3D Picture Research Articles

The accuracy of anatomic landmarks on the occlusal plane: a comparative study between conventional and 3D image method

BackgroundTo establish the occlusal plane, the conventional methods for facial analysis to gain accurate alignment of the occlusal plane are inadequate, while 3D technologies are an ideal diagnostic tool. The aims of this research are to compare the difference accuracy of anatomic landmarks on the occlusal plane and ala-tragus line between the conventional clinical method and 3D image method in both non-orthodontic and orthodontic treatment volunteers.MethodsA total of 44 volunteers (22 non-orthodontic and 22 orthodontic treatment volunteers) with normal occlusion were selected. All volunteers received 2 operative methods for occlusal plane determination. In conventional method, the occlusal plane was defined by the fox plane line. The ala-tragus line was defined by the radio-opaque markers. In the 3D image method, the volunteers were recorded intraoral images, 3D facial images and CBCT images. A 3D virtual picture was created using EXOCAD® software. The occlusal plane was generated by the incisal and occlusal surfaces of the teeth. Both methods, the angles and distances between the occlusal plane and ala-tragus line were measured and compared statistically on both sides of each volunteer.ResultsBoth volunteers’ group, the mean angles and distances between the occlusal plane-ala tragus line in the conventional method were reported to be significantly greater than the 3D method (P < 0.05). The percentage difference of angles in conventional method were reported to be significantly higher by 13.61–21.58% (p < 0.05) compared to the 3D method. The percentage difference of distances in the conventional method were reported to be significantly greater than the 3D method by 4.73–7.51% (p < 0.05).ConclusionsWithin the limitation of the study, it can be concluded that both conventional and digital methods for establishing the occlusal plane are not parallel to the occlusal plane. The occlusal plane and ala-tragus line in the conventional method and the 3D method were significantly different in terms of angles and distances in both non-orthodontic and orthodontic treatment volunteers. However, the deviation angle of both methods is approximately 13–20 degrees, which is clinically acceptable for occlusal plane establishment. The accuracy of both methods is still within the using in clinical implementation.

Handwritten Digit Recognition Using Logistic Regression

With applications in optical character recognition (OCR), digitizing historical documents, and automating data entry procedures, handwritten digit recognition is crucial to pattern recognition and machine learning. This work develops a handwritten digit recognition system using logistic regression. The main objective is to use the MNIST dataset to develop a precise and effective model for classifying handwritten numbers from 0 to 9. Data collection, preprocessing, model installation, training, assessment, and analysis are all included in the methodology. Normalizing pixel values and flattening 2D picture matrices into 1D vectors are steps in the preprocessing process. Using gradient descent optimization, the logistic regression model set up for multi- class classification minimizes the cost function. A testing set will be used to assess performance, and metrics including F1 score, recall, accuracy, and precision will be used. A very precise logistic regression model for handwritten digit identification is the anticipated result. The model's advantages and disadvantages will be emphasized through thorough analysis and visualization, which will include learning weights, biases, and incorrectly categorized images. This work offers useful solutions for automation, postal services, and digital archiving, furthering the field of pattern recognition and highlighting the significance of logistic regression in machine learning.

Investigating explosive events in a 3D quiet-Sun model: Transition region and coronal response

Transition region explosive events are characterized by the non-Gaussian profiles of the emission lines that form at transition region temperatures, and they are believed to be manifestations of small-scale reconnection events in the transition region. Traditionally, the enhanced emission at the line wings is interpreted as bi-directional outflows generated by the reconnection of oppositely directed magnetic fields. We investigate whether the 2D picture also holds in a more realistic setup of a 3D radiation magnetohydrodynamic (MHD) quiet-Sun model. We also compare the thermal responses in the transition region and corona of different events. We took a 3D self-consistent quiet-Sun model extending from the upper convection zone to the lower corona calculated using the MURaM code. We first synthesized the Si iv line profiles from the model and then located the profiles which show signatures of bi-directional flows. These tend to appear along network lanes, and most do not reach coronal temperatures. We isolated two hot events (around 1 MK) and one cool event (order of 0.1 MK) and examined the magnetic field evolution in and around these selected events. Furthermore, we investigated why some explosive events reach coronal temperatures, while most remain cool. We also examined the emission of these events as seen in the 174 AA passband of the Extreme Ultraviolet Imager (EUI) on board Solar Orbiter and all coronal passbands of the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO). The field lines around two events reconnect at small angles (i.e., they undergo component reconnection). The third case is associated with the relaxation of a highly twisted flux rope. All three events reveal signatures in the synthesized EUI 174 AA images. The intensity variations in two events are dominated by variations of the coronal emissions, while the cool component seen in the respective channel contributes significantly to the intensity variation in one case. In comparison, one hot event is embedded in regions with higher magnetic field strength and heating rates while the densities are comparable, and the other hot event is heated to coronal temperatures mainly because of the low density. Small-scale heating events seen in the extreme-ultraviolet (EUV) channels of AIA or EUI might be hot or cool. Our results imply that the major difference between the events in which coronal counterparts dominate or not is the amount of converted magnetic energy and/or density in and around the reconnection region.

A Stride Toward Wine Yield Estimation from Images: Metrological Validation of Grape Berry Number, Radius, and Volume Estimation.

Yield estimation is a key point theme for precision agriculture, especially for small fruits and in-field scenarios. This paper focuses on the metrological validation of a novel deep-learning model that robustly estimates both the number and the radii of grape berries in vineyards using color images, allowing the computation of the visible (and total) volume of grape clusters, which is necessary to reach the ultimate goal of estimating yield production. The proposed algorithm is validated by analyzing its performance on a custom dataset. The number of berries, their mean radius, and the grape cluster volume are converted to millimeters and compared to reference values obtained through manual measurements. The validation experiment also analyzes the uncertainties of the parameters. Results show that the algorithm can reliably estimate the number (MPE=-5%, σ=6%) and the radius of the visible portion of the grape clusters (MPE=0.8%, σ=7%). Instead, the volume estimated in px3 results in a MPE=0.4% with σ=21%, thus the corresponding volume in mm3 is affected by high uncertainty. This analysis highlighted that half of the total uncertainty on the volume is due to the camera-object distance d and parameter R used to take into account the proportion of visible grapes with respect to the total grapes in the grape cluster. This issue is mostly due to the absence of a reliable depth measure between the camera and the grapes, which could be overcome by using depth sensors in combination with color images. Despite being preliminary, the results prove that the model and the metrological analysis are a remarkable advancement toward a reliable approach for directly estimating yield from 2D pictures in the field.

Effects of 3D ultrasonography and 3D printed images on maternal-fetal attachment and its correlation with overall smoking within pregnancy: a pilot study

BackgroundSmoking in pregnancy continues to cause significant morbidity to mothers and babies and contributes to tremendous costs to society. Maternal-fetal attachment (MFA) may differentiate smokers who quit or pregnant smokers from non-smokers. Researchers have recommended utilizing interventions that improve MFA to help decrease smoking within pregnancy.MethodsWe performed a randomized clinical trial of pregnant smokers (n = 33) using an MFA-informed, intention-to-treat protocol. We recruited pregnant smokers and provided timeline follow back (TLFB) interviews from 27 weeks of pregnancy until 6 weeks post-partum. Salivary cotinine was also collected at five different time points. 3D ultrasonography was performed, and patients were randomly assigned a 3D picture or a 3D model of their fetus.ResultsOverall, the average percent reduction in cigarette use was 37.03% (SD = 31.18). The main effect of 3D type was not significant (3D Model vs. 3D Print Estimate = -0.09, 95% CI: − 0.19 to 0.01, p = 0.066). A total of 4 patients (12%) quit smoking within one week of delivery. A 10% reduction in cigarette use was associated with a 30.57 g increase in birth weight (Estimate = 30.57, 95% CI: -14.15 to 75.29); a 10% reduction in cigarette use was associated with a 0.14 week increase in estimate gestational age at delivery (Estimate = 0.14, 95% CI: -0.01 to 0.28).ConclusionsPatients who smoke in pregnancy decrease the number of cigarettes smoked after receiving either a 3D picture or 3D model of their fetus.Trial registrationclinicaltrials.gov (NCT04541121).

Quantum chemical calculations and molecular docking studies of 5-amino-3-(2,5-dimethoxyphenyl)-1-isonicotinoyl-2,3-dihydro-1H-pyrazole-4-carbonitrile

Abstract The five-membered heterocycle pyrazole has two nitrogen atoms next to each other. Natural items and pharmaceuticals using pyrazole as the nucleus have demonstrated a wide range of biological activity. Medications with pyrazole cores may have better pharmacokinetics and pharmacological effects than medicines with similar heterocyclic rings. This is because the pyrazole core has unique physicochemical properties. In this study, 5-amino-3-(2,5-dimethoxyphenyl)-1-isonicotinoyl-2,3-dihydro-1H-pyrazole-4-carbonitrile is synthesized and characterized by means of spectrum and quantum chemical techniques. Using UV–vis absorption technique, Fourier transform infrared (FT-IR), and Fourier transform Raman (FT-Raman) techniques, the spectroscopic properties were examined. There were two regions visible in the experimental Raman as well as infrared spectra: 4,000–400 cm−1 along with 4,000–100 cm−1. The ideal molecular shape, vibrational frequencies, infrared intensity levels, and scattering from Raman were all assessed using density functional theory. The 13C (carbon) and 1H (proton) chemical shifts of the molecule were determined using nuclear magnetic resonance (NMR). The TD-DFT scheme was utilized to figure out speculative ultraviolet values and compare them to oscillator strength, electron excitation energies, and spectrum data from experiments. It is evident from the predicted HOMO-LUMO band separation energies that the transmission of charge takes place within a molecule’s structure. The chemical reactivity of the molecule has been calculated along with other global descriptive properties. Scientists investigated how charges move and the density of electrons inside a molecule using NBO analysis of the chemical they were studying. After examining the molecular electrostatic potential (MEP), a 3D picture was created that shows the compound’s nucleophilic and electrophilic areas. In addition to meeting all pertinent pharmacokinetic requirements, 5-amino-3-(2,5-dimethoxyphenyl)-1-isonicotinoyl-2,3-dihydro-1H-pyrazole-4-carbonitrile is also readily absorbed by the gastrointestinal system. Additionally, the chemical that was synthesized had a positive interaction with the target proteins of treatments for viruses, asthma, and heart failure, as shown by molecular docking.

SwinVNETR: Swin V-net Transformer with non-local block for volumetric MRI Brain Tumor Segmentation

Brain Tumor Segmentation (BTS) and classification are important and growing research fields. Magnetic resonance imaging (MRI) is commonly used in the diagnosis of brain tumours owing to its low radiation exposure and high image quality. One of the current subjects in the field of medical imaging is how to quickly and precisely segment MRI scans of brain tumours. Unfortunately, most existing brain tumour segmentation algorithms use inadequate 2D picture segmentation methods and fail to capture the spatial correlation between features. In this study, we propose a segmentation model (SwinVNETR) Swin V-NetTRansformer-based architecture with a non-local block. This model was trained using the Brain Tumor Segmentation Challenge BraTS 2021 dataset. The Dice similarity coefficients for the enhanced tumour (ET), whole tumour (WT), and tumour core (TC) are 0.84, 0.91, and 0.87, respectively. By leveraging this methodology, we can segment brain tumours more accurately than ever before. In conclusion, we present the findings of our model through the application of the Grad-CAM methodology, an eXplainable Artificial Intelligence (XAI) technique utilized to elucidate the insights derived from the model, which helped in better understanding; doctors can better diagnose and treat patients with brain tumours.

4D Tomography for neutron depth profiling applications

High-rate Neutron Depth Profiling (NDP) is a very efficient and precise probe for studying the evolution of lithium concentration in thin-layer structures, e.g., battery electrodes. NDP is typically limited to a one-dimensional depth analysis summed over the profile area covered by the neutron beam. We developed a detector system based on double-sided silicon strip detectors (DSSSD) with extremely thin and homogeneous entrance windows to provide a new quality of NDP measurements in 3+1 dimensions for the N4DP instrument at the FRM II in Garching, Germany. Using the 6Li(n, α)3H reaction in an experiment conducted at the research reactor in Delft, we achieved a lateral position resolution down to ∼100μm and an energy resolution with FWHM≈10keV for the triton particles at energies of 2.7MeV. High-resolution 3D pictures with a contrast uncertainty <10% per pixel can be achieved faster than 1 picture per minute. This rate can be adjusted individually for each experiment by sacrificing granularity in the position measurement.

A 3D picture of moist-convection inhibition in hydrogen-rich atmospheres: Implications for K2-18 b

While small Neptune-like planets are among the most abundant exoplanets, our understanding of their atmospheric structure and dynamics remains sparse. In particular, many unknowns remain regarding the way moist convection works in these atmospheres, where condensable species are heavier than the non-condensable background gas. While it has been predicted that moist convection could cease above some threshold abundance of these condensable species, this prediction is based on simple linear analysis and relies on some strong assumptions regarding the saturation of the atmosphere. To investigate this issue, we developed a 3D cloud-resolving model for hydrogen-dominated atmospheres with large amounts of condensable species and applied it to a prototypical temperate Neptune-like planet – K2-18 b. Our model confirms the inhibition of moist convection above a critical abundance of condensable vapor and the onset of a stably stratified layer in the atmosphere of such planets, which leads to much hotter deep atmospheres and interiors. Our 3D simulations further provide quantitative estimates of the turbulent mixing in this stable layer, which is a key driver of the cycling of condensables in the atmosphere. This allowed us to build a very simple, yet realistic, 1D model that captures the most salient features of the structure of Neptune-like atmospheres. Our qualitative findings on the behavior of moist convection in hydrogen atmospheres go beyond temperate planets and should also apply to regions where iron and silicates condense in the deep interior of hydrogen-dominated planets. Finally, we used our model to investigate the likelihood of a liquid ocean beneath an H2-dominated atmosphere on K2-18 b. We find that the planet would need to have a very high albedo (A &gt; 0.5–0.6) to sustain a liquid ocean. However, due to the spectral type of the star, the amount of aerosol scattering that would be needed to provide such a high albedo is inconsistent with the latest observational data.

Lower Blepharoplasty with Mid-Face Elevation: A Polydioxanone (PDO) Barbed Suture Loop for Lid-Cheek Junction Blending.

Anti-aging in the lower eyelid-cheek junction area has always been the most widely sought cosmetic surgery. However, orbital fat removal or a midcheek fat pad lift alone does not achieve the best results. This study describes a new technique of lower blepharoplasty combined with a midcheek lift performed using a polydioxanone barbed suture loop based on the entire anatomy of the lower eyelid-cheek junction area. We report our experience with lower blepharoplasty combined with a midcheek lift, covering 38 procedures performed over the past 3 years. We reviewed the technique and results and described the various indications for which the new technique is suitable. The efficacy of the surgeries was delineated using both 3D volume calculation and graphic pictures. All patients demonstrated significant rejuvenation of the lower eyelid with the elimination of the eyebags, elevation of the lid-cheek junction, and improvement of the nasolabial folds. All the patients were satisfied with the procedure. Complication rates were low, and lower lid retraction temporarily occurred in 3% of patients. This new method of lower blepharoplasty with midcheek elevation is safe, effective, convenient, and long-lasting. The technique is more doctor-friendly, recovery is quick, and complications are minimized. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Sailfish optimizer based CLAHE with U-NET for MRI brain tumour segmentation

Semantic brain tumour segmentation is a significant contribution to medical image processing. This research is helpful for doctors making diagnoses and determining the severity of lesions. In recent years, convolutional neural networks have sometimes been known as self-remarkable representations in computer vision tasks. In three-dimensional medical image processing, CNN with architecture and skip connections has become increasingly popular. However, they are inadequate at both acquiring nearby and far-off semantic knowledge. However, the transformer's use of a vision. This accomplishment was made possible by the global information modelling capabilities of the transformer. When tryingto perform challenging prediction tasks, such as segmenting 3D medical pictures, it is vital to consider local and global features. In this study, we propose a hypothesis that predicts pre-processing steps that enhance the image quality and significantly impact accuracy with any statistical image classification method. We used a better picture enhancement methodology to back up our idea. This method has three unique stages: a median filter to eliminate noise, a histogram equalisation technique to boost contrast, and a grayscale-to-RGB conversion. The clipping limit of contrast-limited Adaptive Histogram Equalisation (CLAHE)is calculated by the Sailfish Optimization Algorithm (SOA) to achieve optimal picture enhancement. This study classifies semantically segmenting 3D brain tumours as a sequence-to-sequence prediction problem. U-net is proposed in the article as a novel method for segmenting 3D medical images; it incorporates a structure. A new technique for segmenting 3D medical images, U-net, is emerging. We trained and assessed our method on the BRATS 2019 dataset, which was found to outperform state-of-the-art algorithms and be competitive under similar settings.

MatheMusical Virtual Museum: Virtual Reality application to explore Math-Music World

Virtual Reality is a promising tool for pedagogy in teaching music, and the MatheMusical Virtual Museum takes this promise to a new level. This study aims to share and describe the project's concept and advancement, including expertise and collected experiences in MatheMusic. Mathemusic is the scientific field that studies the relations between math and music; the Society for Mathematics and Computation in Music regroups worldwide researchers in the field. The Mathemusical Virtual Museum is an interactive virtual experience that premiered at the Museum of Design in Atlanta (Moda) in June 2022 (Baroin &amp; de Gérando, 2022). It contains a growing set of interactive models based on the research issued by our society. Mathemusicians have always produced models for understanding, analyzing, or computing music. Visualizing some on paper, theater, or computer screens is expected. Even if it is in a multidimensional space (3D-4D), the viewer ends up with a 2D picture or a movie while displaying these models on a computer screen. Planar projection limits the perception in the era of virtual reality nowadays. This study proposes tools and solutions to apprehend these models better and improve the viewer's immersive experience. Since the beginning of the project, user experiences were collected. Besides desperately unfit users for VR, we noticed that kids are highly engaged and immersed in the learning environment; music learners are not just improving their knowledge but also feeling inspired and hopeful about the future of music education; mathematicians and researchers are feeling like they are finally entering their creation and contributing to improving the project, thereby making significant contributions to their respective fields. Keywords: Virtual Reality, Mathemusic, Visualization, Pedagogy, Learning Strategy Received Date: January 31, 2024Revised Date: March 14 , 2024Accepted Date: April 25, 2024

Building a 3D Reconstruction System for Construction Scenes using Deep Learning Techniques

Due to the developing intricacy and size of construction projects and the way that construction plan the executives is still generally performed physically, many ventures run over financial plan and into legitimate difficulty as an immediate consequence of timetable deferrals. Albeit the result of existing 3D reconstruction techniques is many times a model with immense openings, bends, or foggy segments, the result of man-made intelligence-based 3D remaking procedures is commonly a model with straightforward disengaged pieces that are portrayed as 3D boxes. Hence, overall, these algorithmic systems are lacking for certified use. The focal goal of this study is to apply the creation inadequately organized network system to 3D diversion by setting up a generative seriously organized network model to a related state, subsequently influencing the possibility of the fundamental 3D redirection model. Late 2D pictures are expected as models with no previous information on the 3D concealed shape or reference experiences. The revelations of a standard benchmark for 3D diversion procedures uncover that this algorithmic construction beats state of the art methods. Exploratory results show that our algorithmic system defeats state of the art 3D replication procedures on a standard benchmark dataset for 3D changes.

Visualizing a bivariate discrete distribution and other distributions derived from it

AbstractA single discrete random variable is depicted by a stick diagram, a 2D picture. Naturally, to visualize a bivariate discrete distribution, one can use a bivariate stick diagram, a 3D picture. Unfortunately, many students have difficulty understanding and processing 3D pictures. Therefore, we construct an alternative 2D disc plot to depict the bivariate distribution of (, ), from which we obtain graphically the conditional distributions of given , and given ; the marginal distributions of , , , . Furthermore, we depict the mean and the standard deviation of each distribution using a single‐headed arrow. We hope these visualizations will help students better comprehend these concepts and avoid some misconceptions.

Testing memory of a VR environment: comparison with the real environment and 2D pictures

In recent years, there has been a growing trend in cognitive psychology research towards recreating experimental situations in virtual reality (VR). VR settings are thought to have higher ecological validity than laboratory settings using digital, two-dimensional (2D) pictures. Some studies have shown cognitive performance in VR settings to follow that of the real world. However, other studies obtained controversial results. The present study tested the memory performance of three groups of participants who were exposed to the same environment (a room) through different modalities: in real life, in VR, and through 2D pictures. The results highlighted that participants who were exposed to the target room in real life had an overall better memory performance, compared to participants who saw the room in VR or through 2D pictures. On the other hand, no differences in memory performance emerged between the VR and 2D picture groups, except for the non-suggestive verbal task. The results suggest that future research should be careful in assuming that performance in VR settings is comparable to real life and that VR is more ecological than traditional 2D media.

Cardiac Healthcare Digital Twins Supported by Artificial Intelligence-Based Algorithms and Extended Reality—A Systematic Review

Recently, significant efforts have been made to create Health Digital Twins (HDTs), Digital Twins for clinical applications. Heart modeling is one of the fastest-growing fields, which favors the effective application of HDTs. The clinical application of HDTs will be increasingly widespread in the future of healthcare services and has huge potential to form part of mainstream medicine. However, it requires the development of both models and algorithms for the analysis of medical data, and advances in Artificial Intelligence (AI)-based algorithms have already revolutionized image segmentation processes. Precise segmentation of lesions may contribute to an efficient diagnostics process and a more effective selection of targeted therapy. In this systematic review, a brief overview of recent achievements in HDT technologies in the field of cardiology, including interventional cardiology, was conducted. HDTs were studied taking into account the application of Extended Reality (XR) and AI, as well as data security, technical risks, and ethics-related issues. Special emphasis was put on automatic segmentation issues. In this study, 253 literature sources were taken into account. It appears that improvements in data processing will focus on automatic segmentation of medical imaging in addition to three-dimensional (3D) pictures to reconstruct the anatomy of the heart and torso that can be displayed in XR-based devices. This will contribute to the development of effective heart diagnostics. The combination of AI, XR, and an HDT-based solution will help to avoid technical errors and serve as a universal methodology in the development of personalized cardiology. Additionally, we describe potential applications, limitations, and further research directions.

How Do Children and Adolescents with ASD Look at Animals? A Scoping Review.

Autism spectrum disorder (ASD) is characterized by interaction and communication differences, entailing visual attention skill specificities. Interactions with animals, such as in animal-assisted interventions or with service dogs, have been shown to be beneficial for individuals with ASD. While interacting with humans poses challenges for them, engaging with animals appears to be different. One hypothesis suggests that differences between individuals with ASD's visual attention to humans and to animals may contribute to these interaction differences. We propose a scoping review of the research on the visual attention to animals of youths with ASD. The objective is to review the methodologies and tools used to explore such questions, to summarize the main results, to explore which factors may contribute to the differences reported in the studies, and to deduce how youth with ASD observe animals. Utilizing strict inclusion criteria, we examined databases between 1942 and 2023, identifying 21 studies in international peer-reviewed journals. Three main themes were identified: attentional engagement and detection, visual exploration, and behavior. Collectively, our findings suggest that the visual attention of youths with ASD towards animals appears comparable to that of neurotypical peers, at least in 2D pictures (i.e., eye gaze patterns). Future studies should explore whether these results extend to real-life interactions.

An Approach for Brick Wall Quantity Take-Off by U-Net Method Based on Deep Learning

This study presents a deep learning-based method for the quantity take-off in the construction industry. In this context, the brick wall quantity calculation was performed automatically over two-dimensional (2D) pictures by the U-Net method. 280 photos were first taken in the field at different distances and angles. 1960 images were, then, obtained by augmentation to increase the training accuracy. Pixel calculation of the automatically masked area in the images was made for wall estimation. The wall area was calculated by comparing this pixel value with that of the reference brick surface area. The method was tested on four sample photos including different wall images. A parametric study was carried out to reduce the errors. In the study, it has been shown that the proposed method is suitable for brick quantity calculation. In addition, it was concluded that the photo should be taken as close as possible, and more than one brick should be taken as a reference in close-up photos to increase the accuracy.

3D grape bunch model reconstruction from 2D images

A crucial step in the production of table grapes is berry thinning. This is because the market value of table grape production is significantly influenced by bunch compactness, bunch form and berry size, all of which are primarily regulated by this task. Grape farmers must count the number of berries in the working bunch and decide which berry should be eliminated during thinning, a process requiring extensive viticultural knowledge. However, the use of 2D pictures for automatic berry counting and identifying the berries to be removed has limitations, as the number of visible berries might vary greatly depending on the direction of view. In addition, it is extremely important to understand the 3D structure of a bunch when considering future automation via robotics. For the reasons stated, obtaining a field-applicable 3D grape bunch model is needed. Thus, the contribution of this study is a novel technology for reconstructing a 3D model of a grape bunch with uniquely identified berries from 2D images captured in the real grape field environment.

Effects of High Level of Lead (II) Oxide (PbO) Usage on Accumulator and Response Surface Method

This study involved the preparation of lead oxide paste for use in the production of lead-acid batteries. The paste was applied to the positive plates, and its performance effects were tested on the battery. Morphological and surface area analyses were conducted using SEM and BET, respectively, after the performance tests. Two mixtures of lead oxide ratios, 25%Pb-75%PbO (sample A) and 30% Pb-70% PbO (sample B), were used. The dough was applied to positive grids and passed through the curing process. SEM images revealed that tribasic sulfate (3BS) structures had a higher charge acceptance rate than tetrabasic sulfate (4BS) structures. BET analyses showed that the surface area of the samples with A ratio was higher than that of B. Electrical tests were conducted in the laboratory, and the A sample was found to be 12% more effective in the first charging efficiency than the B sample. Sample A was also found to be 67% more efficient in charge acceptance tests and 6.5% more efficient in cycle tests. The study also showed that increasing the %Pb ratio in the product decreases the initial charge efficiency, charge acceptance, and cycle life. Finally, the response surface method was used to examine the 2D picture of the relationship between lead percentage and yield, and it was found that the highest yield was obtained at 26% lead yield, with the yield being inversely proportional to the increase in lead percentage, likely due to the effect of particle size and surface area.