In this paper, we present a new method, called Spectral Global Silhouette method (GS), to calculate the optimal number of clusters in a dataset using a Spectral Clustering algorithm. It combines both ...a Silhouette Validity Index and the concept of Local Scaling. First, the GS algorithm has first been tested using synthetic data. Then, it is applied on real data for image segmentation task. In addition, three new methods for image segmentation and two new ways to calculate the optimal number of groups in an image are proposed. Our experiments have shown a promising performance of the proposed algorithms.
•A new approach to find the optimal number of clusters is presented.•This approach is used for the Spectral Clustering algorithm.•The method is tested using synthetic data and images.•Two ways to calculate the optimal number of groups in an image are presented.•Three methods for image segmentation are proposed.
Abstract
We present a catalog of about 25,000 images of massive (
M
⋆
≥ 10
9
M
⊙
) galaxies at redshifts 3 ≤
z
≤ 6 from the TNG50 cosmological simulation, tailored for observations at multiple ...wavelengths carried out with JWST. The synthetic images were created with the SKIRT radiative transfer code, including the effects of dust attenuation and scattering. The noiseless images were processed with the
mirage
simulator to mimic the Near Infrared Camera (NIRCam) observational strategy (e.g., noise, dithering pattern, etc.) of the Cosmic Evolution Early Release Science (CEERS) survey. In this paper, we analyse the predictions of the TNG50 simulation for the size evolution of galaxies at 3 ≤
z
≤ 6 and the expectations for CEERS to probe that evolution. In particular, we investigate how sizes depend on the wavelength, redshift, mass, and angular resolution of the images. We find that the effective radius accurately describes the three-dimensional half-mass–radius of the TNG50 galaxies. Sizes observed at 2
μ
m are consistent with those measured at 3.56
μ
m at all redshifts and masses. At all masses, the population of higher-
z
galaxies is more compact than their lower-
z
counterparts. However, the intrinsic sizes are smaller than the mock observed sizes for the most massive galaxies, especially at
z
≲ 4. This discrepancy between the mass and light distributions may point to a transition in the galaxy morphology at
z
= 4–5, where massive compact systems start to develop more extended stellar structures.
22
22
Data publicly released at
https://www.tng-project.org/costantin22
.
This article presents a 3-D anthropometric vision system, free of ionizing radiation for measuring the medial longitudinal arch (MLA) and longitudinal arch angle (LAA) of the foot, essential for ...evaluating foot arch disorders that can affect a person's lifestyle. Existing 2-D techniques for determining MLA based on anthropometric tests have limitations because they exclude important information about foot such as pronation, dorsiflexion, and rotation. To overcome these limitations, the proposed system uses stereo vision and a landmark detection algorithm to measure the 3-D MLA and LAA, considering the <inline-formula> <tex-math notation="LaTeX">z </tex-math></inline-formula>-axis perpendicular to the sagittal plane. The proposed system is compared with a commercial LIDAR using a tridimensional grid (ground truth), obtaining a root mean square error (RMSE) of 1.2° for the proposed system and an RMSE of 4.8° for LIDAR. The proposed system offers several advantages over traditional techniques, including low error, 3-D measurement capabilities, and free of ionizing radiation. In addition, the system's application in human subjects showed a variability range between 3-D and 2-D measurements for MLA, which is consistent with previous research. Overall, the proposed system has the potential to improve the evaluation and treatment of foot arch disorders, thereby enhancing a person's quality of life.
Nuclear fusion is a potential source of energy that could supply the growing needs of the world population for millions of years. Several experimental thermonuclear fusion devices try to understand ...and control the nuclear fusion process. A very interesting diagnostic called Thomson scattering (TS) is performed in the Spanish fusion device TJ-II. This diagnostic takes images to measure the temperature and density profiles of the plasma, which is heated to very high temperatures to produce fusion plasma. Each image captures spectra of laser light scattered by the plasma under different conditions. Unfortunately, some images are corrupted by noise called stray light that affects the measurement of the profiles. In this work, we propose the use of deep learning models to reduce the stray light that appears in the diagnostic. The proposed approach utilizes a Pix2Pix neural network, which is an image-to-image translation based on a generative adversarial network (GAN). This network learns to translateimages affected by stray light to images without stray light. This allows for the effective removal of the noise that affects the measurements of the TS diagnostic, avoiding the need for manual image processing adjustments. The proposed method shows a better performance, reducing the noise up to 98% inimages, which surpassesprevious works that obtained 85% for the validation dataset.
This paper proposes an enhancement of a singular spectrum analysis (SSA) technique based on Hilbert Matrix (SSA-H) for autonomous navigation systems in a harsh environment. SSA is a technique that ...has caught the attention of different fields, and is used to extract trends and patterns in the time series domain. In this work, SSA-H is used to transform raw optical signals into meaningful information to build machine learning (ML) models. A technical vision system (TVS) with laser scanning for depth measurements is presented. According to the implementation of the TVS outdoors, some particular issues, such as interference radiation detected by its photodiode, can affect the system's performance in determining depth measurements. This research extracts the laser beam patterns in a real environment to create ML models to solve the problem and address some of the technical challenges in a real environment. The main contribution of this work is designing an ML framework for recognizing the laser beam of the TVS based on SSA-H. Furthermore, a comparative analysis of ML techniques to discriminate sunlight interference was studied and compared with different configurations of SSA known in the literature. According to the results, the use of SSA-H can enhance the ML models such as Ensemble Learning (EL), Feed-Forward Neural Networks (FNN), Support Vector Machines (SVM), Naive Bayes (NB) in conjunction with autocorrelation function coefficients (ACC) as features.
•JET real-time disruption predictor with metallic wall 991 discharges analyzed.•Predictor training has been carried out with JET C wall data.•Success, false alarm and missed alarm rates are 98.4%, ...0.9% and 1.6%, respectively.•Alarms are triggered in average 426ms before the disruption.
The impact of disruptions in JET became even more important with the replacement of the previous Carbon Fiber Composite (CFC) wall with a more fragile full metal ITER-like wall (ILW). The development of robust disruption mitigation systems is crucial for JET (and also for ITER). Moreover, a reliable real-time (RT) disruption predictor is a pre-requisite to any mitigation method. The Advance Predictor Of DISruptions (APODIS) has been installed in the JET Real-Time Data Network (RTDN) for the RT recognition of disruptions. The predictor operates with the new ILW but it has been trained only with discharges belonging to campaigns with the CFC wall. 7 real-time signals are used to characterize the plasma status (disruptive or non-disruptive) at regular intervals of 32ms. After the first 3 JET ILW campaigns (991 discharges), the success rate of the predictor is 98.36% (alarms are triggered in average 426ms before the disruptions). The false alarm and missed alarm rates are 0.92% and 1.64%.
This essay explores the important but obscured influence of Spanish noventayochistas on the development of Hemingway's distinctive style. Born between 1850 and 1883, the noventayochistas revitalized ...the Spanish language through thematic and stylistic innovations preceding much of what made Hemingway famous a generation later. Had Hemingway never been to Spain, he may not have mastered the combination of short sentences, terse language, clarity, impressionist attention to landscape, poetry hidden in prose, extensive dialogue, and a search for "truth" defined as what one feels, not what one is supposed to feel, in stories of toreo, anarchists and big-game fishermen, linked by an ancient, stoic code of honor.
A novel waterborne coating has been successfully designed by combining good barrier properties and a built-in ability to in situ phosphatize low carbon steel substrates. The physical barrier ...protection was promoted by a homogeneous dispersion of crystalline nanodomains in the polymer matrix, which was achieved by the coalescence of polymer particles with core–shell morphology. The core consisted of semicrystalline polystearyl acrylate, PSA, and the shell consisted of a film forming MMA/BA copolymer. The in situ phosphatization was provided by the incorporation of phosphate functionalities on the particle surface that were able to interact with the steel substrate during film formation. This combined functionality yielded films with excellent corrosion resistance properties as measured by electrochemical impedance spectroscopy analysis of samples either immersed in 3.5 wt % NaCl solution or subjected to an aggressive salt spray chamber. Thus, films containing 40 wt % of PSA and 2 wt % of phosphate surfmer provided corrosion resistance over more than 800 h when exposed to harsh salt-spray chamber conditions.
As the population ages, dementia has become one of the main health issues worldwide affecting the elderly. It is a disease related to the damage of the brain cells, causing memory loss, impairing of ...written and spoken communication skills, difficulty in performing previously routine tasks, as well as personality and mood changes. There is no cure for dementia, but if diagnosed correctly, providing the proper treatment and support allows for a better quality of life for those affected by this disease. People with dementia tend to wander, and a relationship between the wandering pattern and the level of dementia has been established. In this paper, two-time series techniques, the autocorrelation function and the partial autocorrelation function used in conjunction with the machine learning algorithms, including linear discriminant analysis, multivariate Gaussian, adaptive boost, and k-nearest neighbors, were evaluated to classify wandering patterns in people affected by dementia. The main contribution of this work is the use of time-series data techniques and machine learning algorithms to classify wandering patterns. The use of smoothing filters and time series feature extraction techniques, used in combination with ML algorithms, showed a very good performance, with an accuracy greater than 90%.
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