Descent Analysis Research Articles

Advancements In Machine Learning Algorithms for Enhanced Fault Analysis and Categorization in Power Systems

With the growing number of sources, complexity, and dynamic elements of power systems that are prone to disturbance and electrical faults, conventional methods of fault detection are lagging in power system protection. Major faults are exposed to transmission lines due to several factors, such as climate change, heat, lightning strokes, sudden spikes of current and voltage etc. Protecting these lines from faults is cumbersome using traditional methods. However, with the increasing complexity of transmission lines in power systems, advanced technologies such as machine learning come into play for prior fault detection and identification. ML is becoming a popular and intelligent technique for monitoring and predicting health and diagnosing faults in transmission lines of power systems. Since ML is evolving at a faster pace and given the need for and growth of advanced technologies like ML and artificial intelligence, this paper emphasizes comparative analysis of various ML algorithms for transmission line fault analysis. Comparisons for various line faults (LL, LLG, LG, LLL, LLLG, no fault) in power systems using machine learning techniques have been done in terms of accuracy, precision, and other performance measures. The results of the accuracy of various algorithms are represented as tabulated facts in this paper. The Python programming language has been utilized over a dataset to calculate results. For each algorithm, the confusion matrix shows the accuracy of predicting faults over the testing data after training the model or algorithm on the training data. Upon completion of analysis and comparison of MLT's like LR, SVM, DT, RF, K-NN, and gradient descent for analysis of transmission line fault detection, RF and DT machine learning algorithms provided the best accuracy and results. Finally, this paper gives a brief overview of various line faults, ML algorithms accuracy for each transmission fault in a confusion matrix and tabular format and concluded the best machine learning algorithms for power system transmission line fault identification.

Further analysis of multilevel Stein variational gradient descent with an application to the Bayesian inference of glacier ice models

Further analysis of multilevel Stein variational gradient descent with an application to the Bayesian inference of glacier ice models

Correction to: analysis of stochastic gradient descent in continuous time

A correction regarding [Latz 2021, Stat. Comput. 31, 39].

Convergence rate analysis of the gradient descent–ascent method for convex–concave saddle-point problems

In this paper, we study the gradient descent–ascent method for convex–concave saddle-point problems. We derive a new non-asymptotic global convergence rate in terms of distance to the solution set by using the semidefinite programming performance estimation method. The given convergence rate incorporates most parameters of the problem and it is exact for a large class of strongly convex-strongly concave saddle-point problems for one iteration. We also investigate the algorithm without strong convexity and we provide some necessary and sufficient conditions under which the gradient descent–ascent enjoys linear convergence.

Analisis Daya Dukung & Penurunan Bored Pile 80cm di Proyek Kompleks Kantor-Apartemen dengan Metode Analitis & Elemen Hingga

This study will look for the ultimate bearing capacity value of bored pile foundation and foundation subsidence, based on SPT data and loading test calculated empirically with SPT data using equations provided by O'Neil and Reese while loading test data using curve interpretation Davidson Method, Mazurkiewich Method, Chin Method and finite element method using 2D Plaxis software with all types of medium mesh. After analysis, the ultimate bored pile carrying capacity value of ø 80 cm based on SPT data using the O'neill and Reese equations was 1242 tons, then analysis using the Davisson method of 875 tons, using the Mazurkiewiech method of 960 tons and the Chin method of 876 tons. While the ultimate carrying capacity based on PLAXIS 2D calculations is 1364 tons. 5. Based on SPT data, the carrying capacity of a single bored pile axial permit (Qi) was obtained at 497 tons with SF = 2.5. And for the value of the decrease that occurs in the bored pile foundation based on analytical results is 22.85 mm, based on the loading test is 7.95 mm and based on the PLAXIS 2D program is 14.12 mm. Based on the results of the analysis, it can be concluded that the O'Neil and Reese equations provide a greater value than the interpretation of load testing so that it will provide a large safety value if used when design and descent analysis that is closest to the results in the field is analysis with 2D PLAXIS with the Mohr-Coulomb modeling type. There are differences in carrying and lowering capacity analysis results with several methods used, but the use of analytical methods and finite element methods with PLAXIS 2D meets the safety requirements of bored pile foundations.

The Potential Role of Wearable Inertial Sensors in Laboring Women with Walking Epidural Analgesia.

There is a growing interest in wearable inertial sensors to monitor and analyze the movements of pregnant women. The noninvasive and discrete nature of these sensors, integrated into devices accumulating large datasets, offers a unique opportunity to study the dynamic changes in movement patterns during the rapid physical transformations induced by pregnancy. However, the final cut of the third trimester of pregnancy, particularly the first stage of labor up to delivery, remains underexplored. The growing popularity of "walking epidural", a neuraxial analgesia method allowing motor function preservation, ambulation, and free movement throughout labor and during delivery, opens new opportunities to study the biomechanics of labor using inertial sensors. Critical research gaps exist in parturient fall prediction and detection during walking epidural and understanding pain dynamics during labor, particularly in the presence of pelvic girdle pain. The analysis of fetal descent, upright positions, and their relationship with dynamic pelvic movements facilitated by walking during labor is another area where inertial sensors can play an interesting role. Moreover, as contemporary obstetrics advocate for less restricted or non-restricted movements during labor, the role of inertial sensors in objectively measuring the quantity and quality of women's movements becomes increasingly important. This includes studying the impact of epidural analgesia on maternal mobility, walking patterns, and associated obstetrical outcomes. In this paper, the potential use of wearable inertial sensors for gait analysis in the first stage of labor is discussed.

High-Dimensional Analysis of Double Descent for Linear Regression with Random Projections

High-Dimensional Analysis of Double Descent for Linear Regression with Random Projections

Analysis of Gradient Descent with Varying Step Sizes using Integral Quadratic Constraints

Analysis of Gradient Descent with Varying Step Sizes using Integral Quadratic Constraints

Abstract 14779: Whole Exome Sequencing Study in Pediatric Postural Orthostatic Tachycardia Syndrome Unveils a Path Forward From Genes to Drugs

Introduction: Postural orthostatic tachycardia syndrome (POTS) is more common in Caucasian individuals with a positive family history, while the risk in females is ~4-times of that in males. To date, the etiology of POTS is poorly understood. Hypothesis: Integrative sequencing and translational approaches to identify its genetic underpinning may better understand its pathogenesis and molecular mechanisms for the development of novel precision-based therapies. Methods: We adopted exome sequencing to evaluate the etiology and molecular mechanisms of POTS. We examined a unique collection of 87 unrelated pediatric POTS cases (61 females and 26 males, 6~21 years old), using exome sequencing. Non-relationship between individuals were validated by genome wide genotyping and identity by descent (IBD) analysis. Results: All the individuals were classified as European by principal component analysis (Figure 1). We identified 184 pathogenic (P) or likely pathogenic (LP) variants (in 162 genes). Sixty-eight (78%) cases have at least one P/LP variant. Each P/LP mutation is supported by a minimum of two databases, including ClinVar, InterVar or HGMD_Pro_2023.1. Over-representation analysis (ORA) by the DisGeNET approach showed the enriched gene sets of muscle hypotonia and epilepsy/seizures with statistical significance (FDR<E-10). Clinically, among the 87 WES patients, 41 (47%) suffered from chronic fatigue, and 13 (15%) patients have the symptoms of epilepsy, seizure or convulsion. A number of drug targets in these gene sets are highlighted, including vitamin D receptor, carbamoyl-phosphate synthase 1, methylmalonyl-CoA mutase, androgen receptor, and phenylalanine hydroxylase. Conclusions: Our results suggests that chronic fatigue and epilepsy/seizure symptoms are comorbid symptoms in POTS patients, resulting from common genetic defects. Future precision-based therapies targeting these specific genetic defects may lead to improved outcome in POTS.

Whole-genome surveillance identifies markers of Plasmodium falciparum drug resistance and novel genomic regions under selection in Mozambique.

Malaria is a devastating disease caused by Plasmodium parasites. The evolution of parasite drug resistance continues to hamper progress toward malaria elimination, and despite extensive efforts to control malaria, it remains a leading cause of death in Mozambique and other countries in the region. The development of successful vaccines and identification of molecular markers to track drug efficacy are essential for managing the disease burden. We present an analysis of the parasite genome in Mozambique, a country with one of the highest malaria burdens globally and limited available genomic data, revealing current selection pressure. We contribute additional evidence to limited prior studies supporting the effectiveness of SWGA in producing reliable genomic data from complex clinical samples. Our results provide the identity of genomic loci that may be associated with current antimalarial drug use, including artemisinin and lumefantrine, and reveal selection pressure predicted to compromise the efficacy of current vaccine candidates.

Bilateral Asymmetry in Knee and Hip Musculoskeletal Loading During Stair Ascending/Descending in Individuals with Unilateral Mild-to-Moderate Medial Knee Osteoarthritis

Most cases of unilateral knee osteoarthritis (OA) progress to bilateral OA within 10 years. Biomechanical asymmetries have been implicated in contralateral OA development; however, gait analysis alone does not consistently detect asymmetries in OA patient gait. Stair ambulation is a more demanding activity that may be more suited to reveal between-leg asymmetries in OA patients. The objective of this study was to investigate the between-leg biomechanical differences in patients with unilateral mild-to-moderate knee OA. Sixteen unilateral mild-to-moderate medial knee OA patients and 16 healthy individuals underwent kinematic and kinetic analysis of stair ascent and descent. Stair ascent produced higher loading and muscle forces in the unaffected limb compared to the OA limb, and stair descent produced lower loading on the OA limb compared to healthy subjects. These biomechanical differences were apparent in the ankle, knee, and hip joints. The implications of these findings are that OA patients rely more heavily on their unaffected sides than the affected side in stair ascent, a strategy that may be detrimental to the unaffected joint health. The reduction in affected limb loading in stair descent is thought to be related to minimizing pain.

Soliton resolution and large time behavior of solutions to the Cauchy problem for the Novikov equation with a nonzero background

In this paper, we study the soliton resolution and large time behavior of solutions to the Cauchy problem for the Novikov equation with a nonzero backgroundut−utxx+4ux=3uuxuxx+u2uxxx,u(x,0)=u0(x), where u0(x)→κ>0,x→±∞ and u0(x)−κ is assumed in the Schwarz space. It is shown that the solution of the Cauchy problem can be characterized via a Riemann-Hilbert problem in a new scale (y,t) withy=x−∫x∞((u−uxx+1)2/3−1)ds. According to the distribution of other four phase points on the jump contour, we divide the upper half-plane {(y,t):y∈R,t>0} into four space-time regions: ξ=y/t∈(−∞,−1/8)∪(1,+∞) and ξ∈(−1/8,0)∪(0,1). Via ∂‾-steepest descent analysis, we obtain the different long time asymptotic expansions of the solution u(y,t) in these different space-time solitonic regions. The corresponding residual error functions from singularities and a ∂‾-equation respectively. Our result implies that soliton resolution can be characterized with an N(Λ)-soliton whose parameters are modulated by a sum of localized soliton-soliton interactions as one moves through the regions.

Stability analysis of stochastic gradient descent for homogeneous neural networks and linear classifiers

We prove new generalization bounds for stochastic gradient descent when training classifiers with invariances. Our analysis is based on the stability framework and covers both the convex case of linear classifiers and the non-convex case of homogeneous neural networks. We analyze stability with respect to the normalized version of the loss function used for training. This leads to investigating a form of angle-wise stability instead of euclidean stability in weights. For neural networks, the measure of distance we consider is invariant to rescaling the weights of each layer. Furthermore, we exploit the notion of on-average stability in order to obtain a data-dependent quantity in the bound. This data-dependent quantity is seen to be more favorable when training with larger learning rates in our numerical experiments. This might help to shed some light on why larger learning rates can lead to better generalization in some practical scenarios.

Large‐time asymptotics to the focusing nonlocal modified Kortweg‐de Vries equation with step‐like boundary conditions

AbstractWe investigate the large‐time asymptotics of solution for the Cauchy problem of the nonlinear focusing nonlocal modified Kortweg‐de Vries (MKdV) equation with step‐like initial data, that is, as , as , where A is an arbitrary positive real number. We first develop the direct scattering theory to establish the basic Riemann‐Hilbert (RH) problem associated with step‐like initial data. Thanks to the symmetries , of nonlocal MKdV equation, we investigate the asymptotics as and , respectively. Our main technique is to use the steepest descent analysis to deform the original matrix‐valued RH problem to corresponded regular RH problem, which could be explicitly solved. Finally, we obtain the different large‐time asymptotic behaviors of the solution of the Cauchy problem for focusing nonlocal MKdV equation in different space‐time sectors , , , and on the whole ‐plane.

Anticipatory postural adjustments and kinematic analysis of step ascent and descent in adults with Down syndrome.

Step ascent and descent is one of the most common daily tasks. Although it is generally considered a rather simple movement, it may not be so easy for participants with Down syndrome. A kinematic analysis of step ascent and descent was conducted, and a comparison between 11 adult participants with Down syndrome and 23 healthy participants was carried out. This analysis was accompanied by a posturographic analysis with the aim of evaluating aspects relating to balance. The principal aim of postural control was to investigate the trajectory of the centre of pressure, while the kinematic analysis of movement included the following: (1) the analysis of anticipatory postural adjustments, (2) the calculation of spatiotemporal parameters and (3) the evaluation of articular range of motion. A general instability for participants with Down syndrome, highlighted in the postural control by an increased anteroposterior and mediolateral excursion, when the test was conducted with both open and closed eyes, was found out. Regarding anticipatory postural adjustments, this deficit in balance control was revealed by the execution of small steps before completing the movement and by a much longer preparation time anticipating the movement. In addition, the kinematic analysis reported a longer ascent and descent time and a lower velocity, accompanied by a greater rising of both limbs in ascent, which indicates an increased perception of the obstacle. Finally, a wider trunk range of motion in both the sagittal and frontal planes was revealed. All the data confirm a compromised balance control that could be associated with damage to the sensorimotor centre.

Long-time asymptotics of the good Boussinesq equation with q xx-term and its modified version

Two modified Boussinesq equations along with their Lax pairs are proposed by introducing the Miura transformations. The modified good Boussinesq equation with initial condition is investigated by the Riemann–Hilbert method. Starting with the three-order Lax pair of this equation, the inverse scattering transform is formulated and the Riemann–Hilbert problem is established, and the properties of the reflection coefficients are presented. Then, the formulas of long-time asymptotics to the good Boussinesq equation and its modified version are given based on the Deift–Zhou approach of nonlinear steepest descent analysis. It is demonstrated that the results from the long-time asymptotic analysis are in excellent agreement with the numerical solutions. This is the first result on the long-time asymptotic behaviors of the good Boussinesq equation with qxx-term and its modified version.

Painlevé-type asymptotics for the defocusing Hirota equation in transition region

We consider the long-time asymptotics for the defocusing Hirota equation with Schwartz Cauchy data in the transition region. On the basis of direct and inverse scattering transform of the Lax pair of Hirota equations, we first express the solution of the Cauchy problem in terms of the solution of a Riemann–Hilbert problem. Further, we apply nonlinear steepest descent analysis to obtain the long-time asymptotics of the solution in the critical transition region | x / t − ( α 2 / 3 β ) | t 2 / 3 ≤ M , where M is a positive constant. Our result shows that the long-time asymptotics of the Hirota equation can be expressed in terms of the solution of the Painlevé II equation.

Three Term Conjugate Gradient Technique and its Global Convergence based on the Zhang, Zhou and Li methods

The optimal conjugation coefficient distinguishes conjugate gradient methods such as two-term, three-term, and conditional from other descent methods. A novel conjugation parameter formula is constructed from Zhang, Zhou, and Li's well-known formula to formulate a three-term conjugation gradient method in the unconstrained optimization domain. The conjugation parameter and the third term parameter were constructed by incorporating the Perry conjugation condition into Shanno's memory-free strategy of a conjugate gradient. The approach demonstrated a steeply sloped search direction for each iteration by demonstrating stability, global convergence, and sufficient descent analysis in the presence of a strong Wolf case. The empirical results established that the proposed method is more efficient than Zhang et al.'s techniques. Through the use of a collection of nonlinear mathematical functions.

Nearly minimax-optimal rates for noisy sparse phase retrieval via early-stopped mirror descent

AbstractThis paper studies early-stopped mirror descent applied to noisy sparse phase retrieval, which is the problem of recovering a $k$-sparse signal $\textbf{x}^\star \in{\mathbb{R}}^n$ from a set of quadratic Gaussian measurements corrupted by sub-exponential noise. We consider the (non-convex) unregularized empirical risk minimization problem and show that early-stopped mirror descent, when equipped with the hypentropy mirror map and proper initialization, achieves a nearly minimax-optimal rate of convergence, provided the sample size is at least of order $k^2$ (modulo logarithmic term) and the minimum (in modulus) non-zero entry of the signal is on the order of $\|\textbf{x}^\star \|_2/\sqrt{k}$. Our theory leads to a simple algorithm that does not rely on explicit regularization or thresholding steps to promote sparsity. More generally, our results establish a connection between mirror descent and sparsity in the non-convex problem of noisy sparse phase retrieval, adding to the literature on early stopping that has mostly focused on non-sparse, Euclidean and convex settings via gradient descent. Our proof combines a potential-based analysis of mirror descent with a quantitative control on a variational coherence property that we establish along the path of mirror descent, up to a prescribed stopping time.

Genomic confirmation of Gossypium barbadense introgression into G. hirsutum and a subsequent MAGIC population.

Introgression of superior fiber traits from Pima cotton (Gossypium barbadense, GB) into high yield Upland cotton (G. hirsutum) has been a breeding objective for many years in a few breeding programs in the world. However, progress has been very slow due to introgression barriers resulting from whole genome hybridization between the two species. To minimize such barriers, chromosome substitution lines (CS-B) from Pima cotton 3-79 in an Upland cotton cultivar TM-1 were developed. A multiparent advanced generation inter-cross (MAGIC) population consisting of 180 recombinant inbred lines (RILs) was subsequently made using the 18 CS-B lines and three Upland cotton cultivars as parents. In this research, we sequenced the whole genomes of the 21 parents and 180 RILs to examine the G. barbadense introgression. Of the 18 CS-B lines, 11 contained the target GB chromosome or chromosome segment, two contained more than two GB chromosomes, and five did not have the expected introgression. Residual introgression in non-target chromosomes was prevalent in all CS-B lines. A clear structure existed in the MAGIC population and the 180 RILs were distributed into three groups, i.e., high, moderate, and low GB introgression. Large blocks of GB chromosome introgression were still present in some RILs after five cycles of random-mating, an indication of recombination suppression or other unknown reasons present in the population. Identity by descent analysis revealed that the MAGIC RILs contained less introgression than expected. This research presents an insight on understanding the complex problems of introgression between cotton species.