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Gradient Sro
Gradient sro is a Czech aircraft manufacturer based in Prague and founded in 1997. The company specializes in the design and manufacture of paragliders in the form of ready-to-fly aircraft.Bertrand, Noel; Rene Coulon; et al: ''World Directory of Leisure Aviation 2003-04'', page 19. Pagefast Ltd, Lancaster UK, 2003. The company is organized as a společnost s ručením omezeným (sro), a Czech private limited company. The company has produced a wide range of paragliders, including the intermediate sport Aspen, the Avax competition wing, the two-place tandem BiOnyx, the intermediate performance Bliss, the beginner and flight training Bright and the intermediate Golden The company has ceased publishing performance specifications for its gliders, stating: Aircraft Summary of aircraft built by Gradient: * Gradient Agility * Gradient Aspen * Gradient Avax * Gradient BiGolden * Gradient BiOnyx * Gradient Bliss *Gradient Bright The Gradient Bright is a Czech single-place, p ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Privately Held Company
A privately held company (or simply a private company) is a company whose shares and related rights or obligations are not offered for public subscription or publicly negotiated in the respective listed markets, but rather the company's stock is offered, owned, traded, exchanged privately, or Over-the-counter (finance), over-the-counter. In the case of a closed corporation, there are a relatively small number of shareholders or company members. Related terms are closely-held corporation, unquoted company, and unlisted company. Though less visible than their public company, publicly traded counterparts, private companies have major importance in the world's economy. In 2008, the 441 list of largest private non-governmental companies by revenue, largest private companies in the United States accounted for ($1.8 trillion) in revenues and employed 6.2 million people, according to ''Forbes''. In 2005, using a substantially smaller pool size (22.7%) for comparison, the 339 companies on ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gradient Golden
The Gradient Golden is a Czech single-place, paraglider designed and produced by Gradient sro of Prague. Originally produced in the mid-2000s, it was still in production in 2016 as the Golden 4.Bertrand, Noel; Rene Coulon; et al: ''World Directory of Leisure Aviation 2003-04'', page 19. Pagefast Ltd, Lancaster OK, 2003. ISSN 1368-485X Design and development The Golden was designed as an intermediate glider and is the manufacturer's best selling model. The models are each named for their approximate wing area in square metres. The Golden 4 is made from Porcher Marine Everlast fabric. Variants ;Golden 24 :Small-sized model for lighter pilots. Its span wing has a wing area of , 42 cells and the aspect ratio is 5.3:1. The pilot weight range is . The glider model is DHV 1-2 certified. ;Golden 26 :Mid-sized model for medium-weight pilots. Its span wing has a wing area of , 42 cells and the aspect ratio is 5.3:1. The pilot weight range is . The glider model is DHV 1-2 certified. ;Go ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Paragliders
Paragliding is the recreational and competitive adventure sport of flying paragliders: lightweight, free-flying, foot-launched Glider (aircraft), glider aircraft with no rigid primary structure. The pilot sits in a :wikt:harness, harness or lies supine in a cocoon-like 'pod' suspended below a fabric wing. Wing shape is maintained by the suspension lines, the pressure of air entering vents in the front of the wing, and the aerodynamic forces of the air flowing over the outside. Despite not using an engine, paraglider flights can last many hours and cover many hundreds of kilometres, though flights of one to two hours and covering some tens of kilometres are more the norm. By skillful exploitation of sources of lift (soaring), lift, the pilot may gain height, often climbing to altitudes of a few thousand metres. History In 1966, Canadian Domina Jalbert was granted a patent for a ''multi-cell wing type aerial device—''"a wing having a flexible canopy constituting an upper s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Aircraft Manufacturers Of The Czech Republic And Czechoslovakia
An aircraft is a vehicle that is able to fly by gaining support from the air. It counters the force of gravity by using either static lift or by using the dynamic lift of an airfoil, or in a few cases the downward thrust from jet engines. Common examples of aircraft include airplanes, helicopters, airships (including blimps), gliders, paramotors, and hot air balloons. The human activity that surrounds aircraft is called ''aviation''. The science of aviation, including designing and building aircraft, is called ''aeronautics.'' Crewed aircraft are flown by an onboard pilot, but unmanned aerial vehicles may be remotely controlled or self-controlled by onboard computers. Aircraft may be classified by different criteria, such as lift type, aircraft propulsion, usage and others. History Flying model craft and stories of manned flight go back many centuries; however, the first manned ascent — and safe descent — in modern times took place by larger hot-air ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gradient Nevada
In vector calculus, the gradient of a scalar-valued differentiable function of several variables is the vector field (or vector-valued function) \nabla f whose value at a point p is the "direction and rate of fastest increase". If the gradient of a function is non-zero at a point , the direction of the gradient is the direction in which the function increases most quickly from , and the magnitude of the gradient is the rate of increase in that direction, the greatest absolute directional derivative. Further, a point where the gradient is the zero vector is known as a stationary point. The gradient thus plays a fundamental role in optimization theory, where it is used to maximize a function by gradient ascent. In coordinate-free terms, the gradient of a function f(\bf) may be defined by: :df=\nabla f \cdot d\bf where ''df'' is the total infinitesimal change in ''f'' for an infinitesimal displacement d\bf, and is seen to be maximal when d\bf is in the direction of the gradie ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gradient Montana
In vector calculus, the gradient of a scalar-valued differentiable function of several variables is the vector field (or vector-valued function) \nabla f whose value at a point p is the "direction and rate of fastest increase". If the gradient of a function is non-zero at a point , the direction of the gradient is the direction in which the function increases most quickly from , and the magnitude of the gradient is the rate of increase in that direction, the greatest absolute directional derivative. Further, a point where the gradient is the zero vector is known as a stationary point. The gradient thus plays a fundamental role in optimization theory, where it is used to maximize a function by gradient ascent. In coordinate-free terms, the gradient of a function f(\bf) may be defined by: :df=\nabla f \cdot d\bf where ''df'' is the total infinitesimal change in ''f'' for an infinitesimal displacement d\bf, and is seen to be maximal when d\bf is in the direction of the gradie ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gradient Freestyle
In vector calculus, the gradient of a scalar-valued differentiable function of several variables is the vector field (or vector-valued function) \nabla f whose value at a point p is the "direction and rate of fastest increase". If the gradient of a function is non-zero at a point , the direction of the gradient is the direction in which the function increases most quickly from , and the magnitude of the gradient is the rate of increase in that direction, the greatest absolute directional derivative. Further, a point where the gradient is the zero vector is known as a stationary point. The gradient thus plays a fundamental role in optimization theory, where it is used to maximize a function by gradient ascent. In coordinate-free terms, the gradient of a function f(\bf) may be defined by: :df=\nabla f \cdot d\bf where ''df'' is the total infinitesimal change in ''f'' for an infinitesimal displacement d\bf, and is seen to be maximal when d\bf is in the direction of the gradie ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gradient Eiger
In vector calculus, the gradient of a scalar-valued differentiable function of several variables is the vector field (or vector-valued function) \nabla f whose value at a point p is the "direction and rate of fastest increase". If the gradient of a function is non-zero at a point , the direction of the gradient is the direction in which the function increases most quickly from , and the magnitude of the gradient is the rate of increase in that direction, the greatest absolute directional derivative. Further, a point where the gradient is the zero vector is known as a stationary point. The gradient thus plays a fundamental role in optimization theory, where it is used to maximize a function by gradient ascent. In coordinate-free terms, the gradient of a function f(\bf) may be defined by: :df=\nabla f \cdot d\bf where ''df'' is the total infinitesimal change in ''f'' for an infinitesimal displacement d\bf, and is seen to be maximal when d\bf is in the direction of the gradie ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gradient Denali
In vector calculus, the gradient of a scalar-valued differentiable function of several variables is the vector field (or vector-valued function) \nabla f whose value at a point p is the "direction and rate of fastest increase". If the gradient of a function is non-zero at a point , the direction of the gradient is the direction in which the function increases most quickly from , and the magnitude of the gradient is the rate of increase in that direction, the greatest absolute directional derivative. Further, a point where the gradient is the zero vector is known as a stationary point. The gradient thus plays a fundamental role in optimization theory, where it is used to maximize a function by gradient ascent. In coordinate-free terms, the gradient of a function f(\bf) may be defined by: :df=\nabla f \cdot d\bf where ''df'' is the total infinitesimal change in ''f'' for an infinitesimal displacement d\bf, and is seen to be maximal when d\bf is in the direction of the gradie ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gradient Delite
In vector calculus, the gradient of a scalar-valued differentiable function of several variables is the vector field (or vector-valued function) \nabla f whose value at a point p is the "direction and rate of fastest increase". If the gradient of a function is non-zero at a point , the direction of the gradient is the direction in which the function increases most quickly from , and the magnitude of the gradient is the rate of increase in that direction, the greatest absolute directional derivative. Further, a point where the gradient is the zero vector is known as a stationary point. The gradient thus plays a fundamental role in optimization theory, where it is used to maximize a function by gradient ascent. In coordinate-free terms, the gradient of a function f(\bf) may be defined by: :df=\nabla f \cdot d\bf where ''df'' is the total infinitesimal change in ''f'' for an infinitesimal displacement d\bf, and is seen to be maximal when d\bf is in the direction of the gradie ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gradient BiGolden
In vector calculus, the gradient of a scalar-valued differentiable function of several variables is the vector field (or vector-valued function) \nabla f whose value at a point p is the "direction and rate of fastest increase". If the gradient of a function is non-zero at a point , the direction of the gradient is the direction in which the function increases most quickly from , and the magnitude of the gradient is the rate of increase in that direction, the greatest absolute directional derivative. Further, a point where the gradient is the zero vector is known as a stationary point. The gradient thus plays a fundamental role in optimization theory, where it is used to maximize a function by gradient ascent. In coordinate-free terms, the gradient of a function f(\bf) may be defined by: :df=\nabla f \cdot d\bf where ''df'' is the total infinitesimal change in ''f'' for an infinitesimal displacement d\bf, and is seen to be maximal when d\bf is in the direction of the gradie ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gradient Agility
In vector calculus, the gradient of a scalar-valued differentiable function of several variables is the vector field (or vector-valued function) \nabla f whose value at a point p is the "direction and rate of fastest increase". If the gradient of a function is non-zero at a point , the direction of the gradient is the direction in which the function increases most quickly from , and the magnitude of the gradient is the rate of increase in that direction, the greatest absolute directional derivative. Further, a point where the gradient is the zero vector is known as a stationary point. The gradient thus plays a fundamental role in optimization theory, where it is used to maximize a function by gradient ascent. In coordinate-free terms, the gradient of a function f(\bf) may be defined by: :df=\nabla f \cdot d\bf where ''df'' is the total infinitesimal change in ''f'' for an infinitesimal displacement d\bf, and is seen to be maximal when d\bf is in the direction of the gradie ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
