fundamental parameters. The second step uses the estimates obtained in the first step to initialize a re-parameterized state-space-innovations based estimator, which includes information related to future prices. The second step refines the estimates obtained in the first step and also gives estimates of the remaining parameters in the model. This paper is part tutorial in nature and gives an introduction to aspects of commodity price modeling and the associated parameter estimation problem.

Modeling nitrous oxide emissions from irrigated agriculture : testing DayCent with high-frequency measurements

A unique high temporal frequency dataset from an irrigated cotton-wheat rotation was used to test the agroecosystem model DayCent to simulate daily N2O emissions from sub-tropical vertisols under different irrigation intensities. DayCent was able to simulate the effect of different irrigation intensities on N2O fluxes and yield, although it tended to overestimate seasonal fluxes during the cotton season. DayCent accurately predicted soil moisture dynamics and the timing and magnitude of high fluxes associated with fertilizer additions and irrigation events. At the daily scale we found a good correlation of predicted vs. measured N2O fluxes (r2 = 0.52), confirming that DayCent can be used to test agricultural practices for mitigating N2O emission from irrigated cropping systems. A 25 year scenario analysis indicated that N2O losses from irrigated cotton-wheat rotations on black vertisols in Australia can be substantially reduced by an optimized fertilizer and irrigation management system (i.e. frequent irrigation, avoidance of excessive fertiliser application), while sustaining maximum yield potentials.

Mitigation of distorted and unbalanced stator voltage of stand-alone doubly fed induction generators using repetitive control technique

Unbalanced or non-linear loads result in distorted stator currents and electromagnetic torque pulsations in stand-alone doubly fed induction generators (DFIGs). This study proposes the use of a proportional-integral repetitive control (PIRC) scheme so as to mitigate the levels of harmonic and unbalance at the stator terminals of the DFIG. The PIRC is structurally simpler and requires much less computation than existing methods. Analysis of the PIRC operation and the methodology to determine the control parameters is included. Simulation study as well as laboratory test measurements demonstrate clearly the effectiveness of the proposed PIRC control scheme.

Towards the development of 1-to-n human machine interfaces for unmanned aerial vehicles

Multi-touch interfaces across a wide range of hardware platforms are becoming pervasive. This is due to the adoption of smart phones and tablets in both the consumer and corporate market place. This paper proposes a human-machine interface to interact with unmanned aerial systems based on the philosophy of multi-touch hardware-independent high-level interaction with multiple systems simultaneously. Our approach incorporates emerging development methods for multi-touch interfaces on mobile platforms. A framework is defined for supporting multiple protocols. An open source solution is presented that demonstrates: architecture supporting different communications hardware; an extensible approach for supporting multiple protocols; and the ability to monitor and interact with multiple UAVs from multiple clients simultaneously. Validation tests were conducted to assess the performance, scalability and impact on packet latency under different client configurations.

Non-linear model predictive control for UAVs with slung/swung load

Suspended loads on UAVs can provide significant benefits to several applications in agriculture, law enforcement and construction. The load impact on the underlying system dynamics should not be neglected as significant feedback forces may be induced on the vehicle during certain flight manoeuvres. Much research has focused on standard multi-rotor position and attitude control with and without a slung load. However, predictive control schemes, such as Nonlinear Model Predictive Control (NMPC), have not yet been fully explored. To this end, we present software and flight system architecture to test controller for safe and precise operation of multi-rotors with heavy slung load in three dimensions.

Non-linear principal components analysis : an alternative method for finding patterns in environmental data

The main purpose of this article is to gain an insight into the relationships between variables describing the environmental conditions of the Far Northern section of the Great Barrier Reef, Australia. Several of the variables describing these conditions had different measurement levels and often they had non-linear relationships. Using non-linear principal component analysis, it was possible to acquire an insight into these relationships. Furthermore, three geographical areas with unique environmental characteristics could be identified.

Accurately defining the reference condition for summary biotic metrics: A comparison of four approaches

Protocols for bioassessment often relate changes in summary metrics that describe aspects of biotic assemblage structure and function to environmental stress. Biotic assessment using multimetric indices now forms the basis for setting regulatory standards for stream quality and a range of other goals related to water resource management in the USA and elsewhere. Biotic metrics are typically interpreted with reference to the expected natural state to evaluate whether a site is degraded. It is critical that natural variation in biotic metrics along environmental gradients is adequately accounted for, in order to quantify human disturbance-induced change. A common approach used in the IBI is to examine scatter plots of variation in a given metric along a single stream size surrogate and a fit a line (drawn by eye) to form the upper bound, and hence define the maximum likely value of a given metric in a site of a given environmental characteristic (termed the 'maximum species richness line' - MSRL). In this paper we examine whether the use of a single environmental descriptor and the MSRL is appropriate for defining the reference condition for a biotic metric (fish species richness) and for detecting human disturbance gradients in rivers of south-eastern Queensland, Australia. We compare the accuracy and precision of the MSRL approach based on single environmental predictors, with three regression-based prediction methods (Simple Linear Regression, Generalised Linear Modelling and Regression Tree modelling) that use (either singly or in combination) a set of landscape and local scale environmental variables as predictors of species richness. We compared the frequency of classification errors from each method against set biocriteria and contrast the ability of each method to accurately reflect human disturbance gradients at a large set of test sites. The results of this study suggest that the MSRL based upon variation in a single environmental descriptor could not accurately predict species richness at minimally disturbed sites when compared with SLR's based on equivalent environmental variables. Regression-based modelling incorporating multiple environmental variables as predictors more accurately explained natural variation in species richness than did simple models using single environmental predictors. Prediction error arising from the MSRL was substantially higher than for the regression methods and led to an increased frequency of Type I errors (incorrectly classing a site as disturbed). We suggest that problems with the MSRL arise from the inherent scoring procedure used and that it is limited to predicting variation in the dependent variable along a single environmental gradient.

Cheating prevention in linear secret sharing

Cheating detection in linear secret sharing is considered. The model of cheating extends the Tompa-Woll attack and includes cheating during multiple (unsuccessful) recovery of the secret. It is shown that shares in most linear schemes can be split into subshares. Subshares can be used by participants to trade perfectness of the scheme with cheating prevention. Evaluation of cheating prevention is given in the context of different strategies applied by cheaters.