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Journal of the Brazilian Society of Mechanical Sciences and Engineering (16785878) (9)
The purpose of this study is to design and construct a novel interactive game. This game is a robotic learning and imitation task. It is based on visual interaction of the player. The cornerstone technique used in this game is natural learner unit pattern generator neural networks (NLUPGNN), which is able to generate required motion trajectories based on imitation learning. The systematic design of these neural networks is the main problem solved in this paper. The unit pattern generators can be divided into two subsystems, a rhythmic system and a discrete system. A special learning algorithm is designed to use these unit pattern generators. The unit pattern generators are connected and coupled to each other to form a network, and their unknown parameters are found by a natural policy gradient learning algorithm. The motion sequences train some nonlinear oscillators, then they reproduce motions for a humanoid robot. As a result, the joints of the humanoid body imitate the movements of the teacher in real time. The main contribution of this work is the development of this learning algorithm, which is able to search the weights and topology of the network simultaneously. The algorithm synchronizes the learning steps by coupling the neurons in the last step. © The Author(s), under exclusive licence to The Brazilian Society of Mechanical Sciences and Engineering 2024.
Amirkabir Journal of Mechanical Engineering (20086032) (3)pp. 139-142
In this paper, a device based on wearable sensors is introduced to describe quantitative body movements in different sports. This device can be an alternative to Image processing techniques. Image processing devices have always been used to describe quantitative body movements, which in addition to being costly, have to be used in specific conditions. The device is built from a number of wireless modules that are easy to use in real-world environments with no limitations. In this method, a quantitative description of movement is made by wireless modules and is performed by the data collected from these modules. In order to analyze the data that was extracted from an athlete’s body movements with these wearable sensors, the outputs are simulated in Matlab, and some of its kinematic and kinetic parameters have been studied. Then, at the end of this paper, the quality of movement of a professional athlete and a beginner athlete are compared, and the result is shown. Kinematic and dynamic analyzes on the above activities showed the following results: The movements are generally correctly recorded. The kinematic analyzes performed for the various movements are consistent with the facts. For example, the kinematic analysis of the recorded motions showed that the coaching movement was more beautifully performed, and this was evident qualitatively during the movement. © 2022, Amirkabir University of Technology. All rights reserved.
International Journal of Innovation and Technology Management (2198770) (1)
The important role of demographics on technology adoption has been highlighted vastly in the literature. Therefore, this study aims at investigating the moderating role of managers' demographics in their decision-making process to adopt Green information system (Green IS) from the lens of norm activation theory. With 175 valid questionnaires hand collected from organizations' decision-makers, the researchers examined the research model and its related hypotheses utilizing the Partial Least Squares (PLS)-Structural Equation Modeling (SEM). The results showed Green IS attitude together with personal norm to be the most influential factors, followed by environmental attitude. In addition, we found that while awareness of consequences significantly impacted personal norms, its explanatory power on personal norms was higher when it was mediated through ascription of responsibility. Regarding the moderator variables, the model explained better the pro-environmental behavioral intention of managers towards the adoption of Green IS among older female and well-educated managers. Contributions of the study are further discussed. © 2019 World Scientific Publishing Company.
Shahbazi, H. ,
Dalvi-esfahani, M. ,
Nilashi M. ,
Samad S. ,
Mardani, A. ,
Streimikiene D. Economics and Sociology (2071789X) (3)pp. 207-225
The purpose of this study is to investigate the factors that influence beliefs formation towards the adoption of social commerce in SME travel agencies. Accordingly, a distal-proximal model is developed to study CEOs’ beliefs towards the usefulness of social commerce. Data were collected through a questionnaire survey of travel agencies’ CEOs in Isfahan, Iran. With 180 collected data from respondents, the Partial Least Squares-Structural Equation Modeling approach was taken to assess both measurement and structural models of the study. The results revealed that CEOs’ innovativeness and attitude towards IT as individual factors, and organizational resources as institutional factor were significantly explained beliefs formation of respondents towards the usefulness of social commerce. However, it was found that the influences of CEOs’ IT knowledge, subjective norms (professional peers, employees) and firm size on perceived usefulness were found insignificant. Implications of the study are further discussed. © 2018, Centre of Sociological Research. All rights reserved.
Shahbazi, H. ,
Leong, L.W. ,
Ibrahim O. ,
Dalvi-esfahani, M. ,
Nilashi M. Education and Information Technologies (13602357) (6)pp. 2477-2498
With numerous benefits of utilising mobile social network sites (SNSs) for learning purposes, limited studies have been conducted to determine the factors that influence the adoption of mobile SNSs in facilitating learning. Accordingly, the main purpose of this study is to explore the determinants of students’ behavioural intention to use mobile SNSs for their pedagogical purposes by utilising an extended version of Technology Acceptance Model. Furthermore, the moderating effect of users’ experience on their behavioural intention was investigated. Using a structured questionnaire, data were collected from 600 students from top-five public universities of Malaysia. The results revealed perceived task-technology fit as the great predictor of users’ intention and perceived usefulness. Although the moderating impact of students’ experience on the model found to be positive, it was not supported in this study. The contributions of this study both to the literature and practice are discussed. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.
2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025 pp. 354-358
The routing problem in wireless sensor networks is one of the most important issues that guarantee the optimum functionality of a sensor network. Due to the energy limitation of each node in a sensor network, routing should be done in a way that the overall network life time will be maximized. In this paper we present an intelligent method based on self organizing neural networks which optimizes the routing according to the amount of energy of each node in the network and its computation power. ©2008 IEEE.
Shahbazi, H. ,
Aghaei N.G. ,
Farzaneh P. ,
Abdolmaleki, A. ,
Khorsandian A. 2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025 pp. 1201-1206
One of the most important factors which can affect decision making in a disaster environment is the structure of the agent's personality. It is obvious that the more the agent is able to control its emotions in harmful environments, the better it can perform its task. In this paper we will introduce a new structure for decision making in emergency situations, which is based on emotional intelligence of the human being's mind. We have designed a model that combines personality characteristics of an agent, its emotional behaviors and the external events that can affect him. This new decision making model has been tested on a typical disaster space called Robocup Rescue Simulation (RRS). Our method has been implemented on three types of agents in the RRS environment. In fact this model tries to use a different kind of intelligence on these rescuer agents. The results of this research can help disaster managers by optimizing their rescue management in a disaster space. © 2008 IEEE.
Shahgholi, B. ,
Shahbazi, H. ,
Kazemifard M. ,
Zamanifar, K. ,
Shahgholi, B. ,
Shahbazi, H. ,
Kazemifard M. ,
Zamanifar, K. 2025 29th International Computer Conference, Computer Society of Iran, CSICC 2025 pp. 74-80
RoboCupRescue Simulation System is a platform for designing and implementing various artificial intelligent issues. In rescue simulation environments, Firebrigades should select fire points in a collaborative manner such that the total achieved result is optimized. In this work, we are going to propose a new method for fire prediction and selection in Firebrigade agents. This method is based on Evolving Fuzzy Neural Networks to obtain a set of trained fuzzy rules as rule base of Firebrigades Fire Selection System to select targets autonomously.
