حسن نادری

The need for a software or a system in general that can store important information (which a person feels may be needed in the future) on a daily basis and provide this information to the person at the necessary time, It seems necessary and essential. In this article, an attempt is made to help humans by providing a system so that by fully storing information over time, whenever they need information (which they are unable to recall due to mental preoccupations), they can recall a part of it,Get all the information you need in full. In the proposed system, information is initially stored in a knowledge graph, this knowledge graph has connections between nodes, which return the best and most complete answer to the user due to the existence of these connections and using key search methods to be. On a daily basis, the user stores his important information, which he hears or reads and thinks he may need in the future, in this system, and when necessary, just by reminding him. A part of the information gets access to the whole information. On a daily basis, the user stores his important information, which he hears or reads and thinks he may need in the future, in this system, and when necessary, just by reminding him. A part of the information gets access to the whole information.

Today, one of the most popular and challenging tasks in natural language processing is answering complex user questions. Question-answering systems, as a new generation of search engines, receive user questions in natural language without semantic limitations and provide precise answers. In recent years, most research in the field of question-answering systems has been focused on the English language, and not much effort has been made in languages with limited resources, such as Persian. This limitation prevents these systems from efficiently handling questions in languages like Persian.In this regard, this article aims to enhance the efficiency of question-answering systems in the Persian language by creating a dataset for answering complex multi-turn questions. Multi-hop questions, require at least two steps of reasoning to reach an answer. This dataset, called PersianMHQA, is the first open-domain question-answering dataset in Persian and includes 7,000 multi-hop questions. It was generated using the Persian Wikipedia as a knowledge source. To evaluate and benchmark this dataset, it has been fine-tuned on the latest pre-trained language models that support the Persian language.The best results obtained based on F1 score and exact match on this dataset are 75.92% and 71.73%, respectively. These results indicate that this dataset is a powerful starting point for improving multi-hop complex question-answering for Persian language systems.In this regard, this article aims to enhance the efficiency of question-answering systems in the Persian language by creating a dataset for answering complex multi-turn questions. Multi-hop questions, require at least two steps of reasoning to reach an answer. This dataset, called PersianMHQA, is the first open-domain question-answering dataset in Persian and includes 7,000 multi-hop questions. It was generated using the Persian Wikipedia as a knowledge source. To evaluate and benchmark this dataset, it has been fine-tuned on the latest pre-trained language models that support the Persian language.The best results obtained based on F1 score and exact match on this dataset are 75.92% and 71.73%, respectively. These results indicate that this dataset is a powerful starting point for improving multi-hop complex question-answering for Persian language systems.

Question-answering systems, as the next generation of search engines, have the capability to retrieve relevant answers to queries posed in natural language. These systems generally consist of three main components: question processing, information retrieval, and answer extraction, with various methods introduced for each component. One of the most important aspects is information retrieval and selecting relevant paragraphs. Nowadays, most user queries in question-answering systems are complex. To respond to such queries, it initially requires understanding the question and then retrieving various documents that are lexically and semantically related to the query. In recent years, advancements in deep neural network-based learning on one hand and the introduction of high-quality datasets on a large scale on the other have attracted researchers' attention to this field. In this research, a method for selecting relevant paragraphs for complex question-answering systems on the HotpotQA dataset is introduced. To select relevant paragraphs, the type of question is first recognized using a deep neural network. Then, using BERT language models, relevant paragraphs that show evidence of the answer are selected in several steps. This process uses keyword extraction from the question. The results obtained indicate that the outcomes are better compared to the baseline method

Question Answering Systems (QAS) are one of the most important intelligent systems that have the ability to provide instant and explicit answers to input questions. One of the new challenges of these systems is the ability to answer multi-hop complex questions that require information collection from multiple documents. In this paper, a method is proposed to solve the challenge of answering multi-hop complex questions. In this method, first, documents related to the question are retrieved in a two-step process. Then, to facilitate answering the question, knowledge is extracted from the retrieved documents and represented in the form of a graph. Finally, to find the answer to the question, reasoning is performed on the graph using a combination of heterogeneous graph neural network and transformer. To evaluate the effectiveness of the proposed method, this method and other related works have been tested on the HotpotQA open-domain dataset. The results obtained in answering questions based on F1 score and exact match are reported as 86.51 and 78.71 respectively, indicating superiority of this method over similar works.

This study investigates and evaluates the effects of heating type using microwaves and conventional heating on the yield and quality of oil-shale produced from the Qalikuh reservoir with total organic carbon TOC between 3.83 and 26.4% by the weight and average  16.5% by weight. With microwaves heating, Maximum oil produced is %5.9 by weight and  Based on the analysis of SARA shale oil compounds, asphaltene compounds decrease (24% by weight), saturated compounds increase (on average 40% by weight), and resinous and aromatic compounds also have fluctuating behavior. In conventional heating, Maximum oil Produced is 4.5% by weight, and  the amounts of saturated compounds (about 23% by weight) and asphaltic compounds (on average 14% by weight) in shale oil decrease, but resinous compounds (about 28% by weight) decrease and compounds Aromatic values also fluctuate. The highest desulfurization in shale oil produced using microwaves was observed, The amount of nitrogen in the shale oil also decreases with the heating by microwaves finally reaches to 8% by weight. In shale oil produced by normal heating, finally sulfur decreases by 31%, nitrogen increases by 21%, and oxygen increases by 60%.

The need for a software or a system in general that can store important information (which a person feels may be needed in the future) on a daily basis and provide this information to the person at the necessary time, It seems necessary and essential. In this article, an attempt is made to help humans by providing a system so that by fully storing information over time, whenever they need information (which they are unable to recall due to mental preoccupations), they can recall a part of it,Get all the information you need in full. In the proposed system, information is initially stored in a knowledge graph, this knowledge graph has connections between nodes, which return the best and most complete answer to the user due to the existence of these connections and using key search methods to be. On a daily basis, the user stores his important information, which he hears or reads and thinks he may need in the future, in this system, and when necessary, just by reminding him. A part of the information gets access to the whole information. On a daily basis, the user stores his important information, which he hears or reads and thinks he may need in the future, in this system, and when necessary, just by reminding him. A part of the information gets access to the whole information.

Researchers have always been interested in graph nodes clustering based on content or structure. But less attention has been paid to clustering based on both structure and content. But a content-structural clustering is needed in information networks like social networks. In this paper, the ICS-Cluster algorithm is proposed which takes into consideration both the structure and content aspects of the nodes. The purpose of this approach is to gain a coherent internal structure (structural aspect) and homogeneous attribute values (content aspect) in the graph. In this approach firstly the graph is converted into a content-structural graph which edges’ weight show similarity between the connected nodes. Incremental clustering is done based on edges’ weight in this process the edges with the most weight is considered as clusters then the weight of connected edge to the cluster is aggregated and they’ll be one edge, the process is repeated until the algorithm reaches the number of clusters that indicated by the user. ICS-Cluster algorithm number of cluster is indicated by the user. Comparing ICS-Cluster with other content structural algorithm based on six criteria for measuring cluster quality shows that ICS-Cluster has good performance. These criteria contain structural criteria (Modularity, Error Link, and Density), content criterion (Average Similarity), content-structural criterion (CS-Measure) and the run time.

Entities in social networks, in addition to having the relationship with each other, also have content. This type of networks can be modeled by the enriched graph, in which nodes could have text too. Graph clustering is one of the important attempts toward analyzing social networks. Despite these two facts, most of the existing graph clustering methods independently focused on one of the content or structural aspects. Content-Structural graph clustering algorithms simultaneously consider both the structure and the content of the graph. The main aim of this paper is to achieve well connected (structured) clusters while their nodes benefit from homogeneous attribute values (content). The proposed algorithm in this paper so-called RSL-Cluster performs the clustering by hierarchically removing the edge between nodes which has a weight lower that the average similarity of nodes. This stage continues until reaching the user’s desired number of clusters. Comparing the proposed algorithm with three well-known content-structural clustering algorithms represents the proper functioning of the proposed method. The used measures to evaluate our method include structural, content and the content-structural measures.

By increasing the speed of data generation, need to process, store and analyze of Big Data becomes increasing. Related work has been done to create real-time data warehouse, but according to current unstructured data in Big Data, data warehouse with the old structure, it doesn't answer new management requirements of this type of Data. Recently, Data Lake has been proposed for unstructured data (with BASE properties). However, existence of important structured data (with ACID properties) and less sensitive unstructured big data on the other hand, causing new problems in the management of Big Data by using of this methods. In this paper we will offer a solution which is able to store structured data and unstructured data simultaneously and it can response to user’s queries in real-time. As one of the important results of this research, after comparing the data warehouse and Data Lake concluded that the lake is not a replacement for a data warehouse, and data warehouse has particular use, especially in financial data; because the data warehouse compliance ACID theory, and Data Lake cater requirements of BASE theory.  The raised idea in this paper has three main advantage: 1- Simultaneous use of data warehouse and Data Lake to meet the needs of the organization data with the benefits of them. 2- Separating new data from old data to achieve real-time. 3- Development parallelism, thus synchronization loading data and query processing to reduce the cost of time.

This paper presents the feasibility of the removal of asphaltenes from aqueous solutions by using low- cost natural adsorbents such as light expanded clay aggregate (LECA), perlite and bentonite. The structure of adsorbents was characterized by XRD, FTIR, and SEM before and after the adsorption of asphaltenes. The effect of the adsorbent type, initial asphaltene concentration, particle size of the adsorbent and temperature on the adsorption capacity was investigated. The results showed that at the initial asphaltene concentration of 125 mg L-1, contact time of 24 h, temperature of 50°C and adsorbent dosage of 1 g, the removal of asphaltenes onto LECA, perlite and bentonite was 53.59, 93.01 and 99.77%, respectively. Also Langmuir and Freundlich models were applied to describe the experimental data. The results indicated a good fit by Langmuir isotherm. Thermodynamic parameters such as ∆H, ∆S and ∆G were also calculated. It was revealed that the adsorption was spontaneous and of exothermic nature, which was evident by decreasing the randomness of the dye at the solid and liquid interfaces. The characteristic results and dimensionless separation factor (RL) showed that perlite and bentonite can be employed as an alternative to commercial adsorbents for the removal of asphaltenes from the aqueous solution and oil.

The Commanders are valuable resources of a team, group, brigade, division, and corps. They can provide valuable creative ideas, solve hard problems and so determine and manage the war strategy to win the battle. Their knowledge is valuable resources that should not go away with their deaths. In this paper, an expert system is presented that collect the knowledge of this man and build their knowledgebase that based on physical, intellectual, emotional and inner (The Sixth Sense) biorhythm cycle to predicting the level of fighter’s readiness to perform a military mission. In the knowledgebase, the importance of each cycle is modeled on various missions. With insert, the fighter’s information to the expert system, inferential mechanisms that are designed hierarchically, on the on hands prioritize them based on biorhythm and on the other hand, according to the mission requirements in the knowledgebase, prioritize the warriors. By doing so, the mission entrusted to warriors with respect to the preparation of them thus will lead to increased efficiency in the use of human capital.

During recent years, various types of gels are used to control excess water in oil wells. The exploiting of preformed particle gels (PPG) can be considered as a good candidate to shutoff water channels without blocking of oil bearing zones. In this research, the preformed particle gel has been synthesized from Sulfonated polyacrylamide copolymer and chromium acetate (III) as crosslinker. The analysis of low amplitude oscillatory shear method was used to study on gel strength, complex viscosity, ultimate storage, and viscous modulus. The complex viscosity and ultimate storage modulus of gel were determined about 5919 Pa.s and 35.4 kPa respectively. The core flooding test was used to study of PPG performance in porous media. Further, two different size particle gels (63-106 and 106-188 micron) were applied to investigate the particle size effect on injection pressure and residual resistance factor of water and oil. The disproportionate permeability reduction index of 3.196 and 4.038, and water residual resistance factor of 41.42 and 53.22 were determined for small and large particle gels respectively. The results showed that the gel particle size on the residual resistance factor of water was more effective than the oil residual resistance factor.

Today, with the spread of social networks, the opposition's efforts to chill out people from government (known as “soft war”) are increased. Therefore, dealing with this type of networks is important for military and security organizations. Graph clustering is one of the first attempts toward analyzing social networks which can appropriately be modeled by a content graph. In contrast, most of the existing graph clustering methods independently focused on one of the content or structural aspects of a graph. The aim of this paper (implemented as CS-Cluster algorithm) is to achieve well connected clusters while their nodes benefits from homogeneous attribute values (content). In the second step of our research, after an intensive search, no measure has found which could simultaneously consider content and structural features of clustering algorithms. So to be able to appropriately evaluate our algorithm, a new content-structural measure (so-called “CS-Measure”) is proposed. Our experimentation shows that the proposed clustering algorithm outperforms two other well-known content-structural clustering algorithms, using the new content-structural, average similarity, and Error link measure as well as the previous content and structural measures, And it also performed relatively well in density measure.

One of the most promising methods in order to mitigate asphaltene precipitation is to use asphaltene dispersants. In this study, the effect of two dispersants of toluene and dodecylbenzene sulfonic acid on asphaltene precipitation of a dead and a live oil sample has been investigated. Investigations on dead oil were conducted using IP143 standard test and for studying live oil in the presence of asphaltene dispersants high pressure microscopy was used. The obtained pictures from high pressure microscopy were analyzed using a picture analysis software. According to the results, this dispersants in dead oil create an optimum point for asphaltene precipitation. In live oil, this dispersants reduce asphaltene precipitation; moreover, for dodecylbenzene sulfonic acid, the reduction in asphaltene precipitation reaches down to 70 percent. Also, it was observed that in the effect of injection of these dispersants, the average size of asphaltene flocculation has reduced, which this reduction was much more for dodecylbenzene sulfonic acid in comparison with toluene.

Asphaltene precipitation from reservoir fluids during oil production is a serious problem resulting in plugging of the formation, wellbore and production facilities. Generally, asphaltene precipitation has only been investigated from thermodynamic approach in literature, and it assumed that precipitation is relatively fast and has no kinetik effects. Without a good understanding of the associated kinetic effects during the precipitation of asphaltenes, the thermodynamic models can provide misleading predictions for asphaltene stability. So, it should be analyzed from two points of view, thermodynamic and kinetics stability. In this study a molar rich gas and CO2 programmed titration technique was used to evaluate the kinetics of gas-induced asphaltene precipitation from Iranian reservoir oil under isothermal and isobaric initial reservoir conditions in a solids detection system (SDS) and with kinetics of polymerization assumption for reaction between asphaltene and gas, the kinetics parameters of reaction is determined. The results show that asphaltene precipitation occurs in 0.9 mol of rich gas and 0.3 mol of CO2 injected per one mol of reservoir oil. Also, the reaction order of CO2 & rich gas is 2.7 times more than reaction order of asphaltene. So in gas injection, the rate of asphaltene precipitation is highly dependant to the volume of gas.

A system of Polymer gel is widely used in oil production wells in order to reduce unwanted water production. The efficiency of these systems in porous media depended on various parameters such as the composition concentration and the media condition of the polymer gels performance. So it is necessary to study the effective parameters and their interactions in order to increase the efficiency of systems of polymer gels. Therefore، in this research، two-level factorial design as a statistical method was used to study the effective parameters on the gelation time of polymer gel containing sulfonated polyacrylamide copolymer and chromium triacetate as crosslinker to not only reduce the number of experiments in the lowest time and cost، but also present the most effective parameters among the eight studied parameters (pH، CaCl2 concentration، crosslinker/co-polymer ratio، NaCl concentration، co-polymer concentration، sodium lactate، nanoclay and thiouria) on gelation time of polymer gels using 32 bottle testing experiment and finally by modeling the process، the optimum condition is presented. The presented model in 99% significant to predict the gelation time of the polymer gel based on the effective parameters. The results showed that sodium lactate، co-polymer concentration، nanoclay، thiouria and crosslinker/co-polymer ratio are the main effects respectively. Also، among the interactions between parameters، the interaction of sodium lactate and crosslinker/co-polymer ratio has the most effect on the gelation time of the hydrogel.

A key parameter for the application of polymer gels in water shut off treatment is the adsorption of polymer gel onto the rock surface. So, the adsorption properties of a nanocomposite hydrogel were discussed in this research by crosslinking of sulfonated polyacrylamide/sodium montmorillonite aqueous solutions with chromium triacetate. The X-ray diffraction patterns indicated that exfoliated type of microstructure was formed. In addition, fourier transform infrared spectroscopy was used to prove the nanocomposite hydrogel interacted with the rock surface qualitatively and the scanning electron microscopy to determine the surface characteristics of the nanocomposite hydrogel layer adsorbed on powdered rock surface. The general behavior of the response indicated that in comparison with the pressure, the adsorption is much more sensitive to the S/L ratio change. The addition of nanoclay of Na-montmorillonite increased the adsorption of NC hydrogel on the surface of powdered sandstone. The influence of pressure and solid/liquid ratio was investigated on adsorption amount. The results showed that nanocomposite hydrogel adsorption decreased continuously by increase of solid/liquid ratio while its adsorption was almost independent of the pressure. Besides, the maximum amount of nanocomposite hydrogel adsorption was obtained in 2500 psi pressure and 0.005 ratio of solid/liquid.

Generally, gel polymers are an appropriate method for increasing the rate of production of the oil reservoirs. To analyses the effects of gels on the oil reservoirs we will not only need to perform several experiments for determining of gel properties, also require to examine gel motion through the porous media by making use of a simulator software. In this paper a two dimensional, two phase (oil & water) permeability modification modeling developed by including a gelation model into a fluid flow equations. The partial differential equation of motion if the flow & gelation model in porous media one first discretized and then transferred into the non linear-couple algebra equations. The equations will be solved numerically. The results of simulation show the permeability modification in porous media for 5 years. This model is an appropriate mathematical model for examination of both permeability reduction and water production rate effects in porous media; also the permeability modification due to the gel injection in a porous media will be analyzed by using the Civan's power low. Ultimately, the results obtained are compared with experimental data for one of the Iranian Asmari reservoir, which shows a desirable accuracy of the presented mathematical model.

In the fractured carbonate reservoirs the reimbibation process in the gas invaded zone is dominating on producing process. When the gravitational forces exceed the capillary forces, the matrix blocks, which are surrounded by gas, will release their oil. This oil imbibed by below block if possible up to produced. In this study, we used some experiment for finding the relations and effective parameters in reimbibatin process.