Sharif Digital Repository

The Dye-sensitizers loading on TiO2 is decreasing the electron excitation energy and therefore improving the photocatalytic performance from the increasing the sensitivity under visible light irradiation.in this project CoPCTS , Mordant dye and N3(Ruthenium 535) used as dye-sensitizers. Also The addition of VIII group metals on TiO2 is improving the photocatalytic activity that increasing the photocatalytic reaction rate because of the intermediation role of them for moving the conduction band electrons to electron acceptors and increasing the pair electron-holes long-life that in this case Pt loading used as a VIII group metal. In this project Titanium Isopropoxide as a precursore and... 

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... 

This research is conducted aiming to analyze the Customer Knowledge Management and Customer Interaction Management in CRM in Iran Insurance Industry. Cheng and Yang Model was utilized for analyzing the two aforementioned parameters. The current research is descriptive and survey was conducted for data gathering. The research population involves 80 employees working in Technical and Marketing segments of the 5 insurance companies (Iran, Asia, Alborz, Dana, Parsian). The dependent parameter is Customer Interaction Management and the independent parameter is Customer Knowledge Management. The data collected from conducting the survey is analyzed by LISREL software and with Structural Equation... 

Data collected from street networks show that travel time in urban street networks is a stochastic variable, whose range of variation increases with the congestion level. Work and school trips comprise the major part of morning peak volumes, whose common characteristic is that they need to be made on time. For this reason, these travelers are pessimistic in their route choice, and try to choose routes which are more reliable. Travel time standard deviation is one of the common measures for estimating travel time reliability that is related to properties of day-to-day travel time distribution on a particular route. Based on the empirical data collected from Tehran street network, this paper... 

Noise or noise pollution, is defined as an unwanted sound, produced mostly by motor vehicles in urban areas. If the noise exceeds its limit, adverse effects on users and citizens are expected. Thus the assessment of the noise level and its comparison with allowable values is mandatory. Traffic induced noise depends upon different factors such as traffic, weather, and, sound barriers. Noise pollution study has a long history all over the world. Many studies, mostly representing the outdoor noise pollution models, have been done in recent years. This paper presents an assessment of traffic-induced noise in a heavily traveled tunnel, locally referred to as Resalat tunnel, which is located in... 

In this thesis, we introduce a novel Artificial Intelligence (AI) system inspired by the philosophical and psychoanalytical concept of imagination as a ``Re-construction of Experiences". Our AI system is equipped with an imagination-inspired module that bridges the gap between textual inputs and other modalities, enriching the derived information based on previously learned experiences. A unique feature of our system is its ability to formulate independent perceptions of inputs. This leads to unique interpretations of a concept that may differ from human interpretations but are equally valid, a phenomenon we term as ``Interpretable Misunderstanding". We employ large-scale models,... 

With the advancement of automotive industry, the number of electronic systems that need to communicate with each other has increased. An effective strategy to meet these growing demands is using bus-based protocols, which can establish safe communication among numerous nodes with reasonable cost, weight, and space requirements. The objective of this thesis is the design and implementation of a transceiver based on the FlexRay protocol. The significance of this protocol lies in its ability to provide higher data transmission rates compared to other protocols like CAN and LIN, and its role as the foundational communication medium among various domains in modern vehicle architectures. In this... 

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...