A Flexible Methodology and Support Environment for Building Task Models

Mixed Interactive Systems (MIS) is a generic term encompassing mixed and augmented reality, augmented virtuality, and tangible interfaces systems. The work we present in this paper deals with the design of such systems. Several models have been proposed to describe mixed interactive systems. However, these models neither integrate MIS in the global user activity, nor take into account the dynamics of mixed interactive situations. Task models offer an interesting approach to cover these aspects. The purpose of our work is to contribute to the design of MIS by articulating mixed interaction models and tasks models. This paper presents complementarities and common points between these models, which will be used as the basis for the rules to articulate the task and interaction models.

This chapter claims that task models per se do not contain sufficient and necessary information to permit automatic generation of interactive systems. Beyond this, we claim that they must not contain sufficient and necessary information otherwise they could no longer be considered as task models. On the contrary we propose a way of exploiting in a synergistic way task models with other models to be built during the development process. This chapter presents a set of tools supporting the development of interactive systems using two different notations. One of these notations called ConcurTaskTree (CTT) is used for task modeling. The other notation called Interactive Cooperative Objects (ICO) is used for system modeling. Even though these two kinds of models represent two different views of the same world (a user interacting with an interactive system), they are built by different people (human factors specialist for the task models and software engineer for the system models) and are used independently. The aim of this chapter is to propose the use of scenarios as a bridge between these two views. On the task modeling side, scenarios are seen as a possible trace of user’s activity. On the system side, scenarios are seen as a trace of user’s actions. This generic approach is presented on a case study in the domain of Air Traffic Control. As both CTT and ICO notations are tool supported (environments are respectively CTTE and PetShop) an integration tool based on this notion of scenarios is presented. Its use on the selected case study is also presented in detail.KeywordsModel CheckerUser ServiceInteractive SystemTask ModelRadar ImageThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Task modeling is undoubtedly a key step for task analysis during the development of iterative systems since it helps not only in the understanding of what users want but also in how to design for them. As a consequence, it should be considered as indispensable while specifying the requirements of an interactive system. With this in mind, we analyzed the requirement specifications of a typical interactive system which is a compulsory element of the final grade for a human–computer interaction course in two Master’s degree programs at the University of Valenciennes. To that end, we decided to use an approach based on project-based learning. Sixty-three requirement specifications performed since 2010 were investigated to find out how the task modeling was represented. Moreover, suggestions concerning pedagogical improvement made by the students in an open question on the evaluation form were analyzed using the ground theory method. The results showed that since students are not required to perform task modeling by the requirement specification, they do not do so even in the case of complex interactive systems. Criticism, positive and improvement issues raised by the students were also identified. In this paper, we present a detailed analysis of this study that opens up questions about HCI education and effective learning of task modeling, and, as a consequence, its potential use in industry.

This paper presents how to integrate formally based models relying on the Synchronous Dataflow Model-of- Computation (MoC) in a UML/MARTE component-based application model. This model corresponds to a flexible and expressive modelling methodology, which facilitates finding and building an application model with the intended semantics, but does not help to ensure a strict fulfilment of functional and extrafunctional requirements. However, this capability has become a need in the context of modelling mixed-criticality applications. This paper shows how the component-based UML/MARTE models captured in such a flexible methodology can integrate parts transformable into synchronous data-flows. This formalism facilitates the analysis of the functional and extra-functional properties of such parts. Specifically, the paper shows a set of modelling patterns which can be translated into SDF counterparts. Relying on these patterns, a framework has been implemented which enables a bi-directional interoperability between the UML/MARTE models abiding the patterns and the formally-based ForSyDe methodology.

Task models are able to specify the behavior of actors in ambient environments in a compact and readable form. Their original notations have to be extended to meet the requirements in this context. The corresponding tool support has to be flexible in terms of integrating domain concepts rapidly. We propose a model-based approach for tool support of task model editors. By doing so, new modeling concepts can be introduced easily. Thus task models can be extended and provide a basis for analysis and high level design for a wide spread of domains. We fortify our approach by an example in the domain of AmI.KeywordsTask modelAmImodel-based developmentMarkov model

An editor for the conceptual models of interactive knowledge-acquisition tools

INTRODUCTION:The early benefit assessment of drugs was introduced in Germany with the ‘Act to Reorganize the Pharmaceuticals’ Market in the SHI’ (AMNOG) in 2011. Before submitting the manufacturer's dossier, optional scientific advice is offered by the Federal Joint Committee (G-BA). The objective was to elicit manufacturers experience with the scientific advice offered by the Federal Joint Committee.METHODS:To prepare the survey, several manufacturers were interviewed on their experience with the scientific advice offered by the Federal Joint Committee. Subsequently, a questionnaire was developed to collect information for this purpose, comprising eight items on different topics aimed at understanding the perceived quality of the scientific advice provided.RESULTS:The qualitative part comprised seven manufacturers who had received between one and ten advisories before the end of 2012. With regard to the quantitative elicitation part, a total of sixty-one completed questionnaires from nineteen manufacturers were included until the beginning of 2015 (corresponding to almost 25 percent of the overall implemented scientific advice). Fourteen cases were about so called “early” scientific advice in terms of relating to evidence before commencing phase-III trials, forty-four cases concerned “late” scientific advice (pivotal trials were just conducted or already terminated), another two concerned repeated scientific advice and finally, four referred to miscellaneous contents (multiple answers possible). Both, the preceding qualitative and the following quantitative part of the elicitation, highlighted points about the process as well as the content shortcomings from an industry's point of view: inconsistencies, lacking expertise with conducting clinical trials, partially incomplete answers and a low readiness to engage in dialogue were criticized. On the other hand, the majority of respondents showed a positive attitude concerning unambiguousness, completeness, traceability, atmosphere and the protocol of the advice. Over the course of time, propositions on study design, agreement with the determined appropriate comparative therapy and subgroup definitions improved significantly.CONCLUSIONS:A more active involvement of further stakeholders and the incorporation of procedural elements from other health are systems with longer experience could improve the scientific advice provided.

Task models are widely used within the research field of HCI for the model-based development of interactive systems. Recently introduced approaches applied task models further to model the cooperative behavior of people using devices within a smart environment. We describe a method of model-based usability evaluation to evaluate interactive systems, with a particular focus on smart environments, which are developed based on task models. We consider the evaluation in early development stages to interactively walk through the models and in later stages to execute a test case within a real environment. The paper provides results of a prototypical implementation.

Under the modern information-based operational environment, display/control system interface is a bridge between operator and weapon, and almost half of the code of interactive system is related with the graphical user interface, so a successful interface design is critical to interactive system. Based on this background conditions, this paper presents an approach to extract the dialog model from the task model for creating interfaces of the display/control system. Specific processes are as followed: establishing the Concur Task Tree (CTT) task model according to the specific tasks; transforming the task model into the priority model, and then converting it to the tree of temporal relation expression; extracting the dialog model (partially) in the form of state transition net (STN); finally, obtaining the interface model of display/control system.

A new task model is proposed to assist negotiation for resource usage in cyber-physical systems. The task model captures the complex timing behavior in event-triggered control systems so that better resource planning can be obtained.

Multidisciplinary perspective on accident investigation

In this paper the authors present a structured method for automatically generating User Interfaces for e-learning environments. The method starts with a definition of the learning scenario where the different goals, jobs (professor-student/trainer-learner), and tasks are described and stored in a template. After, the description is mapped to FlowiXML, a learning process authoring tool, where graphically trainers or content designers draw the overall process. A learning process is viewed as a workflow and modeled using Petri net notation. From each step in the process model more details are added using user task models; user’s activity interacting with a user interface is stored in such diagrams. Then, a transformational method for developing user interfaces of interactive information systems is used that starts from a task model and a domain model to progressively derive a final user interface. This method consists of three steps: deriving one or many abstract user interfaces from the task model, deriving one or many concrete user interfaces from each abstract interface, and producing the code of the final user interfaces corresponding to each concrete interface. The models and the transformations of these models are all expressed in UsiXML (User Interface eXtensible Markup Language) and maintained in a model repository that can be accessed by the suite of tools. Developing user interfaces in this way facilitates its automated generation over multiple computing platforms while maintaining portability and consistency between the multiple versions. Our approach is illustrated on an open Learning environment using a case study.

This research was motivated by our interest in understanding the criteria for measuring the success of a recommender system from users' point view. Even though existing work has suggested a wide range of criteria, the consistency and validity of the combined criteria have not been tested. In this paper, we describe a unifying evaluation framework, called ResQue (Recommender systems' Quality of user experience), which aimed at measuring the qualities of the recommended items, the system's usability, usefulness, interface and interaction qualities, users' satisfaction with the systems, and the influence of these qualities on users' behavioral intentions, including their intention to purchase the products recommended to them and return to the system. We also show the results of applying psychometric methods to validate the combined criteria using data collected from a large user survey. The outcomes of the validation are able to 1) support the consistency, validity and reliability of the selected criteria; and 2) explain the quality of user experience and the key determinants motivating users to adopt the recommender technology. The final model consists of thirty two questions and fifteen constructs, defining the essential qualities of an effective and satisfying recommender system, as well as providing practitioners and scholars with a cost-effective way to evaluate the success of a recommender system and identify important areas in which to invest development resources.

User interface design should be strongly guided by the user’s tasks to be executed with the system. One practical way of achieving this is the explicit support of the transition from task modelling to dialogue modelling. Here, the integration of the models plays a central role. The models to be used are still under discussion and the adoption of their meta-models becomes an increasing requirement of tools supporting task-based user interface design. To cope with these aspects and as a first step towards modelling explicit links between task models and dialogue models we propose a theoretical modelling framework, called Coherent Modelling Framework CMF, supported by a general modelling tool. This framework can house task models as well as dialogue models, thus integrating them and enabling a smooth transition between the two. In fact, the approach is even more general, covering virtually any type of discrete modelling structure. The approach covers the single models, allows expressing links between the models, and enables the designer to modify the meta-models, i.e. the models describing the models used. In this paper we discuss the modelling framework and briefly describe a proof-concept-version of a tool supporting it.

Intelligent Transportation Systems have gained significant attention among Internet of Things applications due to its specific features and its high capability to promote the innovation of the automotive industries. As part of smart cities, smart mobility initiatives offer new opportunities for intelligent transportation systems to maximize the utilization of the time-sensitive data that are streaming out of different sensory transport resources to support “newcasting” instead of “forecasting” technique. As a result, efficient information dissemination has become the new production factor, notably in terms of mitigating traffic congestion, maximizing bandwidth utilization, and reducing transmission power consumption over the network. Cloud Computing and its counterparts have been established as relatively stable environments for proving a wide number of tackled solutions. However, the limitations of network bandwidth as well as the rapid expansion into the data transfer rate are still the bottlenecks of vehicular networks. The main contribution of this study is to improve Vehicular Ad hoc Network performance in real-time using a geographically distributed computing architecture based on fog technology. This architecture presents a set of novel techniques from different points of view. These novelties include, (i) a flexible registration methodology for improving the navigation process among mobile vehicles; (ii) a generic distributed mechanism to adjust the communication range and the network connectivity; and (iii) a new mathematical model to ensure transmission reliability through establishing powerful communication channels between the vehicular entities and fog layer. The effectiveness of the proposed architecture is evaluated using several performance metrics such as throughput, delay time, and jitter. The experimental results reveal that the worthiness of the proposed architecture to meet the quality of service requirements is more than other state-of-the-art techniques in the literature review.