Regression - Science topic

Conventional slope stability evaluation is limited to deterministic analyses, in which only mean values are used in the numerical simulations. However, natural soils are spatial random fields due to highly complex sediment deposition. Deterministic calculation ignoring soil spatial variability can significantly underestimate the safety factor, posi...

In the manufacturing area, predicting future income is more important to keep maintain their industry profits. In addition to this, most of the manufacturing company having a bit problem in predicting their manufacturing income, especially in terms of data and method used. Hence, this paper proposed another improvise method of fuzzy regression appr...

During the last decades, evidence for a male bias in generically used masculines in German has been brought forward by numerous studies applying a multitude of methodological approaches (e.g. from Braun et al., 1998 to Glim et al., 2024). That is, generically intended masculines are understood not as gender-neutral but as mainly associated with mal...

Sales and rental prices were analysed at parish level using random forest regression for the Lisbon Metropolitan Area. Three dependent variables (new sales, new rents, and all rents) and a set of independent variables/associated factors were used, including location, building/dwelling characteristics, socioeconomic features, and tourism. This geogr...

The strain data from health monitoring systems of large-span bridges is influenced by various load effects, with the extraction and forecasting of temperature-induced strain being particularly significant for precise analysis and early warning of monitoring data. This paper presents a forecasting framework for temperature-induced strain in large-sp...

To enhance the accuracy of excavator external forces estimation, a data-physics hybrid-driven excavator external forces estimation method is proposed. MultiLayer Perceptron (MLP) model is applied for nonlinear component modeling and is used to compensate for Rigid Body Dynamics (RBD) models. Gaussian Process Regression (GPR) model is developed to e...

To develop a novel highly robust humidification technology that requires minimal adjustment of operational methods, we investigated the vapor pressure deficit (VPD) conditions that cause water stress in strawberry (Fragaria × ananassa Duch.) plants. The relationship between the rate of relative change in fruit-stalk diameter (RCFSDt) and VPD condit...

The relationship between financial inclusion and exchange rate has not received any attention in the literature. This study investigates the effect of the official exchange rate on the level of financial inclusion. A sample of 17 countries were analysed from 2012 to 2020. Four financial inclusion indicators were used in the analysis: the number of...

The relationship between financial inclusion and exchange rate has not received any attention in the literature. This study investigates the effect of the official exchange rate on the level of financial inclusion. A sample of 17 countries were analysed from 2012 to 2020. Four financial inclusion indicators were used in the analysis: the number of...

When implementing path analysis between technological and nutritional traits in common bean without considering the degree of multicollinearity, it is important to assess whether there will be errors in indirect selection. This study proposed: to assess path analysis under different degrees of multicollinearity for technological and nutritional tra...

Talent identification and player development are crucial aspects of sports management, particularly in volleyball, where understanding players' performance predictors is essential. The primary objective is to investigate the relationships between players' demographic and physical attributes and their on-court performance, providing valuable insight...

We report a case of a 1-year 7-month-old boy who had resection of a divided nevus and skin grafting that resulted in the disappearance of residual nevi, graying of eyelashes, and depigmentation at the donor site of the skin graft and around the lips. The nevus partially remained on the lid margins, although resected as much as possible from the upp...

This research described corneal maps and anterior-segment tomographic images of young mixed breed cats and compared them to those described in humans. The exams of 13 mixed-breed cats (25 eyes) aged between 18 and 48 months were analyzed. The following maps provided by the Galilei G4 were analyzed qualitatively: axial and instantaneous curvature, p...

The COVID-19 pandemic precipitated an unprecedented disruption to higher education. The necessity to move instruction online within a very short time frame, coupled with the need to master new digital tools and develop compatible and effective pedagogical practices, presented significant challenges for educators, resulting in considerable stress. T...

The main objective of this research is specifically to analyze the effect of SCM Practices on CA and OP. The research used in this study is quantitative and it includes data collection of 100 respondents from the manufacturing sector of Karachi. A questionnaire was adopted to collect the data and then the data were analyzed through SPSS. Further Re...

Tunnel heading stability in two dimensions (2D) has been extensively investigated by numerous scholars in the past decade. One significant limitation of 2D analysis is the absence of actual tunnel geometry modeling with a considerable degree of idealization. Nevertheless, it is possible to study the stability of tunnels in three dimensions (3D) wit...

Under the constraint of carbon neutrality targets, the issue of energy poverty has garnered increasing concerns. This study aims to measure energy poverty and assess the impact of renewable energy technology innovation in 30 provinces across China. Furthermore, it calculates city-level energy poverty in 274 cities. By examining the influence of ren...

The effect of pruning severity on tree growth was analyzed by change point detection using segmented regression. The present study applied this analysis to a well-known published data set including diameter growth response, tree age, pruning severity and pretreatment crown size. First, multiple regression analysis was performed to assess the effect...

The importance of effective carbon capture and storage (CCS) in addressing climate change issues highlights the need for robust CO2 leak monitoring systems. Limitations of conventional methods have prompted interest in alternative approaches, such as optical CO2 sensors, which offer non-invasive and continuous monitoring. Here, we present a novel m...

As one of the primary causes of cancer-related mortality globally, lung cancer still requires efficient early detection techniques to enhance patient outcomes. This paper recommends a remarkable strategy for identifying cellular breakdown in the lungs by utilizing profound learning (DL) and man-made brainpower (ML) approaches, specifically Head Par...

Bee pollen, commonly known as pollen, is a product of exceptionally nutritrional and economic value. It has natural origin because harvested entirely by hand from beekeeping farms. Researching post-harvest techniques to process raw pollen into commerical products that meet requirements for moisture limits and vitamin C content is an urgent need. Th...

The present study aimed to investigate the relationship between the imposter phenomenon and self-handicapping behaviors among medical students (MBBS), with a focus on the moderating role of self-care. For this purpose, a sample of N=300 medical students (n=150 men and n=150 women) from private as well as government medical colleges of Islamabad, Ra...

Panel rockfill dams, due to their cost-effectiveness, short construction periods, high safety standards, and strong adaptability to foundations, have gained rapid development and considerable attention in recent years. However, the inherent material properties and structural behavior of panel rockfill dams change continuously during operation. Part...

In this paper, a digital model of the ball burnishing process, developed using data from tests on bronze and aluminum alloys, to create regular micro-reliefs on a cylindrical surface." is presented. The experiments were carried out on a CNC lathe using a cylindrical stock. The input features were burnishing force, feedrate, machine condition and ma...

We show that the long-time limit of the two-point correlation function obtained via the standard quantum regression theorem (QRT), a standard tool to compute correlation functions in open quantum systems, does not respect the Kubo–Martin–Schwinger equilibrium condition to the non-zero order of the system-bath coupling. We then follow the recently d...

This paper investigates the correlation and regression coefficients (CRCs) of single-valued neutro-sophic graph products (SVNGPs) with a focus on the minimum spanning tree (MST) and their applications in enhancing healthcare strategies. Single-valued neutrosophic Graph (SVNG) is an extension of traditional graph theory that uses neutrosophic logic...

When constructing a dam in a mined-out area, it is necessary to handle the mined-out area effectively. Analyzing the distribution of mined-out areas is essential to ensure the safety of dam structures. In response to this issue, a machine learning-based method for analyzing the settlement of reservoir dam structures in coal mining subsidence areas...

Background: Cardiovascular disease (CVD) is the leading cause of death worldwide. Few studies have investigated the effects of mixed polycyclic aromatic hydrocarbon (PAH) exposure on CVD prevalence. We aimed to evaluate the association between mixed PAHs exposure and CVD and determine the extent to which these links are mediated by inflammatory ind...

Key audit matters (KAMs) are important for financial statement users as they provide clarity and in-depth understanding of financial statement audits. Empirical research on KAMs remains at an early stage particularly in Nigeria. Therefore, this study aims to investigate the effect of audit committee attributes on KAMs of the listed insurance compan...

Uncertainty quantification (UQ) is essential for assessing the reliability of Earth observation (EO) products. However, the extensive use of machine learning models in EO introduces an additional layer of complexity, as those models themselves are inherently uncertain. While various UQ methods do exist for machine learning models, their performance...

This paper proposes a ratemaking framework for claim frequency that utilizes informative telematics data and complies with the "discount only" regulatory requirement mandated by New York Bill A7614. The proposed framework uses a feedforward neural network to extract a one-dimensional risk score from multi-dimensional telematics features and integra...

This study investigates U.S. unemployment rates among individuals aged 25 and older, segmented by four distinct levels of educational attainment. Understanding the interplay between education and employment is crucial for effective policy-making and long-term economic planning. To capture these dynamics, a regression model is utilized to derive equ...

Recent advances unveiled physical neural networks as promising machine learning platforms, offering faster and more energy-efficient information processing. Compared with extensively-studied optical neural networks, the development of mechanical neural networks remains nascent and faces significant challenges, including heavy computational demands...

In this paper, the Nasdaq 100 Index (ETF) is selected as a representative of the technology sector, and the dominant factors affecting the performance of stock returns in the technology market are explored through data processing and regressions of its monthly returns from 2014 to 2023.In this study, the Nasdaq 100 Index (ETF) is used as a proxy fo...

The stock market has been studied and analyzed by scholars and investors for a long time. This paper aims to compare the applicability of the Fama-French three-factor (FF3F), five-factor (FF5F), and Carhart four-factor models (Carhart 4F) in the U.S. consumer discretionary sector. For the market return, data is obtained from the U.S. Consumer Discr...

Conformal prediction is a general method used to convert a point predictor into a prediction band. The accuracy of this prediction band is heavily reliant on the base estimator. This paper is to investigate the use of conformal prediction by least absolute deviation-based deep nonparametric regression. We demonstrate the consistency of the robust d...

The purpose of this study is to investigate how internal communication and leadership affect work satisfaction at PERUMDA Tirta Giri Nata in Cirebon City. This study's research methodology is a quantitative approach. With a sample of 66 workers, the population under study consisted of 190 employees of PERUMDA Tirta Giri Nata Cirebon City. A questio...

Despite questions surrounding their reliability, much of the financial literacy literature continues to rely on simple metrics – without checking whether using an alternative might yield different findings. The present paper does just that: we replicate two prior studies and substitute the Standard & Poor’s indicator originally used with the Big Th...

Extreme learning machine (ELM), as a single hidden layer feedforward neural network (SLFN), has attracted extensive attention because of its fast learning speed and high accuracy. However, the random selection of input weights and hidden biases is the main reason that deteriorates the generalization performance and stability of ELM network. In this...

The need to control the arc overvoltage during the insulation under load test in neutral insulated networks requires the determination of dependencies between single-phase non-stationary ground and parameters characterizing the faults. In most cases, the identification and realization of such dependencies is observed with a number of difficulties....

Zero-cost proxies are nowadays frequently studied and used to search for neural architectures. They show an impressive ability to predict the performance of architectures by making use of their untrained weights. These techniques allow for immense search speed-ups. So far the joint search for well performing and robust architectures has received mu...

Calibration weightings is the process of formulating calibration constraints using a given distance measure to obtain expression of the calibration weights. One of the major limitations of the simple calibration technique by Deville and Sarndal (1992); is that the calibration weights obtained by this process may be negative and or extremely large....

Objective: This study was formulated with the objective of elucidating the correlation between 25-hydroxyvitamin D (25(OH)D) and the occurrence of severe headache or migraine, employing a cross-sectional analytical approach. Methods: A cross-sectional survey was conducted over two cycles involving 7,661 participants, utilizing data from the Nationa...

This short paper is concerned with the use of spherical t-designs as optimal designs for the spherical harmonic regression model in three dimensions over a range of specified criteria. The nature of the designs is explored and their availability and suitability is reviewed.

Purpose: The primary objective of the study is to verify the use of the internal audit function as an instrument of New Public Management (NPM) and a mechanism for improving the activities of Polish universities. Design/Methodology/Approach: The study used public information on the work and results of internal the audit in Polish public higher educ...

Commodity price projections have long been relied upon by investors and governments in general. This study examines the complex issue of predicting steel price indices reported daily for the regional market of northwest China, utilizing data from 01/01/2010 to 04/15/2021. Predictions of this significant commodity price indication have attracted sca...

This work deals with the production planning and control of malt beer production in a brewery. The production and demand data of about 17 years, from 2001 to 2017 were collected and carefully analyzed using the Hoque's production planning and control model, which contains all major inventories when setting a production and control plan. The unit pr...

Background: this study aims to evaluate the survival outcomes of patients suffering from head and neck synovial sarcoma (HNSS), especially in relation to patients with a localized disease at diagnosis. Methods: this retrospective chart review includes 57 patients diagnosed with primary HNSS between 1981 and 2020 who presented with a localized disea...

This paper proposes and validates an automatic control tuning methodology based on initial frequency response. This approach facilitates the design of robust PID controllers for overdamped systems characterized by S-shaped step responses. In the prior autotuner, which is inherently robust, the critical frequency value is determined via the relay te...

Purpose: To evaluate the diagnostic performance of CT radiomic features extracted from tumor and peritumoral regions in identifying pathological subtypes of T1-stage lung adenocarcinoma presenting as pure ground−glass nodules (pGGNs). Methods: A retrospective analysis was conducted on the data of T1-stage lung adenocarcinoma patients who underwent...

The social support paradox describes mixed findings on the effects of social support on well-being. An application of the person-environment fit perspective can address the paradox by reasoning that similar quantities of social support needs and social support supplies should result in optimal well-being outcomes. We integrate a person-environment...

The representation of individuals in Genetic Programming (GP) has a large impact on the evolutionary process. In previous work, we investigated the evolutionary process of three Grammar-Guided GP (GGGP) methods, Context-Free Grammars GP (CFG-GP), Grammatical Evolution (GE) and Structured Grammatical Evolution (SGE), in the context of the complex, r...

Conservative Contextual Bandits (CCBs) address safety in sequential decision making by requiring that an agent's policy, along with minimizing regret, also satisfies a safety constraint: the performance is not worse than a baseline policy (e.g., the policy that the company has in production) by more than $(1+\alpha)$ factor. Prior work developed UC...

Obstacle-aware trajectory navigation is crucial for many systems. For example, in real-world navigation tasks, an agent must avoid obstacles, such as furniture in a room, while planning a trajectory. Gaussian Process (GP) regression, in its current form, fits a curve to a set of data pairs, with each pair consisting of an input point 'x' and its co...

The efficiency of active learning (AL) approaches to identify materials with desired properties relies on the knowledge of a few parameters describing the property. However, these parameters are unknown if the property is governed by a high intricacy of many atomistic processes. Here, we develop an AL workflow based on the sure-independence screeni...

Stochastic configuration networks (SCNs), as a class of randomized learner models, are featured by its way of random parameters assignment in the light of a supervisory mechanism, resulting in the universal approximation property at algorithmic level. This paper presents a kernel version of SCNs, termed KSCNs, aiming to enhance model's representati...

This paper introduces fast R updating algorithms designed for statistical applications, including regression, filtering, and model selection, where data structures change frequently. Although traditional QR decomposition is essential for matrix operations, it becomes computationally intensive when dynamically updating the design matrix in statistic...

Vehicle detection plays a crucial role in various applications such as traffic surveillance, license plate recognition, and the development of autonomous vehicles. The You Only Look Once (YOLO) object detection method is renowned for its high-speed real-time object detection capabilities. In this study, YOLO is employed to detect vehicles in images...

ABSTRAK Departemen Sumber Daya Manusia (SDM) menghadapi tantangan besar dalam mempertahankan retensi karyawan. Pendekatan tradisional, seperti penilaian kinerja, program pengembangan karier, pelatihan, dan paket kompensasi, sudah diterapkan dan memberikan hasil positif. Namun, pendekatan ini hanya mengandalkan data historis dan tidak dapat menganti...

This paper reviews various inverse analysis models used in steel material design, with a focus on integrating process, microstructure, and properties through advanced machine learning techniques. The study underscores the importance of establishing comprehensive models that effectively link these elements for enhanced materials engineering. Key mod...

In estimating spillover effects under network interference, practitioners often use linear regression with either the number or fraction of treated neighbors as regressors. An often overlooked fact is that the latter is undefined for units without neighbors (``isolated nodes"). The common practice is to impute this fraction as zero for isolated nod...

Background The evidence on the effect of age on the receptive and expressive language skills of individuals with Down syndrome is inconclusive. Recent research highlights the relevance of having tools to detect age‐related changes in language skills. Method Data were collected on 45 adults with Down syndrome. All were assessed with the Peabody tes...

This research has been performed to study impact of educating "Islamic knowledges" courses on students' religious attitude. Methodology used is survey and its statistical population is composed of students both female and male – in all education levels namely graduate, post-graduate and PhD from disciplines "Humanities", "Art", "Basic sciences", "M...

In the domain of computer vision, dense pedestrian detection remains a challenging task. Existing one-stage detectors in dense scenes often suffer from difficulties in feature extraction and inaccuracies in localizing small pedestrian targets due to severe occlusions and significant scale variations. To resolve these issues, we propose a new dense...

For highly skewed or fat-tailed distributions, mean or median-based methods often fail to capture the central tendencies in the data. Despite being a viable alternative, estimating the conditional mode given certain covariates (or mode regression) presents significant challenges. Nonparametric approaches suffer from the "curse of dimensionality", w...

This paper presents a loss-based generalized Bayesian methodology for high-dimensional robust regression with serially correlated errors and predictors. The proposed framework employs a novel scaled pseudo-Huber (SPH) loss function, which smooths the well-known Huber loss, achieving a balance between quadratic and absolute linear loss behaviors. Th...

Achieving climate neutrality has become an environmental goal for all European Union (EU) Member States. Thanks to numerous projects and subsidies, EU countries are able to achieve the goal of decarbonizing energy sources. The aim of the presented study is to assess the validity of Member States’ actions to reduce CO2 emissions based on data provid...

Reversible data hiding in encrypted images (RDH-EI) integrates encryption with information hiding, enabling the embedding of additional data while ensuring full recovery of the original image, widely used in multimedia data protection and forensics. However, with the increasingly serious problem of data islands, the existing RDH-EI schemes for end-...

Background Internalising problems have increased considerably among adolescents in the last decades, particularly among girls, resulting in widening gender gaps. This study examined whether the gender gap in psychological symptoms increased more in more gender‐equal countries in the period 2002–2022, and if so, to what extent this could be explaine...

Plain language summary The threshold of national governance quality that alters the performance effects of earnings management Earnings management practices of firms have been widely observed to have devastating consequences on firm value or performance, which ultimately threatens the survival of businesses. Our present study however observes that,...