Geometric modeling and processing

Automated segmentation of brain tumors is a difficult procedure due to the variability and blurred boundary of the lesions. In this study, we propose an automated model based on Bendlet transform and improved Chan-Vese (CV) model for brain tumor segmentation. Since the Bendlet system is based on the principle of sparse approximation, Bendlet transform is applied to describe the images and map images to the feature space and, thereby, first obtain the feature set. This can help in effectively exploring the mapping relationship between brain lesions and normal tissues, and achieving multi-scale and multi-directional registration. Secondly, the SSIM region detection method is proposed to preliminarily locate the tumor region from three aspects of brightness, structure, and contrast. Finally, the CV model is solved by the Hermite-Shannon-Cosine wavelet homotopy method, and the boundary of the tumor region is more accurately delineated by the wavelet transform coefficient. We randomly selected some cross-sectional images to verify the effectiveness of the proposed algorithm and compared with CV, Ostu, K-FCM, and region growing segmentation methods. The experimental results showed that the proposed algorithm had higher segmentation accuracy and better stability.

Keywords: Bendlet system , feature set , image expression , segmentation , Shannon-cosine wavelet

A 59-year-old woman was admitted to the emergency department for heart failure (HF), New York Heart Association (NYHA) IV, showing an anterior, evolved myocardial infarction (MI) with a wide apical left ventricular aneurysm (LVA), ejection fraction (EF) 24%, and global longitudinal strain (GLS) −5. 5% by echo. Cardiac magnetic resonance imaging (MRI) confirmed an apical LVA without thrombus, EF 20%, and a transmural delayed enhancement in the myocardium wall. Coronarography showed a three-vessel disease with occluded proximal left anterior descending (LAD) and proximal right coronary artery (RCA). Based on the cardiac CT scan, we decided to generate a three-dimensional (3D) print model of the heart, for better prediction of residual LV volumes. After LVA surgery plus complete functional revascularization, an optimal agreement was found between predicted and surgical residual LV end-diastolic (24.7 vs. 31.8 ml/m2) and end-systolic (54.1 vs. 69.4 ml/m2) volumes, with an improvement of NYHA class, from IV to I. The patient was discharged uneventfully and at 6- and 12-month follow-up, the NYHA class, and LV volumes were found unchanged. This is a second report describing the use of the 3D print model for the preoperative planning of surgical management of LVA; the first report was described by Jacobs et al. among three patients, one with a malignant tumor and the remaining two patients with LVA. This article focused on the use of the 3D print model to optimize surgical planning and individualize treatment of LVA associated with complete functional revascularization, leading to complete recovery of LV function with a favorable outcome.

Keywords: 3D printing model , CAD , heart failure , left ventricular aneurysm , surgical ventricular restoration

In the last decades, the flourishing of Additive Manufacturing (AM) promoted innovative design solutions in many different sectors. Despite the numerous advantages of AM technology, there are still open challenges in the field. In Fused Deposition Modelling (FDM) structures the layer-by-layer manufacturing process induces anisotropy in the material properties of the structures. The correct characterization of the mechanical properties is fundamental in the design and development stages but at the same time difficult to achieve. The experimental approach can be extremely long and expensive. An alternative is the use of an accurate numerical approach and performing a Finite Element Analysis (FEA) of the geometry which is effectively printed. However, to the best of the authors\' knowledge, there is not a common and well-established procedure to reconstruct the real geometry which is generated after the slicing process. In this paper, starting from the information provided by the G-CODE, an easy-to-use, and reproducible methodology to reconstruct the printed geometry is presented. The performance of the innovative approach is evaluated via qualitative observations by referring to several case studies. The results are thoroughly analysed, and future trends and research needs are highlighted.

Keywords: Additive Manufacturing , CAD , Fused Deposition Modelling , G-CODE

Nowadays, robot-based additive manufacturing (RBAM) is emerging as a potential solution to increase manufacturing flexibility. Such technology allows to change the orientation of the material deposition unit during printing, making it possible to fabricate complex parts with optimized material distribution. In this context, the representation of parts geometries and their subsequent processing become aspects of primary importance. In particular, part orientation, multiaxial deposition, slicing, and infill strategies must be properly evaluated so as to obtain satisfactory outputs and avoid printing failures. Some advanced features can be found in commercial slicing software (e.g., adaptive slicing, advanced path strategies, and non-planar slicing), although the procedure may result excessively constrained due to the limited number of available options. Several approaches and algorithms have been proposed for each phase and their combination must be determined accurately to achieve the best results. This paper reviews the state-of-the-art works addressing the primary methods for the representation of geometries and the subsequent geometry processing for RBAM. For each category, tools and software found in the literature and commercially available are discussed. Comparison tables are then reported to assist in the selection of the most appropriate approaches. The presented review can be helpful for designers, researchers and practitioners to identify possible future directions and open issues.

Keywords: Geometry processing , Multiaxial deposition , Robot-based additive manufacturing , Slicing strategy , Volume decomposition

Lightweight bioinspired structures are extremely interesting in industrial applications for their known advantages, especially when Additive Manufacturing technologies are used. Lattices are composed of axial elements called ligaments: Several unit cells are repeated in three directions to form bodies. However, their inherent structure complexity leads to several problems when lattices need to be designed or numerically simulated. The computational power needed to capture the overall component is extremely high. For this reason, some alternative methodologies called homogenization methods were developed in the literature. However, following these approaches, the designers do not have a local visual overview of the lattice behavior, especially at the ligament level. For this reason, an alternative mono-dimensional (1D) modeling approach, called lattice-to-1D is proposed in this work. This method approximates the ligament element with its beam axis, uses the real material characteristics, and gives the cross-sectional information directly to the solver. Several linear elastic simulations, involving both stretching and bending dominated unit cells, are performed to compare this approach with other alternatives in the literature. The results show a comparable agreement of the 1D simulations compared with homogenization methods for real tridimensional (3D) objects, with a dramatic decrease of computational power needed for a 3D analysis of the whole body.

Keywords: homogenization , lattice structure , periodic structure , structural analysis , voxel

Recently, estimation of the visual saliency map in car driving scenarios has received significant research interests. Visual saliency perception includes the processing of specific parts of the visual driving scene in which the subject (car driver) pays more attention (specifically the parts whose gaze is focused). This work makes further contributions to video saliency research with application on the sustainable assisted driver technologies. Ad-hoc Semantic Fully Convolutional Deep Network embedding Gradient-Reversal domain adaptation layer has been implemented to process the video frames captured by a commercial low frame-rate automotive-grade camera device hosted outside the vehicle. A parallel motion-magnified visual-to-physio drowsiness assessment of the car driver will complete the proposed full automotive solution. The collected experimental results confirmed the effectiveness of the proposed solution.

Keywords: ADAS , Deep Learning , physio-signal , Saliency

Automotive industry is making rapid progress in the development of next generation cars with higher levels of autonomy and intelligent assistance. Although the general advanced driver assistance system (ADAS) architecture is widely discussed, limited interaction between driver and these intelligent solutions sometimes make these approaches inefficient. For these reasons, the authors triggered an investigation about driver's feedback in relation to the assistance inputs provided by the ADAS technologies. In this context, the goal of this proposal is the design of an intelligent system that learns from the analysis of the car driver eyes saccadic movements, the correlated level of attention towards the salient driving scene. With this approach, we enabled a visual-feedback system which learns the driver eye's fixing dynamic associated to the analyzed driving scene. Through ad-hoc enhanced motion magnification technique, the authors were able to amplify the mentioned saccadic dynamics in order to allow a downstream deep classifier to associate this physiological behavior with the corresponding level of the driver attention. The collected performances (over 97%) confirmed the effectiveness of the proposed method.

Keywords: ADAS , Deep Learning , Driver eye saccadic movements , Motion Magnification

The High Energy cosmic-Radiation (HERD) detector is one of the prominent space-borne instruments to be installed on-board the Chinese Space Station (CSS), around 2027. Primary scientific goals regarding this initiative include: precise measurements of cosmic ray (CR) energy spectra and mass composition, at energies up to the PeV range; contributions to high energy gamma-ray astronomy and transient studies; as well as indirect searches for Dark Matter (DM) particles via their possible annihilation/decay to detectable products. HERD is configured to accept incident particles from both its top and four lateral sides. Owing to its pioneering design, an order of magnitude increase in acceptance is foreseen, with respect to previous and ongoing experiments. The Plastic Scintillator Detector (PSD) constitutes an important sub-detector of HERD, particularly aimed towards anti-coincidence (discriminating incident photons from charged particles), while providing precise charge measurement of incoming cosmic-ray nuclei in a range of Z = 1-26. Main requirements concerning its design, include: high detection efficiency, broad dynamic range and good energy resolution. In order to select the optimal layout, two geometries are currently under investigation: one based on long scintillator bars and the other on square tiles, with both layouts being readout by Silicon Photomultipliers (SiPMs). Ongoing activities and future plans regarding the HERD PSD will be presented in this work.

Keywords: Charged particles , Cosmology , Gamma rays , Scintillation counters , Space stations

Since every structure in the human body can vary, customization is important to choose the most appropriate medical option according to the patient. Total knee arthroplasty (TKA) is a surgical procedure for the knee replacement that has a high rate of patient's dissatisfaction. Indeed, conventional prostheses are based on anthropometric data that accommodate common knees. However, mismatch can occur due to anatomical variations among the individuals. Thanks to the advances in imaging techniques and 3D modeling, it is possible to create customized knee implants starting from medical images. In this context, the present research proposes a methodology to design a customized knee implant taking into account clinical (e.g., prosthesis alignment and surgical cuts) and technical parameters (e.g., materials) that have a direct impact on TKA performance and patient's satisfaction. Changing these parameters, different scenarios have been modeled and simulated to understand the most suitable combination. Finite element analysis (FEA) has been employed to simulate and compare the proposed customized models, changing the different clinical and technical parameters. Stress induced by different combinations of the parameters has been evaluated to choose the optimal solution among the eight proposed scenarios. The optimum is reached with a physiological alignment, with six femoral facets and the ultra-high molecular weight polyethylene (UHMWPE) tibial insert. The implant design maintains the natural joint line and allows preserving more bone. The material is the parameter that mostly influences the stress distribution.

Keywords: computer aided design , computer aided engineering , customized knee implant , femoral component optimization , finite element analysis , knowledge engineering , patient-specific knee prosthesis , total knee arthroplasty , virtual prototyping

The 6D pose estimation of an object from an image is a central problem in many domains of Computer Vision (CV) and researchers have struggled with this issue for several years. Traditional pose estimation methods (1) leveraged on geometrical approaches, exploiting manually annotated local features, or (2) relied on 2D object representations from different points of view and their comparisons with the original image. The two methods mentioned above are also known as Feature-based and Template-based, respectively. With the diffusion of Deep Learning (DL), new Learning-based strategies have been introduced to achieve the 6D pose estimation, improving traditional methods by involving Convolutional Neural Networks (CNN). This review analyzed techniques belonging to different research fields and classified them into three main categories: Template-based methods, Feature-based methods, and Learning-Based methods. In recent years, the research mainly focused on Learning-based methods, which allow the training of a neural network tailored for a specific task. For this reason, most of the analyzed methods belong to this category, and they have been in turn classified into three sub-categories: Bounding box prediction and Perspective-n-Point (PnP) algorithm-based methods, Classification-based methods, and Regression-based methods. This review aims to provide a general overview of the latest 6D pose recovery methods to underline the pros and cons and highlight the best-performing techniques for each group. The main goal is to supply the readers with helpful guidelines for the implementation of performing applications even under challenging circumstances such as auto-occlusions, symmetries, occlusions between multiple objects, and bad lighting conditions.

Keywords: 6D position estimation , Computer vision , Deep learning , RGB Input

Purpose: This paper aims to enhance the visual quality of artificial above-ground structures, like pylons, masts, and towers of infrastructures and facilities, through a systematic design method for their morphological and structural optimization. Design/methodology/approach: The method achieves the functional and aesthetic goals based on the application of computer-aided tools. In particular, this is achieved according to three key steps: • Morphological development of landscape-related symbolism, environment, or culture and social needs. • Topology optimization of the design concept to reduce the structural weight and its visual impact. • Engineering of the resulting optimized structure. Practical implications: As a case study, the method is used for designing electricity pylons for the coastal territory of a Mediterranean European country, such as Italy. Citizens were involved during the identification phase of a symbolic shape for the concept development and during the final assessment phase. Research limitations/implications: The engineering phase has been performed by assembling standard lattice components with welded connections. Even if the use of this truss-like structure should lead to a minimum cost, the developed structure employs an additional 15%–20% of trusses and sheet metal covers the final cost is higher than a standard lattice pylon. Findings: The result is a structure with enhanced visual quality according to the international guidelines and fully complying with mandatory and functional requirements, such as regulatory and industrial feasibility, as well as those arising from social components. Originality/value: The method shows its potential in defining a custom design for lightweight structures with enhanced visual quality regarding the critical situation discussed here. The method considers both the subjective perception of citizens and their priorities and the landscape where the structures will be installed.

Keywords: computer-aided tool , design method , landscape impact , pylon , topology optimization , visual impact

This case study aims to develop a new innovative SUV (Sport Utility Vehicle) model exploiting IDeS (Industrial Design Structure), which is an engineering approach conceived to optimize car design projects in the automotive industry like never before. A compact SUV was chosen because it is a type of vehicle that is highly requested by customers, and it is extremely successful in the market due to its versatility. In fact, compact SUVs are mixed vehicles that combine the pragmatism of a car with the typical robustness of an off-road vehicle making them suitable both for urban and off-road scenarios. The following pages will illustrate the steps followed for the realization of the final product using the SDE (Stylistic Design Engineering) method and other various design technologies, such as Quality Function Deployment (QFD), Benchmarking (BM) and Top Flop Analysis (TPA). In the final part of this project, the virtual prototyping of the product is carried out using Additive Manufacturing (AM) with an FDM 3D printer. The combination of these methods forms, to all intents and purposes, the IDeS, a newly developed innovative and cutting-edge discipline capable of schematically guiding the new product development process in companies with unprecedented efficiency.

Keywords: CAD modelling , car design , IDeS , innovation , QFD , SDE

The High Energy cosmic-Radiation Detection (HERD) facility has been proposed as a space astronomy payload onboard the future China's Space Station. HERD is planned for operation starting around 2027 for about 10 years In addition to the unprecedented sensitivity for dark matter searches and cosmic-ray measurements up to the knee energy, it should perform gamma-ray monitoring and full sky survey from few hundred MeV up to tens of TeV. We present the first study of the HERD gamma-ray performance obtained with full simulations of the whole detector geometry. HERD will be a cubic detector composed with 5 active faces. We present a study conducted inside the HERD analysis software package, which includes a detailed description of the detector materials. In this work we present the HERD effective area, the point spread function and the resulting gamma-ray sensitivity.

Keywords: Cosmology , Gamma rays , Optical transfer function , Space stations

The High Energy cosmic-Radiation Detection (HERD) facility is a space payload proposed to be installed onboard the China's Space Station (CSS). The aims of HERD are the indirect detection of dark matter, the direct detection of cosmic rays towards the “knee” of the spectrum (∼ 1 PeV) and the monitoring of the full gamma-ray sky from 100 MeV. The HERD core is a calorimeter capable of accepting particles incident on its top and four lateral sides, each equipped with a sector of the scintillating fiber tracker: FIT. The FIT sectors host 7 tracking planes made of modules. The module, composed of a fiber mat and three arrays of silicon photomultipliers (SiPMs), is the elementary brick of FIT. Several FIT modules have been built and tested with particle beams at CERN. A FIT demonstrator, made of two partially instrumented tracking planes, has been assembled and sent through vibration tests. The results of the performed tests as well as the current design of FIT are presented in this contribution.

Keywords: Cosmology , Gamma rays , Scintillation , Space stations

The High Energy cosmic-Radiation Detection (HERD) facility is a next generation spaceborne detector to be installed onboard the Chinese Space Station for about 10 years. HERD will address major problems in fundamental physics and astrophysics, providing precise measurements of charged-cosmic rays up to PeV energies, performing indirect searches for dark matter in the electron spectrum up to few tens of TeV and monitoring the gamma-ray skymap for surveys and transient searches. HERD is composed of a 3D imaging calorimeter (CALO) surrounded by a scintillating fiber tracker (FIT), a plastic scintillator detector (PSD) and a silicon charge detector (SCD). In addition, a transition radiation detector (TRD) is placed on a lateral side to provide accurate energy calibration. Based on this innovative design, the effective geometric factor of HERD will be one order of magnitud larger than that of current space-based detectors. The HERD trigger strategy is designed to accomplish the scientific goals of the mission, and is based on trigger definitions that rely on the energy deposited in CALO and the PSD. The trigger performances are evaluated using a detailed Monte Carlo simulation that includes the latest HERD geometry. In addition, alternative trigger definitions based on the event topology can be established thanks to the photodiode readout of CALO crystals. The feasibility of these topological triggers is also investigated and presented.

Keywords: Cosmology , Gamma rays , Intelligent systems , Monte Carlo methods , Space stations , Tellurium compounds , Topology

The High Energy cosmic-Radiation Detection (HERD) is a future space experiment which will be installed on the China's Space Station around 2027. The main goal of the experiment is the measurement of cosmic rays up to energies which are not explored by the instruments currently operating in space, in particular protons with energies up to PeV, nuclei up to hundreds of TeV per nucleon and electrons up to tens of TeV. HERD will consist of silicon charge detectors, anti-coincidence scintillators, scintillating fiber trackers, a transition radiation detector and a calorimeter. The latter is a homogeneous, deep, 3D segmented calorimeter made of about 7500 LYSO cubic crystals: thanks to this innovative design, it will achieve large acceptance, good energy resolution and excellent electron/proton discrimination. In order to increase both energy calibration capabilities and redundancy of the instrument, the LYSO scintillation light will be read-out by two independent systems: the first is made of wave-length shifting fibers coupled with imaged intensified CMOS cameras, and the second one consists of photodiodes with different active areas connected to a custom front-end electronics. Both read-out systems are designed to have a large dynamic range, up to 107, and a low power consumption. The design of the calorimeter is validated by several Monte Carlo simulations and beam test results obtained with detector prototypes. In this paper we describe the anticipated performances of the calorimeter and the current status of the double read-out system, and we discuss the recent developments of both the HERD prototype and the flight model design.

Keywords: Cosmic rays , Cosmology , Intelligent systems , Monte Carlo methods , Scintillation counters , Silicon detectors , Space stations

The paper presents the development of a Virtual Reality application to perform dives in the Christoforos Shipwreck. The huge wreck lies in the Panormos Bay of the Skopelos island (Greece) at a depth of 45 meters. Based on a well-known methodology designed for ancient shipwrecks, the 3D reconstruction of the underwater site has been carried out by adjusting the workflow to survey modern shipwrecks. In particular, the methodology, based on photogrammetry, is capable to provide a highly detailed 3D reconstruction of the shipwreck in few dives, considering issues like working depth, elevations, and thin elements modelling. Moreover, the paper describes the optimization of the 3D model and the software to be executed in low-performance HMD devices. The resulting Virtual Reality (VR) application, realized for touristic purposes, recreates the exact ambient conditions inside and outside the water simulating the flora and fauna of the place, the coastline, allowing users to live a recreational and educational experience by virtual diving in the underwater site.

Keywords: 3D modeling , History , Image reconstruction , Ships , Three dimensional computer graphics

The LIFE SNEAK project, started in September 2021, aims at the reduction of noise from road traffic that mainly affects densely populated urban areas where the noise and vibrations produced by the tram overlap with noise produced by road traffic. Applicative measures will be designed and tested in a pilot case of the city of Florence, such as low-noise and vibration surfaces with life cycle costs comparable to those of traditional surfaces, and measures to reduce tram noise aiming to obtain substantial reductions in noise and annoyance. In the first phase, specific attention was dedicated to the state-of-the-art analysis concerning prediction and monitoring of the level of noise and ground-borne vibrations in urban environments. Moreover, the impacts of road traffic and tramway in terms of noise and vibrations on people annoyance in urban context have been investigated to design appropriate questionnaires for citizens. In fact, the exploration of any combined effect of vibration and noise on annoyance is also suggested by recent guidelines for designing dedicated social surveys. In this paper the procedure to design a noise and vibration measurements and survey campaign oriented to support an evaluation of effective reductions in terms of both levels and annoyance is presented.

Keywords: Acoustic variables control , Life cycle , Roads and streets , Vibration measurement

The paper illustrates the design of a new mechanical system for propeller blades pitch calibration in medium power wind turbines. The peculiarity of this system is its capacity of adjusting through a feedback control system, which allows the wind turbine to capture the maximum amount of energy from the wind. In this work an axial drive system was studied by means of racks capable of linearly adjusting the pitch of all wind turbine propeller blades in an intrinsically synchronous way, with an advantage over the traditional methods of propeller blades pitch calibration. For different wind speeds the system adjusts the blades angle of incidence in order to reduce the rotation speed and keep the system as close as possible to the pre-established design conditions generating maximum energy with a high efficiency. The manuscript examines the main analyses and simulations conducted during the design phase. These show that the proposed method allows to reach higher efficiencies with a greater intrinsic stability compared to the traditional pitch control mechanisms in medium power wind turbines. The experimental results on the first prototypes confirm the efficiency increase.

Keywords: Linearly Adjusting , Medium Power Wind Turbines , Pitch Calibration , Propeller Blades , Racks

This research concerns the optimization study of the wing of an ultralight competition sailplane, category F5J/F3J. Fundamental for this category is the characteristic of lightness associated with good wing stiffness (bending/torsional). All the elements composing the wing of the sailplane were modelled in 3D by using the Autodesk Inventor parametric solid modeler. They were assembled in the FEM environment and were suitably constrained and studied from a structural point of view. The structural characteristics of the wing and its components were analysed in detail after assigning the materials currently used and adopting appropriate materials to make the same with the Additive Manufacturing (AM) technic. A topological optimization, performed by using the Simplex Method (SIMP), was conducted on the internal structure of the wing in order to lighten the ribs with the same performance. The experimental investigations implemented in the laboratory allowed the 'Oralight' material used for the wing surface coating to be characterized. It is an extremely thin and light material, whose elasticity and strength were accurately assessed in this study. The data obtained, considered along with the elasticity and the resistance values of the other materials constituting the wing structure, taken from the literature, were inserted into the finite element simulations with the aim of evaluating the torsional and bending stiffness of the wing. Finally, the rib was redesigned using a FDM material which makes construction particularly simple.

Keywords: Oralight Coating Surface , Compound Bio-Plastic Filament , Ribs and Spars' Redesign , Torsional and Bending Wing Stiffness , Wing Parametric Modelling