Building a Hybrid SAT Solver via Conflict-Driven, Look-Ahead and XOR Reasoning Techniques

2009 ◽  
pp. 298-311 ◽  
Author(s):  
Jingchao Chen
Keyword(s):  
Look Ahead ◽  
Sat Solver

March_eq: Implementing Additional Reasoning into an Efficient Look-Ahead SAT Solver

2005 ◽  
pp. 345-359 ◽  
Author(s):  
Marijn Heule ◽  
Mark Dufour ◽  
Joris van Zwieten ◽  
Hans van Maaren
Keyword(s):  
Look Ahead ◽  
Sat Solver

A Goodbye, a Welcome, and a Look Ahead

2016 ◽  
Vol 15 (1) ◽  
pp. 1-3
Author(s):  
Bernd Marcus
Keyword(s):  
Look Ahead

Overseas Chinese Look Ahead

1943 ◽  
Vol 12 (23) ◽  
pp. 230-231
Author(s):  
Guenther Stein
Keyword(s):  
Overseas Chinese ◽  
Look Ahead

Improvement in Look-ahead Matching Hardware for Regular Expression

2016 ◽  
Vol 136 (10) ◽  
pp. 692-697
Author(s):  
Shuto Higa ◽  
Chikatoshi Yamada ◽  
Kei Miyagi ◽  
Shuichi Ichikawa
Keyword(s):  
Regular Expression ◽  
Look Ahead

170-OR: Association of Timing of Physical Activity Bouts with Cardiorespiratory Fitness in Adults with Type 2 Diabetes in the Look AHEAD Study

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 170-OR
Author(s):  
JINGYI QIAN ◽  
MICHAEL P. WALKUP ◽  
SHYH-HUEI CHEN ◽  
PETER H. BRUBAKER ◽  
DALE BOND ◽  
...  
Keyword(s):  
Physical Activity ◽  
Type 2 Diabetes ◽  
Cardiorespiratory Fitness ◽  
Look Ahead ◽  
The Look

2007-P: Weight Change and Intentionality of Weight Loss Relate to Mortality Risk in the Postintervention (Years 8-16) Phase of Look AHEAD

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 2007-P
Author(s):  
RENA R. WING ◽  
JEANNE CLARK ◽  
MARK ESPELAND ◽  
JAMES O. HILL ◽  
ROBERT W. JEFFERY ◽  
...  
Keyword(s):  
Weight Loss ◽  
Mortality Risk ◽  
Weight Change ◽  
Look Ahead

The Taxonomy of Thinking in Reading Questions in “Look Ahead an English Course for Senior High School Level 1, 2, & 3”

2017 ◽  
Vol 6 (2) ◽  
Author(s):  
Beny Septian Panjaitan And Rahmad Husein
Keyword(s):  
High School ◽  
Quantitative Research ◽  
Sampling Technique ◽  
Senior High School ◽  
School Level ◽  
High School Level ◽  
Cognitive Dimension ◽  
Look Ahead ◽  
Table Analysis ◽  
Level 1

This study aimed at analyzing the cognitive dimension based on Revised BloomTaxonomy in reading questions in Look Ahead an English Course for Senior HighSchool Level 1, 2, & 3. This study used quantitative research design. The sampleswere 141 reading questions which taken by using random sampling technique byusing Statistical Program for Social Science (SPSS) version 20.0. in Look Aheadan English Course for Senior High School Level 1, 2, & 3. The data were analyzedby using Table analysis of cognitive dimension of Revised Bloom Taxonomy. Theanalysis showed that the most dominant cognitive dimension of Revised BloomTaxonomy in remembering dimension (57.45%). The second dominant cognitivedimension is understanding dimension (26.24%). The third dominant cognitivedimension is evaluating dimension (10.64%). The fourth dominant cognitivedimension is creating dimension (3.55%). The fifth dominant cognitive dimension isanalyzing dimension (2.13%). There was no cognitive dimension of applyingdimension that applied in reading question of the textbooks.

Enhancing the Performance of One Dimensional Median Filter

2019 ◽  
Vol 118 (7) ◽  
pp. 73-76
Author(s):  
Sharanabasappa ◽  
P Ravibabu
Keyword(s):  
Impulse Noise ◽  
Rank Order ◽  
Median Filter ◽  
Filter Method ◽  
Salt And Pepper Noise ◽  
Edge Preservation ◽  
Word Level ◽  
Look Ahead ◽  
Filter Architecture ◽  
Salt And Pepper

Nowadays, during the process of Image acquisition and transmission, image information data can be corrupted by impulse noise. That noise is classified as salt and pepper noise and random impulse noise depending on the noise values. A median filter is widely used digital nonlinear filter  in edge preservation, removing of impulse noise and smoothing of signals. Median filter is the widely used to remove salt and pepper noise than rank order filter, morphological filter, and unsharp masking filter. The median filter replaces a sample with the middle value among all the samples present inside the sample window. A median filter will be of two types depending on the number of samples processed at the same cycle i.e, bit level architecture and word level architecture.. In this paper, Carry Look-ahead Adder median filter method will be introduced to improve the hardware resources used in median filter architecture for 5 window and 9 window for 8 bit and 16 bit median filter architecture.

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