scholarly journals Dynamic Nonprehensile Manipulation of a Moving Object Using a Batting Primitive

2021 ◽  
Vol 11 (9) ◽  
pp. 3920
Author(s):  
Hyun-Min Joe ◽  
Joonwoo Lee ◽  
Jun-Ho Oh
Keyword(s):  
Success Rate ◽  
Moving Objects ◽  
Control Method ◽  
Weighted Least Squares ◽  
Research Area ◽  
Least Squares Regression ◽  
Primitive Form ◽  
Trajectory Estimation ◽  
Direction Control ◽  
Nonprehensile Manipulation

To achieve human-level object manipulation capability, a robot must be able to handle objects not only with prehensile manipulation, such as pick-and-place, but also with nonprehensile manipulation. To study nonprehensile manipulation, we studied robotic batting, a primitive form of nonprehensile manipulation. Batting is a challenging research area because it requires sophisticated and fast manipulation of moving objects and requires considerable improvement. In this paper, we designed a batting system for dynamic manipulation of a moving ball and proposed several algorithms to improve the task performance of batting. To improve the recognition accuracy of the ball, we proposed a circle-fitting method that complements color segmentation. This method enabled robust ball recognition against illumination. To accurately estimate the trajectory of the recognized ball, weighted least-squares regression considering the accuracy according to the distance of a stereo vision sensor was used for trajectory estimation, which enabled more accurate and faster trajectory estimation of the ball. Further, we analyzed the factors influencing the success rate of ball direction control and applied a constant posture control method to improve the success rate. Through the proposed methods, the ball direction control performance is improved.

Modeling and Interpretation of Tidal Turbine Vibration Through Weighted Least Squares Regression

2020 ◽  
Vol 50 (4) ◽  
pp. 1252-1259 ◽  
Author(s):  
Grant S. Galloway ◽  
Victoria M. Catterson ◽  
Craig Love ◽  
Andrew Robb ◽  
Thomas Fay
Keyword(s):  
Least Squares ◽  
Weighted Least Squares ◽  
Least Squares Regression ◽  
Tidal Turbine

Are the saving decision patterns of bank customers also clouded by psychological biases? Evidence from Ghana

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Joseph Emmanuel Tetteh ◽  
Christopher Boachie
Keyword(s):  
Decision Making ◽  
Loss Aversion ◽  
Design Methodology ◽  
Weighted Least Squares ◽  
Least Squares Regression ◽  
Individual Decision ◽  
Content Type ◽  
Saving Decisions ◽  
The Individual ◽  
Practical Implications

PurposeThis paper attempts to investigate the influence of psychological biases on saving decision-making of bank customers in Ghana.Design/methodology/approachIt employs weighted least squares regression to test the effect of psychological biases on savings decisions of bank customers.FindingsThe findings show that all the nine psychological biases, namely mental accounting, availability, loss aversion, representativeness, anchoring, overconfidence, status quo, framing effect and disposition effect employed for the study have a significant influence on saving decision of bank customers. The results depict that psychological biases are entrenched in the saving pattern of bank customers in Ghana.Practical implicationsFor policy purposes, the study recommends that bank customers need to enhance their knowledge of psychological biases in order to improve their gains from savings, and not to fall prey to these prejudices. The satisfied customer is a dependable source of bank viability and survival.Originality/valueTo the best of the knowledge of the author, this study provides the first empirical evidence of the influence of psychological biases on saving decisions of bank customers in Ghana. The findings of this study will enhance knowledge on the influence of psychological biases on individual decision-making and will accentuate the fact that the individual is not an entirely rational being.

scholarly journals Adaptive Backstepping Control with Online Parameter Estimator for a Plug-and-Play Parallel Converter System in a Power Switcher

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3528 ◽  
Author(s):  
Chujia Guo ◽  
Aimin Zhang ◽  
Hang Zhang ◽  
Lei Zhang
Keyword(s):  
Control Method ◽  
Optimal Algorithm ◽  
Weighted Least Squares ◽  
Backstepping Control ◽  
Parallel Structure ◽  
Adaptive Backstepping ◽  
Parameter Estimator ◽  
Plug And Play ◽  
Adaptive Backstepping Control ◽  
Circulating Current

This study aims to address the inherent uncertainty in plug loads and load extraction, distributed generation, and the inevitable circulating current in a parallel structure. Therefore, in this paper, an adaptive backstepping control scheme with an online parameter estimator (OPE) for a plug-and-play parallel converter system in a four-port power switcher is proposed. The adaptive backstepping control method was designed in the dq0 coordinate system to suppress the circulating current in the zero-component; the circulating current can be suppressed by using an embedded algorithm and omitting the extra controller. An adaptive update law was designed to weaken the influence of the arbitrary plug and extraction operations in the DC and AC buses to realize the plug-and-play function. The transient tracking performance is governed by the limitation of maximum total errors in the voltage and current. As a result, the settling times of the voltage, current, and power decreased. Additionally, to further improve the system robustness, an online inductance and resistance estimator was established using an optimal algorithm that solves the weighted least squares problem. In the estimator, there are no additional voltage and current sensors needed, and the mean squared error (MSE) of the estimation can be minimized. Simulation studies on a two-converter parallel system with a plug-and-play function were conducted using MATLAB/SIMULINK (R2018b, MathWorks, Natick, MA, USA) to verify the effectiveness of the proposed adaptive backstepping control strategy. The results show that this strategy improves system performance over that of a system with unbalanced parameters among a parallel structure with AC and DC system disturbances caused by arbitrary plug and extraction operations.

scholarly journals Tolerance Intervals in a Heteroscedastic Linear Regression Context with Applications to Aerospace Equipment Surveillance

2009 ◽  
Vol 2009 ◽  
pp. 1-8 ◽  
Author(s):  
Janet Myhre ◽  
Daniel R. Jeske ◽  
Michael Rennie ◽  
Yingtao Bi
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Performance Metrics ◽  
Weighted Least Squares ◽  
Ordinary Least Squares ◽  
Automated System ◽  
Least Squares Regression ◽  
Data Set ◽  
Tolerance Intervals ◽  
Power Of The Test

A heteroscedastic linear regression model is developed from plausible assumptions that describe the time evolution of performance metrics for equipment. The inherited motivation for the related weighted least squares analysis of the model is an essential and attractive selling point to engineers with interest in equipment surveillance methodologies. A simple test for the significance of the heteroscedasticity suggested by a data set is derived and a simulation study is used to evaluate the power of the test and compare it with several other applicable tests that were designed under different contexts. Tolerance intervals within the context of the model are derived, thus generalizing well-known tolerance intervals for ordinary least squares regression. Use of the model and its associated analyses is illustrated with an aerospace application where hundreds of electronic components are continuously monitored by an automated system that flags components that are suspected of unusual degradation patterns.

Advances in Tracking and Recognition of Human Motion

2011 ◽  
pp. 65-71
Author(s):  
Niki Aifanti ◽  
Angel D. Sappa ◽  
Nikos Grammalidis ◽  
Sotiris Grammalidis Malassiotis
Keyword(s):  
Moving Objects ◽  
Research Area ◽  
Initial Position ◽  
Human Motion ◽  
Target Person ◽  
Motion Constraints ◽  
Simplifying Assumptions ◽  
Ill Posed ◽  
Important Research Area ◽  
Tracking And Recognition

Tracking and recognition of human motion has become an important research area in computer vision. In real world conditions it constitutes a complicated problem, considering cluttered backgrounds, gross illumination variations, occlusions, self-occlusions, different clothing and multiple moving objects. These ill-posed problems are usually tackled by making simplifying assumptions regarding the scene or by imposing constraints on the motion. Constraints such as that the contrast between the moving people and the background should be high and that everything in the scene should be static except for the target person are quite often introduced in order to achieve accurate segmentation. Moreover, the motion of the target person is often confined to simple movements with limited occlusions. In addition, assumptions such as known initial position and posture of the person are usually imposed in tracking processes.

scholarly journals Analysis of Caesarean Section Rates Using the Robson Classification System at a University Hospital in Spain

2020 ◽  
Vol 17 (5) ◽  
pp. 1575 ◽  
Author(s):  
Rafael Vila-Candel ◽  
Anna Martín ◽  
Ramón Escuriet ◽  
Enrique Castro-Sánchez ◽  
Francisco Javier Soriano-Vidal
Keyword(s):  
Classification System ◽  
Weighted Least Squares ◽  
University Hospital ◽  
Analysis Tool ◽  
Least Squares Regression ◽  
Clinical Method ◽  
Robson Classification ◽  
Relative Contribution ◽  
Group 4 ◽  
Group 2

Background: The WHO recommends the use of the Robson ten-group classification system (RTGCS) as an effective monitoring and analysis tool to assess the use of caesarean sections (CS). The present study aimed to conduct an analysis of births using the RTGCS in La Ribera University Hospital over nine years and to assess the levels and trends of CS births. Methods: Retrospective study between January 1, 2010, and December 31, 2018. All eligible women were allocated in RTGCS to determine the absolute and relative contribution made by each group to the overall CS rate; linear regression and weighted least squares regression analysis were used to analyze trends over time. The risk of CS of women with induced versus spontaneous onset of labor was calculated with an odds ratio (OR) with a 95% CI. Results: 16,506 women gave birth during the study period, 19% of them by CS. Overall, 20.4% of women were in group 1 (nulliparous, singleton cephalic, term, spontaneous labor), 29.4% in group 2 (nulliparous, singleton cephalic, term, induced labor or caesarean before labor), and 12.8% in group 4 (multiparous, singleton cephalic, term, induced or caesarean delivery before labor) made the most significant contributions to the overall rate of CS; Conclusions: In our study, Robson Groups 1, 2, and 4, were identified as the main contributors to the hospital’s overall CS rate. The RTGCS provides an easy way of collecting information about the CS rate, is a valuable clinical method that allows standardized comparison of data, and time point, and identifies the groups driving changes in CS rates.

Assessing the Veterans Affairs Surgical Quality Improvement Program Risk Calculator in Cholecystectomy

2018 ◽  
Vol 84 (6) ◽  
pp. 1039-1042 ◽  
Author(s):  
Jonathan B. Imran ◽  
Oswaldo Renteria ◽  
Maria Ruiz ◽  
Thai H. Pham ◽  
Ali A. Mokdad ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Predictive Accuracy ◽  
Weighted Least Squares ◽  
Veterans Affairs ◽  
Quality Improvement Program ◽  
Least Squares Regression ◽  
Risk Calculator ◽  
Improvement Program ◽  
Surgical Quality ◽  
C Statistic

The Veterans Affairs Surgical Quality Improvement Program (VASQIP) risk calculator has been validated for several operations but has not been assessed specifically for cholecystectomy. Our aim was to externally validate the VASQIP calculator's accuracy in predicting 30-day morbidity and mortality (M&M) for patients undergoing cholecystectomy. A retrospective review of patients undergoing cholecystectomy at the North Texas Veterans Affairs hospital was performed. The VASQIP risk calculator was used to determine predicted 30-day M&M, which was compared with actual M&M. The predictive accuracy of the Veterans Affairs risk calculator was assessed using the C-statistic and a graphical assessment of a locally weighted least squares regression smoother. Overall, 848 patients were included in the study. Actual M&M were 6.3 and 0.94 per cent, respectively, whereas predicted M&M were 6.0 and 0.54 per cent. The C-statistic was 0.75 for morbidity and 0.78 for mortality. In our analysis, the VASQIP risk calculator reasonably predicted 30-day M&M.

A Comparison of Accuracy Based on Data Imputation between Unconstrained Structural Equation Modeling and Weighted Least Squares Regression

2011 ◽  
Vol 130-134 ◽  
pp. 730-733
Author(s):  
Narong Phothi ◽  
Somchai Prakancharoen
Keyword(s):  
Structural Equation Modeling ◽  
Least Squares ◽  
Structural Equation ◽  
Weighted Least Squares ◽  
Equation Modeling ◽  
Data Imputation ◽  
Least Squares Regression ◽  
Waveform Generator ◽  
Data Set ◽  
Testing Group

This research proposed a comparison of accuracy based on data imputation between unconstrained structural equation modeling (Uncon-SEM) and weighted least squares (WLS) regression. This model is developed by University of California, Irvine (UCI) and measured using the mean magnitude of relative error (MMRE). Experimental data set is created using the waveform generator that contained 21 indicators (1,200 samples) and divided into two groups (1,000 for training and 200 for testing groups). In fact, training group was analyzed by three main factors (F1, F2, and F3) for creating the models. The result of the experiment show MMRE of Uncon-SEM method based on the testing group is 34.29% (accuracy is 65.71%). In contrast, WLS method produces MMRE for testing group is 55.54% (accuracy is 44.46%). So, Uncon-SEM is high accuracy and MMRE than WLS method that is 21.25%.

scholarly journals Association between selenium levels and oesophageal adenocarcinoma risk: evidence from a meta-analysis

2016 ◽  
Vol 36 (4) ◽  
Author(s):  
Bin Hong ◽  
Lihong Huang ◽  
Ning Mao ◽  
Tao Xiong ◽  
Chao Li ◽  
...  
Keyword(s):  
Publication Bias ◽  
Dose Response ◽  
Meta Analysis ◽  
Weighted Least Squares ◽  
Selenium Level ◽  
Oesophageal Adenocarcinoma ◽  
Least Squares Regression ◽  
Response Relationship ◽  
Case Control Studies ◽  
Dose Response Relationship

Quantification of the association between selenium and risk of oesophageal adenocarcinoma (OAC) is still conflicting. The purpose of this meta-analysis is to explore the relationship between selenium levels and OAC risk. PubMed and Web of Knowledge were searched for the related articles. Pooled relative risks (RRs) with 95% confidence intervals (CIs) from random effects models were calculated. Sensitivity analysis and publication bias were conducted. Dose–response relationship was assessed by restricted cubic spline and variance-weighted least squares regression analysis. Five articles involving 748 OAC cases were included in this meta-analysis. Pooled results suggest that higher selenium level was not significantly associated with the risk of OAC (summary RRs=1.08, 95% CIs=0.84–1.39, I2=0%). Besides, no significant association was found in case-control studies (summary RRs=1.13, 95% CIs=0.84–1.52, I2=0%) or cohort studies (summary RRs=0.99, 95% CIs=0.55–1.78, I2=32.6%). A linear dose–response relationship was attested that an increase in dietary selenium intake of 10 μg/day is marginally associated with 1% increase in the risk of developing OAC (summary RRs=1.01, 95% CIs=0.99–1.03), but not statistically significant. No publication bias was found. In conclusion, our analysis indicated that a higher selenium level was not significantly associated with the risk of OAC. The relevant further studies are warranted.

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