University of GuilanComputational Sciences and Engineering2783-25034120240826Evaluation of Distillate Yield in 3D-Single Slope Basin Type Solar Still: A Comparative Study of CFD and Experimental Approaches111795710.22124/cse.2024.28065.1084ENShah NawazAnsariNepal Academy of Science and Technology (NAST)SudeepSahSankharapur Polytechnic Institute, CTEVT, NepalNawrajBhattaraiDepartment of Mechanical and Aerospace Engineering, Pulchowk Campus, IOE, TU, NepalSanjayaNeupaneDepartment of Mechanical and Aerospace Engineering, Pulchowk Campus, IOE, TU, NepalJournal Article20240731There are various merits of modelling the problem domain numerically, which include cost reduction, ease in variable control, enhanced yield, etc. These merits are known to everyone. This work provides a one-of-a-kind and complete evaluation of distillate yield i.e. productivity in a single slope solar still by combining computational fluid dynamics (CFD) models with experimental data. Unlike earlier research, which frequently focuses on either simulation or experimental data in isolation, this study presents a direct comparison of the two methodologies, showing their distinct strengths and limitations. The experimental model of solar still was fabricated for experimental study. Based on the experiment, distillate yield was observed every hour of the day. The experiment was conducted on the roof of Balaju School of Engineering and Technology, Kathmandu. On the other hand, CFD model was based on the practical model used for experimentation. Most of the variables were chosen as per the physical domain, such as the material of the solar still and the angle of inclination. From the comparative study, it was found that distillate yield resulted from simulation through CFD analysis, and the experiment followed a similar trend. There was an error of about 26%, which might be the result of losses that occur in practical applications that were not considered during CFD analysis. From the research, it was found that, ANSYS is a powerful tool for performing CFD analysis of practical problems involving fluid flow. Thus, it can be used for modelling and simulating more complex problem in future.https://cse.guilan.ac.ir/article_7957_8a241a7704a401b0a5a8cd393231aeab.pdfUniversity of GuilanComputational Sciences and Engineering2783-25034120240401Identification and Prioritization of Key Factors Affecting Workforce Productivity Using Grey Delphi and Grey DEMATEL: A Case Study1330860910.22124/cse.2025.30110.1097ENSeyed AminBadriUniversity of GuilanJournal Article20240324Enhancing workforce productivity is a critical challenge for industrial and engineering companies. This study aims to identify and prioritize key factors influencing workforce productivity using a structured multi-criteria decision-making approach. Initially, the Grey Delphi Method was employed to gather expert opinions and determine the most influential criteria, leading to the identification of six main criteria and twenty-two sub-criteria. Subsequently, the Grey DEMATEL technique was applied with inputs from four decision-makers to analyze causal relationships and rank these factors. The results indicate that managerial factors had the highest impact on workforce productivity, followed by socio-psychological factors and economic factors. Among the sub-criteria, leadership style, job satisfaction, and alignment between personal interests and job roles were identified as the most critical. These findings provide valuable insights for managers and policymakers, highlighting the need for leadership development, employee engagement, and tailored motivational strategies to enhance productivity. This study demonstrates the effectiveness of integrating Grey Delphi and Grey DEMATEL in decision-making processes, offering a systematic approach to optimizing workforce performance in complex organizational environments.https://cse.guilan.ac.ir/article_8609_1f164350234b735ac1716e2cff396685.pdfUniversity of GuilanComputational Sciences and Engineering2783-25034120250212GiraDP: Enabling Large-Scale Optimization with Dynamic Programming3140846710.22124/cse.2025.29701.1091ENSaeedMirpour MarzuniDepartment of Electrical and Computer Engineering, University of Science and Technology of Mazandaran, Behshahr, IranJavadVahidiDepartment of Computer Science, Iran University of Science and Technology, Tehran, Iran0000-0002-6582-7493Journal Article20250129NP-hard optimization problems are computationally challenging tasks that require significant resources to solve, particularly as problem sizes increase. In this paper, we introduce a novel framework, GiraDP, which converts dynamic programming problems into graphs and solves these large-scale graphs efficiently. GiraDP addresses NP-hard optimization problems by leveraging advanced graph processing techniques. The framework utilizes Giraph and Hadoop in its architecture to manage extensive datasets and complex computations. It generates input data for Giraph and identifies active vertices that correspond to sub-problems within the larger problem. Our experiments include scenarios with 20, 40, and 60 items, across varying knapsack capacities. The results indicate that while the serial algorithm performs best at low capacities, it fails to handle larger instances due to memory limitations, resulting in heap space errors. In contrast, GiraDP demonstrates superior efficiency and scalability for high capacities and large item sets. The MPI-based approach also shows improved performance over the serial algorithm for larger problems, although it does not match the efficiency of GiraDP. These findings underscore the importance of distributed computing solutions for large-scale optimization problemshttps://cse.guilan.ac.ir/article_8467_40d94a5ad35ed3b24c2a846927509afc.pdfUniversity of GuilanComputational Sciences and Engineering2783-25034120240401Multiple Sclerosis Diagnosis Methods Using Machine Learning and Imaging Techniques4151817010.22124/cse.2024.28459.1086ENMandanaAghazadenejatDepartment of Electrical Engineering, University of Science and Culture, Tehran, IranAbdalhosseinRezaiDepartment of Electrical Engineering, University of Science and Culture, Tehran, IranJournal Article20240913Multiple Sclerosis (MS) disease is immune disorder that destroys myelin in the nervous system and causes many complications including motor and sensory disorders. Nowadays, medical images including Magnetic Resonance Imaging (MRI) and Optical Coherence Tomography (OCT) are recognized as the basic tools in the diagnosis of MS disease. Due to the large amount of image data in this method, the use of machine learning methods, especially Neural Networks (NNs) plays an important role in image processing. This paper presents a comprehensive overview of different methods, which utilize NNs to MS diagnosis. This review presents the classical of NNs and Convolutional NNs (CNNs), which are used in the MS diagnosis. In addition, challenges, and recent developments in this field are presented, which provides directions for future researches in this field.https://cse.guilan.ac.ir/article_8170_c6df14cc3d68a2212808ee903a7421f5.pdfUniversity of GuilanComputational Sciences and Engineering2783-25034120241030Solving Weakly Singular Fractional Differential Integration Equations Using Multiple Knot B-Splines and Operational Matrices5365811110.22124/cse.2024.28813.1089ENAli JalalAliUniversity of MazandaranMostafaEslamiUniversity of MazandaranAliTavakoliUniversity of MazandaranJournal Article20240915In this article, we propose a new strategy for solving problems associated with weakly singular partial integro-differential equations. Our approach uses Multiple knot B-splines to develop a powerful arithmetical solution. We analyze the functional matrices used in this technique and provide a detailed overview of its functionality. additionally, we demonstrate the convergence of the proposed advance and verify its effectiveness via several numerical simulation.https://cse.guilan.ac.ir/article_8111_39427129e4d5c537ec5baf52d764b02d.pdfUniversity of GuilanComputational Sciences and Engineering2783-25034120240401A numerical method for solving a variable-order fractional integral-differential equation6778848810.22124/cse.2025.29847.1094ENAhmadSharifGonbad Kavous UniversityJournal Article20240215In this paper, a numerical method based on finite differences is presented for numerically solving a fractional integral-differential equation of variable order with Prabhakar integral and Caputo-Prabhakkar fractional derivative. Using the proposed method, an approximate solution of the desired equation is obtained from solving a system of linear equations. The stability of the method is investigated and it is shown that the proposed method is stable under certain conditions. Three examples are presented to demonstrate the efficiency and accuracy of the proposed method.https://cse.guilan.ac.ir/article_8488_415560e0c550a5d231f58b9b7e173772.pdfUniversity of GuilanComputational Sciences and Engineering2783-25034120250426Validation of Returned Results in Asymmetric Searchable Encryption Schemes79100861110.22124/cse.2025.29912.1095ENArianArabnouriDep. Of Computer Engineering,
University Of Guilan, P.O. Box 3756RezaEbrahimi AtaniDep. Of Computer Engineering,
University Of Guilan, P.O. Box 3756ShivaAzizzadehDep. Of Computer Engineering,
University Of Guilan, P.O. Box 3756Journal Article20250221As organizations increasingly outsource data to cloud storage, ensuring the security and integrity of this data becomes paramount. Searchable encryption (SE) offers a promising solution by enabling secure searches on encrypted data, thereby preserving privacy and confidentiality. However, existing SE schemes often overlook the issue of data integrity, particularly when the cloud server, an external and potentially untrusted entity, returns invalid or malicious results. This paper proposes a novel technique for validating the results returned by the cloud server in asymmetric searchable encryption schemes. The proposed method introduces minimal efficiency overhead and is easily applicable to existing schemes. By applying this technique to the dPEKS (designated Public Key Encryption with Keyword Search) scheme, we demonstrate a significant reduction in search time while enhancing the ability to validate results across multiple servers. Our approach ensures that the integrity of returned data is preserved, even in scenarios where the cloud server may act maliciously. The proposed technique is particularly effective in private scenarios, such as e-care and banking, where only authorized users can send and retrieve data. This work contributes to the ongoing effort to improve the security and reliability of searchable encryption in cloud environments.https://cse.guilan.ac.ir/article_8611_e0e8667deb6987729b78bc7f07ca2f0f.pdfUniversity of GuilanComputational Sciences and Engineering2783-25034120250205Robust Gustafson-Kessel (RGK) Clustering for Segmentation of Brain Tissues Based on MRI images101124844810.22124/cse.2025.28776.1088ENAliFahmi JafargholkhanlooDepartment of Engineering Sciences, Faculty of Advanced Technologies, University of Mohaghegh Ardabili, Namin, IranMousaShamsiFaculty of Biomedical Engineering, Sahand University of Technology, Tabriz, IranMahdiBashiri BawilFaculty of Biomedical Engineering, Sahand University of Technology, Tabriz, IranJournal Article20241022The fuzzy c-means (FCM) algorithm is widely used for image segmentation based on clustering. However, it is sensitive to noise, and its convergence is affected by the data distribution. FCM relies on the Euclidean distance metric, which fails to account for variations in the distances within similar and compact clusters. Moreover, the distance metric is not locally adaptive to the shape of clusters. This paper introduces a robust Gustafson-Kessel (RGK) clustering algorithm to address these limitations for brain tissue segmentation using MRI images. To achieve accurate segmentation under varying noise levels and intensity non-uniformity (INU), a Wiener filter integrated with wavelet transform (WFWT) is employed as a preprocessing step to enhance image quality while preserving object edges. The Mahalanobis distance is used for clustering to better adapt to the shape of the clusters. Additionally, the RGK algorithm incorporates membership matrix filtering to exploit the local spatial constraint. The proposed RGK algorithm was evaluated using two datasets: the BrainWeb simulated dataset and MRI scans from 10 healthy individuals at the Golghasht Medical Imaging Center in Tabriz (GMICT), Iran. In RGK, it is not necessary to compute the distance between pixels within local spatial neighbors and clusters. Experimental results demonstrate that the RGK algorithm outperforms traditional FCM-based methods in the segmentation of brain tissues.https://cse.guilan.ac.ir/article_8448_eea801a11671ea1b1841be22fef9e6f3.pdfUniversity of GuilanComputational Sciences and Engineering2783-25034120250213Optimum Design of a Microwave Low-Noise Amplifier by Means of Least Mean Square Error (LMS) Technique in S Frequency Band125134846910.22124/cse.2025.29132.1090ENSaeed RezaOstadzadehFaculty of Engineering, Arak University, Arak, IranSinaFeyziBSC student from Arak University, Arak, IranJournal Article20241201In this paper a low noise amplifier (LNA) in the frequency interval of [3-5] GHz is designed and optimized. The design process consists of three parts. At first, the stability of the bipolar junction transistor (BJT) is investigated. Simulation results show that it is unconditionally stable in the whole frequency interval. In the second part, the input and output matching networks are constructed in such a way that the desired transducer power gain (G<sub>T</sub>=10dB) and possible minimum noise figure (F<sub>n</sub>) are achieved simultaneously. In order to achieve approximately constant G<sub>T</sub> and F<sub>n</sub> in the desired frequency interval, the input and output matching networks are finally optimized using least mean square error technique. Once the optimization process is converged, variations of G<sub>T</sub> and F<sub>n </sub>in the whole frequency interval are respectively less than 1dB and 0.5 dB. Besides, the variation of output phase is approximately linear. https://cse.guilan.ac.ir/article_8469_10c063c2735e40204e5230afd8a1d4fb.pdfUniversity of GuilanComputational Sciences and Engineering2783-25034120250510Investigation of Immediate Settlement of Shallow Foundations Located on Clayey Soil with Using a New Numerical Model135151874110.22124/cse.2025.30386.1103ENMaysamSalimzadehshooiiliAssistant Professor. Department of Civil Engineering, Faculty of Engineering, University of Guilan, IranJournal Article20250415Determining the exact amount of immediate settlement located on the clay is one of the main problems in geotechnics. However, although traditional methods such as those by Janbu and Bowles are often used for this purpose, they have limitations. Therefore, in this study, a new numerical model is presented and examined in detail using Plaxis 3D finite element software. Parametric analyses with different ratios of foundation dimensions (<em>L/B</em>) from 1 to 10, foundation thickness ( ) from 1 to 4 meters, buried depth ratio of foundation (<em>D/B</em>) from 0 to 3, soil depth ratio under foundation (<em>H/B</em>) from 1 to 5, soil characteristics (including four soil types), and different loading values (from 100 to 300 kPa) were considered. The results, which were compared with existing methods and diagrams for the design of shallow foundations, revealed that settlement decreases with an increasing (<em>D/B</em>) ratio. Additionally, the results of the new numerical analysis indicated that settlement increases with load increase. A similar trend was observed in Plaxis 3D, Janbu, and Bowles methods.https://cse.guilan.ac.ir/article_8741_5e57254f4db00625fa0ce70b3fcf6476.pdfUniversity of GuilanComputational Sciences and Engineering2783-25034120250524The Influence of Impeller Design on Hydraulic Performance of Vortex Pump153176877710.22124/cse.2025.30586.1105ENHadiFallah ArdeshirAssistant Professor, Faculty of Mechanical Engineering, Sahand University of Technology, Tabriz, IranTohidJavadpourFaculty of Mechanical Engineering, Sahand University of Technology, Tabriz, IranJournal Article20250505This study investigates the performance of vortex pumps by focusing on impeller design to improve efficiency and operational capabilities. Vortex pumps are valuable in industries that handle fluids containing solids including wastewater treatment and mining due to their clog-resistant design. However, these pumps often suffer from lower efficiency compared to centrifugal pumps. To address this issue, the study employs Computational Fluid Dynamics (CFD) simulations to analyze various impeller configurations including adjustments to blade count, shape and height. The simulations reveal that a 12-blade impeller configuration significantly enhances pump performance, achieving an increase in head by 4.85 meters and efficiency by 5.46% over the baseline design. These findings provide valuable insights for the vortex pump design, emphasizing that blade configuration especially blade count and angle has a more significant effect on performance than blade height. The results encourage the use of modified impellers to enhance energy efficiency and longevity in industrial applications involving solid-laden fluids.https://cse.guilan.ac.ir/article_8777_10213f549cba68b939e82a34d9c59394.pdfUniversity of GuilanComputational Sciences and Engineering2783-25034120250318Solutions of nonlinear fractional partial differential-difference equations using the generalized-exponential-rational-function177186861810.22124/cse.2025.30132.1098ENSamiraHeidariDepartment of Mathematics, Faculty of Mathematical Sciences, University of Mazandaran, Babolsar, IranMostafaEslamiDepartment of Mathematics, Faculty of Mathematical Sciences, University of Mazandaran, Babolsar, IranHadiRezazadehFaculty of Engineering Technology, Amol University of Special Modern Technologies, Amol, IranJournal Article20250104The central topic of the present article is the investigation of solutions of nonlinear fractional partial differential models (NFPDDEs) using the generalized-exponential-rational-function (GEERAF) Method. In this regard, the jumarie's modified-riemann-liouville (JMRL) derivative has been used to convert the proposed model into ordinary differential-difference model (ODDEM). This efficient proposed method can be used as a replacement for generating novel types of solutions to NFPDDEs in Scientific issues. According to the scientific literature, our findings have not been published before in any other sources.https://cse.guilan.ac.ir/article_8618_5de46839be69421efac0525b221f538b.pdf