Position Variables Research Articles

Fraud Pentagon in Detecting Financial Statement Fraud

Purpose: This study aims to prove the influence of the fraud pentagon on the existence of fraudulent financial statements.
 Methodology/approach: This research approach is quantitative with secondary data in the form of company annual reports in the manufacturing sector with the food & beverage sub-sector listed on the IDX for the 2016-2020 period. Purposive sampling as sampling with a total of 12 companies for 5 periods and a total sample of 60. The analysis technique uses multiple linear regression assisted by SPSS 26.
 Findings: The findings prove that there is an influence of the variables of pressure, opportunity, rationalization, competence, and dualism position on financial statement fraud, while the variable frequent number of CEO's picture does not affect the existence of fraudulent financial statements.
 Practical implications: The findings of this study have an impact on the company's stakeholders and stake holders to detect fraud in the financial statements.
 Originality/value: This research has the novelty of adding a dualism position proxy variable to the arrogance element.

Global Wildfire Danger Predictions Based on Deep Learning Taking into Account Static and Dynamic Variables

Climate change will intensify the danger of wildfires, significantly impacting human life. Deep Learning (DL) has been extensively applied in wildfire prediction research. In the realm of wildfire prediction, previous deep learning methods have overlooked the inherent differences between static positional information and dynamic variables. Additionally, most existing deep learning models have not integrated the global system characteristics of the Earth’s features and teleconnection during the learning phase. Here, we propose a static location-aware ConvLSTM (SLA-ConvLSTM) model that is aware of static positional elements and interconnected with global information and teleconnection. The model we propose can discern the influence of dynamic variables across various geographical locations on predictive outcomes. Compared with other deep learning models, our SLA-ConvLSTM model has achieved commendable performance. The outcomes indicate that the collaborative interplay of spatiotemporal features and the extraction of static positional information present a promising technique for wildfire prediction. Moreover, the incorporation of climate indices and global feature variables enhances the predictive capability of the model in wildfire prediction.

Synthetic Training Data in AI-Driven Quality Inspection: The Significance of Camera, Lighting, and Noise Parameters.

Industrial-quality inspections, particularly those leveraging AI, require significant amounts of training data. In fields like injection molding, producing a multitude of defective parts for such data poses environmental and financial challenges. Synthetic training data emerge as a potential solution to address these concerns. Although the creation of realistic synthetic 2D images from 3D models of injection-molded parts involves numerous rendering parameters, the current literature on the generation and application of synthetic data in industrial-quality inspection scarcely addresses the impact of these parameters on AI efficacy. In this study, we delve into some of these key parameters, such as camera position, lighting, and computational noise, to gauge their effect on AI performance. By utilizing Blender software, we procedurally introduced the "flash" defect on a 3D model sourced from a CAD file of an injection-molded part. Subsequently, with Blender's Cycles rendering engine, we produced datasets for each parameter variation. These datasets were then used to train a pre-trained EfficientNet-V2 for the binary classification of the "flash" defect. Our results indicate that while noise is less critical, using a range of noise levels in training can benefit model adaptability and efficiency. Variability in camera positioning and lighting conditions was found to be more significant, enhancing model performance even when real-world conditions mirror the controlled synthetic environment. These findings suggest that incorporating diverse lighting and camera dynamics is beneficial for AI applications, regardless of the consistency in real-world operational settings.

Tangent functor on microformal morphisms, and non-linear pullbacks for forms and cohomology

We show how the tangent functor extends from ordinary smooth maps to “microformal morphisms” (also called “thick morphisms”) of supermanifolds. Microformal morphisms generalize ordinary maps and correspond to formal canonical relations between the cotangent bundles specified by generating functions depending on position variables on the source manifold and momentum variables on the target manifold (as formal power expansions), regarded as part of the structure. Microformal morphisms act on functions by non-linear (in general) pullbacks. We obtain here non-linear pullbacks of (pseudo)differential forms and show that they respect the de Rham differentials as “non-linear chain maps” that can induce non-linear transformations of cohomology.

Predictors of batting and pitching performance in the USA baseball prospect development pipeline

ABSTRACT This study examined the relationship between psychomotor abilities and baseball performance by analysing data from 379 athletes who participated in the USA Baseball, Prospect Development Pipeline (PDP). Hit and pitch metrics were generated during practice sessions using the RapsodoTM System. Data were compared through exploratory factor analysis and hierarchical regression. Factor analysis grouped batter’s PDP evaluations into four latent variables accounting for 63% of variance. Pitcher performance grouped into three factors accounting for 51% of variance. Regression on batter data revealed a significant demographic/anthropometric base model with height, weight, and age that accounted for 58% of the batted ball speed (R2 = 0.581). Player position explained 2% of the variance (R2 = 0.604), and PDP evaluation scores contributed an additional 3% (R2 = 0.631). Regression of pitcher data showed a significant base demographic/anthropometric model accounting for 36% of fastball pitch speeds (R2 = 0.363), with the PDP evaluation scores adding 6% additional variance (R2 = 0.424). Uniformly, assessments of lower body strength added the greatest predictive information. Hand grip strength did not correlate with pitch metrics. While demographics/anthropometrics are major contributors to batted and pitched ball speed, position and psychomotor variables add statistically significant contributions and may be of practical value for player selection.

Understanding Quality Physical Education from the Perspective of Asian PE Professionals

Physical Education (PE) is an essential compulsory school subject requiring focused and sustained development. This study examined the understanding of Quality Physical Education (QPE) from the perspective of PE professionals primarily entrusted with implementing initiatives to develop QPE. A total of 2,191 individuals from 25 Asian cities participated in this study. They completed a validated QPE questionnaire consisting of 49 items distributed into eight dimensions. The variables of gender, work position, and years of experience were investigated in accounting for the differences in perceptions. The overall mean value for QPE was 7.32, with excellent internal consistency (a= .986). The results indicated similar trends in the perceptions of the QPE and evaluation of the items by professionals. No significant differences between genders and across work positions were found. However, significant differences were found among perceptions depending on the years of experience in teaching PE. Moreover, findings revealed the need for governmental support for research in PE and collaborative work at the international and national levels. This study contributes to the groundwork of policy analyses and strategic development in improving QPE in Asia.

Lewis and berry phases for a gravitational wave interacting with a quantum harmonic oscillator

In this work, we compute the Lewis and Berry phases for a gravitational wave interacting with a two dimensional quantum harmonic oscillator in the transverse-traceless gauge. We have considered a gravitational wave consisting of the plus polarization term only. Considering the cross polarization term to be absent makes the Hamiltonian separable in terms of the first and the second spatial coordinates. We then compute the Lewis phase by assuming a suitable form of the Lewis invariant considering only quadratic order contributions from both position and momentum variables. Next, we obtain two Lewis invariants corresponding to each separable part of the full Hamiltonian of the system. Using both Lewis invariants, one can obtain two Ermakov-Pinney equations, from which we finally obtain the corresponding Lewis phase. Then making an adiabatic approximation enables us to isolate the Berry phase for the full system. After this we obtain some explicit expressions of the Berry phase for a plane polarized gravitational wave with different choices of the harmonic oscillator frequency. Finally, we consider a gravitational wave with cross polarization only interacting with an isotropic two dimensional harmonic oscillator. For this we obtain the Lewis phase and the total Berry phase of the system, which is found to be dependent upon the cross polarization part of the gravitational wave.

The influence of the field orientation on the representativeness of the positional dynamics in soccer small-sided games

The aim of this study was to compare the positional dynamics in soccer small-sided games (SSGs) with either greater length (SSGlength) or width (SSGwidth) with official games. Twenty four Brazilian U-20 national-level players participated in six SSGs training sessions with two different SSG configurations: SSGlength (4v4, 40 m length and 26 m width) and SSGwidth (4v4, 26 m length and 40 m width). Positional dynamics variables were monitored and compared to official games. Linear mixed regression model was fitted using the situations as fixed effect, and, when appropriate, player and/or group as random effects. When compared to SSGlength and SSGwidth, official games showed a greater Relative Team Length, LPWratio, Spacial Exploration Index (SEI), and Strech Index, with a large or very large effect size. The SSGlength elicited higher values of Relative Team Width, LPWratio, and SEI when compared to SSGwidth. No significant differences were found between SSGlength and SSGwidth for Relative Team Length (small effect size), and SI (small effect size). Both group and player as random effects showed low variances. We concluded that the tactical behaviours during the 4v4 SSG differed substantially from the competitive tactical behaviour during the official games. In addition, changing the orientation of the playing field did not make the positional dynamics of the SSGs more similar to the official games.

Fuzzy Controller Implemented for Movement of a Tendon-Driven 3D Robotic Lumbar Spine Mechanism.

Notable efforts have been devoted to the development of biomechanical models of the spine, so the development of a motion system to control the spine becomes expressively relevant. This paper presents a fuzzy controller to manipulate the movement of a 3D robotic mechanism of the lumbar spine, which is driven by tendons. The controller was implemented in Matlab/Simulink R2023a software, MathWorks (Brazil), considering mathematical modeling based on the Lagrangian methodology for simulating the behavior of the lumbar spine dynamic movement. The fuzzy controller was implemented to perform movements of two joints of the 3D robotic mechanism, which consists of five vertebrae grouped into two sets, G1 and G2. The mechanism's movements are carried out by four servomotors which are driven by readings from two sensors. For control, the linguistic variables of position, velocity and acceleration were used as controller inputs and the torque variables were used for the controller output. The experimental tests were carried out by running the fuzzy controller directly on the 3D physical model (external to the simulation environment) to represent flexion and extension movements analogous to human movements.

Evaluating a Public Health Information Service According to Users' Socioeconomic Position and Health Status: Protocol for a Cross-Sectional Study.

The increasing use of information technology in the field of health is supposed to promote users' empowerment but can also reinforce social inequalities. Some health authorities in various countries have developed mechanisms to offer accurate and relevant information to health care system users, often through health websites. However, the evaluation of these sociotechnical tools is inadequate, particularly with respect to differences and inequalities in use by social groups. Our study aims to evaluate the access, understanding, appraisal, and use of the French website Santé.fr by users according to their socioeconomic position and perceived health status. This cross-sectional study involves the entire French population to which Santé.fr is offered. Data will be collected through mixed methods, including a web-based questionnaire for quantitative data and interviews and focus groups for qualitative data. Collected data will cover users' access, understanding, appraisal, and use of Santé.fr, as well as sociodemographic and socioeconomic characteristics, health status, and digital health literacy. A validation of the dimensions of access, understanding, appraisal, and use of Santé.fr will be conducted, followed by principal component analysis and ascendant hierarchical classification based on the 2 main components of principal component analysis to characterize homogeneous users' profiles. Regression models will be used to investigate the relationships between each dimension and socioeconomic position and health status variables. NVivo 11 software (Lumivero) will be used to categorize interviewees' comments into preidentified themes or themes emerging from the discourse and compare them with the comments of various types of interviewees to understand the factors influencing people's access, understanding, appraisal, and use of Santé.fr. Recruitment is scheduled to begin in January 2024 and will conclude when the required number of participants is reached. Data collection is expected to be finalized approximately 7 months after recruitment, with the final data analysis programmed to be completed around December 2024. This study would be the first in France and in Europe to evaluate a public health information service, in this case the Santé.fr website (the official website of the French Ministry of Health), according to users' socioeconomic position and health status. The study could discover issues related to inequalities in access to, and the use of, digital technologies for obtaining health information on the internet. Given that access to health information on the internet is crucial for health decision-making and empowerment, inequalities in access may have subsequent consequences on health inequalities among social categories. Therefore, it is important to ensure that all social categories have access to Santé.fr. PRR1-10.2196/51123.

The Relationship Between Environmental Statistics and Predictive Gaze Behaviour During a Manual Interception Task: Eye Movements as Active Inference

AbstractHuman observers are known to frequently act like Bayes-optimal decision-makers. Growing evidence indicates that the deployment of the visual system may similarly be driven by probabilistic mental models of the environment. We tested whether eye movements during a dynamic interception task were indeed optimised according to Bayesian inference principles. Forty-one participants intercepted oncoming balls in a virtual reality racquetball task across five counterbalanced conditions in which the relative probability of the ball’s onset location was manipulated. Analysis of pre-onset gaze positions indicated that eye position tracked the true distribution of onset location, suggesting that the gaze system spontaneously adhered to environmental statistics. Eye movements did not, however, seek to minimise the distance between the target and foveal vision according to an optimal probabilistic model of the world and instead often reflected a ‘best guess’ about onset location. Trial-to-trial changes in gaze position were, however, found to be better explained by Bayesian learning models (hierarchical Gaussian filter) than associative learning models. Additionally, parameters relating to the precision of beliefs and prediction errors extracted from the participant-wise models were related to both task-evoked pupil dilations and variability in gaze positions, providing further evidence that probabilistic context was reflected in spontaneous gaze dynamics.

The Managerial Role and Psychosocial Factors of Job Satisfaction: A Cross-sectional Study Among Wittyfit's Users.

Job satisfaction is an emerging indicator for measuring workers' occupational well-being; however, this has been poorly studied in managers. We aimed to explore job satisfaction between managers and employees and assess its factors. Data from Wittyfit's users were collected between January 2018 and February 2020. Volunteers anonymously provided their sociodemographic profile, their sense of job satisfaction, and their psychosocial feelings (ambiance, meaning, organization, recognition, values, work-life balance). Data of 10,484 employees and 836 managers were collected. Job satisfaction was higher in managers than employees. All psychosocial factors had an impact on job satisfaction in workers. There was a higher prevalence of satisfied managers than employees. Managerial position and other sociodemographic variables influenced this prevalence. Managers seem to be more satisfied than employees. Psychosocial and sociodemographic factors can influence workers' job satisfaction.

Effectiveness of Flat-Panel Fluoroscopy in Direct Anterior Total Hip Arthroplasty: A Comparison to Image Intensifier Fluoroscopy With Radiopaque Grid

IntroductionThe use of traditional, image intensifier fluoroscopy with a radiopaque grid during direct anterior total hip arthroplasty (DA THA) has demonstrated reduced variability in component positioning and operative time compared to fluoroscopy without a grid. A disadvantage of image intensifier fluoroscopy is spatial distortion, particularly compared to flat-panel fluoroscopy systems. The purpose of this study is to determine whether flat-panel fluoroscopy decreases variability in component positioning during DA THA compared to the use of traditional grid fluoroscopy. MethodsWe retrospectively reviewed 70 consecutive DA THAs between February 2020 and February 2021: 36 using flat-panel fluoroscopy, and 34 using traditional fluoroscopy with a grid. Radiographs were independently reviewed by 2 authors to identify components exceeding goal parameters: cup abduction of 40 ± 10 degrees, as well as offset and limb lengths within 10 mm of the contralateral side. Binary values for goal parameter achievement were assigned for each THA. ResultsNo significant difference was observed in the number of hips that met goals for cup abduction (100% vs 97%, P = 1.00), hip offset (88% vs 88%, P = 1.00), limb length (91% vs 94% [ ±10 mm], P = .669, 65% vs 72% [±5 mm], P = .498), or for the number of hips that met all 3 component goals (79% vs 80%, P = 1.00). No significant difference in operative time was noted between the 2 groups (110.2 minutes vs 100.9, P = .76). ConclusionsWe demonstrated no significant difference in component positioning in DA THAs utilizing flat-panel fluoroscopy as compared to using traditional fluoroscopy with a grid.

Closed Loop Vector Formulation in Eulers Complex Numbers for Multi Loop Planar Mechanisms With N bars A Novel Modeling Approach and Algorithm

This paper presents a novel iterative algorithm incorporated in a user-friendly GUI for modeling the kinematics of multiple looped N-bar closed-loop mechanisms. Past research works have used custom coding or expensive commercial software to analyze the mechanisms of specific applications. The proposed algorithm focuses on kinematics and offers a quick, easy-to-use, cost-effective solution to analyze a wide range of generic mechanisms, reducing the need for custom coding and lowering computational costs. The algorithm employs algebraic equations, such as solving complex closed-loop vector equations using the Euler form of complex numbers, to simulate and derive the unknowns necessary to characterise any generic closed-loop mechanism. The Python code implemented in the algorithm adapts to various scenarios by utilising available information on the position, velocity, and acceleration variables of the mechanisms. The simulation tool can display real-time color contour plots (RGB color scale) for linear and angular velocities and accelerations, simulate mechanisms with multiple loops and switch configurations, and find inverse mechanisms. The approach for solving multiple loop problems and the algorithm utilized to solve the configurations, methods, equations used and GUI features implementation are all described in this study. The case study considered for a four-bar mechanism indicates a strong agreement between the results obtained from the proposed kinematics-based simulator and ANSYS software. These results demonstrate the simulator’s effectiveness in providing low-cost and user-friendly simulation results for various generic mechanisms involving multiple interconnected loops.

The effects of coolant mass flow rate and atmospheric indicators in a PV/T system with experimental and ANN’s models

In this study, the effects of the mass flow rate of coolant and other atmospheric and positional variables on the performance and efficiency of a PV/T system have been experimentally researched and modeled with ANN’s models. Mass flow rate, irradiance, ambient temperature, wind speed, wind direction, relative humidity and coolant water inlet temperature have been measured while solar azimuth angle and solar elevation angle have been calculated. These parameters have been selected as the input parameters (independent variables), mainly having the preliminary focus on the mass flow rate of the coolant. The performance parameters namely, electrical power production, thermal energy production, total energy production, temperature decrease on the PV module, electrical efficiency increase, surface temperature of the PV module and water outlet temperature for the PV modules have been experimentally measured. They were also computed by ANN models, as the output variables (dependent variables) with the most robust estimation of FBPANN based models depending on the real measurement data set from the experimental works. The relevance of the dependability of each targeted variables were revealed by statistical indicators in order to maintain the sensitivity of the ANN calculations. Among all the dependent parameters that were predicted by the ANN models, the strictest predictions were found for electrical power production by the FFANN1 model with the R value of 99.985% and the R2 value of 99.971%. Also, all of the performance parameters have robustly been predicted by the FFANN models. Besides, the order of importance of the predictors that effects dependent variables has been found. The mass flow rate has been determined to be highly effective on electrical efficiency increase, surface temperature of the PV module, electrical power production, thermal energy production and total energy production. The benefit of the present work is that the effects of daily working parameters such as mass flow rate of coolant with respect to the other atmospheric indicators on instantaneous electrical and thermal performance of a PV or PV/T system can be robustly predicted with their order of importance with the developed ANN models. It will make the investors to easily manage their systems.

What can we gain from subpopulation universal pulses? A simulation-based study.

The aim of the study was to explore a novel methodology for designing universal pulses (UPs) that balances the benefits of a calibration-free approach with subject-specific online pulse design. The proposed method involves segmenting the population into subpopulations with variability in anatomical shapes and positions reduced to 75%, 50%, and 25% of their original values while keeping the mean values unchanged. An additional 25% extreme case with a large volume of interest and shifted position was included. For each group, a 5kT-points universal inversion pulse was designed and assessed by the normalized root mean square error (NRMSE) on the target longitudinal magnetization profile. The performance was compared to the conventional one-size-fits-all approach. A total of 132 electromagnetic simulations were executed to generate representative anatomies and specific absorption rate (SAR) distributions in a three-dimensional parameter space comprised of head breadth, head length, and Y-shift. The 99.9th percentile on the peak local SAR distribution was utilized to establish an intersubject variability safety margin. UPs designed for subpopulations with decreased head shape and position variability reduced the anatomical safety margin by up to 20%. Furthermore, when a head was significantly different to the average case, the proposed approach improved the inversion homogeneity by up to 24%, compared to the conventional one-size-fits-all approach. Subpopulation UPs present an opportunity to improve the homogeneity and reduce anatomical SAR safety margins at 7T without additional acquisition time for calibration.

Nonsingular Fast Terminal Sliding Mode Neural Network Decentralized Control of a Quadrotor Unmanned Aerial Vehicle

A nonsingular terminal sliding mode decentralized controller that can ensure the tracking errors of the trajectories and attitude rapid convergence in finite time is proposed for an insufficient driven and strongly coupled nonlinear four-rotor unmanned aerial vehicle (UAV). The total lift of the UAV system is decomposed into three virtual drive separation forces corresponding to the three positions. The insufficient drive UAV system is transformed into a virtual full-drive model for research. The three position states and the three attitude states of UAV are placed correspondingly to the six subsystems by variable substitution. The model uncertainty and unknown disturbance term for each subsystem serves as total coupling terms among the subsystems. The upper bounds of the total coupling terms are considered as unknown ordinary higher order polynomials varying with the six states of the system under the action of time change. With the help of Cauchy inequality, the estimates of the upper bounds are obtained from the approximation performance of the RBF neural network. Finally, the decentralized controller is designed for each attitude subsystem and the virtual decentralized controller for each position subsystem. It is also mapped to the tracking total lift controller by using the virtual decentralized position controller. The controller design process uses the nonsingular terminal sliding mode control technology to ensure that the quadrotor attitude and position variables can quickly converge to the desired value in a short time. Simulation experiments verify that the proposed control method is effective and feasible.

Novel tactical insights from Men’s 2022 FIFA World Cup: Which performance indicators explain the teams’ goal difference?

This study examined positional and event-based tactical variables during the Men’s 2022 FIFA World Cup to detect differences between winning and losing teams and to verify which variables would better predict the goal difference between the teams. All 64 matches played during the competition were initially considered. Due to the purpose of the current article, draw matches were excluded from the sample. The data were compared between the match statuses using a MANOVA. A stepwise multiple linear regression was used to detect which variables predict the outcome of the matches. Results indicated differences between winning and losing in Line Breaks per Pass ( p = 0.011), Defensive Line Break per Pass ( p = 0.004), Final Third Phase Height ( p = 0.023), and Width ( p < 0.001). The best predictors of the goal difference were the Final Third Phase Width (standardized beta = −0.389), the Completed Line Breaks (standardized beta = 0.716), and the movements to receive in the progression phase in between (standardized beta = −0.491). It is concluded that positioning the team closer to the central corridor in the last third of the pitch and successfully breaking the defensive lines increases winning probability during the competition.

An Examination of Parental Weight Stigma and Weight Talk Among Socioeconomically and Racially/Ethnically Diverse Parents.

Parental communication about body weight can influence children's emotional well-being and eating behaviors. However, little is known about the role of parental self-stigma concerning weight and social position variables (ie, race/ethnicity, income, and gender) in weight communication. This study examined how parents' self-stigmatization for their own weight (ie, weight bias internalization) and self-stigmatization for their child's weight (ie, affiliate stigma) relates to weight talk frequency with their children, and whether these associations vary across parental race/ethnicity, income, and gender. Parents (n = 408) completed a cross-sectional, online survey about their weight communication and self-stigmatization. Linear regression was used to examine the relationships among these variables, including interactions between the stigma variables and social position variables in predicting weight talk. Higher levels of weight bias internalization and affiliate stigma were strongly associated with increased parental weight talk frequency; parents who endorsed higher levels of internalized bias about their own weight expressed greater affiliate stigma for their child's weight, regardless of demographic characteristics or weight status. Associations between the stigma variables and weight talk outcomes were stronger among fathers and parents of higher income. Findings highlight the importance of considering weight stigma variables in parental weight communication research.

A Prospective Cohort Study on the Respiratory Effect on Modified Mallampati Scoring.

Mallampati scoring is a common exam method for evaluating the oropharynx as a part of the airway assessment and for anticipation of difficult intubation. It partitions the oropharynx into 4 categories with scores of 1, 2, 3, and 4. Even though its reliability is known to be limited by confounding factors such as patient positioning, patient phonation, tongue protrusion, and examiner variability, the effect of respiration, i.e., inspiration and expiration, has not yet been formally studied. Mallampati scores were collected from 100 surgical patients during both inspiration and expiration and later compared to the score obtained in the medical record, determined by a board certified anesthesiologist. Score deviations from the medical record reference were compared for both inspiration and expiration showing that respiration affects Mallampati scores; for some patients, the scores improved (i.e., decreased), while in others they worsened (i.e., increased). The respiratory change effect was quantified and visualized by plotting the area under the curve of the histogram of the deviations. 42% of the patients had a worsening of scores by 1 or 2 points with inspiration while 36% of the patients had a worsening of scores by 1 or 2 points with expiration. Mallampati scoring is commonly used in evaluating the oropharynx as a part of the airway assessment and as a screening tool for difficult intubations. However, as this study points out, the respiratory cycle substantially affects the Mallampati scoring system, with significant deviations of 1 or 2 points. In a scoring system of 4 score categories, these deviations are remarkable.