Sharif Digital Repository

The human action recognition is one of the most important concepts of computer vision in recent decades. Most of the two dimensional methods in this field are facing serious challenges such as occlusion and missing the third dimension of data. Development of depth sensors has made easy access to tracking people and 3D positions of human body joints. This Thesis proposes a new method of action recognition that utilizes the position of joints obtained by Kinect sensor. The learning stage uses Fisher Linear Discriminant Analysis (LDA) to construct discriminant feature space. Two types of distances, i.e., Euclidean and Mahalanobis, are used for recognizing the states. Also, Hidden Markov Model... 

The non-stationary nature of brain activity signals and their many inter-subject differences have created many challenges in the practical applications of emotion recognition based on electroencephalogram (EEG) signals, such as brain-computer interfaces. In such a way, the use of traditional classifiers in classifying these signals leads to a significant decrease in accuracy when applying the classifier to a new subject. Domain Adaptation methods seem to be an effective way to solve this problem by minimizing the difference between the EEG signals of different subjects. But in the basic techniques for domain adaptation, looking at all subjects' data in the same look causes the loss of a part... 

In this project, a novel action recognition method, named Fisherposes, is proposed, which is improved by several space-time (spatio-temporal) methods afterwards. The proposed method utilizes skeleton data obtained from Kinect sensor. First, pre-processing is performed in which the scales of bodies are canceled and the skeletons become aligned in order to make the method robust to location, orientation, and scale of people. In Fisherposes method, every action is defined as a sequence of body poses. Using the training samples for the poses, a Fisher subspace is created which we name it Fisherposes. Moreover, a novel distance measuring function, named regularized Mahalanobis distance, is... 

One of Iran’s most important priorities at present is the development of the human resources and one of the most important skills of this human resource is decision making and problem solving. During the past few years, there have been numerous criticisms about the educational system in Iran without a substantial solution being offered to replace the existing approach. Aseman Group has been trying to promote system thinking in children. In Aseman, they believe that system thinking is one probable solution in order to develop thinking, decision making and problem solving skills in our human resource at early age. However, one of the many problems facing this group, is the resistance shown by... 

Organizational learning is essential for organizations to grow and survive. Organizations can gain competitive advantage through proper organizational learning. Number of studies in this field in recent years shows the importance of this issue among practioners and academics. The first step in managing organzaitonal learning is its measurement. Organizations can be provided with solutions if an appropriate measurement tool is designed. The main question of this research is whether this tool can be designed or not so that organizational learning in organizational processes can be measured. Despite the significance of organizational learning measurement, the current studies in this field lack... 

Peer-to-peer (P2P) computing is a popular distributed computing paradigm for many applications which in-volve exchange of information among a large number of peers. In such applications, large amount of data is distributed among multiple dispersed sources. Therefore, data analysis is challenging due to processing, storage and transmission costs. Moreover, the data rarely remains static and frequent data changes, quickly out date previously extracted data mining models. Distributed data mining deals with the problem of data analysis in environments with distributed data and computing resources. In this dissertation, we explore distributed data mining in different structures of P2P systems. In... 

The main question of this research is this: what mechanisms drive the increase of the share of health costs in GDP in Germany? Answering this question not only improves our understanding about health systems in general, but also is specifically useful for the health system of Iran, since it is experiencing similar trends as the health system of Germany does. Since these mechanisms are complex and the ability of human brain to process several interacting variables simultaneously is low, we need a strong methodology and a tool to overcome this limitation. System thinking as a methodology and system dynamics as its tool help us do so. Using system dynamics, we will develop a computer model... 

Continuous Blood Pressure monitoring can provide invaluable information about individuals’ health conditions. However, BP is conventionally measured using inconvenient cuff-based instruments, which prevents continuous BP monitoring. This work presents an efficient algorithm, based on the Pulse Arrival Time (PAT), for the continuous and cuff-less estimation of the Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), and Mean Arterial Pressure (MAP) values. The proposed framework estimates the BP values through processing vital signals and extracting two types of features, which are based on either physiological parameters or whole-based representation of vital signals. Finally, the... 

Brain states analysis during consciousness is emerging research in brain-computer interface(BCI). Emotion recognition can be applied to learn brain states and stages of neural activities. Therefore, emotion recognition is crucial to the analysis of brain functioning. Electrical signals such as electroencephalogram (EEG), electrocardiogram (ECG) and functional magnetic resonance imaging(fMRI) are frequently used in emotion recognition researches. Convenience in recording, non-invasive nature and high temporal resolution are the factors that have made EEG popular in brain researches. EEG can be used to identify brain region activity solely or the connectivity of various regions in time in the... 

In this study; technology transfer to the Farab and Butan fromabsorptive capacity perspective is under inquiry. First we have complete literature review until we can provide good understanding toward absorptive capacity concept in organizational level. George and Zahra model has been chosen as a base model. Farab and Butan have chosen because of their recent successes in knowledge transfer. Based on George and Zahra model we develop a semi-structured questionnair and run it in Farab and Butan. We have findings in how organization can transfer knowledge to their networks to increase their AC, also we have findings in different ways organizations transfer different kinds of knowledge