Sharif Digital Repository

Investigating human brain activity during expressing emotional states provides deep insight into complex cognitive functions and neurological correlations inside the brain. To be able to resemble the brain function in the best manner, a complex and natural stimulus should be applied as well, the method used for data analysis should have fewer assumptions, simplifications, and parameter adjustment. In this study, we examined a functional magnetic resonance imaging dataset obtained during an emotional audio-movie stimulus associated with human life. We used Jackknife Correlation (JC) method to derive a representation of time-varying functional connectivity. We applied different binary measures... 

In recent years, the regression dynamic causal modelling (rDCM) method was introduced as a new version of dynamic causal modelling (DCM) to derive effective connectivity in whole-brain networks for functional magnetic resonance imaging (fMRI) data. In this research, we used data obtained while applying the stimulation of audio movie comprised different emotional states. We applied this method to two networks consisting of ten auditory and forty-four regions, respectively. This method was used to study effective connections between emotional states and represent the distinction between emotions. Finally, significant effective connections were found in emotional processing and auditory... 

Cellular CDMA systems have to trade user capacity to increase cell coverage. Moreover, coverage of CDMA is uplink-limited because uplink channels are not orthogonal and transmit powers of mobile stations are limited. In this paper, we propose a coverage-dependent dynamic channel allocation (DCA) method for TDMA-CDMA. In this method, different uplink timeslots have different level of coverage-capacity tradeoff, i.e., Non-Homogeneous Coverage-Capacity Tradeoff (NHCCT). This method reduces uplink power consumption and improves coverage-capacity tradeoff, compared to Load Balancing DCA method. Finally, we verify our approach by numerical analysis and simulation. © 2008 IEEE  

The debate over innovativeness of large firms and SMEs, which was bolded by Schumpeter, still continues under mixed empirical evidences. There are several implications for this debate including policy orientation in support of large firms or SMEs. But there is a scarce of studies in developing countries and no such study in Iran yet. The present study has explored the proportionality of increase of innovation activity versus firm size within 522 Iranian knowledge-based firms categorized in 9 industries. Innovation activity was measured by R&D expenditure while firm size stood for number of employees. Using log-log regression in the first phase, it was found that R&D expenditure confirms a... 

The debate over innovativeness of large firms and SMEs, which was bolded by Schumpeter, still continues under mixed empirical evidences. There are several implications for this debate including policy orientation in support of large firms or SMEs. But there is a scarce of studies in developing countries and no such study in Iran yet. The present study has explored the proportionality of increase of innovation activity versus firm size within 522 Iranian knowledge-based firms categorized in 9 industries. Innovation activity was measured by R&D expenditure while firm size stood for number of employees. Using log–log regression in the first phase, it was found that R&D expenditure confirms a... 

Brain connectivity estimation is a useful method to study brain functions and diagnose neuroscience disorders. Effective connectivity is a subdivision of brain connectivity which discusses the causal relationship between different parts of the brain. In this study, a dual Kalman-based method is used for effective connectivity estimation. Because of connectivity changes in autism, the method is applied to autistic signals for effective connectivity estimation. For method validation, the dual Kalman based method is compared with other connectivity estimation methods by estimation error and the dual Kalman-based method gives acceptable results with less estimation errors. Then, connectivities... 

Most of previous studies on fuzzy regression analysis have a common characteristic of increasing spreads for the estimated fuzzy responses as the independent variable increases its magnitude, which is not suitable for general cases. In this paper, fuzzy linear regression models with fuzzy/crisp output, fuzzy/crisp input are considered, and an estimated method along with a mathematical-programming-based approach is proposed. The advantages of the proposed approach are simplicity in programming and computation, and minimum difference of total spread between observed and estimated values. © 2003 Elsevier Inc. All rights reserved  

Wearable human activity recognition systems (HAR) using inertial measurement units (IMU) play a key role in the development of smart rehabilitation systems. Training of a HAR system with patient data is costly, time-consuming, and difficult for the patients. This study proposes a new scheme for the optimal design of HARs with minimal involvement of the patients. It uses healthy subject data for optimal design for a set of activities used in the rehabilitation of PD1 patients. It maintains its performance for individual PD subjects using a single session data collection and an adaptation procedure. In the optimal design, several classifiers (i.e. NM, k-NN, MLP with RBF as a hidden layer, and... 

Finding binary sequences with low autocorrelation is very important in many applications and their construction is a hard computational problem. Here a new exhaustive search algorithm is developed to find all optimal aperiodic binary sequences which are faster than simple one and it achieves its efficiency through a combination of the following four devices: (1) A branch-and-bound search strategy; (2) Search logic that avoids codes redundant relative to two PSL-preserving operations; (3) A fast recursive method for computing autocorrelation functions of binary sequences; (4) A simple scheme for partitioning and parallelizing, made possible by the fixed upper bound on psl  

This paper develops a new evolutionary algorithm for generating low autocorrelation binary sequences. These sequences are of interest in pulse compression technique. The proposed algorithm is fast enough to yield optimum or near optimum codes. The generated sequences were compared to the best literature and were seen that its results are better than the others. This suggested method could change 11 rows of the previous best known PSLs table, whereas the previous literature could change only one record. These records were combined with the best results reported in the papers to produce a new best minimal-PSL binary sequence table for bit lengths 71 through 100. ©2008 IEEE  

Distinguishing reflected waveforms from two separated targets which are very close to each other is an important challenge in radar signal processing. Pulse compression is a technique used for accounting for this problem. There are several methods for compressing such as phase coding waveform and the goal of this paper is finding these optimal codes. In this paper, by combining several contents, a new optimum method based on Genetic Algorithm is suggested. This method has low computational operation and its speed is faster than the other ordinary algorithms. This method is belonged to local or partial search methods and has following advantages: 1. It uses branch-and-bound strategy; 2. It's... 

To estimate the parameters of fuzzy linear regression models with fuzzy output and crisp inputs, we develop a mathematical programming model in this paper. The method is constructed on the basis of minimizing the square of the total difference between observed and estimated spread values or in other words minimizing the least square errors. The advantage of the proposed approach is its simplicity in programming and computation as well as its performance. To compare the performance of the proposed approach with the other methods, two examples are presented. © 2004 Elsevier Inc. All rights reserved  

In this paper, fuzzy linear regression models with fuzzy/crisp output, fuzzy/crisp input are considered. In this regard, we define risk-neutral, risk-averse and risk-seeking fuzzy linear regression models. In order to do that, two equality indices are applied to express the degree of equality between a pair of fuzzy numbers. We also develop three mathematical models to obtain the parameters of fuzzy linear regression models. Minimizing the difference between the total spread of the observed and estimated values is the objective of these models. The advantage of our proposed models is the simplicity in programming and computation  

In this paper, the nonlinear transversal vibration of an axially moving viscoelastic string on a viscoelastic guide subjected to a mono-frequency excitation is considered. The model of the viscoelastic guide is a parallel combination of springs and viscous dampers. The governing equation of motion is developed using Hamilton's principle. Applying the method of multiple scales to the governing partial differential equation, the solvability condition and approximate solutions are derived. Three cases, namely primary, subharmonic and superharmonic resonances are studied and appropriate analytical solutions are obtained. The effect of mean value velocity, force amplitude, guide stiffness and...