			Home About us Contact

Comparing Performance (comparing + performance)

Distribution by Scientific Domains

Medical Sciences	33%

Selected Abstracts

Comparing performances of logistic regression and neural networks for predicting melatonin excretion patterns in the rat exposed to ELF magnetic fields

BIOELECTROMAGNETICS, Issue 2 2010
Samad Jahandideh
Abstract Various studies have been reported on the bioeffects of magnetic field exposure; however, no consensus or guideline is available for experimental designs relating to exposure conditions as yet. In this study, logistic regression (LR) and artificial neural networks (ANNs) were used in order to analyze and predict the melatonin excretion patterns in the rat exposed to extremely low frequency magnetic fields (ELF-MF). Subsequently, on a database containing 33 experiments, performances of LR and ANNs were compared through resubstitution and jackknife tests. Predictor variables were more effective parameters and included frequency, polarization, exposure duration, and strength of magnetic fields. Also, five performance measures including accuracy, sensitivity, specificity, Matthew's Correlation Coefficient (MCC) and normalized percentage, better than random (S) were used to evaluate the performance of models. The LR as a conventional model obtained poor prediction performance. Nonetheless, LR distinguished the duration of magnetic fields as a statistically significant parameter. Also, horizontal polarization of magnetic fields with the highest logit coefficient (or parameter estimate) with negative sign was found to be the strongest indicator for experimental designs relating to exposure conditions. This means that each experiment with horizontal polarization of magnetic fields has a higher probability to result in "not changed melatonin level" pattern. On the other hand, ANNs, a more powerful model which has not been introduced in predicting melatonin excretion patterns in the rat exposed to ELF-MF, showed high performance measure values and higher reliability, especially obtaining 0.55 value of MCC through jackknife tests. Obtained results showed that such predictor models are promising and may play a useful role in defining guidelines for experimental designs relating to exposure conditions. In conclusion, analysis of the bioelectromagnetic data could result in finding a relationship between electromagnetic fields and different biological processes. Bioelectromagnetics 31:164,171, 2010. © 2009 Wiley-Liss, Inc. [source]

Evaluating high-performance computers,

CONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 10 2005
Jeffrey S. Vetter
Abstract Comparisons of high-performance computers based on their peak floating point performance are common but seldom useful when comparing performance on real workloads. Factors that influence sustained performance extend beyond a system's floating-point units, and real applications exercise machines in complex and diverse ways. Even when it is possible to compare systems based on their performance, other considerations affect which machine is best for a given organization. These include the cost, the facilities requirements (power, floorspace, etc.), the programming model, the existing code base, and so on. This paper describes some of the important measures for evaluating high-performance computers. We present data for many of these metrics based on our experience at Lawrence Livermore National Laboratory (LLNL), and we compare them with published information on the Earth Simulator. We argue that evaluating systems involves far more than comparing benchmarks and acquisition costs. We show that evaluating systems often involves complex choices among a variety of factors that influence the value of a supercomputer to an organization, and that the high-end computing community should view cost/performance comparisons of different architectures with skepticism. Published in 2005 by John Wiley & Sons, Ltd. [source]

Spatial conditional discrimination learning in developing rats

DEVELOPMENTAL PSYCHOBIOLOGY, Issue 2 2005
Kevin L. Brown
Abstract The present study established an effective procedure for studying spatial conditional discrimination learning in juvenile rats using a T-maze. Wire mesh located on the floor of the maze as well as a second, identical T-maze apparatus served as conditional cues which signaled whether a left or a right response would be rewarded. In Experiment 1, conditional discrimination was evident on Postnatal Day (PND) 30 when mesh,+,maze or maze-alone were the conditional cues, but not when mesh-alone was the cue. Experiment 2 confirmed that mesh-alone was sufficiently salient to support learning of a simple (nonconditional) discrimination. Its failure to serve as a conditional cue in Experiment 1 does not reflect its general ineffectiveness as a stimulus. Experiment 3 confirmed that the learning shown in Experiment 1 was indeed conditional in nature by comparing performance on conditional versus nonconditional versions of the task. Experiment 4 showed that PND19 and PND23 pups also were capable of performing the task when maze,+,mesh was the cue; however, the findings indicate that PND19 subjects do not use a conditional strategy to learn this task. The findings suggest postnatal ontogeny of conditional discrimination learning and underscore the importance of conditional cue salience, and of identifying task strategies, in developmental studies of conditional discrimination learning. © 2005 Wiley Periodicals, Inc. Dev Psychobiol 46: 97,110, 2005. [source]

A preference-based index for the SF-12

HEALTH ECONOMICS, Issue 6 2006
D. Stratmann-Schoene
Abstract Background: The SF-12 is a widely used generic measure of subjective health. As the scoring algorithms of the SF-12 do not include preference values, different approaches to assign a preference-based index are available that should be tested regarding their feasibility and validity. Objectives: To develop a concept for a preference-based index for the SF-12 on the basis of multi-attribute decision analysis and to perform initial tests of its feasibility and validity in an empirical study. Methods: A multi-attribute preference function for the SF-12 was developed, estimated and tested for validity. Two mail surveys (n = 100, 200) and an interview (n = 72) were conducted with women who had an operation for breast cancer. Visual analogue scale (VAS) and standard gamble (SG) measures elicited preference-based valuations. Results: Eight attributes were identified in the SF-12. Validity tests showed an average difference of 8 VAS score points between directly measured and predicted values for given health states. Conclusion: The initial results show that this approach might allow the direct assignment of a preference-based valuation to the SF-12. The quality of the psychometric features of the multi-attribute value function is encouraging. Future studies should test this concept more extensively, especially by determining parameters for a representative sample of the general population and by comparing performance with other approaches to value the SF-12. Copyright © 2005 John Wiley & Sons, Ltd. [source]

Efficient Evaluation of Ranking Procedures when the Number of Units is Large, with Application to SNP Identification

BIOMETRICAL JOURNAL, Issue 1 2010
Thomas A. Louis
Abstract Simulation-based assessment is a popular and frequently necessary approach for evaluating statistical procedures. Sometimes overlooked is the ability to take advantage of underlying mathematical relations and we focus on this aspect. We show how to take advantage of large-sample theory when conducting a simulation using the analysis of genomic data as a motivating example. The approach uses convergence results to provide an approximation to smaller-sample results, results that are available only by simulation. We consider evaluating and comparing various ranking-based methods for identifying the most highly associated SNPs in a genome-wide association study, derive integral equation representations of the pre-posterior distribution of percentiles produced by three ranking methods, and provide examples comparing performance. These results are of interest in their own right and set the framework for a more extensive set of comparisons. [source]

Improvement of cognitive functioning in mood disorder patients with depressive symptomatic recovery during treatment: An exploratory analysis

PSYCHIATRY AND CLINICAL NEUROSCIENCES, Issue 5 2006
LAURA MANDELLI Psy.
Abstract, Depressive symptoms have a large impact on cognitive test performance of mood disorder patients. After remission, some improvement of cognitive functioning has been observed, but also stable deficits have been reported both during depression and remission. In the present study, the authors aimed to investigate the cognitive functioning of mood disorder patients in relation to early symptomatic recovery, by comparing performances at the Wechsler Adult Intelligence Scale-Revised (WAIS-R) of responders and non-responders to the antidepressant treatment. The sample was composed of 51 hospitalized patients for a major depressive episode (major depressives/bipolars = 37/14). All patients were treated with fluvoxamine and evaluated at baseline and after 4 weeks using the 21-item Hamilton Rating Scale for Depression. All subjects were once assessed for their cognitive functioning with the WAIS-R, at the end of the fourth week of treatment. In the current sample, patients who showed a significant symptomatic remission after 4 weeks of treatment showed higher total WAIS-R scores and a lower incidence of cognitive impairment, compared to non-responders to treatment. No major differences could be observed on any particular subtest, but rather a global improving of scores in responders compared to non-responders to pharmacotherapy. Pre-treatment illness severity, that was significantly higher among non-responders, was significantly associated with patients' intelligence quotient scores. Despite a number of limitations, present data support a strong effect of depressive symptoms on patients WAIS-R performances and an early global improvement of cognitive functioning concurrent with symptomathology recovery during pharmacological treatment. [source]