scholarly journals Layout Design of Human-Machine Interaction Interface of Cabin Based on Cognitive Ergonomics and GA-ACA

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Li Deng ◽  
Guohua Wang ◽  
Suihuai Yu
Keyword(s):  
Ant Colony Algorithm ◽  
Fitness Function ◽  
Layout Design ◽  
Design System ◽  
Human Machine Interaction ◽  
Cognitive Characteristics ◽  
Cognitive Ergonomics ◽  
Drilling Rig ◽  
Interaction Interface ◽  
Machine Interaction

In order to consider the psychological cognitive characteristics affecting operating comfort and realize the automatic layout design, cognitive ergonomics and GA-ACA (genetic algorithm and ant colony algorithm) were introduced into the layout design of human-machine interaction interface. First, from the perspective of cognitive psychology, according to the information processing process, the cognitive model of human-machine interaction interface was established. Then, the human cognitive characteristics were analyzed, and the layout principles of human-machine interaction interface were summarized as the constraints in layout design. Again, the expression form of fitness function, pheromone, and heuristic information for the layout optimization of cabin was studied. The layout design model of human-machine interaction interface was established based on GA-ACA. At last, a layout design system was developed based on this model. For validation, the human-machine interaction interface layout design of drilling rig control room was taken as an example, and the optimization result showed the feasibility and effectiveness of the proposed method.

scholarly journals Quantitative Evaluation of Visual Aesthetics of Human-Machine Interaction Interface Layout

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Li Deng ◽  
Guohua Wang
Keyword(s):  
Interface Design ◽  
Evaluation Method ◽  
Paired Comparison ◽  
Human Machine Interaction ◽  
Factors Affecting ◽  
Drilling Rig ◽  
Interaction Interface ◽  
Variance Contribution ◽  
The Aesthetic ◽  
Machine Interaction

The current research on human-machine interaction interface layout focused on ergonomic analysis, while the research on aesthetics and aesthetic degree calculation of interface layout was insufficient. In order to objectively evaluate the aesthetic degree of interface layout, this paper put forward an aesthetic degree evaluation method of interface design based on Kansei engineering. Firstly, the perceptual image structure of interface aesthetic degree was analyzed from the perspective of aesthetic cognition. Six aesthetic image factors affecting interface aesthetic degree, including proportion, conciseness, order, rhythm, density, and equilibrium, were extracted by factor analysis method, and the variance contribution rate of each factor was taken as the weight. Secondly, according to the six aesthetic degree indexes, the calculation system of interface aesthetic degree was constructed, and the aesthetic degree value of aesthetic image factor was calculated by the corresponding aesthetic degree evaluation mathematical formula. Then, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method was used to analyze the order of aesthetic degree superiority of design schemes, and the comprehensive aesthetic degree evaluation was carried out. Finally, the aesthetic degree evaluation of human-machine interaction interface layout of the driller’s console of an AC variable frequency drilling rig was taken as an example to verify that this method was helpful for designers to optimize the design scheme. The experimental results showed that the proposed method was feasible and effective compared with the method of paired comparison commonly used in psychophysics.

The More You Know: Trust Dynamics and Calibration in Highly Automated Driving and the Effects of Take-Overs, System Malfunction, and System Transparency

2019 ◽  
Vol 62 (5) ◽  
pp. 718-736 ◽  
Author(s):  
Johannes Kraus ◽  
David Scholz ◽  
Dina Stiegemeier ◽  
Martin Baumann
Keyword(s):  
Design System ◽  
Full Potential ◽  
Positive Outcomes ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Human Machine Interaction ◽  
Temporary Decrease ◽  
Free Interaction ◽  
Machine Interaction ◽  
Transparency Condition

Objective This paper presents a theoretical model and two simulator studies on the psychological processes during early trust calibration in automated vehicles. Background The positive outcomes of automation can only reach their full potential if a calibrated level of trust is achieved. In this process, information on system capabilities and limitations plays a crucial role. Method In two simulator experiments, trust was repeatedly measured during an automated drive. In Study 1, all participants in a two-group experiment experienced a system-initiated take-over, and the occurrence of a system malfunction was manipulated. In Study 2 in a 2 × 2 between-subject design, system transparency was manipulated as an additional factor. Results Trust was found to increase during the first interactions progressively. In Study 1, take-overs led to a temporary decrease in trust, as did malfunctions in both studies. Interestingly, trust was reestablished in the course of interaction for take-overs and malfunctions. In Study 2, the high transparency condition did not show a temporary decline in trust after a malfunction. Conclusion Trust is calibrated along provided information prior to and during the initial drive with an automated vehicle. The experience of take-overs and malfunctions leads to a temporary decline in trust that was recovered in the course of error-free interaction. The temporary decrease can be prevented by providing transparent information prior to system interaction. Application Transparency, also about potential limitations of the system, plays an important role in this process and should be considered in the design of tutorials and human-machine interaction (HMI) concepts of automated vehicles.

scholarly journals A Flexible Temperature Sensor for Noncontact Human-Machine Interaction

Materials ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7112
Author(s):  
Shiqi Chen ◽  
Xiaolong Han ◽  
Peng Hong ◽  
Yue Zhang ◽  
Xiangyu Yin ◽  
...  
Keyword(s):  
Temperature Sensor ◽  
Flexible Substrate ◽  
High Sensitivity ◽  
Human Machine Interaction ◽  
Temperature Changes ◽  
Intelligent Robots ◽  
Sensing Material ◽  
Interaction Interface ◽  
Application Potential ◽  
Machine Interaction

Flexible sensors have attracted extensive attention because of their promising applications in the fields of health monitoring, intelligent robots, and electronic skin, etc. During the COVID-19 epidemic, noncontact control of public equipment such as elevators, game consoles, and doors has become particularly important, as it can effectively reduce the risk of cross-infection. In this work, a noncontact flexible temperature sensor is prepared via a simple dip-drying progress, in which poly(3,4-ethylenedioxythiophene):poly(4-styrene sulfonate) (PEDOT:PSS) and printer paper served as the sensing material and the flexible substrate, respectively. We combined the highly sensitive temperature-responsive property of PEDOT:PSS with the good hygroscopicity of printer paper. The prepared sensor shows high sensitivity and good stability in noncontact sensing mode within the temperature range of 20–50 °C. To prove the practicability of the noncontact temperature sensor, a 3 × 2 sensing array is prepared as a noncontact human-machine interface to realize the interaction between player and “Pound-A-Mole game” and a Bluetooth car. These two demos show the sensor′s ability to perceive nearby temperature changes, verifying its application potential as a noncontact human-machine interaction interface.

Evolutionary Computation with User’s Preference for Solving Fuzzy Fitness Forecasting Problems

2020 ◽  
pp. 2159001
Author(s):  
Guo Guangsong ◽  
Chen Liangji
Keyword(s):  
Evolutionary Computation ◽  
Noise Intensity ◽  
Fitness Function ◽  
Prediction Method ◽  
Gray Model ◽  
Interactive Evolutionary Computation ◽  
Nsga Ii ◽  
Human Machine Interaction ◽  
Fitness Set ◽  
Machine Interaction

Interactive Evolutionary Computation (IEC) is a kind of human–machine interaction calculation method derived from evolutionary computation. The main problem of interactive evolutionary computation is that fitness noise can make evolution direction to deviate from user’s preferences because user’s evaluation has cognitive fluctuations and fatigue. To improve these deficiencies, this paper recommends a fuzzy fitness prediction method based on fuzzy gray model FGM (1,1) with a precise number fitness. First of all, the relationship between fitness noise intensity and the fitness function is proposed. Then, it suggests a linear programming of fuzzy fitness set width under the restriction of minimum noise intensity, which can calculate the fuzzy fitness prediction parameters. Finally, the fuzzy gray model forecasts the fuzzy fitness. The proposed method uses new computation of individual’s dominance relation and crowding distance to realize NSGA–II. The experimental results verify that this method has advantages in improving optimization quality, alleviating user’s fatigue and improving efficiency in exploration.

Parametric Finite Element Analysis of the Shipyard Lifting Lug Based on VB and ANSYS Interface

2013 ◽  
Vol 655-657 ◽  
pp. 264-268
Author(s):  
Shao Fen Lin ◽  
Qing Lin Chen ◽  
Zhao Yi Zhu
Keyword(s):  
Finite Element Analysis ◽  
Finite Element ◽  
Work Efficiency ◽  
Human Machine Interaction ◽  
Element Analysis ◽  
The Finite Element Analysis ◽  
Interaction Interface ◽  
Parametric Finite Element Analysis ◽  
Turn Over ◽  
Machine Interaction

The software compiled by VB had good visualization and the finite element analysis of ANSYS was a rapid, precise and effective method, both of these advantages were combined by the interface technology between VB and ANSYS. Through parameterizing the structure, material and load of the lifting lug, a friendly human-machine interaction interface was developed in this paper. This software improved shipyard's engineering designers work efficiency at all levels, the safety of hull block turn-over and lifting was improved too.

scholarly journals Self-Powered Intelligent Human-Machine Interaction for Handwriting Recognition

Research ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Hang Guo ◽  
Ji Wan ◽  
Haobin Wang ◽  
Hanxiang Wu ◽  
Chen Xu ◽  
...  
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Human Computer Interaction ◽  
Supervised Machine Learning ◽  
Triboelectric Nanogenerator ◽  
Human Machine Interaction ◽  
The Neural Network ◽  
Interaction Interface ◽  
Machine Interaction ◽  
Computer Interaction

Handwritten signatures widely exist in our daily lives. The main challenge of signal recognition on handwriting is in the development of approaches to obtain information effectively. External mechanical signals can be easily detected by triboelectric nanogenerators which can provide immediate opportunities for building new types of active sensors capable of recording handwritten signals. In this work, we report an intelligent human-machine interaction interface based on a triboelectric nanogenerator. Using the horizontal-vertical symmetrical electrode array, the handwritten triboelectric signal can be recorded without external energy supply. Combined with supervised machine learning methods, it can successfully recognize handwritten English letters, Chinese characters, and Arabic numerals. The principal component analysis algorithm preprocesses the triboelectric signal data to reduce the complexity of the neural network in the machine learning process. Further, it can realize the anticounterfeiting recognition of writing habits by controlling the samples input to the neural network. The results show that the intelligent human-computer interaction interface has broad application prospects in signature security and human-computer interaction.

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