A Contextual Topic Modeling and Content Analysis of Iranian laws and Regulations

A constitution is the highest legal document of a country and serves as a guide for the establishment of other laws. The constitution defines the political principles, structure, hierarchy, position, and limits of the political power of a country's government. It determines and guarantees the rights of citizens. This study aimed at topic modeling of Iranian laws. As part of this research, 11760 laws were collected from the Dotic website. Then, topic modeling was conducted on the title and content of the regularizations using LDA. Data analysis with topic modeling led to the identification of 10 topics including Economic, Customs, Housing and Urban Development, Agriculture, Insurance, Legal and judicial, Cultural, Information Technology, Political, and Government. The largest topic, Economic, accounts for 29% of regulations, while the smallest are Political and Government, accounting for 2%. This research utilizes a topic modeling method in exploring law texts and identifying trends in regularizations from 2016-2023. In this study, it was found that regularizations constitute a significant percentage of law, most of which are related to economics and customs. Cultural regularizations have increased in 2023. It can be concluded any law enacted each year can reflect society's conditions and legislators' top concerns

IoT Deployment Data Models in the Wheat Supply Chain Storage Section: Using an Action Design Research Approach

The supply chain for perishable products, especially agricultural goods, has always been one of the most important and challenging management issues at different times. Because, at all stages of the agricultural production process, unsafe and unsanitary factors may endanger the health of agricultural products. In addition, one of the key problems of the agricultural supply chain is the high volume of products wasted throughout the whole supply chain. For example, in Iran, as a developing country, about 30 of all agricultural products are wasted annually. The high volume of agricultural waste is especially important concerning wheat products as a political and strategic product. The results of some studies show that a large amount of wheat waste in developing countries is due to the widespread use of traditional methods in the storage process. Therefore, the application of emerging technologies such as the Internet of Things (IoT) can be an effective solution to this kind of problem. However, there are shortcomings in the IoT deployment in the supply chain, especially in the logistics sector, and researchers need to cover theoretical gaps in this area through modeling and optimization. Therefore, the present study intends to emphasize this important research issue for the first time in Iran using the Action Design Research approach. The most important findings of this research include the conceptual data model, the logical model of the database, and the physical data model for the IoT deployment in the storage section of the wheat supply chain, which has been designed and validated with the participation of industry and software engineering experts. The models designed in this research can be useful for the implementation of IoT technology in wheat storage centers and food factories. The findings of this study can provide a good guideline for officials and decision-makers to deploying IoT in the field of wheat storage

Alignment Maturity Assessment(Case study: Ferdowsi University of Mashhad)

Measuring operational alignment maturity, or in other words, business processes- information systems alignment maturity, has been important as a way to evaluate the success of operational alignment implementation. However, studies on alignment have been mainly focused on measuring strategic alignment maturity. Therefore, given the differences between strategic alignment and operational alignment, the results of these studies have not been very effective in measuring operational alignment maturity. That is why the present study aimed to provide a framework for measuring operational alignment maturity. To that end, ten dimensions of operational alignment were determined and then, confirmed by confirmatory factor analysis. Next, neural networks was used to assess the importance of each of these dimensions. Then, based on the position of each of these dimensions in the importance-performance analysis matrix and after examining the gap between the current and desired status of each dimension using the pairwise mean comparison test, the level of operational alignment maturity for each dimension was determined. As the results indicated, alignment of non-core business processes with management information systems (D7) at optimized level, alignment of core business processes with management information system (D4) at improved and managed levels, as well as alignment of management processes with knowledge-based information systems (D2), alignment of core business processes with strategic information systems (D3) and alignment of non-core business processes with knowledge-based information systems (D8), all three at establised and focused levels, were identified. Moreover, the alignment of management processes with strategic information systems (D1), the alignment of core business processes with knowledge-based information systems (D5), the alignment of core business processes with operational information systems (D6), all three at commited level, as well as alignment of support processes with operational information systems (D9) and alignment of support processes with knowledge-based information systems (D10), both at initial and ad hoc levels, were determined

A New Approach for Hybrid ac-dc Circuit Fault Analysis

Classical fault analysis is a powerful tool for the ac power system fault analysis, which provides the short circuit currents for an effective protection system design. With the rise of dc circuits within the ac grid and the presence of dc loads and power sources, new fault analysis that includes the hybrid system has become an immediate need. Faults at the ac side of the circuit are affected by the dc loads and sources. Thus, a fast and accurate scheme that can analyze the effects of the dc circuit on the ac grid is required. The existing methods for fault analysis of the ac-dc hybrid grids are complex and require different modeling for the ac and dc circuits.This paper aims to extend the results of the classical ac fault analysis to the ac-dc hybrid grids. This will make available the well-developed ac fault analysis methods to the hybrid circuit with accuracy and simplicity. The proposed method finds a Thevenin equivalent of the dc laterals applied to the ac circuit; thus, avoids multiple analyses currently used in ac-dc circuits

A new approach for steady-state analysis of a hybrid ac-dc microgrid

The dc grid became more popular, by emerging the distributed generations (DGs). Despite this popularity, the dc grid is not yet widely used because the majority of loads in a power system are ac, which means the ac grid is still the dominant grid in the power system. Therefore, the concept of a hybrid ac-dc microgrid was emerged because of this contradiction. Hybrid ac-dc microgrid was introduced in order to exploit the benefits of both ac and dc microgrids. However, the combination of both ac and dc microgrids will add more complexity to the network. Because in all studies for hybrid ac-dc microgrid, such as steady-state analysis or dynamic study, two sets of equations should be considered and solved either separately or simultaneously, the solutions that were presented before. These solutions increase the time of simulation and operation.In this paper, a novel procedure for steady-state analysis of a general hybrid ac-dc microgrid is proposed. In this technique, the dc microgrids will be transferred to the ac side by proposing two lemmas and then the whole grid will be analyzed as one ac network. It will be proved that not only the new ac grid has the same power flow result with the initial topology of the ac-dc microgrid, but also the simulation time of the proposed method is less than the other existing methods

A Generalized Model for Unified Ac-Dc Load Flow Analysis

The tendency to gain the benefits of both ac and dc grids pushed the power industries to introduce the ac-dc hybrid system as the future of distribution systems. Although these grids bring substantial advantages for the power system, such as stability, reliability, resiliency, they add more complexities to power network studies, such as load flow, short circuit, dynamic, stability analyses. These complexities arise due to the presence of ac-dc converters. In a hybrid grid, ac and dc system equations should be solved either simultaneously or sequentially. Despite the sequential method that was in a center of attention, the simultaneous approaches have not been deeply researched due to some technical barriers. This paper aims to explore the ac equivalent circuits of dc grids so that the ac-dc hybrid grid can be considered and analyzed as one ac grid. Accordingly, dealing with separate sets of equations for ac and dc networks is avoided. Therefore, all of the classical power system studies, such as the Newton Raphson (NR) based load flow algorithm, stability and dynamic analyses, and short circuit study, can be applied to the ac-dc network with a small modification that substantially saves time and effort

Unified AC-DC Load Flow Via an Alternate AC-Equivalent Circuit

Hybrid ac-dc grids can gain the benefits of both ac and dc grids. The Ac-Dc circuit analysis can be performed using sequential methods that decouple ac and dc systems or unified (simultaneous) methods that solve the ac and dc mismatch equations simultaneously. This paper introduces a unified ac-dc analysis via an improved model for the ac-dc coupling through which the ac and dc load flow analyses can be simultaneously conducted. The ac-dc coupling is modeled by an admittance building block, and thus, the dc grid is converted to an ac-equivalent circuit within the hybrid network. However, unlike past literature, state variables beyond nodal voltages and angles are avoided, leading to a simpler algorithm, and reactive power injection of the coupling mechanism, a requirement for the IEEE 1547 Std, is explicitly modeled. Furthermore, the proposed model can be applied to both voltage-source and line-commuted converters. Accordingly, the conventional ac power flow algorithms can be applied to the hybrid circuit paving the path for seamless adoption of hybrid circuits and significantly saving time and effort in programming, troubleshooting, and upgrading techniques currently used in research and industry as well as a high-level analysis tool regarding the hybrid ac-dc grid is achieved

Intelligent Operation of Small-Scale Interconnected DC Grids via Measurement Redundancy

Interconnected dc grids are studied in this paper, which comprise resistive and constant-power loads (CPLs) fed by photovoltaic (PV) units. All the sources and CPLs are connected to the grid via dc-dc converters. Nonlinear behavior of PV units in addition to the effect of negative-resistance CPLs can destabilize the dc grid. Thus, the decentralized nonlinear model and intelligent control are proposed using adaptive output-feedback controller to stabilize the grid. The use of the output-feedback control makes possible the utilization of other available signals, in case of loss of main signal, at the converter location and creates measurement redundancy that improves reliability of the dc network. The switching between measured signals of different types are performed through using the neural network (NN) controllers without the need to further tuning. The stability of the entire network is assured through Lyapunov stability method while each converter employs only local measurements. The adaptive NNs are utilized to overcome the unknown dynamics of the dc-dc converters at distributed energy resources and CPLs and those of the interconnected network imposed on the converters. Simulation and experimental results are provided on a small-scale dc grid to show the effectiveness of the developed model and the proposed controller

Assessment of virtual education during the covid-19 pandemic from the perspective of faculty members and students: a cross-sectional descriptive study in northwest Iran

Abstract Background Since the coronavirus outbreak, many countries have replaced traditional education with virtual education in order to prevent the disease spread, and also avoid stopping education. The aim of the present study was to assess the virtual education status at Khalkhal University of Medical Sciences during the covid-19 pandemic from the perspective of students and faculty members. Methods This is a descriptive-cross-sectional study that was conducted between December 2021and February 2022. The study population included faculty members and students who were selected by consensus. Data collection instruments included demographic information form and a virtual education assessment questionnaire. Data analysis was carried out using independent T-test, one sample T-test, Pearson Correlation, and ANOVA test in SPSS software. Results A total of 231 students and 22 faculty members of Khalkhal University of Medical Sciences participated in the present study. The response rate was 66.57%. The mean and standard deviation of assessment scores of students (3.3 ± 0.72) were lower than those of faculty members (3.94 ± 0.64), which showed a statistically significant difference (p < 0.01). User access to the virtual education system (3.8 ± 0.85) and lesson presentation (4.28 ± 0.71) obtained the highest scores from the perspective of students and faculty members, respectively. There was a statistically significant association between employment status and the assessment score of faculty members (p = 0.01), and the field of study (p < 0.01), the year of university entrance (p = 0.01), and the assessment score of students. Conclusion The results showed a higher than mean assessment score in both groups of faculty members and students. There was a difference between faculty members and students in terms of virtual education scores in the parts that require the creation of better processes and more complete capabilities in the systems, which seems that more detailed planning and reforms will improve the process of virtual education