Ontology modelling of intelligent HCI in aircraft cockpit

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Xia Zhang ◽  
Youchao Sun ◽  
Yanjun Zhang
Keyword(s):  
Learning Ability ◽  
Knowledge Representation And Reasoning ◽  
Content Type ◽  
Meta Model ◽  
Knowledge Reasoning ◽  
Ontology Model ◽  
Semantic Modelling ◽  
Model Complex ◽  
Cognitive Behaviours ◽  
Traditional Approaches

Purpose Semantic modelling is an essential prerequisite for designing the intelligent human–computer interaction in future aircraft cockpit. The purpose of this paper is to outline an ontology-based solution to this issue. Design/methodology/approach The scenario elements are defined considering the cognitive behaviours, system functions, interaction behaviours and interaction situation. The knowledge model consists of a five-tuple array including concepts, relations, functions, axioms and instances. Using the theory of belief-desire-intention, the meta-model of cognitive behaviours is established. The meta-model of system functions is formed under the architecture of sub-functions. Supported by information flows, the meta-model of interaction behaviours is presented. Based on the socio-technical characteristics, the meta-model of interaction situation is proposed. The knowledge representation and reasoning process is visualized with the semantic web rule language (SWRL) on the Protégé platform. Finally, verification and evaluation are carried out to assess the rationality and quality of the ontology model. Application scenarios of the proposed modelling method are also illustrated. Findings Verification results show that the knowledge reasoning based on SWRL rules can further enrich the knowledge base in terms of instance attributes and thereby improve the adaptability and learning ability of the ontology model in different simulations. Evaluation results show that the ontology model has a good quality with high cohesion and low coupling. Practical implications The approach presented in this paper can be applied to model complex human–machine–environment systems, from a semantics-driven perspective, especially for designing future cockpits. Originality/value Different from the traditional approaches, the method proposed in this paper tries to deal with the socio-technical modelling issues concerning multidimensional information semantics. Meanwhile, the constructed model has the ability of autonomous reasoning to adapt to complex situations.

Modeling Affordances and Functioning for Personalized Robotic Assistance

2020 ◽  
Author(s):  
Alessandro Umbrico ◽  
Gabriella Cortellessa ◽  
Andrea Orlandini ◽  
Amedeo Cesta
Keyword(s):  
Domain Knowledge ◽  
Experimental Tests ◽  
International Classification Of Functioning ◽  
Knowledge Representation And Reasoning ◽  
Health State ◽  
Knowledge Reasoning ◽  
Cognitive Assistance ◽  
Ontological Model ◽  
And Function

A key aspect of robotic assistants is their ability to contextualize their behavior according to different needs of assistive scenarios. This work presents an ontology-based knowledge representation and reasoning approach supporting the synthesis of personalized behavior of robotic assistants. It introduces an ontological model of health state and functioning of persons based on the International Classification of Functioning, Disability and Health. Moreover, it borrows the concepts of affordance and function from the literature of robotics and manufacturing and adapts them to robotic (physical and cognitive) assistance domain. Knowledge reasoning mechanisms are developed on top of the resulting ontological model to reason about stimulation capabilities of a robot and health state of a person in order to identify action opportunities and achieve personalized assistance. Experimental tests assess the performance of the proposed approach and its capability of dealing with different profiles and stimuli.

Real-time modeling of retractable self-launching glider using spreadsheets

2017 ◽  
Vol 89 (6) ◽  
pp. 791-796
Author(s):  
Yasser A. Nogoud ◽  
Attie Jonker ◽  
Shuhaimi Mansor ◽  
A.A.A. Abuelnuor
Keyword(s):  
Control System ◽  
High Performance ◽  
Cost Effective ◽  
Visual Presentation ◽  
Content Type ◽  
Spreadsheet Model ◽  
Time Modeling ◽  
Model Complex ◽  
Effective Development ◽  
And Control

Purpose This paper aims to propose a spreadsheet method for modeling and simulation of a retraction system mechanism for the retractable self-launching system for a high-performance glider. Design/methodology/approach More precisely, the method is based on parametric link design using Excel spreadsheets. Findings This method can be used for kinematic and dynamic analysis, graphical plotting and allows simulation of control kinematics with the ability to make quick and easy parametric changes to a design. It also has the ability to calculate the loads imposed on each component in the control system as a function of input loads and position. Practical implications This paper shows that it is possible to model complex control systems quickly and easily using spreadsheet programs already owned by most small companies. The spreadsheet model is a parametric model, and it gives a simple visual presentation of the control system with interactive movement and control by the user. Originality/value This spreadsheet model in conjunction with a simple CAD program enables the rapid and cost-effective development of control system components.

Conceptualising innovative price models: the RITE framework

2019 ◽  
Vol 14 (4) ◽  
pp. 540-558 ◽  
Author(s):  
Mathias Cöster ◽  
Einar Iveroth ◽  
Nils-Göran Olve ◽  
Carl-Johan Petri ◽  
Alf Westelius
Keyword(s):  
Literature Review ◽  
Design Methodology ◽  
Business Models ◽  
Final Outcome ◽  
Empirical Testing ◽  
Content Type ◽  
Meta Model ◽  
Practical Implications ◽  
A Current ◽  
Structured Literature Review

Purpose The purpose of this paper is to lay a current, research-based foundation for investigation of the concept of innovative price models and its connection to business models. Design/methodology/approach The design is composed of a structured literature review of articles on price models published in 22 journals during 42 years. This then serves as a base for a subsequent conceptual discussion about the foundation of innovative price models. Findings The literature review yields only very few results that are loosely scattered across various areas and mostly without any kind of deeper exploration of the concept of price models. The paper therefore goes on to conceptually explore some fundamental conditions that might influence or even determine price models. The final outcome of this exploration is the relation, intention, technology and environment (RITE) framework that is a meta-model for conceptualising innovative price models. Research limitations/implications The literature review could include additional journals and areas, and empirical testing of the RITE framework as yet has been limited. Practical implications The RITE framework can be used by practitioners as a tool for investigating the potential and usefulness of developing the capability to handle innovative price models. Originality/value The RITE framework provides fundamental conditions, which influence, or even determine, how innovative price models are developed and applied.

Use of a sonification system for science learning by people who are blind

2016 ◽  
Vol 10 (4) ◽  
pp. 187-198 ◽  
Author(s):  
Orly Lahav ◽  
Nuha Chagab ◽  
Vadim Talis
Keyword(s):  
Complex Systems ◽  
Conceptual Knowledge ◽  
Science Curriculum ◽  
Low Cost ◽  
Agent Based Modeling ◽  
Learning System ◽  
Learning Ability ◽  
Content Type ◽  
Agent Based ◽  
K 12

Purpose The purpose of this paper is to examine a central need of students who are blind: the ability to access science curriculum content. Design/methodology/approach Agent-based modeling is a relatively new computational modeling paradigm that models complex dynamic systems. NetLogo is a widely used agent-based modeling language that enables exploration and construction of models of complex systems by programming and running the rules and behaviors. Sonification of variables and events in an agent-based NetLogo computer model of gas in a container is used to convey phenomena information. This study examined mainly two research topics: the scientific conceptual knowledge and systems reasoning that were learned as a result of interaction with the listen-to-complexity (L2C) environment as appeared in answers to the pre- and post-tests and the learning topics of kinetic molecular theory of gas in chemistry that was learned as a result of interaction with the L2C environment. The case study research focused on A., a woman who is adventitiously blind, for eight sessions. Findings The participant successfully completed all curricular assignments; her scientific conceptual knowledge and systems reasoning became more specific and aligned with scientific knowledge. Practical implications A practical implication of further studies is that they are likely to have an impact on the accessibility of learning materials, especially in science education for students who are blind, as equal access to low-cost learning environments that are equivalent to those used by sighted users would support their inclusion in the K-12 academic curriculum. Originality/value The innovative and low-cost learning system that is used in this research is based on transmittal of visual information of dynamic and complex systems, providing perceptual compensation by harnessing auditory feedback. For the first time the L2C system is based on sound that represents a dynamic rather than a static array. In this study, the authors explore how a combination of several auditory representations may affect cognitive learning ability.

Predictors of employees’ self-reported future learning ability and disengagement at work

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Debora Jeske ◽  
Sonia Lippke
Keyword(s):  
Job Characteristics ◽  
Path Model ◽  
Learning Ability ◽  
Cross Sectional ◽  
Content Type ◽  
Work Meaningfulness ◽  
Learning At Work ◽  
Employee Disengagement ◽  
The Relationship ◽  
Future Learning

Purpose The purpose of this study is to examine the relationship between job characteristics that foster learning (experience with and demand for continuous learning at work, skills variety and autonomy) as potential predictors of self-reported outcomes, such as future learning ability and employee disengagement at work for a cohort of employees with no or very limited job change experience. Further consideration was given to employees’ experiences at work (meaningfulness and recognition at work) as potential mediators in this relationship between job characteristics and employee outcomes. Design/methodology/approach A cross-sectional design was applied. Participants (N = 284) were recruited from Northern Germany and asked to complete a paper-and-pencil survey. The results were subsequently analyzed using path models to examine direct and indirect effects associated with mediation. Findings Path model analysis indicated that job characteristics promoting learning at work are positive predictors of self-reported future learning ability and negative predictors of disengagement. Both meaningfulness and recognition predict future learning ability as well. However, these variables only operated as significant mediators in the relationship between job characteristics and employee disengagement (but not self-reported future learning ability). Originality/value The study outlines the importance of job characteristics and employee experience to understand employees’ beliefs about their learning ability and engagement at work. The findings highlight the importance of meaningfulness and recognition for employees, as well as the role of learning-supportive job characteristics.

Micro-drilling process control by using adaptive sliding controller

2014 ◽  
Vol 31 (2) ◽  
pp. 201-215
Author(s):  
Hung-Yi Chen
Keyword(s):  
Process Control ◽  
Controller Design ◽  
Sliding Mode ◽  
Learning Ability ◽  
Sliding Mode Controller ◽  
Drilling Process ◽  
Time Varying ◽  
Content Type ◽  
Micro Drilling ◽  
Fuzzy Compensator

Purpose – Recently, the micro-positioning technology has become more important for achieving the requirement of precision machinery. The piezo-actuator plays a very important role in this application area. A model-free adaptive sliding controller with fuzzy compensation is proposed for a piezo-actuated micro-drilling process control in this paper. The paper aims to discuss these issues. Design/methodology/approach – Due to the system's nonlinear and time-varying characteristics, this control strategy employs the functional approximation technique to establish the unknown function for releasing the model-based requirement of the sliding mode control. In addition, a fuzzy scheme with online learning ability is augmented to compensate for the finite approximation error and facilitate the controller design. Findings – The Lyapunov direct method can be applied to find adaptive laws for updating coefficients in the approximating series and tuning parameter in the fuzzy compensator to guarantee the control system stability. With the addition adaptive fuzzy compensator, as less as five Fourier series functions can be used to approximate the nonlinear time-varying function for designing a sliding mode controller for micro-drilling process control. Originality/value – The important advantages of this approach are to achieve the sliding mode controller design without the system dynamic model requirement and release the trial-and-error work of selecting approximation function.

Village as a discursive space

2014 ◽  
Vol 13 (3) ◽  
pp. 473-489
Author(s):  
Ivan Gololobov
Keyword(s):  
Discourse Analysis ◽  
Rural Communities ◽  
Empirical Studies ◽  
Theory And Practice ◽  
Discursive Space ◽  
Content Type ◽  
Traditional Approaches ◽  
Political Logic

Discourse analysis in both its theory and practice is traditionally concerned with politics. The sphere of the non-political rarely attracts attention of the researchers. It appears to be invisible to discourse theorists and unprivileged in empirical studies of discourse. This article aims at filling this gap. With the example of a Russian village it dwells on the discursive organisation of rural communities whose radically “personalised” world resists traditional approaches to political logic and suggests different modes of relations, agency, and power.

A multi-agent system for distributed smartphone sensing cycling in smart cities

2020 ◽  
Vol 22 (1) ◽  
pp. 119-134
Author(s):  
Theodoros Anagnostopoulos ◽  
Chu Luo ◽  
Jino Ramson ◽  
Klimis Ntalianis ◽  
Vassilis Kostakos ◽  
...  
Keyword(s):  
Real Time ◽  
Smart City ◽  
Spatiotemporal Data ◽  
Inference Model ◽  
Data Set ◽  
Smartphone Sensing ◽  
Content Type ◽  
Traffic Lights ◽  
Model Complex ◽  
Multi Agent

Purpose The purpose of this paper is to propose a distributed smartphone sensing-enabled system, which assumes an intelligent transport signaling (ITS) infrastructure that operates traffic lights in a smart city (SC). The system is able to handle priorities between groups of cyclists (crowd-cycling) and traffic when approaching traffic lights at road junctions. Design/methodology/approach The system takes into consideration normal probability density function (PDF) and analytics computed for a certain group of cyclists (i.e. crowd-cycling). An inference model is built based on real-time spatiotemporal data of the cyclists. As the system is highly distributed – both physically (i.e. location of the cyclists) and logically (i.e. different threads), the problem is treated under the umbrella of multi-agent systems (MAS) modeling. The proposed model is experimentally evaluated by incorporating a real GPS trace data set from the SC of Melbourne, Australia. The MAS model is applied to the data set according to the quantitative and qualitative criteria adopted. Cyclists’ satisfaction (CS) is defined as a function, which measures the satisfaction of the cyclists. This is the case where the cyclists wait the least amount of time at traffic lights and move as fast as they can toward their destination. ITS system satisfaction (SS) is defined as a function that measures the satisfaction of the ITS system. This is the case where the system serves the maximum number of cyclists with the fewest transitions between the lights. Smart city satisfaction (SCS) is defined as a function that measures the overall satisfaction of the cyclists and the ITS system in the SC based on CS and SS. SCS defines three SC policies (SCP), namely, CS is maximum and SS is minimum then the SC is cyclist-friendly (SCP1), CS is average and SS is average then the SC is equally cyclist and ITS system friendly (SCP2) and CS is minimum and SS is maximum then the SC is ITS system friendly (SCP3). Findings Results are promising toward the integration of the proposed system with contemporary SCs, as the stakeholders are able to choose between the proposed SCPs according to the SC infrastructure. More specifically, cyclist-friendly SCs can adopt SCP1, SCs that treat cyclists and ITS equally can adopt SCP2 and ITS friendly SCs can adopt SCP3. Originality/value The proposed approach uses internet connectivity available in modern smartphones, which provide users control over the data they provide to us, to obviate the installation of additional sensing infrastructure. It extends related study by assuming an ITS system, which turns traffic lights green by considering the normal PDF and the analytics computed for a certain group of cyclists. The inference model is built based on the real-time spatiotemporal data of the cyclists. As the system is highly distributed – both physically (i.e. location of the cyclists) and logically (i.e. different threads), the system is treated under the umbrella of MAS. MAS has been used in the literature to model complex systems by incorporating intelligent agents. In this study, the authors treat agents as proxy threads running in the cloud, as they require high computation power not available to smartphones.

Iterative problem solving in teams: insights from an agent-based simulation

2016 ◽  
Vol 22 (1/2) ◽  
pp. 2-21 ◽  
Author(s):  
Aleksey Martynov ◽  
Dina Abdelzaher
Keyword(s):  
Problem Solving ◽  
Majority Rule ◽  
Optimal Solution ◽  
Complex Problem ◽  
Practical Significance ◽  
Problem Complexity ◽  
Content Type ◽  
Agent Based ◽  
Model Complex ◽  
Agent Based Simulations

Purpose – This paper aims to evaluate the effect of knowledge overlap, search width and problem complexity on the quality of problem-solving in teams that use the majority rule to aggregate heterogeneous knowledge of the team members. Design/methodology/approach – The paper uses agent-based simulations to model iterative problem-solving by teams. The simulation results are analyzed using linear regressions to show the interactions among the variables in the model. Findings – We find that knowledge overlap, search width and problem complexity interact to jointly impact the optimal solution in the iterative problem-solving process of teams using majority rule decisions. Interestingly, we find that more complex problems require less knowledge overlap. Search width and knowledge overlap act as substitutes, weakening each other’s performance effects. Research limitations/implications – The results suggest that team performance in iterative problem-solving depends on interactions among knowledge overlap, search width and problem complexity which need to be jointly examined to reflect realistic team dynamics. Practical implications – The findings suggest that team formation and the choice of a search strategy should be aligned with problem complexity. Originality/value – This paper contributes to the literature on problem-solving in teams. It is the first attempt to use agent-based simulations to model complex problem-solving in teams. The results have both theoretical and practical significance.

Application of a new local effective constrained response surface method in structural reliability optimization design

2019 ◽  
Vol 36 (3) ◽  
pp. 1055-1078 ◽  
Author(s):  
Hailiang Su ◽  
Fengchong Lan ◽  
Yuyan He ◽  
Jiqing Chen
Keyword(s):  
Response Surface ◽  
Response Surface Method ◽  
Optimization Design ◽  
Structural Reliability ◽  
Reliability Optimization ◽  
Content Type ◽  
Meta Model ◽  
Proxy Model ◽  
Surface Method ◽  
Sampling Points

Purpose Meta-model method has been widely used in structural reliability optimization design. The main limitation of this method is that it is difficult to quantify the error caused by the meta-model approximation, which leads to the inaccuracy of the optimization results of the reliability evaluation. Taking the local high efficiency of the proxy model, this paper aims to propose a local effective constrained response surface method (LEC-RSM) based on a meta-model. Design/methodology/approach The operating mechanisms of LEC-RSM is to calculate the index of the local relative importance based on numerical theory and capture the most effective area in the entire design space, as well as selecting important analysis domains for sample changes. To improve the efficiency of the algorithm, the constrained efficient set algorithm (ESA) is introduced, in which the sample point validity is identified based on the reliability information obtained in the previous cycle and then the boundary sampling points that violate the constraint conditions are ignored or eliminated. Findings The computational power of the proposed method is demonstrated by solving two mathematical problems and the actual engineering optimization problem of a car collision. LEC-RSM makes it easier to achieve the optimal performance, less feature evaluation and fewer algorithm iterations. Originality/value This paper proposes a new RSM technology based on proxy model to complete the reliability design. The originality of this paper is to increase the sampling points by identifying the local importance of the analysis domain and introduce the constrained ESA to improve the efficiency of the algorithm.

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