Transversal Perspectives on Human–Machine Interaction: The Effect of Age in Human–Machine Systems

Author(s):  
Anabela dos Santos Simões ◽  
Marta Pereira ◽  
Maria Panou
2004 ◽  
pp. 1-27
Author(s):  
Kerstin Rose ◽  
Leon Urbas ◽  
Alexander Kunzer ◽  
Martin Christof Kindsmuller ◽  
Sandro Leuchter

UseWorld.net is a federated user adaptive Internet portal that supports information exchange and cooperation in research and development in the area of human machine interaction. It has been jointly developed with members of Center of Human-Machine-Systems (ZMMS, TU Berlin), Chair of Industrial Engineering and Ergonomics (RWTH Aachen), Chair for Industrial Design (University of Essen) and Center for Human-Machine-Interaction (ZMMI, University of Kaiserslautern). The portal is operated by an independent open incorporated society. It integrates manifold information services (online journal, different thematic link collections, conference database, expert database) and a sophisticated cooperation component to support distributed teams by providing shared workspaces. Software agents for community awareness tasks and a clean and consistent interaction design complete the solution and support the portal’s innovative operation concept, which intends to activate the users to become editors.


1980 ◽  
Vol 24 (1) ◽  
pp. 453-457 ◽  
Author(s):  
John M. Reising ◽  
P.R. Krishnaiah

In complex human-machine systems, multidimensional behavior is required of the operator. Consequently, there is no commonly-accepted, single measure of operator performance which can be utilized to determine the efficiency of the human-machine interaction. Because the behavior is multidimensional, multivariate statistics must be used to analyze the multiple measures gathered during system evaluation. While multivariate analogues to analysis of variance (ANOVA) exist, there are also a number of candidate multivariate analogues to the post-ANOVA simultaneous comparison tests. This paper describes a newly developed multivariate, simultaneous comparison test–Finite Intersection Test (FIT)–and provides an example of FIT's application to the analysis of multivariate data.


Author(s):  
Conghui Liu

Improving user’s trust appropriately could help in designing an intelligent system and make it work effectively, especially with the fast growth of Web-base technology. This chapter introduces the solutions of improving user’s trust in human-machine interaction (HMI), especially for electronic commerce (e-commerce). The author firstly reviews the concept of trust and the main factors that affects the appropriateness of user’s trust in human-machine interaction, such as the properties of machine systems, the properties of human, and context. On the basis of these, the author further discusses the current state, challenges, problems and limitations of establishing and improving the user’s trust in human-machine interaction. Finally, the author summarizes and evaluates the existing solutions for improving the user’s trust appropriately in e-commerce environment.


2017 ◽  
Vol 12 (1) ◽  
pp. 77-82 ◽  
Author(s):  
Matthew Johnson ◽  
Jeffrey M. Bradshaw ◽  
Paul J. Feltovich

The growth of sophistication in machine capabilities must go hand in hand with growth of sophistication in human–machine interaction capabilities. To continue advancement as we build today’s intelligent machines, designers need formative tools for creating sociotechnical systems. In this article, we will briefly assess the appropriateness of “levels of automation” as a tool for designing human–machine systems. Additionally, we present coactive design and interdependence analysis as a viable alternative tool moving forward into more advanced and sophisticated human–machine systems.


Author(s):  
Thorsten Blecker ◽  
Günter Graf

The quality of HMI in automation is an important issue in manufacturing. This special form of interaction occurs when the combination of human abilities and machine features are necessary in order to perform the tasks in manufacturing. Balint (1995) has identified three categories of such human-machine systems: 1. Machines might do the job without human involvement, but the feasibility is questionable. For example, weld seams in car assembly are made mostly autonomously by robots, but in many cases, humans have to guide the robot to the weld point, because the robot is not able to locate the point correctly, which is a relatively easy task for a human. 2. Humans might do the job without machines, but the efficiency/reliability is questionable. This is the case in almost all cases of automation (e.g., the varnishing of cars). 3. HMI is necessary (no purely machine- or human-based execution is possible), although robots today are widely in use; in many cases, they cannot substitute humans completely, because the possible conflicts that can occur are so diverse that a robot alone cannot manage them. The term HMI is used widely for the interaction of a human and a somewhat artificial, automated facility, which is true in many situations, including HCI. In this article, we speak of HMI in industrial settings. We term the machine especially for industrial facilities for producing a certain (physical) output; in this case, the term man-machine interaction also is used synonymously for HMI. We define HMI as the relation between a human operator and one or more machines via an interface for embracing the functions of machine handling, programming, simulation, maintenance, diagnosis, and initialization.


Author(s):  
Conghui Liu

Improving user’s trust appropriately could help in designing an intelligent system and make it work effectively, especially with the fast growth of Web-base technology. This chapter introduces the solutions of improving user’s trust in human-machine interaction (HMI), especially for electronic commerce (e-commerce). The author firstly reviews the concept of trust and the main factors that affects the appropriateness of user’s trust in human-machine interaction, such as the properties of machine systems, the properties of human, and context. On the basis of these, the author further discusses the current state, challenges, problems and limitations of establishing and improving the user’s trust in human-machine interaction. Finally, the author summarizes and evaluates the existing solutions for improving the user’s trust appropriately in e-commerce environment.


2021 ◽  
pp. 1-9
Author(s):  
Harshadkumar B. Prajapati ◽  
Ankit S. Vyas ◽  
Vipul K. Dabhi

Face expression recognition (FER) has gained very much attraction to researchers in the field of computer vision because of its major usefulness in security, robotics, and HMI (Human-Machine Interaction) systems. We propose a CNN (Convolutional Neural Network) architecture to address FER. To show the effectiveness of the proposed model, we evaluate the performance of the model on JAFFE dataset. We derive a concise CNN architecture to address the issue of expression classification. Objective of various experiments is to achieve convincing performance by reducing computational overhead. The proposed CNN model is very compact as compared to other state-of-the-art models. We could achieve highest accuracy of 97.10% and average accuracy of 90.43% for top 10 best runs without any pre-processing methods applied, which justifies the effectiveness of our model. Furthermore, we have also included visualization of CNN layers to observe the learning of CNN.


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