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Все статьи: 2590
Food vulnerability analysis in the central dry zone of Myanmar
Статья научная
The central dry zone of Myanmar is the most water stressed and also one of the most food insecure regions in the country. In the Dry Zone, the total population is 10.1 million people in 54 townships, in which approximately 43 % of people live below the poverty line and 40 - 50 % of the rural population is landless. Agriculture is the most important economic sector in Myanmar as it is essential for the national food security and a major source of livelihood of the people. In this region the adverse effects of climate change such as a late or early onset of the monsoon season, longer dry spells, erratic rainfall, increasing temperatures, heavy rains, stronger typhoons, extreme spatial-temporal variability of rainfall, high intensities, limited rainfall events in the growing season, heat stress, drought, flooding, sea water intrusion, land degradation, desertification, deforestation, and other natural disasters are believed to be major constraints to food security. Theses extreme climatic events are likely to increase in frequency and magnitude, leading to serious drought periods and extreme floods. Food insecurity is an important thing that must be reviewed because it affects the lives of many people. For food vulnerability, we use the following indicators: slope, precipitation, vegetation, soil, erosion, land degradation and harvest failure in ArcGIS software. The erosion is influenced by rainfall and slope, while land degradation is directly related to vegetation, drainage and soil. In the meantime, the harvest failure can be generated by rainfall and flood potential zones. The results show that around 45 % of the area studied comes under a very high erosion danger level, 70 % are in the average harvest failure zone, 59 % are in the intermediate land degradation area, and overall around 45 % of the studied area comes under the insecure food vulnerability zone. Our analysis shows that an increase in the alluvial farming by 1745.33 km2 since 1988 has helped reduce the insecure food vulnerability. The food vulnerability map is also relevant to increased population and low income areas. This paper is helpful for identifying the areas of food needs in central dry zone of Myanmar.
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Frictional scanning probe lithography of advanced materials for dielectric nanophotonics
Статья научная
Creating photonic circuits based on advanced dielectric nanophotonic materials is complicated by the difficulty of selecting effective etchants when using standard lithography methods. We propose a universal approach of frictional mechanical scanning probe lithography, which consists of the local removal of material using a sharp diamond probe tip. We demonstrate planar waveguides and disk microresonators made from 200 nm thick GaP layer grown on sapphire substrate and a 40 nm thick MoSe2microdisk cavities exhibiting an optical quality factor reaching 100.
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Fusion of information from multiple kinect sensors for 3D object reconstruction
Статья научная
In this paper, we estimate the accuracy of 3D object reconstruction using multiple Kinect sen-sors. First, we discuss the calibration of multiple Kinect sensors, and provide an analysis of the ac-curacy and resolution of the depth data. Next, the precision of coordinate mapping between sen-sors data for registration of depth and color images is evaluated. We test a proposed system for 3D object reconstruction with four Kinect V2 sensors and present reconstruction accuracy results. Ex-periments and computer simulation are carried out using Matlab and Kinect V2.
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Статья научная
Accurate detection of air bubbles boundaries is of crucial importance in determining the performance and in the study of various gas/liquid two-phase flow systems. The main goal of this work is edge extraction of air bubbles rising in two-phase flow in real-time. To accomplish this, a fast algorithm based on local variance is improved and accelerated on the GPU to detect bubble contour. The proposed method is robust against changes of intensity contrast of edges and capable of giving high detection responses on low contrast edges. This algorithm is performed in two steps: in the first step, the local variance of each pixel is computed based on integral image, and then the resulting contours are thinned to generate the final edge map. We have implemented our algorithm on an NVIDIA GTX 780 GPU. The parallel implementation of our algorithm gives a speedup factor equal to 17x for high resolution images (1024×1024 pixels) compared to the serial implementation. Also, quantitative and qualitative assessments of our algorithm versus the most common edge detection algorithms from the literature were performed. A remarkable performance in terms of results accuracy and computation time is achieved with our algorithm.
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Generation and study of the synthetic brain electron microscopy dataset for segmentation purpose
Статья научная
Advanced microscopy technologies such as electron microscopy have opened up a new field of vision for biomedical researchers. The use of artificial intelligence methods for processing EM data is largely difficult due to the small amount of annotated data at the training stage. Therefore, we add synthetic images to an annotated real EM dataset or use a fully synthetic training dataset. In this work, we present an algorithm for the synthesis of 6 types of organelles. Based on the EPFL dataset, a training set of 1161 real fragments 256×256 (ORG) and 2000 synthetic ones (SYN), as well as their combination (MIX), were generated. The experiment of training models for 6, 5-classes and binary segmentation showed that, despite the imperfections of synthetics, training on a mixed (MIX) dataset gave a significant increase (about 0.1) in the Dice metric for 6 and 5 and same results at binary. The synthetic data strategy gives annotations for free, but shifts the effort to producing sufficiently realistic images.
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Статья научная
The propagation of a slow surface electromagnetic wave of the whispering gallery mode type formed on the surface of a semiconductor cylindrical waveguide is considered. The dynamic of interaction of circularly propagating electromagnetic radiation at wavelength 1.55 μm with an alternating drift current wave in the bulk of a semiconductor is studied. It is assumed that the drift velocity of charge carriers coincides with the speed of circular surface wave which moves along the axis of a cylindrical waveguide. In this case, it is possible to achieve strong phase modulation of a slow surface wave over a wide range of wavelengths so as, the modulated radiation can be converted into a sequence of short pulses. The peak power of the generated pulses is shown to be orders of a magnitude higher than the average pump power. The length of the optical waveguide at which wave packets are formed is determined by the depth and frequency of light modulation in the semiconductor cylindrical waveguide.
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Generation of linearly polarized modes using a digital micromirror device and phase optimization
Статья научная
Linearly polarized modes were generated from the fundamental LP01 using Lee holograms displayed on a digital micromirror device. The phase in the holograms was optimized using simulated annealing algorithm and complex amplitude correlation to improve the quality of the converted modes. The correlation measurements, and comparisons between numerical and experimental results, show the fidelity of the obtained modes and the effectiveness of the optimization. Furthermore, the optimized holograms can be combined to generate multiple modes spatially addressed with individual control. The results, and the use of a digital micromirror device instead of the most common liquid crystal modulators, make this method suitable for Modal Division Multiplexing systems and compatible with other optical telecommunication techniques like Wavelength and Polarization Division multiplexing, and reconfigurable optical networks.
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Genetic algorithm for optimizing Bragg and hybrid metal-dielectric reflectors
Статья научная
Highly efficient reflectors are in demand in the rapidly developing optoelectronics. At the moment, distributed Bragg reflectors made of semiconductor materials are mainly used in this capacity. A lot of time and financial resources are spent on their production. Reducing the thickness of the reflector while maintaining its reflectivity would make these devices more affordable and extend their lifetime by reducing thermal noise. With the help of genetic optimization algorithms, the structures of multilayer semiconductor and combined metal-semiconductor reflectors were obtained, having a smaller thickness and equal optical characteristics than those of classical analogues. In particular, a 29 % reduction in the thickness of the silicon / silica Bragg reflector was achieved without compromising performance.
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Gradient-based technique for image structural analysis and applications
Статья научная
This paper is devoted to application of gradients field characteristics in selected problems of image intellectual analysis and processing. To analyse the properties and structure of an image several approaches and models based on the use of the gradients field characteristics, are proposed. In this paper, models based on Weibull distribution are considered, an image dominant direction estimation algorithm using the parameters of scattering ellipse of gradients field components is proposed, and a similarity measure of two images with arbitrary dimensions and orientation is proposed. Some examples of applications of these models for estimation of blur and structuredness of an image, for the quality assessment of resizing and rotating algorithms, as well as for detection of a specified object on the image delivered by an unmanned aerial vehicle, are given.
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Handwritten text generation and strikethrough characters augmentation
Статья научная
We introduce two data augmentation techniques, which, used with a Resnet - BiLSTM - CTC network, significantly reduce Word Error Rate and Character Error Rate beyond best-reported results on handwriting text recognition tasks. We apply a novel augmentation that simulates strikethrough text (HandWritten Blots) and a handwritten text generation method based on printed text (StackMix), which proved to be very effective in handwriting text recognition tasks. StackMix uses weakly-supervised framework to get character boundaries. Because these data augmentation techniques are independent of the network used, they could also be applied to enhance the performance of other networks and approaches to handwriting text recognition. Extensive experiments on ten handwritten text datasets show that HandWritten Blots augmentation and StackMix significantly improve the quality of handwriting text recognition models.
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Head model reconstruction and animation method using color image with depth information
Статья научная
The article presents a method for reconstructing and animating a digital model of a human head from a single RGBD image, a color RGB image with depth information. An approach is proposed for optimizing the parametric FLAME model using a point cloud of a face corresponding to a single RGBD image. The results of experimental studies have shown that the proposed optimization approach makes it possible to obtain a head model with more prominent features of the original face compared to optimization approaches using RGB images or the same approaches generalized to RGBD images.
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High performance 2D simulations for the problem of optical breakdown
Статья научная
Methods of numerical simulation of two-dimensional short laser pulse nonlinear dynamics are discussed. In this work parallel processing methods for modern CPU (central processing units) architectures supporting non-uniform memory access are considered. The method of adaptive mesh subdivision is proposed to reduce non-uniform load of each CPU during processing of nonlinearity. The results of the tests performed on the Intel Nehalem based a workstation with eight cores are presented.
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High-Fidelity compression of 3D mesh animation data for humorous cartoon animation production
Статья научная
Humorous cartoon animation with its easy and pleasant style and colorful methods of expression, has become an important entertainment way for people to find relaxation and laughter in their busy lives. However, the data in the current humorous cartoon animation production is too complex. Therefore, the research proposes a new method based on high-fidelity compression algorithm, focusing on the special characteristics of 3D mesh animation data, and optimizing the compression from the two dimensions of time domain and space domain. The experimental results show that the proposed method exhibits higher compression ratio and rate, the average compression ratio reaches 2.55, and the compression rate reaches up to 65.34 Mb/s. It also exhibits lower mean squared deviation and high structural similarity index, the former is 1.56%, and the latter reaches up to 0.98. In the practical application, a compression effect of about 2:1 is achieved. Finally, in the volunteer rating of the produced humorous cartoon animation, the overall average score reaches 9.02. The study provides a new solution for the high-fidelity compression of 3D mesh animation data, which has the potential for practical application and is of great guiding significance for improving the efficiency and quality of animation production.
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Статья научная
The human olfactory bulb (OB) is a complex neural structure critical for odor processing and one of the earliest sites of pathology in a number of neurodegenerative diseases. We used X-ray phase-contrast tomography (XPCT) to obtain high-quality 3D images of OB tissue from postmortem patients, allowing detailed visualization of soft tissue microarchitecture, including the olfactory glomeruli. To improve spatial analysis, we developed a computational unfolding method that transforms the curved surface of the OB into a 2D map. This transformation preserves anatomical relationships, allowing accurate quantification of glomeruli by number, size, shape, and distribution. The unfolded representations of OB image support in-depth statistical analysis and are compatible with machine learning tools for automated detection and classification of OB morphological structures. This method provides a powerful framework for studying olfactory function and identifying early structural changes in diseases such as Parkinson's disease, Alzheimer's disease, and COVID-19-associated anosmia. By integrating XPCT with virtual unfolding, we offer a new approach to mapping OB morphological features with increased clarity and diagnostic accuracy.
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High-resolution X-ray imaging for industrial process monitoring and quality control
Статья научная
High-resolution X-ray imaging is an essential component of advanced workflows for industrial process monitoring and quality control (e.g., for metrology and defect inspection in the semiconductor industry). Depending on the specific application area, however, it is subject to different requirements, particularly regarding imaging accuracy and reconstruction fidelity, which are analyzed and systematically structured in this study. As an example, a seamless workflow of two nondestructive techniques with different spatial resolution and different throughput (here shown for a combination of acoustic and X-ray techniques) is proposed to auto-detect and auto-classify defects. X-ray microcopy and high-resolution X-ray computed tomography (XCT) provide nondestructive characterization capabilities on opaque objects, observing features with sizes down to several 10 nanometers. Because of the ability of micro-XCT and nano-XCT to reveal structural characteristics, to determine deviations from a well-defined standard, or to observe kinetic processes, they are suitable imaging techniques for micro- and nano-structured objects, but also for industrial process monitoring and quality control. Typical applications of high-resolution XCT are categorized into 3 groups: 1) Structure analysis – Creation of 3D digital images of the complete interior structure of an opaque object, 2) Flaw detection – Monitoring industrial processes and defect inspection, and 3) Quality control – Observing kinetic processes in objects important for industrial quality control and reliability engineering. These different categories of applications have different requirements for the accuracy of the 3D reconstruction and for the time-to-data. While the highest possible resolution is requested for group 1, data acquisition and data analysis time are essential for group 2. To get high-resolution 3D information of the complete interior structure of an opaque object using lens-based laboratory nano-XCT requires a thorough data analysis, e.g., the application of deep convolutional neural networks, for denoising and mitigation of artefacts. Kinetic studies for group 3, e.g., of reliability-limiting degradation processes in microchips, provide the opportunity to establish appropriate risk mitigation strategies to avoid catastrophic failure. The rapid evolution of advanced semiconductor technologies, including technologies for heterogeneous 3D integration of ICs and chiplet architectures, provides significant challenges for metrology, defect inspection, and physical failure analysis (PFA). The application of nano-XCT as a highly reliable inspection method requires a balance between throughput and fault detection (i.e., measurement and reconstruction accuracy). Ways to achieve a drastic increase in acquisition speed include high-brilliance laboratory X-ray sources, the application of AI algorithms for new image acquisition protocols, and high-speed data processing. A thorough and systematic analysis of the accuracy needed and the consequences for protocol and data analysis will support the goal of the semiconductor industry to improve throughput in metrology and defect inspection. This work may be of interest to a broad audience, including both specialists in the field of XCT and professionals employing XCT as a tool for industrial applications.
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High-speed recursive-separable image processing filters
Статья научная
The development of modern technologies in the field of image formation leads to an increase in the size of the generated images, as a result the question of reducing the processing computational costs arises, and this is an important factor in the creation of real-time systems. The study provides a description of high-speed recursive-separable filters for improving the quality of images, which, due to the peculiarities of their implementation, can reduce the number of computational operations required for the image processing process. This type of filters is obtained from two-dimensional linear digital filters, which are modified by applying recursive and separable properties to them. The MATLAB environment computing method for implementation of these filters is described. An extensive performance research of the developed filters has been carried out at various sizes of the test image and on various experimental installations. The comparison with the classical two-dimensional convolution method of the developed filters is demonstrated, and it shows the time gain required for the image processing. The results obtained can be applied in biomedical image processing systems or in vision systems working in heavy weather conditions.
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High-speed recursive-separable image processing filters with variable scanning aperture sizes
Статья научная
In the process of development of computer technologies, the number of areas of their application naturally grows and, along with it, the complexity of the tasks to be solved, which entails the need for new research. Similar tasks include digital filtering of images in the field of medical technologies and active-pulse television measuring systems. There are many methods and algorithms of digital filtering designed to solve the problem of improving the quality; algorithms that can improve the quality of images while reducing computational costs are widely used. High demands, which are made due to the constant growth in the size of the generated images, as well as the requirement for modern television systems, is real-time operation. When solving practical problems, it is required to use different filter aperture sizes, which provide an increase in quality and preservation of image details. The solution of these problems was the reason for the emergence of adaptive filters that are able to change the parameters in the process of processing the received data, while not spending additional time on processing with an increase in the size of the aperture. The paper presents the principles of constructing adaptive image processing filters, which, by obtaining an input parameter indicating the required dimension of a multi-element aperture, are able to implement the construction of the required aperture. The Laplacian “Truncated Pyramid” filter and the “double pyramid” Laplacian were modified. A feature of these filters is the oddness of the multi-element aperture, so the coefficient used to build the mask is always set to odd. When using these filters, it is possible to use two coefficients that are responsible for increasing the filtration efficiency, since, in their original form, the Laplacian filters have a sum of coefficients equal to zero. The experiment shows a comparison with high-dimensional filters that work when using classical two-dimensional convolution. The next stage of the presented research will be the application of parallel computing techniques, which will increase the speed of the developed filters.
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Human Action Recognition Based on The Skeletal Pairwise Dissimilarity
Статья научная
The main idea of the paper is to apply the principles of featureless pattern recognition to human activity recognition problem. The article presents the human figure representing approach based on pairwise dissimilarity function of skeletal models and a set of reference objects, also known as a basic assembly. The paper includes a basic assembly analysis and we propose the method for selecting the least-correlated basic objects. The video sequence proposed for analysis of human activity within frames is represented as an activity map. The activity map is a result of computing the pairwise dissimilarity function between skeletal models from the video sequence and the basic assembly of skeletons. The paper conducts frame-by-frame annotation of activities in the TST Fall Detection v2 database, such as standing, sitting, lying, walking, falling, post-fall lying, grasp, ungrasp. A convolutional neural network based on the ResNetV2 with the SE-block is proposed to solve the activity recognition problem. SE-block allows to detect inter-channel dependencies and selecting the most important features. Additionally, we prepare a data for training, determine an optimal hyperparameters of the neural network model. Experimental results of human activity recognition on the TST Fall Detection v2 database using the Leave-one-person-out procedure are provided. Furthermore, the paper presents a frame-by-frame assessment of the quality of human activity recognition, achieving an accuracy exceeding 83%.
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Hybrid Tamm-cavity modes in photonic crystal with resonant nanocomposite defect layer
Статья научная
Hybrid optical modes in a one-dimensional photonic crystal with a resonant nanocomposite defect bounded by a metallic layer are studied. The nanocomposite consists of spherical metallic constituents, that are distributed in a dielectric matrix. Transmittance, reflectance, and absorbance spectra of this structure, which is shined by light with normal incidence, are calculated. The possibility of control of the hybrid modes spectral characteristics by changing the thickness of the layer adjacent to the metal, the number of layers, and the nanocomposite filling factor is shown.
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Статья научная
Unsupervised segmentation of hyperspectral satellite images is a challenging task due to the nature of such images. In this paper, we address this task using the following three-step procedure. First, we reduce the dimensionality of the hyperspectral images. Then, we apply one of classical segmentation algorithms (segmentation via clustering, region growing, or watershed transform). Finally, to overcome the problem of over-segmentation, we use a region merging procedure based on priority queues. To find the parameters of the algorithms and to compare the segmentation approaches, we use known measures of the segmentation quality (global consistency error and rand index) and well-known hyperspectral images.
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