Task models

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Embedding explicit representation of cyber-physical elements in task models

Embedding explicit representation of cyber-physical elements in task models

- The generation paradigm (gathered under the term of model driven development of User Interfaces (UI)) use tasks descriptions as input artefacts. For instance, the CAMELEON framework [3] provides support for the design and development based on tasks and domain models and several approaches are based on this philosophy. Manca et al. propose a solution to handle objects in preconditions during the generation of the UI [10]. Tran et al. propose a framework taking as input task, context and domain models to generate the UI [19]. In these approaches, as the UI is generated from the task models, there is a one-way connection between tasks and UI components. The main drawbacks are that it is difficult to integrate design considerations and craft knowledge in such processes ending up with stereotyped user interfaces far away (in terms of design and interaction techniques) from leading edge applications.
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Rapid Task-Models Development Using Sub-models, Sub-routines and Generic Components

Rapid Task-Models Development Using Sub-models, Sub-routines and Generic Components

This concept has already been applied to task analysis and even task modeling. In such case they are mainly used (as for software engineering) to define a generic solu- tion to a given problem. Paternó et al. in [5] have proposed a pattern called “Multi- values input Task” where a set of iterative tasks are interrupted by a termination task. Such construction deserves the term of patterns as they are supposed to help the per- son in charge of modeling reuse this solution (a combination of the iterative operator with the interruption one) to describe users’ tasks. Other approaches have also been proposed in [8], [9], [19] or [24] in order to provide reusable elements corresponding to solutions to recurring problems. The structuring mechanisms presented in this pa- per are of a different nature. Indeed, they are introduced for addressing scalability and modifiability of task models. Indeed, we don’t present how they help modeling user tasks but instead how they can be used for structuring task models in order to ease their understanding, the modification and their reuse in other contexts. These two approaches (structuring mechanisms and patterns) are even orthogonal. Indeed, one could define design patterns without any structuring concepts (as in [19] for instance) or use structuring mechanisms for tasks models without addressing the aspect of patterns to solve recurring problems (as in [15] for instance). Of course, those two concepts could be integrated but this is beyond the scope of this paper.
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Designing and Assessing Interactive Systems Using Task Models

Designing and Assessing Interactive Systems Using Task Models

§ Université Nice Sophia Antipolis (Polytech) {palanque, martinie, winckler}@irit.fr Abstract - This two-part course takes a practical approach to introduce the prin- ciples, methods and tools in task modelling. Part 1: A non-technical introduction demonstrates that task models support successful design of interactive systems. Part 2: A more technical interactive hands-on exercise of how to "do it right", such as: How to go from task analysis to task models? How to assess (through analysis and simulation) that a task model is correct? How to identify complexity of user tasks …
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Designing and Assessing Interactive Systems Using Task Models

Designing and Assessing Interactive Systems Using Task Models

Task models have also proven being of great help for structuring user documentation, designing and assessing a training program, assessing the complexity of the users’ work. If used for analysis, they can also provide support for identifying types, location and likelihood of human errors. When used for design they

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Enriching Task Models with Usability and User Experience Evaluation Data

Enriching Task Models with Usability and User Experience Evaluation Data

Notations for task models are typically supported by tools. For CTT the corre- sponding tool is called CTTe, for HTA normally paper-based approaches are used. For the HAMSTERS notation the tool is having the same name. For later stages, especially when performing evaluations that ask the user to perform a task, there are evaluation tools available. For example Morae [ 30 ] allows to represent each button-press a user was performing during the study. Table 2 details the abilities of such systems, espe- cially the ability to incorporate data from the system model (SYS), data from the user study including system, evaluator, scenario, conditions (STUD) and the ability to represent properties beyond usability like dimensions or factors of user experience (UX) and the ability to enable different types of visualization that include data visu- alization of more than one user study (VIZ+).
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Rapid Task-Models Development Using Sub-models, Sub-routines and Generic Components

Rapid Task-Models Development Using Sub-models, Sub-routines and Generic Components

As far as task models are a concern, some tasks (such as login into systems) remain structurally similar even when reused in different applications. This feature has been introduced in notations like CTT [20] so that some generic tasks can be used as build- ing blocks that can be integrated along the modeling process. Concerned by the reus- ability of tasks models, Gaffar et al. [9] have investigated structuring mechanisms around the notion of patterns to be used in task models. They propose a method and a tool to model generic task patterns as building blocks that can be instantiated and customized when modeling real-life socio-technical systems. One of the advantages of task patterns with respect to building blocks is the fact they provide more flexibil- ity to adapt the specification to very specific needs. Nonetheless, all these solutions for reusing generic tasks and task patterns are limited to isolated models, lacking of a notational support to describe how such snippets of models are articulated once they are integrated into larger task models.
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Designing and Assessing Interactive Systems Using Task Models

Designing and Assessing Interactive Systems Using Task Models

Task models have also proven being of great help for structuring user documentation, designing and assessing a training program, assessing the complexity of the users’ work. If used for analysis, they can also provide support for identifying types, location and likelihood of human errors. When used for design they Philippe Palanque

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Designing and Assessing Interactive Systems Using Task Models

Designing and Assessing Interactive Systems Using Task Models

Keywords: User interaction design  Task description and modelling 1 Introduction Task analysis is meant to identify user goals and tasks when using an interactive system. In the case of users performing real life work, task analysis can be a cum- bersome process gathering a huge amount of unorganized information. Task Models (TM) provide a mean for the analyst to store information gathered in an abstract way that can be further detailed and analyzed if needed. A task model allows HCI researchers and practionners to record in a systematic, complete and unambiguous way the set of user goals and the way those user goals can be performed on an interactive system. Reasoning about the Task Models produced supports the assessment of effectiveness of an interactive system (which is one of the most difficult dimension of usability to assess). Task models have also proven being of great help for structuring user documentation, designing and assessing a training program, assessing the com- plexity of the users’ work. If used for analysis, they can also provide support for identifying types, location and likelihood of human errors. When used for design they also provide precious support for identification of good candidates for task migration towards automation.
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Structuring and Composition Mechanisms to Address Scalability Issues in Task Models

Structuring and Composition Mechanisms to Address Scalability Issues in Task Models

Abstraction/refinement and composition mechanisms: This section has illustrated the mechanisms currently available for structuring task models. However, when it comes to large systems these mechanisms and tools are insufficient (see CTT model in Fig. 2 ). We propose two new mechanisms to handle more efficiently this complexity. The first one is based on refinement/abstraction principle and makes it possible to decompose a task model in several models and to interconnect them. A large task model can thus be decomposed into several sub-models. These sub-models can then be reused (as a “copy”) in various places of the same model and even in other models. Each time one of these parts is modified, the modification is reflected in all the other “copies”. The Composition mechanism makes it possible to define communication mechanisms between task models. This task model structuring mechanisms is similar to procedures calls in programming languages and parameterization is possible via input and output parameters. In order to keep the same semantics as for the single model, communication protocols have also been introduced.
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Designing and Assessing Interactive Systems Using Task Models

Designing and Assessing Interactive Systems Using Task Models

[6] Martinie C., Palanque P., Winckler M. Structuring and Composition Mechanisms to Address Scalability Issues in Task Models. IFIP INTERACT conference, (2011) 589-609. [7] Martinie C., Palanque P., Ragosta M., Fahssi R. Extending procedural task models by systematic explicit integration of objects, knowledge and information. Europ. Conf. on Cognitive Ergonomics, 2013: 23-34, ACM DL. [8] Forbrig P., Martinie C., Palanque P., Winckler M., Fahssi R. Rapid Task-Models Development Using Sub- models, Sub-routines and Generic Components. IFIP HCSE 2014: 144-163.
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A more intelligent test case generation approach through task models manipulation

A more intelligent test case generation approach through task models manipulation

Because fully testing a GUI is rarely feasible for interactive computing systems of reasonable size, a balance must be reached between the amount of coverage provided by the test cases, and the cost effectiveness of the test suite. The concept of Test Patterns has been used to represent a set of test strategies that simplify the testing of specific GUI features. This approach aims at promoting the reuse of test strategies to test typical behaviors and has been applied both to web [22] and mobile [23] applications, but it is only able to test the aspects of the user interface that are covered by the pattern language in use. Silva et al. [32] use ConcurTaskTree (CTT) [29] task models as oracle in order to both reduce the cost of producing the oracle and focus the test cases on the normative uses of the system. The drawback, however, is that the test suite can become too restrictive as users might deviate from that normative behavior. The work was extended in [5] by including the notion of test cases mutations, in order to take into account the possibility of deviations from the prescribed behavior (more specifically, user errors).
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Autonimic energy-aware task scheduling

Autonimic energy-aware task scheduling

increases considerably their energy consumption which leads to important losses for companies. Energy-aware task scheduling is a new challenge to optimize the use of the computation power provided by multiple resources. In the context of Cloud resources usage depends on users requests which are generally unpredictable. Autonomic computing paradigm provides systems with self-managing capabilities helping to react to unstable situation. This article proposes an autonomic approach to provide energy-aware scheduling tasks. The generic autonomic computing framework FrameSelf coupled with the CloudSim energy-aware simulator is presented. The proposed solution enables to detect critical schedule situations and simulate new placements for tasks on DVFS enabled hosts in order to improve the global energy efficiency.
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LifeCLEF Bird Identification Task 2017

LifeCLEF Bird Identification Task 2017

FHDO BCSG, Germany, 4 runs [4]: Like the DYNI UTLN team, these participants based his system on an adaptation of an image classification model, i.e Inception V3 [12]. Audio records were encoded through spectrograms and fur- ther processed by applying bandpass filtering, noise filtering, and silent region removal. For data augmentation purposes, they intended to use time shifting, time stretching, pitch shifting, and pitch stretching. Unfortunately, the data augmentation was not properly executed and the learned models suffered from overfitting problems. The first three runs differ in term of preprocessing, while the Run 3 is an average of the runs: Run 2 manipulates binary pictures and Run 4 uses grayscale pictures. Run 1 exploited the 3 RGB channels: the original grayscale picture in one channel, its blurred and sharpened versions for the two other channels.
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IEA Wind Task 36 Forecasting

IEA Wind Task 36 Forecasting

This WP brings together global leaders in NWP models as applied to the wind industry to exchange information about future research areas. The emphasis will be on improvements of the wind- related forecast performance of these models especially in typical rotor heights.

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Developmental changes in using verbal self-cueing in task-switching situations: the impact of task practice and task-sequencing demands

Developmental changes in using verbal self-cueing in task-switching situations: the impact of task practice and task-sequencing demands

First, we replicated a number of findings that have already been reported in the literature. Our results indicated reliable mix- ing costs, that is, subjects were slower and made more errors in mixed-task blocks than in single tasks blocks, as shown in nearly all task-switching studies (cf. Kiesel et al., 2010 ). We also found partly that mixing costs were smaller in older children than in younger children, at least when costs were measured on the level of mean latencies (cf. Cepeda et al., 2001; Crone et al., 2004; Reimers and Maylor, 2005; Dibbets and Jolles, 2006; Karbach and Kray, 2007; Kray et al., 2008, 2012a; Manzi et al., 2011 ). However, taking the substantial baseline differences in latencies between both groups of children into account, the younger children in our study did not show proportionally larger mixing costs. Moreover, mixing costs on the level of error rates also did not significantly differ between younger and older children. One explanation for lacking age differences in mixing costs in the present study is that the younger children in the present study were somewhat older than in most other studies (e.g., Dibbets and Jolles, 2006; Karbach and Kray, 2007 ). However, we also intended to investigate even younger children (5–6 years old) in this study, but these children turned out to produce too many errors in this paradigm to obtain reliable findings from this age group.
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A General Manipulation Task Planner

A General Manipulation Task Planner

Fig. 7. A CG ∩ CP path with a sliding motion of the bar (left) transformed into a sequence of three feasible transfer/transit/transfer manipulation paths (right) The difficulty with the Cage example is the complexity of the manipu- lation task. Several consecutive re-graspings motions through the middle of cage obstacle are necessary to move the bar to a position where it can be regrasped by its extremity. The planner automatically computes the required configurations from only one continuous placement domain (the floor) and one grasping zone all along the bar. The path to get the bar out of the cage is found in the CG ∩ CP manifold, and then transformed during the post- processing step in a sequence of transit and transfer paths (see Figure 7). The final path contains 20 elementary paths with 8 re-graspings of the mov- able object. This difficult manipulation problem was solved in less than two minutes, which demonstrates the efficacy of the proposed approach.
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Report from Task 4 of MEWS Project - Task 4-Environmental Conditions Final Report

Report from Task 4 of MEWS Project - Task 4-Environmental Conditions Final Report

characteristics. Since the approach taken in Task 4 was that the climate data would be treated independently of the wall response many of the IEA recommendations do not serve the purposes of this project. A universal method for selected a moisture reference year is not currently available. Karagiozis [16] points to other researchers contributing in this area including: Geving[17], Kuenzel [18], and Hagentoft [19]. The problem still remains as to what to select as input for the parametric study phase of Task 7. One approach is to use the entire hourly weather record, 30 to 40 years, as input. This approach is currently not practical. Another approach is to define a reference year similar to the energy reference years that have been developed for energy calculations. Energy reference years are statistical years in that the values for each hour are synthesized from statistical analysis. Examples of statistical years include, typical reference year (TRY), typical meteorological year (TMY), and weather years for energy calculations (WYEC2 and CWEC). Again this is ongoing problem, currently being addressed for example by ASHRAE Technical Committee 4.2 [20].
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Aix Map Task corpus: The French multimodal corpus of task-oriented dialogue

Aix Map Task corpus: The French multimodal corpus of task-oriented dialogue

Astésano, C., Bard, E., and Turk, A. (2007). Structural influences on initial accent place- ment in French. Language and Speech, 50(3):423-446. Bard, E. G., Astésano, C., Turk, A., D’Imperio, M., Nguyen, N., Prévot, L., and Bigi, B. (2013). Aix Map-Task: A (rather) new French resource for prosodic and discourse studies. In Proceedings of TRASP; Tools and Resources for the Analysis of Speech Prosody, pp. 15-19.

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OpenMATB: A Task Battery promoting task customization, software extensibility and experiment replicability

OpenMATB: A Task Battery promoting task customization, software extensibility and experiment replicability

Santiago-Espada, Y., Myer, R. R., Latorella, K. A., & Comstock, J. R. (2011). The Multi-attribute Task Battery II (MATB-II): Software For Human Performance And Workload Research: A User’s Guide. NASA Technical Memorandum 217164. Thanoon, M. I., Zein-Sabatto, M. S., & McCurry, C. D. (2017). Multi-Attribute Task Battery for Human-Machine Teaming. Paper presented at the International Conference on Advances on Ap- plied Cognitive Computing, Las Vegas, USA.

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IEA Wind Task 36 Forecasting

IEA Wind Task 36 Forecasting

Gregor Giebel Will Shaw Helmut Frank Bri-Mathias Hodge Caroline Draxl Pierre Pinson George Kariniotakis Corinna Möhrlen DTU Wind Energy PNNL DWD NREL DTU Elektro Mines ParisTech WEPROG Summary This poster gives an overview of the IEA Wind Task for Wind Power Forecasting. The Operating Agent is Gregor Giebel of DTU, Co-Operating Agent is Will Shaw of PNNL. Collaboration in the task is solicited from everyone interested in the forecasting business. The task runs for three years, 2016- 2018, but will see a second phase for 2019-2021.
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