Detailed Shape Research Articles

A multi-scale robotic approach for precise crack measurement in concrete structures

This paper introduces a multi-scale robotic approach for measuring the width, length, shape, and profile of hairline cracks in concrete structures. The approach uses a convolutional neural network to identify potential surface cracks, and then robotically navigates a high-resolution laser scanner to measure the detailed shape of the detected cracks. Finally, 3D point cloud registration techniques fuse the laser scans with LiDAR-based scan of the surrounding environment. The proposed method is validated with computer simulations and physical experiments on a concrete specimen. The results are compared against the state-of-the-art, vision-based methods as well as readings of a transparent crack width ruler. The comparison demonstrates the superiority and effectiveness of the proposed multi-scale robotic approach in measuring hairline cracks providing vital data for assessing the conditions of civil infrastructures.

RNO 54: A Previously Unappreciated FU Ori Star

We present evidence in support of the hypothesis that the young stellar object RNO 54 is a mature-stage FU Ori type source. The star was first cataloged as a “red nebulous object” in the 1980s but appears to have undergone its outburst prior to the 1890s. Present-day optical and near-infrared spectra are consistent with those of other FU Ori-type stars, both in the details of spectral line presence and shape, and in the overall change in spectral type from an FGK-type in the optical, to the M-type presented in the near-infrared. In addition, the spectral energy distribution of RNO 54 is well-fit by a pure-accretion disk model with parameters: M ⊙ yr−1, M * = 0.23 ± 0.06 M ⊙, and R inner = 3.68 ± 0.76 R ⊙, though we believe R inner is likely close to its upper range of 4.5R ⊙ in order to produce a K that is consistent with the optical to near-infrared spectra. The resulting L acc is ∼265 L ⊙. To find these values, we adopted a source distance d = 1400 pc and extinction A V = 3.9 mag, along with disk inclination i = 50 deg based on the consideration of confidence intervals from our initial disk model, and in agreement with observational constraints. The new appreciation of a well-known source as an FU Ori-type object suggests that other such examples may be lurking in extant samples.

Evolution of pollen grain morphology in Amorimia and allies evidences the importance of palynological apomorphies and homoplasies in Malpighiaceae systematics

Background and aims – Pollen grain morphology is an important morphological character for aiding the systematics of flowering plants. For Malpighiaceae, only a single unpublished palynological study has comprehensively sampled ca 60 of this family’s 75 currently accepted genera. To test the systematic relevance of pollen morphology in Amorimia and allies, we characterised the pollen morphology of these lineages. We scored, coded, and mapped 12 characters onto the most recent molecular phylogeny of Amorimia and allies. Material and methods – We sampled 13 species of Amorimia as ingroup and two species of Mascagnia and Ectopopterys soejartoi as outgroup. Pollen grains were acetolised, characterised, and measured using light microscopy and scanning electron microscopy. Pollen quantitative measurements were submitted to a PCA multivariate analysis. Additionally, quantitative and qualitative characters were scored and coded into 12 characters and mapped onto the molecular phylogeny of Amorimia and allies. Key results – Amorimia and allies are stenopalynous due to all species showing the same pollen type, with some subtle differences between the pollen grains, such as details of ornamentation, shape, size, and thickness of the pollen exine. However, the patterns of pollen grain evolution showed that few qualitative and apomorphic characters are informative for intrageneric distinction (i.e. type and number of apertures), and almost all quantitative and homoplastic characters analysed were informative at infrageneric levels within Malpighiaceae. Conclusion – Our results demonstrate that even though the pollen morphology characters of Amorimia and allies show subtle variation, both qualitative and quantitative apomorphic and/or homoplastic characters are highly informative for intra- and infrageneric levels in Malpighiaceae when analysed in a phylogenetic context.

Alternativeness in the Architectural Design of Bridges and Overpasses

Modern extensive foreign and domestic experience in design and construction of multifunctional overpasses and bridges indicates that they have become an integral part of urbanised systems. They are endowed with the functions of important urban objects, and with their appearance they have won the right to be considered iconic structures. The subject of the article refers to architectural design of bridges and overpasses. The authors set themselves the task of considering the aspects of combining the main functional characteristics with the aesthetic properties of the object, designating visual components of the project and the specifics of alternativeness of design.The objective of the work is to consider alternativeness in architectural design of bridges and overpasses. A complex method, combining an analysis of the historical and modern experience of architectural theory and design practices, was based on technical literary materials. The study resulted in formulating indicators and leading principles of alternative design.The use of alternatives in the process of designing urban bridges and overpasses allows not only to consider functionality and economic feasibility of a particular project and construction of an object, but also its architectural and artistic orientation, aesthetic component, as well as the designer’s worldview and current trends in architecture. In the process of alternative design of bridges and overpasses, it is required to reproduce the overall complete image of the future structure, consider all kinds of details in structures and shape, and various criteria for layout and location in the environment.

Numerical Determination of Target Values and Process Parameters of Case Hardening, Taking into Account the Local Stress State of Failure-Relevant Construction Details

Abstract Through the thermochemical process of case hardening, the local material strength of steel components can be increased. In addition to the increase in stress due to the notch effect, the shape of construction details also has an effect on key component properties after case hardening, such as edge hardness and case hardening depth. The component-related specification of target values for case hardening is currently based on empirical values or expert knowledge. In addition, the effect of design details during case hardening is not taken into account when specifying process parameters in the control and regulation software of case hardening systems. This article presents a concept for the numerical determination of target values and process parameters for case hardening based on the stress state of the component. Compared to the empirically based determination of target values and process parameters for case hardening, the application of the concept makes it possible to adapt the case hardening of components to their stress in the failure range and thus significantly increase the energy and resource efficiency of case hardening.

Figures of Classic Kamasan Painting as Inspiration for the Creation of Modern Painting

The classic painting of Wayang Kamasan began when the Modara puppet painting, made by I Gede Mersadi was favored by the king of Klungkung. Then he was given the nickname Modara according to the puppet figure he painted. By king Klungkung Modara was sent to work on many projects so that his puppet painting style spread and until now it is known as Classical Painting Wayang Kamasan. The characteristic of this painting can be seen from the coloring technique that uses the sigar warna and sigar mangsi techniques. (Ni Wayan Sri Wedari, 2022:9). Broadly speaking, the forms of wayang can be distinguished through the shape of the face, body shape or abdomen and coils as well as detailed parts of the eyes, eyebrows, nose, mouth, mustache, and other detailed shapes. (I Made Yasana, Menggambar Wayang Klasik Bali 1). Gede Modara who created the Kamasan Wayang style inspired the author to create puppets with a new style through the figures in the Kamasan Classical Puppet. This creation process aims to preserve the Kamasan Classical Puppet and develop it into a modern painting without eliminating the existing packages. The paintings created are expected to be able to become the characteristics of the author.

STED microscopy reveals dendrite-specificity of spines in turtle cortex

Dendritic spines are key structures for neural communication, learning and memory. Spine size and shape probably reflect synaptic strength and learning. Imaging with superresolution STED microscopy the detailed shape of the majority of the spines of individual neurons in turtle cortex (Trachemys scripta elegans) revealed several distinguishable shape classes. Dendritic spines of a given class were not distributed randomly, but rather decorated significantly more often some dendrites than others. The individuality of dendrites was corroborated by significant inter-dendrite differences in other parameters such as spine density and length. In addition, many spines were branched or possessed spinules. These findings may have implications for the role of individual dendrites in this cortex.

Failure identification and location in asphalt materials using coplanar capacitance technology

Compared to traditional non-destructive testing (NDT) methods, coplanar capacitance technology has advantages in intuitive identification and accurate location for identifying and locating the various failures in asphalt materials. At present, research on coplanar capacitance technology for various failure detection and location in asphalt materials is missing. Therefore, this paper aims to develop a various failure detection and location method in asphalt materials using coplanar capacitance technology. Firstly, the capacitance distribution measurement on the single-pair electrode capacitance sensor with constant area (CSCS) is utilized to locate the various failures of asphalt materials. Then, the various failure depth inside asphalt materials can be predicted using a standard curve of the various failure depth-maximum change capacitance. Finally, based on the single-pair electrode capacitance sensor with variable area (VSCS), the spatially resolved capacitance measurement determines the various failure shape details of asphalt materials. It is found that the Ultrasonic Tomography Technology (UTT) method can only identify internal various failures in asphalt materials and is unable to determine the location of various failures. Nevertheless, the capacitance distribution measurement can identify air void and water intrusion various failures in asphalt materials. And the relative error of the measured location results inside asphalt materials is within 7. The predicted curves of various failure depths in asphalt materials have a coefficient of determination (R2) of greater than 0.984. The maximum change capacitance can be utilized to estimate the various failure depth in asphalt materials. The UTT method makes it difficult to determine the shapes and sizes of various failures in asphalt materials. But the spatially resolved capacitance measurement can determine the various failure shape details of asphalt materials. And the errors in the reconstructed results with failure shape details inside asphalt materials are less than 11%. The findings of this investigation can help engineers realize intuitive identification and precise location of invisible failures in shallow asphalt layers in bridge deck asphalt pavement using coplanar capacitance technology.

Recognition of building shape in maps using deep graph filter neural network

Shape is one of the core features of the buildings which are the main elements of the map. The building shape recognition is widely used in many spatial applications. Due to the irregularity of the building contour, it is still challenging for building shape recognition. Inspired by graph signal processing theory, we propose a deep graph filter neural network (DGFN) for the shape recognition of buildings in maps. First, we regard shape recognition as a combination of subjective and objective graph signal filtering process. Second, we construct a shape features extraction framework from the perspective of shape details, shape structure and shape local information. Third, DGFN model can fulfil the tasks of shape classification and shape embedding of building at the same time. Finally, multi angle experiments verify our viewpoint of shape recognition mechanism, and the comparison with similar algorithms proves the high accuracy and availability of DGFN model.

Performance of wildlife fence systems under animal impact load

Wildlife fence protection systems specifically designed for animal protection are critical in mitigating wildlife-vehicle collisions and preserving animal habitats. These systems are quite similar to rockfall barrier systems, which are well studied and developed, however, few studies are specifically oriented toward investigating structural performance of these systems. Despite the similarities, results of studies related to rockfall barriers may not be directly applicable to design and performance evaluation of wildlife barrier systems due to differences in a range of size, shape, and velocity of impactors and structural details. This study aims to bridge this gap by analyzing performance and capacity of wildlife structures in more detail through parametric study with consideration of a wide range of properties and structural details appropriate for these systems, such as mesh type (square and inclined), mesh size, and wire diameters. The behavior of these systems under impact loads is simulated using nonlinear finite element models with consideration of ductile damage and element removal techniques to accurately capture wire rupture and changes in the impactor-fence system interface. The results demonstrate that the response of the system is highly influenced by factors such as mesh type, opening size, wire diameter, and impactor size. Notably, the system utilizing an inclined mesh type exhibits a 35 % higher failure velocity, 50 % greater energy dissipation, and 21 % less maximum displacement compared to the square mesh system. The detailed results and discussions in this study provide valuable insights into the influence of individual parameters on the behavior of wildlife fence systems, aiding in the design of more efficient wildlife barrier systems with enhanced performance.

Local Curvature Estimation and Grasp Stability Prediction Based on Proximity Sensors on a Multi-Fingered Robot Hand

This study aims to realize a precision grasp of unknown-shaped objects. Precision grasping requires a detailed understanding of the surface shapes such as concavity and convexity. If an accurate shape model is not given in advance, it must be addressed by sensing. We have proposed a method for recognizing detailed object shapes using proximity sensors equipped on each fingertip of a multi-fingered robot hand. Direct sensing of the object’s surface from the fingertips enables both avoidance of unintended collision during the approach process and recognition of surface profiles for use in planning and executing stable grasping. This paper introduces local surface curvature estimation to improve the accuracy of local surface recognition. We propose practical and accurate models to estimate local curvature based on various characteristic tests on the proximity sensor and to estimate the distance to the nearest point. In actual experiments, it was shown that it was possible to estimate the position of the nearest point with a mean error of less than 2 mm and to predict grasping stability in reasonable real-time for the object shape.

On the Band-Limited Information Throughput of Free-Selective and Free-Responsive Spatially Non-Local Perception

A single-blind experiment was conducted on free-responsive spatially non-local perception of free-selective simple photographic targets. One author (the tasker) chose a photographic target not subjected to a priori compiling, and the other author (the perceiver) attempted to unconventionally perceive the target. Feedback was expected prior to a new target being selected. A hundred trials were completed over 11 months. Thirteen judges offered gradings that collectively projected an apparent information requisition yield (AIRY). The AIRY refers to two aspects of the matching of a taskette (a target’s counterpart) with respect to the target based on fuzzy scales from 0% to 100%, graded with an increment of 10%. The type-I or “tangibility” aspect of matching assessed the extent of the resemblance of a taskette to the target in terms of the shape or structural details of the primary physical entity/event. The type-II or “intangibility” aspect of the matching assessed the degree of the reconstruction of a taskette to the target in terms of the feature or functionality of the predominant physical entity/event. A total of 6 taskettes received >50% grades in both type-I and type-II aspects of matching with their respective targets. This outcome may correspond to an effect size of 1.47 if the chance-expectation may give a benchmark proportion of 3 out of 100 trials producing >50% grades in both type-I and type-II aspects of matching. Patterns indicating target interference associated with two trials entail further investigation. The approaches offer new insights to quantifying the band-limited information throughputs of spatially non-local perception.

A dense multi‐scale context and asymmetric pooling embedding network for smoke segmentation

AbstractIt is very challenging to accurately segment smoke images because smoke has some adverse vision characteristics, such as anomalous shapes, blurred edges, and translucency. Existing methods cannot fully focus on the texture details of anomalous shapes and blurred edges simultaneously. To solve these problems, a Dense Multi‐scale context and Asymmetric pooling Embedding Network (DMAENet) is proposed to model the smoke edge details and anomalous shapes for smoke segmentation. To capture the feature information from different scales, a Dense Multi‐scale Context Module (DMCM) is proposed to further enhance the feature representation capability of our network under the help of asymmetric convolutions. To efficiently extract features for long‐shaped objects, the authors use asymmetric pooling to propose an Asymmetric Pooling Enhancement Module (APEM). The vertical and horizontal pooling methods are responsible for enhancing features of irregular objects. Finally, a Feature Fusion Module (FFM) is designed, which accepts three inputs for improving performance. Low and high‐level features are fused by pixel‐wise summing, and then the summed feature maps are further enhanced in an attention manner. Experimental results on synthetic and real smoke datasets validate that all these modules can improve performance, and the proposed DMAENet obviously outperforms existing state‐of‐the‐art methods.

A disc wind model for blueshifts in quasar broad emission lines

ABSTRACT Blueshifts – or, more accurately, blue asymmetries – in broad emission lines such as C iv λ1550 are common in luminous quasars and correlate with fundamental properties such as Eddington ratio and broad absorption line (BAL) characteristics. However, the formation of these blueshifts is still not understood, and neither is their physical connection to the BAL phenomenon or accretion disc. In this work, we present Monte Carlo radiative transfer and photoionization simulations using parametrized biconical disc-wind models. We take advantage of the azimuthal symmetry of a quasar and show that we can reproduce C iv blueshifts provided that (i) the disc-mid-plane is optically thick out to radii beyond the line formation region, so that the receding wind bicone is obscured; and (ii) the system is viewed from relatively low (that is, more face-on) inclinations (≲40°). We show that C iv emission-line blueshifts and BALs can form in the same wind structure. The velocity profile of the wind has a significant impact on the location of the line formation region and the resulting line profile, suggesting that the shape of the emission lines can be used as a probe of wind-driving physics. While we are successful at producing blueshifts/blue asymmetries in outflows, we struggle to match the detailed shape or skew of the observed emission-line profiles. In addition, our models produce redshifted emission-line asymmetries for certain viewing angles. We discuss our work in the context of the C iv λ1550 emission blueshift versus equivalent-width space and explore the implications for quasar disc wind physics.

Shaping bridge decks for VIV mitigation: A wind tunnel data-driven adaptive surrogate-based optimization method

Vortex-induced vibration (VIV) of deck girders frequently drives the wind-resistant design of wind-sensitive bridges from the preliminary to final design stages. Shaping bridge decks is a proven strategy to mitigate VIV. While significant shape modifications are commonly restricted to preliminary design stages, only minor medications are possible at advanced design stages, typically involving adding flow modifiers or changing the shape and location of existing appendages. These mitigation strategies have been implemented in the last decades by carrying out expensive wind tunnel campaigns and following heuristic design rules. This paper proposes an experimental data-driven adaptive surrogate-based optimization approach to systematically identify optimum deck shapes that minimizes the economic cost of the bridge while fulfilling the VIV project specifications. The methodology is conceived to carry out simultaneously the general and detailed shape design of the final deck configuration by harnessing a sequential sampling plan aiming at reducing the sectional model construction costs. The proposed holistic design framework is successfully applied to a real application case involving 26 wind tunnel tests of 1.8-meter wide sectional models to figure out the optimal gap distance and location of maintenance tracks of a twin-box deck equipped with all the appendages included in the final deck design.

Patho-morphological and Immunohistochemical Studies on Bovine Horn Core Carcinoma

Background: An investigation was carried out on twelve clinical cases of neoplasm of horn in Durg, Dhamtari and Rajnandgaon districts of Chhattisgarh, suspected of bovine horn core carcinoma (squamous cell carcinoma) revealed the cytology, pathomorphology and immunohistochemical (IHC) expression of Pan-cytokeratin (Pan- CK), p53 gene, epidermal growth factor receptor (EGFR) and p16 gene in tumourous growth at horn in bovines. Methods: In this field-laboratory investigation conducted during January to June 2022, we explicate the cytological, pathological and immunohistochemical alterations in bovine horn core carcinoma from 12 tissue samples. Cytological studies includes special papaniculaou staining and immunohistochemistry was performed through Benchmark automated staining system. Result: Eight out of 12 cases (66.66%) were confirmed as SCC of horn on the basis of histopathological and immunohistochemical analysis. Papanicolaou staining revealed variation in shape and size of cells and altered nuclear details. Grossly unilateral large cauliflower like neoplastic growth at the base of the horn was observed. Differentiation of tumours were based on histopathology and Immunohistochemistry. Well differentiated SCCs (n=4; 50%) were characterized by severe keratinization of horn epithelium with concentric arrangement forming keratin pearls also called as “cell nests”. Moderately differentiated SCCs (n=2; 25%) characterized by small keratin pearl formations and mitotic figures. Poorly differentiated SCCs of horn (n=2; 25%) revealed absence of distinctive keratin pearls although deep invasion from primary site was observed. Tissue samples revealed strong immunohistochemical staining of Pan-CK, p53 and EGFR and negative to p16. Highest immunohistochemical expression was observed in Pan-CK which confirmed the tumours were of epithelial origin and EGFR immunoexpression was confirmatory for malignancy and degree of metastasis.

COMPARISON OF POTENTIAL ENERGY OF SOLAR RADIATION IN ROOFTOP MODELING USING DIFFERENT BUILDING LEVELS OF DETAIL

Abstract. The potential for future energy crises is a problem the world is currently facing. Many countries are switching from fossil to renewable energy to prevent an energy crisis. One of the most developed renewable energy today is solar energy. Easy installation makes solar energy installation not only on a large scale but also on a home scale. Urban areas will be very suitable for building solar photovoltaic (PV) roofs due to minimal open areas. In installing rooftop solar PV, sound planning is needed to predict the energy potential that can be provided by solar energy on the rooftop of a building. Spatial modeling can be done to determine the energy potential and suitable location for rooftop solar PV installation. In building rooftop solar PV modeling, the level of detail of the building will affect the results of the model. The rooftop's shape and the building's height will affect the amount of solar radiation going into the building. However, the higher the level of detail of the building, the higher the cost and processing time will be. This study will review the differences in modeling the potential of rooftop solar PV using different levels of detail. This research will integrate solar radiation data from remote sensing to determine the energy potential of solar radiation and digital surface model data from photogrammetry to create a level of detail for buildings. Integration of solar radiation data and the level of detail of the building will use hillshade analysis. Hillshade analysis can review the shadow effect on the rooftop of a building which will be directly related to the potential of solar energy on the rooftop of the building. This study determines the energy potential on the rooftop of the building with different levels of detail, namely 0, 1, and actual shape, to determine the difference in energy potential in the three scenarios. Hopefully, this research will determine the best level of detail for modeling rooftop solar PV. The best model that can show high accuracy value but at a lower price. Hopefully, this research can also assist policymakers and the public in planning for rooftop solar PV installations to develop renewable energy.

MagicInput: Virtual Handwriting Interface Using Ubiquitous WiFi Signals

Past few years have witnessed the great potential of exploiting WiFi signals for positioning. Prior work focus on discovering the absolute locations of a radio source, and have achieved promising accuracies of tens of centimeters. However, many applications such as aerial gesture or handwriting tracking are more concerned with the detailed motion shape of the target rather than its exact locations, which require a several fold higher accuracy. To this end, we present MagicInput, a virtual handwriting interface by tracking the motion traces of a WiFi source. Based on Channel State Information (CSI), MagicInput elaborately devises an incremental motion-based tracking model by correlating the motion traces with the angle and length variations of propagation paths. The model shifts the tracking task from the transceiver view to the antenna array-oriented view, and eliminates the need for prior knowledge of anchor locations. MagicInput proposes an end-to-end pipeline for tracking refinement, by interference suppression, motion segmentation, and an integrated grasp pressure sensorbased motion instance detection. We prototype MagicInput using off-the-shelf WiFi radios, and extensive experiments attest that MagicInput can achieve the accuracy of 8.5 mm confronting diverse users and environment conditions. With ubiquitous WiFi signals, MagicInput can transform any region into an interactive handwriting interface with millimeter accuracy.

Variational Relational Point Completion Network for Robust 3D Classification.

Real-scanned point clouds are often incomplete due to viewpoint, occlusion, and noise, which hampers 3D geometric modeling and perception. Existing point cloud completion methods tend to generate global shape skeletons and hence lack fine local details. Furthermore, they mostly learn a deterministic partial-to-complete mapping, but overlook structural relations in man-made objects. To tackle these challenges, this paper proposes a variational framework, Variational Relational point Completion network (VRCNet) with two appealing properties: 1) Probabilistic Modeling. In particular, we propose a dual-path architecture to enable principled probabilistic modeling across partial and complete clouds. One path consumes complete point clouds for reconstruction by learning a point VAE. The other path generates complete shapes for partial point clouds, whose embedded distribution is guided by distribution obtained from the reconstruction path during training. 2) Relational Enhancement. Specifically, we carefully design point self-attention kernel and point selective kernel module to exploit relational point features, which refines local shape details conditioned on the coarse completion. In addition, we contribute multi-view partial point cloud datasets (MVP and MVP-40 dataset) containing over 200,000 high-quality scans, which render partial 3D shapes from 26 uniformly distributed camera poses for each 3D CAD model. Extensive experiments demonstrate that VRCNet outperforms state-of-the-art methods on all standard point cloud completion benchmarks. Notably, VRCNet shows great generalizability and robustness on real-world point cloud scans. Moreover, we can achieve robust 3D classification for partial point clouds with the help of VRCNet, which can highly increase classification accuracy. Our project is available at https://paul007pl.github.io/projects/VRCNet.

고구려 곡개의 원형탐색과 3D 디지털 복원

Koguryo's mural tombs contain an object called a 'Gok-gae.' In this study, we discovered and reviewed Koguryo's 'Gok-gae' and restored the 'Gok-gae' of Anak Tomb No.3 using 3D digital data. Anak Tomb No.3 is listed as a UNESCO World Heritage Site. The 'Gok-gae' was a prestigious item used to display one's status in public and was symbolically worn by nobles, including the imperial family of various Chinese dynasties. It later became an ornament in the royal courts of Koryo and Joseon. This study is an interdisciplinary collaboration. The research methodology involved collecting and reviewing literature and paintings from Chinese dynasties to extract their uses, meanings, and forms. Based on this, a comparative analysis of Koguryo's 'Gok-gae' and related pictorial materials was conducted. Through the literature, we examined the meaning, utility, and instances of vouchsafe of the 'Gok-gae.' With the pictorial data, we examined the size, shape, and color in detail. We discovered that the Koguryo 'Gok-gae' were not significantly different from the various ornamental objects used by Chinese dynasties. The digital prototype reconstruction of the 'Gok-gae' is expected to provide valuable clues for reconstructing the political, social, and cultural history of Northeast Asia, particularly regarding Koguryo ornaments.