Facial Expression Recognition for Measuring Jurors' Attention in Acoustic Jury Tests.

The perception of sound greatly impacts users' emotional states, expectations, affective relationships with products, and purchase decisions. Consequently, assessing the perceived quality of sounds through jury testing is crucial in product design. However, the subjective nature of jurors' responses may limit the accuracy and reliability of jury test outcomes. This research explores the utility of facial expression analysis in jury testing to enhance response reliability and mitigate subjectivity. Some quantitative indicators allow the research hypothesis to be validated, such as the correlation between jurors' emotional responses and valence values, the accuracy of jury tests, and the disparities between jurors' questionnaire responses and the emotions measured by FER (facial expression recognition). Specifically, analysis of attention levels during different statuses reveals a discernible decrease in attention levels, with 70 percent of jurors exhibiting reduced attention levels in the 'distracted' state and 62 percent in the 'heavy-eyed' state. On the other hand, regression analysis shows that the correlation between jurors' valence and their choices in the jury test increases when considering the data where the jurors are attentive. The correlation highlights the potential of facial expression analysis as a reliable tool for assessing juror engagement. The findings suggest that integrating facial expression recognition can enhance the accuracy of jury testing in product design by providing a more dependable assessment of user responses and deeper insights into participants' reactions to auditory stimuli.

Neural network based hyperspectral imaging for substrate independent bloodstain age estimation.

Being able to determine the age of a bloodstain can be a key element in a crime scene investigation. Many techniques exploit reflectance spectroscopy because it is very versatile and can be used in the field with ease. However, there are no methods for estimating bloodstain age with adequate uncertainty, and the problem of substrate influence is not yet fully resolved. We develop a hyperspectral imaging based technique for the substrate-independent age estimation of a bloodstain. Once the hyperspectral image is acquired, a neural network model recognizes the pixels belonging to the bloodstain. The reflectance spectra belonging to the bloodstain are then processed by an artificial intelligence model that removes the effect of the substrate on the bloodstain and then estimates its age. The method is trained on bloodstains deposited on 9 different substrates over a time period of 0-385 h obtaining an absolute mean error of 6.9 h over the period considered. Within two days of age, the method achieves a mean absolute error of 1.1 h. The method is finally tested on a new material (i.e., red cardboard) never used to test or validate the neural network models. Also in this case the bloodstain age is identified with the same accuracy.

Development of a Quartz-Based Photo-Mobile Polymer Film for Controlled Motion Triggered by Light or Heat.

We have developed a photo-mobile polymer film, that combines organic and inorganic materials, to allow for controlled motion that can be triggered by light or heat. Our film is made using recycled quartz and consists of two layers: a multi-acrylate polymer layer and a layer containing oxidized 4-amino-phenol and N-Vinyl-1-Pyrrolidinone. The use of quartz in our film also gives it a high temperature resistance of at least 350 °C. When exposed to heat, the film moves in a direction that is independent of the heat source, due to its asymmetrical design. Once the heat source is removed, the film returns to its original position. ATR-FTIR measurements confirm this asymmetrical configuration. This technology may have potential applications in energy harvesting, due to the piezoelectric properties of quartz.

FRMDB: Face Recognition Using Multiple Points of View.

Although face recognition technology is currently integrated into industrial applications, it has open challenges, such as verification and identification from arbitrary poses. Specifically, there is a lack of research about face recognition in surveillance videos using, as reference images, mugshots taken from multiple Points of View (POVs) in addition to the frontal picture and the right profile traditionally collected by national police forces. To start filling this gap and tackling the scarcity of databases devoted to the study of this problem, we present the Face Recognition from Mugshots Database (FRMDB). It includes 28 mugshots and 5 surveillance videos taken from different angles for 39 distinct subjects. The FRMDB is intended to analyze the impact of using mugshots taken from multiple points of view on face recognition on the frames of the surveillance videos. To validate the FRMDB and provide a first benchmark on it, we ran accuracy tests using two CNNs, namely VGG16 and ResNet50, pre-trained on the VGGFace and VGGFace2 datasets for the extraction of face image features. We compared the results to those obtained from a dataset from the related literature, the Surveillance Cameras Face Database (SCFace). In addition to showing the features of the proposed database, the results highlight that the subset of mugshots composed of the frontal picture and the right profile scores the lowest accuracy result among those tested. Therefore, additional research is suggested to understand the ideal number of mugshots for face recognition on frames from surveillance videos.

SwimmerNET: Underwater 2D Swimmer Pose Estimation Exploiting Fully Convolutional Neural Networks.

Professional swimming coaches make use of videos to evaluate their athletes' performances. Specifically, the videos are manually analyzed in order to observe the movements of all parts of the swimmer's body during the exercise and to give indications for improving swimming technique. This operation is time-consuming, laborious and error prone. In recent years, alternative technologies have been introduced in the literature, but they still have severe limitations that make their correct and effective use impossible. In fact, the currently available techniques based on image analysis only apply to certain swimming styles; moreover, they are strongly influenced by disturbing elements (i.e., the presence of bubbles, splashes and reflections), resulting in poor measurement accuracy. The use of wearable sensors (accelerometers or photoplethysmographic sensors) or optical markers, although they can guarantee high reliability and accuracy, disturb the performance of the athletes, who tend to dislike these solutions. In this work we introduce swimmerNET, a new marker-less 2D swimmer pose estimation approach based on the combined use of computer vision algorithms and fully convolutional neural networks. By using a single 8 Mpixel wide-angle camera, the proposed system is able to estimate the pose of a swimmer during exercise while guaranteeing adequate measurement accuracy. The method has been successfully tested on several athletes (i.e., different physical characteristics and different swimming technique), obtaining an average error and a standard deviation (worst case scenario for the dataset analyzed) of approximately 1 mm and 10 mm, respectively.

Light-Controlled Rotational Speed of an Acoustically Levitating Photomobile Polymer Film.

In this work, we study the light-induced changes of the rotational speed of a thin photomobile film using a single-axis acoustic levitator operating at 40 kHz. In our experiments, a 50 µm thick photomobile polymer film (PMP) is placed in one of the nodes of a stationary acoustic field. Under the action of the field, the film remains suspended in air. By externally perturbing this stable equilibrium condition, the film begins to rotate with its natural frequency. The rotations are detected in real time by monitoring the light of a low power He-Ne laser impinging on and reflected by the film itself. During the rotational motion, an external laser source is used to illuminate the PMP film; as a consequence, the film bends and the rotational speed changes by about 20 Hz. This kind of contactless long-distance interaction is an ideal platform for the development and study of many electro-optics devices in microgravity and low-friction conditions. In particular, we believe that this technology could find applications in research fields such as 3D dynamic displays and aerospace applications.

Correction of Substrate Spectral Distortion in Hyper-Spectral Imaging by Neural Network for Blood Stain Characterization.

In the recent past, hyper-spectral imaging has found widespread application in forensic science, performing both geometric characterization of biological traces and trace classification by exploiting their spectral emission. Methods proposed in the literature for blood stain analysis have been shown to be effectively limited to collaborative surfaces. This proves to be restrictive in real-case scenarios. The problem of the substrate material and color is then still an open issue for blood stain analysis. This paper presents a novel method for blood spectra correction when contaminated by the influence of the substrate, exploiting a neural network-based approach. Blood stains hyper-spectral images deposited on 12 different substrates for 12 days at regular intervals were acquired via a hyper-spectral camera. The data collected were used to train and test the developed neural network model. Starting from the spectra of a blood stain deposited in a generic substrate, the algorithm at first recognizes whether it is blood or not, then allows to obtain the spectra that the same blood stain, at the same time, would have on a reference white substrate with a mean absolute percentage error of 1.11%. Uncertainty analysis has also been performed by comparing the ground truth reflectance spectra with the predicted ones by the neural model.

Rivers' Water Level Assessment Using UAV Photogrammetry and RANSAC Method and the Analysis of Sensitivity to Uncertainty Sources.

Water-level monitoring systems are fundamental for flood warnings, disaster risk assessment and the periodical analysis of the state of reservoirs. Many advantages can be obtained by performing such investigations without the need for field measurements. In this paper, a specific method for the evaluation of the water level was developed using photogrammetry that is derived from images that were recorded by unmanned aerial vehicles (UAVs). A dense point cloud was retrieved and the plane that better fits the river water surface was found by the use of the random sample consensus (RANSAC) method. A reference point of a known altitude within the image was then exploited in order to compute the distance between it and the fitted plane, in order to monitor the altitude of the free surface of the river. This paper further aims to perform a critical analysis of the sensitivity of these photogrammetric techniques for river water level determination, starting from the effects that are highlighted by the state of the art, such as random noise that is related to the image data quality, reflections and process parameters. In this work, the influences of the plane depth and number of iterations have been investigated, showing that in correspondence to the optimal plane depth (0.5 m) the error is not affected by the number of iterations.

Testing Surgical Face Masks in an Emergency Context: The Experience of Italian Laboratories during the COVID-19 Pandemic Crisis.

The first wave of the COVID-19 pandemic brought about a broader use of masks by both professionals and the general population. This resulted in a severe worldwide shortage of devices and the need to increase import and activate production of safe and effective surgical masks at the national level. In order to support the demand for testing surgical masks in the Italian context, Universities provided their contribution by setting up laboratories for testing mask performance before releasing products into the national market. This paper reports the effort of seven Italian university laboratories who set up facilities for testing face masks during the emergency period of the COVID-19 pandemic. Measurement set-ups were built, adapting the methods specified in the EN 14683:2019+AC. Data on differential pressure (DP) and bacterial filtration efficiency (BFE) of 120 masks, including different materials and designs, were collected over three months. More than 60% of the masks satisfied requirements for DP and BFE set by the standard. Masks made of nonwoven polypropylene with at least three layers (spunbonded-meltblown-spunbonded) showed the best results, ensuring both good breathability and high filtration efficiency. The majority of the masks created with alternative materials and designs did not comply with both standard requirements, resulting in suitability only as community masks. The effective partnering between universities and industries to meet a public need in an emergency context represented a fruitful example of the so-called university "third-mission".

The Rhodes electric piano: Analysis and simulation of the inharmonic overtones.

The Rhodes piano is an electromechanical keyboard instrument, released for the first time in 1946 and subsequently manufactured for at least four decades, reaching an iconic status and being now generally referred to as the electric piano. A few academic works discuss its operating principle and propose different physical modeling strategies; however, the inharmonic modes that characterize the attack transient have not been subject of a dedicated study before. This study addresses this topic by first observing the spectrum at the pickup output, applying a psychoacoustic model to assess perceptual relevance, and then conducts a series of scanning laser Doppler vibrometry (SLDV) experiments on the Rhodes asymmetric tuning fork. This study compares the modes of the Rhodes piano to those of its individual parts, allowing for the extraction of important information regarding role and natural modes. On the basis of this study, numerical experiments are conducted that show the intermodulation of the modes due to the magnetic pickup and allow the tones produced by the Rhodes from the collected data to be closely matched. Finally, this study is able to extract the distribution of the most important modes found on the whole keyboard range of a Rhodes piano, which can be useful for sound synthesis.

A Smartphone Integrated Hand-Held Gap and Flush Measurement System for in Line Quality Control of Car Body Assembly.

This paper presents the design and the characterization of a portable laser triangulation measurement system for measuring gap and flush in the car body assembly process. Targeting Human in the Loop (HILT) operations in the manufacturing sector, and in line with the vision of human empowerment with Industry 4.0 technologies, the instrument embeds features to ease operators' activity and compensate possible misuse that could affect the robustness and the quality of data acquired. The device is based on a smartphone integrated with a miniaturized laser triangulation system installed in a cover. The device embodies additional sensors and control systems in order to guarantee operators' safety (switching on and off the laser line based on specific conditions), support operators during the measurement execution task, and optimize the image acquisition process for minimizing the uncertainty associated to the measurement. The smartphone performs on-board processing and allows Wi-Fi communication with the plant IT infrastructure. Compliance to Industry 4.0 requirements is guaranteed using OPC-UA (Open Platform Communications-Unified Architecture) communication protocol enabling the exchange of live data with the plant middleware. The smartphone provides also an advanced high-resolution color display and well proven and ergonomic human-machine interfaces, which have been fully exploited in the design. The paper introduces the system optical layout and then presents the algorithms implemented to realize the gap and flush measurement. The paper finally presents the calibration of the instrument and estimates its calibration uncertainty in laboratory conditions. Then it discusses how performance decays when the operator handles the instrument on a reference car body. Finally, it shows the analysis of uncertainty when the device is used on real car bodies of different colors in a production line. It is observed that the measurement uncertainty of the whole measurement chain (measurand + instrument + operator + uncontrolled environmental conditions) is larger than the instrument calibration uncertainty because the measurement process is affected by the operator and the variable conditions of the production line.

Recurrent papillary urothelial neoplasm of low malignant potential. Subtle architectural disorder detected by quantitative analysis in DAXX-immunostained tissue sections.

The aim of the study was to identify subtle changes in the so-called architectural predominant order in nonrecurrent and recurrent papillary urothelial neoplasm of low malignant potential (PUNLMP). Quantitative analysis was performed with a software package written in LabVIEW (National Instruments, Austin, TX) in DAXX-immunostained tissue sections. Twelve cases of PUNLMP with papillary fronds sectioned lengthwise through the core were investigated and subdivided as follows: 7 nonrecurrent and 5 recurrent PUNLMP cases. Six cases of normal urothelium (NU) were included. When an epithelial thickness threshold is set at 108 µm (ie, 400 pixels), there is a complete separation between NU and PUNLMP; however, nonrecurrent and recurrent cases fall in the same range of thickness. In setting a nuclear elongation factor threshold at 2.1, there are differences between the 2 PUNLMP groups, recurrent PUNLMP and NU cases, showing a somewhat similar proportion of elongated nuclei. The nuclear orientation separates nonrecurrent from recurrent PUNLMP groups; however, NU cases do not appear as a separate group from the 2 PUNLMP groups. In combining epithelial thickness, nuclear elongation, and orientation in a multivariate analysis, the 2 PUNLMP groups appear separate between them and from NU. NU is less thickened than the 2 PUNLMP groups and shows a combination of elongated and less elongated nuclei. Elongated nuclei are more numerous in nonrecurrent PUNLMP, whereas the nuclei in recurrent PUNLMP are less elongated and less polarized than in the other group. Such finding can be used routinely to identify those PUNLMP patients who will have recurrence.

Immunohistochemical analysis of chromatin remodeler DAXX in high grade urothelial carcinoma.

BACKGROUND/AIMS: The chromatin remodeler DAXX, a predominantly nuclear protein, regulates the status of chromatin organization. The aim of this exploratory immunohistochemical study was to evaluate DAXX protein expression in high grade invasive urothelial carcinoma (UC) of the bladder as a biological regulator of aggressiveness. METHODS: Quantitative analysis was made on DAXX immunostained nuclei in tissue sections from 5 cases of bladder normal urothelium (NU) and 5 cases of bladder pT1 UC. Carcinoma in situ (CIS) and high grade papillary carcinoma (HGPCa) were identified in 2 out of 5 UC cases. RESULTS: The nuclei in UC show an open configuration of the chromatin composed of granules varying in size and distribution and a mean nuclear area 1.7 times greater than that in NU (UC: mean and SD 24.4 ± 11.4 square microns; NU: 14.8 6.5 square microns. The differences are statistically significant). 70% of the NU nuclei are immunostained, whereas 90% of UC nuclei are positive. The mean gray level value in UC, related to the intensity of nuclear immunostaining, is lower than in NU by a factor of 0.94 (UC: mean and SD 100 ± 15; NU: 106 ± 15. The differences are statistically significant). In particular, the value in the nuclei adjacent to the stroma in UC is slightly lower than in the intermediate cell layers by factor of 0.98, whereas in NU it is slightly greater by a factor 1.02 and 1.04 compared to the intermediate and superficial cell layers. The values in CIS and HGPCa are similar to those in UC. CONCLUSIONS: The quantitative immunohistochemical analysis shows an altered protein expression of chromatin remodeler DAXX in UC and in its preinvasive phases, when compared to NU. DAXX evaluation, if associated with markers related to global DNA methylation and histone acetylation, could be used in clinical practice as a marker of aggressiveness. VIRTUAL SLIDES: The virtual slides for this article can be found here:http://www.diagnosticpathology.diagnomx.eu/vs/1398457297102379.

Phase mapping of acoustic sources by beamforming and iterative far field monopole substitution.

The first aim of this paper is to give emphasis to the importance of assessing phase information when reconstructing and mapping a sound field. In fact, in acoustic analysis phase distribution is frequently simply either not considered or ignored, even though it can supply very useful information for the understanding of the mapping itself or for further analyses. In this paper a procedure to carry out phase mapping of acoustic sources in beamforming measurement is illustrated. The second aim of this paper is to propose a straightforward iterative optimization algorithm based on the monopole substitution starting from beamforming results. It allows for the reconstruction of sound field without the use of any matrix inversion. Both numerical and experimental validations of the method are presented. Results shown hereafter prove the effectiveness of the approach.

System for measuring the coordinates of tire surfaces in transient conditions when rolling over obstacles: description of the system and performance analysis.

This paper describes the development of a system for measuring surface coordinates (commonly known as "shape measurements") which is able to give the temporal evolution of the position of the tire sidewall in transient conditions (such as during braking, when there are potholes or when the road surface is uneven) which may or may not be reproducible. The system is based on the well-known technique of projecting and observing structured light using a digital camera with an optical axis which is slanted with respect to the axis of the projector. The transient nature of the phenomenon has led to the development of specific innovative solutions as regards image processing algorithms. This paper briefly describes the components which make up the measuring system and presents the results of the measurements carried out on the drum bench. It then analyses the performance of the measuring system and the sources of uncertainty which led to the development of the system for a specific dynamic application: impact with an obstacle (cleat test). The measuring system guaranteed a measurement uncertainty of 0.28 mm along the Z axis (the axial direction of the tire) with a measurement range of 250(X) x 80(Y) x 25(Z) mm(3), with the tire rolling at a speed of up to 30 km/h.

Particle image velocimetry for flow analysis in longitudinal planes across a mechanical artificial heart valve.

In the last decades a great number of in vitro studies have been conducted to improve the design and to understand the transvalvular flow patterns under steady-state and pulsating flow conditions. Steady-state tests are useful for studying the flow established upstream and downstream of the valve prosthesis in different flow conditions and, in particular, at the peak flow rate. In the present study, the particle image velocimetry (PIV) technique is employed to visualize the flow patterns in a precommercial model of a bi-leaflet mechanical heart valve prosthesis in a steady-state flow regime. The use of the PIV technique and a convenient test rig provide good conditions with which to investigate the whole flow field upstream and downstream of the valve. Velocity and vorticity maps are obtained for the flow passing through the prosthesis in different axial planes. A new and simple solution for the measurement test chamber is proposed. This innovative approach of observing the flow in staggered planes (other than diametrical planes) allows a flow analysis to be performed upstream and downstream of the valve in regions near the tube wall where it has the maximum potential for injury of the vessel's inner cell layer.