Projectivity Research Articles

Effect of storing conditions (lighting, temperature and bottle color) on rosé wine attributes

The majority of rosé wines are bottled in clear bottles as color is an important factor in consumer preference. Post-bottling wine can be exposed to UV–visible light and temperature fluctuations resulting in quality degradation. This study investigated the impact of bottle color (flint and antique green), light exposure (darkness, LED and fluorescent bulb), and temperature (12 °C and 22 °C) on rosé wine quality using a full factorial design with three different wines (Grenache, Pinot noir and Zinfandel). The impact on chemical composition, color, phenolics and aromatics was determined. Projective mapping was carried out for sensorial analysis. Changes in the aromatics, color and phenolic composition were detectable after three months and more noticeable after six months of storage. Overall, all variables studied impacted rosé wine characteristics significantly. However, higher temperature in combination with clear glass bottles under fluorescent light were the most detrimental conditions.

Linear and nonlinear optical absorption of 2D monolayer NbOCl2

The in-layer crystal structure of a two-dimensional material is stable, but the interaction force between the atomic layers is much weaker. Niobium oxide dichloride (NbOCl2) not only has high second-order nonlinear coefficients unique to common monolayer two-dimensional materials but also weak electronic coupling between layers. These characteristics make NbOCl2 very suitable as a quantum light source in quantum optical systems. This article mainly studies the linear and nonlinear optical absorption of two-dimensional monolayer NbOCl2. The characterization means include a surface distance projection map and three views, total density of states, photoelectron spectrum, charge density difference, transition dipole moment density, one-photon absorption spectrum, and two-photon absorption spectrum. There is a size effect on the total density of states, photoelectronic energy spectrum, and one-photon absorption spectrum, that is, as the size increases, the total density of states is red-shift, the photoelectronic energy spectrum is blue-shift, and the absorption spectrum has a significant red-shift. The charge density difference indicates that there is charge transfer around the Nb atom of NbOCl2. The transition dipole moment density changes periodically. The study of the two-photon absorption spectrum shows that it is dominated by a one-step transition. In summary, our work provides an in-depth understanding of its optical properties and is of great significance for the miniaturization of quantum light sources.

Laparoscopic Projection Mapping of the Liver Portal Segment, Based on Augmented Reality Combined With Artificial Intelligence, for Laparoscopic Anatomical Liver Resection

Laparoscopic Projection Mapping of the Liver Portal Segment, Based on Augmented Reality Combined With Artificial Intelligence, for Laparoscopic Anatomical Liver Resection

Neural Projection Mapping Using Reflectance Fields.

We introduce a high resolution spatially adaptive light source, or a projector, into a neural reflectance field that allows to both calibrate the projector and photo realistic light editing. The projected texture is fully differentiable with respect to all scene parameters, and can be optimized to yield a desired appearance suitable for applications in augmented reality and projection mapping. Our neural field consists of three neural networks, estimating geometry, material, and transmittance. Using an analytical BRDF model and carefully selected projection patterns, our acquisition process is simple and intuitive, featuring a fixed uncalibrated projected and a handheld camera with a co-located light source. As we demonstrate, the virtual projector incorporated into the pipeline improves scene understanding and enables various projection mapping applications, alleviating the need for time consuming calibration steps performed in a traditional setting per view or projector location. In addition to enabling novel viewpoint synthesis, we demonstrate state-of-the-art performance projector compensation for novel viewpoints, improvement over the baselines in material and scene reconstruction, and three simply implemented scenarios where projection image optimization is performed, including the use of a 2D generative model to consistently dictate scene appearance from multiple viewpoints. We believe that neural projection mapping opens up the door to novel and exciting downstream tasks, through the joint optimization of the scene and projection images.

BathyGlobe GapFiller: A planning tool to help fill the gaps in world bathymetry

To efficiently map the oceans in support of the SeaBed 2030 project and other mapping programs, newly collected mapping lines should ideally not duplicate existing data but slightly overlap prior mapping coverage. BathyGlobe GapFiller is a software tool designed to support planning for transit and area mapping. At its core is an algorithm that adjusts transit lines so that they overlap existing lines by a specified amount. Two novel methods for accomplishing this are presented. The better solution uses a custom overlap detecting filter. While it is more computationally intensive than the alternative, it performs better and is robust. Other capabilities of the BathyGlobe GapFiller are described, including swath width estimation based on system specifications and/or past performance, automatic transit planning, polygon filling, and the production of detailed statistics representing planned survey coverage, overlap and time to complete the survey.

Postcolonial Italy, A Public History Project Mapping Colonial Heritage

Postcolonial Italy: Mapping Colonial Heritage is a public history project which Daphné Budasz and Markus Wurzer founded in Florence in 2018. The project is designed as an independent, bottom-up initiative which aims to (a) identify and collect colonial traces, (b) provide critical knowledge on these traces in order to (c) trigger debate on colonial legacies and reflect on the social, political, and cultural consequences of colonialism beyond the academic context within Italy’s contemporary society. For the purpose of dissemination and accessibility, in 2019 Budasz and Wurzer created the website www.postcolonialitaly.com, which presents an interactive map that provides information about geographical sites related to colonialism. What started as a locally grounded public history project about colonial traces in Florence has over the past three years evolved into an Italy-wide participatory and collaborative venture. The map keeps growing by scholars who are working on colonial legacies in other Italian cities like Rome, Venice, Bolzano, Cagliari, Milan, Trieste, and Parma, and who are sharing their knowledge.

Ecc‐RCNN: An efficient and high‐accuracy object detection framework for transmission line defect identification

AbstractIn order to improve the accuracy of image‐based transmission line defect detection, while reducing the computational complexity and the high demand on chip performance, an object detection framework is proposed, which aims to improve model performance without increasing the scale of the model and the amount of calculation. An efficient feature fusion module to combine different‐level semantic features in non‐linear transformations is introduced. It includes channel‐level hierarchy features, linear projection and residual mappings to gather task‐oriented features across different spatial locations and scales. Then a context information modelling module is proposed to extract features around the target objects, which further increases the detection accuracy. Finally, an Intersection‐over‐Union‐based training examples sampling strategy is adopted to alleviate the class imbalance problem. Experiments on dataset show that the proposed method, with a similar number of model parameters, has an accuracy improved by 8.1% compared to the baseline, and outperforms all the competitors in the area of transmission line defect detection.

Are You Talking to Me? A Case Study in Emotional Human-Machine Interaction

We present Stanley, a digital sculpture designed to engage audiences with the spontaneous and captivating emotional expressions of an artificial human. A 3D-printed face is brought to life through video projection mapping and a set of machine learning libraries and APIs, enabling real-time, embodied interactions with our virtual character. Stanley’s personality is shaped by traditional acting methods applied to a large language model. By creating human-machine encounters in emotionally salient scenarios, we explore how insights from acting and directing for the stage and the screen can enhance the development of compelling virtual agents. By interacting with Stanley, the audience experiences an entertaining yet unsettling encounter with AI technology, fostering a deeper understanding of machine learning techniques and enabling their critical reflection.

Focal surface projection: Extending projector depth of field using a phase‐only spatial light modulator

AbstractWe present a focal surface projection to solve the narrow depth‐of‐field problem in projection mapping applications. We apply a phase‐only spatial light modulator to realize nonuniform focusing distances, whereby the projected contents appear focused on a surface with considerable depth variations. The feasibility of the proposed technique was validated through a physical experiment.

Convergence of the arcuate fasciculus and third branch of the superior longitudinal fasciculus with direct cortical stimulation-induced speech arrest area in the anterior ventral precentral gyrus.

The objective was to identify the correspondence between the anterior terminations of the arcuate fasciculus (AF) and third branch of the superior longitudinal fasciculus (SLF-III) and the intraoperative direct cortical electrical stimulation (DCS)-induced speech arrest area. The authors retrospectively screened 75 glioma patients (group 1) who received intraoperative DCS mapping in the left dominant frontal cortex. To minimize the influence of tumors or edema, we subsequently selected 26 patients (group 2) with glioma or edema not affecting Broca's area, the ventral precentral gyrus (vPCG), and the subcortical pathways to generate DCS functional maps and to construct the anterior terminations of AF and SLF-III with tractography. Next, a grid-by-grid pairwise comparison was performed between the fiber terminations and the DCS-induced speech arrest sites to calculate Cohen's kappa coefficient (κ) in both groups 1 and 2. Finally, the authors also demonstrated the distribution of the AF/SLF-III anterior projection maps obtained in 192 healthy participants (group 3) and subsequently correlated these with the speech arrest sites in group 2 to examine their validity in predicting speech output area. The authors found that speech arrest sites were substantially consistent with SLF-III anterior terminations (group 1, κ = 0.64 ± 0.03; group 2, κ = 0.73 ± 0.05) and moderately consistent with AF (group 1, κ = 0.51 ± 0.03; group 2, κ = 0.49 ± 0.05) and AF/SLF-III complex (group 1, κ = 0.54 ± 0.03; group 2, κ = 0.56 ± 0.05) terminations (all p < 0.0001). The DCS speech arrest sites of the group 2 patients mainly (85.1%) emerged at the anterior bank of the vPCG (vPCGa). In group 3, both terminations of AF and SLF-III converged onto the vPCGa, and their terminations well predicted the DCS speech output area of group 2 (AF, area under the curve [AUC] 86.5%; SLF-III, AUC 79.0%; AF/SLF-III complex, AUC 86.7%). This study supports the key role of the left vPCGa as the speech output node by showing convergence between speech output mapping and anterior AF/SLF-III connectivity in the vPCGa. These findings may contribute to the understanding of speech networks and could have clinical implications in preoperative surgical planning.

포스트(Post) 동북공정, 중국역사교과서 고대 한반도북부 속국 표기 고찰

Chinese Northeast Project for three Northeastern provinces on the basis of the unified multi-ethnic state theory was expanded to the history, culture and territory of Korea beyond the simple ancient history and has been accelerating the forgery of Chinese history that the territories around China were the subject countries of China. Such movement has high possibility to create the diplomatic issues on the territory against South and North Korea. It was widely known up to now that Northeast Project distorted mainly the history of Goguryeo, Balhae or Buyeo to the history of subject countries of China through media. Moreover, introduction of Hanbok and Kimchin in 2022 Beijing Olympics as a part of Chinese culture is also a part of Northeast Project. Reasoning of Northeast Project on the history established by the new Sinocentrism was reflected and described on the government designated history textbook of Korea as it was. The government designated textbook of China used in these days marked the northern region of Korean peninsula in the ancient history as the territory of Han, Wei and Jin dynasty. This study investigated the background of reasoning above by analyzing the contents of the government designated textboom of China describing the northern region of Korean peninsula in the ancient times as the territory of subject countries of China, and discussed the approach to solve the issue above. The existing researches on Northeast Project in Korea and abroad tended to focus on the clearly exposed issues. Reasoning for insisting the territories of Gojoseon, Goguryeo, Balhae and Buyeo as the subject countries through Northeast Project is the ‘insistence that Pyeongyang in Korean peninsula was Nakrang-gun’. It’s the reasoning that has been continuously insisted by the academic world of Korea. For correcting the history textbook of China describing the northern region of Korean peninsula as the territory of Nakrang-gun of Han dynasty and furthermore, the territory of Wei and Jin dynasty as the territory of Korean peninsula, this study suggested the practical tasks for Korean government and the historical studies world of Korea to solve the issues of Northeast Project. The suggestions are ‘complete review on the location of Hansagun and Nakrang-gun in Pyeongyang’, ‘publication of Korean ancient history map’ that can acknowledge the accurate Korean history to the world against the Northeast Project map, and ‘revision of national history book’ eliminating Northeast Project of China and the peninsula historical view by Korean History Compilation Committee of Japan during the Japanese colonial era, which have a thread of connection each other.

On Shor's r-Algorithm for Problems with Constraints

Introduction. Nonsmooth optimization problems arise in a wide range of applications, including engineering, finance, and deep learning, where activation functions often have discontinuous derivatives, such as ReLU. Conventional optimization algorithms developed primarily for smooth problems face difficulties when applied to nonsmooth contexts due to discontinuities and other associated irregularities. Possible approaches to overcome these problems include smoothing of functions and applying non-smooth optimization techniques. In particular, Shor's r-algorithm (Shor, Zhurbenko (1971), Shor (1979)) with space stretching in the direction of the difference of two subsequent subgradients is a competitive non-smooth optimization method (Bagirov et al. (2014)). However, the original r-algorithm is designed to minimize unconstrained convex functions. The goal of the work. The standard technique for applying this algorithm to problems with constraints consists in the use of exact non-smooth penalty functions (Eremin (1967), Zangwill (1967)). At the same time, it is necessary to correctly choose (quite large) the penalty coefficient of the penalty functions. Norkin (2020, 2022), Galvan et al. (2021) propose the so-called projective exact penalty functions method, which theoretically does not require choice of the penalty coefficient. The purpose of the present work is to study an applicability of the new exact projective non-smooth penalty functions method for solving conditional problems of non-smooth optimization by Shor's r-algorithm. The results. In this paper, the original optimization problem with convex constraints is first transformed into an unconstrained problem by the projective penalty function method, and then the r-algorithm is used to solve the transformed problem. The results of testing this approach on problems with linear constraints using a program implemented in Matlab are presented. The results of the present study show that the standard method of non-smooth penalties combined with Shor's r-algorithm is fast, due to the use of the provided program to calculate the subgradients, but it requires the correct selection of the penalty parameter. The projective penalty method is slow because in this study it uses finite differences to calculate the gradients, but it is quite stable with respect to the choice of the penalty parameter. Further research will be aimed at investigating the differential properties of the projection mapping and reducing the time of computing subgradients for account of parallel calculations. Keywords: Subgradient descent, constrained optimization, r-algorithm, exact projective penalty.

Safe range of femoral neck system insertion and the risk of perforation

BackgroundInternal fixation of the femoral neck carries a risk of perforation due to the presence of the isthmus of the femoral neck. At present, there are few studies on the safe and risk zones of the femoral neck system (FNS) implantation. This study aimed to recommend the safe range of injection of FNS in the lateral wall of the proximal femur, parallel to the axis of the femoral neck, during FNS treatment of femoral neck fracture (FNF).MethodsFemoral computed tomography (CT) data of 80 patients (male: 40; female: 40) who met the inclusion criteria were collected. Mimics 21.0 software was used to complete the modeling. 3-Matic 13.0 software was used to establish the axis of the femoral neck and its vertical plane, perform the cutting of the femoral neck, and project it on the vertical plane of the femoral neck axis. After matching a rectangle for each projection map, all sample sizes (80 cases) were standardized and superimposed to obtain gradient maps of the safe zone (SZ) and dangerous zone (RZ), thereby securing edge key points and safe FNS insertion range.ResultsIn the 80 samples, the mean diameter of the smallest femoral neck section was 33.87 ± 2.32 mm for men and 29.36 ± 1.92 mm for women. All 80 femoral necks had safe and risky areas. The SZ/S × 100% was 77.59 (± 2.22%), and the RS/S × 100% was 22.39% (± 2.22%). The risk area was composed of four parts: (1), (2), (3), and (4), respectively, corresponding to 3.45 ± 1.74%, 5.51 ± 2.63%, 6.22 ± 1.41%, and 7.22 ± 1.39%. Four marginal key points, perforation risk, and safe ranges (SR) of FNS were analyzed on the lateral wall of the femoral neck.ConclusionsThe SR of FNS placement was recommended by digital simulation. In addition, Regions (3) and (4) posed a higher risk of penetrating the cortex. Using the gradient map of RZ for preoperative evaluation is recommended to avoid iatrogenic perforation.

Vibration Suppression of an Input-Constrained Wind Turbine Blade System

During the actual wind power generation process, wind turbines are often affected by side effects such as blade vibrations, input constraints, and actuator faults. This can lead to a reduction in power generation efficiency and even result in unforeseen losses. This study discusses a robust adaptive fault-tolerant boundary control approach to address the issues of input-constrained and actuator-fault problems in wind turbine blade vibration control. By employing projection mapping techniques and hyperbolic tangent functions, a novel robust adaptive controller based on online dynamic updates is constructed to constrain vibrations, compensate for unknown disturbance upper bounds, and ensure the robustness of the coupled system. Additionally, considering the possibility of actuator faults during the control process, a fault-tolerant controller is proposed to effectively suppress elastic vibrations in the wind turbine blade system even in the presence of actuator faults. The effectiveness of the proposed controller is validated through numerical simulations.

Mopane (Colophospermum mopane): A potential winner under climate change in southern Africa

AbstractDistribution and abundance under climate change of particularly non‐timber forest product tree species is vital since they sustain many livelihoods, especially in rural sub‐Saharan Africa. The aim of the study was to determine the current and future natural range of mopane (Colophospermum mopane (J. Kirk ex Benth.) J. Léonard, Fabaceae), a dominant tree species in mopane woodlands of southern Africa. An ensemble model was built in ‘biomod2’ from eight algorithms and used to estimate the current and future distribution. Seven bioclimatic variables and 269 occurrence records were used to calibrate individual models that were later combined into an ensemble model. The ensemble model was projected to two time periods, 2041–2060 and 2081–2100, under two shared socio‐economic pathways (SSPs), SSP2‐4.5 and SSP5‐8.5, and three general circulation models (GCMs). The ensemble model showed high performance (KAPPA = 0.770, ROC = 0.961, TSS = 0.792, ACCURACY = 0.900). A map of the current distribution shows occurrence predominantly in low‐lying areas, including the Zambezi, Save and Limpopo valleys, Okavango and Cuvelai basins, and in southern and central Mozambique. Projection maps show expansion under all SSPs, GCMs and time periods. Averaged across GCMs in 2041–2060, the range expanded by 22.37% under SSP2‐4.5, and by 19.94% under SSP5‐8.5. In 2081–2100, the range expanded by 20.43% under SSP2‐4.5, and by 27.62% under SSP5‐8.5. Notably, the range expansion was highest under SSP5‐8.5, an SSP that envisages unmitigated greenhouse gas release and the largest mean global temperature increase. It is highly likely that mopane is not directly threatened by climate change. Indirect climate change threats, however, remain uncertain.

Projection mapping system for laser speckle contrast image: feasibility study for clinical application.

Laser speckle contrast images (LSCIs) have been utilized to monitor blood flow perfusion. However, they have conventionally been observed on monitor screens, resulting in potential spatial mismatching between the imaging region of interest (IROI) and monitor screen. This study proposes a projection mapping (PM) system for LSCIs (PMS_LSCI) that projects LSCIs to directly observe the blood flow perfusion in the IROI. The PMS_LSCI consists of a camera, imaging optics, a laser projector, and graphic user interface software. The spatial matching in the regions of interest was performed by adjusting the software screen of the LSCI in the IROI and evaluated by conducting in-vitro and in-vivo studies. An additional in-vivo study was performed to investigate the feasibility of real-time PM of the LSCI. The spatial mismatching in the regions of interest was ranged from 2.74% to 6.47% depending on the surface curvature. The PMS_LSCI could enable real-time PM of LSCI at four different blood flow states depending on blood pressure. The PMS_LSCI projects the LSCI in the IROI by interacting with a projector instead of the monitor screen. The PMS_LSCI presented clinical feasibility in the in-vitro and in-vivo studies.

A weighted local‐spherical grid based lightweight descriptor for 3D point cloud registration

AbstractEstablishing effective feature descriptors is a crucial step in 3D point cloud registration task. Existing manual‐based methods are noise‐susceptible and time‐consuming when running on low‐cost edge computing devices. To this end, the authors proposed a Local Reference Frame (LRF) based approach that can quickly and robustly register point clouds by using a novel lightweight local‐spherical grid weighted descriptor (LSGWD). Firstly, the LRF of the proposed algorithm is established by the covariance matrix eigenvector of KeyPoint's spherical support set and the centroid vector's projection on its orthogonal plane. Then the spherical support is grided to 32 bins, and the 4D geometric features of each subset are constructed by the centroid moment and the cosine value of the angles between the centroid vector and axes of LRF. Secondly, to restrain the insufficient discriminative information presented in the purely geometric features, the Gaussian projection and gradient mapping are proposed to calculate the smooth density and the correlation of structural characteristics, which are obtained as the distribution information of each bin to weigh the feature representation. Finally, the 32 × 4‐dimensional KeyPoint descriptor is obtained and used in the 3D point cloud registration framework. Experiments are carried out on three test datasets and real scene data. Compared to previous baselines, our descriptor achieves the state‐of‐the‐art performance in terms of efficiency and accuracy owing to its compact structure and noise robustness. The proposed method enhances the recognition and registration performance of 3D point cloud matching in low‐cost edge computing applications.

Multimodal construction of human movement dataset under the development of physical dance teaching in colleges and universities

Abstract First, this paper proposes a multimodal fusion-based human motion recognition technique applied to college physical dance teaching, where feature-level or decision-level fusion maps human kinematic semantic information from datasets to classifiers under a single-level stage. Secondly, a multi-level multimodal fusion approach for human motion recognition is proposed to make it more adaptable to practical application scenarios. The depth data is converted into a depth motion projection map at the input side, and the inertial data is converted into a signal image. Finally, all the modalities are trained by a convolutional neural network for extracting features, and the extracted features are fused at the feature level by discriminant correlation analysis. The results show that the multi-level multimodal fusion framework achieves 99.8% and 99.9% recognition accuracy on the two datasets, respectively, with 100% accuracy in the Throw and Catch action recognition and the lowest recognition rate of 95.36% in the Clap action test, with an average recognition rate of 97.89%, which has a high recognition accuracy. The multi-level multimodal fusion model can obtain movement data close to the actual movement data after optimization in low-precision movement data, which provides data support for physical dance teaching and learning.

Visual perception-oriented quality assessment for high dynamic range stereoscopic omnidirectional video system

High dynamic range stereoscopic omnidirectional video (HSOV) system provides users with an immersive visual experience, but the distortions generated in the process of visual content generation, coding, and visualization also brings challenges to visual quality assessment. This paper proposes a visual perception-oriented quality metric for HSOV system. Considering the computational efficiency, for frames within each second, several key frames are selected so that features reflecting distortions can be extracted from the viewports and equi-angular cubemap (EAC) projection surfaces of these frames. In viewport feature extraction module, the sum and difference maps of the left and right views of the key frames are used to simulate the binocular perception. Considering that distortions will affect the structure, color and statistical properties of the image, the gradient, local binary pattern and statistical features are extracted, respectively. To reduce projection distortion, EAC projection is used to instead of other projections normally used in quality assessment, and the Sigma domain feature extraction and color feature extraction are performed on EAC projection map. In temporal feature extraction module, wavelet decomposition is used to perform temporal domain bandpass filtering on partial continuous frames to calculate the naturalness features. Finally, the above features of the frames at different scales are pooled through random forest model to predicate the quality score of HSOV. Experimental results on the NBU-HSOVD dataset show that the proposed metric is superior to some blind image/video quality assessment metrics and has higher consistency with the human visual perception.

Data management and protection in occupational and environmental exposome research - A case study from the EU-funded EXIMIOUS project

Within collaborative projects, such as the EU-funded Horizon 2020 EXIMIOUS project (Mapping Exposure-Induced Immune Effects: Connecting the Exposome and the Immunome), collection and analysis of large volumes of data pose challenges in the domain of data management, with regards to both ethical and legal aspects. However, researchers often lack the right tools and/or accurate understanding of the ethical/legal framework to independently address such challenges. With the guidance and support within and between the partner institutes (the researchers and the ethical and legal teams) in the EXIMIOUS project, we have been able to understand and solve most challenges during the first two project years. This has fed into the development of a Data Management Plan and the establishment of data management platforms in accordance with the ethical and legal framework laid down by the EU and the different national regulations of the partners involved. Through this elaborate exercise, we have acquired tools which allow us to make our research data FAIR (Findable, Accessible, Interoperable, and Reusable), while at the same time ensuring data privacy and security (GDPR compliant). Herein we share our experience of creating and managing the data workflow through an open research communication, with the aim of helping other researchers build their data management framework in their own projects. Based on the measures adopted in EXIMIOUS to ensure FAIR data management, we also put together a checklist “DMP CHECK” containing a series of recommendations based on our experience.