scholarly journals Subsequence Matching Under Time Warping in Time-Series Databases : Observation, Optimization, and Performance Results

2004 ◽  
Vol 11D (7) ◽  
pp. 1385-1398 ◽  
Author(s):  
Man-Soon Kim ◽  
Sang-Wook Kim
Keyword(s):  
Time Series ◽  
Time Warping ◽  
Subsequence Matching ◽  
And Performance ◽  
Performance Results ◽  
Optimization And Performance

scholarly journals On Extending the Prefix-Querying Method for Efficient Time-Series Subsequence Matching Under Time Warping

2006 ◽  
Vol 13D (3) ◽  
pp. 357-368
Author(s):  
Byoung-Chol Chang ◽  
Sang-Wook Kim ◽  
Jae-Hyuk Cha
Keyword(s):  
Time Series ◽  
Time Warping ◽  
Subsequence Matching

scholarly journals Efficient Subsequence Search on Streaming Data Based on Time Warping Distance

1970 ◽  
Vol 5 (1) ◽  
pp. 2-8 ◽  
Author(s):  
Sura Rodpongpun ◽  
Vit Niennattrakul ◽  
Chotirat Ann Ratanamahatana
Keyword(s):  
Time Series ◽  
Similarity Search ◽  
Time Series Data ◽  
Distance Measure ◽  
Computational Cost ◽  
Streaming Data ◽  
Series Data ◽  
Search Problem ◽  
Time Warping ◽  
Subsequence Matching

Many algorithms have been proposed to deal with subsequence similarity search problem in time series data stream. Dynamic Time Warping (DTW), which has been accepted as the best distance measure in time series similarity search, has been used in many research works. SPRING and its variance were proposed to solve such problem by mitigating the complexity of DTW. Unfortunately, these algorithms produce meaningless result since no normalization is taken into account before the distance calculation. Recently, GPUs and FPGAs were used in similarity search supporting subsequence normalization to reduce the computation complexity, but it is still far from practical use. In this work, we propose a novel Meaningful Subsequence Matching (MSM) algorithm which produces meaningful result in subsequence matching by considering global constraint, uniform scaling, and normalization. Our method significantly outperforms the existing algorithms in terms of both computational cost and accuracy.

The Relation Between Financial Incentives, Motivation, and Performance

2017 ◽  
Vol 16 (2) ◽  
pp. 61-76 ◽  
Author(s):  
Anaïs Thibault Landry ◽  
Marylène Gagné ◽  
Jacques Forest ◽  
Sylvie Guerrero ◽  
Michel Séguin ◽  
...  
Keyword(s):  
Financial Incentives ◽  
Work Performance ◽  
Autonomous Motivation ◽  
Compensation Plans ◽  
Work Settings ◽  
Path Analyses ◽  
Three Samples ◽  
And Performance ◽  
Performance Results

Abstract. To this day, researchers are debating the adequacy of using financial incentives to bolster performance in work settings. Our goal was to contribute to current understanding by considering the moderating role of distributive justice in the relation between financial incentives, motivation, and performance. Based on self-determination theory, we hypothesized that when bonuses are fairly distributed, using financial incentives makes employees feel more competent and autonomous, which in turn fosters greater autonomous motivation and lower controlled motivation, and better work performance. Results from path analyses in three samples supported our hypotheses, suggesting that the effect of financial incentives is contextual, and that compensation plans using financial incentives and bonuses can be effective when properly managed.

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