Comparison Of Multiple Techniques Research Articles

Evaluation of the accuracy and efficiency of the modified maximum variance method for multiaxial fatigue analysis under constant amplitude loading

An optimized version of the Maximum Variance Method (MVM) is employed to determine maximum shear stress amplitudes in high-cycle multiaxial fatigue analysis using the critical plane approach, increasing accuracy and reducing computational burden. This refined approach posits that the MVM assumes that the critical plane is the one subjected to the maximum variance of the shear stress history. Comprehensive statistical analyses, including Analysis of Variance (ANOVA) and multiple comparison techniques such as Tukey’s HSD and Bonferroni correction, were conducted to systematically investigate the impact of critical factors on fatigue resistance, such as mean stress, phase, synchrony, failure criteria, and the strategy for calculating maximum shear stress amplitude. These analyses highlighted significant effects of mean stress and phase on the accuracy of fatigue strength predictions, underscoring the effectiveness of the enhanced MVM in managing complex loading scenarios. The results demonstrate that the proposed methodology performs equal to or better than conventional methods, with significantly lower computational costs.

The Contribution of Lecturer Pedagogical Competence, Intellectual Intelligence and Self-Efficacy of Student Learning Motivation

This study aims to investigate the contribution lecturers’ pedagogical competences, intellectual intelligence and self-efficacy of student learning motivation. The analysis technique in this study is a multiple regression and comparison technique. It observes the relationship or influence among three variables. The sample of this study consisted of 30 students. The validity test results for each variable of lecturer pedagogical competence, intellectual intelligence, self-efficacy, and student learning motivation are valid, while the reliability of each variable is all reliable. The research findings show that the results of the analysis obtained the price of Fhit = 371,862, db = (3.26), p-value = 0,000 <0.05, Ho is rejected. The price of R2 = 0.977, Fhit = 371,862, db = (3.26) p-value = 0,000 <0.05 or Ho is rejected. The contribution of lecturers 'pedagogical competence, intellectual intelligence and self-efficacy to students' learning motivation is 0.977 or 97.7%. Thus, lecturers' pedagogical competence, intellectual intelligence and self-efficacy simultaneously influence student learning motivation.

The Usage Level of Time-Saving Measurement and Evaluation Techniques in Teacher Training Programs

The aim of this study is to explore the level of use of timesaving measurement and evaluation techniques in pre-service teacher training. The research is designed and conducted as a descriptive survey. 200 teacher candidates studying in seven different teacher education programs conveniently sampled from the education faculty located in the Mediterranean region of Turkey. The data was collected through the inventory developed by the researcher. The data analyzed with pairwise and multiple comparison techniques. The study revealed that the instructors at the education faculty were using time-saving measurement and evaluation techniques in their courses at a moderate level. These techniques were mostly used the by pre-school education, and least used in the department of mathematics education. The most commonly used time-saving measurement and evaluation technique in all teacher training programs was the Advantage/Disadvantage Listing Technique. The least-used technique was One Minute Paper Test. The prospective teachers’ opinions did not differ according to their gender. Findings have been discussed in terms of teacher qualifications on the relative to current literature.

Relationship between oral environment and frailty among older adults dwelling in a rural Japanese community: a cross-sectional observational study

BackgroundOral functions are known to decline with aging. However, there is limited evidence that supports the relationship between oral health and frailty. This study aimed to clarify the relationship between oral hygiene conditions, measured by remaining teeth and mucosa, and frailty among elderly people dwelling in a Japanese rural community.MethodsWe surveyed self-reliant elderly individuals aged ≥65 years who were dwelling in the Sasayama-Tamba area of Hyogo, Japan. Frailty was evaluated according to the total score of the Kihon Checklist (KCL). Based on the KCL score, elderly participants were divided into three groups: robust, pre-frail, and frail. The items measured to evaluate oral environment included the number of remaining teeth, denture usage condition, oral hygiene status, dry mouth condition, and salivary bacterial count. For statistical analysis, Fisher’s exact test, one-way analysis of variance, and multiple comparison technique were used.ResultsOf 308 elderly participants, 203 (65.9%), 85 (27.6%), and 20 (6.5%) belonged to the robust, pre-frail, and frail groups, respectively. The proportion of participants who were judged to have poor hygiene was significantly higher in the frail group than in the other two groups. The bacterial count was significantly smaller in the frail group than in the robust group, and the frail group had fewer number of remaining teeth than the other two groups, suggesting that the number of remaining teeth may be associated with bacterial count.ConclusionIn elderly adults, physical frailty may affect the oral hygiene status and condition of the remaining teeth.

Cougar response to a gradient of human development

AbstractHuman populations continue to increase and transform Earth's ecosystems. For large carnivores, human development reduces habitat abundance, alters predator–prey dynamics, and increases the risk of mortality, which may threaten the viability of many populations. To investigate how the cougar (Puma concolor) responds to a gradient of human development in four areas in Washington, USA, we used utilization distributions, county tax parcel data, Weibull modeling analysis, and multiple comparison techniques. Cougars used wildland areas the majority of the time (79% ± 2%, n = 112 cougars), with use decreasing as housing densities increased. When present in human‐developed areas in eastern Washington, 99% of the habitat that cougars used had housing densities ≤76.5 residences/km2, which was <846.0 residences/km2 observed in western Washington (P < 0.01). Cougars used areas in western Washington with greater housing density likely because of the clustered nature of housing developments, the connectivity with greenbelts and forested corridors, and security cover of dense maritime vegetation. Our findings suggest a consistent, albeit nuanced response by cougars to human development that may be used by wildlife managers, landscape planners, and environmental educators to guide and enhance their efforts to minimize the impacts of human development on cougars and reduce the potential for conflicts with people. Our model may also provide guidance for thresholds of human development for other adaptable large carnivores.

Classification of gamma-ray burst durations using robust model-comparison techniques

Gamma-Ray Bursts (GRBs) have been conventionally bifurcated into two distinct categories dubbed "short" and "long", depending on whether their durations are less than or greater than two seconds respectively. However, many authors have pointed to the existence of a third class of GRBs with mean durations intermediate between the short and long GRBs. Here, we apply multiple model comparison techniques to verify these claims. For each category, we obtain the best-fit parameters by maximizing a likelihood function based on a weighted superposition of lognormal distributions. We then do model-comparison between each of these hypotheses by comparing the chi-square probabilities, Akaike Information criterion (AIC), and Bayesian Information criterion (BIC). We uniformly apply these techniques to GRBs from Swift (both observer and intrinsic frame), BATSE, BeppoSAX, and Fermi-GBM. We find that the Swift GRB distributions (in the observer frame) show evidence for three categories at about $2.4\sigma$ from difference in chi-squares and show decisive evidence in favor of the two components using both AIC and BIC. For all the other datasets, evidence for three components is either very marginal or not favored.

Geographical classification of Spanish bottled mineral waters by means of iterative models based on linear discriminant analysis and artificial neural networks

The composition of Spanish natural mineral waters has been determined by means of inductively coupled plasma-mass spectrometry, inductively coupled plasma-atomic emission spectrometry, ionic chromatography and other routine techniques. Methods were applied to samples of bottled water from springs situated in five different mountain systems such as Cordillera Costero-Catalana, Macizo Galaico, Sistemas Beticos, Sistema Central and Sistema Iberico. Pattern recognition techniques have been applied to differentiate the origin of samples. Data were initially studied by using nonparametric multiple comparison techniques and principal component analysis to highlight data trends. Classification models based on linear discriminant analysis and multilayer perceptron artificial neural networks have been built and validated by means of a stratified jackknifing methodology. An iterative approach has been used to build an artificial neural network model based on the variables selected by linear discriminant analysis. The prediction ability of the constructed model was 94 %.

Experiences of using a commercial dose management system (GE DoseWatch) for CT examinations.

To assess the use of a commercial dose management system (GE DoseWatch; GEMS, Milwaukee, WI) for CT dose management for six common CT examinations. Data were acquired over several months using GE DoseWatch for six common CT examinations on three CT scanners. The dose length product (DLP) was taken as the dose indicator. The data were analysed using four different filtering methods: study description, the National Interim Clinical Imaging Procedure code, protocol name and a more detailed filtering method (the reference data set). The filtering methods were compared using an analysis of variance and multiple comparison technique. The different scanners were compared using the reference data set. It was found that integrating DoseWatch with the radiology information system provided improved results compared with using the study description. Filtering by study description was found to be a poor indicator of the mean dose for all three scanners and consistently overestimated (p < 0.05) the head and thorax-abdo-pelvis mean DLP values, despite the large sample sizes. Filtering by the National Interim Clinical Imaging Procedure code or protocol name produced mean DLPs which were not statistically different from the reference data. The scanner intercomparison showed some significant differences between the scanners, usually due to different tube current modulation settings. The use of a commercial dose monitoring system provided fast and efficient filtering of substantial amounts of data. The filtering method affected the mean DLP value despite large sample sizes. Dose management systems are relatively new in the UK, and this article shares knowledge on the use of one system.

Evaluation of a commercial electronic nose system coupled with universal gas sensing chamber for sensing indicator compounds associated with meat safety

This study was conducted to evaluate the performance of a commercial electronic nose (Cyranose 320™) for sensing indicator compounds (ethanol and acetic acid) associated with spoiled beef. The present study reported the sensitivity of an array of 32 sensors to ethanol and acetic acid. Different vapor concentrations of ethanol (37, 100, 250 and 500 ppm) and acetic acid (38, 75, 100, 200 and 300 ppm) were tested to evaluate the performance of the commercial system. An in-house designed universal gas sensing and characterization system was coupled with the electronic nose system to generate the desired gas concentration. The raw smell print patterns were obtained and analyzed for individual and multiple detectors. Tukey’s multiple comparison technique was performed to analyze the response of individual detectors. Area above and below the baseline were selected as two features for pair wise comparison of the detectors. Different sensors showed different responses between various concentrations of gases. Analysis of multiple detectors was performed using linear and quadratic discriminant analysis (LDA and QDA) along with bootstrap. LDA along with bootstrap provided the highest total classification accuracies of 94.34 % between 100 and 200 ppm of acetic acid. QDA provided higher total classification accuracy of 89.69 % at lower concentration level of 38 and 75 ppm for acetic acid and 84.78 % between 37 and 100 ppm of ethanol. Hence, QDA was a better model of choice at lower concentrations. This study proved non-selective nature of sensors and showed that simultaneous use of multiple sensor information provided better classification accuracy for discriminating various gas concentrations as compared to using individual sensor output.

A Reinforced Randomized Block Design with Correlated Errors

In the analysis of variance the errors are assumed to be independent which may not always be true. In this article, a restricted randomized block design under compound autocorrelated structure is considered. A method of analysis for such a randomized block design has been developed. It provides confidence ellipsoid and confidence interval of a set of estimable functions and an estimable function of treatment parameters, respectively. Analogous to Scheffe's method, the multiple comparison technique of judging all possible treatment contrasts has been derived. In the process, a method of estimation of unknown parameters has been also developed. An example (simulated data) illustrates this approach.

Wellcome Trust Genome-Wide Association Study of Ischemic Stroke

Twin and family history studies suggest that genetic risk factors are important for ischemic stroke.1,2 However, identifying the underlying genes has proved challenging. Until recently, the main technique used was the candidate gene method. In this, genetic variants, usually single nucleotide type polymorphisms (SNPs), are identified in a proposed candidate gene, which is thought to be involved in stroke risk. The frequency of the SNP in patients with stroke compared with controls is then determined. Many candidate gene studies have been published in stroke, but the results of these have been disappointing with few replicable associations. This situation is common with the genetics of many other complex diseases, and the reasons for lack of success include small sample sizes, a failure to adequately phenotype stroke subtypes, and a lack of primary replication of positive associations.3 An additional problem with candidate gene studies is that associations can only be identified in genes already known about and implicated in stroke risk; therefore, completely novel genes cannot be identified. The genetics of complex diseases such as stroke, in which multiple genes interact with environmental risk factors to increase risk, has been revolutionized by the Genome-Wide Association Study (GWAS) approach. This uses microarray technology to genotype up to ≥1 million SNPs, which span the whole genome. A case–control methodology is used to compare the frequency of individual SNPs between cases and controls. This is combined with rigorous multiple comparison techniques to account for the many associations tested. A great advantage of the GWAS approach, in contrast to the candidate gene method, is that it allows associations between completely novel chromosomal loci and disease to be identified. This technology has been combined with much improved study design with both very large sample sizes and replication of positive associations before publication. GWAS …

Whose trade statistics are correct? Multiple mirror comparison techniques: a test case of Cambodia

Ideally, statistics on the goods traded between two countries should be captured by each side’s respective customs office. Country A’s recorded exports to Country B should be identical to Country B...

Evaluating Efficiency of Training: An Application in Primary Health Centers Using Multiple Comparison Techniques

The purpose of this research is to measure the efficiency of trainings in the general principles of vaccine applications, the cold chain, and the adverse effects after vaccination for 51 employees (31 midwives and 20 nurses) working at primary health centers in Tuzla Health Group Region via test and retest method. The data collected through measurement of test scores before and after trainings is analyzed via multiple comparison techniques such as general test scores, the scores of each training, the scores of previously trained subjects, and difference scores. Achievement scores after training were significantly high. Previous trainings did not reveal significant effects on the results. Having been trained before did not cause permanent influence.

Literacy for Good Health: Pre-Menopause Women in Cross River State, Nigeria

This article examines the influence of literacy on the health of menopausetting (or pre-menopause) women in urban Calabar Metropolis of Cross River State, Nigeria. Two null hypotheses were formulated with a 45-item questionnaire from a representative sample size of 500 urban women between ages 35 and above, using purposive, stratified, and simple random sampling procedures. The research design is survey inferential, while data analysis was by one-way analysis of variance (ANOVA). Fisher's multiple comparison (LSD) and Independent t-test techniques were carried out. The analysis revealed that literacy level significantly influences the health of menopausetting women and that menopausetting women who are highly literate live healthier lives than their counterparts who are averagely and lowly literate. Some recommendations were made which will enhance longevity and ultimate well-being of menopausetting women.

Extent of Gastric Resection Impacts Patient Quality of Life: The Dysfunction after Upper Gastrointestinal Surgery for Cancer (DAUGS32) Scoring System

Quality of life is an important outcome measure in the care of patients with cancer. We developed a new scoring system specifically for the evaluation of patients with upper gastrointestinal cancer and postoperative gastrointestinal dysfunction. This study was undertaken to evaluate the scoring system's validity in comparing outcomes after gastric resection. Patients with gastric cancer, 3 months to 3 years postoperatively, were surveyed using the survey instrument. Postoperative dysfunction scores and the status of resuming activities of daily living were compared with the surgical procedure performed by analysis of variance and multiple-comparison techniques. Of 211 patients surveyed, 165 (119 men, 46 women; mean age, 65.1 ± 10.5 years) responded. Procedures included distal gastrectomy in 100, total gastrectomy in 57, and pylorus-preserving gastrectomy in 8. The overall dysfunction score was 61.8 ± 15.5. The dysfunction score was 58.9 ± 15.0 after distal gastrectomy, 66.8 ± 14.1 after total gastrectomy, and 62.4 ± 21.6 after pylorus-preserving gastrectomy. These values differed significantly among the groups (P = .007). Dysfunction scores according to postoperative activity status were 49.1 ± 15.6 in 71 patients who resumed their activities, 56.9 ± 15.7 in 39 patients with reduced activities, 57.3 ± 8.8 in 15 patients with minimal activities, and 63.3 ± 11.8 (P < .05) in 16 patients who did not resume activities because of poor physical condition. This scoring system for postoperative gastrointestinal dysfunction provides an objective measure of dysfunction related to specific surgical procedures and correlates with activities of daily living in the postoperative period.

Statistics for terrified biologists

Statistics for terrified biologists

Bayesian multiple comparisons of simply ordered means using priors with a point mass

Comparison of k treatment means under the simple-order assumption ( μ 1 ≤ μ 2 ≤ ⋯ ≤ μ k ) is considered. Under an order restriction, isotonic estimates and global tests of homogeneity have been known for several decades. Recently, some multiple-comparison techniques have been proposed, but none has become the standard. In this article, we develop multiple-comparison and clustering techniques for simply ordered means using a Bayesian hierarchical model. We parameterize each individual mean in terms of the difference between the preceding mean and itself. Estimates for such difference parameters are obtained using the MCMC method. Pairwise comparisons and determination of the most probable ordered clustering are based on the posterior probabilities of the difference parameters being zero. Numerical examples are given.

Assessment of Right Ventricular Function by Cardiac MRI: A Comparison of Multiple Techniques

Inter-study reproducibility was lower and varied across myocardial segments. doi:10.1016/j.hlc.2008.05.109

A Comprehensive Empirical Study of Count Models for Software Fault Prediction

Count models, such as the Poisson regression model, and the negative binomial regression model, can be used to obtain software fault predictions. With the aid of such predictions, the development team can improve the quality of operational software. The zero-inflated, and hurdle count models may be more appropriate when, for a given software system, the number of modules with faults are very few. Related literature lacks quantitative guidance regarding the application of count models for software quality prediction. This study presents a comprehensive empirical investigation of eight count models in the context of software fault prediction. It includes comparative hypothesis testing, model selection, and performance evaluation for the count models with respect to different criteria. The case study presented is that of a full-scale industrial software system. It is observed that the information obtained from hypothesis testing, and model selection techniques was not consistent with the predictive performances of the count models. Moreover, the comparative analysis based on one criterion did not match that of another criterion. However, with respect to a given criterion, the performance of a count model is consistent for both the fit, and test data sets. This ensures that, if a fitted model is considered good based on a given criterion, then the model will yield a good prediction based on the same criterion. The relative performances of the eight models are evaluated based on a one-way anova model, and Tukey's multiple comparison technique. The comparative study is useful in selecting the best count model for estimating the quality of a given software system

Permutation Methods for Comparing Process Capabilities

The statistical comparison of competing manufacturing processes is an important aspect of statistical quality control that aids quality managers in the choice of potential suppliers of products, manufacturing methodologies, or proposed adjustments to the manufacturing process. The selection criteria, in the absence of considerations such as cost, is based on a quality metric, such as the capability of each manufacturing process. Because quality metrics are estimated based on sample process data, the inherent variability in the estimates must be accounted for when selecting the best manufacturing process. In this paper, we consider solutions to this problem based on permutation testing methodology. In the case of two processes, the methodology is based on a simple permutation test of the null hypothesis that the two processes have equal capability. In the case of more than two processes, multiple-comparison techniques are used in conjunction with the proposed permutation tests. The advantage of using the permutation methods is that the significance levels of the permutation tests are exact regardless of the distribution of the process data. The methodology is demonstrated using several examples, and the potential performance of the methods are investigated empirically.