مجله انجمن مهندسی صوتیات ایران
سال دهم شماره 2 (پاییز و زمستان 1401)

One popular method to produce 2D materials is the physical method of liquid phase exfoliation (LPE) utilizing ultrasound technique. In this research, our aim is to obtain the optimum conditions for the exfoliation of 2D materials of graphene from graphite utilizing LPE by simulation of ultrasonic waves irradiation and the pressure difference in the solution using COMSOL physics interactive. These simulations are carried on for the probe of 14 mm in diameter and 22 kHz in frequency, and then for the probe of 22 mm and 40 mm in diameter and 20 kHz frequency to obtain the maximum acoustic pressure difference in the solution. Then the probe, which the simulation shows produces the maximum acoustic pressure difference is used for the experimental investigation of the volume and the density of the graphite solution, which is irradiated by ultrasound for graphene, produced. The numerical simulations give an expectation to have more graphene exfoliation when the pressure difference in solution sonication is more. This expectation is verified by the experimentation. The experimental results which are analyzed using UV-visible spectroscopy, FESEM, TEM, and Raman spectrum show the probes with 14 mm and 22 mm produce less flakes which are in smaller size compared to the probe with diameter 40 mm which few-layer and even bilayer graphene with larger size are observed. Also we observed the density and the volume of the solution has importance in the layer number of the flakes production.

In this research, TDNN model and x-vector are presented in order to robust noise and frequency filtering caused by telephone communication. MFCC is used as the speaker-related audio feature as input to this model. The output of neural network of this model is considered as an x-vector so that it can be used in the decision stage. In the decision stage, PLDA was used for scoring and comparison. In order to increase accuracy and reduce EER, the training dataset is a combination of relatively clean VoxCeleb 1,2 dataset and Callhome telephone dataset, as well as noise and telephone dataset obtained from the data augmentation method. The results of using this method for EER in the clean state are 3.09%, which has improved about 0.15% (3.24% has been obtained in previous works) in the worst case and 6.93% (10.2% has been obtained in previous works) in the best case compared to the base models. When training with Voxceleb1,2 and Callhome datasets was used as an adaptation, the EER was 4.95%. In the worst case, when only the Voxceleb1 data is converted to a telephone, the EER is 14.34%.

Technologies related to underwater acoustics are used for underwater communication, determining the location and discovering unknown targets under the sea, depth finding, seabed mapping, shipping, navigation, etc. Estimating the effectiveness and efficiency of underwater acoustic equipment requires underwater acoustic modeling. In this research, in order to implement different scenarios of acoustic wave propagation modeling in the waters of the Gulf of Oman, different methods of solving acoustic equations and, accordingly, several acoustic models have been used. In the following, the results of these scenarios are examined and compared. The results show that the acoustic pressure obtained from the acoustic models are related to water depth, independent issues with frequency (low and high) and dependent on range (short or long).

Sonar systems are of special importance in many ways, including military applications, shipping, fishing, etc. Therefore, the classification of sonar data is always of interest to experts in this field. In this article, two data preparation methods were used. In the first method, all the features extracted from the data and in the proposed method were averaged out of the time period used to extract the feature in the form of ten period. Different structures of artificial neural network and hybrid neural network were compared with particle swarm algorithm (PSO) to achieve the highest performance in classifying sounds emitted by floats based on float length. The results showed that in the case of using raw extracted features in the use of artificial neural network, the 2-2-2 structure in the hidden layer had the highest performance for training and testing conditions equal to 90.61 and 90% respectively. By using the hybrid neural network, the classification accuracy increased and reached 94.44% in the test conditions. In using the proposed method to prepare the extracted data, the simple structure of one layer with 6 neurons in the hidden layer provided the highest performance in the classification of the extracted features by 100% for training and testing.

The sensors used to detect acoustic waves were included only electrical and magnetic methods before. But today, more advanced technologies such as micro-electromechanical sensors and fiber optics have been studied to design sensors. In this paper, we are intended to introduce a new sensor based on fiber optic technology, designed and built for implementation in sonars for tracking drones. Among the various types of fiber optic sensors, phase interferometers, especially Fabry-Perot, are the most sensitive. However, their output signals require advanced signal processing due to their interference and nonlinearity. In this paper, the design and fabrication of the Fabry-Perot sensor is discussed which is combined with the diaphragm structure to adjust the frequency response to the common acoustic wave frequency emitted by the drone engine. Digital programs based on the FMCW method have also been developed to process the output signal from this sensor; which can instantly receive information from the sensor. The sensor designed and built in this paper has a significant sensitivity of 6.25 microvolts per pascal after characterization and also shows an SNR of 56 at its operating frequency in case of data collection with the program developed for signal processing.

In this paper, phonon modes and charge density of titanium indium carbide compound are calculated.The calculations have been performed using Pseudopotential method in the framework of density functional theory by the Quantum Espresso package.The number of phonon modes has been reduced from 24 to 16 due to the symmetry of the crystal. Also, the charge density diagram shows a strong bond between carbon and titanium atoms and a weaker bond between titanium and indium atoms. The calculations are in good agreement with other results.

Internal jugular vein pressure changes, as one of the central veins, indicate hemodynamic changes in the right side of the heart. Inflammation caused by MS (multiple sclerosis) causes the destruction of the endothelial layer of blood vessels. The aim of the study is to extract the pressure of the internal jugular vein from the changes in the diameter of the vein wall. 42 cases of internal jugular vein with relapsing MS (n=21) and healthy (n=21) groups were studied. Sequential B-mode ultrasound images with a minimum of 30 frames per second were recorded and stored from the jugular vein. The maximum and minimum diameters of the internal jugular vein were extracted from ultrasound images using the maximum gradient algorithm. By using the pressure-diameter relationship, internal jugular vein pressure was extracted. The maximum and minimum pressure of the jugular vein in the group of patients with MS were measured as 5.64 ± 1.62 and 5.05 ± 1.67 cmH2O in the healthy group as 4.08 ± 1.12 and 3.58 ± 1.06 cmH2O respectively (p<0.05). It is concluded that by using the processing of ultrasound images and estimating the temporal changes in diameter, it is possible to extract the pressure of the jugular vein.

In recent years, to reduce the complexity of implementation, the use of 2D arrays with restricted row-column addressing has been considered for 3D ultrasound imaging. In this paper, two methods of adaptive beamforming based on the minimum variance method are represented in such a way that the computational load is much less than using the full adaptive beamforming method. In both proposed methods, to reconstruct each point of the image, only two covariance matrices and two weight vectors are determined. These methods perform significant improvement both in lateral resolution and contrast compared with delay and sum method. To evaluate the proposed methods, the data obtained from a 32+32 element array has been analyzed using the FIELD-II ultrasound simulator. By using a point phantom, it has been shown that the value of the full width at half maximum of the point spread function is reduced by 95% in the first method compared to the delay and sum method. Also, by using the cyst phantom, it can be seen that the contrast ratio and the contrast to noise ratio can be improved by almost 100% and 50%, respectively in comparison to the delay and sum method.