Comfort Evaluation Model Based on Region of Interest and Contrast of Stereo Images

2018 ◽  
Vol 47 (12) ◽  
pp. 1210002
Author(s):  
权巍 QUAN Wei ◽  
赵云秀 ZHAO Yun-xiu ◽  
韩成 HAN Cheng ◽  
丁莹 DING Ying ◽  
姜珊 JIANG Shan ◽  
...  
Keyword(s):  
Evaluation Model ◽  
Region Of Interest ◽  
Stereo Images ◽  
Model Based ◽  
Comfort Evaluation

scholarly journals Mechanical Energy Expenditure-based Comfort Evaluation Model for Gesture Interaction

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Wenjie Wang ◽  
Xiansheng Qin ◽  
Chen Zheng ◽  
Hongbo Wang ◽  
Jing Li ◽  
...  
Keyword(s):  
Energy Expenditure ◽  
Degrees Of Freedom ◽  
Evaluation Model ◽  
Mechanical Energy ◽  
Recognition Rate ◽  
Mechanical Efficiency ◽  
Model Based ◽  
Comfort Evaluation ◽  
Dynamic Gestures ◽  
Advanced Interaction

As an advanced interaction mode, the gesture has been widely used for the human-computer interaction (HCI). The paper proposes a comfort evaluation model based on the mechanical energy expenditure (MEE) and the mechanical efficiency (ME) to predict the comfort of gestures. The proposed comfort evaluation model takes nineteen muscles and seven degrees of freedom into consideration based on the data of muscles and joints and is capable of simulating the MEE and the ME of both static and dynamic gestures. The comfort scores (CSs) can be therefore calculated by normalizing and assigning different decision weights to the MEE and the ME. Compared with the traditional comfort prediction methods based on measurement, on the one hand, the proposed comfort evaluation model makes it possible for providing a quantitative value for the comfort of gestures without using electromyography (EMG) or other measuring devices; on the other hand, from the ergonomic perspective, the results provide an intuitive indicator to predict which act has the higher risk of fatigue or injury for joints and muscles. Experiments are conducted to validate the effectiveness of the proposed model. According to the comparison result among the proposed comfort evaluation model, the model based on the range of motion (ROM) and the model based on the method for movement and gesture assessment (MMGA), a slight difference can be found due to the ignorance of dynamic gestures and the relative kinematic characteristics during the movements of dynamic gestures. Therefore, considering the feedback of perceived effects and gesture recognition rate in HCI, designers can achieve a better optimization for the gesture design by making use of the proposed comfort evaluation model.

scholarly journals Establishment of Thermal Comfort Evaluation Model Based on Individual Difference

2019 ◽  
Vol 136 ◽  
pp. 04101
Author(s):  
Yalong Yang ◽  
Yufu Liu ◽  
Rui Zhang ◽  
Xulai Zhu ◽  
Mingyue Wang
Keyword(s):  
Neural Network ◽  
Thermal Comfort ◽  
Energy Saving ◽  
Rbf Neural Network ◽  
Evaluation Model ◽  
Building Energy ◽  
Physiological Signals ◽  
Model Based ◽  
Comfort Evaluation ◽  
Building Energy Saving

“People-oriented” and “Energy saving” are the two major themes of current social development. In the field of thermal comfort, establishment of thermal comfort model based on physiological parameters plays an important role in meeting the needs of human health and comfort, optimizing the design of building environment and building energy saving. In this paper, three types of physiological signals (skin temperature, skin conductance and heart rate) were collected through comfort physiological experiments. The changes of the three types of physiological signals under environmental temperature were analyzed. Furthermore, subjective questionnaire survey of human thermal comfort under five experimental conditions was performed. In addition, the thermal comfort evaluation model based on individual differences was established by partial least squares regression and ELM-RBF neural network. The established models were compared with the classical PMV model to analyze the superiority of the model. The results show that the thermal comfort evaluation model based on individual differences established by ELM-RBF neural network can better predict the trend of people's thermal comfort and satisfy the individual's demand for thermal comfort. Meanwhile, it can achieve the goal of building energy saving. Therefore, it has high practical and social significance.

Load-balancing evaluation model based on pre-defined variability

2009 ◽  
Vol 29 (10) ◽  
pp. 2849-2851
Author(s):  
Li-lun ZHANG ◽  
Jian-ping WU ◽  
Jun-qiang SONG
Keyword(s):  
Load Balancing ◽  
Evaluation Model ◽  
Model Based

Recognition of teaching method effects based on grid model simplification and artificial intelligence

2020 ◽  
pp. 1-11
Author(s):  
Guo Yunfeng ◽  
Li Jing
Keyword(s):  
Artificial Intelligence ◽  
Teaching Method ◽  
Evaluation Model ◽  
Geometric Constraints ◽  
Sorting Algorithm ◽  
Grid Model ◽  
Model Based ◽  
Refinement Method ◽  
Method Effects ◽  
Structure Simplification

In order to improve the effect of the teaching method evaluation model, based on the grid model, this paper constructs an artificial intelligence model based on the grid model. Moreover, this paper proposes a hexahedral grid structure simplification method based on weighted sorting, which comprehensively sorts the elimination order of candidate base complexes in the grid with three sets of sorting items of width, deformation and price improvement. At the same time, for the elimination order of basic complex strings, this paper also proposes a corresponding priority sorting algorithm. In addition, this paper proposes a smoothing regularization method based on the local parameterization method of the improved SLIM algorithm, which uses the regularized unit as the reference unit in the local mapping in the SLIM algorithm. Furthermore, this paper proposes an adaptive refinement method that maintains the uniformity of the grid and reduces the surface error, which can better slow down the occurrence of geometric constraints caused by insufficient number of elements in the process of grid simplification. Finally, this paper designs experiments to study the performance of the model. The research results show that the model constructed in this paper is effective.

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