Knockout-Tournament Procedures for Large-Scale Ranking and Selection in Parallel Computing Environments

2021 ◽  
Author(s):  
Ying Zhong ◽  
L. Jeff Hong
Keyword(s):  
Parallel Computing ◽  
Sample Size ◽  
Large Scale ◽  
Total Sample ◽  
Ranking And Selection ◽  
Total Sample Size ◽  
Sequential Procedures ◽  
Comparison Time ◽  
Computing Environments ◽  
Knockout Tournament

On one hand, large-scale ranking and selection (R&S) problems require a large amount of computation. On the other hand, parallel computing environments that provide a large capacity for computation are becoming prevalent today, and they are accessible by ordinary users. Therefore, solving large-scale R&S problems in parallel computing environments has emerged as an important research topic in recent years. However, directly implementing traditional stagewise procedures and fully sequential procedures in parallel computing environments may encounter problems because either the procedures require too many simulation observations or the procedures’ selection structures induce too many comparisons and too frequent communications among the processors. In this paper, inspired by the knockout-tournament arrangement of tennis Grand Slam tournaments, we develop new R&S procedures to solve large-scale problems in parallel computing environments. We show that no matter whether the variances of the alternatives are known or not, our procedures can theoretically achieve the lowest growth rate on the expected total sample size with respect to the number of alternatives and thus, are optimal in rate. Moreover, common random numbers can be easily adopted in our procedures to further reduce the total sample size. Meanwhile, the comparison time in our procedures is negligible compared with the simulation time, and our procedures barely request for communications among the processors.

Speeding Up Paulson’s Procedure for Large-Scale Problems Using Parallel Computing

2021 ◽  
Author(s):  
Ying Zhong ◽  
Shaoxuan Liu ◽  
Jun Luo ◽  
L. Jeff Hong
Keyword(s):  
Parallel Computing ◽  
Operations Research ◽  
Large Scale ◽  
Selection Process ◽  
Research Topic ◽  
Pairwise Comparisons ◽  
Important Research ◽  
Sequential Procedures ◽  
Important Research Topic ◽  
Computing Environments

With the rapid development of computing technology, using parallel computing to solve large-scale ranking-and-selection (R&S) problems has emerged as an important research topic. However, direct implementation of traditionally fully sequential procedures in parallel computing environments may encounter various problems. First, the scheme of all-pairwise comparisons, which is commonly used in fully sequential procedures, requires a large amount of computation and significantly slows down the selection process. Second, traditional fully sequential procedures require frequent communication and coordination among processors, which are also not efficient in parallel computing environments. In this paper, we propose three modifications on one classical fully sequential procedure, Paulson’s procedure, to speed up its selection process in parallel computing environments. First, we show that if no common random numbers are used, then we can significantly reduce the computation spent on all-pairwise comparisons at each round. Second, by batching different alternatives, we show that we can reduce the communication cost among the processors, leading the procedure to achieve better performance. Third, to boost the procedure’s final-stage selection, when the number of surviving alternatives is less than the number of processors, we suggest to sample all surviving alternatives to the maximal number of observations that they should take. We show that, after these modifications, the procedure remains statistically valid and is more efficient compared with existing parallel procedures in the literature. Summary of Contribution: Ranking and selection (R&S) is a branch of simulation optimization, which is an important area of operations research. In recent years, using parallel computing to solve large-scale R&S problems has emerged as an important research topic, and this research topic is naturally situated in the intersection of computing and operations research. In this paper, we consider how to improve a fully sequential R&S procedure, namely, Paulson’s procedure, to reduce the high computational complexity of all-pairwise comparisons and the burden of frequent communications and coordination, so that the procedure is more suitable and more efficient in solving large-scale R&S problems using parallel computing environments that are becoming ubiquitous and accessible for ordinary users. The procedure designed in this paper appears more efficient than the ones available in the literature and is capable of solving R&S problems with over a million alternatives in a parallel computing environment with 96 processors. The paper also extended the theory of R&S by showing that the all-pairwise comparisons may be decomposed so that the computational complexity may be reduced significantly, which drastically improves the efficiency of all-pairwise comparisons as observed in numerical experiments.

Farmers Sustainability and Social Justice: Evidences of Land Inequalities in Uttar Pradesh

2020 ◽  
pp. 232-238
Keyword(s):  
Social Justice ◽  
Sample Size ◽  
Field Survey ◽  
Uttar Pradesh ◽  
Total Sample ◽  
Small Farmers ◽  
Land Fragmentation ◽  
Total Sample Size ◽  
Fragmentation Index ◽  
State Economy

The present study is an attempt to inspect the aspect of social justice among the farmers in terms of fragmented land and farmers’ distress in Uttar Pradesh. The data were obtained through field survey via interview scheduled. A sample of 80 respondents from each targeted village namely, Jansar, Sithauli, Charsoni, and Jonai were selected from each region of Uttar Pradesh state economy. Thus, the study used a total sample size of 320 samples. Simmons index (1968) for canvassing the land fragmentation index (LFI) was applied in the Uttar Pradesh context. Further distress was measured via the help of ratios. It flaunted causes and degrees of distress were relatively high among marginal and small farmers. The result of LFI confirms that high fragmentation was a cause of subsistence income among marginal and small farms compared to semi-medium, and medium farms.

Growth in Self-Actualization (Personal Orientation Inventory) in Adult Encounter Groups

1981 ◽  
Vol 1 (1) ◽  
pp. 5-8
Author(s):  
Les Beach
Keyword(s):  
Sample Size ◽  
Personal Growth ◽  
Total Sample ◽  
Small Samples ◽  
Total Sample Size ◽  
Personal Orientation Inventory ◽  
Self Actualization ◽  
Personal Orientation

To test the efficacy of the Personal Orientation Inventory in assessing growth in self-actualization in relation to encounter groups and to provide a more powerful measure of such changes, pre- and posttest data from 3 highly comparable encounter groups (N = 43) were combined for analysis. Results indicated that the Personal Orientation Inventory is a sensitive instrument for assessing personal growth in encounter groups and that a larger total sample size provides more significant results than those reported for small samples (e. g., fewer than 15 participants).

Unequal Randomisation Can Improve the Economic Efficiency of Clinical Trials

1997 ◽  
Vol 2 (2) ◽  
pp. 81-85 ◽  
Author(s):  
David Torgerson ◽  
Marion Campbell
Keyword(s):  
Clinical Trials ◽  
Sample Size ◽  
Statistical Power ◽  
Cost Effective ◽  
Total Sample ◽  
Cost Ratio ◽  
Treatment Groups ◽  
Total Sample Size ◽  
Effectiveness Analysis ◽  
Research Resources

Objectives: In the majority of clinical trials patients are randomised equally between treatment groups. This approach maximises statistical power for a given total sample size. The objectives of this paper were to determine if, when research costs between treatments differ, it is more economically efficient to randomise additional patients to the cheaper treatment, and how the optimum randomisation ratio can be estimated. Methods: Estimation of the most economically efficient randomisation ratio for four hypothetical clinical trials using cost-effectiveness analysis. Results: When research costs differ between treatments, and there is no constraint on total sample size, it is always more cost-effective to randomise more patients to the cheaper treatment. For example, a cost ratio between the lesser and more expensive treatment of ten, results in a randomisation ratio of 3.2:1. Conclusions: Unequal randomisation ratios should be more widely used as this will achieve optimum statistical power for the lowest expenditure of research resources.

scholarly journals Evaluation of the Skin Infections and Conditions among Students of Gomal Medical College Pakistan

2021 ◽  
pp. 218-222
Author(s):  
Shumaila Parveen ◽  
Yaser M. Alahmadi ◽  
Faryal Adnan ◽  
Eshawa Darr ◽  
Ali Alalawi ◽  
...  
Keyword(s):  
Medical Students ◽  
Observational Study ◽  
Sample Size ◽  
Total Sample ◽  
Skin Infections ◽  
Age Group ◽  
Cross Sectional ◽  
Total Sample Size ◽  
Medical College ◽  
Dermatological Disorders

Objective: The objective of the current study is to determine the pattern of dermatological disorders and to find out their connection with different socioeconomically factors among students of the Medical College. Methodology: The Cross sectional observational study was carried out for the period of three months .The research instrument used was the well developed questionnaire. Results: The questionnaire was administered among total 350 students and the most participant age group was the > 22 and that was about 47.4% of the total sample size the more skin complication seen was the acne that was about 59.7%, in addition to this dandruff contributed very heavily to the hair complexities which makes about 35.7% of the sample. Conclusion: Skin infections especially the cosmetic are very common among the Medical students.

scholarly journals TO STUDY THE EFFICACY OF AYURVEDIC TREATMENT IN COVID-19/SARS-COV-2

2021 ◽  
Vol p5 (02) ◽  
pp. 2680-2688
Author(s):  
Ravindrakumar Mane ◽  
Ram Lade
Keyword(s):  
Clinical Trial ◽  
Sample Size ◽  
Death Rate ◽  
Total Sample ◽  
Management Plan ◽  
Effective Management ◽  
Total Sample Size ◽  
Corona Virus ◽  
Ayurvedic Treatment ◽  
Contemporary Medicine

To overcome COVID-19 infection there is no any precise & effective management plan so far available in contemporary Medicine. Therefore, an attempt of administering Ayurvedic medicines to alleviate signs & symptoms of Novel Corona virus is taken into consideration. A clinical trial was performed in hospital with the combination of pure herbo-mineral Ayurvedic medicines named as ‘Shwashara’ along with modern medicines over 93 infected indoor subjects. In total sample size, 76.34% subjects had co-morbidities, after treatment it is been observed that, 29.58% of these subjects did not need oxygen support. 52.69% of sub-jects had HRCT score more than half. 58.06% were recovered within 7 Days. Out of 471 patients, who re-ceived only modern medicines had death rate of 10.02% and the Subjects treated with both systems of medicines have recorded 2.15% death. The ‘Shwashara’ medicine decreases symptoms of pneumonia & COVID-19, strengthen lungs and reduces death rate significantly.

scholarly journals FACTORS AFFECTING STUDENTS’ THESIS COMPLETION ON DEPARTMENT OF MANAGEMENT STIE MIKROSKIL

2021 ◽  
Vol 27 (2) ◽  
Author(s):  
Ella Silvana Ginting ◽  
Apren Halomoan Hutasoit
Keyword(s):  
Sample Size ◽  
Comparative Research ◽  
Total Sample ◽  
Factors Affecting ◽  
Total Sample Size ◽  
Partial Analysis ◽  
Scientific Papers ◽  
Causal Comparative

This study is aimed to investigate the factors that influence the completion of students' final task, thesis. The research is causal comparative research which the data were   obtained by directly surveying respondents through questionnaire. The population in this study were students who finishing their final task, who in semester 8 students students, with total sample size of 67. From the results of the hypothesis analysis simultaneously, a significant value was obtained of 0.000, which means that motivation to graduate on time, the ability to write scientific papers, and the quality of assignment guidance final possess effect on the completion of student final assignments. Partial analysis obtained a significant value of the motivation variable of 0.012, the variable of the ability to write scientific papers of 0.018, and the variable of quality of guidance of 0.000, which means that partially motivation, the ability to write scientific papers, and the quality of final assignment guidance stimulate bring effect on the completion of students' final tasks

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