The complex representation of algebraic curves and its simpleexploitation for pose estimation and invariant recognition

Representations are introduced for handling 2D algebraic curves (implicit polynomial curves) of arbitrary degree in the scope of computer vision applications. These representations permit fast, accurate pose-independent shape recognition under Euclidean transformations with a complete set of invariants, and fast accurate pose-estimation based on all the polynomial coefficients. The latter is accomplished by a centering of a polynomial based on its coefficients, followed by rotation estimation by decomposing polynomial coefficient space into a union of orthogonal subspaces for which rotations within two-dimensional subspaces or identity transformations within one-dimensional subspaces result from rotations in x, y measured-data space. Angles of these rotations in the two-dimensional coefficient subspaces are proportional to each other and are integer multiples of the rotation angle in the x, y data space. By recasting this approach in terms of a complex variable, i.e., x+iy=z, and complex polynomial-coefficients, further conceptual and computational simplification results. Application to shape-based indexing into databases is presented to illustrate the usefulness and the robustness of the complex representation of algebraic curves     

A palmer-based continuous fuzzy flexible flow-shop scheduling algorithm

 Flexible flow shops can be thought of as generalizations of simple flow shops. In the past, the processing time for each job was usually assumed to be known exactly, but in many real-world applications, processing times may vary dynamically due to human factors or operating faults. In the past, we demonstrated how discrete fuzzy concepts could easily be used in the Palmer algorithm for managing uncertain flexible-flow-shop scheduling. In this paper, we generalize it to continuous fuzzy domains. We use triangular membership functions for flexible flow shops with more than two machine centers to examine processing-time uncertainties and to make scheduling more suitable for real applications. We first use the triangular fuzzy LPT algorithm to allocate jobs, and then use the triangular fuzzy Palmer algorithm to deal with sequencing the tasks. The proposed method thus provides a more flexible way of scheduling jobs than conventional scheduling methods.     

An Optimality Principle Governing Human Walking

In this paper, we investigate different possible strategies underlying the formation of human locomotor trajectories in goal-directed walking. Seven subjects were asked to walk within a motion capture facility from a fixed starting point and direction, and to cross over distant porches for which both position and direction in the room were changed over trials. Stereotyped trajectories were observed in the different subjects. The underlying idea to attack this question has been to relate this problem to an optimal control scheme: the trajectory is chosen according to some optimization principle. This is our basic starting assumption. The subject being viewed as a controlled system, we tried to identify several criteria that could be optimized. Is it the time to perform the trajectory? The length of the path? The minimum jerk along the path? We found that the variation (time derivative) of the curvature of the locomotor paths is minimized. Moreover, we show that the human locomotor trajectories are well approximated by the geodesics of a differential system minimizing the norm of the control. Such geodesics are made of arcs of clothoids. The clothoid or Cornu spiral is a curve, whose curvature grows with the distance from the origin.     

A new liquid crystal lens with axis-tunability via three sector electrodes

A novel liquid crystal (LC) lens with an on-line tunability on focus length and optical axis is proposed in this study. The designed lens has a LC layer sandwiched by two ITO glasses, one of which is patterned with three sector electrodes. With varied sets of pre-designed voltages applied to these three electrodes, the LC lens can not only render focusing effects but also tunability on the optical axis of the lens to an arbitrary axis. A vector-form equation is developed to predict the direction of axis tuning. Simulations are next conducted to predict dynamics of the LCs in the lens and also the focusing and axis-tuning properties of the lens. Important sizes and materials and fabrication process of the lens are determined and optimized based on simulation results. The designed LC lens is fabricated, and then experiments are conducted to demonstrate the performance of the designed LC lens on axis tuning. It shows that the focusing axis of the LC lens can be effectively changed by pre-calculated combinations of three voltages. It is also shown that the average movement of the focal point per applied voltage reaches 4.778?μm/V.     

NOX removal in excess oxygen by plasma-enhanced selective catalytic reduction

In the off-gases of internal combustion engines running with oxygen excess, non-thermal plasmas (NTPs) have an oxidative potential, which results in an effective conversion of NO to NO₂. In combination with appropriate catalysts and ammonia (NH₃-SCR) or hydrocarbons (HC-SCR) as a reducing agent, this can be utilized to reduce nitric oxides (NO and NO₂) synergistically to molecular nitrogen.

The combination of SCR and cold plasma enhanced the overall reaction rate and allowed an effective removal of NO_X at low temperatures. Using NH₃ as a reducing agent, NO_X was converted to N₂ on zeolites or NH₃-SCR catalysts like V₂O₅–WO₃/TiO₂ at temperatures as low as 100–200 °C. Significant synergetic effects of plasma and catalyst treatment were observed both for NH₃ stored by ion exchange on the zeolite and for continuous NH₃ supply.

Certain modifications of Al₂O₃ and ZrO₂ have been found to be effective as catalysts in the plasma-assisted HC-SCR in oxygen excess. With an energy supply of about 30 eV/NO-molecule, 500 ppm NO was reduced by more than half at a temperature of 300 °C and a space velocity of 20 000 h⁻¹ at the catalyst. The synergistic combinations of NTP and both NH₃- and HC-SCR have been verified under real diesel engine exhaust conditions.     

The influence of porosity on the fatigue crack growth behavior of Ti–6Al–4V laser welds

The effect of porosity––a common welding defect––on the fatigue crack growth rate (FCGR) in Ti–6Al–4V laser welds was investigated. The experimental results reveal that porosity was present in partial penetration welds over a narrow fusion zone (FZ) with martensite structure. The FCGR of the FZ was lower than that of the base plate. The fracture surface morphology of weld metal was much rougher as compared to that of the base plate. Randomly oriented martensite in the FZ led to local cleavage fracture along a preferred plane, thus, altering the crack growth direction significantly out of the primary crack plane. The zigzag crack path in the FZ resulted in a reduced FCGR at a given ΔK compared to the base plate. Besides, the porous weld showed a serration on the crack growth curve, and behaved the similar crack growth characteristics as the defect free one. SEM fractography revealed that the deflection of crack path around porosity together with local notch blunting as the crack tip pierced into porosity, balanced the increased FCGR for the occurrence of instant crack advance as the crack front reached the porosity at a low stress ratio. In contrast, the serration and drop in FCGR occurred sparingly at a high stress ratio as the crack front met the porosity.     

ICCAP-a linear time sparsification and reordering algorithm for 3-D BEM capacitance extraction

This paper presents an efficient, simple, hierarchical, and sparse three-dimensional capacitance extraction algorithm, i.e., ICCAP. Most previous capacitance extraction algorithms, such as FastCap and HiCap, introduce intermediate variables to facilitate the hierarchical potential calculation, but still preserve the basic panels as basis. In this paper, we discover that those intermediate variables are a fundamentally much better basis than leaf panels. As a result, we are able to explicitly construct the sparse potential coefficient matrix and solve it with linear memory and linear run time in comparison with the most recent hierarchical O(nlogn) approach in PHiCap. Furthermore, the explicit sparse formulation of a potential matrix not only enables the usage of preconditioned Krylov subspace iterative methods, but also the reordering technique. A new reordering technique, i.e., level-oriented reordering (LOR), is proposed to further reduce over 20% of memory consumption and run time compared with no reordering techniques applied. In fact, LOR is even better than the state-of-the-art minimum degree reordering and more efficient. Without complicated orthonormalization matrix computation, ICCAP is very simple, efficient, and accurate. Experimental results demonstrate the superior run time and memory consumption over previous approaches while achieving similar accuracy.     

Comprehensive Study of Emitter-Ledge Thickness of InGaP/GaAs HBTs

A comprehensive study of emitter-ledge thickness of InGaP/GaAs heterojunction bipolar transistors (HBTs) has been undertaken. It is shown that the recombination rate and electron densities are drastically increased near the exposed base surface between the base contact and the emitter ledge. In contrast, the corresponding hole densities are decreased. If the emitter ledge is too thick, current will flow through the undepleted ledge, which increases the emitter-size effect. In contrast, if the emitter ledge is too thin, it may not effectively passivate the surface. Therefore, the thickness of the emitter ledge is a crucial issue and should be carefully considered. It is shown that, from simulated and experimental results, the optimum emitter-ledge thickness of InGaP/GaAs HBT is 100-200 Aring     

Lossless image coding using adaptive, switching algorithm with automatic fuzzy context modelling

A switching adaptive predictor (SWAP) with automatic fuzzy context modelling is proposed for lossless image coding. Depending on the context of the coding pixel, the SWAP encoder switches between two predictors: the adaptive neural predictor (ANP) and the texture context matching (TCM) predictor. The ANP is known to perform well and gives small prediction errors except for pixels around edges. For areas with edges, TCM is used. To decide which is to be used, a switching criterion is proposed to pick out pixels around edges effectively. With the switching predictor structure, small prediction errors can be achieved in both slowly varying areas and edges. Furthermore, the use of the so-called fuzzy context clustering for prediction error refinement is proposed. The proposed compensation mechanism is proved to be very useful through experiments. It further improves the bit rates by, on average, 0.2 bpp in test images. The experiments also show that an average improvement of 0.3 and 0.05 bpp in first-order entropy can be achieved when the proposed switching predictor is compared with the gradient adjusted predictor and a six-order edge directed predictor, respectively. Moreover, the lossless image coder built upon the proposed algorithm also provides lower bit rates than the state-of-the-art context-based, adaptive, lossless image coding (CALIC) system and is comparable to that obtained by the highly complex two-pass coder called TMW