Projective Image Research Articles

Review: Branding Brazil: Transforming Citizenship on Screen, by Leslie L. Marsh

Review: <i>Branding Brazil: Transforming Citizenship on Screen</i>, by Leslie L. Marsh

Multifocal Near-Eye Display: Timing of Optical Diffuser Elements and Synchronization to DLP-Based Projection Microunit

Abstract The paper present the key technical details of a multifocal near-eye display concept. Along with an overview of the basic architecture, a particular implementation that utilises a digital light processing (DLP®) based spatial light modulator as the image source is provided in the study. The investigated approach involves the utilisation of a small-scale volumetric screen formed by a stack of fast-switching optical diffuser elements based on liquid crystal technology. The volumetric screen is illuminated by a rear image projector. To make the whole system functional and small, the challenge lies within the development of integrated control board for the projection modules as well as the synchronization of the DLP® projector image output to the optical diffuser element switching-cycle. The main difficulty of the development process is accounting for the peculiarities of in-house developed diffuser elements and the off-the-shelf DLP®, which is the main focus of this paper. There is no direct control over the full set of DLP® operational parameters, an indirect method for adjusting frame dead time is proposed, showing that an increase in dead time close to 0.3 ms (from 0.3 ms to 0.6 ms in the particular setup) can be achieved without significantly sacrificing image colour depth or quality. Tuneable dead time mitigates the limitations set by the non-instantaneous switching of liquid crystal diffuser elements as longer dead times allow for the removal of image bleeding between frames.

A Blend of Magnificent Sustainable Architectural Design: An Overview of the King Abdullah Financial District; Potentials and Challenges; Riyadh Kingdom of Saudi Arabia

The research paper explores the impact of the construction of mega architectural projects on the surrounding area. The King Abdullah Financial District (KAFD), a magnificent and sustainable architectural masterpiece that consists of the largest cluster of high-rise buildings constructed in Saudi Arabia, with total of about 83 buildings that vary in heights and functions. The paper points out an overview of the KAFD project&amp;rsquo;s and will elaborate on the potentials and future challenges on the surrounding transportation system and the social context. numerous visits to the project site, aerial and current project images, provided insight into three anticipated challenges of the project; mainly the anticipated traffic that will generate on the surrounding transportation system, accesses that may improve the anticipated traffic congestion on the surrounding system and the impact of the project on the social context. The research paper has concluded that the KAFD project will impact the surrounding highway corridors and has developed several alternative solutions to mitigate the adverse impact of the project to further improve the local transportation system. The researchers also believe that this megaproject has a great potential of providing significant benefits to the public. The researchers strongly support this magnificent architectural masterpiece will certainly benefit the local and national economy. The researchers referred to other enhancements that may include continued improvements of the project area signage and bikeways (where appropriate) to encourage pedestrians and help reduce anticipated traffic.

Longitudinal manganese-enhanced magnetic resonance imaging of neural projections and activity.

Manganese-enhanced magnetic resonance imaging (MEMRI) holds exceptional promise for preclinical studies of brain-wide physiology in awake-behaving animals. The objectives of this review are to update the current information regarding MEMRI and to inform new investigators as to its potential. Mn(II) is a powerful contrast agent for two main reasons: (1) high signal intensity at low doses; and (2) biological interactions, such as projection tracing and neural activity mapping via entry into electrically active neurons in the living brain. High-spin Mn(II) reduces the relaxation time of water protons: at Mn(II) concentrations typically encountered in MEMRI, robust hyperintensity is obtained without adverse effects. By selectively entering neurons through voltage-gated calcium channels, Mn(II) highlights active neurons. Safe doses may be repeated over weeks to allow for longitudinal imaging of brain-wide dynamics in the same individual across time. When delivered by stereotactic intracerebral injection, Mn(II) enters active neurons at the injection site and then travels inside axons for long distances, tracing neuronal projection anatomy. Rates of axonal transport within the brain were measured for the first time in "time-lapse" MEMRI. When delivered systemically, Mn(II) enters active neurons throughout the brain via voltage-sensitive calcium channels and clears slowly. Thus behavior can be monitored during Mn(II) uptake and hyperintense signals due to Mn(II) uptake captured retrospectively, allowing pairing of behavior with neural activity maps for the first time. Here we review critical information gained from MEMRI projection mapping about human neuropsychological disorders. We then discuss results from neural activity mapping from systemic Mn(II) imaged longitudinally that have illuminated development of the tonotopic map in the inferior colliculus as well as brain-wide responses to acute threat and how it evolves over time. MEMRI posed specific challenges for image data analysis that have recently been transcended. We predict a bright future for longitudinal MEMRI in pursuit of solutions to the brain-behavior mystery.

A 3D shape measurement method for high-reflective surface based on accurate adaptive fringe projection

Fringe projection profilometry (FPP) is a popular three-dimensional (3D) shape measurement technique with advantages of high-precision and non-contact. However, measuring high-reflective surface is still a challenging task for conventional FPP because image saturation leads to absolute phase errors and reconstruction errors. In this paper, a new adaptive fringe projection (AFP) method is proposed. Compared with existing AFP methods, we simplify the experimental process and get more accurate coordinate mapping. First, we built the projection intensity model for each projector pixel rather than camera pixel. Then, a uniform gray pattern was projected and two images were captured under high and low exposures respectively to calculate the quantitative low projection intensity. In coordinate mapping, sub-pixel coordinates were mapped from camera image onto projector image. They were filtered with absolute phase to deal with resolution difference between camera and projector and get accurate coordinate correspondence. Finally, adaptive fringe patterns were generated. Besides, we proposed a novel quantitative criterion to evaluate the effectiveness of AFP methods called point cloud integrality (PCI), which is calculated based on the number of 3D points of high-reflective areas. The experiments demonstrate that the proposed method increases both the measurement accuracy and PCI compared with conventional FPP and some existing AFP methods.

Experimental validation of liquid metal MHD numerical models

This study is aimed at experimental validation of a numerical model of fully coupled electromagnetic and fluid dynamics processes. The experiment is a laboratory-scale system, where a rotating permanent magnet induces an intense flow and free surface deformation of liquid Galinstan in a rectangular vessel. The numerical model is two-phase, 3D, transient, turbulent, and is constructed using ElmerFEM, OpenFOAM and EOF-Library codes. Validation is based on optical imaging of free surface projections. Statistical data, such as the time-average and standard deviation of the free surface profile, are compared with experiments and simulations. Results show that a Large Eddy Simulation turbulence model gives a good agreement with experiments, whereas a Reynolds-Averaged Navier-Stokes k-ω SST model causes artificial damping of free surface deformation. Figs 8, Refs 9.

Breast cancer Classification with Multi-Fusion Technique and Correlation Analysis

Breast cancer is responsible for the deaths of the vast majority of women who succumb to the disease. By detecting and treating the disease at an earlier stage, it is feasible to reduce the mortality rate associated with breast cancer. Mammography is the technique of breast cancer screening that has received the most amount of approval from the medical community. Imaging of the ipsilateral projections of the bilateral (right and left) breasts, also known as mediolateral oblique (MLO) and craniocaudal (CC) views, is often necessary for this surgery. This imaging technique is also known as the craniocaudal projection. Sonography, which is also known as ultrasound imaging, is used in combination with mammography during the diagnostic phase (which occurs after the screening phase) to offer a more accurate examination of any abnormalities that may have been detected. Radiologists may be able to make a more precise diagnosis of breast cancer by carrying out an objective assessment with the assistance of CAD systems. CAD is an abbreviation that stands for computer-aided detection and diagnosis. Researchers have proposed computer-aided design (CAD) systems as a viable technique for increasing system performance. These CAD systems take information from a variety of sources and combine it into a single database. In the majority of occurrences, this necessitates the inclusion of qualities or evaluations that were collected from a wide range of information sources. Fusion of choices is effective when dealing with sources that are statistically independent, while fusion of characteristics is good when dealing with sources that have a significant degree of correlation with one another. However, sources often contain a mix of information that is associated with one another as well as information that is independent of one another; as a consequence, none of these approaches is the greatest choice available to choose from. The development of optimal fusion strategies for Multiview and multimodal breast CAD systems is the major focus of this thesis. Canonical correlation analysis is the name of the statistical approach that serves as the foundation for these tactics (CCA). The CCA algorithm alters two multivariate datasets in such a manner as to maximize the correlation that already exists between them. This, in turn, optimizes the feature fusion that occurs after the CCA method has been applied. On the other hand, the performance of benchmark fusion schemes that combine all three sources of information is only at most equivalent to the performance of benchmark schemes that fuse two information sources. In addition, the performance of benchmark fusion schemes that combine all three sources of information is worse than the performance of CCA-based feature fusion schemes that combine two sources of information. This indicates that even if increasing the number of sources could bring new information, only a fusion approach that is optimized to exploit its maximum potential would be able to make the most of this extra data. In conclusion, the CCA-based fusion schemes exhibit robustness when tested against a wide array of performance indicators, datasets, information sources, and diagnostic tasks that are related to the diagnosis of breast cancer. The benchmark fusion techniques, on the other hand, do not demonstrate this resilience.

Lines of Curvature on the Double Torus

We describe the $\nu$-lines of curvature of an embedding of the double torus into $\mathbb R^4$, defined as the link of the real part of the Milnor fibration of a polynomial, where $\nu$ is its gradient. Through this analysis, we present a complete description of the foliation of lines of curvature of the embedding, defined as the image of the stereographic projection of this link into $\mathbb R^3$.

Технологии позиционирования оборонно-промышленного комплекса в стратегии российского национального брендинга как ответ на глобальные угрозы и вызовы

The article is aimed at studying the symbolic and political grounds for the formation of a strategy for national branding of the Russian Federation using the innovative competencies of the domestic military-industrial complex and their positioning in the context of modern global challenges and threats. A study of the foreign policy situation indicates an increase in geopolitical tension and an increase in the values of national security and defense capabilities, which form the basis of the identity of the national brand of the Russian Federation. The intensification of efforts in the field of international branding of armed forces and military associations indicates the need for similar measures by Russia. The study is based on value and historical approaches that allow us to determine the competitive identity and symbolic foundations of the Russian national brand in the field of defense industry, method of unincorporated observation, the induction method in terms of studying certain successful practices of positioning the defense industry for their possible further replication as part of the implementation of the national branding strategy. An important part of the national branding strategy is the implementation of an active memory policy in order to consolidate in the mass consciousness a special perception of some historical events to design a projective image of the future. Political elites and the state as a whole play a key role in carrying out events within the framework of the policy of remembrance and national branding in general. The topic of the defense industry occupies a significant place in the rhetoric of the Russian top leadership, including Russian President Vladimir Putin, which indicates the possibility of implementing national branding in this way. Imagery and visualization in systematic messages about products, projects and developments in the domestic defense industry, which is strategically significant and one of the most innovative industries in the Russian economy, ensure the effectiveness of the national branding strategy of the Russian Federation. The modern policy of innovation contributes to the fillability of the national brand, specifies it. The use of innovation tools by innovative actors in strategic industries, including in the field of defense and security, allows us to identify Russian “innovative belts”, whose representatives can co-realize the strategy of national branding. The article identifies key target audiences and subjects of national branding, offers recommendations for its practical step-by-step implementation. A forecast of the prospects for the implementation of the policy of forming a national brand on the basis of innovative competencies of the defense industry in the domestic and foreign policy aspects has been given. A conceptual model of the national branding of the Russian Federation is presented, based on the innovative competencies of the defense industry and including a memory policy.

Adaptive stimulus selection for consolidation in the hippocampus.

Associative memories guide behavioural adaptation by binding together outcome-predictive sensory stimuli1,2. However, in a feature-rich environment, only a subset of stimuli may predict a desired outcome3,4. How neural circuits enable behavioural adaptation by selectively and durably representing subsets of sensory stimuli that arepertinent to a specific outcome is not known. We investigated this feature selection process in the hippocampus during memory acquisition and subsequent consolidation. Two-photon calcium imaging of CA3 axonal projections to CA1 combined with simultaneous local field potential recordings revealed that CA3 projections that encode behaviourally informative sensory stimuli were selectively recruited during the memory replay events that underlie hippocampal memory consolidation5. These axonal projections formed sequential assemblies thatconjunctively link sensory features to spatial location and thus reward proximity. By contrast, axons encoding uninformative, peripatetic sensory cues were notably suppressed during memory replay. Thus, while the hippocampus comprehensively encodes the real-time sensory environment, it implements a flexible filtering mechanism to maximize the utility of memories destined for long-term storage. We propose thatutility-dependent recruitment of sensory experience during memory consolidation is a general coding principle for associative learning.

ReMember‐Me system: Developing a new, remote digital tool for detecting and preventing cognitive decline

AbstractBackgroundThe COVID19 pandemic and social distancing measures imposed have intensified the need for tools allowing the remote and early assessment of cognitive decline, in order to prevent undiagnosed neurocognitive disorder cases among older adults. The goal of the ReMember‐Me project (Image 1), funded by the EC and AAL Programme, is to create a remote, digital system for detecting, preventing and addressing cognitive decline early on. The first system prototype released includes the ReMember‐Me Cognitive Assessment Scale (RMCAS), a new digital instrument to detect cognitive difficulties, as well as, measures of physical, psychoemotional and motor status, sleep quality and serious games. The RMCAS includes 19 tasks assessing orientation, verbal, visual and prospective memory, calculation, attention, executive function, language and abstract thinking.MethodThe system is being, currently, pilot‐tested with 14 healthy and cognitively fit older adults (M=74.50, SD=4.14, 77.8% females) in a pre‐post intervention study. Participants completed a baseline assessment with the ReMember‐Me system and other standardized tools and will be tested again after two months to explore any intervention effects.ResultThe preliminary results showed that RMCAS has good fidelity and homogeneity (Table 1), individual items can yield results comparable to the Mini Mental State Examination (Table 2) while the digital administration of RMCAS did not seem to have any effect on performance compared to the traditional, hard copy administration (F=2.319, p&gt;.05)ConclusionThe preliminary results of the study indicate that the RMCAS may be a promising new digital instrument for the remote assessment of cognitive decline. Further testing is planned with 350 people in total, including participants with neurocognitive disorder, in total, to draw more concrete conclusions regarding its validity and reliability.

Explicit small image theorems for residual modular representations

Let [Formula: see text] be the residual Galois representation attached to a newform [Formula: see text] and a prime ideal [Formula: see text] in the integer ring of its coefficient field. In this paper, we prove explicit bounds for the residue characteristic of the prime ideals [Formula: see text] such that [Formula: see text] is exceptional, that is reducible, of projective dihedral image, or of projective image isomorphic to [Formula: see text], [Formula: see text] or [Formula: see text]. We also develop explicit criteria to check the reducibility of [Formula: see text], leading to an algorithm that computes the exact set of such [Formula: see text]’s. We have implemented this algorithm in PARI/GP. Along the way, we construct lifts of Katz’ [Formula: see text] operator in characteristic zero, and we prove a new Sturm bound theorem.

Large-scale interactive retrieval in art collections using multi-style feature aggregation.

Finding objects and motifs across artworks is of great importance for art history as it helps to understand individual works and analyze relations between them. The advent of digitization has produced extensive digital art collections with many research opportunities. However, manual approaches are inadequate to handle this amount of data, and it requires appropriate computer-based methods to analyze them. This article presents a visual search algorithm and user interface to support art historians to find objects and motifs in extensive datasets. Artistic image collections are subject to significant domain shifts induced by large variations in styles, artistic media, and materials. This poses new challenges to most computer vision models which are trained on photographs. To alleviate this problem, we introduce a multi-style feature aggregation that projects images into the same distribution, leading to more accurate and style-invariant search results. Our retrieval system is based on a voting procedure combined with fast nearest-neighbor search and enables finding and localizing motifs within an extensive image collection in seconds. The presented approach significantly improves the state-of-the-art in terms of accuracy and search time on various datasets and applies to large and inhomogeneous collections. In addition to the search algorithm, we introduce a user interface that allows art historians to apply our algorithm in practice. The interface enables users to search for single regions, multiple regions regarding different connection types and holds an interactive feedback system to improve retrieval results further. With our methodological contribution and easy-to-use user interface, this work manifests further progress towards a computer-based analysis of visual art.

Glaucoma classification in 3 x 3 mm en face macular scans using deep learning in different plexus

Glaucoma is among the leading causes of irreversible blindness worldwide. If diagnosed and treated early enough, the disease progression can be stopped or slowed down. Therefore, it would be very valuable to detect early stages of glaucoma, which are mostly asymptomatic, by broad screening. This study examines different computational features that can be automatically deduced from images and their performance on the classification task of differentiating glaucoma patients and healthy controls. Data used for this study are 3 x 3 mm en face optical coherence tomography angiography (OCTA) images of different retinal projections (of the whole retina, the superficial vascular plexus (SVP), the intermediate capillary plexus (ICP) and the deep capillary plexus (DCP)) centered around the fovea. Our results show quantitatively that the automatically extracted features from convolutional neural networks (CNNs) perform similarly well or better than handcrafted ones when used to distinguish glaucoma patients from healthy controls. On the whole retina projection and the SVP projection, CNNs outperform the handcrafted features presented in the literature. Area under receiver operating characteristics (AUROC) on the SVP projection is 0.967, which is comparable to the best reported values in the literature. This is achieved despite using the small 3 × 3 mm field of view, which has been reported as disadvantageous for handcrafted vessel density features in previous works. A detailed analysis of our CNN method, using attention maps, suggests that this performance increase can be partially explained by the CNN automatically relying more on areas of higher relevance for feature extraction.

Modular chains in infinite groups

The aim of this paper is to investigate the behaviour of projective images of the groups which are finite over a term of their upper central series. In particular, we prove that for any positive integer k, the class of finitely generated groups in which the k-th term of the upper central series has finite index can be described in terms of lattice invariants, and so it is invariant under projectivities. In this context, we also study groups that have only finitely many maximal subgroups which are not permodular.

Deep-learning-based image registration for nano-resolution tomographic reconstruction.

Nano-resolution full-field transmission X-ray microscopy has been successfully applied to a wide range of research fields thanks to its capability of non-destructively reconstructing the 3D structure with high resolution. Due to constraints in the practical implementations, the nano-tomography data is often associated with a random image jitter, resulting from imperfections in the hardware setup. Without a proper image registration process prior to the reconstruction, the quality of the result will be compromised. Here a deep-learning-based image jitter correction method is presented, which registers the projective images with high efficiency and accuracy, facilitating a high-quality tomographic reconstruction. This development is demonstrated and validated using synthetic and experimental datasets. The method is effective and readily applicable to a broad range of applications. Together with this paper, the source code is published and adoptions and improvements from our colleagues in this field are welcomed.

In situ imaging of bacterial outer membrane projections and associated protein complexes using electron cryo-tomography.

The ability to produce outer membrane projections in the form of tubular membrane extensions (MEs) and membrane vesicles (MVs) is a widespread phenomenon among diderm bacteria. Despite this, our knowledge of the ultrastructure of these extensions and their associated protein complexes remains limited. Here, we surveyed the ultrastructure and formation of MEs and MVs, and their associated protein complexes, in tens of thousands of electron cryo-tomograms of ~90 bacterial species that we have collected for various projects over the past 15 years (Jensen lab database), in addition to data generated in the Briegel lab. We identified outer MEs and MVs in 13 diderm bacterial species and classified several major ultrastructures: (1) tubes with a uniform diameter (with or without an internal scaffold), (2) tubes with irregular diameter, (3) tubes with a vesicular dilation at their tip, (4) pearling tubes, (5) connected chains of vesicles (with or without neck-like connectors), (6) budding vesicles and nanopods. We also identified several protein complexes associated with these MEs and MVs which were distributed either randomly or exclusively at the tip. These complexes include a secretin-like structure and a novel crown-shaped structure observed primarily in vesicles from lysed cells. In total, this work helps to characterize the diversity of bacterial membrane projections and lays the groundwork for future research in this field.

Color speckle measurement in laser display

In recent years, with the continuous development of laser projection display technology, people’s choice of electronic display equipment has become more diversified.However, due to the high coherence of the laser used for imaging in the laser projection display device, the speckle phenomenon is more obvious than other display devices, which will greatly affect the user’s actual perception. A color speckle measurement device based on XYZ filter is designed. The computer software is used to control the camera to take speckle pictures under different filters, and calculate the speckle contrast of red, green, blue and white fields. A color speckle measurement device based on XYZ filter is designed. The computer software is used to control the camera to take speckle pictures under different filters, and calculate the speckle contrast of red, green, blue and white fields.

Hierarchical Microphase Behaviors of Chiral Block Copolymers under Kinetic and Thermodynamic Control

Hierarchical Microphase Behaviors of Chiral Block Copolymers under Kinetic and Thermodynamic Control

Malls, modernity and consumption: Shopping malls as new projectors of modernity in Accra, Ghana

Shopping malls in the global South have been expanding rapidly, especially in sub-Saharan Africa, since 2000. Among others, they are seen as part of the processes of globalization, modernization and modernity. Using a mixed-methods approach based on case study of malls in Accra, Ghana, this study argues that malls in the global South, particularly sub-Saharan Africa, project images of modernity on account that they are framed as multiple loci of collective consumption and, as well, tend to represent nodes of global convergence.