On Enhanced GLM-Based Monitoring: An Application to Additive Manufacturing Process

Innovations in technology assist the manufacturing processes in producing high-quality products and, hence, become a greater challenge for quality engineers. Control charts are frequently used to examine production operations and maintain product quality. The traditional charting structures rely on a response variable and do not incorporate any auxiliary data. To resolve this issue, one popular approach is to design charts based on a linear regression model, usually when the response variable shows a symmetric pattern (i.e., normality). The present work intends to propose new generalized linear model (GLM)-based homogeneously weighted moving average (HWMA) and double homogeneously weighted moving average (DHWMA) charting schemes to monitor count processes employing the deviance residuals (DRs) and standardized residuals (SRs) of the Poisson regression model. The symmetric limits of HWMA and DHWMA structures are derived, as SR and DR statistics showed a symmetric pattern. The performance of proposed and established methods (i.e., EWMA charts) is assessed by using run-length characteristics. The results revealed that SR-based schemes have relatively better performance as compared to DR-based schemes. In particular, the proposed SR-DHWMA chart outperforms the other two, namely SR-EWMA and SR-HWMA charts, in detecting shifts. To illustrate the practical features of the study’s proposal, a real application connected to the additive manufacturing process is offered.

Emergence of Lie Symmetries in Functional Architectures Learned by CNNs

In this paper we study the spontaneous development of symmetries in the early layers of a Convolutional Neural Network (CNN) during learning on natural images. Our architecture is built in such a way to mimic some properties of the early stages of biological visual systems. In particular, it contains a pre-filtering step ℓ0 defined in analogy with the Lateral Geniculate Nucleus (LGN). Moreover, the first convolutional layer is equipped with lateral connections defined as a propagation driven by a learned connectivity kernel, in analogy with the horizontal connectivity of the primary visual cortex (V1). We first show that the ℓ0 filter evolves during the training to reach a radially symmetric pattern well approximated by a Laplacian of Gaussian (LoG), which is a well-known model of the receptive profiles of LGN cells. In line with previous works on CNNs, the learned convolutional filters in the first layer can be approximated by Gabor functions, in agreement with well-established models for the receptive profiles of V1 simple cells. Here, we focus on the geometric properties of the learned lateral connectivity kernel of this layer, showing the emergence of orientation selectivity w.r.t. the tuning of the learned filters. We also examine the short-range connectivity and association fields induced by this connectivity kernel, and show qualitative and quantitative comparisons with known group-based models of V1 horizontal connections. These geometric properties arise spontaneously during the training of the CNN architecture, analogously to the emergence of symmetries in visual systems thanks to brain plasticity driven by external stimuli.

Modified chess patterns: handcrafted feature descriptors for facial expression recognition

Facial expressions are predominantly important in the social interaction as they convey the personal emotions of an individual. The main task in Facial Expression Recognition (FER) systems is to develop feature descriptors that could effectively classify the facial expressions into various categories. In this work, towards extracting distinctive features, Radial Cross Pattern (RCP), Chess Symmetric Pattern (CSP) and Radial Cross Symmetric Pattern (RCSP) feature descriptors have been proposed and are implemented in a 5 $$\times $$ × 5 overlapping neighborhood to overcome some of the limitations of the existing methods such as Chess Pattern (CP), Local Gradient Coding (LGC) and its variants. In a 5 $$\times $$ × 5 neighborhood, the 24 pixels surrounding the center pixel are arranged into two groups, namely Radial Cross Pattern (RCP), which extracts two feature values by comparing 16 pixels with the center pixel and Chess Symmetric Pattern (CSP) extracts one feature value from the remaining 8 pixels. The experiments are conducted using RCP and CSP independently and also with their fusion RCSP using different weights, on a variety of facial expression datasets to demonstrate the efficiency of the proposed methods. The results obtained from the experimental analysis demonstrate the efficiency of the proposed methods.

Force Production and Coordination from Older Women in Water Fitness Exercises

The aim of this study was to compare bilateral propulsive forces and coordination while exercising at static and dynamic conditions in the water. A total of 27 older women (age: 65.1 ± 6.7 years old) performed the following exercises: (i) horizontal upper-limbs adduction (HA; static condition) and (ii) rocking horse (RH; dynamic condition) through an incremental protocol with music cadences from 105 up to 150 b·min−1. The duration of each trial was set at 30 second (sec). Propulsive peak force (in Newton, N) of dominant (PFD) and nondominant (PFND) upper limbs was retrieved using hand sensors coupled to a differential pressure system. Significant differences in force production were found between static and dynamic exercises at higher cadences (120, 135, and 150 b·min−1). The static condition elicited higher bilateral propulsive forces and a more symmetric pattern. The in-water static exercise with bilateral action from the upper limbs proved to be the most appropriate strategy for older women to work strength and to reduce asymmetries.

Linear and Nonlinear Quantitative EEG Analysis during Neutral Hypnosis Following an Opened/Closed Eye Paradigm

Hypnotic susceptibility is a major factor influencing the study of the neural correlates of hypnosis using EEG. In this context, while its effects on the response to hypnotic suggestions are undisputed, less attention has been paid to “neutral hypnosis” (i.e., the hypnotic condition in absence of suggestions). Furthermore, although an influence of opened and closed eye condition onto hypnotizability has been reported, a systematic investigation is still missing. Here, we analyzed EEG signals from 34 healthy subjects with low (LS), medium (MS), and (HS) hypnotic susceptibility using power spectral measures (i.e., TPSD, PSD) and Lempel-Ziv-Complexity (i.e., LZC, fLZC). Indeed, LZC was found to be more suitable than other complexity measures for EEG analysis, while it has been never used in the study of hypnosis. Accordingly, for each measure, we investigated within-group differences between rest and neutral hypnosis, and between opened-eye/closed-eye conditions under both rest and neutral hypnosis. Then, we evaluated between-group differences for each experimental condition. We observed that, while power estimates did not reveal notable differences between groups, LZC and fLZC were able to distinguish between HS, MS, and LS. In particular, we found a left frontal difference between HS and LS during closed-eye rest. Moreover, we observed a symmetric pattern distinguishing HS and LS during closed-eye hypnosis. Our results suggest that LZC is better capable of discriminating subjects with different hypnotic susceptibility, as compared to standard power analysis.

Long-term changes of forest biomass and its driving factors in karst area, Guizhou, China

The spatiotemporal dynamic changes of forest biomass can provide scientific reference and scheme for improving the quality of forest resources and the ecological environment in karst areas. In this article, the China’s National Forest Continuous Inventory data (from 1984 to 2015) was used to analyze the dynamic changes of forest biomass with the univariate linear slope k, barycenter trajectory, improved hot spots detection which was applied in the analysis of forest biomass dynamic change, and geospatial detector method in Guizhou in the first time. The results showed that the total forest biomass had a steady upward trend, 29.3% unit biomass of the forest had significantly increased, while 1.4% decreased dramatically. The forest biomass gravity center shifted from Qiandongnan to Qiannan, with a total distance of 54.1 km. Thus, the following conclusions were drawn: (1) benefiting from the effective implementation of forestry-related policies, the forest biomass had significant increased in a long time series, especially for the artificial shelter forest; (2) the gravity center shifted to the northwest and the number of level 1 forest biomass hot spots increased year by year, which showed a generalized symmetric pattern along the Wujiang River mainstream; and (3) the results of geographical survey showed that the change of forest biomass was greatly affected by topography, climate and human activities, among which terrain factors had the greatest impact.

Unsteady MHD natural convection flow of a nanofluid inside an inclined square cavity containing a heated circular obstacle

The phenomena of unsteady magnetohydrodynamics (MHD) natural convection flow in an inclined square cavity filled with nanofluid and containing a heated circular obstacle at its center with heat generation/absorption impact are examined numerically. The cavity’s right and left walls are maintained at low temperatures, while the remaining walls are adiabatic. The volumetric external force, MHD, is applied across the inclined cavity. A penalty formulation-based finite element method is used to solve the nonlinear set of governing equations iteratively. The numerical scheme and results are validated through a comparison with the benchmark results, and it shows that our solutions are in good agreement with them. The results are shown in terms of contours of streamlines, isotherms, and average Nusselt number. It is observed that MHD alters the streamlines, isotherms, and average Nusselt number and dominates the flow as compared to any other physical parameter. The average Nusselt number is found sensitive to the central obstacle’s size, and it reduces sufficiently when the radius of the inner cylinder increases. For all the parameters, the streamlines’ symmetric pattern holds, such that the anti-clockwise cells on the left side of the cavity have their symmetric clockwise cells on the right side.

Experimental Study on Physical Behavior of Fluidic Oscillator in a Confined Cavity with Sudden Expansion

In this study, two-dimensional time-resolved particle image velocimetry (2D-TR-PIV) was used to investigate the effect of the external domain on oscillating jets from double-feedback fluidic oscillators. Two different cases with different Re numbers (2680–10,730), as free external domain and fully confined were studied. Time-averaged results showed although a self-oscillating jet was attained for the free external domain, it could not be achieved for a fully confined geometry. For a fully confined geometry at Re = 2680, two symmetric vortices did not allow the jet to oscillate and at Re = 6440, the flow pattern in the external region became non-symmetric due to the Coanda vortex, subsequently, the self-oscillating jet was not observed. At Re = 10,730, the strength of the jet was inclined to cope with such vortices and tended to oscillate. However, strong vortices were created near the exit region of the fluidic oscillator, which led to an almost non-symmetric pattern. In addition, the proper orthogonal decomposition (POD) method and phase-averaged analysis were applied to obtain the unsteady behavior of flow and the most energetic dynamic structure. Interestingly, at Re = 6440, the third mode was still energetic for fully confined, but for other cases, the first two modes were the most energetic modes, which showed vigorous coherent structures.

Deciphering Role of Cytokines for Therapeutic Strategies Against Rheumatoid Arthritis

: Rheumatoid Arthritis (RA) is a systemic, chronic, autoimmune, inflammatory disorder which affects of the both large and small synovial joints in a symmetric pattern. RA initiates as painful inflammation of the joints leading to stiffness of joint, joint destruction and further worsens the condition causing permanent irreversible damage to the joints making them physically disabled. Across the globe, there are around 1.2 million cases of RA reported. Inspite of various available therapeutic and pharmacological agents against RA, none of the treatment assure complete cure. Understanding the in depthrole of cytokines and interleukins in disease pathogenesis of RA could help in exploiting them for developing novel therapeutic strategies against RA. This review provides insights into pathogenesis of RA and gives a brief overview of cytokines which play an important role in the progression of the disease. We have also discussed possible role of interleukins in context of RA which could help future researchers to explore them for identifying new therapeutic agents.

Application of a Novel Automatic Method for Determining the Bilateral Symmetry Midline of the Facial Skeleton Based on Invariant Moments

Assuming a symmetric pattern plays a fundamental role in the diagnosis and surgical treatment of facial asymmetry, for reconstructive craniofacial surgery, knowing the precise location of the facial midline is important since for most reconstructive procedures the intact side of the face serves as a template for the malformed side. However, the location of the midline is still a subjective procedure, despite its importance. This study aimed to automatically locate the bilateral symmetry midline of the facial skeleton based on an invariant moment technique using pseudo-Zernike moments. A total of 367 skull images were evaluated using the proposed technique. The technique was found to be reliable and provided good accuracy in the symmetry planes. This new technique will be utilized for subsequent studies to evaluate diverse craniofacial reconstruction techniques.