Current Computer-aided Design Research Articles

Enhancing Myocardial Infarction Diagnosis: LSTM-based Deep Learning Approach Integrating Echocardiographic Wall Motion Analysis

PurposeOwing to the increased mortality of heart diseases worldwide, especially myocardial infarction (MI), early detection is essential for improved diagnosis and treatment. The main purpose of this study is to develop a myocardial infarction detection method that combines deep learning and image processing, focusing on abnormalities in left ventricular (LV) wall motion.MethodsThe proposed method primarily uses the LV wall motion movement as a feature to train an LSTM network for MI detection. LV wall motion annotated by expert cardiologists was used as the ground truth. Accuracy, sensitivity, specificity, and area under the curve (AUC) were used to evaluate model performance. The proposed method primarily uses LV wall motion as a feature, combined with LV size and image pixels, to improve diagnostic accuracy over existing computer-aided design (CAD) systems.ResultsThe LSTM model achieved the highest diagnostic performance when trained on a combination of LV wall motion, LV size, and image pixel features with an accuracy of 95%, sensitivity of 96%, specificity of 94%, and an AUC value of 0.98. The LSTM model significantly outperformed models trained on individual feature sets or conventional machine learning algorithms. The inclusion of LV wall motion analysis improved accuracy by 10% compared to using only LV size and pixel data.ConclusionOur MI diagnosis system uses echocardiographic image analysis and LSTM-based deep learning to accurately detect LV wall motion issues related to MI. Compared with current CAD systems, the inclusion of LV wall motion analysis significantly improves diagnosis accuracy. The proposed system can help physicians detect MI early, thereby accelerating treatment and improving patient outcomes.

CNN-O-ELMNet: Optimized Lightweight and Generalized Model for Lung Disease Classification and Severity Assessment.

The high burden of lung diseases on healthcare necessitates effective detection methods. Current Computer-aided design (CAD) systems are limited by their focus on specific diseases and computationally demanding deep learning models. To overcome these challenges, we introduce CNN-O-ELMNet, a lightweight classification model designed to efficiently detect various lung diseases, surpassing the limitations of disease-specific CAD systems and the complexity of deep learning models. This model combines a convolutional neural network for deep feature extraction with an optimized extreme learning machine, utilizing the imperialistic competitive algorithm for enhanced predictions. We then evaluated the effectiveness of CNN-O-ELMNet using benchmark datasets for lung diseases: distinguishing pneumothorax vs. non-pneumothorax, tuberculosis vs. normal, and lung cancer vs. healthy cases. Our findings demonstrate that CNN-O-ELMNet significantly outperformed (p < 0.05) state-of-the-art methods in binary classifications for tuberculosis and cancer, achieving accuracies of 97.85% and 97.70%, respectively, while maintaining low computational complexity with only 2481 trainable parameters. We also extended the model to categorize lung disease severity based on Brixia scores. Achieving a 96.20% accuracy in multi-class assessment for mild, moderate, and severe cases, makes it suitable for deployment in lightweight healthcare devices.

Exploring the rate of adoption and implementation depth of building information modeling (BIM): A case of Kuwait

The Architecture, Engineering, and Construction (AEC) industry in the State of Kuwait has witnessed a decline in efficiency with most projects going above budget and past project deadlines. Building Information Modeling (BIM) creates a collaborative common-data working environment between various stakeholders leading to improved productivity and efficiency while also minimizing technical challenges, and reducing design errors. Moreover, adding the concept of time to the model (4D BIM) for the purposes of planning and scheduling further optimizes inter-disciplinary collaboration. The first phase of this research aims to evaluate current BIM adoption rates and implementation depth in Kuwait through a survey distributed to organizations in the Union of Kuwait Engineering Offices and Consultant Houses. The results indicated that the rate of BIM adoption, represented by whether or not organizations have used BIM in previous/current projects is relatively high. Implementation depth, represented by the percentage of projects for which BIM is being used, is concluded to be low. In terms of willingness to adopt BIM, most organizations use and are considering using BIM as a visualization tool. The second phase aims to examine the applicability of generating predefined process templates for Tract Houses in the northwest Sulibikhat area constructed by the Public Authority of Housing Welfare (PAHW) used for 4D BIM. The Process Pattern Recognition approach is applied to a BIM-based construction schedule where the schedule is extracted, decomposed, processed, and filtered. Relevant and potentially relevant processes are identified and verified leading to defined process templates. This research contributes to the AEC industry by aiding in transitioning from current Computer-Aided-Design (CAD) practices to BIM technology.

A decision-support method for multi-parameter editing of parametric CAD models

Parametric modeling is a computer-aided design (CAD) paradigm where a design can be created by defining geometric constraints with parameters. In design change as well as design optimization, the design is often edited by modifying the values of relevant parameters. Without guidance on allowable parameter ranges that can guarantee the intrinsic solvability of the geometric constraint system, the user could assign improper values to the model’s parameters, which would further lead to a failure in model updating. However, current commercial CAD systems provide little support on such guidance. Existing methods, though able to compute allowable ranges for individual parameters, face difficulties in handling multi-parameter situations. To solve this problem, a systematic method is proposed, supporting decision-making in multi-parameter model editing by computing allowable parameter ranges. In the method, a set of variable parameters from the geometric constraint system are first selected by the user; these variable parameters are to be sequentially edited within several editing operations. Before each editing operation, 1D allowable ranges of the variable parameters are computed. By editing parameter values within the provided ranges, the solvability of the geometric constraint system can be guaranteed. The effectiveness and efficiency of the proposed approach is verified by several experimental results.

Intuitive approach for design of inner structure by mimicking magnetic effect

Abstract Three-dimensional (3D) printers enable the realization of parts with complex shapes, particularly parts with an internal structure as well as an external shape. They are beginning to be used in real production as well as for prototyping. Because 3D printers allow shapes for parts that could not be imagined when conventional machining processes were the only fabrication methods, designers need to design porous parts with minimum weights that can maintain the required load-bearing capability without concerns about the realization of those parts. However, designers cannot design the internal structure of the parts using the current computer-aided design systems as freely as they can design the external shape. Therefore, in this paper, an intuitive design tool is proposed for users to interactively design an internal structure inside given external shape. To create a porous structure inside given closed volume, we aimed to generate a honeycomb-like structure comprising cells whose size and crowdedness can be intuitively manipulated by a designer. Thus, fine cells exist in certain regions, while coarse cells exist in the remaining regions according to the design. To realize this aim, the phenomenon in which more iron particles are attracted near a magnet and fewer are attracted further away from the magnet is imitated. More and finer honeycomb-like cells are attracted near a magnet located on the external surface of the closed volume. The designer can add magnets and move them on the external surface until the desired internal honeycomb-like structure is obtained.

Surgical Guides and Prebent Titanium Improve the Planning for the Treatment of Dentofacial Deformities Secondary to Condylar Osteochondroma.

To investigate current Computer-Aided Design and Computer-Aided Manufacturing (CAD/CAM) technologies applied in the treatment of dentofacial deformities secondary to condylar osteochondroma and introduce a modified method with additional pre-bent titanium miniplates to improve the accuracy of operation. Literature review about the application of CAD/CAM in the treatment of condylar osteochondroma and secondary dentofacial deformities was conducted. And 8 patients with condylar osteochondroma and secondary dentofacial deformities were treated by the CAD/CAM cutting and drilling surgical guides as well as pre-bent titanium miniplates. Pre- and post-operative 3D-cephalometric measurement were recorded and the difference between virtual simulation and postoperative modeling images was measured. Follow-up and radiographic examinations were performed. A total of 17 studies (including 216 patients) about the application of CAD/CAM in the treatment of dentofacial deformities secondary to condylar osteochondroma have been reported since 2010, including the 8 present patients. In our study, all patients were satisfied with the surgical outcome, without obvious relapse or evidence of temporomandibular joint disorder or other complications during follow-up; all patients avoided condylar reconstruction and sagittal split of ramus osteotomy on the ipsilateral mandible side. Comparison between simulated plans and actual postoperative outcomes showed surgical simulation plan was accurately transferred to the actual surgery. The application of CAD/CAM cutting and drilling guides as well as pre-bent titanium plates could achieve more accurate and favorable outcomes, improving the clinical planning and surgical execution for patients with condylar osteochondroma and secondary dentofacial deformities.

Wear behavior of current computer-aided design and computer-aided manufacturing composites and reinforced high performance polymers: An in vitro study.

To analyze the wear rate of computer-aided design and computer-aided manufacturing (CAD/CAM) composites, polyetheretherketones and glass ceramics. Our study groups were prepared from two different resin-based composites (Brillant Crios, Cerasmart), a glass ceramic (IPS Emax CAD) and reinforced polyetheretherketone (BioHPP) material (n=10). Premolar teeth were used as antagonists. The specimens, which were subjected to two body wear tests (240,000 cycles, 1.2Hz, 50N) in the chewing simulator, were scanned with a 3D laser scanner both before and after the wear test. Volume loss and wear depth were determined by means of the obtained images software program. The wear pattern was examined by scanning electron microscopy. Kruskal Wallis test served for analyzing. The least volume loss and wear depth were seen in the polyetheretherketone material (0.06 ± 0.04 mm3 , 0.02 ± 0.01 mm), while the maximum volume loss was seen in the groups containing resin-based composite. (p=0.05). The volume loss value in glass ceramics is between CAD/CAM composites and polyetheretherketone. The behavior of polyetheretherketone against enamel was different from glass ceramics and composite materials in terms of the amount of wear. Polyetheretheketone can be considered as an alternative to other chairside materials in terms of wear resistance.

Shipbuilding 3D CAD Tools as an Integrated Solution from Concept to Product

In the naval design process, there is still no consensus on the use of 3D CAD (Computer Aided Design) systems in the early stages of design. However, the integration capability of different modules is currently making their incorporation in the initial stages more appealing. The objective of this paper is to study the early stages of design as part of the whole process and to demonstrate the convenience of using a single 3D tool during the whole project. Therefore, its impact on the whole design process will be analysed by considering the basic and early design capabilities of current CAD systems, reviewing how the main naval architecture and marine engineering demands match the features and what is the solution provided by the CAD for each case. The methodology presented offers advantages from a technical, economic and time point of view.

Evaluating Protein Tyrosine Phosphatase 1B Inhibitory Activity of Bioactive Compounds from Momordica charantia for Diabetes Treatment Type 2 by using Molecular Docking Method

Evaluating Protein Tyrosine Phosphatase 1B Inhibitory Activity of Bioactive Compounds from Momordica charantia for Diabetes Treatment Type 2 by using Molecular Docking Method

Wear resistance of crowns made from different CAM/CAD materials

ObjectivesThe aim of this laboratory study was to evaluate the wear resistance of crowns made from current computer-aided design and computer-aided manufacture (CAD/CAM) materials. In addition, the abrasion of the steatite antagonist against these materials was compared. MethodsIdentically shaped crowns of lithium disilicate, zirconia-reinforced lithium disilicate and a polymer-infiltrated ceramic network (PICN) were fabricated with an occlusal thickness of 1.5mm and a lateral wall thickness of 1.2mm (n=8). The crowns were cemented with a dual-polymerizing luting resin on composite resin dies. Using spherical steatite antagonists, all specimens were loaded with 49N for 1,200,000 cycles in a mastication simulator with additional thermocycling. After 120,000, 240,000, 480,000, 960,000, and 1,200,000 cycles, precision impressions were made and investigated with a laser scanning microscope. The vertical and volume substance loss was measured. Additionally, the substance loss of the antagonists was evaluated after 1,200,000 loading cycles. ResultsNo significant difference (p>0.05) was found in the median volume loss of the test materials after 1,200,000 cycles (lithium disilicate: 0.405mm3, PICN: 0.362mm3, zirconia-reinforced lithium disilicate: 0.340mm3). The vertical substance loss of PICN (157μm) was significantly lower (p≤0.05) than that of lithium disilicate (201μm) and zirconia reinforced lithium disilicate (191μm). However, the substance loss of steatite against zirconia-reinforced lithium disilicate (0.191mm3) was significantly lower (p≤0.05) than against lithium disilicate (0.296mm3) and PICN (0.531mm3). SignificanceAll three CAD/CAM materials showed wear resistance that seems appropriate for clinical application. Also, the abrasion of the antagonist looks promising.

Withdrawal Notice: Design and Synthesis of a Novel Gabapentin- Phosphotidylcholine Conjugate for Targeting to Phospholipase A2 Enzyme through Nanostructured Lipid Carrier

It is a condition of publication that manuscripts submitted to this journal have not been published and will not be simultaneously submitted or published elsewhere. Furthermore, any data, illustration, structure or table that has been published elsewhere must be reported, and copyright permission for reproduction must be obtained. Plagiarism is strictly forbidden, and by submitting the article for publication the authors agree that the publishers have the legal right to take appropriate action against the authors, if plagiarism or fabricated information is discovered. By submitting a manuscript, the authors agree that the copyright of their article is transferred to the publishers if and when the article is accepted for publication.

Comparison between Occlusal Errors of Single Posterior Crowns Adjusted Using Patient Specific Motion or Conventional Methods

Recently, digital technology has been used in dentistry to enhance accuracy and to reduce operative time. Due to advances in digital technology, the integration of individual mandibular motion into the mapping of the occlusal surface is being attempted. The Patient Specific Motion (PSM) is one such method. However, it is not clear whether the occlusal design that is adjusted using PSM could clinically show reduced occlusal error compared to conventional methods based on static occlusion. In this clinical comparative study including fifteen patients with a single posterior zirconia crown treatment, the occlusal surface after a clinical adjustment was compared to no adjustment (NA; design based on static occlusion), PSM (adjusted using PSM), and adjustment using a semi-adjustable articulator (SA) for the assessment of occlusal error. The root mean square (RMS; μm), average deviation value (±AVG; μm), and proportion inside the tolerance (in Tol; %) were calculated using the entire, subdivided occlusal surface and the out of tolerance area. Using a one-way ANOVA, the RMS and +AVG from the out of tolerance area showed a statistical difference between PSM (202.3 ± 39.8 for RMS, 173.1 ± 31.3 for +AVG) and NA (257.0 ± 73.9 for RMS, 210.9 ± 48.6 for +AVG). For the entire and subdivided occlusal surfaces, there were no significant differences. In the color-coded map analysis, PSM demonstrated a reduced occlusal error compared to NA. In conclusion, adjustment occlusal design using PSM is a simple and effective method for reducing occlusal errors that are difficult to identify in a current computer-aided design (CAD) workflow with static occlusion.

Integration of 3D printing in computer-aided design and engineering course

Engineering students at an undergraduate level typically learn the design aspect and concept through lectures and practical sessions using computeraided software. However, the current computer-aided design and engineering (CAD/CAE) course did not expose the students to apply and relate the latest advanced technologies to solve global issues, for instance as listed in the United Nations Sustainable Development Goals (UN SDG). Therefore, an improved CAD/CAE course taken by the students of the Electrical and Electronic Engineering Programme in Universiti Kebangsaan Malaysia integrates 3D printing and conduct their project based on UN SDG themes. A total of 22 projects was produced, which involves both mechanical and electrical design with some of the physical models were 3D printed. Thus, students able to strengthen their understanding of the design concept through the integration of 3D printing and simultaneously aware of the current global issues.

Parametric modeling method for integrated design and manufacturing of radial compressor impeller

Radial compressor impeller (RCI) manufacturing is moving toward to improve competitiveness through smart manufacturing. Although current CAD (computer-aided design) and CAM (computer-aided manufacturing) techniques provide multiple tools to construct and optimize complicated geometries of RCI, an adjustment of blade shape often leads to nonparametric geometric reconstruction. As the key geometric elements in RCI, set of streamlines (SSL) and meridional section (MS) play vital roles in modeling and aerodynamic optimization. This paper presents a novel approach for automatic extraction of SSL and MS from a RCI 3D model or workpiece. Furthermore, the presented method can interactively construct a parameterized RCI platform, which inputs and outputs the presented RCI parameters to existing CFD and CAM systems rapidly and effectively. An integrated acquisition is employed. The straight generatrix vectors (SGVs) are identified and their boundary points are defined. After the uniform partition of SGV segments, the sequent equant points along spanwise direction are packaged to fit SSL. To manipulate the smoothness and approximation, a double-fitting method is performed to generate SSL. A parameterized system for extracting SSL and modeling RCI is developed. The validities of the presented method in different systems are demonstrated. Furthermore, the presented method breaks conventional RCI development procedure and shortens RCI product cycles, which is desirable and significative for integrated RCI design and manufacturing.

Integrating Materials Model-Based Definitions into Design, Manufacturing, and Sustainment: A Digital Twin Demonstration of Incorporating Residual Stresses in the Lifecycle Analysis of a Turbine Disk

Abstract Model-based definitions (MBDs) aim to capture both geometric and non-geometric data in digital product definitions using 3D computer-aided design (CAD) models, as a form of product definition baseline, to disseminate product information across different stages of the lifecycle. MBDs can potentially eliminate error-prone information exchange associated with traditional paper-based drawings and improve the fidelity of component details, captured using 3D CAD models. A component’s behavior during its lifecycle stages influences its downstream performance, and if included within the MBD of a part, could be used to forecast performance upfront during the design and explore newer designs to enhance performance. However, current CAD capabilities limit associating behavioral information with the component’s shape definition. This paper presents a CAD-based tool to store and retrieve metadata using point objects within a CAD model, creating linkages to spatial locations within the component. The tool is illustrated for storage and retrieval of bulk residual stresses developed during the manufacturing of a turbine disk acquired from process modeling and characterization. Further, variations in residual stress distribution owing to process model uncertainties have been captured as separate instances of the disk’s CAD models to represent part-to-part variability as an analogy to track individual serialized components for digital twins. The propagation of varying residual stresses from these CAD models within the damage tolerance analysis performed at critical locations in the disk has been demonstrated. The combination of geometric and non-geometric data inside the MBD, via storage of spatial and feature varying information, presents opportunities to create digital twin(s) of actual component(s).

Constructing assembly design model capable of capturing and sharing semantic dynamic motion information in heterogeneous CAD systems

Over the last decades, collaborative assembly design has received much attention, which has provided fruitful results in terms of data models, knowledge-based, and top-down geometric modeling approaches, to name a few. Particularly, researchers have focused their efforts towards assembly relationships within product models, but have limited the scope to static assembly geometric description as currently stated in computer-aided design (CAD) systems. A disruptive vision is assumed in this research work, arguing that the assembly design itself presents a dynamic nature via, especially, dynamic motion. Such a paradigm shift requires an appropriate logical and semantic foundation to augment current CAD systems and data models’ capabilities with the capture of dynamic phenomena such as assembly motions and kinematic behaviors. Traditional CAD systems nowadays can handle the kinematics-related motion-related information; however, the interoperation of this motion-related information from one CAD system to the other is still a limitation of the interoperability standards. To tackle this research challenge, this paper aims at defining an original framework built upon a formal ontology to capture and share dynamic assembly motion among heterogeneous CAD systems. The formal ontology uses spatiotemporal mereotopology, which serves as a theoretical backbone to qualitatively describe the dynamic behavior of a product. This theory addresses the qualitative description of the temporal dimension over the spatial dimension of 3D objects. The proposed ontology is then enhanced to maintain semantic continuity of the spatial and temporal aspects embedded in assembly design ontology models. Built with a Web Ontology Language (OWL) data structure to interact with a CAD system and a motion visualization application, the ontology ensures the dynamic motion information capturing and sharing. SWRL (Semantic Web Rule Language) is utilized to show the semantic reasoning among the moving and non-moving parts of the product assembly. As a result, a semantic articulation ensuring flexibility and interoperability as a competitive industrial edge is demonstrated with proof of concept to be effective in a collaborative assembly design environment.

Problems of Creation and Usage of 3D Model of Structures and Theirs Possible Solution

This article describes problems that occur when creating three-dimensional (3D) building models. The first problem is geometric accuracy; the next is the quality of visualization of the resulting model. The main cause of this situation is that current Computer-Aided Design (CAD) software does not have sufficient means to precision mapping the measured data of a given object in field. Therefore the process of 3D model creation is mainly a relatively high proportion of manual work when connecting individual points, approximating curves and surfaces, or laying textures on surfaces. In some cases, it is necessary to generalize the model in the CAD system, which degrades the accuracy and quality of field data. The article analyzes these problems and then recommends several variants for their solution. There are described two basic methods: using topological codes in the list of coordinates points and creating new special CAD features while using Python scripts. These problems are demonstrated on examples of 3D models in practice. These are mainly historical buildings in different locations and different designs (brick or wooden structures). These are four sacral buildings in the Czech Republic (CR): the church of saints Johns of Brno-Bystrc, the Church of St. Paraskiva in Blansko, further the Strejc’s Church in Židlochovice, and Church of St. Peter in Alcantara in Karviná city. All of the buildings were geodetically surveyed by terrestrial method while using total station. The 3D model was created in both cases in the program AUTOCAD v. 18 and MicroStation.

Research on Design Strategies of Cognitive Training System Based on SCD Elderly Behavioral and Psychological Characteristics

Alzheimer’s disease (hereinafter referred to as AD) has become a major global health problem for the elderly. Combining with the current computer-aided design system design for prevention and training of Alzheimer’s disease is one of the important ways to solve this problem. This study aims at the early subjective cognitive decline of Alzheimer’s disease (hereinafter referred to as SCD) . Through investigation and research, the behavior and psychological characteristics of SCD elderly are sorted out, and the main functions of cognitive training system are located. The main functions, interactions, colors and layout of the current cognitive system are summarized by analyzing the existing cognitive training system, and compared with the research results, a more reasonable system function, interaction mode, interface color and layout are determined. Therefore, the cognitive training system design strategy based on the behavioral and psychological characteristics of SCD elderly is summarized.

A New Hybrid Differential Evolution with Gradient Search for Level Set Topology Optimization

Topology optimization is an effective structural optimization concept for optimal design of engineering structures. However, it has many difficulties due to high number of design variables and complex problems same as compliant mechanisms and crashworthiness. Conventional methods for topology optimization does not have enough adaptability with current computer aided design (CAD) softwares and they are not powerful in solving difficult optimization problems. Level set which is a novel boundary tracking method had been recently used to solve problems in conventional methods. This paper is dedicated to propose a new hybrid method based on differential evolution (DE) and globally convergent method of moving asymptotes (GCMMA) to use both gradient direction of GCMMA and excellent exploration of DE. The method has been validated in familiar benchmark problems in compliance minimization.

AN INTEGRATED SYSTEM FOR PROCESS-FIXTURE LAYOUT DESIGN OPTIMISATION FOR CUBICAL PARTS

In this article, an integrated computer-assisted process-planning and computer-assisted fixture layout planning system is presented for the automatic generation of process and fixture maps. The part feature model is created using various algorithms and the geometric reasoning approach. The feature-based methodology based on the machining database is then applied for the generation of process maps. The setup scheme algorithm allocates each feature to a definite setup based on its location. The part geometric database and setup plan aids the fixture layout planning process. During fixture layout planning, the standard fixture rules are applied to determine the locating arrangement and feasible datum along with the suitable positions using a fixture database for initial fixture layout planning data. Visual C++ is used to implement the proposed methodology because it interacts with current computer-aided design software. Then a case study is presented to develop an initial fixture layout. Afterwards, the ANSYS parametric design language optimisation tool is applied to automatically optimise locator and clamp positions that yield minimum workpiece deformation. At the end, finite element analysis results depicting deformation magnitudes are presented.