Computer Assisted Mechanics and Engineering Sciences最新文献

{"title":"Image Mining Based on Deep Belief Neural Network and Feature Matching Approach Using Manhattan Distance","authors":"Faiyaz Ahmad, Tanvir Ahmad","doi":"10.24423/CAMES.323","DOIUrl":"https://doi.org/10.24423/CAMES.323","url":null,"abstract":"Over the past few decades multimedia content, particularly digital images, has increased at a rapid pace, with several complex images being uploaded to various social websites such as Instagram, Facebook and Twitter. Therefore, it is difficult to search and retrieve the relevant image in seconds. Search engines retrieve images based on traditional textbased methods that depend on metadata and captions. In the last few years, a wide range of research has focused on content-based image retrieval (CBIR) based on image mining approaches. This is a challenging research area due to the ever-increasing multimedia database and other image libraries. In order to offer an effective search and retrieval, a novel CBIR system is proposed using the image mining-based deep belief neural network (IMDBN) technique. The proposed method is designed to enhance retrieval accuracy while diminishing the semantic gap between human visual understanding and image feature representation. To achieve this objective, the proposed system carries several steps like preprocessing, feature extraction, classification, and feature matching. Initially, the input database images are fed into the proposed image mining-based CBIR system, whereas colour-shape-texture (CST) feature extraction technique is applied to extract relevant feature set. The extracted features are fused and stored in the feature vector and aresubjected to the proposed IMDBN classification step to retrieve similar images in one label. Whenever a new query content is created, the most relevant images are retrieved. This, in turn, achieves 94% accuracy, which is higher than in existing approaches.","PeriodicalId":448014,"journal":{"name":"Computer Assisted Mechanics and Engineering Sciences","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124842335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Designing a Cross Trainer Using an Artificial Neural Network","authors":"S. Patra","doi":"10.24423/CAMES.322","DOIUrl":"https://doi.org/10.24423/CAMES.322","url":null,"abstract":"Cross-trainers are machines that use link mechanisms to mimic walking or running as part of workout sessions or rehabilitation systems. The simplest cross-trainer incorporates a crank-rocker or a crank-slider mechanism and provides a nearly elliptical path for foot motion. However, the natural human foot trajectories are far from being elliptical. Therefore, existing designs require modifications. Artificial neural networks are used for this purpose. Instead of trying to match the foot trajectory directly, here we tried to match different geometric properties of the area enclosed by the foot trajectory. Neural networks are trained to predict these geometric properties as outputs with the dimensions of the linkage as inputs. With the help of the same trained network, the “best-fit dimensions” were predicted for the desired trajectories.","PeriodicalId":448014,"journal":{"name":"Computer Assisted Mechanics and Engineering Sciences","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116545839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effect of Thermal Radiation on Biomagnetic Fluid Flow and Heat Transfer over an Unsteady Stretching Sheet","authors":"Md. Jahangir Alam, Md. Ghulam Murtaza, E. Tzirtzilakis, M. Ferdows","doi":"10.24423/CAMES.327","DOIUrl":"https://doi.org/10.24423/CAMES.327","url":null,"abstract":"This study examines the influence of thermal radiation on biomagnetic fluid, namely blood that passes through a two-dimensional stretching sheet in the presence of magnetic dipole. This analysis is conducted to observe the behavior of blood flow for an unsteady case, which will help in developing new solutions to treat diseases and disorders related to human body. Our model is namely biomagnetic fluid dynamics (BFD), which is consistent with two principles: ferrohydrodynamic (FHD) and magnetohydrodynamic (MHD), where blood is treated as electrically conductive. It is assumed that the implemented magnetic field is sufficiently strong to saturate the ferrofluid, and the variation of magnetization with temperature may be approximated with the aid of a function of temperature distinction. The governing partial differential equations (PDEs) converted into ordinary differential equations (ODEs) using similarity transformation and numerical results are thus obtained by using the bvp4c function technique in MATLAB software with considering applicable boundary conditions. With the help of graphs, we discuss the impact of various parameters, namely radiation parameter, unsteady parameter, permeability parameter, suction parameter, magnetic field parameter, ferromagnetic parameter, Prandtl number, velocity and thermal slip parameter on fluid (blood) flow and heat transfer in the boundary layer. The rate of heat transfer and skin friction coefficient is also computationally obtained for the requirement of this study. The fluid velocity decreases with increasing values of the magnetic parameter, ferromagnetic interaction parameter, radiation parameter whereas temperature profile increases for the unsteady parameter, Prandtl number, and permeability parameter. From the analysis, it is also observed that the skin friction coefficient decreases and the rate of heat transfer increases respectively with increasing values of the ferromagnetic interaction parameter. The most important part of the present analysis is that we neither neglect the magnetization nor electrical conductivity of the blood throughout this study. To make the results more feasible, they are compared with the data previously published in the literature and found to be in good accuracy.","PeriodicalId":448014,"journal":{"name":"Computer Assisted Mechanics and Engineering Sciences","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116757627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Statistical Comparison of Feature Selection Techniques for Solar Energy Forecasting Based on Geographical Data","authors":"Saloua El Motaki, Abdelhak El Fengour","doi":"10.24423/CAMES.324","DOIUrl":"https://doi.org/10.24423/CAMES.324","url":null,"abstract":"In recent years, solar energy forecasting has been increasingly embraced as a sustainable low-energy solution to environmental awareness. It is a subject of interest to the scientific community, and machine learning techniques have proven to be a powerful means to construct an automatic learning model for an accurate prediction. Along with the various machine learning and data mining utilities applied to solar energy prediction, the process of feature selection is becoming an ultimate requirement for improving model building efficiency. In this paper, we consider the feature selection (FS) approach potential. We provide a detailed taxonomy of various feature selection techniques and examine their usability and ability to deal with a solar energy forecasting problem, given meteorological and geographical data. We focus on filter-based, wrapper-based, and embedded-based feature selection methods. We use the reduced number of selected features, stability, and regression accuracy and compare feature selection techniques. Moreover, the experimental results demonstrate how the feature selection methods studied can considerably improve the prediction process and how the selected features vary by method, depending on the given data constraints.","PeriodicalId":448014,"journal":{"name":"Computer Assisted Mechanics and Engineering Sciences","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126604281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Metamodeling and Fluid-Structure Interaction Analysis in Multi-Objective Optimization of a Butterfly Valve","authors":"Laura Pałys, M. Mrzygłód","doi":"10.24423/CAMES.311","DOIUrl":"https://doi.org/10.24423/CAMES.311","url":null,"abstract":"Along with the increase in computing power, new possibilities for the use of parametric coupled analysis of fluid flow machines and metamodeling for many branches of industry and medicine have appeared. In this paper, the use of a new methodology for multiobjective optimization of a butterfly valve with the application of the fluid-structure interaction metamodel is presented. The optimization objective functions were to increase the value of the KV valve’s flow coefficient while reducing the disk mass. Moreover, the equivalent von Mises stress was accepted as an additional constraint. The centred composite designs were used to plan the measuring point. Full second-order polynomials, non-parametric regression, Kriging metamodeling techniques were implemented. The optimization process was carried out using the multi-objectives genetic algorithm. For each metamodel, one of the optimization candidates was selected to verify its results. The best effect was obtained using the Kriging method. Optimization allowed to improve the KV value by 37.6%. The metamodeling process allows for the coupled analysis of the fluid flow machines in a shorter time, although its main application is geometry optimization.","PeriodicalId":448014,"journal":{"name":"Computer Assisted Mechanics and Engineering Sciences","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123345749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computational Fluid Dynamics and Experimental Hydrodynamic Analysis of a Solar AUV","authors":"Ehsan Asadi Asrami, M. Moonesun, F. A. Abi","doi":"10.24423/CAMES.301","DOIUrl":"https://doi.org/10.24423/CAMES.301","url":null,"abstract":"In the present study, the effect of free surface on the hydrodynamic forces acting on the motion of an autonomous underwater vehicle (AUV) has been investigated. The AUV is powered by solar energy. Using computational fluid dynamics, the Reynolds averaged Navier Stokes (RANS) equations for the flow around the AUV are solved, and the free surface effect is simulated using the volume of fluid (VOF) two-phase flow model. For this purpose, the commercial code ANSYS FLUENT 18 was used. The results of the numerical solution are compared with experimental results of the AUV model in the surface motion in the towing tank of the Persian Gulf National Laboratory with a scale of 1:1. The experiment was performed in a fixed draft and the velocity was ranging from 0.2 m/s to 1.4 m/s (according to Reynolds number 2.4 x 105 to 1.7 x 106).","PeriodicalId":448014,"journal":{"name":"Computer Assisted Mechanics and Engineering Sciences","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126591302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Structural Design Optimization of Steel Beams and Frames with Web-Tapered Members Using the PSO-FEM Algorithm","authors":"Piotr Sych, Marek Słoński","doi":"10.24423/CAMES.284","DOIUrl":"https://doi.org/10.24423/CAMES.284","url":null,"abstract":"This paper presents an algorithm for structural design optimization of steel beams and frames with web-tapered members using the particle swarm optimization (PSO) algorithm and the finite element method (FEM). The design optimization is done in accordance with Eurocode 3 (EC 3) for the minimum mass. The proposed algorithm is more flexible and efficient than traditional design methods based on a trial and error approach. The effectiveness of the presented PSO-FEM algorithm is evaluated on examples of the size optimization of web-tapered members cross-section. The results show that the PSO-FEM algorithm is feasible and effective for finding useful designs.","PeriodicalId":448014,"journal":{"name":"Computer Assisted Mechanics and Engineering Sciences","volume":"181 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130012425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Primal- and Dual-Mixed Finite Element Models for Geometrically Nonlinear Shear-Deformable Beams – A Comparative Study","authors":"E. Bertóti","doi":"10.24423/CAMES.299","DOIUrl":"https://doi.org/10.24423/CAMES.299","url":null,"abstract":"The relationships between the system matrices of the displacement-based, a primal-mixed, a dual-mixed and a consistent primal-dual mixed finite element model for geometrically nonlinear shear-deformable beams are investigated. Employing Galerkin-type weak formulations with the lowest possible order, constant and linear, polynomial approximations, the tangent stiffness matrices and the load vectors of the elements are derived and compared to each other in their explicit forms. The main difference between the standard and the dual-mixed element can be characterized by a geometry-, material- and meshdependent constant that can serve not only as a locking indicator but also to transform the displacement-based element into a shear-locking-free dual-mixed beam element. The numerical performances of the four different elements are compared to each other through two simple model problems. The superior performance of the mixed, and especially the dual-mixed, beam elements in the nonlinear case is demonstrated, not only for the deflection, but also for the force and moment computations.","PeriodicalId":448014,"journal":{"name":"Computer Assisted Mechanics and Engineering Sciences","volume":"2092 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127465657","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Application of Affine/Interval Algebra to Determine the Time of Concrete Cover Damage in Reinforced Concrete Due to Corrosion","authors":"T. Krykowski","doi":"10.24423/CAMES.297","DOIUrl":"https://doi.org/10.24423/CAMES.297","url":null,"abstract":"This paper presents the application of affine numbers to determine the time of concrete cover cracking in reinforced concrete elements from the initiation of the reinforcement corrosion. This issue is crucial for evaluating sustainability and durability of reinforced concrete structures. The proposed general approach has been used to forecast displacements and crack propagation versus time in reinforced concrete elements subjected to corrosion tests. The affine approach equations describing changes caused by the formation of corrosion products are defined and the corresponding tensor of the volumetric strain rate is formulated. The time of cover cracking has been analysed using the Finite Element Method (FEM) and the Monte Carlo (MC) method to verify the correctness of calculations.","PeriodicalId":448014,"journal":{"name":"Computer Assisted Mechanics and Engineering Sciences","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114824075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Building Information Modeling and Building Knowledge Modeling in Project Management","authors":"N. Jasim, H. Aljumaily, I. F. Varouqa, F. Al-Zwainy","doi":"10.24423/CAMES.302","DOIUrl":"https://doi.org/10.24423/CAMES.302","url":null,"abstract":"Background: The key element for the success of construction projects in the era of technology and information is knowledge. Knowledge management in the construction sector has become a necessary and vital matter, starting with the planning stage, designing, implementing and ending with operation and maintenance stage. One of the most prominent features of knowledge in the construction sector is the building knowledge modeling (BKM). Problem: Although the design stage is considered one of the most important stages of the construction project in terms of eliciting the knowledge element, designers suffer from poor knowledge management, as well as their inability to exploit the capabilities and benefits of building information modeling (BIM), especially knowledge management. Objective: The main aim of this study is to present a conceptual model that integrates the basic principles of knowledge management with contemporary principles of BIM in the design stage and has the ability to store, classify and share the knowledge generated from past designs into future projects. Methodology: The research methodology is constructed on reviewing the pillars of the proposed conceptual model, namely: BKM parameters, BKM library, and BKM clash detection system, then a hypothetical case to prove the validity of the proposed conceptual model using Basmaya residential complex project in the Republic of Iraq is presented as a case study. Results: New four definitions  are introduced: client knowledge, context knowledge, standards knowledge and technical knowledge. The conceptual model proposed in this study has shown great ability and high efficiency in improving and developing knowledge management in the design stage of buildings and projects. In addition, the knowledge stored in the BKM library can be reused in designing new projects in the future. Novelty: The conceptual model has the ability to update constantly itself over time by sharing the knowledge of designers, suppliers and other stakeholders.","PeriodicalId":448014,"journal":{"name":"Computer Assisted Mechanics and Engineering Sciences","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125523334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}