mahdi yaghoobi

The current research focuses on the fuzzy system with the aim of introducing a novel approach to modeling Persian vernacular architecture. The main objective of utilizing the Delphi method is to attain the most reliable consensus among a group of expert opinions. This advantage aids in addressing the primary research question: determining the ecacy of the fuzzy Delphi technique in intelligently modeling Persian vernacular architecture. To identify the main factors of the research model, systematic literature reviews were conducted alongside semi-structured interviews with experts. Subsequently, Qualitative Content Analysis (QCA) was employed to extract various themes, which served as the primary factors of the research model. Finally, by applying the fuzzy Delphi technique, the present study examined the degree of certainty and accuracy of these factors in two stages, ultimately identifying 28 factors relevant to the modeling of Persian vernacular architecture.
 

In the IoT-based IoT environment, users can monitor tasks in the network environment and participate in the data collection process by smart devices. Users monitor their environment data in the form of fog computing during this process, also called mobile mass monitoring, and service providers are required to pay user rewards. But rewards should not be such as to increase platform costs. At the same time, maximizing the maximization rate is one of the main goals of service providers. Increasing network coverage rates and reducing platform costs can be considered as an optimization problem. But providing an algorithm that is less involved in local optimizations and can always provide good results is a challenge in itself. This article is tried to present an efficient approach based on the improved forest optimization algorithm using chaos theory and fuzzy parameter adjustment to reduce platform costs and maximize mobile mass monitoring coverage rate. The proposed method is implemented in MATLAB software and the analysis of the findings shows that the proposed method can optimize the network coverage rate by 31% (average) and the monitoring cost by 11% (average) compared to the CMST plan.

By focusing on the fuzzy Delphi technique (FDM), the current research introduces a novel approach to modeling Persian vernacular architecture. Fuzzy Delphi is a more advanced version of the Delphi Method, which utilizes triangulation statistics to determine the distance between the levels of consensus within the expert panel and deals with the measurement uncertainty of qualitative data. In this sense, the main objective of the Delphi method is to acquire the most reliable consensus of a group of expert opinions; an advantage that helps the current study to answer the main question of the research, that is, determining the efficacy of fuzzy Delphi technique in intelligent modeling of Persian vernacular architecture. Therefore, in order to identify the main factors of the research model, systematic literature reviews as well as semi-structured interviews with experts were conducted. Then, with the usage of Qualitative Content Analysis (QCA), various themes were obtained and employed as the main factors of the research model. Finally, by utilizing the fuzzy Delphi technique, the present study examined the degree of certainty and accuracy of the factors in two stages and identified 28 factors in the modeling of Persian vernacular architecture.

New spiritual movements express the movement from abstract spirituality towards subjects that have gradually found a metaphysical form. Art, with the help of the media, is representative and influenced by the world thought, which presents the meanings and possible ways of looking at morality and spirituality. Cinema, as a media consisting of various scientific and artistic paradigms, and as a source with special capabilities in producing effective content and representing complex concepts, has displayed human concerns regarding the world, God, and human relationships on its screen. This research tries to represent the supernatural signs of trans-modernism paradigm in the movie "Thor" by Kenneth Branagh. In order to identify and formulate the supernatural concepts and presuppositions of the trans-modern paradigm, the descriptive-analytical method has been used. The discourse analysis of the story elements, based on Fairclough's critical discourse analysis theory with the PDAM approach, has been carried out on three levels: description, interpretation and explanation. The method of conducting this research is descriptive-analytical, and by analyzing selected parts of the film, the writer came to the conclusion that discourse styles such as the savior and the future, direct the attention of the audience to the decoding of metaphysical topics, and this component is considered to be the basis of future developments. slow The findings of the research indicate the emergence of a new future for mankind in the third millennium with the approach of the modern trans paradigm and its impact on Hollywood cinema.

Natural products currently often consider starting points in drug discovery, followed by synthetic reforms to increase bioavailability and alleviate side effects. Approximately, fifty percent of the approved drugs by the U.S. Food and Drug Administration (FDA) are inspired by natural products. Glycyrrhizin is a well-known anti-inflammatory component that has been shown to prolong the coagulation time of thrombin and fibrinogen and to increase the duration of plasma recalcification. Suberosin, also known as 7-methoxy-6-prenylcoumarin, belongs to the class of coumarin compounds. The purpose of this article is to purify, identify, and standardize glycyrrhizin and suberosin, from Glycyrrhiza glabra L. and Ferulago trifida L. First, two plants were pulverized and then extracted using a percolator. The extracts were then divided into different fractions by column chromatography and mixed with thin-layer chromatography. Finally, we obtained pure compounds after using column chromatography and thin-layer chromatography. 1H-NMR and 13C-NMR have been used to purify compounds and also the HPLC method was used to standardize these compounds. Glycyrrhizin and Suberosin were extracted from Glycyrrhiza glabra L. and Ferulago trifida L respectively and 1H-NMR 13C-NMR techniques approved the structure of these two compounds, also, standardization of these compounds was correctly done by HPLC.

Since it might delay making significant expenditures in substations and generation, increasing the efficiency of power systems is an important priority. By altering the status of switches, the distribution feeder reconfiguration (DFR) can reduce system losses in this regard. Power loss and voltage deviation of buses are frequently taken into account as objective functions while solving the distribution feeder reconfiguration problem, however reliability indices have received less consideration. The proposed reliability index, coupled with power loss and switching number in the presence of distributed generators, are used in this study to address DFR as a multi-objective problem. The DFR problem is complex inherently, considering impacts of distributed generators makes the problem more be complex than before. For this purpose, an evolutionary method based on the combination of particle swarm optimization and modified shuffled frog leaping has been used to solve the nonlinear optimization problem in this study. Two 33-bus and 70-bus systems are evaluated to gauge the effectiveness of the suggested hybrid algorithm.

Distribution network reconfiguration is one of the well-known and effective strategies in the distribution networks which performs by the status management of the network switches in order to obtain a new optimal configuration for the feeders. This study formulates multi-objective distribution feeder reconfiguration in the presence of distributed generators and capacitors. Common objective functions in the Distribution network reconfiguration problem include power losses and voltage deviations, which are important goals in traditional distribution systems. Usually, less attention has been paid to the reliability and voltage security target functions. Therefore, the main objectives of this study are to improve the reliability and maintenance of voltage by solving the problem of Distribution network reconfiguration. The inherent complexities of the distribution network rearrangement problem have made it a serious challenge to provide a practical and robust solution to overcome the complexities of this problem, therefore, the improved gravitational search optimization algorithm to solve this problem Has been. In order to show the efficiency of the proposed method, it has been tested on a 33-bus test system.and the results are compared with theresults of using other evolutionary algorithms, such as particleswarm optimization and shuffled frog leaping

In most Internet of Things (IoT) applications, network nodes are limited in terms of energy source. Therefore, the need for innovative methods to eliminate energy loss which shortens the life of networks is fully felt in such networks. One of the optimization techniques of energy consumption on the Internet of things is efficient energy routing that the required energy can be reduced by choosing an optimal path. In this paper, an informed or efficient energy approach is proposed for routing on the Internet of Things in which focus is on the sleep-wake schedule of nodes; therefore, a new optimization algorithm called chaos fuzzy grasshopper optimization algorithm was used. In chaos fuzzy grasshopper algorithm, the initial population of grasshoppers is generated by Lorenz chaos theory and the input and output parameters of the algorithm are adjusted by fuzzy approach. To evaluate the efficiency of the proposed method, three criteria of evaluation of remaining energy, network life and coverage rate were used. Investigating the findings in two different scenarios (efficiency over time and efficiency per number of different nodes) showed that the proposed method always is better than the base methods in all scenarios and for all performance evaluation criteria. So that in the study of the death of 30% of nodes which indicates the life of the network, results showed that the proposed method of the paper (FLGOA) has 9% better efficiency than FGOA, 12% better than GOA and 16% better than GSO. Also, the findings about the remaining energy of the network showed that the proposed method has 16% better efficiency than FGOA method, 21% better than GOA and 22% better than GSO. Finally, studies in the coverage rate evaluation criterion showed that the proposed method has 12% coverage rate better than FGOA method, 15% better than GOA and 16% better than GSO.

Flavonoids, a group of natural substances, are found in flowers, fruits, roots and stems. These natural products are well known for their health-beneficial effects. Hence, isolation and purifying of flavonoids from the ingredients is worthwhile. Flavonoids are now considered indispensable in various nutraceutical, pharmaceutical, medicinal and cosmetic applications. Apigenin, quercetin, and apigenin-7-O-glycoside have therapeutic properties that these two are in the flavonoid group.

In this study, apigenin, quercetin, and apigenin 7-O-glycoside were purified by column chromatography and identified by NMR and HPLC UV-visible techniques.

Total extracts of three plants (Apium graveolens, Petroselinum crispum, Allium cepa) were divided into different solvent fractions. Column chromatography is used to purify these fractions. Finally, 1H-NMR, 13C-NMR, and mass spectrometry techniques were used for identification. Also, the HPLC technique was used for identifying these compounds and standardized.

In the present work, apigenin was extracted from ethyl acetate fraction of Apium graveolens seeds. High purity of apigenin 7-O-glycoside isolated from the butanol fraction of Petroselinum crispum aerial parts. Also, ethyl acetate fraction isolated quercetin from the Allium cepa. Identification of the data obtained from 1H-NMR and 13C-NMR, which were proofed by comparison with the sources of purified compounds.

The methods used in this research were able to produce these three compounds with a high percentage of purity to be used in industry as standards.

In this paper, an adaptive neural fuzzy control method is proposed to control hyper-chaotic dynamic systems. Due to the inherent complexity of hyper-chaotic systems, the neural fuzzy network training architecture is described, which includes the type and number of training inputs. The training data for the adaptive neural fuzzy network is based on nonlinear control. In other words, the data of a nonlinear controller, which includes error vectors and control input vectors, is used for neural fuzzy training. The numerical simulation results show that the proposed method is suitable for controlling hyper-chaotic systems. After the controller design, an external disturbance is added to the model to evaluate the performance of the ANFIS controller. The time to reach zero error and the behavior of the control signal are discussed, this can be an important issue in real-world implementation and manufacturing.

Silybum marianum (L.) Gaertn. (Milk thistle) is a perennial herb with medicinal properties. The seeds of these plants contain silymarin compounds with flavonolignan structure and antioxidant, anti-inflammatory and hepatoprotective effects. The major bioactive constituent of S. marianum is silybin A and B. It is used in the treatment of various liver conditions and exhibits high anti-tumor promoting activity.

The purpose of this study was to purify, identify, and standardize of silybin A and B from the seeds extract of Silybum marianum.

At first, the milk thistle seeds were defatted with hexane and then extracted with methanol as solvent. Isolation and further purification of silybin A and B was carried out by column chromatography using Diaion HP-20 resin, silica gel and Sephadex LH-20 as stationary phase, respectively. 1H-NMR and 13C-NMR techniques were used to identify these compounds. Finally, the HPLC method has been used to standardize.

1H-NMR and 13C-NMR techniques characterized the structure of silybin A and B extracted from Silybum marianum L. and standardization and determination of their purity was performed using HPLC.

Our proposed system presented significant advantages in increasing efficiency and reducing cost, and the diastereoisomers of silybin A and silybin B in silymarin were successfully isolated with high purities.

The green synthesis of nanoparticles using plants presents important advantages over other biological systems. Natural compounds present in plant extracts can reduce metal ions to nanoparticles in a single-step green synthesis process. Seeds of fenugreek with various compounds and antioxidant activity are suitable for green synthesis.

In this study, the performance of fenugreek seeds extract was evaluated for iron nanoparticles production.

The fenugreek (Trigonella foenum-graecum L.) seeds were extracted with a distilled water solution at environmental temperature and this aqueous extract was used for the iron nanoparticles synthesis. Response surface methodology was applied to optimize nanoparticle production by considering three independent variables: the extract to metal ion ratio (1.5-6.5), incubation time (30-90 min), and temperature (35-65 °C).

Mixing the fenugreek seeds extract and iron salt solution with a volume ratio of 1.5 at 36.5 °C for 90 min led to the optimization of iron nanoparticle production with the narrowest size distribution. At the optimized condition, the nanoparticle size was in the range of 20-40 nm.

Iron nanoparticles were successfully synthesized with fenugreek seed extract. Physical parameters such as time, temperature, and mixing volume ratio of the extract to metal ions can control the average size of the synthesized green iron nanoparticles.

Photovoltaic (PV) systems are widely used due to low maintenance costs and being non-pollutant. Selecting proper parameters for the inverter is essential for its stable performance. The inverter connected to the grid should be able to transfer maximum PV energy to the power grid. To have the complete transmission, the output current of the inverter should be synchronous with the voltage of the power network in terms of phase and frequency. The inverter affects the quality of the power generated by the PV and chaotic behavior can affect the performance of the PV system, negatively. Due to chaotic behavior, by determining the correlation coefficient, PV voltage and circuit parameters, phase and frequency can be synchronized. Therefore, in this paper, determining parameters of the inverter connected to the single-phase full-bridge PV system for phase and frequency synchronization is studied. To increase the accuracy of estimating system parameters and reduce synchronization error, the adaptive chaotic grey wolf Algorithm is used. Simulations are compared with PSO and GWO indicating the superiority of the proposed method in terms of phase and frequency synchronization.

In organizations and large companies that are using business process management systems (BPMSs), process model can change due to upstream laws, market conditions. BPMSs have flexible to these changes. Effect of these change are saved in storage devises and event logs; these changes are sometimes applied suddenly or gradually on the event logs. Changing the season or starting a new financial term can be a factor to make these changes. This change is called concept drift in business process model. On time detection and recognition of process concept drift can affect the decision making of managers and administrations of systems. An analysis of the event logs in BPMS allows the automatic detection of the concept drift. This paper presents an innovative method by introducing a modified distance function to identify the concept drift. Experimental results were performed on 72 datasets in the research history, which included 648 concept drifts in 12 different types. It shows that the proposed method detects 98.18% of the drifts, while the proposed method is much faster than other state of the art methods.

Lack of water resources is one of the most problems ofincreasing urban green spaces. Over the last threedecades, turfgrass and lawn researches have put significant effort into developing and evaluating turf species that have good drought resistance. As water conservation becomes an important issue, considerable interest is increasing in identifying grasses that require less water. Plants with good drought resistance are those that are able to survive stress by means of drought avoidance, drought tolerance at leaf water potentials, or both. The efficient use of water is made possible by understanding the effects of irrigation water on crop development and yield. Drought affects the visual quality, growth rate and evapotranspiration. Researchers reported that turfgrass subjected to drought conditions for short periods could sustain a fairly good appearance by irrigation about half of its consumptive use whenever soil moisture level falls to near permanent wilting point. Drought stress caused decrease in RWC and visual quality of many grass cultivars. In drought conditions resistance grass showed increase in proline content on their leaves. Therefore the use of native grasses with high-strength instead of grass imported with low-resistance is one way to increase green space and reduce costs. The purpose of this study was comparednative grasses with commercial grass cultivars.
This study was to evaluate the yield and resistance of native grasses to drought stress in 2014. This experiment was conducted in Khorasan Agricultural Research Center. NativeAgropyron grass species includedAgropyronelangatum, A. desertrum, A. cristatum and commercial cultivarwassuper sport and third level of stress, including severe stress (45% FC), moderate stress (65% FC) and control (85% field capacity) were experimental treatments. Plants were cultured in PVC containers measuring 9 cm in diameter and 60 cm deep under greenhouse condition. Soil was mixture of 70% loam soil, 20% pit mass and 10% sand. Greenhouse air temperature was maintained between 22 and 28 centigrade degree. All plants were maintained under well watered conditions for 45 days before drought stress. This experiment was designed in factorial experiment based on completely random with fourreplicates. After the stress treatment parameters such as length and width of leaves, chlorophyll a, chlorophyll b and total chlorophyll content, visual quality, electrolyte leakage, RWC and proline content of leaves were measured. Length and width of leaves were measured with ruler. Proline content, RWC percent, chlorophyll a, chlorophyll b and total chlorophyll content of leaf, visual quality and leaf electrolyte leakage weremeasured with standard protocols. Analysis of the data by statistical software JMP 8 and graphs with Excel 2010 was drawn.
Result of the experiment showed that those native species have different response to soil moisture stress conditions. The highest and lowest lengths of leaf were observed under45% field capacity in A. elangatum and super sport grass, respectively. The results showed that width of leaves of A. elangatum increase and then decrease in super sport. Under drought stress conditions A. desertrum has best visual quality with 6.07 score. Highest chlorophyll a and total chlorophyll were observed in A. elangatum. The lowest electrolyte leakage under drought stress was obtained from A. elangatum with 17.91 percent. RWC content in the native A. elangatum increased to 82.12 compared with super sport (control). A. elangatum under drought stress showed highest proline content and commercial cultivar (super sport) indicated lowest proline content at 45% field capacity irrigation. Selahvarzi and et al. (2009) found that visual quality of tall fescue decrease in drought stress. In drought stress, RWC percent decrease in grass species. Proline content was increasedupondrought stress inLoliumperenecool season grass. Many studies on native cultivar indicated that native turfgrass cultivar have more resistance to drought stress compared with exotic turfgrass cultivars.
According to the results, we said native grass species under drought stress conditions have better quality compared with imported grass cultivar such as Super sport. Visual quality in native grass was suitable for use in urban landscape, that visual quality show little change in drought stress and leaves were fresh in this conditions. The best visual quality of two native species A. elongatum and A. desertrum was observed under 65% field capacity. Nativegrass cultivars were more resistance than imported grass cultivars. This study showed that native grass such asA. elongatum and A. desertrumhas low cost to use and these turfgrass need to lower water irrigation than commercial grass Super sport. Then two species can be introduced as low-input cultivars.

How to reconfigure a logic gate is an attractive subject for different applications.Chaotic systems can yield a wide variety of patterns. Here, we use this feature for produce a logic gate.This feature forms the basis for designing a dynamical computing device that can be rapidly reconfigure to become any desired logic operator.This logic gate that can reconfigure to any logic operator when placed in its chaotic state, called chaotic logic gate.The reconfiguration realize by set the parameter values of chaotic logic gate.In this paper we present mechanisms about how to produce a logic gate based on the logistic map.Furthermore,we propose a reconfigurable structure based on a chaotic system and genetic algorithm is used to set the parameter values.

We here proposed the indirect model reference fuzzy control scheme to control the chaotic attitude of a satellite. This paper adopted Lorenz-type attitude motion. This non- linear chaotic system is modeled as a Takagi–Sugeno (TS) fuzzy system. It was shown that using stable adaption law and model reference method, it is possible to control of chaotic behavior of satellite. Our simulation results have demonstrate that the proposed method can satisfy the control object and enhanced stability as well as ease of tuning.

Early detection of heart diseases/abnormalities can prolong life and enhance the quality of living through appropriate treatment. Whereas clustering of electrocardiogram (ECG) signals will help to identification of heart diseases as soon as possible. In this regard, neural network and fuzzy logic have been used in many application areas while each of them has advantages and disadvantages. Thus, the present paper utilizes the proposed fuzzy neural network (FNN) with initial weights generated by genetic algorithm (GFNN) for the sake of improvement training speed, accurate and to reduce the chance of the FNN getting stuck on a local minimum.Four types of ECG beats (normal beat, congestive heart failure beat, ventricular tachyarrhythmia beat and atrial fibrillation beat) obtained from the PhysioBank database was clustered by the proposed GFNN model. Model evaluation results indicate that the proposed model can perform more accurately and less training speed than the conventional statistical methods, a single ANN and FNN. The total clustering accuracy of the GFNN model is 98.23%.

Nowadays, uncertainty in management projects managers has faced numerous challenges. Old and unscientific methods do not meet their needs. Therefore different managers have benefited from the fuzzy set theory to state uncertainty. In this paper, the first stage of the risk management process is used to determine the risk of the general risks affecting the project and including conversion projects Credit and financial institutions to the banks are identified and prioritized. At this stage for identifying the risks affecting in the project process the fuzzy Delphi method was used. This method is a structured process for collecting and classifying the knowledge among a group of expert in the form of natural language which is distributed through questionnaires among individuals and controlled feedback and comments received will be done.The results showed that after the implementation the three stages of survey and achievement of consensuses among experts in training and test data, finally, it was found that the integration of financial and credit risk relative to other risks can be better estimated. Also, the results with consideration of three hypotheses for the project show that if attract resources risks, profits, interest, credit and equity occurs profits will be change, if risks occur within the organization and technology will bring cost to the project and if risk of rules and regulations, events (political) institutions integration, open activities (non-professional), likely to occur on the property and the classic elite, the project will be loss.