Amirkabir University of TechnologyAUT Journal of Modeling and Simulation2588-295357120250601Computational Simulation of Applying Oscillatory Flow on a Stem Cell Using Fluid-Structure Interaction Method: Role of Primary Cilia and Cytoskeleton316579210.22060/miscj.2025.23528.5384ENHamidrezaAziziDepartment of Life Science Engineering, Faculty of New Sciences and Technologies, University of Tehran, Tehran, IranBahmanVahidiDepartment of Life Science Engineering, Faculty of New Sciences and Technologies, University of Tehran, Tehran, Iran0000-0001-5597-3748SaharJianian TehraniDepartment of Life Science Engineering, Faculty of New Sciences and Technologies, University of Tehran, Tehran, IranJournal Article20240914Load-induced fluid flow acts as a dominant biophysical signal for bone cell mechanotransduction <em>in vivo</em>. Oscillatory fluid flow has been used in bone tissue engineering strategies due to its similarity to the fluid dynamics within the human body. In this study, a fluid-structure interaction method was used to subject the mesenchymal cell to steady and oscillatory fluid flow. Three models were considered for a steady flow, including cytoplasm, nucleus, primary cilium, and cytoskeleton, to investigate the effects of cilium and cytoskeleton on cell mechanical responses (stress and strain). The fourth model, including cytoplasm, primary cilium, and cytoskeleton components has been considered to evaluate the stress and strain values created in the cell and its components in the oscillatory flow regime. The length and mechanical properties of the primary cilium (Young's modulus) were also varied to investigate cell responses. The results indicated that the presence of the cytoskeleton reduced the amount of stress experienced in the cell by about 35%. The presence of primary cilium, also, increased stress in the cell by about ten times in an oscillatory regime. The peak von Mises stress was 11.5 Pa in the oscillatory flow, which is three times greater than the level observed in the steady state condition. Moreover, the highest amount of strain occurred at the base of the cilium, indicating this component's importance in receiving and transmitting stress to other components. Our results revealed a direct relationship between the properties of the cilium and the stress and strain created in the cell. For a cilium with a length of 4 µm, the deflection at the tip of the cilium was 0.77 µm. This represented a 78% increase compared to a 10 µm cilium. This research can be a basis for future numerical studies in tissue engineering and improvements in the related experimental approaches.https://miscj.aut.ac.ir/article_5792_89b9c689a57b82e59074c6ba09aa394d.pdfAmirkabir University of TechnologyAUT Journal of Modeling and Simulation2588-295357120250601A Risk-Adjusted CUSUM Chart for Monitoring Surgical Performance with Ordinal Outcomes and Random Effects1728580610.22060/miscj.2025.23841.5400ENRamezanKhosraviDepartment of Industrial Engineering, University of Gonabad, Gonabad, Iran0000-0002-2010-1672HadiGholinezhadDepartment of Industrial Engineering, University of Gonabad, Gonabad, Iran.HamidEsmaeeliDepartment of Industrial Engineering, Islamic Azad University- North Tehran Branch, Tehran, Iran.0000-0003-0149-8077Journal Article20250119Monitoring healthcare processes poses unique challenges due to the substantial variability in patient risk profiles, which can significantly influence surgical outcomes. Traditional control charts often neglect these individual differences, leading to potentially biased and misleading performance assessments. To overcome these limitations, risk-adjusted control charts have been developed to incorporate patient-specific covariates for more equitable monitoring. This study extends previous approaches by proposing a risk-adjusted cumulative sum (RA-CUSUM) control chart that accommodates <em>ordinal</em> surgical outcomes and incorporates <em>random effects</em> to model unobserved heterogeneity among healthcare providers. The proposed RA-CUSUM chart employs dynamic probability control limits (DPCLs) to maintain a constant conditional false alarm rate, enabling consistent performance across heterogeneous patient populations. Through extensive simulation studies, we demonstrate its efficacy in detecting shifts in surgical performance stability, particularly in response to changes in location and scale. A real-world case study using cardiac surgery data demonstrates the practical applicability of the method. This work provides a more refined and fair framework for evaluating surgical quality and lays the groundwork for integrating adaptive techniques in future healthcare monitoring systems. In addition to healthcare monitoring, the method can be extended to other domains where ordinal outcomes and case heterogeneity are relevant, such as education and finance. This adaptability makes it a valuable decision-support tool for quality improvement programs and real-time risk management.https://miscj.aut.ac.ir/article_5806_9873eaad153c6c960616c89e54fe155a.pdfAmirkabir University of TechnologyAUT Journal of Modeling and Simulation2588-295357120250601Robust Model Predictive Terminal Guidance Law Using Laguerre Functions2952580710.22060/miscj.2025.23244.5361ENMohammad SadeghNazariFaculty of Electrical and Computer Engineering, Malek Ashtar University of Technology, Tehran, Iran0000-0002-3069-7529SaeedNasrollahiFaculty of Electrical and Computer Engineering, Malek Ashtar University of Technology, Tehran, Iran0000-0002-8067-1394Journal Article20240602This paper presents a new approach for guiding a pursuer to intercept a maneuvering target in two dimensions. This robust nonlinear approach is based on the combination of predictive control and sliding mode control. The guidance strategy uses a model predictive control method based on the Laguerre function to calculate the pursuer’s acceleration command independently of the target’s acceleration. To handle unknown target maneuvers, a sliding mode term is added to adjust to the target’s acceleration commands, making the algorithm more robust against uncertainties and improving its ability to pursue maneuvering targets effectively. The proposed guidance algorithm was extensively tested through simulations with various target maneuvers, including non-maneuvering, step maneuvers, sinusoidal maneuvers, and stochastic maneuvers. A detailed comparison was made with traditional methods like proportional navigation, ant colony optimization-based predictive control, proportional guidance with a bias switch, and a square programming approach based on differential game theory. Additionally, to observe the effect of the design parameters in the proposed guidance law, a sensitivity analysis is done on the convergence of the pursuer acceleration and the line-of-sight rate. Finally, the influence of disturbances was investigated by adjusting the target acceleration parameter to 10%, 20%, 30%, 50%, 75%, and 100% beyond the maximum value.https://miscj.aut.ac.ir/article_5807_681a23b0649e61ca572cb5bb8db206ec.pdfAmirkabir University of TechnologyAUT Journal of Modeling and Simulation2588-295357120250601Double Deep Q Network with Adaptive Prioritized Experience Replay5362580810.22060/miscj.2025.23426.5373ENMajidAdibianDepartment of Computer Engineering, Amirkabir University of Technology, Tehran, Iran0009-0007-5361-4937Mohammad MahdiEbadzadehDepartment of Computer Engineering, Amirkabir University of Technology, Tehran, Iran0000-0001-6466-5229Journal Article20240808In deep reinforcement learning, experience replay buffers are used to reduce the effects of sequential data and make better use of past experiences. Prioritized Experience Replay (PER) improves upon random sampling by selecting transitions based on their temporal difference (TD) error. However, PER does not consider how important each transition is or how many times it has been used during training. In this paper, we propose a new method for adaptive prioritization that takes into account three additional transition-level factors: reward, usage count (counter), and policy probability—collectively referred to as RCP values. These values are normalized and used alongside the TD error to calculate the probability of selecting each transition from the replay buffer. We evaluate our method on several Atari environments and show that using any of the RCP values individually can improve performance compared to standard PER. To combine all three RCP components, we explore three aggregation functions: minimum, maximum, and mean. Experimental results show that the best aggregation method depends on the environment. However, the mean function generally provides stable improvements across tasks, as it balances all RCP signals and avoids over-relying on any single factor.https://miscj.aut.ac.ir/article_5808_b448d8292fd27ae25bbc2e09ad43ff88.pdfAmirkabir University of TechnologyAUT Journal of Modeling and Simulation2588-295357120250601An Investigation of Heat Flow in Hydromagnetic Eyring-Powell Fluid in the Presence of Cattaneo-Christov Heat Flux6372581310.22060/miscj.2025.23842.5404ENLateef OSogbetunDepartment of Mathematics, Federal University of Agriculture, Abeokuta, Nigeria0009-0001-8273-7617Bakai IsholaOlajuwonDepartment of Mathematics, Federal University of Agriculture, Abeokuta, NigeriaOlalekanFagbemiroDepartment of Mathematics, Federal University of Agriculture, Abeokuta, NigeriaJournal Article20250225This paper examines the flow and heat transfer characteristics of an Eyring-Powell fluid passing over a stretched sheet surface that is being heated by hot fluid from beneath. The thermal mechanism of the model is analyzed on the considerations that the thermal conductivity is a linear function of temperature, the fluid viscosity obeys the Reynolds model, and that the Cattaneo–Christov heat flux model is incorporated into the energy equation. The governing nonlinear partial differential equations were transformed into a system of nonlinear ordinary differential equations using suitable similarity variables. The resulting self-similar problems were then solved using the spectral quasi-linearization method (SQLM). The effectiveness and accuracy of this method were demonstrated through error analysis and comparative studies with relevant existing results. Graphical outcomes illustrating the impact of pertinent fluid parameters in the model equations are presented as velocity and temperature profiles. It is noteworthy that both fluid temperature and velocity decline when the thermal relaxation parameter and slip velocity parameter are increased. The results also reveal that the fluid variables, such as the thermal relaxation time parameter , Eyring-Powell parameter , slip velocity parameter , surface-convection parameter , or radiation parameter boost the rate of heat transfer when any of these parameters is increased.https://miscj.aut.ac.ir/article_5813_069090145d54bf4aa3894133f7e89873.pdfAmirkabir University of TechnologyAUT Journal of Modeling and Simulation2588-295357120250601Optimizing Multi-Microgrid Operations: A Compromise Approach Incorporating Loss Considerations and Renewable Energy Uncertainty7388582910.22060/miscj.2025.23814.5398ENHosseinKianiDepartment of Electrical Engineering, Amirkabir University of Technology, Tehran, IranMohammad HassanNazariDepartment of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran
Department of Smart Control Systems, Niroo Research Institute (NRI), Tehran, IranSeyed HosseinHosseinianDepartment of Electrical Engineering, Amirkabir University of Technology, Tehran, IranJournal Article20250106The significant integration of variable renewable energy sources, along with the uncertainties in their generation, presents a substantial challenge for the distribution system operator. Microgrids, recognized as intelligent grid systems, offer a promising solution for the efficient integration of local renewable energy resources. However, the intermittent nature of renewable energy introduces operational complexities and additional costs associated with maintaining stable performance within the microgrid's energy management system. The presence of multiple microgrids facilitates the creation of a flexible and diversified energy market structure. This paper investigates the impact of losses on microgrid expenses through the analysis of various scenarios. A compromise model objective is proposed, focusing on the minimization of microgrid costs. To address the uncertainties associated with variable renewable energy sources and their impact on system costs, distributed energy resource schedules, and the overall energy market, we propose a new data-driven probabilistic efficient point method. This method calculates the optimal generation from sustainable energy at various risk levels, which can then be integrated into a suggested transactive day-ahead market model. Simulation results confirm that the proposed compromise strategy is feasible, with system cost nearly matching the minimum achievable. Specifically, during peak demand periods, the compromise scenario yields a 3% reduction compared to the actual system cost. Likewise, system losses, which reach their maximum during high-demand intervals, are reduced by 2.5% under the compromise-based solution relative to the actual system. These outcomes confirm the effectiveness of the proposed approach in simultaneously achieving economic efficiency and technical reliability.https://miscj.aut.ac.ir/article_5829_d9909824688daaad46d441eefd81eb38.pdfAmirkabir University of TechnologyAUT Journal of Modeling and Simulation2588-295357120250601COTSA: A Load-Balanced Task Scheduling Algorithm using Coati Optimization in Cloud Computing Environment89112583510.22060/miscj.2025.23520.5381ENZahraJalali Khalil AbadiDepartment of Computer Science, Shahid Bahonar University of Kerman, Kerman, Iran.NajmeMansouriDepartment of Computer Science, Shahid Bahonar University of Kerman, Kerman, Iran.Mohammad MasoudJavidiDepartment of Computer Science, Shahid Bahonar University of Kerman, Kerman, Iran.0000-0002-7955-8220BehnamMohammad Hasani ZadeDepartment of Computer Science, Shahid Bahonar University of Kerman, Kerman, Iran.Journal Article20240910During the scheduling process, it is important to respect the constraints given by the jobs and the cloud providers. In addition to maintaining a balance between Quality of Service (QoS), fairness, and efficiency of jobs, scheduling is challenging. This paper aims to propose an efficient algorithm for load-balanced task scheduling in the cloud. Our algorithm uses a new meta-heuristic algorithm called COA (Coati Optimization Algorithm) to solve the task scheduling problem. This method is called COTSA (Coati Optimization-based Task Scheduling Algorithm). Its main goal is to reduce execution costs, load balancing, resource consumption, and makepan. Additionally, experimental results indicate that COTSA contributes to reduced energy consumption and enhanced system scalability and fault tolerance under simulated conditions. These improvements suggest potential suitability for dynamic and large-scale cloud infrastructures, though performance may vary depending on workload characteristics and system configurations. It is compared with Walrus Optimizer (WO), Slap Swarm Algorithm (SSA), Whale Optimization Algorithm (WOA), Zebra Optimization Algorithms (ZOA), Grasshopper Optimization Algorithm (GOA), Sooty Tern Optimization Algorithm (STOA), Golden Eagle Optimizer (GEO), Grey Wolf Optimizer (GWO), Subtraction-Average-Based Optimizer (SABO), and Sand Cat Swarm Optimization (SCSO), which are popular meta-heuristics. Experimental results demonstrate that COTSA reduces makespan by approximately 9%, lowers execution cost by up to 40%, improves resource utilization by around 3%, and enhances load balance by up to 30%, energy consumption about 36%, scalability near 17%, and fault tolerance about 16%, making it a robust and scalable solution for efficient cloud task scheduling.https://miscj.aut.ac.ir/article_5835_6dd3e6a48b7117f6ae04a6664beb740b.pdfAmirkabir University of TechnologyAUT Journal of Modeling and Simulation2588-295357120250601Classifying AI-Generated Text in Low-Resource Languages like Arabic113124585910.22060/miscj.2025.24060.5408ENOhoodAl MinshidawiComputer Engineering Department, College of Alborz, University of Tehran, Tehran, IranAbdol-HosseinVahabieComputer Engineering Department, College of Alborz, University of Tehran, Tehran, Iran
School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, IranSchool of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, IranJournal Article20250423AI-Generated Texts (AIGTs) refer to written content produced by artificial intelligence systems using technologies such as natural language processing and machine learning. The rise of AIGT has introduced new challenges in content authenticity, trustworthiness, and information integrity across digital platforms. In low-resource languages, like Arabic, AIGT detection is challenging because of their more complex structural features. Accurate identification of AI-generated versus human-written text is essential to combat misinformation, preserve credibility in communication, and enhance content moderation systems. In this study, we propose a novel framework for AIGT detection on the AutoTweet Dataset, an annotated corpus of Arabic tweets. To the best of our knowledge, this is the first work to leverage Large Language Models (LLMs) for AIGT detection in Arabic, addressing a critical gap in low-resource natural language processing. We introduce a dynamic few-shot prompting technique, powered by a retrieval-based Judge Prompter module, which selects semantically and stylistically relevant support examples to enhance the contextual understanding of LLMs. We conduct a comprehensive evaluation across multiple LLMs, including Mistral-7B, LLaMA-3.1-8B, and ALLaM-7B-Instruct-preview, under zero-shot, few-shot, and fine-tuning scenarios. Our best results were achieved using Mistral-7B with QLoRA fine-tuning and dynamic few-shot prompting, reaching an accuracy of 88.69% and an F1-score of 88.35%. These findings demonstrate the feasibility of adapting LLMs for AIGT detection in Arabic and highlight the effectiveness of context-aware prompting in low-resource settings, paving the way for future progress in text classification.https://miscj.aut.ac.ir/article_5859_60106888f8977b71e1f15db7bc9a88d1.pdf