Semnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863420250201Reinforcement Learning-Based Chaotic Communication System for Secure Transmission of Encrypted State Information in the Smart Grid16942610.22075/mseee.2025.35058.1174ENShahramHosseinzadehAzarbaijan Shahid Madani University, Tabriz, Iran.0000-0002-6765-3730RuhollahJafari LagranAzarbaijan Shahid Madani University, Tabriz, Iran.Journal Article20240817This paper proposes a system for transmitting and receiving encrypted state information via a communication channel in the presence of noise and interference. The proposed system uses a chaotic signal generated by a Lorentz oscillator to encrypt the state information, which is then transmitted through the communication channel. At the receiver end, the received signal is decrypted using a similar key generated by a forced Lorentz oscillator. The accurate determination of the force signal is essential for synchronizing chaotic signals, and this paper proposes the use of reinforcement deep learning agents to train and determine the force signal. The proposed communication scheme involves the use of a state estimator, a master chaotic oscillator, two slave oscillators, and two RL agents. The proposed system was simulated using MATLAB Simulink, and the results show that the errors exhibit a repetitive nature, with low and high values corresponding to the input signal. The proposed system provides a reliable and secure system for transmitting sensitive information over communication channels.https://mseee.semnan.ac.ir/article_9426_c45114e543800e035c8e58f364ac0f44.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863420240201Enthusiasms, Challenges, and Future Trends in Procedural Content Generation in Games Using Machine Learning722946710.22075/mseee.2025.32606.1136ENShaqayeqSaffariFaculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran.MortezaDorrigivFaculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran.FarzinYaghmaeeFaculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran.Journal Article20231208-- Procedural Content Generation (PCG) in video games, defined as the automated creation of game content through algorithmic processes, has experienced significant evolution over time. This advancement enables the generation of diverse game elements with minimal designer input. Historically, the development of PCG in games has utilized various methodologies, including search-based, solver-based, rule-based, and grammar-based approaches. These techniques have played a crucial role in producing a broad spectrum of content, such as levels, maps, character models, and textures. More recently, the incorporation of artificial intelligence, notably machine learning, has revolutionized the field of content generation within the gaming industry. Leveraging vast datasets and enhanced computational capabilities, machine learning algorithms offer unprecedented opportunities for creating dynamic and immersive game environments. Despite these advancements, a significant lack of comprehensive research thoroughly examines this field from crucial perspectives. This paper analyzes machine learning applications in game content generation, focusing on key issues in the PCG domain, such as enthusiasm, current challenges, and exploring potential future trends.https://mseee.semnan.ac.ir/article_9467_613bbcad7cc83fa0866b868639b350b4.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863420240201Design of Novel 2:4 Decoder Circuits for Quantum-dot Cellular Automata Technology2330942410.22075/mseee.2025.35950.1188ENMohammadhosseinHeydariDepartment of Electrical Engineering, University of Science and Culture, Tehran, Iran.AbdalhosseinRezaiDepartment of Electrical Engineering, University of Science and Culture, Tehran, Iran.FarbodJavaheriDepartment of Electrical Engineering, University of Science and Culture, Tehran, Iran.Journal Article20241117Quantum-dot Cellular Automata (QCA) technology is a highly promising emerging technology that serves as a viable alternative to CMOS technology. On the other hand, the decoder is one of the vital building blocks in digital circuits. This paper presents and evaluates two novel 2:4 decoder circuits in QCA technology. The 2:4 decoder is a crucial component in digital systems, responsible for translating binary information from encoded input signals to a unique output signal. The first proposed circuit is implemented in a single layer, and the second proposed circuit is implemented in 3 layers. The functionality of the proposed decoder circuits is verified using the QCADesigner tool. The obtained results demonstrate that the designed coplanar QCA decoder has 34 cells, 0.02 , and 0.5 clock cycles delay. In addition, our proposed multilayer decoder has 34 cells, 0.01 area, and 0.5 clock cycle delay. The coplanar and multilayer developed decoder circuits have 2.08 and 2.33 , average Ebath energy, respectively. The comparison results indicate that the proposed circuits have advantages compared to other decoder circuits.https://mseee.semnan.ac.ir/article_9424_76009be5ef98afa6f2f666ab9b89bcfc.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863420240201Discovery and Evaluation of Fixed Capital Facility Processes Based on Process Mining Approach: A Case Study of the Bank Loan Acceptance Process in Iran3141942010.22075/mseee.2025.35345.1177ENEhsan AllahKhoshkhoy NilashDepartment of Management, Hamedan Branch, Islamic Azad University, Hamedan, Iran.MansourEsmaeilpourDepartment of Computer Engineering, Hamedan Branch, Islamic Azad University, Hamedan, Iran.0000-0002-2475-518XBehroozBayatDepartment of Knowledge and Information Science, Hamedan Branch, Islamic Azad University, Hamedan, Iran.AlirezaIsfandyari MoghaddamDepartment of Knowledge and Information Science, Hamedan Branch, Islamic Azad University, Hamedan, Iran.ErfanHassannayebiDepartment of Industrial Engineering, Sharif University of Technology, Tehran, Iran.Journal Article20240917Fixed capital facility processes have many steps, control points, and approvals with long durations. In this regard, banks with more awareness and knowledge by analyzing and evaluating their processes can do better than their competitors in improving them and providing customer service. To tackle this challenge, process mining is one of the effective and efficient methods for analyzing processes, i.e., discovering and evaluating their quality. This paper aims to find and evaluate the model of the fixed capital facilities acceptance process based on the mentioned method. The proposed six-step method includes event logs preparation, process model discovery, evaluation and compliance checking, results analysis, analysis based on the fuzzy method, and comparison of results. The discovered process model is evaluated based on the quality dimensions of the process model, namely precision, fitness, simplicity, and generalization. Also, the results obtained from different methods are compared with each other. In addition to the discovery of the process model, one of the results was the heuristic algorithm having the best performance in terms of the mentioned criteria, with a value of 0.833. Particularly, it excelled in precision with a value of 0.656. The genetic algorithm, with a value of 0.946, exhibited the best fitness performance. Another result is the superior performance of the fuzzy technique compared to other methods. Furthermore, bottlenecks, activities with the highest repetition in a case, and branches and users with the most significant role in the process were identified.https://mseee.semnan.ac.ir/article_9420_838a115bf3ace5bc71de62f3d696554d.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863420240201Overcurrent Coordination by Eel Swarm Optimization Algorithm4351947210.22075/mseee.2025.33340.1146ENZahraMoravejFaculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran.MahsaSalariFaculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran.Journal Article20240219In recent years, the complexity of modern distribution systems has increased due to the integration of dispersed generation resources. Coordinating directional overcurrent relays (DOCR) for protecting these systems poses a challenging optimization problem. This study introduces the Eel Swarm Optimization Algorithm (ESOA) to address this issue. Inspired by eels' hunting behavior, ESOA effectively explores the solution space. Testing on various error scenarios in 3-bus and 15-bus systems demonstrates ESOA's superior performance in reducing primary relay performance time compared to other optimization algorithms. The algorithm demonstrates proficiency in ensuring synchronization between primary relay pairs and backup relays, reducing the time difference in coordination.https://mseee.semnan.ac.ir/article_9472_899301efe0ce6733e0fbafda7a93503f.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863420240201Handling the Impact of Uncertainties on Predicting the Quality Aspects of Doogh5362947310.22075/mseee.2025.34738.1170ENMohammadAmini HoshiarDepartment of Food science & Technology, Noor Branch, Islamic Azad University, Noor, Iran.SaraJafarianDepartment of Food Science & Technology, Noor Branch, Islamic Azad University, Noor, Iran.RamezanRezaianDepartment of Mathematics, Noor Branch, Islamic Azad University, Noor, Iran.MahdiSharifi SoltaniDepartment of Veterinary, Chalous Branch, Islamic Azad University, Chalous, Iran.Journal Article20240713Support Vector Machines (SVMs) are a valuable tool in the food industry due to their ability to handle complex, nonlinear relationships between variables, even with limited datasets, high-dimensional data, and noisy data. This makes SVMs well-suited for applications such as food quality and safety assessment, sensory evaluation, process optimization, and food authentication. Accordingly, a new approach is introduced to predict different features of a traditional yogurt drink, also called doogh. The proposed model combines the principles of Support Vector Regression with fuzzy logic to handle uncertainty and approximate complex relationships between inputs (retentate, xanthan, and shelf-life) and target variables including viscosity, syneresis, color values, and total acceptability. The implemented approach is particularly useful when dealing with problems where the relationships are not easily captured by traditional mathematical models due to their non-linearity or imprecision. Also, it mitigates the limitations of data availability. The predictive ability of the proposed model has been evaluated in terms of MSE, R2, RMSE, and MAE when adding different noise levels. Additionally, the conditions necessary to attain optimized metric values have been found. At the optimum point, the viscosity, syneresis, L*, a*, b* and total acceptability are 19.70 mPa.s, 11.30%, 97.04, -1.43, 8.13, and 5.00, respectively. Besides, the findings indicate that samples containing 0.8% retentate, 0.4% xanthan, and a 31-day shelf-life exhibit the highest viscosity, while those with 0.6% retentate, 0.4% xanthan, and a 31-day shelf-life show the lowest syneresis. Moreover, samples with 0.7% retentate, 0.2% xanthan, and a 13-day shelf-life demonstrate the highest total acceptability.https://mseee.semnan.ac.ir/article_9473_8dd0ee4a1002acdc0ddfb4716dd7fdec.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863420240201Increase Power Grid Stability Using Dual-Excited Synchronous Generator6371947410.22075/mseee.2025.33398.1152ENAlirezaAkramFaculty of Electrical & Computer Engineering, Semnan University, Semnan, Iran.HamidYaghobiFaculty of Electrical and Computer Engineering, Semnan University, Semnan, Iran.Journal Article20240228Transient stability in interconnected power systems remains a pivotal concern for operators, particularly amidst the ever-expanding and intricate nature of modern power grids. This study delves into a novel approach to bolstering power grid stability by proposing the implementation of dual-excited synchronous generators (DESGs). Unlike conventional synchronous generators, DESGs feature dual windings on the rotor, strategically positioned to optimize performance and stability. This paper presents a thorough assessment of synchronous generators and DESGs under varying fault conditions, including three-phase to ground, two-phase to ground, and more. Leveraging advanced simulation techniques in Matlab/Simulink, the dynamic behavior and stability of these generators are meticulously analyzed. The results unveil a paradigm shift: DESGs exhibit superior stability and dynamic performance compared to their conventional counterparts across diverse fault scenarios. By harnessing the advantages of DESGs, including enhanced efficiency, the overall stability and reliability of power grids can be significantly augmented. In summary, this study not only sheds light on the critical importance of power grid stability but also presents a promising solution in the form of DESGs. By pushing the boundaries of traditional generator technology, this research paves the way for a more resilient and efficient electrical infrastructure.https://mseee.semnan.ac.ir/article_9474_904f78a8212e6b5ce49fab2ade6b22a5.pdf