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Metal halide perovskites have emerged as highly promising candidates for next‐generation X‐ray detectors due to their facile and low‐cost processability, high attenuation coefficient, and tunable optoelectrical properties. In this work, quasi‐2D Dion‐Jacobson (DJ) perovskites are introduced in a flat panel X‐ray imager (FPXI) for X‐ray imaging. This study demonstrates that the diammonium interlayers in DJ perovskites play a key role in enhancing structural stability, suppressing ion migration, and improving charge transport. As a result, DJ perovskite‐based X‐ray FPXIs achieve a sensitivity of 18000 µC Gyair−1 cm−2, a low detection limit of 5.7 nGyair s−1, representing performance comparable to that of state‐of‐the‐art 3D perovskite FPXIs. Thanks to the decrease in the signal crosstalk effect of the FPXIs, a high spatial resolution of 0.54 line‐pair‐per‐pixel is achieved, which is higher than that of 3D perovskite FPXIs. Remarkably, high‐quality X‐ray imaging is achieved at a total dose of 20 µGyair, which is only 1/5 of the dose typically used in commercial equipment. This work not only provides valuable insights and guidance for the fabrication of 2D DJ perovskite X‐ray detectors but also lays the groundwork for the adoption of high‐performance, stable DJ perovskite imagers as novel flat‐panel X‐ray detectors. [ABSTRACT FROM AUTHOR]

Aim Saline contrast-enhanced electrical impedance tomography (EIT) has been used to identify the respiratory failure etiologies through assessment of regional lung perfusion at the bedside. In this study, we introduce a novel approach to detect right-to-left intracardiac shunt based on the center of heart (CoH) parameter determined from the early phase of impedance–time curve after saline bolus injection. Methods and result The timepoints when the saline bolus enter the heart (T0) and the lung regions (T1) are identified at first. A moving time window from T0 to T1 is then generated with steps of 0.5 s and the slope of the impedance–time curve in each pixel within the window calculated. CoH is calculated as the geometric center of pixel slope values in the right-to-left image direction. To illustrate how this method works in practice, we calculated the CoH values at T0 to T1 in 10 control hypoxic patients with no right-to-left shunt. In addition, we examined two critically ill patients with right-to-left intracardiac shunt. One was postcardiac surgery patient who had a residual atrial septal defect by color doppler of transesophageal echocardiograph. The other patient had a congenital heart disease of ventricular septal defect by color doppler of trans-thoracic echocardiography. A large difference in CoH between T0 to T1 was observed in the two patients with intracardiac shunt than in the control patients (11.06 ± 3.17% vs. 1.99 ± 1.43%, P  = 0.030). Conclusion Saline bolus EIT for lung perfusion might be used as ventriculography to identify the right-to-left intracardiac shunt at the bedside. [ABSTRACT FROM AUTHOR]

The display of the future is multimodal, integrating optical sensors, RFID antennas, ultrasound transducers, etc. The sensors produce a large amount of redundant data, which should be preprocessed on the substrate, ideally on the backpanel. Control gates and select and data drivers need to be more configurable and partitionable to create operational flexibility. This paper presents various circuit blocks for processing and control, including operational amplifiers, high‐resolution analog‐to‐digital converters, a microprocessor, DC‐DC converters, and high resolution sensor pixel array architectures. Moreover, the performance of the basic building blocks is compared in LTPS and IGZO technology. [ABSTRACT FROM AUTHOR]

We propose a novel pulse width modulation (PWM) micro‐LED pixel circuit utilizing LTPO TFTs. It can compensate for VTH variation, ensuring uniform micro‐LED current pulse width and amplitude. In addition, the circuit exhibits excellent IR‐drop compensation. The fabricated LTPO pixel circuit was found to perform PWM with VTH and IR‐drop compensation. [ABSTRACT FROM AUTHOR]

The image graininess of displays is a subjective indicator and is very difficult to be evaluated quantitatively. In this paper, we will introduce a visual optical simulation system and the quantitative evaluation criteria for graininess. [ABSTRACT FROM AUTHOR]

The synthesis and crystal structure of 2-bromo-4,6-bis(dibromoacetyl)resorcinol, I, was reported. In the title compound, I, crystalized in the triclinic crystal system with Pī space group. The two carbon and the oxygen atom of the acetyl groups (atoms C7, C8, O3, and C9, C10, O4) are nearly co-planar with the central phenyl ring. Intramolecular O–H···O, C–H···Br, and intermolecular C–H···Br/O interactions, two non-bonded contacts (Br5···Br3 and O4···C8) and π-π stacking interaction are stabilized the crystal packing of the title compound. Intermolecular interactions that exist in the title compound, I, are quantified with the aid of PIXEL and Hirshfeld surface (HS) analysis and the decomposed fingerprint (FP) plots. The FP plot reveals that the Br···Br contacts are comparably higher than the other contacts in the title crystal structure. Furthermore, the theoretical density functional theory (DFT) calculations were performed at the M062X/cc-PVTZ level of theory. The experimental geometry parameters of the title molecule are compared with the geometry of the optimized molecule in the gas phase. The chemical reactivity and charge transfer properties of the title compound were calculated from the HOMO and LUMO energy. In addition, the molecular electrostatic potential map was generated at their crystal structure geometry and quantitatively analyzed. [ABSTRACT FROM AUTHOR]

In our paper, we present an extension of text embedding architectures for grayscale medical image classification. We introduce a mechanism that combines n-gram features with an efficient pixel flattening technique to preserve spatial information during feature representation generation. Our approach involves flattening all pixels in grayscale medical images using a combination of column-wise, row-wise, diagonal-wise, and anti-diagonal-wise orders. This ensures that spatial dependencies are captured effectively in the feature representations. To evaluate the effectiveness of our method, we conducted a benchmark using 5 grayscale medical image datasets of varying sizes and complexities. 10-fold cross-validation showed that our approach achieved test accuracy score of 99.92 % on the Medical MNIST dataset, 90.06 % on the Chest X-ray Pneumonia dataset, 96.94 % on the Curated Covid CT dataset, 79.11 % on the MIAS dataset and 93.17 % on the Ultrasound dataset. The framework and reproducible code can be found on GitHub at https://github.com/xizhou/pixel_embedding.

In Korea, most drivers equip their vehicles with a black box camera, used to estimate the speed of the vehicle in case of traffic accidents such as car-to-car collisions, single-car accidents, and car-to-pedestrian accidents. Traditionally, speed estimation using the camera video has been done by using the distance between the road lane, surrounding structures, etc.However, when the following vehicle collides with a stationary leading vehicle or barrier, and no road lanes or structures are visible around the driving path in the black box camera video of the following vehicle, the speed of the following vehicle could be just estimated according the deformations on the collided vehicles or objects.Therefore, in this study, when a vehicle collision occurs, a virtual parallel line is drawn between the leading vehicle and the following vehicle in the black box camera image of the following vehicle and analyzed geometrically to estimate the distance and the speed of the following vehicle.After the vehicle collision experiment, the speed was estimated using the method proposed in this study using the captured black box video. As a result, it was confirmed that the accuracy was high when the collision speed was low. So The method proposed in this study is expected to be used to estimate collision speed in the cases of low impact speed in the rear end collisions.

With the rapid advancements in 3D game technology, workload characterization has become crucial for each new generation of games. The increased complexity of scenes in 3D games allows for stunning realtime visual quality. However, handling such workloads results in significant power consumption over the GPU rendering pipeline. The focus of the current paper is low power optimization, targeting texture memory, geometry engine, pixel, and rasterization, as these components are significant contributors to the power consumption of a typical GPU. The proposed methodology integrates the Dynamic Voltage Frequency Scaling (DVFS) technique, adjusting voltage and frequency based on the workload analysis of frame rates with respect to the scenes of 3D games. Frame rates of 60 fps and 30 fps are set up to understand and manage the workload on frames. Furthermore, for comparative analysis, various framelevel power analysis schemes such as No DVFS implemented, Frame History Method, Frame Signature Method, and Tiled History-based are introduced. The proposed scheme consistently surpasses these framelevel schemes, with fewer missed deadlines, while having the lowest energy consumption per frame rate. The implementation resulted in a remarkable 65% improvement in quality, indicated by a reduction in deadline misses, along with a substantial 60% energy saving. [ABSTRACT FROM AUTHOR]

In this interview, Cécile Massart looks back over her career. She discusses her beginnings. She started with printmaking, moved on to computers and made her consider the use of other media. The discovery of radioactivity issues constituted a "turning point" for her work. She emphasises upon her use of photography in order to question what the wastes we hide say about us as society and as a legacy? [ABSTRACT FROM AUTHOR]

Theoretical calculations for a single element of a hexagonal raster are considered. It has been analyzed and proven that the hexagonal lattice gives the lowest ratio of perimeter to area covering the plane of any equilateral polygons. Thus, based on the calculations, the edge aliasing effect is reduced to a minimum for the hexagonal lattice. [ABSTRACT FROM AUTHOR]

In this research paper, a comparative analysis of various image enhancements in the spatial domain techniques was performed based on three-dimensional image quality statistics such as mean squared error (MSE), peak signal-to-noise ratio (PSNR), and structural similarity for measuring the image quality (SSIM). The conditions for choosing the best method are low mean square error (MSE) and high peak signal-to-noise ratio as well as the structural similarity for measuring the image quality. The pre-processed image was subjected to a classification task using a stepwise version of pre-trained deep convolutional neural networks. The problem of driver drowsiness caused by fatigue, lack of sleep, medication, etc. will have to be solved by improving the efficiency of driver drowsiness detection. Many traffic accidents are largely caused by drowsy drivers. Driver fatigue and distraction can cause a lack of alertness, which can lead to driver inattention. In this paper, we proposed a new deep-learning technique for driver drowsiness detection. Two methods using convolutional deep neural network and GoogleNet transfer learning are compared to achieve a better accuracy of 99%. [ABSTRACT FROM AUTHOR]

When plastics are discarded, they do not biodegrade and instead break down over time into progressively smaller particles, termed secondary microplastics, which adversely impact biota and human health as well as persist in the environment for centuries. Our research objective was to evaluate the capabilities of object-based image analyses in detecting compositionally varied microplastics suspended in an aquatic mesocosm under no-slip and turbulent water conditions. We found that the presence of polypropylene, polyethylene terephthalate, and low-density polyethylene microplastic pollution in both single-type and mixed-type suspensions was not detectable by either average red (R), average blue (B), average green (G), or average RBG pixel intensities, but was significantly detectable by means of total RBG pixel intensity from digital imagery of the surface-water. Our findings suggest that object-based image analyses of surface waters to quantify pixel information is better suited for monitoring the presence and absence of suspended microplastics, rather than for the stepwise determination of microplastic concentrations. We propose the development of a smartphone application to facilitate citizen-science monitoring of microplastic contamination as well as comment on future applications utilizing drone imagery to boost cloud-based mapping spatiotemporal plumes.

This document explores the impact of pixel size on the quality of digital images in intraoral dental radiography. The research compares two types of imaging plates with different pixel sizes and finds that the plate with smaller pixels (FCR HR) produces higher image quality. The document also references other studies on pixel size and image quality in different radiographic systems. Ultimately, the choice between imaging plates depends on the specific needs and preferences of the dental practitioner. [Extracted from the article]

When plastics are discarded, they do not biodegrade and instead break down over time into progressively smaller particles, termed secondary microplastics, which adversely impact biota and human health as well as persist in the environment for centuries. Our research objective was to evaluate the capabilities of object-based image analyses in detecting compositionally varied microplastics suspended in an aquatic mesocosm under no-slip and turbulent water conditions. We found that the presence of polypropylene, polyethylene terephthalate, and low-density polyethylene microplastic pollution in both single-type and mixed-type suspensions was not detectable by either average red (R), average blue (B), average green (G), or average RBG pixel intensities, but was significantly detectable by means of total RBG pixel intensity from digital imagery of the surface-water. Our findings suggest that object-based image analyses of surface waters to quantify pixel information is better suited for monitoring the presence and absence of suspended microplastics, rather than for the stepwise determination of microplastic concentrations. We propose the development of a smartphone application to facilitate citizen-science monitoring of microplastic contamination as well as comment on future applications utilizing drone imagery to boost cloud-based mapping spatiotemporal plumes. [ABSTRACT FROM AUTHOR]

The Nyabarongo basin in Rwanda is subjected to hydrometeorological hazards, particularly floods, which are the most prevailing and devastating. Therefore, understanding flood-controlling factors is so pertinent for the development of scientifically driven flood prevention strategies. This study aimed at exploring a form of pixel-based information value model integrated with remote sensing techniques and geo-information system to assess the probability of flood incidence and geo-visualize prone areas at basin's scale. To do this, a flood inventory was initially generated using 226 past flooded locations, which were split into a 75:25 ratio for model training and validation, respectively. Fourteen flood-controlling factors were selected after a multicollinearity diagnosis. The results unveiled that more than half of the basin's surface area is covered by very high (8.6%) and high (21.5%) to medium (31.8%) probability of flood incidence. This dispersion was mainly influenced by rainfall, proximity to rivers, Land Use/Land Cover, elevation, and SPI which influence the basin's hydrological behavior. The evaluated accuracy of the applied model using the Area Under Curve of the Receiver Operating Characteristics (AUC–ROC) highlighted a commendable and accurate performance of 0.883 and 0.828 for success and prediction rate, respectively. The study's findings provide a scientifically driven reference for flood mitigation plans and act as a benchmark for decision-making and policy updates regarding flood risk management toward the Nyabarongo basin and other basins with similar characteristics nationally or regionally. [ABSTRACT FROM AUTHOR]

A visualization and interactive network topology model are studied based on real-time features generated during spaceflight. Start by establishing a consistent set of data and logical interaction interfaces. This paper presents a method of scenario model construction and application programming based on virtual reality technology. The scene elements are extracted into two types of primitives, namely logical type and simulated object type. This provides a unified architecture for the editing and processing of graphic elements. This system can realize the automatic creation of the scene. Then the point cloud data obtained by sparse reconstruction of SFM is reconstructed to the Poisson surface. You get a dense, uniform grid. Experiments show that the proposed algorithm can realize the 3D reconstruction of non-cooperative objects. The spatial feature points obtained in the spatial positioning of non-cooperative objects can provide necessary technical support for its orbit positioning. The model can quickly generate new model scenario pages according to the characteristics of the task. This method changes the display mode, which can only be static or limited dynamic before. It has also improved the efficiency of space mission preparation. [ABSTRACT FROM AUTHOR]

Background. The necessity of creating diagnostic systems for vibration-loaded objects is shown. It is noted that non-contact systems have sufficient capabilities to determine the vibration amplitude. It is shown that the analysis of image sequences from the camera makes it possible to estimate the vibration parameters. Materials and methods. Mechanisms for analyzing the image from the camera by counting lines and pixels when measuring the radius of the image of a round mark are proposed. Numerical modeling of the processes of measuring the radius of the image of a round mark using technologies for counting lines and pixels with different parameters was carried out. Result. Simulations have shown that the accuracy gain of applying the pixel counting technology to the line counting technology will increase as the label image radius increases. Conclusion. It is predicted that the maximum absolute error in measuring the radius of the mark image using the pixel counting technology will decrease with an increase in the radius of the mark image.

OLED display quality is closely related to pixel design. Usually, in order to evaluate the effect of pixel design on display quality, we need to make panel samples and light them up, or observe killer pattern samples that putted on the back light. Either method costs a considerable amount of time and money. In this paper, we will introuce a novel optical simulation system that we established to evaluate and optimize pixel design qualitatively or quantitatively. [ABSTRACT FROM AUTHOR]

Image segmentation plays an important role in detecting various diseases and pathologies through medical image processing. Over the years, a number of traditional approaches such as the binary threshold method (Otsu method), watershed method, and K-means clustering method have been developed to perform image segmentation, using domain-specific knowledge to efficiently solve segmentation problems in specific applications. But unfortunately, these methods were not effective. In fact, the essence of image segmentation is the classification of containing each pixel with similar attributes. And the goal of classifying a pixel is to treat it coarse, insensitive to noise, fine, and a medium star filter. Something that traditional methods cannot do. Therefore, there is a need to propose a new method that allows eliminating these disadvantages. We propose a method based on autoencoder (a special architecture of artificial neural networks that allows the application of learning without a teacher using the method of back propagation of the error), which allows compressing any large image into a small one, (with the same properties as the input). This method also saves resources. In this case, we use an image processing method called "MaxPooling" (U-Net). In the work, we created our own metric to track the result of the network training. In the practical part, we tried segmenting into classes the images from the construction site, as well as pixel by pixel the locations of the aircraft in the images.

The technique most widely used to quantitatively measure leg edema is only a pitting edema method. It has recently become possible to digitize B-mode ultrasound images and accurately quantify their brightness using an image-analysis software program. The purpose of this study was to find new indices of the grade of leg skin, to study whether or not analyses of the subcutaneous layer of leg skin on ultrasound images using image-editing software program can be used to evaluate it and to digitize it. Images of 282 subcutaneous layers of leg skin in 141 pregnant women were obtained using a B-scan portable ultrasound device. Rectangular photographs (vertical: skin thickness; horizontal: width of probe) were obtained using an image-editing program, and the luminous intensity (pixel grayscale: 0–255) and thickness of the skin were calculated using a histogram. We investigated the correlation between these parameters and the grade of pitting edema (0–3). There was a significant positive correlation between the grade of pitting edema and the average luminous intensity value, its standard deviation, and the skin thickness (ρ = 0.36, ρ = 0.22, ρ = 0.51, p < 0.0001, respectively). In particular, there was strong positive correlation between the grade of pitting edema and both the total number of pixels in a rectangle × (multiplied by) the average luminous intensity value and the total number of pixels in a rectangle × the standard deviation of the average luminous intensity value (ρ = 0.58 and ρ = 0.59, p < 0.0001, respectively). We could quantitatively evaluate the grade of leg edema by analyzing ultrasound photographs of the subcutaneous layer of the leg skin using an image-editing software program and found new indices to digitize it. [ABSTRACT FROM AUTHOR]

It is necessary to improve the generalization of tomato maturity grading for better consistent criteria in modern agriculture. In this study, an extraction was proposed for red-colored regions from the fruit surfaces using region brightness correction. The R-G method was used to enhance the red areas on the tomato surface, and then the Otsu method was used to segment them. All the colored areas on the tomato surface were obtained to evaluate the relationship between the contours of each red region of tomato after segmentation by the contour tree structure. The proportion of the area of the red region to the total area of the image was calculated as the main feature of maturity grading. The surface red coloring area ratio, color moments, and color histograms were selected to perform the feature importance analysis, in order to screen out the color features with a significant impact on the maturity grading. The random forest model was used to determine and grade the different maturity stages of tomatoes. Among them, the image in-painting technique based on the fast marching method was used to reduce the high brightness reflection of surface that reduced by the illumination changes. The test results showed that the effect of the area ratio of fruit surface coloring areas on the tomato maturity grading was significantly greater than the color histogram and color moment. The coloring area ratio, G-component third order color moments, and G-component color histogram feature posed the greatest impact on the maturity grading, with importance scores of 0.293, 0.199, and 0.127, respectively. Among all color features, the tomato coloring area ratio as a classification index shared the highest classification accuracy, with an average classification accuracy of 92.96%, which was 6.53 and 20.6 percent point higher than the traditional color moment and color histogram indicators. The domain pixel-weighted sum performed an excellent correction effect on the brightness of the tomato-highlighted areas. After correction, the proportion of the fruit surface colored area of immature, slightly mature, and mature tomato images to the total area of the tomato images increased by 0.06, 0.15, and 0.11, respectively, compared with before correction. The classification accuracy was improved by 17.24, 11.47, and 4.69 percent point, respectively. The area extraction of tomato red areas with the image fast restoration can be used as the recommended extraction of tomato maturity grading. [ABSTRACT FROM AUTHOR]

Background. The necessity of creating diagnostic systems for vibro-loaded objects is shown. Contactless systems have sufficient capabilities to determine the amplitude of vibrations, it is noted that an important part of such systems is the calibration process. The purpose of the study is to improve the accuracy of calibration of vibration displacement meters, develop methods for modeling vibration displacement and estimating errors of measurement conversion Materials and methods. The principle of operation of the dynamic calibration system for measuring vibration displacement is proposed. Results. Modeling using this technique has been carried out. A method for estimating measurement errors of calibration vibration displacement has been developed, justified and illustrated with a specific numerical example. A family of curves has been constructed showing the dependence of the reduced error of the calibration system of vibration displacement measuring instruments on the radius of the calibration round mark for different values of the number of pixels per image of the calibration round mark. Conclusions. A technique for numerical simulation of the process of measuring transformation of the image of a calibration round mark and the trace of its vibrational blur has been developed.

Images captured in dim light are hardly satisfactory and increasing the International Organization for Standardization (ISO) for a short duration of exposure makes them noisy. The image restoration methods have a wide range of applications in the field of medical imaging, computer vision, remote sensing, and graphic design. Although the use of flash improves the lighting, it changed the image tone besides developing unnecessary highlight and shadow. Thus, these drawbacks are overcome using the image restoration methods that recovered the image with high quality from the degraded observation. The main challenge in the image restoration approach is recovering the degraded image contaminated with the noise. In this research, an effective algorithm, named T2FRF filter, is developed for the restoration of the image. The noisy pixel is identified from the input fingerprint image using Deep Convolutional Neural Network (Deep CNN), which is trained using the neighboring pixels. The Rider Optimization Algorithm (ROA) is used for the removal of the noisy pixel in the image. The enhancement of the pixel is performed using the type II fuzzy system. The developed T2FRF filter is measured using the metrics, such as correlation coefficient and Peak Signal to Noise Ratio (PSNR) for evaluating the performance. When compared with the existing image restoration method, the developed method obtained a maximum correlation coefficient of 0.7504 and a maximum PSNR of 28.2467dB, respectively. [ABSTRACT FROM AUTHOR]

Edge detection is an important and growing area in different fields such as image pattern recognition, machine learning and processing, and Computer vision. Edge detection of an image of the object is the main goal for different Edge detection algorithms. In Edge detection, the most important step is to identify the edges of an image of the object and pixel information of the Image In every edge detection algorithm. There will be 2 types of masks one in the horizontal direction and the other in the vertical direction. The kernel or mask is a convolution vector of the nXn matrix which is multiplied by the sub-window of an image. The effective and efficient performance of a digital system mainly depends on the delay, area, and power consumption. These parameters decide the efficiency of any digital core system. This project converts the image pixel information to binary for processing with different edge detection algorithms like Canny, Sobel, Prewitt, and Roberts. The algorithms are then simulated and synthesized on FPGA with the targeted device xc3s4000-4fg900. The input image with resolution 256X256 is given as input to the MATLAB version 2014a. The MATLAB code converts image pixel intensity information to binary form as hardware input can only be in binary not the pixel intensity information, so we use MATLAB software to convert pixel intensity information to a hexadecimal value which is given as input to the model sim version 6.4a. The Different edge detection algorithm like Sobel, Canny, Prewitt, and Robert is implemented using Verilog HDL, the model sim is used for simulation, and synthesis is performed using Xilinx software. The design parameters results obtained for different edge detection algorithms are compared, The Generated text file is sent to MATLAB software for the extraction of edges. and synthesis is performed in the Xilinx platform to generate a synthesis report for RTL schematic and Technology Schematic with a target device xc3s4000-4fg900. The Proposed methodology gives better performance with fewer lut's of 119, slices 77, gates 1736, overall delay 28.121ns, gate delay 15.304ns, and path delay 12.817ns along with 0 block ram and 0 distributed ram. [ABSTRACT FROM AUTHOR]

Summary: Liver disease is a form of sickness that starts in the ovaries and is particularly dangerous for women. As a result, aberrant cells develop that have the potential to spread to other parts of the body. Liver disease is a sort of risky improvement that impacts ovaries in ladies, and is hard to perceive at early phase because of which it stays as one of the guideline wellsprings of illness end. Unquestionable confirmation of intrinsic and typical parts is immense in making novel frameworks to perceive and ruin danger. Here, using hybrid machine learning approaches, we propose an early detection and classification of liver disease (EDCLD) in ultrasound images. This study is aimed at detecting and evaluating liver disease, which may be benign or malignant depending on the cancer type. To begin with, we use an improved ant swarm optimization algorithm for both high and low level feature extraction models. For liver disease classification, we used hybrid swallow swarm intelligent‐deep neural network (HSSI‐DNN) classifier to identify the disease stage. By using training and testing liver datasets, we are improving the accuracy of liver disease detection with several stages. Second, we present a search optimization for whales algorithm for cascaded and segmentation as a single fusion feature capable of representing both the texture patterns and semantic background distributed in the image. Third, the dividend yields are commitment to the HSSI‐DNN classifier used to detect the "Normal" and "Diseases" from input image. The proposed HSSI‐DNN classifier performance outperformed the existing classifier in terms of accuracy (0.98), specificity (0.98), and sensitivity (1). The proposed EDCLD technique implemented in MATLAB. [ABSTRACT FROM AUTHOR]

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Ink-jet printing combines large-area film fabrication with low-cost solution processing. A high-resolution display calls for small-sized and closely arranged pixels, which can be realised using ink-jet printing. Here, we introduce the relevant steps of ink-jet printing, namely, droplet formation, falling, hitting the substrate, spreading, and the formation of a pixel. On the basis of a summarisation of factors that affect pixel formation, an approximation model is established to explore the minimum size of a pixel. [ABSTRACT FROM AUTHOR]

The High Luminosity Large Hadron Collider (HL-LHC) will achieve unparallelled instantaneous luminosity, leading to approximately 200 proton–proton interactions during a bunch crossing. The existing ATLAS Inner Detector will be replaced by an entirely silicon-based system known as the Inner Tracker (ITk). The ITk's innermost section will incorporate a cutting-edge pixel detector with diverse silicon sensor technologies being used across the five barrel and end-cap layers. As initial modules have been assembled with the prototype ITkPix readout chip, a variety of aspects are under investigation. These range from production-related ones such as bump bonding, to assembly methods of dedicated wire-bond mechanical protection and layout-related aspects such as the distribution of data links amongst several chips and modules. This article presents results of several such studies, directly affecting the module production for the ATLAS ITk Pixel detector. [ABSTRACT FROM AUTHOR]