Developing an Affect-Aware Rear-Projected Robotic Agent

Social (or Sociable) robots are designed to interact with people in a natural and interpersonal manner. They are becoming an integrated part of our daily lives and have achieved positive outcomes in several applications such as education, health care, quality of life, entertainment, etc. Despite significant progress towards the development of realistic social robotic agents, a number of problems remain to be solved. First, current social robots either lack enough ability to have deep social interaction with human, or they are very expensive to build and maintain. Second, current social robots have yet to reach the full emotional and social capabilities necessary for rich and robust interaction with human beings. To address these problems, this dissertation presents the development of a low-cost, flexible, affect-aware rear-projected robotic agent (called ExpressionBot), that is designed to support verbal and non-verbal communication between the robot and humans, with the goal of closely modeling the dynamics of natural face-to-face communication. The developed robotic platform uses state-of-the-art character animation technologies to create an animated human face (aka avatar) that is capable of showing facial expressions, realistic eye movement, and accurate visual speech, and then project this avatar onto a face-shaped translucent mask. The mask and the projector are then rigged onto a neck mechanism that can move like a human head. Since an animation is projected onto a mask, the robotic face is highly flexible research tool, mechanically simple, and low-cost to design, build and maintain compared with mechatronic and android faces. The results of our comprehensive Human-Robot Interaction (HRI) studies illustrate the benefits and values of the proposed rear-projected robotic platform over a virtual-agent with the same animation displayed on a 2D computer screen. The results indicate that ExpressionBot is well accepted by users, with some advantages in expressing facial expressions more accurately and perceiving mutual eye gaze contact. To improve social capabilities of the robot and create an expressive and empathic social agent (affect-aware) which is capable of interpreting users\u27 emotional facial expressions, we developed a new Deep Neural Networks (DNN) architecture for Facial Expression Recognition (FER). The proposed DNN was initially trained on seven well-known publicly available databases, and obtained significantly better than, or comparable to, traditional convolutional neural networks or other state-of-the-art methods in both accuracy and learning time. Since the performance of the automated FER system highly depends on its training data, and the eventual goal of the proposed robotic platform is to interact with users in an uncontrolled environment, a database of facial expressions in the wild (called AffectNet) was created by querying emotion-related keywords from different search engines. AffectNet contains more than 1M images with faces and 440,000 manually annotated images with facial expressions, valence, and arousal. Two DNNs were trained on AffectNet to classify the facial expression images and predict the value of valence and arousal. Various evaluation metrics show that our deep neural network approaches trained on AffectNet can perform better than conventional machine learning methods and available off-the-shelf FER systems. We then integrated this automated FER system into spoken dialog of our robotic platform to extend and enrich the capabilities of ExpressionBot beyond spoken dialog and create an affect-aware robotic agent that can measure and infer users\u27 affect and cognition. Three social/interaction aspects (task engagement, being empathic, and likability of the robot) are measured in an experiment with the affect-aware robotic agent. The results indicate that users rated our affect-aware agent as empathic and likable as a robot in which user\u27s affect is recognized by a human (WoZ). In summary, this dissertation presents the development and HRI studies of a perceptive, and expressive, conversational, rear-projected, life-like robotic agent (aka ExpressionBot or Ryan) that models natural face-to-face communication between human and emapthic agent. The results of our in-depth human-robot-interaction studies show that this robotic agent can serve as a model for creating the next generation of empathic social robots

Supplier Knowledge Management For Supplier Development

Due to rapid and unpredictable changes in the business environment, nowadays organizations have to be innovative to survive in the marketplace.  Many firms have applied knowledge management to reduce production costs, innovate new products, and attract customers and suppliers.  Hence, firm's management has to maintain competitive advantage by providing inputs through a dynamic supplier network. Supplier development programs help businesses to identify collaborative suppliers.  Therefore, Supplier Knowledge Management plays an important role for the firms to create switching costs and raise barriers to entry. In this paper, initially we define knowledge management, and supplier knowledge management, and then a conceptual framework is presented to enhance supplier performance.  We will demonstrate how companies can benefit by adopting supplier knowledge management

A survey of the relationship between EQ and organizational entrepreneurship of the employees of Bank Maskan in Kerman province (Iran)

In recent decades, organizational entrepreneurship is taken into attention by researchers. The concept of organizational entrepreneurship is of great importance for the organizations in a new era, as well as the factors affecting the entrepreneurial orientation are. EQ as a variable related to the management of our own feelings and establishing the effective communication with others took our attention. One of the psychological variables in relation with organizational entrepreneurship is EQ. EQ is an array of non-cognitive capabilities, competencies, and skills that influence one’s ability to succeed in coping with environmental demands and pressures. Based on the importance of organizational entrepreneurship and the effect of personality characteristics including EQ on organizational entrepreneurship, the present study attempted to evaluate the relation between EQ and organizational entrepreneurship in Bank Maskan of Kerman province. The present study is applied in terms of aim and it is descriptive-correlation in terms of method. The study population was the employees of Bank Maskan in Kerman province as 357 people. The sample size was selected randomly based on Cochran’s formula, 185 employees of Bank Maskan in Kerman province. For data collection of EQ data, Shrink test was applied and to evaluate the organizational entrepreneurship, Dr. Moqimi questionnaire was used and their reliability by Cronbach’s alpha were 0.89, 0.87, respectively. For data analysis, one-sample t-test and Pearson correlation analysis were applied and the results showed a positive and strong relation between EQ and organizational entrepreneurshi

A survey of the relationship between EQ and organizational entrepreneurship of the employees of Bank Maskan in Kerman province (Iran)

In recent decades, organizational entrepreneurship is taken into attention by researchers. The concept of organizational entrepreneurship is of great importance for the organizations in a new era, as well as the factors affecting the entrepreneurial orientation are. EQ as a variable related to the management of our own feelings and establishing the effective communication with others took our attention. One of the psychological variables in relation with organizational entrepreneurship is EQ. EQ is an array of non-cognitive capabilities, competencies, and skills that influence one’s ability to succeed in coping with environmental demands and pressures. Based on the importance of organizational entrepreneurship and the effect of personality characteristics including EQ on organizational entrepreneurship, the present study attempted to evaluate the relation between EQ and organizational entrepreneurship in Bank Maskan of Kerman province. The present study is applied in terms of aim and it is descriptive-correlation in terms of method. The study population was the employees of Bank Maskan in Kerman province as 357 people. The sample size was selected randomly based on Cochran’s formula, 185 employees of Bank Maskan in Kerman province. For data collection of EQ data, Shrink test was applied and to evaluate the organizational entrepreneurship, Dr. Moqimi questionnaire was used and their reliability by Cronbach’s alpha were 0.89, 0.87, respectively. For data analysis, one-sample t-test and Pearson correlation analysis were applied and the results showed a positive and strong relation between EQ and organizational entrepreneurshi

A survey of the relationship between EQ and organizational entrepreneurship of the employees of Bank Maskan in Kerman province (Iran)

In recent decades, organizational entrepreneurship is taken into attention by researchers. The concept of organizational entrepreneurship is of great importance for the organizations in a new era, as well as the factors affecting the entrepreneurial orientation are. EQ as a variable related to the management of our own feelings and establishing the effective communication with others took our attention. One of the psychological variables in relation with organizational entrepreneurship is EQ. EQ is an array of non-cognitive capabilities, competencies, and skills that influence one’s ability to succeed in coping with environmental demands and pressures. Based on the importance of organizational entrepreneurship and the effect of personality characteristics including EQ on organizational entrepreneurship, the present study attempted to evaluate the relation between EQ and organizational entrepreneurship in Bank Maskan of Kerman province. The present study is applied in terms of aim and it is descriptive-correlation in terms of method. The study population was the employees of Bank Maskan in Kerman province as 357 people. The sample size was selected randomly based on Cochran’s formula, 185 employees of Bank Maskan in Kerman province. For data collection of EQ data, Shrink test was applied and to evaluate the organizational entrepreneurship, Dr. Moqimi questionnaire was used and their reliability by Cronbach’s alpha were 0.89, 0.87, respectively. For data analysis, one-sample t-test and Pearson correlation analysis were applied and the results showed a positive and strong relation between EQ and organizational entrepreneurshi

Measuring the impact of service quality on post-purchase intention

This paper presents an empirical investigation to study the effects of service quality on post-purchase intention. The study is applied among some small and medium enterprises (SMEs) in city of Kerman, Iran. There were approximately 300 people working for these units and the study chose 168 people as a sample study. The study used a standard questionnaire consists of 20 questions in Likert scale and distributed it among the sample size. Using structural equation modeling the study has determined that service quality as well as perceived quality influenced positively on customer satisfaction and post-purchase intention

Facial Expression Recognition from World Wild Web

Recognizing facial expression in a wild setting has remained a challenging task in computer vision. The World Wide Web is a good source of facial images which most of them are captured in uncontrolled conditions. In fact, the Internet is a Word Wild Web of facial images with expressions. This paper presents the results of a new study on collecting, annotating, and analyzing wild facial expressions from the web. Three search engines were queried using 1250 emotion related keywords in six different languages and the retrieved images were mapped by two annotators to six basic expressions and neutral. Deep neural networks and noise modeling were used in three different training scenarios to find how accurately facial expressions can be recognized when trained on noisy images collected from the web using query terms (e.g. happy face, laughing man, etc)? The results of our experiments show that deep neural networks can recognize wild facial expressions with an accuracy of 82.12%