ASIC power-estimation accuracy evaluation: A case study using video-coding architectures

2018 ◽  
Author(s):  
Murilo R. Perleberg ◽  
Jones W. Goebel ◽  
Mateus S. Melo ◽  
Vladimir Afonso ◽  
Luciano V. Agostini ◽  
...  
Keyword(s):  
Video Coding ◽  
Power Estimation ◽  
Estimation Accuracy ◽  
Accuracy Evaluation

A Review on Enhanced Stability Analyses of Soil Slopes Using Statistical Design

2018 ◽  
pp. 446-481
Author(s):  
Srđan Kostić
Keyword(s):  
Slope Stability ◽  
External Validation ◽  
Statistical Design ◽  
Estimation Accuracy ◽  
Rupture Surface ◽  
Stability Of Slopes ◽  
Mathematical Expressions ◽  
Grid Search Method ◽  
Homogeneous Soil

This chapter deals with the application of experimental design in slope stability analysis. In particular, focus of the present chapter is on the application of Box-Behnken statistical design for assessment of stability of slopes in homogeneous soil (general case), for estimation of slope stability in clay-marl deposits at the edge of Neogene basins (case study) and for the extension of grid search method for locating the critical rupture surface. Extensive statistical analysis, internal and external validation imply high estimation accuracy and reliability of developed mathematical expressions for slope safety factor and for parameters of location of critical rupture surface. Main advantages and limitations of the proposed approach are thoroughly discussed with suggestions for main directions of further research.

scholarly journals Estimating Fire Background Temperature at a Geostationary Scale—An Evaluation of Contextual Methods for AHI-8

2018 ◽  
Vol 10 (9) ◽  
pp. 1368 ◽  
Author(s):  
Bryan Hally ◽  
Luke Wallace ◽  
Karin Reinke ◽  
Simon Jones ◽  
Chermelle Engel ◽  
...  
Keyword(s):  
Contextual Information ◽  
Window Size ◽  
Fire Detection ◽  
Estimation Accuracy ◽  
Significant Deterioration ◽  
Temperature Estimation ◽  
Landscape Characteristics ◽  
Detection And Attribution ◽  
Background Temperature

An integral part of any remotely sensed fire detection and attribution method is an estimation of the target pixel’s background temperature. This temperature cannot be measured directly independent of fire radiation, so indirect methods must be used to create an estimate of this background value. The most commonly used method of background temperature estimation is through derivation from the surrounding obscuration-free pixels available in the same image, in a contextual estimation process. This method of contextual estimation performs well in cloud-free conditions and in areas with homogeneous landscape characteristics, but increasingly complex sets of rules are required when contextual coverage is not optimal. The effects of alterations to the search radius and sample size on the accuracy of contextually derived brightness temperature are heretofore unexplored. This study makes use of imagery from the AHI-8 geostationary satellite to examine contextual estimators for deriving background temperature, at a range of contextual window sizes and percentages of valid contextual information. Results show that while contextual estimation provides accurate temperatures for pixels with no contextual obscuration, significant deterioration of results occurs when even a small portion of the target pixel’s surroundings are obscured. To maintain the temperature estimation accuracy, the use of no less than 65% of a target pixel’s total contextual coverage is recommended. The study also examines the use of expanding window sizes and their effect on temperature estimation. Results show that the accuracy of temperature estimation decreases significantly when expanding the examined window, with a 50% increase in temperature variability when using a larger window size than 5 × 5 pixels, whilst generally providing limited gains in the total number of temperature estimates (between 0.4%–4.4% of all pixels examined). The work also presents a number of case study regions taken from the AHI-8 disk in more depth, and examines the causes of excess temperature variation over a range of topographic and land cover conditions.

Failure Probability of Thermally Stable Diamond Composite Tips for Cutting Rock Segments

2018 ◽  
Vol 936 ◽  
pp. 192-197 ◽  
Author(s):  
Yong Sun ◽  
Xing Sheng Li
Keyword(s):  
Failure Probability ◽  
Rock Cutting ◽  
Estimation Accuracy ◽  
Segment Length ◽  
High Wear Resistance ◽  
Failure Behavior ◽  
Thermally Stable ◽  
Diamond Composite ◽  
The Impact

Thermally Stable Diamond Composite (TSDC) tips have attracted a great attention of rock cutting industry due to the higher thermal stability and high wear resistance of TSDC. To make the TSDC tipped picks practical for real application, it is important to understand the failure behavior of the TSDC tips for rock cutting. One of the failure characters of TSDC tips is random failures. In this paper, a method is proposed to calculate the failure probability of TSDC tips for cutting individual rock segments. This method enables to link the segment length to the failure probability of the tip for cutting the segment. A numerical case study is presented to validate the method. The method can effectively reduce the impact of the number of segments on failure probability estimation accuracy.

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