scholarly journals A Semi-Automatic Reconstruction of Archaeological Pottery Fragments from 2D Images Using Wavelet Transformation

Heritage ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 76-90
Author(s):  
Dariush Eslami ◽  
Luca Di Angelo ◽  
Paolo Di Stefano ◽  
Emanuele Guardiani
Keyword(s):  
Wavelet Transformation ◽  
State Of The Art ◽  
Three Dimensional ◽  
Correlation Coefficients ◽  
Transformation Method ◽  
3D Objects ◽  
Archaeological Pottery ◽  
Computer Based ◽  
Approximation Coefficients ◽  
2D Images

The problem of matching fragments of three-dimensional (3D) objects has gained increasing attention, and several approaches have been developed to solve this problem. To date, however, to the best knowledge of the authors, there is no computer-based method supporting archaeologists in this activity. For this purpose, in this paper, a semi-automatic approach is proposed for the reconstruction of archaeological pottery fragments based on two-dimensional (2D) images. Firstly, the method, considering the curves as features, involves the extraction of edge curves by applying the Canny filter algorithm to the fragments’ image. Next, the wavelet transformation method is used to fit the edge curves and obtain the approximation coefficients. Then, the correlation coefficients between fragments are computed and the matching of fragments is done by comparing their values. The proposed approach is tested on some real cases. The results of the experimentation show, if compared with the state-of-the-art, that the method seems to be efficient and accurate in the reconstruction of pottery from 2D images of their fragments.

scholarly journals Evaluation of visual cues of three-dimensional virtual environments for helicopter simulators

2011 ◽  
Vol 9 (4) ◽  
pp. 347-360
Author(s):  
Yasemin Çetin ◽  
Erdal Yılmaz ◽  
Yasemin Yardımcı Çetin
Keyword(s):  
Visual Cues ◽  
Three Dimensional ◽  
Distance Estimation ◽  
3D Object ◽  
3D Objects ◽  
Helicopter Flight ◽  
Flight Simulators ◽  
Computer Based ◽  
Low Altitude ◽  
Military Pilots

Visual cues are an essential part of helicopter flight simulators. The required cues for hover are particularly large, due to closeness to the ground and small movements. However, the research on low-altitude helicopter flight is limited. In this research, the density and height of the three-dimensional (3D) objects in the scene are analysed to find their effect on hovering and low-altitude helicopter flight. An experiment is conducted using a personal computer-based flight simulator on 10 professional military pilots. The results revealed that 3D object density and 3D object height affect both horizontal and vertical hovering performance. In hover and low-altitude flight, altitude control is positively affected by smaller object height. Paradoxically, the pilots preferred the scenes composed of tall and mixture objects. Pilot distance estimation was significantly affected by the knowledge of both object density and object height, but these factors do not individually improve distance estimation.

Enhanced context-aware recommendation using topic modeling and particle swarm optimization

2021 ◽  
pp. 1-16
Author(s):  
Ibtissem Gasmi ◽  
Mohamed Walid Azizi ◽  
Hassina Seridi-Bouchelaghem ◽  
Nabiha Azizi ◽  
Samir Brahim Belhaouari
Keyword(s):  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
State Of The Art ◽  
Weighting Function ◽  
Contextual Factors ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Pso Algorithm ◽  
Context Aware ◽  
Proposed Model

Context-Aware Recommender System (CARS) suggests more relevant services by adapting them to the user’s specific context situation. Nevertheless, the use of many contextual factors can increase data sparsity while few context parameters fail to introduce the contextual effects in recommendations. Moreover, several CARSs are based on similarity algorithms, such as cosine and Pearson correlation coefficients. These methods are not very effective in the sparse datasets. This paper presents a context-aware model to integrate contextual factors into prediction process when there are insufficient co-rated items. The proposed algorithm uses Latent Dirichlet Allocation (LDA) to learn the latent interests of users from the textual descriptions of items. Then, it integrates both the explicit contextual factors and their degree of importance in the prediction process by introducing a weighting function. Indeed, the PSO algorithm is employed to learn and optimize weights of these features. The results on the Movielens 1 M dataset show that the proposed model can achieve an F-measure of 45.51% with precision as 68.64%. Furthermore, the enhancement in MAE and RMSE can respectively reach 41.63% and 39.69% compared with the state-of-the-art techniques.

scholarly journals Do 3D Face Images Capture Cues of Strength, Weight, and Height Better than 2D Face Images do?

2021 ◽  
Vol 7 (3) ◽  
pp. 209-219
Author(s):  
Iris J Holzleitner ◽  
Alex L Jones ◽  
Kieran J O’Shea ◽  
Rachel Cassar ◽  
Vanessa Fasolt ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Physical Characteristics ◽  
Two Dimensional ◽  
3D Images ◽  
3D Face ◽  
Face Images ◽  
Similar Accuracy ◽  
2D And 3D ◽  
2D Images ◽  
Better Than

Abstract Objectives A large literature exists investigating the extent to which physical characteristics (e.g., strength, weight, and height) can be accurately assessed from face images. While most of these studies have employed two-dimensional (2D) face images as stimuli, some recent studies have used three-dimensional (3D) face images because they may contain cues not visible in 2D face images. As equipment required for 3D face images is considerably more expensive than that required for 2D face images, we here investigated how perceptual ratings of physical characteristics from 2D and 3D face images compare. Methods We tested whether 3D face images capture cues of strength, weight, and height better than 2D face images do by directly comparing the accuracy of strength, weight, and height ratings of 182 2D and 3D face images taken simultaneously. Strength, height and weight were rated by 66, 59 and 52 raters respectively, who viewed both 2D and 3D images. Results In line with previous studies, we found that weight and height can be judged somewhat accurately from faces; contrary to previous research, we found that people were relatively inaccurate at assessing strength. We found no evidence that physical characteristics could be judged more accurately from 3D than 2D images. Conclusion Our results suggest physical characteristics are perceived with similar accuracy from 2D and 3D face images. They also suggest that the substantial costs associated with collecting 3D face scans may not be justified for research on the accuracy of facial judgments of physical characteristics.

scholarly journals The patellofemoral morphology and the normal predicted value of tibial tuberosity-trochlear groove distance in the Chinese population

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Zhe Li ◽  
Guanzhi Liu ◽  
Run Tian ◽  
Ning Kong ◽  
Yue Li ◽  
...  
Keyword(s):  
Individual Differences ◽  
Chinese Population ◽  
Pearson Correlation ◽  
Three Dimensional ◽  
Correlation Coefficients ◽  
Tibial Tuberosity ◽  
Trochlear Groove ◽  
Lasso Regression ◽  
Cross Sectional ◽  
Anterior Posterior

Abstract Background Our objective was to obtain normal patellofemoral measurements to analyse sex and individual differences. In addition, the absolute values and indices of tibial tuberosity-trochlear groove (TT-TG) distances are still controversial in clinical application. A better method to enable precise prediction is still needed. Methods Seventy-eight knees of 78 participants without knee pathologies were included in this cross-sectional study. A CT scan was conducted for all participants and three-dimensional knee models were constructed using Mimics and SolidWorks software. We measured and analysed 19 parameters including the TT-TG distance and dimensions and shapes of the patella, femur, tibia, and trochlea. LASSO regression was used to predict the normal TT-TG distances. Results The dimensional parameters, TT-TG distance, and femoral aspect ratio of the men were significantly larger than those of women (all p values < 0.05). However, after controlling for the bias from age, height, and weight, there were no significant differences in TT-TG distances and anterior-posterior dimensions between the sexes (all p values > 0.05). The Pearson correlation coefficients between the anterior femoral offset and other indexes were consistently below 0.3, indicating no relationship or a weak relationship. Similar results were observed for the sulcus angle and the Wiberg index. Using LASSO regression, we obtained four parameters to predict the TT-TG distance (R2 = 0.5612, p < 0.01) to achieve the optimal accuracy and convenience. Conclusions Normative data of patellofemoral morphology were provided for the Chinese population. The anterior-posterior dimensions of the women were thicker than those of men for the same medial-lateral dimensions. More attention should be paid to not only sex differences but also individual differences, especially the anterior condyle and trochlea. In addition, this study provided a new method to predict TT-TG distances accurately.

scholarly journals A computer-based approach for developing linamarase inhibitory agents

2020 ◽  
Vol 5 (7) ◽  
Author(s):  
Lucas Paul ◽  
Celestin N. Mudogo ◽  
Kelvin M. Mtei ◽  
Revocatus L. Machunda ◽  
Fidele Ntie-Kang
Keyword(s):  
Structure Elucidation ◽  
Three Dimensional ◽  
Data Bank ◽  
Competitive Inhibitor ◽  
Industrial Applications ◽  
Dimensional Structure ◽  
Full Understanding ◽  
The Poor ◽  
Computer Based ◽  
Inhibitory Agents

AbstractCassava is a strategic crop, especially for developing countries. However, the presence of cyanogenic compounds in cassava products limits the proper nutrients utilization. Due to the poor availability of structure discovery and elucidation in the Protein Data Bank is limiting the full understanding of the enzyme, how to inhibit it and applications in different fields. There is a need to solve the three-dimensional structure (3-D) of linamarase from cassava. The structural elucidation will allow the development of a competitive inhibitor and various industrial applications of the enzyme. The goal of this review is to summarize and present the available 3-D modeling structure of linamarase enzyme using different computational strategies. This approach could help in determining the structure of linamarase and later guide the structure elucidation in silico and experimentally.

scholarly journals Automatic 3D dense phenotyping provides reliable and accurate shape quantification of the human mandible

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Pieter-Jan Verhelst ◽  
H. Matthews ◽  
L. Verstraete ◽  
F. Van der Cruyssen ◽  
D. Mulier ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Intraclass Correlation ◽  
Three Dimensional ◽  
Correlation Coefficients ◽  
Surface Registration ◽  
Anatomical Landmarks ◽  
Centroid Size ◽  
Intraclass Correlation Coefficients ◽  
Total Variability ◽  
Automatic Phenotyping

AbstractAutomatic craniomaxillofacial (CMF) three dimensional (3D) dense phenotyping promises quantification of the complete CMF shape compared to the limiting use of sparse landmarks in classical phenotyping. This study assesses the accuracy and reliability of this new approach on the human mandible. Classic and automatic phenotyping techniques were applied on 30 unaltered and 20 operated human mandibles. Seven observers indicated 26 anatomical landmarks on each mandible three times. All mandibles were subjected to three rounds of automatic phenotyping using Meshmonk. The toolbox performed non-rigid surface registration of a template mandibular mesh consisting of 17,415 quasi landmarks on each target mandible and the quasi landmarks corresponding to the 26 anatomical locations of interest were identified. Repeated-measures reliability was assessed using root mean square (RMS) distances of repeated landmark indications to their centroid. Automatic phenotyping showed very low RMS distances confirming excellent repeated-measures reliability. The average Euclidean distance between manual and corresponding automatic landmarks was 1.40 mm for the unaltered and 1.76 mm for the operated sample. Centroid sizes from the automatic and manual shape configurations were highly similar with intraclass correlation coefficients (ICC) of > 0.99. Reproducibility coefficients for centroid size were < 2 mm, accounting for < 1% of the total variability of the centroid size of the mandibles in this sample. ICC’s for the multivariate set of 325 interlandmark distances were all > 0.90 indicating again high similarity between shapes quantified by classic or automatic phenotyping. Combined, these findings established high accuracy and repeated-measures reliability of the automatic approach. 3D dense CMF phenotyping of the human mandible using the Meshmonk toolbox introduces a novel improvement in quantifying CMF shape.

scholarly journals Small footprint optoelectrodes using ring resonators for passive light localization

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Vittorino Lanzio ◽  
Gregory Telian ◽  
Alexander Koshelev ◽  
Paolo Micheletti ◽  
Gianni Presti ◽  
...  
Keyword(s):  
State Of The Art ◽  
Three Dimensional ◽  
Network Activity ◽  
Ring Resonators ◽  
Spatiotemporal Resolution ◽  
Optical Ring Resonators ◽  
Light Localization ◽  
Order Of Magnitude ◽  
Small Footprint

AbstractThe combination of electrophysiology and optogenetics enables the exploration of how the brain operates down to a single neuron and its network activity. Neural probes are in vivo invasive devices that integrate sensors and stimulation sites to record and manipulate neuronal activity with high spatiotemporal resolution. State-of-the-art probes are limited by tradeoffs involving their lateral dimension, number of sensors, and ability to access independent stimulation sites. Here, we realize a highly scalable probe that features three-dimensional integration of small-footprint arrays of sensors and nanophotonic circuits to scale the density of sensors per cross-section by one order of magnitude with respect to state-of-the-art devices. For the first time, we overcome the spatial limit of the nanophotonic circuit by coupling only one waveguide to numerous optical ring resonators as passive nanophotonic switches. With this strategy, we achieve accurate on-demand light localization while avoiding spatially demanding bundles of waveguides and demonstrate the feasibility with a proof-of-concept device and its scalability towards high-resolution and low-damage neural optoelectrodes.

TRANSFORMATION OF NESTED LOOPS WITH MODULO INDEXING TO AFFINE RECURRENCES

1994 ◽  
Vol 04 (03) ◽  
pp. 271-280 ◽  
Author(s):  
FLORIN BALASA ◽  
FRANK H.M. FRANSSEN ◽  
FRANCKY V.M. CATTHOOR ◽  
HUGO J. DE MAN
Keyword(s):  
Code Generation ◽  
State Of The Art ◽  
Transformation Method ◽  
Control Flow ◽  
Code Optimization ◽  
Transformation Techniques ◽  
Hermite Normal Form ◽  
Nested Loops ◽  
Affine Functions ◽  
Systems Transformation

For multi-dimensional (M-D) signal and data processing systems, transformation of algorithmic specifications is a major instrument both in code optimization and code generation for parallelizing compilers and in control flow optimization as a preprocessor for architecture synthesis. State-of-the-art transformation techniques are limited to affine index expressions. This is however not sufficient for many important applications in image, speech and numerical processing. In this paper, a novel transformation method is introduced, oriented to the subclass of algorithm specifications that contains modulo expressions of affine functions to index M-D signals. The method employs extensively the concept of Hermite normal form. The transformation method can be carried out in polynomial time, applying only integer arithmetic.

scholarly journals GRAVITY-WAVE DETECTORS AS PROBES OF EXTRA DIMENSIONS

2005 ◽  
Vol 14 (12) ◽  
pp. 2347-2353 ◽  
Author(s):  
CHRIS CLARKSON ◽  
ROY MAARTENS
Keyword(s):  
Black Holes ◽  
String Theory ◽  
Gravity Wave ◽  
Gravity Waves ◽  
Extra Dimensions ◽  
State Of The Art ◽  
Three Dimensional ◽  
Observable Universe ◽  
Dimensional Spacetime ◽  
Higher Dimensional

If string theory is correct, then our observable universe may be a three-dimensional "brane" embedded in a higher-dimensional spacetime. This theoretical scenario should be tested via the state-of-the-art in gravitational experiments — the current and upcoming gravity-wave detectors. Indeed, the existence of extra dimensions leads to oscillations that leave a spectroscopic signature in the gravity-wave signal from black holes. The detectors that have been designed to confirm Einstein's prediction of gravity waves, can in principle also provide tests and constraints on string theory.

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