Comparing Online Webcam- and Laboratory-Based Eye-Tracking for the Assessment of Infants’ Audio-Visual Synchrony Perception

Online data collection with infants raises special opportunities and challenges for developmental research. One of the most prevalent methods in infancy research is eye-tracking, which has been widely applied in laboratory settings to assess cognitive development. Technological advances now allow conducting eye-tracking online with various populations, including infants. However, the accuracy and reliability of online infant eye-tracking remain to be comprehensively evaluated. No research to date has directly compared webcam-based and in-lab eye-tracking data from infants, similarly to data from adults. The present study provides a direct comparison of in-lab and webcam-based eye-tracking data from infants who completed an identical looking time paradigm in two different settings (in the laboratory or online at home). We assessed 4-6-month-old infants (n = 38) in an eye-tracking task that measured the detection of audio-visual asynchrony. Webcam-based and in-lab eye-tracking data were compared on eye-tracking and video data quality, infants’ viewing behavior, and experimental effects. Results revealed no differences between the in-lab and online setting in the frequency of technical issues and participant attrition rates. Video data quality was comparable between settings in terms of completeness and brightness, despite lower frame rate and resolution online. Eye-tracking data quality was higher in the laboratory than online, except in case of relative sample loss. Gaze data quantity recorded by eye-tracking was significantly lower than by video in both settings. In valid trials, eye-tracking and video data captured infants’ viewing behavior uniformly, irrespective of setting. Despite the common challenges of infant eye-tracking across experimental settings, our results point toward the necessity to further improve the precision of online eye-tracking with infants. Taken together, online eye-tracking is a promising tool to assess infants’ gaze behavior but requires careful data quality control. The demographic composition of both samples differed from the generic population on caregiver education: our samples comprised caregivers with higher-than-average education levels, challenging the notion that online studies will per se reach more diverse populations.

Design Of Portable Injection Waste Destruction Machine With Sterilization System

The Community Health Center (Puskesmas) does not yet have special facilities for treating medical waste such as hospitals. Hospital/Puskesmas waste and waste generated by hospital activities and other supporting activities. Make a machine that destroys waste injection equipment equipped with a knife made of SKD as a plastic syringe destroyer. Design of a syringe crushing machine in the form of needles and syringes, Analyze the von misses stress received by the frame structure of the syringe crusher, Analyze the displacement by the load received by the frame structure of the syringe crusher, Analyze the safety factor of the frame structure of the crusher syringe. Analyzing using solidworks 2016 software, the results obtained are the maximum value of von misses, displacement, and safety of factor from the lower frame of the syringe waste crusher machine. Von misses stress obtained in the analysis using Solidworks 2016 gets a value of 48.54 Mpa in software calculations, while in theoretical calculations it is 48.01 Mpa. The percentage of errors calculated by software and theory is 1%. The displacement obtained in the analysis using Solidworks 2016 software is 0.34 mm in theoretical calculations of 0.35 mm. The percentage of errors calculated by software and theory is 2%. The safety factor obtained in the solidwork analysis gets a value of 4.7 ul (upper limit), while the theoretical calculation is 5.2 ul (upper limit) which means this frame is declared safe when the engine is operating.

Robot movement controller based on dynamic facial pattern recognition

In terms of movement, mobile robots are equipped with various navigation techniques. One of the navigation techniques used is facial pattern recognition. But Mobile robot hardware usually uses embedded platforms which have limited resources. In this study, a new navigation technique is proposed by combining a face detection system with a ram-based artificial neural network. This technique will divide the face detection area into five frame areas, namely top, bottom, right, left, and neutral. In this technique, the face detection area is divided into five frame areas, namely top, bottom, right, left, and neutral. The value of each detection area will be grouped into the ram discriminator. Then a training and testing process will be carried out to determine which detection value is closest to the true value, which value will be compared with the output value in the output pattern so that the winning discriminator is obtained which is used as the navigation value. In testing 63 face samples for the Upper and Lower frame areas, resulting in an accuracy rate of 95%, then for the Right and Left frame areas, the resulting accuracy rate is 93%. In the process of testing the ram-based neural network algorithm pattern, the efficiency of memory capacity in ram, the discriminator is 50%, assuming a 16-bit input pattern to 8 bits. While the execution time of the input vector until the winner of the class is under milliseconds (ms).

Design of Vehicle Lifting Equipment Using Progressive Methods

The main objective of this article is to analyse the structural design of tire lifting equipment for tire services. To gain a better insight into the problem, several steps must be taken. The first step is to conduct a market analysis, which involves identifying all available equipment. Several types of lifting devices were distinguished within the development process, which differ from each other in terms of design and power supply. The type of structure and power unit represent the second steps in the design process. This is a critical aspect of the design since the forces necessary to move the system change as a result of these attributes. The design itself is the last step in the device’s design. Passenger cars differ from each other by their weight, which is limited to 3.5 tons. Based on the weight, basic strength calculation and dimensioning of the lifting device are carried out. Based on the calculations, the scissor lift device is selected. The lower frame, scissor legs, ramp, mechanical lock, and scissors drive mechanism are five main components of the device. This type of structure is best used with a hydraulic drive unit, which is calculated in the article.

Multivariate Gabor frames for operators in matrix-valued signal spaces over locally compact abelian groups

In this paper, we study multivariate Gabor frames in matrix-valued signal spaces over locally compact abelian (LCA) groups, where the lower frame condition depends on a bounded linear operator [Formula: see text] on the underlying matrix-valued signal space. This type of Gabor frame is also known as a multivariate [Formula: see text]-Gabor frame. By extending work of Gǎvruta, we present necessary and sufficient conditions for the existence of [Formula: see text]-Gabor frames of multivariate matrix-valued Gabor systems. Some operators which can transform multivariate matrix-valued Gabor and [Formula: see text]-Gabor frames into [Formula: see text]-Gabor frames in terms of adjointable operators are discussed. Finally, we give a Paley–Wiener-type perturbation result for multivariate matrix-valued [Formula: see text]-Gabor frames.

Some curious results related to a conjecture of Strohmer and Beaver

We study results related to a conjecture formulated by Strohmer and Beaver about optimal Gaussian Gabor frame set-ups. Our attention will be restricted to the case of Gabor systems with standard Gaussian window and rectangular lattices of density 2. Although this case has been fully treated by Faulhuber and Steinerberger, the results in this work are new and quite curious. Indeed, the optimality of the square lattice for the Tolimieri and Orr bound already implies the optimality of the square lattice for the sharp lower frame bound. Our main tools include determinants of Laplace–Beltrami operators on tori as well as special functions from analytic number theory, in particular Eisenstein series, zeta functions, theta functions and Kronecker’s limit formula. We note that our results also carry over to energy minimization problems over lattices and a heat distribution problem over flat tori.

GALLERIA MELLONELLA L. GARBAGE SORTING MECHANIZATION TECHNOLOGY

In the modern world, insects are widely used for scientific and industrial purposes. For their cultivation in the laboratory, various plants have been developed, the main disadvantage of which is poor-quality sorting from garbage. Therefore, the question of cultivating and sorting the larvae of bee moth (Galleria mellonella L.) in laboratory conditions for the purpose of further use as a model object in various fields of biological sciences and medical purposes is relevant. The effect of the temperature gradient and exposure on the movement of G. mellonella larvae from the heated compartment of the plant was determined by their reproduction into the cold by the number of individuals that moved for 10, 15, and 20 minutes at 35, 40, 45, 50, 55 0С, visual counting. At 35 0С, regardless of the exposure time, the larvae remained on a honeycomb frame; at 40 ° C and 45 0С, on average, 11.5% and 31.8% of individuals, respectively, moved. The higher the temperature gradient, the faster the larvae moved into the cold compartment. More larvae passed from the lower frame to it than from the upper one. The difference at a temperature of 45 ° C averaged 2%, 50 0С - 18.7%, 55 0С - 0.4%. The optimum temperature gradient for sorting larvae is 50 ... 55 0С during an exposure of 15 ... 20 minutes, in this case more than 98% of the larvae were transferred to the cold compartment. The use of an infrared electric heating system will optimize the breeding process of G. mellonella larvae and ensure their high-quality sorting

Realistic Dynamic Numerical Phantom for MRI of the Upper Vocal Tract

Dynamic and real-time MRI (rtMRI) of human speech is an active field of research, with interest from both the linguistics and clinical communities. At present, different research groups are investigating a range of rtMRI acquisition and reconstruction approaches to visualise the speech organs. Similar to other moving organs, it is difficult to create a physical phantom of the speech organs to optimise these approaches; therefore, the optimisation requires extensive scanner access and imaging of volunteers. As previously demonstrated in cardiac imaging, realistic numerical phantoms can be useful tools for optimising rtMRI approaches and reduce reliance on scanner access and imaging volunteers. However, currently, no such speech rtMRI phantom exists. In this work, a numerical phantom for optimising speech rtMRI approaches was developed and tested on different reconstruction schemes. The novel phantom comprised a dynamic image series and corresponding k-space data of a single mid-sagittal slice with a temporal resolution of 30 frames per second (fps). The phantom was developed based on images of a volunteer acquired at a frame rate of 10 fps. The creation of the numerical phantom involved the following steps: image acquisition, image enhancement, segmentation, mask optimisation, through-time and spatial interpolation and finally the derived k-space phantom. The phantom was used to: (1) test different k-space sampling schemes (Cartesian, radial and spiral); (2) create lower frame rate acquisitions by simulating segmented k-space acquisitions; (3) simulate parallel imaging reconstructions (SENSE and GRAPPA). This demonstrated how such a numerical phantom could be used to optimise images and test multiple sampling strategies without extensive scanner access.

Inferring Surface Flow Velocities in Sediment-Laden Alaskan Rivers from Optical Image Sequences Acquired from a Helicopter

The remote, inaccessible location of many rivers in Alaska creates a compelling need for remote sensing approaches to streamflow monitoring. Motivated by this objective, we evaluated the potential to infer flow velocities from optical image sequences acquired from a helicopter deployed above two large, sediment-laden rivers. Rather than artificial seeding, we used an ensemble correlation particle image velocimetry (PIV) algorithm to track the movement of boil vortices that upwell suspended sediment and produce a visible contrast at the water surface. This study introduced a general, modular workflow for image preparation (stabilization and geo-referencing), preprocessing (filtering and contrast enhancement), analysis (PIV), and postprocessing (scaling PIV output and assessing accuracy via comparison to field measurements). Applying this method to images acquired with a digital mapping camera and an inexpensive video camera highlighted the importance of image enhancement and the need to resample the data to an appropriate, coarser pixel size and a lower frame rate. We also developed a Parameter Optimization for PIV (POP) framework to guide selection of the interrogation area (IA) and frame rate for a particular application. POP results indicated that the performance of the PIV algorithm was highly robust and that relatively large IAs (64–320 pixels) and modest frame rates (0.5–2 Hz) yielded strong agreement ( R 2 > 0.9 ) between remotely sensed velocities and field measurements. Similarly, analysis of the sensitivity of PIV accuracy to image sequence duration showed that dwell times as short as 16 s would be sufficient at a frame rate of 1 Hz and could be cut in half if the frame rate were doubled. The results of this investigation indicate that helicopter-based remote sensing of velocities in sediment-laden rivers could contribute to noncontact streamgaging programs and enable reach-scale mapping of flow fields.