Search

The article discusses the potential of advanced technologies in the field of cultural heritage. It highlights how these technologies, such as virtual reality, artificial intelligence, and 3D printing, can be used to understand, preserve, and enhance cultural heritage. The article also presents scientific papers from the Florence Heri-Tech International Conference, showcasing the various applications of these technologies. The papers cover topics such as the use of hyperspectral imaging for hieroglyph recognition, the enhancement of user experience in cultural spaces through advanced systems, and the use of non-invasive techniques for conservation. Overall, the article emphasizes the significant impact of technology on the research, preservation, and promotion of cultural heritage. [Extracted from the article]

Galleries, libraries, archives, and museums are nowadays striving to implement innovative approaches to adequately use and distribute the wealth of knowledge found in cultural heritage. A range of technologies can be used to enhance the viewing experience for visitors and boost the expertise of museologists, art historians, scholars, and audience members. The present work aims to provide an overview of current methods and most pertinent studies addressing the use of the innovative technologies for enhancing the fruition of artifacts in traditional museums in an effort to improve the public experience and education. For all the technologies discussed, the paper focuses on the main results obtained in literature and on their possible implementation in the museal context. The overview demonstrates the liveliness of the world of research in the field of technologies for the digital development of museums and how many technologies commonly used in industry are increasingly finding their way into the cultural sphere. [ABSTRACT FROM AUTHOR]

In recent years, breakthroughs in the fields of reverse engineering and additive manufacturing techniques have led to the development of innovative solutions for personalized medicine. 3D technologies are quickly becoming a new treatment concept that hinges on the ability to shape patient-specific devices. Among the wide spectrum of medical applications, the orthopaedic sector is experiencing the most benefits. Several studies proposed modelling procedures for patient-specific 3D-printed casts for wrist orthoses, for example. Unfortunately, the proposed approaches are not ready to be used directly in clinical practice since the design of these devices requires significant interaction among medical staff, reverse engineering experts, additive manufacturing specialists and CAD designers. This paper proposes a new practical methodology to produce 3D printable casts for wrist immobilization with the aim of overcoming these drawbacks. In particular, the idea is to realize an exhaustive system that can be used within a paediatric environment. It should provide both a fast and accurate dedicated scanning of the hand-wrist-arm district, along with a series of easy-to-use semi-automatic tools for the modelling of the medical device. The system was designed to be used directly by the clinical staff after a brief training. It was tested on a set of five case studies with the aim of proving its general reliability and identifying possible major flaws. Casts obtained using the proposed system were manufactured using a commercial 3D printer, and the device's compliance with medical requirements was tested. Results showed that the designed casts were correctly generated by the medical staff without the need of involving engineers. Moreover, positive feedback was provided by the users involved in the experiment. [ABSTRACT FROM AUTHOR]

Highligths • Strategy envisaging a virtual/mock surgery on a CAD/AM model of the patient cranium. • Additive Manufacturing based intervention simulation. • Additive Manufacturing based design of implants. • Complex craniofacial defects corrected using a single-step intervention. Abstract Background and objective The purpose of the present paper is to pave the road to the systematic optimization of complex craniofacial surgical intervention and to validate a design methodology for the virtual surgery and the fabrication of cranium vault custom plates. Recent advances in the field of medical imaging, image processing and additive manufacturing (AM) have led to new insights in several medical applications. The engineered combination of medical actions and 3D processing steps, foster the optimization of the intervention in terms of operative time and number of sessions needed. Complex craniofacial surgical intervention, such as for instance severe hypertelorism accompanied by skull holes, traditionally requires a first surgery to correctly "resize" the patient cranium and a second surgical session to implant a customized 3D printed prosthesis. Between the two surgical interventions, medical imaging needs to be carried out to aid the design the skull plate. Instead, this paper proposes a CAD/AM-based one-in-all design methodology allowing the surgeons to perform, in a single surgical intervention, both skull correction and implantation. Methods A strategy envisaging a virtual/mock surgery on a CAD/AM model of the patient cranium so as to plan the surgery and to design the final shape of the cranium plaque is proposed. The procedure relies on patient imaging, 3D geometry reconstruction of the defective skull, virtual planning and mock surgery to determine the hypothetical anatomic 3D model and, finally, to skull plate design and 3D printing. Results The methodology has been tested on a complex case study. Results demonstrate the feasibility of the proposed approach and a consistent reduction of time and overall cost of the surgery, not to mention the huge benefits on the patient that is subjected to a single surgical operation. Conclusions Despite a number of AM-based methodologies have been proposed for designing cranial implants or to correct orbital hypertelorism, to the best of the authors' knowledge, the present work is the first to simultaneously treat osteotomy and titanium cranium plaque. [ABSTRACT FROM AUTHOR]

Color matching of fabric blends is a key issue for the textile industry, mainly due to the rising need to create high-quality products for the fashion market. The process of mixing together differently colored fibers to match a desired color is usually performed by using some historical recipes, skillfully managed by company colorists. More often than desired, the first attempt in creating a blend is not satisfactory, thus requiring the experts to spend efforts in changing the recipe with a trial-and-error process. To confront this issue, a number of computer-based methods have been proposed in the last decades, roughly classified into theoretical and artificial neural network (ANN)-based approaches. Inspired by the above literature, the present paper provides a method for accurate estimation of spectrophotometric response of a textile blend composed of differently colored fibers made of different materials. In particular, the performance of the Kubelka-Munk (K-M) theory is enhanced by introducing an artificial intelligence approach to determine a more consistent value of the nonlinear function relationship between the blend and its components. Therefore, a hybrid K-M+ANN-based method capable of modeling the color mixing mechanism is devised to predict the reflectance values of a blend. [ABSTRACT FROM AUTHOR]

One of the most important parameters to be controlled during the production of textile yarns obtained by mixing pre-colored fibers, is the color correspondence between the manufactured yarn and a given reference, usually provided by a designer or a customer. Obtaining yarns from raw pre-colored fibers is a complex manufacturing process entailing a number of steps such as laboratory sampling, color recipe corrections, blowing, carding and spinning. Carding process is the one devoted to transform a “fuzzy mass” of tufted fibers into a regular mass of untwisted fibers, named “tow”. During this process, unfortunately, the correspondence between the color of the tow and the target one cannot be assured, thus leading to yarns whose color differs from the one used for reference. To solve this issue, the main aim of this work is to provide a system able to perform a spectral camera-based real-time measurement of a carded tow, to assess its color correspondence with a reference carded fabric and, at the same time, to monitor the overall quality of the tow during the carding process. Tested against a number of differently colored carded fabrics, the proposed system proved its effectiveness in reliably assessing color correspondence in real-time. [ABSTRACT FROM AUTHOR]

Home-based rehabilitation is becoming a gold standard for patient who have undergone knee arthroplasty or full knee replacement, as it helps healthcare costs to be minimized. Nevertheless, there is a chance of increasing adverse health effects in case of home care, primarily due to the patients' lack of motivation and the doctors' difficulty in carrying out rigorous supervision. The development of devices to assess the efficient recovery of the operated joint is highly valued both for the patient, who feels encouraged to perform the proper number of activities, and for the doctor, who can track him/her remotely. Accordingly, this paper introduces an interactive approach to angular range calculation of hip and knee joints based on the use of low-cost devices which can be operated at home. First, the patient's body posture is estimated using a 2D acquisition method. Subsequently, the 3D posture is evaluated by using the depth information coming from an RGB-D sensor. Preliminary results show that the proposed method effectively overcomes many limitations by fusing the results obtained by the state-of-the-art robust 2D pose estimation algorithms with the 3D data of depth cameras by allowing the patient to be correctly tracked during rehabilitation exercises. [ABSTRACT FROM AUTHOR]

Abstract: The influence of ripening degree of drupes during the harvesting period is well established in olive oil sector. A range of methods for expressing the stage of maturity of olives have been proposed in scientific literature. One of the most commonly adopted methods provides the evaluation of a Ripening Index (RI) on the basis of olive skin and pulp colour. Unfortunately, the RI evaluation technique is time-consuming, subjective (depending on expert skill) and depends on environmental conditions that may affect colour appearance of olives. This work describes a novel method for rapid, automatic and objective prediction of the Ripening Index of an olive lot. The method integrates a Machine Vision system, capable of performing a colour-based raw prediction of RI, with an Artificial Neural Network (ANN) based algorithm to refine it. Such a refinement is based on a set of chemical parameters (oil content, sugar content and phenol content) which are provided as input to the ANN and which can be obtained by historical curves for the region where the RI needs to be predicted. Experimental results demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Colour matching between carded and finished fibres is an important challenge for textile industry. The straightforward approach for mixing together some differently coloured fibres in order to obtain a blend of a desired colour is to perform a trial and error approach starting from a given colour recipe and optimizing it with several attempts. Unfortunately, dyeing process so as the carding procedure may result in a carded fibre whose colour is different from the desired one. As a consequence textile companies have to modify the original recipe in order to reduce the gap between the colour of the final product and the desired one. The present work describes a model able to simulate the colour mixing of fibres in order to assess the best recipe. The model consists in two modules: a "prediction module" predicts the colour of a blend obtained by mixing together several fibres; an "optimization module" is used to optimize the final recipe. The devised system has been tested for optimizing the recipe of a set of 200 blends. The mean error in predicting the blend colour is about 15% with a variance of 0.165. The time for optimizing the recipe is reduced by 92%. [ABSTRACT FROM AUTHOR]

Recycling of clothes is a straightforward approach for the supply of a coloured raw material which does not involve the cost of the colouring process. A real time and completely automated colour classification tool for woollen clothes to be recycled is proposed. The tool uses the combination of a statistical method, called matrix approach, of a self-organizing feature map (SOFM) and a feed-forward backpropagation artificial neural network (FFBP ANN)-based approach, to correctly classify the clothes by respecting the selection criteria provided by human know-how. The developed tool, which uses an appositely developed workbench with a spectrophotometer, is aware of the way the different coloured clothes to be recycled combine each other to create a new one. The tool has been validated using a set of 5,000 differently coloured clothes to be recycled and the classification error in classifying the clothes is within 5%, i.e., lower than the one resulting from the use of an expert human operator. [ABSTRACT FROM AUTHOR]

Abstract: This work provides a software based on the combination of a artificial neural network (ANN) approach and a numerical method (called “refining algorithm”) for the estimation of the acidity level and of peroxides number of olive oil extracted by a continuous extraction process. The estimation is achieved through the measurement of some agronomical and technological parameters commonly measured by the technicians working at the oil mills. The ANN based approach is able to perform a rough prediction of the two parameters; this prediction is then refined by means of the numerical approach. The devised software, developed using a database of experimental data collected in the years 1997–2004 in the Tuscany Region (Italy), is able to estimate the two parameters during the continuous oil extraction, thus allowing a real-time control of the oil quality during the extraction process. The experimental data are related to different kinds of extraction systems: the data collected before 2003 are mainly referred to three phases decanting while the one collected in years 2003–2004, are referred to a two phases decanter. The goal of this approach is to build up a fast and reliable quality control without performing the standard laboratory analysis. The results of the estimation achieved by the ANN based system are compared with the results of the chemical analyses carried out by Florence Commerce Chamber “Laboratorio Chimico Merceologico—Azienda Speciale CCIAA di Firenze” according in force to European Union Rules standards. The mean error in estimation of the parameters with the combination of the ANN approach and the refining algorithm, in comparison with the standard chemical analysis, is in the range 6–8% for an oil extraction with a three phases decanting system and about 6–7% for an oil extraction with a two phases decanting system. The maximum error affecting the method (ANN+Refining) described in this work is about 15% for the first case and about 11% for the second one. The system developed in the present work is actually running on the oil mill “TEM Toscana Enologica Mori” of Florence, Italy. The present work has been financed by the Tuscany Regional Agricultural Development and Innovation Office (ARSIA: Azienda Regionale per lo Sviluppo e l’Innovazione dell’Agricoltura) and is a part of a 3-year project whose objective is to create an entirely software+hardware controlled oil mill. [Copyright &y& Elsevier]

Purpose. High-fidelity mannequins are increasingly used to train the medical staff on many medical procedures. Lately, a new challenge regarding echogenic materials to build ultrasound-responding phantoms has emerged. The challenge is to find materials with a suitable combination of ultrasound velocity and consistency to the touch. Methods. Bibliographic research was performed to identify materials with promising stiffness, shape retention, and ultrasound velocity combinations. As-standardized-as-possible specimens were realized and tested using an A-mode ultrasound machine to evaluate the US velocity through them. Four differently doped silicones, five gelatin-based materials, five synthetic gelatins, and a 3D printable resin were included in the study. After being tested, the materials were monitored for 12 days to assess their durability and shape retention and tested again to evaluate the ultrasound velocity's stability. In the paper, the results of the characterization and follow-up of the materials are presented. Results. Outcomes show that gelatins are exceptional soft tissue-mimicking materials in terms of ultrasound velocity and consistency to the touch, but are poor in terms of overtime stability and therefore suitable for disposable short-term phantoms only. Doped silicones present lower ultrasound velocity compared to the reference value of 1540 m/s found in the literature, but excellent overtime stability, and shape retention properties. Values close to biological ones were also given by the Elastic 50A and by polyvinyl chloride plastisol. Conclusion. The paper gives a quantitative overview of the fidelity of both already-in-use and non-conventional materials, focusing on the ultrasound velocity value through them and their longevity in terms of macroscopically observed dehydration, shape retention, and bacterial onset. [ABSTRACT FROM AUTHOR]

Designing an acquisition system for 2D or 3D information, based on the integration of data provided by different sensors is a task that requires a labor-intensive initial design phase. Indeed, the definition of the architecture of such acquisition systems needs to start from the identification of the position and orientation of the sensors observing the scene. Their placement is carefully studied to enhance the efficacy of the system. This often coincides with the need to maximize the surfaces observed by the sensors or some other metric. An automatic optimization procedure based on the Particle Swarm Optimization (PSO) algorithm, to seek the most convenient setting of multiple optical sensors observing a 3D scene, is proposed. The procedure has been developed to provide a fast and efficient tool for 2D and 3D data acquisition. Three different objective functions of general validity, to be used in future applications, are proposed and described in the text. Various filters are introduced to reduce computational times of the whole procedure. The method is capable of handling occlusions from undesired obstacle in the scene. Finally, the entire method is discussed with reference to 1) the development of a body scanner for the arm-wrist-hand district and 2) the acquisition of an internal environment as case studies. [ABSTRACT FROM AUTHOR]

Low-cost RGB-D cameras are increasingly being used in several research fields, including human–machine interaction, safety, robotics, biomedical engineering and even reverse engineering applications. Among the plethora of commercial devices, the Intel RealSense cameras have proven to be among the most suitable devices, providing a good compromise between cost, ease of use, compactness and precision. Released on the market in January 2018, the new Intel model RealSense D415 has a wide acquisition range (i.e., ~160–10,000 mm) and a narrow field of view to capture objects in rapid motion. Given the unexplored potential of this new device, especially when used as a 3D scanner, the present work aims to characterize and to provide metrological considerations for the RealSense D415. In particular, tests are carried out to assess the device performance in the near range (i.e., 100–1000 mm). Characterization is performed by integrating the guidelines of the existing standard (i.e., the German VDI/VDE 2634 Part 2) with a number of literature-based strategies. Performance analysis is finally compared against the latest close-range sensors, thus providing a useful guidance for researchers and practitioners aiming to use RGB-D cameras in reverse engineering applications. [ABSTRACT FROM AUTHOR]

Versatile, cheap and non-invasive 3D acquisition techniques have received attention and interest in the field of biomedicine in recent years as the accuracy of developed devices permits the acquisition of human body shapes in detail. Interest in these technologies derives from the fact that they have the potential to overcome some limitations of invasive techniques (CT, X-rays, etc.) and those based on 2D photographs for the acquisition of 3D geometry. However, the data acquired from the 3D scanner cannot be directly used but need to be processed as they consist of 3D coordinates of the acquired points. Therefore, many researchers have proposed different algorithms which recognise the shape of human body and/or its features when starting from a 3D point cloud. Among all possible human body features to be evaluated, symmetry results the most relevant one. Accordingly, this survey systematically investigates the methods proposed in the literature to recognise 2D symmetry by the symmetry line and bilateral symmetry by the symmetry plane. The paper also analyses qualitative comparisons among the proposed methods to provide a guide for both practitioners and researchers. [ABSTRACT FROM AUTHOR]

To date, standard methods for assessing the severity of chest wall deformities are mostly linked to X-ray and CT scans. However, the use of radiations limits their use when there is a need to monitor the development of the pathology over time. This is particularly important when dealing with patients suffering from Pectus Carinatum, whose treatment mainly requires the use of corrective braces and a systematic supervision. In recent years, the assessment of severity of chest deformities by means of radiation-free devices became increasingly popular but not yet adopted as standard clinical practice. The present study aims to define an objective measure by defining a severity index (named External Pectus Carinatum Index) used to monitor the course of the disease during treatment. Computed on the optical acquisition of the patients' chest by means of an appositely devised, fast and easy-to-use, body scanner, the proposed index has been validated on a sample composed of a control group and a group of Pectus Carinatum patients. The index proved to be reliable and accurate in the characterization of the pathology, enabling the definition of a threshold that allows to distinguish the cases of patients with PC from those of healthy subjects. [ABSTRACT FROM AUTHOR]

Purpose This paper aims to argue about the involvement of additive technologies (ATs) in the prototyping issues of designing. More precisely, it reviews the literature contributions focused on the different perspectives of prototyping activities for design purposes, searching for both available knowledge and research needs concerning the correct exploitation of ATs.Design/methodology/approach A two-step literature review has been performed. In the first step, general information has been retrieved about prototyping issues related to design. In the second step, the literature searches were focused on retrieving more detailed information about ATs, concerning each of the main issues identified in the previous step. Extracted information has been analyzed and discussed for understanding the actual coverage of the arguments and for identifying possible research needs.Findings Four generally valid prototyping issues have been identified in the first step of the literature review. For each of them, available information and current lacks have been identified and discussed about the involvement of AT, allowing to extract six different research hints for future works.Originality/value This is the first literature review concerning AT-focused contributions that cover the complex and inter-disciplinary issues characterizing prototyping activities in design contexts. [ABSTRACT FROM AUTHOR]

Purpose: Among thoracic malformations, pectus deformities have the highest incidence and can result in a wide range of severe and mild clinical manifestations. Recently, the treatment of pectus deformities is shifting from traditional approaches toward customized solutions. This occurs by leveraging innovative rapid prototyping tools that allow for the design and fabrication of patient-specific treatments and medical devices. This paper aims to provide a comprehensive view of the growing literature in this area to analyze the progress made in this direction. Design/methodology/approach: The search was performed on major search engines through keywords inherent to reverse engineering (RE) and additive manufacturing (AM) technologies applied to pectus deformities and related treatments, selecting 54 papers. These were analyzed according to the addressed pathology, the hardware and software tools used and/or implemented and their integration within the clinical pathway. Findings: First, the analysis led to analyze and divide the papers according to how RE and AM technologies are applied for surgical and non-surgical treatments, pathological assessment and preoperative simulation and planning. Second, all papers were considered within the typical rapid prototyping framework consisting of the three phases of three-dimensional (3D) scanning, 3D modelling and 3D printing. Originality/value: To the best of the authors' knowledge, to date, no survey has provided a comprehensive view of innovative and personalized treatment strategies for thoracic malformations; the present work fills this gap, allowing researchers in this field to have access to the most promising findings on the treatment and evaluation of pathology. [ABSTRACT FROM AUTHOR]

Nowadays, the creation of methodologies and tools for facilitating the 3D reproduction of artworks and, contextually, to make their exploration possible and more meaningful for blind users is becoming increasingly relevant in society. Accordingly, the creation of integrated systems including both tactile media (e.g., bas-reliefs) and interfaces capable of providing the users with an experience cognitively comparable to the one originally envisioned by the artist, may be considered the next step for enhancing artworks exploration. In light of this, the present work provides a description of a first-attempt system designed to aid blind people (BP) in the tactile exploration of bas-reliefs. In detail, consistent hardware layout, comprising a hand-tracking system based on Kinect® sensor and an audio device, together with a number of methodologies, algorithms and information related to physical design are proposed. Moreover, according to experimental test on the developed system related to the device position, some design alternatives are suggested so as to discuss pros and cons. [ABSTRACT FROM AUTHOR]

Within the literature concerning modern machine learning techniques applied to the medical field, there is a growing interest in the application of these technologies to the nephrological area, especially regarding the study of renal pathologies, because they are very common and widespread in our society, afflicting a high percentage of the population and leading to various complications, up to death in some cases. For these reasons, the authors have considered it appropriate to collect, using one of the major bibliographic databases available, and analyze the studies carried out until February 2022 on the use of machine learning techniques in the nephrological field, grouping them according to the addressed pathologies: renal masses, acute kidney injury, chronic kidney disease, kidney stone, glomerular disease, kidney transplant, and others less widespread. Of a total of 224 studies, 59 were analyzed according to inclusion and exclusion criteria in this review, considering the method used and the type of data available. Based on the study conducted, it is possible to see a growing trend and interest in the use of machine learning applications in nephrology, becoming an additional tool for physicians, which can enable them to make more accurate and faster diagnoses, although there remains a major limitation given the difficulty in creating public databases that can be used by the scientific community to corroborate and eventually make a positive contribution in this area. [ABSTRACT FROM AUTHOR]

In brain tumor surgery, an appropriate and careful surgical planning process is crucial for surgeons and can determine the success or failure of the surgery. A deep comprehension of spatial relationships between tumor borders and surrounding healthy tissues enables accurate surgical planning that leads to the identification of the optimal and patient-specific surgical strategy. Aphysical replica of the region of interest is a valuable aid for preoperative planning and simulation, allowing the physician to directly handle the patient's anatomy and easily study the volumes involved in the surgery. In the literature, different anatomical models, produced with 3D technologies, are reported and several methodologies were proposed. Many of them share the idea that the employment of 3D printing technologies to produce anatomical models can be introduced into standard clinical practice since 3D printing is now considered to be a mature technology. Therefore, the main aim of the paper is to take into account the literature best practices and to describe the current workflow and methodology used to standardize the pre-operative virtual and physical simulation in neurosurgery. The main aim is also to introduce these practices and standards to neurosurgeons and clinical engineers interested in learning and implementing cost-effective in-house preoperative surgical planning processes. To assess the validity of the proposed scheme, four clinical cases of preoperative planning of brain cancer surgery are reported and discussed. Our preliminary results showed that the proposed methodology can be applied effectively in the neurosurgical clinical practice both in terms of affordability and in terms of simulation realism and efficacy. [ABSTRACT FROM AUTHOR]

The present paper proposes a methodology to design and manufacture optimized turbomachinery components by leveraging the potential of Topology Optimization (TO) and Additive Manufacturing (AM). The method envisages the use of TO to define the best configuration of the rotoric components in terms of both static and dynamic behavior with a resultant reduction of overall weight. Eventually, the topology-optimized component is manufactured by using appropriate materials that can guarantee valid mechanical performances. The proposed strategy has been applied to a 2D impeller used for centrifugal compressors to prove the effectiveness of a TO+AM-based approach. Although this approach has never been extensively used before to centrifugal compressors and expanders, its application on rotor and stator components might unlock several benefits: tuning the natural frequencies, a reduction in the stress level, and a lighter weight of the rotating part. These objectives can be reached alone or in combination, performing a single analysis or a multiple analyses optimization. Finally, the introduction of AM technologies as standard manufacturing resources could bring sensible benefits with respect to the time to production and availability of components. Such aspects are essential in the Oil and Gas context, when dealing with new projects but also for service operations. [ABSTRACT FROM AUTHOR]

To date, standard methods for assessing the severity of chest wall deformities are mostly linked to X-ray and CT scans. However, the use of radiations limits their use when there is a need to monitor the development of the pathology over time. This is particularly important when dealing with patients suffering from Pectus Carinatum, whose treatment mainly requires the use of corrective braces and a systematic supervision. In recent years, the assessment of severity of chest deformities by means of radiation-free devices became increasingly popular but not yet adopted as standard clinical practice. The present study aims to define an objective measure by defining a severity index (named External Pectus Carinatum Index) used to monitor the course of the disease during treatment. Computed on the optical acquisition of the patients' chest by means of an appositely devised, fast and easy-to-use, body scanner, the proposed index has been validated on a sample composed of a control group and a group of Pectus Carinatum patients. The index proved to be reliable and accurate in the characterization of the pathology, enabling the definition of a threshold that allows to distinguish the cases of patients with PC from those of healthy subjects. Graphical abstract. [ABSTRACT FROM AUTHOR]

RGB-D cameras are employed in several research fields and application scenarios. Choosing the most appropriate sensor has been made more difficult by the increasing offer of available products. Due to the novelty of RGB-D technologies, there was a lack of tools to measure and compare performances of this type of sensor from a metrological perspective. The recent ISO 10360-13:2021 represents the most advanced international standard regulating metrological characterization of coordinate measuring systems. Part 13, specifically, considers 3D optical sensors. This paper applies the methodology of ISO 10360-13 for the characterization and comparison of three RGB-D cameras produced by Intel® RealSense™ (D415, D455, L515) in the close range (100–1500 mm). ISO 10360-13 procedures, which focus on metrological performances, are integrated with additional tests to evaluate systematic errors (acquisition of flat objects, 3D reconstruction of objects). The present paper proposes an off-the-shelf comparison which considers the performance of the sensors throughout their acquisition volume. Results have exposed the strengths and weaknesses of each device. The D415 device showed better reconstruction quality on tests strictly related to the short range. The L515 device performed better on systematic depth errors; finally, the D455 device achieved better results on tests related to the standard. [ABSTRACT FROM AUTHOR]

The set-up of machining parameters for non-ferric materials such as wood and wood-based materials is not yet defined on a scientific basis. In this paper, a new rapid experimental method to assess the specific cutting coefficients when routing isotropic and orthotropic wood-based materials is presented. The method consists of routing, with different depths of cut, a given material previously machined to a round shape after having it fixed on a dynamometric platform able to measure the cutting forces. The execution of subsequent cuts using different depths of cut allows the calculation of the specific cutting coefficients. With the measurement being done during real routing operations, a method to remove machine vibrations was also developed. The specific cutting coefficients were computed for the whole set of grain orientations for orthotropic materials and as an average for isotropic ones. The aim of this paper is to present and validate the whole method by machining selected materials such as Polytetrafluoroethylene—PTFE (isotropic), Medium Density Fiberboard—MDF (isotropic), beech Laminate Veneer Lumber—LVL (orthotropic) and poplar LVL (orthotropic). The method and the proposed analysis have been shown to work very effectively and could be used for optimization and comparison between materials and processes. [ABSTRACT FROM AUTHOR]