Sharif Digital Repository

In this article a new scheme is proposed to use mean supervector in text-prompted speaker verification system. In this scheme, for each month name a subsystem is constructed and a final score based on passphrase is computed by the combination of the scores of these subsystems. Results from the telephony dataset of Persian month names show that the proposed method significantly reduces EER in comparison with the-State-of-the-art State-GMM-MAP method. Furthermore, it is shown that based on training set and testing set we can use 12 models per speaker instead of 220. Therefore, this scheme reduces EER and computational burden. In addition, the use of HMM instead of GMM as words' model improves... 

In this paper, statistical speech enhancement using hidden Markov model (HMM) is studied and new techniques for applying non-Gaussian distributions are proposed. The superiority of using non-Gaussian distributions in online adaptive noise suppression algorithms has been proven; however, in this study, this approach is formulated in an HMM-based mean-square error estimator (MMSE) estimator in which a priori models are trained in an off-line manner. In addition, an analytical study of using different distributions other than autoregressive (AR) Gaussian distribution, such as Laplace, is presented in order to construct an accurate HMM as a priori model for discrete Fourier transform and... 

Pricing is seen as a viable alternative to manage the demand for transportation facilities. While supply increase might aggravate the problem, pricing is envisaged to relieve large cities from adverse traffic effects (congestion and pollution, among others). Nevertheless, pricing has its own drawbacks, often overlooked by the operators of the networks. It will cause changes in the travel behavior of the different groups and their demands (shoppers, retailers, and even basic businesses/ employees). This paper presents an extensive review of the subject, and an equilibrium model to estimate the long–run effects of a cordon pricing scheme. The problem of designing a price for a Central Business... 

In the present research, ultrasonic-assisted emulsification-microextraction (USAEME) coupled with gas chromatography-mass spectrometry (GC-MS) has been proposed for analysis of thirteen environmental protection agency (EPA) polycyclic aromatic hydrocarbons (PAHs) in aqueous samples. Tetrachloroethylene was selected as extraction solvent. The main parameters of USAEME affecting the efficiency of the method were modeled and optimized using a central composite design (CCD). Under the optimum conditions (9 μL for extraction solvent, 1.15% (w/v) NaCl (salt concentration) and 10min for ultrasonication time), preconcentration factor (PF) of the PAHs was in the range of 500-950. In order to have a... 

Multivariate curve resolution-alternating least squares (MCR-ALS) as a second-order calibration algorithm was proposed for the simultaneous analysis of eighteen fatty acid methyl esters (FAMEs) in a standard mixture and pomegranate seed sample using vortex-assisted extraction-dispersive liquid-liquid microextraction (VAE-DLLME), followed by gas chromatography-mass spectrometry (GC-MS). The chemometric resolution, identification and quantification of the target FAMEs in the standard mixture and real sample (i.e., the pomegranate seed) were carried out successfully in the presence of some uncalibrated interferences. The lack of fit (LOF) and reverse match factor (RMF) were used for the... 

Chromatographic fingerprinting is an effective methodology for authentication and quality control of herbal products. In the presented study, a chemometric strategy based on multivariate curve resolution-alternating least squares (MCR-ALS) and multivariate pattern recognition methods was used to establish a gas chromatography-mass spectrometry (GC-MS) fingerprint of saffron. For this purpose, the volatile metabolites of 17 Iranian saffron samples, collected from different geographical regions, were determined using the combined method of ultrasound-assisted solvent extraction (UASE) and dispersive liquid-liquid microextraction (DLLME), coupled with GC-MS. The resolved elution profiles and... 

This paper proposes a high performance voltage tracking and current sharing among parallel connected inverters by applying optimal control and minimizing the cost function. The control system forces the voltage of load to track the voltage reference, and the current of all inverters becomes equal. Therefore, both current sharing and voltage tracking are obtained. In addition, the smallest input energy and simplicity in control circuit are the other advantages of the suggested method. To show the performance of the proposed control scheme, the simulations with two-modular practical systems are performed and the results are provided. The results indicate that the control objectives are... 

In this paper, a novel spatial six-degree-of freedom parallel manipulator actuated by three base-mounted partial spherical actuators is studied. This new parallel manipulator consists of a base platform and a moving platform, which are connected by three legs. Each leg of the manipulator is composed of a spherical joint, prismatic joint and universal joint. The base-mounted partial spherical actuators can only specify the direction of their corresponding legs. In other words, the spin of each leg is a passive degree-of-freedom. The inverse pose and forward pose of the new mechanism are described. In the inverse pose kinematics, active joint variables are calculated with no need for... 

The duration of utterances is one of the effective factors on the performance of speaker verification systems. Text dependent speaker verification suffers from both short duration and unmatched content between enrollment and test segments. In this paper, we use Discriminative Gaussian Process Latent Variable Model (DGPLVM) to deal with the uncertainty caused by short duration. This is the first attempt to utilize Gaussian Process for speaker verification. Also, to manage the unmatched content between enrollment and test segments we proposed the localized-DGPLVM that trains DGPLVM for each phrase in dataset. Experiments show the relative improvement of 27.4% in EER on RSR2015  

Loss of lower extremities has been one of the main problems in human life. Although most of the available knee devices are aesthetically acceptable, there is a necessity for lighter and more compact mechanisms, especially for younger amputees. This problem can be solved by the combining compliant mechanism design with traditional mechanism design methods. In this study, one group of the prosthetics that is known as the compliant knee mechanisms" is evaluated. At first, the different knee mechanisms, such as fourand six-bar knee linkages are investigated to calculate the values of the control moments (actuator torque). Then, the suitable location (where the actuator torque is to be exerted)... 

Design and fabrication of solar collectors with high performance of energy efficiency to convert solar energy to utility energy is vitally important. This article reports the results obtained from design, construction and investigation of the performance of a Combined Multi-Purpose Vacuum Solar Collector (CMPVSC). This collector consists of three sections: the vacuum section, the liquid section and the air section. In the present collector, it is capable of transferring heat to two flows (liquid and air) simultaneously and separate with the possibility of multipurpose applications. The CMPVSC is compared with the existing individual collectors and the effects of different parameters on the... 

In the aftermath of earthquakes, hospitals serve the critical role of treating casualties. In many cases, the key components of a hospital (i.e., the building, staff, medicine inventory, technical systems, and medical equipment) are affected by an earthquake. To handle the demand surge, affected hospitals should recover in an effective manner. Hospital recovery is a complex and dynamic process because each component requires specific types and amount of resources to recover. Furthermore, the recovery of each component not only affects its performance but also plays a role in the overall hospital recovery. Hospital administrators need to model the complex recovery process after a future... 

Nowadays, with the advancement of technology, humans are looking for ways to cure various diseases. Meanwhile, musculoskeletal injuries usually have a long treatment period. Therefore, in recent years, Researchers working one exoskeleton with rehabilitation application which conduct physiotherapy tasks. In current study, a portable two degree of freedom hand exoskeleton is designed which its mechanism is a combination of cable and link mechanism, MCP1 1Metacarpophalangeal joint between metacarpal and proximal phalanges joints move by link mechanism, DIP2 2Distal interphalangeal joint between proximal phalanges and middle phalanges and PIP3 3Proximal interphalangeal joint between middle... 

In this paper, chaos in spatial attitude dynamics of a triaxial rigid satellite in an elliptic orbit is investigated analytically and numerically. The goal in the analytical part is to prove the existence of chaos and then to find a relation for the width of chaotic layers (i.e. the initial values needed to have a chaotic attitude motion) based on the parameters of the system. The numerical part is aimed at validating the analytical method using the Poincaré maps and the maximum value of the Lyapunov exponents. The rotational–translational Hamiltonian of the system is first derived. This Hamiltonian has six degrees of freedom. Choosing a proper set of coordinates and given the fact that the... 

In this paper, chaos in spatial attitude dynamics of a triaxial rigid satellite in an elliptic orbit is investigated analytically and numerically. The goal in the analytical part is to prove the existence of chaos and then to find a relation for the width of chaotic layers (i.e. the initial values needed to have a chaotic attitude motion) based on the parameters of the system. The numerical part is aimed at validating the analytical method using the Poincaré maps and the maximum value of the Lyapunov exponents. The rotational–translational Hamiltonian of the system is first derived. This Hamiltonian has six degrees of freedom. Choosing a proper set of coordinates and given the fact that the... 

Spin-transfer torque magnetic RAM (STT-MRAM) is known as the most promising replacement for static random access memory (SRAM) technology in large last-level cache memories (LLC). Despite its high density, nonvolatility, near-zero leakage power, and immunity to radiation as the major advantages, STT-MRAM-based cache memory suffers from high error rates mainly due to retention failure (RF), read disturbance, and write failure. Existing studies are limited to estimate the rate of only one or two of these error types for STT-MRAM cache. However, the overall vulnerability of STT-MRAM caches, whose estimation is a must to design cost-efficient reliable caches, has not been studied previously. In... 

Background: While decoding visual and auditory stimuli using recorded EEG signals has enjoyed significant attention in the past decades, decoding olfactory sensory input from EEG data remains a novelty. Recent interest in the brain's mechanisms of processing olfactory stimuli partly stems from the association of the olfactory system and its deficit with neurodegenerative diseases. New Methods: An olfactory stimulus decoder using features that represent nonlinear behavior content in the recorded EEG data has been introduced for classifying 4 olfactory stimuli in 5 healthy male subjects. Results: We show that by using nonlinear and chaotic features, a subject-specific classifier can be... 

Autoregressive models are among the most successful neural network methods for estimating a distribution from a set of samples. However, these models, such as other neural methods, need large data sets to provide good estimations. We believe that knowing structural information about the data can improve their performance on small data sets. Masked autoencoder for distribution estimation (MADE) is a well-structured density estimator, which alters a simple autoencoder by setting a set of masks on its connections to satisfy the autoregressive condition. Nevertheless, this model does not benefit from extra information that we might know about the structure of the data. This information can... 

In this paper, we introduce a new dataset for SAD and evaluate certain common methods such as GMM, DNN, and RNN on it. We have collected our dataset in a semi-supervised approach, using subtitled movies, with a labeling accuracy of 95%. This semi-automatic method can help us collect huge amounts of labeled audio data with very high diversity in language, speaker, and channel. We model the problem of SAD as a classification task to two classes of speech and non-speech. When using GMM for this problem, we use two separate mixtures to model speech and non-speech. In the case of neural networks, we use a softmax layer at the end of the network, with two neurons which represent speech and... 

In this paper, we want to solve multi-objective robot path planning problem. A new elitist multi-objective approach is proposed to determine Pareto front based on coefficient of variation. Intelligent water drops (IWD) algorithm is generalized by this approach and as a new multi-objective IWD algorithm. We call our new algorithm CV-based MO-IWD. It tried to optimize two objectives: length and safety of the path. In the CV-based MO-IWD, we want to discover solutions as close to optimal Pareto solutions as possible and find solutions as diverse as possible in the obtained Pareto front. In this way, coefficient of variation of Pareto front is determined in each objective. Then, appropriate...