scholarly journals Street Design for Hedonistic Sustainability through AI and Human Co-Operative Evaluation

2021 ◽  
Vol 13 (16) ◽  
pp. 9066
Author(s):  
Kanyou Sou ◽  
Hiroya Shiokawa ◽  
Kento Yoh ◽  
Kenji Doi
Keyword(s):  
Facial Expression ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Well Being ◽  
Objective Evaluation ◽  
Expression Recognition ◽  
Street Design ◽  
Street Space ◽  
Operative Evaluation ◽  
Basic Functions

Recently, there has been an increasing emphasis on community development centered on the well-being and quality of life of citizens, while pursuing sustainability. This study proposes an AI and human co-operative evaluation (AIHCE) framework that facilitates communication design between designers and stakeholders based on human emotions and values and is an evaluation method for street space. AIHCE is an evaluation method based on image recognition technology that performs deep learning of the facial expressions of both people and the city; namely, it consists of a facial expression recognition model (FERM) and a street image evaluation model (SIEM). The former evaluates the street space based on the emotions and values of the pedestrian’s facial expression, and the latter evaluates the target street space from the prepared street space image. AIHCE is an integrated framework for these two models, enabling continuous and objective evaluation of space with simultaneous subjective emotional evaluation, showing the possibility of reflecting it in the design. It is expected to contribute to fostering people’s awareness that streets are public goods reflecting the basic functions of public spaces and the values and regional characteristics of residents, contributing to the improvement of the sustainability of the entire city.

scholarly journals A multi-objective evaluation method based on connection numbers theory of hazardous chemical accidents emergency medical rescue capability

2019 ◽  
Vol 27 (3) ◽  
pp. 125-133
Author(s):  
Yapeng Wang ◽  
Jinguo Zhang ◽  
Yundou Wang ◽  
Xiaowen Xiong ◽  
Xin Zhao
Keyword(s):  
Index System ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Objective Evaluation ◽  
Evaluation Index System ◽  
Evaluation Index ◽  
Chemical Accidents ◽  
Hazardous Chemical ◽  
Emergency Medical ◽  
Partial Connection

Background: An objective, comprehensive and scientific evaluation of emergency medical rescue capability (EMRC) is of great realistic significance in assisting the health administrative department to grasp the overall response capability of all emergency medical rescue teams, enabling each team to have a full understanding of its own strengths and weakness and improve itself accordingly. At present, the research on the evaluation of EMRC in Hazardous Chemicals Accidents (HCA) is not systematic and in-depth, and the existing research results also have some shortcomings, such as, the lack of strong theoretical support for the evaluation index system, the relatively single function of evaluation methods, and so on. Objectives: The objective of this article is to research the evaluation index system and a new evaluation method of EMRC in HCA to overcome the above shortcomings. Methods: It establishes an emergency medical rescue capability model by employing the competency model and then constructs the evaluation index system on the basis of the analysis of all the factors of emergency medical rescue capability in hazardous chemical accidents and sets up an evaluation model based on the theory of connection numbers and partial connection numbers. It determines the competence ranking of several emergency medical rescue teams and the competence state of an individual emergency medical rescue team by calculating the connection principal value, and it also predicts how the emergency medical rescue capability will develop based on the values of partial connection numbers. Results: The example shows that the calculation process of this model is relatively simple, and its assessment results are objective and authentic, and moreover, its multi-functions can make up for the deficiency of the simplified function of other evaluation models. Conclusion: This method is scientific and rational to some extent and can provide reference for evaluation problems of the same kind.

scholarly journals An Evaluation Method of Mode Switching Quality for Double-Belt Continuously Variable Transmission

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Lanchun Zhang ◽  
Zhongwei Zhu ◽  
Bin Huang ◽  
Tianbo Wang
Keyword(s):  
Evaluation Method ◽  
Evaluation Model ◽  
Subjective Evaluation ◽  
Objective Evaluation ◽  
Transmission Efficiency ◽  
Continuously Variable Transmission ◽  
Mode Switching ◽  
Evaluation Indexes ◽  
Variable Transmission ◽  
Driver’S Intention

In order to improve the transmission efficiency and carrying capacity of conventional single-belt continuously variable transmission (CVT), one new type of dual-belt CVT is proposed in this paper. Under the situation that this new dual-belt CVT should be switched between single- and dual-belt modes frequently according to driver’s intention and road conditions, so five objective evaluation indexes of mode switching quality for the dual-belt CVT are proposed, considering the aspects of vehicle power, comfort, and transmission durability comprehensively. Then, the objective evaluation model of mode switching quality is established by the BP neural network optimized by the genetic algorithm. It is found that the prediction results are consistent with the subjective evaluation. After analyzing the influence of the selected five evaluation indexes on the prediction results, it is obvious that these five evaluation indexes of mode switching quality for dual-belt CVT are reasonable.

Research on Facial Feature Detection Based on Correlation Analysis

2014 ◽  
Vol 1044-1045 ◽  
pp. 1489-1493
Author(s):  
Ming Zhou ◽  
Shu He ◽  
Yong Jun Cheng
Keyword(s):  
Facial Expression ◽  
Feature Detection ◽  
Evaluation Method ◽  
Facial Feature ◽  
Expression Recognition ◽  
3D Images ◽  
Modified Method ◽  
Innovative Methods ◽  
Combined Features ◽  
2D And 3D

In order to enhance the extraction efficiency of facial feature, the paper explores a novel defect evaluation method that uses combined features and modified method classifiers to characterize and classify the defects of facial expression. It provides a good approach to implement facial expression recognition both in 2D and 3D images. Innovative methods which are aimed at reducing the computational complexity and improving the accuracy of expression recognition are proposed.The experiments result showed the proposed method achieved lower error rate than other method.

Online teaching quality evaluation based on emotion recognition and improved AprioriTid algorithm

2020 ◽  
pp. 1-11
Author(s):  
Hui Yu
Keyword(s):  
Data Mining ◽  
Facial Expression ◽  
Emotion Recognition ◽  
Facial Expression Recognition ◽  
Online Teaching ◽  
Quality Evaluation ◽  
Evaluation Model ◽  
Teaching Quality ◽  
Practical Significance ◽  
Expression Recognition

The association rule algorithm in data mining is used to study the factors that may affect students’ performance, to make suggestions for teaching work, and to provide decision-making basis for teachers and teaching administrators, which has practical significance. There are many potential applications for facial expression recognition technology. For example, in the teaching process, facial expression recognition technology helps teachers understand students and judge students’ reactions to certain things. Based on the current research status of emotion recognition and data mining algorithms, this paper improves the AprioriTid algorithm and constructs an online teaching quality evaluation model based on teaching needs. In addition, this article applies the model constructed in this article to the evaluation of English online teaching quality and evaluates teaching quality through data mining. The experimental research shows that the model constructed in this paper has good performance.

scholarly journals New model for flavour quality evaluation of soy sauce

2013 ◽  
Vol 31 (No. 3) ◽  
pp. 292-305 ◽  
Author(s):  
J. Feng ◽  
X.-B. Zhan ◽  
Z.-Y. Zheng ◽  
D. Wang ◽  
L.-M. Zhang ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Quality Evaluation ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Principal Component ◽  
Objective Evaluation ◽  
Component Analysis ◽  
Soy Sauce ◽  
Complex Information

The soy sauce samples established a model for its flavour quality evaluation. Initially, 39 types of flavour compounds, organic acids and free amino acids in six different types of soy sauce were identified and determined by HS-SPME GC/MS and HPLC. The model was developed based on the principal component analysis method for assessing and ranking of flavour quality of soy sauce. Using the principal component analysis which simplifies complex information, our correlative evaluation model was established, tested by comparing the traditional sensory evaluation method, providing a new methodology for objective evaluation of the flavour quality of soy sauce.  

scholarly journals Personalized Movie Summarization Using Deep CNN-Assisted Facial Expression Recognition

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Ijaz Ul Haq ◽  
Amin Ullah ◽  
Khan Muhammad ◽  
Mi Young Lee ◽  
Sung Wook Baik
Keyword(s):  
Facial Expression ◽  
User Satisfaction ◽  
Facial Expression Recognition ◽  
Subjective Evaluation ◽  
Objective Evaluation ◽  
User Preference ◽  
Expression Recognition ◽  
Hollywood Movies ◽  
Deep Cnn ◽  
Movie Summarization

Personalized movie summarization is demand of the current era due to an exponential growth in movies production. The employed methods for movies summarization fail to satisfy the user’s requirements due to the subjective nature of movies data. Therefore, in this paper, we present a user-preference based movie summarization scheme. First, we segmented movie into shots using a novel entropy-based shots segmentation mechanism. Next, temporal saliency of shots is computed, resulting in highly salient shots in which character faces are detected. The resultant shots are then forward propagated to our trained deep CNN model for facial expression recognition (FER) to analyze the emotional state of the characters. The final summary is generated based on user-preferred emotional moments from the seven emotions, i.e., afraid, angry, disgust, happy, neutral, sad, and surprise. The subjective evaluation over five Hollywood movies proves the effectiveness of our proposed scheme in terms of user satisfaction. Furthermore, the objective evaluation verifies the superiority of the proposed scheme over state-of-the-art movie summarization methods.

A Novel Real-Time Facial Expression Capturing Method

2013 ◽  
Vol 273 ◽  
pp. 826-830
Author(s):  
Yong Sheng Wang
Keyword(s):  
Facial Expression ◽  
Real Time ◽  
Evaluation Method ◽  
Feature Model ◽  
Svm Classifier ◽  
Expression Recognition ◽  
Human Face ◽  
Real Time Mode ◽  
Detection Approach ◽  
Online Process

In this paper, we propose a new facial expression capturing method in real-time mode. Our proposed method main includes two processes: 1) Online process and 2) Offline process. The offline process adopt human face database to build 2D face model and 3D shape model, and then train an expression feature model. Afterwards, online process extracts feature points from human face images, and then obtains facial expression by SVM classifier which is trained from offline process. The main creativity of our method lies in that we propose an effective face detection approach and propose an optimal evaluation method to facial expression recognition. Experimental results show that our approach can capture facial expression precisely in real-time mode.

scholarly journals Intelligent Emotion Evaluation Method of Classroom Teaching Based on Expression Recognition

2019 ◽  
Vol 14 (04) ◽  
pp. 127 ◽  
Author(s):  
Yanqiu Liang
Keyword(s):  
Facial Expression ◽  
Facial Expressions ◽  
Evaluation Method ◽  
Teaching Method ◽  
Facial Feature ◽  
Support Vector ◽  
Expression Recognition ◽  
Feature Points ◽  
Recognition Of Facial Expressions

To solve the problem of emotional loss in teaching and improve the teaching effect, an intelligent teaching method based on facial expression recognition was studied. The traditional active shape model (ASM) was improved to extract facial feature points. Facial expression was identified by using the geometric features of facial features and support vector machine (SVM). In the expression recognition process, facial geometry and SVM methods were used to generate expression classifiers. Results showed that the SVM method based on the geometric characteristics of facial feature points effectively realized the automatic recognition of facial expressions. Therefore, the automatic classification of facial expressions is realized, and the problem of emotional deficiency in intelligent teaching is effectively solved.

The Evaluating Method for Module Partition Schemes of Complex Product Systems

2011 ◽  
Vol 486 ◽  
pp. 37-40 ◽  
Author(s):  
Xiao Yan Teng ◽  
Fan Kai Kong ◽  
Jia Tai Zhang
Keyword(s):  
Evaluation Method ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Objective Evaluation ◽  
Complex Product ◽  
Evaluation Indexes ◽  
Complex Product Systems ◽  
Multi Level ◽  
Module Partition

Module partition of Complex product system (CoPS) usually produces a number of schemes, and how to choose the best one amongst the themes is very important. In this research, according to the features of CoPS, the multi-level evaluation indexes are built based on the DFX (design for X) method, which can evaluate the scheme comprehensively. The weight of indexes are obtained with the method of analytical network process. Then, the multi-level grey fuzzy comprehensive evaluation method is proposed to make the well-chosen decision based on the DFX multi-objective evaluation model. The evaluation method are illustrated using the partition schemes of the experiment platform of a bevel gearbox.

scholarly journals A robust evaluation of sustainability initiatives with analytic network process (ANP)

2015 ◽  
Vol 3 (2) ◽  
pp. 123 ◽  
Author(s):  
Lanndon Ocampo ◽  
Christine Omela Ocampo
Keyword(s):  
Structural Changes ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Sustainable Manufacturing ◽  
Well Being ◽  
Analytic Network Process ◽  
Toxic Substances ◽  
Evaluation Approach ◽  
Network Process ◽  
Manufacturing Initiatives

<p>This paper presents a methodology on evaluating sustainable manufacturing initiatives using analytic network process (ANP) as its base.The evaluation method is anchored on the comprehensive sustainable manufacturing framework proposed recently in literature. A numerical example that involves an evaluation of five sustainable manufacturing initiatives is shown in this work. Results show that sustainable manufacturing implies enhancing customer and community well-being by means of addressing environmental issues related to pollution due to toxic substances, greenhouse gas emissions and air emissions. To test the robustness of the results, two approaches are introduced in this work: (1) using Monte Carlo simulation and (2) introducing structural changes on the evaluation model. It suggests that the results are robust to random variations and to marginal changes of the network structure. The contribution of this work lies on presenting a sustainable manufacturing evaluation approach that addresses complexity and robustness in decision-making. </p>

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