Search

Purpose: The present research aims to develop a model for automatically inferring the relationships between terms in the Thesaurus of Islamic Sciences using Graph Convolutional Networks (GCN). By employing new algorithms in the field of deep learning, the research seeks to enhance the efficiency of information retrieval in the Thesaurus of Islamic Sciences. To enhance accuracy and comprehensiveness, reduce costs, and improve relationships between terms. Method: The current research employed used of convolutional networks method, networks, is are one of the crucial techniques methods in the field of learning. This method is capable of leveraging from the relationship patterns in the while also focusing on to the characteristics of each node. The dataset under study comprises all the terms from the thesaurus of Islamic sciences generated between 1994 and the early 2022, which are represented as a graph. The vertices represent the terms, and the edges represent the relationships between the terms in the graph. This graph is provided as input to the convolutional network, which then generates a model for the automatic inference of connections. And in order to analyze the obtained outputs, AP and ROC standards have been used. Findings: The revealed showed the model achieved the average accuracy 75% and a Roc score of 72% obtained for the data. It is noteworthy to accept the results considering that this method was used for the first time in the field of Islamic sciences and thesauruses. Conclusion: Despite shift in preference opinion thesauri thesauruses to ontologies, the use thesauri remains still of particularly especially in Iran. Compared to previous research, the method used to construct the thesaurus is different, resulting in more reliable outcomes. Consequently, we can expect improved results for various purposes, such as automatic indexing. New advancements in natural language processing and deep learning also give us hope for improvements in information retrieval and automatic indexing. [ABSTRACT FROM AUTHOR]

Some of the most important challenges facing water managers are to increase water supply and reduce its demand. A single systematic method is needed to address both issues, such as the System Dynamics (SD) modeling approach. In this approach all the factors, parameters, and their influences on the problem are considered by causal loops and stock-flow diagrams. The multipurpose Dez Reservoir in southwestern Iran is a good case study for this approach, and we simulated 10 years under differing operation strategies to develop the most appropriate operation policy. A hydrologic time series analysis was conducted to generate simulated inflow to the reservoir, and differing policies, including hedging rules and a “goal-seeking hedge,” were applied. By using performance criteria and a new measure entitled “corrected reliability,”, the most appropriate scenarios were identified. We found that using the goal-seeking hedge in combination with water demand management offers the best chance for effectively meeting demands and minimizing supply shortages. [ABSTRACT FROM AUTHOR]

The first three formants, i.e., the first three spectral prominences of the short-time magnitude spectra, have been the most commonly used acoustic cues for vowels ever since the work of Peterson and Barney [J. Acoust. Soc. Am. 24, 175-184 (1952)]. However, spectral shape features, which encode the global smoothed spectrum, provide a more complete spectral description, and therefore might be even better acoustic correlates for vowels. In this study automatic vowel classification experiments were used to compare formants and spectral-shape features for monopthongal vowels spoken in the context of isolated CVC words, under a variety of conditions. The roles of static and time-varying information for vowel discrimination were also compared. Spectral shape was encoded using the coefficients in a cosine expansion of the nonlinearly scaled magnitude spectrum. Under almost all conditions investigated, in the absence of fundamental frequency (F0) information, automatic vowel classification based on spectral-shape features was superior to that based on formants. If F0 was used as an additional feature, vowel classification based on spectral shape features was still superior to that based on formants, but the differences between the two feature sets were reduced. It was also found that the error pattern of perceptual confusions was more closely correlated with errors in automatic classification obtained from spectral-shape features than with classification errors from formants. Therefore it is concluded that spectral-shape features are a more complete set of acoustic correlates for vowel identity than are formants. In comparing static and time-varying features, static features were the most important for vowel discrimination, but feature trajectories were valuable secondary sources of information. [ABSTRACT FROM AUTHOR]

This paper investigates the dynamic response of a clamped-free CNT-reinforced-MRE beam which is actuated by the combination of a constant and a harmonic time-dependent magnetic field. Using Hamilton’s principle, the equation of motion has been obtained and discretized using the Galerkin method. This procedure transforms the governing PDE equation of motion into a nonlinear ODE equation in the form of the nonlinear Mathieu equation with cubic damping. Then, the method of multiple scales is employed to obtain the dynamic response of the system. Furthermore, a stability analysis is also performed and the effects of a magnetic field on the dynamic response and stability of the system is investigated. The stability analysis shows that as the amplitude of the constant magnetic field is increased, the stable region decreases. Also, a numerical bifurcation analysis has been performed and Feigenbaum diagrams are obtained, indicating that when the constant magnetic field is less than the harmonic one, the system approaches greater amplitudes and undergoes more chaos, and vice versa. [ABSTRACT FROM AUTHOR]