A 231-MHz, 2.18-mW 32-bit Logarithmic Arithmetic Unit for Fixed-Point 3-D Graphics System

A 32-bit fixed-point logarithmic arithmetic unit is proposed for the possible application to mobile three-dimensional (3-D) graphics system. The proposed logarithmic arithmetic unit performs division, reciprocal, square-root, reciprocal-square-root and square operations in two clock cycles and powering operation in four clock cycles. It can program its number range for accurate computation flexibility of 3-D graphics pipeline and eight -region piecewise linear approximation model for logarithmic and antilogarithmic conversion to reduce the operation error under 0.2%. Its test chip is implemented by 1-poly 6-metal 0.18-mum CMOS technology with 9-k gates. It operates at the maximum frequency of 231 MHz and consumes 2.18 mW at 1.8-V supply     

An approximate nonlinear observer with polynomial coordinatetransformation maps

The state equivalence condition to the nonlinear observer form is stated in terms of the exactness of one-form. Using the definition of the approximate closedness, we relax the equivalence condition, thereby obtaining a necessary and sufficient condition for the approximate observer error linearizability. This approximate observer theory extends the realm of applications. Another great advantage of this approximation method is that the coordinate transformation is directly obtainable as vectors of polynomials, while it is, in general, not possible with the existing method,     

Exact static element stiffness matrices of non‐symmetric thin‐walled curved beams

An evaluation procedure of exact static stiffness matrices for curved beams with non‐symmetric thin‐walled cross section are rigorously presented for the static analysis. Higher‐order differential equations for a uniform curved beam element are first transformed into a set of the first‐order simultaneous ordinary differential equations by introducing 14 displacement parameters where displacement modes corresponding to zero eigenvalues are suitably taken into account. This numerical technique is then accomplished via a generalized linear eigenvalue problem with non‐symmetric matrices. Next, the displacement functions of displacement parameters are exactly calculated by determining general solutions of simultaneous non‐homogeneous differential equations. Finally an exact stiffness matrix is evaluated using force–deformation relationships. In order to demonstrate the validity and effectiveness of this method, displacements and normal stresses of cantilever thin‐walled curved beams subjected to tip loads are evaluated and compared with those by thin‐walled curved beam elements as well as shell elements. Copyright © 2004 John Wiley & Sons, Ltd.     

A study on a generalized parametric interpolator with real-time jerk-limited acceleration

The impossibility of exact arc length computation for ‘standard’ parametric curves such as Bézier/B-spline curves makes it difficult to generate a feedrate profile with desired accelerations in real-time. This paper presents a new recursive trajectory generation method that estimates an admissible path increment and determines the initiation of the final deceleration stage according to the distance left to travel estimated at every sampling time, resulting in exact feedrate trajectory generation through jerk-limited acceleration profiles for the parametric curves. The proposed approach allows the feedrate profile to be dynamically adjusted according to geometrical path constraints for the curved path. The simulation result has been also provided to illustrate the generation of smooth feedrate profile encompassing a sequence of mixed NC blocks including traditional linear and circular blocks.     

Plasmon Enhanced Fluorescence Based on Porphyrin–Peptoid Hybridized Gold Nanoparticle Platform

A porphyrin–peptoid‐hybridized silica‐coated gold nanoparticle is developed, which is inspired by the protein–chlorophyll ensemble found in photosynthetic antenna. In the natural antenna, chlorophylls are integrated into dense assemblies that are supported by frameworks of proteins, which ensure optimal pigment arrangement for effective light harvesting. In the subject platform, porphyrins are conjugated to the peptoid helix scaffold in a structurally well‐defined alignments and subsequently immobilized on the surface of nanoparticles. This prevents intermolecular aggregation among porphyrins and allows high resolution analysis of the effect of porphyrin configuration on the optical properties of the system. Interestingly, under the influence of plasmon from the gold nanoparticle core, the fluorescence of porphyrin is enhanced up to 24‐fold at the wavelength where the plasmon resonance matches the porphyrin excitation wavelength. In addition, differences in porphyrin configuration result in spectral modification of their fluorescence emissions. Particularly, the peptoid bearing two porphyrins at a distance of 6 Å shows the most significant alteration in fluorescence. The platform can facilitate extensive studies on the relationship between porphyrin arrangement design and their photophysical interaction in antenna complexes.     

Shift and scale‐invariant correlation for pattern recognition based on the bidimensional empirical mode decomposition with noise robustness

Abstract

A novel filter is proposed to improve the noise robustness and discrimination capability for shift and scale invariant pattern recognition. This filter is a combination of mellin radial harmonic filter (RHF) and the bidimensional empirical mode decomposition. The basic principle of this method is to make use of partial reconstructions of the image by the relevant intrinsic mode functions corresponding to the most important structures of the image. A criterion is proposed to determine the proper number of intrinsic mode functions to be discarded for denoising by discussing the characteristic of the noise. The proposed filter provides a wider allowable scale change of the object. Within this range, the correlation peak intensity is relatively uniform even in the case of noise. This proposed filter has been tested experimentally to confirm the result from numerical simulations for cases with and without additive white Gaussian noise.     

Multifunctional Chemical Linker Imidazoleacetic Acid Hydrochloride for 21% Efficient and Stable Planar Perovskite Solar Cells

Chemical interaction at a heterojunction interface induced by an appropriate chemical linker is of crucial importance for high efficiency, hysteresis‐less, and stable perovskite solar cells (PSCs). Effective interface engineering in PSCs is reported via a multifunctional chemical linker of 4‐imidazoleacetic acid hydrochloride (ImAcHCl) that can provide a chemical bridge between SnO₂ and perovskite through an ester bond with SnO₂ via esterification reaction and an electrostatic interaction with perovskite via imidazolium cation in ImAcHCl and iodide anion in perovskite. In addition, the chloride anion in ImAcHCl plays a role in the improvement of crystallinity of perovskite film crystallinity. The introduction of ImAcHCl onto SnO₂ realigns the positions of the conduction and valence bands upwards, reduces nonradiative recombination, and improves carrier life time. As a consequence, average power conversion efficiency (PCE) is increased from 18.60% ± 0.50% to 20.22% ± 0.34% before and after surface modification, respectively, which mainly results from an enhanced voltage from 1.084 ± 0.012 V to 1.143 ± 0.009 V. The best PCE of 21% is achieved by 0.1 mg mL^?1 ImAcHCl treatment, along with negligible hysteresis. Moreover, an unencapsulated device with ImAcHCl‐modified SnO₂ shows much better thermal and moisture stability than unmodified SnO₂.     

Data Parallel Implementation of Belief Propagation in Factor Graphs on Multi-core Platforms

We investigate data parallel techniques for belief propagation in acyclic factor graphs on multi-core systems. Belief propagation is a key inference algorithm in factor graph, a probabilistic graphical model that has found applications in many domains. In this paper, we explore data parallelism for basic operations over the potential tables in belief propagation. Data parallel techniques for these table operations are developed for shared memory platforms. We then propose a complete belief propagation algorithm using these table operations to perform exact inference in factor graphs. The proposed algorithms are implemented on state-of-the-art multi-socket multi-core systems with additional NUMA-aware optimizations. Our proposed algorithms exhibit good scalability using a representative set of factor graphs. On a four-socket Intel Westmere-EX system with 40 cores, we achieve 39.5 $\times $ speedup for the table operations and 39 $\times $ speedup for the complete algorithm using factor graphs with large potential tables.     

Spatiotemporal bag-of-features for early wildfire smoke detection

Wildfire smoke detection is particularly important for early warning systems, because smoke usually rises before flames arise. Therefore, this paper presents an automatic wildfire smoke detection method using computer vision and pattern recognition techniques. First, candidate blocks are identified using key-frame differences and nonparametric smoke color models to detect smoke-colored moving objects. Subsequently, three-dimensional spatiotemporal volumes are built by combining the candidate blocks in the current key-frame with the corresponding blocks in previous frames. A histogram of oriented gradient (HOG) is extracted, and a histogram of oriented optical flow (HOOF) is extracted as a temporal feature based on the fact that the direction of smoke diffusion is upward owing to thermal convection. From spatiotemporal features of training data, a visual codebook and a bag-of-features (BoF) histogram are generated using our proposed weighting scheme. For smoke verification, a random forest classifier is built during the training phase using the BoF histogram. The random forest with the BoF histogram can increase the detection accuracy performance when compared with related methods and allow smoke detection to be carried out in near real time.     

Light‐Induced Surface Modification of Natural Plant Microparticles: Toward Colloidal Science and Cellular Adhesion Applications

Playing an instrumental role in the life of plants, pollen microparticles are one of the most fascinating biological materials in existence, with abundant and renewable supply, ultrahigh durability, and unique, species‐specific architectural features. Aside from their biological role, pollen microparticles also demonstrate broad utility as functional materials for drug delivery and microencapsulation, and increasingly for emulsion‐type applications. As natural pollen microparticles are predominantly hydrophobic, developing robust surface functionalization strategies to increase surface hydrophilicity would increase the range of colloidal science applications, including opening the door to interfacing microparticles with biological cells. This research investigates the extraction and light‐induced surface modification of discrete pollen microparticles from bee‐collected pollen granules toward achieving functional control over the responses elicited from discrete particles in colloidal science and cellular applications. Ultraviolet–ozone treatment is shown to increase the proportion of surface elemental oxygen and ketones, leading to increased surface hydrophilicity, enhanced particle dispersibility, tunable control over Pickering emulsion characteristics, and enhanced cellular adhesion. In summary, the findings demonstrate that light‐induced surface modification improves the functional properties of pollen microparticles, and such insights also have broad implications across materials science and environmental science applications.