Rotation Problem Research Articles

Rotation of Galaxies within Gravity of the Universe

Rotation of galaxies is examined by the general principle of least action. This law of nature describes a system in its surroundings, here specifically a galaxy in the surrounding Universe. According to this holistic theory the gravitational potential due to all matter in the expanding Universe relates to the universal curvature which, in turn, manifests itself as the universal acceleration. Then the orbital velocities from the central bulge to distant perimeters are understood to balance both the galactic and universal acceleration. Since the galactic acceleration decreases with distance from the galaxy’s center to its luminous edge, the orbital velocities of ever more distant stars and gas clouds tend toward a value that tallies the universal acceleration. This tiny term has been acknowledged earlier by including it as a parameter in the modified gravitational law, but here the tiny acceleration is understood to result from the gravitational potential that spans across the expanding Universe. This resolution of the galaxy rotation problem is compared with observations and contrasted with models of dark matter. Also, other astronomical observations that have been interpreted as evidence for dark matter are discussed in light of the least-action principle.

Вещественная задача о вращении несимметричного твердого тела относительно неподвижной точки

The version problem of an asymmetrical solid body rotation relatively fixed center of inertia – pole described by autonomous system of the material differential equations is considered and constructive aspects solutions of a sought for nonrelativistic problem with the fixed moments of inertia are proposed.

Recent methods in vision-based hand gesture recognition

The goal of static hand gesture recognition is to classify the given hand gesture data represented by some features into some predefined finite number of gesture classes. The main objective of this effort is to explore the utility of two feature extraction methods, namely, hand contour and complex moments to solve the hand gesture recognition problem by identifying the primary advantages and disadvantages of each method. Artificial neural network is built for the purpose of classification by using the back-propagation learning algorithm. The proposed system presents a recognition algorithm to recognize a set of six specific static hand gestures, namely: Open, Close, Cut, Paste, Maximize, and Minimize. The hand gesture image is passed through three stages, namely, pre-processing, feature extraction, and classification. In the pre-processing stage, some operations are applied to extract the hand gesture from its background and prepare the hand gesture image for the feature extraction stage. In the first method, the hand contour is used as a feature which treats scaling and translation problems (in some cases). The complex moments algorithm is, however, used to describe the hand gesture and treat the rotation problem in addition to the scaling and translation. The back-propagation learning algorithm is employed in the multi-layer neural network classifier. The results show that hand contour method has a performance of (71.30 %) recognition, while complex moments have a better performance of (86.90 %) recognition rate.

Capture into resonance and phase-space dynamics in an optical centrifuge

The process of capture of a molecular ensemble into rotational resonance in the optical centrifuge is investigated. The adiabaticity and phase-space incompressibility are used to find the resonant capture probability in terms of two dimensionless parameters ${P}_{1,2}$ characterizing the driving strength and the nonlinearity, and related to three characteristic time scales in the problem. The analysis is based on the transformation to action-angle variables and the single resonance approximation, yielding reduction of the three-dimensional rotation problem to one degree of freedom. The analytic results for capture probability are in good agreement with simulations. The existing experiments satisfy the validity conditions of the theory.

On the Existence for the Free Interface 2D Euler Equation with a Localized Vorticity Condition

We prove a local-in-time existence of solutions result for the two dimensional incompressible Euler equations with a moving boundary, with no surface tension, under the Rayleigh---Taylor stability condition. The main feature of the result is a local regularity assumption on the initial vorticity, namely $$H^{1.5+\delta }$$H1.5+� Sobolev regularity in the vicinity of the moving interface in addition to the global regularity assumption on the initial fluid velocity in the $$H^{2+\delta }$$H2+� space. We use a special change of variables and derive a priori estimates, establishing the local-in-time existence in $$H^{2+\delta }$$H2+�. The assumptions on the initial data constitute the minimal set of assumptions for the existence of solutions to the rotational flow problem to be established in 2D.

Dynamic modelling and experimental validation of small-size wind turbine using flexible multibody approach

The wind energy is observed as an essential and powerful energy resource for the socio-economic development. It is proposed that the small-size wind turbines can demonstrate the innovative solution for the wind energy conversion for low speed regions. An innovative design, control, and monitoring processes require accurate and validated dynamic model of such turbines. In this investigation, the flexible multibody dynamics approach is used to extend the traditional method of dynamic modeling of small-size wind turbines. A systematic approach is developed based on floating frame of reference formulation (FFR) that includes the dynamics of the flexible blades as well as the aerodynamic loads. Beam element is used to model the blade structure with variable twist angle. In order to counteract the effect of the geometric stiffening, which comes due to high speed rotations, the coupling terms in the expression of axial strain energy are taken into account. In the other hand, the circulation theory is used to calculate the pressure coefficient difference along the blade, and the generalized aerodynamic forces are established. An experimental test-rig equipped with wind generator is used for the FFR model validation. The equipment gives a maximum discharge flow of 10 (m/s) in a 500 (mm) diameter duct. The dynamic effect of the twist angle of 30 (cm) diameter of rotor blades is studied based on the measured rotor speed of the wind turbine. The comparison of experimental results and numerical solution shows a very good agreement and consequently the wind turbine model obtained is suitable for stress analysis, structural and control design. It is concluded that the FFR formulation is best suited for large rotation and small deformation problems, which coincide with the operational conditions of small-size wind energy systems.

An ear biometric system based on artificial bees and the scale invariant feature transform

Ear recognition is a new biometric technology that competes with well-known biometric modalities such as fingerprint, face and iris. However, this modality suffers from common image acquisition problems, such as change in illumination, poor contrast, noise and pose variation. Using a 3D ear models reduce rotation, scale variation and translation-related problems, but they are computationally expensive. This paper presents a new architecture of ear biometrics that aims at solving the acquisition problems of 2D ear images. The proposed system uses a new ear image contrast enhancement approach based on the gray-level mapping technique, and uses an artificial bee colony (ABC) algorithm as an optimizer. This technique permits getting better-contrasted 2D ear images. In the feature extraction stage, the scale invariant feature transform (SIFT) is used. For the matching phase, the Euclidean distance is adopted. The proposed approach was tested on three reference ear image databases: IIT Delhi, USTB 1 and USTB 2, and compared with traditional ear image contrast enhancement approaches, histogram equalization (HE) and contrast limited adaptive histogram equalization (CLAHE). The obtained results show that the proposed approach outperforms traditional ear image contrast enhancement techniques, and increases the amount of detail in the ear image, and consequently improves the recognition rate.

S–R decomposition based numerical manifold method

The numerical manifold method (NMM) surmounting the mesh dependence has successfully solved very complicated problems involving small deformation and large movement, but had few applications to large deformation and large rotation problems because the false volume expansion and other issues exist. In this study it is shown that the false volume expansion in NMM can be excellently resolved by using the S–R (strain–rotation) decomposition theorem which can precisely reflect complex physical behaviors occurring in the process of large rotation and large deformation. The numerical methods based on the S–R decomposition theorem have been limited to the static analysis of large deformations. To remove this limitation, a new formulation taking into account dynamical features is proposed based on the weak form of momentum conservation law. Under the framework of NMM, the generalized-α method is employed to discretize the temporal variables. The updates of variables are described using the updated co-moving coordinate system. Thus, a new method named S–R-D-based NMM is established. The new formulation can be implemented in any other partition of unity based methods as well, so as to improve the performances of such methods in the analysis of dynamic large deformations.

Informational model of mental rotation of figures

Subject of Study.The subject of research is the information structure of objects internal representations and operations over them, used by man to solve the problem of mental rotation of figures. To analyze this informational structure we considered not only classical dependencies of the correct answers on the angle of rotation, but also the other dependencies obtained recently in cognitive psychology. Method.The language of technical computing Matlab R2010b was used for developing information model of the mental rotation of figures. Such model parameters as the number of bits in the internal representation, an error probability in a single bit, discrete rotation angle, comparison threshold, and the degree of difference during rotation can be changed. Main Results.The model reproduces qualitatively such psychological dependencies as the linear increase of time of correct answers and the number of errors on the angle of rotation for identical figures, "flat" dependence of the time of correct answers and the number of errors on the angle of rotation for mirror-like figures. The simulation results suggest that mental rotation is an iterative process of finding a match between the two figures, each step of which can lead to a significant distortion of the internal representation of the stored objects. Matching is carried out within the internal representations that have no high invariance to rotation angle. Practical Significance.The results may be useful for understanding the role of learning (including the learning with a teacher) in the development of effective information representation and operations on them in artificial intelligence systems.

Bayesian analysis of static and dynamic factor models: An ex-post approach towards the rotation problem

Due to their indeterminacies, static and dynamic factor models require identifying assumptions to guarantee uniqueness of the parameter estimator. The indeterminacy of the parameter estimator with respect to an orthogonal transformation is known as the rotation problem. The typical strategy in Bayesian factor analysis to solve the rotation problem is to introduce ex-ante constraints on certain model parameters via degenerate and truncated prior distributions. This strategy, however, results in posterior distributions whose shapes depend on the ordering of the variables in the data set. We propose an alternative approach where the rotation problem is solved ex-post using Procrustean postprocessing. The resulting order invariance of the posterior estimator is illustrated in a simulation study and an empirical application using an established data set containing 120 macroeconomic time series. Favorable properties of the ex-post approach with respect to convergence, statistical and numerical accuracy are revealed.

Reducing production cycle time by ergonomic workforce scheduling

Job rotation and allocation problems play important roles in the workforce scheduling domain. In this paper, the ergonomic considerations are employed for determining an efficient workforce schedule for a given planning period. This schedule contains both worker assignment and rotating among the workstations in a production line. Ergonomic adequation level between job and operator is the basis for the assignment. The studied production system is a continuous assembly line that must work all seven days a week. In the research, the main objective is to analyse the impact of the adequation level between workers and jobs on the operation time of the operators. In this way, an integer linear mathematical model is proposed to reduce the daily production cycle time by an ergonomic workforce scheduling. The model is solved by applying an optimization software named GUROBI. The output of the model is an optimal ergonomic worker assignment to different posts that can be changed from a day to another during a given planning period.

Гладкость обобщённых форм колебаний в задаче колебаний оболочки вращения в зависимости от некоторых несуммируемых коэффициентов.

Гладкость обобщённых форм колебаний в задаче колебаний оболочки вращения в зависимости от некоторых несуммируемых коэффициентов.

Determination of Displacement of the Piece Center in the Process of Centerless Grinding

Chatter, geometric lobbing and work piece rotation problems are the main problems which affect the centerless grinding productivity. An original method was developed and implemented to determine the displacement of the centre of the piece in centerless grinding. Until now no functional tool has been developed to solve these coupled problems. In conclusion, future trends and research work in centerless grinding technology are analyzed and discussed.

Does rotational malalignment cause knee pain? Comparison of gait between symptomatic and asymptomatic children and adolescents with rotational problems of the legs

Does rotational malalignment cause knee pain? Comparison of gait between symptomatic and asymptomatic children and adolescents with rotational problems of the legs

Riemannian Optimization for Registration of Curves in Elastic Shape Analysis

In elastic shape analysis, a representation of a shape is invariant to translation, scaling, rotation, and reparameterization, and important problems such as computing the distance and geodesic bet...

Unusual internal rotation coupling in the microwave spectrum of pinacolone

The molecular beam Fourier-transform microwave spectrum of pinacolone (methyl tert-butyl ketone) has been measured in several regions between 2 and 40GHz. Fits of the assigned spectrum using several computer programs based on different models for treating torsion–rotation interaction lead to the conclusion that no existing program correctly captures the internal dynamics of this molecule. Quantum chemical calculations at the MP2/6-311++G(d,p) level of theory indicate that this molecule does not have a plane of symmetry at equilibrium, and that internal rotation of the light methyl group induces a large oscillatory motion of the heavy tert-butyl group from one side of the Cs configuration to the other. This effect has been modeled for J=0 levels by a relatively simple two-top torsional Hamiltonian, where the magnitudes of the strong coupling terms between the tops are determined directly from the ab initio two-dimensional potential surface. A plot of the resultant 0A, 0E, 1E, 1A torsional levels on the same scale as a one-dimensional potential curve along the zig-zag path connecting the six (unequally spaced) minima bears a striking resemblance to the 1:2:1 splitting pattern of the A, E, E, B levels of an internal rotation problem with a sixfold barrier. It seems likely that rotational transitions within the 1E and 1A torsional levels are the cause of the roughly 50% of the spectrum that remains unassigned after all predicted transitions within the 0A and 0E torsional levels are removed. However, a much more complete measurement campaign and some new torsion–rotation theory will be needed to verify this hypothesis.

Drag phenomena within a torque converter driven automotive transmission - laminar flow approach

When discussing a torque converter driven, automotive transmission with respect to the vehicle's coasting mode, automotive engineers have to take into account the slip between the converter's propeller and turbine. If the turbine isn't locked to the propellers during coasting process, drag phenomena within the converter's fluid occur and they have to be properly assessed when computing the coasting process dynamics. The best way to make the needed evaluation is to have a separate torque converter and test it on a test bench, if the data provided by the manufacturer, in this respect, weren't available. But there are several issues that could baffle this action. Among them, one could find the lack of information from the manufacturer, missing (bankrupted) manufacturer, classified information, old (out of date) products and so on. An even more challenging situation consists in dealing with a military special vehicle. Actually, the vehicle that would be subjected to the following topic is a military tracked, heavy vehicle (MBT) with a planetary driveline, driven by its engine via a hydraulic torque converter. In the attempt to assess its’ coasting dynamic performances, we faced the problem of the reverse rotation of the torque converter that strongly influences the general drag of the vehicle's motion. Hence, this paper tries to provide a method to determine the transmission overall drag considering the torque converter as being its main contributor. The method is based on the experimental research our team has performed in the last several months. Using high-quality software and adjacent mathematics while assuming a certain sort of flow type within the torque converter, we aimed at determining the parameter of interest of the flow. The method can be successfully used for all type of hydrodynamic components of the transmission under the condition of developing the necessary experimental research. As far as the test were concerned, they were the typical ones designed to determine - on experimental basis - the mass inertial moments of the transmission components using the “falling weight” principle.

A fully and discriminatorily informed particle swarm optimization with different sharing strategies for superior and inferior information

What kind of information is used and in which way the particles interact with each other have direct effects on the particle swarm optimization (PSO) algorithm efficiency. In order to use the information more fully, effectively and reasonably, the paper proposes a fully and discriminatorily informed PSO (FDIPSO) algorithm. Unlike the traditional PSO algorithm, the algorithm takes the positive effects of all the superior neighbors and the negative effects of the inferior particles into account and employs different mechanisms for attractive and repulsive effects to prevent confusion of swarm evolution caused by the different effects. The superior information is fully used to build high quality equilibrium points as attractors to guide particles while the repulsive effect from inferior information is embodied by introducing an ‘escape coefficient’ to help adjust the movement of particles. Experimental studies are conducted on a set of well-known benchmark functions including unimodal, multimodal and rotated problems. Computational results show positive effect and negative effect work collaboratively in FIDPSO, verify the relative superiority of this strategy over four other information sharing strategies and indicate that the approach outperforms several other state-of-art PSO variants on the test problems.

Static Hand Gesture Recognition Method Based on Depth Images with Shape Context Feature

Static hand gesture recognition is very important for human-computer interaction systems, which is widely used in human-computer interaction systems. Using visible RGB images as the input method would be more stable, but the illumination and skin color are big problems; by contrast the depth images is a better choice. A novel algorithm which recognizes static hand gesture based on depth images using 3d shape context feature and improves the performance by arm major axis correction and contour-center sampling is proposed. Arm major axis correction can solve the rotation problem and the sampling, which increases the recognition rate. Besides, using 3d space information makes the algorithm more stable. Experimental results show that the average recognition rate gets to 95.8%, and the performance and speed are superior to existing algorithms. Recognition results can be widely used in the follow-on real scene human-computer interaction (HCI) operations.

Numerical investigation of submarine hydrodynamics and flow field in steady turn

This paper presents numerical simulations of viscous flow past a submarine model in steady turn by solving the Reynolds-Averaged Navier-Stokes Equations (RANSE) for incompressible, steady flows. The rotating coordinate system was adopted to deal with the rotation problem. The Coriolis force and centrifugal force due to the computation in a bodyfixed rotating frame of reference were treated explicitly and added to momentum equations as source terms. Furthermore, velocities of entrances were coded to give the correct magnitude and direction needed. Two turbulence closure models (TCMs), the RNG κ - e model with wall functions and curvature correction and the Shear Stress Transport (SST) κ - ω model without the use of wall functions, but with curvature correction and low-Re correction were introduced, respectively. Take DARPA SUBOFF model as the test case, a series of drift angle varying between 0° and 16° at a Reynolds number of 6.53×106 undergoing rotating arm test simulations were conducted. The computed forces and moment as a function of drift angle during the steady turn are mostly in close agreement with available experimental data. Though the difference between the pressure coefficients around the hull form was observed, they always show the same trend. It was demonstrated that using sufficiently fine grids and advanced turbulence models will lead to accurate prediction of the flow field as well as the forces and moments on the hull.