LCD OF AIR INTAKE MANIFOLDS PHASE 2: FORD F250 AIR INTAKE MANIFOLD
The life cycle design methodology was applied to the design analysis of three alternatives for the lower plehum of the air intake manifold for us with a 5.4L F-250 truck engine: a sand cast aluminum, a lost core molded nylon composite, and a vibration welded nylon composite. The ...
Engine Air Intake Manifold Having Built In Intercooler
Freese, V, Charles E.
2000-09-12
A turbocharged V type engine can be equipped with an exhaust gas recirculation cooler integrated into the intake manifold, so as to achieve efficiency, cost reductions and space economization improvements. The cooler can take the form of a tube-shell heat exchanger that utilizes a cylindrical chamber in the air intake manifold as the heat exchanger housing. The intake manifold depends into the central space formed by the two banks of cylinders on the V type engine, such that the central space is effectively utilized for containing the manifold and cooler.
LIFE CYCLE DESIGN OF AIR INTAKE MANIFOLDS; PHASE I: 2.0 L FORD CONTOUR AIR INTAKE MANIFOLD
The project team applied the life cycle design methodology to the design analysis of three alternative air intake manifolds: a sand cast aluminum, brazed aluminum tubular, and nylon composite. The design analysis included a life cycle inventory analysis, environmental regulatory...
Brazing retort manifold design concept may minimize air contamination and enhance uniform gas flow
NASA Technical Reports Server (NTRS)
Ruppe, E. P.
1966-01-01
Brazing retort manifold minimizes air contamination, prevents gas entrapment during purging, and provides uniform gas flow into the retort bell. The manifold is easily cleaned and turbulence within the bell is minimized because all manifold construction lies outside the main enclosure.
40 CFR 91.309 - Engine intake air temperature measurement.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 40 Protection of Environment 21 2013-07-01 2013-07-01 false Engine intake air temperature... Provisions § 91.309 Engine intake air temperature measurement. (a) Engine intake air temperature measurement... the supply system or in the air stream entering the engine. (b) The temperature measurements must...
40 CFR 91.309 - Engine intake air temperature measurement.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 20 2014-07-01 2013-07-01 true Engine intake air temperature... Provisions § 91.309 Engine intake air temperature measurement. (a) Engine intake air temperature measurement... the supply system or in the air stream entering the engine. (b) The temperature measurements must...
40 CFR 91.309 - Engine intake air temperature measurement.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 21 2012-07-01 2012-07-01 false Engine intake air temperature... Provisions § 91.309 Engine intake air temperature measurement. (a) Engine intake air temperature measurement... the supply system or in the air stream entering the engine. (b) The temperature measurements must...
40 CFR 92.108 - Intake and cooling air measurements.
Code of Federal Regulations, 2013 CFR
2013-07-01
....108 Intake and cooling air measurements. (a) Intake air flow measurement. Measurement of the flow rate..., the measurement technique shall conform to the following: (1) The air flow measurement method used... 40 Protection of Environment 21 2013-07-01 2013-07-01 false Intake and cooling air......
40 CFR 92.108 - Intake and cooling air measurements.
Code of Federal Regulations, 2012 CFR
2012-07-01
....108 Intake and cooling air measurements. (a) Intake air flow measurement. Measurement of the flow rate..., the measurement technique shall conform to the following: (1) The air flow measurement method used... 40 Protection of Environment 21 2012-07-01 2012-07-01 false Intake and cooling air......
40 CFR 91.416 - Intake air flow measurement specifications.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 20 2014-07-01 2013-07-01 true Intake air flow measurement... Procedures § 91.416 Intake air flow measurement specifications. (a) If used, the engine intake air flow measurement method used must have a range large enough to accurately measure the air flow over the...
40 CFR 92.108 - Intake and cooling air measurements.
Code of Federal Regulations, 2014 CFR
2014-07-01
... and cooling air measurements. (a) Intake air flow measurement. Measurement of the flow rate of intake... measurement technique shall conform to the following: (1) The air flow measurement method used must have a... 40 Protection of Environment 20 2014-07-01 2013-07-01 true Intake and cooling air......
40 CFR 92.108 - Intake and cooling air measurements.
Code of Federal Regulations, 2011 CFR
2011-07-01
....108 Intake and cooling air measurements. (a) Intake air flow measurement. Measurement of the flow rate..., the measurement technique shall conform to the following: (1) The air flow measurement method used... 40 Protection of Environment 20 2011-07-01 2011-07-01 false Intake and cooling air......
40 CFR 92.108 - Intake and cooling air measurements.
Code of Federal Regulations, 2010 CFR
2010-07-01
....108 Intake and cooling air measurements. (a) Intake air flow measurement. Measurement of the flow rate..., the measurement technique shall conform to the following: (1) The air flow measurement method used... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Intake and cooling air......
40 CFR 91.416 - Intake air flow measurement specifications.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 20 2011-07-01 2011-07-01 false Intake air flow measurement... Procedures § 91.416 Intake air flow measurement specifications. (a) If used, the engine intake air flow measurement method used must have a range large enough to accurately measure the air flow over the...
40 CFR 91.416 - Intake air flow measurement specifications.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Intake air flow measurement... Procedures § 91.416 Intake air flow measurement specifications. (a) If used, the engine intake air flow measurement method used must have a range large enough to accurately measure the air flow over the...
40 CFR 91.416 - Intake air flow measurement specifications.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 21 2012-07-01 2012-07-01 false Intake air flow measurement... Procedures § 91.416 Intake air flow measurement specifications. (a) If used, the engine intake air flow measurement method used must have a range large enough to accurately measure the air flow over the...
40 CFR 90.310 - Engine intake air humidity measurement.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 20 2011-07-01 2011-07-01 false Engine intake air humidity measurement... Emission Test Equipment Provisions § 90.310 Engine intake air humidity measurement. This section refers to... for the engine intake air, the ambient test cell humidity measurement may be used. (a)...
40 CFR 90.310 - Engine intake air humidity measurement.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 40 Protection of Environment 21 2013-07-01 2013-07-01 false Engine intake air humidity measurement... Emission Test Equipment Provisions § 90.310 Engine intake air humidity measurement. This section refers to... for the engine intake air, the ambient test cell humidity measurement may be used. (a)...
40 CFR 90.310 - Engine intake air humidity measurement.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 21 2012-07-01 2012-07-01 false Engine intake air humidity measurement... Emission Test Equipment Provisions § 90.310 Engine intake air humidity measurement. This section refers to... for the engine intake air, the ambient test cell humidity measurement may be used. (a)...
40 CFR 90.310 - Engine intake air humidity measurement.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 20 2014-07-01 2013-07-01 true Engine intake air humidity measurement... Emission Test Equipment Provisions § 90.310 Engine intake air humidity measurement. This section refers to... for the engine intake air, the ambient test cell humidity measurement may be used. (a)...
30 CFR 250.610 - Diesel engine air intakes.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 30 Mineral Resources 2 2010-07-01 2010-07-01 false Diesel engine air intakes. 250.610 Section 250... engine air intakes. No later than May 31, 1989, diesel engine air intakes shall be equipped with a device to shut down the diesel engine in the event of runaway. Diesel engines which are...
30 CFR 250.510 - Diesel engine air intakes.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 30 Mineral Resources 2 2010-07-01 2010-07-01 false Diesel engine air intakes. 250.510 Section 250... engine air intakes. Diesel engine air intakes must be equipped with a device to shut down the diesel engine in the event of runaway. Diesel engines that are continuously attended must be equipped...
30 CFR 250.610 - Diesel engine air intakes.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 30 Mineral Resources 2 2011-07-01 2011-07-01 false Diesel engine air intakes. 250.610 Section 250... Well-Workover Operations § 250.610 Diesel engine air intakes. No later than May 31, 1989, diesel engine air intakes shall be equipped with a device to shut down the diesel engine in the event of...
30 CFR 250.510 - Diesel engine air intakes.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 30 Mineral Resources 2 2011-07-01 2011-07-01 false Diesel engine air intakes. 250.510 Section 250... Well-Completion Operations § 250.510 Diesel engine air intakes. Diesel engine air intakes must be equipped with a device to shut down the diesel engine in the event of runaway. Diesel engines that...
40 CFR 89.325 - Engine intake air temperature measurement.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 40 Protection of Environment 21 2013-07-01 2013-07-01 false Engine intake air temperature... Test Equipment Provisions § 89.325 Engine intake air temperature measurement. (a) Engine intake air temperature measurement must be made within 122 cm of the engine. The measurement location must be made...
40 CFR 89.325 - Engine intake air temperature measurement.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 20 2014-07-01 2013-07-01 true Engine intake air temperature... Test Equipment Provisions § 89.325 Engine intake air temperature measurement. (a) Engine intake air temperature measurement must be made within 122 cm of the engine. The measurement location must be made...
40 CFR 89.325 - Engine intake air temperature measurement.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 21 2012-07-01 2012-07-01 false Engine intake air temperature... Test Equipment Provisions § 89.325 Engine intake air temperature measurement. (a) Engine intake air temperature measurement must be made within 122 cm of the engine. The measurement location must be made...
40 CFR 89.325 - Engine intake air temperature measurement.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 20 2011-07-01 2011-07-01 false Engine intake air temperature... Test Equipment Provisions § 89.325 Engine intake air temperature measurement. (a) Engine intake air temperature measurement must be made within 122 cm of the engine. The measurement location must be made...
30 CFR 250.610 - Diesel engine air intakes.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 30 Mineral Resources 2 2013-07-01 2013-07-01 false Diesel engine air intakes. 250.610 Section 250... Operations § 250.610 Diesel engine air intakes. No later than May 31, 1989, diesel engine air intakes shall be equipped with a device to shut down the diesel engine in the event of runaway. Diesel...
30 CFR 250.510 - Diesel engine air intakes.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 30 Mineral Resources 2 2012-07-01 2012-07-01 false Diesel engine air intakes. 250.510 Section 250... Operations § 250.510 Diesel engine air intakes. Diesel engine air intakes must be equipped with a device to shut down the diesel engine in the event of runaway. Diesel engines that are continuously attended...
30 CFR 250.610 - Diesel engine air intakes.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 30 Mineral Resources 2 2012-07-01 2012-07-01 false Diesel engine air intakes. 250.610 Section 250... Operations § 250.610 Diesel engine air intakes. No later than May 31, 1989, diesel engine air intakes shall be equipped with a device to shut down the diesel engine in the event of runaway. Diesel...
30 CFR 250.610 - Diesel engine air intakes.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 30 Mineral Resources 2 2014-07-01 2014-07-01 false Diesel engine air intakes. 250.610 Section 250... Operations § 250.610 Diesel engine air intakes. No later than May 31, 1989, diesel engine air intakes shall be equipped with a device to shut down the diesel engine in the event of runaway. Diesel...
30 CFR 250.510 - Diesel engine air intakes.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 30 Mineral Resources 2 2014-07-01 2014-07-01 false Diesel engine air intakes. 250.510 Section 250... Operations § 250.510 Diesel engine air intakes. Diesel engine air intakes must be equipped with a device to shut down the diesel engine in the event of runaway. Diesel engines that are continuously attended...
30 CFR 250.510 - Diesel engine air intakes.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 30 Mineral Resources 2 2013-07-01 2013-07-01 false Diesel engine air intakes. 250.510 Section 250... Operations § 250.510 Diesel engine air intakes. Diesel engine air intakes must be equipped with a device to shut down the diesel engine in the event of runaway. Diesel engines that are continuously attended...
40 CFR 90.416 - Intake air flow measurement specifications.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Intake air flow measurement... Gaseous Exhaust Test Procedures § 90.416 Intake air flow measurement specifications. (a) If used, the engine intake air flow measurement method used must have a range large enough to accurately measure...
40 CFR 90.416 - Intake air flow measurement specifications.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 21 2012-07-01 2012-07-01 false Intake air flow measurement... Gaseous Exhaust Test Procedures § 90.416 Intake air flow measurement specifications. (a) If used, the engine intake air flow measurement method used must have a range large enough to accurately measure...
40 CFR 1065.225 - Intake-air flow meter.
Code of Federal Regulations, 2011 CFR
2011-07-01
... CONTROLS ENGINE-TESTING PROCEDURES Measurement Instruments Flow-Related Measurements § 1065.225 Intake-air flow meter. (a) Application. You may use an intake-air flow meter in combination with a chemical... 40 Protection of Environment 33 2011-07-01 2011-07-01 false Intake-air flow meter....
40 CFR 90.416 - Intake air flow measurement specifications.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 20 2014-07-01 2013-07-01 true Intake air flow measurement... Gaseous Exhaust Test Procedures § 90.416 Intake air flow measurement specifications. (a) If used, the engine intake air flow measurement method used must have a range large enough to accurately measure...
40 CFR 1065.225 - Intake-air flow meter.
Code of Federal Regulations, 2013 CFR
2013-07-01
... CONTROLS ENGINE-TESTING PROCEDURES Measurement Instruments Flow-Related Measurements § 1065.225 Intake-air flow meter. (a) Application. You may use an intake-air flow meter in combination with a chemical... 40 Protection of Environment 34 2013-07-01 2013-07-01 false Intake-air flow meter....
40 CFR 1065.225 - Intake-air flow meter.
Code of Federal Regulations, 2010 CFR
2010-07-01
... CONTROLS ENGINE-TESTING PROCEDURES Measurement Instruments Flow-Related Measurements § 1065.225 Intake-air flow meter. (a) Application. You may use an intake-air flow meter in combination with a chemical... 40 Protection of Environment 32 2010-07-01 2010-07-01 false Intake-air flow meter....
40 CFR 1065.225 - Intake-air flow meter.
Code of Federal Regulations, 2014 CFR
2014-07-01
... CONTROLS ENGINE-TESTING PROCEDURES Measurement Instruments Flow-Related Measurements § 1065.225 Intake-air flow meter. (a) Application. You may use an intake-air flow meter in combination with a chemical... 40 Protection of Environment 33 2014-07-01 2014-07-01 false Intake-air flow meter....
40 CFR 90.416 - Intake air flow measurement specifications.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 20 2011-07-01 2011-07-01 false Intake air flow measurement... Gaseous Exhaust Test Procedures § 90.416 Intake air flow measurement specifications. (a) If used, the engine intake air flow measurement method used must have a range large enough to accurately measure...
40 CFR 1065.225 - Intake-air flow meter.
Code of Federal Regulations, 2012 CFR
2012-07-01
... CONTROLS ENGINE-TESTING PROCEDURES Measurement Instruments Flow-Related Measurements § 1065.225 Intake-air flow meter. (a) Application. You may use an intake-air flow meter in combination with a chemical... 40 Protection of Environment 34 2012-07-01 2012-07-01 false Intake-air flow meter....
40 CFR 89.326 - Engine intake air humidity measurement.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Engine intake air humidity measurement... Test Equipment Provisions § 89.326 Engine intake air humidity measurement. (a) Humidity conditioned air supply. Air that has had its absolute humidity altered is considered humidity- conditioned air. For...
40 CFR 89.326 - Engine intake air humidity measurement.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 20 2011-07-01 2011-07-01 false Engine intake air humidity measurement... Test Equipment Provisions § 89.326 Engine intake air humidity measurement. (a) Humidity conditioned air supply. Air that has had its absolute humidity altered is considered humidity- conditioned air. For...
40 CFR 89.326 - Engine intake air humidity measurement.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 40 Protection of Environment 21 2013-07-01 2013-07-01 false Engine intake air humidity measurement... Test Equipment Provisions § 89.326 Engine intake air humidity measurement. (a) Humidity conditioned air supply. Air that has had its absolute humidity altered is considered humidity- conditioned air. For...
40 CFR 89.326 - Engine intake air humidity measurement.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 20 2014-07-01 2013-07-01 true Engine intake air humidity measurement... Test Equipment Provisions § 89.326 Engine intake air humidity measurement. (a) Humidity conditioned air supply. Air that has had its absolute humidity altered is considered humidity- conditioned air. For...
40 CFR 89.326 - Engine intake air humidity measurement.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 21 2012-07-01 2012-07-01 false Engine intake air humidity measurement... Test Equipment Provisions § 89.326 Engine intake air humidity measurement. (a) Humidity conditioned air supply. Air that has had its absolute humidity altered is considered humidity- conditioned air. For...
40 CFR 91.310 - Engine intake air humidity measurement.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 21 2012-07-01 2012-07-01 false Engine intake air humidity measurement... Provisions § 91.310 Engine intake air humidity measurement. This section refers to engines which are supplied... air, the ambient testcell humidity measurement may be used. (a) Humidity conditioned air supply....
40 CFR 91.310 - Engine intake air humidity measurement.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 40 Protection of Environment 21 2013-07-01 2013-07-01 false Engine intake air humidity measurement... Provisions § 91.310 Engine intake air humidity measurement. This section refers to engines which are supplied... air, the ambient testcell humidity measurement may be used. (a) Humidity conditioned air supply....
40 CFR 91.310 - Engine intake air humidity measurement.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 20 2011-07-01 2011-07-01 false Engine intake air humidity measurement... Provisions § 91.310 Engine intake air humidity measurement. This section refers to engines which are supplied... air, the ambient testcell humidity measurement may be used. (a) Humidity conditioned air supply....
40 CFR 91.310 - Engine intake air humidity measurement.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 20 2014-07-01 2013-07-01 true Engine intake air humidity measurement... Provisions § 91.310 Engine intake air humidity measurement. This section refers to engines which are supplied... air, the ambient testcell humidity measurement may be used. (a) Humidity conditioned air supply....
40 CFR 1065.125 - Engine intake air.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 32 2010-07-01 2010-07-01 false Engine intake air. 1065.125 Section 1065.125 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Equipment Specifications § 1065.125 Engine intake air. (a) Use the...
40 CFR 1065.125 - Engine intake air.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 40 Protection of Environment 34 2013-07-01 2013-07-01 false Engine intake air. 1065.125 Section 1065.125 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Equipment Specifications § 1065.125 Engine intake air. (a) Use the...
40 CFR 1065.125 - Engine intake air.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 34 2012-07-01 2012-07-01 false Engine intake air. 1065.125 Section 1065.125 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Equipment Specifications § 1065.125 Engine intake air. (a) Use the...
40 CFR 1065.125 - Engine intake air.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 33 2014-07-01 2014-07-01 false Engine intake air. 1065.125 Section 1065.125 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Equipment Specifications § 1065.125 Engine intake air. (a) Use the...
40 CFR 1065.125 - Engine intake air.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 33 2011-07-01 2011-07-01 false Engine intake air. 1065.125 Section 1065.125 Protection of Environment ENVIRONMENTAL PROTECTION AGENCY (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Equipment Specifications § 1065.125 Engine intake air. (a) Use the...
Comparison of Space Shuttle Hot Gas Manifold analysis to air flow data
NASA Technical Reports Server (NTRS)
Mcconnaughey, P. K.
1988-01-01
This paper summarizes several recent analyses of the Space Shuttle Main Engine Hot Gas Manifold and compares predicted flow environments to air flow data. Codes used in these analyses include INS3D, PAGE, PHOENICS, and VAST. Both laminar (Re = 250, M = 0.30) and turbulent (Re = 1.9 million, M = 0.30) results are discussed, with the latter being compared to data for system losses, outer wall static pressures, and manifold exit Mach number profiles. Comparison of predicted results for the turbulent case to air flow data shows that the analysis using INS3D predicted system losses within 1 percent error, while the PHOENICS, PAGE, and VAST codes erred by 31, 35, and 47 percent, respectively. The INS3D, PHOENICS, and PAGE codes did a reasonable job of predicting outer wall static pressure, while the PHOENICS code predicted exit Mach number profiles with acceptable accuracy. INS3D was approximately an order of magnitude more efficient than the other codes in terms of code speed and memory requirements. In general, it is seen that complex internal flows in manifold-like geometries can be predicted with a limited degree of confidence, and further development is necessary to improve both efficiency and accuracy of codes if they are to be used as design tools for complex three-dimensional geometries.
40 CFR 91.309 - Engine intake air temperature measurement.
Code of Federal Regulations, 2011 CFR
2011-07-01
... must be made within 100 cm of the air-intake of the engine. The measurement location must be either in... 40 Protection of Environment 20 2011-07-01 2011-07-01 false Engine intake air temperature... PROGRAMS (CONTINUED) CONTROL OF EMISSIONS FROM MARINE SPARK-IGNITION ENGINES Emission Test...
40 CFR 91.309 - Engine intake air temperature measurement.
Code of Federal Regulations, 2010 CFR
2010-07-01
... must be made within 100 cm of the air-intake of the engine. The measurement location must be either in... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Engine intake air temperature... PROGRAMS (CONTINUED) CONTROL OF EMISSIONS FROM MARINE SPARK-IGNITION ENGINES Emission Test...
40 CFR 90.309 - Engine intake air temperature measurement.
Code of Federal Regulations, 2010 CFR
2010-07-01
... location must be within 10 cm of the engine intake system (i.e., the air cleaner, for most engines.) (b... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Engine intake air temperature... PROGRAMS (CONTINUED) CONTROL OF EMISSIONS FROM NONROAD SPARK-IGNITION ENGINES AT OR BELOW 19...
40 CFR 90.309 - Engine intake air temperature measurement.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 21 2012-07-01 2012-07-01 false Engine intake air temperature... Emission Test Equipment Provisions § 90.309 Engine intake air temperature measurement. (a) The measurement...) The temperature measurements must be accurate to within ±2 °C....
40 CFR 90.309 - Engine intake air temperature measurement.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 40 Protection of Environment 20 2014-07-01 2013-07-01 true Engine intake air temperature... Emission Test Equipment Provisions § 90.309 Engine intake air temperature measurement. (a) The measurement...) The temperature measurements must be accurate to within ±2 °C....
40 CFR 90.309 - Engine intake air temperature measurement.
Code of Federal Regulations, 2013 CFR
2013-07-01
... 40 Protection of Environment 21 2013-07-01 2013-07-01 false Engine intake air temperature... Emission Test Equipment Provisions § 90.309 Engine intake air temperature measurement. (a) The measurement...) The temperature measurements must be accurate to within ±2 °C....
40 CFR 90.309 - Engine intake air temperature measurement.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 20 2011-07-01 2011-07-01 false Engine intake air temperature... Emission Test Equipment Provisions § 90.309 Engine intake air temperature measurement. (a) The measurement...) The temperature measurements must be accurate to within ±2 °C....
40 CFR 90.310 - Engine intake air humidity measurement.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Engine intake air humidity measurement... PROGRAMS (CONTINUED) CONTROL OF EMISSIONS FROM NONROAD SPARK-IGNITION ENGINES AT OR BELOW 19 KILOWATTS Emission Test Equipment Provisions § 90.310 Engine intake air humidity measurement. This section refers...
40 CFR 91.310 - Engine intake air humidity measurement.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Engine intake air humidity measurement... PROGRAMS (CONTINUED) CONTROL OF EMISSIONS FROM MARINE SPARK-IGNITION ENGINES Emission Test Equipment Provisions § 91.310 Engine intake air humidity measurement. This section refers to engines which are...
Working Characteristics of Variable Intake Valve in Compressed Air Engine
Yu, Qihui; Shi, Yan; Cai, Maolin
2014-01-01
A new camless compressed air engine is proposed, which can make the compressed air energy reasonably distributed. Through analysis of the camless compressed air engine, a mathematical model of the working processes was set up. Using the software MATLAB/Simulink for simulation, the pressure, temperature, and air mass of the cylinder were obtained. In order to verify the accuracy of the mathematical model, the experiments were conducted. Moreover, performance analysis was introduced to design compressed air engine. Results show that, firstly, the simulation results have good consistency with the experimental results. Secondly, under different intake pressures, the highest output power is obtained when the crank speed reaches 500 rpm, which also provides the maximum output torque. Finally, higher energy utilization efficiency can be obtained at the lower speed, intake pressure, and valve duration angle. This research can refer to the design of the camless valve of compressed air engine. PMID:25379536
Working characteristics of variable intake valve in compressed air engine.
Yu, Qihui; Shi, Yan; Cai, Maolin
2014-01-01
A new camless compressed air engine is proposed, which can make the compressed air energy reasonably distributed. Through analysis of the camless compressed air engine, a mathematical model of the working processes was set up. Using the software MATLAB/Simulink for simulation, the pressure, temperature, and air mass of the cylinder were obtained. In order to verify the accuracy of the mathematical model, the experiments were conducted. Moreover, performance analysis was introduced to design compressed air engine. Results show that, firstly, the simulation results have good consistency with the experimental results. Secondly, under different intake pressures, the highest output power is obtained when the crank speed reaches 500 rpm, which also provides the maximum output torque. Finally, higher energy utilization efficiency can be obtained at the lower speed, intake pressure, and valve duration angle. This research can refer to the design of the camless valve of compressed air engine.
Curved centerline air intake for a gas turbine engine
NASA Technical Reports Server (NTRS)
Ruehr, W. C.; Younghans, J. L.; Smith, E. B. (Inventor)
1980-01-01
An inlet for a gas turbine engine was disposed about a curved centerline for the purpose of accepting intake air that is flowing at an angle to engine centerline and progressively turning that intake airflow along a curved path into alignment with the engine. This curved inlet is intended for use in under the wing locations and similar regions where airflow direction is altered by aerodynamic characteristics of the airplane. By curving the inlet, aerodynamic loss and acoustic generation and emission are decreased.
Measuring Outdoor Air Intake Rates into Existing Building
Fisk, William; Sullivan, Douglas; Cohen, Sebastian; Han, Hwataik
2009-04-16
Practical and accurate technologies are needed for continuously measuring and controlling outdoor air (OA) intake rates in commercial building heating, ventilating, and air conditioning (HVAC) systems. This project evaluated two new measurement approaches. Laboratory experiments determined that OA flow rates were measurable with errors generally less than 10 percent using electronic air velocity probes installed between OA intake louver blades or at the outlet face of louvers. High accuracy was maintained with OA flow rates as low as 15 percent of the maximum for the louvers. Thus, with this measurement approach HVAC systems do not need separate OA intakes for minimum OA supply. System calibration parameters are required for each unique combination of louver type and velocity sensor location but calibrations are not necessary for each system installation. The research also determined that the accuracy of measuring OA flow rates with velocity probes located in the duct downstream of the intake louver was not improved by installing honeycomb airflow straighteners upstream of the probes. Errors varied with type of upstream louver, were as high as 100 percent, and were often greater than 25 percent. In conclusion, use of electronic air velocity probes between the blades of OA intake louvers or at the outlet face of louvers is a highly promising means of accurately measuring rates of OA flow into HVAC systems. The use of electronic velocity probes downstream of airflow straighteners is less promising, at least with the relatively small OA HVAC inlet systems employed in this research.
Incorporation of air into a snack food reduces energy intake
Osterholt, Kathrin M.; Roe, Liane S.
2007-01-01
This study investigated how the air content of a familiar snack food affected energy intake and whether varying the method of serving the snack modified intake. We tested two versions of an extruded snack (cheese puffs) that were equal in energy density (5.7 kcal/g), but differed in energy per volume (less-aerated snack: 1.00 kcal/ml; more- aerated snack: 0.45 kcal/ml). In a within-subjects design, 16 women and 12 men consumed the snacks ad libitum in the laboratory during four afternoon sessions. A standard volume (1250 ml) of each snack was served once in a bowl and once in an opaque bag. Results showed that intake of the two snacks differed significantly by energy (p=0.0003) and volume (p<0.0001); subjects consumed 21% less weight and energy (70±17 kcal) of the more-aerated snack than the less-aerated snack, although they consumed a 73% greater volume of the more-aerated snack (239±24 ml). These findings suggest that subjects responded to both the weight and volume of the snack. Despite differences in intake, hunger and fullness ratings did not differ across conditions. The serving method did not significantly affect intake. Results from this study indicate that incorporating air into food provides a strategy to reduce energy intake from energy-dense snacks. PMID:17188782
Air intakes for a probative missile of rocket ramjet
NASA Technical Reports Server (NTRS)
Laruelle, G.
1984-01-01
The methods employed to test air intakes for a supersonic guided ramjet powered missile being tested by ONERA are described. Both flight tests and wind tunnel tests were performed on instrumented rockets to verify the designs. Consideration as given to the number of intakes, with the goal of delivering the maximum pressure to the engine. The S2, S4, and S5 wind tunnels were operated at Mach nos. 1.5-3 for the tests, which were compartmentalized into fuselage-intake interaction, optimization of the intake shapes, and the intake performance. Tests were performed on the length and form of the ogive, the presence of grooves, the height of traps in the boundary layer, the types and number of intakes and the lengths and forms of diffusers. Attention was also given to the effects of sideslip, effects of the longitudinal and circumferential positions of the intakes were also examined. Near optimum performance was realized during Mach 2.2 test flights of the prototype rockets.
40 CFR 89.325 - Engine intake air temperature measurement.
Code of Federal Regulations, 2010 CFR
2010-07-01
... temperature measurement must be made within 122 cm of the engine. The measurement location must be made either... 40 Protection of Environment 20 2010-07-01 2010-07-01 false Engine intake air temperature... PROGRAMS (CONTINUED) CONTROL OF EMISSIONS FROM NEW AND IN-USE NONROAD COMPRESSION-IGNITION ENGINES...
Gary D. Bourn; Ford A. Phillips; Ralph E. Harris
2005-12-01
This document provides results and conclusions for Task 15.0--Detailed Analysis of Air Balance & Conceptual Design of Improved Air Manifolds in the ''Technologies to Enhance the Operation of Existing Natural Gas Compression Infrastructure'' project. SwRI{reg_sign} is conducting this project for DOE in conjunction with Pipeline Research Council International, Gas Machinery Research Council, El Paso Pipeline, Cooper Compression, and Southern Star, under DOE contract number DE-FC26-02NT41646. The objective of Task 15.0 was to investigate the perceived imbalance in airflow between power cylinders in two-stroke integral compressor engines and develop solutions via manifold redesign. The overall project objective is to develop and substantiate methods for operating integral engine/compressors in gas pipeline service, which reduce fuel consumption, increase capacity, and enhance mechanical integrity.
Air Intakes for High Speed Vehicles (Prises d’Air pour Vehicules a Grande Vitesse)
1991-09-01
directly from material supplied by AGARD or the authors . Published aeptember 1991 Copyright C AGARD 1991 All Rights Reserved ISBN 92-835-0637-5 Printed by...of Air Intakes Committee C (Chairman: J. Leynaert) Air Intakes Testing Methods The chapters were written by the authors noted in parenthesis and...fuel injection and effect expansion waves and separation induced mixing as well as chemical kinetics. Reference shockwaves. The author points to good
40 CFR 1065.655 - Chemical balances of fuel, intake air, and exhaust.
Code of Federal Regulations, 2013 CFR
2013-07-01
... (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Calculations and Data Requirements § 1065.655 Chemical balances of fuel, intake air, and exhaust. (a) General. Chemical balances of fuel, intake air, and... 40 Protection of Environment 34 2013-07-01 2013-07-01 false Chemical balances of fuel, intake...
40 CFR 1065.655 - Chemical balances of fuel, intake air, and exhaust.
Code of Federal Regulations, 2011 CFR
2011-07-01
... (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Calculations and Data Requirements § 1065.655 Chemical balances of fuel, intake air, and exhaust. (a) General. Chemical balances of fuel, intake air, and... 40 Protection of Environment 33 2011-07-01 2011-07-01 false Chemical balances of fuel, intake...
40 CFR 1065.655 - Chemical balances of fuel, intake air, and exhaust.
Code of Federal Regulations, 2014 CFR
2014-07-01
... (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Calculations and Data Requirements § 1065.655 Chemical balances of fuel, intake air, and exhaust. (a) General. Chemical balances of fuel, intake air, and... 40 Protection of Environment 33 2014-07-01 2014-07-01 false Chemical balances of fuel, intake...
40 CFR 1065.655 - Chemical balances of fuel, intake air, and exhaust.
Code of Federal Regulations, 2012 CFR
2012-07-01
... (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Calculations and Data Requirements § 1065.655 Chemical balances of fuel, intake air, and exhaust. (a) General. Chemical balances of fuel, intake air, and... 40 Protection of Environment 34 2012-07-01 2012-07-01 false Chemical balances of fuel, intake...
40 CFR 1065.655 - Chemical balances of fuel, intake air, and exhaust.
Code of Federal Regulations, 2010 CFR
2010-07-01
... (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Calculations and Data Requirements § 1065.655 Chemical balances of fuel, intake air, and exhaust. (a) General. Chemical balances of fuel, intake air, and... 40 Protection of Environment 32 2010-07-01 2010-07-01 false Chemical balances of fuel, intake...
Manuel, Christopher A; Pugazhenthi, Umarani; Leszczynski, Jori K
2016-01-01
Corynebacterium bovis causes an opportunistic infection of nude (Foxn1, nu/nu) mice, leading to nude mouse hyperkeratotic dermatitis (scaly skin disease). Enzootic in many nude mouse colonies, C. bovis spreads rapidly to naive nude mice, despite modern husbandry practices, and is very difficult to eradicate. To facilitate rapid detection in support of eradication efforts, we investigated a surveillance method based on quantitative real-time PCR (qPCR) evaluation of swabs collected from the horizontal exhaust manifold (HEM) of an IVC rack system. We first evaluated the efficacy of rack sanitation methods for removing C. bovis DNA from the HEM of racks housing endemic colonies of infected nude mice. Pressurized water used to flush the racks' air exhaust system followed by a standard rack-washer cycle was ineffective in eliminating C. bovis DNA. Only after autoclaving did all sanitized racks test negative for C. bovis DNA. We then measured the effects of stage of infection (early or established), cage density, and cage location on the rack on time-to-detection at the HEM. Stage of infection significantly affected time-to-detection, independent of cage location. Early infections required 7.3 ± 1.2 d whereas established infections required 1 ± 0 d for detection of C. bovis at the HEM. Cage density influenced the quantity of C. bovis DNA detected but not time-to-detection. The location of the cage on the rack affected the time-to-detection only during early C. bovis infections. We suggest that qPCR swabs of HEM are useful during the routine surveillance of nude mouse colonies for C. bovis infection.
Surveillance of a Ventilated Rack System for Corynebacterium bovis by Sampling Exhaust-Air Manifolds
Manuel, Christopher A; Pugazhenthi, Umarani; Leszczynski, Jori K
2016-01-01
Corynebacterium bovis causes an opportunistic infection of nude (Foxn1, nu/nu) mice, leading to nude mouse hyperkeratotic dermatitis (scaly skin disease). Enzootic in many nude mouse colonies, C. bovis spreads rapidly to naive nude mice, despite modern husbandry practices, and is very difficult to eradicate. To facilitate rapid detection in support of eradication efforts, we investigated a surveillance method based on quantitative real-time PCR (qPCR) evaluation of swabs collected from the horizontal exhaust manifold (HEM) of an IVC rack system. We first evaluated the efficacy of rack sanitation methods for removing C. bovis DNA from the HEM of racks housing endemic colonies of infected nude mice. Pressurized water used to flush the racks’ air exhaust system followed by a standard rack-washer cycle was ineffective in eliminating C. bovis DNA. Only after autoclaving did all sanitized racks test negative for C. bovis DNA. We then measured the effects of stage of infection (early or established), cage density, and cage location on the rack on time-to-detection at the HEM. Stage of infection significantly affected time-to-detection, independent of cage location. Early infections required 7.3 ± 1.2 d whereas established infections required 1 ± 0 d for detection of C. bovis at the HEM. Cage density influenced the quantity of C. bovis DNA detected but not time-to-detection. The location of the cage on the rack affected the time-to-detection only during early C. bovis infections. We suggest that qPCR swabs of HEM are useful during the routine surveillance of nude mouse colonies for C. bovis infection. PMID:26817981
Inhalation intake of ambient air pollution in California's South Coast Air Basin
NASA Astrophysics Data System (ADS)
Marshall, Julian D.; Granvold, Patrick W.; Hoats, Abigail S.; McKone, Thomas E.; Deakin, Elizabeth; W Nazaroff, William
Reliable estimates of inhalation intake of air pollution and its distribution among a specified population are important for environmental epidemiology, health risk assessment, urban planning, and environmental policy. We computed distributional characteristics of the inhalation intake of five pollutants for a group of ˜25,000 people (˜29,000 person-days) living in California's South Coast Air Basin. Our approach incorporates four main inputs: temporally resolved information about people's location (latitude and longitude), microenvironment, and activity level; temporally and spatially explicit model determinations of ambient concentrations; stochastically determined microenvironmental adjustment factors relating the exposure concentration to the ambient concentration; and, age-, gender-, and activity-specific breathing rates. Our study is restricted to pollutants of outdoor origin, i.e. it does not incorporate intake in a microenvironment from direct emissions into that microenvironment. Median estimated inhalation intake rates (μg d -1) are 53 for benzene, 5.1 for 1,3-butadiene, 8.7×10 -4 for hexavalent chromium in fine particulate matter (Cr-PM 2.5), 30 for diesel fine particulate matter (DPM 2.5), and 68 for ozone. For the four primary pollutants studied, estimated median intake rates are higher for non-whites and for individuals in low-income households than for the population as a whole. For ozone, a secondary pollutant, the reverse is true. Accounting for microenvironmental adjustment factors, population mobility and temporal correlations between pollutant concentrations and breathing rates affects the estimated inhalation intake by 40% on average. The approach presented here could be extended to quantify the impact on intakes and intake distributions of proposed changes in emissions, air quality, and urban infrastructure.
Influence of intake air temperature on internal combustion engine operation
NASA Astrophysics Data System (ADS)
Birtok-Băneasă, C.; Raţiu, S.; Hepuţ, T.
2017-01-01
This paper presents three methods for reduce thermal losses in the intake system with improvement of airflow and thermal protection. In the experiment are involved two patented devices conceived by the author and one PhD theme device: 1- Dynamic device for air transfer, 2-Integrated thermal deflector, and, 3-Advanced thermal protection. The tests were carried on different vehicle running in real traffic and in the Internal Combustion Engines Laboratory, within the specialization “Road vehicle” belonging to the Faculty of Engineering Hunedoara, component of Politehnica University of Timişoara. The results have been processed and compared whit the ones obtained without these devices.
40 CFR 1065.670 - NOX intake-air humidity and temperature corrections.
Code of Federal Regulations, 2013 CFR
2013-07-01
... (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Calculations and Data Requirements § 1065.670 NOX intake-air humidity and temperature corrections. See the standard-setting part to determine if you... 40 Protection of Environment 34 2013-07-01 2013-07-01 false NOX intake-air humidity...
40 CFR 1065.670 - NOX intake-air humidity and temperature corrections.
Code of Federal Regulations, 2010 CFR
2010-07-01
... (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Calculations and Data Requirements § 1065.670 NOX intake-air humidity and temperature corrections. See the standard-setting part to determine if you... 40 Protection of Environment 32 2010-07-01 2010-07-01 false NOX intake-air humidity...
40 CFR 1065.670 - NOX intake-air humidity and temperature corrections.
Code of Federal Regulations, 2014 CFR
2014-07-01
... (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Calculations and Data Requirements § 1065.670 NOX intake-air humidity and temperature corrections. See the standard-setting part to determine if you... 40 Protection of Environment 33 2014-07-01 2014-07-01 false NOX intake-air humidity...
40 CFR 1065.670 - NOX intake-air humidity and temperature corrections.
Code of Federal Regulations, 2011 CFR
2011-07-01
... (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Calculations and Data Requirements § 1065.670 NOX intake-air humidity and temperature corrections. See the standard-setting part to determine if you... 40 Protection of Environment 33 2011-07-01 2011-07-01 false NOX intake-air humidity...
40 CFR 1065.670 - NOX intake-air humidity and temperature corrections.
Code of Federal Regulations, 2012 CFR
2012-07-01
... (CONTINUED) AIR POLLUTION CONTROLS ENGINE-TESTING PROCEDURES Calculations and Data Requirements § 1065.670 NOX intake-air humidity and temperature corrections. See the standard-setting part to determine if you... 40 Protection of Environment 34 2012-07-01 2012-07-01 false NOX intake-air humidity...
30 CFR 75.341 - Direct-fired intake air heaters.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Direct-fired intake air heaters. 75.341 Section... air heaters. (a) If any system used to heat intake air malfunctions, the heaters affected shall switch off automatically. (b) Thermal overload devices shall protect the blower motor from overheating....
Variable oxygen/nitrogen enriched intake air system for internal combustion engine applications
Poola, Ramesh B.; Sekar, Ramanujam R.; Cole, Roger L.
1997-01-01
An air supply control system for selectively supplying ambient air, oxygen enriched air and nitrogen enriched air to an intake of an internal combustion engine includes an air mixing chamber that is in fluid communication with the air intake. At least a portion of the ambient air flowing to the mixing chamber is selectively diverted through a secondary path that includes a selectively permeable air separating membrane device due a differential pressure established across the air separating membrane. The permeable membrane device separates a portion of the nitrogen in the ambient air so that oxygen enriched air (permeate) and nitrogen enriched air (retentate) are produced. The oxygen enriched air and the nitrogen enriched air can be selectively supplied to the mixing chamber or expelled to atmosphere. Alternatively, a portion of the nitrogen enriched air can be supplied through another control valve to a monatomic-nitrogen plasma generator device so that atomic nitrogen produced from the nitrogen enriched air can be then injected into the exhaust of the engine. The oxygen enriched air or the nitrogen enriched air becomes mixed with the ambient air in the mixing chamber and then the mixed air is supplied to the intake of the engine. As a result, the air being supplied to the intake of the engine can be regulated with respect to the concentration of oxygen and/or nitrogen.
Effect of Intake Air Filter Condition on Vehicle Fuel Economy
Norman, Kevin M; Huff, Shean P; West, Brian H
2009-02-01
The U.S. Department of Energy (DOE) Office of Energy Efficiency and Renewable Energy and the U.S. Environmental Protection Agency (EPA) jointly maintain a fuel economy website (www.fueleconomy.gov), which helps fulfill their responsibility under the Energy Policy Act of 1992 to provide accurate fuel economy information [in miles per gallon (mpg)] to consumers. The site provides information on EPA fuel economy ratings for passenger cars and light trucks from 1985 to the present and other relevant information related to energy use such as alternative fuels and driving and vehicle maintenance tips. In recent years, fluctuations in the price of crude oil and corresponding fluctuations in the price of gasoline and diesel fuels have renewed interest in vehicle fuel economy in the United States. (User sessions on the fuel economy website exceeded 20 million in 2008 compared to less than 5 million in 2004 and less than 1 million in 2001.) As a result of this renewed interest and the age of some of the references cited in the tips section of the website, DOE authorized the Oak Ridge National Laboratory (ORNL) Fuels, Engines, and Emissions Research Center (FEERC) to initiate studies to validate and improve these tips. This report documents a study aimed specifically at the effect of engine air filter condition on fuel economy. The goal of this study was to explore the effects of a clogged air filter on the fuel economy of vehicles operating over prescribed test cycles. Three newer vehicles (a 2007 Buick Lucerne, a 2006 Dodge Charger, and a 2003 Toyota Camry) and an older carbureted vehicle were tested. Results show that clogging the air filter has no significant effect on the fuel economy of the newer vehicles (all fuel injected with closed-loop control and one equipped with MDS). The engine control systems were able to maintain the desired AFR regardless of intake restrictions, and therefore fuel consumption was not increased. The carbureted engine did show a decrease in
System and method for conditioning intake air to an internal combustion engine
Sellnau, Mark C.
2015-08-04
A system for conditioning the intake air to an internal combustion engine includes a means to boost the pressure of the intake air to the engine and a liquid cooled charge air cooler disposed between the output of the boost means and the charge air intake of the engine. Valves in the coolant system can be actuated so as to define a first configuration in which engine cooling is performed by coolant circulating in a first coolant loop at one temperature, and charge air cooling is performed by coolant flowing in a second coolant loop at a lower temperature. The valves can be actuated so as to define a second configuration in which coolant that has flowed through the engine can be routed through the charge air cooler. The temperature of intake air to the engine can be controlled over a wide range of engine operation.
Method and apparatus for reducing cold-phase emissions by utilizing oxygen-enriched intake air
Poola, Ramesh B.; Sekar, Ramanujam R.; Stork, Kevin C.
1997-01-01
An oxygen-enriched air intake control system for an internal combustion engine includes air directing apparatus to control the air flow into the intake of the engine. During normal operation of the engine, ambient air flowing from an air filter of the engine flows through the air directing apparatus into the intake of the engine. In order to decrease the amount of carbon monoxide (CO) and hydrocarbon (HC) emissions that tend to be produced by the engine during a short period of time after the engine is started, the air directing apparatus diverts for a short period of time following the start up of the engine at least a portion of the ambient air from the air filter through a secondary path. The secondary path includes a selectively permeable membrane through which the diverted portion of the ambient air flows. The selectively permeable membrane separates nitrogen and oxygen from the diverted air so that oxygen enriched air containing from about 23% to 25% oxygen by volume is supplied to the intake of the engine.
Prototype Systems for Measuring Outdoor Air Intake Rates in Rooftop Air Handlers
Fisk, William J.; Chan, Wanyu R.; Hotchi, Toshifumi
2015-01-01
The widespread absence of systems for real-time measurement and feedback control, of minimum outdoor air intake rates in HVAC systems contributes to the poor control of ventilation rates in commercial buildings. Ventilation rates affect building energy consumption and influence occupant health. The project designed fabricated and tested four prototypes of systems for measuring rates of outdoor air intake into roof top air handlers. All prototypes met the ±20% accuracy target at low wind speeds, with all prototypes accurate within approximately ±10% after application of calibration equations. One prototype met the accuracy target without a calibration. With two of four prototype measurement systems, there was no evidence that wind speed or direction affected accuracy; however, winds speeds were generally below usually 3.5 m s^{-1} (12.6 km h^{-1}) and further testing is desirable. The airflow resistance of the prototypes was generally less than 35 Pa at maximum RTU air flow rates. A pressure drop of this magnitude will increase fan energy consumption by approximately 4%. The project did not have resources necessary to estimate costs of mass produced systems. The retail cost of components and materials used to construct prototypes ranged from approximately $1,200 to $1,700. The test data indicate that the basic designs developed in this project, particularly the designs of two of the prototypes, have considerable merit. Further design refinement, testing, and cost analysis would be necessary to fully assess commercial potential. The designs and test results will be communicated to the HVAC manufacturing community.
Fabrication of a smart air intake structure using shape memory alloy wire embedded composite
NASA Astrophysics Data System (ADS)
Jung, Beom-Seok; Kim, Min-Saeng; Kim, Ji-Soo; Kim, Yun-Mi; Lee, Woo-Yong; Ahn, Sung-Hoon
2010-05-01
Shape memory alloys (SMAs) have been actively studied in many fields utilizing their high energy density. Applying SMA wire-embedded composite to aerospace structures, such as air intake of jet engines and guided missiles, is attracting significant attention because it could generate a comparatively large actuating force. In this research, a scaled structure of SMA wire-embedded composite was fabricated for the air intake of aircraft. The structure was composed of several prestrained Nitinol (Ni-Ti) SMA wires embedded in ∩-shape glass fabric reinforced plastic (GFRP), and it was cured at room temperature for 72 h. The SMA wire-embedded GFRP could be actuated by applying electric current through the embedded SMA wires. The activation angle generated from the composite structure was large enough to make a smart air intake structure.
NASA Technical Reports Server (NTRS)
Roelke, R. J.; Haas, J. E.
1981-01-01
The aerodynamic performance of the inlet manifold and stator assembly of the compressor drive turbine was experimentally determined with cold air as the working fluid. The investigation included measurements of mass flow and stator-exit fluid torque as well as radial surveys of total pressure and flow angle at the stator inlet and annulus surveys of total pressure and flow angle at the stator exit. The stator-exit aftermixed flow conditions and overall stator efficiency were obtained and compared with their design values and the experimental results from three other stators. In addition, an analysis was made to determine the constituent aerodynamic losses that made up the stator kinetic energy loss.
The effects of oxygen-enriched intake air on FFV exhaust emissions using M85
Poola, R.B.; Sekar, R.; Ng, H.K.; Baudino, J.H.; Colucci, C.P.
1996-05-01
This paper presents results of emission tests of a flexible fuel vehicle (FFV) powered by an SI engine, fueled by M85 (methanol), and supplied with oxygen-enriched intake air containing 21, 23, and 25 vol% O2. Engine-out total hydrocarbons (THCs) and unburned methanol were considerably reduced in the entire FTP cycle when the O2 content of the intake air was either 23 or 25%. However, CO emissions did not vary much, and NOx emissions were higher. HCHO emissions were reduced by 53% in bag 1, 84% in bag 2, and 59% in bag 3 of the FTP cycle with 25% oxygen-enriched intake air. During cold-phase FTP,reductions of 42% in THCs, 40% in unburned methanol, 60% in nonmethane hydrocarbons, and 45% in nonmethane organic gases (NMOGs) were observed with 25% enriched air; NO{sub x} emissions increased by 78%. Converter-out emissions were also reduced with enriched air but to a lesser degree. FFVs operating on M85 that use 25% enriched air during only the initial 127 s of cold-phase FTP or that use 23 or 25% enriched air during only cold-phase FTP can meet the reactivity-adjusted NMOG, CO, NO{sub x}, and HCHO emission standards of the transitional low-emission vehicle.
Schechter, M.M.; Simko, A.O.
1980-12-23
An internal combustion engine has a fuel injection pump and an air/fuel ratio controller. The controller has a lever that is connected to the pump lever. An aneroid moves the controller lever as a function of changes in intake manifold vacuum to maintain a constant air/fuel ratio to the mixture charge. A fuel enrichment linkage is provided that modifies the movement of the fuel flow control lever by the aneroid in response to changes in manifold gas temperature levels and exhaust gas recirculation to maintain the constant air/fuel ratio. A manual override is provided to obtain a richer air/fuel ratio for maximum acceleration.
Experimental Studies of Active and Passive Flow Control Techniques Applied in a Twin Air-Intake
Joshi, Shrey; Jindal, Aman; Maurya, Shivam P.; Jain, Anuj
2013-01-01
The flow control in twin air-intakes is necessary to improve the performance characteristics, since the flow traveling through curved and diffused paths becomes complex, especially after merging. The paper presents a comparison between two well-known techniques of flow control: active and passive. It presents an effective design of a vortex generator jet (VGJ) and a vane-type passive vortex generator (VG) and uses them in twin air-intake duct in different combinations to establish their effectiveness in improving the performance characteristics. The VGJ is designed to insert flow from side wall at pitch angle of 90 degrees and 45 degrees. Corotating (parallel) and counterrotating (V-shape) are the configuration of vane type VG. It is observed that VGJ has the potential to change the flow pattern drastically as compared to vane-type VG. While the VGJ is directed perpendicular to the side walls of the air-intake at a pitch angle of 90 degree, static pressure recovery is increased by 7.8% and total pressure loss is reduced by 40.7%, which is the best among all other cases tested for VGJ. For bigger-sized VG attached to the side walls of the air-intake, static pressure recovery is increased by 5.3%, but total pressure loss is reduced by only 4.5% as compared to all other cases of VG. PMID:23935422
CFD simulation analysis and research based on engine air intake system of automotive
NASA Astrophysics Data System (ADS)
Liu, Xia; Yan, Hua Jin; Tian, Ning; Zhao, GuoQi
2017-01-01
Traditional method for the design of automotive engine intake system has many issues, such as period, high costs, energy consumption and so on. The paper utilized one kind of CFD numerical simulation analysis based on the basic theory of CFD. It use the three-dimensional geometry modal grid, computational modeling and model analysis to identify the turbulence due to unreasonable design of air filter inlet position, and then through the test to verify the correctness of the results of CFD calculations. It provide a theoretical basis for the intake system structural optimization.
Preliminary Design of the Low Speed Propulsion Air Intake of the LAPCAT-MR2 Aircraft
NASA Astrophysics Data System (ADS)
Meerts, C.; Steelant, J.; Hendrick, P.
2011-08-01
A supersonic air intake has been designed for the low speed propulsion system of the LAPCAT-MR2 aircraft. Development has been based on the XB-70 aircraft air intake which achieves extremely high performances over a wide operation range through the combined use of variable geometry and porous wall suction for boundary layer control. Design of the LAPCAT-MR2 intake has been operated through CFD simulations using DLR TAU-Code (perfect gas model - Menter SST turbulence model). First, a new boundary condition has been validated into the DLR TAU-Code (perfect gas model) for porous wall suction modelling. Standard test cases have shown surprisingly good agreement with both theoretical predictions and experimental results. Based upon this validation, XB-70 air intake performances have been assessed through CFD simulations over the subsonic, transonic and supersonic operation regions and compared to available flight data. A new simulation strategy was deployed avoiding numerical instabilities when initiating the flow in both transonic and supersonic operation modes. First, the flow must be initiated with a far field Mach number higher than the target flight Mach number. Additionally, the inlet backpressure may only be increased to its target value once the oblique shock pattern downstream the intake compression ramps is converged. Simulations using that strategy have shown excellent agreement with in-flight measurements for both total pressure recovery ratio and variable geometry schedule prediction. The demarcation between stable and unstable operation could be well reproduced. Finally, a modified version of the XB-70 air intake has been integrated in the elliptical intake on the LAPCAT vehicle. Operation of this intake in the LAPCAT-MR2 environment is under evaluation using the same simulation strategy as the one developed for the XB-70. Performances are assessed at several key operation points to assess viability of this design. This information will allow in a next
Effect of Intake Air Filter Condition on Light-Duty Gasoline Vehicles
Thomas, John F; Huff, Shean P; West, Brian H; Norman, Kevin M
2012-01-01
Proper maintenance can help vehicles perform as designed, positively affecting fuel economy, emissions, and the overall drivability. This effort investigates the effect of one maintenance factor, intake air filter replacement, with primary focus on vehicle fuel economy, but also examining emissions and performance. Older studies, dealing with carbureted gasoline vehicles, have indicated that replacing a clogged or dirty air filter can improve vehicle fuel economy and conversely that a dirty air filter can be significantly detrimental to fuel economy. The effect of clogged air filters on the fuel economy, acceleration and emissions of five gasoline fueled vehicles is examined. Four of these were modern vehicles, featuring closed-loop control and ranging in model year from 2003 to 2007. Three vehicles were powered by naturally aspirated, port fuel injection (PFI) engines of differing size and cylinder configuration: an inline 4, a V6 and a V8. A turbocharged inline 4-cylinder gasoline direct injection (GDI) engine powered vehicle was the fourth modern gasoline vehicle tested. A vintage 1972 vehicle equipped with a carburetor (open-loop control) was also examined. Results reveal insignificant fuel economy and emissions sensitivity of modern vehicles to air filter condition, but measureable effects on the 1972 vehicle. All vehicles experienced a measured acceleration performance penalty with clogged intake air filters.
NASA Astrophysics Data System (ADS)
Begue, C.; Periaux, J.; Perrier, P.; Pouletty, C.
1985-11-01
A self-adaptive finite-element method, coupled to a homogenization model of turbulence, is presented for the numerical simulation of unsteady turbulent flow of viscous fluids in air intakes. The nonlinear subproblem due to the convection is solved by an iterative algorithm, and the linear Stokes subproblem due to the diffusion is solved by a Hood-Taylor type iterative algorithm. An efficient and precise minielement approximation is used, and the adaptive mesh procedure is automatic in the calculation, using the physical criteria of rotation and divergence to determine the submeshing zones. The numerical method is demonstrated for the example of three-dimensional laminar flow around and in air intake at a Reynolds number of 200.
A Method for Reducing the Temperature of Exhaust Manifolds
NASA Technical Reports Server (NTRS)
Schey, Oscar W; Young, Alfred W
1931-01-01
This report describes tests conducted at the Langley Memorial Aeronautical Laboratory on an "air-inducting" exhaust manifold for aircraft engines. The exhaust gases from each cylinder port are discharged into the throat of an exhaust pipe which has a frontal bellmouth. Cooling air is drawn into the pipe, where it surrounds and mixes with the exhaust gases. Temperatures of the manifold shell and of the exhaust gases were obtained in flight for both a conventional manifold and the air-inducting manifold. The air-inducting manifold was installed on an engine which was placed on a test stand. Different fuels were sprayed on and into the manifold to determine whether the use of this manifold reduced the fire hazard. The flight tests showed reductions in manifold temperatures of several hundred degrees, to values below the ignition point of aviation gasoline. On the test stand when the engine was run at idling speeds fuels sprayed into the manifold ignited. It is believed that at low engine speeds the fuel remained in the manifold long enough to become thoroughly heated, and was then ignited by the exhaust gas which had not mixed with cooling air. The use of the air-inducting exhaust manifold must reduce the fire hazard by virtue of its lower operating temperature, but it is not a completely satisfactory solution of the problem.
Utilizing intake-air oxygen-enrichment technology to reduce cold- phase emissions
Poola, R.B.; Ng, H.K.; Sekar, R.R.; Baudino, J.H.; Colucci, C.P.
1995-12-31
Oxygen-enriched combustion is a proven, serious considered technique to reduce exhaust hydrocarbons (HC) and carbon monoxide (CO) emissions from automotive gasoline engines. This paper presents the cold-phase emissions reduction results of using oxygen-enriched intake air containing about 23% and 25% oxygen (by volume) in a vehicle powered by a spark-ignition (SI) engine. Both engineout and converter-out emissions data were collected by following the standard federal test procedure (FTP). Converter-out emissions data were also obtained employing the US Environmental Protection Agency`s (EPA`s) ``Off-Cycle`` test. Test results indicate that the engine-out CO emissions during the cold phase (bag 1) were reduced by about 46 and 50%, and HC by about 33 and 43%, using nominal 23 and 25% oxygen-enriched air compared to ambient air (21% oxygen by volume), respectively. However, the corresponding oxides of nitrogen (NO{sub x}) emissions were increased by about 56 and 79%, respectively. Time-resolved emissions data indicate that both HC and CO emissions were reduced considerably during the initial 127 s of the cold-phase FTP, without any increase in NO, emissions in the first 25 s. Hydrocarbon speciation results indicate that all major toxic pollutants, including ozone-forming specific reactivity factors, such as maximum incremental reactivity (NUR) and maximum ozone incremental reactivity (MOIR), were reduced considerably with oxygen-enrichment. Based on these results, it seems that using oxygen-enriched intake air during the cold-phase FTP could potentially reduce HC and CO emissions sufficiently to meet future emissions standards. Off-cycle, converter-out, weighted-average emissions results show that both HC and CO emissions were reduced by about 60 to 75% with 23 or 25% oxygen-enrichment, but the accompanying NO{sub x}, emissions were much higher than those with the ambient air.
Mendler, Edward Charles
2005-02-01
The volumetric efficiency and power of internal combustion engines is improved with an intake port having an intake nozzle, a venturi, and a surge chamber. The venturi is located almost halfway upstream the intake port between the intake valves and the intake plenum enabling the venturi throat diameter to be exceptionally small for providing an exceptionally high ram velocity and an exceptionally long and in turn high efficiency diffuser flowing into the surge chamber. The intake port includes an exceptionally large surge chamber volume for blow down of the intake air into the working cylinder of the engine.
NASA Astrophysics Data System (ADS)
Pilca, Mihaela
2016-09-01
Vaisman manifolds are strongly related to Kähler and Sasaki geometry. In this paper we introduce toric Vaisman structures and show that this relationship still holds in the toric context. It is known that the so-called minimal covering of a Vaisman manifold is the Riemannian cone over a Sasaki manifold. We show that if a complete Vaisman manifold is toric, then the associated Sasaki manifold is also toric. Conversely, a toric complete Sasaki manifold, whose Kähler cone is equipped with an appropriate compatible action, gives rise to a toric Vaisman manifold. In the special case of a strongly regular compact Vaisman manifold, we show that it is toric if and only if the corresponding Kähler quotient is toric.
NASA Astrophysics Data System (ADS)
Renteln, Paul
2013-11-01
Preface; 1. Linear algebra; 2. Multilinear algebra; 3. Differentiation on manifolds; 4. Homotopy and de Rham cohomology; 5. Elementary homology theory; 6. Integration on manifolds; 7. Vector bundles; 8. Geometric manifolds; 9. The degree of a smooth map; Appendixes; References; Index.
Geologic mapping of the air intake shaft at the Waste Isolation Pilot Plant
Holt, R.M.; Powers, D.W. )
1990-12-01
The air intake shaft (AS) was geologically mapped from the surface to the Waste Isolation Pilot Plant (WIPP) facility horizon. The entire shaft section including the Mescalero Caliche, Gatuna Formation, Santa Rosa Formation, Dewey Lake Redbeds, Rustler Formation, and Salado Formation was geologically described. The air intake shaft (AS) at the Waste Isolation Pilot Plant (WIPP) site was constructed to provide a pathway for fresh air into the underground repository and maintain the desired pressure balances for proper underground ventilation. It was up-reamed to minimize construction-related damage to the wall rock. The upper portion of the shaft was lined with slip-formed concrete, while the lower part of the shaft, from approximately 903 ft below top of concrete at the surface, was unlined. As part of WIPP site characterization activities, the AS was geologically mapped. The shaft construction method, up-reaming, created a nearly ideal surface for geologic description. Small-scale textures usually best seen on slabbed core were easily distinguished on the shaft wall, while larger scale textures not generally revealed in core were well displayed. During the mapping, newly recognized textures were interpreted in order to refine depositional and post-depositional models of the units mapped. The objectives of the geologic mapping were to: (1) provide confirmation and documentation of strata overlying the WIPP facility horizon; (2) provide detailed information of the geologic conditions in strata critical to repository sealing and operations; (3) provide technical basis for field adjustments and modification of key and aquifer seal design, based upon the observed geology; (4) provide geological data for the selection of instrument borehole locations; (5) and characterize the geology at geomechanical instrument locations to assist in data interpretation. 40 refs., 27 figs., 1 tab.
Fisk, William; Sullivan, Douglas; Cohen, Sebastian; Han, Hwataik
2008-10-01
Practical and accurate technologies are needed for continuously measuring and controlling outdoor air (OA) intake rates in commercial building heating, ventilating, and air conditioning (HVAC) systems. This project evaluated two new measurement approaches. Laboratory experiments determined that OA flow rates were measurable with errors generally less than 10percent using electronic air velocity probes installed between OA intake louver blades or at the outlet face of louvers. High accuracy was maintained with OA flow rates as low as 15percent of the maximum for the louvers. Thus, with this measurement approach HVAC systems do not need separate OA intakes for minimum OA supply. System calibration parameters are required for each unique combination of louver type and velocity sensor location but calibrations are not necessary for each system installation. The research also determined that the accuracy of measuring OA flow rates with velocity probes located in the duct downstream of the intake louver was not improved by installing honeycomb airflow straighteners upstream of the probes. Errors varied with type of upstream louver, were as high as 100percent, and were often greater than 25percent. In conclusion, use of electronic air velocity probes between the blades of OA intake louvers or at the outlet face of louvers is a highly promising means of accurately measuring rates of OA flow into HVAC systems. The use of electronic velocity probes downstream of airflow straighteners is less promising, at least with the relatively small OA HVAC inlet systems employed in this research.
Reif, R H; Andrews, D W
1995-06-01
Monitoring workers and work areas at the Department of Energy Uranium Mill Tailings Remedial Action Project sites is complex because all radionuclides in the 238U and 235U decay chains may be present in an airborne uranium mill tailings matrix. Previous monitoring practices involved isotopic analysis of the air filter to determine the activity of each radionuclide of concern and comparing the results to the specified derived air concentration. The annual limit on intake and derived air concentration values have been derived here for the uranium mill tailings matrix to simplify the procedure for evaluation of air monitoring results and assessment of the need for individual monitoring. Implementation of the derived air concentration for uranium mill tailings involves analyzing air samples for long-lived gross alpha activity and comparing the activity concentration to the derived air concentration. Health physics decisions regarding assessment of airborne concentrations is more cost-effective because isotopic analysis of air samples is not necessary.
Ramsdell, J.V.
1991-03-01
This report presents the NRC staff with a tool for assessing the potential effects of accidental releases of radioactive materials and toxic substances on habitability of nuclear facility control rooms. The tool is a computer code that estimates concentrations at nuclear facility control room air intakes given information about the release and the environmental conditions. The name of the computer code is EXTRAN. EXTRAN combines procedures for estimating the amount of airborne material, a Gaussian puff dispersion model, and the most recent algorithms for estimating diffusion coefficients in building wakes. It is a modular computer code, written in FORTRAN-77, that runs on personal computers. It uses a math coprocessor, if present, but does not require one. Code output may be directed to a printer or disk files. 25 refs., 8 figs., 4 tabs.
Flight-determined characteristics of an air intake system on an F-111A airplane
NASA Technical Reports Server (NTRS)
Hughes, D. L.; Johnson, H. J.
1972-01-01
Flow phenomena of the F-111A air intake system were investigated over a large range of Mach number, altitude, and angle of attack. Boundary-layer variations are shown for the fuselage splitter plate and inlet entrance stations. Inlet performance is shown in terms of pressure recovery, airflow, mass-flow ratio, turbulence factor, distortion factor, and power spectral density. The fuselage boundary layer was found to be not completely removed from the upper portion of the splitter plate at all Mach numbers investigated. Inlet boundary-layer ingestion started at approximately Mach 1.6 near the translating spike and cone. Pressure-recovery distribution at the compressor face showed increasing distortion with increasing angle of attack and increasing Mach number. The time-averaged distortion-factor value approached 1300, which is near the distortion tolerance of the engine at Mach numbers above 2.1.
NASA Astrophysics Data System (ADS)
Borok, S.; Goldfarb, I.; Gol'dshtein, V.
2009-05-01
The paper concerns intrinsic low-dimensional manifold (ILDM) method suggested in [Maas U, Pope SB. Simplifying chemical kinetics: intrinsic low-dimensional manifolds in composition space, combustion and flame 1992;88:239-64] for dimension reduction of models describing kinetic processes. It has been shown in a number of publications [Goldfarb I, Gol'dshtein V, Maas U. Comparative analysis of two asymptotic approaches based on integral manifolds. IMA J Appl Math 2004;69:353-74; Kaper HG, Kaper TJ, Asymptotic analysis of two reduction methods for systems of chemical reactions. Phys D 2002;165(1-2):66-93; Rhodes C, Morari M, Wiggins S. Identification of the low order manifolds: validating the algorithm of Maas and Pope. Chaos 1999;9(1):108-23] that the ILDM-method works successfully and the intrinsic low-dimensional manifolds belong to a small vicinity of invariant slow manifolds. The ILDM-method has a number of disadvantages. One of them is appearance of so-called "ghost"-manifolds, which do not have connection to the system dynamics [Borok S, Goldfarb I, Gol'dshtein V. "Ghost" ILDM - manifolds and their discrimination. In: Twentieth Annual Symposium of the Israel Section of the Combustion Institute, Beer-Sheva, Israel; 2004. p. 55-7; Borok S, Goldfarb I, Gol'dshtein V. About non-coincidence of invariant manifolds and intrinsic low-dimensional manifolds (ILDM). CNSNS 2008;71:1029-38; Borok S, Goldfarb I, Gol'dshtein V, Maas U. In: Gorban AN, Kazantzis N, Kevrekidis YG, Ottinger HC, Theodoropoulos C, editors. "Ghost" ILDM-manifolds and their identification: model reduction and coarse-graining approaches for multiscale phenomena. Berlin-Heidelberg-New York: Springer; 2006. p. 55-80; Borok S, Goldfarb I, Gol'dshtein V. On a modified version of ILDM method and its asymptotic analysis. IJPAM 2008; 44(1): 125-50; Bykov V, Goldfarb I, Gol'dshtein V, Maas U. On a modified version of ILDM approach: asymptotic analysis based on integral manifolds. IMA J Appl Math 2006
Hildebrand, Richard J.; Wozniak, John J.
2001-01-01
A compressed gas storage cell interconnecting manifold including a thermally activated pressure relief device, a manual safety shut-off valve, and a port for connecting the compressed gas storage cells to a motor vehicle power source and to a refueling adapter. The manifold is mechanically and pneumatically connected to a compressed gas storage cell by a bolt including a gas passage therein.
Zhang, Zhenyue; Wang, Jing; Zha, Hongyuan
2012-02-01
Manifold learning algorithms seek to find a low-dimensional parameterization of high-dimensional data. They heavily rely on the notion of what can be considered as local, how accurately the manifold can be approximated locally, and, last but not least, how the local structures can be patched together to produce the global parameterization. In this paper, we develop algorithms that address two key issues in manifold learning: 1) the adaptive selection of the local neighborhood sizes when imposing a connectivity structure on the given set of high-dimensional data points and 2) the adaptive bias reduction in the local low-dimensional embedding by accounting for the variations in the curvature of the manifold as well as its interplay with the sampling density of the data set. We demonstrate the effectiveness of our methods for improving the performance of manifold learning algorithms using both synthetic and real-world data sets.
Ensemble manifold regularization.
Geng, Bo; Tao, Dacheng; Xu, Chao; Yang, Linjun; Hua, Xian-Sheng
2012-06-01
We propose an automatic approximation of the intrinsic manifold for general semi-supervised learning (SSL) problems. Unfortunately, it is not trivial to define an optimization function to obtain optimal hyperparameters. Usually, cross validation is applied, but it does not necessarily scale up. Other problems derive from the suboptimality incurred by discrete grid search and the overfitting. Therefore, we develop an ensemble manifold regularization (EMR) framework to approximate the intrinsic manifold by combining several initial guesses. Algorithmically, we designed EMR carefully so it 1) learns both the composite manifold and the semi-supervised learner jointly, 2) is fully automatic for learning the intrinsic manifold hyperparameters implicitly, 3) is conditionally optimal for intrinsic manifold approximation under a mild and reasonable assumption, and 4) is scalable for a large number of candidate manifold hyperparameters, from both time and space perspectives. Furthermore, we prove the convergence property of EMR to the deterministic matrix at rate root-n. Extensive experiments over both synthetic and real data sets demonstrate the effectiveness of the proposed framework.
Reduction of polysymplectic manifolds
NASA Astrophysics Data System (ADS)
Marrero, Juan Carlos; Román-Roy, Narciso; Salgado, Modesto; Vilariño, Silvia
2015-02-01
The aim of this paper is to generalize the classical Marsden-Weinstein reduction procedure for symplectic manifolds to polysymplectic manifolds in order to obtain quotient manifolds which inherit the polysymplectic structure. This generalization allows us to reduce polysymplectic Hamiltonian systems with symmetries, such as those appearing in certain kinds of classical field theories. As an application of this technique, an analogue to the Kirillov-Kostant-Souriau theorem for polysymplectic manifolds is obtained and some other mathematical examples are also analyzed. Our procedure corrects some mistakes and inaccuracies in previous papers (Günther 1987 J. Differ. Geom. 25 23-53 Munteanu et al 2004 J. Math. Phys. 45 1730-51) on this subject.
Hierarchical manifold learning.
Bhatia, Kanwal K; Rao, Anil; Price, Anthony N; Wolz, Robin; Hajnal, Jo; Rueckert, Daniel
2012-01-01
We present a novel method of hierarchical manifold learning which aims to automatically discover regional variations within images. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate its utility in two very different settings: (1) to learn the regional correlations in motion within a sequence of time-resolved images of the thoracic cavity; (2) to find discriminative regions of 3D brain images in the classification of neurodegenerative disease,
Air-Quality Impacts and Intake Fraction of PM2.5 during the 2013 Rim Megafire.
Navarro, Kathleen M; Cisneros, Ricardo; O'Neill, Susan M; Schweizer, Don; Larkin, Narasimhan K; Balmes, John R
2016-11-01
The 2013 Rim Fire was the third largest wildfire in California history and burned 257 314 acres in the Sierra Nevada Mountains. We evaluated air-quality impacts of PM2.5 from smoke from the Rim Fire on receptor areas in California and Nevada. We employed two approaches to examine the air-quality impacts: (1) an evaluation of PM2.5 concentration data collected by temporary and permanent air-monitoring sites and (2) an estimation of intake fraction (iF) of PM2.5 from smoke. The Rim Fire impacted locations in the central Sierra nearest to the fire and extended to the northern Sierra Nevada Mountains of California and Nevada monitoring sites. Daily 24-h average PM2.5 concentrations measured at 22 air monitors had an average concentration of 20 μg/m(3) and ranged from 0 to 450 μg/m(3). The iF for PM2.5 from smoke during the active fire period was 7.4 per million, which is slightly higher than representative iF values for PM2.5 in rural areas and much lower than for urban areas. This study is a unique application of intake fraction to examine emissions-to-exposure for wildfires and emphasizes that air-quality impacts are not only localized to communities near large fires but can extend long distances and affect larger urban areas.
Reif, R.H.; Andrews, D.W.
1995-06-01
Monitoring workers and work areas at the Department of Energy Uranium Mill Tailings Remedial Action Project sites is complex because all radionuclides in the {sup 238}U and {sup 235}U decay chains may be present in an airborne uranium mill tillings matrix. Previous monitoring practices involved isotopic analysis of the air filter to determine the activity of each radionuclide of concern and comparing the results to the specified derived air concentration. The annual limit on intake and derived air concentration values have been derived here for the uranium mill tailings matrix to simplify the procedure for evaluation of air monitoring results and assessment of the need for individual monitoring. Implementation of the derived air concentration for uranium mill tailings involves analyzing air samples for long-lived gross alpha activity and comparing the activity concentration to the derived air concentration. Health physics decisions regarding assessment of airborne concentrations is more cost-effective because isotopic analysis of air samples is not necessary. 12 refs., 2 tabs.
40 CFR 1066.615 - NOX intake-air humidity correction.
Code of Federal Regulations, 2014 CFR
2014-07-01
... vapor pressure at the ambient dry bulb temperature. RH = relative humidity of ambient air M air = molar mass of air. p atmos = atmospheric pressure. ER28AP14.106 Where: x NOXdexh = measured dilute...
Potential benefits of oxygen-enriched intake air in a vehicle powered by a spark-ignition engine
NASA Astrophysics Data System (ADS)
Ng, H. K.; Sekar, R. R.
1994-04-01
A production vehicle powered by a spark-ignition engine (3.1-L Chevrolet Lumina, model year 1990) was tested. The test used oxygen-enriched intake air containing 25 and 28% oxygen by volume to determine (1) if the vehicle would run without difficulties and (2) if emissions benefits would result. Standard Federal Test Procedure (FTP) emissions test cycles were run satisfactorily. Test results of catalytic converter-out emissions (emissions out of the converter) showed that both carbon monoxide and hydrocarbons were reduced significantly in all three phases of the emissions test cycle. Test results of engine-out emissions (emissions straight out of the engine, with the converter removed) showed that carbon monoxide was significantly reduced in the cold phase. All emission test results were compared with those for normal air (21% oxygen). The catalytic converter also had an improved carbon monoxide conversion efficiency under the oxygen-enriched-air conditions. Detailed results of hydrocarbon speciation indicated large reductions in 1,3-butadiene, formaldehyde, acetaldehyde, and benzene from the engine with the oxygen-enriched air. Catalytic converter-out ozone was reduced by 60% with 25%-oxygen-content air. Although NO(x) emissions increased significantly, both for engine-out and catalytic converter-out emissions, we anticipate that they can be ameliorated in the near future with new control technologies. The automotive industry currently is developing exhaust-gas control technologies for an oxidizing environment; these technologies should reduce NO(x) emissions more efficiently in vehicles that use oxygen-enriched intake air. On the basis of estimates made from current data, several production vehicles that had low NO(x) emissions could meet the 2004 Tier 2 emissions standards with 25%-oxygen-content air.
Lin, Tong; Zha, Hongbin
2008-05-01
Recently, manifold learning has been widely exploited in pattern recognition, data analysis, and machine learning. This paper presents a novel framework, called Riemannian manifold learning (RML), based on the assumption that the input high-dimensional data lie on an intrinsically low-dimensional Riemannian manifold. The main idea is to formulate the dimensionality reduction problem as a classical problem in Riemannian geometry, i.e., how to construct coordinate charts for a given Riemannian manifold? We implement the Riemannian normal coordinate chart, which has been the most widely used in Riemannian geometry, for a set of unorganized data points. First, two input parameters (the neighborhood size k and the intrinsic dimension d) are estimated based on an efficient simplicial reconstruction of the underlying manifold. Then, the normal coordinates are computed to map the input high-dimensional data into a low-dimensional space. Experiments on synthetic data as well as real world images demonstrate that our algorithm can learn intrinsic geometric structures of the data, preserve radial geodesic distances, and yield regular embeddings.
Liu, Yang; Liu, Yan; Chan, Keith C C; Hua, Kien A
2014-12-01
In this brief, we present a novel supervised manifold learning framework dubbed hybrid manifold embedding (HyME). Unlike most of the existing supervised manifold learning algorithms that give linear explicit mapping functions, the HyME aims to provide a more general nonlinear explicit mapping function by performing a two-layer learning procedure. In the first layer, a new clustering strategy called geodesic clustering is proposed to divide the original data set into several subsets with minimum nonlinearity. In the second layer, a supervised dimensionality reduction scheme called locally conjugate discriminant projection is performed on each subset for maximizing the discriminant information and minimizing the dimension redundancy simultaneously in the reduced low-dimensional space. By integrating these two layers in a unified mapping function, a supervised manifold embedding framework is established to describe both global and local manifold structure as well as to preserve the discriminative ability in the learned subspace. Experiments on various data sets validate the effectiveness of the proposed method.
Manifold Learning by Graduated Optimization.
Gashler, M; Ventura, D; Martinez, T
2011-12-01
We present an algorithm for manifold learning called manifold sculpting , which utilizes graduated optimization to seek an accurate manifold embedding. An empirical analysis across a wide range of manifold problems indicates that manifold sculpting yields more accurate results than a number of existing algorithms, including Isomap, locally linear embedding (LLE), Hessian LLE (HLLE), and landmark maximum variance unfolding (L-MVU), and is significantly more efficient than HLLE and L-MVU. Manifold sculpting also has the ability to benefit from prior knowledge about expected results.
Manifold Regularized Reinforcement Learning.
Li, Hongliang; Liu, Derong; Wang, Ding
2017-01-27
This paper introduces a novel manifold regularized reinforcement learning scheme for continuous Markov decision processes. Smooth feature representations for value function approximation can be automatically learned using the unsupervised manifold regularization method. The learned features are data-driven, and can be adapted to the geometry of the state space. Furthermore, the scheme provides a direct basis representation extension for novel samples during policy learning and control. The performance of the proposed scheme is evaluated on two benchmark control tasks, i.e., the inverted pendulum and the energy storage problem. Simulation results illustrate the concepts of the proposed scheme and show that it can obtain excellent performance.
Djordjevic, Aleksandar
1983-12-27
A tool guide that makes possible the insertion of cleaning and/or inspection tools into a manifold pipe that will dislocate and extract the accumulated sediment in such manifold pipes. The tool guide basically comprises a right angled tube (or other angled tube as required) which can be inserted in a large tube and locked into a radially extending cross pipe by adjustable spacer rods and a spring-loaded cone, whereby appropriate cleaning tools can be inserted into to cross pipe for cleaning, inspection, etc.
Djordjevic, A.
1982-07-08
A tool guide that makes possible the insertion of cleaning and/or inspection tools into a manifold pipe that will dislocate and extract the accumulated sediment in such manifold pipes. The tool guide basically comprises a right angled tube (or other angled tube as required) which can be inserted in a large tube and locked into a radially extending cross pipe by adjustable spacer rods and a spring-loaded cone, whereby appropriate cleaning tools can be inserted into to cross pipe for cleaning, inspection, etc.
Djordjevic, A.
1983-12-27
A tool guide is described that makes possible the insertion of cleaning and/or inspection tools into a manifold pipe that will dislocate and extract the accumulated sediment in such manifold pipes. The tool guide basically comprises a right angled tube (or other angled tube as required) which can be inserted in a large tube and locked into a radially extending cross pipe by adjustable spacer rods and a spring-loaded cone, whereby appropriate cleaning tools can be inserted into the cross pipe for cleaning, inspection, etc. 3 figs.
Dual manifold heat pipe evaporator
Adkins, D.R.; Rawlinson, K.S.
1994-01-04
An improved evaporator section is described for a dual manifold heat pipe. Both the upper and lower manifolds can have surfaces exposed to the heat source which evaporate the working fluid. The tubes in the tube bank between the manifolds have openings in their lower extensions into the lower manifold to provide for the transport of evaporated working fluid from the lower manifold into the tubes and from there on into the upper manifold and on to the condenser portion of the heat pipe. A wick structure lining the inner walls of the evaporator tubes extends into both the upper and lower manifolds. At least some of the tubes also have overflow tubes contained within them to carry condensed working fluid from the upper manifold to pass to the lower without spilling down the inside walls of the tubes. 1 figure.
Dual manifold heat pipe evaporator
Adkins, Douglas R.; Rawlinson, K. Scott
1994-01-01
An improved evaporator section for a dual manifold heat pipe. Both the upper and lower manifolds can have surfaces exposed to the heat source which evaporate the working fluid. The tubes in the tube bank between the manifolds have openings in their lower extensions into the lower manifold to provide for the transport of evaporated working fluid from the lower manifold into the tubes and from there on into the upper manifold and on to the condenser portion of the heat pipe. A wick structure lining the inner walls of the evaporator tubes extends into both the upper and lower manifolds. At least some of the tubes also have overflow tubes contained within them to carry condensed working fluid from the upper manifold to pass to the lower without spilling down the inside walls of the tubes.
Microwave waveguide manifold and method
Staehlin, John H.
1987-12-01
A controllably electrically coupled, physically intersecting plural waveguide manifold assembly wherein the intersecting waveguide elements are fabricated in integral unitary relationship from a single piece of metal in order to avoid the inaccuracies and difficult-to-control fabrication steps associated with uniting separate waveguide elements into a unitary structure. An X-band aluminum airborne radar manifold example is disclosed, along with a fabrication sequence for the manifold and the electrical energy communicating apertures joining the manifold elements.
Eigenvalue pinching on spinc manifolds
NASA Astrophysics Data System (ADS)
Roos, Saskia
2017-02-01
We derive various pinching results for small Dirac eigenvalues using the classification of spinc and spin manifolds admitting nontrivial Killing spinors. For this, we introduce a notion of convergence for spinc manifolds which involves a general study on convergence of Riemannian manifolds with a principal S1-bundle. We also analyze the relation between the regularity of the Riemannian metric and the regularity of the curvature of the associated principal S1-bundle on spinc manifolds with Killing spinors.
Microwave waveguide manifold and method
Staehlin, John H.
1987-01-01
A controllably electrically coupled, physically intersecting plural waveguide manifold assembly wherein the intersecting waveguide elements are fabricated in integral unitary relationship from a single piece of metal in order to avoid the inaccuracies and difficult-to-control fabrication steps associated with uniting separate waveguide elements into a unitary structure. An X-band aluminum airborne radar manifold example is disclosed, along with a fabrication sequence for the manifold and the electrical energy communicating apertures joining the manifold elements.
Partially integrated exhaust manifold
Hayman, Alan W; Baker, Rodney E
2015-01-20
A partially integrated manifold assembly is disclosed which improves performance, reduces cost and provides efficient packaging of engine components. The partially integrated manifold assembly includes a first leg extending from a first port and terminating at a mounting flange for an exhaust gas control valve. Multiple additional legs (depending on the total number of cylinders) are integrally formed with the cylinder head assembly and extend from the ports of the associated cylinder and terminate at an exit port flange. These additional legs are longer than the first leg such that the exit port flange is spaced apart from the mounting flange. This configuration provides increased packaging space adjacent the first leg for any valving that may be required to control the direction and destination of exhaust flow in recirculation to an EGR valve or downstream to a catalytic converter.
Lazure, Louis; Saathoff, Pat; Stathopoulos, Ted
2002-02-01
The establishment of a safe distance between sources of pollution and air intakes is based on a complex exercise that should take into account several wind, physical, and topographical factors. To estimate the maximum concentrations of the pollutants as a function of the distance from the emission source, some heating, ventilation, and air conditioning (HVAC) system designers use the atmospheric dispersion models suggested by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). Two of these models, the Halitsky and Wilson-Chui-Lamb models, have been developed and evaluated mainly with laboratory data. There have been relatively few evaluations with full-scale field data. The objective of this study, carried out on a building in downtown Montreal, Quebec, Canada, was to compare the measured concentrations of a tracer gas emitted by an exhaust stack with those predicted by these models. The results indicate that the Halitsky model gives lower than actual dilution, while the Wilson-Chui-Lamb model generally gives acceptable estimates, with occasional over-estimations of the dilution.
Apte, Joshua S; Bombrun, Emilie; Marshall, Julian D; Nazaroff, William W
2012-03-20
We model intraurban intake fraction (iF) values for distributed ground-level emissions in all 3646 global cities with more than 100,000 inhabitants, encompassing a total population of 2.0 billion. For conserved primary pollutants, population-weighted median, mean, and interquartile range iF values are 26, 39, and 14-52 ppm, respectively, where 1 ppm signifies 1 g inhaled/t emitted. The global mean urban iF reported here is roughly twice as large as previous estimates for cities in the United States and Europe. Intake fractions vary among cities owing to differences in population size, population density, and meteorology. Sorting by size, population-weighted mean iF values are 65, 35, and 15 ppm, respectively, for cities with populations larger than 3, 0.6-3, and 0.1-0.6 million. The 20 worldwide megacities (each >10 million people) have a population-weighted mean iF of 83 ppm. Mean intraurban iF values are greatest in Asia and lowest in land-rich high-income regions. Country-average iF values vary by a factor of 3 among the 10 nations with the largest urban populations.
NASA Astrophysics Data System (ADS)
Oxley, Mark E.; Schubert, Christine M.; Thorsen, Steven N.
2010-04-01
A Classification system such as an Automatic Target Recognition (ATR) system with N possible output labels (or decisions) will have N(N-1) possible errors. The Receiver Operating Characteristic (ROC) manifold was created to quantify all of these errors. Finite truth data will produce an approximation to a ROC manifold. How well does the approximate ROC manifold approximate the TRUE ROC manifold? Several metrics exist that quantify the approximation ability, but researchers really wish to quantify the confidence in the approximate ROC manifold. This paper will review different confidence definitions for ROC curves and will derive an expression for confidence of a ROC manifold. The foundation of the confidence expression is based upon the Chebychev inequality..
NASA Astrophysics Data System (ADS)
Ejiri, Arata; Sasaki, Jun; Kinoshita, Yusuke; Fujimoto, Junya; Maruyama, Tsugito; Shimotani, Keiji
For the purpose of contributing to global environment protection, several research studies have been conducted involving clean-burning diesel engines. In recent diesel engines with Exhaust Gas Recirculation (EGR) systems and a Variable Nozzle Turbocharger (VNT), mutual interference between EGR and VNT has been noted. Hence, designing and adjusting control of the conventional PID controller is particularly difficult at the transient state in which the engine speed and fuel injection rate change. In this paper, we formulate 1st principal model of air intake system of diesel engines and transform it to control oriented model including an engine steady state model and a transient model. And we propose a model-based control system with the LQR Controller, Saturation Compensator, the Dynamic Feed-forward and Disturbance Observer using a transient model. Using this method, we achieved precise reference tracking and emission reduction in transient mode test with the real engine evaluations.
Seafloor manifold center installed
Edmiston, K.
1982-07-01
The Shell/Esso Underwater Manifold Center (UMC), designed and tested as a diverless production facility, is a significant step toward really deep water oil and gas production. In May 1982, the 2100 metric ton unit was towed 645 miles from its Dutch fabrication yard and precisely emplaced in 500 ft water in the Cormorant field in only 6 days. When fully installed with all of its wells drilled and testing completed, the UMC will have cost an estimated $700 million. During its anticipated 25 yr operating life, the UMC is expected to produce ca 110 million bbl from the central Cormorant area. Design and operational criteria are described.
Adaptive individual-cylinder thermal state control using intake air heating for a GDCI engine
Roth, Gregory T.; Sellnau, Mark C.
2016-08-09
A system for a multi-cylinder compression ignition engine includes a plurality of heaters, at least one heater per cylinder, with each heater configured to heat air introduced into a cylinder. Independent control of the heaters is provided on a cylinder-by-cylinder basis. A combustion parameter is determined for combustion in each cylinder of the engine, and control of the heater for that cylinder is based on the value of the combustion parameter for combustion in that cylinder. A method for influencing combustion in a multi-cylinder compression ignition engine, including determining a combustion parameter for combustion taking place in a cylinder of the engine and controlling a heater configured to heat air introduced into that cylinder, is also provided.
Fuel cell manifold sealing system
Grevstad, Paul E.; Johnson, Carl K.; Mientek, Anthony P.
1980-01-01
A manifold-to-stack seal and sealing method for fuel cell stacks. This seal system solves the problem of maintaining a low leak rate manifold seal as the fuel cell stack undergoes compressive creep. The seal system eliminates the problem of the manifold-to-stack seal sliding against the rough stack surface as the stack becomes shorter because of cell creep, which relative motion destroys the seal. The seal system described herein utilizes a polymer seal frame firmly clamped between the manifold and the stack such that the seal frame moves with the stack. Thus, as the stack creeps, the seal frame creeps with it, and there is no sliding at the rough, tough to seal, stack-to-seal frame interface. Here the sliding is on a smooth easy to seal location between the seal frame and the manifold.
2010-09-01
Propulsion a vitesse elevee : Conception du moteur - integration et gestion thermique) 14. ABSTRACT Intake design for supersonic engines, in common...exhaust velocity to free stream velocity, with exhaust velocity calculated by assuming the captured air is expanded isentropicaly back to ambient ...2.1 [23] with the actual value probably determined by engine mass flow demand and therefore dependent on ambient temperature. The lowest
Manifold-Based Image Understanding
2010-06-30
compressing data on manifolds: We sought to develop efficient sampling and measurement schemes for manifold-modeled data. Our key result was in proving the...struction. We have proposed a framework for compressive classification that operates directly on the compressive measurements without first reconstructing the...likelihood hypothesis testing into the compressive domain; we find that the number of measurements required for a given classification performance level does
Manifold-valued Dirichlet Processes
Kim, Hyunwoo J.; Xu, Jia; Vemuri, Baba C.; Singh, Vikas
2016-01-01
Statistical models for manifold-valued data permit capturing the intrinsic nature of the curved spaces in which the data lie and have been a topic of research for several decades. Typically, these formulations use geodesic curves and distances defined locally for most cases — this makes it hard to design parametric models globally on smooth manifolds. Thus, most (manifold specific) parametric models available today assume that the data lie in a small neighborhood on the manifold. To address this ‘locality’ problem, we propose a novel nonparametric model which unifies multivariate general linear models (MGLMs) using multiple tangent spaces. Our framework generalizes existing work on (both Euclidean and non-Euclidean) general linear models providing a recipe to globally extend the locally-defined parametric models (using a mixture of local models). By grouping observations into sub-populations at multiple tangent spaces, our method provides insights into the hidden structure (geodesic relationships) in the data. This yields a framework to group observations and discover geodesic relationships between covariates X and manifold-valued responses Y, which we call Dirichlet process mixtures of multivariate general linear models (DP-MGLM) on Riemannian manifolds. Finally, we present proof of concept experiments to validate our model. PMID:26973982
Flowfield visualization for SSME hot gas manifold
NASA Technical Reports Server (NTRS)
Roger, Robert P.
1988-01-01
The objective of this research, as defined by NASA-Marshall Space Flight Center, was two-fold: (1) to numerically simulate viscous subsonic flow in a proposed elliptical two-duct version of the fuel side Hot Gas Manifold (HGM) for the Space Shuttle Main Engine (SSME), and (2) to provide analytical support for SSME related numerical computational experiments, being performed by the Computational Fluid Dynamics staff in the Aerophysics Division of the Structures and Dynamics Laboratory at NASA-MSFC. Numerical results of HGM were calculations to complement both water flow visualization experiments and air flow visualization experiments and air experiments in two-duct geometries performed at NASA-MSFC and Rocketdyne. In addition, code modification and improvement efforts were to strengthen the CFD capabilities of NASA-MSFC for producing reliable predictions of flow environments within the SSME.
Quantization of Multiply Connected Manifolds
NASA Astrophysics Data System (ADS)
Hawkins, Eli
2005-04-01
The standard (Berezin-Toeplitz) geometric quantization of a compact Kähler manifold is restricted by integrality conditions. These restrictions can be circumvented by passing to the universal covering space, provided that the lift of the symplectic form is exact. I relate this construction to the Baum-Connes assembly map and prove that it gives a strict quantization of the original manifold. I also propose a further generalization, classify the required structure, and provide a means of computing the resulting algebras. These constructions involve twisted group C*-algebras of the fundamental group which are determined by a group cocycle constructed from the cohomology class of the symplectic form. This provides an algebraic counterpart to the Morita equivalence of a symplectic manifold with its fundamental group.
Parallel spinors on flat manifolds
NASA Astrophysics Data System (ADS)
Sadowski, Michał
2006-05-01
Let p(M) be the dimension of the vector space of parallel spinors on a closed spin manifold M. We prove that every finite group G is the holonomy group of a closed flat spin manifold M(G) such that p(M(G))>0. If the holonomy group Hol(M) of M is cyclic, then we give an explicit formula for p(M) another than that given in [R.J. Miatello, R.A. Podesta, The spectrum of twisted Dirac operators on compact flat manifolds, Trans. Am. Math. Soc., in press]. We answer the question when p(M)>0 if Hol(M) is a cyclic group of prime order or dimM≤4.
NASA Astrophysics Data System (ADS)
Oliveira, Goncalo
2017-04-01
On a projective complex manifold, the Abelian group of divisors maps surjectively onto that of holomorphic line bundles (the Picard group). On a G2-manifold we use coassociative submanifolds to define an analogue of the divisors, and a gauge theoretical equation for a connection on a gerbe to define an analogue of the Picard group. Then, we construct a map from the former to the later. We also prove that the canonical map from our analogue of the Picard group to the third cohomology group with integer coefficients is surjective. As a side remark we make an observation relating the topological type of coassociative submanifolds and the cohomology classes they represent.
Linear readout of object manifolds
NASA Astrophysics Data System (ADS)
Chung, SueYeon; Lee, Daniel D.; Sompolinsky, Haim
2016-06-01
Objects are represented in sensory systems by continuous manifolds due to sensitivity of neuronal responses to changes in physical features such as location, orientation, and intensity. What makes certain sensory representations better suited for invariant decoding of objects by downstream networks? We present a theory that characterizes the ability of a linear readout network, the perceptron, to classify objects from variable neural responses. We show how the readout perceptron capacity depends on the dimensionality, size, and shape of the object manifolds in its input neural representation.
Robotic Welding Of Injector Manifold
NASA Technical Reports Server (NTRS)
Gilbert, Jeffrey L.; Shelley, D. Mark
1992-01-01
Brief report presents history, up through October 1990, of continuing efforts to convert from manual to robotic gas/tungsten arc welding in fabrication of main injector inlet manifold of main engine of Space Shuttle. Includes photographs of welding machinery, welds, and weld preparations. Of interest to engineers considering establishment of robotic-welding facilities.
Fluid delivery manifolds and microfluidic systems
Renzi, Ronald F.; Sommer, Gregory J.; Singh, Anup K.; Hatch, Anson V.; Claudnic, Mark R.; Wang, Ying-Chih; Van de Vreugde, James L.
2017-02-28
Embodiments of fluid distribution manifolds, cartridges, and microfluidic systems are described herein. Fluid distribution manifolds may include an insert member and a manifold base and may define a substantially closed channel within the manifold when the insert member is press-fit into the base. Cartridges described herein may allow for simultaneous electrical and fluidic interconnection with an electrical multiplex board and may be held in place using magnetic attraction.
Flexible fuel cell gas manifold system
Cramer, Michael; Shah, Jagdish; Hayes, Richard P.; Kelley, Dana A.
2005-05-03
A fuel cell stack manifold system in which a flexible manifold body includes a pan having a central area, sidewall extending outward from the periphery of the central area, and at least one compound fold comprising a central area fold connecting adjacent portions of the central area and extending between opposite sides of the central area, and a sidewall fold connecting adjacent portions of the sidewall. The manifold system further includes a rail assembly for attachment to the manifold body and adapted to receive pins by which dielectric insulators are joined to the manifold assembly.
Geodesic Monte Carlo on Embedded Manifolds
Byrne, Simon; Girolami, Mark
2013-01-01
Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows in the Hamilton–Jacobi representation. This paper takes the differential geometric basis of Markov chain Monte Carlo further by considering methods to simulate from probability distributions that themselves are defined on a manifold, with common examples being classes of distributions describing directional statistics. Proposal mechanisms are developed based on the geodesic flows over the manifolds of support for the distributions, and illustrative examples are provided for the hypersphere and Stiefel manifold of orthonormal matrices. PMID:25309024
Manifold seal structure for fuel cell stack
Collins, William P.
1988-01-01
The seal between the sides of a fuel cell stack and the gas manifolds is improved by adding a mechanical interlock between the adhesive sealing strip and the abutting surface of the manifolds. The adhesive is a material which can flow to some extent when under compression, and the mechanical interlock is formed providing small openings in the portion of the manifold which abuts the adhesive strip. When the manifolds are pressed against the adhesive strips, the latter will flow into and through the manifold openings to form buttons or ribs which mechanically interlock with the manifolds. These buttons or ribs increase the bond between the manifolds and adhesive, which previously relied solely on the adhesive nature of the adhesive.
Symmetries from the solution manifold
NASA Astrophysics Data System (ADS)
Aldaya, Víctor; Guerrero, Julio; Lopez-Ruiz, Francisco F.; Cossío, Francisco
2015-07-01
We face a revision of the role of symmetries of a physical system aiming at characterizing the corresponding Solution Manifold (SM) by means of Noether invariants as a preliminary step towards a proper, non-canonical, quantization. To this end, "point symmetries" of the Lagrangian are generally not enough, and we must resort to the more general concept of contact symmetries. They are defined in terms of the Poincaré-Cartan form, which allows us, in turn, to find the symplectic structure on the SM, through some sort of Hamilton-Jacobi (HJ) transformation. These basic symmetries are realized as Hamiltonian vector fields, associated with (coordinate) functions on the SM, lifted back to the Evolution Manifold through the inverse of this HJ mapping, that constitutes an inverse of the Noether Theorem. The specific examples of a particle moving on S3, at the mechanical level, and nonlinear SU(2)-sigma model in field theory are sketched.
Anomalies, conformal manifolds, and spheres
Gomis, Jaume; Hsin, Po-Shen; Komargodski, Zohar; ...
2016-03-04
The two-point function of exactly marginal operators leads to a universal contribution to the trace anomaly in even dimensions. We study aspects of this trace anomaly, emphasizing its interpretation as a sigma model, whose target space $M$ is the space of conformal field theories (a.k.a. the conformal manifold). When the underlying quantum field theory is supersymmetric, this sigma model has to be appropriately supersymmetrized. As examples, we consider in some detail $N$ = (2; 2) and $N$ = (0; 2) supersymmetric theories in d = 2 and $N$ = 2 supersymmetric theories in d = 4. This reasoning leads tomore » new information about the conformal manifolds of these theories, for example, we show that the manifold is K ahler-Hodge and we further argue that it has vanishing K ahler class. For $N$ = (2; 2) theories in d = 2 and N = 2 theories in d = 4 we also show that the relation between the sphere partition function and the K ahler potential of $M$ follows immediately from the appropriate sigma models that we construct. Ultimately, along the way we find several examples of potential trace anomalies that obey the Wess-Zumino consistency conditions, but can be ruled out by a more detailed analysis.« less
Manifold learning for robot navigation.
Keeratipranon, Narongdech; Maire, Frederic; Huang, Henry
2006-10-01
In this paper we introduce methods to build a SOM that can be used as an isometric map for mobile robots. That is, given a dataset of sensor readings collected at points uniformly distributed with respect to the ground, we wish to build a SOM whose neurons (prototype vectors in sensor space) correspond to points uniformly distributed on the ground. Manifold learning techniques have already been used for dimensionality reduction of sensor space in navigation systems. Our focus is on the isometric property of the SOM. For reliable path-planning and information sharing between several robots, it is desirable that the robots build an internal representation of the sensor manifold, a map, that is isometric with the environment. We show experimentally that standard Non-Linear Dimensionality Reduction (NLDR) algorithms do not provide isometric maps for range data and bearing data. However, the auxiliary low dimensional manifolds created can be used to improve the distribution of the neurons of a SOM (that is, make the neurons more evenly distributed with respect to the ground). We also describe a method to create an isometric map from a sensor readings collected along a polygonal line random walk.
Anomalies, conformal manifolds, and spheres
Gomis, Jaume; Hsin, Po-Shen; Komargodski, Zohar; Schwimmer, Adam; Seiberg, Nathan; Theisen, Stefan
2016-03-04
The two-point function of exactly marginal operators leads to a universal contribution to the trace anomaly in even dimensions. We study aspects of this trace anomaly, emphasizing its interpretation as a sigma model, whose target space $M$ is the space of conformal field theories (a.k.a. the conformal manifold). When the underlying quantum field theory is supersymmetric, this sigma model has to be appropriately supersymmetrized. As examples, we consider in some detail $N$ = (2; 2) and $N$ = (0; 2) supersymmetric theories in d = 2 and $N$ = 2 supersymmetric theories in d = 4. This reasoning leads to new information about the conformal manifolds of these theories, for example, we show that the manifold is K ahler-Hodge and we further argue that it has vanishing K ahler class. For $N$ = (2; 2) theories in d = 2 and N = 2 theories in d = 4 we also show that the relation between the sphere partition function and the K ahler potential of $M$ follows immediately from the appropriate sigma models that we construct. Ultimately, along the way we find several examples of potential trace anomalies that obey the Wess-Zumino consistency conditions, but can be ruled out by a more detailed analysis.
... do to protect yourself from dirty air . Indoor air pollution and outdoor air pollution Air can be polluted indoors and it can ... this chart to see what things cause indoor air pollution and what things cause outdoor air pollution! Indoor ...
Similarity Learning of Manifold Data.
Chen, Si-Bao; Ding, Chris H Q; Luo, Bin
2015-09-01
Without constructing adjacency graph for neighborhood, we propose a method to learn similarity among sample points of manifold in Laplacian embedding (LE) based on adding constraints of linear reconstruction and least absolute shrinkage and selection operator type minimization. Two algorithms and corresponding analyses are presented to learn similarity for mix-signed and nonnegative data respectively. The similarity learning method is further extended to kernel spaces. The experiments on both synthetic and real world benchmark data sets demonstrate that the proposed LE with new similarity has better visualization and achieves higher accuracy in classification.
Connecting interacting galaxies with manifolds
NASA Astrophysics Data System (ADS)
Romero-Gomez, M.; Athanassoula, E.
2017-03-01
It is well known that the interaction between two disk galaxies generates tidal spiral arms and a connection in the form of a bridge. Here we address the question of the formation of tidal arms and bridges from a dynamical point of view. We model the bridges and tails observed in interacting galaxies using the invariant manifolds associated to the Lyapunov orbits of the Lagrangian points of the galactic system, when the two galaxies are considered as two point masses in a circular orbit.
Munson, D.E.; Hoag, D.L.; Ball, J.R.
1995-07-01
Data are presented from the Air Intake Shaft Test, an in situ test fielded at the Waste Isolation Pilot Plant (WIPP). The construction of this shaft, well after the initial three access shafts, presented an unusual opportunity to obtain valuable detailed data on the mechanical response of a shaft for application to seal design. These data include selected fielding information, test configuration, instrumentation activities, and comprehensive results from a large number of gages. Construction of the test began in December 1987; gage data in this report cover the period from May 1988 through July 1995, with the bulk of the data obtained after obtaining access in November, 1989 and from the heavily instrumented period after remote gage installation between May, 1990, and October, 1991.
Manifold learning in protein interactomes.
Marras, Elisabetta; Travaglione, Antonella; Capobianco, Enrico
2011-01-01
Many studies and applications in the post-genomic era have been devoted to analyze complex biological systems by computational inference methods. We propose to apply manifold learning methods to protein-protein interaction networks (PPIN). Despite their popularity in data-intensive applications, these methods have received limited attention in the context of biological networks. We show that there is both utility and unexplored potential in adopting manifold learning for network inference purposes. In particular, the following advantages are highlighted: (a) fusion with diagnostic statistical tools designed to assign significance to protein interactions based on pre-selected topological features; (b) dissection into components of the interactome in order to elucidate global and local connectivity organization; (c) relevance of embedding the interactome in reduced dimensions for biological validation purposes. We have compared the performances of three well-known techniques--kernel-PCA, RADICAL ICA, and ISOMAP--relatively to their power of mapping the interactome onto new coordinate dimensions where important associations among proteins can be detected, and then back projected such that the corresponding sub-interactomes are reconstructed. This recovery has been done selectively, by using significant information according to a robust statistical procedure, and then standard biological annotation has been provided to validate the results. We expect that a byproduct of using subspace analysis by the proposed techniques is a possible calibration of interactome modularity studies. Supplementary Material is available online at www.libertonlinec.com.
Manifold For Flushing Tubes With Cleaning Solution
NASA Technical Reports Server (NTRS)
Morgan, Gene E.; Fogel, Irving
1995-01-01
Custom-built manifold mounted on cleaning basket enables simultaneous flushing of 80 tubes with cleaning solution. In original application, tubes components of rocket-engine nozzle under construction. However, basic manifold configuration adapted to other applications (e.g., fabrication of heat exchangers) in which there is need for simultaneous cleaning of many tubes of identical size and shape.
An Explicit Nonlinear Mapping for Manifold Learning.
Qiao, Hong; Zhang, Peng; Wang, Di; Zhang, Bo
2013-02-01
Manifold learning is a hot research topic in the held of computer science and has many applications in the real world. A main drawback of manifold learning methods is, however, that there are no explicit mappings from the input data manifold to the output embedding. This prohibits the application of manifold learning methods in many practical problems such as classification and target detection. Previously, in order to provide explicit mappings for manifold learning methods, many methods have been proposed to get an approximate explicit representation mapping with the assumption that there exists a linear projection between the high-dimensional data samples and their low-dimensional embedding. However, this linearity assumption may be too restrictive. In this paper, an explicit nonlinear mapping is proposed for manifold learning, based on the assumption that there exists a polynomial mapping between the high-dimensional data samples and their low-dimensional representations. As far as we know, this is the hrst time that an explicit nonlinear mapping for manifold learning is given. In particular, we apply this to the method of locally linear embedding and derive an explicit nonlinear manifold learning algorithm, which is named neighborhood preserving polynomial embedding. Experimental results on both synthetic and real-world data show that the proposed mapping is much more effective in preserving the local neighborhood information and the nonlinear geometry of the high-dimensional data samples than previous work.
Integrability conditions on Engel-type manifolds
NASA Astrophysics Data System (ADS)
Calin, Ovidiu; Chang, Der-Chen; Hu, Jishan
2015-09-01
We introduce the concept of Engel manifold, as a manifold that resembles locally the Engel group, and find the integrability conditions of the associated sub-elliptic system , . These are given by , . Then an explicit construction of the solution involving an integral representation is provided, which corresponds to a Poincaré-type lemma for the Engel's distribution.
Target manifold formation using a quadratic SDF
NASA Astrophysics Data System (ADS)
Hester, Charles F.; Risko, Kelly K. D.
2013-05-01
Synthetic Discriminant Function (SDF) formulation of correlation filters provides constraints for forming target subspaces for a target set. In this paper we extend the SDF formulation to include quadratic constraints and use this solution to form nonlinear manifolds in the target space. The theory for forming these manifolds will be developed and demonstrated with data.
Sasakian manifolds and M-theory
NASA Astrophysics Data System (ADS)
Figueroa-O'Farrill, José; Santi, Andrea
2016-05-01
We extend the link between Einstein Sasakian manifolds and Killing spinors to a class of η-Einstein Sasakian manifolds, both in Riemannian and Lorentzian settings, characterizing them in terms of generalized Killing spinors. We propose a definition of supersymmetric M-theory backgrounds on such a geometry and find a new class of such backgrounds, extending previous work of Haupt, Lukas and Stelle.
Manifold Coal-Slurry Transport System
NASA Technical Reports Server (NTRS)
Liddle, S. G.; Estus, J. M.; Lavin, M. L.
1986-01-01
Feeding several slurry pipes into main pipeline reduces congestion in coal mines. System based on manifold concept: feeder pipelines from each working entry joined to main pipeline that carries coal slurry out of panel and onto surface. Manifold concept makes coal-slurry haulage much simpler than existing slurry systems.
Manifold-based learning and synthesis.
Huang, Dong; Yi, Zhang; Pu, Xiaorong
2009-06-01
This paper proposes a new approach to analyze high-dimensional data set using low-dimensional manifold. This manifold-based approach provides a unified formulation for both learning from and synthesis back to the input space. The manifold learning method desires to solve two problems in many existing algorithms. The first problem is the local manifold distortion caused by the cost averaging of the global cost optimization during the manifold learning. The second problem results from the unit variance constraint generally used in those spectral embedding methods where global metric information is lost. For the out-of-sample data points, the proposed approach gives simple solutions to transverse between the input space and the feature space. In addition, this method can be used to estimate the underlying dimension and is robust to the number of neighbors. Experiments on both low-dimensional data and real image data are performed to illustrate the theory.
A Light-Activated Reaction Manifold.
Hiltebrandt, Kai; Elies, Katharina; D'hooge, Dagmar R; Blinco, James P; Barner-Kowollik, Christopher
2016-06-08
We introduce an efficient reaction manifold where the rate of a thermally induced ligation can be controlled by a photonic field via two competing reaction channels. The effectiveness of the reaction manifold is evidenced by following the transformations of macromolecular chain termini via high-resolution mass spectrometry and subsequently by selective block copolymer formation. The light-controlled reaction manifold consists of a so-called o-quinodimethane species, a photocaged diene, that reacts in the presence of light with suitable enes in a Diels-Alder reaction and undergoes a transformation into imines with amines in the absence of light. The chemical selectivity of the manifold is controlled by the amount of ene present in the reaction and can be adjusted from 100% imine formation (0% photo product) to 5% imine formation (95% photo product). The reported light-controlled reaction manifold is highly attractive because a simple external field is used to switch the selectivity of specific reaction channels.
NASA Astrophysics Data System (ADS)
Berglund, Per; Brandhuber, Andreas
2003-04-01
We describe how chiral matter charged under SU(N) and SO(2N) gauge groups arises from codimension seven singularities in compactifications of M-theory on manifolds with G(2) holonomy. The geometry of these spaces is that of a cone over a six-dimensional Einstein space which can be constructed by (multiple) unfolding of hyper-Kahler quotient spaces. In type IIA the corresponding picture is given by stacks of intersecting D6-branes and chiral matter arises from open strings stretching between them. Usually one obtains (bi)fundamental representations but by including orientifold six-planes in the type IIA picture we find more exotic representations like the anti-symmetric, which is important for the study of SU(5) grand unification, and trifundamental representations. We also exhibit many cases where the G(2) metrics can be described explicitly, although in general the metrics on the spaces constructed via unfolding are not known.
The Fundamental Manifold of Spheroids
NASA Astrophysics Data System (ADS)
Zaritsky, Dennis; Gonzalez, Anthony H.; Zabludoff, Ann I.
2006-02-01
We present a unifying empirical description of the structural and kinematic properties of all spheroids embedded in dark matter halos. We find that the intracluster stellar spheroidal components of galaxy clusters, which we call cluster spheroids (CSphs) and which are typically 100 times the size of normal elliptical galaxies, lie on a ``fundamental plane'' as tight as that defined by elliptical galaxies (rms in effective radius of ~0.07) but having a different slope. The slope, as measured by the coefficient of the logσ term, declines significantly and systematically between the fundamental planes of ellipticals, brightest cluster galaxies (BCGs), and CSphs. We attribute this decline primarily to a continuous change in Me/Le, the mass-to-light ratio within the effective radius re, with spheroid scale. The magnitude of the slope change requires that it arise principally from differences in the relative distributions of luminous and dark matter, rather than from stellar population differences such as in age and metallicity. By expressing the Me/Le term as a function of σ in the simple derivation of the fundamental plane and requiring the behavior of that term to mimic the observed nonlinear relationship between logMe/Le and logσ, we simultaneously fit a two-dimensional manifold to the measured properties of dwarf elliptical and elliptical galaxies, BCGs, and CSphs. The combined data have an rms scatter in logre of 0.114 (0.099 for the combination of ellipticals, BCGs, and CSphs), which is modestly larger than each fundamental plane has alone, but which includes the scatter introduced by merging different studies done in different filters by different investigators. This ``fundamental manifold'' fits the structural and kinematic properties of spheroids that span a factor of 100 in σ and 1000 in re. While our mathematical form is neither unique nor derived from physical principles, the tightness of the fit leaves little room for improvement by other unification
MacNeill, M; Dobbin, N; St-Jean, M; Wallace, L; Marro, L; Shin, T; You, H; Kulka, R; Allen, R W; Wheeler, A J
2016-10-01
Traffic emissions have been associated with a wide range of adverse health effects. Many schools are situated close to major roads, and as children spend much of their day in school, methods to reduce traffic-related air pollutant concentrations in the school environment are warranted. One promising method to reduce pollutant concentrations in schools is to alter the timing of the ventilation so that high ventilation time periods do not correspond to rush hour traffic. Health Canada, in collaboration with the Ottawa-Carleton District School Board, tested the effect of this action by collecting traffic-related air pollution data from four schools in Ottawa, Canada, during October and November 2013. A baseline and intervention period was assessed in each school. There were statistically significant (P < 0.05) reductions in concentrations of most of the pollutants measured at the two late-start (9 AM start) schools, after adjusting for outdoor concentrations and the absolute indoor-outdoor temperature difference. The intervention at the early-start (8 AM start) schools did not have significant reductions in pollutant concentrations. Based on these findings, changing the timing of the ventilation may be a cost-effective mechanism of reducing traffic-related pollutants in late-start schools located near major roads.
Harmonic maps between quaternionic Kahler manifolds
NASA Astrophysics Data System (ADS)
Ianus, S.; Mazzocco, R.; Vilcu, G. E.
We introduce a natural notion of quaternionic map between almost quaternionic manifolds and we prove the following, for maps of rank at least one: 1) A map between quaternionic manifolds endowed with the integrable almost twistorial structures is twistorial if and only if it is quaternionic. 2) A map between quaternionic manifolds endowed with the nonintegrable almost twistorial structures is twistorial if and only if it is quaternionic and totally-geodesic. As an application, we describe the quaternionic maps between open sets of quaternionic projective spaces.
Loops in Reeb Graphs of 2-Manifolds
Cole-McLaughlin, K; Edelsbrunner, H; Harer, J; Natarajan, V; Pascucci, V
2003-02-11
Given a Morse function f over a 2-manifold with or without boundary, the Reeb graph is obtained by contracting the connected components of the level sets to points. We prove tight upper and lower bounds on the number of loops in the Reeb graph that depend on the genus, the number of boundary components, and whether or not the 2-manifold is orientable. We also give an algorithm that constructs the Reeb graph in time O(n log n), where n is the number of edges in the triangulation used to represent the 2-manifold and the Morse function.
Loops in Reeb Graphs of 2-Manifolds
Cole-McLaughlin, K; Edelsbrunner, H; Harer, J; Natarajan, V; Pascucci, V
2004-12-16
Given a Morse function f over a 2-manifold with or without boundary, the Reeb graph is obtained by contracting the connected components of the level sets to points. We prove tight upper and lower bounds on the number of loops in the Reeb graph that depend on the genus, the number of boundary components, and whether or not the 2-manifold is orientable. We also give an algorithm that constructs the Reeb graph in time O(n log n), where n is the number of edges in the triangulation used to represent the 2-manifold and the Morse function.
Magnetic quantization over Riemannian manifolds
NASA Astrophysics Data System (ADS)
Karasev, M. V.; Osborn, T. A.
2006-06-01
We demonstrate that Weyl's pioneering idea (1918) to intertwine metric and magnetic fields into a single joint connection can be naturally realized, on the phase space level, by the gauge-invariant quantization of the cotangent bundle with magnetic symplectic form. Quantization, for systems over a noncompact Riemannian configuration manifold, may be achieved by the introduction of a magneto-metric analog of the Stratonovich quantizer - a family of invertible, selfadjoint operators representing quantum delta functions. Based on the quantizer, we construct a generalized Wigner transform that maps Hilbert-Schmidt operators into L-2 phase-space functions. The algebraic properties of the quantizer allow one to extract a family of symplectic reflections, which are then used to (i) derive a simple, explicit, and geometrically invariant formula for the noncommutative product of functions on phase space, and (ii) construct a magneto-metric connection on phase space. The classical limit of this product is given by the usual multiplication of functions (zeroth-order term), the magnetic Poisson bracket (first-order term), and by the magneto-metric connection (second-order term).
Regional manifold learning for disease classification.
Ye, Dong Hye; Desjardins, Benoit; Hamm, Jihun; Litt, Harold; Pohl, Kilian M
2014-06-01
While manifold learning from images itself has become widely used in medical image analysis, the accuracy of existing implementations suffers from viewing each image as a single data point. To address this issue, we parcellate images into regions and then separately learn the manifold for each region. We use the regional manifolds as low-dimensional descriptors of high-dimensional morphological image features, which are then fed into a classifier to identify regions affected by disease. We produce a single ensemble decision for each scan by the weighted combination of these regional classification results. Each weight is determined by the regional accuracy of detecting the disease. When applied to cardiac magnetic resonance imaging of 50 normal controls and 50 patients with reconstructive surgery of Tetralogy of Fallot, our method achieves significantly better classification accuracy than approaches learning a single manifold across the entire image domain.
Hierarchical manifold learning for regional image analysis.
Bhatia, Kanwal K; Rao, Anil; Price, Anthony N; Wolz, Robin; Hajnal, Joseph V; Rueckert, Daniel
2014-02-01
We present a novel method of hierarchical manifold learning which aims to automatically discover regional properties of image datasets. While traditional manifold learning methods have become widely used for dimensionality reduction in medical imaging, they suffer from only being able to consider whole images as single data points. We extend conventional techniques by additionally examining local variations, in order to produce spatially-varying manifold embeddings that characterize a given dataset. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate the utility of our method in two very different settings: 1) to learn the regional correlations in motion within a sequence of time-resolved MR images of the thoracic cavity; 2) to find discriminative regions of 3-D brain MR images associated with neurodegenerative disease.
Polynomial chaos representation of databases on manifolds
NASA Astrophysics Data System (ADS)
Soize, C.; Ghanem, R.
2017-04-01
Characterizing the polynomial chaos expansion (PCE) of a vector-valued random variable with probability distribution concentrated on a manifold is a relevant problem in data-driven settings. The probability distribution of such random vectors is multimodal in general, leading to potentially very slow convergence of the PCE. In this paper, we build on a recent development for estimating and sampling from probabilities concentrated on a diffusion manifold. The proposed methodology constructs a PCE of the random vector together with an associated generator that samples from the target probability distribution which is estimated from data concentrated in the neighborhood of the manifold. The method is robust and remains efficient for high dimension and large datasets. The resulting polynomial chaos construction on manifolds permits the adaptation of many uncertainty quantification and statistical tools to emerging questions motivated by data-driven queries.
Adiabatic limits on Riemannian Heisenberg manifolds
Yakovlev, A A
2008-02-28
An asymptotic formula is obtained for the distribution function of the spectrum of the Laplace operator, in the adiabatic limit for the foliation defined by the orbits of an invariant flow on a compact Riemannian Heisenberg manifold. Bibliography: 21 titles.
Modeling Flow through a Lock Manifold Port
2013-01-01
computational model is to provide reliable loss coefficients. Energy losses for flow issuing from a port occur primarily in the submerged jet . The...computational flow model to determine the velocity and pressure distribution in a single-port manifold for a range of port-to-culvert discharge ...Engineers 2006). Navigation lock manifolds can be evaluated using analytical methods when the hydraulic characteristics associated with the manifold’s
Computer calculation of Witten's 3-manifold invariant
NASA Astrophysics Data System (ADS)
Freed, Daniel S.; Gompf, Robert E.
1991-10-01
Witten's 2+1 dimensional Chern-Simons theory is exactly solvable. We compute the partition function, a topological invariant of 3-manifolds, on generalized Seifert spaces. Thus we test the path integral using the theory of 3-manifolds. In particular, we compare the exact solution with the asymptotic formula predicted by perturbation theory. We conclude that this path integral works as advertised and gives an effective topological invariant.
Quaternionic-like manifolds and homogeneous twistor spaces.
Pantilie, Radu
2016-12-01
Motivated by the quaternionic geometry corresponding to the homogeneous complex manifolds endowed with (holomorphically) embedded spheres, we introduce and initiate the study of the 'quaternionic-like manifolds'. These contain, as particular subclasses, the CR quaternionic and the ρ-quaternionic manifolds. Moreover, the notion of 'heaven space' finds its adequate level of generality in this setting: (essentially) any real analytic quaternionic-like manifold admits a (germ) unique heaven space, which is a ρ-quaternionic manifold. We, also, give a natural construction of homogeneous complex manifolds endowed with embedded spheres, thus, emphasizing the abundance of the quaternionic-like manifolds.
Spectral Quasi-Equilibrium Manifold for Chemical Kinetics.
Kooshkbaghi, Mahdi; Frouzakis, Christos E; Boulouchos, Konstantinos; Karlin, Iliya V
2016-05-26
The Spectral Quasi-Equilibrium Manifold (SQEM) method is a model reduction technique for chemical kinetics based on entropy maximization under constraints built by the slowest eigenvectors at equilibrium. The method is revisited here and discussed and validated through the Michaelis-Menten kinetic scheme, and the quality of the reduction is related to the temporal evolution and the gap between eigenvalues. SQEM is then applied to detailed reaction mechanisms for the homogeneous combustion of hydrogen, syngas, and methane mixtures with air in adiabatic constant pressure reactors. The system states computed using SQEM are compared with those obtained by direct integration of the detailed mechanism, and good agreement between the reduced and the detailed descriptions is demonstrated. The SQEM reduced model of hydrogen/air combustion is also compared with another similar technique, the Rate-Controlled Constrained-Equilibrium (RCCE). For the same number of representative variables, SQEM is found to provide a more accurate description.
Einstein Manifolds as Yang-Mills Instantons
NASA Astrophysics Data System (ADS)
Oh, John J.; Yang, Hyun Seok
2013-07-01
It is well known that Einstein gravity can be formulated as a gauge theory of Lorentz group where spin connections play a role of gauge fields and Riemann curvature tensors correspond to their field strengths. One can then pose an interesting question: What is the Einstein equation from the gauge theory point of view? Or equivalently, what is the gauge theory object corresponding to Einstein manifolds? We show that the Einstein equations in four dimensions are precisely self-duality equations in Yang-Mills gauge theory and so Einstein manifolds correspond to Yang-Mills instantons in SO(4) = SU(2)L × SU(2)R gauge theory. Specifically, we prove that any Einstein manifold with or without a cosmological constant always arises as the sum of SU(2)L instantons and SU(2)R anti-instantons. This result explains why an Einstein manifold must be stable because two kinds of instantons belong to different gauge groups, instantons in SU(2)L and anti-instantons in SU(2)R, and so they cannot decay into a vacuum. We further illuminate the stability of Einstein manifolds by showing that they carry nontrivial topological invariants.
Conharmonic Tensor of Certain Classes of Almost Hermitian Manifold
NASA Astrophysics Data System (ADS)
Abood, Habeeb Mtashar; Lafta, Gassan Irhaim
2010-11-01
Most of the conharmonic tensor studies are applied on Riemannian space. In this work we investigated the conharmonic curvature tensor of some more specific important classes, In particular, the nearly Kahler and almost Kahler manifolds. Firstly, three special classes of almost Hermitian manifold depending on conharmonic tensor have been defined. We found the relation between these classes and the class nearly Kahler manifold. The conharmonic recurrent of nearly Kahler manifold has been studied. Secondly, we found the necessary condition where an almost Kahler manifold is a manifold of a pointwise holomrphic conharmonic tensor.
Infinitely many singular interactions on noncompact manifolds
Kaynak, Burak Tevfik Turgut, O. Teoman
2015-05-15
We show that the ground state energy is bounded from below when there are infinitely many attractive delta function potentials placed in arbitrary locations, while all being separated at least by a minimum distance, on two dimensional non-compact manifold. To facilitate the reading of the paper, we first present the arguments in the setting of Cartan–Hadamard manifolds and then subsequently discuss the general case. For this purpose, we employ the heat kernel techniques as well as some comparison theorems of Riemannian geometry, thus generalizing the arguments in the flat case following the approach presented in Albeverio et al. (2004). - Highlights: • Schrödinger-operator for infinitely many singular interactions on noncompact manifolds. • Proof of the finiteness of the ground-state energy.
Unraveling flow patterns through nonlinear manifold learning.
Tauro, Flavia; Grimaldi, Salvatore; Porfiri, Maurizio
2014-01-01
From climatology to biofluidics, the characterization of complex flows relies on computationally expensive kinematic and kinetic measurements. In addition, such big data are difficult to handle in real time, thereby hampering advancements in the area of flow control and distributed sensing. Here, we propose a novel framework for unsupervised characterization of flow patterns through nonlinear manifold learning. Specifically, we apply the isometric feature mapping (Isomap) to experimental video data of the wake past a circular cylinder from steady to turbulent flows. Without direct velocity measurements, we show that manifold topology is intrinsically related to flow regime and that Isomap global coordinates can unravel salient flow features.
Isoperimetric inequality on conformally hyperbolic manifolds
Kesel'man, V M
2003-04-30
It is shown that on an arbitrary non-compact Riemannian manifold of conformally hyperbolic type the isoperimetric inequality can be taken by a conformal change of the metric to the same canonical linear form as in the case of the standard hyperbolic Lobachevskii space. Both the absolute isoperimetric inequality and the relative one (for manifolds with boundary) are obtained. This work develops the results and methods of a joint paper with Zorich, in which the absolute isoperimetric inequality was obtained under a certain additional condition; the resulting statements are definitive in a certain sense.
Manifolds for pose tracking from monocular video
NASA Astrophysics Data System (ADS)
Basu, Saurav; Poulin, Joshua; Acton, Scott T.
2015-03-01
We formulate a simple human-pose tracking theory from monocular video based on the fundamental relationship between changes in pose and image motion vectors. We investigate the natural embedding of the low-dimensional body pose space into a high-dimensional space of body configurations that behaves locally in a linear manner. The embedded manifold facilitates the decomposition of the image motion vectors into basis motion vector fields of the tangent space to the manifold. This approach benefits from the style invariance of image motion flow vectors, and experiments to validate the fundamental theory show reasonable accuracy (within 4.9 deg of the ground truth).
Twistorial Constructions of Special Riemannian Manifolds
Albuquerque, Rui
2008-06-25
We use twistor theory to describe virtually new constructions of Hermitian and quaternionic Kaehler structures on tangent bundles and a G{sub 2} structure on the unit sphere tangent bundle of a Riemannian 4-manifold--fundamental to holonomy theory and subject of deep research in physics.We interpret 'self-holomorphic' complex structures on a symplectic manifold. These complex structures give an interesting set of problems in the first possible dimension, the case of Riemann surfaces, from which should follow some interplay with Teichmuller theory, as well as with SL(2) connections.
Isoperimetric inequality on conformally hyperbolic manifolds
NASA Astrophysics Data System (ADS)
Kesel'man, V. M.
2003-04-01
It is shown that on an arbitrary non-compact Riemannian manifold of conformally hyperbolic type the isoperimetric inequality can be taken by a conformal change of the metric to the same canonical linear form as in the case of the standard hyperbolic Lobachevskii space. Both the absolute isoperimetric inequality and the relative one (for manifolds with boundary) are obtained.This work develops the results and methods of a joint paper with Zorich, in which the absolute isoperimetric inequality was obtained under a certain additional condition; the resulting statements are definitive in a certain sense.
Approaching Moons from Resonance via Invariant Manifolds
NASA Technical Reports Server (NTRS)
Anderson, Rodney L.
2012-01-01
In this work, the approach phase from the final resonance of the endgame scenario in a tour design is examined within the context of invariant manifolds. Previous analyses have typically solved this problem either by using numerical techniques or by computing a catalog of suitable trajectories. The invariant manifolds of a selected set of libration orbits and unstable resonant orbits are computed here to serve as guides for desirable approach trajectories. The analysis focuses on designing an approach phase that may be tied into the final resonance in the endgame sequence while also targeting desired conditions at the moon.
Noncommutative deformations of locally symmetric Kähler manifolds
NASA Astrophysics Data System (ADS)
Hara, Kentaro; Sako, Akifumi
2017-04-01
We derive algebraic recurrence relations to obtain a deformation quantization with separation of variables for a locally symmetric Kähler manifold. This quantization method is one of the ways to perform a deformation quantization of Kähler manifolds, which is introduced by Karabegov. From the recurrence relations, concrete expressions of star products for one-dimensional local symmetric Kähler manifolds and CPN are constructed. The recurrence relations for a Grassmann manifold G2,2 are closely studied too.
Fluid manifold design for a solar energy storage tank
NASA Technical Reports Server (NTRS)
Humphries, W. R.; Hewitt, H. C.; Griggs, E. I.
1975-01-01
A design technique for a fluid manifold for use in a solar energy storage tank is given. This analytical treatment generalizes the fluid equations pertinent to manifold design, giving manifold pressures, velocities, and orifice pressure differentials in terms of appropriate fluid and manifold geometry parameters. Experimental results used to corroborate analytical predictions are presented. These data indicate that variations in discharge coefficients due to variations in orifices can cause deviations between analytical predictions and actual performance values.
Method of producing suction manifolds for automobile engines
Enomoto, M.; Shimizu, Y.
1984-05-29
A method of producing suction manifolds for automobile engines is disclosed. In forming an exhaust gas re-circulating pipe passage integrally with a suction manifold for re-circulating exhaust gases from the engine to the suction manifold, a curved pipe of aluminum having a high-temperature resistant film formed on its surface is molded into a manifold of aluminum alloy at a suitable place on the latter.
On the conformal geometry of transverse Riemann Lorentz manifolds
NASA Astrophysics Data System (ADS)
Aguirre, E.; Fernández, V.; Lafuente, J.
2007-06-01
Physical reasons suggested in [J.B. Hartle, S.W. Hawking, Wave function of the universe, Phys. Rev. D41 (1990) 1815-1834] for the Quantum Gravity Problem lead us to study type-changing metrics on a manifold. The most interesting cases are Transverse Riemann-Lorentz Manifolds. Here we study the conformal geometry of such manifolds.
Manifold gasket accommodating differential movement of fuel cell stack
Kelley, Dana A.; Farooque, Mohammad
2007-11-13
A gasket for use in a fuel cell system having at least one externally manifolded fuel cell stack, for sealing the manifold edge and the stack face. In accordance with the present invention, the gasket accommodates differential movement between the stack and manifold by promoting slippage at interfaces between the gasket and the dielectric and between the gasket and the stack face.
Special-holonomy manifolds and quartic-curvature string corrections
NASA Astrophysics Data System (ADS)
Stelle, K. S.
2004-06-01
The quartic-curvature corrections derived from string theory have a very specific impact on the geometry of target-space manifolds of special holonomy. In the cases of Calabi-Yau manifolds and D = 7 manifolds of G2 holonomy, we show how the corrections conspire to preserve the unbroken supersymmetry of these backgrounds.
Fuel-air ratio controlled carburetion system
Abbey, H. G.
1980-02-12
An automatic control system is disclosed supplying a fuel-air mixture to an internal combustion engine including a variable-venturi carburetor. Air is fed into the input of the venturi, the air passing through the throat thereof whose effective area is adjusted by a mechanism operated by a servo motor. Fuel is fed into the input of the venturi from a fuel reservoir through a main path having a fixed orifice and an auxiliary path formed by a metering valve operated by an auxiliary fuel-control motor. The differential air pressure developed between the inlet of the venturi and the throat thereof is sensed to produce an airvelocity command signal that is applied to a controller adapted to compare the command signal with the servo motor set point to produce an output for governing the servo motor to cause it to seek a null point, thereby defining a closed process control loop. The intake manifold vacuum, which varies in degree as a function of load and speed conditions is sensed to govern the auxiliary fuel-control motor accordingly, is at the same time converted into an auxiliary signal which is applied to the controller in the closed loop to modulate the command signal in a manner establishing an optimum air-fuel ratio under the varying conditions of load and speed.
Banks, E.M.; Wikoff, W.O.; Shaffer, L.L.
1997-08-01
At the current level of maturity and experience in the nuclear industry, regarding testing of air treatment systems, it is now possible to design and qualify injection and sample manifolds for most applications. While the qualification of sample manifolds is still in its infancy, injection manifolds have reached a mature stage that helps to eliminate the {open_quotes}hit or miss{close_quotes} type of design. During the design phase, manifolds can be adjusted to compensate for poor airflow distribution, laminar flow conditions, and to take advantage of any system attributes. Experience has shown that knowing the system attributes before the design phase begins is an essential element to a successful manifold design. The use of a spreadsheet type program commonly found on most personal computers can afford a greater flexibility and a reduction in time spent in the design phase. The experience gained from several generations of manifold design has culminated in a set of general design guidelines. Use of these guidelines, along with a good understanding of the type of testing (theoretical and practical), can result in a good manifold design requiring little or no field modification. The requirements for manifolds came about because of the use of multiple banks of components and unconventional housing inlet configurations. Multiple banks of adsorbers and pre and post HEPA`s required that each bank be tested to insure that each one does not exceed a specific allowable leakage criterion. 5 refs., 5 figs., 1 tab.
NASA Astrophysics Data System (ADS)
Sparks, Rachel; Madabhushi, Anant
2012-03-01
Gleason patterns of prostate cancer histopathology, characterized primarily by morphological and architectural attributes of histological structures (glands and nuclei), have been found to be highly correlated with disease aggressiveness and patient outcome. Gleason patterns 4 and 5 are highly correlated with more aggressive disease and poorer patient outcome, while Gleason patterns 1-3 tend to reflect more favorable patient outcome. Because Gleason grading is done manually by a pathologist visually examining glass (or digital) slides, subtle morphologic and architectural differences of histological attributes may result in grading errors and hence cause high inter-observer variability. Recently some researchers have proposed computerized decision support systems to automatically grade Gleason patterns by using features pertaining to nuclear architecture, gland morphology, as well as tissue texture. Automated characterization of gland morphology has been shown to distinguish between intermediate Gleason patterns 3 and 4 with high accuracy. Manifold learning (ML) schemes attempt to generate a low dimensional manifold representation of a higher dimensional feature space while simultaneously preserving nonlinear relationships between object instances. Classification can then be performed in the low dimensional space with high accuracy. However ML is sensitive to the samples contained in the dataset; changes in the dataset may alter the manifold structure. In this paper we present a manifold regularization technique to constrain the low dimensional manifold to a specific range of possible manifold shapes, the range being determined via a statistical shape model of manifolds (SSMM). In this work we demonstrate applications of the SSMM in (1) identifying samples on the manifold which contain noise, defined as those samples which deviate from the SSMM, and (2) accurate out-of-sample extrapolation (OSE) of newly acquired samples onto a manifold constrained by the SSMM. We
Kernel Manifold Alignment for Domain Adaptation.
Tuia, Devis; Camps-Valls, Gustau
2016-01-01
The wealth of sensory data coming from different modalities has opened numerous opportunities for data analysis. The data are of increasing volume, complexity and dimensionality, thus calling for new methodological innovations towards multimodal data processing. However, multimodal architectures must rely on models able to adapt to changes in the data distribution. Differences in the density functions can be due to changes in acquisition conditions (pose, illumination), sensors characteristics (number of channels, resolution) or different views (e.g. street level vs. aerial views of a same building). We call these different acquisition modes domains, and refer to the adaptation problem as domain adaptation. In this paper, instead of adapting the trained models themselves, we alternatively focus on finding mappings of the data sources into a common, semantically meaningful, representation domain. This field of manifold alignment extends traditional techniques in statistics such as canonical correlation analysis (CCA) to deal with nonlinear adaptation and possibly non-corresponding data pairs between the domains. We introduce a kernel method for manifold alignment (KEMA) that can match an arbitrary number of data sources without needing corresponding pairs, just few labeled examples in all domains. KEMA has interesting properties: 1) it generalizes other manifold alignment methods, 2) it can align manifolds of very different complexities, performing a discriminative alignment preserving each manifold inner structure, 3) it can define a domain-specific metric to cope with multimodal specificities, 4) it can align data spaces of different dimensionality, 5) it is robust to strong nonlinear feature deformations, and 6) it is closed-form invertible, which allows transfer across-domains and data synthesis. To authors' knowledge this is the first method addressing all these important issues at once. We also present a reduced-rank version of KEMA for computational
Kernel Manifold Alignment for Domain Adaptation
Tuia, Devis; Camps-Valls, Gustau
2016-01-01
The wealth of sensory data coming from different modalities has opened numerous opportunities for data analysis. The data are of increasing volume, complexity and dimensionality, thus calling for new methodological innovations towards multimodal data processing. However, multimodal architectures must rely on models able to adapt to changes in the data distribution. Differences in the density functions can be due to changes in acquisition conditions (pose, illumination), sensors characteristics (number of channels, resolution) or different views (e.g. street level vs. aerial views of a same building). We call these different acquisition modes domains, and refer to the adaptation problem as domain adaptation. In this paper, instead of adapting the trained models themselves, we alternatively focus on finding mappings of the data sources into a common, semantically meaningful, representation domain. This field of manifold alignment extends traditional techniques in statistics such as canonical correlation analysis (CCA) to deal with nonlinear adaptation and possibly non-corresponding data pairs between the domains. We introduce a kernel method for manifold alignment (KEMA) that can match an arbitrary number of data sources without needing corresponding pairs, just few labeled examples in all domains. KEMA has interesting properties: 1) it generalizes other manifold alignment methods, 2) it can align manifolds of very different complexities, performing a discriminative alignment preserving each manifold inner structure, 3) it can define a domain-specific metric to cope with multimodal specificities, 4) it can align data spaces of different dimensionality, 5) it is robust to strong nonlinear feature deformations, and 6) it is closed-form invertible, which allows transfer across-domains and data synthesis. To authors’ knowledge this is the first method addressing all these important issues at once. We also present a reduced-rank version of KEMA for computational
Manifold learning-based subspace distance for machinery damage assessment
NASA Astrophysics Data System (ADS)
Sun, Chuang; Zhang, Zhousuo; He, Zhengjia; Shen, Zhongjie; Chen, Binqiang
2016-03-01
Damage assessment is very meaningful to keep safety and reliability of machinery components, and vibration analysis is an effective way to carry out the damage assessment. In this paper, a damage index is designed by performing manifold distance analysis on vibration signal. To calculate the index, vibration signal is collected firstly, and feature extraction is carried out to obtain statistical features that can capture signal characteristics comprehensively. Then, manifold learning algorithm is utilized to decompose feature matrix to be a subspace, that is, manifold subspace. The manifold learning algorithm seeks to keep local relationship of the feature matrix, which is more meaningful for damage assessment. Finally, Grassmann distance between manifold subspaces is defined as a damage index. The Grassmann distance reflecting manifold structure is a suitable metric to measure distance between subspaces in the manifold. The defined damage index is applied to damage assessment of a rotor and the bearing, and the result validates its effectiveness for damage assessment of machinery component.
NASA Astrophysics Data System (ADS)
Sun, Chuang; Zhang, Zhousuo; Guo, Ting; Luo, Xue; Qu, Jinxiu; Zhang, Chenxuan; Cheng, Wei; Li, Bing
2014-06-01
Viscoelastic sandwich structures (VSS) are widely used in mechanical equipment; their state assessment is necessary to detect structural states and to keep equipment running with high reliability. This paper proposes a novel manifold-manifold distance-based assessment (M2DBA) method for assessing the looseness state in VSSs. In the M2DBA method, a manifold-manifold distance is viewed as a health index. To design the index, response signals from the structure are firstly acquired by condition monitoring technology and a Hankel matrix is constructed by using the response signals to describe state patterns of the VSS. Thereafter, a subspace analysis method, that is, principal component analysis (PCA), is performed to extract the condition subspace hidden in the Hankel matrix. From the subspace, pattern changes in dynamic structural properties are characterized. Further, a Grassmann manifold (GM) is formed by organizing a set of subspaces. The manifold is mapped to a reproducing kernel Hilbert space (RKHS), where support vector data description (SVDD) is used to model the manifold as a hypersphere. Finally, a health index is defined as the cosine of the angle between the hypersphere centers corresponding to the structural baseline state and the looseness state. The defined health index contains similarity information existing in the two structural states, so structural looseness states can be effectively identified. Moreover, the health index is derived by analysis of the global properties of subspace sets, which is different from traditional subspace analysis methods. The effectiveness of the health index for state assessment is validated by test data collected from a VSS subjected to different degrees of looseness. The results show that the health index is a very effective metric for detecting the occurrence and extension of structural looseness. Comparison results indicate that the defined index outperforms some existing state-of-the-art ones.
Potts-model critical manifolds revisited
NASA Astrophysics Data System (ADS)
Scullard, Christian R.; Lykke Jacobsen, Jesper
2016-03-01
We compute critical polynomials for the q-state Potts model on the Archimedean lattices, using a parallel implementation of the algorithm of Jacobsen (2014 J. Phys. A: Math. Theor 47 135001) that gives us access to larger sizes than previously possible. The exact polynomials are computed for bases of size 6 × 6 unit cells, and the root in the temperature variable v={{{e}}}K-1 is determined numerically at q = 1 for bases of size 8 × 8. This leads to improved results for bond percolation thresholds, and for the Potts-model critical manifolds in the real (q, v) plane. In the two most favourable cases, we find now the kagome-lattice threshold to eleven digits and that of the (3,{12}2) lattice to thirteen. Our critical manifolds reveal many interesting features in the antiferromagnetic region of the Potts model, and determine accurately the extent of the Berker-Kadanoff phase for the lattices studied.
Manifold Learning by Preserving Distance Orders.
Ataer-Cansizoglu, Esra; Akcakaya, Murat; Orhan, Umut; Erdogmus, Deniz
2014-03-01
Nonlinear dimensionality reduction is essential for the analysis and the interpretation of high dimensional data sets. In this manuscript, we propose a distance order preserving manifold learning algorithm that extends the basic mean-squared error cost function used mainly in multidimensional scaling (MDS)-based methods. We develop a constrained optimization problem by assuming explicit constraints on the order of distances in the low-dimensional space. In this optimization problem, as a generalization of MDS, instead of forcing a linear relationship between the distances in the high-dimensional original and low-dimensional projection space, we learn a non-decreasing relation approximated by radial basis functions. We compare the proposed method with existing manifold learning algorithms using synthetic datasets based on the commonly used residual variance and proposed percentage of violated distance orders metrics. We also perform experiments on a retinal image dataset used in Retinopathy of Prematurity (ROP) diagnosis.
Adaptive graph construction for Isomap manifold learning
NASA Astrophysics Data System (ADS)
Tran, Loc; Zheng, Zezhong; Zhou, Guoqing; Li, Jiang
2015-03-01
Isomap is a classical manifold learning approach that preserves geodesic distance of nonlinear data sets. One of the main drawbacks of this method is that it is susceptible to leaking, where a shortcut appears between normally separated portions of a manifold. We propose an adaptive graph construction approach that is based upon the sparsity property of the l1 norm. The l1 enhanced graph construction method replaces k-nearest neighbors in the classical approach. The proposed algorithm is first tested on the data sets from the UCI data base repository which showed that the proposed approach performs better than the classical approach. Next, the proposed approach is applied to two image data sets and achieved improved performances over standard Isomap.
Positively invariant manifolds: concept and applications
NASA Astrophysics Data System (ADS)
Sazhin, Sergei S.; Shchepakina, Elena; Sobolev, Vladimir
2017-02-01
In many applications of the system order reduction models, including those focused on spray ignition and combustion processes, it is assumed that all functions in corresponding differential equations are Lipschitzian. This assumption has not been checked in most cases and the cases when these functions were non-Lipschitzian have sometimes been overlooked. This allows us to question the results of application of the conventional theory of integral manifolds to some such systems. The aim of this paper is to demonstrate that even in the case of singular perturbed systems with non-Lipschitzian nonlinearities the order reduction can be performed, using a new concept of positively invariant manifolds. This is illustrated by several examples including the problem of heating, evaporation, ignition and combustion of Diesel fuel sprays.
A Further Examination of Manifold Theory
NASA Astrophysics Data System (ADS)
Treuthardt, Patrick; Grouchy, Rebecca
2015-08-01
Manifold theory, an alternative to density wave theory, proposes that the spiral structure found in disk galaxies is the result of chaotic orbits guided by invariant manifolds. One prediction by this theory is that galaxies with stronger bars have more open spiral arms (i.e. larger pitch angles, P) compared to galaxies with weaker bars. A study by Martínez-García examined a limited sample of 27 galaxies from the Ohio State University Bright Galaxy Survey (OSUBGS) and found a trend between the overall perturbation strength in a galaxy, Qt(r), and P. While Qt(r) is a good measure of bar strength, it is affected by spiral arm torques. Our analysis advances that of Martínez-García by studying approximately 100 galaxies from the OSUBGS that have separate bar and spiral perturbation strength calculations and comparing these values to robust measurements of P via an algorithm developed by Davis et al.
Comparative Performance of Engines Using a Carburetor, Manifold Injection, and Cylinder Injection
NASA Technical Reports Server (NTRS)
Schey, Oscar W; Clark, J Denny
1939-01-01
The comparative performance was determined of engines using three methods of mixing the fuel and the air: the use of a carburetor, manifold injection, and cylinder injection. The tests were made of a single-cylinder engine with a Wright 1820-G air-cooled cylinder. Each method of mixing the fuel and the air was investigated over a range of fuel-air ratios from 0.10 to the limit of stable operation and at engine speeds of 1,500 and 1,900 r.p.m. The comparative performance with a fuel-air ratio of 0.08 was investigated for speeds from 1,300 to 1,900 r.p.m. The results show that the power obtained with each method closely followed the volumetric efficiency; the power was therefore the highest with cylinder injection because this method had less manifold restriction. The values of minimum specific fuel consumption obtained with each method of mixing of fuel and air were the same. For the same engine and cooling conditions, the cylinder temperatures are the same regardless of the method used for mixing the fuel and the air.
Variable Cycle Intake for Reverse Core Engine
NASA Technical Reports Server (NTRS)
Suciu, Gabriel L (Inventor); Chandler, Jesse M (Inventor); Staubach, Joseph B (Inventor)
2016-01-01
A gas generator for a reverse core engine propulsion system has a variable cycle intake for the gas generator, which variable cycle intake includes a duct system. The duct system is configured for being selectively disposed in a first position and a second position, wherein free stream air is fed to the gas generator when in the first position, and fan stream air is fed to the gas generator when in the second position.
Regional manifold learning for deformable registration of brain MR images.
Ye, Dong Hye; Hamm, Jihun; Kwon, Dongjin; Davatzikos, Christos; Pohl, Kilian M
2012-01-01
We propose a method for deformable registration based on learning the manifolds of individual brain regions. Recent publications on registration of medical images advocate the use of manifold learning in order to confine the search space to anatomically plausible deformations. Existing methods construct manifolds based on a single metric over the entire image domain thus frequently miss regional brain variations. We address this issue by first learning manifolds for specific regions and then computing region-specific deformations from these manifolds. We then determine deformations for the entire image domain by learning the global manifold in such a way that it preserves the region-specific deformations. We evaluate the accuracy of our method by applying it to the LPBA40 dataset and measuring the overlap of the deformed segmentations. The result shows significant improvement in registration accuracy on cortex regions compared to other state of the art methods.
Towards a double field theory on para-Hermitian manifolds
NASA Astrophysics Data System (ADS)
Vaisman, Izu
2013-12-01
In a previous paper, we have shown that the geometry of double field theory has a natural interpretation on flat para-Kähler manifolds. In this paper, we show that the same geometric constructions can be made on any para-Hermitian manifold. The field is interpreted as a compatible (pseudo-)Riemannian metric. The tangent bundle of the manifold has a natural, metric-compatible bracket that extends the C-bracket of double field theory. In the para-Kähler case, this bracket is equal to the sum of the Courant brackets of the two Lagrangian foliations of the manifold. Then, we define a canonical connection and an action of the field that correspond to similar objects of double field theory. Another section is devoted to the Marsden-Weinstein reduction in double field theory on para-Hermitian manifolds. Finally, we give examples of fields on some well-known para-Hermitian manifolds.
Towards a double field theory on para-Hermitian manifolds
Vaisman, Izu
2013-12-15
In a previous paper, we have shown that the geometry of double field theory has a natural interpretation on flat para-Kähler manifolds. In this paper, we show that the same geometric constructions can be made on any para-Hermitian manifold. The field is interpreted as a compatible (pseudo-)Riemannian metric. The tangent bundle of the manifold has a natural, metric-compatible bracket that extends the C-bracket of double field theory. In the para-Kähler case, this bracket is equal to the sum of the Courant brackets of the two Lagrangian foliations of the manifold. Then, we define a canonical connection and an action of the field that correspond to similar objects of double field theory. Another section is devoted to the Marsden-Weinstein reduction in double field theory on para-Hermitian manifolds. Finally, we give examples of fields on some well-known para-Hermitian manifolds.
Modified pressure loss model for T-junctions of engine exhaust manifold
NASA Astrophysics Data System (ADS)
Wang, Wenhui; Lu, Xiaolu; Cui, Yi; Deng, Kangyao
2014-11-01
The T-junction model of engine exhaust manifolds significantly influences the simulation precision of the pressure wave and mass flow rate in the intake and exhaust manifolds of diesel engines. Current studies have focused on constant pressure models, constant static pressure models and pressure loss models. However, low model precision is a common disadvantage when simulating engine exhaust manifolds, particularly for turbocharged systems. To study the performance of junction flow, a cold wind tunnel experiment with high velocities at the junction of a diesel exhaust manifold is performed, and the variation in the pressure loss in the T-junction under different flow conditions is obtained. Despite the trend of the calculated total pressure loss coefficient, which is obtained by using the original pressure loss model and is the same as that obtained from the experimental results, large differences exist between the calculated and experimental values. Furthermore, the deviation becomes larger as the flow velocity increases. By improving the Vazsonyi formula considering the flow velocity and introducing the distribution function, a modified pressure loss model is established, which is suitable for a higher velocity range. Then, the new model is adopted to solve one-dimensional, unsteady flow in a D6114 turbocharged diesel engine. The calculated values are compared with the measured data, and the result shows that the simulation accuracy of the pressure wave before the turbine is improved by 4.3% with the modified pressure loss model because gas compressibility is considered when the flow velocities are high. The research results provide valuable information for further junction flow research, particularly the correction of the boundary condition in one-dimensional simulation models.
A Generalization of Warped Product Manifolds with Spin(7) Holonomy
NASA Astrophysics Data System (ADS)
Bilge, Ayşe H.; Uǧuz, Selman
2008-06-01
We define warped-like product manifolds and prove that if M is a 3+3+2 warped-like product manifold where the fibers are connected, simply connected and complete and if M has Spin(7) holonomy, then the fibers are isometric to S3. This work is an abbreviated version of the paper [Bilge, A. H., Uǧuz, S., Warped-like products manifolds with Spin(7) holonomy, submitted for publication].
NASA Technical Reports Server (NTRS)
Dean, Edwin B.
1990-01-01
Design-to-cost is a popular technique for controlling costs. Although qualitative techniques exist for implementing design to cost, quantitative methods are sparse. In the launch vehicle and spacecraft engineering process, the question whether to minimize mass is usually an issue. The lack of quantification in this issue leads to arguments on both sides. This paper presents a mathematical technique which both quantifies the design-to-cost process and the mass/complexity issue. Parametric cost analysis generates and applies mathematical formulas called cost estimating relationships. In their most common forms, they are continuous and differentiable. This property permits the application of the mathematics of differentiable manifolds. Although the terminology sounds formidable, the application of the techniques requires only a knowledge of linear algebra and ordinary differential equations, common subjects in undergraduate scientific and engineering curricula. When the cost c is expressed as a differentiable function of n system metrics, setting the cost c to be a constant generates an n-1 dimensional subspace of the space of system metrics such that any set of metric values in that space satisfies the constant design-to-cost criterion. This space is a differentiable manifold upon which all mathematical properties of a differentiable manifold may be applied. One important property is that an easily implemented system of ordinary differential equations exists which permits optimization of any function of the system metrics, mass for example, over the design-to-cost manifold. A dual set of equations defines the directions of maximum and minimum cost change. A simplified approximation of the PRICE H(TM) production-production cost is used to generate this set of differential equations over [mass, complexity] space. The equations are solved in closed form to obtain the one dimensional design-to-cost trade and design-for-cost spaces. Preliminary results indicate that cost
SSME hot gas manifold flow comparison test
NASA Technical Reports Server (NTRS)
Cox, G. B., Jr.; Dill, C. C.
1988-01-01
An account is given of the High Pressure Fuel Turbopump (HPFT) component of NASA's Alternate Turbopump Development effort, which is aimed at the proper aerodynamic integration of the current Phase II three-duct SSME Hot Gas Manifold (HGM) and the future 'Phase II-plus' two-duct HGM. Half-scale water flow tests of both HGM geometries were conducted to provide initial design data for the HPFT. The results reveal flowfield results and furnish insight into the performance differences between the two HGM flowpaths. Proper design of the HPFT can potentially secure significant flow improvements in either HGM configuration.
Optical manifold for light-emitting diodes
Chaves, Julio C.; Falicoff, Waqidi; Minano, Juan C.; Benitez, Pablo; Parkyn, Jr., William A.; Alvarez, Roberto; Dross, Oliver
2008-06-03
An optical manifold for efficiently combining a plurality of blue LED outputs to illuminate a phosphor for a single, substantially homogeneous output, in a small, cost-effective package. Embodiments are disclosed that use a single or multiple LEDs and a remote phosphor, and an intermediate wavelength-selective filter arranged so that backscattered photoluminescence is recycled to boost the luminance and flux of the output aperture. A further aperture mask is used to boost phosphor luminance with only modest loss of luminosity. Alternative non-recycling embodiments provide blue and yellow light in collimated beams, either separately or combined into white.
Manifold parameter space and its applications
NASA Astrophysics Data System (ADS)
Sato, Atsushi
2004-11-01
We review the several features of the new parameter space which we presented in the previous paper, and show the differentiable manifold properties of this parameter space coordinate. Using this parameter coordinate we calculate three Feynman amplitudes of the vacuum polarization with a gluon loop, a quark loop and a ghost loop in QCD and show that the results are perfectly equal to those of the usual calculations by the Feynman parametrization technique in the scheme of the dimensional regularization. Then we try to calculate the anomalous magnetic moment of an on-shell quark in QCD by using the dimensional regularization, our new parametrization and integral method.
Laplacian embedded regression for scalable manifold regularization.
Chen, Lin; Tsang, Ivor W; Xu, Dong
2012-06-01
Semi-supervised learning (SSL), as a powerful tool to learn from a limited number of labeled data and a large number of unlabeled data, has been attracting increasing attention in the machine learning community. In particular, the manifold regularization framework has laid solid theoretical foundations for a large family of SSL algorithms, such as Laplacian support vector machine (LapSVM) and Laplacian regularized least squares (LapRLS). However, most of these algorithms are limited to small scale problems due to the high computational cost of the matrix inversion operation involved in the optimization problem. In this paper, we propose a novel framework called Laplacian embedded regression by introducing an intermediate decision variable into the manifold regularization framework. By using ∈-insensitive loss, we obtain the Laplacian embedded support vector regression (LapESVR) algorithm, which inherits the sparse solution from SVR. Also, we derive Laplacian embedded RLS (LapERLS) corresponding to RLS under the proposed framework. Both LapESVR and LapERLS possess a simpler form of a transformed kernel, which is the summation of the original kernel and a graph kernel that captures the manifold structure. The benefits of the transformed kernel are two-fold: (1) we can deal with the original kernel matrix and the graph Laplacian matrix in the graph kernel separately and (2) if the graph Laplacian matrix is sparse, we only need to perform the inverse operation for a sparse matrix, which is much more efficient when compared with that for a dense one. Inspired by kernel principal component analysis, we further propose to project the introduced decision variable into a subspace spanned by a few eigenvectors of the graph Laplacian matrix in order to better reflect the data manifold, as well as accelerate the calculation of the graph kernel, allowing our methods to efficiently and effectively cope with large scale SSL problems. Extensive experiments on both toy and real
New hyper-Kähler manifolds by fixing monopoles
NASA Astrophysics Data System (ADS)
Houghton, Conor J.
1997-07-01
The construction of new hyper-Kähler manifolds by taking the infinite monopole mass limit of certain Bogomol'nyi-Prasad-Sommerfield monopole moduli spaces is considered. The one-parameter family of hyper-Kähler manifolds due to Dancer is shown to be an example of such manifolds. A new family of fixed monopole spaces is constructed. They are the moduli spaces of four SU4 monopoles, in the infinite mass limit of two of the monopoles. These manifolds are shown to be nonsingular when the fixed monopole positions are distinct.
30 CFR 36.23 - Engine intake system.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Engine intake system. 36.23 Section 36.23... EQUIPMENT Construction and Design Requirements § 36.23 Engine intake system. (a) Construction. The intake... operator's compartment, to shut off the air supply to the engine. This valve shall be constructed to...
30 CFR 36.23 - Engine intake system.
Code of Federal Regulations, 2014 CFR
2014-07-01
... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Engine intake system. 36.23 Section 36.23... EQUIPMENT Construction and Design Requirements § 36.23 Engine intake system. (a) Construction. The intake... operator's compartment, to shut off the air supply to the engine. This valve shall be constructed to...
30 CFR 36.23 - Engine intake system.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Engine intake system. 36.23 Section 36.23... EQUIPMENT Construction and Design Requirements § 36.23 Engine intake system. (a) Construction. The intake... operator's compartment, to shut off the air supply to the engine. This valve shall be constructed to...
40 CFR 1065.325 - Intake-flow calibration.
Code of Federal Regulations, 2013 CFR
2013-07-01
... CONTROLS ENGINE-TESTING PROCEDURES Calibrations and Verifications Flow-Related Measurements § 1065.325 Intake-flow calibration. (a) Calibrate intake-air flow meters upon initial installation. Follow the... 40 Protection of Environment 34 2013-07-01 2013-07-01 false Intake-flow calibration....
40 CFR 1065.325 - Intake-flow calibration.
Code of Federal Regulations, 2010 CFR
2010-07-01
... CONTROLS ENGINE-TESTING PROCEDURES Calibrations and Verifications Flow-Related Measurements § 1065.325 Intake-flow calibration. (a) Calibrate intake-air flow meters upon initial installation. Follow the... 40 Protection of Environment 32 2010-07-01 2010-07-01 false Intake-flow calibration....
40 CFR 1065.325 - Intake-flow calibration.
Code of Federal Regulations, 2011 CFR
2011-07-01
... CONTROLS ENGINE-TESTING PROCEDURES Calibrations and Verifications Flow-Related Measurements § 1065.325 Intake-flow calibration. (a) Calibrate intake-air flow meters upon initial installation. Follow the... 40 Protection of Environment 33 2011-07-01 2011-07-01 false Intake-flow calibration....
40 CFR 1065.325 - Intake-flow calibration.
Code of Federal Regulations, 2012 CFR
2012-07-01
... CONTROLS ENGINE-TESTING PROCEDURES Calibrations and Verifications Flow-Related Measurements § 1065.325 Intake-flow calibration. (a) Calibrate intake-air flow meters upon initial installation. Follow the... 40 Protection of Environment 34 2012-07-01 2012-07-01 false Intake-flow calibration....
40 CFR 1065.325 - Intake-flow calibration.
Code of Federal Regulations, 2014 CFR
2014-07-01
... CONTROLS ENGINE-TESTING PROCEDURES Calibrations and Verifications Flow-Related Measurements § 1065.325 Intake-flow calibration. (a) Calibrate intake-air flow meters upon initial installation. Follow the... 40 Protection of Environment 33 2014-07-01 2014-07-01 false Intake-flow calibration....
Riemannian Optimization Method on Generalized Flag Manifolds for Complex and Subspace ICA
NASA Astrophysics Data System (ADS)
Nishimori, Yasunori; Akaho, Shotaro; Plumbley, Mark D.
2006-11-01
In this paper we introduce a new class of manifolds, generalized flag manifolds, for the complex and subspace ICA problems. A generalized flag manifold is a manifold consisting of subspaces which are orthogonal to each other. The class of generalized flag manifolds include the class of Grassmann manifolds. We extend the Riemannian optimization method to include this new class of manifolds by deriving the formulas for the natural gradient and geodesics on these manifolds. We show how the complex and subspace ICA problems can be solved by optimization of cost functions on a generalized flag manifold. Computer simulations demonstrate our algorithm gives good performance compared with the ordinary gradient descent method.
The "parity" anomaly on an unorientable manifold
NASA Astrophysics Data System (ADS)
Witten, Edward
2016-11-01
The "parity" anomaly—more accurately described as an anomaly in time-reversal or reflection symmetry—arises in certain theories of fermions coupled to gauge fields and/or gravity in a spacetime of odd dimension. This anomaly has traditionally been studied on orientable manifolds only, but recent developments involving topological superconductors have made it clear that one can get more information by asking what happens on an unorientable manifold. In this paper, we give a full description of the "parity" anomaly for fermions coupled to gauge fields and gravity in 2 +1 dimensions on a possibly unorientable spacetime. We consider an application to topological superconductors and another application to M theory. The application to topological superconductors involves using knowledge of the "parity" anomaly as an ingredient in constructing gapped boundary states of these systems and in particular in gapping the boundary of a ν =16 system in a topologically trivial fashion. The application to M theory involves showing the consistency of the path integral of an M theory membrane on a possibly unorientable worldvolume. In the past, this has been done only in the orientable case.
Fuel rod assembly to manifold attachment
Donck, Harry A.; Veca, Anthony R.; Snyder, Jr., Harold J.
1980-01-01
A fuel element is formed with a plurality of fuel rod assemblies detachably connected to an overhead support with each of the fuel rod assemblies having a gas tight seal with the support to allow internal fission gaseous products to flow without leakage from the fuel rod assemblies into a vent manifold passageway system on the support. The upper ends of the fuel rod assemblies are located at vertically extending openings in the support and upper threaded members are threaded to the fuel rod assemblies to connect the latter to the support. The preferred threaded members are cap nuts having a dome wall encircling an upper threaded end on the fuel rod assembly and having an upper sealing surface for sealing contact with the support. Another and lower seal is achieved by abutting a sealing surface on each fuel rod assembly with the support. A deformable portion on the cap nut locks the latter against inadvertent turning off the fuel rod assembly. Orienting means on the fuel rod and support primarily locates the fuel rods azimuthally for reception of a deforming tool for the cap nut. A cross port in the fuel rod end plug discharges into a sealed annulus within the support, which serves as a circumferential chamber, connecting the manifold gas passageways in the support.
Hamiltonian vector fields on almost symplectic manifolds
NASA Astrophysics Data System (ADS)
Vaisman, Izu
2013-09-01
Let (M, ω) be an almost symplectic manifold (ω is a nondegenerate, not closed, 2-form). We say that a vector field X of M is locally Hamiltonian if LXω = 0, d(i(X)ω) = 0, and it is Hamiltonian if, furthermore, the 1-form i(X)ω is exact. Such vector fields were considered in Fassò and Sansonetto ["Integrable almost-symplectic Hamiltonian systems," J. Math. Phys. 48, 092902 (2007)], 10.1063/1.2783937, under the name of strongly Hamiltonian, and a corresponding action-angle theorem was proven. Almost symplectic manifolds may have few, nonzero, Hamiltonian vector fields, or even none. Therefore, it is important to have examples and it is our aim to provide such examples here. We also obtain some new general results. In particular, we show that the locally Hamiltonian vector fields generate a Dirac structure on M and we state a reduction theorem of the Marsden-Weinstein type. A final section is dedicated to almost symplectic structures on tangent bundles.
Multiple Manifold Clustering Using Curvature Constrained Path
Babaeian, Amir; Bayestehtashk, Alireza; Bandarabadi, Mojtaba
2015-01-01
The problem of multiple surface clustering is a challenging task, particularly when the surfaces intersect. Available methods such as Isomap fail to capture the true shape of the surface near by the intersection and result in incorrect clustering. The Isomap algorithm uses shortest path between points. The main draw back of the shortest path algorithm is due to the lack of curvature constrained where causes to have a path between points on different surfaces. In this paper we tackle this problem by imposing a curvature constraint to the shortest path algorithm used in Isomap. The algorithm chooses several landmark nodes at random and then checks whether there is a curvature constrained path between each landmark node and every other node in the neighborhood graph. We build a binary feature vector for each point where each entry represents the connectivity of that point to a particular landmark. Then the binary feature vectors could be used as a input of conventional clustering algorithm such as hierarchical clustering. We apply our method to simulated and some real datasets and show, it performs comparably to the best methods such as K-manifold and spectral multi-manifold clustering. PMID:26375819
Zhong, Jia; Colicino, Elena; Lin, Xinyi; Mehta, Amar; Kloog, Itai; Zanobetti, Antonella; Byun, Hyang‐Min; Bind, Marie‐Abèle; Cantone, Laura; Prada, Diddier; Tarantini, Letizia; Trevisi, Letizia; Sparrow, David; Vokonas, Pantel; Schwartz, Joel; Baccarelli, Andrea A.
2015-01-01
Background Short‐term fine particles (PM2.5) exposure is associated with reduced heart rate variability, a strong predictor of cardiac mortality among older people. Identifying modifiable factors that confer susceptibility is essential for intervention. We evaluated whether Toll‐like receptor 2 (TLR2) methylation, a reversible immune‐epigenetic process, and its dietary modulation by flavonoids and methyl nutrients, modify susceptibility to heart rate variability effects following PM2.5 exposure. Methods and Results We measured heart rate variability and PM2.5 repeatedly over 11 years (1275 total observations) among 573 elderly men from the Normative Aging Study. Blood TLR2 methylation was analyzed using pyrosequencing. Daily flavonoid and methyl nutrients intakes were assessed through the Food Frequency Questionnaire (FFQ). Every 10 μg/m3 increase in 48‐hour PM2.5 moving average was associated with 7.74% (95% CI: −1.21% to 15.90%; P=0.09), 7.46% (95% CI: 0.99% to 13.50%; P=0.02), 14.18% (95% CI: 1.14% to 25.49%; P=0.03), and 12.94% (95% CI: −2.36% to 25.96%; P=0.09) reductions in root mean square of successive differences, standard deviation of normal‐to‐normal intervals, low‐frequency power, and high‐frequency power, respectively. Higher TLR2 methylation exacerbated the root mean square of successive differences, standard deviation of normal‐to‐normal intervals, low‐frequency, and high‐frequency reductions associated with heightened PM2.5 (Pinteraction=0.006, 0.03, 0.05, 0.04, respectively). Every interquartile‐range increase in flavonoid intake was associated with 5.09% reduction in mean TLR2 methylation (95% CI: 0.12% to 10.06%; P=0.05) and counteracted the effects of PM2.5 on low frequency (Pinteraction=0.05). No significant effect of methyl nutrients on TLR2 methylation was observed. Conclusions Higher TLR2 methylation may confer susceptibility to adverse cardiac autonomic effects of PM2.5 exposure in older individuals. Higher
46 CFR 153.285 - Valving for cargo pump manifolds.
Code of Federal Regulations, 2011 CFR
2011-10-01
... 46 Shipping 5 2011-10-01 2011-10-01 false Valving for cargo pump manifolds. 153.285 Section 153... Piping Systems and Cargo Handling Equipment § 153.285 Valving for cargo pump manifolds. (a) When cargo lines serving different tanks enter a pumproom and connect to the same pump: (1) Each cargo line...
46 CFR 153.285 - Valving for cargo pump manifolds.
Code of Federal Regulations, 2014 CFR
2014-10-01
... 46 Shipping 5 2014-10-01 2014-10-01 false Valving for cargo pump manifolds. 153.285 Section 153... Piping Systems and Cargo Handling Equipment § 153.285 Valving for cargo pump manifolds. (a) When cargo lines serving different tanks enter a pumproom and connect to the same pump: (1) Each cargo line...
46 CFR 153.285 - Valving for cargo pump manifolds.
Code of Federal Regulations, 2013 CFR
2013-10-01
... 46 Shipping 5 2013-10-01 2013-10-01 false Valving for cargo pump manifolds. 153.285 Section 153... Piping Systems and Cargo Handling Equipment § 153.285 Valving for cargo pump manifolds. (a) When cargo lines serving different tanks enter a pumproom and connect to the same pump: (1) Each cargo line...
46 CFR 153.285 - Valving for cargo pump manifolds.
Code of Federal Regulations, 2012 CFR
2012-10-01
... 46 Shipping 5 2012-10-01 2012-10-01 false Valving for cargo pump manifolds. 153.285 Section 153... Piping Systems and Cargo Handling Equipment § 153.285 Valving for cargo pump manifolds. (a) When cargo lines serving different tanks enter a pumproom and connect to the same pump: (1) Each cargo line...
Manifold to uniformly distribute a solid-liquid slurry
Kern, Kenneth C.
1983-01-01
This invention features a manifold that divides a stream of coal particles and liquid into several smaller streams maintaining equal or nearly equal mass compositions. The manifold consists of a horizontal, variable area header having sharp-edged, right-angled take-offs which are oriented on the bottom of the header.
Variable volume combustor with nested fuel manifold system
McConnaughhay, Johnie Franklin; Keener, Christopher Paul; Johnson, Thomas Edward; Ostebee, Heath Michael
2016-09-13
The present application provides a combustor for use with a gas turbine engine. The combustor may include a number of micro-mixer fuel nozzles, a fuel manifold system in communication with the micro-mixer fuel nozzles to deliver a flow of fuel thereto, and a linear actuator to maneuver the micro-mixer fuel nozzles and the fuel manifold system.
Interference evaluation between manifold and wet Christmas tree CP systems
Brasil, S.L.D.C.; Baptista, W.
2000-05-01
Offshore production wells are controlled by valves installed in the marine soil, called wet Christmas trees (WCTs). A manifold receives the production of several wells and transports it to the platform. The manifold is cathodically protected by Al anodes and the WCT by Zn anodes. A computer simulation was carried out to evaluate the interference between the equipment cathodic protection systems.
Characterizing pathological deviations from normality using constrained manifold-learning.
Duchateau, Nicolas; De Craene, Mathieu; Piella, Gemma; Frangi, Alejandro F
2011-01-01
We propose a technique to represent a pathological pattern as a deviation from normality along a manifold structure. Each subject is represented by a map of local motion abnormalities, obtained from a statistical atlas of motion built from a healthy population. The algorithm learns a manifold from a set of patients with varying degrees of the same pathology. The approach extends recent manifold-learning techniques by constraining the manifold to pass by a physiologically meaningful origin representing a normal motion pattern. Individuals are compared to the manifold population through a distance that combines a mapping to the manifold and the path along the manifold to reach its origin. The method is applied in the context of cardiac resynchronization therapy (CRT), focusing on a specific motion pattern of intra-ventricular dyssynchrony called septal flash (SF). We estimate the manifold from 50 CRT candidates with SF and test it on 38 CRT candidates and 21 healthy volunteers. Experiments highlight the need of nonlinear techniques to learn the studied data, and the relevance of the computed distance for comparing individuals to a specific pathological pattern.
Hetero-manifold Regularisation for Cross-modal Hashing.
Zheng, Feng; Tang, Yi; Shao, Ling
2016-12-28
Recently, cross-modal search has attracted considerable attention but remains a very challenging task because of the integration complexity and heterogeneity of the multi-modal data. To address both challenges, in this paper, we propose a novel method termed hetero-manifold regularisation (HMR) to supervise the learning of hash functions for efficient cross-modal search. A hetero-manifold integrates multiple sub-manifolds defined by homogeneous data with the help of cross-modal supervision information. Taking advantages of the hetero-manifold, the similarity between each pair of heterogeneous data could be naturally measured by three order random walks on this hetero-manifold. Furthermore, a novel cumulative distance inequality defined on the hetero-manifold is introduced to avoid the computational difficulty induced by the discreteness of hash codes. By using the inequality, cross-modal hashing is transformed into a problem of hetero-manifold regularised support vector learning. Therefore, the performance of cross-modal search can be significantly improved by seamlessly combining the integrated information of the hetero-manifold and the strong generalisation of the support vector machine. Comprehensive experiments show that the proposed HMR achieve advantageous results over the state-of-the-art methods in several challenging cross-modal tasks.
46 CFR 153.285 - Valving for cargo pump manifolds.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 46 Shipping 5 2010-10-01 2010-10-01 false Valving for cargo pump manifolds. 153.285 Section 153... Piping Systems and Cargo Handling Equipment § 153.285 Valving for cargo pump manifolds. (a) When cargo lines serving different tanks enter a pumproom and connect to the same pump: (1) Each cargo line...
Manifold, bus support and coupling arrangement for solid oxide fuel cells
Parry, G.W.
1988-04-21
Individual, tubular solid oxide fuel cells (SOFCs) are assembled into bundles called a module within a housing, with a plurality of modules arranged end-to-end in a linear, stacked configuration called a string. A common set of piping comprised of a suitable high temperature resistant material (1) provides fuel and air to each module housing, (2) serves as electrically conducting buses, and (3) provides structural support for a string of SOFC modules. Ceramic collars are used to connect fuel and air inlet piping to each of the electrodes in an SOFC module and provide (1) electrical insulation for the current carrying bus bars and gas manifolds, (2) damping for the fuel and air inlet piping, and (3) proper spacing between the fuel and air inlet piping to prevent contact between these tubes and possible damage to the SOFC. 11 figs.
Method for producing a fuel cell manifold seal
Grevstad, Paul E.; Johnson, Carl K.; Mientek, Anthony P.
1982-01-01
A manifold-to-stack seal and sealing method for fuel cell stacks. This seal system solves the problem of maintaining a low leak rate manifold seal as the fuel cell stack undergoes compressive creep. The seal system eliminates the problem of the manifold-to-stack seal sliding against the rough stack surface as the stack becomes shorter because of cell creep, which relative motion destroys the seal. The seal system described herein utilizes a polymer seal frame firmly clamped between the manifold and the stack such that the seal frame moves with the stack. Thus, as the stack creeps, the seal frame creeps with it, and there is no sliding at the rough, tough to seal, stack-to-seal frame interface. Here the sliding is on a smooth easy to seal location between the seal frame and the manifold.
MOCVD manifold switching effects on growth and characterization
NASA Technical Reports Server (NTRS)
Clark, Ivan O.; Fripp, Archibald L.; Jesser, William A.
1991-01-01
A combined modeling and experimental approach is used to quantify the effects of various manifold components on the switching speed in metalorganic chemical vapor deposition (MOCVD). In particular, two alternative vent-run high-speed switching manifold designs suitable for either continuous or interrupted growth have been investigated. Both designs are incorporated in a common manifold, instrumented with a mass spectrometer. The experiments have been performed using nitrogen as the transport gas and argon as the simulated source gas. The advantages and limitations of two designs are discussed. It is found that while constant flow manifold switching systems may have fluid dynamic advantages, care must be taken to minimize sections of the supply manifold with low flow rates if rapid changes in alloy composition are required.
Dual manifold system and method for fluid transfer
Doktycz, Mitchel J.; Bryan, William Louis; Kress, Reid
2003-09-30
A dual-manifold assembly is provided for the rapid, parallel transfer of liquid reagents from a microtiter plate to a solid state microelectronic device having biological sensors integrated thereon. The assembly includes aspiration and dispense manifolds connected by a plurality of conduits. In operation, the aspiration manifold is actuated such that the aspiration manifold is seated onto an array of reagent-filled wells of the microtiter plate. The wells are pressurized to force reagent through conduits toward the dispense manifold. A pressure pulse provided by a standard ink-jet printhead ejects nanoliter-to-picoliter droplets of reagent through an array of printhead orifices and onto test sites on the surface of the microelectronic device.
Dual manifold system and method for fluid transfer
Doktycz, Mitchel J.; Bryan, William Louis; Kress, Reid
2003-05-27
A dual-manifold assembly is provided for the rapid, parallel transfer of liquid reagents from a microtiter plate to a solid state microelectronic device having biological sensors integrated thereon. The assembly includes aspiration and dispense manifolds connected by a plurality of conduits. In operation, the aspiration manifold is actuated such that the aspiration manifold is seated onto an array of reagent-filled wells of the microtiter plate. The wells are pressurized to force reagent through conduits toward the dispense manifold. A pressure pulse provided by a standard ink-jet printhead ejects nanoliter-to-picoliter droplets of reagent through an array of printhead orifices and onto test sites on the surface of the microelectronic device.
Biomedical data analysis by supervised manifold learning.
Alvarez-Meza, A M; Daza-Santacoloma, G; Castellanos-Dominguez, G
2012-01-01
Biomedical data analysis is usually carried out by assuming that the information structure embedded into the biomedical recordings is linear, but that statement actually does not corresponds to the real behavior of the extracted features. In order to improve the accuracy of an automatic system to diagnostic support, and to reduce the computational complexity of the employed classifiers, we propose a nonlinear dimensionality reduction methodology based on manifold learning with multiple kernel representations, which learns the underlying data structure of biomedical information. Moreover, our approach can be used as a tool that allows the specialist to do a visual analysis and interpretation about the studied variables describing the health condition. Obtained results show how our approach maps the original high dimensional features into an embedding space where simple and straightforward classification strategies achieve a suitable system performance.
Initial experience with an Underwater Manifold Centre
Osborne, J.M.
1984-10-01
In July 1983 comingled production from the first two completed wells of the Shell/Esso Underwater Manifold Centre (the UMC), reached the Cormorant Alpha platform. This moment was the culmination of design and development effort which had begun as early as the spring of 1975. But being both the largest subsea system to become operational in the North Sea, and the first designed to the production of several subsea wells, whilst injecting into others, how would the UMC continue to perform. This paper details the operational experience gained to date with the UMC, tracing its brief history since it was first powered up in September 1982 to the present. This is discussed in the main body of the paper under the headings: Commissioning Experience; Operating Experience; Reliability and Maintenance.
Geometric solitons of Hamiltonian flows on manifolds
Song, Chong; Sun, Xiaowei; Wang, Youde
2013-12-15
It is well-known that the LIE (Locally Induction Equation) admit soliton-type solutions and same soliton solutions arise from different and apparently irrelevant physical models. By comparing the solitons of LIE and Killing magnetic geodesics, we observe that these solitons are essentially decided by two families of isometries of the domain and the target space, respectively. With this insight, we propose the new concept of geometric solitons of Hamiltonian flows on manifolds, such as geometric Schrödinger flows and KdV flows for maps. Moreover, we give several examples of geometric solitons of the Schrödinger flow and geometric KdV flow, including magnetic curves as geometric Schrödinger solitons and explicit geometric KdV solitons on surfaces of revolution.
Diffusion Harmonics and Dual Geometry on Carnot Manifolds
NASA Astrophysics Data System (ADS)
Constantin, Sarah
The "curse of dimensionality" motivates the importance of techniques for computing low-dimensional approximations of high-dimensional data. It is often necessary to use nonlinear techniques to recover a low-dimensional manifold embedded via a nonlinear map in a high-dimensional space; this family of techniques is referred to as "manifold learning." The accuracy of manifold-learning-based approximations is founded on asymptotic results that assume the data is drawn from a low-dimensional Riemannian manifold. However, in natural datasets, this assumption is often overly restrictive. In the first part of this thesis we examine a more general class of manifolds known as Carnot manifolds, a type of sub-Riemannian manifold that governs natural phenomena such as chemical kinetics and configuration spaces of jointed objects. We find that diffusion maps can be generalized to Carnot manifolds and that the projection onto diffusion harmonics gives an almost isometric embedding; as a side effect, the diffusion distance is a computationally fast estimate for the shortest distance between two points on a Carnot manifold. We apply this theory to biochemical network data and observe that the chemical kinetics of the EGFR network are governed by a Carnot, but not Riemannian, manifold. In the second part of this thesis we examine the Heisenberg group, a classical example of a Carnot manifold. We obtain a representation-theoretic proof that the eigenfunctions of the sub-Laplacian on SU(2) approach the eigenfunctions of the sub-Laplacian on the Heisenberg group, in the limit as the radius of the sphere becomes large, in analogy with the limiting relationship between the Fourier series on the circle and the Fourier transform on the line. This result also illustrates how projecting onto the sub-Laplacian eigenfunctions of a non-compact Carnot manifold can be locally approximated by projecting onto the sub-Laplacian eigenfunctions of a tangent compact Carnot manifold. In the third part
Stable/unstable slow integral manifolds in critical cases
NASA Astrophysics Data System (ADS)
Shchepakina, Elena
2017-02-01
The paper deals with the problem of a construction of global stable/unstable slow integral manifolds of the singularly perturbed systems in critical cases. In addition to the well-known critical cases a novel scenario of the stability change of the slow integral manifold is considered. All three critical cases leading to the change of the stability are discussed via the Hindmarsh-Rose dynamic model. It is shown that the suitable choice of the additional parameters of the system yields the slow integral manifold with multiple change of its stability.
Manifold Regularized Experimental Design for Active Learning.
Zhang, Lining; Shum, Hubert P H; Shao, Ling
2016-12-02
Various machine learning and data mining tasks in classification require abundant data samples to be labeled for training. Conventional active learning methods aim at labeling the most informative samples for alleviating the labor of the user. Many previous studies in active learning select one sample after another in a greedy manner. However, this is not very effective because the classification models has to be retrained for each newly labeled sample. Moreover, many popular active learning approaches utilize the most uncertain samples by leveraging the classification hyperplane of the classifier, which is not appropriate since the classification hyperplane is inaccurate when the training data are small-sized. The problem of insufficient training data in real-world systems limits the potential applications of these approaches. This paper presents a novel method of active learning called manifold regularized experimental design (MRED), which can label multiple informative samples at one time for training. In addition, MRED gives an explicit geometric explanation for the selected samples to be labeled by the user. Different from existing active learning methods, our method avoids the intrinsic problems caused by insufficiently labeled samples in real-world applications. Various experiments on synthetic datasets, the Yale face database and the Corel image database have been carried out to show how MRED outperforms existing methods.
Learning the manifold of quality ultrasound acquisition.
El-Zehiry, Noha; Yan, Michelle; Good, Sara; Fang, Tong; Zhou, S Kevin; Grady, Leo
2013-01-01
Ultrasound acquisition is a challenging task that requires simultaneous adjustment of several acquisition parameters (the depth, the focus, the frequency and its operation mode). If the acquisition parameters are not properly chosen, the resulting image will have a poor quality and will degrade the patient diagnosis and treatment workflow. Several hardware-based systems for autotuning the acquisition parameters have been previously proposed, but these solutions were largely abandoned because they failed to properly account for tissue inhomogeneity and other patient-specific characteristics. Consequently, in routine practice the clinician either uses population-based parameter presets or manually adjusts the acquisition parameters for each patient during the scan. In this paper, we revisit the problem of autotuning the acquisition parameters by taking a completely novel approach and producing a solution based on image analytics. Our solution is inspired by the autofocus capability of conventional digital cameras, but is significantly more challenging because the number of acquisition parameters is large and the determination of "good quality" images is more difficult to assess. Surprisingly, we show that the set of acquisition parameters which produce images that are favored by clinicians comprise a 1D manifold, allowing for a real-time optimization to maximize image quality. We demonstrate our method for acquisition parameter autotuning on several live patients, showing that our system can start with a poor initial set of parameters and automatically optimize the parameters to produce high quality images.
TESTING DISTANCE ESTIMATORS WITH THE FUNDAMENTAL MANIFOLD
Zaritsky, Dennis; Zabludoff, Ann I.; Gonzalez, Anthony H.
2012-03-20
We demonstrate how the Fundamental Manifold (FM) can be used to cross-calibrate distance estimators even when those 'standard candles' are not found in the same galaxy. Such an approach greatly increases the number of distance measurements that can be utilized to check for systematic distance errors and the types of estimators that can be compared. Here we compare distances obtained using Type Ia supernova (SN Ia), Cepheids, surface brightness fluctuations, the luminosity of the tip of the red giant branch, circumnuclear masers, eclipsing binaries, RR Lyrae stars, and the planetary nebulae luminosity functions. We find no significant discrepancies (differences are <2{sigma}) between distance methods, although differences at the {approx}10% level cannot yet be ruled out. The potential exists for significant refinement because the data used here are heterogeneous B-band magnitudes that will soon be supplanted by homogeneous, near-infrared magnitudes. We illustrate the use of FM distances to (1) revisit the question of the metallicity sensitivity of various estimators, confirming the dependence of SN Ia distances on host galaxy metallicity, and (2) provide an alternative calibration of H{sub 0} that replaces the classical ladder approach in the use of extragalactic distance estimators with one that utilizes data over a wide range of distances simultaneously.
An underlying geometrical manifold for Hamiltonian mechanics
NASA Astrophysics Data System (ADS)
Horwitz, L. P.; Yahalom, A.; Levitan, J.; Lewkowicz, M.
2017-02-01
We show that there exists an underlying manifold with a conformal metric and compatible connection form, and a metric type Hamiltonian (which we call the geometrical picture), that can be put into correspondence with the usual Hamilton-Lagrange mechanics. The requirement of dynamical equivalence of the two types of Hamiltonians, that the momenta generated by the two pictures be equal for all times, is sufficient to determine an expansion of the conformal factor, defined on the geometrical coordinate representation, in its domain of analyticity with coefficients to all orders determined by functions of the potential of the Hamiltonian-Lagrange picture, defined on the Hamilton-Lagrange coordinate representation, and its derivatives. Conversely, if the conformal function is known, the potential of a Hamilton-Lagrange picture can be determined in a similar way. We show that arbitrary local variations of the orbits in the Hamilton-Lagrange picture can be generated by variations along geodesics in the geometrical picture and establish a correspondence which provides a basis for understanding how the instability in the geometrical picture is manifested in the instability of the the original Hamiltonian motion.
Underwater manifold marks North Sea first
Steven, R.R.
1981-01-01
In the 12 years since commercial oil was first discovered in the area, the North Sea has been the stimulus for technologic development unrivalled in the history of the petroleum industry. However, technology still has a long way to go before the North Sea can be mastered, insuring that there will be no let-up as long as there is oil to be found. Evidence for this will be provided later this year when Shell UK exploration and production, on behalf of Shell and Esso, installs an Underwater Manifold Center (UMC) in 490 ft of water as part of the $650-million development of the Central Cormorant field, northeast of Shetland. While the East Shetland Basin can no longer be described as frontier territory in terms of environment and water depth, Shell/Esso's UMC is certainly in the frontier class. The manfold center is characterized as a revolution in underwater techniques and an extremely important landmark, not only in North Sea history but in world oil production. The UMC will have future applications in 3 distinct situations. It will be suitable for economically developing satellite fields out of reach of a centrally installed platform. It also will foster exploitation of marginal oil deposits in combination with a floating platform and possible surface storage. However, perhaps the most exciting possibility raised by the UMC is its application in deep-water production.
Manifold learning based registration algorithms applied to multimodal images.
Azampour, Mohammad Farid; Ghaffari, Aboozar; Hamidinekoo, Azam; Fatemizadeh, Emad
2014-01-01
Manifold learning algorithms are proposed to be used in image processing based on their ability in preserving data structures while reducing the dimension and the exposure of data structure in lower dimension. Multi-modal images have the same structure and can be registered together as monomodal images if only structural information is shown. As a result, manifold learning is able to transform multi-modal images to mono-modal ones and subsequently do the registration using mono-modal methods. Based on this application, in this paper novel similarity measures are proposed for multi-modal images in which Laplacian eigenmaps are employed as manifold learning algorithm and are tested against rigid registration of PET/MR images. Results show the feasibility of using manifold learning as a way of calculating the similarity between multimodal images.
Supervised learning for neural manifold using spatiotemporal brain activity
NASA Astrophysics Data System (ADS)
Kuo, Po-Chih; Chen, Yong-Sheng; Chen, Li-Fen
2015-12-01
Objective. Determining the means by which perceived stimuli are compactly represented in the human brain is a difficult task. This study aimed to develop techniques for the construction of the neural manifold as a representation of visual stimuli. Approach. We propose a supervised locally linear embedding method to construct the embedded manifold from brain activity, taking into account similarities between corresponding stimuli. In our experiments, photographic portraits were used as visual stimuli and brain activity was calculated from magnetoencephalographic data using a source localization method. Main results. The results of 10 × 10-fold cross-validation revealed a strong correlation between manifolds of brain activity and the orientation of faces in the presented images, suggesting that high-level information related to image content can be revealed in the brain responses represented in the manifold. Significance. Our experiments demonstrate that the proposed method is applicable to investigation into the inherent patterns of brain activity.
Conformally flat Lorentzian manifolds with special holonomy groups
Galaev, A S
2013-09-30
We obtain a local classification of conformally flat Lorentzian manifolds with special holonomy groups. The corresponding local metrics are certain extensions of Riemannian spaces of constant sectional curvature to Walker metrics. Bibliography: 28 titles.
Fixed points, stable manifolds, weather regimes, and their predictability
Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael
2009-10-27
In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model’s fixed points in phase space. The model dynamics is characterized by the coexistence of multiple ''weather regimes.'' To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, ''bred vectors'' and singular vectors. These results are then verified in the framework of ensemblemore » forecasts issued from clouds (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.« less
Fixed points, stable manifolds, weather regimes, and their predictability
Deremble, Bruno; D'Andrea, Fabio; Ghil, Michael
2009-10-27
In a simple, one-layer atmospheric model, we study the links between low-frequency variability and the model’s fixed points in phase space. The model dynamics is characterized by the coexistence of multiple ''weather regimes.'' To investigate the transitions from one regime to another, we focus on the identification of stable manifolds associated with fixed points. We show that these manifolds act as separatrices between regimes. We track each manifold by making use of two local predictability measures arising from the meteorological applications of nonlinear dynamics, namely, ''bred vectors'' and singular vectors. These results are then verified in the framework of ensemble forecasts issued from clouds (ensembles) of initial states. The divergence of the trajectories allows us to establish the connections between zones of low predictability, the geometry of the stable manifolds, and transitions between regimes.
4. FIRST FLOOR SOUTH WALL, WITH PIPE MANIFOLDS AND (RIGHTCENTER) ...
4. FIRST FLOOR SOUTH WALL, WITH PIPE MANIFOLDS AND (RIGHT-CENTER) PORTABLE STEAM PUMP FOR PIPE MAINTENANCE AND CLEANING - Colgate & Company Jersey City Plant, Building No. B-3, 47-51 York Street, Jersey City, Hudson County, NJ
Flat coordinates for Saito Frobenius manifolds and string theory
NASA Astrophysics Data System (ADS)
Belavin, A. A.; Gepner, D.; Kononov, Ya. A.
2016-12-01
We investigate the connection between the models of topological conformal theory and noncritical string theory with Saito Frobenius manifolds. For this, we propose a new direct way to calculate the flat coordinates using the integral representation for solutions of the Gauss-Manin system connected with a given Saito Frobenius manifold. We present explicit calculations in the case of a singularity of type A n . We also discuss a possible generalization of our proposed approach to SU( N) k /( SU( N) k+1 × U(1)) Kazama-Suzuki theories. We prove a theorem that the potential connected with these models is an isolated singularity, which is a condition for the Frobenius manifold structure to emerge on its deformation manifold. This fact allows using the Dijkgraaf-Verlinde-Verlinde approach to solve similar Kazama-Suzuki models.
Harmonic vector fields on pseudo-Riemannian manifolds
NASA Astrophysics Data System (ADS)
Friswell, R. M.; Wood, C. M.
2017-02-01
The theory of harmonic vector fields on Riemannian manifolds is generalised to pseudo-Riemannian manifolds. The congruence structure of conformal gradient fields on pseudo-Riemannian hyperquadrics and Killing fields on pseudo-Riemannian quadrics is elucidated, and harmonic vector fields of these two types are classified up to congruence. A para-Kähler twisted anti-isometry is used to correlate harmonic vector fields on the quadrics of neutral signature.
Solid state optical refrigeration using stark manifold resonances in crystals
Seletskiy, Denis V.; Epstein, Richard; Hehlen, Markus P.; Sheik-Bahae, Mansoor
2017-02-21
A method and device for cooling electronics is disclosed. The device includes a doped crystal configured to resonate at a Stark manifold resonance capable of cooling the crystal to a temperature of from about 110K to about 170K. The crystal host resonates in response to input from an excitation laser tuned to exploit the Stark manifold resonance corresponding to the cooling of the crystal.
NASA Technical Reports Server (NTRS)
Dittrich, R. T.
1972-01-01
Water flow tests with circumferential inlet and outlet manifolds were conducted to determine factors affecting fluid distribution and pressure losses. Various orifice sizes and manifold geometries were tested over a range of flow velocities. With inlet manifolds, flow distribution was related directly to orifice discharge coefficients. A correlation indicated that nonuniform distribution resulted when the velocity head ratio at the orifice was not in the range of constant discharge coefficient. With outlet manifolds, nonuniform flow was related to static pressure variations along the manifold. Outlet manifolds had appreciably greater pressure losses than comparable inlet manifolds.
Morse theory and Seiberg-Witten monopoles on 3-Manifolds
NASA Astrophysics Data System (ADS)
Lee, Yi-Jen
1997-11-01
This thesis explores the Seiberg-Witten theory on 3- manifolds and its fascinating interplay with Morse theory, surrounding the conjectured equivalence of the Seiberg-Witten invariant of 3-manifolds and a counting invariant of gradient flows of a Morse function. (Conjecture 3.1.1 below). It comes in two main parts, which appear in Chapter 1 and Chapter 3 respectively. Chapter 1 constitutes part of the analytical component and technical details of the main theme. Here we lay down the foundation of the perturbed/unperturbed Seiberg- Witten theory on asymptotically flat 3-manifolds. Chapter 2 serves as an annex between Chapter 1 and Chapter 3. It formulates the conjecture on the equivalence of the Seiberg-Witten invariant and a counting invariant I of gradient flows. We also outline a rough sketch of proof for this conjecture via application of results in Chapter 1. Chapter 3 comprises of the topological component. It calculates the counting invariant I for closed 3- manifolds via circle-valued Morse theory, and equates it (up to a sign) with the Reidemeister torsion of the manifold. Assuming Conjecture 3.1.1, it yields a refinement of the Meng-Taubes theorem. Furthermore, this calculation generalizes to higher dimensional cases (Theorem 3.1.1, Theorem 3.1.2), by way of which, a homotopy invariant of gradient flow is equated with the Reidemeister torsion of the manifold, supposing the Morse complex of the flow is Q-acyclic.
Semisupervised Support Vector Machines With Tangent Space Intrinsic Manifold Regularization.
Sun, Shiliang; Xie, Xijiong
2016-09-01
Semisupervised learning has been an active research topic in machine learning and data mining. One main reason is that labeling examples is expensive and time-consuming, while there are large numbers of unlabeled examples available in many practical problems. So far, Laplacian regularization has been widely used in semisupervised learning. In this paper, we propose a new regularization method called tangent space intrinsic manifold regularization. It is intrinsic to data manifold and favors linear functions on the manifold. Fundamental elements involved in the formulation of the regularization are local tangent space representations, which are estimated by local principal component analysis, and the connections that relate adjacent tangent spaces. Simultaneously, we explore its application to semisupervised classification and propose two new learning algorithms called tangent space intrinsic manifold regularized support vector machines (TiSVMs) and tangent space intrinsic manifold regularized twin SVMs (TiTSVMs). They effectively integrate the tangent space intrinsic manifold regularization consideration. The optimization of TiSVMs can be solved by a standard quadratic programming, while the optimization of TiTSVMs can be solved by a pair of standard quadratic programmings. The experimental results of semisupervised classification problems show the effectiveness of the proposed semisupervised learning algorithms.
Manifold learning of brain MRIs by deep learning.
Brosch, Tom; Tam, Roger
2013-01-01
Manifold learning of medical images plays a potentially important role for modeling anatomical variability within a population with pplications that include segmentation, registration, and prediction of clinical parameters. This paper describes a novel method for learning the manifold of 3D brain images that, unlike most existing manifold learning methods, does not require the manifold space to be locally linear, and does not require a predefined similarity measure or a prebuilt proximity graph. Our manifold learning method is based on deep learning, a machine learning approach that uses layered networks (called deep belief networks, or DBNs) and has received much attention recently in the computer vision field due to their success in object recognition tasks. DBNs have traditionally been too computationally expensive for application to 3D images due to the large number of trainable parameters. Our primary contributions are (1) a much more computationally efficient training method for DBNs that makes training on 3D medical images with a resolution of up to 128 x 128 x 128 practical, and (2) the demonstration that DBNs can learn a low-dimensional manifold of brain volumes that detects modes of variations that correlate to demographic and disease parameters.
Dimensionality reduction of collective motion by principal manifolds
NASA Astrophysics Data System (ADS)
Gajamannage, Kelum; Butail, Sachit; Porfiri, Maurizio; Bollt, Erik M.
2015-01-01
While the existence of low-dimensional embedding manifolds has been shown in patterns of collective motion, the current battery of nonlinear dimensionality reduction methods is not amenable to the analysis of such manifolds. This is mainly due to the necessary spectral decomposition step, which limits control over the mapping from the original high-dimensional space to the embedding space. Here, we propose an alternative approach that demands a two-dimensional embedding which topologically summarizes the high-dimensional data. In this sense, our approach is closely related to the construction of one-dimensional principal curves that minimize orthogonal error to data points subject to smoothness constraints. Specifically, we construct a two-dimensional principal manifold directly in the high-dimensional space using cubic smoothing splines, and define the embedding coordinates in terms of geodesic distances. Thus, the mapping from the high-dimensional data to the manifold is defined in terms of local coordinates. Through representative examples, we show that compared to existing nonlinear dimensionality reduction methods, the principal manifold retains the original structure even in noisy and sparse datasets. The principal manifold finding algorithm is applied to configurations obtained from a dynamical system of multiple agents simulating a complex maneuver called predator mobbing, and the resulting two-dimensional embedding is compared with that of a well-established nonlinear dimensionality reduction method.
Industries use large volumes of water for cooling. The water intakes pull large numbers of fish and other organisms into the cooling systems. EPA issues regulations on intake structures in order to minimize adverse environmental impacts.
The world problem: on the computability of the topology of 4-manifolds
NASA Technical Reports Server (NTRS)
vanMeter, J. R.
2005-01-01
Topological classification of the 4-manifolds bridges computation theory and physics. A proof of the undecidability of the homeomorphy problem for 4-manifolds is outlined here in a clarifying way. It is shown that an arbitrary Turing machine with an arbitrary input can be encoded into the topology of a 4-manifold, such that the 4-manifold is homeomorphic to a certain other 4-manifold if and only if the corresponding Turing machine halts on the associated input. Physical implications are briefly discussed.
14 CFR 23.1091 - Air induction system.
Code of Federal Regulations, 2010 CFR
2010-01-01
... directed into the engine or auxiliary power unit air intake ducts in hazardous quantities. The air intake ducts must be located or protected so as to minimize the hazard of ingestion of foreign matter...
STAR CLUSTERS, GALAXIES, AND THE FUNDAMENTAL MANIFOLD
Zaritsky, Dennis; Zabludoff, Ann I.; Gonzalez, Anthony H. E-mail: azabludoff@as.arizona.edu
2011-02-01
We explore whether global observed properties, specifically half-light radii, mean surface brightness, and integrated stellar kinematics, suffice to unambiguously differentiate galaxies from star clusters, which presumably formed differently and lack dark matter halos. We find that star clusters lie on the galaxy scaling relationship referred to as the fundamental manifold (FM), on the extension of a sequence of compact galaxies, and so conclude that there is no simple way to differentiate star clusters from ultracompact galaxies. By extending the validity of the FM over a larger range of parameter space and a wider set of objects, we demonstrate that the physics that constrains the resulting baryon and dark matter distributions in stellar systems is more general than previously appreciated. The generality of the FM implies (1) that the stellar spatial distribution and kinematics of one type of stellar system do not arise solely from a process particular to that set of systems, such as violent relaxation for elliptical galaxies, but are instead the result of an interplay of all processes responsible for the generic settling of baryons in gravitational potential wells, (2) that the physics of how baryons settle is independent of whether the system is embedded within a dark matter halo, and (3) that peculiar initial conditions at formation or stochastic events during evolution do not ultimately disturb the overall regularity of baryonic settling. We also utilize the relatively simple nature of star clusters to relate deviations from the FM to the age of the stellar population and find that stellar population models systematically and significantly overpredict the mass-to-light ratios of old, metal-rich clusters. We present an empirical calibration of stellar population mass-to-light ratios with age and color. Finally, we use the FM to estimate velocity dispersions for the low surface brightness, outer halo clusters that lack such measurements.
Manifold alignment for classification of multitemporal hyperspectral image data
NASA Astrophysics Data System (ADS)
Yang, Hsiu-Han
Analyzing remotely sensed images to obtain land cover classification maps is an effective approach for acquiring information over landscapes that can be accomplished over extended areas with limited ground surveys. Further, with advances in remote sensing technology, spaceborne hyperspectral sensors provide the capability to acquire a set of images that have both high spectral and temporal resolution. These images are suitable for monitoring and analyzing environmental changes with subtle spectral characteristics. However, inherent characteristics of multitemporal hyperspectral images, including high dimensionality, nonlinearity, and nonstationarity phenomena over time and across large areas, pose several challenges for classification. This research addresses the issues of classification tasks in the presence of spectral shifts within multitemporal hyperspectral images by leveraging the concept of the data manifold. Although manifold learning has been applied successfully in single image hyperspectral data classification to address high dimensionality and nonlinear spectral responses, research related to manifold learning for multitemporal classification studies is limited. The proposed approaches utilize spectral signatures and spatial proximity to construct similar "local" geometries of temporal images. By aligning these underlying manifolds optimally, the impacts of nonstationary effects are mitigated and classification is accomplished in a representative temporal data manifold. "Global" manifolds learned from temporal hyperspectral images have a major advantage in faithful representation of the data in an image, such as retaining relationships between different classes. Local manifolds are favored in discriminating difficult classes and for computation efficiency. A new hybrid global-local manifold alignment method that combines the advantages of global and local manifolds for effective multitemporal image classification is also proposed. Results illustrate the
[A new algorithm for NIR modeling based on manifold learning].
Hong, Ming-Jian; Wen, Zhi-Yu; Zhang, Xiao-Hong; Wen, Quan
2009-07-01
Manifold learning is a new kind of algorithm originating from the field of machine learning to find the intrinsic dimensionality of numerous and complex data and to extract most important information from the raw data to develop a regression or classification model. The basic assumption of the manifold learning is that the high-dimensional data measured from the same object using some devices must reside on a manifold with much lower dimensions determined by a few properties of the object. While NIR spectra are characterized by their high dimensions and complicated band assignment, the authors may assume that the NIR spectra of the same kind of substances with different chemical concentrations should reside on a manifold with much lower dimensions determined by the concentrations, according to the above assumption. As one of the best known algorithms of manifold learning, locally linear embedding (LLE) further assumes that the underlying manifold is locally linear. So, every data point in the manifold should be a linear combination of its neighbors. Based on the above assumptions, the present paper proposes a new algorithm named least square locally weighted regression (LS-LWR), which is a kind of LWR with weights determined by the least squares instead of a predefined function. Then, the NIR spectra of glucose solutions with various concentrations are measured using a NIR spectrometer and LS-LWR is verified by predicting the concentrations of glucose solutions quantitatively. Compared with the existing algorithms such as principal component regression (PCR) and partial least squares regression (PLSR), the LS-LWR has better predictability measured by the standard error of prediction (SEP) and generates an elegant model with good stability and efficiency.
Diffusion in narrow channels on curved manifolds
NASA Astrophysics Data System (ADS)
Chacón-Acosta, Guillermo; Pineda, Inti; Dagdug, Leonardo
2013-12-01
In this work, we derive a general effective diffusion coefficient to describe the two-dimensional (2D) diffusion in a narrow and smoothly asymmetric channel of varying width, embedded on a curved surface, in the simple diffusion of non-interacting, point-like particles under no external field. To this end, we extend the generalization of the Kalinay-Percus' projection method [J. Chem. Phys. 122, 204701 (2005); Kalinay-Percus', Phys. Rev. E 74, 041203 (2006)] for the asymmetric channels introduced in [L. Dagdug and I. Pineda, J. Chem. Phys. 137, 024107 (2012)], to project the anisotropic two-dimensional diffusion equation on a curved manifold, into an effective one-dimensional generalized Fick-Jacobs equation that is modified according to the curvature of the surface. For such purpose we construct the whole expansion, writing the marginal concentration as a perturbation series. The lowest order in the perturbation parameter, which corresponds to the Fick-Jacobs equation, contains an additional term that accounts for the curvature of the surface. We explicitly obtain the first-order correction for the invariant effective concentration, which is defined as the correct marginal concentration in one variable, and we obtain the first approximation to the effective diffusion coefficient analogous to Bradley's coefficient [Phys. Rev. E 80, 061142 (2009)] as a function of the metric elements of the surface. In a straightforward manner, we study the perturbation series up to the nth order, and derive the full effective diffusion coefficient for two-dimensional diffusion in a narrow asymmetric channel, with modifications according to the metric terms. This expression is given as D(ξ )=D_0/w^' (ξ )}√{g_1/g_2} lbrace arctan [√{g_2/g_1}(y^' }_0(ξ )+w^' }(ξ )/2)]-arctan [√{g_2/g_1}(y^' }_0(ξ )-w^' }(ξ )/2)] rbrace, which is the main result of our work. Finally, we present two examples of symmetric surfaces, namely, the sphere and the cylinder, and we study certain
Enhanced manifold regularization for semi-supervised classification.
Gan, Haitao; Luo, Zhizeng; Fan, Yingle; Sang, Nong
2016-06-01
Manifold regularization (MR) has become one of the most widely used approaches in the semi-supervised learning field. It has shown superiority by exploiting the local manifold structure of both labeled and unlabeled data. The manifold structure is modeled by constructing a Laplacian graph and then incorporated in learning through a smoothness regularization term. Hence the labels of labeled and unlabeled data vary smoothly along the geodesics on the manifold. However, MR has ignored the discriminative ability of the labeled and unlabeled data. To address the problem, we propose an enhanced MR framework for semi-supervised classification in which the local discriminative information of the labeled and unlabeled data is explicitly exploited. To make full use of labeled data, we firstly employ a semi-supervised clustering method to discover the underlying data space structure of the whole dataset. Then we construct a local discrimination graph to model the discriminative information of labeled and unlabeled data according to the discovered intrinsic structure. Therefore, the data points that may be from different clusters, though similar on the manifold, are enforced far away from each other. Finally, the discrimination graph is incorporated into the MR framework. In particular, we utilize semi-supervised fuzzy c-means and Laplacian regularized Kernel minimum squared error for semi-supervised clustering and classification, respectively. Experimental results on several benchmark datasets and face recognition demonstrate the effectiveness of our proposed method.
Hierarchical discriminant manifold learning for dimensionality reduction and image classification
NASA Astrophysics Data System (ADS)
Chen, Weihai; Zhao, Changchen; Ding, Kai; Wu, Xingming; Chen, Peter C. Y.
2015-09-01
In the field of image classification, it has been a trend that in order to deliver a reliable classification performance, the feature extraction model becomes increasingly more complicated, leading to a high dimensionality of image representations. This, in turn, demands greater computation resources for image classification. Thus, it is desirable to apply dimensionality reduction (DR) methods for image classification. It is necessary to apply DR methods to relieve the computational burden as well as to improve the classification accuracy. However, traditional DR methods are not compatible with modern feature extraction methods. A framework that combines manifold learning based DR and feature extraction in a deeper way for image classification is proposed. A multiscale cell representation is extracted from the spatial pyramid to satisfy the locality constraints for a manifold learning method. A spectral weighted mean filtering is proposed to eliminate noise in the feature space. A hierarchical discriminant manifold learning is proposed which incorporates both category label and image scale information to guide the DR process. Finally, the image representation is generated by concatenating dimensionality reduced cell representations from the same image. Extensive experiments are conducted to test the proposed algorithm on both scene and object recognition datasets in comparison with several well-established and state-of-the-art methods with respect to classification precision and computational time. The results verify the effectiveness of incorporating manifold learning in the feature extraction procedure and imply that the multiscale cell representations may be distributed on a manifold.
The Equivariant Cohomology Theory of Twisted Generalized Complex Manifolds
NASA Astrophysics Data System (ADS)
Lin, Yi
2008-07-01
It has been shown recently by Kapustin and Tomasiello that the mathematical notion of Hamiltonian actions on twisted generalized Kähler manifolds is in perfect agreement with the physical notion of general (2, 2) gauged sigma models with three-form fluxes. In this article, we study the twisted equivariant cohomology theory of Hamiltonian actions on H-twisted generalized complex manifolds. If the manifold satisfies the {overline{partial} partial}-lemma, we establish the equivariant formality theorem. If in addition, the manifold satisfies the generalized Kähler condition, we prove the Kirwan injectivity in this setting. We then consider the Hamiltonian action of a torus on an H-twisted generalized Calabi-Yau manifold and extend to this case the Duistermaat-Heckman theorem for the push-forward measure. As a side result, we show in this paper that the generalized Kähler quotient of a generalized Kähler vector space can never have a (cohomologically) non-trivial twisting. This gives a negative answer to a question asked by physicists whether one can construct (2, 2) gauged linear sigma models with non-trivial fluxes.
Locating an atmospheric contamination source using slow manifolds
NASA Astrophysics Data System (ADS)
Tang, Wenbo; Haller, George; Baik, Jong-Jin; Ryu, Young-Hee
2009-04-01
Finite-size particle motion in fluids obeys the Maxey-Riley equations, which become singular in the limit of infinitesimally small particle size. Because of this singularity, finding the source of a dispersed set of small particles is a numerically ill-posed problem that leads to exponential blowup. Here we use recent results on the existence of a slow manifold in the Maxey-Riley equations to overcome this difficulty in source inversion. Specifically, we locate the source of particles by projecting their dispersed positions on a time-varying slow manifold, and by advecting them on the manifold in backward time. We use this technique to locate the source of a hypothetical anthrax release in an unsteady three-dimensional atmospheric wind field in an urban street canyon.
Why Deep Learning Works: A Manifold Disentanglement Perspective.
Brahma, Pratik Prabhanjan; Wu, Dapeng; She, Yiyuan
2016-10-01
Deep hierarchical representations of the data have been found out to provide better informative features for several machine learning applications. In addition, multilayer neural networks surprisingly tend to achieve better performance when they are subject to an unsupervised pretraining. The booming of deep learning motivates researchers to identify the factors that contribute to its success. One possible reason identified is the flattening of manifold-shaped data in higher layers of neural networks. However, it is not clear how to measure the flattening of such manifold-shaped data and what amount of flattening a deep neural network can achieve. For the first time, this paper provides quantitative evidence to validate the flattening hypothesis. To achieve this, we propose a few quantities for measuring manifold entanglement under certain assumptions and conduct experiments with both synthetic and real-world data. Our experimental results validate the proposition and lead to new insights on deep learning.
Manifold learning for robust classification of hyperspectral data
NASA Astrophysics Data System (ADS)
Kim, Wonkook
Accurate land cover classification that ensures robust mapping under diverse acquisition conditions is important in environmental studies where the identification of the land cover changes and its quantification have critical implications for management practices, functioning of ecosystems, and impact of climate. While remote sensing data have served as a useful tool for large scale monitoring of the earth, hyperspectral data offer an enhanced capability for more accurate land cover classification. However, constructing a robust classification framework for hyperspectral data poses issues that stem from inherent properties of hyperspectral data, including highly correlated spectral bands, high dimensionality of data, nonlinear spectral responses, and nonstationarity of samples in space and time. This dissertation addresses the issues in hyperspectral data classification by leveraging the concept of manifolds. A manifold is a nonlinear low dimensional subspace that is supported by data samples. Manifolds can be exploited in developing robust feature extraction and classification methods that are pertinent to the aforementioned issues. In this dissertation, various manifold learning algorithms that are widely used in machine learning community are investigated for the classification of hyperspectral data. Performance of global and local manifold learning methods is investigated in terms of (a) parameter values, (b) number of features retained, and (c) scene characteristics of hyperspectral data. The empirical study involving several data sets with diverse characteristics is outlined in Chapter 3. Results indicate that the manifold coordinates produce generally higher classification accuracies compared to those obtained by linear feature extraction methods, when they are used with proper settings. Chapter 4 addresses two limitations in manifold learning---(a) heavy computational requirements and (b) lack of attention to spatial context---which limits the applicability
Rigidity of complete noncompact bach-flat n-manifolds
NASA Astrophysics Data System (ADS)
Chu, Yawei; Feng, Pinghua
2012-11-01
Let (Mn,g) be a complete noncompact Bach-flat n-manifold with the positive Yamabe constant and constant scalar curvature. Assume that the L2-norm of the trace-free Riemannian curvature tensor R∘m is finite. In this paper, we prove that (Mn,g) is a constant curvature space if the L-norm of R∘m is sufficiently small. Moreover, we get a gap theorem for (Mn,g) with positive scalar curvature. This can be viewed as a generalization of our earlier results of 4-dimensional Bach-flat manifolds with constant scalar curvature R≥0 [Y.W. Chu, A rigidity theorem for complete noncompact Bach-flat manifolds, J. Geom. Phys. 61 (2011) 516-521]. Furthermore, when n>9, we derive a rigidity result for R<0.
Qualitative Features of High Lift Hovering Dynamics and Inertial Manifolds
NASA Astrophysics Data System (ADS)
Gustafson, K.; Leben, R.; McArthur, J.; Mundt, M.
1996-03-01
Hovering aerodynamics, such as that practiced by dragonflys, hummingbirds, and certain other small insects, utilizes special patterns of vorticity to generate high lift flows. Such lift as we measure it computationally on the airfoil surface is in good agreement with downstream thrust measured in the physical laboratory. In this paper we examine the qualitative signatures of this dynamical system. A connection to the theory of inertial manifolds, more specifically the instance of time-dependent slow manifolds, is initiated. Additional interest attaches to the fact that in our compact computational domain, the forcing is on the boundary. Because of its highly oscillatory nature, in this dynamics one proceeds rapidly up the bifurcation ladder at relatively low Reynolds numbers. Thus, aside from its intrinsic interest, the hover model provides an attractive vehicle for a better understanding of dynamical system attractor dynamics and inertial manifold theory.
Monopoles on the Bryant-Salamon G2-manifolds
NASA Astrophysics Data System (ADS)
Oliveira, Goncalo
2014-12-01
G2-monopoles are solutions to gauge theoretical equations on noncompact 7-manifolds of G2 holonomy. We shall study this equation on the 3 Bryant-Salamon manifolds. We construct examples of G2-monopoles on two of these manifolds, namely the total space of the bundle of anti-self-dual two forms over the S4 and CP2. These are the first nontrivial examples of G2-monopoles. Associated with each monopole there is a parameter m ∈R+, known as the mass of the monopole. We prove that under a symmetry assumption, for each given m ∈R+ there is a unique monopole with mass m. We also find explicit irreducible G2-instantons on Λ-2(S4) and on Λ-2(CP2) . The third Bryant-Salamon G2-metric lives on the spinor bundle over the 3-sphere. In this case we produce a vanishing theorem for monopoles.
NASA Astrophysics Data System (ADS)
Aspiras, Theus H.; Asari, Vijayan K.; Sakla, Wesam
2015-03-01
The human brain has the capability to process high quantities of data quickly for detection and recognition tasks. These tasks are made simpler by the understanding of data, which intentionally removes redundancies found in higher dimensional data and maps the data onto a lower dimensional space. The brain then encodes manifolds created in these spaces, which reveal a specific state of the system. We propose to use a recurrent neural network, the nonlinear line attractor (NLA) network, for the encoding of these manifolds as specific states, which will draw untrained data towards one of the specific states that the NLA network has encoded. We propose a Gaussian-weighted modular architecture for reducing the computational complexity of the conventional NLA network. The proposed architecture uses a neighborhood approach for establishing the interconnectivity of neurons to obtain the manifolds. The modified NLA network has been implemented and tested on the Electro-Optic Synthetic Vehicle Model Database created by the Air Force Research Laboratory (AFRL), which contains a vast array of high resolution imagery with several different lighting conditions and camera views. It is observed that the NLA network has the capability for representing high dimensional data for the recognition of the objects of interest through its new learning strategy. A nonlinear dimensionality reduction scheme based on singular value decomposition has found to be very effective in providing a low dimensional representation of the dataset. Application of the reduced dimensional space on the modified NLA algorithm would provide fast and more accurate recognition performance for real time applications.
On pseudo-Riemannian manifolds with many Killing spinors
Alekseevsky, D. V.; Cortes, V.
2009-02-02
Let M be a pseudo-Riemannian spin manifold of dimension n and signature s and denote by N the rank of the real spinor bundle. We prove that M is locally homogeneous if it admits more than (3/4)N independent Killing spinors with the same Killing number, unless n {identical_to} 1(mod 4) and s {identical_to} 3(mod 4). We also prove that M is locally homogeneous if it admits k{sub +} independent Killing spinors with Killing number {lambda} and k{sub -} independent Killing spinors with Killing number -{lambda} such that k{sub +}+k{sub -}>(3/2)N, unless n {identical_to} s {identical_to} 3(mod 4). Similarly, a pseudo-Riemannian manifold with more than (3/4)N independent conformal Killing spinors is conformally locally homogeneous. For (positive or negative) definite metrics, the bounds (3/4)N and (3/2)N in the above results can be relaxed to (1/2)N and N, respectively. Furthermore, we prove that a pseudo-Riemannnian spin manifold with more than (3/4)N parallel spinors is flat and that (1/4)N parallel spinors suffice if the metric is definite. Similarly, a Riemannnian spin manifold with more than (3/8)N Killing spinors with the Killing number {lambda}(set-membership sign)R has constant curvature 4{lambda}{sup 2}. For Lorentzian or negative definite metrics the same is true with the bound (1/2)N. Finally, we give a classification of (not necessarily complete) Riemannian manifolds admitting Killing spinors, which provides an inductive construction of such manifolds.
Postoperative 3D spine reconstruction by navigating partitioning manifolds
Kadoury, Samuel; Labelle, Hubert Parent, Stefan
2016-03-15
Purpose: The postoperative evaluation of scoliosis patients undergoing corrective treatment is an important task to assess the strategy of the spinal surgery. Using accurate 3D geometric models of the patient’s spine is essential to measure longitudinal changes in the patient’s anatomy. On the other hand, reconstructing the spine in 3D from postoperative radiographs is a challenging problem due to the presence of instrumentation (metallic rods and screws) occluding vertebrae on the spine. Methods: This paper describes the reconstruction problem by searching for the optimal model within a manifold space of articulated spines learned from a training dataset of pathological cases who underwent surgery. The manifold structure is implemented based on a multilevel manifold ensemble to structure the data, incorporating connections between nodes within a single manifold, in addition to connections between different multilevel manifolds, representing subregions with similar characteristics. Results: The reconstruction pipeline was evaluated on x-ray datasets from both preoperative patients and patients with spinal surgery. By comparing the method to ground-truth models, a 3D reconstruction accuracy of 2.24 ± 0.90 mm was obtained from 30 postoperative scoliotic patients, while handling patients with highly deformed spines. Conclusions: This paper illustrates how this manifold model can accurately identify similar spine models by navigating in the low-dimensional space, as well as computing nonlinear charts within local neighborhoods of the embedded space during the testing phase. This technique allows postoperative follow-ups of spinal surgery using personalized 3D spine models and assess surgical strategies for spinal deformities.
Real-analytic hypersurfaces in complex manifolds
NASA Astrophysics Data System (ADS)
Vitushkin, A. G.
1985-04-01
functions holomorphic in M cannot, in general, be continued to this part of the neighbourhood. These examples are only fascinating fragments of the trend in modern complex analysis discussed in this paper. We discuss the basic stages in the development of this trend, concentrating attention on recent results. Our subject matter is hypersurfaces in \\mathbf C^n and in other complex manifolds that are non-degenerate in the sense of Levi, the forms of representing these surfaces, their automorphism groups, the geometry of Chern-Moser chains, the continuation of holomorphic maps, questions of classifications, and others.
Light transport on path-space manifolds
NASA Astrophysics Data System (ADS)
Jakob, Wenzel Alban
-stepping limitations of the theory, they often suffer from unusably slow convergence; improvements to this situation have been hampered by the lack of a thorough theoretical understanding. We address these problems by developing a new theory of path-space light transport which, for the first time, cleanly incorporates specular scattering into the standard framework. Most of the results obtained in the analysis of the ideally smooth case can also be generalized to rendering of glossy materials and volumetric scattering so that this dissertation also provides a powerful new set of tools for dealing with them. The basis of our approach is that each specular material interaction locally collapses the dimension of the space of light paths so that all relevant paths lie on a submanifold of path space. We analyze the high-dimensional differential geometry of this submanifold and use the resulting information to construct an algorithm that is able to "walk" around on it using a simple and efficient equation-solving iteration. This manifold walking algorithm then constitutes the key operation of a new type of Markov Chain Monte Carlo (MCMC) rendering method that computes lighting through very general families of paths that can involve arbitrary combinations of specular, near-specular, glossy, and diffuse surface interactions as well as isotropic or highly anisotropic volume scattering. We demonstrate our implementation on a range of challenging scenes and evaluate it against previous methods.
Manifold, bus support and coupling arrangement for solid oxide fuel cells
Parry, Gareth W.
1989-01-01
Individual, tubular solid oxide fuel cells (SOFCs) are assembled into bundles called a module within a housing, with a plurality of modules arranged end-to-end in a linear, stacked configuration called a string. A common set of piping comprised of a suitable high temperture resistant material (1) provides fuel and air to each module housing, (2) serves as electrically conducting buses, and (3) provides structural support for a string of SOFC modules. The piping thus forms a manfold for directing fuel and air to each module in a string and makes electrical contact with the module's anode and cathode to conduct the DC power generated by the SOFC. The piping also provides structureal support for each individual module and maintains each string of modules as a structurally integral unit for ensuring high strength in a large 3-dimensional array of SOFC modules. Ceramic collars are used to connect fuel and air inlet piping to each of the electrodes in an SOFC module and provide (1) electrical insulation for the current carrying bus bars and gas manifolds, (2) damping for the fuel and air inlet piping, and (3) proper spacing between the fuel and air inlet piping to prevent contact between these tubes and possible damage to the SOFC.
Geometry and physics of pseudodifferential operators on manifolds
NASA Astrophysics Data System (ADS)
Esposito, Giampiero; Napolitano, George M.
2016-09-01
A review is made of the basic tools used in mathematics to define a calculus for pseudodifferential operators on Riemannian manifolds endowed with a connection: existence theorem for the function that generalizes the phase; analogue of Taylor's theorem; torsion and curvature terms in the symbolic calculus; the two kinds of derivative acting on smooth sections of the cotangent bundle of the Riemannian manifold; the concept of symbol as an equivalence class. Physical motivations and applications are then outlined, with emphasis on Green functions of quantum field theory and Parker's evaluation of Hawking radiation.
Donaldson Invariants for Non-Simply Connected Manifolds
NASA Astrophysics Data System (ADS)
Mariño, Marcos; Moore, Gregory
We study Coulomb branch (``u-plane'') integrals for supersymmetric SU(2),SO(3) Yang-Mills theory on 4-manifolds X of b1(X)>0, b2+(X)= 1. Using wall-crossing arguments we derive expressions for the Donaldson invariants for manifolds with b1(X)>0, b2+(X)>0. Explicit expressions for , where Fg is a Riemann surface of genus g are obtained using Kronecker's double series identity. The result might be useful in future studies of quantum cohomology.
Parallel second-order tensors on Vaisman manifolds
NASA Astrophysics Data System (ADS)
Bejan, Cornelia Livia; Crasmareanu, Mircea
The aim of this paper is to study the class of parallel tensor fields α of (0, 2)-type in a Vaisman geometry (M,J,g). A sufficient condition for the reduction of such symmetric tensors α to a constant multiple of g is given by the skew-symmetry of α with respect to the complex structure J. As an application of the main result, we prove that certain vector fields on a P0K-manifold turn out to be Killing. Also, we connect our main result with the Weyl connection of conformal geometry as well as with possible Ricci solitons in P0K manifolds.
Girardet, J-P; Rieu, D; Bocquet, A; Bresson, J-L; Briend, A; Chouraqui, J-P; Darmaun, D; Dupont, C; Frelut, M-L; Hankard, R; Goulet, O; Simeoni, U; Turck, D; Vidailhet, M
2014-05-01
Very early in life, sodium intake correlates with blood pressure level. This warrants limiting the consumption of sodium by children. However, evidence regarding exact sodium requirements in that age range is lacking. This article focuses on the desirable sodium intake according to age as suggested by various groups of experts, on the levels of sodium intake recorded in consumption surveys, and on the public health strategies implemented to reduce salt consumption in the pediatric population. Practical recommendations are given by the Committee on nutrition of the French Society of Pediatrics in order to limit salt intake in children.
92. STARBOARD CATAPULT HYDRAULIC MANIFOLD FORWARD LOOKING AFT SHOWING ...
92. STARBOARD CATAPULT HYDRAULIC MANIFOLD - FORWARD LOOKING AFT SHOWING THE SEVEN (7) DISCHARGE LINES FROM THE SEVEN (7) HYDRAULIC PUMPS THROUGH SHUT-OFF VALVES TO ACCUMULATOR TANKS. - U.S.S. HORNET, Puget Sound Naval Shipyard, Sinclair Inlet, Bremerton, Kitsap County, WA
Nonparametric Bayes Classification and Hypothesis Testing on Manifolds
Bhattacharya, Abhishek; Dunson, David
2012-01-01
Our first focus is prediction of a categorical response variable using features that lie on a general manifold. For example, the manifold may correspond to the surface of a hypersphere. We propose a general kernel mixture model for the joint distribution of the response and predictors, with the kernel expressed in product form and dependence induced through the unknown mixing measure. We provide simple sufficient conditions for large support and weak and strong posterior consistency in estimating both the joint distribution of the response and predictors and the conditional distribution of the response. Focusing on a Dirichlet process prior for the mixing measure, these conditions hold using von Mises-Fisher kernels when the manifold is the unit hypersphere. In this case, Bayesian methods are developed for efficient posterior computation using slice sampling. Next we develop Bayesian nonparametric methods for testing whether there is a difference in distributions between groups of observations on the manifold having unknown densities. We prove consistency of the Bayes factor and develop efficient computational methods for its calculation. The proposed classification and testing methods are evaluated using simulation examples and applied to spherical data applications. PMID:22754028
Multiple Frameworks?: Evidence of Manifold Conceptions in Individual Cognitive Structure.
ERIC Educational Resources Information Center
Taber, Keith S.
2000-01-01
Reports that learners' alternative ideas in science may be coherent, stable, and theory-like. Studies how a learner can simultaneously hold several alternative explanatory schemes, each of which is persistent over time and applied coherently across a wide range of overlapping contexts. Concludes that the manifold nature of learners' conceptions…
Manifold learning on brain functional networks in aging.
Qiu, Anqi; Lee, Annie; Tan, Mingzhen; Chung, Moo K
2015-02-01
We propose a new analysis framework to utilize the full information of brain functional networks for computing the mean of a set of brain functional networks and embedding brain functional networks into a low-dimensional space in which traditional regression and classification analyses can be easily employed. For this, we first represent the brain functional network by a symmetric positive matrix computed using sparse inverse covariance estimation. We then impose a Log-Euclidean Riemannian manifold structure on brain functional networks whose norm gives a convenient and practical way to define a mean. Finally, based on the fact that the computation of linear operations can be done in the tangent space of this Riemannian manifold, we adopt Locally Linear Embedding (LLE) to the Log-Euclidean Riemannian manifold space in order to embed the brain functional networks into a low-dimensional space. We show that the integration of the Log-Euclidean manifold with LLE provides more efficient and succinct representation of the functional network and facilitates regression analysis, such as ridge regression, on the brain functional network to more accurately predict age when compared to that of the Euclidean space of functional networks with LLE. Interestingly, using the Log-Euclidean analysis framework, we demonstrate the integration and segregation of cortical-subcortical networks as well as among the salience, executive, and emotional networks across lifespan.
Multiscale envelope manifold for enhanced fault diagnosis of rotating machines
NASA Astrophysics Data System (ADS)
Wang, Jun; He, Qingbo; Kong, Fanrang
2015-02-01
The wavelet transform has been widely used in the field of machinery fault diagnosis for its good property of band-pass filtering. However, the filtered signal still faces the contamination of in-band noise. This paper focuses on wavelet enveloping, and proposes a new method, called multiscale envelope manifold (MEM), to extract the envelope information of fault impacts with in-band noise suppression. The MEM addresses manifold learning on the wavelet envelopes at multiple scales. Specifically, the proposed method is conducted by three following steps. First, the continuous wavelet transform (CWT) with complex Morlet wavelet base is introduced to obtain the wavelet envelopes at all scales. Second, the wavelet envelopes are restricted in one or more narrow scale bands to simply include the envelope information of fault impacts. The scale band is determined through a smoothness index-based (SI-based) selection method by considering the impulsiveness inside the power spectrum. Third, the manifold learning algorithm is conducted on the wavelet envelopes at selected scales to extract the intrinsic envelope manifold of fault-related impulses. The MEM combines the envelope information at multiple scales in a nonlinear approach, and may thus preserve the factual envelope structure of machinery fault. Simulation studies and experimental verifications confirm that the new method is effective for enhanced fault diagnosis of rotating machines.
Manifold learning for object tracking with multiple nonlinear models.
Nascimento, Jacinto C; Silva, Jorge G; Marques, Jorge S; Lemos, Joao M
2014-04-01
This paper presents a novel manifold learning algorithm for high-dimensional data sets. The scope of the application focuses on the problem of motion tracking in video sequences. The framework presented is twofold. First, it is assumed that the samples are time ordered, providing valuable information that is not presented in the current methodologies. Second, the manifold topology comprises multiple charts, which contrasts to the most current methods that assume one single chart, being overly restrictive. The proposed algorithm, Gaussian process multiple local models (GP-MLM), can deal with arbitrary manifold topology by decomposing the manifold into multiple local models that are probabilistic combined using Gaussian process regression. In addition, the paper presents a multiple filter architecture where standard filtering techniques are integrated within the GP-MLM. The proposed approach exhibits comparable performance of state-of-the-art trackers, namely multiple model data association and deep belief networks, and compares favorably with Gaussian process latent variable models. Extensive experiments are presented using real video data, including a publicly available database of lip sequences and left ventricle ultrasound images, in which the GP-MLM achieves state of the art results.
Sampling from Determinantal Point Processes for Scalable Manifold Learning.
Wachinger, Christian; Golland, Polina
2015-01-01
High computational costs of manifold learning prohibit its application for large datasets. A common strategy to overcome this problem is to perform dimensionality reduction on selected landmarks and to successively embed the entire dataset with the Nyström method. The two main challenges that arise are: (i) the landmarks selected in non-Euclidean geometries must result in a low reconstruction error, (ii) the graph constructed from sparsely sampled landmarks must approximate the manifold well. We propose to sample the landmarks from determinantal distributions on non-Euclidean spaces. Since current determinantal sampling algorithms have the same complexity as those for manifold learning, we present an efficient approximation with linear complexity. Further, we recover the local geometry after the sparsification by assigning each landmark a local covariance matrix, estimated from the original point set. The resulting neighborhood selection .based on the Bhattacharyya distance improves the embedding of sparsely sampled manifolds. Our experiments show a significant performance improvement compared to state-of-the-art landmark selection techniques on synthetic and medical data.
Sampling from Determinantal Point Processes for Scalable Manifold Learning
Golland, Polina
2015-01-01
High computational costs of manifold learning prohibit its application for large datasets. A common strategy to overcome this problem is to perform dimensionality reduction on selected landmarks and to successively embed the entire dataset with the Nyström method. The two main challenges that arise are: (i) the landmarks selected in non-Euclidean geometries must result in a low reconstruction error, (ii) the graph constructed from sparsely sampled landmarks must approximate the manifold well. We propose to sample the landmarks from determinantal distributions on non-Euclidean spaces. Since current determinantal sampling algorithms have the same complexity as those for manifold learning, we present an efficient approximation with linear complexity. Further, we recover the local geometry after the sparsification by assigning each landmark a local covariance matrix, estimated from the original point set. The resulting neighborhood selection based on the Bhattacharyya distance improves the embedding of sparsely sampled manifolds. Our experiments show a significant performance improvement compared to state-of-the-art landmark selection techniques on synthetic and medical data. PMID:26221713
Bounding the heat trace of a Calabi-Yau manifold
NASA Astrophysics Data System (ADS)
Fiset, Marc-Antoine; Walcher, Johannes
2015-09-01
The SCHOK bound states that the number of marginal deformations of certain two-dimensional conformal field theories is bounded linearly from above by the number of relevant operators. In conformal field theories defined via sigma models into Calabi-Yau manifolds, relevant operators can be estimated, in the point-particle approximation, by the low-lying spectrum of the scalar Laplacian on the manifold. In the strict large volume limit, the standard asymptotic expansion of Weyl and Minakshisundaram-Pleijel diverges with the higher-order curvature invariants. We propose that it would be sufficient to find an a priori uniform bound on the trace of the heat kernel for large but finite volume. As a first step in this direction, we then study the heat trace asymptotics, as well as the actual spectrum of the scalar Laplacian, in the vicinity of a conifold singularity. The eigenfunctions can be written in terms of confluent Heun functions, the analysis of which gives evidence that regions of large curvature will not prevent the existence of a bound of this type. This is also in line with general mathematical expectations about spectral continuity for manifolds with conical singularities. A sharper version of our results could, in combination with the SCHOK bound, provide a basis for a global restriction on the dimension of the moduli space of Calabi-Yau manifolds.
Energy identity for harmonic maps into standard stationary Lorentzian manifolds
NASA Astrophysics Data System (ADS)
Han, Xiaoli; Zhao, Liang; Zhu, Miaomiao
2017-04-01
For a harmonic map from a closed Riemann surface into a standard stationary Lorentzian manifold, we prove that its Hopf differential is holomorphic. Moreover, we prove that for a sequence of such maps with their energy uniformly bounded, the Lorentzian energy identity holds during the blow-up process.
Warped product Finsler manifolds from Hamiltonian point of view
NASA Astrophysics Data System (ADS)
Joharinad, Parvaneh
In this paper, the Finslerian warped product structures are introduced as Hamiltonian formalism without restricting Finsler functions to be absolutely homogeneous. Afterwards, the constituents of the related variational problem and Finslerian connections of this warped product are obtained according to those of its constructing Finsler manifolds.
Subsea manifolds optimization -- The combination of mature and new technologies
Paulo, C.A.S.
1996-12-31
Subsea equipment can now be considered a mature option for offshore field developments. In Brazil, since the first oil in Campos Basin, different concepts ranging from one-atmosphere chambers to deepwater guidelineless X-mas trees, have been tested, contributing to this development. The experience acquired during these years makes it possible to combine the proven systems with new technologies being developed, for the design of subsea manifolds. The main target is more efficiency and cost reduction. When choosing a manifold concept, a usual rule is applicable: the simpler the better. The maturity, confidence and reliability obtained, allow the usage of resident hydraulically actuated valves, simplifying considerably the manifold arrangement. Other contributions come from: the reduction of piping bend radius allowed by the new pigs; the increased reliability of subsea instrumentation and chokes, allowing elimination of the gas-lift-test flowline; and the development of the direct vertical connection, that turns subsea tie-ins into very fast and easy operations. Combining all that with the new technology of a multiphase meter (to eliminate the test flowline and even the test separator on the platform), one can achieve a cost effective solution. This paper describes the possibilities of simplifying the subsea manifolds and presents a comparison of different designs. The usage of mature technology combined with the new developments, can help the industry to make deep water developments profitable, worldwide.
Energy Minimization on Manifolds for Docking Flexible Molecules.
Mirzaei, Hanieh; Zarbafian, Shahrooz; Villar, Elizabeth; Mottarella, Scott; Beglov, Dmitri; Vajda, Sandor; Paschalidis, Ioannis Ch; Vakili, Pirooz; Kozakov, Dima
2015-03-10
In this paper, we extend a recently introduced rigid body minimization algorithm, defined on manifolds, to the problem of minimizing the energy of interacting flexible molecules. The goal is to integrate moving the ligand in six dimensional rotational/translational space with internal rotations around rotatable bonds within the two molecules. We show that adding rotational degrees of freedom to the rigid moves of the ligand results in an overall optimization search space that is a manifold to which our manifold optimization approach can be extended. The effectiveness of the method is shown for three different docking problems of increasing complexity. First, we minimize the energy of fragment-size ligands with a single rotatable bond as part of a protein mapping method developed for the identification of binding hot spots. Second, we consider energy minimization for docking a flexible ligand to a rigid protein receptor, an approach frequently used in existing methods. In the third problem, we account for flexibility in both the ligand and the receptor. Results show that minimization using the manifold optimization algorithm is substantially more efficient than minimization using a traditional all-atom optimization algorithm while producing solutions of comparable quality. In addition to the specific problems considered, the method is general enough to be used in a large class of applications such as docking multidomain proteins with flexible hinges. The code is available under open source license (at http://cluspro.bu.edu/Code/Code_Rigtree.tar) and with minimal effort can be incorporated into any molecular modeling package.
Pseudo-Riemannian manifold of mixmaster dynamical systems
NASA Astrophysics Data System (ADS)
Szydlowski, M.; Lapeta, A.
1990-08-01
The local instability of mixmaster dynamical systems and their generalization to higher dimensions is discussed. The mixmaster Hamiltonian dynamical system is reduced to a geodesic flow on the pseudo-Riemannian space. The geometric structure of the mixmaster dynamical system manifold is investigated in connection with the chaotic beha viour in mixmaster world models.
Slow Integral Manifolds and Control Problems in Critical and Twice Critical Cases
NASA Astrophysics Data System (ADS)
Sobolev, Vladimir
2016-06-01
We consider singularly perturbed differential systems in cases where the standard theory to establish a slow integral manifold existence does not work. The theory has traditionally dealt only with perturbation problems near normally hyperbolic manifold of singularities and this manifold is supposed to isolated. Applying transformations we reduce the original singularly perturbed problem to a regularized one such that the existence of slow integral manifolds can be established by means of the standard theory. We illustrate our approach by several examples.
33 CFR 149.110 - What are the requirements for pipeline end manifold shutoff valves?
Code of Federal Regulations, 2014 CFR
2014-07-01
... pipeline end manifold shutoff valves? 149.110 Section 149.110 Navigation and Navigable Waters COAST GUARD... EQUIPMENT Pollution Prevention Equipment § 149.110 What are the requirements for pipeline end manifold shutoff valves? Each pipeline end manifold must have a shutoff valve capable of operating both...
33 CFR 149.110 - What are the requirements for pipeline end manifold shutoff valves?
Code of Federal Regulations, 2012 CFR
2012-07-01
... pipeline end manifold shutoff valves? 149.110 Section 149.110 Navigation and Navigable Waters COAST GUARD... EQUIPMENT Pollution Prevention Equipment § 149.110 What are the requirements for pipeline end manifold shutoff valves? Each pipeline end manifold must have a shutoff valve capable of operating both...
33 CFR 149.110 - What are the requirements for pipeline end manifold shutoff valves?
Code of Federal Regulations, 2011 CFR
2011-07-01
... pipeline end manifold shutoff valves? 149.110 Section 149.110 Navigation and Navigable Waters COAST GUARD... EQUIPMENT Pollution Prevention Equipment § 149.110 What are the requirements for pipeline end manifold shutoff valves? Each pipeline end manifold must have a shutoff valve capable of operating both...
33 CFR 149.110 - What are the requirements for pipeline end manifold shutoff valves?
Code of Federal Regulations, 2013 CFR
2013-07-01
... pipeline end manifold shutoff valves? 149.110 Section 149.110 Navigation and Navigable Waters COAST GUARD... EQUIPMENT Pollution Prevention Equipment § 149.110 What are the requirements for pipeline end manifold shutoff valves? Each pipeline end manifold must have a shutoff valve capable of operating both...
Hardy-Littlewood-Sobolev inequalities on compact Riemannian manifolds and applications
NASA Astrophysics Data System (ADS)
Han, Yazhou; Zhu, Meijun
2016-01-01
In this paper we extend Hardy-Littlewood-Sobolev inequalities on compact Riemannian manifolds for dimension n ≠ 2. As one application, we solve a generalized Yamabe problem on locally conformally flat manifolds via a new designed energy functional and a new variational approach. Even for the classic Yamabe problem on locally conformally flat manifolds, our approach provides a new and relatively simpler solution.
Environmental continuous air monitor inlet with combined preseparator and virtual impactor
Rodgers, John C.
2007-06-19
An inlet for an environmental air monitor is described wherein a pre-separator interfaces with ambient environment air and removes debris and insects commonly associated with high wind outdoors and a deflector plate in communication with incoming air from the pre-separator stage, that directs the air radially and downward uniformly into a plurality of accelerator jets located in a manifold of a virtual impactor, the manifold being cylindrical and having a top, a base, and a wall, with the plurality of accelerator jets being located in the top of the manifold and receiving the directed air and accelerating directed air, thereby creating jets of air penetrating into the manifold, where a major flow is deflected to the walls of the manifold and extracted through ports in the walls. A plurality of receiver nozzles are located in the base of the manifold coaxial with the accelerator jets, and a plurality of matching flow restrictor elements are located in the plurality of receiver nozzles for balancing and equalizing the total minor flow among all the plurality of receiver nozzles, through which a lower, fractional flow extracts large particle constituents of the air for collection on a sample filter after passing through the plurality of receiver nozzles and the plurality of matching flow restrictor elements.
NASA Astrophysics Data System (ADS)
Grochowski, Marek; Warhurst, Ben
2015-04-01
In this article we develop some elementary aspects of a theory of symmetry in sub-Lorentzian geometry. First of all we construct invariants characterizing isometric classes of sub-Lorentzian contact 3 manifolds. Next we characterize vector fields which generate isometric and conformal symmetries in general sub-Lorentzian manifolds. We then focus attention back to the case where the underlying manifold is a contact 3 manifold and more specifically when the manifold is also a Lie group and the structure is left-invariant.
[Phosphorus intake and osteoporosis].
Omi, N; Ezawa, I
2001-10-01
Phosphorus (P) is one of the most important nutrients for bone metabolism, such as calcium. In general, P intake is usually adequate in our daily diet, and there is a risk of over-consumption from processed food. On the other hand, Ca intake is not always adequate from the Japanese daily diet. When Ca/P is taken from the daily diet at a level of 0.5 - 2.0, the P intake level dose not affect intestinal Ca absorption. Therefore, it is important not only to pay attention to preventing the over-consumption of P, but also to obtain a sufficient intake of Ca. For the prevention of osteoporosis, it is important to consume sufficient Ca and to maintain and appropriate Ca/P balance from diet.
Exposure to motor vehicle emissions: An intake fraction approach
Marshall, Julian D.
2002-05-22
Motor vehicles are a significant source of population exposure to air pollution. Focusing on California's South Coast Air Basin as a case study, the author combines ambient monitoring station data with hourly time-activity patterns to determine the population intake of motor vehicle emissions during 1996-1999. Three microenvironments are considered wherein the exposure to motor vehicle emissions is higher than in ambient air: in and near vehicles, inside a building that is near a freeway, and inside a residence with an attached garage. Total motor vehicle emissions are taken from the EMFAC model. The 15 million people in the South Coast inhale 0.0048% of primary, nonreactive compounds emitted into the basin by motor vehicles. Intake of motor vehicle emissions is 46% higher than the average ambient concentration times the average breathing rate, because of microenvironments and because of temporal and spatial correlation among breathing rates, concentrations, and population densities. Intake fraction (iF) summarizes the emissions-to-intake relationship as the ratio of population intake to total emissions. iF is a population level exposure metric that incorporates spatial, temporal, and interindividual variability in exposures. iFs can facilitate the calculation of population exposures by distilling complex emissions-transport-receptor relationships. The author demonstrates this point by predicting the population intake of various primary gaseous emissions from motor vehicles, based on the intake fraction for benzene and carbon monoxide.
A Numerical Scheme for Computing Stable and Unstable Manifolds in Nonautonomous Flows
NASA Astrophysics Data System (ADS)
Balasuriya, Sanjeeva
2016-12-01
There are many methods for computing stable and unstable manifolds in autonomous flows. When the flow is nonautonomous, however, difficulties arise since the hyperbolic trajectory to which these manifolds are anchored, and the local manifold emanation directions, are changing with time. This article utilizes recent results which approximate the time-variation of both these quantities to design a numerical algorithm which can obtain high resolution in global nonautonomous stable and unstable manifolds. In particular, good numerical approximation is possible locally near the anchor trajectory. Nonautonomous manifolds are computed for two examples: a Rossby wave situation which is highly chaotic, and a nonautonomus (time-aperiodic) Duffing oscillator model in which the manifold emanation directions are rapidly changing. The numerical method is validated and analyzed in these cases using finite-time Lyapunov exponent fields and exactly known nonautonomous manifolds.
Understanding 3D human torso shape via manifold clustering
NASA Astrophysics Data System (ADS)
Li, Sheng; Li, Peng; Fu, Yun
2013-05-01
Discovering the variations in human torso shape plays a key role in many design-oriented applications, such as suit designing. With recent advances in 3D surface imaging technologies, people can obtain 3D human torso data that provide more information than traditional measurements. However, how to find different human shapes from 3D torso data is still an open problem. In this paper, we propose to use spectral clustering approach on torso manifold to address this problem. We first represent high-dimensional torso data in a low-dimensional space using manifold learning algorithm. Then the spectral clustering method is performed to get several disjoint clusters. Experimental results show that the clusters discovered by our approach can describe the discrepancies in both genders and human shapes, and our approach achieves better performance than the compared clustering method.
Holomorphic Yukawa couplings for complete intersection Calabi-Yau manifolds
NASA Astrophysics Data System (ADS)
Blesneag, Stefan; Buchbinder, Evgeny I.; Lukas, Andre
2017-01-01
We develop methods to compute holomorphic Yukawa couplings for heterotic compactifications on complete intersection Calabi-Yau manifolds, generalising results of an earlier paper for Calabi-Yau hypersurfaces. Our methods are based on constructing the required bundle-valued forms explicitly and evaluating the relevant integrals over the projective ambient space. We also show how our approach relates to an earlier, algebraic one to calculate the holomorphic Yukawa couplings. A vanishing theorem, which we prove, implies that certain Yukawa couplings allowed by low-energy symmetries are zero due to topological reasons. To illustrate our methods, we calculate Yukawa couplings for SU(5)-based standard models on a co-dimension two complete intersection manifold.
Manifold damping of the NLC detuned accelerating structure
NASA Astrophysics Data System (ADS)
Kroll, N.; Thompson, K.; Bane, K.; Gluckstern, R.; Ko, K.; Miller, R.; Ruth, R.
1995-06-01
In order to mitigate the reappearance of the HOM wakefield of a detuned accelerator structure and relax tolerance requirements, we propose to provide low level damping by coupling all cavities to several identical and symmetrically located waveguides (manifolds) which run parallel to each accelerator structure and are terminated at each end by matched loads. The waveguides are designed such that all modes which couple to the acceleration mode are non-propagating at the acceleration mode frequency. Hence the coupling irises can be designed to provide large coupling to higher frequency modes without damping the acceleration mode. Because the higher order modes are detuned, they are localized and have a broad spectrum of phase velocities of both signs. They are therefore capable of coupling effectively to all propagating modes in the waveguides. Methods of analyzing and results obtained for the very complex system of modes in the accelerating structure and manifolds are presented.
Manifold damping of the NLC detuned accelerating structure
Kroll, N.; Thompson, K.; Bane, K.; Ko, K.; Miller, R.; Ruth, R.; Gluckstern, R.
1994-09-01
In order to investigate the reappearance of the HOM wakefield of a detuned accelerator structure and relax tolerance requirements, we propose to provide low level damping by coupling all cavities to several identical and symmetrically located waveguides (manifolds) which run parallel to each accelerator structure and are terminated at each end by matched loads. The waveguides are designed such that all modes which couple to the acceleration mode are non-propagating at the acceleration mode frequency. Hence the coupling irises can be designed to provide large coupling to higher frequency modes without damping the acceleration mode. Because the higher order modes are detuned, they are localized and have a broad spectrum of phase velocities of both signs. They are therefore capable of coupling effectively to all propagating modes in the waveguides. Methods of analyzing and results obtained for the very complex system of modes in the accelerating structure and manifolds are presented.
Local matrix learning in clustering and applications for manifold visualization.
Arnonkijpanich, Banchar; Hasenfuss, Alexander; Hammer, Barbara
2010-05-01
Electronic data sets are increasing rapidly with respect to both, size of the data sets and data resolution, i.e. dimensionality, such that adequate data inspection and data visualization have become central issues of data mining. In this article, we present an extension of classical clustering schemes by local matrix adaptation, which allows a better representation of data by means of clusters with an arbitrary spherical shape. Unlike previous proposals, the method is derived from a global cost function. The focus of this article is to demonstrate the applicability of this matrix clustering scheme to low-dimensional data embedding for data inspection. The proposed method is based on matrix learning for neural gas and manifold charting. This provides an explicit mapping of a given high-dimensional data space to low dimensionality. We demonstrate the usefulness of this method for data inspection and manifold visualization.
Triangular de Rham cohomology of compact Kahler manifolds
Brudnyi, A Yu; Onishchik, A L
2001-02-28
The de Rham H{sup 1}{sub DR}(M,G) of a smooth manifold M with values in a group Lie G is studied. By definition, this is the quotient of the set of flat connections in the trivial principal bundle MxG by the so-called gauge equivalence. The case under consideration is the one when M is a compact Kahler manifold and G is a soluble complex linear algebraic group in a special class containing the Borel subgroups of all complex classical groups and, in particular, the group of all triangular matrices. In this case a description of the set H{sup 1}{sub DR}(M,G) in terms of the cohomology of M with values in the (Abelian) sheaves of flat sections of certain flat Lie algebra bundles with fibre g (the tangent Lie algebra of G) or, equivalently, in terms of the harmonic forms on M representing this cohomology is obtained.
SYZ Mirror Symmetry for Toric Calabi-Yau Manifolds
NASA Astrophysics Data System (ADS)
Lau, Siu Cheong
This thesis gives a procedure to carry out SYZ construction of mirrors with quantum corrections by Fourier transform of open Gromov-Witten invariants. Applying to toric Calabi-Yau manifolds, one obtains the Hori-Iqbel-Vafa mirror together with a map from the Kahler moduli to the complex moduli of the mirror, called the SYZ map. It is conjectured that the SYZ map equals to the inverse mirror map. In dimension two this conjecture is proved, and in dimension three supporting evidences of the equality are studied in various examples. Since the SYZ map is expressed in terms of open Gromov-Witten invariants, this conjectural equality established an enumerative meaning of the inverse mirror map. Moreover a computational method of open Gromov-Witten invariants for toric Calabi-Yau manifolds is invented. As an application, the Landau-Ginzburg mirrors of compact semi-Fano toric surfaces are computed explicitly.
Triangular de Rham cohomology of compact Kahler manifolds
NASA Astrophysics Data System (ADS)
Brudnyi, A. Yu; Onishchik, A. L.
2001-02-01
The de Rham H^1_{DR}(M,G) of a smooth manifold M with values in a group Lie G is studied. By definition, this is the quotient of the set of flat connections in the trivial principal bundle M\\times G by the so-called gauge equivalence. The case under consideration is the one when M is a compact Kahler manifold and G is a soluble complex linear algebraic group in a special class containing the Borel subgroups of all complex classical groups and, in particular, the group of all triangular matrices. In this case a description of the set H^1_{DR}(M,G) in terms of the cohomology of M with values in the (Abelian) sheaves of flat sections of certain flat Lie algebra bundles with fibre \\mathfrak{g} (the tangent Lie algebra of G) or, equivalently, in terms of the harmonic forms on M representing this cohomology is obtained.
Slow manifold and Hannay angle in the spinning top
NASA Astrophysics Data System (ADS)
Berry, M. V.; Shukla, P.
2011-01-01
The spin of a top can be regarded as a fast variable, coupled to the motion of the axis which is slow. In pure precession, the rotation of the axis round a cone (without nutation), can be considered as the result of a reaction from the fast spin. The resulting restriction of the total state space of the top is an illustrative example, at graduate-student level, of the general dynamical concept of the slow manifold. For this case, the slow manifold can be calculated exactly, and expanded as a series of reaction forces (of magnetic type) in powers of slowness, corresponding to a modified precession frequency. The forces correspond to a series for the Hannay angle for the fast motion, describing the location of a point on the top.
Heterotic compactifications on nearly Kähler manifolds
NASA Astrophysics Data System (ADS)
Lechtenfeld, Olaf; Nölle, Christoph; Popov, Alexander D.
2010-09-01
We consider compactifications of heterotic supergravity on anti-de Sitter space, with a six-dimensional nearly Kähler manifold as the internal space. Completing the model proposed by Frey and Lippert [10] with the particular choice of SU(3)/U(1) × U(1) for the internal manifold, we show that it satisfies not only the supersymmetry constraints but also the equations of motion with string corrections of order α'. Furthermore, we present a nonsupersymmetric model. In both solutions we find confirmed a recent result of Ivanov [18] on the connection used for anomaly cancellation. Interestingly, the volume of the internal space is fixed by the supersymmetry constraints and/or the equations of motion.
A Brownian dynamics algorithm for colloids in curved manifolds.
Castro-Villarreal, Pavel; Villada-Balbuena, Alejandro; Méndez-Alcaraz, José Miguel; Castañeda-Priego, Ramón; Estrada-Jiménez, Sendic
2014-06-07
The many-particle Langevin equation, written in local coordinates, is used to derive a Brownian dynamics simulation algorithm to study the dynamics of colloids moving on curved manifolds. The predictions of the resulting algorithm for the particular case of free particles diffusing along a circle and on a sphere are tested against analytical results, as well as with simulation data obtained by means of the standard Brownian dynamics algorithm developed by Ermak and McCammon [J. Chem. Phys. 69, 1352 (1978)] using explicitly a confining external field. The latter method allows constraining the particles to move in regions very tightly, emulating the diffusion on the manifold. Additionally, the proposed algorithm is applied to strong correlated systems, namely, paramagnetic colloids along a circle and soft colloids on a sphere, to illustrate its applicability to systems made up of interacting particles.
Fuel cell stack with internal manifolds for reactant gases
Schnacke, Arthur W.
1985-01-01
A fuel cell stack includes a plurality of plate-like fuel cells arranged along an axis generally parallel to cell thickness with electrically conductive separator plates between each pair of cells. A plurality of axial manifolds are provided at opposite sides of the stack in outer marginal portions beyond the edges of electrodes and electrolyte tiles. Sealing rings prevent cross-leakage of oxidant fuel gases through use of pairs of outwardly extending lips from opposite tile surfaces bonded to first and second electrode frames respectively. The frames provide transition between electrode edges and manifold perimeters. The pairs of extension lips are sealingly bonded together through an electrically insulative sealing ring with wedge shaped fastening members.
Distorted Plane Waves on Manifolds of Nonpositive Curvature
NASA Astrophysics Data System (ADS)
Ingremeau, Maxime
2017-03-01
We will consider the high frequency behaviour of distorted plane waves on manifolds of nonpositive curvature which are Euclidean or hyperbolic near infinity, under the assumption that the curvature is negative close to the trapped set of the geodesic flow and that the topological pressure associated to half the unstable Jacobian is negative. We obtain a precise expression for distorted plane waves in the high frequency limit, similar to the one in Guillarmou and Naud (Am J Math 136:445-479, 2014) in the case of convex co-compact manifolds. In particular, we will show {L_{loc}^∞} bounds on distorted plane waves that are uniform with frequency. We will also show a small-scale equidistribution result for the real part of distorted plane waves, which implies sharp bounds for the volume of their nodal sets.
Fitting manifold surfaces to three-dimensional point clouds.
Grimm, Cindy M; Crisco, Joseph J; Laidlaw, David H
2002-02-01
We present a technique for fitting a smooth, locally parameterized surface model (called the manifold surface model) to unevenly scattered data describing an anatomical structure. These data are acquired from medical imaging modalities such as CT scans or MRI. The manifold surface is useful for problems which require analyzable or parametric surfaces fitted to data acquired from surfaces of arbitrary topology (e.g., entire bones). This surface modeling work is part of a larger project to model and analyze skeletal joints, in particular the complex of small bones within the wrist and hand. To demonstrate the suitability of this model we fit to several different bones in the hand, and to the same bone from multiple people.
A note on para-holomorphic Riemannian-Einstein manifolds
NASA Astrophysics Data System (ADS)
Ida, Cristian; Ionescu, Alexandru; Manea, Adelina
2016-06-01
The aim of this note is the study of Einstein condition for para-holomorphic Riemannian metrics in the para-complex geometry framework. First, we make some general considerations about para-complex Riemannian manifolds (not necessarily para-holomorphic). Next, using a one-to-one correspondence between para-holomorphic Riemannian metrics and para-Kähler-Norden metrics, we study the Einstein condition for a para-holomorphic Riemannian metric and the associated real para-Kähler-Norden metric on a para-complex manifold. Finally, it is shown that every semi-simple para-complex Lie group inherits a natural para-Kählerian-Norden Einstein metric.
Shell's underwater manifold ready for launching. [North Sea
Not Available
1982-02-01
A description is given of the first commercial underwater manifold center (UMC) in the Cormorant field 90 miles northeast of Shelland in the United Kingdom. The massive UMC, weighing 2,425 tons, is 172-ft long, 139-ft wide, and 50-ft high. Pipelines will connect the UMC to the South Cormorant platform more than 4 miles away. The UMC can handle up to nine wells, which are either drilled through it or tied back to it from outlying locations. The system is designed to produce 50,000 b/d of oil and inject 56,000 b/d of water. A discussion is presented of structure design, manifolding and valving, pipelines, and maintenance.
DeepStar evaluation of subsea trees and manifold concepts
Kirkland, K.G.; Richardson, E.M.; Hey, C.
1996-12-31
This paper reviews the results of a study performed for the DeepStar Project, CTR A802-2, Concept Study and Investigation of Key Areas of Interest for Subsea Systems in Deepwater. The report documents the results of a study of subsea manifold systems as applied to the deepwater Gulf of Mexico. Of particular interest is the development of a range of system level philosophies based on recent and ongoing experience from the operators and vendors.
Logarithmic Sobolev Inequalities on Path Spaces Over Riemannian Manifolds
NASA Astrophysics Data System (ADS)
Hsu, Elton P.
Let Wo(M) be the space of paths of unit time length on a connected, complete Riemannian manifold M such that γ(0) =o, a fixed point on M, and ν the Wiener measure on Wo(M) (the law of Brownian motion on M starting at o).If the Ricci curvature is bounded by c, then the following logarithmic Sobolev inequality holds:
Einstein Finsler metrics and killing vector fields on Riemannian manifolds
NASA Astrophysics Data System (ADS)
Cheng, XinYue; Shen, ZhongMin
2017-01-01
In this paper, we use a Killing form on a Riemannian manifold to construct a class of Finsler metrics. We find equations that characterize Einstein metrics among this class. In particular, we construct a family of Einstein metrics on $S^3$ with ${\\rm Ric} = 2 F^2$, ${\\rm Ric}=0$ and ${\\rm Ric}=- 2 F^2$, respectively. This family of metrics provide an important class of Finsler metrics in dimension three, whose Ricci curvature is a constant, but the flag curvature is not.
Barbero-Immirzi parameter, manifold invariants and Euclidean path integrals
NASA Astrophysics Data System (ADS)
Liko, Tomáš
2012-05-01
The Barbero-Immirzi parameter γ appears in the real connection formulation of gravity in terms of the Ashtekar variables, and gives rise to a one-parameter quantization ambiguity in loop quantum gravity. In this paper, we investigate the conditions under which γ will have physical effects in Euclidean quantum gravity. This is done by constructing a well-defined Euclidean path integral for the Holst action with a non-zero cosmological constant on a manifold with a boundary. We find that two general conditions must be satisfied by the spacetime manifold in order for the Holst action and its surface integral to be non-zero: (i) the metric has to be non-diagonalizable; (ii) the Pontryagin number of the manifold has to be non-zero. The latter is a strong topological condition and rules out many of the known solutions to the Einstein field equations. This result leads us to evaluate the on-shell first-order Holst action and corresponding Euclidean partition function on the Taub-NUT-ADS solution. We find that γ shows up as a finite rotation of the on-shell partition function which corresponds to shifts in the energy and entropy of the NUT charge. In an appendix, we also evaluate the Holst action on the Taub-NUT and Taub-bolt solutions in flat spacetime and find that in that case as well γ shows up in the energy and entropy of the NUT and bolt charges. We also present an example whereby the Euler characteristic of the manifold has a non-trivial effect on black hole mergers. Communicated by PRLV Moniz
Sliding regimes on slow manifolds of systems with fast actuators
NASA Technical Reports Server (NTRS)
Sira-Ramirez, Hebertt; Dwyer, Thomas A. W., III
1987-01-01
In this article the slow manifold of a system with actuator parasitics is used as a sliding surface on which a Variable Structure Controller recovers the qualitative properties of the reduced order, closed loop system obtained from an ideal actuator-based feedback controller design. Illustrative examples are presented, where (1) the simplicity of reduced order singular perturbation design methods; and (2) the robustness of Variable Structure sliding modes, are advantageously combined.
Quantum chaos on hyperbolic manifolds: A new approach to cosmology
NASA Astrophysics Data System (ADS)
Tomaschitz, Roman
1992-04-01
We consider classical and quantum motion on multiply connected hyperbolic spaces, which appear as space-like slices in Robertson-Walker cosmologies. The topological structure of these manifolds creates on the one hand bounded chaotic trajectories, and on the other hand quantal bound states whose wave functions can be reconstructed from the chaotic geodesics. We obtain an exact relation between a probabilistic quantum mechanical wave field and the corresponding classical system, which is likewise probabilistic because of the instabilities of the trajectories with respect to the initial conditions. The central part in this reconstruction is played by the fractal limit set of the covering group of the manifold. This limit set determines the bounded chaotic trajectories on the manifold. Its Hausdorff measure and dimension determine the wave function of the quantum mechanical bound state for geodesic motion. We investigate relativistic scalar wave fields in de Sitter cosmologies, coupled to the curvature scalar of the manifold. We study the influence of the topological structure of space-time on their time evolution. Likewise we calculate the time asymptotics of their energies in the early and late stages of the cosmic expansion. While in the late stages both bounded and unbounded states approach the same rest energy, they show significantly different behavior at the beginning of the expansion. While the stable bound states have simple power law behavior, extended states show oscillations in their energy, with a frequency and an amplitude both diverging to infinity, indicating the instability of the quantum field at the beginning of the cosmic expansion.
Curved manifolds with conserved Runge-Lenz vectors
Ngome, J.-P.
2009-12-15
van Holten's algorithm is used to construct Runge-Lenz-type conserved quantities, induced by Killing tensors, on curved manifolds. For the generalized Taub-Newman-Unti-Tamburino metric, the most general external potential such that the combined system admits a conserved Runge-Lenz-type vector is found. In the multicenter case, the subclass of two-center metric exhibits a conserved Runge-Lenz-type scalar.
Underwater manifold centre-drilled cuttings disposal system
Biddlestone, P.A.
1983-09-01
During the construction of the Central Cormorant Underwater Manifold Centre (UMC), it was recognised that the cuttings produced during the drilling of template wells would interfere with UMC operations, if deposited on top of the structure. A dual system was developed and installed on the Stadrill (the unit planned to drill the wells) to remove the cuttings from the rig to the seabed away from the UMC.
A rigidity theorem for complete noncompact Bach-flat manifolds
NASA Astrophysics Data System (ADS)
Chu, Yawei
2011-02-01
Let (M4,g) be a four-dimensional complete noncompact Bach-flat Riemannian manifold with positive Yamabe constant. In this paper, we show that (M4,g) has a constant curvature if it has a nonnegative constant scalar curvature and sufficiently small L2-norm of trace-free Riemannian curvature tensor. Moreover, we get a gap theorem for (M4,g) with positive scalar curvature.
Multirobot Simultaneous Localization and Mapping Using Manifold Representations
2006-07-01
and search; multirobot systems ; simultaneous localization and mapping (SLAM) I . INTRODUCTION Many mobile robot tasks, such as exploration and search...remote operator. The multirobot systems built to meet this challenge are described in [13] and [14]. III . MAPPING ON A MANIFOLD: CORE CONCEPTS The key...is discretized by dividing it into a set of overlapping patches, each of which has finite extent and defines a local (planar) coordinate system . Let
NASA Astrophysics Data System (ADS)
Voronin, A. A.; Zheltikov, A. M.
2017-02-01
Analysis of the group-velocity dispersion (GVD) of atmospheric air with a model that includes the entire manifold of infrared transitions in air reveals a remarkably broad and continuous anomalous-GVD region in the high-frequency wing of the carbon dioxide rovibrational band from approximately 3.5 to 4.2 μm where atmospheric air is still highly transparent and where high-peak-power sources of ultrashort midinfrared pulses are available. Within this range, anomalous dispersion acting jointly with optical nonlinearity of atmospheric air is shown to give rise to a unique three-dimensional dynamics with well-resolved soliton features in the time domain, enabling a highly efficient whole-beam soliton self-compression of such pulses to few-cycle pulse widths.
Localization using omnivision-based manifold particle filters
NASA Astrophysics Data System (ADS)
Wong, Adelia; Yousefhussien, Mohammed; Ptucha, Raymond
2015-01-01
Developing precise and low-cost spatial localization algorithms is an essential component for autonomous navigation systems. Data collection must be of sufficient detail to distinguish unique locations, yet coarse enough to enable real-time processing. Active proximity sensors such as sonar and rangefinders have been used for interior localization, but sonar sensors are generally coarse and rangefinders are generally expensive. Passive sensors such as video cameras are low cost and feature-rich, but suffer from high dimensions and excessive bandwidth. This paper presents a novel approach to indoor localization using a low cost video camera and spherical mirror. Omnidirectional captured images undergo normalization and unwarping to a canonical representation more suitable for processing. Training images along with indoor maps are fed into a semi-supervised linear extension of graph embedding manifold learning algorithm to learn a low dimensional surface which represents the interior of a building. The manifold surface descriptor is used as a semantic signature for particle filter localization. Test frames are conditioned, mapped to a low dimensional surface, and then localized via an adaptive particle filter algorithm. These particles are temporally filtered for the final localization estimate. The proposed method, termed omnivision-based manifold particle filters, reduces convergence lag and increases overall efficiency.
Manifold regularized non-negative matrix factorization with label information
NASA Astrophysics Data System (ADS)
Li, Huirong; Zhang, Jiangshe; Wang, Changpeng; Liu, Junmin
2016-03-01
Non-negative matrix factorization (NMF) as a popular technique for finding parts-based, linear representations of non-negative data has been successfully applied in a wide range of applications, such as feature learning, dictionary learning, and dimensionality reduction. However, both the local manifold regularization of data and the discriminative information of the available label have not been taken into account together in NMF. We propose a new semisupervised matrix decomposition method, called manifold regularized non-negative matrix factorization (MRNMF) with label information, which incorporates the manifold regularization and the label information into the NMF to improve the performance of NMF in clustering tasks. We encode the local geometrical structure of the data space by constructing a nearest neighbor graph and enhance the discriminative ability of different classes by effectively using the label information. Experimental comparisons with the state-of-the-art methods on theCOIL20, PIE, Extended Yale B, and MNIST databases demonstrate the effectiveness of MRNMF.
Robust head pose estimation via supervised manifold learning.
Wang, Chao; Song, Xubo
2014-05-01
Head poses can be automatically estimated using manifold learning algorithms, with the assumption that with the pose being the only variable, the face images should lie in a smooth and low-dimensional manifold. However, this estimation approach is challenging due to other appearance variations related to identity, head location in image, background clutter, facial expression, and illumination. To address the problem, we propose to incorporate supervised information (pose angles of training samples) into the process of manifold learning. The process has three stages: neighborhood construction, graph weight computation and projection learning. For the first two stages, we redefine inter-point distance for neighborhood construction as well as graph weight by constraining them with the pose angle information. For Stage 3, we present a supervised neighborhood-based linear feature transformation algorithm to keep the data points with similar pose angles close together but the data points with dissimilar pose angles far apart. The experimental results show that our method has higher estimation accuracy than the other state-of-art algorithms and is robust to identity and illumination variations.
On the geometry of an atmospheric slow manifold
NASA Astrophysics Data System (ADS)
Camassa, Roberto
We examine the hyperbolic structure and the invariant manifolds of a model proposed by Lorenz to introduce the concept of an atmospheric slow manifold within the framework of dynamical system theory. We address the question of the long time asymptotic behaviour of the system using the (global) geometric point of view. It is shown that the model can be reduced to the classical example of a pendulum coupled to a harmonic oscillator. The dynamical regimes of interest for the slow manifold hypothesis correspond to regions of phase space near the saddle-center fixed point of this model which were not previously explored. These phase space regions are analysed using a combination of Melnikov-type methods and ideas from singular perturbation theory. By using the reversible symmetries of the model, an extension of the Melnikov theory is derived. This extension allows us to find homoclinic orbits and determine their approximation by simply computing the zeros of a certain function, which is constructed in terms of the usual Melnikov function. Countable infinities of global homoclinic bifurcations and existence of chaotic dynamics can be shown to exist by using the new tool.
Metastatic liver tumour segmentation from discriminant Grassmannian manifolds
NASA Astrophysics Data System (ADS)
Kadoury, Samuel; Vorontsov, Eugene; Tang, An
2015-08-01
The early detection, diagnosis and monitoring of liver cancer progression can be achieved with the precise delineation of metastatic tumours. However, accurate automated segmentation remains challenging due to the presence of noise, inhomogeneity and the high appearance variability of malignant tissue. In this paper, we propose an unsupervised metastatic liver tumour segmentation framework using a machine learning approach based on discriminant Grassmannian manifolds which learns the appearance of tumours with respect to normal tissue. First, the framework learns within-class and between-class similarity distributions from a training set of images to discover the optimal manifold discrimination between normal and pathological tissue in the liver. Second, a conditional optimisation scheme computes non-local pairwise as well as pattern-based clique potentials from the manifold subspace to recognise regions with similar labelings and to incorporate global consistency in the segmentation process. The proposed framework was validated on a clinical database of 43 CT images from patients with metastatic liver cancer. Compared to state-of-the-art methods, our method achieves a better performance on two separate datasets of metastatic liver tumours from different clinical sites, yielding an overall mean Dice similarity coefficient of 90.7+/- 2.4 in over 50 tumours with an average volume of 27.3 mm3.
Hyperspectral target detection using manifold learning and multiple target spectra
Ziemann, Amanda K.; Theiler, James; Messinger, David W.
2016-03-31
Imagery collected from satellites and airborne platforms provides an important tool for remotely analyzing the content of a scene. In particular, the ability to remotely detect a specific material within a scene is of critical importance in nonproliferation and other applications. The sensor systems that process hyperspectral images collect the high-dimensional spectral information necessary to perform these detection analyses. For a d-dimensional hyperspectral image, however, where d is the number of spectral bands, it is common for the data to inherently occupy an m-dimensional space with m << d. In the remote sensing community, this has led to recent interestmore » in the use of manifold learning, which seeks to characterize the embedded lower-dimensional, nonlinear manifold that the data discretely approximate. The research presented in this paper focuses on a graph theory and manifold learning approach to target detection, using an adaptive version of locally linear embedding that is biased to separate target pixels from background pixels. Finally, this approach incorporates multiple target signatures for a particular material, accounting for the spectral variability that is often present within a solid material of interest.« less
Cosmic topology of polyhedral double-action manifolds
NASA Astrophysics Data System (ADS)
Aurich, R.; Lustig, S.
2012-12-01
A special class of non-trivial topologies of the spherical space S^3 is investigated with respect to their cosmic microwave background (CMB) anisotropies. The observed correlations of the anisotropies on the CMB sky possess on large separation angles surprising low amplitudes which might be naturally be explained by models of the Universe having a multiconnected spatial space. We analysed in Aurich and Lustig (2012 Class. Quantum Grav. 29 215005) the CMB properties of prism double-action manifolds that are generated by a binary dihedral group D⋆p and a cyclic group Zn up to a group order of 180. Here we extend the CMB analysis to polyhedral double-action manifolds which are generated by the three binary polyhedral groups (T⋆, O⋆, I⋆) and a cyclic group Zn up to a group order of 1000. There are 20 such polyhedral double-action manifolds. Some of them turn out to have even lower CMB correlations on large angles than the Poincaré dodecahedron.
Hyperspectral target detection using manifold learning and multiple target spectra
Ziemann, Amanda K.; Theiler, James; Messinger, David W.
2016-03-31
Imagery collected from satellites and airborne platforms provides an important tool for remotely analyzing the content of a scene. In particular, the ability to remotely detect a specific material within a scene is of critical importance in nonproliferation and other applications. The sensor systems that process hyperspectral images collect the high-dimensional spectral information necessary to perform these detection analyses. For a d-dimensional hyperspectral image, however, where d is the number of spectral bands, it is common for the data to inherently occupy an m-dimensional space with m << d. In the remote sensing community, this has led to recent interest in the use of manifold learning, which seeks to characterize the embedded lower-dimensional, nonlinear manifold that the data discretely approximate. The research presented in this paper focuses on a graph theory and manifold learning approach to target detection, using an adaptive version of locally linear embedding that is biased to separate target pixels from background pixels. Finally, this approach incorporates multiple target signatures for a particular material, accounting for the spectral variability that is often present within a solid material of interest.
SeaStar: Subsea cluster manifold system design and installation
Mason, P.G.T.; Upchurch, J.L.
1996-12-31
The SeaStar Cluster Manifold system was engineered as a low cost alternative to larger and more expensive completion template designs. Utilizing field-proven equipment and installation techniques, it was the first of its kind to be installed in the Gulf of Mexico. The Cluster Manifold system allows the connection of flowlines from adjacent satellite wells and numerous infield flowlines consisting of export, service, and methanol lines. With new technological advances, and a variety of flowline connection systems on the market today, deep water completions are being used with increasing frequency. Subsea operations are becoming more routine and installation times are being reduced. The SeaStar system was successfully installed in Garden Banks Block 70/71 in the Gulf of Mexico during the first quarter of 1995. Currently two 4 x 2-in. 10,000 psi lay-away trees are installed and connected to the manifold. Production is being processed at a Marathon platform in Vermilion Block 386B approximately 13.5 miles away from the subsea installation.
Curvature properties of some class of warped product manifolds
NASA Astrophysics Data System (ADS)
Deszcz, Ryszard; Głogowska, Małgorzata; Jełowicki, Jan; Zafindratafa, Georges
2016-10-01
We prove that warped product manifolds with p-dimensional base, p = 1, 2, satisfy some pseudosymmetry type curvature conditions. These conditions are formed from the metric tensor g, the Riemann-Christoffel curvature tensor R, the Ricci tensor S and the Weyl conformal curvature C of the considered manifolds. The main result of the paper states that if p = 2 and the fiber is a semi-Riemannian space of constant curvature (when n is greater or equal to 5) then the (0, 6)-tensors R ṡ R - Q(S,R) and C ṡ C of such warped products are proportional to the (0, 6)-tensor Q(g,C) and the tensor C is a linear combination of some Kulkarni-Nomizu products formed from the tensors g and S. We also obtain curvature properties of this kind of quasi-Einstein and 2-quasi-Einstein manifolds, and in particular, of the Goedel metric, generalized spherically symmetric metrics and generalized Vaidya metrics.
Conformal manifolds in four dimensions and chiral algebras
NASA Astrophysics Data System (ADS)
Buican, Matthew; Nishinaka, Takahiro
2016-11-01
Any { N }=2 superconformal field theory (SCFT) in four dimensions has a sector of operators related to a two-dimensional chiral algebra containing a Virasoro sub-algebra. Moreover, there are well-known examples of isolated SCFTs whose chiral algebra is a Virasoro algebra. In this note, we consider the chiral algebras associated with interacting { N }=2 SCFTs possessing an exactly marginal deformation that can be interpreted as a gauge coupling (i.e., at special points on the resulting conformal manifolds, free gauge fields appear that decouple from isolated SCFT building blocks). At any point on these conformal manifolds, we argue that the associated chiral algebras possess at least three generators. In addition, we show that there are examples of SCFTs realizing such a minimal chiral algebra: they are certain points on the conformal manifold obtained by considering the low-energy limit of type IIB string theory on the three complex-dimensional hypersurface singularity {x}13+{x}23+{x}33+α {x}1{x}2{x}3+{w}2=0. The associated chiral algebra is the { A }(6) theory of Feigin, Feigin, and Tipunin. As byproducts of our work, we argue that (i) a collection of isolated theories can be conformally gauged only if there is a SUSY moduli space associated with the corresponding symmetry current moment maps in each sector, and (ii) { N }=2 SCFTs with a≥slant c have hidden fermionic symmetries (in the sense of fermionic chiral algebra generators).
Swaminathan, Sumathi; Vaz, Mario; Kurpad, Anura V
2012-08-01
Indian diets derive almost 60 % of their protein from cereals with relatively low digestibility and quality. There have been several surveys of diets and protein intakes in India by the National Nutrition Monitoring Board (NNMB) over the last 25 years, in urban and rural, as well as in slum dwellers and tribal populations. Data of disadvantaged populations from slums, tribals and sedentary rural Indian populations show that the protein intake (mainly from cereals) is about 1 gm/kg/day. However, the protein intake looks less promising in terms of the protein digestibility corrected amino acid score (PDCAAS), using lysine as the first limiting amino acid, where all populations, particularly rural and tribal, appear to have an inadequate quality to their protein intake. The protein: energy (PE) ratio is a measure of dietary quality, and has been used in the 2007 WHO/FAO/UNU report to define reference requirement values with which the adequacy of diets can be evaluated in terms of a protein quality corrected PE ratio. It is likely that about one third of this sedentary rural population is at risk of not meeting their requirements. These levels of risk of deficiency are in a population with relatively low BMI populations, whose diets are also inadequate in fruits and vegetables. Therefore, while the burden of enhancing the quality of protein intake in rural India exists, the quality of the diet, in general, represents a challenge that must be met.
NASA Astrophysics Data System (ADS)
Rosenstock, Sarita; Weatherall, James Owen
2016-10-01
A classic result in the foundations of Yang-Mills theory, due to Barrett [Int. J. Theor. Phys. 30, 1171-1215 (1991)], establishes that given a "generalized" holonomy map from the space of piece-wise smooth, closed curves based at some point of a manifold to a Lie group, there exists a principal bundle with that group as structure group and a principal connection on that bundle such that the holonomy map corresponds to the holonomies of that connection. Barrett also provided one sense in which this "recovery theorem" yields a unique bundle, up to isomorphism. Here we show that something stronger is true: with an appropriate definition of isomorphism between generalized holonomy maps, there is an equivalence of categories between the category whose objects are generalized holonomy maps on a smooth, connected manifold and whose arrows are holonomy isomorphisms, and the category whose objects are principal connections on principal bundles over a smooth, connected manifold. This result clarifies, and somewhat improves upon, the sense of "unique recovery" in Barrett's theorems; it also makes precise a sense in which there is no loss of structure involved in moving from a principal bundle formulation of Yang-Mills theory to a holonomy, or "loop," formulation.
Assessing regional intake fractions in North America.
Humbert, Sebastien; Manneh, Rima; Shaked, Shanna; Wannaz, Cédric; Horvath, Arpad; Deschênes, Louise; Jolliet, Olivier; Margni, Manuele
2009-08-15
This paper develops the IMPACT North America model, a spatially resolved multimedia, multi-pathway, fate, exposure and effect model that includes indoor and urban compartments. IMPACT North America allows geographic differentiation of population exposure of toxic emissions for comparative risk assessment and life cycle impact assessment within U.S. and Canada. It looks at air, water, soil, sediment and vegetation media, and divides North America into several hundred zones. It is nested within a single world box to account for emissions leaving North America. It is a multi-scale model, covering three different spatial scales--indoor, urban and regional--in all zones in North America. Model results are evaluated against monitored emissions and concentrations of benzo(a)pyrene, 2,3,7,8-TCDD and mercury. Most of the chemical concentrations predicted by the model fall within two orders of magnitude of the monitored data. The model shows that urban intake fractions are one order of magnitude higher than rural intake fractions. The model application and importance is demonstrated by a case study on spatially-distributed emissions over the life cycle of diesel fuel. Depending on population densities and agricultural intensities, intake fractions can vary by eight orders of magnitudes, and even limited indoor emissions can lead to intakes comparable to those from outdoor emissions. To accurately assess these variations in intake fraction, we require the essential three original features described in the present paper: i) inclusion of the continental model within a world box for persistent pollutants, ii) addition of an urban box for short- and medium-lived substances (for grid size larger than 100 km), and iii) assess indoor emissions. This model can therefore be used to screen chemicals and assess regionalized intake fractions within North America for population-based human exposure assessment, life cycle impact assessment, and comparative risk assessment. The model can be
On removability of singularities on manifolds for solutions of non-linear elliptic equations
Skrypnik, I I
2003-10-31
A precise condition is found for the removability of a singularity on a smooth manifold for solutions of non-linear second-order elliptic equations of divergence form. The condition is stated in the form of a dependence of the pointwise behaviour of the solution on the distance to the singular manifold. The condition obtained is weaker than Serrin's well-known sufficient condition for the removability of a singularity on a manifold.
The Kastler-Kalau-Walze type theorem for six-dimensional manifolds with boundary
Wang, Jian; Wang, Yong E-mail: wangy581@nenu.edu.cn
2015-05-15
In this paper, we define lower dimensional volumes of spin manifolds with boundary. We compute the lower dimensional volume V ol{sub 6}{sup (1,3)} for 6-dimensional spin manifolds with boundary and derive the gravity on boundary from the noncommutative residue associated with Dirac operators. For 6-dimensional manifolds with boundary, we also get a Kastler-Kalau-Walze type theorem for a general fourth order operator.
NASA Technical Reports Server (NTRS)
1981-01-01
An analytical comparison of the efficiency of solar thermal collector arrays with and without external manifolds is reported. A FORTRAN computer program was written for the computation of the thermal performance of solar thermal collector arrays with and without external manifolds. Arrays constructed from two example solar thermal collectors are computated. Typical external manifold sizes and thermal insulations are presented graphically and are compared with the thermal performance of the collector alone.
Dictionary Pair Learning on Grassmann Manifolds for Image Denoising.
Zeng, Xianhua; Bian, Wei; Liu, Wei; Shen, Jialie; Tao, Dacheng
2015-11-01
Image denoising is a fundamental problem in computer vision and image processing that holds considerable practical importance for real-world applications. The traditional patch-based and sparse coding-driven image denoising methods convert 2D image patches into 1D vectors for further processing. Thus, these methods inevitably break down the inherent 2D geometric structure of natural images. To overcome this limitation pertaining to the previous image denoising methods, we propose a 2D image denoising model, namely, the dictionary pair learning (DPL) model, and we design a corresponding algorithm called the DPL on the Grassmann-manifold (DPLG) algorithm. The DPLG algorithm first learns an initial dictionary pair (i.e., the left and right dictionaries) by employing a subspace partition technique on the Grassmann manifold, wherein the refined dictionary pair is obtained through a sub-dictionary pair merging. The DPLG obtains a sparse representation by encoding each image patch only with the selected sub-dictionary pair. The non-zero elements of the sparse representation are further smoothed by the graph Laplacian operator to remove the noise. Consequently, the DPLG algorithm not only preserves the inherent 2D geometric structure of natural images but also performs manifold smoothing in the 2D sparse coding space. We demonstrate that the DPLG algorithm also improves the structural SIMilarity values of the perceptual visual quality for denoised images using the experimental evaluations on the benchmark images and Berkeley segmentation data sets. Moreover, the DPLG also produces the competitive peak signal-to-noise ratio values from popular image denoising algorithms.
Sobrino Crespo, Carmen; Perianes Cachero, Aránzazu; Puebla Jiménez, Lilian; Barrios, Vicente; Arilla Ferreiro, Eduardo
2014-01-01
The mechanisms for controlling food intake involve mainly an interplay between gut, brain, and adipose tissue (AT), among the major organs. Parasympathetic, sympathetic, and other systems are required for communication between the brain satiety center, gut, and AT. These neuronal circuits include a variety of peptides and hormones, being ghrelin the only orexigenic molecule known, whereas the plethora of other factors are inhibitors of appetite, suggesting its physiological relevance in the regulation of food intake and energy homeostasis. Nutrients generated by food digestion have been proposed to activate G-protein-coupled receptors on the luminal side of enteroendocrine cells, e.g., the L-cells. This stimulates the release of gut hormones into the circulation such as glucagon-like peptide-1 (GLP-1), oxyntomodulin, pancreatic polypeptides, peptide tyrosine tyrosine, and cholecystokinin, which inhibit appetite. Ghrelin is a peptide secreted from the stomach and, in contrast to other gut hormones, plasma levels decrease after a meal and potently stimulate food intake. Other circulating factors such as insulin and leptin relay information regarding long-term energy stores. Both hormones circulate at proportional levels to body fat content, enter the CNS proportionally to their plasma levels, and reduce food intake. Circulating hormones can influence the activity of the arcuate nucleus (ARC) neurons of the hypothalamus, after passing across the median eminence. Circulating factors such as gut hormones may also influence the nucleus of the tractus solitarius (NTS) through the adjacent circumventricular organ. On the other hand, gastrointestinal vagal afferents converge in the NTS of the brainstem. Neural projections from the NTS, in turn, carry signals to the hypothalamus. The ARC acts as an integrative center, with two major subpopulations of neurons influencing appetite, one of them coexpressing neuropeptide Y and agouti-related protein (AgRP) that increases food
Sobrino Crespo, Carmen; Perianes Cachero, Aránzazu; Puebla Jiménez, Lilian; Barrios, Vicente; Arilla Ferreiro, Eduardo
2014-01-01
The mechanisms for controlling food intake involve mainly an interplay between gut, brain, and adipose tissue (AT), among the major organs. Parasympathetic, sympathetic, and other systems are required for communication between the brain satiety center, gut, and AT. These neuronal circuits include a variety of peptides and hormones, being ghrelin the only orexigenic molecule known, whereas the plethora of other factors are inhibitors of appetite, suggesting its physiological relevance in the regulation of food intake and energy homeostasis. Nutrients generated by food digestion have been proposed to activate G-protein-coupled receptors on the luminal side of enteroendocrine cells, e.g., the L-cells. This stimulates the release of gut hormones into the circulation such as glucagon-like peptide-1 (GLP-1), oxyntomodulin, pancreatic polypeptides, peptide tyrosine tyrosine, and cholecystokinin, which inhibit appetite. Ghrelin is a peptide secreted from the stomach and, in contrast to other gut hormones, plasma levels decrease after a meal and potently stimulate food intake. Other circulating factors such as insulin and leptin relay information regarding long-term energy stores. Both hormones circulate at proportional levels to body fat content, enter the CNS proportionally to their plasma levels, and reduce food intake. Circulating hormones can influence the activity of the arcuate nucleus (ARC) neurons of the hypothalamus, after passing across the median eminence. Circulating factors such as gut hormones may also influence the nucleus of the tractus solitarius (NTS) through the adjacent circumventricular organ. On the other hand, gastrointestinal vagal afferents converge in the NTS of the brainstem. Neural projections from the NTS, in turn, carry signals to the hypothalamus. The ARC acts as an integrative center, with two major subpopulations of neurons influencing appetite, one of them coexpressing neuropeptide Y and agouti-related protein (AgRP) that increases food
On the elliptic genera of manifolds of Spin(7) holonomy
Benjamin, Nathan; Harrison, Sarah M.; Kachru, Shamit; Paquette, Natalie M.; Whalen, Daniel
2015-12-16
Superstring compactification on a manifold of Spin(7) holonomy gives rise to a 2d worldsheet conformal field theory with an extended supersymmetry algebra. The N=1 superconformal algebra is extended by additional generators of spins 2 and 5/2, and instead of just superconformal symmetry one has a c = 12 realization of the symmetry group SW(3/2,2). In this paper, we compute the characters of this supergroup and decompose the elliptic genus of a general Spin(7) compactification in terms of these characters. Here, we find suggestive relations to various sporadic groups, which are made more precise in a companion paper.
On the Elliptic Genera of Manifolds of Spin(7) Holonomy
Benjamin, Nathan; Harrison, Sarah M.; Kachru, Shamit; Paquette, Natalie M.; Whalen, Daniel
2015-12-16
Superstring compactification on a manifold of Spin(7) holonomy gives rise to a 2d worldsheet conformal field theory with an extended supersymmetry algebra. The N=1N=1 superconformal algebra is extended by additional generators of spins 2 and 5/2, and instead of just superconformal symmetry one has a c = 12 realization of the symmetry group SW(3/2,2)SW(3/2,2) . In this paper, we compute the characters of this supergroup and decompose the elliptic genus of a general Spin(7) compactification in terms of these characters. We find suggestive relations to various sporadic groups, which are made more precise in a companion paper.
Dynamic Determinants of the Uncontrolled Manifold during Human Quiet Stance
Suzuki, Yasuyuki; Morimoto, Hiroki; Kiyono, Ken; Morasso, Pietro G.; Nomura, Taishin
2016-01-01
Human postural sway during stance arises from coordinated multi-joint movements. Thus, a sway trajectory represented by a time-varying postural vector in the multiple-joint-angle-space tends to be constrained to a low-dimensional subspace. It has been proposed that the subspace corresponds to a manifold defined by a kinematic constraint, such that the position of the center of mass (CoM) of the whole body is constant in time, referred to as the kinematic uncontrolled manifold (kinematic-UCM). A control strategy related to this hypothesis (CoM-control-strategy) claims that the central nervous system (CNS) aims to keep the posture close to the kinematic-UCM using a continuous feedback controller, leading to sway patterns that mostly occur within the kinematic-UCM, where no corrective control is exerted. An alternative strategy proposed by the authors (intermittent control-strategy) claims that the CNS stabilizes posture by intermittently suspending the active feedback controller, in such a way to allow the CNS to exploit a stable manifold of the saddle-type upright equilibrium in the state-space of the system, referred to as the dynamic-UCM, when the state point is on or near the manifold. Although the mathematical definitions of the kinematic- and dynamic-UCM are completely different, both UCMs play similar roles in the stabilization of multi-joint upright posture. The purpose of this study was to compare the dynamic performance of the two control strategies. In particular, we considered a double-inverted-pendulum-model of postural control, and analyzed the two UCMs defined above. We first showed that the geometric configurations of the two UCMs are almost identical. We then investigated whether the UCM-component of experimental sway could be considered as passive dynamics with no active control, and showed that such UCM-component mainly consists of high frequency oscillations above 1 Hz, corresponding to anti-phase coordination between the ankle and hip. We also
Quantum error correcting codes and 4-dimensional arithmetic hyperbolic manifolds
Guth, Larry; Lubotzky, Alexander
2014-08-15
Using 4-dimensional arithmetic hyperbolic manifolds, we construct some new homological quantum error correcting codes. They are low density parity check codes with linear rate and distance n{sup ε}. Their rate is evaluated via Euler characteristic arguments and their distance using Z{sub 2}-systolic geometry. This construction answers a question of Zémor [“On Cayley graphs, surface codes, and the limits of homological coding for quantum error correction,” in Proceedings of Second International Workshop on Coding and Cryptology (IWCC), Lecture Notes in Computer Science Vol. 5557 (2009), pp. 259–273], who asked whether homological codes with such parameters could exist at all.
Crossing of manifolds leads to flat dispersion: Blazed Littrow waveguides
Benisty, H.; Khayam, O.; Piskunov, N.; Kashkarov, P. K.
2011-12-15
We display a photonic embodiment of the Demkov-Ostrovsky solution to the crossing of two manifolds made of equidistant modes thanks to broad periodic waveguides. We find clearly narrowing resonances that signal the singular, flat dispersion case that we had termed ''critical coupling.'' The reconciliation of band-edge confinement and cavity confinement, two pillars of photonics, appear from the guide length dependence of spectra. We suggest the generality of the Demkov-Ostrovsky or critical coupling flat dispersion across all kinds of waves, e.g., electronic and acoustic.
Reduced dynamics and Lagrangian submanifolds of symplectic manifolds
NASA Astrophysics Data System (ADS)
García-Toraño Andrés, E.; Guzmán, E.; Marrero, J. C.; Mestdag, T.
2014-06-01
In this paper, we will see that the symplectic creed by Weinstein ‘everything is a Lagrangian submanifold’ also holds for Hamilton-Poincaré and Lagrange-Poincaré reduction. In fact, we show that solutions of the Hamilton-Poincaré equations and of the Lagrange-Poincaré equations are in one-to-one correspondence with distinguished curves in a Lagrangian submanifold of a symplectic manifold. For this purpose, we will combine the concept of a Tulczyjew triple with Marsden-Weinstein symplectic reduction.
Symmetry and degeneracy manifolds in Jahn-Teller molecules
NASA Astrophysics Data System (ADS)
Mead, C. A.
2013-04-01
We consider problems in dealing with molecular systems of n identical nuclei. One problem is that of finding suitable internal coordinates. For n <= 4, these can be simply the internuclear distances. For n > 4, it is shown that, with perhaps one exception, there is no internal coordinate system that treats all nuclei equivalently. We also consder the properties of conical intersections between two Born-Oppenheimer electronic energy surfaces, in particular the problem of identifying the two coordinates that remove the degeneracy to first order in the near neighborhoods of symmetry manifolds.
Euler-Lagrange formulas for pseudo-Kähler manifolds
NASA Astrophysics Data System (ADS)
Park, JeongHyeong
2016-01-01
Let c be a characteristic form of degree k which is defined on a Kähler manifold of real dimension m > 2 k. Taking the inner product with the Kähler form Ωk gives a scalar invariant which can be considered as a generalized Lovelock functional. The associated Euler-Lagrange equations are a generalized Einstein-Gauss-Bonnet gravity theory; this theory restricts to the canonical formalism if c =c2 is the second Chern form. We extend previous work studying these equations from the Kähler to the pseudo-Kähler setting.
Statistical shape analysis for face movement manifold modeling
NASA Astrophysics Data System (ADS)
Wang, Xiaokan; Mao, Xia; Caleanu, Catalin-Daniel; Ishizuka, Mitsuru
2012-03-01
The inter-frame information for analyzing human face movement manifold is modeled by the statistical shape theory. Using the Riemannian geometry principles, we map a sequence of face shapes to a unified tangent space and obtain a curve corresponding to the face movement. The experimental results show that the face movement sequence forms a trajectory in a complex tangent space. Furthermore, the extent and type of face expression could be depicted as the range and direction of the curve. This represents a novel approach for face movement classification using shape-based analysis.
A general Kastler-Kalau-Walze type theorem for manifolds with boundary
NASA Astrophysics Data System (ADS)
Wang, Jian; Wang, Yong
2016-11-01
In this paper, we establish a general Kastler-Kalau-Walze type theorem for any dimensional manifolds with boundary which generalizes the results in [Y. Wang, Lower-dimensional volumes and Kastler-Kalau-Walze type theorem for manifolds with boundary, Commun. Theor. Phys. 54 (2010) 38-42]. This solves a problem of the referee of [J. Wang and Y. Wang, A Kastler-Kalau-Walze type theorem for five-dimensional manifolds with boundary, Int. J. Geom. Meth. Mod. Phys. 12(5) (2015), Article ID: 1550064, 34 pp.], which is a general expression of the lower dimensional volumes in terms of the geometric data on the manifold.
The use of invariant manifolds for transfers between unstable periodic orbits of different energies
NASA Astrophysics Data System (ADS)
Davis, Kathryn E.; Anderson, Rodney L.; Scheeres, Daniel J.; Born, George H.
2010-08-01
Techniques from dynamical systems theory have been applied to the construction of transfers between unstable periodic orbits that have different energies. Invariant manifolds, trajectories that asymptotically depart or approach unstable periodic orbits, are used to connect the initial and final orbits. The transfer asymptotically departs the initial orbit on a trajectory contained within the initial orbit’s unstable manifold and later asymptotically approaches the final orbit on a trajectory contained within the stable manifold of the final orbit. The manifold trajectories are connected by the execution of impulsive maneuvers. Two-body parameters dictate the selection of the individual manifold trajectories used to construct efficient transfers. A bounding sphere centered on the secondary, with a radius less than the sphere of influence of the secondary, is used to study the manifold trajectories. A two-body parameter, κ, is computed within the bounding sphere, where the gravitational effects of the secondary dominate. The parameter κ is defined as the sum of two quantities: the difference in the normalized angular momentum vectors and eccentricity vectors between a point on the unstable manifold and a point on the stable manifold. It is numerically demonstrated that as the κ parameter decreases, the total cost to complete the transfer decreases. Preliminary results indicate that this method of constructing transfers produces a significant cost savings over methods that do not employ the use of invariant manifolds.
New hyper-K{umlt a}hler manifolds by fixing monopoles
Houghton, C.J.
1997-07-01
The construction of new hyper-K{umlt a}hler manifolds by taking the infinite monopole mass limit of certain Bogomol{close_quote}nyi-Prasad-Sommerfield monopole moduli spaces is considered. The one-parameter family of hyper-K{umlt a}hler manifolds due to Dancer is shown to be an example of such manifolds. A new family of fixed monopole spaces is constructed. They are the moduli spaces of four SU{sub 4} monopoles, in the infinite mass limit of two of the monopoles. These manifolds are shown to be nonsingular when the fixed monopole positions are distinct. {copyright} {ital 1997} {ital The American Physical Society}
Data assimilation on the exponentially accurate slow manifold.
Cotter, Colin
2013-05-28
I describe an approach to data assimilation making use of an explicit map that defines a coordinate system on the slow manifold in the semi-geostrophic scaling in Lagrangian coordinates, and apply the approach to a simple toy system that has previously been proposed as a low-dimensional model for the semi-geostrophic scaling. The method can be extended to Lagrangian particle methods such as Hamiltonian particle-mesh and smooth-particle hydrodynamics applied to the rotating shallow-water equations, and many of the properties will remain for more general Eulerian methods. Making use of Hamiltonian normal-form theory, it has previously been shown that, if initial conditions for the system are chosen as image points of the map, then the fast components of the system have exponentially small magnitude for exponentially long times as ε→0, and this property is preserved if one uses a symplectic integrator for the numerical time stepping. The map may then be used to parametrize initial conditions near the slow manifold, allowing data assimilation to be performed without introducing any fast degrees of motion (more generally, the precise amount of fast motion can be selected).
Applying manifold learning to plotting approximate contour trees.
Takahashi, Shigeo; Fujishiro, Issei; Okada, Masato
2009-01-01
A contour tree is a powerful tool for delineating the topological evolution of isosurfaces of a single-valued function, and thus has been frequently used as a means of extracting features from volumes and their time-varying behaviors. Several sophisticated algorithms have been proposed for constructing contour trees while they often complicate the software implementation especially for higher-dimensional cases such as time-varying volumes. This paper presents a simple yet effective approach to plotting in 3D space, approximate contour trees from a set of scattered samples embedded in the high-dimensional space. Our main idea is to take advantage of manifold learning so that we can elongate the distribution of high-dimensional data samples to embed it into a low-dimensional space while respecting its local proximity of sample points. The contribution of this paper lies in the introduction of new distance metrics to manifold learning, which allows us to reformulate existing algorithms as a variant of currently available dimensionality reduction scheme. Efficient reduction of data sizes together with segmentation capability is also developed to equip our approach with a coarse-to-fine analysis even for large-scale datasets. Examples are provided to demonstrate that our proposed scheme can successfully traverse the features of volumes and their temporal behaviors through the constructed contour trees.
Manifold regularized multitask feature learning for multimodality disease classification.
Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang
2015-02-01
Multimodality based methods have shown great advantages in classification of Alzheimer's disease (AD) and its prodromal stage, that is, mild cognitive impairment (MCI). Recently, multitask feature selection methods are typically used for joint selection of common features across multiple modalities. However, one disadvantage of existing multimodality based methods is that they ignore the useful data distribution information in each modality, which is essential for subsequent classification. Accordingly, in this paper we propose a manifold regularized multitask feature learning method to preserve both the intrinsic relatedness among multiple modalities of data and the data distribution information in each modality. Specifically, we denote the feature learning on each modality as a single task, and use group-sparsity regularizer to capture the intrinsic relatedness among multiple tasks (i.e., modalities) and jointly select the common features from multiple tasks. Furthermore, we introduce a new manifold-based Laplacian regularizer to preserve the data distribution information from each task. Finally, we use the multikernel support vector machine method to fuse multimodality data for eventual classification. Conversely, we also extend our method to the semisupervised setting, where only partial data are labeled. We evaluate our method using the baseline magnetic resonance imaging (MRI), fluorodeoxyglucose positron emission tomography (FDG-PET), and cerebrospinal fluid (CSF) data of subjects from AD neuroimaging initiative database. The experimental results demonstrate that our proposed method can not only achieve improved classification performance, but also help to discover the disease-related brain regions useful for disease diagnosis.
Nonlinear dynamical modes of climate variability: from curves to manifolds
NASA Astrophysics Data System (ADS)
Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander
2016-04-01
The necessity of efficient dimensionality reduction methods capturing dynamical properties of the system from observed data is evident. Recent study shows that nonlinear dynamical mode (NDM) expansion is able to solve this problem and provide adequate phase variables in climate data analysis [1]. A single NDM is logical extension of linear spatio-temporal structure (like empirical orthogonal function pattern): it is constructed as nonlinear transformation of hidden scalar time series to the space of observed variables, i. e. projection of observed dataset onto a nonlinear curve. Both the hidden time series and the parameters of the curve are learned simultaneously using Bayesian approach. The only prior information about the hidden signal is the assumption of its smoothness. The optimal nonlinearity degree and smoothness are found using Bayesian evidence technique. In this work we do further extension and look for vector hidden signals instead of scalar with the same smoothness restriction. As a result we resolve multidimensional manifolds instead of sum of curves. The dimension of the hidden manifold is optimized using also Bayesian evidence. The efficiency of the extension is demonstrated on model examples. Results of application to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510
Experimental study of a novel manifold structure of micro-channel heat exchanger
NASA Astrophysics Data System (ADS)
Xu, Bo; Xu, Kunhao; Wei, Wei; Han, Qing; Chen, Jiangping
2013-07-01
Refrigerant flow distribution with phase change heat transfer was experimentally studied for a micro-channel heat exchanger having horizontal headers. In order to solve the problem of maldistribution, a novel manifold structure with orifice and bypass tube was proposed and experimentally studied compared to the conventional structure. Tests were conducted with downward flow for mass flux from 70 to 110 kg m-2s-1 (air side flow velocity from 1 to 2ms-1). The surface temperature distribution of the heat exchanger recorded by thermal imager and the square deviation of it were used to judge the uniformity of flow distribution. It is shown that as mass flux increased, better flow distribution is obtained (small square deviation of temperature distribution means better flow distribution: conventional structure from 32 to 27, novel structure from 19 to 14), and flow distribution of the novel structure was much better than that of the conventional one. The heat transfer performances of the two heat exchangers were also studied. The cooling capacity of the novel heat exchanger was 14.8% higher than that of the conventional because of the better flow distribution. And the refrigerant pressure drop was 120% higher because of bigger mass flow and the resistance of the orifice. It's worth noting that the air pressure drop of novel heat exchanger was also higher (about 28.3%)than that of the conventional one, even when they have same fin and flat tube structure. From the pictures of the heat exchanger surfaces, it was found that some surface area of the conventional heat exchanger was not wet because of the low mass flow and high superheat, which leaded to a poor performance and relatively small air pressure drop.
A Dynamical Model of General Intelligence: The Positive Manifold of Intelligence by Mutualism
ERIC Educational Resources Information Center
Van Der Maas, Han L. J.; Dolan, Conor V.; Grasman, Raoul P. P. P.; Wicherts, Jelte M.; Huizenga, Hilde M.; Raijmakers, Maartje E. J.
2006-01-01
Scores on cognitive tasks used in intelligence tests correlate positively with each other, that is, they display a positive manifold of correlations. The positive manifold is often explained by positing a dominant latent variable, the g factor, associated with a single quantitative cognitive or biological process or capacity. In this article, a…
Ho, Shen-Shyang; Dai, Peng; Rudzicz, Frank
2016-06-01
Multivariate variable-length sequence data are becoming ubiquitous with the technological advancement in mobile devices and sensor networks. Such data are difficult to compare, visualize, and analyze due to the nonmetric nature of data sequence similarity measures. In this paper, we propose a general manifold learning framework for arbitrary-length multivariate data sequences driven by similarity/distance (parameter) learning in both the original data sequence space and the learned manifold. Our proposed algorithm transforms the data sequences in a nonmetric data sequence space into feature vectors in a manifold that preserves the data sequence space structure. In particular, the feature vectors in the manifold representing similar data sequences remain close to one another and far from the feature points corresponding to dissimilar data sequences. To achieve this objective, we assume a semisupervised setting where we have knowledge about whether some of data sequences are similar or dissimilar, called the instance-level constraints. Using this information, one learns the similarity measure for the data sequence space and the distance measures for the manifold. Moreover, we describe an approach to handle the similarity search problem given user-defined instance level constraints in the learned manifold using a consensus voting scheme. Experimental results on both synthetic data and real tropical cyclone sequence data are presented to demonstrate the feasibility of our manifold learning framework and the robustness of performing similarity search in the learned manifold.
21 CFR 870.4290 - Cardiopulmonary bypass adaptor, stopcock, manifold, or fitting.
Code of Federal Regulations, 2010 CFR
2010-04-01
..., or fitting. 870.4290 Section 870.4290 Food and Drugs FOOD AND DRUG ADMINISTRATION, DEPARTMENT OF... Devices § 870.4290 Cardiopulmonary bypass adaptor, stopcock, manifold, or fitting. (a) Identification. A cardiopulmonary bypass adaptor, stopcock, manifold, or fitting is a device used in cardiovascular...
Some Results About Concircular and Concurrent Vector Fields On Pseudo-Kaehler Manifolds
NASA Astrophysics Data System (ADS)
Sevinç, Sibel; Aydin Şekerci, Gülşah; Ceylan Çöken, A.
2016-10-01
Kaehler manifolds which are used in physics have a lot of application fields. In this study we only state concircular and concurrent vector field that are defined on these manifolds. A vector field on a pseudo-Riemannian manifold N is called concircular, if it satisfies ∇ X υ = μX for any vector X tangent to N, where ∇ is the Levi-Civita connection of N. Furthermore, a concircular vector field υ is called a concurrent vector field if the function μ is non-constant. So, we provide some results on submanifolds of pseudo-Kaehler manifolds with respect to a concircular vector field or a concurrent vector field. Morever, we investigate this problem for another manifolds and proof some theorems.
Manifold Kernel Sparse Representation of Symmetric Positive-Definite Matrices and Its Applications.
Wu, Yuwei; Jia, Yunde; Li, Peihua; Zhang, Jian; Yuan, Junsong
2015-11-01
The symmetric positive-definite (SPD) matrix, as a connected Riemannian manifold, has become increasingly popular for encoding image information. Most existing sparse models are still primarily developed in the Euclidean space. They do not consider the non-linear geometrical structure of the data space, and thus are not directly applicable to the Riemannian manifold. In this paper, we propose a novel sparse representation method of SPD matrices in the data-dependent manifold kernel space. The graph Laplacian is incorporated into the kernel space to better reflect the underlying geometry of SPD matrices. Under the proposed framework, we design two different positive definite kernel functions that can be readily transformed to the corresponding manifold kernels. The sparse representation obtained has more discriminating power. Extensive experimental results demonstrate good performance of manifold kernel sparse codes in image classification, face recognition, and visual tracking.
Park, Hyunjin
2012-04-04
Neuroimaging data are high dimensional and thus cumbersome to analyze. Manifold learning is a technique to find a low dimensional representation for high dimensional data. With manifold learning, data analysis becomes more tractable in the low dimensional space. We propose a novel shape quantification method based on a manifold learning method, ISOMAP, for brain MRI. Existing work applied another manifold learning method, multidimensional scaling (MDS), to quantify shape information for distinguishing Alzheimer's disease (AD) from normal. We enhance the existing methodology by (1) applying it to distinguish mild cognitive impairment (MCI) from normal, (2) adopting a more advanced manifold learning technique, ISOMAP, and (3) showing the effectiveness of the induced low dimensional embedding space to predict key clinical variables such as mini mental state exam scores and clinical diagnosis using the standard multiple linear regression. Our methodology was tested using 25 normal, 25 AD, and 25 MCI patients.
System theory on group manifolds and coset spaces.
NASA Technical Reports Server (NTRS)
Brockett, R. W.
1972-01-01
The purpose of this paper is to study questions regarding controllability, observability, and realization theory for a particular class of systems for which the state space is a differentiable manifold which is simultaneously a group or, more generally, a coset space. We show that it is possible to give rather explicit expressions for the reachable set and the set of indistinguishable states in the case of autonomous systems. We also establish a type of state space isomorphism theorem. Our objective is to reduce all questions about the system to questions about Lie algebras generated from the coefficient matrices entering in the description of the system and in that way arrive at conditions which are easily visualized and tested.
Decision Manifold Approximation for Physics-Based Simulations
NASA Technical Reports Server (NTRS)
Wong, Jay Ming; Samareh, Jamshid A.
2016-01-01
With the recent surge of success in big-data driven deep learning problems, many of these frameworks focus on the notion of architecture design and utilizing massive databases. However, in some scenarios massive sets of data may be difficult, and in some cases infeasible, to acquire. In this paper we discuss a trajectory-based framework that quickly learns the underlying decision manifold of binary simulation classifications while judiciously selecting exploratory target states to minimize the number of required simulations. Furthermore, we draw particular attention to the simulation prediction application idealized to the case where failures in simulations can be predicted and avoided, providing machine intelligence to novice analysts. We demonstrate this framework in various forms of simulations and discuss its efficacy.
Abelian gauge theories on compact manifolds and the Gribov ambiguity
Kelnhofer, Gerald
2008-05-15
We study the quantization of Abelian gauge theories of principal torus bundles over compact manifolds with and without boundary. It is shown that these gauge theories suffer from a Gribov ambiguity originating in the nontriviality of the bundle of connections whose geometrical structure will be analyzed in detail. Motivated by the stochastic quantization approach, we propose a modified functional integral measure on the space of connections that takes the Gribov problem into account. This functional integral measure is used to calculate the partition function, Green's functions, and the field strength correlating functions in any dimension by using the fact that the space of inequivalent connections itself admits the structure of a bundle over a finite dimensional torus. Green's functions are shown to be affected by the nontrivial topology, giving rise to nonvanishing vacuum expectation values for the gauge fields.
Multispectral Electrical Impedance Tomography using Optimization over Manifolds
NASA Astrophysics Data System (ADS)
Fouchard, A.; Bonnet, S.; David, O.
2016-10-01
Electrical impedance tomography under spectral constraints uses a material basis decomposition to combine the different information embedded in the tissue spectra. This approach offers an alternative to static imaging while benefiting from systemic error cancellation using difference data. It suits well cases where no prior solution is known and the contrast lies entirely between frequencies, e.g. to diagnose acute stroke or cancer. In this work, a computational framework is presented to deal with the extra frequency dimensions and the constraints during reconstruction. A fraction volume approach is demonstrated with explicit Euclidean gradient, usage of a finite volume element solver and minimization over the oblique manifold. It is applied to synthetic data. Parameter estimations are compared between a monofrequency inversion and the proposed multispectral implementation. Results suggest that the proposed workflow enables to reduce the computational workload of multispectral inversion while ensuring valid proportions of materials within each control volume.
Fibrations and globalizations of compact homogeneous CR-manifolds
NASA Astrophysics Data System (ADS)
Gilligan, B.; Huckleberry, Alan T.
2009-06-01
Fibration methods which were previously used for complex homogeneous spaces and CR-homogeneous spaces of special types [1]-[4] are developed in a general framework. These include the \\mathfrak{g}-anticanonical fibration in the CR-setting, which reduces certain considerations to the compact projective algebraic case, where a Borel-Remmert type splitting theorem is proved. This leads to a reduction to spaces homogeneous under actions of compact Lie groups. General globalization theorems are proved which enable one to regard a homogeneous CR-manifold as an orbit of a real Lie group in a complex homogeneous space of a complex Lie group. In the special case of CR-codimension at most two, precise classification results are proved and are applied to show that in most cases there exists such a globalization.
[Anomaly Detection of Multivariate Time Series Based on Riemannian Manifolds].
Xu, Yonghong; Hou, Xiaoying; Li Shuting; Cui, Jie
2015-06-01
Multivariate time series problems widely exist in production and life in the society. Anomaly detection has provided people with a lot of valuable information in financial, hydrological, meteorological fields, and the research areas of earthquake, video surveillance, medicine and others. In order to quickly and efficiently find exceptions in time sequence so that it can be presented in front of people in an intuitive way, we in this study combined the Riemannian manifold with statistical process control charts, based on sliding window, with a description of the covariance matrix as the time sequence, to achieve the multivariate time series of anomaly detection and its visualization. We made MA analog data flow and abnormal electrocardiogram data from MIT-BIH as experimental objects, and verified the anomaly detection method. The results showed that the method was reasonable and effective.
Landtesting the underwater Manifold Centre for the Central Cormorant field
Brady, M.M.
1983-05-01
This paper describes the commissioning on land prior to installation of the Underwater Manifold Centre (UMC) for the Central Cormorant field. The test programme was unique in its scope and depth requiring 15 months and 11 million pounds to complete. Included in the paper are guidelines to assist future projects as well as summaries of technical results and a list of the principal problems that were encountered. Management practices utilised to guide the programme to its successful completion are emphasised throughout. Finally, the paper concludes that the landtest programme was a cost-effective and indispensable step which resulted in the UMC being installed in May, 1982 with full confidence, especially in the essential high technology components.
Underwater Manifold Centre - drilled-cuttings disposal system
Biddlestone, P.A.
1983-01-01
During the construction of the Central Cormorant Underwater Manifold Centre (UMC), it was recognized that the cuttings produced during the drilling of template wells would interfere with UMC operations, if deposited on top of the structure. A dual system was developed and installed on the Stadrill (the unit planned to drill the wells) to remove the cuttings from the rig to the seabed away from the UMC. The system as conceived and designed has been successful; it fulfills the requirements for flexibility, reliability, and efficiency. Its dependence on equipment external to the rig is minimal and after the capital outlay, the running costs are only for extra crew to operate the equipment and for maintenance. However, the system has been tailor-made for the UMC, the Stadrill, and the conditions prevailing in the Cormorant area.
Scene recognition by manifold regularized deep learning architecture.
Yuan, Yuan; Mou, Lichao; Lu, Xiaoqiang
2015-10-01
Scene recognition is an important problem in the field of computer vision, because it helps to narrow the gap between the computer and the human beings on scene understanding. Semantic modeling is a popular technique used to fill the semantic gap in scene recognition. However, most of the semantic modeling approaches learn shallow, one-layer representations for scene recognition, while ignoring the structural information related between images, often resulting in poor performance. Modeled after our own human visual system, as it is intended to inherit humanlike judgment, a manifold regularized deep architecture is proposed for scene recognition. The proposed deep architecture exploits the structural information of the data, making for a mapping between visible layer and hidden layer. By the proposed approach, a deep architecture could be designed to learn the high-level features for scene recognition in an unsupervised fashion. Experiments on standard data sets show that our method outperforms the state-of-the-art used for scene recognition.
On the Circulation Manifold for Two Adjacent Lifting Sections
NASA Technical Reports Server (NTRS)
Zannetti, Luca; Iollo, Angelo
1998-01-01
The circulation functional relative to two adjacent lifting sections is studied for two cases. In the first case we consider two adjacent circles. The circulation is computed as a function of the displacement of the secondary circle along the axis joining the two centers and of the angle of attack of the secondary circle, The gradient of such functional is computed by deriving a set of elliptic functions with respect both to their argument and to their Period. In the second case studied, we considered a wing-flap configuration. The circulation is computed by some implicit mappings, whose differentials with respect to the variation of the geometrical configuration in the physical space are found by divided differences. Configurations giving rise to local maxima and minima in the circulation manifold are presented.
Manifold regularized discriminative nonnegative matrix factorization with fast gradient descent.
Guan, Naiyang; Tao, Dacheng; Luo, Zhigang; Yuan, Bo
2011-07-01
Nonnegative matrix factorization (NMF) has become a popular data-representation method and has been widely used in image processing and pattern-recognition problems. This is because the learned bases can be interpreted as a natural parts-based representation of data and this interpretation is consistent with the psychological intuition of combining parts to form a whole. For practical classification tasks, however, NMF ignores both the local geometry of data and the discriminative information of different classes. In addition, existing research results show that the learned basis is unnecessarily parts-based because there is neither explicit nor implicit constraint to ensure the representation parts-based. In this paper, we introduce the manifold regularization and the margin maximization to NMF and obtain the manifold regularized discriminative NMF (MD-NMF) to overcome the aforementioned problems. The multiplicative update rule (MUR) can be applied to optimizing MD-NMF, but it converges slowly. In this paper, we propose a fast gradient descent (FGD) to optimize MD-NMF. FGD contains a Newton method that searches the optimal step length, and thus, FGD converges much faster than MUR. In addition, FGD includes MUR as a special case and can be applied to optimizing NMF and its variants. For a problem with 165 samples in R(1600), FGD converges in 28 s, while MUR requires 282 s. We also apply FGD in a variant of MD-NMF and experimental results confirm its efficiency. Experimental results on several face image datasets suggest the effectiveness of MD-NMF.
Infinitesimal moduli of G2 holonomy manifolds with instanton bundles
NASA Astrophysics Data System (ADS)
de la Ossa, Xenia; Larfors, Magdalena; Svanes, Eirik E.
2016-11-01
We describe the infinitesimal moduli space of pairs ( Y, V) where Y is a manifold with G 2 holonomy, and V is a vector bundle on Y with an instanton connection. These structures arise in connection to the moduli space of heterotic string compactifications on compact and non-compact seven dimensional spaces, e.g. domain walls. Employing the canonical G 2 cohomology developed by Reyes-Carrión and Fernández and Ugarte, we show that the moduli space decomposes into the sum of the bundle moduli {H}_{{overset{ěe }{d}}_A}^1(Y,End(V)) plus the moduli of the G 2 structure preserving the instanton condition. The latter piece is contained in {H}_{overset{ěe }{d}θ}^1(Y,TY) , and is given by the kernel of a map overset{ěe }{F} which generalises the concept of the Atiyah map for holomorphic bundles on complex manifolds to the case at hand. In fact, the map overset{ěe }{F} is given in terms of the curvature of the bundle and maps {H}_{overset{ěe }{d}θ}^1(Y,TY) into {H}_{{overset{ěe }{d}}_A}^2(Y,End(V)) , and moreover can be used to define a cohomology on an extension bundle of TY by End( V). We comment further on the resemblance with the holomorphic Atiyah algebroid and connect the story to physics, in particular to heterotic compactifications on ( Y, V) when α' = 0.
Multimodal manifold-regularized transfer learning for MCI conversion prediction.
Cheng, Bo; Liu, Mingxia; Suk, Heung-Il; Shen, Dinggang; Zhang, Daoqiang
2015-12-01
As the early stage of Alzheimer's disease (AD), mild cognitive impairment (MCI) has high chance to convert to AD. Effective prediction of such conversion from MCI to AD is of great importance for early diagnosis of AD and also for evaluating AD risk pre-symptomatically. Unlike most previous methods that used only the samples from a target domain to train a classifier, in this paper, we propose a novel multimodal manifold-regularized transfer learning (M2TL) method that jointly utilizes samples from another domain (e.g., AD vs. normal controls (NC)) as well as unlabeled samples to boost the performance of the MCI conversion prediction. Specifically, the proposed M2TL method includes two key components. The first one is a kernel-based maximum mean discrepancy criterion, which helps eliminate the potential negative effect induced by the distributional difference between the auxiliary domain (i.e., AD and NC) and the target domain (i.e., MCI converters (MCI-C) and MCI non-converters (MCI-NC)). The second one is a semi-supervised multimodal manifold-regularized least squares classification method, where the target-domain samples, the auxiliary-domain samples, and the unlabeled samples can be jointly used for training our classifier. Furthermore, with the integration of a group sparsity constraint into our objective function, the proposed M2TL has a capability of selecting the informative samples to build a robust classifier. Experimental results on the Alzheimer's Disease Neuroimaging Initiative (ADNI) database validate the effectiveness of the proposed method by significantly improving the classification accuracy of 80.1 % for MCI conversion prediction, and also outperforming the state-of-the-art methods.
Smectic phases of semiflexible manifolds: Constant-pressure ensemble
NASA Astrophysics Data System (ADS)
Gao, Lianghui; Golubović, Leonardo
2002-11-01
We pursue the constant-pressure ensemble approach to elucidate the statistical mechanics of the smectic phases of semiflexible manifolds, such as two-dimensional smectic phases of long semiflexible polymers and three-dimensional lamellar fluid membrane phases. We use this approach to consider in detail sterically stabilized phases of semiflexible polymers in two-dimensional (2D) smectic systems. For these 2D systems, we obtain the universal constants characterizing the entropic repulsion between semiflexible polymers, such as those in the osmotic pressure P=α(kBT)4/3/κ1/3(a- amin)5/3 with α found here to be ≅0.432 (here, a is the smectic phase period, and amin and κ are the polymer cross-sectional diameter and bending rigidity constant, respectively). We address, by numerical simulations and analytic arguments, finite stacks of N semiflexible manifolds, and discuss in detail the practically interesting thermodynamic limit N-->∞. We show that the thermodynamic limit is quickly approached within the constant-pressure ensemble: Already from numerical simulations involving just few semiflexible polymers under constant isotropic pressure, one can obtain the infinite 2D smectic equation of state within a few percent accuracy. We use our results to discuss the competition of electrostatic and entropic effects in quasi-2D smectic phases of DNA-cationic-lipid complexes. We use our quantitative results to discuss in detail the elasticity, topological defects, anomalous elasticity, and the effects of externally applied tension in sterically stabilized 2D smectic phases of long semiflexible polymers.
Sodium intake and cardiovascular health.
O'Donnell, Martin; Mente, Andrew; Yusuf, Salim
2015-03-13
Sodium is an essential nutrient. Increasing sodium intake is associated with increasing blood pressure, whereas low sodium intake results in increased renin and aldosterone levels. Randomized controlled trials have reported reductions in blood pressure with reductions in sodium intake, to levels of sodium intake <1.5 g/d, and form the evidentiary basis for current population-wide guidelines recommending low sodium intake. Although low sodium intake (<2.0 g/d) has been achieved in short-term feeding clinical trials, sustained low sodium intake has not been achieved by any of the longer term clinical trials (>6-month duration). It is assumed that the blood pressure-lowering effects of reducing sodium intake to low levels will result in large reductions in cardiovascular disease globally. However, current evidence from prospective cohort studies suggests a J-shaped association between sodium intake and cardiovascular events, based on studies from >300 000 people, and suggests that the lowest risk of cardiovascular events and death occurs in populations consuming an average sodium intake range (3-5 g/d). The increased risk of cardiovascular events associated with higher sodium intake (>5 g/d) is most prominent in those with hypertension. A major deficit in the field is the absence of large randomized controlled trials to provide definitive evidence on optimal sodium intake for preventing cardiovascular events. Pending such trials, current evidence would suggest a recommendation for moderate sodium intake in the general population (3-5 g/d), with targeting the lower end of the moderate range among those with hypertension.
Viscous flow computations for elliptical two-duct version of the SSME hot gas manifold
NASA Technical Reports Server (NTRS)
Roger, R. P.
1986-01-01
The objective of the effort was to numerically simulate viscous subsonic flow in a proposed elliptical two-duct version of the fuel side Hot Gas Manifold (HGM) for the Space Shuttle Main Engine (SSME). The numerical results were to complement both water flow and air flow experiments in the two-duct geometry performed at NASA-MSFC and Rocketdyne. The three-dimensional character of the HGM consists of two essentially different geometries. The first part of the construction is a concentric shell duct structure which channels the gases from a turbine exit into the second part comprised of two cylindrically shaped transfer ducts. The initial concentric shell portion can be further subdivided into a turnaround section and a bowl section. The turnaround duct (TAD) changes the direction of the mean flow by 180 degress from a smaller radius to a larger radius duct which discharges into the bowl. The cylindrical transfer ducts are attached to the bowl on one side thus providing a plane of symmetry midway between the two. Centerline flow distance from the TAD inlet to the transfer duct exit is approximately two feet. Details of the approach used to numerically simulate laminar or turbulent flow in the HGM geometry are presented. Computational results are presented and discussed.
Technology Solutions Case Study: Sealed Air-Return Plenum Retrofit
none,
2012-08-01
In this project, Pacific Northwest National Laboratory researchers greatly improved indoor air quality and HVAC performance by replacing an old, leaky air handler with a new air handler with an air-sealed return plenum with filter; they also sealed the ducts, and added a fresh air intake.
Global patterns of water intake: how intake data affect recommendations.
Shirreffs, Susan M
2012-11-01
Studies to assess water intake have been undertaken in many countries around the world. Some of these have been large-scale studies, whereas others have used a small number of subjects. These studies provide an emerging picture of water and/or fluid consumption in different populations around the world. Studies of this nature have also formed the basis of a number of recommendations published by different organizations, including the US Institute of Medicine and the European Food Safety Authority. The results of these intake studies indicate substantial differences in water and/or fluid intake in different populations, which have translated into different intake recommendations.
NASA Astrophysics Data System (ADS)
Hernandez Perez, Francisco E.; Lee, Bok Jik; Im, Hong G.; Fancello, Alessio; Donini, Andrea; van Oijen, Jeroen A.; de Goey, L. Philip H.
2016-11-01
Large eddy simulations (LES) of a turbulent premixed jet flame in a confined chamber are performed using the flamelet-generated manifold technique for tabulation of chemical kinetics and the OpenFOAM framework for computational fluid dynamics. The configuration is characterized by an off-center nozzle having an inner diameter of 10 mm, feeding a lean methane-air mixture with an equivalence ratio of 0.71 and mean velocity of 90 m/s, at 573 K and atmospheric pressure. Conductive heat loss is accounted for in the manifold via burner-stabilized flamelets and the subgrid-scale (SGS) turbulence-chemistry interaction is modeled via presumed filtered density functions. The effects of heat loss inclusion as well as SGS modeling for both the SGS stresses and SGS variance of progress variable on the numerical predictions are all systematically investigated. Comparisons between numerical results and measured data show a considerable improvement in the prediction of temperature when heat losses are incorporated into the manifold, as compared to the adiabatic one. In addition, further improvements in the LES predictions are achieved by employing SGS models based on transport equations.
Numerical simulation of pump-intake vortices
NASA Astrophysics Data System (ADS)
Rudolf, Pavel; Klas, Roman
2015-05-01
Pump pre-swirl or uneven flow distribution in front of the pump can induce pump-intake vortices. These phenomena result in blockage of the impeller suction space, deterioration of efficiency, drop of head curve and earlier onset of cavitation. Real problematic case, where head curve drop was documented, is simulated using commercial CFD software. Computational simulation was carried out for three flow rates, which correspond to three operating regimes of the vertical pump. The domain consists of the pump sump, pump itself excluding the impeller and the delivery pipe. One-phase approach is applied, because the vortex cores were not filled with air during observation of the real pump operation. Numerical simulation identified two surface vortices and one bottom vortex. Their position and strength depend on the pump flow rate. Paper presents detail analysis of the flow field on the pump intake, discusses influence of the vortices on pump operation and suggests possible actions that should be taken to suppress the intake vortices.
NASA Astrophysics Data System (ADS)
Donini, A.; Martin, S. M.; Bastiaans, R. J. M.; van Oijen, J. A.; de Goey, L. P. H.
2013-10-01
In the present paper a computational analysis of a high pressure confined premixed turbulent methane/air jet flames is presented. In this scope, chemistry is reduced by the use of the Flamelet Generated Manifold method [1] and the fluid flow is modeled in an LES and RANS context. The reaction evolution is described by the reaction progress variable, the heat loss is described by the enthalpy and the turbulence effect on the reaction is represented by the progress variable variance. The interaction between chemistry and turbulence is considered through a presumed probability density function (PDF) approach. The use of FGM as a combustion model shows that combustion features at gas turbine conditions can be satisfactorily reproduced with a reasonable computational effort. Furthermore, the present analysis indicates that the physical and chemical processes controlling carbon monoxide (CO) emissions can be captured only by means of unsteady simulations.
Learning an intrinsic-variable preserving manifold for dynamic visual tracking.
Qiao, Hong; Zhang, Peng; Zhang, Bo; Zheng, Suiwu
2010-06-01
Manifold learning is a hot topic in the field of computer science, particularly since nonlinear dimensionality reduction based on manifold learning was proposed in Science in 2000. The work has achieved great success. The main purpose of current manifold-learning approaches is to search for independent intrinsic variables underlying high dimensional inputs which lie on a low dimensional manifold. In this paper, a new manifold is built up in the training step of the process, on which the input training samples are set to be close to each other if the values of their intrinsic variables are close to each other. Then, the process of dimensionality reduction is transformed into a procedure of preserving the continuity of the intrinsic variables. By utilizing the new manifold, the dynamic tracking of a human who can move and rotate freely is achieved. From the theoretical point of view, it is the first approach to transfer the manifold-learning framework to dynamic tracking. From the application point of view, a new and low dimensional feature for visual tracking is obtained and successfully applied to the real-time tracking of a free-moving object from a dynamic vision system. Experimental results from a dynamic tracking system which is mounted on a dynamic robot validate the effectiveness of the new algorithm.
Out-of-Sample Generalizations for Supervised Manifold Learning for Classification
NASA Astrophysics Data System (ADS)
Vural, Elif; Guillemot, Christine
2016-03-01
Supervised manifold learning methods for data classification map data samples residing in a high-dimensional ambient space to a lower-dimensional domain in a structure-preserving way, while enhancing the separation between different classes in the learned embedding. Most nonlinear supervised manifold learning methods compute the embedding of the manifolds only at the initially available training points, while the generalization of the embedding to novel points, known as the out-of-sample extension problem in manifold learning, becomes especially important in classification applications. In this work, we propose a semi-supervised method for building an interpolation function that provides an out-of-sample extension for general supervised manifold learning algorithms studied in the context of classification. The proposed algorithm computes a radial basis function (RBF) interpolator that minimizes an objective function consisting of the total embedding error of unlabeled test samples, defined as their distance to the embeddings of the manifolds of their own class, as well as a regularization term that controls the smoothness of the interpolation function in a direction-dependent way. The class labels of test data and the interpolation function parameters are estimated jointly with a progressive procedure. Experimental results on face and object images demonstrate the potential of the proposed out-of-sample extension algorithm for the classification of manifold-modeled data sets.
Xie, Xiaofeng; Yu, Zhu Liang; Lu, Haiping; Gu, Zhenghui; Li, Yuanqing
2016-07-07
In motor imagery brain-computer interfaces (BCIs), the symmetric positive-definite (SPD) covariance matrices of electroencephalogram (EEG) signals carry important discriminative information. In this paper, we intend to classify motor imagery EEG signals by exploiting the fact that the space of SPD matrices endowed with Riemannian distance is a highdimensional Riemannian manifold. To alleviate the overfitting and heavy computation problems associated with conventional classification methods on high-dimensional manifold, we propose a framework for intrinsic sub-manifold learning from a high-dimensional Riemannian manifold. Considering a special case of SPD space, a simple yet efficient bilinear sub-manifold learning (BSML) algorithm is derived to learn the intrinsic submanifold by identifying a bilinear mapping that maximizes the preservation of the local geometry and global structure of the original manifold. Two BSML-based classification algorithms are further proposed to classify the data on a learned intrinsic sub-manifold. Experimental evaluation of the classification of EEG revealed that the BSML method extracts the intrinsic submanifold approximately 5 faster and with higher classification accuracy compared with competing algorithms. The BSML also exhibited strong robustness against a small training dataset, which often occurs in BCI studies.
Subspace learning of dynamics on a shape manifold: a generative modeling approach.
Yi, Sheng; Krim, Hamid
2014-11-01
In this paper, we propose a novel subspace learning algorithm of shape dynamics. Compared to the previous works, our method is invertible and better characterizes the nonlinear geometry of a shape manifold while retaining a good computational efficiency. In this paper, using a parallel moving frame on a shape manifold, each path of shape dynamics is uniquely represented in a subspace spanned by the moving frame, given an initial condition (the starting point and starting frame). Mathematically, such a representation may be formulated as solving a manifold-valued differential equation, which provides a generative modeling of high-dimensional shape dynamics in a lower dimensional subspace. Given the parallelism and a path on a shape manifold, the parallel moving frame along the path is uniquely determined up to the choice of the starting frame. With an initial frame, we minimize the reconstruction error from the subspace to shape manifold. Such an optimization characterizes well the Riemannian geometry of the manifold by imposing parallelism (equivalent as a Riemannian metric) constraints on the moving frame. The parallelism in this paper is defined by a Levi-Civita connection, which is consistent with the Riemannian metric of the shape manifold. In the experiments, the performance of the subspace learning is extensively evaluated using two scenarios: 1) how the high dimensional geometry is characterized in the subspace and 2) how the reconstruction compares with the original shape dynamics. The results demonstrate and validate the theoretical advantages of the proposed approach.
[Dietary reference intakes of phosphorus].
Uenishi, Kazuhiro
2012-10-01
Phosphorus (P) exists at the all organs and plays important physiological roles in the body. A wide range of food contains P, which is absorbed at a higher level (60-70%) and its insufficiency and deficiency are rarely found. P is used as food additives in many processed food, where risk of overconsumption could be an issue. P has less evidence in terms of nutrition. P has the adequate intake and the tolerable upper intake level, for risk reduction of health disorders associated with excess intake, at the Dietary Reference Intakes for Japanese (2010 edition).
Using manifold learning for atlas selection in multi-atlas segmentation.
Hoang Duc, Albert K; Modat, Marc; Leung, Kelvin K; Cardoso, M Jorge; Barnes, Josephine; Kadir, Timor; Ourselin, Sébastien
2013-01-01
Multi-atlas segmentation has been widely used to segment various anatomical structures. The success of this technique partly relies on the selection of atlases that are best mapped to a new target image after registration. Recently, manifold learning has been proposed as a method for atlas selection. Each manifold learning technique seeks to optimize a unique objective function. Therefore, different techniques produce different embeddings even when applied to the same data set. Previous studies used a single technique in their method and gave no reason for the choice of the manifold learning technique employed nor the theoretical grounds for the choice of the manifold parameters. In this study, we compare side-by-side the results given by 3 manifold learning techniques (Isomap, Laplacian Eigenmaps and Locally Linear Embedding) on the same data set. We assess the ability of those 3 different techniques to select the best atlases to combine in the framework of multi-atlas segmentation. First, a leave-one-out experiment is used to optimize our method on a set of 110 manually segmented atlases of hippocampi and find the manifold learning technique and associated manifold parameters that give the best segmentation accuracy. Then, the optimal parameters are used to automatically segment 30 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). For our dataset, the selection of atlases with Locally Linear Embedding gives the best results. Our findings show that selection of atlases with manifold learning leads to segmentation accuracy close to or significantly higher than the state-of-the-art method and that accuracy can be increased by fine tuning the manifold learning process.
NASA Astrophysics Data System (ADS)
Miyazaki, Takeji
The reduction of intake of outdoor air volume in air conditioned buildings, adopted as the strategy for saving energy, has caused sick building syndrome abroad. Such symptoms of sick building as headache, stimuli of eye and nose and lethargy, appears to result from cigarette smoke, folmaldehyde and volatile organic carbons. On the other hand, in airtight residences not only carbon monoxide and nitrogen oxides from domestic burning appliances but also allergens of mite, fungi, pollen and house dust, have become a subject of discussion. Moreover, asbestos and radon of carcinogen now attract a great deal of attention. Those indoor air pollutants are discussed.
Chen, Xiaoguang; Liu, Dan; Xu, Guanghua; Jiang, Kuosheng; Liang, Lin
2014-12-26
For decades, bearing factory quality evaluation has been a key problem and the methods used are always static tests. This paper investigates the use of piezoelectric ultrasonic transducers (PUT) as dynamic diagnostic tools and a relevant signal classification technique, wavelet packet entropy (WPEntropy) flow manifold learning, for the evaluation of bearing factory quality. The data were analyzed using wavelet packet entropy (WPEntropy) flow manifold learning. The results showed that the ultrasonic technique with WPEntropy flow manifold learning was able to detect different types of defects on the bearing components. The test method and the proposed technique are described and the different signals are analyzed and discussed.
Building robust neighborhoods for manifold learning-based image classification and anomaly detection
NASA Astrophysics Data System (ADS)
Doster, Timothy; Olson, Colin C.
2016-05-01
We exploit manifold learning algorithms to perform image classification and anomaly detection in complex scenes involving hyperspectral land cover and broadband IR maritime data. The results of standard manifold learning techniques are improved by including spatial information. This is accomplished by creating super-pixels which are robust to affine transformations inherent in natural scenes. We utilize techniques from harmonic analysis and image processing, namely, rotation, skew, flip, and shift operators to develop a more representational graph structure which defines the data-dependent manifold.
Encoding quantum information in a stabilized manifold of a superconducting cavity
NASA Astrophysics Data System (ADS)
Touzard, S.; Leghtas, Z.; Mundhada, S. O.; Axline, C.; Reagor, M.; Chou, K.; Blumoff, J.; Sliwa, K. M.; Shankar, S.; Frunzio, L.; Schoelkopf, R. J.; Mirrahimi, M.; Devoret, M. H.
In a superconducting Josephson circuit architecture, we activate a multi-photon process between two modes by applying microwave drives at specific frequencies. This creates a pairwise exchange of photons between a high-Q cavity and the environment. The resulting open dynamical system develops a two-dimensional quasi-energy ground state manifold. Can we encode, protect and manipulate quantum information in this manifold? We experimentally investigate the convergence and escape rates in and out of this confined subspace. Finally, using quantum Zeno dynamics, we aim to perform gates which maintain the state in the protected manifold at all times. Work supported by: ARO, ONR, AFOSR and YINQE.
Invariant Manifolds, the Spatial Three-Body Problem and Space Mission Design
NASA Technical Reports Server (NTRS)
Gomez, G.; Koon, W. S.; Lo, Martin W.; Marsden, J. E.; Masdemont, J.; Ross, S. D.
2001-01-01
The invariant manifold structures of the collinear libration points for the spatial restricted three-body problem provide the framework for understanding complex dynamical phenomena from a geometric point of view. In particular, the stable and unstable invariant manifold 'tubes' associated to libration point orbits are the phase space structures that provide a conduit for orbits between primary bodies for separate three-body systems. These invariant manifold tubes can be used to construct new spacecraft trajectories, such as 'Petit Grand Tour' of the moons of Jupiter. Previous work focused on the planar circular restricted three-body problem. The current work extends the results to the spatial case.
Three-dimensional representations of the tube manifolds of the planar restricted three-body problem
NASA Astrophysics Data System (ADS)
Lega, Elena; Guzzo, Massimiliano
2016-06-01
The stable and unstable manifolds of the Lyapunov orbits of the Lagrangian equilibrium points L1, L2 play a key role in the understanding of the complicated dynamics of the circular restricted three-body problem. By developing a recent technique of computation of the stable and unstable manifolds, based on the use of Fast Lyapunov Indicators modified by the introduction of a filtering window function, we compute sample three-dimensional representations of the manifolds which show an original vista about their complicated development in the phase-space.
Chen, Xiaoguang; Liu, Dan; Xu, Guanghua; Jiang, Kuosheng; Liang, Lin
2015-01-01
For decades, bearing factory quality evaluation has been a key problem and the methods used are always static tests. This paper investigates the use of piezoelectric ultrasonic transducers (PUT) as dynamic diagnostic tools and a relevant signal classification technique, wavelet packet entropy (WPEntropy) flow manifold learning, for the evaluation of bearing factory quality. The data were analyzed using wavelet packet entropy (WPEntropy) flow manifold learning. The results showed that the ultrasonic technique with WPEntropy flow manifold learning was able to detect different types of defects on the bearing components. The test method and the proposed technique are described and the different signals are analyzed and discussed. PMID:25549173
Chapter 11: Dietary reference intakes
Technology Transfer Automated Retrieval System (TEKTRAN)
The Dietary Reference Intakes (DRI) are a set of recommendations intended to provide guidance in evaluating nutrient intakes and planning meals on the basis of nutrient adequacy. In contrast to their predecessor, Recommended Dietary Allowances last published in 1989, the DRIs differ in two ways: th...
Vitamin K Intake and Atherosclerosis
Technology Transfer Automated Retrieval System (TEKTRAN)
It has been hypothesized that insufficient intake of vitamin K may increase soft tissue calcification due to impaired gamma-carboxylation of the vitamin K-dependent protein, matrix gamma-carboxyglutamic acid (MGP). The evidence to support this putative role of vitamin K intake in atherosclerosis is ...
Air-liquid solar collector for solar heating, combined heating and cooling, and hot water subsystems
NASA Technical Reports Server (NTRS)
1978-01-01
A collection of quarterly reports consisting of the installation and layout design of the air collector system for commercial applications, completion of the preliminary design review, detailed design efforts, and preparation of the verification test plan are given. Performance specifications and performance testing of a prototype model of a two manifold, 144 tube air collector array is presented.
The Einstein-Λ flow on product manifolds
NASA Astrophysics Data System (ADS)
Fajman, David; Kröncke, Klaus
2016-12-01
We consider the vacuum Einstein flow with a positive cosmological constant {{Λ }} on spatial manifolds of product form M={M}1× {M}2. In dimensions n=\\dim M≥slant 4 we show the existence of continuous families of recollapsing models whenever at least one of the factors M 1 or M 2 admits a Riemannian Einstein metric with positive Einstein constant. We moreover show that these families belong to larger continuous families with models that have two complete time directions, i.e. do not recollapse. Complementarily, we show that whenever no factor has positive curvature, then any model in the product class expands in one time direction and collapses in the other. In particular, positive curvature of one factor is a necessary criterion for recollapse within this class. Finally, we relate our results to the instability of the Nariai solution in three spatial dimensions and point out why a similar construction of recollapsing models in that dimension fails. The present results imply that there exist different classes of initial data which exhibit fundamentally different types of long-time behavior under the Einstein-{{Λ }} flow whenever the spatial dimension is strictly larger than three. Moreover, this behavior is related to the spatial topology through the existence of Riemannian Einstein metrics of positive curvature.
Seven-disk manifold, α -attractors, and B modes
NASA Astrophysics Data System (ADS)
Ferrara, Sergio; Kallosh, Renata
2016-12-01
Cosmological α -attractor models in N =1 supergravity are based on the hyperbolic geometry of a Poincaré disk with the radius square R2=3 α . The predictions for the B modes, r ≈3 α 4/N2, depend on moduli space geometry and are robust for a rather general class of potentials. Here we notice that starting with M theory compactified on a 7-manifold with G2 holonomy, with a special choice of Betti numbers, one can obtain d =4 , N =1 supergravity with the rank 7 scalar coset [S/L (2 ) S O (2 ) ]7. In a model where these seven unit size Poincaré disks have identified moduli one finds that 3 α =7 . Assuming that the moduli space geometry of the phenomenological models is inherited from this version of M theory, one would predict r ≈10-2 for N =53 e -foldings. We also describe the related maximal supergravity and M/string theory models leading to preferred values 3 α =1 , 2, 3, 4, 5, 6, 7.
Flowing on Riemannian manifold: domain adaptation by shifting covariance.
Cui, Zhen; Li, Wen; Xu, Dong; Shan, Shiguang; Chen, Xilin; Li, Xuelong
2014-12-01
Domain adaptation has shown promising results in computer vision applications. In this paper, we propose a new unsupervised domain adaptation method called domain adaptation by shifting covariance (DASC) for object recognition without requiring any labeled samples from the target domain. By characterizing samples from each domain as one covariance matrix, the source and target domain are represented into two distinct points residing on a Riemannian manifold. Along the geodesic constructed from the two points, we then interpolate some intermediate points (i.e., covariance matrices), which are used to bridge the two domains. By utilizing the principal components of each covariance matrix, samples from each domain are further projected into intermediate feature spaces, which finally leads to domain-invariant features after the concatenation of these features from intermediate points. In the multiple source domain adaptation task, we also need to effectively integrate different types of features between each pair of source and target domains. We additionally propose an SVM based method to simultaneously learn the optimal target classifier as well as the optimal weights for different source domains. Extensive experiments demonstrate the effectiveness of our method for both single source and multiple source domain adaptation tasks.
Descriptor Learning via Supervised Manifold Regularization for Multioutput Regression.
Zhen, Xiantong; Yu, Mengyang; Islam, Ali; Bhaduri, Mousumi; Chan, Ian; Li, Shuo
2016-06-08
Multioutput regression has recently shown great ability to solve challenging problems in both computer vision and medical image analysis. However, due to the huge image variability and ambiguity, it is fundamentally challenging to handle the highly complex input-target relationship of multioutput regression, especially with indiscriminate high-dimensional representations. In this paper, we propose a novel supervised descriptor learning (SDL) algorithm for multioutput regression, which can establish discriminative and compact feature representations to improve the multivariate estimation performance. The SDL is formulated as generalized low-rank approximations of matrices with a supervised manifold regularization. The SDL is able to simultaneously extract discriminative features closely related to multivariate targets and remove irrelevant and redundant information by transforming raw features into a new low-dimensional space aligned to targets. The achieved discriminative while compact descriptor largely reduces the variability and ambiguity for multioutput regression, which enables more accurate and efficient multivariate estimation. We conduct extensive evaluation of the proposed SDL on both synthetic data and real-world multioutput regression tasks for both computer vision and medical image analysis. Experimental results have shown that the proposed SDL can achieve high multivariate estimation accuracy on all tasks and largely outperforms the algorithms in the state of the arts. Our method establishes a novel SDL framework for multioutput regression, which can be widely used to boost the performance in different applications.
Manifold-Based Reinforcement Learning via Locally Linear Reconstruction.
Xu, Xin; Huang, Zhenhua; Zuo, Lei; He, Haibo
2017-04-01
Feature representation is critical not only for pattern recognition tasks but also for reinforcement learning (RL) methods to solve learning control problems under uncertainties. In this paper, a manifold-based RL approach using the principle of locally linear reconstruction (LLR) is proposed for Markov decision processes with large or continuous state spaces. In the proposed approach, an LLR-based feature learning scheme is developed for value function approximation in RL, where a set of smooth feature vectors is generated by preserving the local approximation properties of neighboring points in the original state space. By using the proposed feature learning scheme, an LLR-based approximate policy iteration (API) algorithm is designed for learning control problems with large or continuous state spaces. The relationship between the value approximation error of a new data point and the estimated values of its nearest neighbors is analyzed. In order to compare different feature representation and learning approaches for RL, a comprehensive simulation and experimental study was conducted on three benchmark learning control problems. It is illustrated that under a wide range of parameter settings, the LLR-based API algorithm can obtain better learning control performance than the previous API methods with different feature representation schemes.
Multimodal Medical Image Fusion by Adaptive Manifold Filter.
Geng, Peng; Liu, Shuaiqi; Zhuang, Shanna
2015-01-01
Medical image fusion plays an important role in diagnosis and treatment of diseases such as image-guided radiotherapy and surgery. The modified local contrast information is proposed to fuse multimodal medical images. Firstly, the adaptive manifold filter is introduced into filtering source images as the low-frequency part in the modified local contrast. Secondly, the modified spatial frequency of the source images is adopted as the high-frequency part in the modified local contrast. Finally, the pixel with larger modified local contrast is selected into the fused image. The presented scheme outperforms the guided filter method in spatial domain, the dual-tree complex wavelet transform-based method, nonsubsampled contourlet transform-based method, and four classic fusion methods in terms of visual quality. Furthermore, the mutual information values by the presented method are averagely 55%, 41%, and 62% higher than the three methods and those values of edge based similarity measure by the presented method are averagely 13%, 33%, and 14% higher than the three methods for the six pairs of source images.
Fibromyalgia: generalized pain intolerance and manifold symptom reporting.
Quimby, L G; Block, S R; Gratwick, G M
1988-08-01
We tested the current criteria for fibromyalgia. Pain tolerance was measured at tender point and control point sites using a pressure algometer, and responses to 6 standard psychological self-reports were obtained from 125 patients with generalized nonarticular rheumatism, rheumatoid arthritis, or osteoarthritis. Among patients with generalized nonarticular rheumatism, published symptom criteria for fibromyalgia did not correlate significantly with the number of tender points. Only lower generalized pressure point pain tolerance distinguished fibromyalgia from other generalized nonarticular rheumatism. Generalized nonarticular rheumatism mean scores were much higher than controls on tests measuring the tendency to report physical symptoms, including headaches and functional bowel syndrome. It is probable that patients with fibromyalgia do not differ in any important physical or psychological respect from other patients with generalized nonarticular rheumatism except for the presence of tender points. However, the presence of tender points is merely a reflection of the patient's general pressure pain sensitivity and is not indicative of any special localized pathological phenomenon. The concept of fibromyalgia as an entity separate from the rest of generalized nonarticular rheumatism may be an artifact of a physician's approach to the patient. Most patients with generalized nonarticular rheumatism demonstrate an abnormally high frequency of reporting manifold disagreeable symptoms and probably come to the attention of many medical disciplines.
Surrogate based wind farm layout optimization using manifold mapping
NASA Astrophysics Data System (ADS)
Kaja Kamaludeen, Shaafi M.; van Zuijle, Alexander; Bijl, Hester
2016-09-01
High computational cost associated with the high fidelity wake models such as RANS or LES serves as a primary bottleneck to perform a direct high fidelity wind farm layout optimization (WFLO) using accurate CFD based wake models. Therefore, a surrogate based multi-fidelity WFLO methodology (SWFLO) is proposed. The surrogate model is built using an SBO method referred as manifold mapping (MM). As a verification, optimization of spacing between two staggered wind turbines was performed using the proposed surrogate based methodology and the performance was compared with that of direct optimization using high fidelity model. Significant reduction in computational cost was achieved using MM: a maximum computational cost reduction of 65%, while arriving at the same optima as that of direct high fidelity optimization. The similarity between the response of models, the number of mapping points and its position, highly influences the computational efficiency of the proposed method. As a proof of concept, realistic WFLO of a small 7-turbine wind farm is performed using the proposed surrogate based methodology. Two variants of Jensen wake model with different decay coefficients were used as the fine and coarse model. The proposed SWFLO method arrived at the same optima as that of the fine model with very less number of fine model simulations.
Stretch fast dynamo mechanism via conformal mapping in Riemannian manifolds
Garcia de Andrade, L. C.
2007-10-15
Two new analytical solutions of the self-induction equation in Riemannian manifolds are presented. The first represents a twisted magnetic flux tube or flux rope in plasma astrophysics, where the rotation of the flow implies that the poloidal field is amplified from toroidal field, in the spirit of dynamo theory. The value of the amplification depends on the Frenet torsion of the magnetic axis of the tube. Actually this result illustrates the Zeldovich stretch, twist, and fold method to generate dynamos from straight and untwisted ropes. Based on the fact that this problem was previously handled, using a Riemannian geometry of twisted magnetic flux ropes [Phys Plasmas 13, 022309 (2006)], investigation of a second dynamo solution, conformally related to the Arnold kinematic fast dynamo, is obtained. In this solution, it is shown that the conformal effect on the fast dynamo metric enhances the Zeldovich stretch, and therefore a new dynamo solution is obtained. When a conformal mapping is performed in an Arnold fast dynamo line element, a uniform stretch is obtained in the original line element.
Multiple Brake Orbits and Homoclinics in Riemannian Manifolds
NASA Astrophysics Data System (ADS)
Giambò, Roberto; Giannoni, Fabio; Piccione, Paolo
2011-05-01
Let ( M, g) be a complete Riemannian manifold, {Ωsubset M} an open subset whose closure is homeomorphic to an annulus. We prove that if ∂Ω is smooth and it satisfies a strong concavity assumption, then there are at least two distinct geodesics in {overlineΩ=Ω\\cupd \\ppartialΩ} starting orthogonally to one connected component of ∂Ω and arriving orthogonally onto the other one. Using the results given in Giambò et al. (Adv Differ Equ 10:931-960, 2005), we then obtain a proof of the existence of two distinct homoclinic orbits for an autonomous Lagrangian system emanating from a nondegenerate maximum point of the potential energy, and a proof of the existence of two distinct brake orbits for a class of Hamiltonian systems. Under a further symmetry assumption, the result is improved by showing the existence of at least dim( M) pairs of geometrically distinct geodesics as above, brake orbits and homoclinic orbits. In our proof we shall use recent deformation results proved in Giambò et al. (Nonlinear Anal Ser A: Theory Methods Appl 73:290-337, 2010).
The manifold zoology of anelastic dynamos with variable conductivity
NASA Astrophysics Data System (ADS)
Dietrich, Wieland; Jones, Chris
2015-04-01
Whereas the dynamo processes in terrestrial planets is strongly influenced by the overlying rocky mantle, the induction of global magnetic fields in gas giants is mainly affected by internal properties, such as the rapid outward decay of static density, pressure and temperature throughout the gaseous shell. Further for Jupiter and Saturn it is well known that the transition from metallic to molecular hydrogen leads to a steep decrease in the electrical conductivity. This drop-off radius is closer to the surface for heavy Jupiter (at 90% of its respective radius), but much deeper for the less massive Saturn (65%). From the modelling perspective this leads to an inner conducting shell where the magnetic fields dominate the dynamics, and outer hydro dynamic shell where the strong Coriolis force reigns. Within this study we parametrise the conductivity drop-off radius and investigate the interaction between these shells, such as the emergence of differential rotation and induction of magnetic fields. Remarkably, we could identify numerous rather different self-consistent dynamo solutions. E.g., hemispherical dynamos, quadrupolar dynamos, octupolar dynamos, dipolar dynamo waves or many mixed modes, such as solutions where the quadrupole is stable in time and the dipole periodically reverses. In summary, our results suggest anelastic dynamo models with variable conductivity yield manifold different solutions in close poriximity in the parameter space. Unfortunately for Saturn-like models with deep conductivity drop-off, Saturn-like magnetic field (stable, strongly dipolar) seemed rather unlikely.
Manifold and method of batch measurement of Hg-196 concentration using a mass spectrometer
Grossman, M.W.; Evans, R.
1991-11-26
A sample manifold and method of its use has been developed so that milligram quantities of mercury can be analyzed mass spectroscopically to determine the [sup 196]Hg concentration to less than 0.02 atomic percent. Using natural mercury as a standard, accuracy of [+-]0.002 atomic percent can be obtained. The mass spectrometer preferably used is a commercially available GC/MS manufactured by Hewlett Packard. A novel sample manifold is contained within an oven allowing flow rate control of Hg into the MS. Another part of the manifold connects to an auxiliary pumping system which facilitates rapid clean up of residual Hg in the manifold. Sample cycle time is about 1 hour. 8 figures.
NASA Astrophysics Data System (ADS)
Balasuriya, Sanjeeva
2016-12-01
State-dependent time-impulsive perturbations to a two-dimensional autonomous flow with stable and unstable manifolds are analysed by posing in terms of an integral equation which is valid in both forwards- and backwards-time. The impulses destroy the smooth invariant manifolds, necessitating new definitions for stable and unstable pseudo-manifolds. Their time-evolution is characterised by solving a Volterra integral equation of the second kind with discontinuous inhomogeniety. A criteria for heteroclinic trajectory persistence in this impulsive context is developed, as is a quantification of an instantaneous flux across broken heteroclinic manifolds. Several examples, including a kicked Duffing oscillator and an underwater explosion in the vicinity of an eddy, are used to illustrate the theory.
Computing (Un)stable Manifolds with Validated Error Bounds: Non-resonant and Resonant Spectra
NASA Astrophysics Data System (ADS)
van den Berg, Jan Bouwe; Mireles James, Jason D.; Reinhardt, Christian
2016-08-01
We develop techniques for computing the (un)stable manifold at a hyperbolic equilibrium of an analytic vector field. Our approach is based on the so-called parametrization method for invariant manifolds. A feature of this approach is that it leads to a posteriori analysis of truncation errors which, when combined with careful management of round off errors, yields a mathematically rigorous enclosure of the manifold. The main novelty of the present work is that, by conjugating the dynamics on the manifold to a polynomial rather than a linear vector field, the computer-assisted analysis is successful even in the case when the eigenvalues fail to satisfy non-resonance conditions. This generically occurs in parametrized families of vector fields. As an example, we use the method as a crucial ingredient in a computational existence proof of a connecting orbit in an amplitude equation related to a pattern formation model that features eigenvalue resonances.
Conjugate Heat Transfer Analyses on the Manifold for Ramjet Fuel Injectors
NASA Technical Reports Server (NTRS)
Wang, Xiao-Yen J.
2006-01-01
Three-dimensional conjugate heat transfer analyses on the manifold located upstream of the ramjet fuel injector are performed using CFdesign, a finite-element computational fluid dynamics (CFD) software. The flow field of the hot fuel (JP-7) flowing through the manifold is simulated and the wall temperature of the manifold is computed. The three-dimensional numerical results of the fuel temperature are compared with those obtained using a one-dimensional analysis based on empirical equations, and they showed a good agreement. The numerical results revealed that it takes around 30 to 40 sec to reach the equilibrium where the fuel temperature has dropped about 3 F from the inlet to the exit of the manifold.
The role of invariant manifolds in lowthrust trajectory design (part III)
NASA Technical Reports Server (NTRS)
Lo, Martin W.; Anderson, Rodney L.; Lam, Try; Whiffen, Greg
2006-01-01
This paper is the third in a series to explore the role of invariant manifolds in the design of low thrust trajectories. In previous papers, we analyzed an impulsive thrust resonant gravity assist flyby trajectory to capture into Europa orbit using the invariant manifolds of unstable resonant periodic orbits and libration orbits. The energy savings provided by the gravity assist may be interpreted dynamically as the result of a finite number of intersecting invariant manifolds. In this paper we demonstrate that the same dynamics is at work for low thrust trajectories with resonant flybys and low energy capture. However, in this case, the flybys and capture are effected by continuous families of intersecting invariant manifolds.
Manifold and method of batch measurement of Hg-196 concentration using a mass spectrometer
Grossman, Mark W.; Evans, Roger
1991-01-01
A sample manifold and method of its use has been developed so that milligram quantities of mercury can be analyzed mass spectroscopically to determine the .sup.196 Hg concentration to less than 0.02 atomic percent. Using natural mercury as a standard, accuracy of .+-.0.002 atomic percent can be obtained. The mass spectrometer preferably used is a commercially available GC/MS manufactured by Hewlett Packard. A novel sample manifold is contained within an oven allowing flow rate control of Hg into the MS. Another part of the manifold connects to an auxiliary pumping system which facilitates rapid clean up of residual Hg in the manifold. Sample cycle time is about 1 hour.
Fast sampling in the slow manifold: The momentum-enhanced hybrid Monte Carlo method
NASA Astrophysics Data System (ADS)
Andricioaei, Ioan
2005-03-01
We will present a novel dynamic algorithm, the MEHMC method, which enhances sampling and at the same time yielding correct Boltzmann weighted statistical distributions. The gist of the MEHMC method is to use momentum averaging to identify the slow manifold and bias along this manifold the Maxwell distribution of momenta usually employed in Hybrid Monte Carlo. Several tests and applications are to exemplify the method.
A twistor-sphere of generalized Kaehler potentials on hyperkaehler manifolds
NASA Astrophysics Data System (ADS)
Dyckmanns, Malte
2011-12-01
We consider generalized Kahler structures ( g,J+,J--) on a hyperkahler manifold (M,g,I,J,K), where we use the twistor space of M to choose J+ and J --. Relating semi-chiral to arctic superfields, we can determine the generalized Kahler potential for hyperkahler manifolds whose description in projective superspace is known. This is used to determine an S2-family of generalized Kahler potentials for Euclidean space and for the Eguchi-Hanson geometry.
Characteristic classes of star products on Marsden-Weinstein reduced symplectic manifolds
NASA Astrophysics Data System (ADS)
Reichert, Thorsten
2017-04-01
In this note we consider a quantum reduction scheme in deformation quantization on symplectic manifolds proposed by Bordemann, Herbig and Waldmann based on BRST cohomology. We explicitly construct the induced map on equivalence classes of star products which will turn out to be an analogue to the Kirwan map in the Cartan model of equivariant cohomology. As a byproduct, we shall see that every star product on a (suitable) reduced manifold is equivalent to a reduced star product.
The relative isoperimetric inequality on a conformally parabolic manifold with boundary
Kesel'man, Vladimir M
2011-07-31
For an arbitrary noncompact n-dimensional Riemannian manifold with a boundary of conformally parabolic type it is proved that there exists a conformal change of metric such that a relative isoperimetric inequality of the same form as in the closed n-dimensional Euclidean half-space holds on the manifold with the new metric. This isoperimetric inequality is asymptotically sharp. Bibliography: 6 titles.
Characteristic classes of star products on Marsden-Weinstein reduced symplectic manifolds
NASA Astrophysics Data System (ADS)
Reichert, Thorsten
2016-12-01
In this note we consider a quantum reduction scheme in deformation quantization on symplectic manifolds proposed by Bordemann, Herbig and Waldmann based on BRST cohomology. We explicitly construct the induced map on equivalence classes of star products which will turn out to be an analogue to the Kirwan map in the Cartan model of equivariant cohomology. As a byproduct, we shall see that every star product on a (suitable) reduced manifold is equivalent to a reduced star product.
Analytical invariant manifolds near unstable points and the structure of chaos
NASA Astrophysics Data System (ADS)
Efthymiopoulos, Christos; Contopoulos, George; Katsanikas, Matthaios
2014-08-01
It is known that the asymptotic invariant manifolds around an unstable periodic orbit in conservative systems can be represented by convergent series (Cherry, Proc Lond Math Soc ser 2, 27:151-170, 1926; Moser, Commun Pure Appl Math 9:673, 1956 and 11:257, 1958; Moser, Giorgilli, Discret Contin Dyn Syst 7:855, 2001). The unstable and stable manifolds intersect at an infinity of homoclinic points, generating a complicated homoclinic tangle. In the case of simple mappings it was found (Da Silva Ritter et al., Phys D 29:181, 1987) that the domain of convergence of the formal series extends to infinity along the invariant manifolds. This allows in practice the study of the homoclinic tangle using only series. However in the case of Hamiltonian systems, or mappings with a finite analyticity domain, the convergence of the series along the asymptotic manifolds is also finite. Here, we provide numerical indications that the convergence does not reach any homoclinic points. We discuss in detail the convergence problem in various cases and we find the degree of approximation of the analytical invariant manifolds to the real (numerical) manifolds as (i) the order of truncation of the series increases, and (ii) we use higher numerical precision in computing the coefficients of the series. Then we introduce a new method of series composition, by using action-angle variables, that allows the calculation of the asymptotic manifolds up to an a arbitrarily large extent. This is the first case of an analytic development that allows the computation of the invariant manifolds and their intersections in a Hamiltonian system for an extent long enough to allow the study of homoclinic chaos by analytical means.
An adaptive locally linear embedding manifold learning approach for hyperspectral target detection
NASA Astrophysics Data System (ADS)
Ziemann, Amanda K.; Messinger, David W.
2015-05-01
Algorithms for spectral analysis commonly use parametric or linear models of the data. Research has shown, however, that hyperspectral data -- particularly in materially cluttered scenes -- are not always well-modeled by statistical or linear methods. Here, we propose an approach to hyperspectral target detection that is based on a graph theory model of the data and a manifold learning transformation. An adaptive nearest neighbor (ANN) graph is built on the data, and then used to implement an adaptive version of locally linear embedding (LLE). We artificially induce a target manifold and incorporate it into the adaptive LLE transformation. The artificial target manifold helps to guide the separation of the target data from the background data in the new, transformed manifold coordinates. Then, target detection is performed in the manifold space using Spectral Angle Mapper. This methodology is an improvement over previous iterations of this approach due to the incorporation of ANN, the artificial target manifold, and the choice of detector in the transformed space. We implement our approach in a spatially local way: the image is delineated into square tiles, and the detection maps are normalized across the entire image. Target detection results will be shown using laboratory-measured and scene-derived target data from the SHARE 2012 collect.
Constrained manifold learning for the characterization of pathological deviations from normality.
Duchateau, Nicolas; De Craene, Mathieu; Piella, Gemma; Frangi, Alejandro F
2012-12-01
This paper describes a technique to (1) learn the representation of a pathological motion pattern from a given population, and (2) compare individuals to this population. Our hypothesis is that this pattern can be modeled as a deviation from normal motion by means of non-linear embedding techniques. Each subject is represented by a 2D map of local motion abnormalities, obtained from a statistical atlas of myocardial motion built from a healthy population. The algorithm estimates a manifold from a set of patients with varying degrees of the same disease, and compares individuals to the training population using a mapping to the manifold and a distance to normality along the manifold. The approach extends recent manifold learning techniques by constraining the manifold to pass by a physiologically meaningful origin representing a normal motion pattern. Interpolation techniques using locally adjustable kernel improve the accuracy of the method. The technique is applied in the context of cardiac resynchronization therapy (CRT), focusing on a specific motion pattern of intra-ventricular dyssynchrony called septal flash (SF). We estimate the manifold from 50 CRT candidates with SF and test it on 37 CRT candidates and 21 healthy volunteers. Experiments highlight the relevance of non-linear techniques to model a pathological pattern from the training set and compare new individuals to this pattern.
Dietary Salt Intake and Hypertension
2014-01-01
Over the past century, salt has been the subject of intense scientific research related to blood pressure elevation and cardiovascular mortalities. Moderate reduction of dietary salt intake is generally an effective measure to reduce blood pressure. However, recently some in the academic society and lay media dispute the benefits of salt restriction, pointing to inconsistent outcomes noted in some observational studies. A reduction in dietary salt from the current intake of 9-12 g/day to the recommended level of less than 5-6 g/day will have major beneficial effects on cardiovascular health along with major healthcare cost savings around the world. The World Health Organization (WHO) strongly recommended to reduce dietary salt intake as one of the top priority actions to tackle the global non-communicable disease crisis and has urged member nations to take action to reduce population wide dietary salt intake to decrease the number of deaths from hypertension, cardiovascular disease and stroke. However, some scientists still advocate the possibility of increased risk of CVD morbidity and mortality at extremes of low salt intake. Future research may inform the optimal sodium reduction strategies and intake targets for general populations. Until then, we have to continue to build consensus around the greatest benefits of salt reduction for CVD prevention, and dietary salt intake reduction strategies must remain at the top of the public health agenda. PMID:25061468
Shephard, Roy J.; Allen, C.; Benade, A. J. S.; Davies, C. T. M.; di Prampero, P. E.; Hedman, R.; Merriman, J. E.; Myhre, K.; Simmons, R.
1968-01-01
Lack of cardiorespiratory fitness may well contribute to the increasing prevalence of degenerative cardiovascular disease throughout the world. As a first step towards co-ordinated and internationally comparable investigation of this problem, methods of measuring the reference standard of cardiorespiratory fitness—the maximum oxygen intake, (V̇o2)max—were compared by an international working party that met in Toronto in the summer of 1967. Repeated testing of 24 subjects showed that the (V̇o2)max was greatest on the treadmill, 3.4% smaller in a stepping test, and 6.6% smaller during use of a bicycle ergometer. There were also parallel differences in cardiac stroke volume. Uphill treadmill running was recommended for the laboratory measurement of (V̇o2)max, and stepping or bicycle exercise for field studies. A discontinuous series of maximum tests caused some improvement in the fitness of subjects, and a “continuous” test (with small increases in load at 2-min intervals) was preferred. PMID:5303329
11. Photocopied August 1978. INTAKE LOOKING NORTH AT UPPER INTAKE ...
11. Photocopied August 1978. INTAKE LOOKING NORTH AT UPPER INTAKE COFFER DAM, OCTOBER 10, 1900. ONE OF THE HUBBELL COMPANY DREDGES IS AT WORK IN THE CENTER OF THE ILLUSTRATION, THE TIMBER FLOATING AROUND WAS PROBABLY FOR USE IN THE CONSTRUCTION OF SIDE WALL RETAINING CRIBS. ONE OF THESE IS BEING CONSTRUCTED JUST TO THE LEFT AND TOWARDS THE VIEWER FROM THE DREDGES. (87) - Michigan Lake Superior Power Company, Portage Street, Sault Ste. Marie, Chippewa County, MI
Girls' dairy intake, energy intake, and weight status.
Fiorito, Laura M; Ventura, Alison K; Mitchell, Diane C; Smiciklas-Wright, Helen; Birch, Leann L
2006-11-01
We explored the relationships among girls' weight status, dairy servings, and total energy intake. The hypothesis that consuming dairy could reduce risk for overweight was evaluated by comparing energy intake and weight status of girls who met or consumed less than the recommended three servings of dairy per day. Participants included 172 11-year-old non-Hispanic white girls, assessed cross-sectionally. Intakes of dairy, calcium, and energy were measured using three 24-hour recalls. Body mass index and body fat measures from dual-energy x-ray absorptiometry were obtained. Because preliminary analyses suggested systematic underreporting of energy intake, the relationships among dairy servings and measures of weight status were examined for the total sample and for subsamples of under-, plausible, and overreporters. Data for the total sample provided support for the hypothesized relationship among weight status, dairy servings, and energy intake. Thirty-nine percent of girls reported consuming the recommended >/=3 servings of dairy per day; these girls also reported higher energy intake but had lower body mass index z scores and body fat than the girls who consumed fewer than three dairy servings each day. Among plausible reporters, no relationship between dairy intake and weight status was noted. This discrepancy may be attributable to a high percentage (45%) of overweight underreporters in the total sample. Our findings reveal that reporting bias, resulting from the presence of a substantial proportion of underreporters of higher weight status, can contribute to obtaining spurious associations between dairy intake and weight status. These findings underscore the need for randomly controlled trials to assess the role of dairy in weight management.
Girls’ Dairy Intake, Energy Intake, and Weight Status
FIORITO, LAURA M.; VENTURA, ALISON K.; MITCHELL, DIANE C.; SMICIKLAS-WRIGHT, HELEN; BIRCH, LEANN L.
2008-01-01
We explored the relationships among girls’ weight status, dairy servings, and total energy intake. The hypothesis that consuming dairy could reduce risk for overweight was evaluated by comparing energy intake and weight status of girls who met or consumed less than the recommended three servings of dairy per day. Participants included 172 11-year-old non-Hispanic white girls, assessed cross-sectionally. Intakes of dairy, calcium, and energy were measured using three 24-hour recalls. Body mass index and body fat measures from dual-energy x-ray absorptiometry were obtained. Because preliminary analyses suggested systematic underreporting of energy intake, the relationships among dairy servings and measures of weight status were examined for the total sample and for subsamples of under-, plausible, and overreporters. Data for the total sample provided support for the hypothesized relationship among weight status, dairy servings, and energy intake. Thirty-nine percent of girls reported consuming the recommended ≥3 servings of dairy per day; these girls also reported higher energy intake but had lower body mass index z scores and body fat than the girls who consumed fewer than three dairy servings each day. Among plausible reporters, no relationship between dairy intake and weight status was noted. This discrepancy may be attributable to a high percentage (45%) of overweight underreporters in the total sample. Our findings reveal that reporting bias, resulting from the presence of a substantial proportion of underreporters of higher weight status, can contribute to obtaining spurious associations between dairy intake and weight status. These findings underscore the need for randomly controlled trials to assess the role of dairy in weight management. PMID:17081836
Emergence from general anesthesia and the sleep-manifold
Hight, Darren F.; Dadok, Vera M.; Szeri, Andrew J.; García, Paul S.; Voss, Logan; Sleigh, Jamie W.
2014-01-01
The electroencephalogram (EEG) during the re-establishment of consciousness after general anesthesia and surgery varies starkly between patients. Can the EEG during this emergence period provide a means of estimating the underlying biological processes underpinning the return of consciousness? Can we use a model to infer these biological processes from the EEG patterns? A frontal EEG was recorded from 84 patients. Ten patients were chosen for state-space analysis. Five showed archetypal emergences; which consisted of a progressive decrease in alpha power and increase peak alpha frequency before return of responsiveness. The five non-archetypal emergences showed almost no spectral EEG changes (even as the volatile general anesthetic decreased) and then an abrupt return of responsiveness. We used Bayesian methods to estimate the likelihood of an EEG pattern corresponding to the position of the patient on a 2-dimensional manifold in a state space of excitatory connection strength vs. change in intrinsic resting neuronal membrane conductivity. We could thus visualize the trajectory of each patient in the state-space during their emergence period. The patients who followed an archetypal emergence displayed a very consistent pattern; consisting of progressive increase in conductivity, and a temporary period of increased connection strength before return of responsiveness. The non-archetypal emergence trajectories remained fixed in a region of phase space characterized by a relatively high conductivity and low connection strength throughout emergence. This unexpected progressive increase in conductivity during archetypal emergence may be due to an abating of the surgical stimulus during this period. Periods of high connection strength could represent forays into dissociated consciousness, but the model suggests all patients reposition near the fold in the state space to take advantage of bi-stable cortical dynamics before transitioning to consciousness. PMID:25165436
Emergence from general anesthesia and the sleep-manifold.
Hight, Darren F; Dadok, Vera M; Szeri, Andrew J; García, Paul S; Voss, Logan; Sleigh, Jamie W
2014-01-01
The electroencephalogram (EEG) during the re-establishment of consciousness after general anesthesia and surgery varies starkly between patients. Can the EEG during this emergence period provide a means of estimating the underlying biological processes underpinning the return of consciousness? Can we use a model to infer these biological processes from the EEG patterns? A frontal EEG was recorded from 84 patients. Ten patients were chosen for state-space analysis. Five showed archetypal emergences; which consisted of a progressive decrease in alpha power and increase peak alpha frequency before return of responsiveness. The five non-archetypal emergences showed almost no spectral EEG changes (even as the volatile general anesthetic decreased) and then an abrupt return of responsiveness. We used Bayesian methods to estimate the likelihood of an EEG pattern corresponding to the position of the patient on a 2-dimensional manifold in a state space of excitatory connection strength vs. change in intrinsic resting neuronal membrane conductivity. We could thus visualize the trajectory of each patient in the state-space during their emergence period. The patients who followed an archetypal emergence displayed a very consistent pattern; consisting of progressive increase in conductivity, and a temporary period of increased connection strength before return of responsiveness. The non-archetypal emergence trajectories remained fixed in a region of phase space characterized by a relatively high conductivity and low connection strength throughout emergence. This unexpected progressive increase in conductivity during archetypal emergence may be due to an abating of the surgical stimulus during this period. Periods of high connection strength could represent forays into dissociated consciousness, but the model suggests all patients reposition near the fold in the state space to take advantage of bi-stable cortical dynamics before transitioning to consciousness.
Manifold learning approach for chaos in the dripping faucet.
Suetani, Hiromichi; Soejima, Karin; Matsuoka, Rei; Parlitz, Ulrich; Hata, Hiroki
2012-09-01
Dripping water from a faucet is a typical example exhibiting rich nonlinear phenomena. For such a system, the time stamps at which water drops separate from the faucet can be directly observed in real experiments, and the time series of intervals τn between drop separations becomes a subject of analysis. Even if the mass mn of a drop at the onset of the nth separation, which is difficult to observe experimentally, exhibits perfectly deterministic dynamics, it may be difficult to obtain the same information about the underlying dynamics from the time series τn. This is because the return plot τn-1 vs. τn may become a multivalued relation (i.e., it doesn't represent a function describing deterministic dynamics). In this paper, we propose a method to construct a nonlinear coordinate which provides a "surrogate" of the internal state mn from the time series of τn. Here, a key of the proposed approach is to use isomap, which is a well-known method of manifold learning. We first apply it to the time series of τn generated from the numerical simulation of a phenomenological mass-spring model for the dripping faucet system. It is shown that a clear one-dimensional map is obtained by the proposed approach, whose characteristic quantities such as the Lyapunov exponent, the topological entropy, and the time correlation function coincide with the original dripping faucet system. Furthermore, we also analyze data obtained from real dripping faucet experiments, which also provide promising results.
Quantization of Chern-Simons Theories on Manifolds with Boundaries
NASA Astrophysics Data System (ADS)
Bimonte, Giuseppe Roberto
The subject matter of this thesis deals with Chern -Simons Topological Field Theories in 2 + 1 space-time dimensions on manifolds with boundaries. We develop elementary canonical methods for the quantization of Abelian and non-Abelian Chern-Simons actions, only using well known ideas in gauge theories and quantum gravity. In particular, our approach does not involve choice of gauge or delicate manipulations of functional integrals. When the spacial slice is a disc, it yields Witten's edge states carrying a representation of the Kac -Moody algebra. The canonical expression for the generators of diffeomorphisms acting on the boundary of the disc are also found, and it is established that they are the Chern -Simons version of the Sugawara construction. The formalism is then extended to the inclusion of sources. The quantum states of a source with a fixed spatial location are shown to be those of a conformal family. The internal states of a source are not thus associated with just a single ray of a Hilbert space. Vertex operators for both abelian and non-abelian sources are constructed. The regularized abelian Wilson line is proved to be a vertex operator. The spin-statistics theorem is established for Chern-Simons dynamics even though the sources are not described by relativistic quantum fields. The proof employs particularly simple and transparent geometrical methods. These results are finally applied to the Chern -Simons formulation of gravity in 2 + 1 dimensions, due to Witten. Here also, when the spatial slice is a disc, edge states are found, carrying a representation of the ISO(2,1) Kac-Moody algebra. The appropriate vertex operator is constructed also for this theory. It is shown that when acting on the vacuum it creates particles with a discrete mass spectrum. The lowest mass particle induces a cylindrical space time geometry, while higher mass particles give an n-fold covering of the cylinder.
Prediction of imminent impactors: Manifold Of Variations methods
NASA Astrophysics Data System (ADS)
Tommei, G.; Milani Comparetti, A.; Spoto, F.; Bernardi, F.
2014-07-01
The asteroid impact risk has recently been demonstrated by the Celyabinsk and 2014AA events. In cases, like the two mentioned before, it is important to know, even with very few observations, whether or not there is the possibility of an immediate impact with the Earth. When such small asteroids are discovered, the confidence region resulting from preliminary orbit determination is not elongated in one direction, thus the Line Of Variations (LOV) is not representative of the entire region. If we use for a short arc of observations the attributable elements (A,ρ,dotρ), where A is the attributable, the confidence region is a thin shell surrounding a subset of the Admissible Region (AR). The Manifold Of Variations (MOV) is the set of the points S where the target function has a local minimum with respect to changes of A, for each fixed (ρ, dotρ), with minimum RMS of the residuals below some control Σ. When there is little information beyond A, S is parameterized by (A(ρ,dotρ), ρ,dotρ), defined on a subset B of the (ρ,dotρ) plane: B is an open set, not necessarily connected. Then the surface S can be computed point by point using a cobweb sampling (or a grid); then, each point could be used as Virtual Asteroid (VA) and propagated for some months in the future in order to have the trace of the cobweb (or grid) on the Target Plane (TP) of the immediate impact. In this presentation we are going to - define the MOV tool showing how it is used to predict imminent impactors; - discuss how to assign a Probability Density Function (PDF) to the MOV: this is not a simple problem because we want to take into account the PDF for observations, but also some constraints deriving from population and physical models. Moreover, we will address some examples using data from the NEOCP list of the Minor Planet Center (MPC).
A manifold learning approach to target detection in high-resolution hyperspectral imagery
NASA Astrophysics Data System (ADS)
Ziemann, Amanda K.
Imagery collected from airborne platforms and satellites provide an important medium for remotely analyzing the content in a scene. In particular, the ability to detect a specific material within a scene is of high importance to both civilian and defense applications. This may include identifying "targets" such as vehicles, buildings, or boats. Sensors that process hyperspectral images provide the high-dimensional spectral information necessary to perform such analyses. However, for a d-dimensional hyperspectral image, it is typical for the data to inherently occupy an m-dimensional space, with m << d. In the remote sensing community, this has led to a recent increase in the use of manifold learning, which aims to characterize the embedded lower-dimensional, non-linear manifold upon which the hyperspectral data inherently lie. Classic hyperspectral data models include statistical, linear subspace, and linear mixture models, but these can place restrictive assumptions on the distribution of the data; this is particularly true when implementing traditional target detection approaches, and the limitations of these models are well-documented. With manifold learning based approaches, the only assumption is that the data reside on an underlying manifold that can be discretely modeled by a graph. The research presented here focuses on the use of graph theory and manifold learning in hyperspectral imagery. Early work explored various graph-building techniques with application to the background model of the Topological Anomaly Detection (TAD) algorithm, which is a graph theory based approach to anomaly detection. This led towards a focus on target detection, and in the development of a specific graph-based model of the data and subsequent dimensionality reduction using manifold learning. An adaptive graph is built on the data, and then used to implement an adaptive version of locally linear embedding (LLE). We artificially induce a target manifold and incorporate it into
Statistical Shape Model for Manifold Regularization: Gleason grading of prostate histology.
Sparks, Rachel; Madabhushi, Anant
2013-09-01
Gleason patterns of prostate cancer histopathology, characterized primarily by morphological and architectural attributes of histological structures (glands and nuclei), have been found to be highly correlated with disease aggressiveness and patient outcome. Gleason patterns 4 and 5 are highly correlated with more aggressive disease and poorer patient outcome, while Gleason patterns 1-3 tend to reflect more favorable patient outcome. Because Gleason grading is done manually by a pathologist visually examining glass (or digital) slides subtle morphologic and architectural differences of histological attributes, in addition to other factors, may result in grading errors and hence cause high inter-observer variability. Recently some researchers have proposed computerized decision support systems to automatically grade Gleason patterns by using features pertaining to nuclear architecture, gland morphology, as well as tissue texture. Automated characterization of gland morphology has been shown to distinguish between intermediate Gleason patterns 3 and 4 with high accuracy. Manifold learning (ML) schemes attempt to generate a low dimensional manifold representation of a higher dimensional feature space while simultaneously preserving nonlinear relationships between object instances. Classification can then be performed in the low dimensional space with high accuracy. However ML is sensitive to the samples contained in the dataset; changes in the dataset may alter the manifold structure. In this paper we present a manifold regularization technique to constrain the low dimensional manifold to a specific range of possible manifold shapes, the range being determined via a statistical shape model of manifolds (SSMM). In this work we demonstrate applications of the SSMM in (1) identifying samples on the manifold which contain noise, defined as those samples which deviate from the SSMM, and (2) accurate out-of-sample extrapolation (OSE) of newly acquired samples onto a
Power Plant Water Intake Assessment.
ERIC Educational Resources Information Center
Zeitoun, Ibrahim H.; And Others
1980-01-01
In order to adequately assess the impact of power plant cooling water intake on an aquatic ecosystem, total ecosystem effects must be considered, rather than merely numbers of impinged or entrained organisms. (Author/RE)
Fiber Intake and Childhood Appendicitis.
ERIC Educational Resources Information Center
Brender, Jean D.; And Others
1985-01-01
Parents of 135 children with appendicitis and of 212 comparison children were interviewed about their children's diet. Results suggest that a liberal intake of whole-grain breads and cereals may decrease the risk of appendicitis during childhood. (KH)
The Geometric Median on Riemannian Manifolds with Application to Robust Atlas Estimation
Fletcher, P. Thomas; Venkatasubramanian, Suresh; Joshi, Sarang
2009-01-01
One of the primary goals of computational anatomy is the statistical analysis of anatomical variability in large populations of images. The study of anatomical shape is inherently related to the construction of transformations of the underlying coordinate space, which map one anatomy to another. It is now well established that representing the geometry of shapes or images in Euclidian spaces undermines our ability to represent natural variability in populations. In our previous work we have extended classical statistical analysis techniques, such as averaging, principal components analysis, and regression, to Riemannian manifolds, which are more appropriate representations for describing anatomical variability. In this paper we extend the notion of robust estimation, a well established and powerful tool in traditional statistical analysis of Euclidian data, to manifold-valued representations of anatomical variability. In particular, we extend the geometric median, a classic robust estimator of centrality for data in Euclidean spaces. We formulate the geometric median of data on a Riemannian manifold as the minimizer of the sum of geodesic distances to the data points. We prove existence and uniqueness of the geometric median on manifolds with non-positive sectional curvature and give sufficient conditions for uniqueness on positively curved manifolds. Generalizing the Weiszfeld procedure for finding the geometric median of Euclidean data, we present an algorithm for computing the geometric median on an arbitrary manifold. We show that this algorithm converges to the unique solution when it exists. In this paper we exemplify the robustness of the estimation technique by applying the procedure to various manifolds commonly used in the analysis of medical images. Using this approach, we also present a robust brain atlas estimation technique based on the geometric median in the space of deformable images. PMID:19056498
The geometric median on Riemannian manifolds with application to robust atlas estimation.
Fletcher, P Thomas; Venkatasubramanian, Suresh; Joshi, Sarang
2009-03-01
One of the primary goals of computational anatomy is the statistical analysis of anatomical variability in large populations of images. The study of anatomical shape is inherently related to the construction of transformations of the underlying coordinate space, which map one anatomy to another. It is now well established that representing the geometry of shapes or images in Euclidian spaces undermines our ability to represent natural variability in populations. In our previous work we have extended classical statistical analysis techniques, such as averaging, principal components analysis, and regression, to Riemannian manifolds, which are more appropriate representations for describing anatomical variability. In this paper we extend the notion of robust estimation, a well established and powerful tool in traditional statistical analysis of Euclidian data, to manifold-valued representations of anatomical variability. In particular, we extend the geometric median, a classic robust estimator of centrality for data in Euclidean spaces. We formulate the geometric median of data on a Riemannian manifold as the minimizer of the sum of geodesic distances to the data points. We prove existence and uniqueness of the geometric median on manifolds with non-positive sectional curvature and give sufficient conditions for uniqueness on positively curved manifolds. Generalizing the Weiszfeld procedure for finding the geometric median of Euclidean data, we present an algorithm for computing the geometric median on an arbitrary manifold. We show that this algorithm converges to the unique solution when it exists. In this paper we exemplify the robustness of the estimation technique by applying the procedure to various manifolds commonly used in the analysis of medical images. Using this approach, we also present a robust brain atlas estimation technique based on the geometric median in the space of deformable images.
Antioxidant Vitamin Intake and Mortality
Paganini-Hill, Annlia; Kawas, Claudia H.; Corrada, María M.
2015-01-01
To assess the relationship between antioxidant vitamin intake and all-cause mortality in older adults, we examined these associations using data from the Leisure World Cohort Study, a prospective study of residents of the Leisure World retirement community in Laguna Hills, California. In the early 1980s, participants (who were aged 44–101 years) completed a postal survey, which included details on use of vitamin supplements and dietary intake of foods containing vitamins A and C. Age-adjusted and multivariate-adjusted (for factors related to mortality in this cohort—smoking, alcohol intake, caffeine consumption, exercise, body mass index, and histories of hypertension, angina, heart attack, stroke, diabetes, rheumatoid arthritis, and cancer) hazard ratios for death were calculated using Cox regression for 8,640 women and 4,983 men (median age at entry, 74 years). During follow-up (1981–2013), 13,104 participants died (median age at death, 88 years). Neither dietary nor supplemental intake of vitamin A or vitamin C nor supplemental intake of vitamin E was significantly associated with mortality after multivariate adjustment. A compendium that summarizes previous findings of cohort studies evaluating vitamin intake and mortality is provided. Attenuation in the observed associations between mortality and antioxidant vitamin use after adjustment for confounders in our study and in previous studies suggests that such consumption identifies persons with other mortality-associated lifestyle and health risk factors. PMID:25550360
A High Elevation Aerosol Manifold Modeling Study and Inter-comparison
NASA Astrophysics Data System (ADS)
Hallar, A. G.; Mccubbin, I. B.; Novosselov, I.; Gorder, R.
2012-12-01
Via a National Science Foundation grant the Desert Research Institute required professional engineering services to design and model a new fluid dynamics aerosol sampling manifold system to be installed in the renovated Storm Peak Laboratory. The technical objectives include evaluation of the transmission efficiencies for particles with diameters from 3 nanometers to 20 micrometers in the aerosol manifold and to investigate the particulate dispersion and deposition in three different manifold designs currently used throughout the world. Information was collected pertaining to three highly regarded atmospheric aerosol manifolds. The following aerosol manifolds were considered as models: 1. DOE ASR design used throughout the world (e.g. Barrow, Alaska). 2. The aerosol manifold used at the Swiss high elevation site, Jungfraujoch, located at 3.5 km. 3. Current Storm Peak Laboratory aerosol manifold. Based on all available information, DRI assimilated 3-D CAD drawings of these three manifolds. Enertechnix, Inc (http://www.enertechnix.com) was identified by DRI as having the appropriate skills and expertise to perform the Computational Fluid Dynamic (CFD) modeling required for this project. Enertechnix Inc. has completed initial CFD modeling of the three manifold discussed above. The following results will be presented. Transient CFD simulations of the inlets were performed for the wind speed range of 2.5-15 m/s in 3-dimentional numerical wind tunnel at a sampling rate of 1000 lmp. The transmission efficiencies for these inlets were evaluated for particles in 10 nm-20um range. Two different turbulence models (k-epsilon and detached eddy simulations) were used, and the effects of particle - turbulence coupling were examined. The modeling results show that for all three inlets transmission decreases with increase of particle size, due to particle inertial impaction on the inner walls of the inlets. Additionally, the transmission efficiency decreases at higher wind speeds
Dimensionality Reduction on SPD Manifolds: The Emergence of Geometry-Aware Methods.
Harandi, Mehrtash; Salzmann, Mathieu; Hartley, Richard
2017-01-18
Representing images and videos with Symmetric Positive Definite (SPD) matrices, and considering the Riemannian geometry of the resulting space, has been shown to yield high discriminative power in many visual recognition tasks. Unfortunately, computation on the Riemannian manifold of SPD matrices -especially of high-dimensional ones- comes at a high cost that limits the applicability of existing techniques. In this paper, we introduce algorithms able to handle high-dimensional SPD matrices by constructing a lower-dimensional SPD manifold. To this end, we propose to model the mapping from the high-dimensional SPD manifold to the low-dimensional one with an orthonormal projection. This lets us formulate dimensionality reduction as the problem of finding a projection that yields a low-dimensional manifold either with maximum discriminative power in the supervised scenario, or with maximum variance of the data in the unsupervised one. We show that learning can be expressed as an optimization problem on a Grassmann manifold and discuss fast solutions for special cases. Our evaluation on several classification tasks evidences that our approach leads to a significant accuracy gain over state-of-the-art methods.
Gifani, Parisa; Behnam, Hamid; Shalbaf, Ahmad; Sani, Zahra Alizadeh
2010-09-01
The automatic detection of end-diastole and end-systole frames of echocardiography images is the first step for calculation of the ejection fraction, stroke volume and some other features related to heart motion abnormalities. In this paper, the manifold learning algorithm is applied on 2D echocardiography images to find out the relationship between the frames of one cycle of heart motion. By this approach the nonlinear embedded information in sequential images is represented in a two-dimensional manifold by the LLE algorithm and each image is depicted by a point on reconstructed manifold. There are three dense regions on the manifold which correspond to the three phases of cardiac cycle ('isovolumetric contraction', 'isovolumetric relaxation', 'reduced filling'), wherein there is no prominent change in ventricular volume. By the fact that the end-systolic and end-diastolic frames are in isovolumic phases of the cardiac cycle, the dense regions can be used to find these frames. By calculating the distance between consecutive points in the manifold, the isovolumic frames are mapped on the three minimums of the distance diagrams which were used to select the corresponding images. The minimum correlation between these images leads to detection of end-systole and end-diastole frames. The results on six healthy volunteers have been validated by an experienced echo cardiologist and depict the usefulness of the presented method.
Manifold regularized multitask learning for semi-supervised multilabel image classification.
Luo, Yong; Tao, Dacheng; Geng, Bo; Xu, Chao; Maybank, Stephen J
2013-02-01
It is a significant challenge to classify images with multiple labels by using only a small number of labeled samples. One option is to learn a binary classifier for each label and use manifold regularization to improve the classification performance by exploring the underlying geometric structure of the data distribution. However, such an approach does not perform well in practice when images from multiple concepts are represented by high-dimensional visual features. Thus, manifold regularization is insufficient to control the model complexity. In this paper, we propose a manifold regularized multitask learning (MRMTL) algorithm. MRMTL learns a discriminative subspace shared by multiple classification tasks by exploiting the common structure of these tasks. It effectively controls the model complexity because different tasks limit one another's search volume, and the manifold regularization ensures that the functions in the shared hypothesis space are smooth along the data manifold. We conduct extensive experiments, on the PASCAL VOC'07 dataset with 20 classes and the MIR dataset with 38 classes, by comparing MRMTL with popular image classification algorithms. The results suggest that MRMTL is effective for image classification.
Enhanced low-rank representation via sparse manifold adaption for semi-supervised learning.
Peng, Yong; Lu, Bao-Liang; Wang, Suhang
2015-05-01
Constructing an informative and discriminative graph plays an important role in various pattern recognition tasks such as clustering and classification. Among the existing graph-based learning models, low-rank representation (LRR) is a very competitive one, which has been extensively employed in spectral clustering and semi-supervised learning (SSL). In SSL, the graph is composed of both labeled and unlabeled samples, where the edge weights are calculated based on the LRR coefficients. However, most of existing LRR related approaches fail to consider the geometrical structure of data, which has been shown beneficial for discriminative tasks. In this paper, we propose an enhanced LRR via sparse manifold adaption, termed manifold low-rank representation (MLRR), to learn low-rank data representation. MLRR can explicitly take the data local manifold structure into consideration, which can be identified by the geometric sparsity idea; specifically, the local tangent space of each data point was sought by solving a sparse representation objective. Therefore, the graph to depict the relationship of data points can be built once the manifold information is obtained. We incorporate a regularizer into LRR to make the learned coefficients preserve the geometric constraints revealed in the data space. As a result, MLRR combines both the global information emphasized by low-rank property and the local information emphasized by the identified manifold structure. Extensive experimental results on semi-supervised classification tasks demonstrate that MLRR is an excellent method in comparison with several state-of-the-art graph construction approaches.
Butail, Sachit; Bollt, Erik M; Porfiri, Maurizio
2013-11-07
In this paper, we build a framework for the analysis and classification of collective behavior using methods from generative modeling and nonlinear manifold learning. We represent an animal group with a set of finite-sized particles and vary known features of the group structure and motion via a class of generative models to position each particle on a two-dimensional plane. Particle positions are then mapped onto training images that are processed to emphasize the features of interest and match attainable far-field videos of real animal groups. The training images serve as templates of recognizable patterns of collective behavior and are compactly represented in a low-dimensional space called embedding manifold. Two mappings from the manifold are derived: the manifold-to-image mapping serves to reconstruct new and unseen images of the group and the manifold-to-feature mapping allows frame-by-frame classification of raw video. We validate the combined framework on datasets of growing level of complexity. Specifically, we classify artificial images from the generative model, interacting self-propelled particle model, and raw overhead videos of schooling fish obtained from the literature.
A framework for optimal kernel-based manifold embedding of medical image data.
Zimmer, Veronika A; Lekadir, Karim; Hoogendoorn, Corné; Frangi, Alejandro F; Piella, Gemma
2015-04-01
Kernel-based dimensionality reduction is a widely used technique in medical image analysis. To fully unravel the underlying nonlinear manifold the selection of an adequate kernel function and of its free parameters is critical. In practice, however, the kernel function is generally chosen as Gaussian or polynomial and such standard kernels might not always be optimal for a given image dataset or application. In this paper, we present a study on the effect of the kernel functions in nonlinear manifold embedding of medical image data. To this end, we first carry out a literature review on existing advanced kernels developed in the statistics, machine learning, and signal processing communities. In addition, we implement kernel-based formulations of well-known nonlinear dimensional reduction techniques such as Isomap and Locally Linear Embedding, thus obtaining a unified framework for manifold embedding using kernels. Subsequently, we present a method to automatically choose a kernel function and its associated parameters from a pool of kernel candidates, with the aim to generate the most optimal manifold embeddings. Furthermore, we show how the calculated selection measures can be extended to take into account the spatial relationships in images, or used to combine several kernels to further improve the embedding results. Experiments are then carried out on various synthetic and phantom datasets for numerical assessment of the methods. Furthermore, the workflow is applied to real data that include brain manifolds and multispectral images to demonstrate the importance of the kernel selection in the analysis of high-dimensional medical images.
Dimensionality reduction of hyperspectral images based on sparse discriminant manifold embedding
NASA Astrophysics Data System (ADS)
Huang, Hong; Luo, Fulin; Liu, Jiamin; Yang, Yaqiong
2015-08-01
Sparse manifold clustering and embedding (SMCE) adaptively selects neighbor points from the same manifold and approximately spans a low-dimensional affine subspace, but it does not explicitly give a projection matrix and encounters the out-of-sample problem. To overcome this drawback, we propose a new dimensionality reduction method, called sparse manifold embedding (SME), based on graph embedding and sparse representation for hyperspectral image (HSI). It utilizes the sparse coefficients of affine subspace to construct a similarity graph and preserves this sparse similarity in embedding space. Furthermore, we try to make full use of the prior label information to design a novel supervised learning method termed sparse discriminant manifold embedding (SDME). SDME not only inherits the merits of the sparsity property of affine subspace but also boosts the compactness of intra-manifold, which achieves discriminating features and further improves the classification performance of HSI. Experiments on two real hyperspectral data sets (Indian Pines and PaviaU) show the benefits of the proposed SME and SDME methods.
Parts-based stereoscopic image assessment by learning binocular manifold color visual properties
NASA Astrophysics Data System (ADS)
Xu, Haiyong; Yu, Mei; Luo, Ting; Zhang, Yun; Jiang, Gangyi
2016-11-01
Existing stereoscopic image quality assessment (SIQA) methods are mostly based on the luminance information, in which color information is not sufficiently considered. Actually, color is part of the important factors that affect human visual perception, and nonnegative matrix factorization (NMF) and manifold learning are in line with human visual perception. We propose an SIQA method based on learning binocular manifold color visual properties. To be more specific, in the training phase, a feature detector is created based on NMF with manifold regularization by considering color information, which not only allows parts-based manifold representation of an image, but also manifests localized color visual properties. In the quality estimation phase, visually important regions are selected by considering different human visual attention, and feature vectors are extracted by using the feature detector. Then the feature similarity index is calculated and the parts-based manifold color feature energy (PMCFE) for each view is defined based on the color feature vectors. The final quality score is obtained by considering a binocular combination based on PMCFE. The experimental results on LIVE I and LIVE Π 3-D IQA databases demonstrate that the proposed method can achieve much higher consistency with subjective evaluations than the state-of-the-art SIQA methods.
Out-of-Sample Generalizations for Supervised Manifold Learning for Classification.
Vural, Elif; Guillemot, Christine
2016-03-01
Supervised manifold learning methods for data classification map high-dimensional data samples to a lower dimensional domain in a structure-preserving way while increasing the separation between different classes. Most manifold learning methods compute the embedding only of the initially available data; however, the generalization of the embedding to novel points, i.e., the out-of-sample extension problem, becomes especially important in classification applications. In this paper, we propose a semi-supervised method for building an interpolation function that provides an out-of-sample extension for general supervised manifold learning algorithms studied in the context of classification. The proposed algorithm computes a radial basis function interpolator that minimizes an objective function consisting of the total embedding error of unlabeled test samples, defined as their distance to the embeddings of the manifolds of their own class, as well as a regularization term that controls the smoothness of the interpolation function in a direction-dependent way. The class labels of test data and the interpolation function parameters are estimated jointly with an iterative process. Experimental results on face and object images demonstrate the potential of the proposed out-of-sample extension algorithm for the classification of manifold-modeled data sets.
Access to Mars from Earth-Moon Libration Point Orbits:. [Manifold and Direct Options
NASA Technical Reports Server (NTRS)
Kakoi, Masaki; Howell, Kathleen C.; Folta, David
2014-01-01
This investigation is focused specifically on transfers from Earth-Moon L(sub 1)/L(sub 2) libration point orbits to Mars. Initially, the analysis is based in the circular restricted three-body problem to utilize the framework of the invariant manifolds. Various departure scenarios are compared, including arcs that leverage manifolds associated with the Sun-Earth L(sub 2) orbits as well as non-manifold trajectories. For the manifold options, ballistic transfers from Earth-Moon L(sub 2) libration point orbits to Sun-Earth L(sub 1)/L(sub 2) halo orbits are first computed. This autonomous procedure applies to both departure and arrival between the Earth-Moon and Sun-Earth systems. Departure times in the lunar cycle, amplitudes and types of libration point orbits, manifold selection, and the orientation/location of the surface of section all contribute to produce a variety of options. As the destination planet, the ephemeris position for Mars is employed throughout the analysis. The complete transfer is transitioned to the ephemeris model after the initial design phase. Results for multiple departure/arrival scenarios are compared.
An ordered-patch-based image classification approach on the image Grassmannian manifold.
Xu, Chunyan; Wang, Tianjiang; Gao, Junbin; Cao, Shougang; Tao, Wenbing; Liu, Fang
2014-04-01
This paper presents an ordered-patch-based image classification framework integrating the image Grassmannian manifold to address handwritten digit recognition, face recognition, and scene recognition problems. Typical image classification methods explore image appearances without considering the spatial causality among distinctive domains in an image. To address the issue, we introduce an ordered-patch-based image representation and use the autoregressive moving average (ARMA) model to characterize the representation. First, each image is encoded as a sequence of ordered patches, integrating both the local appearance information and spatial relationships of the image. Second, the sequence of these ordered patches is described by an ARMA model, which can be further identified as a point on the image Grassmannian manifold. Then, image classification can be conducted on such a manifold under this manifold representation. Furthermore, an appropriate Grassmannian kernel for support vector machine classification is developed based on a distance metric of the image Grassmannian manifold. Finally, the experiments are conducted on several image data sets to demonstrate that the proposed algorithm outperforms other existing image classification methods.
On a holomorphic Lefschetz formula in strictly pseudoconvex subdomains of complex manifolds
Kytmanov, A M; Myslivets, S G; Tarkhanov, N N
2004-12-31
The classical Lefschetz formula expresses the number of fixed points of a continuous map f:M{yields}M in terms of the transformation induced by f on the cohomology of M. In 1966, Atiyah and Bott extended this formula to elliptic complexes over a compact closed manifold. In particular, they obtained a holomorphic Lefschetz formula on compact complex manifolds without boundary. Brenner and Shubin (1981, 1991) extended the Atiyah-Bott theory to compact manifolds with boundary. On compact complex manifolds with boundary the Dolbeault complex is not elliptic, therefore the Atiyah-Bott theory is not applicable. Bypassing difficulties related to the boundary behaviour of Dolbeault cohomology, Donnelly and Fefferman (1986) obtained a formula for the number of fixed points in terms of the Bergman metric. The aim of this paper is to obtain a Lefschetz formula on relatively compact strictly pseudoconvex subdomains of complex manifolds X with smooth boundary, that is, to find the total Lefschetz number for a holomorphic endomorphism f{sup *} of the Dolbeault complex and to express it in terms of local invariants of the fixed points of f.
Legendre submanifolds in contact manifolds as attractors and geometric nonequilibrium thermodynamics
Goto, Shin-itiro
2015-07-15
It has been proposed that equilibrium thermodynamics is described on Legendre submanifolds in contact geometry. It is shown in this paper that Legendre submanifolds embedded in a contact manifold can be expressed as attractors in phase space for a certain class of contact Hamiltonian vector fields. By giving a physical interpretation that points outside the Legendre submanifold can represent nonequilibrium states of thermodynamic variables, in addition to that points of a given Legendre submanifold can represent equilibrium states of the variables, this class of contact Hamiltonian vector fields is physically interpreted as a class of relaxation processes, in which thermodynamic variables achieve an equilibrium state from a nonequilibrium state through a time evolution, a typical nonequilibrium phenomenon. Geometric properties of such vector fields on contact manifolds are characterized after introducing a metric tensor field on a contact manifold. It is also shown that a contact manifold and a strictly convex function induce a lower dimensional dually flat space used in information geometry where a geometrization of equilibrium statistical mechanics is constructed. Legendre duality on contact manifolds is explicitly stated throughout.
Preliminary Study of Geosynchronous Orbit Transfers from LEO using Invariant Manifolds
NASA Astrophysics Data System (ADS)
Davis, Kathryn E.; Anderson, Rodney L.; Born, George H.
2011-07-01
The invariant manifolds of libration point orbits (LPOs) in the Sun-Earth/Moon system are used to construct low-energy transfers from Low Earth Orbits (LEOs) to geosynchronous orbits. A maneuver is performed in LEO to insert onto a stable manifold trajectory of an LPO. The spacecraft travels to the host LPO and then follows an unstable manifold trajectory back to a geosynchronous orbit, where an orbit insertion maneuver is performed. The gravitational effects of the Sun-Earth/Moon three-body system act in such a way that large plane changes between the initial and final orbits at Earth may be realized without the execution of any plane change maneuvers. The maneuver costs of the transfers that employ invariant manifolds are compared to those using traditional techniques. The transfers that employ manifold trajectories can lower the cost of traditional Hohmann transfers by up to 3.15 km/s for transfers involving large differences in initial and final inclinations. The decrease in fuel expenditure is accompanied by an increase in time of flight; transfer durations are slightly over one year.
EPA's air research provides the critical science to develop and implement outdoor air regulations under the Clean Air Act and puts new tools and information in the hands of air quality managers and regulators to protect the air we breathe.
Thin-Film Air-Mass-Flow Sensor of Improved Design Developed
NASA Technical Reports Server (NTRS)
Fralick, Gustave C.; Wrbanek, John D.; Hwang, Danny P.
2003-01-01
used to provide accurate information about the amount of air entering the engine so that the amount of fuel can be adjusted to give the most efficient combustion. The ideal mass-flow sensor would be a rugged design that minimizes the disturbance to the flow stream and provides an accurate reading of both smooth and turbulent flows; NASA's design satisfies these requirements better than any existing design. Most of the mass-flow sensors used today are the hot wire variety. Hot wires can be fragile and cannot accurately measure a turbulent or reversing flow, which is often encountered in an intake manifold. Other types of mass-flow sensors include pitot tubes, vane anemometers, and thermocouple rakes-all of which suffer from some type of performance problem. Because it solves these performance problems while maintaining a simple design that lends itself to low-cost manufacturing techniques, NASA s thin-film resistance temperature detector air-mass-flow sensor should lead to more widespread use of mass-flow sensors.