Machine learning (ML) has proved useful across a wide range of applications in the very-large-scale integration computer-aided design (VLSI CAD) domain. To avoid overestimating ML models' generalization capabilities for real-world deployments, best ...

Machine Learning (ML) models sometimes make inaccurate predictions for the routability of field-programmable gate array (FPGA) circuit designs. This risks time wasted attempting to route an unroutable design or the premature termination of a routable ...

The last few decades have witnessed exponential rise in leprosy also called Hansen diseases globally. Being chronic and infectious in nature, eradicating leprosy has remained a challenge. Despite a few recent efforts employing vision computing-...

The benefits of integrated design using the Model Based System Engineering (MBSE) approach in the design process of mechatronic systems have gradually become apparent. The automatic generation of simulation models and geometric models based on ...

Lattice structures have been widely used in applications due to their superior mechanical properties. To fabricate such structures, a geometric processing step called triangulation is often employed to transform them into the STL format before ...

Display Omitted

• A meta-mesh representation scheme of lattice structures that is lightweight and reusable to attain multiresolution triangulation.
• A warp-centric GPU meta-meshing algorithm that can handle billion-scale lattice structures in minutes.

We present an algorithm for fast generation of quasi-uniform and variable-spacing nodes on domains whose boundaries are represented as computer-aided design (CAD) models, more specifically non-uniform rational B-splines (NURBS). This new algorithm ...

This research involves interdisciplinary scientific areas to describe a digital simulation multi-system of indoor unhealthy emissions in a multi-simulation environment in order to record, manage, evaluate and communicate the health status of a ...

Coarse-grained reconfigurable arrays (CGRAs) are programmable hardware platforms that are a means of realizing application accelerators. A CGRA is a 2D array of configurable processing elements (PEs), that connect to one another through programmable ...

This study proposes a non-invasive method for predicting Coronary Artery Disease (CAD) using iris analysis, patient data, and Machine Learning (ML), primarily with iris images. It involved 281 participants, comprising 155 CAD patients and 126 non-...

• Novel method integrates iris images & biodemographic data for CAD prediction.
• Comparative analysis of three data scenarios reveals insights.
• Comprehensive evaluation of ML techniques per scenario enhances CAD detection.
• ...

Reverse engineering Computer-Aided Design (CAD) models based on the original geometry is a valuable and challenging research problem that has numerous applications across various tasks. However, previous approaches have often relied on excessive ...

• We develop a systematic CAD reconstruction pipeline for reverse engineering CAD modeling, which ensures faithful CAD reconstruction with high precision and significantly reduces the reliance on manual or interactive operations.
• We ...

This study aims to address the need for reliable diagnosis of coronary artery disease (CAD) using artificial intelligence (AI) models. Despite the progress made in mitigating opacity with explainable AI (XAI) and uncertainty quantification (UQ), ...

Automated computer-aided diagnosis (CAD) has become an essential approach in the early detection of health issues. One of the significant benefits of this approach is high accuracy and low computational complexity without sacrificing model ...

• Automated detection of epilepsy using EEG signals is provided.
• Geometry invariants multi-channel fusion is utilized.
• Reduced processing times making the analysis more efficient and feasible for real-time applications.
• Method ...

Exploiting the capability of deep learning-based techniques, this research addresses an important and relevant problem on how to cost effectively detect thyroid cancer. In recent decades, there has been a significant increase in the incidence of ...

As one of the core competitiveness of the product, the appearance should be designed to cater to the various personalized needs of consumers and adapt to the rapid iterations of the product. To improve the design efficiency, reduce the design ...

The Coronavirus Disease (COVID-19) caused a lot of mortality. The high mortality rate occurred because of the physicians’ wrong or late identification of COVID-19 severity. So, developing Computer-Aided Design (CAD) systems using Artificial ...

• This paper proposes a CAD system for COVID-19 severity prediction.
• The proposed system uses a two-stage neural network architecture.
• The proposed system consists of two phases: feature extraction and severity identification.
• A ...

The preoperative evaluation of myometrial tumors is essential to avoid delayed treatment and to establish the appropriate surgical approach. Specifically, the differential diagnosis of leiomyosarcoma (LMS) is particularly challenging due to the ...

Display Omitted

• Leiomyosarcoma (LMS) diagnosis is complex due to clinical overlap between fibroids and LMS and class imbalance.
• A machine learning (ML) methodology is proposed for preoperative LMS vs. leiomyomas diagnosis.
• XAI is embedded to ...

Creativity, the process of creating something new and valuable, benefits children by improving their skills and development, encouraging interaction and engagement, and enabling the generation and expression of novel ideas. In recent years, ...

This publication presents a novel numerical avenue for the assessment of masonry structures. To circumvent the labor-intensive finite element method modeling and pre-processing step, the isogeometric analysis is enhanced within this contribution ...

• Advancing the isogeometric analysis to cope with shell-based masonry structures.
• Proposing a damage model in the context of the isogeometric analysis.
• Newly proposed element length regularization technique for NURBS.
• ...

Software engineering refers to the science of analysing programme operation. Software engineers use reverse engineering to create code from a previously created model. Software engineers utilise the abstract-present model to transform the sequence model ...

Thanks to the enhanced computational capacity of modern computers, even sophisticated analog/radio frequency (RF) circuit sizing problems can be solved via electronic design automation (EDA) tools. Recently, several analog/RF circuit optimization ...