Animated feather coats using field lines

The tedious task of manually placing feathers on computer animated objects involves aligning feathers, ensuring that they do not insect each other or penetrate the surface, deforming every feather to match the local surface features, and ensuring that the feather coat is consistent when the underlying object is animated.

We present a technique for generating a feather coat over an object. Feather orientation is specified quickly and easily, feathers are deformed while ensuring collision prevention, and the coat can be animated. We create a vector field in the space surrounding the body object and deform feathers to align with the field lines. The non-intersection property of the field lines ensures that feather intersections are avoided. We provide a formulation of a suitable vector field and demonstrate that it is capable of producing realistic feather coats. The process can easily be integrated into the work-flow of standard modelling and animation processes.

We show examples of feather coat creation on a range of objects, proving that field line based placement of feather coats provides the desired functionality for feather modelling and animation.

Biologically inspired vector fields to generate hair directions

This paper describes how biologically inspired vector fields can be used to partially automate the manual and time-consuming process of specifying hair directions. This approach replicates the consequence of stretching of skin from natural hair development process, in contrast to replicating the appearance of hair. The direction of each hair on the surface of an arbitrary 3D model is determined by interpolating the solution vector field that satisfies a set of user-defined constraints describing the stretching of skin. Results found that the generated hair directional pattern closely resembles that found naturally. Further investigation revealed that the presence of naturally occurring hair types and the varying distribution of hair directions induced by the calculated vector field enhanced the realism of hair coats generated using this approach. Aside from hair or fur, this approach can also be applied to hair-like masses such as grass, feathers, or scales.

Identification of moving obstacles with pyramidal Lucas Kanade optical flow and k means clustering

This paper describes the methodology for identifying moving obstacles by obtaining a reliable and a sparse optical flow from image sequences. Given a sequence of images, basically we can detect two-types of on road vehicles, vehicles traveling in the opposite direction and vehicles traveling in the same direction. For both types, distinct feature points can be detected by Shi and Tomasi corner detector algorithm. Then pyramidal Lucas Kanade method for optical flow calculation is used to match the sparse feature set of one frame on the consecutive frame. By applying k means clustering on four component feature vector, which are to be the coordinates of the feature point and the two components of the optical flow, we can easily calculate the centroids of the clusters and the objects can be easily tracked. The vehicles traveling in the opposite direction produce a diverging vector field, while vehicles traveling in the same direction produce a converging vector field

Space vector modulation based fast speed response field-orientation control of induction motor drive with adaptive neural integrator

This paper presents a novel fast speed response control strategy for the poly-phase induction motor drive system based on flux angle. The control scheme is derived in rotor field coordinates and employs the estimation of the rotor flux and its position. An adaptive notch filter is proposed to eliminate the dc component of the integration of signals used for the rotor flux estimation. To improve the performance of the rotor flux estimator, derivative term of the back emf is incorporated in the system. The voltage components in the synchronous reference frame are generated in the controllers which are transformed to stationary reference frame for driving the motor. Space vector modulation technique is used here. Simulation of the drive system was carried out and the results were compared with those obtained for a system that produces the above mentioned voltage components using the conventional PI controller. It is observed that the proposed control methodology provides faster response than the conventional PI controller incorporated system.

On rapid vector alignment in permanent magnet brushless motor

A software replacement for the commutation signals of a permanent magnet brushless motor is presented. The feedback observed acceleration loop or equivalently the high-order position polynomial controller allows finding the initial relative orientation between the two magnetic fields of the motors within a fraction of a second. Also, using the proposed method allows a considerable cost saving, since the transducer that is usually used for this purpose can be eliminated. The cost saving is most obvious in the case of linear motors and angle motors with large diameters. The way the problem is posed is an essential part of this work and it is the reason behind the apparent simplicity of the solution. The method has been tested when a relative encoder was used and the motor current was regulated.

Boron nitride nanotubes : a novel vector for targeted magnetic drug delivery

Whereas several biomedical applications of carbon nanotubes have been proposed, the use of boron nitride nanotubes (BNNTs) in this field has been largely unexplored despite their unique and potentially useful properties. Our group has recently initiated an experimental program aimed at the exploration of the interactions between BNNTs and living cells. In the present paper, we report on the magnetic properties of BNNTs containing Fe catalysts which confirm the feasibility for their use as nanovectors for targeted drug delivery. The magnetisation curves of BNNTs characterised by the present study are typical of superparamagnetic materials with important parameters, including magnetic permeability and magnetic momentum, derived by employing Langevin theory. In-vitro tests have demonstrated the feasibility for influencing the uptake of BNNTs by living cells by exposure to an external magnetic source. A finite element method analysis devised to predict this effect produced predictive data with close agreement with the experimental observations.

Sharpening the focus of force field analysis

The purpose is to explore the inherent complexity of Kurt Lewin's force field theory through applied analysis of organizational case examples and related methods. The methodology applies a range of tools from the consultancy research domain, including force field analysis of complex organizational scenarios, and applies bricolage and corroboration to emerging discoveries from semi-structured interviews, author experience, critical reflection and literature survey. Findings are that linear representation of internal and external forces in organizational applications of field theory does not fully explain the paradox of inverse vectors in the forces of change. The force field is not an impermeable thing; instead, it morphs. Examples of the inverse principle and its effects are detailed and extended in this analysis. The implications of the research are that force field analysis and related change processes promoted in organizational change literature run the risk of missing key complexities. The inclusion of the inverse principle can provide enhanced, holistic understanding of the prevailing forces for change. The augmentation of the early work of Kurt Lewin, and extension of previous analyses of his legacy in the Journal of Change Management and elsewhere, provide, in this article, change analysis insights that align well with current organizational environments.

Switch point finding using polynomial regression for fuzzy type reduction algorithms

Karnik-Mendel (KM) algorithm is the most widely used type reduction (TR) method in literature for the design of interval type-2 fuzzy logic systems (IT2FLS). Its iterative nature for finding left and right switch points is its Achilles heel. Despite a decade of research, none of the alternative TR methods offer uncertainty measures equivalent to KM algorithm. This paper takes a data-driven approach to tackle the computational burden of this algorithm while keeping its key features. We propose a regression method to approximate left and right switch points found by KM algorithm. Approximator only uses the firing intervals, rnles centroids, and FLS strnctural features as inputs. Once training is done, it can precisely approximate the left and right switch points through basic vector multiplications. Comprehensive simulation results demonstrate that the approximation accuracy for a wide variety of FLSs is 100%. Flexibility, ease of implementation, and speed are other features of the proposed method.