The amount of scientific knowledge from randomized parallel group trials have been improved by the CONSORT Guideline, but important intelligence with important clinical implications remains to be extracted. This may t...The amount of scientific knowledge from randomized parallel group trials have been improved by the CONSORT Guideline, but important intelligence with important clinical implications remains to be extracted. This may though be obtained if the conventional statistical significance testing is supplied by 1) Addition of an unbiased and reproducible quantification of the magnitude or size of the clinical significance/importance of a difference in treatment outcome;2) Addition of a quantification of the credulity of statements on any possible effect size and finally;3) Addition of a quantification of the risk of committing an error when the null hypothesis is either accepted or rejected. These matters are crucial to proper conversion of trial results into good usage in every-day clinical practice and may produce immediate therapeutic consequence in quite opposite direction to the usual ones. In our drug eluting stent trial “SORT OUT II”, the implementation of our suggestions would have led to immediate cessation of use of the paclitaxel-eluting stent, which the usual Consort like reporting did not lead to. Consequently harm to subsequent patients treated by this stent might have been avoided. Our suggestions are also useful in cancer treatment trials and in fact generally so in most randomized trial. Therefore increased scientific knowledge with immediate and potentially altered clinical consequence may be the result if hypothesis testing is made complete and the corresponding adjustments are added to the CONSORT Guideline—first of all— for the potential benefit of future patients.展开更多
Hyperparameter tuning is a key step in developing high-performing machine learning models, but searching large hyperparameter spaces requires extensive computation using standard sequential methods. This work analyzes...Hyperparameter tuning is a key step in developing high-performing machine learning models, but searching large hyperparameter spaces requires extensive computation using standard sequential methods. This work analyzes the performance gains from parallel versus sequential hyperparameter optimization. Using scikit-learn’s Randomized SearchCV, this project tuned a Random Forest classifier for fake news detection via randomized grid search. Setting n_jobs to -1 enabled full parallelization across CPU cores. Results show the parallel implementation achieved over 5× faster CPU times and 3× faster total run times compared to sequential tuning. However, test accuracy slightly dropped from 99.26% sequentially to 99.15% with parallelism, indicating a trade-off between evaluation efficiency and model performance. Still, the significant computational gains allow more extensive hyperparameter exploration within reasonable timeframes, outweighing the small accuracy decrease. Further analysis could better quantify this trade-off across different models, tuning techniques, tasks, and hardware.展开更多
The purpose of this paper is to discuss the closure properties of increasing convex average order and NBUCA life distributions. Under the assumption that the units are only independent, characterizations of NBUCA clas...The purpose of this paper is to discuss the closure properties of increasing convex average order and NBUCA life distributions. Under the assumption that the units are only independent, characterizations of NBUCA class of life distributions are given. It is shown that NBUCA class is closed under the random maxima and the formation of parallel systems of independent units. As an application of the main results, the behavior of this class is developed in terms of the monotonicity of the residual life of k-out-of n systems given the time at which the （n -k ）-th failure has occurred.展开更多
MVP is a digital signal processor, which is of MIMD structure and fit for multimedia application. MVP has several processors in it, and its operation is characteristic of parallelism and pipeline; therefore, real-time...MVP is a digital signal processor, which is of MIMD structure and fit for multimedia application. MVP has several processors in it, and its operation is characteristic of parallelism and pipeline; therefore, real-time signal processing can be done on it. This paper presents the image processing system based on MVP, explains the principles of parallel task assignment and hardware pipeline design, and gives out the example of target tracking and edge detection.展开更多
文摘The amount of scientific knowledge from randomized parallel group trials have been improved by the CONSORT Guideline, but important intelligence with important clinical implications remains to be extracted. This may though be obtained if the conventional statistical significance testing is supplied by 1) Addition of an unbiased and reproducible quantification of the magnitude or size of the clinical significance/importance of a difference in treatment outcome;2) Addition of a quantification of the credulity of statements on any possible effect size and finally;3) Addition of a quantification of the risk of committing an error when the null hypothesis is either accepted or rejected. These matters are crucial to proper conversion of trial results into good usage in every-day clinical practice and may produce immediate therapeutic consequence in quite opposite direction to the usual ones. In our drug eluting stent trial “SORT OUT II”, the implementation of our suggestions would have led to immediate cessation of use of the paclitaxel-eluting stent, which the usual Consort like reporting did not lead to. Consequently harm to subsequent patients treated by this stent might have been avoided. Our suggestions are also useful in cancer treatment trials and in fact generally so in most randomized trial. Therefore increased scientific knowledge with immediate and potentially altered clinical consequence may be the result if hypothesis testing is made complete and the corresponding adjustments are added to the CONSORT Guideline—first of all— for the potential benefit of future patients.
文摘Hyperparameter tuning is a key step in developing high-performing machine learning models, but searching large hyperparameter spaces requires extensive computation using standard sequential methods. This work analyzes the performance gains from parallel versus sequential hyperparameter optimization. Using scikit-learn’s Randomized SearchCV, this project tuned a Random Forest classifier for fake news detection via randomized grid search. Setting n_jobs to -1 enabled full parallelization across CPU cores. Results show the parallel implementation achieved over 5× faster CPU times and 3× faster total run times compared to sequential tuning. However, test accuracy slightly dropped from 99.26% sequentially to 99.15% with parallelism, indicating a trade-off between evaluation efficiency and model performance. Still, the significant computational gains allow more extensive hyperparameter exploration within reasonable timeframes, outweighing the small accuracy decrease. Further analysis could better quantify this trade-off across different models, tuning techniques, tasks, and hardware.
基金The Science Foundation of Shaanxi Pro-vincial Educational Department (06JK325)
文摘The purpose of this paper is to discuss the closure properties of increasing convex average order and NBUCA life distributions. Under the assumption that the units are only independent, characterizations of NBUCA class of life distributions are given. It is shown that NBUCA class is closed under the random maxima and the formation of parallel systems of independent units. As an application of the main results, the behavior of this class is developed in terms of the monotonicity of the residual life of k-out-of n systems given the time at which the （n -k ）-th failure has occurred.
文摘MVP is a digital signal processor, which is of MIMD structure and fit for multimedia application. MVP has several processors in it, and its operation is characteristic of parallelism and pipeline; therefore, real-time signal processing can be done on it. This paper presents the image processing system based on MVP, explains the principles of parallel task assignment and hardware pipeline design, and gives out the example of target tracking and edge detection.
