Background: Recent advancements in brachytherapy necessitate precise dose calculations, transitioning from the traditional TG43 planning methods to the more sophisticated TG186 recommendations. However, the availabili...
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Background: Recent advancements in brachytherapy necessitate precise dose calculations, transitioning from the traditional TG43 planning methods to the more sophisticated TG186 recommendations. However, the availability of accessible and efficient Monte Carlo (MC) codes capable of interfacing with clinical data for these advanced calculations remains limited. Purpose: This study presents and validates eb_gui, a graphical user interface designed to seamlessly integrate DICOM clinical data with egs_brachy, a fast MC dose calculation algorithm tailored for brachytherapy applications. Methods: The egs_brachy graphical user interface (eb_gui) was developed using C++ with the Qt5 framework. Five benchmarking scenarios were employed to validate the use of eb_gui. Simulations were compared against three non-clinical test cases developed by the joint Working Group on Model-Based Dose Calculations (WG-MBDC), assessing local and global dose difference ratios with reference MC data. An interstitial HDR breast case and a low dose rate (LDR) prostate case were also analyzed, evaluating dose difference histograms, dose ratio maps, dose-volume histograms, and extracted dose metrics. Results: For the three WG-MBDCA test cases, over 95% of evaluated voxels showed local dose differences of less than +/- 0.40%, with all voxels demonstrating global dose differences within +/- 0.02%. In the interstitial HDR breast case, over 95% of voxels exhibited global difference ratios within [-0.31%, +0.39%] relative to the reference dataset, while local difference ratios varied due to simulation conditions. Results of the LDR prostate test case simulations underscored the eb_gui's comprehensive capabilities and accuracy. Conclusion: eb_gui successfully bridges clinical data with egs_brachy MC simulations, facilitating advanced, patient-specific dose evaluations in accordance with TG186 recommendations. By releasing eb_gui as open-source software on GitHub, this study promotes widespread adoption wi
We present MADGUI, Multi-Application Design graphical user interface (GUI) using Bayesian Optimization and prediction model for data analysis and optimize process or composition. Its strength is its user-friendly desi...
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We present MADGUI, Multi-Application Design graphical user interface (GUI) using Bayesian Optimization and prediction model for data analysis and optimize process or composition. Its strength is its user-friendly design, which requires no programming knowledge. It is built using the Streamlit library in Python and is divided into three parts, allowing users to select various parameters and fill csv/xlsx files without any coding required. Overall, MADGUI is designed as an optimal experiment design platform with active machine learning, which accelerates the discovery of optimal solutions and provides an intuitive GUI for users with no experience in coding, machine learning, or optimization.
In this study, the flexural capacity of reinforced concrete (RC) beams strengthened with fiber-reinforced cementitious matrices (FRCM) was computed using machine learning (ML) algorithms including: (i) adaptive neuro-...
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In this study, the flexural capacity of reinforced concrete (RC) beams strengthened with fiber-reinforced cementitious matrices (FRCM) was computed using machine learning (ML) algorithms including: (i) adaptive neuro-fuzzy inference system (ANFIS), (ii) artificial neural network (ANN), and (iii) extreme gradient boosting (XGBoost). A total of 198 pertinent experimental datasets were compiled and included six types of FRCM composites (PBO, carbon, glass, basalt, coated carbon, and combined glass and carbon). The considered input parameters comprise the beam cross-sectional details, area of tensile and compressive steel reinforcement, mechanical properties of FRCM composite, and concrete compressive strength. To assess the reliability of ML models, four existing analytical models and one established standard guideline were used for comparison. Moreover, six statistical metrics were employed, along with an overfitting analysis, to determine the best-fitting model. graphical fitting of the optimal model was depicted using the Taylor diagram, violin plot, as well as multi-panel histogram plot. Based on both graphical and statistical metrics, the XGBoost model attained the highest precision compared to all analytical and ML-based models. The correlation coefficient and MAPE of the XGBoost model were 0.9977% and 2.98%, respectively. To interpret the influence of individual parameters on the flexural strength of the FRCM-strengthened RC beams, a feature importance plot based on SHAP explanatory theory was deployed. Ultimately, a user-friendly graphicalinterface was developed and made accessible to aid practicing engineers in estimating the flexural strength of FRCM-strengthened RC beams, offering an effective alternative to complex design procedures.
Designing descriptors for materials and catalysts within machine learning is a complex process. In particular, material compositions can be represented using information from the periodic table. Additionally, feature ...
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Designing descriptors for materials and catalysts within machine learning is a complex process. In particular, material compositions can be represented using information from the periodic table. Additionally, feature engineering and feature selection add further complexity, requiring significant programming skills and knowledge of machine learning. To address this challenge, a web-based graphical user interface (GUI) for feature assignment, feature engineering, and feature selection has been developed. This GUI is designed to facilitate materials and catalysts design using machine learning, without the need for advanced programming or machine learning expertise.
Convolutional Neural Networks have been widely applied in fault diagnosis tasks of mechanical systems due to their strong feature extraction and classification capabilities. However, they have limitations in handling ...
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Convolutional Neural Networks have been widely applied in fault diagnosis tasks of mechanical systems due to their strong feature extraction and classification capabilities. However, they have limitations in handling global context information. Vision Transformers, by leveraging self-attention mechanisms to capture global dependencies, have shown excellent performance in many visual tasks, but often come with high computational costs. Therefore, this paper proposes a lightweight and efficient intelligent fault diagnosis method based on the fusion of Convolutional Network and Vision Transformer features (FCNVT). This method combines the local feature extraction capability of CNNs with the global dependency capturing ability of ViTs, while maintaining computational efficiency. Random overlapping sampling (ROS) techniques are used to preprocess signals, generating two-dimensional synchronized wavelet transform (SWT) images as inputs to the network. Experimental verification has shown that the proposed method achieves up to 100% classification accuracy, with the model having 7 million parameters and a computational cost of only 0.28 G, outperforming other state-of-the-art methods. Finally, a graphical user interface (GUI)-based mechanical equipment fault detection system was developed using this method, which holds positive implications for advancing the practical application of intelligent fault diagnosis in mechanical equipment.
SDTrimSP is a popular simulation program to compute several effects of the interaction between an impinging ion and a solid, such as ion implantation ranges, damage formation or sputtering of surface atoms. We now int...
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SDTrimSP is a popular simulation program to compute several effects of the interaction between an impinging ion and a solid, such as ion implantation ranges, damage formation or sputtering of surface atoms. We now introduce a graphical user interface for SDTrimSP to make its operation more accessible for a broad group of users. It is written as a separate Python program and is not restricted to any specific operating system. The interface allows a quick and easy start as well as the direct evaluation of SDTrimSP simulations. Its capabilities are demonstrated here in the form of several example cases, including the dynamic simulations with SDTrimSP, where ion-induced target changes are taken into account. The presented graphical user interface is made freely available to support a large number of users in performing simulations of ion-solid interaction.
The SHETRAN physically-based distributed rainfall-runoff modelling system gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. It is therefore a powerful to...
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The SHETRAN physically-based distributed rainfall-runoff modelling system gives detailed simulations in time and space of water flow and sediment and solute transport in river catchments. It is therefore a powerful tool for studying hydrological and environmental impacts associated with land-use and climate change. A graphical user interface (GUI) has been developed that allows a catchment data set to be set up quickly using a minimum of information. The GUI has an algorithm for the automatic generation of river channel networks from a DEM and has access to libraries of soil and vegetation parameters. (C) 2009 Elsevier Ltd. All rights reserved.
The simulation of the water distribution network (WDN) can be carried out either by demand-driven analysis (DDA) or by pressure driven analysis (PDA). DDA fails to present the real scenario when a pressure deficiency ...
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The simulation of the water distribution network (WDN) can be carried out either by demand-driven analysis (DDA) or by pressure driven analysis (PDA). DDA fails to present the real scenario when a pressure deficiency problem happened. On the other hand, in PDA, a relation between the available pressure and the actual demand exists. Many researchers have tried to model PDA using different methodologies by changing the source code of EPANET, adding artificial elements (AE) to the network, or changing demand nodes (DN) to emitters. Recent softwares are available to model the network in normal conditions using DDA;however, solving PDA's automated process is not available in any available software. This paper describes the development of a MATLAB-based program, which simulates the WDN in normal and abnormal situations. The developed program uses different existing PDA methods that add artificial elements to the network, which helps the decision-maker evaluate the network in different failure scenarios.
Cardiovascular diseases are among the most lethal diseases globally. Reconstruction of the electrical activity of the heart in a non-invasive way is crucial for the diagnosis and treatment of these diseases. Electroca...
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ISBN:
(纸本)9798350343557
Cardiovascular diseases are among the most lethal diseases globally. Reconstruction of the electrical activity of the heart in a non-invasive way is crucial for the diagnosis and treatment of these diseases. Electrocardiographic imaging (ECGI) is an effective imaging modality to obtain the electrical potential distribution of the heart and the distribution can be further processed to extract information about the propagation patterns and the pacing location. In this study, we develop a graphical user interface to compute activation time maps from cardiac signals and find the pacing location in a fast way and open-source it and make it available for other researchers in the field on https://***/METUHRL/AT-GUI.
In the frame of naval forces, coordination means have always been in constant evolution through centuries, from marine flags to radio communications and more recently with tactical data links. Nowadays a naval ship is...
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ISBN:
(纸本)9781538648766
In the frame of naval forces, coordination means have always been in constant evolution through centuries, from marine flags to radio communications and more recently with tactical data links. Nowadays a naval ship is being considered as part of larger systems-of-systems, and could even be possibly a kind of system-of-systems itself. Through interactions anticipation within others existing and future contributing systems, that will possibly include some sub-systems to be integrated on board, and more surely crews to operate them, the design of next generation surface and submarine combat ships has to cope with the systems-of-systems issues. The question to be raised is thereby: How methods and tools that support graphical user interface definition and development process are facing the systems-of-systems issues? This article aims to first list the existing and emerging solutions for graphical user interface design in the frame of combat ship: (i) from a crew-centered approach point of view, (ii) for specification and modelling, in the frame of system engineering;(iii) for specification, prototyping and (iv) for development and testing. In a second time, we will discuss if those emerging solutions can handle the SoS specificities, and what are the ones they can't, trying to propose tracks for those.
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