مهندس علی جمالی

The present study investigates the narratives of children with autism spectrum disorder and normal developing children focusing on the language used to describe character’s thoughts and emotions (i.e., internal state language, ISL).

the sample of the study consisted of 21 autistic children and 24 normal developing children who were matched on IQ, receptive and expressive vocabulary.

The present study had three major.

First, despite equivalent performance on standardized language assessments, the volume of children’s narratives (i.e., the number of utterances and words, the range of unique verbs and adjectives) was lower in children with ASD than in typically developing controls. Second, after controlling for narrative volume, the narratives of children with ASD were less likely to reference the characters’ emotions than was the case for typically developing controls. Finally, our results revealed a specific association between children’s use of emotion terms and their performance on a battery of experimental tasks evaluating children’s Theory of Mind abilities.

The results of the study showed that the poor narrative skills of children with ASD may at least in part be attributed to deficits in the ability to interpret others’ thoughts internal states.

Simile understanding requires two distinct pragmatic skills: understanding the intended similarity and deriving a scalar implicature (e.g., “Nina is like a rabbit” normally implies that “Nina is not a rabbit”). However, the second skill has not been studied yet by Iranian researchers. The aim of the present study was to investigate the ability of mono-lingual Persian-speaking children aged 3 to 7 years old and adults in understanding scalar implicature. To this aim, 50 Persian-speaking children, 3, 4, 5, 6, and 7 years old were selected through a semi-random method and were compared with 10 adults. The groups were investigated and compared in the first experiment which was a form of similarity judgment task and in the second experiment, which was in a form of a game. In the first experiment, subjects should understand “x is like a y” as an expression of similarity. In the second experiment, the subjects received metaphors (“Nina is a rabbit”) and similes (“Nina is like a rabbit) as clues to select one of three images (a rabbit, a girl, or a rabbit-looking girl). The results showed that 3-year-old children could understand the implicature “x is not a y”, whereas 5 years old children performed like adults. The results showed that children from early childhood were able to understand and derive scalar implicature, and the literal meaning of simile and metaphor decreased with increasing age.

Some literary works, despite their simple appearance and small volume, are so rich in content and have such strong symbolism that they encompass the equations of the greatest contemporary philosophers. The stronger by August Strindberg is not an exception to this rule. The main objective of this article, after redefining ambiguity, going beyond the definition of Empson and metaphor, broader than the Derridean meaning, relying on the inevitable process of inclusion, exclusion and identification, to discover how the author's power is exerted and his role in creating the work—which is itself a reading of the world surrounding the work—and also the mode of the reader's exercise of power in interpreting the text—which is a rewriting of the work from a different perspective—and in this regard, it establishes a general framework that Foucault has presented in his examination of power and discourse. After finding the connection between ambiguity and metaphor, the role of these two in exercising power or preventing it is explored, and ultimately, the relationship of these concepts with literature, the creation, and the reading of this literary work are examined. In the world of the text, similar to the world of the metatext, the arena of ambiguity and metaphorization, and consequently the field of battle of wills, instincts, interests, and various metaphors, sometimes result in a temporary peace, but if such methods do not yield results, only inevitable violence can expose one metaphor as unjust and invalid in favor of another metaphor.

Fault diagnosis of mechanical systems is of special importance for better system performance as well as its protection. In this work, a rotary motor laboratory system is used to generate signals and data. The obtained data are placed in the pre-processing process. In this article, to improve the performance of signal analysis, the combined analysis methods using signal features and Kalman filter are proposed. At first, the Kalman filter is used to reduce the signal noise. And in the following, for signal pre-processing, the features of the signal in the time domain and frequency domain are suggested, which have been used as one-dimensional signal pre-processing. In the following, several neural networks such as support vector machine, multilayer perceptron, and convolutional neural networks have been used to analyze the obtained features. To check the results, the data is divided into training data and validation data. Accuracy results for validation data are examined in different methods. The results indicate the better performance of the AlexNet convolutional neural network in the presence of the Kalman filter denoising process. In this case, this network has reached an average of 96.1% accuracy for validation data, which has been improved compared to other classifiers and fault diagnosis without noise reduction.

In recent years the use of artificial intelligence techniques in the financial and investment markets instead of customary quantitative methods has been increasing and gives better performance towards classic methods usually. Artificial Neural Network (ANN), has weaknesses points despite its enormous benefits also. In this study, in order to overcome the weaknesses of the network consists of combining artificial intelligence methods with Evolutionary algorithms, means of artificial neural network combined with genetic algorithm (GA) and Particle Swarm algorithm (PSO) to model and daily predict of nominal exchange rates or the exchange rate dollar by Rial in Iran in the period 21.03.2013 to 22.12.2019 is used. This combined model with neural networks method as one artificial intelligence model according to the criteria of MSE , RMSE, MAE, U.Theil compared. The results of this research show the superiority of synthetic neural network model -Particle Swarm algorithm compare to other models of investigation.

This article addresses the bi-level multi-objective optimization problems raised in reliability-based robust design optimization of mechanism synthesis through establishing a state-of-the-art game theoretic scenario. A novel bi-level decentralized decision-making approach is proposed using the synergy of reliability-based robust design optimization (RBRDO), Stackelberg/cooperative game theory, Monte Carlo simulation (MCS) and genetic programming (GP). The application of the proposed approach is elaborated in a case-study of multi-objective robust synthesis of high-speed path generating four-bar. The four performance criteria, namely, accuracy (), robustness ( and ), reliability () at upper level and quality of motion () at lower level are assigned to four players so that each of whom is in charge of one objective criterion being optimized. The peak input driving torque as the dynamic constraint is associated with the upper-level problem. The genetic programming (GP) metamodel is used to capture the Stackelberg protocol between two levels i.e., constructing the follower’s rational reaction set (RRS) and the Nash arbitration scheme is hired to model the cooperative behaviors in upper level. By this way, the four-objective optimization problem of four-bar linkage is reduced into a single-objective robust design problem. The obtained results show a considerable enhancement in reliability and robust behavior of mechanism, whilst the deterministic criteria of accuracy and quality of motion is preserved.

These days, societies' need for energy increased due to the expansion of societies, industries, and technology. The production of electricity from renewable energy sources such as solar energy, which does not harm the environment and has little pollution, has attracted the attention of many researchers and engineers. This article will present a new plan for the dual polar axis solar tracker, its design and construction in laboratory dimensions, and the experimental evaluation of its performance using the open-loop control method. For this purpose, after examining the advantages and disadvantages of the previous designs, a new and different conceptual design for the tracker is proposed. Among the features of the proposed tracker, we can point out the ability to combine, install and operate quickly and easily, the self-locking feature, and the ability to rotate 360 ​​degrees around both axes. This tracker has no restrictions for use in different geographical areas, including areas near the North or South Pole and in the early and late hours of the day when the direction of the sun's radiation is strongly inclined. In the following, the detailed design of the proposed detector and the presentation of the open-loop control method will be discussed. Finally, by conducting experimental tests, the production power of the proposed detector is evaluated in comparison with a fixed solar panel. Based on the results, the electricity energy produced from the proposed solar tracker is 49% more than the fixed solar panel.

The present study investigated the effects of bilingualism and Autism Spectrum Disorder (ASD) on children’s abilities to narrate a story. To this aim, the stories narrated by monolingual and bilingual Kurdish-Persian-speaking children with and without ASD were compared. They were given a set of 3 picture cards depicting a scenario and were asked to sequence the cards and tell a story. Then, their language productions (number of utterances and total number of words), macrostructures (appropriate sequencing of events, number of events mentioned, and coherence), and microstructures (character introductions, maintenance of referential terms, use of grammatical gender, and use of connectives) were measured. The findings showed that the bilinguals produced more utterances compared to the monolinguals despite having marginally lower receptive vocabulary scores in Persian. Also, the typically-developing children provided more coherent narratives. No significant differences were found in their microstructures. There were no decrements in the narratives of the monolingual and bilingual children with and without ASD. In fact, an increased number of utterances were found in the bilinguals’ narratives. The current findings suggested that bilingualism does not negatively affect narrative skills in children with ASD.

Ever since the publication of Susan Glaspell's play in one act, Trifles, in 1916, it has become a playground for different feminist theories to counterpart, many of which struggle to categorize the play as a reproduction of the traditional gender roles set by patriarchy. Since there seems to be no unity in defining the term 'feminism,' many believe that it would do justice to call its varieties, 'feminisms'. Being one of the most well-known terms in feminism, men's gaze has been viewed and reviewed constantly throughout the years. Yet, what seems to be new to this field is the concept of the 'female gaze'. Unlike anti-essentialists, essentialist feminists believe in embracing the 'essential' differences between men and women. Therefore, this paper analyzes Glaspell's play in the light of these two points of view on feminism, especially the theories of gaze, and looks for a shared ground for reconciliation. So, by delving into these theories, the researcher eventually concludes that although Trifles is criticizing the female status in a patriarchal society, relating all associated with her to 'trifles,' at the same time, it reproduces the traditional gender roles by approving essentially feminine characteristics which need to be celebrated instead of criticized.

Given the varying water demand for various hours of the day from different seasons, the pressure of the water distribution network (WDN) will vary at different times. In the event of a decrease in demand, the network pressure increases, and the excess pressure leads to increase the leakage from old connections and small fractures. One of the ways to reduce leakage is the network pressure management and reduce excess pressure, which it can be achieved by the pressure reducing valves.‏ But the question is, how many pressure reducing valves and at which points of the water network should be installed. In the first part of this study, the optimal location of the pressure reducing valves (PRV's) was found by the combination of the binary genetic optimization algorithm (GA) and real differential evolution (DE) optimization algorithm. For this purpose, the GA proposes the potential locations (pipes) for the valve installation to the DE algorithm, and it attempts to eliminate surplus head in the WDN by making changes in the Hazen-William coefficient of proposed pipes and creating a head loss on the pipes. These changes should be in such a way that the WDN's constraints like the minimum allowable pressure to be respected. The related hybrid algorithm was coded in MATLAB software and connected to the Epanet software as a hydraulic solver. After determining the hydraulic model of the water network and the number of PRVs by the designer, the proposed code determines the optimal installation location of the PRVs in order to the reduction of network background leakage. In the next part of the study, after determining the optimal location of the PRVs, the optimal set-point of each PRVs has been determined. To this end, a single objective differential evolution algorithm is used. The design variable of the optimization algorithm is the outlet pressure of the installed PRVs and the permissible pressure ratio on both sides of PRVs considered as a new network constraint alongside the minimum allowable pressure. The objective function of this optimization problem is minimizing of WDN's background leakage. After validating of presented codes, they applied on a local WDN in the north of IRAN, Guilan, entitled Mehr Water Network. The covered area of this network is 144 acres and its daily average demand is 366 m3 per hour. The altitude difference of Mehr WDS is about 4 meters and it has 371 pipes with the length of 33 kilometers, 366 junctions, one reservoir and a pump station with 3 pumps. Results show that installing two pressure reducing valves in determined locations and control them with DE optimization algorithm can reduce the surplus head and background water leakage from 21.9% to 12.3% (about 41.3%) On a full day. It is noteworthy that this method can be used in Supervisory control and data acquisition (SCADA) in order to pressure management of WDNs and leakage reduction. A calibrated hydraulic model of WDN, current state of valves and pumps and demand multiplier (obtained from installed flow meters or estimated demand profile) are required as the input of the optimization code to determine the optimum output pressure (set-point) of PRVs in SCADA telecontrol system.

In this study, a new method for the fault detection of the locomotive engine injector nozzle based on vibration analysis and statistical tests, inside artificial neural networks, is presented. For this point, first the under study received vibration signals in the frequency domain is divided into several smaller ranges and the RMS of each range is then extracted as a frequency property and given as an input to the neural network. Because the high selection of the features reduces the accuracy of the neural network, the extracted feature vector with different levels of significance passes through the T-test filters, firstly, and then enters the neural network as an input. Using of this method, the accuracy of the neural network increases from 78.4 to 94.6%, and also help to detect the frequency ranges. According to the results, the fault of the injector nozzle crack increases the intensity of vibrations in the upper band frequencies of 1500 Hz.

In recent decades, due to the high cost of running a water supply network, designers have been trying to design networks with the least cost and maximum reliability. Networks that are able to provide good services in the face of demand changes or failure of the pipeline. Several indexes for reliability measurements were introduced and used as one of the objective functions along with cost in water distribution systems design problem. One of the issues that has been highlighted in recent years is which of these indicators are more successful in measuring the reliability of a water supply network. In this study, six famous reliability indicator entitled Minimum surplus head (MSH), total surplus head (TSH), resilience index (RI), network resilience index (NRI) and modified resilience index (MRI), entropy reliability indicator (ERI) and a new presented reliability indicator entitled Ratio of surplus head (MSH) described and used as one of the objective functions of a water distribution system design optimization problem. For this purpose, a multi-objective differential evolution algorithm has been developed in Matlab software and linked to the Epanet as the hydraulic solver. The generated algorithm applied on two different sample networks with different nature (gravitational feeding and feeding with pumping stations). To analysis of real hydraulic and mechanical reliability of obtained networks in optimization processes, a large number of abnormal operating conditions such as water demand uncertainty or pipes burst scenarios have been generated and applied on obtained Pareto Fronts of each optimization process. Then, the percentage of scenarios that each network could not satisfy the design’s constraints or failed in response to them has been calculated. The over demand’s scenarios were sampled using the general normal distribution method. The percentage of scenarios that each answer (water network in Pareto Front) cannot satisfy the design constraint has been measured and called Hydraulic Failure Percentage (HFP). Also, for modeling the abnormal mechanical conditions, lot of scenarios were produced with broken pipes. In each of these scenarios, there is a possibility of one to ten different pipes break. The locations of burst pipes are selected randomly. The percentage of scenarios that each case cannot satisfy the design constraint has been measured and called Mechanical Failure Percentage (MFP). These scenarios would remain constant for all of members of Pareto Fronts. The lower value of HFP and MFP demonstrate the greater ability of the network to deal with changes in nodal demand and the pipe bursts respectively. For deeper analysis, the conditions of failing (Not satisfying the constraints) divides into three sub-state as flowing: State A: Pressure of all nodes is more than the minimum acceptable pressure in all time. State B: Pressure of all nodes is more than 95% of the minimum acceptable pressure in all time. State C: Pressure of 95% of nodes is more than the minimum acceptable pressure in all time. The results of calculations summarized and have been shown in the diagrams. Results show that MSH and RI are the best indicators for optimal design of water supply networks without pumping station and include it.

Vibration analysis is one of the most practical methods for monitoring and troubleshooting rotating equipment. In this research, vibration analysis and support vector machine algorithms were used for monitoring and troubleshooting Alstom locomotive blowers. First, vibration data were collected from the blowers and the received signals were categorized into four groups: healthy blowers and blowers with problems of unbalance, loose shaft (base), and warped blades. Sixteen frequency and time features were then extracted from the received signals. Because in rotating systems, the ratio of the intensity of vibrations in the harmonics of the rotation of the machine can help diagnose the faults, the ratios of all features were calculated and defined as new features. The accuracy of the network can be sometimes lowered by the multitude of features, thus, a t-test filter was inserted into the support vector machine algorithm to select the features. The results show that the t-test filter increased the accuracy of the support vector machine algorithm. Finally, the feature selection of this network was compared with the feature selection by the genetic algorithm. The results show that the network designed in this research has a better performance in feature selection than the genetic algorithm.

Exchange rate is one of the most important variables in financial systems and identifying its determinants can significantly improve the performance of such systems. This paper proposes a hybrid exchange rate monetary model for the Iranian economy that has more explanatory variables than the classical monetary exchange rate models and uses the annual data of the period 1398-1398 and Johansen's approach. According to the results of long-term co-integration test, it can be inferred that the variables of real GDP difference and nominal interest rate difference have a negative impact and the variables of inflation rate difference, liquidity difference, crude oil real price, government expenditure share of GDP and the productivity difference of the tradable sector has a positive effect on the exchange rate. The positive effect of the difference in the productivity of the tradable sector on the exchange rate denies the existence of the Balassa-Samuelson effect in Iran. According to the impulse response function, the exchange rate itself has the greatest effect on the exchange rate by creating an impulse equal to a standard deviation on the variables affecting the exchange rate. The results of the variance decomposition also indicate that the most explanation of exchange rate fluctuations during 10 years is the exchange rate variable itself.

In this paper, stability of a group of networked cascade control systems based on a new continuous-time model is investigated and H∞ state feedback controllers considering H∞ norm bounded constraint are designed in order to attenuate external disturbances. The main objective of this research is to simplify stability analysis and provide the possibility of considering different configurations based on a continuous-time state-space model for these systems.To this aim, here it is assumed that data transformation between the secondary controller and the actuator is performed through a communication network. Using communication networks would result in some imperfections such as communication delay and data packet loss which are considered in the modelling of the system. Then, the state-space equations of the systems are converted to an equivalent augmented state-space equation. Stability of the system is analyzed based on the Lyapunov-Krasovskii theorem and using free weighting matrix method and controller gains as well as maximum allowable delay bound are computed. Simulation results confirm the validity of the proposed method.

Integrated modeling of multi-domain physical systems requires a common language. One of the methods which has been used to do so, is called bond graph. The bond graph provides a common and core language for describing basic elements and connections across different fields by using its elements, bonds and junctions. Also, by using genetic programming as an evolutionary method, an initial model can be evolved into a final model. The initial model of a system in bond graph called “Embryo” and must have input, output and basic elements of the desired model. By defining a series of operational functions in genetic programming, an embryo model evolves and a final model obtained in one objective and multi-objective approaches. The current research presents an optimized design tool by integration of bond graph and a Pareto multi-objective genetic programming for guiding automated topology synthesis. In order to evaluate the performance of the proposed method, obtained results were first compared to the 20-sim software and then two models of electric filter and a mass, spring and damper system compared to the reference.