Sharif Digital Repository

The age-hardening behavior and microstructure of selected samples of a Ni-Co alloy were studied using hardness testing, optical microscopy, and scanning and transmission electron microscopy. The final microstructure of the material was found to be sensitive to the temperature of the solution treatment. This approach may be used to optimize the microstructure of the alloy for different applications. © 2007 Acta Materialia Inc  

Increasing the number of car accidents and other cerebral disease cause to progress in using Brain-Compute Interface (BCI) as a common subject for research and treatment. The aim of Brain-Computer Interface system is to establish a new communication system that translates human intentions, reflected by brain signals, into a control signal for an output device such as a computer. To this end, different processes must be done on brain signals and these signals must be classified by suitable methods. There are various methods to classify ECoG signals which are different in features and classifiers. Used features depend on extracted features, feature reduction methods and measures of feature... 

Feature extraction and classification are the most important parts of BCI systems. The new branch of BCI studies focuses on the design of a classifier that is trained to function properly for each individual. This problem is known as Transfer Learning. In between-subject classification, due to the differences in the neural signals' distribution of different individuals, using the common methods of feature extraction for training the classifier, does not lead to high accuracy for the test subject. As a result, in this study, we present a method for extracting features that perform well in between subjects classifications. The data that we used in this study are EEG signals recorded during... 

Classification is the most important part of brain-computer interface (BCI) systems. Because the neural activities of different individuals are not identical, using the ordinary methods of subject-dependent classification, does not lead to high accuracy in betweensubject classification problems. As a result, in this study, we propose a novel method for classification that performs well in between-subject classification. In the proposed method, at first, the subject-dependent classifiers obtained from the train subjects are applied to the test trials to obtain a set of scores and labels for the trials. Using these scores and the real labels of the labeled test trials, linear regression is... 

Brain is the most complicated organ of body. It controls the activity of all other organs. Understanding its function and its language could give us a direct communication pathway for connecting with injured motor organ and it could be the core of functional repairing. Neurons are the vertices of a vast network that generates the brain signals. Neuronal recordings capture brain activity signatures. The processing of these signals can help to translate brain's language. Usually it follows three main stages: spike detection and extraction, spike sorting, and intention extraction from the encoded signal. In this work, we introduce an original idea based on Hidden Markov Models (HMM) which helps... 

Migraine is a common type of headache with neurovascular origin. In this paper, a quantitative analysis of spontaneous EEG patterns is used to examine the migraine patients with maximum and minimum pain levels. The analysis is based on alpha band phase synchronization algorithm. The efficiency of extracted features are examined through one-way ANOVA test. we reached the P-value of 0.0001, proving that the EEG patterns are statistically discriminant in maximum and minimum pain levels. We also used a Neural Network based approach in order to classify the EEG patterns, distinguishing between minimum and maximum pain levels. We achieved the total accuracy of 90.9 %  

Learning a foreign language encompasses a process of trial and error that can lead to the progression of the learner's interlanguage, meaning that the learners make use of their language knowledge that receives feedback and brings about progress through diagnosis of the problems and being corrected by the teacher. Therefore, there exists a need to analyze the underlying reasons causing the students to remain taciturn with a low willingness to communicate (WTC) during a language class. There has been much work done investigating the role of the learner's stable personal characteristics (traits) along with their situational changes at a specific time (states) that influence the student's... 

Using 3-D scanned data to analyze and extract pore network plays a vital role in investigation of porous media's characteristics. In this paper, a new simple method is developed to detect pores and throats for analyzing the connectivity and permeability of the network. This automated method utilizes some of the common and well-known image processing functions which are widely accessible by researchers and this has led to an easy algorithm implementation. In this method, after polishing and quality control of images, using city-block distance function and watershed segmentation algorithm, pores and throats are detected and 3-D network is produced. This method can also be applied on 2-D images... 

In this paper, we try to recognize and distinguish different groups of arrhythmia using novel features which have been obtained from the heart rate's phase space in recent years. For this purpose, we used Triangular Phase Space Mapping (TPSM) and Parabolic Phase Space Mapping (PPSM). For recognition, we used three groups of 15 subjects using the Physionet database (Arrhythmia, Congestive Heart Failure (CHF), and Atrial Fibrillation (AF)) with Normal Sinus Rhythm (NSR). The obtained features discriminate arrhythmia from NSR by p